From b2507b82791e2c246c15197579ce5462f4bcb160 Mon Sep 17 00:00:00 2001 From: elisno Date: Fri, 6 Sep 2024 19:44:25 +0000 Subject: [PATCH] deploy: cleanlab/cleanlab@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774 --- master/.buildinfo | 2 +- .../cleanlab/benchmarking/index.doctree | Bin 3248 -> 3248 bytes .../benchmarking/noise_generation.doctree | Bin 81345 -> 81345 bytes .../.doctrees/cleanlab/classification.doctree | Bin 290735 -> 290735 bytes master/.doctrees/cleanlab/count.doctree | Bin 283717 -> 283717 bytes .../.doctrees/cleanlab/data_valuation.doctree | Bin 26578 -> 26578 bytes .../cleanlab/datalab/datalab.doctree | Bin 174487 -> 174487 bytes .../guide/_templates/issue_types_tip.doctree | Bin 4354 -> 4354 bytes .../guide/custom_issue_manager.doctree | Bin 31452 -> 31452 bytes .../guide/generating_cluster_ids.doctree | Bin 6318 -> 6318 bytes .../cleanlab/datalab/guide/index.doctree | Bin 12087 -> 12087 bytes .../guide/issue_type_description.doctree | Bin 264696 -> 265656 bytes .../cleanlab/datalab/guide/table.doctree | Bin 63584 -> 63584 bytes .../.doctrees/cleanlab/datalab/index.doctree | Bin 5445 -> 5445 bytes .../datalab/internal/adapter/imagelab.doctree | Bin 159126 -> 159126 bytes .../datalab/internal/adapter/index.doctree | Bin 3624 -> 3624 bytes .../cleanlab/datalab/internal/data.doctree | Bin 105136 -> 105136 bytes .../datalab/internal/data_issues.doctree | Bin 77301 -> 77301 bytes .../cleanlab/datalab/internal/factory.doctree | Bin 64553 -> 64553 bytes .../cleanlab/datalab/internal/index.doctree | Bin 4620 -> 4620 bytes .../datalab/internal/issue_finder.doctree | Bin 46989 -> 46989 bytes .../_notices/not_registered.doctree | Bin 3440 -> 3440 bytes .../issue_manager/data_valuation.doctree | Bin 79832 -> 79832 bytes .../internal/issue_manager/duplicate.doctree | Bin 75245 -> 75245 bytes .../internal/issue_manager/imbalance.doctree | Bin 68346 -> 68346 bytes .../internal/issue_manager/index.doctree | Bin 5282 -> 5282 bytes .../issue_manager/issue_manager.doctree | Bin 80662 -> 80662 bytes .../internal/issue_manager/label.doctree | Bin 88614 -> 88614 bytes .../issue_manager/multilabel/index.doctree | Bin 3685 -> 3685 bytes .../issue_manager/multilabel/label.doctree | Bin 79258 -> 79258 bytes .../internal/issue_manager/noniid.doctree | Bin 90556 -> 90556 bytes .../internal/issue_manager/null.doctree | Bin 68181 -> 68181 bytes .../internal/issue_manager/outlier.doctree | Bin 78825 -> 78825 bytes .../issue_manager/regression/index.doctree | Bin 3685 -> 3685 bytes .../issue_manager/regression/label.doctree | Bin 108542 -> 108542 bytes .../underperforming_group.doctree | Bin 116536 -> 116536 bytes .../datalab/internal/model_outputs.doctree | Bin 78458 -> 78458 bytes .../cleanlab/datalab/internal/report.doctree | Bin 34190 -> 34190 bytes .../cleanlab/datalab/internal/task.doctree | Bin 57819 -> 57819 bytes .../datalab/optional_dependencies.doctree | Bin 3451 -> 3451 bytes master/.doctrees/cleanlab/dataset.doctree | Bin 100920 -> 100920 bytes .../cleanlab/experimental/cifar_cnn.doctree | Bin 407995 -> 407995 bytes .../cleanlab/experimental/coteaching.doctree | Bin 48525 -> 48525 bytes .../cleanlab/experimental/index.doctree | Bin 5365 -> 5365 bytes .../experimental/label_issues_batched.doctree | Bin 158466 -> 158466 bytes .../experimental/mnist_pytorch.doctree | Bin 555175 -> 555175 bytes .../experimental/span_classification.doctree | Bin 34890 -> 34890 bytes master/.doctrees/cleanlab/filter.doctree | Bin 94218 -> 94218 bytes .../.doctrees/cleanlab/internal/index.doctree | Bin 4532 -> 4532 bytes .../internal/label_quality_utils.doctree | Bin 19410 -> 19410 bytes .../cleanlab/internal/latent_algebra.doctree | Bin 85348 -> 85348 bytes .../internal/multiannotator_utils.doctree | Bin 46750 -> 46750 bytes .../internal/multilabel_scorer.doctree | Bin 183513 -> 183513 bytes .../internal/multilabel_utils.doctree | Bin 34042 -> 34042 bytes .../cleanlab/internal/neighbor/index.doctree | Bin 6725 -> 6725 bytes .../internal/neighbor/knn_graph.doctree | Bin 111899 -> 111899 bytes .../cleanlab/internal/neighbor/metric.doctree | Bin 38404 -> 38404 bytes .../cleanlab/internal/neighbor/search.doctree | Bin 32456 -> 32456 bytes .../cleanlab/internal/outlier.doctree | Bin 29778 -> 29778 bytes .../token_classification_utils.doctree | Bin 69171 -> 69171 bytes .../.doctrees/cleanlab/internal/util.doctree | Bin 212686 -> 212686 bytes .../cleanlab/internal/validation.doctree | Bin 41565 -> 41565 bytes .../.doctrees/cleanlab/models/index.doctree | Bin 4972 -> 4972 bytes .../.doctrees/cleanlab/models/keras.doctree | Bin 106237 -> 106237 bytes .../.doctrees/cleanlab/multiannotator.doctree | Bin 165197 -> 165197 bytes .../multilabel_classification/dataset.doctree | Bin 67275 -> 67275 bytes .../multilabel_classification/filter.doctree | Bin 86794 -> 86794 bytes .../multilabel_classification/index.doctree | Bin 4916 -> 4916 bytes .../multilabel_classification/rank.doctree | Bin 47085 -> 47085 bytes .../cleanlab/object_detection/filter.doctree | Bin 38032 -> 38032 bytes .../cleanlab/object_detection/index.doctree | Bin 3852 -> 3852 bytes .../cleanlab/object_detection/rank.doctree | Bin 149811 -> 149811 bytes .../cleanlab/object_detection/summary.doctree | Bin 166920 -> 166920 bytes master/.doctrees/cleanlab/outlier.doctree | Bin 98688 -> 98688 bytes master/.doctrees/cleanlab/rank.doctree | Bin 113711 -> 113711 bytes .../cleanlab/regression/index.doctree | Bin 3738 -> 3738 bytes .../cleanlab/regression/learn.doctree | Bin 222189 -> 222189 bytes .../cleanlab/regression/rank.doctree | Bin 19815 -> 19815 bytes .../cleanlab/segmentation/filter.doctree | Bin 28604 -> 28604 bytes .../cleanlab/segmentation/index.doctree | Bin 3788 -> 3788 bytes .../cleanlab/segmentation/rank.doctree | Bin 51266 -> 51266 bytes .../cleanlab/segmentation/summary.doctree | Bin 69021 -> 69021 bytes .../token_classification/filter.doctree | Bin 27210 -> 27210 bytes .../token_classification/index.doctree | Bin 3934 -> 3934 bytes .../token_classification/rank.doctree | Bin 60167 -> 60167 bytes .../token_classification/summary.doctree | Bin 79564 -> 79564 bytes master/.doctrees/environment.pickle | Bin 17048794 -> 17050694 bytes master/.doctrees/index.doctree | Bin 43029 -> 43029 bytes master/.doctrees/migrating/migrate_v2.doctree | Bin 28116 -> 28116 bytes .../tutorials/clean_learning/tabular.ipynb | 130 +- .../tutorials/clean_learning/text.ipynb | 1650 ++++---- .../nbsphinx/tutorials/datalab/audio.ipynb | 1188 +++--- .../tutorials/datalab/datalab_advanced.ipynb | 336 +- .../datalab/datalab_quickstart.ipynb | 138 +- .../nbsphinx/tutorials/datalab/image.ipynb | 3400 ++++++++--------- .../nbsphinx/tutorials/datalab/tabular.ipynb | 138 +- .../nbsphinx/tutorials/datalab/text.ipynb | 172 +- .../tutorials/datalab/workflows.ipynb | 1224 +++--- .../nbsphinx/tutorials/dataset_health.ipynb | 34 +- master/.doctrees/nbsphinx/tutorials/faq.ipynb | 656 ++-- .../tutorials/improving_ml_performance.ipynb | 306 +- .../nbsphinx/tutorials/indepth_overview.ipynb | 210 +- .../nbsphinx/tutorials/multiannotator.ipynb | 146 +- .../tutorials/multilabel_classification.ipynb | 98 +- .../nbsphinx/tutorials/object_detection.ipynb | 195 +- .../nbsphinx/tutorials/outliers.ipynb | 552 ++- .../nbsphinx/tutorials/regression.ipynb | 202 +- .../nbsphinx/tutorials/segmentation.ipynb | 1068 +++--- .../tutorials/token_classification.ipynb | 184 +- .../tutorials/clean_learning/index.doctree | Bin 3019 -> 3019 bytes .../tutorials/clean_learning/tabular.doctree | Bin 64488 -> 64488 bytes .../tutorials/clean_learning/text.doctree | Bin 233886 -> 233886 bytes .../.doctrees/tutorials/datalab/audio.doctree | Bin 333645 -> 333645 bytes .../datalab/datalab_advanced.doctree | Bin 203507 -> 203507 bytes .../datalab/datalab_quickstart.doctree | Bin 145956 -> 145956 bytes .../.doctrees/tutorials/datalab/image.doctree | Bin 454840 -> 454840 bytes .../.doctrees/tutorials/datalab/index.doctree | Bin 3367 -> 3367 bytes .../tutorials/datalab/tabular.doctree | Bin 121626 -> 121626 bytes .../.doctrees/tutorials/datalab/text.doctree | Bin 150907 -> 150907 bytes .../tutorials/datalab/workflows.doctree | Bin 413674 -> 413674 bytes .../tutorials/dataset_health.doctree | Bin 329657 -> 329657 bytes master/.doctrees/tutorials/faq.doctree | Bin 199351 -> 199351 bytes .../improving_ml_performance.doctree | Bin 372312 -> 372312 bytes .../tutorials/indepth_overview.doctree | Bin 224033 -> 224033 bytes master/.doctrees/tutorials/index.doctree | Bin 3181 -> 3181 bytes .../tutorials/multiannotator.doctree | Bin 137334 -> 137334 bytes .../multilabel_classification.doctree | Bin 68223 -> 68223 bytes .../tutorials/object_detection.doctree | Bin 140181 -> 140181 bytes master/.doctrees/tutorials/outliers.doctree | Bin 107891 -> 107891 bytes .../tutorials/pred_probs_cross_val.doctree | Bin 20514 -> 20514 bytes master/.doctrees/tutorials/regression.doctree | Bin 110660 -> 110660 bytes .../.doctrees/tutorials/segmentation.doctree | Bin 1994473 -> 1994473 bytes .../tutorials/token_classification.doctree | Bin 176649 -> 176715 bytes .../datalab/guide/issue_type_description.rst | 8 + .../tutorials/clean_learning/tabular.ipynb | 2 +- .../tutorials/clean_learning/text.ipynb | 2 +- master/_sources/tutorials/datalab/audio.ipynb | 2 +- .../tutorials/datalab/datalab_advanced.ipynb | 2 +- .../datalab/datalab_quickstart.ipynb | 2 +- .../_sources/tutorials/datalab/tabular.ipynb | 2 +- master/_sources/tutorials/datalab/text.ipynb | 2 +- .../_sources/tutorials/dataset_health.ipynb | 2 +- .../tutorials/improving_ml_performance.ipynb | 2 +- .../_sources/tutorials/indepth_overview.ipynb | 2 +- .../_sources/tutorials/multiannotator.ipynb | 2 +- .../tutorials/multilabel_classification.ipynb | 2 +- .../_sources/tutorials/object_detection.ipynb | 2 +- master/_sources/tutorials/outliers.ipynb | 2 +- master/_sources/tutorials/regression.ipynb | 2 +- master/_sources/tutorials/segmentation.ipynb | 2 +- .../tutorials/token_classification.ipynb | 2 +- master/cleanlab/datalab/guide/index.html | 1 + .../datalab/guide/issue_type_description.html | 9 + master/objects.inv | Bin 39442 -> 39474 bytes master/searchindex.js | 2 +- master/tutorials/clean_learning/tabular.ipynb | 130 +- master/tutorials/clean_learning/text.html | 18 +- master/tutorials/clean_learning/text.ipynb | 1650 ++++---- master/tutorials/datalab/audio.html | 2 +- master/tutorials/datalab/audio.ipynb | 1188 +++--- .../tutorials/datalab/datalab_advanced.html | 4 +- .../tutorials/datalab/datalab_advanced.ipynb | 336 +- .../datalab/datalab_quickstart.ipynb | 138 +- master/tutorials/datalab/image.html | 64 +- master/tutorials/datalab/image.ipynb | 3400 ++++++++--------- master/tutorials/datalab/tabular.ipynb | 138 +- master/tutorials/datalab/text.html | 2 +- master/tutorials/datalab/text.ipynb | 172 +- master/tutorials/datalab/workflows.html | 442 +-- master/tutorials/datalab/workflows.ipynb | 1224 +++--- master/tutorials/dataset_health.ipynb | 34 +- master/tutorials/faq.html | 6 +- master/tutorials/faq.ipynb | 656 ++-- .../tutorials/improving_ml_performance.ipynb | 306 +- master/tutorials/indepth_overview.ipynb | 210 +- master/tutorials/multiannotator.ipynb | 146 +- .../tutorials/multilabel_classification.ipynb | 98 +- master/tutorials/object_detection.ipynb | 195 +- master/tutorials/outliers.html | 6 +- master/tutorials/outliers.ipynb | 552 ++- master/tutorials/regression.ipynb | 202 +- master/tutorials/segmentation.html | 10 +- master/tutorials/segmentation.ipynb | 1068 +++--- master/tutorials/token_classification.html | 18 +- master/tutorials/token_classification.ipynb | 184 +- versioning.js | 2 +- 186 files changed, 12518 insertions(+), 12166 deletions(-) diff --git a/master/.buildinfo b/master/.buildinfo index 78490854b..130d6ba05 100644 --- a/master/.buildinfo +++ b/master/.buildinfo @@ -1,4 +1,4 @@ # Sphinx build info version 1 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. -config: e4fe37ef90e9fd174f1301a92f0b3ef8 +config: 6c1b6ba46e7b82b74029d5189564c63b tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/master/.doctrees/cleanlab/benchmarking/index.doctree b/master/.doctrees/cleanlab/benchmarking/index.doctree index 196515a48e862ae2c76f2416e73d5aaedbb6045b..3787fc9c4b3217f68f324f26e6d3b4ab2f774c88 100644 GIT binary patch delta 117 zcmdlWxj}M6IHO@&W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Yl6jJ;xw&EL<_^XHPBOG{axZ5D0AU&;?EnA( delta 117 zcmdlWxj}M6IHO@knVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Yp`~S7qJ>e~<_^XHPBOG{axZ5D0A*Sur2qf` diff --git a/master/.doctrees/cleanlab/benchmarking/noise_generation.doctree b/master/.doctrees/cleanlab/benchmarking/noise_generation.doctree index f19c8a72cb851cf66f3be00ad071ce78f88b45ab..ed7d710812adeec8adafd0b0b3442093fb3f476e 100644 GIT binary patch delta 1464 zcmX^3o8{ndmJRWYhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+t;FtU=NZL*_z+-4PKKNiw$1ZkbFYs1JtS%9OEEbZ-^EjjOjglSY+1j)Dn@l|inYJ3Kb&?lBJ)0}EOPI;Db)`NVxqi(t zT0(|{H#?eNXD7?CC7bu!FXSXsE3?-_DYCT2PhPLbwYe@ekGyyVYoA<~DzJH4UVtnG zE@!&gMt2gt;itzVU0C44K*=n5b_*C&buCuJs`O!g7q= OOjglSY+1j)Dn@l|inYJ3Kb&?lBJ)0}EOPI;Db)`NVxqi(t zT0(|{H#?eNXD7?CC7bu!FXSXsE3?-_DYCT2PhPLbwYe@ekGyyVYoA<~DzJH4UVtnG zE@!&gMt2gt;itzVU0C44K*=n5b_*C&buCuJs`O!g7q= O_)u zbF!H^BbPcOeeS-Xy*$*mzdYztf}yr>*cFU~+?7>|D^%&Ka5^H2qavh)+=}81Ys2g# zAdB9fuTj^}7|hWsbGo)HMt$+4w>_A@7n0X&tNs;%Nu#TN>%%3Z*553WAcv;cp)WQ_ z>DR*jt=OWsYW|xsWBgP#-(+yAH6;dbG&bbW3@?FD7_-YZ@D6L;%v z+i9_(u2b-SmxZ<2&ppYQwnLl$`hcTa<5D5euzKbWZRW=bm^-<=0BehW zWx$!=t!gkg@6UNyyL)XI*(Ulrlb5kEWP5CgZwPh|O-;{|m=Pu)NMUU-*_+Ppz~q35 zJ%-667B&Zyg_XU4$<;RIfyr6ftP>!UY?7BS^miT`1E3q@gPeQWH<&zGz^=mN=|Xk{ zCO;`+<1l%ygtdTkppm8>?0XJ2=o=}&jtzJK@&5<4ox1L_z#!lvyX++S(s_#=6E{RZ ztR$1$!+pTzNN=}I1Jfb?b{C$&q*~5$Bc1l~Qt+_WW0**~95aJ4=u9(gm; zrdG`;7G`xO)nFk}C`OUXqHaUd<~TAgwn{lj>xy{VoWOF{QuU}1*D;4Cl1s1;sGej2 jQwbHW%EHYwlxH|+!m>L_ejL`7#V^*s;z|Aq&}{zzG)D@D delta 4230 zcmbuD-%C?r7{__fd*<)cCbOmDMG7LCxE)isu_abUfuv1q{cwhJZi$tNv%tD3H3|}p zW}JeeK%$#K?GR7?0p3Y<6={-#3ZYPlyeRad_b6gs?z@X~`Tc&r&wHNtdEav;7PBW7 zvnN}b+I6i)jrI&g?bV^sez&vAr3PIQXI0qM8R`f*I~-LJM`cYo915y#cO>YljOZim zBOr_2ny=H=&&cMO+nlK{^D$rI=xq#0_lW^;8 z+v)M)-cyMeB^u~W;wo(_pM~|=&(Ty&+pW)ky)U6!(^4_eutw%?edfmrm^-<=0BcKr zWx<)>t?Dqh;LmwjyL)W}*(Sz1lb5k^WP5CguXA=6O-)ZzmL^M3!8(<+{&KA{l`2U02PQ7^ ztfW%4NAdxeBct6m4U|LD+g*49MYEihOmx~Om4k=15kn#2a?A|Ipif=W&ooqgxKE1a zVq)LJo6MrkE=f5QxF?Y{8JG7fQYyWACXF7&T$;4FiDi=r(}(uMrh^DFl!0dOtVxQt z_*Ys04M-TYrvu`xJ(;J~?%`G{HStk7X&X)0*eH;}FJvX-MIw?HnU6b)DyPDH-iW*z zVN*=)(z=sBX-#4|>#25(^Q)Lc3yCGz2UJg@ jfT^Sk*F@oF8ZMB}DOh%u#K&PnMdD)PE1txk0NwTvNF*Yg diff --git a/master/.doctrees/cleanlab/count.doctree b/master/.doctrees/cleanlab/count.doctree index 72717fbaa28c2a750afff3d765160dc060b137be..c3e898c86fdcb2952c4a7fe41b6c00e41ddefb68 100644 GIT binary patch delta 3571 zcmX@QLh$Gc!3~~_hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+vY74c{!F*1<%ktqPjlEM#iktQ$M42)VYd zv0g!L2;Xt|!c2PPY-V)*Lat+LJ$94p*aN<8WH=U_e$NHYA=lPVVdu%U)iZhvxmsJ} zzmS`f7?T>vjU3KYTXMCYOHU!!ue-8ekrz4kn?(w>cu7ycz$9V6d0pMSAhNXTPxe!n zoE{s+D7yL9#oL_Zo3UB%j+H&>+NTFTX0(`YAjQbO{f0E-EixQ{WP*|!;}K)h-2ebn8myXJ%@`$MV)j5 KwgbCfElL0aZAi)h delta 3571 zcmX@QLh$Gc!3~~_h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroU?74c{!F*1<%ktqPjlEM#iktQ$M42)VYd zv0g!L2;Xt|!c2PPY-V)*Lat+LJ$94p*aN<8WH=U_e$NHYA=lPVVdu%U)iZhvxmsJ} zzmS`f7?T>vjU3KYTXMCYOHU!!ue-8ekrz4kn?(w>cu7ycz$9V6d0pMSAhNXTPxe!n zoE{s+D7yL9#oL_Zo3UB%j+H&>+NTFTX0(`YAjQbO{f0E-EixQ{WP*|!;}K)h-2ebn8myXJ%@`$MV)j5 KwgbCfElL1eJY7Zr diff --git a/master/.doctrees/cleanlab/data_valuation.doctree b/master/.doctrees/cleanlab/data_valuation.doctree index 20b3c1388a95995423d63783f9b211da32d09cee..86f86f7617fa509c01193cf42a8e0c3ad9a3e7c5 100644 GIT binary patch delta 477 zcmca~p7GLo#tqSohH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+W#7;liFt5MKl^HruDOyp^u{ExMPES-Uy*j-u3(>aMaMtw={k@+dvOIgbc|$&P-Eq*Fp8GEJ_|G}rrW~4ylKJKp@n7U589x6$cC)#u9C zq0bA*D?;4gFQTbfR=z?kc$YPcHwffUhSi$JaLNFY+?pxE~@nI zgxUyjdzj|1n?0Zlb|3F;r4`uG4NN?%?g#0PHD hS$pwP-8UiNrw?ch*f%cVeq`4+{>X3V-Wl3X{{hApC&d5& delta 4228 zcmbuC-%FEG7{@thZMiLN*$?v~vV?x!xS4J5A|$1d+C(i!28q6#ds~WQG=H#?ejrIm zhU{g$5Db@L60?XM;sjwgMKv<>ZC8?Ab)z@ZeG#2E|AKw}13u5^`9AM+&d#)gO)J=5 zHWOE5$nA*{(-}+gMgvtBO%63>ivhHr=wzzhwgp0i%;}KK04jI4u+`niN+I+DOI3eB8kV~| z+1imN4`iJIC^1~Mb+n94%MqksJrQJSr32X~1HB&!Q>f`6yVLg&wLb3eL#2mPq^=a`|_p@TZcB5nLlWU?j;|q&v#)~pIVEsePaZRvR{^uLXfnVDwVAdSpMf{V?B(RA#%v@BNF9&CEZk=2N<$UiilHY-O zwf%>wl`E7^A&*#bS~d!dZ>4uD@ecOz^Z{xCzaSS8KJCKgX057$mhjjqTC<56n7ODD z-wCzh=Z*l)V>i2B6YM@7@1W(_(e)>vRq)C%O=02xMX+m}rq^Zjx$|lAM%mo@8K>W?*ENnwp$w RXla?2XknDLxtyh&2LN0^6AJ(U diff --git a/master/.doctrees/cleanlab/datalab/guide/custom_issue_manager.doctree b/master/.doctrees/cleanlab/datalab/guide/custom_issue_manager.doctree index fb64fbc189a7f6cac561a2e22cf81952ebc2107f..2e496792700045e5d1c9aecf99680a528ccf5398 100644 GIT binary patch delta 64 zcmccfmGRD3#ti|ChH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo T24+d-Nv7uJhN+ty8KWx!`Fa&r delta 64 zcmccfmGRD3#ti|Ch8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 T$%%%RmT8F=MroTH8KWx!@wgST diff --git a/master/.doctrees/cleanlab/datalab/guide/generating_cluster_ids.doctree b/master/.doctrees/cleanlab/datalab/guide/generating_cluster_ids.doctree index 40a6a5ed94aa7babd9ebd6afef38b7bf88e8f609..21ed5b2b52708fa32dd7cd721a59d164852d9570 100644 GIT binary patch delta 62 zcmZ2yxXy4xHltx$W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<~fW);sA#`68iuE delta 62 zcmZ2yxXy4xHltxinVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<~fW);sAen6ITEL diff --git a/master/.doctrees/cleanlab/datalab/guide/index.doctree b/master/.doctrees/cleanlab/datalab/guide/index.doctree index 4baf2660da64da79013363497b252db08b499b90..39b5e1c4835597ac6bd72d3e9cde7f62700ac24a 100644 GIT binary patch delta 62 zcmdlUw>@q{G^1f!W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<{rk?x&WRP6ZQZA delta 62 zcmdlUw>@q{G^1fgnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<{rk?x&W3_6jA^H diff --git a/master/.doctrees/cleanlab/datalab/guide/issue_type_description.doctree b/master/.doctrees/cleanlab/datalab/guide/issue_type_description.doctree index e410f80ee370c2449cccf694ec13c0a2e57afe34..bc551b6d96a277d891bb7f0fef586a3bd42d88ea 100644 GIT binary patch delta 1421 zcmb`HZD?Cn7{~89&rM>4Zi#KPjilQx8zpvKn=~)CelsaEVmG0RIB{j(>uz^*X__oA zon@qUxH*UWu#(JYW3;pbUtll_W290T%A~Lg!oX70&AL~SXh)~uWb5WRN%LV*LB#vv z&w0*0|KIbRhjY%ooNelqZBircz0tnjfxv*$)~@dMwJUyEQFm*aU+Gl?9nZ*qwZk9u zdU|C~P?gnyEPJ)KT#s!dUa*SJcjn09IYJ6^gw8%BaDE&fULj4m>jUb*&={<(jK>GS zi9cP1P;E10RO2hBAUu5_pUt~<)6pXC{fO2h8HWb5r`6XYZN%Yuc)lqbQ}$?5A{kF; z$#hgpNik(m(v<;CQl!54K1u73XZGm0eUz@J={Syj4V#|K=53!A@ z??LdAX59Nb-GF0Pp^IJ$;ej#m*k(e4pu2R?8}t@^{dQkr^Y>r_`dtVwyQn9Zu-I|v z8U*Ql2yI2^LUJ8^_98Q7^v$}V4|Wk&$UJVn4(ZaGSID~D>=TE;SY9E#ZGD5X1&cS} zq`f9w?K^Q3KCJlgn;$@>8^ZsPdH6QV-1Zm37q{VCGLI8iAYcjbuFQncdy3W;7Jr0~ zDebDlkqE9X!m$1IDo~^_UW6|RjfBz0_JHsH0tp%`o6)@p5oSy*!ilG{)y8nHyS@>R z#i-RRm+}{0xC6I{{WM#cVqG#u*nroC&n`ih_zD-6Kmu~Bu<#qaB$}t$Ut_8u{{gG1 z`5X@>aoc@Jwq0aRHa_EWhR=S&R0ig`TVEi z8bW@>%S4=}J3DjAP%Ai%*U)1UC0w9l!1XFy&)T=G<*|brA?zyeKo5u`^sS05Q?}KK zjG4q1QFMvijdzmN0mhEb+>+|VVNuM|T*Y#%WFdF4+ax-eX$yN;8dg$P-HjlBJysyo zCYJYX1#+eYp><)LFpKs7o>D61QiU>8rUd^J)n!D@w21S0Pgoa4<5N5f%&NdAA!Rl5^_<<3Y z2&Su@A|wlXl_+8ad&(ybf$IOS+b4ZEo;3n{%DcY+HU#fz@8%%FhuC>YNT|zQdB^vSj6nqSJ1**pa$dTP2gO}eHDQKpG7xk<>YVc49-k~t_R!$=k&4FexYxM8R;EKEv}KuVM{q@=Uy z%KJGm0C~Y%tiC3#5!=2&9vQ)EKeQX)ux^i(F3FO&oJb~l1eg8L!gg!tVVF#DsGp9o zCf}UyA_f-Vgz?jV$jL=`rXmM$a}gZm`%Yn%n6?BKqo!zkqPzq%41Y2Uxte3Zh8R*h zmSIdFhtU2RZU{+5c*zgtNLC=nn6(X0Qc73gE#Xb}d5Fi1RcIn59JJ!QRVX7#7`p}! zqRwyUihNZuDR{45&}qzSXkZQeB+APgo7s`b61(BU6kM=0JW$KU#wD8z&zCPS@$~3jjg2i0jV#PFn>zgj@|G zWCD#k8q1)s`=}}LPvo}$Arp9{YI0M@a&L!BI#rY9U77?Z84j5YsU~`?-MgDff+k}j UlTp>g_P0sg&W~fkgL?Y#H)0xKF#rGn diff --git a/master/.doctrees/cleanlab/datalab/guide/table.doctree b/master/.doctrees/cleanlab/datalab/guide/table.doctree index 13f4509bc9521c506dc769e7f61b92268f348f77..196394de92297e6c74a0ea92174343acc39007fa 100644 GIT binary patch delta 64 zcmaFxf%(A)<_)J=4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE U4a}0vlT6Lc4O2J&VNLl202s~|*Z=?k delta 64 zcmaFxf%(A)<_)J=4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Yl6jJ;xw&EL<~qjhf@Ek*6TZ&~0GDMXF#rGn delta 117 zcmX@AbyRDEFQZ{bnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Yp`~S7qJ>e~<~qjhf@Ek*6TZ&~0Gp*G=>Px# diff --git a/master/.doctrees/cleanlab/datalab/internal/adapter/imagelab.doctree b/master/.doctrees/cleanlab/datalab/internal/adapter/imagelab.doctree index dbcf4f4760fc547ed58748f89c9b429d9d5998ae..d1047312b36a760d38b7af63b082e42f44acceaa 100644 GIT binary patch delta 6027 zcmb_g|8G-O6wfJi>$-J=wlITZYcgE`2W7Kekti-22|@xUKv4#!En62e$d;H4(EtO2 zQ3*10&2BSj>_9}sjfFeC#RvkKu)xMQox~ssH5wdS8ZywB7!vO5qeXx0=lKVGzMRiJ z=bm?8$Mw99>v_G)s4D!%`f#haHR!Gm)jwSw^!S3I`i2HiFdXvEd&cJp&GXb$%?4fYRQ&3xOkr{)sfYT|?6|4hIr{KedmrS@ib5%|h z%k8b80}*h(V#!`zBuegLk-g7c$IXJ3AI1#p@PD4%k42`#*UZc_0)L{i+X%efJz%8v z;_CB8)MMTrY)tg%Z1ZPN%)VXJl(mY)f>}8r^w>*YI{@v9wlP=0ETXSoMU)j>xB^R& z!_t*4Z1r1K{&_8V*@?lKVo%6E1+GHlS`MKZpVLD&v1QW`7D7ZgxBZFqOjk4_uI}82 z~Mxs_2g;0Y#=o zZ2R;+s`|rc{itf-i-V}@#V>zGRa<&L!ur3BCF9lF_!Wxrz9k@sNXAEzJ6F4dlJPQe z_+)u5)XZ%x&|fC@oy|u!y{4|gHx71Uqol6x136;grx$F1`9z7I-zleJRy$H5F8=l- z5`CIO)Q+6D8uMTgz4xXejhptM>ad8GzdDL=A1>LQL&HcTJv8Csiohmo3g{_h89!vH zkcDMb2ilP8Os^H=85Hwf&(jq7_OtXRau=jeLn@YQ;85_uLKUKGAvGcWpr%SEczF>G z=R-j>vOAUeJhqmKMtPBU-srK$4q9=d`AsZ68@ zcwL+xliwV}y8gc`BYpHOvTo8WQhC{mbXA6+{RDkyC=Eqmmew<5LB8d*wdo$B>HO;p zG!8U|!b^o8bYzd^RrhEcKRQZgesnLrBWM3gZeTPrG!{PfHr+DdqYlHyQg3+q#~3vL zjiA{-D9gv`25{#}1wIWlk1jg!H(dsnj|SfTmEZIt@Qstg9$HmkdM^8{)sHGai;d;* plS@o)=~!$k1rke>NJVl88<<9Uf2FD42^A1#>VLLuY%;k`4*>QqoJ9Zt delta 6027 zcmb_g{clrM7|vVh)^+O!ZD9n*)?~T>4ok;AjpCw_AS7S{6lGw#b?ZnL*pel~Nx-4O zs05igW~Ui6b|50+#=@DNVg!{;Sa9P@2Qf%O2?Xbsh72?$goJZ@Y1JS5T>pUQ<9*Ki zp7);Hbv2{wYDWJ`@@#A?_q1+qZ*`aX{fnw9N-I6Jm4S-VhRS+>oxh@PVQFAtNqIwq zzt&S#6{xK&35X7w4!~G6FCgYlSurJb#W>WKo@2(K%;$89Gg*GnbR0gKecpttGgt9c zvC7^CIuJhRtCrN&MKtd&7TE{Pb=)ji;bF|M4u9~}ek?K_zJ6YY5%`nEy++`j?ja+! z=a!r`q8={m!^T99&i3qrsj0V%nzA+#T|7SxgdTgj%nm?%LLJQIGmFq`mk?zI7cSol z^q%_Yim)|L*Tvk0+B+lLZ z6^TBD%imo&xDS`?O`}nyksh0HaYbO0DI@)BgEUQ#(;4|qTOLAHh-NNobjl?0t?c_(k{PY8IaD_KZ^)j!;EgzC2zM$pG_ox|fADvDrx}UJSO+PE;X_-M2 zSu)CKHn#Db*$<`DvqENrFQZ{vW=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<~qhzJOFft6BYmf delta 62 zcmZ1>vqENrFQZ{bnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<~qhzJOFIO6LJ6m diff --git a/master/.doctrees/cleanlab/datalab/internal/data.doctree b/master/.doctrees/cleanlab/datalab/internal/data.doctree index 4f59cfbc5dbb1535a38c025857c15e02ff48eea6..d54999be1f519080b5e5a8cfef5969cfd940f9eb 100644 GIT binary patch delta 5702 zcmbtYUuaWj6z5cLT1|SJrj$0!nJTGOyDd%EG_6)z*A^>wHnbSTYT9Hb)UDR3YpB{- z$EIV$+3L4(hf~%EUj}aLILz-sWy1C}7(`Hp4z|Gt8)Db7Q5gFp`);m`KL0+rufIR% zoZq?kaOXaA&8cS_g);|6GucQs8EQ=Jf3`8%6iue~r_)WzOe)gS8f{9oG&P4CGSPAJEUhF5W)dpBrasaNrq z(%nU{dNn`g9m3VCd9Ck7P@UbCVi{!oFn9PFgJ${SlLxVSv;1+O2dg#9m)Gt^RcC|y zP}M7SZ9tp2y#5lF=LEMkta3p!O^9-LGS6Sd+|=NDKF9P7SqK+pl<-Q^M2G9&Eoy#=IAl-Cz1 z_(05u&EA2#`(MSnXTulZ(yRIXcn+JoEo_R=9)mv_oW#ACic?8be3f_z*WfS=b?@NW z;WKCoe(-ttTIK~E_=lrKXaa2Y&0`xi)Wvjmg?M!IKG;QNpuq56dJQ^G!V9tz?A(ucv}29ib3U>(+2t-jd;cveG3r)~tjtcQXox#U`EQMd{ zju(gLnV*NjISB6qlWQKnhTRnd!dx^t^2aVPNNg@nVG-^V!!?HWdMl0a@qepVKm&C+ zs)`A_Z3=MtRtb%p8uAKXVOdqwqruU)h5}Z;lYWse`DqYKrqc|?6qJWnQ5+lS5|Xji zv{%E4R8F42cEg#=LXa{#MJRlkHQ7&FV>=#ste-ZNXiTT3mrUzii0Wi=kXm%?6qrtgX{$W4k9zRX8nQi2 zT^e{x;a6I|gY+BR7sKH=KStQi(I@h?hV}UoDwnxKl*aSokl5Et;bM?8M|Dk$emLCkNtM}f8-U%n*aa+ delta 5702 zcmbtYZERCz6wVpkZqV+o>#}T(NC)W{I<@QEM++kxZVMw!)@-3647!!lX6hKiT(iN- zFbYP4Z1QTZL5=&t9~0D>6M27#kpzB`kkmwC)I>-$(GbRrW{L5G_}*S(_WOC0`}g@c z=RD`$le_S_Ye79bC_IvF36GCWjfa|3si&i@O_6Xil4)&9M-HV9rdkg+G-VnZThi%N zG8~O&l99%Yn50DjRbIcFe=eFw1Qpb}^$wK@pK%mZ7VgRlu5?{o4a2Lr&%GBkuhgq} zTj|~+SiPE`@DAbX)x6R7JgCm@O0fzuev~`>j6t(};nBlby;=Sw(1X>QFrz!|#K_v8em}OPfU7md|hkaUs5w z^IP|UeG?t+#eB765*u_v#JYXrW};R+=)8v2z_ISH4G20Qyn8(2a%P16y;p&>iSqga z1wR+_VY7GO?*5mt?%D7qxb$j%FP_7uZVQ_tw9nvA2d8oGrQ%f56gLw0;2Io;q3&Hg zKYRvF!5yE6FK1FZ@Q+4|&;;1(TgM*PP#3e=HR8ee_h1*5fda$3@m+jnq8UwuqB(!U z#jhRDp@FcC1ZM2l!IR?88NXQH)g>BE4&h~SU}h2QE6<(&t{7CFJ8kgqZ>~ZEq2MC_ zqseDyFM+e*D{uFPF!Ox&`WJo-Djef+5beF|vA*o24gBrxzt99dM)&FE9^pa_v3sId+4pKzNPJ!t}n6}Gf2dD=Rts&df z)TM#96n?GcJ50a9eK8!4x5fy&Ir>Dt*08=hM&&Yhgwl9k91{C_DO?P4Zd_*tRlE}riQFyK|JWZ^{|EFY=HCDS diff --git a/master/.doctrees/cleanlab/datalab/internal/data_issues.doctree b/master/.doctrees/cleanlab/datalab/internal/data_issues.doctree index 6b3affe1fbd231a7dcdc4e5a5f5a46fdc8ff2022..625aa8a6f86572471570fda1c3366137800794d1 100644 GIT binary patch delta 2812 zcmex*o8{|mmJOkdhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+v|7?~IiNYyrZBBRFU2TVt}$kI9a0h7gK6TVtnYKD?UZMD#jaeSA1JJ8Qa;7uAzw9DoK0 zZ#L0xP@upC(PZikp6n~ZyE)$XIJsdLvH4nXGPzz4nJiZ+xcOUXD+ig*kJzjoznWaz zBR01s?qed`<}WGCmZpSZQ^mys7*lNIhbPF}#pF*&wf7?{WSHcx8SqRgbtvF)bhm8&qfY&Pzx z=O!z?PY>W=beilti)ZqwTdJFDXPA)}9bjWN`_7s}X5|J6Q`X537PD{eTY7?`(14io zdsVAASs?-qQ;;bvlj9F^ZPqz#N?tO1D1n%u_h}P(2^8uE-pT%D9Gj>8OX4KUC)di~th;X1@Rc delta 2705 zcmex*o8{|mmJOkdh8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroVd7@5e>HrY`zX0s@BKNsmXg0xOHP=X_z|&4K&}naR_>dA=|+ z3t3vzCp*XpZ}ydlCeP;d%?>gb$gp{{qhb;}Sq{$G?4apMUexAnR@3fNAkWsxYTA60 z<9$5H(hUye$-WZ2o8x_tvyyFu#O7ez*4z!NE|ncciQiRnWy#EBz{r!>{ITE!CAMc4|0mP$o63vGw^(Ge zTxAR;NnWdd85yCrnX!2{8QLZ@HaBlBXjdYmL<4Fq*lgTW&rL@1W^B%wyr7MH@`+pO zn`>v7krUcbBQ}T6nnX_Jwee8l=I*7Z$?-Qx>yK3(;-vd~^TtCP$VnO-57liJILRYO zx{Z?s{}oJrf0JkO$y@))*S)#)4wC>`+G{8Cec;(__|}=6fEN4*(XRJt6B&tYv*5qy zoMbo}n6ReH@Gy#QU&g_Bmz)v=Xux)$0c2M9vD58^7)2*X%o5&iBEq&uEyInUhv#T9&A9l$2s@lxSj}n3R&5YLb|iWNKk)ZjxkSVrFQNW^Q1X fWS(SdZf=;mxq)#mvk}SK^d~2&uExYW@cENS6QrYnw)HGX>MX+m}rq^Zjx$|lAM%mo@8K>W?*ENnwp$w fXla?2XknDLxq)#mvk}SK^d~2`7t!bMRcoewF()y4rU2&5Olz1ld$q8?E zkThl?--yk8aw=?OYv?J&+-8RWd1kU5Zm?M{WHXsjzd0dVmb}y+HyNmP ivt~M*E!hs|-F$k9Hkm;-*&%>;^64cqo7XM7F8~1XPhGtL delta 1125 zcmeBu&(!;#X+t=pVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQGDXMoD(kwN2hAUa;ATvz>`7t!bMRcoewF()y4rU2&5Olz1ld$q8?E zkThl?--yk8aw=?OYv?J&+-8RWd1kU5Zm?M{WHXsjzd0dVmb}y+HyNmP ivt~M*E!hs|-F$k9Hkm;-*&%>;^64cqo7XM7F8}}j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<}#*VTmY2U6XE~> delta 62 zcmew$^+9TbE0bYHnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<}#*VTmX#~6g~g| diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/data_valuation.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/data_valuation.doctree index c266b5bbfac62dbc27756f1f5c61ab85147422b6..2129f3be701a49edc909ef7df401557549f2c1c3 100644 GIT binary patch delta 2628 zcmccdp5?}SmJQL2hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+W#81IsyOVOxqvjlSk=EeSN$Vg3-Ax21Swh8Sd$ImeBo5INoZJ_qe_0e^d z*!(K?6&WE8_xHg>JxXl9ll+Jh+gGPAB_q-{H|CtgL%khskx0fV046iwPC{q&sKx!}-B%q-z64{LIb&mX&dk zsnu=+6B&NpT)0b=oC>CJ*Q(8lhtfF7aIB(H!Q_TF(vu%t5ZpZF%mi|Z7pM`NA6(c@ zUfm3Gf!gM{`;9#0d0=zH8zoILv;yOJ`Z^Itw#mvZ!rNQL7+;VX+mjcVv2M3fU`!=5 Mp>5ArXUr7<0AyJ~y#N3J delta 2628 zcmccdp5?}SmJQL2h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro6K81IsyOVOxqvjlSk=EeSN$Vg3-Ax21Swh8Sd$ImeBo5INoZJ_qe_0e^d z*!(K?6&WE8_xHg>JxXl9ll+Jh+gGPAB_q-{H|CtgL%khskx0fV046iwPC{q&sKx!}-B%q-z64{LIb&mX&dk zsnu=+6B&NpT)0b=oC>CJ*Q(8lhtfF7aIB(H!Q_TF(vu%t5ZpZF%mi|Z7pM`NA6(c@ zUfm3Gf!gM{`;9#0d0=zH8zoILv;yOJ`Z^Itw#mvZ!rNQL7+;VX+mjcVv2M3fU`!=5 Mp>5ArXUr7<0G1+AF#rGn diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/duplicate.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/duplicate.doctree index 2b8621628969559bba461bd8bc6ae2bdb643650e..a60a9643e3bdb9c1a7820eb2dbe24dc4b8db34bb 100644 GIT binary patch delta 2632 zcmaERn&s_jmJNZ7wrQC;X=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN=1~`N_rl#rdU0$*Gek+8b{^$T*kLkYrlB_WVQ+7B zUB4u^0EEejzP`gh!hj(*WA1fOL+BK%8kZbz~FW$|O^QV$)J4pNPWoG2s?w`gs z`NKM%$tJNu)2E9ws&2O0c!<0NkUcs6y!2!pf1b_z_e>z8r~#%SxDk{0?_u36esB$W z^>6m(`16Z+$cjyn3)D6rzVk_gEbaZ%<9Qfaw^y+-zU3g#0AMa+-L50R7)EA#nBFVJ V$g$l^oKcFr04UiGY`Z;S1OTU$LEQiV delta 2631 zcmaERn&s_jmJNZ7HW_7RhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mrryf`N_rl#rdU0$&(uuOg0~6oXcoPvMG}%+Luh{RAJ*)+sz$!rtEM zx_(J+0SJ>5eSMo(E5D>H>{&NwYc`OVctEiaiayrOhqR9}kr@s!BjWUXD0Rg_!D6#+2na0qFvnMJ9++wX#eP4M2YQg zezz&Hoh3+*OxrgLgxsLS=F{P`$;-d9HXFtYa*>`)fQ5elWdAhY&HNc6++=FsP$Rhc zOK}xHdD=JYwM280r*(2d5AWu%K2|mgv};UFA=mZ~Uc8$l=T9Zqc98bn%go5N-9L?O z@`rUilTBiSrcW1VRNZW~@ep|lAbWEBdFjbI{ydxa@0mbGQ3Fgva3dz~-^03D{NNh$ z>fh|m@#h!ukQJLC7pQGMeCLw}S=#%j$MZ01;IHMGK0Z_6X*miru2mpZtPz3-0 diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/imbalance.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/imbalance.doctree index ecb0cad532e2424f3a14e6a19a0e59e2b033daea..8769952481e435c0d16cc97420a37c4c0fe329b7 100644 GIT binary patch delta 2563 zcmex0mF3q|mJNZ7wrQC;X=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN=1~`N_rl#rdU0$*GeYcNuR!$T*kLkYrHY?fMl{eoO@Zlm~`{cE<9FyNm|0Cao&1+?SDRY4E*O+9CFjcgK+oFf4nov4FiyNPrtY1`X8iSDkz;2 z+fzgCk!kzp2jQiZ*lZbfjZB*-gZ%wDb{@Hr)}UvwIWD<|oy;WDprM@8+3xF64&+#E8|+N}S|+qT6WmoZf6U3bbFFVoA2`dMcYQ z%p)@h+a@nqBe*$wMIU*^M%(5EYc}wb?(fZwy9CJ425fdr+#G!3iU#R6LRu`qpnCC9 lh}?z)D7`0qwl1Tsi1U9 zY)=ijN2cwYAB2}uVzXt`H8O3U4D$Eq*m>keT7#a!=D6e#1zM zFptb2Y@57bjo{|!6@BCt8*Q5xtl7Xzy1zF!?h+tF8?f0iadYsAD;lKR2x+kZgX+ac lA#xiIp!A;bjbroS?}8KXXIA>z$VvrB~Hd0i~xf)R@wjn diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/index.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/index.doctree index b2ad4c1a10234c9abfb90db06300a930592f40a5..bbac177f3a9ad93609b44526dabb899bd8e37e04 100644 GIT binary patch delta 62 zcmZ3axkz(EB%@(kW=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<}OAFVE}o760raP delta 62 zcmZ3axkz(EB%@(QnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<}OAFVE}Qz6Ab_W diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/issue_manager.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/issue_manager.doctree index 2acd7837be33a336439234887bb173202280141f..4b3e332e4c28b0a1ff70c9ccf5f4ac665a78c6e5 100644 GIT binary patch delta 2506 zcmbRCjb++5mJN}NhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+vo7+;W~ZL;Hvn#uAk4WwHL)Y&)yo*bO zl{_OhcL;1?CsXSu2_5o6taI}XDK<6oY@IyAF`7J`o7Xy>qb#6VH~V@tkm+S$RD73y=}Yn?+L!$P0(A%?@cF$@4$NX8x=cGHnJsJTT_~CAPoM*Q3Pt--SCUv3+7` z4Y`q~;KsfAa@8qLvXV{rWIbQ5&B?7CJVvJW&Fc<)B(Hkwn!N6Sz~-#u+T{7W zYjeOwQSxfXuFVQJZOOECvR*FFW|ha1b=>{x}+?!**Ns_65J5c|2 SJ+kZuwWRpBFE(Z@W(NR(-X16b delta 2506 zcmbRCjb++5mJN}Nh8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroV77+;W~ZL;Hvn#uAk4WwHL)Y&)yo*bO zl{_OhcL;1?CsXSu2_5o6taI}XDK<6oY@IyAF`7J`o7Xy>qb#6VH~V@tkm+S$RD73y=}Yn?+L!$P0(A%?@cF$@4$NX8x=cGHnJsJTT_~CAPoM*Q3Pt--SCUv3+7` z4Y`q~;KsfAa@8qLvXV{rWIbQ5&B?7CJVvJW&Fc<)B(Hkwn!N6Sz~-#u+T{7W zYjeOwQSxfXuFVQJZOOECvR*FFW|ha1b=>{x}+?!**Ns_65J5c|2 SJ+kZuwWRpBFE(Z@W(NQit}KWE diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/label.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/label.doctree index b3653eb119953f83ca7d15c4fd041bcbe92497a9..803371b437d106b7cef1794db876a8c0215a6f10 100644 GIT binary patch delta 3034 zcmZ3sg>~5$)(xJFhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+vY7%z~aZL(oY&UA|iM*hj)mh$65c%L(kb#v4xr+eBFp_b+kvg?cZ>ke9>-Sz delta 3034 zcmZ3sg>~5$)(xJFh8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroU?7%z~aZL(oY&UA|iM*hj)mh$65c%L(kb#v4xr+eBFp_b+kvg?cZ>j#7TEIu diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/multilabel/index.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/multilabel/index.doctree index 4c75814a29d780696c9459af21a1939ffdd728ab..5e1717e32d5d56cec4c732aadb367a77babd9304 100644 GIT binary patch delta 62 zcmaDV^HgR-Fr#5wW=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<`%|>JOGn)6Vm_y delta 62 zcmaDV^HgR-Fr#5cnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<`%|>JOGQb6fXb( diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/multilabel/label.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/multilabel/label.doctree index ed00be1d69f38be6a6e9095f74ac2ea57b7bdad1..04e4f5607e6a512cb9d7ea3b1439aa874239b265 100644 GIT binary patch delta 2706 zcmbRBnq}5&mJObahH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+vY7(bGsZSukRrs)Ta8TlvcvJ{eTD^UB)$pS{go2yw5vXHG^e6uXK z7%O?&H~$sr;vi4!bfARxdV)IhX z26DYEU?j1bUFRYb*^Zakyi31_OxrgL81XVwVDo>|6=d2BOy&}sJ1yQ*;_oP%4oYl4 zVz-tO+k>4dDG9oDZuOLC=l8xtp5u3HzT&r=ytKY|b8Sc{c_F@c^MSDE#$9ZwdUHqX0<+f-Y?o* zw|y&lQC&2-ZoAHAracRJ$#OhMyY%Gs*SR<6oNDDE--ylYuQO?qrG3`+8b-z+bfARxdV)IhX z26DYEU?j1bUFRYb*^Zakyi31_OxrgL81XVwVDo>|6=d2BOy&}sJ1yQ*;_oP%4oYl4 zVz-tO+k>4dDG9oDZuOLC=l8xtp5u3HzT&r=ytKY|b8Sc{c_F@c^MSDE#$9ZwdUHqX0<+f-Y?o* zw|y&lQC&2-ZoAHAracRJ$#OhMyY%Gs*SR<6oNDDE--ylYuQO?qrG3`+8b-z+3aH-A6LxWvSD`dbR;cIN9C65ngRH`- zX|h9`;O2zWo5|Jw;1ciV%U8CN>v)iMkGrqPwcTMk&*qQMn#s#9K)(aE8^7h@Bs1s~ z>e(hw_{zPR`FkOG9>|#P$HJ(w)s(S;ykaI}J5c{xUb37Iwp)7pdLhPq9tsSY4m5y! z`(1g)Z5m{m(lq_QJ0sh6A5X^H>i~x-@$C>~D delta 3021 zcmdmUn03!#)(zf_h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroUC7_XC|ZL;9Jyy-XM8TltOvJ{eTD@gm~1zf_LRaoz`kf(j~03aH-A6LxWvSD`dbR;cIN9C65ngRH`- zX|h9`;O2zWo5|Jw;1ciV%U8CN>v)iMkGrqPwcTMk&*qQMn#s#9K)(aE8^7h@Bs1s~ z>e(hw_{zPR`FkOG9>|#P$HJ(w)s(S;ykaI}J5c{xUb37Iwp)7pdLhPq9tsSY4m5y! z`(1g)Z5m{m(lq_QJ0sh6A5X^H>i~yZ9*xCR9 diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/null.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/null.doctree index 7490a0b323b2d8c422283e6a99555591f90de27b..092bf199be2bab24164a615610b67b45dd1bb58e 100644 GIT binary patch delta 2688 zcmbuA%PT}-7{(jsj5CulB3Tfp(Aa2h=gdJFL@}k zHYf`-UWt{Ijg1wGNY-qGmE2DL0?+&bzkbj2z2EzNSBu80MPsba;MRHvw2%~19B#G8 z<5omjQF{UbQPEVXv`iM&Qqk*jYO>R-%Bm#Gu7HD8CyQ*u&e6W1jdT5*XOHE5Y}uSa zM=7-i7@vg52whuJjS$Lc%a)7P4YMkNqoFK651DnGr@_2J?6ksEC4A$-Gnvp>$tvt- zD0_ss;&b%C7fL3v%8afZD@jmbMv`X^wa!QR delta 2688 zcmbuA-7AA(7{(iW=e5j4azMO==0vmaO&OwCtvErFkL|TLA0@Tvvtx{oK!Uy{x=mR>m3>#=cRj!9O(N*IPu< zI@}>GTPP_V0DA6M&QVw>*67^jPo>HSc08akZOc)Ja`ThnyOiq zE*;7qCa&xPJ@BRSX{<7%gnlgr3e3o2T0pIHmQ&QqJ9YspJyyC?!JaS9dBFI)y^N}A z$IzbR^>t|AsYVxyF1YWIz-RFgbG8(csksZe!@oE=Tf)dG|Cx(vz3l`KUQDGOo@DH; zozND^y*GLmlQDmKO1mH$#`@#lLA|_s9nYnb`H~^?sHTS3jjBc&f*vOkTJw!eiaK} ysj1=e37L1~eu>_127xz?BKIl{7+QGY$n_LQXWaA3)BanY3be<*cnW^pX8r*2#CMed diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/outlier.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/outlier.doctree index 51f32664f30ef4beb1d8bb36f6ebd8fdbe9a7c39..9a9a216c69e77f896021dde723d2a7ebb1dec38e 100644 GIT binary patch delta 2967 zcmaF)oaNpF)snYcgb<^!mX{76B6Y%zX@GWMlm%R zqFs4&Npv|mAq~@hB=#AZj^CV+IEzf1H*ZKL*H&PVDR0hC*CW$ru=cXd-DLV1teq>j zmD~suC==KmTI9)2Mj{18*aSzm$pr>1o8zkdILI`@-%Mb0QL{8Bnc5q=MK?$EvU8EA zeY5C{Cu9cQ=Jj*+$f;yN!6vXqVDsX|+sO>|%>ru@$Ox{@3%3@N7fI7L-`*!ehK=AN zVS*$7<}D|x$+21SW6NaAE4-UOUaTgkD1>R(yEcoLjO3yCv43;NlMEixwQg4Yn5{{= vHgIt9d$MkKmu4h4RRVJ)>-J{~jIYT|)sy7|*thqoF&-i#Lv05(k29D6yosyv delta 2967 zcmaF)oaNpF)snYcgb<^!mX{76B6Y%zX@GWMlm%R zqFs4&Npv|mAq~@hB=#AZj^CV+IEzf1H*ZKL*H&PVDR0hC*CW$ru=cXd-DLV1teq>j zmD~suC==KmTI9)2Mj{18*aSzm$pr>1o8zkdILI`@-%Mb0QL{8Bnc5q=MK?$EvU8EA zeY5C{Cu9cQ=Jj*+$f;yN!6vXqVDsX|+sO>|%>ru@$Ox{@3%3@N7fI7L-`*!ehK=AN zVS*$7<}D|x$+21SW6NaAE4-UOUaTgkD1>R(yEcoLjO3yCv43;NlMEixwQg4Yn5{{= vHgIt9d$MkKmu4h4RRVJ)>-J{~jIYT|)sy7|*thqoF&-i#Lv05(k29D67&pC* diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/regression/index.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/regression/index.doctree index 49afbf84563735523820e4617c446aa07b4b7afd..d74d3d7f321d211287dd9dd419c59257cdfd55f0 100644 GIT binary patch delta 62 zcmaDV^HgR-Fr#5wW=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<`%|>JOGn)6Vm_y delta 62 zcmaDV^HgR-Fr#5cnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<`%|>JOGQb6fXb( diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/regression/label.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/regression/label.doctree index 79881bf4520af891ac28d88eb7164d901e690ea1..8c745bcc3590b4bc650b08349f6601afbc8f8989 100644 GIT binary patch delta 3483 zcmbuC-%C?r7{_^QXIgU;Tj|6SB#4O0v$gHmMd8&zp&TY+O4N?qnyeqVa2FLebb*vw z_%e1;jnyiIf~_9h3lVuybS1f)=w{Ify67f0g1RV1=XjI1`|c0;Jm2U0eV*q%oa(x< zx^B$%F?(?0LNMxz`nnye|A@oqRD7yG5ODf}s;lRy;#7N_Zo3>*WVfoQE=92i=qjrK z7-#Yf?=-|}7u3lmla>6^cLPShG%aie$V%u1PxqVYdh-|}TnXjr&CY2gD;?e2_Gb&! zbe^P+yApshIYSd&=Pk9P#N_9QPbNR*;XV`HaY(JTt7?m(p8!e^#El5iGY!coW zVpm814wlfdz8#)NRo$lz*ahUN>&!B$nmb!Xy(Y%zP*p?lHK0nB&~fz2TQ4o5>E4bM zfo8SMPx0Q9O?)73)t)E|jYrc+^Z(1(=+`w5lKAEl-P6D8Gh?InnXx*$pnxUgHLL_B%&VntOai(Ss7tNI4*XLvJX2jKKW&eb&8dXEDDAov;vQ@^_|tl c+mqfnYJP(klQ-E^8{}U9HEI^i57_Ybe{-!%s{jB1 delta 3483 zcmbuC-%C?r7{_^QXIgU;UFpOUB#4O0v$gi)qVQ^AMc2Ul|s*17s!mQcd?8=|=M?B3udP>Fus*BrAdLYyYzi zYC2C+=RFBPnVg|Z-4{)@qr~JFh)*UzQ$u|Qx@(i#YFE`3L*SOQxOs^-pDQLhPQ4pr3!-T13L!m>JjgVH_=Sv_K0mFZxa=_!&xUt^ z>H?QuFBm|4?@gmxUXv*D;Sus#5b+l z^S7K4icjF3i6S%5{LiH(yu?b8l@CC8ir+uT4x^JRgc^8C#`)DNjr_5Lozz3U&#Kv$ zJ$&^z`-&azCZE)JiAO!`c?;e|vNFPkaGdWx%RaVZeDcc_>*6bySriO`YXzQQ>pLsN cJCfcwYJQXFlegGZJLF#c8a4CfhirJ~KM>hp%K!iX diff --git a/master/.doctrees/cleanlab/datalab/internal/issue_manager/underperforming_group.doctree b/master/.doctrees/cleanlab/datalab/internal/issue_manager/underperforming_group.doctree index 976445b62a7582a74d50e1c9020c7a0db91af875..a6ff95b197a1d5fcf2b5a341107afd8e283e1895 100644 GIT binary patch delta 3789 zcmbuB?MqW(7{+gc+PG@L_!2KECr@f=#++mBkGUp$CfRhK)lmS?E1{|aCwAzX(V0}&Ho z{L}9Ejq_-`rF=bVwMYVLJu|chwf4kbA(u`FKcSr?KakI=5RUV*2^}f#XVlQ8i{Gp( zqJ_t?RTxbz$$cQo6E8Q@o!8A^Zf@_?(&Fs9mEdC^uA$*8mh{|_QBe6;5qsouo*hAs z%&sD=dHykEp!Q`e@?VtOnk+646|i4=Q2%CN6JMNNCy$n}Y3zL;=h+$Z*)q1J7|hUq zT`LDgM%oqdCH1TuU4nFtQkp-)R*zk>Gh{~8)-65jVH>5ljjT|1G_i-so9F*2>1Os` z2lVl8ict=>u^3Wlc7U8cO!W>xo?XaW_n1aC}j0LNZP6|eZBkxe)sQsu5&-f0Y)CNrD(^oGw3-3CrVIjxM>izs!q+LHO-$M0|L_{vAY1=B7MgvB&-mc;UhvJ z<#{}Ez$}Djsk`SY(r^y_={o?_#B*qM-vDZTe(?}$Rb2LBEzeT_z!ktsLZ}Wk`oc!Q z_@~{88|Tq>OZZ0AS{W5kYy0pz)asADLN1*UdP2KLe;}V#Ar$AOlNyrW&nTfw7r$9o zM2nAOYcQHxlKVlFCthx)JFlC;+}!R})6(3#)!^eFuA$+}m$lrHkx|)KGxo^iJUfCM znLR~V^Za8_M_nrx`XkrhMH_!i5(#`C> z2I%A86oV8v%VJ2O*#T1aFx9&Nd3GUh-D7fTVU#tX3!Sc!N!m%)2=dXEDW;U{3HGh{ EH@ODTuK)l5 diff --git a/master/.doctrees/cleanlab/datalab/internal/model_outputs.doctree b/master/.doctrees/cleanlab/datalab/internal/model_outputs.doctree index ae8b4e4e5775f31357608fc56ac776198a2911ee..858ba07dc26b121cbc00a3950416c583da52e0e7 100644 GIT binary patch delta 4920 zcmb_gTS!v@80OTLbE~bI*1|4?2$tnG(;XXS1c8y1iuBM@aH}n>8OD}HMQf#$CawIX zb*0{VsaE~eKr$~BA@*_#!n6!aC`%-4K}feVj|e^Xt%p5+m;XQC|DD6ehg9Q3syo{R ztEbBAsm-f(nsZz`SLHZ!MW<`0+nww5xbpH>i@C1+T$|P65iK^C=*kmCtD74I4FIFN z>nk~Z`tIrft{8{X;-q5`(n|rok+*1C)EJxt`W@J~UJlH@J`GcqP0!~S#+RV-1iWJ2 zw$8&@Bk0U3n~}^bv>eLr1=UGq+m893h`2%Q zOJw0!?Qbx69h(bEfve`b>pQSzH*nU58q911Z!H`F%*qwCkKY&Bu}oG|N12Y+gfjSZ zsff*7%^hXWL3Oq`+@LC199mvmuGIj+lze_N>{ZjQ;r;A!2N3fLg@&8=^dbW&@GjW9 zk=`C!XKyq6t83!Fe|}Yxo=tAL^&___%5}L`~ zXUoyU(T6qR;xr+cFa12?&B*VQg z1IW=&>1*ipSSzrOgg?cWBL_d}fj-5IR8pvB>AUrR(6s*mKRi6)JIO-k zeTU!&ZN%~BXp2gKDnwp~LU3+|0Df_JqOyZRqz)#<=Tm0m=IEGSmHVPl$ zI8DHH)O~hi^h~Odg5Q?me6pYkm!t{(xR*Eum0#EtO;Vm^1AUT0=xf delta 4920 zcmb_gTS!v@80Og2xz$$9bfFd@g5BI!wlk#^AyAY`ksg`~>e|ZEP-b>9TI)h-;>urI zSL&^oYT8c?#A_5G_A&#pETapQCLv}JQrVeDf*$+U!ydoO|DW&w&S5hj6f++bZMy{1 z-a50%dEkiCu*qiIm?oxLOl1~_m}1_w6^N&rUf zS*4t~VBdm&R}4aFMdS$xSxGL9j<+jY!!bC!G&XG9N_H*26^5xwrepcJZU|JKgO|iy z3q}3T@{^&czl-yPqMo#}5Pe|FlEesX>pZr00-af5){$YIiajaApgJkcMVRloh-<}{ zp)CAH`fCh+nhhBRz*Td5Rxh^f241_h8Z+C#JF_PMvr+}s@cX=UER$8#Td1bZo+SQU zAYwCDac|)usLn>K9aJTwRmEG1RZ1Y30cR~~4}{a6v4iZeyAbm-g_2wL43;Os*38gMpo-r-k(qGY<3s+*!{ z)+IGs#t?TOqY!9#*0lqDcCrgSN1r?wf&*y~J(r)+E5IC7H>r4aV>t>pdOm@|M$ba- zzfg=Gj>fC>?uZjoTD~^ZW%28NE0TDbM$ZKgMWi$&I2$^q5#_!C7v-Lj z3!}693QnQtgh$XjQg)!{_{T`kk_2b#Q!{Yo+&3@*z$C>(bUmP?lE7QwO6Jl0Wv~Ld zk|4bFNhFEZWJ-DQ5Huh$c!%SKJRW_y9%%{51@l`K(h>ougYsuIEtBEAXKWf-!92tL z$x-C!|L7~}{8R_9zrP67^z&;DPQv5UYmkGV_dw&*I?B%u=fHQ<|Dfsl0e*NmylqiJ z@&l_-3)%?c4gOYz09A;z4w>L$gaCeVIQ)`>Y@`n6#bYVCahrciBgB9t(p6}^_jJNX zI8JkLHT7S}@i#9MqVe0(UWyWw-uyUW1osl8pyJE9{=@`f71A+s#&!NLiNc5)@FD;C Mr1e)Ag(YFX0rkURPXGV_ diff --git a/master/.doctrees/cleanlab/datalab/internal/report.doctree b/master/.doctrees/cleanlab/datalab/internal/report.doctree index b25a8eb82d092d3c7372480b2b146d7a4659c917..3fab2289659ed1c51dc99dbb5fa9b0aa8a21473e 100644 GIT binary patch delta 1062 zcmeC{X6ox^+ThJ-n3kE7R%Tk3sBe^%Vr-OXVxE|klA3Cgn3iN}VQFrXWMN`vXpm-Z zV3uT_WNL11n7X-!@je^r+9q%044wRtV?OCRH*e(pMTR@U78>%@l5XMTj{(t>_X-Mc z_T_!TOrG}5djtu7EXtH#cZnp64AR~Y` ze++m?PJ;LtP_?->xR$&Ss@l9X%#?*JeoinU-i_l(xBs@je^r+9q%044wRtV?OCRH*e(pMTR@U78>%@l5XMTj{(t>_X-Mc z_T_!TOrG}5djtu7EXtH#cZnp64AR~Y` ze++m?PJ;LtP_?->xR$&Ss@l9X%#?*JezK136VafYx z$RpcRGxmIJ-n^w)=`O`oHPcFGGOB4?F}+(;EnSVvlC4Q`OS58{CTBS3`R#R&kr5rG zgStFM@?T#Vmj>yre-;p%y3Ow!w-B+ZPxGH^wRM2ih(6-EP)`elj!{qK*geTc^k=<$ z%vq{UFOB|9r2&A&c=O5;I^M7rMB;1e#TuyCY5siM4;V>gVXXH)YE2Bl){{F6sP!zN zqP^}7K1HqHM{c6lSNCA+i_yDC2rH@Qlve`0{xDMOK2cmrRe@gF^Y|As-AZbaH^z4W zBMJ0)VjQ)enymoJa=H~;$|6@MyU;%OrUrmwFGf_H8Af6tXDy%m^f<;OmAm~!*$`_v zLOvSj2!62q5hz;Nd1ZALn{tv?RvUSFts?~X-IoY*{PhHC7x;}gS?s@)sJz|IZSOLO z-H1wD-abI~?VyginIi>g>X*20=NS@}|2P$j4b-`Nox)2#4t$Zo8C*0{DE>q4_hlv3 xul3xy`{XJWI7filr>2nrZ>lBN9*E$2P<$mRe5 delta 3077 zcmbuA-%C?r7{^)Dp_8Ugb`vxRj13ez=eTyxjLKm6BS|?jMyVKQ$DImeFsxicB1ji0 zg7jR9Fd`C3nDQX*MsG&Yjp3Cbf^J)QBbMdH-%dN z#3Sggd)<#w>({<^)VkCUTNeiIBPFaPUs7K2@w=f=jq^rvC0PY_W!Ix)B;87Kn&(G1 z0V4_YbZiv0{xn(ul;!aj>`TGFZw9nw@LlnYY&h;NExQevU4Wp>~0{tz@zHPNMSaRlf2m zjo9_D#O2ikE~3zK15W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL=B-S}xB#fI6hZ(1 delta 62 zcmew@^;>E~3zK0+nVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~=B-S}xB#H;6rKP8 diff --git a/master/.doctrees/cleanlab/dataset.doctree b/master/.doctrees/cleanlab/dataset.doctree index 4726a8132b66326ad93f38a3c6cf15385cb5fed5..e50f79695f4180dca3f40c5aa573b9ecd3b02c2c 100644 GIT binary patch delta 1253 zcmdlng>Ag*W3#8}h6-0u~hf+c$SGwlV?$b8&c$ delta 1253 zcmdlng>Ag*W3#8}h6-0u~hf+c$SGwlV?$*ol9= diff --git a/master/.doctrees/cleanlab/experimental/cifar_cnn.doctree b/master/.doctrees/cleanlab/experimental/cifar_cnn.doctree index 967a175ec633275f9503ac80cd521191eee366f2..e189057663b489784aa07e438f8f580a6d171adb 100644 GIT binary patch delta 13101 zcmbuG`*VzE6vyYhm&8VPH&=JkhA?r1q5;{{a3yTpGcvQX`le@RSfl$z_05Rx8`;N_9c78kh{~`= zMfJ%F%gmcHH*9X+yg5^{Y=ymFwH=_-eVXkel_Tx-iieI##r19;X4}dZvoX1Sp<$nj zNo@-a{P;GrYQGvv>rm~D;e@^t zaMcJxpQrfBD4GTAKN0sf<*~fP4FSX~#mI*O2lQQDHwl8e#1k^e2t@1>8?)(kP&|>V zr%?@$S^HUW~bQ~dDsMA|Y0o=w88SbAN9Pef-$5*H{Yj-98hL}PFkmZi;tKy<)4YdWk%5pKmGq=Sj`ZOW-G zXdow#D~2Z9#Isz9M*EGWS2tKZ^^CFyEe5YYt5{562{`_e5`&(Ttkx)O0m-7oPxTVF zlGPBALDMu z9Ihp+KJJvkLr4cNUNTOtY2{8J;-gurQ9Nb}5v}vo`|en=v>M+Db4YcCAWGEo<{Pk_ z`2<%X=$K|;@7?NE;6B22@;e-abnxS%z3O#zEC{E~;v=d-JStZkn_q^P!LW46>FSPy zs0r0th^2L^#*1s!Tj;cM<@D04;jX&b>TXLVVm)>3(Sie^Dy8=R$LY4|M6-H=QocAf0VuwX5KWnA0c3Q5S2T!tKO({e+> z;8=F|ZS=Tx)TSFBIHi5x9>j}3Yh^Ly^+-Be43-X$(T5G!;^y7ambg;_gOCm;UUpw= zgx^veLxzo{_ka%{=a`ZX0bH%Lj9tDQY=!aCp%fm8 zyP|d9CJ(?lR{aQi^04%}gZ3o*#OQu-7f7*@%VPC{o?rureKYh*P|FQ7^|eD$am&Mc z0a`R6#YXl&sh>k1|9J8Ry%?SXQtZXEtMrZN0N@q3^-#F+!|&@4fE~|CPxPlq&Qh1c z7oX{k@P$?{9}g3!d3g*&SDd9oJK(Pd&JPMAF-zXaRd?_x_G*5&I{u-;@^2>BeE$O$ CxY0!b delta 13100 zcmbuG`*VzE6vyYhmt`Zno2&b!6T-wTE99msA(|Q`5`-urvLD+V2tis~K)i*0qwd6?Y3*jS=s zQrlvquPr-8v!5_sRUnH5TX6dpwugSc;@)^N+he@DVWBvE><|5pYgice;P#tZK+=i! zxB$ho`BHm+-vVmBO!mrT+vK6G?Axs&-mrWuprqt?9gAeLkBceyf%LQOJU$M|nUZJQ zcO|7GE#{E!p41zl+9~-mN?edK3Lx4X!A_k%6r~PM--k*IW{g3lIkR4(xmxBcsb^M9M5$$ku_$%hnrA3A zWbHtdYFytRrC!-E1*QH{JOrg4+8m8ii#~mVQUkW7q13LQTTtoGJC~r++q-9?xjxvF zi&AO7KPt6<1yjop!qoQR4xAka+Z}4EWOh=Buv#Iphc9eSen@#0mKT6}2}nrnI0bCf#e$~KfLuH8eaU2e=ose!d4QL6d( z{U|l@7JSn6zq1vkX5NoNbB%p)9Hs8~dkjh~sy~lXpFV+~5&!tN3Z*8!fV*i(<5Q5z zl|iYI~Zf52}4+p*mE%%$LH@Iw$y310w) zCE&`@gg#I4)iIO}>_0K&9m-;Pi5m!rS&ESl1rF$YykQCib%`fUCle5{OKi%ZL7;dt zSIwj-SiEZvsV$p-Q|<^mk$dIR>%eg&^4F{JB54Wvix+ux6`(r|SQ-=?K(WXwB#SUr zYZ+Yo5qTozbH*TTa$BJ>WZ38@P|M#G)6O=aSTr0WlZZX8d5I59N*D(npm^ZBo^u&l zdd-7-;6Bq0FbN)6MpOI%v9oin6%-2hPUdA#6J$dkvnQ#{dD=HI#~7vTmD4N!IfUs+w_zam_*G-;udP-Pb! zi1fM(mmo4qS%<8Ea~BPNQ;9{z;=&9?6P-rO7V7-Ak_Wf3!-l2JC&)B(4io9%Cu+Lu z|DOj1Y07yt8kSzy;SQ!5uml`)S&2f=NmgqVwt{3)PXyQ%HaxhSOAiyH#f10BKG9S#Q3H%7hVjsbr*Og-%7 zmc#W#)ythS7=(22;AIokn%3?FB0kPmP2vetplFk&*12QF(rRL7%putof+$kUns2~z z<`Z0nF2^+^d+t@Q0rwHEli%SWq=OF^>{qMNu^^l_OOL8X@wiNFYVKyTEJlowvRTemQ9DC1aN_2isx1bSQ>L z;+_cIyU7D^W~hD?J$YDq-9dYjy`pp)%$yw@> z_|kK|5x&ss<7F^&iicq&y5cMy+5>+zaDGq_aq03#uBxM<(4+a?>iCBW%fFdi_x=w& CaUAUc diff --git a/master/.doctrees/cleanlab/experimental/coteaching.doctree b/master/.doctrees/cleanlab/experimental/coteaching.doctree index 3a05c6815c807309742cd2ee1aecc33dcb6a562d..f61266729b3ab4f7036e812480226408d7e97dc1 100644 GIT binary patch delta 1676 zcmeDE&D8swX+tohZCYkdTA68CqP|g5im_3miFsmDN@}V}Vp@`^g{8Skl7)$xp+TCt zfmxDylBv15VXA&gesZyXaeir0a_Z!RjY^X@F&;G}*%YA8pv}LSI@rk5I{E!>{>dU- zg=Fato;*QNX|p!>Lss&%Z=N6+%}Acs$sZ)tH%}AZ$V7qmPhwSM+P?XN#A!-wPLpvW z(`K;0gXPvyV*47!UP^3#q8v_%?a$O4DY5;MMlvO~KhU;hAv4KL5ai#y#$Y7}1=?R& zGE0)F-62$Jb7!zInL)SNA=HVBOq2XFqfu7HOutwEdL@1Dm902a$0=>Px# delta 1675 zcmeDE&D8swX+tohO-7lSVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQJQ{AesZyXaeir0@?=9r<;j~Ej~bF}$mD~KL7RUub+D1Ab@Kb&{F6nv z3dzzPJb8kk(q?V$hpgmj-#kGunvp!MlRrqPZ=NQ+k%%eST7x#f-#w2J04hT#NB{r; diff --git a/master/.doctrees/cleanlab/experimental/index.doctree b/master/.doctrees/cleanlab/experimental/index.doctree index 246374e6afd654d51eb4cf517b399d1503e70cdc..54f40e282350927a3eb33b06695fa1ba6afb41bd 100644 GIT binary patch delta 117 zcmeyW`Big6IHO@&W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Yl6jJ;xw&EL<_<zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Yp`~S7qJ>e~<_<I_x*lz?>+ZUVXdRE z*6}P0QRCdWVJ6IUe@x57V`)WAYZ+Zv(uS58NU4f8pd_OaLyaUgRZFO9ROfeKGXb-P zs|Fux+12GdaRaT%#TFWBErbGAZ&>EBz(^}u5#-Sz&>IB#`gVnw&KE+9wB)Qc(HG;r z;ip8LPxM{$ke19&-pv>LSsM-K>&dW}h~7W=nUrIM=7ObgvGtT?+;p!1;;Nbha&I84TQ{Y!WT+cX1*-Q~G;nIE> z@loLygYcU$bdBWELm&?klbNRor=7DXJ~`g*oU;o*w3b62oGpP#xS^VY?>C{FD!?zd z;UX2@sNXXSdtC_v58#R`!DJb>x)Pk3gV(ME^?67Up10-}wmpXmVaS_;dmR2sZcgEO zge-CHN_e9Jp9qhRUBAQx?7=-%Xeay}*@hg8d<7qyuY;dGs(^+kS0O@dlSAS9NO*c1 zMJ9hh0AGFsFL5PvC=64bw0+F6{2%b*<2oFs#y1S*e{ias*1=>Kwn-s&s{(#p-6GY9 z+hC&59N*-;1OD76jZ@Z7a3$Okm&!rsq2j^JvXxOuM*W!dmT(W)0u+KLgo7to!>Y+X K^q-Y}b^Qk(QxSUr delta 3290 zcmbuB&1(}u7>9YcP3cG6L_;z4Ga|wEAk8K*$qI!QMG!r-s3-_ZvfYh{+Cng3K$-?3 z2okM}j#^M8Xu%fLj_@LwwtfT!QR$_4?LiPcDI_X*aJD(*yzl-2&-453%)B#OSm`LN zbUaIgawZ#7G8Zmo`uAvBM2$xiN-|-@qk3XgOKI^`C~AblFfl3ALtGIe06h_n9k<{^R(o&Io22E zy}_qMoR9TgbCH(JO5V=r`&kbK%H&uXN zZbOC&uhs9FhMkTCz6Wr{kzl+G8yyKw&A@9%g8D3|gy*ffg>BEFLKyO<;2wv+l9N+- z79mZXyAs~0z$e0^W7RJ)0lRQV71{|uN0uSSLSMndX6xW(k1CMDW6KaCw#lJzeIz`+ zjUwYez=totft$FJITVJ8PTD@^SpE;V@o^mvP~#hh@;^A}9LZ!+_JU>hRn}EG6QgtUo{i3lvE}6E<>$xb*mJFMlWZ}$aWSz` z7Q4+7n`_Ip+H6tzjxDSoP}PKHI0I#i0h99je4jwaC9MRLJE{YNoSi;PK)R3*ad!Lv z5UG|c@9Mxa5*&D#Qw}PUJ(oLcLc0K&qb78%!?aRyP98o9%hxTB961Ne*)6wxuMJzQ zLg(JGTTtmoKj`!Eywaj%+0N9M4vd=ZNR1ipyfo>L2sxo3*I`LgoD&jD5V~7_8%Wu$ z^l?z~@4Zl~GtwaSO6S0g`({X5=G?O|4QcFzf-+}S&T6EoUDA_z6Huzdz80W56AI3u zMCVdy^Sbgpw)_APtivT$OY=}^$jSjU*M`*vD7Ce0I!ZnJI-F~3c{)mM-B5z&diM=D z;K!SPiBhL-orUH)ZbZYR2qM<5|#e!NCBGbwqtLi)Q00BsI>fjn0o94Of5YH z@0^0u56}v0XH(HKN$23RNo_ogQWrH>pwhQnE}~L%D}2+LKi`8=Gutks>-yyva1Wb0 z+EMDRt959ux32#OrB>cJgi>#Ibpuo$v52j4uDe}^V)x#i31Icnw5sPMN@cz9Rd?sB z-=WlLeer0n&-AyT)cpflAe9a=_9cj=ScRcuB1LQL7Rvpzk)a(`cXALzUT4INNlQ#@ z4q9frnHf-SNGLO-rTR3C?MAg>BUl8g?F?rFsJ3zxi$&{PJceCGxqaiP#D6VCPZhqa>CA zFkP1)^`|i80ZP}7d714+xuvOW9-8m!G-gG)bJJNm%AK3RUPQIYS!^$= z)r&GuFJ>!%y~lgjvqFBbm<7?5CCuiHLl`wKWyz=mi5Px@id_kW(c#zFQ{FjjSj{$p z4#iZvh7D6Ze+DP90&9S;8(b^5_`NM`A#gkKno-gmzHmDW;g2fWHP3_A4M-TARZ;PN z&NxzQJ#--sq}JW6*bl_>rw%Y5-crY!Km!s6&LNcHL&x$j;MS z@DIK07LfcCt&tz+%*>~3R?_L6hwT0!)N8#_@}VJ$)QL6%35OTp7ECcoXV7g-JA$PS zf6o&qQN#ye#0zOmq?Cz>^|tLO6@3#vQL@5q+h&z+0>hAd!%vHo-T=O8b@%+0m!v?N zKSO#9pMn>jkGaKdIfQqRVHOnZjQ7YX;fWYkuOyNM;!_AMr2Tcv|&x?G3@Xz+IF=OLbNPTq4svUB3h#MkCX=~PiG{RjwzgpGA9 zfOoYE{kBDV8|f6i*M!)YKK@*aLmg;yyVL;W?B3%|SEMNcXyTRsl9J&oO^AbO#Y1Va z1;q1=@$zL*OYcR>vj+p>lI8L|a{O2xiX3aY*fv={Iszo~J6W2JS=0|0jK?o14)1CqT>Pltp!C3>1@vQNO_(y?yJJK+gz}O53}#;Rnc*d> z9i~*GCjoshMzO-nBg8>e5vi;LrgZn%_0|;S1d6A|MCDy{?4o-!l@V}12=QQgH&wX` z_hn|k<8stKNN&7DWpbl$Q_X~m>8ezQ`Sf@yhSn=*)tXIm4Me5$+# z6wnns375;j{H7<~eMj+iNAUM9Wh2l8dIZ8{CvXxRKdNpAI$j_%sYy{E!aMy%lZt;l z+8V6-q0+F6%5#j(cN2&q9TOG}^s_T)blTUip`Ly6UH7?ZiCg-|%beamC z^18Tfj@q*fBy%AS;sqb7Nti*IV_-%A6`oO>kR=o0m(xEQRU2}{>Eh-lbr~}0>*8B~ zRTE)y`vn#G<+5wN%jtTn+5nShUsUJAIWM@ZroiNkc6A3#uIf-*Ve-gpD)KW8ceR&v zs>pZSZt=_;>Uucm*SpkG;Kp#1e|<;24i_xyo{IeT!A(B&K)nx;N%Z!3INbw})P2BJ z$7jjfGU|S;B7-Rj@k-#TaFr>0SC6XfI1mL2 zv{sFf6SA~Ce$%2|1FjC2ma?O@e*+V_`1_!hAIZ}q_}%BVNMg@v;Qv(JE+kxb0Qr9> zj3C~estt92U0n9E_CBx}-}NKmH_hmIWl2=l7nu57bP`2fJI-_FlgN|lZ`-uksklKV uPYd(eN%jj`67T@{Z5Y`%G+UGxVUP&p1Fs@D@r;i>7K$K)#9z0+G5;4cQ;U}X delta 15985 zcmbuG`&U%g701`PckaC~2#mu+e39a#N^9ak7#?kuAjSZi6h$J4s0fULB7#*LjH1hk ziCUI%mYx(%Si}lS>vL*$QmxczYY13ONEAbZSgA_UDq3QsM0(~foPPArcKN}Mj5gnElZHtP?jn2tllpVFm5@EB1 zN9N{cXNASY*s`L-ZT79K4^UMFra63Nivg4J+FTD``(>>NliMqO{Tv-0i$S`O4{>yP z{}ic~Gw({@vl1M5kVEz>kOwYzR0VbdGJ93vI=g9=;+Ql%2Fuqa4;?uh%h@Hj{HO(6 ztbE75v0G8;$3N-y7c$ub?u5p5VX)1DkL+;KVPPY5|KZ;{=Spg1PP7a??){5FuX zOX*>!#6P&9R;Q;x>Q#>Z>G#c$w8XJ@K?>5?ad{<n0#Iq`2Qc;cNtjxE z8s0g1XC9yx*3KoPWs=UrXOmig1f?!)EJLMlHC;lb=4SY&Gk>ucrKY!BLD%)GFX0|G zwY8$u-R(7KuD7oL7p0cpIE+$nc6I?&9))f)slBmiuFv!}q0|HY86cGoGximTrAURLV=w%Xi;5uVurOfj@(jSb?>`*A32<%YJ_=TL9cnylRv*n=jbG0{EkHc5UE6>joqY&Z(&Q z0B0PjwH~?<`%?2BR_F!d`BMj(2XCrj4WI!D1IG|h%-=lEytyq^nntx}*j%7%Tniv< zHp9#R?FDA!?=-SjFbNU{tNj77vvK*K3&aWrUT4X019f$>p}=YB>U|;hrroz$C9?DM z7W`umy9FfwL~G z&3oX9lPKZ?FyaL?CR9pC#CqGd6^p(Jo+w%2wr#OWH-TZuwc)2mORoc8wYqx#>PwO@ z&6_SghVjDT8#wWKsnXj>-Sr(K#75ebA-#e)%q)@8Xi=852WeDYT$U?U07o4O@g`(n z3f&SaD3vZF_nRK^g>BLyG+i#lJ~ViT^lHGsHz)5tDA_o1X5#Czq*N-amVO2VLc+#6 z7Qj2(g?`s0y@hm&-fKeaNuPWnMWYV1rB$i}a(3Wc9~%LZ`JD{ei?5$6cYp>Y433*H zaSlZk$b*2qN#wm8nO^mJ<(J800VvnS!`_fnf`N4Pt-0iY?9KbDpOgc=DxLl9{rb<)|N{>mi~UOqO2R z=;@ZjMcI&H1szDlFh>K$&TyF~-ir^oe$|j%*^azB@F5o0MaZKF-bi6>OQ-h*Dgm?OjCKdm9 zw9Q}jLZ>GhK3dHI*4g!bBE&vq4pn`Cw>p|>RW~3{C!hAH^JxBaYINYho1E+7(J3l) z%Io5m*=qMPkj#bHkLP`)CSV37_WtQUlz&!jK$c8|UrPV1SEG;{P8T;esLPN^Ul-r{ zn;H+3TQ91}FPEL`T}s!R)jF6w>ykPT&UyY7H3=rCwW>Q|az&fk43kG*Q<0x(xT?Ll zLq)#Zc8O=)P&dFizt*W112=|?{O%p~I$W@@dn)qV2N(J91NA;YCehpD;dBo^QuhN_ z9iJ&{%c$$IiVUVC#H)a-!da%w-QB9P`+};_e3SMunD+N3r~S1{Xe2ahlqLfUrl&!U z(OM-!j?2(;_)Uv;4Y)d-TFMO9{sTx^V+%K8ZY${=Qv{oPryq v^OPWuU1YncB>)eA--nTTLyHP?BMcH@eCSpLC!g`KMM4pzk@)NOx90x=H%REK diff --git a/master/.doctrees/cleanlab/experimental/span_classification.doctree b/master/.doctrees/cleanlab/experimental/span_classification.doctree index dd6c07427221ef91f9d9ad78958e0bbc085274f8..2f528220d314b157c1b47d3a146c51859a2df4ce 100644 GIT binary patch delta 1022 zcmX>#f$7u)rVXi#hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+vUG4e4Qkg9F+LPniU%z`XrX`IAtGx=;A&*ZJ_g=FftoZKLzy7>V| zGb;rKXl_>IuO`pylbAs+(Apd=IE{${7iewXAQH$-kpTxJw8=JLbAt>Y8wIutZ8lX- zq9g!?HruIY0h1$%X%>|DKrwJZSYWenxPkyh1_)(1kRJvIq@^}9=4*10?E;ViH_K!A N$TYxa^VzmqMgZZ5GxY!f delta 976 zcmX>#f$7u)rVXi#h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroU;G4he2ZSsDll+BjRH<(Gc5u|nUsW$$}TiFZA(p|RsEXOof^0ZDq z%OSj3mcO1nFPDL}hY8MRqQLgmB4Ol(8pQV95(boLUn=vGjG)`RU+D&UK~}lhQ8nF= ztl&!BY!|LCK%UmgcHzRC#WHNz$kcwITy`^SzA6WK+BY94FXbakYs%(RZ4Hb7Yw#sg&N+Nf@@c`j2o2bo$sxeJ)d((1A~kH3VKJgt+@Nl9$Z7u`!v zC~Z`C0c+nWzJQ55+c%$+>LXJt*yfkAB4h>`SbLY^H!^~4^G5XroMidec(R>=_~tW) z^U2e0IQ>F6qu}Oy){K&5Sr6486q>S)eEqDG8zh9c8}KlCkeANEjsP1n9cT#a_U|H$ r2c*e&j^On7HjK*KeGM7)xhXJZJJ1w0L$VAonB2+Dzr8h&v6T@3r9fhz delta 1139 zcmeBrz}oeIb%QsfVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQG7h#sg&N+Nf@@c`j2o2bo$sxeJ)d((1A~kH3VKJgt+@Nl9$Z7u`!v zC~Z`C0c+nWzJQ55+c%$+>LXJt*yfkAB4h>`SbLY^H!^~4^G5XroMidec(R>=_~tW) z^U2e0IQ>F6qu}Oy){K&5Sr6486q>S)eEqDG8zh9c8}KlCkeANEjsP1n9cT#a_U|H$ r2c*e&j^On7HjK*KeGM7)xhXJZJJ1w0L$VAonB2+Dzr8h&v6T@3Jf3M6 diff --git a/master/.doctrees/cleanlab/internal/index.doctree b/master/.doctrees/cleanlab/internal/index.doctree index c3c934dc11526f9ac56b11d2144b2c063dba07a9..7791925f8264574ca84b764c7de6f583f7147d93 100644 GIT binary patch delta 117 zcmdm@yhV9~Kcitj}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Yl6jJ;xw&EL<_5-YW-_$duvYK@0CbomHvj+t delta 117 zcmdm@yhV9~KcitrnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Yp`~S7qJ>e~<_5-YW-_$duvYK@0C?CV?*IS* diff --git a/master/.doctrees/cleanlab/internal/label_quality_utils.doctree b/master/.doctrees/cleanlab/internal/label_quality_utils.doctree index 4b9954ef50a883e11263c91beb67b53e45e7c593..f6fdb4ecfd3fdb361b53e80056b8d6f58dde888e 100644 GIT binary patch delta 493 zcmcaKo$=Ci#to^AhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+vUF)}e4kg9F+LPm|vADC{Fr*rZLCX31OUObc2SqsUt+JNm43t2iR r8?eQ1Udg?iY~4PaIRsCzk!!cl<`Ri$U<8mDOQ7He1={9#uVO|3T&k8p delta 480 zcmcaKo$=Ci#to^Ah8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroU;F*1>%Z8D=o%w|>QWn^ld9OK15Ii0nTboT-+F5Xne}*2y(& j!kbre?mhg0W+vvkY{1<>y3WlHxqHa5@S}X^W_1yFCem%3 z4AQD0ew$pad!?$$i4u^lpJdLFVe96P@}gvD1N-xU(m!&wR;aO(tJPeym0Yc5I_xZD z#;Lhs7rC}po6I365kBND+`Q9fA{!YF25Oxw*TAv)i}N>evb4ucz9T8Txhv)!Il=Xi z8?1e@d;|Mt`J@O@vRn{7nXf@~a$k(VW{rv{@`5jVGhai7JejsnP?g#&vw)j}0_|s4 zWUG;-J!UfhUAE1q&u`};Py1&6yIB_GY2D5y##m3Dr(?DY$uk=2kY#TWuzcs=e$|_? GpAi602ox0n delta 1690 zcmaDdi}lGY)(z2&h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro6K7(bJt>mhg0W+vvkY{1<>y3WlHxqHa5@S}X^W_1yFCem%3 z4AQD0ew$pad!?$$i4u^lpJdLFVe96P@}gvD1N-xU(m!&wR;aO(tJPeym0Yc5I_xZD z#;Lhs7rC}po6I365kBND+`Q9fA{!YF25Oxw*TAv)i}N>evb4ucz9T8Txhv)!Il=Xi z8?1e@d;|Mt`J@O@vRn{7nXf@~a$k(VW{rv{@`5jVGhai7JejsnP?g#&vw)j}0_|s4 zWUG;-J!UfhUAE1q&u`};Py1&6yIB_GY2D5y##m3Dr(?DY$uk=2kY#TWuzcs=e$|_? GpAi5gBpxLI diff --git a/master/.doctrees/cleanlab/internal/multiannotator_utils.doctree b/master/.doctrees/cleanlab/internal/multiannotator_utils.doctree index 6bf37b863c04b726e3a698d42c99e49d77483eae..3db4d59f3228e8dfc162cb34a808099108df2f92 100644 GIT binary patch delta 1932 zcmbRDmTBHwrVZ(ghH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+upFtU=NZSqH!#LfE56Uozhk92oVUZ^`|^At8A4zje)*qqOAL5^D& z>dx3)Ah@21EL&%8ekn4EJX>dOb`?KNuC14(K9j4pU+x&WTIH2)kn7ijDqG04)m~!< z*|utt6R(>W>Ruq%vDSu5$dx3)Ah@21EL&%8ekn4EJX>dOb`?KNuC14(K9j4pU+x&WTIH2)kn7ijDqG04)m~!< z*|utt6R(>W>Ruq%vDSu5$r0bS9LG6FXUpl^G7tqqoF5{U_aAs=ay38(*mEDPP zqK6Sl5xwXFRtG#rMOtsVP!SOkC8B5$W%Z(Z5oMichEnhLU4Ovm`~CiY=XWlgS0U4@ zkm;&I7FXA7uJ-5pm8@(}RZh0zbSa)Huh*$mdvX`$yPTdy&OC>`+GWr4xIDQom&2P? zRbSbZ)l}cSwbILi?o4)%JaR;=BFS=|67z*%sCN1xwXpMsMhxd?;;tAll=WIu_`8H= zFnAarF_%%yo%dRYac3K^opJ(nmcecObjti#D0mCAms)u1^n+N}Rep2kcC2od56v#e zYF7EDIV(`t;kjL)>-n_{K$1_iZ$i=3oKtA2N^U|7G!-gO&o9F!qJ~=vYpsxL4YL#) zcxrJfR&N+*3)YxfUr7fZKq{0$bPKna9>R8^%6%2BSk)?T-*6Y0Egp2608CyFDqrOp zLD3QKEo3B>z%hAHnfU=<3Nn^TAjmg0^dcSB(VtuQAoc2Kfj@-0hPG>fD^~(b0gUNk zy}O}HNJl%>`)Hj@_U}Lg2M*?-t__EqP}d8`mIK?IX9V{p00)Z_@bSX-86e8iz0-N} zWrqoKX1lsfY`F6)M)O@=GbdpvYj|ShOCK~~%j*l{rH|exNAAuW2ks%RjRPfI48~4~ z+>td76miFgotSG8&-i!-ITUqQ=NG8MIy&v!GGG^kYkm2B3tH>VAHM)sttW=~wLy($ ziZ)8(0dpZ0j@W^<4Z7E{_RI<5jg!1JM!~NxAm@@WUfWwo;EM2(A5#V9V7 z6KHH?FUGPYiS7!r*%D=z^-=Jmqn2bNkCCx5q`+kM*(%#wPu?K6$seUOVQwNPqKJ~F zNrBNQ728M;utVg#F1$8rqPv9{%y?T(n!A}8wYGjTRct#-;*gW+PnJ*92Er) zS~3eT?O8)T@sV?yS1J#Dv#8#RyHF94)^hUNMFH`huG#@Y@ S7kC_^Mc7NIT*%+y0{R=@-92gm delta 5859 zcmb`L>r0bS9LG6FXUplu-|z2te&@n@5i-39 znXV{g!N$g1hkwfsf7X1DC&!iN%y%gHRe4Tt{svE_C$G}(tg>h4dc7XS;c`_e`Po%j z8)`lNEPrjoRu2n)pTX{s2abqESkPV0Q)0dl4AoBGrxteJP>8>(tBC5Hiu*M3xRx?YX zfu|OyV)ce`Hg~0&^_8^a0i;41L^pAJ=^<B0 zSnqD=64KEQ^)6cH!u>nYz=4A~sB7I}Kk9nn*b-oy^NirW1mIv%0zO{YIt4^ox_2^9 zzU(kz&TLnwi4Asq#b~~(bLuz@Wp$5?e9^r+YwSJ(4i`TJZ zB6no<14Z2NVJGHV#4|pgK@LUT)%gYLu#Qgpwiwt2;aZ=6--6cK_2U=ds`bQ>M(wpm zGerv}@qoFI3P6p(XC7_aT!Oyad}A2EpI#YByZQpG4P zl@n-eWG_atB#G_{vdI!P>Bae}hGNizG_Sq`iT1#Fbx5*!+G-39W6H!D- z)1<&~l!|Sn2iPItJOTI4Z=9M>mc1CELU z2Q8TfnD(rsmGO~tn&cYAeK$>=5;?4&vtsjJnhaDMW)quf#>B{d_0a3s!rV;JuTd9Z TJ}U4qM2oPOP`Qx5!v*v=L3v+j diff --git a/master/.doctrees/cleanlab/internal/multilabel_utils.doctree b/master/.doctrees/cleanlab/internal/multilabel_utils.doctree index 4c24ef79170d17e9ce16221f460ab3c699ed2741..448ec3015df4b65192bcaf919d364e23183933e8 100644 GIT binary patch delta 1199 zcmey>$@Hs}X+u1tVOnNRTA68CqP|g5im_3miFsmDN@}V}Vp@`^g{8Skl7)$xp+TCt zfmxDylBv15Vd~@wj6ccHRmc;zS%7&RITix7PA+KXpB%zkNS4J_n+w=3u#&EIb0N=b z^4wd$nTLNq6X`Zio+wqnIa;Wh99uzJ`$YW7wY69LG8tMoPn5buhBmN2h2>1hh?L2N zJn5V7D+iDhL?ErlRYir!h?qj2@X1|f5}Ru*nAj-LE@!`#gG}vfM7cJHdgQQEpglNX iGCz6RH|Hf>CNHwWC+8*bZ@!TxC_|RbVVet@yBGmSs&D)N delta 1199 zcmey>$@Hs}X+u1tVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQG7Qj6ccHRmc;zS%7&RITix7PA+KXpB%zkNS4J_n+w=3u#&EIb0N=b z^4wd$nTLNq6X`Zio+wqnIa;Wh99uzJ`$YW7wY69LG8tMoPn5buhBmN2h2>1hh?L2N zJn5V7D+iDhL?ErlRYir!h?qj2@X1|f5}Ru*nAj-LE@!`#gG}vfM7cJHdgQQEpglNX iGCz6RH|Hf>CNHwWC+8*bZ@!TxC_|RbVVet@yBGoI3wJC4 diff --git a/master/.doctrees/cleanlab/internal/neighbor/index.doctree b/master/.doctrees/cleanlab/internal/neighbor/index.doctree index 289c648767d2c068abfc843f583f1ac8ce7ab7d9..3c22507a6f4e25608690a56343bed774e27f1ce0 100644 GIT binary patch delta 122 zcmX?Va@1slKcitj}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l fl6jJ;xw&EL<_5;oJVqpI)1Ry$Aia48-&$?}T1+Kt delta 122 zcmX?Va@1slKcitrnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# fp`~S7qJ>e~<_5;oJVqpI)1Ry$Aia48-&$?}Vk9Ob diff --git a/master/.doctrees/cleanlab/internal/neighbor/knn_graph.doctree b/master/.doctrees/cleanlab/internal/neighbor/knn_graph.doctree index 9d1e6392912840e36ce4ecdf6bf93176a1a6af9c..a9dc9f30f2d408daaf111342d6d6daafced96dc2 100644 GIT binary patch delta 1928 zcmbRJif#5Qwhe)dwrQC;X=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN=1~`N_rl#rdU0$*Ge+x~gs7!dS~_NU||Ntx=QrFgK8=bMtYQBo^|t zPCm{ey!kk%D|yWXiQvnh3jok}kSuGpNQeu+{S+}B*rOkr#o>%F1W6=w{dQ4kKm#4WKo-XxNh zY>#kn_P6TdBujhl=5iNLGW@^!qpPGY={8Px!8Ao_hi9FZa2{_Q~h xKiNsw2eNnZc0Msi^*Hi0*KB`O!Wc?sh}Ud?QpU()L%Pk-dXIm5(`Lq*i~x0>TaEw# delta 1927 zcmbRJif#5Qwhe)dHW_7RhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mrryf`N_rl#rdU0$&(YA)i-ZptYtJL*_6p2U85%NVQwH#=jP)qNi5`P zoqU`{c=K^iSMsz+PgbztoSdL8ym<@XJ~pyk05d{jv%J_2@~Gb@NtX89&E+nhWcYvcM^{N*(rujX$jcZz`CO6Q=557hWLS&PKcm!0k39Qh zCd(;GP2O6pzInzHKQi3_He++|vUq3m+>kzb!wdG!-LI6$h;&dGK=k{3I3h#3{o8^1 xf3lOV4`lD+?R;X4>T%?0uG#*mgfW!N5U<((q>PcphIE^u^&bEBrp=5q83CdiWgh?l diff --git a/master/.doctrees/cleanlab/internal/neighbor/metric.doctree b/master/.doctrees/cleanlab/internal/neighbor/metric.doctree index 228bb266337a9501d419d6f476cae2b21476789f..c7a519e77c60a8b7933199604b697a4c11dfee84 100644 GIT binary patch delta 1023 zcmZo!!_=~dX@fVTVOnNRTA68CqP|g5im_3miFsmDN@}V}Vp@`^g{8Skl7)$xp+TCt zfmxDylBv15Vd~}@#${w^n|wheWOCIM{>j^z3rV*WqC*KEsC~12 Q?lv_tYzF0`swrKJ0J#7_tpET3 delta 1023 zcmZo!!_=~dX@fVTVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQGDj#${w^n|wheWOCIM{>j^z3rV*WqC*KEsC~12 Q?lv_tYzF0`swrKJ0J1Aa$p8QV diff --git a/master/.doctrees/cleanlab/internal/neighbor/search.doctree b/master/.doctrees/cleanlab/internal/neighbor/search.doctree index cd9afc739f1f7f20fc103f518f9650a334f6f563..0ef7889dafd470d976b9be6bd67319f3c97008a4 100644 GIT binary patch delta 527 zcmX@{m+{13#tq(#hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+ut7&nliZE`I071Ax6Y|B}?`8ta!3+Y-n+j2^?lCBMCW76i=d=>0u kYW*hWCr*~u)%*mT?RlQ>d0Ja~Yk^lez delta 527 zcmX@{m+{13#tq(#h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroUC7&nliZE`I071Ax6Y|B}?`8ta!3+Y-n+j2^?lCBMCW76i=d=>0u kYW*hWCr*~u)%*mT?RlQ>d0B!Q5&Hw-a diff --git a/master/.doctrees/cleanlab/internal/outlier.doctree b/master/.doctrees/cleanlab/internal/outlier.doctree index ede760258a339adac698226449dbf3b5749a5080..6ea814e668af5dea5d9ec9a5542c8a4a52f4d38d 100644 GIT binary patch delta 731 zcmccgg7MM|#tpuVhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+Y581IpxD_+!P^F^jPg=ATrGg=ATrGwrQC;X=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN=1~`N_rl#rdU0$*GeArSvA>W4vofvME5FS)0R{7ci2ib^25uM*hhQ zSPRM0-nID*n;sikTKhKdr*V^+tfWxB*2Ua*aC^Oh|NWZJ&DVA~S|@@(Gx;kh}Pwod-=TyXMiH=)hXUWzD@ NWqa0kU=cr$5daL+5UKzG delta 1704 zcmdlyhh_5|mJP*>HW_7RhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mrryf`N_rl#rdU0$&($~^e5kAylY6ZA(I28vNne?FJL53>-4ESjQo=q zuojY~y=(IsHa#}7wDxV@$y-UDqx&|0?bm81E!?@&B_X;WY`GS8ljv+uB|PqUF6z&PU9vsSxKRMv%hW_c@8e$ z?5lr3ge+ULC*N}x+`P-hm^_;y+Gn|a*Cx|;KQZ3TR>dad+78k#UK%G)rtR~k**8l} zRU+4RkoLRNbY;o3yoZJqq#x!~m4ZbF-%y%bR* N%l548z#@JgBLF{d8ZiI> diff --git a/master/.doctrees/cleanlab/internal/util.doctree b/master/.doctrees/cleanlab/internal/util.doctree index 13bb07ffab48496ab360a6530d6c085ef65b476f..d7db46d316947abafdf24a5a115a3395f76d0620 100644 GIT binary patch delta 7878 zcmbuE{ZHFf6vlIJ*A{7|E${DJaMpyNFxk!>LiC3B)= zOBOQtiZ^?~nQbg&FKq6zoMA8;C(B#{K^>alRKUdeg9wRpmPCl(mbpLR;SYG8&vVYb z=X`J4@g?KgzGpa6~O|HNpWhMA-P|=bR`x@+9>38MyN$J#9@)t6C;QeRuY1E9(o>o6cwW~>2OlsSS*KX|qWm5ye&q0*o8E}+t< z>~*O0nT;LjnU-!6099HX5r8awrZ-=3q0+Nk_M>$Uy|f*ro-1t!sIuHOixR&r%L9nv z?w;Si52fCyfW8%>IX$%lxkcf?-|XB5)GEuXrqMbls%rsaIP7?>8>NnWx>4$~cNa=s z+|!9t)9Z5qsyy6q4<$YbI00h#V7_ZEN2#~=Z$PQtEeBBQ`Bpzlz5Lc7N?mO4LaEln zp8`~A=@>$Z-p)M$QN0fJ(s!g(3%vycvaIW6l$vw={u+>axwjXi2IREpL_4fKwTM#t z`l?atiH~oh)P=M4D0Q*_B1+vn08?F;22g6xl_Ip(`fGoo(tl+$Dm4;(hn>SU2(`Sb zNfwWsjDUu&Qr3>XtH-2D?Wk5Zj>X49a)>ObOp&DpOlfk}NyP6n|&8%-#F;s(O+UH_%IxxoZ z+kB0Zo@XY*D=Zh=7Y^~iiP$^EV`;L2nN3g}r}*5>;^>XtEDigHJ~D{%v$wGu>J-~r zSt=#8u_0_i9vSRB#ImrTgd8I6Ll#5&Zgv4n;2_l?DginGhcZ@Trb|~?GuHnV{b|Vt z(CM82o9V>-4=h?l%`-FIzsvfJSScc8MXHrPZWRW~FXcvRont0+HbN;vCSq4mz1r#X z%z!O^N2s1u(Kg4d;>U;VAH1eistK~nRix0}$mHu+(~sUv{-n5bm&FRTAA0(O@fdIm zQd1;<8oaAQ)h1AinV$m)-h&K!nFuq*^tAS(Ls( z_2XE|<7w_8zlwfZR1->C=IhW$Xr@JzEN+=J;5&m<{YPMSv6QAsS{X%mq9zM$BdIRO P5}_qlOzQu^-|PPad11q` delta 7878 zcmbuE`%l|d7{+r>*A{7|E%#g5g0m(B9XGiwlh$PpNi#MiBNGQ$3LPL68Os7FnG+>j zvXH@7JlUnrY-1t2u(`wX4ujD+S>_T5>d*wI0w%^EL`a;oBtrbQ%>4mR|A6QDJnwtX z`+iT_$ra<|it$+nrsImy@6A%J<~u)aBQ@YutG?89APetlYXf zw=1)tz~jo#@+j?W8c@yI3gsBraZD=wxf+w=(6&PI2Im1p>3#Fbb?gFT?)H#n5zb(lI zh{5ij-?bm5-YA2<6@fWDwHvub!NA|_*$LDtODks4I;SeD0b(%hWVH*WPS*6H)YaO( zD0O*X4@ymG%mS$LaML}M_`vG`h{1#TuC)}U-fG)~Qu_`bK&j{38&K-yw}w&ba#t@( zwH^Kxph`>k2uiH&*#{8S>(D4YM~b!3ThJ>@dS6DVnaA(11F4q>1~95u&Wawi!`f5J zDAnhyM5!k}zKK$o&Niad<-v<6b?XpJbzT}msr^?9&{`X>{e?>Zm941MNbntYj8-Ak z(ux*YICe4&8oF{>J^rp9lPcBYTG>1i8x6_r%ImX{Qaj&(ZHqPe(r?pdke;!@ART_) z6S!P)__cJKvC3G?L!5CkBb|w7zhY-+4;l#7Kuelb_Qm>8V%WDbUq~@jgGAczWHCB0 z#_`*HosyDmCc`T%3)>fV@xO_vpW)FoUB=8ND2_vX?qV_YhMQTjZ|Ea~hz9mHc0(Ov zXFE%#xK1{LO~@mIJ%?C2_LGoZSU+S@r0-)FumpBe4I<*81F$O-MP|Bmg|%Y+U(=tK zYzUps#lM+OEdIbEMZ_XA)BU^5XT(Yo0V`6i^f4hAD8G~%seOT&(Afy22$+bye)Vdn zEHVSO`0asul11kNvxy%cvVZWJlBvqi%0oz@yOG8>hSHCLH2$QxbC*R6wI6!=gYhVE z3sOrse;T~2Le<7ml9`_a4V0^OCVC;3mw?MRs1LXDc634GDtnb5!}$iPsN(&oeySsqylx%_j)oG@ z`)m2pM6mw!L&@T~K^{Y?@9wSycL6bkYo3==(+vL#=mDwXDFCYeYP0r&6@M=AD526V^!4xj6ClE4D^jhRz$}Vy zSp7H_^H^GV$giTG7S)6jR`~|>5t?SvB#K)m4fxI=RsRu~U94C&32US1ir1urZ6wv@ PSUj}E3Q7Gx_RqPPPy>vb9HSX6C)dM1l5tfyrcQ-<%+Ph+M4&V&}=!Iypf&a`Q7uCGz7e za`SrW9!hL~B$q~s_Vu!F=)W%4@_R0Gf z@K656Qb@K5A)7hbLfFXG9&J^!w%uYR@ULIZjKGmF$$}xS7qMkdG4W_GaW} zlMjAAo3FW^;ULfU%^&>ElJ9TR%?_bEn8~vlnAS}vJA?{v?u(p7i3?W8oA6NJg4OZD zn@e-@$#;R?=7b`77P4KSH#wn5WHW#Hb@G#s-eiStxy=o2DipY4vqHCuDA}IS-MoLn GJVpRLIxXG+ diff --git a/master/.doctrees/cleanlab/models/index.doctree b/master/.doctrees/cleanlab/models/index.doctree index 8006f9a3205783102bc5de7e21482d34119abddf..1b80f4a607ae736d471d3aeda41412cdcb24b8e6 100644 GIT binary patch delta 117 zcmaE(_C{@kH=|)%W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Yl6jJ;xw&EL<{HMuY-DH);E>@40IdEadH?_b delta 117 zcmaE(_C{@kH=|)jnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Yp`~S7qJ>e~<{HMuY-DH);E>@40I@zKG5`Po diff --git a/master/.doctrees/cleanlab/models/keras.doctree b/master/.doctrees/cleanlab/models/keras.doctree index 0cd44e6c753afa83b36c837b07b264f26f911437..39957fbecbc0c26cb86e0bf0051c02fe0e067d73 100644 GIT binary patch delta 4131 zcmbuC-AmI^7{__am%U}?R2G#^Y9yw)SAR1mc%kJ$w_p)n6tW*~X(}OYBi10rybvpd z6C4ZC5lC0r;6Ud}%1Q_Y^OtTC#C*JaF8t7BPh9#BwCGZ+3~OdEjO`0?&19s^0Joi`*3oWXf4;|FJ+4z zKehSG#6<;|J5YhEHNZYxe0~&nD$z$&l+s61Q+i^J8<{RTjlE)F!L0ERVj@Jx{t=j% zl87L$Iah>i2gDXvU}Whp}Udt@p4CskRB>!cGm zl)JC9g!(;TA%pY{Zp2t>>P!(%O4gGlq=Q<>%4Z{aHk-n^u=Qj;5`c|A$>1W($9_E> zEXM&8>tZQw?1dP+_PQ0Zzq4yac(CSo7j#Gj^V$KLNWf(l{ZfxyjLf_?ii;5+nc2{i zQ|Yfrc%fzwzRee-5VkOL%^NhN>Z z0$aEo5iO{J3erw%>8&<+i-gE}Y$UJp=CiPh1re3#X=4C1e5Ml&xJ1n^H9Z$D1GsSX z(o!3g(cvM`ldV@b_*^geu{(O#i3_KGTuA0nW=Eiqi>Rd7?U=<7E@QZ`%)SrD-o?o3f~MQlnwoeyH1bF~JM14Ri*J=%Nrew^n8$n^HDNF)zdl z;RMG*bOh2>HaOt9lCly43#^E|kU=+wcF~{LNCWGaL?e*xl|(hvJB^ez>XH zy^PFzJ*>T8y$UC#ZI59;S#ZQraz9Bl>e*uLqdc_S$o?n;dnM#04d3_RQ14#K z=Dj})cP|qc6<|uB6jy72eKklI)LUimO zfswfqapX1UiZHU)J7;7moP$1Dipsl3WhqvNsVqgs$b>A#rO}8iMfgFdEJfE?P?q8b zX~7NU_UkO7Z5}X_Zu$l{Vk|X&Djz2$>0}Y{QZrfltS8T>QaBfuPF5oU*vQiiF0%aW z*RyT|4w%^Hi>WmVeeCM%M#TQkt`*_I-0#k5kO-!geKe7Pi>&ucHF7aB)5;JoM*L)Q zt&p5p{fdMaYWDEkOaV&nqi4%OLo%Bxw)kTS*Z%(=YIgj0Gj8^FJXmJ4>5yC8Mg~_2J0pm!fnEwf#Db+lPPDAHp2xZ0T(@p zAj{`tRqzRU?oRJDCjps;K5nwX6RE?m)B-XDb8U~;Lyr`}Jq7F%Ls&*zJ&-{TkXR;V z{Cxv#;BrK?pb|<+Gqup$P4E^8k@Z+hUgqx8u#5!}m1wCo0BSzj0yvg*NPt-ge@`sS6j9Ih3hEP;n8J6uTX>7{X;37na!n(5iCt zW9|Fogb+w;j@}0*GHqoudPJ_RlT2ojYwI<0Ei$xjHnj3&CexoPb`Qw)=Q@Y!WH=Ta zr|+HbkZWtH+ahvpJ?QzEoJ8oToCr$#tedTa=82IJ%uxO8n~O4k>?BYBWCsJT>D_M` zMYc<+Fy0U(-;nKnW{gfrr0d_#IFpf^i*$X{f%+1*&t1$I;Ypt6=*jW6T-$+OZ{VcF zfQ8=~?^=*+^YX-u}V NWa)R<4ov&=7y$#24c!0$ delta 1709 zcmX@x#dWreYeO`nVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQG7l#v5ela#VKMe3i*vo;n(5iCt zW9|Fogb+w;j@}0*GHqoudPJ_RlT2ojYwI<0Ei$xjHnj3&CexoPb`Qw)=Q@Y!WH=Ta zr|+HbkZWtH+ahvpJ?QzEoJ8oToCr$#tedTa=82IJ%uxO8n~O4k>?BYBWCsJT>D_M` zMYc<+Fy0U(-;nKnW{gfrr0d_#IFpf^i*$X{f%+1*&t1$I;Ypt6=*jW6T-$+OZ{VcF zfQ8=~?^=*+^YX-u}V NWa)R<4ov&=7y(PH7wrH5 diff --git a/master/.doctrees/cleanlab/multilabel_classification/dataset.doctree b/master/.doctrees/cleanlab/multilabel_classification/dataset.doctree index b2460e7abbb5b04c4f64c39823ff27b26c3dfd36..ee1cd6aa5babff4cee66ad68f38da0bd07e60d9f 100644 GIT binary patch delta 1200 zcmX@z%W}GxWrHuHVOnNRTA68CqP|g5im_3miFsmDN@}V}Vp@`^g{8Skl7)$xp+TCt zfmxDylBv15Vd~~OMnN*PO*WKE+pNaCgqd_3L0Ts#vNw>WbJFG|96@YkX`QxtFaLD% zygF^Ow9pSGvTU8c`L^gT@@$>HIacB|xwZ<(d?3Tt&4zMu{H0 ZxOjq(Jli)nJkU}hOKaM8M^?rzMgTR0ao7L= delta 1200 zcmX@z%W}GxWrHuHVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQGD@MnN*PO*WKE+pNaCgqd_3L0Ts#vNw>WbJFG|96@YkX`QxtFaLD% zygF^Ow9pSGvTU8c`L^gT@@$>HIacB|xwZ<(d?3Tt&4zMu{H0 ZxOjq(Jli)nJkU}hOKaM8M^?rzMgZA0c?bXi diff --git a/master/.doctrees/cleanlab/multilabel_classification/filter.doctree b/master/.doctrees/cleanlab/multilabel_classification/filter.doctree index 661a4dcff14236b3c07bf9413dead6c9347d3aee..dd2c4c9661c60dd6a3dee9fb70dbb3a8f48a0b64 100644 GIT binary patch delta 751 zcmeBL#@e-vb%QsfVOnNRTA68CqP|g5im_3miFsmDN@}V}Vp@`^g{8Skl7)$xp+TCt zfmxDylBv15Vd~}@Mm{pMO*aT+Oy8`;JfE3#D?xgTC#SL(lBYFgasZ#|<_R3ytYqrn z9Kd&kOfQ4%*4lho;0Y6%b_4ZmZY~v(WFuFj}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l ul6jJ;xw&DgeoB6Fv3_xWX;E^j{^UXqjm_5?MOckUHwUO!d9wri7j6I}7%M3N delta 139 zcmdm@wnc42A){SJnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# up`~S7qJ>eKeoB6Fv3_xWX;E^j{^UXqjm_5?MOckUHwUO!d9wri7j6JC3@hOP diff --git a/master/.doctrees/cleanlab/multilabel_classification/rank.doctree b/master/.doctrees/cleanlab/multilabel_classification/rank.doctree index 39e0baf4260d30a1b20a1dd63f51128a16a4d33c..f415b5e8589f10d9450338d590b9586f1c1d70ae 100644 GIT binary patch delta 760 zcmaF+p6Ts-rVZ|lhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+t?7&*w%wvp)MWO f+U!%3ORft*kq9y(x2)2hELVV15YOheZRv~v$~@^J delta 760 zcmaF+p6Ts-rVZ|lh8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=MroTX7&*w%wvp)MWO f+U!%3ORft*kq9y(x2)2hELVV15YOheZRv~vf%5Hg diff --git a/master/.doctrees/cleanlab/object_detection/filter.doctree b/master/.doctrees/cleanlab/object_detection/filter.doctree index 62e1793cf11eb10d6364d5642216470ea952c32f..74389f8ee008720b6dabc2bf251ca983fe91861d 100644 GIT binary patch delta 474 zcmbQRl4-(9rVZYVhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+Wl7&nrk%Yi3o@&=|wyg_K&uEyInUhv#T9&A9l$2s@lxSj}n3R&5YLb|iWNKk)ZjxkSVrFQNW^Q1X XWS(SdZf=;mc>-fEIokY~_i+ONS6L%c delta 117 zcmeB?>yg_K&uExYW@cENS6QrYnw)HGX>MX+m}rq^Zjx$|lAM%mo@8K>W?*ENnwp$w XXla?2XknDLc>-fEIokY~_i+ONTbU#Z diff --git a/master/.doctrees/cleanlab/object_detection/rank.doctree b/master/.doctrees/cleanlab/object_detection/rank.doctree index 605ec114720f455ce3d2db28349db35dfbba576a..91629228c338ce5854352ec52d0834fccc3ad0f2 100644 GIT binary patch delta 1704 zcmdlyiF5NL&JFI2hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+V)7~hhiYoVau<|j;cOyp^uKGmIxfAR*_Lb9}1Z9c>Hk)159^_z3~ znaObU=7oZP$l?61IWQWvMb58^@)NKxmvd>&m~tY zqk0OtT1B+hk*l>(cRefViEwkEu@Nun+9n4Y=WJGRH1H%{>*mI;iR9###;&x@DA z8E2B|i0K6iOyb*tfl)0$o&z8T)U9On$s^Bz?Oqa0THNI6oetD1w_QkuiA9+#1N^oF IOZ<6^02;3hi2wiq delta 1704 zcmdlyiF5NL&JFI2h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro5P7~hhiYoVau<|j;cOyp^uKGmIxfAR*_Lb9}1Z9c>Hk)159^_z3~ znaObU=7oZP$l?61IWQWvMb58^@)NKxmvd>&m~tY zqk0OtT1B+hk*l>(cRefViEwkEu@Nun+9n4Y=WJGRH1H%{>*mI;iR9###;&x@DA z8E2B|i0K6iOyb*tfl)0$o&z8T)U9On$s^Bz?Oqa0THNI6oetD1w_QkuiA9+#1N^oF IOZ<6^08HN&nE(I) diff --git a/master/.doctrees/cleanlab/object_detection/summary.doctree b/master/.doctrees/cleanlab/object_detection/summary.doctree index 43c99411d8d089756807e8f7b19c217c6fbd48a2..bcec63f159b984d76220adb7ab959e412fe5d51f 100644 GIT binary patch delta 2429 zcmbW&&nts*90%~e5A$P)*g-s&Ur{W!+4hWuFqXstk8;xU*w$oM+XYj0P#Wn`k8*IB z?4;BO-;$e@+*}>3iKFu4;G{hA7wr89yx#B6_w()Bck95sbznZ5WRCDsG#qosly0XQ z>~ShCNl}BLkV^@xZf~#TQoSyZ!ycCG9#vA^lH>?!>x=-E^UZ46qH66<*uykE6|4#v zHHtSNnV`y&?^1|v(pB{?vfi9;lYT6>*in-duYJc_lO)!kfUW7c6_jLaxTkEy&zRDXar07+hweww`JL0o{~E$xpV8nn(T7r<-(P6?niE-M^yp>>7-ObdI>2t3gnZs)-~|11OjLK06ijzWc#%_5tqxFNy0(d;pt-i(cUi PT)U>*dVV!7`1^hVnz;}B diff --git a/master/.doctrees/cleanlab/outlier.doctree b/master/.doctrees/cleanlab/outlier.doctree index 6cccbb7f0c125ae00691807db652113b7765fa8c..2d2f7ea83ee8c272028d259e532f795492ee4829 100644 GIT binary patch delta 1486 zcmZo@W@~6>+u+M+n3kE7R%Tk3sBe^%Vr-OXVxE|klA3Cgn3iN}VQFrXWMN`vXpm-Z zV3uT_WNL11m^!(R@h};>KByUOUc$7Bg*>g(SJX1{Pd>n2NS1cj&C5Ah$+OvY@^TKL z%_h9OtYq2jGTA|jb@Of^0e14VZ+4K1ASaGKsDW(e*eoiuii>ocH-At&L7uH{oAot! z_mghpWT=BDr|%3VQ}=?CvYUN&wUHOiE|V9WRN9=m|0a3fhG@TeFqw&L$182Vd?b|; z+s_}1A=CEF3r>o#k?HUWd$~3nUpPQUA_GS`NPE%kc0=-PpC-o0y1kf}(UeT8_WQA4%Z|A delta 1486 zcmZo@W@~6>+u+M+m{DeCSe#c`tZ$l}Y;0+6VqutQk!Eg^YLSwhlx&`4V3KBFWR{wm zoM>oinU-i_ls37J@h};>KByUOUc$7Bg*>g(SJX1{Pd>n2NS1cj&C5Ah$+OvY@^TKL z%_h9OtYq2jGTA|jb@Of^0e14VZ+4K1ASaGKsDW(e*eoiuii>ocH-At&L7uH{oAot! z_mghpWT=BDr|%3VQ}=?CvYUN&wUHOiE|V9WRN9=m|0a3fhG@TeFqw&L$182Vd?b|; z+s_}1A=CEF3r>o#k?HUWd$~3nUpPQUA_GS`NPE%kc0=-PpC-o0y1kf}(UeT8_WPEy5GbA diff --git a/master/.doctrees/cleanlab/rank.doctree b/master/.doctrees/cleanlab/rank.doctree index 71d708d6fc10f48bad860017d23e622d33ab6e45..50a7b4c11ca0e5063f8b2dc4c0977b00b27f3aff 100644 GIT binary patch delta 2066 zcmZ4ggKhl}whiu#hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+V)7P|LL)!w{G;yoMr z`VBVgD`b%oSks~Q8*ElrTFpeJ{hJL`Pf%ocn|dI*b_2uCU~{V08jAGK*DYZo)9+yW z7aFBdT1ZF?xP-_!mBMfM+eVq_&h{v+#sg(lxwEVy~wVp$wgbz6JKUt}1C@M}jLCl;wWn{WWMqK^%dP2*3KZln7MOAD+xzA+PLd(rVcUUK^F2lY D3s!4P delta 2066 zcmZ4ggKhl}whiu#h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro5P7P|LL)!w{G;yoMr z`VBVgD`b%oSks~Q8*ElrTFpeJ{hJL`Pf%ocn|dI*b_2uCU~{V08jAGK*DYZo)9+yW z7aFBdT1ZF?xP-_!mBMfM+eVq_&h{v+#sg(lxwEVy~wVp$wgbz6JKUt}1C@M}jLCl;wWn{WWMqK^%dP2*3KZln7MOAD+xzA+PLd(rVcUUK^F2lY DKCyPp diff --git a/master/.doctrees/cleanlab/regression/index.doctree b/master/.doctrees/cleanlab/regression/index.doctree index e2c96c80eaaf740149d8a48e2c5df1521892e1b6..04972d6d0f34df832af9eb5ae5bdcc21e01719bf 100644 GIT binary patch delta 120 zcmbOwJ4<#$Fr#5wW=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l el6jJ;xw&EL<`%|wMgvl{P3~tD+Z@R3$qfL*)g!L} delta 121 zcmbOwJ4<#$Fr#5cnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# cp`~S7qJ>e~<`%|wGPF&ez$m&oklB+P0PsH~%>V!Z diff --git a/master/.doctrees/cleanlab/regression/learn.doctree b/master/.doctrees/cleanlab/regression/learn.doctree index 58716cb25e7b543b6c1ba6e20c5b43914e368231..15354ab29a399b2bb525368bfd5c59da56a9dea3 100644 GIT binary patch delta 4106 zcmbuC+e=hY6vjFGj80AJI8zaae5fo8temmYW0X&6pas@=>q0s+%#4{i)_9@lK@oc} z1Fa+NVqz-j0$Fs~>4LzbP$VIVdFf^_y%k~fUO{^Xy1bsxKj8O$YpuQZT6-_dWG~EQ zKWJ9m;nri}o{}DaQE?!+wb<{`{efU8UM>7S7|^Gl<2xUBu12P z0A@Ji6}+ZNwHwRU+eDV-K!JJde;Qv3yCB>vlAC_1AnJ1`GC*`(cRE0{y6Om4Zm)5% z*J%t_*~GrxTBdn-e!|E0@TWy;zOZ?hZZUs9Ah9#=Q>by zdf1PhR76al52LQLqlBVsE={0lcdQLSg(LnGz+@vu#NF#Q6s^DU0YHWSHtcA-^BQnW z=XvVhL9~ma_m85kryrdGT!s5_7B)>IVxHasj_DHBJ-LPEd3ka>>e~4%inF_S=DEwf#y>#A3ksOyh8cx+cDaxL-*i3t4i_ zwA`mebIhA^rGeG)zIG*(ayyhBV6*mR^ziSZ+g=C##gVp90NM_LwW?xS)ooW!7#D5d#GI2Y7TC4id`jPye RT66%W-?eP1zm$^#ZPMQqRTgnzua;@touBlwef(*WnlCJ#n=^9Xiu~QK!q*#6ToC6g~Z+K78I?&@c}@E?>6jcx$_!u zOy}8m?=ad$;rqu?*VB*A0ItIMI18JmA+bR30LOHR>Ym&}^SnI06LpO|3!|<>FUnC@ z@60&rs>c(kt7)zqbzSqS5_SDC50CB2L@u_Q8^pq!DLb?*8ie+>trzyX zTA7*7PAL6HAeCC(anr>2TbYfIL}gIPMpjCn%`6F=jZ7^qM^bK6795VoN6Oi1D#&AR z@gOw1lFvLE7{rMQjXQR;3>qtEDt4!8btytpEDZEE$+zxz zlktkB-pD;<4zdp5%u{ePpYCBAt&K1{FmTffBo#U=Kw&n_<~vN!xX9Bw`L{R!WEZ|dvUEpJz9%faIfVZoGkMxK i-xIz_hStpw#J7w&n_<~vN!xX9Bw`L{R!WEZ|dvUEpJz9%faIfVZoGkMxK i-xIz_hStpw#J7F`jq; delta 525 zcmdmUpK;H9#tq(#h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro647*`sRtV@4#Ah*oq9%h5dk!<{vH!<~)X~gCpW`8C!^+K($C11Pl qjdq#FcIHO@&W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l fl6jJ;xw&EL<_^YMMkA87=}(@(BDUF=xt<#UJme(Z delta 122 zcmX>jdq#FcIHO@knVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# fp`~S7qJ>e~<_^YMMkA87=}(@(BDUF=xt<#UM7$-H diff --git a/master/.doctrees/cleanlab/segmentation/rank.doctree b/master/.doctrees/cleanlab/segmentation/rank.doctree index d3c6c4978ce765552cf57e5569fd108331a5ede3..1d8062f6da2e50d72f0ff481701fe8d1cd0a11fc 100644 GIT binary patch delta 707 zcmX>!f%(t`<_+$QhH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+V)7$1_MOP9@lPt%^Z~iMalaEZTYFh2VWNCGuT;D0a*{1F^7kSz@*LPmCAw#P? LYv|_N$I=-Atx?;$ delta 707 zcmX>!f%(t`<_+$Qh8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro5P7$1_MOP9@lPt%^Z~iMalaEZTYFh2VWNCGuT;D0a*{1F^7kSz@*LPmCAw#P? LYv|_N$I=-A)=c0E diff --git a/master/.doctrees/cleanlab/segmentation/summary.doctree b/master/.doctrees/cleanlab/segmentation/summary.doctree index 1a3c99467d3d10037ad6afd1de7bf5964a7e38ad..4c3a712f203b0a372017b4ed3951a2b4863d75ed 100644 GIT binary patch delta 1026 zcmbO`n`Q27mJPm)hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+Y57+;aDYx+fQM*qz(m>ikN(;Gc`D{CQnT74$_bMa69ASk@~D4QZH zWoC$P?&R4-MxcSb4|9k3=6if?WCjD+jLjbe=TqngiOt3$6_mIE7@iWF{l%ZMkQ<)$ zQi7Wg$?WE*L_fFgPcL%y+X;$po>mdeONsvKwmNTe_2-KUY;L>c!A^<(=v%Iar0d@f IOp9k20a@of-v9sr delta 1026 zcmbO`n`Q27mJPm)h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro7l7+;aDYx+fQM*qz(m>ikN(;Gc`D{CQnT74$_bMa69ASk@~D4QZH zWoC$P?&R4-MxcSb4|9k3=6if?WCjD+jLjbe=TqngiOt3$6_mIE7@iWF{l%ZMkQ<)$ zQi7Wg$?WE*L_fFgPcL%y+X;$po>mdeONsvKwmNTe_2-KUY;L>c!A^<(=v%Iar0d@f IOp9k20nR}}p8x;= diff --git a/master/.doctrees/cleanlab/token_classification/filter.doctree b/master/.doctrees/cleanlab/token_classification/filter.doctree index d98422268b51603bbf6f2432f880e4069de46e5c..fee804d081bf338e949b842db4feb81b42f66756 100644 GIT binary patch delta 483 zcmX?gh4IuC#tq(#hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+Wl82^)@>n?ljW=`hCEM#fDMV79p$q9U_o6|Y-$g?zRa{}KEW-@JV h;1=4vRcJ9e;d_@oYBEUsSCP12vTV=X{5B(&5diXem>B>7 delta 483 zcmX?gh4IuC#tq(#h8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 z$%%%RmT8F=Mro6482^)@>n?ljW=`hCEM#fDMV79p$q9U_o6|Y-$g?zRa{}KEW-@JV h;1=4vRcJ9e;d_@oYBEUsSCP12vTV=X{5B(&5db3wn)v_# diff --git a/master/.doctrees/cleanlab/token_classification/index.doctree b/master/.doctrees/cleanlab/token_classification/index.doctree index 316a0afd03a8c3a48d0b9b6ec7e16a1184ff314c..b4388ecf70be759cc99d6333aa7f60c291e12de7 100644 GIT binary patch delta 122 zcmca7cTa9ZI-_A)W=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l fl6jJ;xw&EL<{6CZ8I4HRrayTfi`?ev%*VL_X`Ch< delta 122 zcmca7cTa9ZI-_AmnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# fp`~S7qJ>e~<{6CZ8I4HRrayTfi`?ev%*VL_adalt diff --git a/master/.doctrees/cleanlab/token_classification/rank.doctree b/master/.doctrees/cleanlab/token_classification/rank.doctree index 0ee622aa95817a66f42b57befc16e6acc67e2db5..4f0395bb02f962bc3624a3ddc37d4cc1111a1839 100644 GIT binary patch delta 699 zcmZp_#@v35d4oHnVOnNRTA68CqP|g5im_3miFsmDN@}V}Vp@`^g{8Skl7)$xp+TCt zfmxDylBv15Vd~@x#-C*9y2u{6`8U&27P7QnBSV)Wf79kD&S|WqYu&8KKbwhkZIc!G z+cp;qEhJa#X;BRhvTV)YJX!7pIWeiopTGIHf@m)3wr+OpTS1PEj(s_s+a|O`kZ$AT Ni|nbJ7rabo1OVD}*ogoD delta 699 zcmZp_#@v35d4oHnVMdvmVR2q%vA$_?vazMPiG^XJMVh%uszpk2QnGoHfk~Qyky&bL za-yN7Wm=+zQQG7R#-C*9y2u{6`8U&27P7QnBSV)Wf79kD&S|WqYu&8KKbwhkZIc!G z+cp;qEhJa#X;BRhvTV)YJX!7pIWeiopTGIHf@m)3wr+OpTS1PEj(s_s+a|O`kZ$AT Ni|nbJ7rabo1OVxe+}QvC diff --git a/master/.doctrees/cleanlab/token_classification/summary.doctree b/master/.doctrees/cleanlab/token_classification/summary.doctree index 95d850528d393162d39ba97e957ce5f14645bf4b..e15c33d9e7f02abd9c4fbf27b59d38f53d419943 100644 GIT binary patch delta 1014 zcmX@}mgUS_mJPm)hH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo z24+d-Nv7uJhN+wD7@5e?wvlNK6X~{1-pCX`-QSdvXYx5JwS%vfu4Z5LVWXV{<-9Z1I!4C&2NNSDR9MRUeVc5JwS%vfu4Z5LVWXV{<-9Z1I!4C&2NNSDR9MRUeVcS*YD^cieN#o_ikeB*t>LTA|fJIM5D2wf{Tn@?7hXZc0pr} z{bMYNy~Gw3Vu>+Pf79-6ImPckNB+KE-tMzA&+~rIGtWFTJG*!MaxzDH>}rlQXH95q zd{S(Bo%DzrH6x>I)r_cJFCsEJCZ={oY-FAK4eHg7tY5osXh>|mkh+oeBJ0$v7aEg$ zHCk#>+TNO3>m?l?lQe30Olti0SKi62ysmF(gNC(gHmuozOY-x`v{e27Y(FnsHhk!a z)To%~_|&}YHZ{_Qq@e%*+D?t=p;5zYa84B>|9u;|`4v2w0I)5pdjQup)|;sevYsYZ z7UgAE0WCJTSL22U27!WU6=m>BC9v)9u6nN14;m&9gpVKM&-o41bLyz-j0fk(8@WXh zo}h4Xh6Gj(1k9|GK(0f$9^6hed2(I)SLA+(3t=jP+&P&6(5Mz&cLLYeXxzEPXeAhZ zqPYoLZL!ohgsU0QknsUozt#6+OyJJr7!wy3S&<9%uLutIoaDwu#Z}=%k)FVp@8^VB z<<`oo#AQ_pW`aP`{?0+%&Y-H?`I&02ILL#$P_ZR6(z)2hG$%ZeD;!vz@d9Cm<9)b( z@jg1&sHB*PvKhu>T|;?RpX9E>m>2X(J>iZ^UChr%P2o5DkjJJbJ_qupjj6j!Yv!< z!wnzg$4v;X!_}(d4&>MFnK)79X0RLlxjQwgFm<;pL&Q~K51T>w-RVYd ze6S~XEy|tyBgl=LRHZ*d!U5tMxv+sc1VcL*^$6FudVLypobNziaHh*7R}=$Wx5x^p zS&Tnmn)dM5=Y8U*Y|^tF6B)pmLD-ZG{hU}QrV>B_0l|EMU)9O(+?GL7z1r&G=!mq4 z;W25bbl8dJzOWkV!&=oLRi?3s0-DXsCh;&kHh^&l zIW7Nihd2VS2UZmf5NTdEjin{kLdaN?;!uMs+_GvWX<9^NQcPa98@TY>LN{p0Zs>Bw z!3I!xq67_0J;>!t^k^&$uT+H#tQrK=8h@E0FWVO3n}e%yDX~?#M*i+Fj&Ph<$HU#Y zAVKKSDBBuW6BKma>&a;XDll%)YXjW4Wf3Nv3pl2-FV`ZXG8z$Z=)n&0;)=rcG>|}e z*S)^^T_#n6BMF3!3#tX0U#a9ovOvyYPs><+UQG@b#Pspth7Ixu6MIfFajz>>0XcPR zXt>ltp4@~eG1nrYDjZNc>p(fsbCNroZ3elO;7HO`ss$o?PVxc~C7G2tNo*BM9WMO6i@*A6y7O1@O)@h4oD#NSDdL}| zSmLmBfAF_hT1lkeJ7H-RmL6a1jHSm|8hfJ$mVU(2v{ytrhNZ@}d*ZTRu(Yfdk&a|y zF({UZbFlRCZf{)m1eOXm_QBG8EOq^vNT;xrA{~Uw&S9x_1tPt`()f?@xNHxW^tnk` zD#DWN&txnu6KA5<&o>Xn;-9#1>wpw29mJ9(fk*{d@)(ec%g$q|bKNv7{e-3PXCtum z2up*V(y_D%OTWJui6wxgfe~Y{^icd&CWOx(PQ<@);l?@RaN#Q~-S0dZOV_ZJ;yM*e zg;<&krekR%mPW24(sL{gyFL?_?Znax*IX=J#?rlD4og>|lsVm5^;I4gf5(MJE+0!* zu(V<&k=A2Lq@Rb&7GP;co%LASfTi&f8?bZ>OVuY5X(5*W$k~j`&SGhv`~a3dA}P~( z-(4c^$Ax~c4&lN-uvFbth^4P2sGDYtAksg$thv)+Tvm*wulgRr(h4kfmLA8_MJyHn zL8KBaRnwlpWlyn``P(TP)3Ydz*>H zO<3Gf^DUO%V5xWCuSTJiv=&Q`6)cvHVrk$wBAvlf(P1K8$I_y6L|TWXsHGg%yNjjs zP9sMno2Rj~VUu}mCK9(`(RIg!u}Hd&rQNF@V`&$bw%2Vn6_w>-X;o(;oy5|}yXSD( zJ1kW+Et!UD9>7xARP78TEydEq2ZdPr0Zaef8=IYx2@8M2V%pF3XQHZyv80#X$I?A4 zdHE9QC6=Cv+sr~W_hIRsNj@7%zhWslt5#|F9GyPr=f5EcFv_9pi&51FSW0C5mu7G$hJPzV^TX`C!0gIg$23na;h{pDmy@uK>%TmR>oHl) z^-uE?OFT+f7hc3ZDOHR&cLI2g7QoFf(Wngh=biIG6EN+3b4A7PoM$ z8~641{kS%ZF(4>>;-xAL%|(>OpMAMoDk0SoPnyN`3+Uinph*B z4OVbF=CH1CaMAhJRb{B#mvI}utIPb!Wv(@GU8d`C>+epk#Z8>p2y6L{tBINk zy;i`rn>C9IpV@-T$!dw~ogY<^IS;RP;7}{RpWF{(j926&pt%zg&Thy>%&Y;Lzp1F; z-cD=@O)Rp)teW1G+c~!-H4V7M{I}ecY=2~kiQ_c+9k_!l6#rH(|95gdgc`35{1)o@ulD zBK875(CE3wrA%up^jug@TP|dM7t{@qd?B_labhs;gg1*@V_(2lGyP#-x8XXklyHY; zJ97teUAVA0&7sC~WRPo`*9r!)2E54JtN>fo4yR6YgAwG;#e#v( zXzoWk%f?sb-hdX)Xud~s=WQNb`W!WPdz3i;H7DkttZM^<49)+jbi(`&T;2Hw?$Erd z@G4pdkgE|~4A5}r=c&N$3(b{E7&&NF0Lx$&L0Lh%K*cQNwyiV4IxeMh1j+}!Hno7A zhSmy5qZ-lxx7BUbaBL0210`g>6W42z2`7|x3lHN2@{yA*KJARw5Qu`$(z@2PQ>uSg zWF&Gccayw>@(>v`Xt9CR?i9Ei1`Uc&j!zpj2>U1jEj&;O@&g*@1>1aKU;TsAUo1c} zNqKVEMzjziRsy*0lQlS~)YZG2xcq|lP-z7xUzWyY|KL_S;<|1O<&G_jfh|Uh6{w$G zl^eDi-h!fV%rEeVnk6vT)#JKvbVD}=+|A`mcnp0kI)8CqD{6C-yuZfbHf5E8>4E(hxJnDV3oUUF-ISH_-1$}2Vf`C8|4mqJl%XXK zqEZJ_DGnRp1)bj)E8kn)2UeYnJr?NN`N{qPRZphsE8+qeH_YMXa$7$_$-ZLVYY@tHD4Al=YrRFrM-j}MWjMq zlnS87(837Otc_}OUVD_RZH%L+LrW!8ZX5Ur^32BST(^zAkyU5|Euc`H%G}Z|zM#vV zA!xGbf<_G2Xp<)#9BOX!77b{AK1s&C++5c(#-S!!Y$466NRwNb$4#bmI)}%q34$1jwG=)jm_?Z^O@VWdYsep06aay^Z>ns7HH4} zcVU4WPW=VjlDX08o^ZlI?tjmzw}&t{ai^qmm6!-@SHO{>gx z;yt-~yh?_aedvlmx&jK!Q+Fs6Bx)v^Yfeg1N%o6+!Wq5~&2{HbLB?bPaLQ z3J=wr3?e$tNdt1jOD(*LR(j~__vq?W=w-CnLl7kgMuHEcfD<=*e;O$M4#>FVgK1y` z`%=cm9ZKUK9T>+AIy8<;gvaZL#(^6mSnw3qP>bQo`+aHL^Znz%Pk#a#w22mi$mX!4 z8DL3=3gRK?HB^=GQf?YXyRI{$lZ zP~ur^+Me)m5d$PYnA>ul9`E?~MmWt)|NLkct{J?FC0x>zm;c@b<^gSdv;FzgkK%IZ zbI+eTf$W`~rQGzAZI0V%3qI6m4BK!2@ydzW#{K-){qmXuzQK(5_OX8-W1+oPA5#At zdl?_QLwo!ghPf+Zwt=k@X5)WinD=pJUO>yhRnDaUHx}C}m_7{Tx?IUTMaNkx<~Ta` zRFk8(mU)HRpffW3e}g#F#GI5si@m&<5&w~bV(DH$5%)#@b(Ul^F?6Tgg_57q3 zOfGV(p$${sapA?+{+bCxRHw9M`k~|9cFbNF1^nVJ%sJ=}en=1IHweae@54NSW1DXl z&b&g`YsWBq%F`rJAZ84p_u>c-ep4dT3Ar9OPMyLOIhDgz*e;(wl4*+A?i|MipyTyP zOceAV-#nZ74Y9AB%OonxgOakmzArde$VkD4)qQpRfF;a&4@(m~_cEe#H31ptp>Z^L z__QCH=BPtiVBLEnA4hcqw}Yg=h;o%OFp+QnN5UZsRptR#GkxZLI(w;|#3MI`h}O zS-qS(2mIy5>cDv|$(+3EFhX~zJJASCmdZXrFsL%FA$7)SjSJa-yt=R48 zSo|&f99_TFiM>*exE%==Br-aFY7h2XYm?@8w=_u?&aQH_NxP!iLe$?ygV|H)n4QR0 zMuc|^Wt*Y?f0f2QL&v+L+1u#)kxaIQ)N%KHW1IO;z0iOkrn0*j4rtm)zX4mPv0MMW zVLo>{Tb2FydLZJNs5xJKChI0*IR2X)_N59Q8!cr|GVmx_#%fu3G_PQPK=My3S!Y!5 ze{0C~-`24&Dnt451$H&k8+V&^bB0IokiCrRCqHJdqhtH0tT)n2c+Spqq=yhm07?45 z$BUwYp!g5g%dw_*;v8Li9g00@6l`en-cMQKCQ5vCkM$Kcv4iQ#2CQuRcli4qXqNEV_w~ z&fkm9qw80vi*k{jgqfoG$iA2(a{gS=9aNq%U$owlZYkB(*^Wh994Kz!ujd~v5pmE3 zVC-tqV#f@n@O#&Yo}tiRyIwTXQ5%IDMA6VCpwbr6GDmF;-YVLJco?=j&ZGJckpb~& z#fuzx{R|Dl6n@5T(KckG$$rOq^f(}Th1$}tP_)!he@rhD?L#)c{?TzB1CNTnK_R{R zm}nn5MxGGuLTz(9E!yBHub4BUDh|$eDSXIz(G1k6{TD^+9VOs=NtEqKGQ+)F`!Y%N z%dd)7I!fT-HIdR`59D1JEkGWqam(>87;{^+)?ora-V-fF1fqWvZFbZH+aHP!JKP1v zC!!IEK=$vBbO8^$v9`mFuUjlygRpP@AzJ5X;{#ubwmVEdHgY+fbHU5-h%ij>AL5@Xns&&(#$Bp@l+81MxL<{ijCaeP}}ezJ)m61zqnX zE|J3Hy=t)G$BO&JPUu+mfcRH*bS@N+fZpcE9TEE>dFfGcuoFC< z{Yl&o;klg`yP;#POJaO;((#J;4&qbeh8V9%``i{EMtYw2#P^XM=AjtgMRUCJvAClQ z9{c_wc0%?d-iq(Lk)>A1tgo=%7$wlPQ#~R55 z1fO7()I!&nxJmFmQJjb50V?n0C0T{aU-?PqIJg4q&MN{W-yvV-RF`yA!sE>bk~mLz z{HCYG1%dYHBRS>B{W8o?ok8IMi4=H$Kgt~py3r$nuNp34AYmNpfE^^EcOA*ml4B0? zw?R1bN8%)S!CWIrg5z73ESZVi15zbM)N7kZO1hM%CC*^Wj^CWY&}Q6eJ@ExZf`k*G{SQxX~g>yl9D}3baHz z;p!sV32TO~kT`0WFJ32Ek4P`vL`aX=BI%4ge{{QKI3nF(k7Ol^v73dGVs!o7Q3>k^ z7>ubf&?V%R225z_pFfuz zLh|O9lHX8Dn#($MQo!SV7pELFTt>J%eL!+rfYWFX$EMQG;C$LB4WHT4sU{rNWF9!y z%4xHM9wO#|>z=VLytcj5PpB0)J37IK2rz|rc1l1UQm2PgRR^9L@i2-eI5Oozy+NSb z)zPuQxxZ79rI9!KJBj4~-e)|VFftr*4%AEMLz11)Z87j`snhe_Q=C#@A_gH7p>S=q zQ@kT-2$~(hpC9k!&}s-N1E}oDSD)zg81<3qJEz4c;&x7T(xbjRHQlM5BZ&oC4h6T) zIP3UnIZjU<=xwx7K`lI<>ogY)@XYy6vk@oPMNY{mj>a!@>gmW52wH|)GX7(l@-x>t z-5vMuW5BwJQWf~V9pl7%1Ulo~|9w^GzmOBNsyjQw)WA<`<2(TomA7|3h_0XP;Jg+c zQ#&~qp=0eX&L_|e{k|tD-`|^*$MhxTmHRv2N9D>WQvOpkDNl&fhNO^JrDK{-A<=0j?A4d9%)|2vn8%eo%Gbul|#rZrc2fIjl&)uZ_ z;~r98w9ok&%G_IyIGf57gq6VU(b1#%<0qYWIXJ{Zc^J!RhlW3M-g!Oh(~Qf`q3F2& zSLcNea%;!KeZijE^2gudS0w&|-;($XeCI4h@fWIM0$J{Oep%+RBm5d^jVLZE60OYSOx9W+mFef8aoS;O4!FZ~C?LPe;q z4|?y>bgP$!&XkTX4<*vZF|(vsB_tf8^Q1$|Z!lu6bSN2$;Ldz$LHP~3E|jt&!mz>; zX=M2gYL`l<(`>S-KzftfUbIp=zx=k3tdiECtrxAA#+KV4xVBNM1RgnxYJ80i(#n+f z;EmEply>-5>B4fO@YA+Q$5Gm*UH^rToq6eN%Ftz>bWV8~@~->gFf5M+66tjhNf*%3 ze5a^%EjVCy9)o`c`_Js)fIkcA*uD-b?qn z;5@?5RLCNY_;gnVSwE_kR9Pm{lJW@+WZh-t^g&D6pVYv!uVsB5p6HsVN!|Fu4zm9_ z6JM?EE=w$zF#wH8`Mkce4P=$UcZrcbQs)ng(DLolWxHtmH5oFC+g^^A`8bhA`De*? zDah%QY*~9LIsJOB?4{Yk?gJ^~r7C{SW?5Z1Y2P2aWm-pLff!5OFRMhEt^HAEiG!45 zv_V?F+ew+8#zDpz*$EmQVdrH}=+zEC%huAqlU$R1q{a+)Wl^+qr#+Rmcc%UPhwPln z!N%vGlbgZJzB0IowT!|O>`u@w!xb4+=bLw0vDn2RjA@ zk__A|lB@Xno8)mMG(oS;avf;iOy4!h$?zHcM{*(`JWFG{tU~#L9fi#deeUx)F6c4Es zeI41ev9q{dr?^04G25iLq$I5zR#Bm*xn)ijg(d0|t1EUnc=wmi*J$E0jO82DRIH}n zDXyisLj(72OGPDDf^6=pu*C4n?uuV&(BuqISfVv%kiz2XMiB~&tKUUhPxnMC0%;fi z5wDOrc<)#P?uARM0=bjY9lju=$S{%wP(54G)!{UcEb{U>3bP}xP2zro7OLX|VrBMGWl_E6l&_uzWWtt9E=@HM>hM>+L3RLDtge4 z?0-q|1BLVX#oCb@t}D{$md}ZzFHE*mvJ?^cd4z+va zy<%_qMp9w#J^sARN!i^E_bHG$D{1~%>Z7dYaPQ(#ifjYf9EA#;n6Fd;Wu8LEKQ${V zF<@3@rB{9$)0S6PR&JvmbumQQih3iUzVfDn^Xo^xb`zy#f$(=zf zb{Y~2Jr`R-;oKIb(Lv|o)FI~~ls^sXNxQB6eC1F%`uV|+)_&f2%-YY>&nZ>Z@#`+r z?$Gd;ZYV7y&Fg`+JB~b7cA%tupDPzqzn*@nJXfxH6Er<6bp_`=T%19pfv!5f`UmAg znlW$aUB)=Pc)(){+2*0`U6d{GbNQK0PU8Yy9C<^Whsks&O`#8iT`U9UXg!y54Hy&k zY_AqBmZ9=(7ngmMtD%>R<<=ytzl)`BPDQy`hDu7DizN&C4{@;!mAA<*mZ5Ss#l=W{ z@Op%c%E6KF4LCc+MG8h24Kecz$GI$WA~Rcu?_A^#-j#pDLyL`RGd*UySeCK(X1Q3F zu}5=VEX&xZb6qS8iXZ2>Shjf=FLs&Cg5vk^cBgiM%W|5+9A<3udpwz<0b*;ue&(#au57=o)M^j(1?MuYOxBOndzqh%_mgs3EXF}T9BiG zqyFp%7X|2f)1`+4i_uQSF3mykY(FR9{M1X&*S+OZ*O7_AVnzj?-gR;0?OA9bjQ{JN z3w#xQ75Mp~%O=O#5(c0RBbV|~%2#;oB64JUg-m+!o1VL*II#HSq4Ikd*aH0aRQLy% z$tq?Q|C>^^Q38*gRt3M?vWidCt6Iz9ajUlqK4M+PFYr}OmBOQckP5yUy^8;{iYkYN z$Enp-ol(83^;EBs{@Es~zUUa#N;O31n166z<4)3mfL^Lu%wv#M64wFvW>>2W0(+|* z__m-WK&7BCxLCoz?X8lrA^&z82V6L6)`1CERUyD-xyA?F9Pg^;SM*aIaxS;2&3~x| zf}=xJx`x@Dqi@Mu>2=x_qbd-Atvj_Euq{rN?>M`j{Ox$vJtxNv)CVC`RZ<`u=B4BN z3{&lJL466oJ^{?BDqa3-l{?=#Q`LkeTo-4llFA9C;^$0M`Af=Sg@=UuOE4jR@l4fe zhMbO`ty)P>YviinSDBG_`RjA6r_=IO9!7F?=X%wz@OMp6g=M=`QBLI4a6olfQx0Ot zlRf|jN@|1uAVkO$yxjAud16ctH2hgL!*O;!`GJ>Jw;0C^@Nh`&pfS+qSJiCCte}C} zlOJ+jWhlqU?#X-HQbnG(XyYH$FIp`767WD&FJL;Cihvn;?*^gk>E{|XT zexe#exr}%eI%QY31SazgMcBj%JGjAJ-ma82$WC^^uHn z@PKj6agY$SH-I;YToW914mRN9#b2MnMfk8^wRLbS9%GJ?v zjZJCPt~JZ$mwQ^*xhyz;S*r!p4X$&`(?^GluG7oK<*}P<9Q8}2r|Zn}aGCApde*@{ z;-O;|beXWfg6op<(0J$XddWc=0QYZlfa^NylE5I>#pU4=Q^i$9oAq6F*Oc;@$_sWq zPfd-e>FQ{v!3|te%k_G>g2ug`Yj^6Q%m(G-vbLe?da>hvX~th_=6bFi-Q5g)9USGs zH*e`WN#!_=27I$H*Bj-a(EvaLYA|qdgn>WM%{9-_WjyTP2K_9TE5VtA{_db-H;?&zQle{51zmXaSJGX_lp_usSdBY_7m*%L z{KHYM^IgdbH+P!rPjq2CWQHqi0y%Z`T0U#JYnvES;fk~RDp_vwg-Z2tH*$4efI6@e zIla(ceMDN0mhia57Q)SWWl5&Lyw59@^E7o%2r^l+{9tK|0A52i!piBA>DeC>S z!9S&{2hzKSh8gO7TH(%k^(}gOVX}HHJ)NGd-bRge$W_OQ%G2PGx$2+G)kbJQ$4tymrD=(vM8Ey4Le)$q4PHSSCK z5%1Ir$e)LI`DYxY4oaDH201?CopwIfc+lZvaMoBx-Cd~${suj6joDSRnGV1!dd)sZ z_becEQ_!G-M!|b~Y8F^K;*5{xsiOgdO!ClV0;RX3vXy^Ukj6x>t_#-ep?x$wL<65) z;Z`-Qsi{vpaZ+7PS~+f28iMEbUbyqK8f)q>mhigTMC0RVAHg}xVzRkr0$G^wKCLuC z^t4YKYkT~^(TpUkD1JjbP1SNWVrWme@s^q9rvtY;c!q&Joi#deI$Way|BQ4G11Ub5 zY9K94Qw;{-vM`Nh?KZK8rX0(_hCBrQkv6M!A8WHz{jAN(AE>!njs;Z%pbm8v^UtF+ zi^Q;RB4)rh%?jc)TzO^&Y!X0|Qhr~OW+(N3R*Ggnji*i{G{4ia(|)XGKsnNXLr{>V z5%WRcY2eN;+27;mP1A_V6#Wre1? z2yF3IX@Gf+#(~!wE!)W|9{yFFKw^s5ZqQtkfI1-wUf`F3hqb`4P2<=P9U6J{51P7S zaC>p0hVQjY6U&m*v%57r8hKWinPKnw>5tBRC!O+jao=~s5$LI>UMms znJglw_ugt=(h3jXYu+;CYVk)+9crO2s~xW)SC8tntEk!-llBg+JH$=E1y37l3;+GLzty3;8f)PLvI*&fHT>PC+L;n^I-#`|CP#d=-PhWR3g!rTWVI_y z>%gxrS;4p$l_h*(SM6>&m~q3yg`Ye?8z&~G?;^Cn`!aI~Oz9D@;GA zJxwhPKCF$VSFiu5?N3j?J+7TfPw$@8#?#aOr>%Cq&RXd_IIo4zBQVMQOIA8}E?en@ zU$d(D{c5H2({=4RYInmeEllRvLiRmv0=??|n-+cteGd6vVv|Q&_?i^1a`K7x6|H^t zxpo%4I;2GV8$FGFrG;-;;JW^Av^(hOqd%?CbNS`Y@YNW6 zdbhc*DXh)IZ;Zn1g)hx(t+T{ryS6$@OwMhm>q{!^>Zr3sa#1IpB@PS1be1?A*Td?s zKYHmb10cGuRjpEgon-(#8>q8H+>%HHhTHojTGxlN=|0%1W{B5qrdKZ|>Sod289vn7 zlN*Ow9rDj`9ekdH+mkX{*T?GWM`Ltx)JDX3_=|R=%Ebw~0muum*L-P5L`=7K#LAhd zBe1P+b9KQ~XDVmyh#%)#arN`84W6>V%KV!})&{#SwR*Q`xz)SMRTl5^BiC5f>aRoY z?Q+Xa%bPdqexe*+ZLzvH{s$}CuRE-2i*{MjqW4(cYdBy<3qNE<`>DvPmVLzP-uB0= z?tOC7>R$iT)@BYrtGi3x8~d{^R!qEeYak?x{mbp!%bZ}tuXnX?lld(84s*> ze|%`ITj7Z=!1*Q#bt~3Ze4Q zpQ5LaJ@xRlLR@#Bw|TOTUetE~}%5 zvp2r_zk2!$26DQyqyCzloG$IHw~X`2ef1UK+eL`v?s$DP?ZWCq^g%Lmb#S^K4olp} zff;&BhI=+j--G(M+XQRd^b_^T)B-nIf1O&GFkA0WPj}4Id(-&6SD=rjb^ET=uTT>- z)lRFibG!6!Xt!M6r$0>Fw(fwnnTdz=@NF1Oy;hOF3$>efQlCltqT*%!7}~b253Fjb z5A_eITHIs(915X$t{+0_Oe@g?N+*;xSe*J&WQe2{Vx0~56$H4S&Tx~ux}DMR1GVd7 zHjJfL7q}bl(yKE)4KpcPRX+nmD>U&p+@lpjD;YdZ#O}bxhU>Jm+J9q!&tXV!erqVE zbuYCyT&Jf+9Sx^w-9^0(y=b?H2N^8>9TRDQ?}#D`yAli`)K-fm!v<>L{Sd>iv}uor z8OBjZjvQ@mWzrPGUsNr9njw(7cgtLZrMH9U8xGPge!tvsgW7$%(y*D!8%9xP-##+HH$Sl(V%}Ii9r)Jp4>eZjZ-XT| z-~D6QK|OtlFt-+GC0dvBHNurFHa59}5x(w^PkUB0!f)Q-Q$El*hsI0a+Qw|E_GevV7uw?9EsSZj znKxP+;nxVT+KG-v_@Wv>Nc>1n0KM$1@OQD9s{jrCh^w8ZR?jm8H~V1gT* z`J=ZRAJJ|ZaM%dH&4|%%95W85BQN5z@f&J)&uycQu1Ib?Fg~Lketl_dP9dtjH#U$$ zkSs=}<3~wMPpRSvwF%yLV#|&6rdPCfb8pjC+Wer(rU;WUpj*m_)cBzzhWoY}nwlDu z6pRCDBrk<^cdd=-=v`(LkF zJ~H-V&3!?OXe0a!6X3$-BRW35naLnxtM>(d5@RRO{Ld zP9_g@%{5*-3LWoE(^dr&TAOAwoq@WIX+N!R00(Dkdw`jTYkGigUz>uNL0A+1LDwZ; zn>J9ze0JF9knXjGNLiNpjlVVBM)f1Q8zSU&M5OJIw%=5(55KmZX%EXT7FwB)`Su0j zolMP{O~lH4{y->;XkCSBVNmB3aSfa|KmisgWc4_!^K7||bn84xxa=#UGC?K1>}`aMkFLqCRII-=(<^)NjWIm`MnUnMy8 zAevC*s4*PdpUSNW(A4uzO>dglB z184i29KYFg*YX zzC@5$=6gq&LK(JcKfu(`bp;cq4upOHnhzeKydlcu!mxd4Nq8(HVSCb|&Cw>9j?#oh z!$=X+8id7~T3X_ktt$c-&bU+qw_;5T*x42ZSw#y96Z`r4O=C<`*!7nB2zw0$nEC~U zqZS2IrWIgEsrr)oq7jiXVB1l%0US;=^<_?=y#X&!IAV%BkZ+$@1&mKJwN^ZV{z<5U zM)4gG`lG1=c#&jEW*_zgw{x{dAj#D>Qv7XSWzdd^mMUQiW&ckN$iUz^+8E{`2;F4% z0=M-}g%%P^uOi=zXQ)e(E#iXUDIfKmPG=dH44>o?M;}m@a7MWC2uX5~UfK90; z6Wg;txWkxRFx`MA%~S(;PSI6U3=@D1i!^uA4MrELK}WQglaZY))QVC}En7iB6ebH5 zYJeoMd97lpK&!;VTmcl$*A8aa^#@r&x=_UiVd)f8ZLl>-AHuHb4~p(;8tP8Kzmk$I zOO1(*9y%la<{2(Y$5=x5*CAJ%^uvy!J?E)>#)71mMqfBz- zZ%wvtF8c%?m+0Kl@j^A7zv6|ERi-J1{hbifenRLkP&nEY_9^Tm4AVkT;6nI3pf0*g zdLn19uA;(yfGvRRdO}6COan;&VJ&ZvlH;ib=V$9?vGoRk+$s+%fr4=+XGH^nof1U5 z&VVxf*lGaKEY;Nn<8pPC1RPxnTIc}eBO!S;DF}x4-sy}We2y*zG+(7Pf##Ve__u=R z=+tZkq^L3nDWdF23?d{x_1zF~d!nf>IK=6E1ROL3s^2FZw52(yS821@83Vx0JYA4t zrakDivOoa>?IFO^5wnv&!P8suvhsCn*qsBwtu@-}3f>-Sds$FLAY`(sj{wR*EN=M( z%4mg(xTCHI!gY+Cp#k#uI&DAp5!8684OBc4VoxzevA+@QPY22?*c-L<{RH3?<1W;g zp!ZVT6`DfBviU+?MOHZwlsM}G6sm!?h%A9Xj2z@B~gtyYwXIl@%qfy)%k^n_lo_gkQ(K;)>6;gu1&3yeO zO5LE1rMhlfTTY|MEs<7B!F4lX)C^s(k6q6;9td&|X}c=Y1dwQ43bfpa*09oAS-{)? zY@P)j1qX*3Yz1aH65$^*0mZXSH58n{AR3^|>@T%pF?8#Aa~}b!J3*a++aU0&2f03V zAXt`ZUdrqPO><4v6bJ0l_IwHLIQCdg$Xr)Z0O?6g@3e>XvO-!zmijFi^x{kj?DK&n zW{ZU^P$>QWB^K{sn@h(n1$s1)#O))YIcwZ%2a&kd53-9}HON|GYV>KydJnP>*-|)0 zaPC~R6AMB8-oce}c=G{r zjV%cAghhtNY&IFfqd5v5mmSbnQw$fmf`agXg#Q}j89Q=FA zAbcDVt_2nz)&>h$`w^s_n6<#C70C4;1_79+4WKyNyqbM52s}HYt*Llu4|%T)$Pxmn zKB}!Mfb=J(Z`nguEDf2w+|+^$cz71Zx`ub&>R~1cvR*<>S$EX z5tbsbSziKM6pn|cpsf}#P_n+%pa>#ujY8HegF-Ma+k(yKwDs5%kOdl?@K}&%uB134 zU=u1c$9{>+m2lwK$lO)Hg<>87?!Wk==;5D%4QNzl^He(U@(HSc> zg3MTHLKY~LQoh7uJoHBC8H)lXMUc2n5}LElSoslTkjxX7BCxzKfh~t%rB_;|!05CE zk!{n~Ug#w>K=#`M?fw$bu?YLQ%LZgOcZCqY#v^lN?qUkjD5?*(UKYt&GJkajC-<6~ zvwuJ`Xq>=f(M`CR{!>T_<;YiGBE>|K4!?Cv8z=}oN}w323WrN5A@+$UA7vepz}d^3*QWUIB2S;Xd$qIC$uKO@9^gq8|^9Y z!h6~p0^YR}{GUjUe8G6#UA54C=ZC4#GP-=rVhUO~S$ z%;raeW{sy6nroE(y?7&1po9fz!IN>?6h`tX zJd0qPMFFOPv4Nt6J${q2@Y_>-$yrlP0e)iw)8G^QCRTiF9)$z`_F2ORww$Q`lQyhHrx*&?A)J66{^U4BR4S`Ch zQyWn38?Dc$K)68%NrMXQarT#mbLtBX+V;2BorMjvW$e4KLr})PZ*Tv0S@xet*=K88 zJD7J`Z)(30>l968O7(`6)UG?8Br}3EXNWG6VI6?o#0OL2I<+Am~q& zg9O%_lBkV`JpngD(Qq%7fV__CLfQ0aGCRRz(otOn#TWq?PVgCJG-fhXL@SZZV>&NE z`k|OdxPyQS&tK7M*yL!EgH{W0?Q&3aqP4=N#U$t7GVNuLM1u$s zTtXcc=wi-AWpF-6IeVWfb-&+&035J!7C5mbDclRA2&JBbr*z}lXVIYPPr5+G3wz+F zWdQ$$fop-@r**ypf3zaDAKHKgg{>(t2>s1+e+-?K<*e(F?ONt z4g5;VT+3FC!5QFFD0ieKoR!-U3MO=&E_0F*otAWk(-z?MY`k38l( zqQ8(5TIKZl5~Wy3X*`_Enm#fG2zXKa9`?MxCcL`Zc(I*hP#gt=#*a-E6yFQL?SknW zqWWEFRm<(W94vieYKHFN-O*WRb|v)m|MWVrRt3k#YJpiCXUo6TrmgTXOenl%@ci8* zT)DL+1eV}73F7Qqa(!V8i8Hu5Sk0b|$&Yzh6&#f4oE7Ko!B2k){1@08Xmo~Xb;7&* zb_4{jT3|;Dz}s8Ft@9i5C|n8E0L{%RJ!rpJt7hNRu!BdOtl3z*u>1HWO3GOK`%jAc zH)bQ~_6~&2TXdc73_&uM+_lW0Yk{6(gw1lV4-SpcY1x4Opd>}(30{nVFQxgz?bTg= z25{)Mrvwxj;ggM40-Es2Qfmeq0>A0jM76Mj6r5B}^DXk;v!WtxE}ZaPmvPjn`2kBkLw z?r@X;6R@G~x=L^h_4XT6pd!~EY-U+t3$gE;fju5N4}qgCU?B9ZDL^T}>IX`;8#)ST zbs@CEV$n+3z;1#o$1yrRc>dO;)vblg$A|<)_zA34K+j;Q5YB|oy<_%g=W2nf(zjk9$K5puxJ=g7R74E64RO0n+J`_41h*M; zOSa!&l7I1I){L^X`Vy@XRxO-k`iso96tm0L>PNJ)ty(zO<7cg_1zNUety>3^XRSX7 zORdjZHxI^x^3#3e{a~4sIa3h06nHgsVCmiK{)EvAD zJmM#{8Mr16=@3+>{_l!KnH3UbUKf>WR1par3zIpL(R z4s2%`&sdo_a9d@rqDZi(0bi{6ERD1{aA%^a4t~Tcpb4vgg*lMBn|;cFX-{D~+QWQX223vkBM5g3OdPqT7y1V_rxiOi9xUr) z_E!wEhZs@@#F%)H)z{qfvk>@>QV4~r`4o2{7un&q0RDr(!qg?tIFX#z>Qc2BUAi0x|jm_w|X zwk$wAN1tQGz(%8&AqERspezveB^JYAqf758QJ_Ka@fUiIHAraA`W$N-B#$|0M{;TQ;62{(pr`~R{FqMl}H{qs}oBHE2~T_ zW2xf~?`q&3H+teMNFT!pm^2aZzzW)wN(v+(x0xCKVI}m$xqc#f;@q$_W-PoHLbp7h zuC7`WNc6;606Cmku1O#T1!)vAk?hXnEouDhww2VAimftTEzh`bT`3l@iagToD_jKa-!-NofD3OHdp8`A-q5@MR ziN-6N27c74Pa=<6jY)PvsZA>5rr0;h_Lx;*KZDp;CD}h07)1&cNo7B0ZJI=$vo^OU z(YP!U?I3N-GgbkK(FCjhCnUyLN!XGqaT<-&VM!!ThYKm7@EKYbg>ldir4uRzNrW0G zP7{TutZ_OQGDis&2ul$VR~FE+B>OnE0oldrSklZmNDb{K!xjoMX}w$6>UhjW}Pp>>Z;E(0RaR@BguFL^YwC;2zv*Ma5)WoZGhFd~H{)+iw+;(e|4M z2p^~OW9ou}KIV#w`nGy_3y!G`E=1Br@uw4iOHk6^+zcG*Yc>l)mJ$k02B*jC8Y)7C zCQ(YOm8nZ%`zC``nYvU(e_<)~G1L1?fNe_giJl58q*r!Ts0WDBr2 z^*}KZ?!+zpzg*S01!O$u^u`SZdvdQx7d8vwB0d(qDO?$kL(qUwPmNCCN~- zdV=?sgX!vt*^6k_C*OL2j>LO$-G<@`3Vtc%P8`JlE+BTFe*(DB3W)dLyi>^jn{SFBj-i_wPneTGw~16G#eV;7 z5wU1S3gpqZfX8AhoOK$ekr52=_Z`CEyUghO4&8(VP@?Nx27v*vt)*YWqZsW|$QrS| z&=N|hc(-gs3Yp_a3QG~r@G@|+AWrGEs13(%Q+x?&WLx3^yio+BA5ZgbVFy?@iZ-R- zQ7GO7IoLLeeh@N3uHRAyqy135^hOZ{-avru-a1%HSgjSXT9rb^~3mSk!E&+)X<_7wonkQv)Szs z8{N;qBi^zXjuiX}3#?y3sFF%HgsRyC2Bww~ zm331|RN8F`ttZASrrJm41}my9ixOASs2q?=qH>Us0t%LXWl@MvwU0^)(hF*!sO%*) zWsS-#$Q(uGBw;B6$}9_LW~zNu+JNk$awBPGcSsFIC2XM}D(UO@dmsTAnsC2pX`VSi zaZtzuMdrS;c$`SZ@7@bKnZog(xO)@fv4is1mP&&1u>i|1C^r+0--rgY4NL&$W31C~ zvJoU5UOE!tD|mh@%iK!W!Wro^@7!-85MLoxxVmfPDi<_mD=B=RTK0xe$Z)bDRMVbJ z@R!ImhE1?+3JLBjwh_E4pC$8ym5eP~i4SSCMhz#?8Y83vg9yH}{RO`ag?=fWM=8*N z;Ur=Q2+dg|_Iua@6tUBUr3h^Dm%zB;_EBpCvzz_5ljg#oHCPGnL|{Wp1ufnmIs`eO zdNuQEQil z+7hFFvOBb!7!Uabb&nO*7NXEe_$|YjH1d`qJmP0U2|^Yq)eSC-MOvDDgi@TSPYCQK z1j3;PN_7z15;bU7h~d!vTqqd&hsmAELHBcB_$@DHCOS8OK^1gLF#6!cnj#N!$6W>f zF!0%8zL$yK=a0x{V{7KYAC*Aw*&?A9 z640Y+B-BO%dR`haBH;-A5sFPv3tq*_3H_j!MLEG2RKa_LW1w$ zO!$fP6THwpH&RZRh|Z9v?N>OE##C4veWHp}aV5cTZlD*iFq;JQ_7H9dLBMaZVF3JE z71|`i4NE|K8?aTK;U`8tj&`sRY698-vi;n~3E1VB49TqoFzgo=)BEr zsE$!FAU2CE#w6T;%^v`NQUrg40>9CWR1zX-}{p6tecJp?Hz&QA@-JGFNk0=dqaaM-);w`KJF67Vg2Zi22H5381>!8Ihb0^k&1jyZGuCEj-pcn2sfaIRq zua!b1P_)cw0P2gHLGT+m!}glvyqY3w_!lcgWayNtj&eu-|1`@LoduxKeXT*rY_r1C zs_Xn2T@1BlkGY5$U=JnxOm)2FrPycgY7#iFlxuFTm{bR>+Xvs?$tcaHlVODIf=vaq z*l!*Rl9#qnfPMSTRatHXxNyVc8!dD*ZL*f|m;zcHFt;tk$go2Ajk~=E%*_p-moub5P!(r-uVcsbaVtLS?VifM8cAOw6nI%v*xw=o6Rsmp*U(2Q`WT8n zmZOiQ=;IRlxBx$F=>#cE!N5>oa zt8dSLG}o(Ix>w++$CPmtW6C%*5aonbpvzJ74?&nC&{Wd40wKR@F}#m@NEKce!f)0 z&PxXu65T>UlZ$2t{!WvXb^l+?-Y!!h6pTLnb7^`Ia@MSO&m+HY7D%&XPEri6b5|6ZV z)eXx37wW3?r3wo|)kfT{ixw0mI>cg5~QLc|1WFG14cn-mo ztHU44m|1MDqHG`}f=BBBbVV2mbu&nR)`DOELy0Y~#C#gecx{%maIVEUZA%neUOsHH z4FyL{NCwGiFPvQE;QlLfAF%h8d69S?WCwr5X&Gz+DMXY(pNqZI`{)so9|NXiyh#BWTn4F#e%j~K= zCA9UQ`SZ99zLY=1{gWj8uYa3mjJN~>gT8CrYbaj|DPSkQ5IXU_ARK)|dYFLk2XmKl z`V#*1Y2AX^+$S^3FJTX zqwgpZ{SaK}N8U%|=Ff=RK}>MrqI)f62O&CkVcSuH5#4hX9?>WxZ|&$C1i~-42Z6b{ zKAQhzFt-M)oZM?qqs)J7(RpCENhVVK3B zMCR5&xm0KtH*KM?Y3oSS;1F|HxH<4wYv@vp<|P2SDBXgUK!}N(vd_LLd6adouqmf) z7cJd|Cm)!J@#JI7uuVQ%n4RI|V-(I6&|UaGOOpXwymN;?)8Xp2q|_1?6y5M{1Xiov zeo$&h3j%IfglAMomEa1sl>Pr``|kLtimqYr4J9O#kU|o6_ufqbLI@!R5~L{!9U(vz z1gQxqWhn-*Q4>UZ=#ZgF6%=WSB9WdT#fo4~uK9ZL| z!rdvS&6$~V&a`UVE-0A#d`XC9Ad4mlct*T7D%=Z7N7Qs)yhzjd+)&GOb~mj8GiO}k zU|WI$CHCsQ)THS=B?VrAUN$W-gpaSC5X4IxSVH;MX@NTH>sgUson5=R+Dledl6YyD z<^HPhS3GIm;L~Wj!nXwaM=?sIh;Bry^``TRbG9+TP~z(|JLJB~gzO zKd9dNQ(}t4tVtzx8d@4F>}i@_eFNK&HM%l+6m;-e%M1uF0#(itMwqBdfgJjNnEM9Bz(`XcOQ;j!bxvBU1`;^lgl#BQqr5Xnpi$kX7TJ;OH-Cd%e&0+ z8I-?8GteCO0Tt)PzUn>dlQSTe60ET&XH%+!2 z@G|b}DV7baj{x8t2Ht(wn!z5VDLBR+s?%KUGm}?Lu=dKlkK{s4A;N;g)%863^W0$; zU%uj^bpabs5O6UOg?T~gfa4{pmWgZ{EsRr$*TOU96tX1^sw}5f1bbp8NPs5AIb^|1 zUKVP9ggx)ARC9F)DHdkQ3a7$1l)@pJwfM^7<> z%$Uh@rddOEhsdClM|Y9nY%no-aG!P-2m6F3OTWG1p#c8RQ@Wk6sAmu11$U=e)vspq zj34zl_6;qK3Vsb3ca6z6rGf__RmHwY4y*{YN$c6Jh8jCi{bVL?dDN9z9t?hDqD`zB z3MY;EigHfA#pKwwX4Ec_nGnL~+uV8Ix8Jt8?XW`r! zkV!XTPGC$ZmY)^+wG62{opQ7yFG^8PYQBuiaxVQQw*JjV~s~syfd(M z41&5h${wZO2cU9;yTe}PoGvh2Qq-`47iLOR3eGFGXnPNHvY1zt6rP`D>7*vk;!2GD zb+($)hU_gj*jr9=4E828vLCCp2hw@Y!N@4KkCc#n?WTN{NWK_VG2W|*JyqQ~OU@@d zDFD>y7W-10@(Z_g#`Bum1GrzT-3o6CT9j&l;S%S+o#^J^=oP$DzITR$%IYJ zF>o0LN|SObrD;k*X>N?O-^)zND9r+wG|}uBo@psz;j@Vvqew$$OKU2G<{-Zpe0#&Q zuAhvJ^@*PizIv}Q%~%30B=}U~c-CNu9QVs&HrT{|v9Be~pU9L4_p`)>gbV55AmS&d zh7f+SKWK^xC2EQ(1$jHs&ob7dpwN{10xfC^^7eCp5#AR3ue=$vFWjFccr&3y-b^XTTbBWrt{w#iZ`o$v20RG7y-JBg-VPeP9i%ze zCTQ_I{j*wjpSOXnoX=`Sv-30`*?N<(^)a&L(Y-Hjt79jP7APC-pk&O14;eG1AY;oP zf<`kXqe2$D7(=VE`7CKOS!YR`DMIuTOGW@45RCw4?xF#)s+Pwmb+gAZyI9|M4#gP1 z3|iXPU&-Su-)@-ke={s&)YC+lVSBt$UE9MU1D@Xuw_Na1JLi#rC;Y(0oDGc<{YsXM zvh-7was0D~E%&hTQ~(%67?bB7vz5pBh4GeFp`;s%DeWbgNBQlxH%IdU9a&J}2Fo41 zr)q>3rudA?Q+P#If1SaHyDc!but20xiy=EtMtz1s1G&N^>)eSLCV_`wHd}g@%ot}G zrl`mA_>a@U_0A4KsE=_|?-~`M3I}W8yQ4i(u`)1nX*ddA*dAjV$ z)5`|=MaWYkcTBRBvKzD>nh4d_jw$L7ZcIc_ykpKVKYnhqB++yRo&61%%kBw=7k^CcPn5f4 zLcV3PqK3}lU(A84g?=78q(tJxJ{>3~?KI=*W)X;dKz@rleN-DAJg_bl$oiK;z zkGChYNfa?k4E$A>#GdjZv9iUMnbnZkXeqJL6fa6_v8TjFN%FJj@NJXqyZFr&7T3~O z+iG|2Dau9{cp@GCj$b!F-fo3uJkK3vhxY_lSeC(A-IFUU$?O~@8AbIP5!FR6qWXTN zWyYP0NZcTZu3Nqe;Rvi zpxHj*Ba)g$y8+%gQ?!QoKcXs!${0kdbUQtL@T$}ijSEVnw)6kr{#kngH%^!MjCM_D5IlP_5QRBO#8Hb4AGsbkOK zNki>^+_KyrD|$o%fAkS+J^u6Gn$Dw=VP}^|#`HxN8@vM9aSu#d33Ew{q58zlC4H~; z+<)zR@ZjF2>%si?1i=2z-fHNOo564%^>DL#>Rj+fKMIUsjVXPoQ9VQo)u`yXvP0VE zN{!n0vV9~QLhGSM{q3oVgWUDRkfqw@@(jhEAq0$?q|9||(mzkj-hU=xm>xs z*z%J(IETxXpTA@|!*)<|MBq1b3rTV6$;Z{#lP?Zh-egAzY_U%fW5&(ZLvv-&_@%i# zXSX$sFFgdiCTAV8bYSmQs*w9fhXfD+2AQFJnTQ^HA=yz3LVD7=o{xFe(v`m$=pV*t zDH%TA0B~Aavm-Ek+)YG_e;4?0O zA5N1E;R#BvH4M%S4}JzxaIqmoeBok4$TPUu;O|~+fV+6It#H-eQOoyU+N}7P*?g>Y^7 zL0L*|_l#^UFT^_9J|kNz@e~-I*jludY^@l8V{WZ{fe>43p|iDmzGj)Cw-xEMwHi~( zFxHQL?h2YLW=I}&rdneK3JlkYmr~HUPP~(*2yf7TyGX$>cw1h6*76}cLW^K*>=5uQ zR)`PL9Q4TY@-pi2gak{Bdj1*SF9BTU3$%=I%hb0);;yxb%g;!+4@7mBL#{>e!*5s` zhi(=LD6QHuJ_bl}UDbpX17xNY43Ld{)6&OGU6xoWe)$<05!?O@M#PjYe8pRqhgrZp zK;_h2Tng|LDN+W{a9l>s{lzj>jhn}>){Bf`@w5WY0V)HWanwJqwh zfaTArzmkTY7R(FR@TF;kZlQuLP z`)4Wz-${aJ1pG{naT96xkGlhWDOBt}wdc$3^NZ|0N(F3Gwsc}QsH8zFu=n_fkyIjg>^wUJXzV=Ci7)It z&&{u*^L+ND<(8Mu6aFBle#?dTg!U(0YM@= zP;z=)0tg%pleeMCMK|z5isP;M!W_`lgHRTxGi3%J@|~r(&o9uFXm6bR&N5SfOMs`^ zeTd@284O}H-?D#bGR$BP-m$CcVlaUHX#y%1j?esHS;yD{pvl=ggypLHixi}?mYg|E zHF4I9qLr`@>LLaEAV>oGU>F;73^M1Ss*7oib^g~no@AW z8~C%OJu@YX2~SBB;8Hlo5%mRfZm|M|V)M`{N+HT%xkw>0NaHx`?OPycy#urY#&Y%$ zmJS2>CDxWEmc*>5Jnv?S?Vun;*HyL>3YWVn#M#f(ZtmHSDjgvhJMhl}0e0Y9;tML`u|^+<}rLycg4lQkxg z$s8KBP>ul_Jk&16051eMYzyTW-~(l04Dfe3AO#70@@tkDp1a86=etJEdtG?+ZObg( zCeYC#p$^55L&Ce0>`$>wnvC7Fwr9=zOhwLG2B>RO_#6eE@fe<3%ffPKHtOqek%IbK zd!d{+Z`Y3O$NxLYUYGyy0R)52y=ZUAo}l$a7xtO55aKTpgLDQT?sma`bZ_0rzUE{! z93NdMCz#<2Wgi-{Q1+p16adn+xe`s-hmI|jedq+OfR^Ktg>o_%OKu8)7k#LUC}kMK zXgMBQh?Zl-OQgD+cZkgVIiQ<*z#ww7n@G`(BB)$xrQpDRJ=pIAqEMI4_{>O^b+STx z+DhgIM6OX-okc`=qDAfQ7WI__uL(21me-^~$qIj~uBZ(b@v@*u*kDDlyGi5GO>I5G zsUkV^q=sgOHy60EnQ!w*hw=; ziUFyhq}oG+*y5t`70K3GJSpf8-@@y5U!MPHTqrO9BWNBQN^p|yJ7|$KfgLm(O<>4D z6Zk2b1I-b~w|3~+Sy_Y@u+pEG>DCk;^{5gZ?u9MK1B+zW@36=@{eRZL+QDc2B4he* z6J{N%KOj)hzJ4#kSpt1MOJUndl00$KXGzmL50=JPmR2C!LUG`HUP4o_A08Ab*!I90 z+SEzk*}rFR(}L*Bz78CNFB|YW$uTDMsM)jH@Ss7#(LB4Znx=lei08zDNBb=)2|Ewv zp*DB~9waOmf|YWfp;=S?L3*xkoUd8is#g|Cll%&W;5Ny97fX}eZ!y$!P8Yb6S%+_H z4$UWa0jUiZqwT;5bi*PC@MtodzzdUE1t!sVrc6px!jytTVE!d7fKRkoHJ*RN9_S&L z=)tw4V1uvwtB$_4%L9$|BbMYcMtd63vu{pCv zim5q^Vyyer*^BwLUn3gu?4RwSET7gwv4LD%Vq5G@Y!@%syC_eIQaaBqNK5diAkaR6 z8?>5RJE_@=DTT(q;}Tk0YMlp}sl4ODklH0b##&b?%6Xm_XH8%iXe}i3Z9?W{Nv276 zb~m#&(~E@8VCORi*VhT0lAFz}gA_)SxFKaE|Dc9UI^^rpgOF~{s()B7Q{hyKX8plNNA4xti@RnoH%RoI?cw|!|5d?wDH~&Insfw zoZ~2La6WCfhZc$yl$Q}41cc(&Gq#^X%s2suJA#(YXsrIv5@~+@NVAKV+eaxB->*xg z`9<(?Fux)jIK1JL$5tpn3`UwLzyY=XeXVNqe)m`t0%#swQQ;a(8x#OL&Mx5|OKEYA zpnBhHoo40{&C@+gqdD*s0Cw7iCmFF-=(C_gfI0%;fPE2c+zK#UBb1NmTbCY zZ=|qV6r@-*)ZO}Sl)Z}z#3a{PuIxg80?mT2{ChOpb+1Zvj=V)*iMsi_9$rDry8>dGI6tt z%A8P&wo{X3kb>G7E51-WW0zI3ol0PhwT0p}B6YgD8rPo}?X@ue@kr}=mM(~JPB(Zc ztOrejhKehMLt#ofFP~uTo!Nn88k`l>6g~T1wD)Gi2m(AQ9N`6}W9Tx4mv^df;~Vza zA7YQvI)Y-Juh(s^j$g)$KY^v9S)SR*(0HCR-rAV2Sk^C;E%7MPfp2}aUTt2!tY22J z*g93(%Ds0le!r>=3#;9_or2ZD;mT3fR%9yKLu$OYg{czS7_V7AYrhylFlW}R+T z02h>Jy%vxiF!ruzwwtlm>~oJy18tC2H;$(l+vENPcg1;-T7^e_7iU5b!n`&L z&zfk})z%<(xoQAbZkmt(a$|Ukon#GD7|)(&ZJ-di zU)X`$F0VS?)Mgpa(Dm+N^faFnxPzBYwq}NRbAjyc0@+=H^mfSe=oIVoUJiNgo@!ml zvIPKBe;!Lyoc&qNUM>%L4kft;RRyn9Yk=VwX2Xpke?JZfJZBN$c)&B<3p&S4*qfcM z*?6NTtv%TiT18B{VP327@+YkueU^f5;X!>`MlRD11peUMr3OWe#o4{$OZ;@6yId-D zai&P8Gv-4g!70L()2x$NF-^f3&CO#ECiol$^eftTZp4n$e6+(3FDG``x#ehw1t0|& z$`yoXoOm#bZ=PYj!%0_&dAM49=Dl4q( zS@24#IAW7x07-GSMfL9Oa%qe|FBmq(k1t(i-Ol0&8X3;I@K8*GvQn<_MXi+E6~ot9 z8}MEYng((BYRS?oRl;p>9Xx9JuLb{lkoU6vSIU6dXqt@yGsr3a2rio|P0NX7kI`%~ z`EZPyK^csiIq4h1twY$-N@dG`=`2{m4L=)cE+SgA5}w$B*TYY(v&OUCG#e2GIZ`@9 zWhWlohUukI9FZ&Krk~;s)&#lfhnAAFi7)U3HjNc$6WoS*LEytpKOe(aK^V{Z1ukmM~W=kTm2|)xbNp%nu0FPS0V*n8lcDJ(x}QR8LaYI1=-Fy30<1oE6EHKunJuo zCTNk1g-c~OQ~v_);J`ThjbcQf<`)p3xJcwH&=KL&TwN)Bn$Jxojh!-n;gktND*80t z1a)WC^1zleby>gwyHO2?$JpvdPxo;r(5J2DktXkbt}yLho+3?(kv= z9o}Kx$R-H@PKlvo^8`(C8bS&@V6_t*8wbfWs4955+CyhIKH`YgmlqYoAAJ{CL`w)7 zX%Trr>{txVDJ-Hc&s)2)^|Xqxh{CI=f_EpyzhGU&4$vyt8L)rvStU2aKF_mvTSv2V zl}Z&Q!4*rcLLis+g(K96s_@~}7aLch2^Q^7fx)B|tv<3!-h2TijGpp~_!2*z7T8AM zQ`~&9SY*&1Ge#sh8xKveKWK{E1oK&Km|(S6lN!PVQxtyfD2(Q~PF8=lw7`%8w7>-2 zXn{>y+^rhskGp{bl|O_g$y0oKv>=Ca^ed$w-4wVE?rRojB3qbaMVGqN3_Ywe$}fr` z5OX(03CfYFw{{V0ct(|LqDj|%wKVB^dO(mSozhhZyiMWYdVc>`OyJRQN*o9ojhr`Y zrl;2D{l=w*7d{f$pd|T_)uO1ARuiKUe&B(TqDT7sar>**Ys#9!!`3FOkctDXpjB?w zgH27>4ujE1G>=Cfu{!SDXhfAmO6@+&K>hJzNBD4e7_=E*ay6=Py)rC99R*ux;cAZO ze*@20hw=l*teeBQb9Wk9?m^#*imD|r?jKOy|k8N z^lEwPCZ1*EI(e9_LGs3+9cW7&*VX){mYg1_$ z&{EPcsJ#Xag9set&@gBv$V9`S{Tdizc3h9(zfDOC=BrOzlXOjF(qW-4VM<14pX#FX#FT< z4KYaa)<}Z{WMCL1FxCsZU!4e26$Z&TS|1IP(QBkZG63odgXI1-(jYNW47v@Mr2onM z!$^HXDB2^hiafMO4vR0eM-Hz+dxW{S1pNvVlxrJ3opGGtU>ZiNR zC5M1F0$-^tnu2m$EBadL!&ue|ALbF(woWvMWp|B*G2=Y9mC*{n+C z(Fn@)sPOK|IDh`=hf%%QIPVo6St}ioCuuf1Admx|P8yp>bC3aaav&R>4;N`ef}UiX zE0sm6HW*0u(riQmIk2ZIoEQ1|HDO0+wi^?aF=1NKIPG!vexS>__#SqX=D2Y{wh6~uSF975Zz0hFchl7>lt{v9HX?x>MADe%V8#4j#&uQ-T{zHP zt3svF@C;aM#Qta@IVfL(&Li$zgCfRIe7`^^emX7B08lDndHyXlpAN{M(5`@i=+R$U zN3nsFUNk@ZwW(j5Zz&0`%m02#xA7I z+N4Mu+N6S|z6fk3?-wZFg^1aoes0TnM&Q~0i10}^j zSVt-9hmd&K+L&FUjH93ZK5esWg?Oenz}#jR$25=OTUA>!|L4W)b@>I}%&%T&`G7l4OU+-WS@C1Mx3@GRb(-@)1h3h;pNS?KrT?Nq!==bO=Ku{`@f)>eG) z=(HprmC)6XyVL%;WwpU!1`JE(K-20f7qoOHO;5FC)n^GdbaZj=rq8x{~w8gjHwlfet=f(ql?p_BWl5s&%tSu=Z?{7?7M<%My>*PcQGBj*?F;OYw zgWy=wIyB~0K!sc2C@Q(9*pvdhw#G423T|0zxK0}Wb=OJ5zt%dr^>-$v3wfU=QcS$# zi3+|>`XuXV1suKCQbu+Fd^l3UC?nD-St@(R8e5)o3- zEBQ7|z!?5=JHjpwCv()z%O1KTY28|4_s zgj*!VV4;RkM)5C#ZJY(J2e3|+b{ma;>!l@MXT97>>xB+S?e%gC)K8$=5RX^EjPq|` zYw44?-ss*#8rXX4wFLs&waW=h(#wW{dAYv_9hv$~QI1wjH5CzesrRBOsFOWJ3hLy| zb)-LL(}JQuDnog2Lz@;blw{EE_!RJf-Elf8AiLue>q&QfX1(l=z_Vv}oU&ea$Dtr5 zagjPjCA*_31-qju1-s)z@P?sS80fKHcE_&kWp_MI=|a|zh!hj+7qS{ZrhW`9D7N%o zrWMct{)jU2wPb`*M&xng_aq+?=LrBeCgX_HTLzg&Ok^5+DT6mad8dvct$`xNL~HJl z7LWVHZBTgW?j}uHJgtGm#%>@|Pu+l0Hxrv1V{2k}D~<6YVGMx;YB{V$2S$_RCe_Fd zQpkZDTtdbJT2$lQ1S=d5XpJP0#Y8F(XoY#LQ*x!T?Xsfg0uyk$%6l0e)zsEAoc0bU zO4-pe!xjjPIA$#rUpQvL$-t(zSaP-s2Pvm$#a@?i>P0z0Lij*LQ^MA|Ko+_{g1rhL z$tdW$(EPDxwqh^AlnL>+o$P?9?`&iYrj*bWF|>#sQR;yWGMKW5%ek+#-hJn+R9iU#3+shEhcpT-o_M(U#B3X%+X_`QrvTc76xo z#q~7qD2VSyA|rQ&S{t!~@*Pi3fjK$KdnrwpQUNUb<5iG{{`hCmk#H{#EhG)IT_Atq zk3$i|9Lp5=#80O`{uvN1{PDL$5jq0DKp94>Y*wmm0=u6QjQ)6dn(ZMNVsq1M@oYHF z#lAdvBk9XyH)3B7L@Lnp7No$g`mlyPYNxF}kNPJnlsA1nDwrpg+<%9b9Y@s|_pLQh zy?>+h!lw(eD06*Hbh^Coxf`VyK96Q&cgM%W=D^K+aQkjGLc%W6n27>(z-bDQE4pU3v6z9Rijt#i?aPYUl_eRCt9Rx7$K zdy`Uy&i4(GLL2qmM(KQ?-dK`TJ336^Cvt4{n7RpyImaq=8t(ieA2(UIUAUy1UA9rW z*^%EQ`SC@*(P=`s3B2#Y>lR+_8=bKF#BY_-Pj<7}YBdA$cuKJ?jWwr)qTHKqB7G-q z6UyD6$ejoDusw5U-nN^QMw|GfJ#CFxBZ?jc++Czl0Y`0;0@gQ`WZY*9QP>b#r+A!g zq58-sKBrk|3L9g}Srj@-9YvX$yoskM4O-TB5N^askhL+SYv^{*h8+S`zY2~vqeBua z6&>Uv(bX>K(1Y@$L;w6nw?n@JI)r%6$xFv`Y~LtX%Iy7YZ@)XXBX<*w(Wv1Ovyw?&VE#2Ks1|oPm<-b{filrN!Kn&(E7= zc(~THq)#9e$iV~5Av6aoiio=MGY@*m)?0Pr2%4VwAZuQ!C;^ok)iM8t@Ryu2dG03^kBUqS=T9auCT(n&Uvv|`3^km?J`PPyHp`)@sVPScO^r5_aW-YMF*JdM4L1*s z6dan|bQnjnY*1AUO(t|WG*v1Z0r=O!?MqwZBK+)W#@+zR2cSb+{?}(ENAD&^Pxl$H z8DgM$_1gsuBxHjlW~&#)UzljiX2VIkbWM_LsebCf&3saFbUQ|?p)5n)gc*m!9xw;4o5+Nf722Bi9Y0-_9_t~O?$ z(tNa1FH!j4fCj+5Kmim!Jeh9kk|q$~;r;^@0v_%M{?PNM{GsO`KvU#P4<%m|)PGT7 z^|lZdh0%kmd5}D}N9*Ft+$G~XM0ZpIB1lz38Qz&;>%t;Qy6joK$N0kydlP2b7JF2> zcKg0YJh@}^JuIb)N^@>Buri9tvoD5vA#$5ITv!MiB_4xYy;(j6x8*r_la=M!{$fKZ zE)32L;yL*?jSZq1*k*|hJJ;jKJ4Gj|xm);8ouXT^DYT4eH?fCskZ(ahd0`c?Maztn8# zrKS*|GC=SJTj(yt1UrRzs7G`Yg`J_$P<~}7zko85Vf3pL3v7GT&$q~a^##dy^(*C5 zBERpqRMo96ZIL%-T%s_rjq)P{JFBqMD!X@d9P`;q1t6N|HUS^76`RMOG!LJ-#MVs( z=-8)B(6LXI8O=m_lYNS&7|nF7!1gsup(J=TlT8YnR+W$4H(zG^iFKqkk+ z5{8eXt5>(m(B_ww;9enA|L6^{xF`_-=Wc{y#zZyVlUQq;aZh5MZA5)tH_E6yW0$jq zgJ6-Nl1$Pe#RtH0<@hjo=b4g+N(@bc69a7$sl+tJm>3Ff*FU1LR7#157Dr0`p><0p zkBt6a4d_H_8FRv{9kzDtK9cS>5a5l4;OA@)FF5O+r~US}RHDjH97RLUHQnRvx~zwBVY z2K^0lii(9-jEnBB!1Gos$ViHBGOd8=NyORnz~&J9-DYl7=#>pfZlSIN&4c0b!DSH0+fAdld@DN4yBIP5HiAy&SW*Cgk7DbGs)!ypk?zo>a8 znhS5!^b4ovKA~8weuaf?hZKw?hl?+aB!}~hM@(T~@PXyx*ZKXnZ!*1j#06#5@?&AS zHJ%6c3a%qUd?EbNBHM2)S&-v2(b0cSASnhLHI6rm=k|lMD@6^P1oQIZM;>I|2~u>a zeL8Pfc*@Ay_p$*r3p%24Cwb@X(!cAt9T&{PypZjXb)NJ5a#-g2IA)t?|8s}UfUw46g-BZ0?s~Qg@a)c=C+iTnDi;2&2yeumzI zD;>0u7zLx1k9qky+t?r|VZ=wa34}lMv9H@Y=r=_wRrJeL?07D0AEgh6{uf0GY9WXp zhkm>d`t=>szIl^Yz?tr>5J(Chdr>~%+upLJsoQq&ZN1<`-tB3Y#_FjZ(uzJsYog(_ zLcE~$;|^)y+@RSA_*lDSq)Cuxd;o(W(i0&ai4io&z?VO6{_00(nL| zP134ru%QQR7-btD@vg0%AQR1T6HH;ruoILroT-jV%EU|ss|?VXoy0}6AO)P6SKKq% z-``XR_cK12?%#mO-z8-nFy(RoqRIZT;SUMQajY0DzHqD<{G8`r^7>B*1&H#AbF|>Y z-?R0Iz-{IR!%o;y@Je%W$CPw6>WPw-eL}h_J|bn#eD!+bC;>Yg{!De8gB6!qYaAkF z(Nsqg{))pq2aF$gIa)xS=%ktPYKtd$Sx#izwp*$@6tv^wL4Z7j?jrf|k&b%P0bQW@ z({(2N!N-j^%!My}ry}MV_`)|3W{X?2@uu{H;tpfHQrbt{=7|@}b`Y1<;XRWv;({!^ zAZ@a^VFmBFX)W$^z}qCo4-_ZG@g%>mID&|$Fdq@ertrL5ZLu*I4`5spU%2ZRT*bQ_ zxDo6pv2z1=jO+q$$AN2*Cq(cO!^RMp8RRBU!OJZRPiOcW5MJ*mHH#AgRg}174xEl3&)p-@(yn`N#Hr3 z*mnE80G*{`ZAN0iixeGKUf$Y>kH2hd;a}`dH;5Aag;KyQ`;pvDcpS-)hsyNiy$03pX0&9LdL-Jyak`z zIx9E$h0kq02pD5m#5Dm%=jFCp&8q@4`Ojc0-+sl`Ibx-oX7PpN9}p&c&(7zJ-Xl^( z?}__I6#5hXxO$IBarGX|aschTv~jaM9{|oX{z>i4N6Zh7WwAS65Tb_U2=F3b};My}yaSEMR zOC%-P-`Rdq)EPV7d%ndFeC##q2iyC#wgI#Jq2t#ZhZ+vw4$3_`Q(FY%?fKRF(}LA~ zJH_%R+@k)I?a4b@^3-_LFSab7jXM?I`}tOO1|M$q6Gm=GsYs!%1-l`I;4fSX30Bwc zlpBi&$7+Rq@y|9t6|`3FK|Oqj=U630%0)94JmeTHGY>|dh)|8PT@rfp zk7`Ls>BCR`X^UfhC_bS^p;J8N)61Z|$1bTtN#nG9HlNlLgGK06PxYJYu7{h`SM8Lq z#z8m2gP%_cxyuVQ9+OQVF3C3L0z{}Mze6jEBOmyTUWA|4g1=Tz z+W;@F5BJj=vyqen96^Q?VNH<2@;L$hKRIbc1YhE>wZ5}~M97R6B{!?bA7$D-Y%s-( z#t5Qr`; zNZY6!=EXtq(Be_b0*bDLi0%v#UDP|RZMv5qU$fr1{DjWI6URSAXl>Zb6gvv= zlBWQR2y^>TfGzmdP^~NMHgt0h8D6=5uNHd&hSI=2dMpcsFY_qs_W~J38@_;D3bn+^ zY6LGm2MZ>RBQ#s}_*Lt?z;8roce6T_2<&6=B8B!bpBLn$aMue$TO_k;dv~IfQQQLr zqX_N+y0Xi?2k0`4EMgCkm*LFu2^ipiT66eVoA!{|X2Lx{zM8g-&7m~nPS`~>MMOGq zC+wUTyx}9Mr)uyE7GZ+Ocx1Gs{l8%e(_FPDF3^Y zmdtL^JP4k|@)eRvnwOZx?FK?}N;T=k^*W>=Zv{w9sW?ByGP8q``gU%$S#t{#0 zu8j}#g26F>PfpZy`|I5 zEI_TJXUz%jBGSN1KHo7ojKVWmmIU<)pD!w4%xr=9!kF2D-54_qj}k^*Gl-x#u(8m! z@3>nIag&o^ETe5GZ&>S=to3JG-9+rf77s~0Jlv997 zPI6H!ELGd)RmFEzo9jXR=7U-y-f<~S<^`_frqt<6PWj*6 zMoUufdXbN9qh;$i1tC=MmkDJ&XO4EA)q4?&I0qfn=TAH<)o~Xg`bTW7V2Flm8hdMu=XM2RCw9~x zWseXnXbgmT!RvUKXQ#tBb}yfut|hUlw2sifD(a+UXv=He3xzpO*A%c^jp@jPJ8468 zQAAGEtHqc2>71zVeNlGkheZa}s|=Cgl%~f_y^iL2%+%WS>2KkRM){#3o%cZ3KA$+YfUtXd0GTW*f~?OxPARan11lBvb}SoXk$cOA4a{&%L9uKVus zXyIFgN;1jEh;mMK#zFCCm$;2RE0OLZ?m;n}!ZWxwD9a3MD{A1V*iL-msMwBI^w(m^ zB#$kHll;#w%1QoeKaekNKsm{mWN8D~18yRWNxm;hF$gGlwnkbS{DucKyL#UqVbk}A z!Dq_@TCC4lr+hzu04&~dkSUI(f-G})lmk+Vk(`0+fqVN7h;G*J&_ zHeGz7%%-Ev$e<6xk%Ru?0oo3)x?a5ymvf*F;7J3uApXOH+Ag++GK31hf}|L{6x1l* z6N5BIxECyr?NasC#jd6)en?C9dD+=Ce>|l1*0&4tXp<}@^h#6U7)?Q~FYv5%*j!WR6XYOOEWBX57F6N(e$!#rr1mKAo*1@TK4#4kN{f*Jxt zyx0K6!!^$S67`+k9Blxfy(GnD1N^l|+5o?i@&-{gVFPR(t2L0*e?y91>}3h}g3=MO zSH=P=fE*G-kENA`N>)`FBLV-6)WZ4JuIWJ>zJ{{)w6b8Fm!@=2;By{@FeTnN(n@~g zjU!bM}3h1Jsv^B;G0>n?Jtx;i&B@rTnD()|&73A#%?x?^- z%7%xn@g(F)TVon6g_|`Vm)xz`SKCi6T+Q7p_dO$7XmC{UpT<hw11nEr?r~ zPwnN`?2(#3&A2u}>)~^Gufj8Xw2Nk+(JU1D$DTs}){D@4P12%5Ulesw2aH8_fll1m zaEb!OH^fXS`0Q2rB#26ylC#A7&L;)-PU?Q>Ot4i`*&}|o;idglzW^#8V`>32s#W2i zwtD=nnVKK>xle1#FU*3kzEd zJqD&%x*(2r4($%7>l;b8Ly5FvA>MKvE2%YQh}DCW)J_MXFD` zB))mN7AtPg6%zk!Iv8WyAWIly>je!|^3M>Wh%rW!4O$)R_qmO+@M2L9rTCKgLMgr^ zrReVtzc@;wXKMb6*Zxog_7JchErKtt`R^aXDeZd)f{Xt)WeB^%>mP4r@Zotmeu zVyy%K=Lm-8S9_Y`G{2NqTv?#?&P*bi22}+G)pu=fEPzFregw8$gz zttlH$s|ckF^IC-$EdopPFjVgZ0;|<+Vi4!CN>Ns zWu2MD>7)eNe~H6g~4m? zZ_yOom5VP8{j=Y==KeO#N2B8}AwOe}LA?WLo7zJYu34w0s#6Zg4d7EK z6jZe@wrE{_HUXA7OA|tQ={KW-*=AY@qnH~gnir(P`4ffXJ-0!CZwjy21wpFZB|ddo zWklrx!JX971LVE#QpL`0wija&!E*m4JRpftGtA zK4_540!y zBorBYvFUOnfUTbwvLP?#2;6}109(7@F z-tGE+4cq{XL+sJTaA1|6jluS4i|TgL%H~VNGFEJnB_q zq`stK5-^gouSa+O(-Cm>7V?HiVJ&L0M`cR8QE$G1bgn_W|1qr#+;!0JnAVeR`%)R{BcpMM(Bq zyd>MZWb_#=Tw(qGw`#`y3cZbLJoy}K3>eKHJg3F8u^yE(L)8lUB*=t=OkU7 zywlY{N~|NHtA%&E3^wE4bosL=cKC`!%i#EDX>vX;@^cc|4e<^tT1k}VjMnLl~ zK?Ky4j1ka8fxMHHWg>t2W9>jS%=A}20ZWj*NIAp?*(Dn!U>C_T?zX7^VCxM&r(RZg zP*GYmJ537UHNHxzr*O_o;dmHa?+k3+OF1UW8qZ_yl9Hhq<<$)|#khZD_!rto>;^^c z;rbXiH_)o`2++x^phJIq)+82#aSsEn2{#%2(- zPKQxSfEDxY7l%gr5hv21lFEbQRVh21dN}7t7suxH$ab7OjeG{Ul?0Jt`a?&IHI#pKPagc9a9Fl^^^M zI147cxTV@XT^c1{ftGO@JV3QKgU8@$t5FoErA=J>4Gf<3-W#-~TY#cL;Y_1ngRL@+ zHU&Jxa(0}R=QfLNrUt#jNBjZc?Wyr5OSudF@rr*sS^4?Ic78lS)d$o%0C@Nt57duk#gqmV z4#e4o9=U~cR0_vqZdi6REk+2&k0*7%>CaF4=y!gsgGy(&Q#$Zrl1`ssPvPt$GT4E_ zN#wI@>x0=)Nd zT-TcDtIsnHrgBeF+j{x}7I%nngi-lqngWE%vk`HJ?JA0q$gu@Pg9O<&eV5JJq-G#JBX`Y#^;8Nap!^-R9~8hj{TP5Db6BGaFBPK^FaA-kGgL7;{CgD?~;*=vyq47;%qjb8>~meeMLKi z^(gf;q>5lW$j{uVqbVl$9&MUzG`FJ*->T{T!aoo-aJlJ2@rBDxA0EQxCbBdHdMS5n zjSAK0W_r=mf@+_vX~Pq{-wfcrvg)_wXB+7A*-gp|>hy0k#ii3X4W0ghX>&TrH*~$(y_}{JxUqO|FY_l>W~ttW59}8$G#(S zmU{qjWE|;1Vy1Ro6r@wm2zL>(7)s$8?FRDW+cdpz_%u-iwR5`oLhYOmdD+$`VeZvy z)JI&oxX#mcy+=4*b8>=&6)$|~a)ArvLKnz|5+qT0*IMX0yZ)$`wa`A1`Zl&r0C4I8 zYUpm7f-T+ebWj4k{Dco(K1*^9vI>?~*S<;Rxi9N=_>yS-33h@YkSn5IP&$r7%Zm3I zw#Dep*xR&<(C6?fs^A8+@s0F6_9d-?*CN5afKBw?>SX{dRzu$nv3FsA(o!gj^7_3J z%mr}`G~`txMJ$MGpnQ; zfMz2O$N?P2iR{;W--&tvJcS8OWh}Fv5VTN^R#W22{tON0c}e4UC`F&Gun#CkX#Pz7eHX39BCDyUdy(}!S`+u?eIrtEsDfSy zw>XdG?Njy1%;zv^Jq*FzepRlN-XFkQmbX?^rxEr*H!+Vn6sA|s7h z!tdLrbyvd<%h!|u9WK03bQphOrWA}!`L)qon3FLw^|w%+PU;`8%8Q77+Ukqga7q{Q zH5d+fpR(K7V44%0)F6iEhx;~BryQ1xkB`x8WGI(1G}{|P8K>>`PNyqju0C?_s~NG-YARqvyy?T(P!GT;Z^ma%m}SARYuUvJKnd+00R{)e(2 zdORCRB_KRtb@&m|D<{BpjN>gWJ=*y~8+bT0C`%9Fk@x9$e!f4I1G!D*r4Siex`hp< z#9%yXwn(8P?!Y5>#2@ZRD((fUvXa)ok#_5t$m)!=f+D=yW0^#x_6J$+56Muoj>z!B z7V%1In^GNa7Z?Qsh+6>Bg5^Kh{P@v6`e60dBfMwL<#uj+Il@>KmWXrosHUvh{=XzN`;HAcGNJ zP&zV?(qKe3ts^Lw!HA*opsVoNCV6I~&jz^|jF{<>OM(%>LM>@9;yf=NqBl?lU=fR0 z;ZfC%*By)4>`}(;4R-q%@ED4C$)l6_T3n>M`d=A$e zDsS^ohU?MlJCHA85+FwNs1i?6qGfuum%f;NK$As3(3^SIyhw{guh&cBvyH^+jI0)P@@9 zQls>DS%YIhj?d3V<&=Kci>}$M-jKG%fLrf`VK%a?%|zAsnLGNP^0S_8qF)NU60_2 zpXqg!JU-T;$Ef*GK&Uh@Wmf3`N)=u+fgz9uG+Ah;#yo32<1Ru%AQYa_cpyosp_@ew z)X**B3pI2L2#VD6JJy~RL$C+X9?#6Vu3q_1aZ z1pt$to~J3;=((f%B*0=X#z0PyT!XBFRn_k^+236E=jvpLfqX>}$QXzhl#VZ8jDh?(MW4ay9w%%glejnBhhHnuJMr>Y6+iVhpb*iJD^2tU{NBg( zPAt-UC7YK@{q{qp^!-rjZqG`EgW25Mr|Uhd5qdy1X){X?P{$pYXZltO5-2C5O*G-|Zm~qV z0Z0~0q?>3qG`z7y3a=thgGdHm9J=%sy*gI1i$-Q51w9*@0(7IPw7>ejr)ZPz&p%%V zf1JytCAMyQsG^pElqN^?;LCq(Xcs@w*@4$uE-2S|#vHK4zo+8BMZRxH3*I`89u6Zd zc#QWw3ikbqAh`OiC|_s7%L(CIj#f)#Ci?9@*Nz*@pzz_=N?Zo5eZr%;ugHeOi$^~_ zE|x(Pxv)?8gqkLSla=xxBN=JTRf!>^D2pXMz3H_UU zP7t@T*9k8|JyGTq>Wz(hAisU{dR;!dpYB(~l5Km!kSu(-X+#%jn5Sf08(g+JA*9-Z z`arp~wwNeG4~v$f-EgA2HoAx(AD1_Bf)e5iDhOd3EYLsJt+@i;QUMsRUiyaP@NsFb zEj_EZlsfn6Qhjiym!bumYpxr;&0eJpqV-lvQ*gp4?*+5s2{|hsB)K36?AJ9&P%z&z zNbku$Bv_;g=LN6h188ISqU?2A2k91zvdUMyVil~q{>L*HEx4~vNH@smBvBHmOWdFk zF(gno2xb;slZCqI2Ss?)HT)pRcKbn1Jj%F@!*2fuA045#9(CRD(QfoE7-=`|KOyZ# zoF}^l@L}IxxAD!vU^hO%H*h@`;wNQXZ=i!9%{pC7rRDa7hIo*YsTX`-5_&?E07K27xuu<%F94#QIY)eEr=5vC2R)&p6S8aNZ`4l>QL4P@OQr3qXIUl?!I73udZ>>CGRi*yYt9Dt;dPp-ch5 z$unx}0Gi^`*343=tvyMuK~_!pLsxg}bC`p`madQ&Y>sizs=^gg_JAw&6s>};P!(0& zuFx`C1yvhep~bvtFD%2(2k2%mXqWf$+s)mV)=cfuH-OkT+03w|q zT9g-$j*5XT%kHIDQBL|kKZq~!)9L$6H?)78$e^Z5H<93Ma<}hOPLtif&!45z_xYP< z<08=SrNqjsQzn<}kPLKw0RM>TdXH*&KS2lehH81KbbK0?d9d-5i6EEb6I~`9pGKm* zlS^o3!|{pa*N*9J3J2Ho4(6~CbddZCJfhobO#(UavO#)NmP;jqzRv_947z$gy^I&1i)!U3L@OJS_c^NH z;d23E5sC}CInW(07E*l1mKpXqe7IW&J)HuPLe=yUL0l(wWSQH^VOwZ5T;i#wr(+^d zffwQpl*;3wos=@U%9FQakRN~Nr2eLQwoI<*yiUnLNuKtUtCB6I|K>wL`b2E1z=)Hil+M_QfLu z;a)m`BfZS!*R0I+QlKWh8IVr|@AxKMG=5{5p341Shkd3UPZ8nZ?AD#8xMsJGr{wI` zp5#K!n(}L$r1fD#2?Dgm!n~k#4B^3V>EqZWS{P?4++gZBC5^C|p4q~zR2*D6uQ%pb zd(;nQi#8Zj5CNEuAZ;inxBv1bO%_V8 z-|boR3t9yImvWloQOWRMOqI}op#&J}Zg7rnL2*NAU3(W8i4 z`wicwiY}l66jXBWG)g6J_?lD6*=Ks3vXrNNrZ-iWL8?%4;KZ!tHcE@zmsv}bg}!Q5 z&zh^;MTjp$;TdfQ;*&bNSJXhA-6y_KXW=@Zs&v*0&((^neyG9e1PN9=zR`Ka1@fp1 zB&=BiNao%!+i0f<`-_+SGI-$^dU^zA84Brym?vCP0SiD8KTzuiBwD*a-3Goir#o`NZ>-<@K;XR0P;sz(Y zKkaGpg_ncnof4n&PAPH!1zwvIDYiS~UjA>y7w))TCw67xZqKG-c^TK&{lroUu1g*l zU$_{vUj%$G=Co3H$mptf5k@0=D`{e^#Bsc#5WM|0@w8udVb&=t&&~@8=0V@+YuGK3 zy^MTu|qxQ62J+2fA3;!gUn^575NPTvZSm=|yE+d@JJJnaEN@#i@e z5I6+@I=_5f_xBFP4^Git+}pRYuh1fBi^Dv)t8aIn`<C4Q>gjugw zDoGjT6=h*zC6{jKJr$NmDM9x$YC`0b>Y~%~`S2w)8wp)d1)*zCSF)lVtr zXZ{2GjA$(}pi$}6lcZHb$otJ{9P9J`Y4DrG>s%jJLVzb8FY@5qhFAM}YVSK8uRvko zrj3#C44{b&bZcpfvj^;~mVOH5&)~!UE6+KW?D#_uQ`A3CyM0^b&ywiB^md9Gb%tmB zsK>FGGtLeVofF+IJJ0a3O9wWjlEx;$i;{Y)T2nz}eD>EP!wW~I1@jBHz#rZ46Zpv! z#q*{j{!_ zszZJjtxW6oHP^*exL}zUw6~$35F5Hf-}nM=<=p)kq2>|dC)^g{RQey`gfjWQn2zZIGW;A zo1$u}&HeU~g^vU_;9u6Vf2Qs`LlkCTNpcxUc7TjfJK(Z+AG=(Gg!ik26wqP! z(ngM*(B;GfSGxl23(TVd-bDIXpnVC;q(sTkF->uK1(|21SJ0E>I(4C%4*`|lZ|}|X zEOuXBZ?YcBw>1unwFJUZMyN*6_CT=;$QC4Rc%!oalfB*uvhs(sx=f>X)x=EIL^ z3eL%R^Wm3gjhhd@rui5Xz6#8I8QiY2`EcVb#)kut92r^!C>bXnjN(@s+V6PAGTJ{- z{rId56W?{tgR2isG>R}W4!U(kIVZCiNlflueKME{oBLpmMzP`Tg%**5p8Ysps{KFK z-aIg;qk9~8Z$!x4EKedK+jH;pL?V$y62wwkg4z>_Zd8@n+QybptuBb7s@0+@Q|(Ks zZmNp5Z}WChbkouz6tySlqV_5+rM_p*+$ZO+b>D_^Uhsi#Xz!2~lCQUF;_JieeDz9jW~r}jlJ6_NMnR!Mr>$xQ zuWX-(FnnrLXAloebVjRNH}S(gqf)f(v^A>tcQqm2R~>QRrp`eEF+LqdRVMOVR2e@}P~7{zWX(x?qte9i%%{yb zv-)h91pWU%G$&k&zp(@}WMF*<(Hyg~p{zvB@%z@7=9mrZSmY7Su}Q+x94cB%0t)}$ zb*GEZ3vLo1)n}l9iRyEY_=W0o&$l(I&;2($pZB3Y#_R52-uD(~s4{^Mxdmpii597* z_7sy6iyl6A3uw>iZ@nGP;EqlMw5Oz_Q&*n?nTSxwvLy52zp(_Qa5&erxwOPfam*L( z=GdB4Db8|QjEb{Vln}*<<>}-68gZ?4y->gRJu39RsX|zApsq{%gu+1;f~(9mtI$_c zg}ef)@@4g$L{H3j@BZskiOkBiM2VLAR3fwCVv9hjL?v^J8M6w%6nh%d`$SR!6Jb1e zt1~b1FVO`R=aTq^igU@Q;)rKcdC}}U5|wLwOgCp!P1y_`JVpwmWFG2Yl`LR3bM1$5 zxc_0BL*?kssfC3sKie+8VOd&F=P*AtakI6Q6@SQ^ns0Rp=39!R3=yR0d_|6Pk=kc7 zZ$CaNQOl*$5Q|&2*XA0+@BW)H2{)KTd@w`v)%Bfer59l3^k!e@b>7|Num+P0UA5b0 zzU0BErdl^jmsshB7m5xtuEOtUxBotf_>e57keE^LZm` z!Cx#krMZ}rh|=8XEzOrqUilX3FDfFUJMcwUg1hrW`)^<^VwI}c$ z77H^T-19e;aZcflESAw;n^QQyG35KHyuG)da<*oqTcZxKRhj}qjnc1KnN2O*`cr8 z)U6(D7x)yYt8a?CG+b}TLmzZr=X-tD)CXHIl@B_TwZ4=xAu%0V<#F@`iA8~#L-^4xf zh_k)6hLVILf9Kys{;?Ff%>f&aImh3K(ylohQ=j*I9HjgfB?hJZowt-1)Uj5Eyd)yF@Tr8gMJXLoHFvGXE(Nndd)!4eXCbmWkwpx16DOYvF zRoX^RDt+?Cj4z{Ce0^U2q%&5#o05cnY>FtMQ}SKk%PINx@1@y2-9LJX_B`z;7JlJQ z@4#lR)z4!zm;?zix;R%+;~`cma>T;1TdD#PCOmJ^$j5S_5a7xKHhgww)Auq@`CBji za!I3p^*u&eaSgqRp^)Vn8!hoD^hY;*#@2@~&2cv1OXoY~JGAwlb#7NreNUDs@JD7n zX954@J$Q9?<#SLSz7_VKU`~nH>aF#Ttu=&d`c|KzT6=z_H@v0#={r%5cD2ci(=TYN znSu;ItZ57tCR3D9g$dj$6((S-RG3xoJBMmrX+Kn$pS%?<+v$k5&LX8PmvOjCfwLVLc+E6;oGnL z63Cq|I$zP26AU83A&FvT!x9`@|8tf- z;>?fq!9d|lTji&};0&xCU-Pn4SKtAttDy}w+E`u-pAK?Y^??z1`X%1{DEwLA?Jj>c-#D4=6JlTrpxkS^4&&=TCxxg<((LkEb#FO(YlqPD4xw#gM_)HbND3W(s# zLu$mf8q__0o80(2Eg+g1_F@UCI=0CZ3I~N{tsvWPlPk!ZX*I4O+tq}syF{fCRA0*_ zB;dji3D|InC8XcrZLpB-lVoTG6i?M6a!^gUMs357ATffA<1!LZ;WE;ON-QI_Ac_I= zzXG?(_2Z?jV(Q9PFK)%9qIRB+2k4Hu#Y6{=3{PcaM^5Bh0yu6ltq{L(i)qES8uuo5 zzu{b*wtgHn$n)jwt<3A3KZprU^%Q;8;g7S^0=38iqunkN&{Q@KhukGfnC$%P< zwMW*fx1D{o3W7nV(E7kxcoS)`@Az51Hj;}W#__Hl++8!J7x+rPoj{~|O? z>+03lf{*Vg_4BUAvGQPF`ekUCHpHumi9Iwn0M1?3!s*bzu!vWEAM^rXk$}0wz6VF< z4u7-_9iZ}P>HE$^g7+5tZqlKiMYJ zR@R^G?$7ss=zP(~-1%{tbAq;ul7Vw)IVmy8s2w{i1M^Sc;0)j!3PZyA*-N1_wUY#w zoJBEjyj}x7~XhO&54^8g0YBT<7c?cT|u_r_rsHX4Iv_FGp?GI#Pn=Qg-^SHXUa23 z>p)>cuEk^8?X(1E?tD>#GdJ*$Gxwm4&P&<@w4q2xP)6`IpTjC*1g)^1`J7xXr{Afx z8mHgK%4?YEXP3*FzK!T&&h(wWbn0O_q5wr_erJ3HFNT*u?WnUqgBM0apL?u{x~yET zB$rdvxRQKDqOQJ@T*Wtj`e(;e|d>XMPQjo7%X>*Enq@n1c|~tEE5ByE!^F zh}N0OuUqx#By9_&5Ujro&w%7tJ8%Tm=a%S4?8W&aV`ON#od5I7<@}#p&gXB5O6O;z z?rf(0PJ!dlo)IOUp*{C?RBQfHr|3_#z#UNRF%cZv0A9Y^*@AEQwjSf}-gS3ItR|YA zJ5;C6Q-!PRLug0@C1)Eyza4O{+o*q>20tulNc{G+Az?wZ7)9XbTRTU$&{Ak~O9Zqz zM<|bViSA_wE<^y!Yalg~^{U~gdKwnYfkpL?98h7+6b<7U(5zle7m(W;c zl)&L5o8gfi)fKk*yz^H0ULAChpFPrsQE(z^gSSI1lKbwkk6fOnrfP4{E=c!sFS=Wm z?duu+kE(9m!LOVNP1C-hJ&?X0q;%nVXS=Wn z;z-HxLRcH`SE%pc^Dc%qjnoA#I4?Hd3BPb&Y`n9^_%`sMb7i%e@Cz+d^!1nuPJ(Hq z#6&*lz1oO@%bf6a6gW62{RMJ0OU5Oc6JZa6k4%JJcgl(IPFgJ{LZvIut8{kIhSLfd zizGP@LO(GNDxG-cZ(v5oIK>s|gQdcbJIP#_bJUsSnG0!SITt4F^qvc!5x8+KT)>l$ zIS0jc6a{oHY(}UngSjwY(OxD+@(3uSAyOUYhTfZn3}h7r%XKDNNUW~JY&jaNGk3R2SP&v)GYPjPF|1*C((yV%c`#*EBnPT z`0zBxcgj!ZE)c!UTu?qOHoC34XQx~R@1gLlRj~4doQC~=fQ}x;MF(*WQB|J`gLvk7 zXO?Eew5-ydDlp-~)P@PqH-URh%%j}P#5`LGx^ejET@W7=6&=eI>r zX@NGE)55)HoCTV#7^ekzTT19NP7A9*`PBa5i%k|E~W*w_y^pQ*2Yj!xR5XW0Vi^0058An>}*n+&T%$aLt9I= z^dc8t=6x#6zwBgU^z(|k=?9rp_ATv(^nO(ny*qsj`P<3SNpUNLQlXuiX@?sL(6Teh z(ft*T7IBP9J~NqFRmBWCZ=1oP^A=fmk<|3bDBz|<;4UaZr_IDKblPlJjZS;R73V6S zn-cHWhC?3Z4Cn7&iK@pB4vlWkANa>PTT2jBd8`Vj0~aYVxtUX&*q3P?2nIO;bo!@5 zDlZPyGx^e~K`}}z`5Rri4{{1y?h>xt9k5Wr>n^-}OG*chTZIp*da}o_)1K0=$L#X< z>q7-8=+_H*zMnoguB9lTe%(ol#Wl{hvCc`_cv_5sL7aEbakeI6sq!Q(K|7c(O3-ZM zc1ibq&0o*s|BQvD!HQ%Ch|b9JLG($ zz#9AHhxd#rn;xXUplB&xJ#(Dah?>5`hM8ARO=ws)k43|yi0$}>P`zKIt=<|}SJRjt zkyMX7RD&L)lgJaO(MjZsU+5(Ach|h*0lI=0b!LX?TdIY4?KuzEKhz2-J80M=Nr_3p zoX=~=t-z5{z^~DKeMJJK1^*niNSj7*Suq}bXt^>{Z_kS&100Zf4Zr(E`k<yzUqi2`cU!zgiR(r_04vsOlnaob`@v&0(< z*G7rMG*dD`+6OiSVgv1~6HzZ}U(;fAC0~gWq}aTYYU_!S-agt%*e%;5O3;-|;%npd zUD_Gi1Y^7tyJd`bg4CEXUb8b%`_zCv^4@KOJpjrxDPXAO&&w0RJBtq(SI@Nw--C-t zZM6XF3GLF)MU7J6&UK<`>M9_|5Q`$0A(pKKeb`;UN43{%#puI+6)IzfM0<9lBLgQ< z9Ip@8`cRTl9z8{gC6CrzxH0vuSp}6s7AC{7Q=cl6H`wkv_rrvLIDTT}=DxE|8OWhHXk3 zbQznbchxRb?=qsNR~PxPG->FO-4A<+7r7^0Z|U(OlwavZ*6l$r5^0?w#{39i(2K(D6N(j{8@(Z=F&yP|Ib7=?M-|O{b4O@%- zf0P;+FS?NFRPFYo49PoFSe2vQxyp}nYppr-6zZ4qBbX_C>o|!v#3^#kw-2xg!VRGr zwQs)Yf!g=H_=Vc{{EsziUukQ7g%9m}vW@uCpV@Ws4x-`&ygX=i9L&MT)y2@-4`%-DLuyb{N^{nCA~=C>Ex+4Q)M zC_z02=~;U0+$;6ipdC<;WB1me$IbRiJ^oS9LiM=uUa7|oDJ)!CI`&FMt^-|#B40HX z*+#wPN9iaKs)Z&;3=_anlZT66sL8{5c~?DAqen|Z1nl-m3q{$F=I5Zu%1K8PVS(@!|qV>zGAKOuTb$JguWM-}?C3h=nP7 z1HO2a63Q!XAL7sN?xBauoAWObr1BP*4>AfD?UmP|2S4cu=FOB=cQD!wG%bna(bhZA z4z5J2Z|#*QR5ifz7$aPE{tp16mz^=?gLad)`NUpfn|Jf=z4iK`qK`DogW}hJ_^-Y7 zmT`;3Z)%$}M1e=b81&&K`=hiNgTCwkew4_Ykpkx5hZsG^#2C^ zPU_5Eql3A6bL}!I7n5WcUh(Jz#z*vpwHNIp1d$VWPPC>5Z9|EHV&i>;Z=91NLgcIA5hhW)?%>OkuSTa#$YjL9|nt% zeR%(EdSbZ6L4dsb21qeXv?0agDO(AKiQ%{FEi_v(hKY#+e`hsfpL7>t`{Yu$gc6F9 zm@G-Y_kipGo){ks>+q%dSePim$HH0**e&6os>i}a z33)6`)D_~R89kwocq~lm$u|_}U9LB~+4JnqRQpRD@HACd@pu6~4ADZ|TE(l^+r%%t zQ9D{(pTpac(?yCD=EHp?QZ+C|cTBeW#vfJgcNh0UtI(pB-dF!^KU(vZ#@;rNm}g_>n4n>-YLR z`TS>H$qUvz!T9!>`px|0LL-SJ(;DHl#xBB;fp8vL< z$gYwmAi5FirJAG`a6nEg>v)d`^=3p`Ob)_1KI1|Cjp{h_+J^Y^SIQi{{qzIi3!Y7F z!dwR|4Hrn2I6i+8>~K~SS;_%?bj)wveud9}X(D`=D<&l=ywH+G74FD~^^yOEyNd_+ zt=_n^Yrx(2|2OXYAJHe;a9535cr{8-?H38?ZFtF}x}y;tLXZf~lhA{&eY|5s{^_Io zB)Gku^_ZT@CK95(26D;)Igll!3Ci^G8u)s;rg1bcwNK=Z$@)MW$|`=ysGF^e1(wVO z^UenFP$M}oHc~2sPtJs8!>iSI4Ty*PFXN`@P1qVjG`c!`cI_R6DZiprTOLNE6v+gC zT4G9n&h;n7Q>S*Dcu1@4mT7upMcs9P2I-A(VR|cozf$iLqMi5lKCv0>GydB{Id87#4jCn4g#@FtDw zO3m7H{d@gXdv4}=&+EFp!oF^f{*9u}I!JT~{=h5j#sauNG;prIS6y`wRuPUwwwmyT zI<)4}hz!A%56}7$)u3Vj_YkWZ!A+Gn`K0IdrtD2Zg{3fCL@6EY*T`TmJ17w30>mA~Mm+Ea;{X>@W zTBcc-yO#SBY}g@>X}Vw3AFK_*s&x+WA&YdK)ggpfl5HYNsbsGb7B3&<%f>p>xwE6= zVXiOH0~Hxl)~-;qge*+M1&lVKb}Sea$O{+i!+D3r`pUY4fm&Yqh|!7_5N<574yr+{ zqpHLj@`^s8R>V5M6zc#&h$Ys^-eSFzFnQY{sj!1nLJqU}q(4s1dF?VX{9Zn!@THU8 z&Ddg6Ev*uQQ)N*Ne7<=|#HKApl=x_gk#q3g8M4Wn%oTO3!z^qiez&#>YpJ@7*4hi3?7lYY2F>K#6QNc|jTA2bxk9X4-lG+wFiWa*?|Wto1vnsONLYOtG0MgAK7cDRUL z`3`uK-lW|1q23=ZFX-)IA~*i48_*{Ezj|vnn6wc-p38ak)00yQJ z$I6!fR+;TpDf9vFm-tpCdB3FIVe#BjW@$n5B)J})I@w@xL4sX84H+naia$M%O@h|q z3rwJkcHdv$648EnJ_145MK**`RW+wh|3trC8)Vh&=XgG0Ja7|ab?2#pL9`CenZ>I? z4}7YB$tGESI@^$)4b=kANx;M1Co2ekPD-`ay znh;)g;&c62UF9{teUqNYR@gh|s&7>Ab9?m|_6Du^MqlQ)4*F+)l$OEPlNvDX5$Y!u zHEaxg3l;nIR&|BE`LvJI3K|w#WSMEqfKN$*cUr1dyjp=TGpest@a%76Blxph^e5Hh zK;7?pZ+4o{00WS#o-oNiK`JW0(_dEANRY9)i8-K)p43|cPs z6)HaJ>(57(>reT0uT=Qp#__FLPtpeIzqKa%Z}ZS^?9|5)`ZcLW8I|7jn-!^*c7gZ# zL4QV_P|3?TLG(N|&d6Ys2n|U8L`nZdS}y3{vP*wlom0uTJE7Neq!uZEx+cnBM9QVQ zIR1znLWnn0*C$pZ-mED0B7W|V`Wx#1OyL`^j;_n^+^ctD>j*8#!N-z=k7>E!0A8o@ z=eO+BpRQXDRp6+av}QX=BV=S-O^h7$48g_y`dGq6upEMqt8rmgeCWkR{6YOo^{UB5 z-9uon>Jdwgk%4QHfop^|44VEtq`#>~9^p$5>$kARq?e#vX$Yyho&%3+yF~6I#B9I6 zJM(dBw&ufz*Q&8#R{ZV7g5!w(mfHDmJK2ekc|QV#>Rb=jloSDjUxjQDhC2E3tJAeoR3){QuE(-^7#NPXfcnSy2!5|HW{Ce<@&g^;&32fYmR z;~cb@v_bk8)kOcBl73KMuSv*!q!O@t(Qa0hP}(Co&Ow_{;^rLm9iagk_||0LTUsF) zz)7g$sGNk3kXi_YT@4oc)e#>as8fe$|62c6`0_G72wu$>o}>feH77NeP6P<>;>E1^ z%En9C%AfUC3JW`CDK63K?o+OF1L{HL$FN-vMY)Z8_hN^Em5#r^{ zr!s?icB0W1?X`Mkpa7c5^R~Mk>Ur=+9&bWgnnrR)7)e`iXJS?!JYqSM2%pZRtfYZ) zLS-WfS0I>bZX`xZd+0Gw7^@lW{M5-HJrNK-Veg%*PBq0kl~xF`X3UH7=TQ!0wqGfL zx|){UlD$aUpg>=!L7=Zz3G}-#qnJn{P7*iOr$Eih$A~~D9g{&VdX&$PNsqFLkb$c4 zrOCsWv_g24{XjW-l!K%ODTkAMpQ`YSq}&R{!$~Oal+?pRwm#Istc36OR;h!BdW>)b z;Q5!T2v_^bOS>EVB(=K%t+2Zn<0sR-xJesi#>tCyqkZ)V9d2I47$QRVaxS{$18{nI zbF;!^@S7#1E^1_+lj9XOL@1 z`T?I8{bofki+*L&hc2TRd`gO-MPe72#4ex}c6YK8s)##TMOq@|D{7#;%p-QMki;d) z2FzY$n-y~@*+R!M`Gy1|rn>n&h&qOcUm`N8-e9Qc-MOZir1-KU-)V(%=DL?Io6V!Z z*rrB~a)uW+HTto0g!?MDLomln=1w6GRp)YXIkMOW+}xLg=m=kopnC^k6}V>?cUbID zB=fw5dG5%dpP?8NMS{gIOcV+JSth9t7r_?3Yz|w0G8=DqvhkAlK3@l3*34MPnu`AB z;ubgi;;jNt)K*)YeWmLh4fx4ca6-0dR(3=Fb*hoZT3hI>-M&a4L=(&IeYp+$zeOlzSa-Y}$5jJp&r7 zt+k-z=G9~DTdTyxXZQzdUyD-IXBf_nvCjK>Zfh9MW8RH7^b818D_}T3cg6%&Shb+h z8+$c1_;Z0{1NhiB#+P-kKqY=ggZ*PQ6RI>qy$mSCw_2)&X7zuO2^8=0rM->z>O~ND zx+9idBmi(FyuF?AfNK0A(@WgHRLK>=D^6a}#fak-M!2&&iqt9;t82Xm)MXn$`);fr@Q6FT%48R@;tfzV;j z!q0^eP@l})8-ffnCd8oyDG~abs~!Y<$%luL_x;SXcf>X?Q#%>a3VVjof&LK(b=EI( zP-j`SoDN|qv%lC_nf zWaGLTcQ8^cC7W^6V1NEvS7VT}i>tR9_p&{9x@3kEyvP49BCh-ePm&urdR|m(HJ%0N(@#cLR4vyZz!&_ki5tL23m)JtWGEEzu73i=QzA zlr{dtm#_0i+V4-%%6vVO7x4egHb!4~35QQ<71X8c3kZiTD9HVoUs0X3|IeDpO;n zVB{@r_JVg8l+JunYLm|RJfl!q$q(ikZnlc_LE=}`M0{Bl@#pi61Tx^}e(CE3QmcMO zHlqb-QLmcB&zHn2U*HI15P=5*)ZZ#R_3OI~KJRk#RQ3~rjH19Bp|;j0hoFUg?RxlP z>7%zB``LNgPsDt}qrhXVIBM5OB{KeZO^i1(#O zwx)FR`Ntg*W&Qetzg82D^Wx2pkwmZ!WyC`|h!m$GEbF+J72pAhg~$w#Nk2#?1VlWe z_3XMI-eb&E)h-fQoYl!)4cUH-+ae5W0`bI7g;{*aU?VT`9zh63Y=guvjMxSpuQ6h~ zcZl(6^@y#Y!1y0~h_Hka+jy(MgLTdq*PD;ZZ4*4tdjLMT#sV`N^4Ru{zHFw2ibQKZ z2q>I!Tt;gpyQ72oqr;8c*~_FahHRa7^hxDwM+s*pF2XO6zwsh`4G_J8saXKAS};Yr z%3x~DabLld=qrP%Z^W-zJnufEUEB=un+8+kM1d`sitFf@#I{<+Rtj#&;pW$IgSMKy zlh_slT_oz2ebUL{RMxs11IT(?$aV1(}=IUr$zB{w9NgEK(~xkdj#gj*b=%5eEqHIB!t!IB!7Qm7*Rz zj_c02YP^#X*v~6oi;3W)?{TbGhyBJCXLt;UxKQJ%-(Kj-r;azG)Iy+AWblsmrt-rfE^GC}Mj88rP>(LF z%qpmIS+$n3H_dSI_V>b5gjaGMxooqAinuHv1QdSzo43oVAbqP=nF?f%f{>-tg4=oG zH#)5vV0t;N?*L{sr$xF-r}Z9~MYTMHP|;U9t)LU|>pT9^WTS1|x1y9ftq&}+%@rVI zN8QBxPcdF+;i99t-nX1c+zHc(=%l*JiKsCrYKQ@oPe?BkbV7KMtQ$@Sn`Sgs!%xVp zDncpv9j~maPJ~X3bHq!0qAM;?NLL|FGrVXo`cOHAT0qQ<3vnZq-D?%gm21V@qZku~ zXgZ)K7&xC!xVIjUo&n!je}r$CVZ^h?NIwjd9+qOOz6&{%FPmv(sUS7W5l#S6ibd!I z0>yHKi%&>L_zI~-952^|V?`AXTo6s*<+F?!8}uqa$i@+`4;tfG6aikPnbn&|oRnM(C+_UMNXDB!Svn#8I5l~q zsOZP<5IE6~-zk2fAHVY?`f)}!3x%b);8GbJ1J5_QHNqM*^6@~N1cr#0$|mhMFO`WB zyi_(=fW8O*sk&4qO30-$QCEn`h%<#b!=*BHCR}hS(A%}U{;R(B;7QzHYHiPVgbQ8u zL?RaEd^tsUj+<>`M6iRA;(NkZmcayGbq`E14&9b<$F23d^J}F>b8Ug39cA(CNqJEf zFM`b@#n3=_hdB>iZ{S^Z5iE>P?R_qgci55;#q}4Bb$+j%gw*+k+0BFAp!j%s>GSdY z=0!%jwu+RSb3bLW4K0f;r-k2WuiU0PxD#VS4|~_ z+a``kAF?Q1c9NHm32Vqp-Zi3l?Bin`{P2D7`PFX!F|z;fGezd6#<6_oe~eBVMa9>y zHU{!X7aL8KBm9-cMsyIZRru=f9v-hOD{HsJcur~NcM3T07ykr^e;SB?nD{41{1YPn zafpAyPw{iF7~KiSW`@eelj7QbEI%7FIi)6!;V2=R&q(TbYolk0fB`B_9w0<%LCa2> z79>i91!cMgY90QmvLI1HEJ)N9B6~*!WXKd+Zv3Hkhx3KajtoBJxtkqo*Hgk(L2S|{ zOjmye_tYk=F+a28;pqB;7|`lJd4A;N9{l^)jVv}oz(cJb%pGS8^LFDwXN~244lp7X>-KV~B zicd=p&tz{AG_HGH@BrkwhNVelOW)0RvXW%dr$GDi;butQUUVA zgwmO7jOFYUkpvEnaiVJje(zc%LH!dHEh{FOT_R0jOh%{|sGR&xi$z{bzVtogo*N}! zImKUk-xzHpN{BWt^0a4^6*)ChcKErC5fNqcKQK-x%q1F{Dvs>n5&pX$8nYphyKR}# zhNY1f*3c)P#wi~)Ol<=!DGgir7dC{pJo~6)Ot?jWsb;Rz{Mi3sW2+j%Az`ikdG1HX zy=vdnJo{u^63ZtTQGPiT*+BS1z1n@|RAm|YDC!&pBOt8_81`ug@m>-^R%>$S)|qy&~!@kd?_G55D+g|Z{!dn%>>uSpt&#- ziVBUy5~SJkVL&U4MBK{sX&;f$Ks+yzH?2vc-+xcT-MFy$1Xf0MdxQ;2O`TXx1 zXY4E&`uZ*Lr zdPW*z-7}VQqjL=XB0PgDyI?&k-Y%2M8+-;YLHU6`@pA`8G=i7G!s~P6^_UQDTs6XZ z({GIH_&A)$%?w^pbge#o0`Tu|jMnT59RuM34M8AXa9uhrKR0v{24+2Ep$Bg^Mk=fo z<)fP`H|z%ii1y2rT;X*@=!@51&VxCLPY!{6@RLJ(PvhK-pB&nCnv0KA`P82upx@=_ zg3_(VGxjmX@5ArdYP_gDZV_~fi!Ye48CD5Dx7$d@k77K2Mt;C#l2s{OBhHx1uXn~2 z`>&{WJ$c^>I4K|4HaVO-<6y?~HVdycJ4{a-6T(4O-UVtflop*eKBpzYPIIiRaNG zdiZcq&ZklH>(uRW{a;p>0;C>4)DpKH6U+)>truW}=f7?R*#1ix}cU{^D z+~QBq?T-~82=V>x7ey1Qu@fy8PVxDVM2}@12;Jyq&wP4ks$aLW3ZK`$OFZjAs>Q4T z4}nkn*=EW8&f@lI5E6lpNg+F*-D&X2_YSxL2Zx##tadmnH$#UDN+>VwEYct_7L)6t z1IB|Y8)cRA%5JV49x^U9@cQR`Nrq;_hMs;(h4CbN)Q&7S?vW}o%}Xw}j&R8(ov)}g zdMMBG-z$wAHrK0vnAP9R_IXAKymQ1;Rzr_97e2z3qsDl+`10UUV<3COY9aW}C7{gJ z{;U56YW^|fKIIdB>6mddTSq`;|77%MUy=fx$L8%TWGX1h(j$H@TXQje63k|LHhekk zUzv#IfBbB0V?Pr#UM!gN@DT(Q=~EhKxyY9yBVbCirlhp#_r#1jFUOT0MlI%mXa1luW@Fkmaegn|1`8MoTVf+6WCzxNz{P9{V&I)@1n ze9~#-IX0e<2xFV8jx|{uODd4HrR|~<)hEx%Ex)HoEpj%4a`wFBOe36~;o0!H6~bDW z43fu6)(AF}HCqX?_WH`;?8Y-+nD)Zt7n01*gbIt#QC@t$`@8WP`+_zVe6Bb7Tu&;H z&(Je%6aDtU5LP}AYOuYe8X4V189gc)^>%*^y2cSs&CKETl2d}uJG71<2)0A1)+;0GBDV57_*uqwl!M5PAly>p5bTb1xfiKfwr79MaaV_N-*(foM z>yfiETrQe@N1~elJ0IK4naFPQMvaes^hJnxA3bzj>J3jQc2ABGvkwC2tgnSgX-b4k z<9&O^M9QZc7XM@XS5YVZPNHb|1D|Rr>Yo_MFYjuSCZgXkjvWW@Zqk6?d`rwNe9iX8 z)oMdjSN(v6bui_BLBZ7sb;<9g9bp-~l*kaYwG|Kja~M4Fpt(r&t-Q@0elGY>k#M(i z%I1CjT-W!=gBcZicy%f-@=0}FH?bE9A*d>!iUK-;FBD{TR-P{#;_r%7_-6$%4cK&NZ!D_H2Duj8gYcpnzwtjmct{ zC@n&i_~Ob1FJY>F=W!_$Or!}>7QeP%Zz@M~+?tpe-YGuB!KZ%F_lEShiW&9X?|fX( zn0R)M(1=owIPWFp(~|8Izn5kAiV0I#vS>i}9&lOR^1NJDXOUWKS)F;FOj;e!k zp%=sXFNfV4UL@$DgPaUq#S)vM6@*rAnRs5V!cJHNgbxXTjo?E969pskA%S8!2I3)s z2p`5Ed&Ri+G! zNmYZsB1Mq0-%&I8;Z~y(+4ojC?$DP`^9%HY#${U{4_T-%(oF~>H||T(9+@+9cqlIM zGF=2;b$`rKe(FubA%6YEjuQ+RlA)72|A%x^7f7w;q|W_8oYb{HOegiOXzN*)*5T-+ zEPBl4$#Li^oD@ZiPO4hVpMZp_&GN;~T>+7l7eIwehc5x1;A&fQ*Q0*%7vMV~Q$ucI z2^XN=^t|)aT~Dx7QXoSuI3H6JF7UA#FoDwMUc{JJ#9bFGVq*KsV9O^tyg1YKILq@! zCl)*`N0cJf%ggdxxE_K9w7p#}e2C7K<%$iu&nkz_dCYeoG9l(Ab@~PT7!{jo)pHn@ z;p(&tWJKm(ke@0h1Hv~BaJ5q>UyvCFlSy|R^NKM+t>De5$~LY227Y~EZZ6!N9FxjL)EL6aa;UV%?3ba$omS6&MVX_a>4G z9IfV!yENeII=h-HxA2plA-e2DTHug%xJcBY*G0MXB}2yJy1FvLEn>|T1z^Nvd4f?c zn}TSGd0KSsjgSx7aEjSJMCOHJ+EXq>oZVdiW8=L#63Ll2U`a5aotq6c?T zw(-GzT*<7QRN_c{PeJdOBcYLzIKwAD6LYKj`bB9w6gb+>yuHm*6?0f9U($4Fi8(Bv z&WSn3u2C}V!(v{Ar9I`aq&ydMiUs{?DIqckuOs^NUUOrHsg3@WQ$iGJf-FY-Nt7)f z{(#e~V9Fwd=w6e7d8;+(Puy@MV{cXv>g3qZ@r=E&n&xG_o{!m~vRpz5DnPG4<;{{_ zR)t3a)-R0tK^^(0RDk=fdZ_@zDGTF)ssZqES;B&JpF{qX?sEv~jzU^GExo1kCqARi z=8#Gh&r=k3>7Qteb`5a69@|Qlz$194>FEIg%XK*{f@22kyKrJ((b&b-cmsZi0{+++ zVEhaq02a?>GcT(9`R({q;rTPuU4aBJPA1za;6qXxc8WWJeEa|)SJn-Rwm}w3TiPrt z6<9!5LWe@?EG>~bTQ=uf$j1s(|FU#XY)KNeFz?`!u4P3-UB9U;l=MMIKY4k~O{_5~ zwH$ruUp#iCtG}&}aN1;AG4uKfo>LsNKOh z#r>;-3mmtq?uA)KY*pnzz#u*%(d&Y|6EvNWi;}^>q(qd;z=T6!lE^#xM^9Im{Dq&p zU`t6KU{UUKz#AOmW}Q4@eETo_%7tA=ltevEeeo}GCfA+4Kw)%qnVY2ZfiXd43G_Fq z6c48}5?P6`wkyXE57Icjie6aBiZ2Eo74R{`?U?w58E(h^l9|eb#X=LW!@>eqUWeUN zx>R9|E#Y?O+okm;YzH>m~LN;Tl)Jm#u=T)$jFxd&q{;;6-_GYh_L21P4F6 zcEp`5;u5fJ#=upJOh3mZxcxuW{}vYSU5y{Ha9on>w4h7!BNjdgF4Qj7yiV)#u&ae! zr;(m=o%Y9H|GG}=Dd@pc4KhbQFnZ)eSq~MYw-`FSWs8DVZ3>1CA2Fg;!N{RmZQHeJ zHMDK3)|nY2+hnvJ+Gc20n>LwM>6bm!lK@9#n4FpEdPciO!Q;0q#zl|Rc!xfQQ#=sp z-~oktwA$b@gdUDWja??h;J1MSE=zseI?LryBQEpGS+3dP{|KO{T4pNcH9!eBYwg&? zS5K-p1?upLC4A%COn*8~hy=)}SpV=Lvt8}ge=eCr2RO?rKW|;E)EBKG6>zCcaD62U z9yQs1ASjCssv`a__`^UXZyJc4;WgQ}&vkm#SXI*Qq>%_PnuedWf zjvMd0l6mvFu3(LlDU(8%&vj+1#g{SPjge|zu+i<7=|i(Fo9RQdEhZ)Fp#wf)%4L~8 zl>1E6>)TBJcOvmbgwRzb-OB5guE-rRab_HJ4Zx?*2QF}BD(btJ$yo^eff+?NZR--q zTOQHJ@Nxf33+0Cvx;|EaxXk+=gSSz46M-z-=^Cc)F!i`($P|ZKaarudXL2}aTYDqJ z2UHd)TY3LQt`=-7!RXrU$_+m+3aJ0x0@kB6&Q`yHae?e1e&0*3-7Mg5Xoco~7cc(a zog4m!celEKV>jg+Ui=@Iyc@MQSYB-<2%r%FNw$N}GPMJ0o;RAW$D8B4f*BJJwcL(tZZ=}x-f6H4_tCzd}!{(80 zjtRi$9H{q~r&BH+t=Fxo!O+sQ?EATSsE&9cpn``Abqe?H%_hQGvV4 z9@tBg;u)W^JuR0VBu$Zwy(WeeqyjN?+8C3nmr$sMy<$dfcaU0v zTj^o}5F*CS^%@2Vuc7@j$lbGU;p2ZRJf!(lgOR2jY|gEA`&&k7gV(rkO7P@AL31-U zdqUtBe|qwt9*1Ft{HNGaq6xLt9z>R|9_|dDF)8zLZI(qp*s>n(5;rLyQ0HHftEmN6 zH7_>YBh}o*`CLcmUs)of61HzjobFK!MX{DpxkSqF5@SN=%z! zd7^--ZL%PCFeMBgo`CqGMGz4rnEGc=CBv)7{m!)FYnp>7mv)P< zB~i|hqMSjEK35n&JR~`WZ|e*B^P~5zD$4Wx zgCnjC_5#692!n=R$`B+4y~SA@sjs%(%P zK3T;f=D@%VfH^P?gaXSP7=LMAA_u0Ck6Ed(E*K_!*{G9x{vVlLcY)9YBLe%E;-g0A z1U~sAR6Ab7w72YQmaxTut2bXGFGu&hR+Feul z{-NDQ?-=Z4GJ6?s% z&rU-V!`jt?aR^mYPApvFcCizL928zi9o4R9znaYbWD4)_V`+D@c+tw5QS^X?3MP*7 z%&Z0(e9C#(_2m%BO&vj=YSiHypKg+^0$Q6)xBGR|_~S#e3^_BcU*oRFjer*LN#zHV z;Zs^evS7uh3GhyM7OrigcO<5)Ymy=7 zR{$5lw?7>3s4e-cU4g8pQ`)euge)9^`@KgX+Z4qub@()vw1GWNdf--&!&~7Wv3i`# zO3YTlY|-n32gEyMk=Lv}pfK=?;trV)M_lN*Cij3EY3>TTR^zw_bW4!?LG~pf2J~5e z#VBWkRq9!>%{h4EUY&zi?+ac#J*MVs^Lg+;_$$-E>kAVu8?g1zL3&W z{FCv$)C(Y;Y4M5dPtpKLhne81m<-5sw6sEjQ-D+PExqFNji=(Emg36m+Zr^NLX{JHeHHBe(`kzPVQE=kYQ=1I}Ly<4c#$}0O!-Xx%)@@ z5NqKMShmfKk5xYb4Zh7iT6vrs5$@J%cZmJ`<8_|7JzZu}Wdv@arhpmG*qMhmkt5!D1d|66hW+5acfVATckpNI=7L zpknb0&w+{|3GAvnf!!rq<5A`ee(tLKe%>|8eTeE`Sz5Ha5j?zUQ6zW!#O7VjEUVOm zbDa*6o<4T3C_y`YPYpwnY|;CKZ;cLM@6ciPUYVx@3Q~n<|ar-K(h$)$Xb^hDAa`)EH(Ek%2Kd`I_8Y z!+6osl=Uo^&>>uI+;s2Gy{#6PWfCPGg%X$^WfWpV6Br@7pb3l=zt99mg1o>4B8drz z7+QqIh0|dKpM|exFHLg)8f0_VJn-}6o5e(x&Np;SxS8M5%w57tEQ*MAJZ_bG2%1wH z`%PdSN7w=jI5CX5<|r>CwK&R9frhabm==cdK51YX#%h%)?mD$bk35&>r-MhHYXPBl zu?sp1kG#jKmV2)|Dfmj&w_PZ6xg!%iG662l!iP8upHrn-Y|M1$GsVx#BCeVi5ke{~ zi-20Rh&WO!WCc4#OIo@!*i}M48bl2Qpg}yOqCqgzAmBhVnO7#eQ}~&8oBONn{iIQZ ztZp8qcJPx%@tlB9jp7l45RGEU)G!C`bg(XjMl^~^-km#HEvQitm>wMzLUVncm>(f} zpiK-EztAQI`qgX`lVJ3OO=Pxp{}y4h33DwumX{xM4dPP{!2U?d=gBSk^zQC7el{@S zPBzh^P8vwb``z02u?ju3%{fvFvj;>j@QUIAmxC`&Op4|e|A}AEp0aQebD7~MRiKpA zqPai?n#&s?4`D8Ekp`Bzyyi#Dlm zd-;aIS9bGxo!nXWZ6nO{s~Ng+JSo}lv>%L{xC?pK8~jNM{xX913cr+5p(%p;^5yX{ zKBzaw7%kMWy1eAS@ov_zu4R2V3x?Ju(s9Dk0mNTk@V9>u-|}CigYjMKy3(7p^@iVy z!tX5MSBvlbK<0e0F)oG?;Y)u~Y{|o;eudM)HbsOt%Fh$wJ=)#fUL9Un+V49d3DNM0 zjdR`I4P&Q^?$mt8TJXxid^LrQrX-80Y>aoG2doy}fnEfy^UO>*VifeBPNYKFgO)Lh~hj+)EAhRFY? zJKTq>4;8!1{Vcml^tSdO%%N&+m3lDO*2=RhKi%K`F3YztaB(>8m*Wrf>`J8-8%%0& zobX&f$Db=7rnF~cNG%?_L&dUY@qHAiFH5`j)BBHv z{0JX>7xsWx$J{^i=;l)+7^xR4w0OWOg5}7n*r4!ZfdNw!KR1W}-ofs^u{}gF9rl)l z5*YUMvcCqqmndvADPC3p@#hXw0Q^9Fy2{_5mwc)ENB#g+6ARmkp!T6A@DHx_HuKp- zVR1#_0HHZI)!y(Osz{E~Hd$n$cYBQeZk0&Kh3__;5v3S+_W& z4!G*d@na8u^36;nwO64w5YLiOQA5jyOi9CChJDxpE`hfQwrcNN7 zDbwJweRoTZF!ndc^yzW+__71;?raq4?mFVmRqr>6yQ>}&r=A33_$MiwkufCO4MZ_L zre7$=?)Su;$d3hRoGLyMztHJ?Qm+Q5Q!vh5S>5T(E^q1u`s z=04_bSo(bPa6WIm`yqD1LWSN({iPmPE+zI>kAjR|XnsHQ3jqF1w}_77n$T`2`xeb9P&RjNCFs%c>li%B+l3 zC0n%Zp|%U)(|EIN{^_Ic8_GezxE+QdT5D}l1v!G^S-GXZB|>8EL$o~eP*fr>N)1U- zO8An=?o{@KRVx-5aHc=HVTJ-H>o$h`<^-rbdr^lLL3WM`x;PTTiUkOisQI$+L;Ttl zx2q<^uSvvj_(c4wH{vz_H^hfa+)Wwbm^-GqbJ^Df7y1f(rTU=&o@pdHy_>sv$+7t6 z?8ln=6yK83!PW`5j7LruY&aex-v*f>ogy72Pk>q+z#XqQ&yFOT=rPm6Bj5yt zgSaNhK?hN%KKw!lQKx0s>AYSrVT6k=hz)U?x7$F5c z2A(-hB&DEaxjgN_bw1u=<_<5t7N4h$x1gHgz|&R<2?u70Qk?j*Kr2Kzu>FmsiR=~c z#uyH~Tpz;$_A;#nC&$-ZOB|?_@ip_@P1r}I61?0<<3@{iRX#3rqko#R zRrptFatJcF%Y;y z=(GZXOQO^!k2UV-RcfOKJbyj7h^PioZO%ft@Q!FeVx0H}$eKo3P|8ezhmPcAzIh$2+GBrl}_`u;5&V-PxfTnT!;P>9Z%_-uA9~5CdYAmD4~5GBaS*L?A=7&kSV3 zhO!#04Bgb*0wKDomEsq=sg(_Ca8u7LcJHTdstk_p+AG?ZglL(z{hd`JUDTJ57b0BL z2CJgVMQyGH7qv!BoyICH;FgPu^ntRlq5)rfUqU7Olk~vY=6nMg{G5UR%TnN>#x)}x z{Fd;h9au;ph=+zjEYRN6c--72bz*`GZJ}AipH`6={JOUiZR~x5_<~ z9U`p|!#)p&lcdICVjsv^tc)*{T7(W2RrEv1T9Z!5b5AfSdG7i08h54|!{kJBYK{BW z*b1R9bY@vc6iCi24<$U$nlMXOfVy1X@xi1U3K~JZyYhFNw5+GOEYRlk(#|R&(@Sen ziv9|89j2EAUi9qfu4Nk@&xlgk?cQB*lF4IolF6gBAG+UBM)SP&?j$yrl%tO;gbwC1 z6D}1>4;&*JnUjn3z#~C`uozPTJgzP&c$`>h0bVg$^HcL~>_v(VwiRPrhys+o`7AT( z2f5yn@;h#CkZvG)bJLJC^|+nF7L4b2Y7$$vy*vrt(*3~RFPYEV21l=?pY**$Mk@Yl z4&!T+Q{Z+mD?69kG*)4|?48Xue7Pyla#}0oc}mLj3@Jx>p0MQUP%qUe&|ge}0(=xG zg^vQI1t8GTEK0NVQ5>ugS(-0`kS>-io04vpEJ@R9vJCmcT~}dQ_I{=;Nk1aXtyQw* z`3I7IWp~>9cI8D{0aG-onf+*`2!H0aZu+J=R+A?SMWj~96ZE!nlP4eNQO$>b;>p7O z8dsi6h}G`5y3=#M=QX)A|AJMGn=Hya0)2^u&WQGNk$9m3a6DG90f#kRzVacj*z9(* z{}HgboWq=v4+!kffdI%E(Fp9nxp+wcfs3kbahq{6V@|IzpOy>Bx4b23g7oJxuK&J*0MY3MqiSo=p(J=52R7z}9$X z?b9L$z6W!gUkb>n@KflNjt6_qH!{88e|@D zX9ZDt!;1}YNTg)(f}OAxpa)6GQcNgWuYyK=?yW7;87;L!wu+}x4^J>BFG|AlElCw0ir8E<~BB0n~JD?Z?EuE2MW z#0c#&xuHmq8?S;!d~0sY-i(%7-0Z00X4&$DY_&U+A$Myg*E21dxt{49Y*Xm295*&Q zic&HGuTTc@k_xc+!KArhP8}FrHH|vd2ZGU0**HT_a#yfi$lOM{i-nAm$BT}DB6SS5 z$ij6@DQSq(N3s@pk(I@Z2Bu9^R|WI+D-x2}YSIabTSsh59%yV|v!mI8p2 zcy8LOEY3nBLOGd#s6_G5OR%a)A(eQ19~B~w?;|)KueT48li5`4AuX%(R3G-!h^ra^T&^xq6=G&2d{ zs(DbIMxoCI8pK3sBOWJ00bWdm1iU=`_AzdSjYH)Ak`m&H^K;I-)77;hGR|Lo-W{yI z2W`X=Wn)1VjraWsnGo+gWy&HRQIaZ;jtE@hh%(}H(G9ip3-JrJ^9#QA4|ihq+{9iN z+`FqQ=Y1F5BiI3g-BQjUtx^x-IX~8pa`xm!4Im$H$o~?@urn4KqMRqBa$Y5ssGKKE zwe)HHSp=#SuIj+A6a_PA4BJ_KWE2;8`S0Kf4?I9S#aqTI7;kfqX z8?M^NwG47jJ1N!2bka5V{cI?a365!}M`GLeu?jsn=j^S8A;rUoCDWSCWfLt7)@X(l zL+Qk!3xhHDz7Ay8zE>}kO(#upY>Qzyh2z1oU0{ywLedJyc0L{3S85ttrI?r0jqek2 zuhredabXd!tQ#Mv4hZ!a>KOm{7Rov?o|)=r=1>-ij&vvoT98BvGBMEzQbmvy*Ne}O z*eZJANNy9qa3r@?8%gd6h|i5AceJa(jDkz#@ODhZfhsr$tKh%~$Ltz$x0uviJgI(s zej`lGH23#C=L@4?$`qdqR7RDR*N^X}_=y7Xe9Y9J1<<4LPu24=qJ%sjBkBtA`GsOZ z+i3AmH*u#NudII}(z7w?dz#2M#pKtAM3Nn5{f!cdJD4!^k;ufr^o~q%NQ`IwTj1EO zbs-++g^F!U+*SNUOv$*zrU(l{f4fusLQ@?eh=GyinWe@MzO>KB&3Gp*z8?#8K)Jb> zCSn-B0Ef!U=QV7|)u8x%wXuU&_IAhec`LL8zVzl9feh-+U}}_jbfN{kLees+8A!!* z>VI^q=hWZV(-Wh3dT{(YwUr6CWKaVGKR2Lc@{ABb_%NKmdEUpVF9rl&dD$*sd8r#3 zpTYW7(c6d54~sV+cV^IbBPFgIy$3v9ZQ7hSij9AQog;lwkMPs2^St|>w)*02 zo7E1n@@T_D-)S5ugtK;AlV0jV2QU9E;s3Gr-hok8OaJ)$Jb?f?8%QCcB!MJb(+j;P zfOL`&dQa#q0s+A;1hI=6R5)H04fYOPg(w07qM}z3?5JS4Dk3U^dQ~oh-gYGpB!^!RA_EFx)jfK7@_DRiG5SpXTgn-x+9DV{)fnGA-Hus;x(i zzdg}%?L#p6F4QS<)IIhwMi03*#Xe$W7oCn0RH^*57zN1UrIb`75|M z0@;QA>Ejm>>vszbF4h^upE0W(gRc=!+(&cU~lj7sdFcB8W@8tN@sluq~jPvOg0& z;>AFoMaCvn4UEepW&t2$!+6^mZ)+suDWDFDVU0DC)tv5Ozr-{@i&di-{Do0$hO8Y3 zZ~sLfdxX*C0yI`(qWn*5zY9tKAO_z94DA*Xt?4nTjk!h4`kjtExqGEOm*JzlP(9${ zj+yj$+`;@aRvw#@)>izb>TKCV?r~8*f>3;ob02rwlZMVyVB`4a->|e7Y8b|q0DCIxFWYo%kCs_H9TDqui zU2|quT7)5g91T5NEej}KHj00L?&o6pcMbUWLc?qlC$}7MXNmB*5aGi#ypc=M;v`k2B@sK^>f8L7)gl=3G#4jJ=?P_sw82I6bvy;wd0AjWi8<;*lXs z9<5^szhS>DhmXKtPftS+TxjgnWOx zeWkfIPA*9T42c@nP~AUYtk0eHgm5Psj(jX_a`(&0QL=3QMSGL4scA4DI6MR1rfp&( z>hAd=rgC?9&T@yRK`X+OBTG7Ftrg#~y8g(x;4=HgjzfOo%x^S1ii}Ux6wI;1u1d>z zdB~BSE~4T=J~dO+!@OyWucx23kEebbF#Y>!p8dLuoc?J!o5#zsURXOfXY!C1tG_9Z ziNQp!#HR78Pnq$!c6~_{uv(3)zdnkS0ne$I+54MMfD@P6hsfMZ21UqszHxL_PP}-L zeU~{mUPfhtO6N0Sw6D&tPoO z_-amngS4D2=}ziDSk=Z=^?JoEP|?#O=PQg8nAG%?r*FzAl({EiU_H9rzTDg$uW(NG zGMPx@o4=ls3sU2LOWldnyGr2!b5)sKoRKFhr=7@`2W47Bk4Dq@b`TLUPqs4=wZ@MI zYrMvC?3Y002z>GjtER`8n}dVO&z6_I<8jPIPRL6a?26>L|X3vR7r&F zJ1{$2uD{*BL>O&>kTtfEyPju)Ll(_=K4`eR`gq?XS~HH&T`hQ?sJ6;mQ&}!~D`b$j z=F4LbAq*+Y*WQ}jwjOWo+cvbf8c{Op5qpA&V&uqK$3X>j)(I?woOMinEM~N=&sjlq za#qd+oi#p$j=ingDtL%lt^_!iu&EFr|uRXyrj}G-Av=#ByoRcZK}mUVFM& z!P5UX0qExJAF96?bL6>o_AbT_IQFr3Hg~pF-J=zf;@#uF%wJ?-b;c>Nk8$(I?UcpZuv{`UWT3m7 z?sf{zA&nK#{_bp7kH2?n7uw%VWQftZDWgYwoOJJGcsq6PWF*TauOC_;qw(!Rc>Sse zU7hRWlr3uu-AQ4K+gUgGmISj}SRbovLa{1*H9r$s;f0jCjUu#%d)g_qhjqc6*4D@A zVZ|w6Y^&a8?^0izhMP5@Zwwc&1oPNhACK2VwFbwwFffgRf8aKv?i#{5y-nJw3ot)I z_<`XKy6eiP?7hry+o>@P;UCQ7PzEo+G(qWj-}_m6yR1D7yN`gS3b#a};Dy*vtR=el zp27;8!bx3Bjc@Th#n%f@wUx;+S%XEB_5q#1y3ZZDh5~^wW7^~K@u>R95()%shOg72 zUMOIsAxjDv>G+ERMtb}D0|tmn0ps}>?8ocO?Rv@2H`&*S0jwDmHTvlUp8#vVX!u|$ z+n1hbE#KT?e@cwg9N65hw7m)+vsf;L56GZP9oPYkWpd?KyIow)3Sp;))0o1SLY-Sw zwy%3`LGF+2FnE+QN)$YZ&3%f^{VbE%tgna7WB*4sR^-^x-ijQ%f*EbEhtYn;C~y%& zfdd*;csM;Fph48rLKxILs=exIJ%OC+X8G^y|tLp za$^_I#CVz68Kaogc7{=1nE0)*)9~L~KY<0T)m);$@#V>^&0gn8!V#B@>aNZE?q}yT#)y6$34; zBJR9!(dTruC`6;IPtLW8M;LWD7L1ph-?FccdwPCH z!5X6PZzR2lbx8Bp2cVf2;9A6w7XcoDiHEF%%zw?)Sk zk;N*|1Z=m{$T8tMW$2BQZizDG($sw01{6h|{l>^MzoccE&O~+fJB1Nc1MGbG8gqw4 zbuT?KQ9T8Xp#OK1RY#f$-i07a^^v%8jAvfu>(}VgbdS0Mc~CT2g1;!5EJ+Nxbeu2W zJ``d%qnAAXfqlKWjR{L5-c35e$92s|jWFU>&xPHLC7Tl@q5;`NR`pV$|PS3(xu%8FtT2qC-ozC?czxWd=}Svl4JS0x7b|F4iC_5be@ zRsScbi(3!ddnMk7dA$FxX3|0b|J(MnPJl~NKY3CR<|6DoxLo;{O;W_)Ive+!XPf8h z^R^aAY8L(-*6?}T+D^_a^AF{1=Ff=)c+sOVZPZfys3ok)Ici^Hh|DCAz#4XFYEaT6 zH`nZ%Bp<#mHA8e~xzvde?!xSxM4hO0oeLEGlN9WQVC|BH$L#J{HxeSXNcI!zV?XEr!d})^rn+pb`8=>*%NSE%r@)$-qylSjrDAbsedP)Lf|b`n zudYfwNpj1#_95}iNWQM>btfsz3+9skJm?A(Jhq|`6g;-!FA5&pl0pWLd9wUF`_agN zEhm}NKD95N@#f32fw|!_Dm^tvo;hJ(DGsvMQ80N|C-|gj=#4}i1!1qL74lYa&|hmN zYzF-mC<3=k&ahnCGWklD{0N(tMhCV24(p)(nmm_wNB>r?Q+MAyvO_)VZ{&wl=&u+* z+Hi704O~IG0~yUW?H%eFV)8nKSbEd$C@`T7C(eYXwILMkJqm7uFun6n+ee8}j5{qP zMnd}$p?5mV01viy>mZl3w~*zM_D0G2Fup(g(+PVH zL6I7_%gw*S#`2mDYKDCjRmbD%+gg`!MRG~jNpTP3tH#z|ts;{42Uo1p#njeQ947@_ zXg+WhK#D@GSnK?(i&Vr@o!1{oot8^Yqd0_9G!C>9CMYP{&rgmuIcE?c<`* z#m#qh3SHbZ_ko8H>VnSj_m+P(Z0LpS!iDnm6{*y$U*FOYR88^tPIsJ#Q{`UhHYGPZK$^s^f}qTaqSE6GuQbKbAI4bkWI@W{>%p zK;BXdF5$<28OF-3H5^68AX#fT5^aNYx*GTq`lW4i>oW-e)&64tw(_gLU76;Lj&e&C zJffVXYtUT4D3fQJIYL}IT-1@GLS!4PU`++!%0A-4Ou;J9f?JX^WpWcof?#6E)A^2! z-~sSWZWnEF(JHlT2FD&tsSnpdZ46+1pV) zCECZz<4gxWOB1?v2UP29ymhktI_E&xpQgr@+}$)oyv)e?r`E<+Ch%igV0vD8j@2N6 z|Ewc0A;iQaD}g z2hE%C-T~oa;Opb4bu*`?{{CSSEk65GG zPz;L?!Pk3xvI32HgcYWNjUw4Y$!c|RKl}|uj@cfv{I;O-8b0QO;PMq`duJL!#R)>@ zWN=B8Bjr*vf4oLwSur@ItCX-Hn7#QB+1cL zWCdr^E=@uTajb(G7i>tBhhlLJ@+%(hK zOag>gxcO#^8r1-8CR*-Kb#zX=9gWCGwRy~{v?ufxLe9J&D3co1c8<<#(5U9?C9Q4m zYVv$k`$i|LQSBHeP}GLr5)3=@H!F=}n|UsUARBDwbcQv!?LO1tHnUBth5ePPU6o=z zT(roCVW~DbwnN>CG~B+&JM^|Uk*IHFO93BV%H%tSAXkDqU|iK$#uMnx6#>xCre=%ootSM`{W)9jgs7J+Ov_jKONKi2i4a!l3z2 ziiJT_$t&Z;;aXXk3loQHbvoDWeU@(T*V$^8u>OD3?PK-o_HL!yYg3hO8CRuSoL%wfv5#>NrCSS~hF2!teh^%bbjylq-Ad4HQjG$psST`VDVSB$3Wg^d=ws{GUgk9a zlcKO`47>J2nwyJpjYBchqp$7EasT?#NN_H3v8ejDzoh@(}I$9i2grbY<9a zyLEJRLT9O+y>IGM_%EUCOJ`TLc7??i;-c1pED2^M}0PxVjc&A05n0HgqH(j0-E z!*n|2s)W2mq0_B46*{ao4bWMtP5m78bc~UX5FLZs)C+Qw@`e}=)g&h)N$ZoK1Pi`~ zr|KpFYyjeVDO;ToH!xZ>TvdX2Xr@Y?q53;w*O(7F#qxpv+Bcmv~kX% z1U>1{g3{uvkZ~tL`(gqU)Pl8{;8d_SlUR9@c3eHu&I%>%p1(X!HsD(bH>Heb)p$o= z!4v$-hqpb@O10=U`#RMT%~6_zBCUZA8eR`v`Q)=(tl2r6*V^vg0@P*zp(3jsf>TX(UC4xShI>k)n|_!lgXh z<_h#|v$?CDs1)x~t{uRHMp9rxBWVy5Yb4DEf;f`q26D1S(#-nU^#lQNBn@CkBPp`O zk(9Fo51bGm!m8faowT0@Z?mdqIp)FbpR=_l5E% zT(_7&nBZ?hwA#B4Ooh9nE1wVTZGM<>p~B%-m(Az7 zt#jfxT!0S;#qrWm0*b|L8Ls8DY{^rgFm+AfhPI5m3QLnMuf|_w%d6$6D;+Ky>zVKx z{mQfflHjfQqjw**v2a1*b?1nnex((G$;&+QHiu4b=J#b4+SjRIFweXAov=2tq-*f$yQp_==@KLuF1PP@wiHYPX{>h48p#s;jc(B8 zY~pq;f!17lgQJ;Y3Xgj34}X22H8p*2a&$ME++e z8hpb)-H~ASf!bTr^X0?0IG((CE!<#aNat+o~;5LLI zykVXiIPXk00v(5-X@=b8c*^#imd7m*73KDi&O6(72aLZtcQ9>;3&6RQEr zSLdU~_ezD;DiSe|^9$hdpYH1d{|h{o|OR z0;5|2w_MFyaImY>0&ckhbVj&^*#F_{Cv~3bV z{}E>!SurcDbs$$vZFNVNrgGC=nMDCv;C9wG%|1v|dtL9RDG=(*pLFaNozwl!B&kuk z>8eq=ECU*KojD?1oyZsQ3}}xrOfK2#=(WDe9&JuYCx;4XQsH=K4xIl(8MRAd0taeV z00)1w>ZA^M*0EUdRDX+%ETn2dYeTDOTj23ji(|SrCv<^%b2P+$jWeM>V*!1b@_Tgu&gy@p(I44eaoj zaC{E#&55Y_*NYCD(d1`nuEOy-!y2wf_Mfy}&!sEq4d$vId1@XY<|JQwqPu**Fe5@% zY;#QRtwsD_qV8tR#$uuE#e(-8ik%zkOpnossP zoQAm}L*|WukDEQrcxz=nU@7ZqQdT7QF;hPOM@p{TU2&q1!pdo=lSxZ^l1W0^do@^l z_gdOpi`vVU{Wj(ukvrdUL>ROhX}Dwk%Tn9gAhi+p&}+6z0MmXcud}SJal$8DKT3&^ zWq)TStzYPlki~oR>SX4Q%}6l+13rnkI)AXnX*K_<)NC4=)RzPGy#6$(*~crf!F~B> zOU*wsNl4AHnL&N|M@!8xMFc1Haep&EG@BTJN581(-7_(*n$y63821+hK8MOhA6!3BM)gr_5b?Lde~tT`{s_?M26R5V8uVH*G$B>M55G+*u(MEG@9sA$+vK zr$hK$(3zhcodQ+3<&_+z!lUQl5##1_&|@2@LgTEAJ?6+3XPGKUfk`MJSK#leZNGv7 z5%MOFHK0*+mo3kH4V@0?bKTYK{>I@j%n4Zv+h!8uN@|OGA}kjxD#tTs)u*&?p+v!q zhP#|unx!CYN|_|2u*-uLR;(H{B1>%`(AC=8Sgl6U+Rc6@0b2X+2ZzUij}}J#9gC9tS-k0 z`7Y6uWq_&yczJAQLVO5Gy*;wk30ErIc6H8cMmq%n-*W6XM`k#^yz;IOcc#dqo9uDs z0w|07={=A-4+sv;4p!O--m+Aus6}?%ImdF_Vx8(%a4jqaw=S%YmvDN(idM=XD4nd_ zgEVM2{$Bh=yYcsC(?OZ-H8cR>wOo-Vt0#7vE2o@ye8Lw)HGM8PS{vd8EeLK^%^LZP zPVgJCLC<%|h;wDs1&5HiThrRh>S#}?*rVAnbMCav`98}fb3z81GkK@Z@JUxh23Yq$ z^z{L`_Cnf-_z-RI?#NcpPu?<}Bg7AyjM@_X4)li4PtLLo^0MSR?U{xpRkIvWs&aS32M;hVI&Za9zdDRZ2$Gz%F&A_cN zPqLUO7!Z=42(FW^OTft$!kus`z<_)Sv_dC41F&t1t^?TKs^ zBeGgJ{~h2|?IWC-a3xXmR!%ipC-}_PurE_sPIYjvBT7E(@~jX`H3#ia#v-{Y(%Ds1 zvP^QPMLDw1=c>T~RA%Z}TBCU9u$ji-#@yEkvr^ zeiJksII=hl?~OG6#S=OY1use(A6)xUT|&i*c%I@j$@m-veX&!QMtTbRA}(Z&nhi0| zwubqy974VbT}CFgb`Fi_4e&7pjgag78yS-8e2u@zb-u3ObwEyfuCyY~`DuvZ<-vI8 zO7RzK0|li&b%Ni28a}ejRkQA@!)Xa}b6Y1MM{k)uPQ>OyEA*Czg<;+*SElT>_Y*0> zxp)EGgk0JM7rAoPU+{)2guLE}T>r~oy?Y%YhbK7m<=}nxIKe8Z&Ff#4ufYOcsm>8mA~}HkKxxTW|jZG(d0v_XZQJUDitoOr+Qg4&i_QZyb@w98SCV zidCU$X>w(UTq9Q*y2N09Xh|Y5q&UMZPC7#tF~x& z(ErsItzcrac?WkOE-$|3fzR7o9UeZYV|94gnZye^A?6)Mn)7goex8!dZkdwlTrEax4r-i;iYm&K(b>)s#&9_*%ULEC1ec&E9&@RT zIXq7qcsvzCQ17t35FNaa>f5Zm>f4?2XdGdEdoA*%zWonif_7S5HtH0K$0PLEe^Z|I*nbPp#p8tMv1QgC#jAPhJmDW$NO_p7 z>g3Eep2kAfdBVm#dg2eCeYwbYB3AG?b+f0v?IA6WyC(Oj{dPkf)kzXg*GkP3dFoaF zNtQvK17GzU$F=-nzd9I?^4H;JgY$I65NMeX z6)flUb2B6IsV|1L&Huk}Qjhi-D>p+!$!3gb#HL_)6ub$8VQ{5lQBYrbdbH2VQ=p2e z)9}wpVfR#>ZYFo{Fe8$ttA)ZtTD!i!=RKUKp6_!f1FcZ_0(Ym!eREM98vp0vFB<>n z<<}Pu7W8%228M%z`|W*cD|CH2yyHLL&$&um&ss=vVTDfc$=0xs)%oU+Z#(Ga{z9=% zb5L;sF-?uNvhWg^KR(JbY5ur2U#%|JvJ5?c3?Z$zDqk%>&JJ*viq}{*qW3E33zr}7 zu?%np>r;-eDk;8TnY8?PRepMjGf%wA(*Hk&ph@hN`MybPv%$_@=GlA|Zw~%yZ)g5D zUoAqakSY%}*Jw5nXz=yB(Fuy^nNm^G)xmWx@H(^z;Z&eDc@pSm?ZoU+aY&9FsU7|z zM{3uJ94X`?&0wVn7n{SpmMonJcMBQyjc!lQTcv% zppV?tLv2f0c9PMFY%Tng$Te_@;i?mEx%j7yX6B8Zlk35-rUqz% zp1kLFRyR@eStS_8W}Dfa)oiji{Kc;Z@kW(h=e)#B@2n=1fUU{dS(8cl;1)d!kCA(3 z!?Yp!U+tqwLV95_Kd_1=;hZ`W(i`{6&gzZ(^{f&}xWbZfjgrvDB!tUM_@w0wsyliu6_*28xd%=gqx_+W9SprE95?u!c8Pw833>&TP> z);|120c)QupW$?cmOovz&(Q2$!Cs)VDf?q7I2$jd8Dr$0OJQ_h7Mw{Bv&VE% zOM0JJ^rroe;G(C08<1)GxI7S?OI&V6E^TCWf}^8&I=DoX7vKkjIMJK-y}>21?P0ro ztPTce6RTawDqbc>hIz!%;1blTT|vC)QTrdkMTyt1z-!5XRb3*w1{s-H{i;}1f6>$> zVuMQ%t6v!_Tr!39Bj}E}tM*Z6--P7sa%aBTxvLtLMqch5lynvyl8;KCXb<&`O8Az& zPoNYd<&M#L4H}i8Ph{JAYN~udD%Ht)KoZ56N}>3y%zNDFk`;GcIHiUJHLQe0RnI)|f=$du3M&-^P4dev>mn z1dzuuDR;IfPH3ubb?2HMt#8rE*s7wW;g~?Wx8AEWYVanYpQBK`7FfrE+U4bZIvEa4 zDsUv$96aQiV~Fsc>iSv?lD=X6z1EN9k~U++vZ#3@#nba~R!9Tn@ z5Jj)(W}8jADP6|E-;lcepKeN*CzUP($os~38%wp6Nw3uN8Mh#1S`X9%Dv~k_0_#}H ze&Nx z=c04oXesm_rBEAlPPlUoXx+xD^>;dx#41*iF3?s@=$K|c+fBWtd!FUegy3n5Y)vS# z^mJ}jH}!Nbh_GAc=0#_i??Y?w>D-|}!q(Hd_blpP0DF8X7a%mfltb$HQjSxHIYpXG zUX+pvp9-hRUx2Fo&cRa2IVOw0nGivKVZAvIs6&1c*68C$-hEPI-c->IPK>HfZ{A$1CC&CKxs7 zl+~b9ECU-v@6025sCVYJ9@>+rZ#D0s>=O@v!9J1PKGw7HCOwpafC059fPud~L8&tY zPtZ;I!QYhXN1gr6vaV`xy11)a?2PDYEp{d|LCNKD$tNaYsvcpVF)#0-V#bxMIJIk; z)voJRy8``=Vn&5(mbjEv1y0sVVSW!K*n}QhFk0hm3M{VHIO4fL!Me(d$yv+cTHLOu zooQk}t3txkIAiF2=!K$Mb6|FOP}$)HmPwnL z56XqFI9=jFmafeZLRjwumKknPX7FFwDcbc{l;ncuSv@&MB32DwQy zv<$*idPvKAS8hU$dz6N^QoHbJ3b-Z17+dbHHQsf|uMJrCX9U z0d$!sdP!S{v>Sq|9a?|4UGDCXmScM@WVJBhB9recOto=#_)vai>_)6X-Jz*EiF*Y4 z$-h&($*APC=(rG?@NSg3?>j4PwRKs6?%Et-$(HWCz(cOxHz+~&I_Rvjonj@Val3m& z5*Dz85K0I}MHU=_%W5ZTo<8JsnHdqip`;D}X^HPiy=q9{*{J|FrLI%FXW5 z?&;nZ@Za*~-X35?ZwdZG-C1*tR2={6g%Ame@^r#=8EqMRl+0g4KAbqLo&4w{=iGWU zQ}VI%9$O9yP{*s{GFh^ps2uf)bFpzk?)k*Iw)rqDF+xc`G)9YPt<3t!!jo_YgA#TO zNzAXsB)OzpPOQxN%(=8pNE3oVwtO|Lz5L)aXL0-;%piWjdZ};%LMT)NW24;tx%1?- znJ8l!{*#9PxbUCJ_|F9RXSw$+(C~Hldc0WdRw{BUW#78on`32BWs-_2ldiF{7uuxy zD0Id`XPWAxVhv`IHgA&0I=U=mfLnDc{-Q3rvJtvy?IWk7<+&ry-))=&Lk4)ZH$w(^ zUQ3~5qsJppqn)~|FKfRs=3<}8RsHE4EqB#ATLwyU=H|SaBe`t8);H+0h3OL5mB~B1 zxZ(*Xp!dI>O$_4$S@^YcuK7W4KTLqc7lktJ8|NQke}c8>!SR2Y5=K?JETn+nQ3-jn z>iMP-^7OlD(PooA3NFBX+_~{0ud(}N>|p#NH-6`Y&!#ZeYlRzDL;I3MbRYC3aJJ!w z>e@e(J!Dy|5n=w=TbBPjFGoIk!uhnwz>?gx=zHDoAW>f5(?`7ugt~aW-S{5q^+&bP z?e_Qazv_1Tzf_~?c6$gLdEe=+4voM30ZxZ`0ZE6(2Yz(kZo5ni)mt4JU!zmxmY)DZ z;IcmI(0H-VK$)o%?7i4dAlKfJLT)fm{(N0#tQ`2W^EOeXIY_Xrg(VPzulKG#7M8%` z)3DHaD7fC~hm4-_q3bC?f!lhfEfX)XYS2>aNM~~&bw=|X{KX@kl4W@X;$2qsOs#8- zxxbHk;Qu+x&@>S581_3S0$$w^D4ZrvxxhA(e-#5Ox(v zW8`JawWjNSQ5{HhAhkV4%V=FO+aRl&yZW0@6%O*d$>d#$5v_G0i}2;(T7{9rTGtF{ z;=0rjdjm-q%NF6TVzG;*`lXH4v?7#{+btn~33uJn!W$0}c! zFgi4pqw1O9Efk&4mEb_mFL+&Mms`0Nr+P+&ErnJbx@1HjxqD1lgjgKN22!2L2}xR9 ztLZItG3CZJLn2(s@D0;`x)1uLWG-M+QnKpkTJbf%3fCkl@Wz~))K;#eVPXhl3Ze`XB`krwafsX$>)Kwo z;EcKj+s3)xty^$eP{By#2}?W&7=KNPtc-DulBeTckpVSBwbMG38rYBa&f^L-UEj#& z9V%aI<0@r#wCb?dTXr1K))j7u`!o$nmU#cG=y+NCO;iU_&9X=l_sJ&hT{i?&DRjCf zh=0~Cn49eC7*LRCSG|_eUF-`gZQj>UMlXP)8!n2!^~|N(hIFa8n*E8cy+)I7fvh}q z`IL6@$qufr;$#pPcnH+3qic}(j-``K^tHRcSSmI3J4r35Q@ZjSc(dQKAi(#FfOeA< zmn(p_zX7aMS}T;VmHEuteh50!y5^@8*N2Aa985G{?rp>Dxnovt1M1+@yiL8Z;y0=nH=w>atG+7QLza%;SN#|@g`LWj~sqB3P>0XZ^i z0??k|rqUBF+t=0Cm#kYe$F{Ut$FU{imxMi4V9K&T6FuUYKta{hb@Pb=#3d_~WsN!V z(yD{Y18zdo&Bj`F;9K{PWs^NAAIj>Dc`an$Y}dW!`vvOJJNzX$lbk6XB4m25YpN{x zIx9gY=ejBZ_;_QkD_#7-bm3own7@LdVR~d3vaGwSla0-e`pBZ|vf_Ji6$WYouhjihK=t6P#ktZ4O+&obKZ4k5||GxQ46)Gi92%+R9g{b82u7Zo7h+4uADpW`)gP06Tx35&!)$IVQ zsReR#PnRDJ?M zOuld;T3*-{*Fxs@PrKMVMgFC;xxrH81}2gYWP31`PxkM(G$~1we#nlGSnbAD^T$w9FR(+WgEgPfL zo4;8K{f&vE7239ckV4N`?K@Rib7odrgdsApMDQ*|%v%^kxFO*3>3EpVpHgZuj~7UK zV-K+rcOlGo3*@1b&cVihSvlM_A}&O%_Pzx#EnWS?%KBT-Co_T>)9%$Y2C;xMrOv5^t-zaKlg%F1^jLLIy* zEnK?0^n@3vxvmKL-YD1Q=5zfOF3Jn6g?eou*c2UEGlA5|8whUWVKQsnlD{)OxM+O*h<469nAFZ?_R zxnTpS81PYQDkiu(7-rJ}3L2%^0PUfEHJV`q)ZRn%0P1Khc}If@>-3zo9JzUd%PouN z+W}anG4%Jh(%;`9^=C&Zx&HoAZ95D41AG+uQ(2>`&g?uujo(0@>rU3bQXEn9>U3Cw zn9~L*kd(4u1y<}X$c1mq(cX>sf6*U&tX)43N=3IUM2@##+1KR!fbqD>VjA@(#{b zqbPkit(iP{g}re!X>I|TZp-KkM}XtH znolnj^dS<`*7IugaJBWk5`S92wLD5gpTLQ_cLjvR&S^8`{6((U19#PE>-n<9uDK#_ zU_d`lm$e(pdyUYEzNPq@2I1DH1Hzl@oEWI-;;y!JDWG7Wx)e|vm^;RRVQwjW2z$mr z^`+WbEFXMfmRUAX%|aK+W0$!)3l@xI@-kNs6A9xt6be{H+F_;3pEnIu7rAa>xwOH0 zgCc9*Jy2aBWOQMB7d{Dsgz0)FCk*?<6XLTpEuZ4N{RXOw3Z8-fJ>(wEY1bGKVr9i* zR|i3la9@JDYizRMCcE9-3U%P(LSjFp$KzYNW+3%Ga`maqm&6X1<)5DYd8Ny1dqwBK z`9*ZrM8Q%dxNuQCqss+XS5UCJx`Kkg)D;x42|mBR2}={~ON+h=_NDVRuDybJqcpB{ z{U!d?BB(R{ovfs-t_?pLWnfD5D3CL$nw6w=HyF__hyTIHr zCS(A#{xCD`66JCktN^;40SNimyLze9tuB|)_1(IDhvd=knz7p2??ys3{2p>K%SFF~ z=ir+5#7pY)Js?iL$BC2gg;1t9{1WSu4D&tHTP-Ku;PQlD0|J1I1UUb&JL!}C!E(a%Wwtd4?`uicL|$k!ggU*u~K zfHCk}#N5{)k3!t(f$DVaA2-8RCG)zPid$S!hSbx6g9DPXcqtn25s?Y0yuKIKfqf1^FLYLmxEw6j_5*_huzK92##EJ6I z3)yx95ZTuP3}g?04o25|9Z7TVd4cl+*Sn|kuPE7SY1R%=z#5?4@A+T?eONJazlxuR zi#ScyXM7Zxyl*^KAn%)izsUP0465Jzo(IGtd=Tuu*L8q<-?nuyhY?E|d+mISbgGa4 zng+sMDd)SyMaV=6vi3pyYvM-DhI!wrK`QXw6PP>3gbeb&N1?T=>@M**D}df-ZnRuv z6ZjCkS*RQIkTiPUDpr#`kG_ob)*$tO<878puJ?vT_e14+0dy-Lbag?=LeowD-jf#g z!yxM!z)!)1zqbhg5z43O830hGuOHQsIC)`mzS(N9tlVl(714u(I!okW&_LPWebNv$2w4)PL$MD}Jm~P%+)d~BBB8=0HFc4I3NM4)}pkwNVA)Lxv3H=J6y3HG; zdm+aDv`1ap;pM;`V*f*}oE~$=VATODQH8t%E?_#P$wpOX{wXn^2~M4_5_aPfgX_-G zrPQ1wo~HmK3g6yA3PY+=msXc*@EeEq)TntV#@WU&?;K1ZQuP#)9a=kw#IpwY`WmW* z`ugL@lKT1+_>21b6NBsT>mVxi^*&F#wuP8X_k6|$Fbk|1y2rn&Q+-mbd8@(OCFQci zCTF;uepl8b;secrb@l^;RcEga%pHS|&7XG-F;5RxeexHUPkr)~<%xeOPps1?fk5;o zILJJ}D(d-7>mka)a>OMrhsp`q-QfTUG z(H#hk@i|q%e4U+3}()6|kAUdeN0)%$3GV zuGWd~Vf%T9d6_8$I?SXvmf$nJMPEkU(lt^RbV_u`Ux5uGPrMR;ktbd`q`vv}!&_b3 zL-=3yHaNOm8>kvs1d?uJ_Nt+%YC(=xRSWBkZ}9%h%p=+2Ewr6CpRh;~FToYc^^jUb!@>SDa4t@%Fv~ zb|08^lQ^jJBwf0DcPIiA#>w2fhr7g4maA{xK@mbH+&>g=?@bcFvrU7&>d5GeOa2Q;C zn7BDa$?WO*9Ro`GcTbasU~$s9b&D^c(FAVzcpya!>g5qkrMV<{gdg27Z1*r&7qsY@ zBKERc5Jmw3=Ia@`@I@QihJSaM!Z$=0P>=?2fs^nJw-2KisA3zdu2!1(!QU6*i#Y#I zEi@k)Mo%@(hw1;_YhzM4Lw$_;U@Xke0W=)3!V~RB4_=_S<`0)B7&CN$#Z-f{w z?m6nZMs&pbb%u)so$BMgrh#wn$U`e0JrOB)U*~Brrym*X6qs{>4=kKL=%?urU{Z zQP`L}qMoo}l*t3fGrG%zTU`k<>NnRFAwtN3-&`APmAYltWaSo}q9!YqBh)K|YjuWC z?na3#Rkx&06&o~heO3@3f~EJt5emQVMOMQfB8*Mz&$>pK&w|K^kX%oF-y~wZEUNZI z$^~D;bu*etu<|NYTron23O5!M6b7dz!h*>;nT*U;{L4z>v zzGqp!nMC9C^U==sw&R*Q*wznocR?qseHVhcJBO(>rh3TPvNbf}Y&`w`;PQF;XGkW$A1RdPds1jc)58rQ1k~dy%L=U)+OdVSAcp8BQo= zp}+zo0)t?TtlI!QW5j6JxlfZ>AEn5+n+bi7-HCfy!Fxhb6{Qszxxvc%duOH z8KQzoOwA?TEX33R-4OWQ?IYC!=nhs1W4m#yZl+Yt6s(yNSF^^A{zi&btUfVKhWUoE z!Y`(=P#VJBpQI#kh<(8oNXk8Rq$B{mFW{?Ib26Ob2&+U=9@bKRr=+woDd8OrVBjVG zf#%^6{9{HYFT&kP@B|eCQTh+G^m|Bp^Uo0qB7%9PI)-HZ!)Gt-#Q?;0yWCsNwuR>O9g*7 zR&%hT-OPc#;&h^qt#?e3+%ngBOf1lOYMD-8opS*I-#x;dSriO`w>o6;m4U@I1l|L| z#S1mO-JKpxYpqW^+FA z3H$Cua8Y9MjgQ6eESp$-LoDJI@LiK)zl}*t>*rrSzzE_(xOYiG1toE5S8O#TgJlz! zcE#!owS;-sgXL0dlB*XFFp2{kLy&i+!6k`J5wOWyczKrymP=fUilwnFqnB93GPJrN z*RL*|{D$ySbQj;)HdLPO=E9>#6B%7m-p1H}pi>t8jeGu;51H;&b%v8=*YE{qbT*HWFy^}47;>9s;ezaM6i}OV z{8Vs7(lIX=tYd|xw~f`)I%f5>jv=%_>-wAj0waCtIUzn}RY}&e?{fVr{!nLHDkdzw zpG(xS&l#PqRQyx0iqF+mF&)W%Um}e=or&UmMnRwd#Ew$uKXIe9uhJwVTCVNyoAPxW zrIxzPeClo$yi^#~(_M$Qbq3UJlsW_I!D!J(P3J%$IGqD=!QmVz zP3CUznF*dr9g?YyISWfAXPGSKG8sboiS?o{_;#?l+r3=qO~f5QU?Vj_#=z4L9QLBygube&kN#jCY5f^IjcG6bgtE$Hlnq#0MLqP4v=ggeqDf#^~du7Nsv2cyo~!BdwEaSstZLAT>ie>=c7--$^~9Nms_ zrOGVhbgt^Y1gp2SRKe;k)46Kksj!-|LNz6ld%p#%cd6AD;6QC*99UcGq#h{hG+gjh ze}l}?rRvEW#3TAP_x@tFFyC8e_Z0r3`L`D=it;DChc-#$=<7E*~*w``SrJyIOkJ$z00Ws8?DojLnn?@)L(Z=orD zy%O$~Tlana0{A@x3(8eP^HzvcA?g1>;+aGH%IAjVC3a-@H3LYfxojld`zqKiT8#1Y zQ4@OV$KhjSN>N@>_oxO*=?FzQ3RisPgLB^{Vo@+3u|7=+N-|UCLv# z-HXLQKgqsw<2;xe6S`QTPQ_msR2l_ctmFki7kk2$Rxa1ib>Ao$8(H{`CsmfLa=6Ty z06V`54s4@F=S7RzS`w76$S9Ym=edVpMKv18+S6 zw*?4QB!@3>pEPe9qn?PtUw9&xwC?Y=1GmA~(~YprV@$d7y^h)9pRBE`49`sSg)s>D z)l+tO=lW=K2h`h=o-flEyVqZQ^Dl#^Wp`G_6o*}+wb<6j;N4EA}A6&0i*P~}48^l z8i)^f4UZ3D1E8$#vE8)H{dj=Y$`^Wi%caZRABc>xzAo2Srqp=)i%u+I)jH1@1HQ?A zxqHM&w@ycS$*pS|b{hq3JXS{C=5DSKi5yqDuNFfz8(IFG+d?D?!Q4A|tc6I_?<#kJ z7#CcR5Q#$9Q;0;#SG%`~OIfvJSG&iU^TsMLqFL}4!HC{}I;EeuA*fVXCGd_mmUoF@ z8PLP5&pB3(#ciW*qMGGKU*}$6RH7>T%hN9dQk9QE?RDNsB?mIPD(9;A98}1lVL}CAFX( z$0^jNJeEs(h78=+GG@tDH^5Ax9z#VJdLC@*odB{+qvh&2dHeaO2*Juq=zXbX>R7d{ z6}8%v=bYCap4z~`g_YEv)->de|Mej^O&Cj;V3P)85#C`Pm_P$<-!am-GVfV2lgs_A zJ5?U+kvtzZ<`3QM&Jc@PX5sUm+2(?AEaqG_PE8JpJ)Q6Z-{Ma8sXZF0+q5)ij#Cg$ zx1%7uA!S-Jh#jA2#i`hHw@#K2dx~Vy?H4_5@^#*pwg6^u-ZVs3f7mQvJjs|9KH({{ zJ%$N1#~wTukD8n^Dx&28*=qdVP359NXUl;!BoGX84So;dm%BjC$NL)cgos5O?Q*3oVg2mow{phfQ@-H(#5R8X%Dx z0q*P*ZN55AEs6q|2I(?nz;J6JYz`m6_?H(**6b<(u5I z%$x~2w1xG7VrP0Z&5z`g!hn@Ht8bFG8oMI}BMa|~vyzXx-2uF{vsIubf}HKP$Djkv zVX~03%>Y?2EX-gT+SyisaO7;2EE{!gUd!5G-lmitU_##yOLGc-uB1@v3j4tWm1gHCZy$%P2$>BI*?QmcKayV`P?QnHc$>DhFmKWStn8_1m`X+a# zNSzquY8@srSIeBJT&-n*tNo9B?_}3*$;{U*U}44uW~tJ+Yo~QY_1HMI>9UdjZ+*v@4RLC*71bjn-2~AHsL9J(K9%>@xQyN0O}g!5tyXUU6U6 zWGggWE?HrBiyEc^T7JFAjA-tes30VQY`8fgIS1)Fdp{0x6^86754wilHRr7y}Tg?o@%LVD&wnFwklXT~uExs%U3puyi>P`2J-2BXugc8_+}UC$6PZ-? z3RBfvq^jV+i?}c3bGiL^lVzSQ+acyK z<}_B!;EJeFiU^uozObw_ti9hn(OFhpk=F1iHw`%AC^3zRqV;fnupTB`O`gE@aJNnj z(8K$O$3@7`_vWa`Ty{-b3z;}41FqwK3yR?BsphuHct_90tw9QT$x_Ivuda_Vls;m) zV}P0d+5CSX-Y)!kn9N;$qM5v_7I51e8v8d}TG<>@D<1`G<#|g1&v31LqZ3gp0Erd# z4TNi$R?x2Hnu%)H@)nq8;I3te8IAYmiE_!?IfY?urdU8`?WX9SL-VURxhK*CXUl49 z6js@6)(C4!NmboombCljfWB~H;{OBHy;uEOY zZStD`xLsl!lS(W0^I*lksGDkRR*GHmyZd@^idAns#r~kVnVW+YJ0dYVLS8+=)fFT7 z`W+{1a`%5yTFL6=_U7`Yv+gI%xTy*-uFX{4AxYn{a>?H?4Wt`ev`LjRm3%p1o>gIb zh5^;qa`QR&#Uk7JJ;ZD^RX+5WyR&G;WYJpggsI$pZ75-Xv&B>bixY!ct;SO>AURn~ zXhg6ac58tr!Y~(2RakKqj5F!((qP?Pt#sEKBmO#*Zm`3Cw%S3Kpu{B?Ia$@Zn>SS! z&U7VTiQpy^FK})ALH<*(1)fO5mj@A+AUZZ!P=091=hfTeR)}Cy$a+)kj_Oy{jH`(LN zRZtMWI#-NTdA#YV*}w_Rsm!m%EjmRVzI+ttnQOaIr^3N5;?DEFk3GBZ_YyTsb;{e`=Mps zZ&@x`7c$7YAF>RxZU{lWA54>5wx>-K#&pn)I_{H1vshV0W(a+l3HQ{19?F)zAd zx-#T?mP>|&j6S2YyNMfE26|E45}n|a*}GbnXM2*21@f53GYf*lpfpb>xMTBw#St^ z)yH~GV~qZr2YO=VZf~nt8PU`8u((IFk#v>it}^Sg%tn?&al7PcBg42$8ht&z#U_@C zS6R%vKr46!<#uWG^Tf-jtFy<6{j3nt-shwJ3Cq#6_bJ-nuuP)8kJFwk&a-@~oIAWY z(}}I5PJ3ACZh^HZ%NT|wNSTWSRr*Q<}&6|@pK!8 z?#1LGH+t*Uqg?sdwCSmFa(91Ee$s6yCikx8T5h;XhLMWa{Dn+nT0OP;D*Ixu-_raJ zEZol4S5qCs-Yt*Q$rA68h|!opqtj7T_Z^vJ*jnLwP5is3ID701cb<2&SN#+tIH68K$kMk^M_c^lxIK1YWvjJIqZWOmS=y&vPpMvtK6@!bIa*D5nKc%kB^$0 z9&L^;SNIGi5CI6E;cea=90T6O1U&{k9rn#kD2gCZ$5~O_3NruAT5g^OSGY7aKQJ^B z3e-_>t|mD{B3N}8+J?%qIYv|S)0ygW$eT0O<&YBS;rJql4Owih&PPqZm@v)y#WgZM zZ5E`^6f7No(G)CwR((^j-JcGCgTG5XZwAkc-xdR~dYvh8Kb`8If;A8`5C-V;Vv?py zb1rk-EOk%16fW=r zq*0j6rzgF&RMzx_cFwDGvOIH{=VEVfK*K9!RmTOTKXN_ey`TL&uVaYv zN#V6c?~OST!j={;&O9_K$ruz!=s`w^aLQBxpTb_xKmnK9SBksWrZ*tTOEOc!SQBAJ zl1(IfV9+K~jI^nVEF37C$cSm_cgA`!nKzN^m<%|B|HoLNQUuHdK-P8VV+Tb!;NC@)j57)YpPqG*e|Ix7M)4FQ%dRRVRl0LxCQBpmmf2Jw)Ux-nBH7MDEju}oP|Jd|3mqic)foh}e6fx< zWor&n1`BC0=>LWtL6@0~Uw6@eZAOA1v_}VHBqs#}0Epq_KmstURH=(`V^!q|!HhAH zy#qaAs$_!y3?u}z*s*dCd8x9kKce4M9AsTA7QjP;HVtn@o8Li^O5iZ7tR zIJA@1V6ZQs8saYssD^_npn`5xkA_BxUvKzuMfxk12d&RmrmrzPNXTl)^b)QGOCZ~O z21}qQhswB0F(%+OO&bAU0~>4HrHHHZmgpcXy>||lh24cb5I4VdM>!^f0*fV>EY zS4CxVa`IrClkZ%co~aiNmQL=QpAs!Lu1#+idndBs9!^y}t(g}A+dZk0t9g-;tdS|F zUo#X{zA>~)CCfS3a!jCp2TY@|?Dnv7v~b=D09yEdU?U^x^58(J@MHfp_8DHTENY$EyBOZv9Ka-O#woQ1e` zO9or(qKF|XX6cPpI40OkK#+B=ArflG!^`6=)Gj4;;88mDP8ywB^}|_J;aKWbp0zyM^JSWhDfNoNxVEtH;zj;lcY14bRuDQdQuaC z9^k|FXhx>r?(}8`Pf$i3X^GumimfjJcj20jMH`zp^ML0j#(DD#$dE?2L->n2qeFmA zgdfe~r)Ki}HEv(}!OC4w+#UKwZ#BLu429zRK`-K}V`Lm!>WVzU52b z(z5{Teo<^#XB33F_vaxJvCbF@7O;9z>Wo5%%FZYR{^A_GsC;0gXwx9=CL<}ZXk0*1 zg;aNAV9}NVMG2>_TR^FhE<<&Z-@dR#7|Wo+vY=jPw>DIw)Qw=7w0GZSs6<@zNlXBB zvsfuQ7?=*U>4olMmP5qx&_SP0)GdIzb*u=nfLuI!(0wcjo$h&7idY;(@jvNMS$yJf za3}+(JIU%22gtQ?AYi&5St;W1gHMTTyvl7#i66kq_{_L2%O&cN;irx(ohl-NMwoY? zeRWF&NRw&lIic1$gm@>^5sjC5YKeJ?$)S3tSB^N}mnTMuTaTuDVt>ZS<0H-q6^gzQ z=dqNhjaE!FJc?+2HCsVLvxOqhhn`Lh;~|z#;}5~j6?tV}{W!~|z17KL>N{}jRb6T<_R7^*CYJQA#<0T%z%(d& zhyIXPjzFA|8i9B!AxM;ek#U=`jj;uT!U6Pcm_n|wAm>;`fY@uBoM$}4Dna;Ihs?a3 z&pfw*b_#OtD65zEUV0y!N&H zUPc0OIuQsUez*PxRL7Hsw-{YKY0!^yx*q^{#Fb-ots^uf{GGe8!3jg8T1P)%F`Dyn zi>ct?sSq5!jX$^$0gcVVlw)W{=3AXvQ)iD8_|!c?4#qLnGpie3nBl>jYK&0nzJ`APtQ0*Y13TrkPqZ zaqgS+7=trVHmsC7@789SwzB?yL(h7I6oUAU|1N!}@idc*RGDk3GM8nLDqDQ2Y-2g3 z$|kPL{wh^jXQ?t*s=^s4RVt;{yQ^8Y!Bdqgv!yD~|DkWbGQMYmkuDc3T`sT;Y^#JM zS96#|k_#QCLWk4|8OA&lIZUo;c+gvLa{pTTT#)*3CQ6@5se~rSQ_n%)YQ zzJO@eOZLS@FWi=*-6bHsUC8ZTYo&89mmJX~x?utvaX0IQ!(@-~C@+f3h!I@LNm9wm zJ;uYs}^AY40{nu5nNsqM(;&w0>lm#FKl8 zmq+0aap8^y5$^C`>8Y`547Tv(o>g>UVuE;bEQPh{1D4<$rQq--L$debu6mfkCO2%Q z!zWtY#JJL_F&t88rBf4s(MqT0@TyiiZ~dEIUTLMX=q1N}MpLZq+cd?!yR7snH+EEs z{x!{W)mqcQ*4?PkMb}6W_<0@O_Zr!XhuXN)JR(2RalO%&Wy%eo;qoe%hh;zr_lRn& z5`3b1-J;NN#OhJQ)pQqj&CbKC}xnu^~rrA;#69# z#c`Pr8_O9}T6f?!rY596HnU9fhZrt~A52Lx1j`_QOjikhOD&fEn8N(Qmmf{(t8n^j zmTPVvo*bbcwOq3p$#K_ARrIB6SV90p=9-VN7P;mm{vy|$tkN}Kggf?EcFp;^j(*0E zjJ?|G{z0YsWGFsVE#C;bj0H~?L&eUX?njK8BS37cnfkq>Ya`?)a|4!3?tu()kH#|4 zJ<&lV^k9o8nd+=9QzEw_va(uol=X71KHVbL5I3aZes10Y5OjoH;tF5gcsUy?J_?oS@} zun9HNy?wij(lyRJxl1i=>zDBE?h+gG?(RNpOh_SY%$`X4KKRFvjfp7?8x!-qgaOwV z?vo%krq)*+zs_;X6+RY%-5`nfH^mMt2k3{1h>}GhT&?h~IlZ5F27l3A`-kz)FWr}} zgO>;C((9x6i!LbMfXCQ$4ImnilIXPaQQY{alaOTG%A?)tcW|{&y9!OB(6`j#PQhQ) z)Gy#Kh$@l2IDU$bU|j>#i>Emlm~Syp{1NpY$+n*9g)#NEZ|)+ zLgbxD8LWLJR>wQ?wJ*fwct;0D$2tQ2Xavp=n}|y>lU&yZrvnF^hubz5uO&F{jGm>$ z#$VJ$dh_a(ew@Bd4#w^)lew7>@DR%C@R8wq9b^Kv+E)uPufH!X{P{5mJ z8zzYqF!!;VVE|*XE634lanCyNRJ-?mS9&~NzQA$6IIzK4*DlKCnb`w6ap8O>IDe(F zF6Pfka0*~oAdbJ77ENfJAuh+?+5n-sp_L9O@Pl!RxR6F+Vywq8RE#*_F-4z8-N|CO z$59NhT7P;REzH?Ai(HrVAY8BoV^~i{`@IL3z7_#F#ORF6bnLpqPRl22Q@EdbFbg7O z8fOdLd8hiDFoh2tMJPu*eNutM=zJmDG0S|8SJP&vb!_166_&0Ag=3LfqmV`X{8a$c z$rJKcC3Vwl6v~r3N0nP~m3yi-!t`Kxsa}i)oEgx&eq$ z|C=1wn-BAh1gw95q1?a5`nZ2xg$U>7I5&oPvkS#LZ#WZ7UPw&so}Qrp3Ehw89OlQI z%tl5uZCQf9@V`FHNgzTG1;H5h`1{)yYk)avuEZj~?(M|&DG3BR8L|<~c)3=D!`#gC zcYT)ekiNc9ocP+=LElp-w^oQdZ3qKfgq#$IzD%h`e^Y=ct#$R4g%WP^l|UVqaft|S zlA6(5JQqHg0~rN%I`%cH)wwlX)6bXbg%6$?;B}A8XS5m6tC2D65nH zVSAGnJ~DegeaL&aBXl;T)sQ$|Wu4){x`99bnWNL_p>p~d3Q zzD^efVd;hhG&_5+3w$y8ZpXA5>%k@jXl8D-SqBHKwSjKlHBw?6u+}D?o8{;!3Vz5m z8Kl`e-5u2mdKi40YOBSOdmN3-)m$tZ&|bn6KA^3Tav~&`zH}sqH8VfpwW&dt_PGkO zy=Ui0@Ansj%@M2vCIMlh_nQgL#o>_`JtFJP1i>669$(DwLb!lU;9xqegkHFY_|l9lRx6(1EM?wAms=W?W)-SS84xWxnyMj#*YTr z|0iaROP2kghtsFz0@H(KeLeeCv%l_qRKhd?H=FI>=>m3s=bL`f; zJxV}n<~>{-G_#)ns2oW8O6!{3x*~f;W;RiRm$s3j!V`V+i4ziJC}fL zxY@E{g|uNfx1lcT-4T;0ibgnKY1a2bwD{+Rs5;{9?vAkP&Up3pmKE1?fyj!l2U>BB zrQT}L;fB-u}f^-%V)NAmO=mGRw0ANqnNzQ{oT^=S2C!?Nz<}W^maO= zajh%Pj&ju2^zNew3(dT@lE!xjYTQq191us}&Tr(4qf-D?eN`G_=TWjDcIHA+CpR)s zWB6_{DtE^y1q`P>?oZ3GeZwfa=w)u=49L&x0=3>PwYK#@i=R)H9T4qM zW={LMw!}TVD$18y%9nE4Ncooom0u|pUB;Dv-=F4Fo^V)T>Oo7vi8v_8rQlfn*)clE zB*;5vq(nXo9W9a1%sQiagTS4RezhMkMD{Fb6L?`ec39x(&&i4^XInp1dqMcLoM^3| z=J;OIJ)`AB3;xnX>v+g*Vd9VfB+H2wJnl8b@fnWS^lqaG3(dU8rWTIx`KZ&4f;IyB zjt)AnD!TG6a+%giWIyG|GCOg`-bl7mB zjdc##L0hqL!I;t7ixUeS@cm9eJgPW5#}Th-+k`gH;WBq{sj0baVdgpz#9Wc9 zVH#Rg;z+B8&GZeU2_?$hz}b`0-Uu|>TBc5^Wi*0`8ou}{8toH17iqK#FxnVRulX1u zL7AbC@fL$~nvlojoF?)y3acvm(d*@HG#>)gmEx1Z4%9OJ-_eBmWd2*pa7ic~kG8*< zO232QjP%21ORmDzh&H|XV{(EB99X1PtY6`{P1E~;eUdYrWE2rf7oomuL*!R*1AVr(^-7-*tG&=xD9_ith4#17Mpj~pxX!&rUe4XR8eMwEbbN^ZIC^SFf65*Csr}tS3 zc%050PFK6nohY&{WyUQ2#XZXWmN5{8vs1h2UqJ)-J+X!PJI|q=LCDGfF6l14&KTUH zPBo1&tcgr5bPmu%$H*oUHAdcgVvdGQiczVpi29nO#^zU?I_*szUf^_UP!CY-%}h?2 zcBWhw<t+hKJII+il^C-~BpG zbd5@^rS}>mism_+NN}#+W8|LOmnbxEbtkwM2+m~=;F43Do4wO9#_Y$F5uMAP0s(uA zpaViq(Q-HnOXrQ#kqDhPK7qgJyzvR}1zr!o7I*&$o@-g5ydM7kF2^ZbpjAA#+fiRL zS94J)$dk2>_P0&oS5B%{a&?+c8E)*D0|zA zg;P~V8B)h6+rjHnl+l&IpRF+am1k3!{b-TCW^5H<29znx?35wQqJmh_yIqt&(mg}Tsld<&r%FN(7)chcan%_-4$5#i@!OSK+=LAN0P}UH$Pb4+b7mcw+xOiZX zBTZa<-ceKUIaY@Fj=$Xv^9QDkIM`D7ZN- zE6}{#LB74IU8Bcg4GQk@_=|#jJXi^WJDLZ#ubvnq`_rf+j<4-uUgt%JQ!^JT2?_*- zc?nCgs1$#86~f$x7xuonk+G4nzSeT-KAuA^g&d0YS3pthQD5UFDAr#ZD|^%vW2@>> zkvhiuT3%Q7sQ1R@=oiM);_w2g66>_+2)>|oO!O`whUYJ-R!KP)~+%N7Z5Ig-p~l_+Ogly443xom$@bG>S* zsqx=4PL476RU+NZBHdq-t~ADkfQiM*_z{6ZV-pM#T;4U%rmzV<1uHceWI(50#~rQo zY2#$OBW${6&rZ=s0TZQNbE}aYe!h zj<%YuoeP>bZT!$N(>!OB9_LM;vJ{JXarNg-Fr@hr#I~MvJYoLE*a$ih{CS)_P`m_x zD_lLzi1EPQ*EH}fQ8(cu^nli7Hsv`~7joz^4A#ZN#2`v|FM{RgI5&w!pE@$cCvP~T zOkPT!CVn)I;w{>m)Bxshd*nsui5VQWvkhp%S$tx z=f)>i<2-_l*~rZ2WZ@7lR>Yrk^f8C>WIBW!gei0g2R5KXxa-b4-ZLljf^_~ie!M(? z8_#p_{Hg zUR-v#V+~#%I^0x|l^yBQp8@vpF2H<_XJcQk9Z=NuSK(z1ybCZGc~Lmh*&K;ezgWVn z%c%=OYn_JZIp<6=&+=@N{gk4veM7RFj5r+Vc1b7d1esJK&RuYH(Dey~L1fmL0809z zl&D=Jj{IcbFP#9d^OIYIAzx_@k^iluRS3u_frz-kkYoebGLtz2dD8~bwXiZG5t+QQ zAZ-EpOu}pFttJo@k$D5BK|)?1C}evnBzeYnY#q@({d%oL-1>vVV`l>=@7;6=7CJn& z1q&UX2Bt)dJMKxp$+RWo;VG3TJ*N9>r0hbytaGyi^)PtYLU(|!2pHS6W%*}El!s59ABNm zOVU%#aXbeXCs9EKfX~i5W3?YespcF3^P&jd*;22VD2FD1gt*RJLaCq6NgBvwQfwP`~96`W$o32~eWL*6Zu z(DAXNUw%rIm}xp&#hOT-d+h>KUE+u0uCUpWi$Qae>Rk*XTUcNbcXHZlV$z={Cq%hB z8<;>nIvB?f7GXZd%h9}K= zu)2Rjl6|D6N1ruG0!07^8q91QXfO**i57qok!|Be7lB4hk{5yc051fH=ru_`n=;?y zLeofg98+w16GFrf5Fv*W)67e}0_pLcrNr6f z0tKXXpScw$(SLV(j%iCFW44$qjhQ@Ij<&tPJviFhBMV2{f)$BI6bo@KJ&v|hksI|q zkK-@uc^;o!)o5FHndX{9fYyBVlv@Em~Y!kW6$%(WZCn)3V&_D5aySa%AOA>>qCZUX;douM?g_T zhA^Y2fFXRLhKsh4`cou)gPF{;Xr)(w3IRiyIkucb>0TXjXr<>98Id8(4!juAz8z>! z?Q>5HgXa+G+ljP9g)j%(vXMSy+vp=KgjvLk5&eli+2`^sVlZ)v0);SF*s_rUWZM`3 zD#QSrl(eATHAQqCoO!)1WB%aG?%EWBgD_82q6;MI_KD^7LfiDAF|BnW6tU zMNS_G`eA&wGbgqJeac6Xh1|)svONRP59XgXG4Oh6$@r{ltZY?;H#C3awACmQQN-d1 zyDTFdQ>e?T5c&O_@P!&b?t|&#rD-flE0SYL8qcAzgrFa8DUzM=tvs7Ly1XJem~<%; z{m&)J$g*|9Hy6pb(`jOAo-@X@F`%KumO|G-5$?ep!CB$ltEsmRCXxLuya!uV#CtF& z@mjR+#LM_BQU}!WV?CI&d7b$!nmu3_lDghxxQ*{{<>?7U66L|%#w(EtH(4g!#B-Dh zUnUc#8$6dR_@ZUO<5gMk1S2(?v`Ttj* z1O6WyQvY%5T%h6OEYQe95sypXH+{Ua@99{;d|XatfjUiPZPdwdfho}ffg4O)GKKI@ zN{@u^(s!8maA`<|{KsVo=kpv=VVF;a5j=}jc-T^5TvaLzwp0M>q=Jn)sSubFEfBE5 zv?Y@Yoge3}_{uEj(vS+^K;oC7Vu2pLK8Ph1POee3Y))r~gP^Nb9+{-T#EiH!e z;v|ySE)rb#K~#q6(+HKpoWaYJV2@jZl}N#8F60|Q7Ce~&RU}HJkJ{QXU0LEwqBYh_o(#gz|l9#$$gY* zxPb?sD8X~l`qSn3)Q}e=k3~$k`l#ta&Ms+yLKe7-cZoAs1Jw1?2{KI z<$XM$Oe0hvWov}$IbEJD^yZXli0WZc9t6B`h+;QycWPdH)alk|O_y_Qz@Mn6O_%#}7tsiOmi;leN?D8a`=fb^6$Z$GjslmWDinUp z@E3*OvguWY-wUIi?*|FLlaDzcH1}|$Q26a+DHh-2lUE`9;G5L7Mfib~Mxx(=)M4hU zjE#)J7pG$kUT^RW3PH%A5WEx~*-rl){)1a3U-DuUg6A!7UJ4e1v{wRzaE%@vL`Clr z@C-U{%XFXfV1bk%KaC z2gc(sa$x)uRXOmL$<7agIPm-w=RmVH*7vnoa$pOVV(~5h_$oNihfEP89oUhvkq*4$ z3E7GCO)$Wb2j!hg_%kMLsXL2Zc8ikj>FT{*TrPFS z>RC^aBYn5j#F;71CWue}nB`n(9^$;or_Zt!i+Ayv>ig7(-rrc5vz?2~4;U9Znb+P$ zk95@EenRdN6&x?9EgmU$_A`H|RP-BF6gDBEf=KK=CeF@rek4!edA>Y>-!C1;PT(8P z0A0ytO=e&p>Ww{yY`L2ba5->yqGH5{ISn;48LRr5g<4?c%#Z_EbDmAHmnHI+JFPqL zZDz=@Yl5YG^9~xs+%x1V%gyVnLG0ccauDmmvxz)>G15=|K}p_V5v?*EBUBvKzy;Yxs5n2w~#oFWj5lp+)4(ih4Zc}zffGLJ{XX|WRo8Z zFt@WLJf_aqD`pUSzj=`7gVMPi9YiD`;4E$I? z5LTa9tUj&8>Lg?J)&CVM`Jn)tTK*3On16FdaA@C2-#$ZrBp|Rt7qi|>7Nowi_<;bs zB6RD&lFFM={_F)MmqNwi=kzc!xzrgN&CL(AX%(<(27MwRiZ>Ns-ZAVeJ4auSf>77h z5`R(G)pBN#;Yi)NDt zSszJPfy6Iy75MN=Aca7AIwR>0@Q)wA1XKL@CFzvsCAf!H1rn4;Z&e^pT<2&l{#sw1 zm+%q*WQrY00-$;R#OuU_Q}7O6ai%NOi|~>sT{V3QFPqVgw~z3O0Np_P5f57FtoJKC z$e`oDr*XfPws1efIU!9nx8UT0W-VFR-_ZzPdq4h!Zj@knYU2$skl|+$d28+4Ma(9r z(|8;$MD~P(?qkmO5~yX0O2uCoBE@5`bSP1XJRz?EKo~91x@>5iT_kNed~P zsV_*llxD0|0!Xp&<-5Kb5XS2#<%yzUwXSp*`FMNRt>S~NfX!l)fZk#86ra`=SE{wd zW1?jm_yIH)9bR>|F)lIPr{=l_ z=-+|b2+nz_R#7Cpv+lafdFl%LVbUJN0lb3qb?fLe;W|-%_gLd=#<9P{b*DHh^qLLA zXMqv;IQj)N&!=Ebd>%BxM^|6&ac(jau#^g*P7S?>ks7bp6mXubdi2)g%uL)9fcLfA zt_wr6;DZnSm6_tiHz~L4M}T;T)DF=>oB@>a^<7g@@=r{XelJj+3X9H&ZrPDW54#lY z1;tDESr{+5O}+aAMdH-uBRrnsbAB~v#9-~)MEMV2CsxEBbY^M##91-|;IBUdF0L9I zCKl90(s)hljMC8xW zeQ&7lJl-$00I8!F6#QFTTOmqcfWzArOcEI;@9wWv9}~H^ms;Ll4BBFp0MJMs@$4bz z6ytqXANm>yl~I9}PpHZiDhp<@PyxG9sEnH>LuE8@s47%OfsycYBCo#ae9K_I6(@GO zZW1S7a(-bnc~V6#7}iPnIGwIjsTefW^;PrxY-G_(&t6IvbzgN(FkFg*Ains$_UIsd zz0M~k#*Xtf=N==ERnzLYx@$L!BOky@sB}tr6993d6WY?F&hf_mfd%ie7sTVgD!A=> z)3vgO*Yl(nycjpta|vZk)i`T@`$!L|>mjEz%IIkk}Y!C>?q*$-5XnD2BC zgtZa)=tkAP0UYncJ#CV(4IuYqgqz`Utzlr|uI}?pRSSCbE zb8&oDOqTX5qg&%C+L-R=P?;`%Yg20imT)E;O`ihAt$rIt)f+#>x|Q^& z{IV_{*r&DjwkZ10*#s%mmu~3}Y04b%ViikDMD^%x~kqRunuG(y(%B=Eu&PZK*)1Gb|UVnRGp#7^&}m zQl7lD`owwEn90N?|4svO(ZADFhV<|1r!4=LsT}gJzLIOW)vn=<`qHPQgO{>uJ_l!O zP!(a$UtyVk2kS>T;dksFZVgq*!IkKegTImvzQE{`gTLS;e^RodgHcqvzr0k;KkvLt zH)e}Z&pT6$@Yw-TQfD@cl51!CqeQtBN#&h%#u!{WSgVAHW3F?5`JxzjBV( zC(M=~7MjG0lj+8Bt!FZ=^KTu|Odma)jzEk;Rt>r{>&v9WXUkKW2WB(5dK-ILVG?PV zU8G&wniq>&_lBx(>c-bO;L*2#=Dv_^QEC9=_VMX|_&P?6N`yXT*N_n6H zoazAl7A%Hi<0}mmz5(C64Ej0zVjds3`~mYME?^y^ywFIE>VrIKQQQ}Q(W1DoIP$wQ z)trdb=;7#;neyRi&p(`-E6+vl`qO#Z9IIrXNw-yvB9$T{pLTWE#}>=WW201tPu}8Z zs=Z3-Auj#x6viS&T+U4hGcX8C@4{jWGcf&MXFFqUU_F}C1g|IOG;!CtYKw}s3H8LN zKb^NM8t58q9ArdrhNJH*mKV@=!C$<9HcxYPHBJPS3OR<7^k~_lp~~IgE?HK?s zkKgmS^D{<6&dSU zQQ}kPUdg!VE7&~?$7U6T_ zLKTfOg$C%7Mq{k&TTw^4W``utmAH~dD$AjvAQ8S^;a>`7&6PXS#G7`cfhl22W>(x? zjr|hp8fuH&MVYnq#&adWWIL3Et8uLo4HoGid!pF7?@pD64X*Rz8(ddM9D{KcFv-7D zl)e|5WAtJCaA-AqVFHcz3ybBqpJ!CZm(lKSkq@){0sp=l83qNcW$QtQoWQB&-k2bbb`7R_%*igJgm zojzhN4zZq!+*sGWn(;mpkF+{&X?2`skXB7@>G@*FcMxIcZt0n5{J^t)s}21duG?>O zX}J*|g+;9}gW8S9HP^qKE9bjkGAcCRrT4)R^XTBis6S7|H<_;PJQl@G<^_r3!c}Q* z?Mrbv83uu~Z}zPn7RVqz_r4Y(&FAT&@b;c5#`TPYno{R*Hn|`S9OnmUap{eFTS`7L zs0^)jF7;yl?hfCt%v^H8>^ zl=_;-HN++lO=`EylM_$bDl#hm%y7kMhEbv-kMs#G5%V`CHwk0uesw~UO2Fs%wWJi5 zO$sHzD^Fjyt7VGI*{&9q^@%N!`T&m;Tasfq52a2hCyguHm}agDgQt=@HA?*I&`qyL z=E^liuetJ;QV;sSgq00vogz%!vnEHzS8QzIdP+AYFlNvX!~WZS*p8?hw{}g&0HZHp zhy8RbS7@}2kkx_S2b{2XC#2f>V4;4$HAy!X*eP4vuk*l6uw8%Ex_grgBzJ9j3aE0G zcI$>Sj9PeHT-3%jSU*rAk<$PZv8^~h!IdJBX|ulZgb8O>Y6~kZ*A-LaG+2W$YK^nZ zF3=GT&`+_*(Z4B?FlxLh6y&)^Uis$!WBNzHpts{X<0HlyLg-FWvj4$a^)Zo;+W&zV z4asQ-uXqt=QX438zw&sEdh=B?fjFtgw%lX7Ip4>DaIM}E3H?Brc=xSgBK|hlk9v#w z1So5?WIV}I&E~TRN7qV!=&!wtZ@QQQpbrMx@vnQLs2JOnlQm z^#)A4RWF`Tz_G?$CJ34HDQ?asWKLU`71zZzraEyq!?NED#+dAv_1TPC^#jc}&C;!C ze#Pa79ATOme~&9nqZ7z#McXrex)Mgs3b*p-GwX@Id$XHEyf{R^e?9OdawXX9?e4Bg z`sd(6z=<`!WRjD~&U2GpB9k@X5eOkcV8&f{q&R_awuFj3d#~$Cp<-bl`!W5rWysS^ z92JQA(*c3_iKX#JG7x=8u|^aY^erN)*@o*sErT6+@JJkSYwIxK?&bPezwv28hc#|y zOv!|;pJt8tb}@gjD{#iOV^s4*QBvcAg$rBVX50c8Vl!^RBvID8KhSzPmS&kxE0k1y zs7jRTRzRQCLeu9wO^C3@JVu+eoXxd_4OGxFXrP=JbFn?#k#*G+orYYfBaT1lx>68B zijKGaGxA#-i&3?oe@dJU}4CKN43{ zl)n&COMLQTW){nR^QFuf?Tpwt$dziGV*-(ZKII1bmJDR;eBK%C8eW~w=cHwclZ>&l z#NUCI_`p*7J#LBc1v1DX5iOy=Qz8KgVce%f$9*u3!}IA~CGyZQ$jrlAULw(9a~DW- zSfkwnTPw8YMQs*X$I=@D$74>k>Iu#V)!XeWdCqme=r_-0h{FR@qvcd*!Eo0%nm%ZO zJfMcZh!VTth5t&BSn1~o}Lh+7cU?n zSz|7<0L8*npuBJHtS?y*bOzK>054Ma63qN}+Fs*YEZ{qpylQ4{xKOrj z;3Caj0cO5W)7vZ*5$+79k;}M})oxnIg7mJ1m4g(l_UIM%SOErWwU97;jaEzsWw73X z25VudlCx0Wt{@EGw`N}DxE!Xq@VG46+9|AJ)eINFql<-v=4&ivVw33>anr4prmJc+ z>>!ShNrDd*Z(ODN(#Xhrp&S$UYV4=D3nI+ukKzO6fSyHOzoE6bMXx0;O*0lM8RSt~#21Z% zdh(U4;K}2wU8d+dIkk~=;zq_BBH1CxiEAwTwGk@N|I2l#$p*(1jTB?2WRo)q-&4?534zhV{WPIqS0V6lu)auP5=WLSSLai znJFR@)AOPk6>cYts3<3vrigOkFN!Fa=)cC58qEU=vZ#+J28HnU+COVtZ`pUf3TLIZ z!MT=GOnK4KTy+2S>lAS@Eag7qRwa)Nx6;;k-q=wk`a~*z^D2Z}+fJ?su{t$AtmnNHjK1{Im#`|zEc!Lq%1IsRUWDU&b~RY`je`N>`$V3iqC5| zFDA@SW34JJj%NfWj_~daZ%DppoM$@FID`lKoldJ%pNFo(K=g<>?5)>892=Lh)c9R-5OiSt z%VO)qJyd{Fs!hTbvCW!G|7Ec})Q<|xrL$tl#dBWm^5P0ORL%-**W1Wo1&M)Ez{Bj9 z+qMW}8Pr+DJKMS!?|0o~+!dHZw4FlH?qv)JEJM=u6$D9Y6tY}8fQAe@fW8dk;{kLK z!+I}4WWVWJC3YNy*8aubq9}uvk_XTyWwVI3Iz9j-708L6L#-B8*Y}L;j@V0RR^A{! zQFfMBGDVj-&(q@63%-50&LaN7>P*WHCFz z5))Xyi*Y4)H9pjutanQJPA-V4v2%RBpXQ z9xbj$mcG+{I$BIyBCnq%vHB3e*7dXaCGx1K-V%9KWYYgzijtcP4Ic71DT?Azp~S=< z82g#*=#j{Rx|m1t7j-d@E~#o_bmMETmjZj1o5Zb0T@#FACadaRW~o$v_ww3R7_MM> z8!iq{N^dMK4as@TSgY7jAEU2cBJUY3UqTRjQ9F)4o@tR?Xc@H*Ilv8FqyZ*CzLGI4*xMusuY2Tk&B;5zdz(F2$KG%Y9tsJST3DK ze!+v}rzP_6`~;Tr1&D4{8D<+XC$&*@O^Vp{z$_tz3EaF>>=)@*0VmFBJ`{;5^IwMt!I7F zOYvD>6+GKpJZ}rivmNKz_5X^eeBZ|uwa(zn*JQYjL5v&qWzkDzUlv%ti!nAxQGDHJ z)5qW8G^nI~{iSqZ8(Sj#AMOmW6ZJEZOXX!o9%{b4Wzcv5t0HPOia`y#6n{~}E*0}X zcJX_Rz6Fo-6W1HOU03}3i7QGoo?)t}Hoae^`rC9h-&4?{ANJ8BL~gsRnus|&*f^%x zsClUNx;S#qb-nQk%cKR*>r3T==XI9hpNB>V5!rhb?2HSZsb^hx8UJO~h~7_2<$|Z? zGBBPm@O|qp?I$Tk1C~jX;h)5P=UootCr0i6C1ff|x zD77*Au=+I3%bMG+7QA*q=>TRm`)^k}5)NUOj51c3gj-cfI0A4zu$%x~jb~VS5^g^i z?&V;@l|7i1*yMe*J|C5LGeZ6Uay2t-324xrmdL9}Wc@$jBzSgU3o+WL;{nbMix5kH zA{Xj*{=#3>?fkX8s`+UAzpm$PoegfgE=qR)W=5@m+A_qf>-VuLMRqt*D`bZgsWSW> z&WqLSaN--f`-d*luF?Hy3mhu?a=F*dO1sDPq~-)fWulnN^Q(_d z?Unv0k#mfKeHyZXEB{df~A2c#qQDWm-X&LNhmZJ>jS}8X= zIt1pDCXnkl815%j5hgTyFjvs*feki|#Qe6d2IA1au22C;*|qdXR?0OCLB95=@6L$L zMyv2~r>-)SZ`=XMS7WqYyv_m;SFd#3fp#(67|95#A?GQUO3Uh*m_VH_eBdb0%~4*B z^{g?NXZ3Jh+gV=)aR6wq+VYD0rtVnHNM+T?l8LLNB@mn?Y`RP$T%u2of8veha%fCCpAz&RIXN|tJw5>a0bFJl^LO6!%GttOdrEUQGO zl|AOTb^>dv1#bDI&dcF?S=}~GW z>X+_onx%)XmakpwtX6?Xi+_C1tk;BGe>^l;O;__xTgy7J*x8I&;3ay_0^-zqEeyt^ zDB;FaQNmIwN_rVBnJ9q)Vxhv?Dp7#k$|_NS@FMmAIc{`gg;i*<8ZtCW?V*wNcg9R( z6st<1Q2-{wtM>&ggF*wZ-iH*gw(hFWW!dDtr?_dCtfr=BFw@G*_cK<@mIhqNhMbGv zhBn@miU6^;RO&T`t+s`Fm+#VxjCYt^q|cj{K5w!NrO#JBeJ-$U(&r1V&ren9bI#HS zxR5@ai_)i3Dx$?2JeBl0YS*W4hvb8XvsA?~>62P2{gcWvP#=PeZC8qLv57`|mPy*= zLM?ybcZMC8+{EVL%scS(j6h>=DwX~LE~F3VqVx$!ebC?uq)Jk$d`Pey#wd6=tuI+A zS2Z(N%2myDn1s-(W&x9w2G|lzPy_51eFx~YGA%KT6(p6mah0BtD%smIbr+kYM#ef; zAKHkuYh6|<i*qBfKDUcyp~n7GN~p2MHD$_6B-~$IxUjMy0}nyRszKL+ zj{QwZ2@3>(jx|_{Y{kD=B7ZJL)~BzO3mQIwp#=?}Ir(k6LSn||p}@4DX@|dPLDR0R zss+utJKb<)iobbS{9@&P!$RpdT^vDlg-3M$Q*_H2J zX1t;}s-;|~BP!MJj3ZaU8Fa(AppIjh@sZ-d{P4czhc8(!`2jM9A52Lx-e(!g4?)EB zzGwO2Iq3)6lA>%0T<0lyF15B^V~unRVWZYuBi-^IGU0A{L2CB)F#& z;m9}IDK^YOZQu)uctNHs%cTwDHX^dOJJo2z(v^RLi0r)?jE#V`scQn4e2wLj59Fz< z54Ze7V5cK2|J;mBxPQ_WSIa*<1q##P0369bQ?N8On}13M3dFnkjWkab@X+Ag;R9e7lw5&?t` zeC$fCqo4yTx()(3CF8WBjyyYyxV{Pxlf z6{UwFBSok;uCexCF@LB#&G=mv7TKfR1N2{@rND%&!O0pRcb$;~2R$@mSpT8J7kWe1 z;`w{F$o(ubT*S>v=urPVtV=DVraXN6UPL_Xj?l#VoWnY#V3MfBS%*!pwi5 zz9@-IB7U_(oNIMawle-YlNXh{7G0+%r|P+D85Cc;wESUI4_6c0YOLZZ6Pgt`*N@ zInvCTiv1da0oh<1rtr>vI(QHv8mF!m{m*A-ig9Dyn~lS&p4fHX-MK;Ez-rH{YIGfX z@>-m>TgZ-JBzigX&{}yZx*r%1;rfEO$lDhTg6Dxd#=FbxQAS^MTs*-&&#b-9A6TFU zo(e{&6zmNgi}%-Z>9yC%jrtlY6B{Z;!rp2}!rfxWgPAen@Dt#lx0|QOiNj5N2jAYyov*Fn41LSjVB6n7h=SztZF&Iw*mV&^<{gJYC&C##0ai?fq! zy7XJu$u0jp_={WqgpSfbuqbZ9!zWKqOm$yxj0nsmIuERq8_GxrHw^%K)qHeDXjr+>=^eJ z z4M1`3wKX<_{t^LUE3*U+ecHzV<=B1e>8X`zYiY*^yK+Rtd+vA%N}mJ5)S^K9(9VV)T)|=Z z^X@yv>H+Z7?}l$Y%|+=_PmIWVGa*qF6$5sHEiF{I*JL)*uh}4>6!Z18`SSazZ1qZUVAFhqIAg-}si>b}xP%cSfd()xcW`&rg+ic)jy|CgEN zXUqB)%tAKPu)5aI5dHT;M?+2qHr)E&I*r0AzFp_mHT}K~5?A4V#+kzT9;|+2JNql9qisaVSJy0;2TJR~h)FiVJkK62k7%9ndWMVBGaBNmKt zgjL%XcU!i&TM1^_;;}$mbYUuY+^BFX;C;KY1!PEDRKPfrt?64f%KKg06n&}qrYaQQ zFBK1Gio@hN;hDxT0Hs`LCgz>ZtiIOkEUnimsVuFJ25Jr4zJ5oq;#z-X&p@s9WiYk; zJS`8WD!2mGif|~2T|DYG7huf5&yLYS=1JZO>m_=FvB^Sj2;ZdIi+>iU*V$yDHxvfW z7dTP58^Ke67Og>#S8okka>_kQPRG(-b-%0W+3+>oHm*VVm!@N94|b_1{{2sKmZ0g_ zrFf45Z7@W}4+#L`u>fWe54`R!)bHCQQ5x=Nn&Pmg-vdep-Jlq->3_`7q6DzBa2tld zd&PY%s5nv2-y}YMFe$~%SE9+-XfPU6c<<18lia-M0H*L`HPk!d8{#?(b(GLkGa z6a$K{JHXa=C*2|904Am4%scKHnqIz10x;}W;!*?CcT{D`=YmElM)WkZ%VXa-*f^Ixr-nF`QRb9S>g&9n^oJRiB_nH{H)3aVbo@d%D`@V=oL<}$mt=Q#gXo*PBTPFVs%bwn8E`P zzP$07yPf_wnJq)qxyv(G)ID?6;!kVkr*E?wz*>cgH$G3kUPesUvu;yF6uHtw!MABJ z$2#qPRDW=@M7VfJDIxp)e*epy!=*XxlUEg*!03w6La=G~hR;$BNR2mpE1@jQ76n@N zeyRDrn-$uHu~1c`ZOQtMz&M`oujR8B4F}Lg(uQOPv{giDaDu-Or6EW!?R8Wf{~UIF z?JIrSi){9#`(fi0lL5lhDd>6ZM=I67<#@Q--F+XCbtyAu@h|RC#zn7Va#zUvv*N9%8BGk)EC=OQ4XxMdWU+6Bf9M2U@L{Hco6NZurSP z#8}IORI$2RrTRoFuI^QkQ|@lWJ8Pd~uCZS+pjg#+Z;{8^FS85`R@$|PObXWbtzi9t z6#}8HV12i$;5l1mup(Cs*4>IA57ytTVEsd7V+Yw>P_X`56~7u=s|Z%ql7N00KN+n- z4DQ{vMZPMV_J=#qNZtz0R_CeGF7aFC%d#Ani7j7;47wzc%QF1dgv|WE+;K)c%cLe# zg%ET}U@5c=Yd=0)YazUUyWM)9t+KTcen#J|asz%B+KRW970P&PL|&=u2V)Rpj7LYY z%LD5SP$l5H1L9|JD!_pDn885QNG4%vY9y2K7d4W}U>ba1#v6&R-g0Qz%^eRe+U+Wj8A}vzbT;+gnf({lq!$?Qh<>IC|4_4As7m@7ge@wCIzwg=V(>2`(3sY+qA6z)1DT3)!gDQq&q?)w^_GY8*BrIT1`T=%6i+X zP%m~{kXD)ZY>pcl(pOU}s~0~kK1Xk{O%&}*N;Fyq<=3n#etE(8mF-Vz{y!9?A@crh za)|5|l;3?-@f#S79}bZrpqE$~KO)9p3d(LLNCbN~KtslBL35#XvlhRso+n42xlOis z!c&>GO}6+A=yu-X=c_n?3ls1~FQM>M<}szP?Kde2tX<4X;IJ9R5`4|fTO#7>d+snc zu(Hq$+KYZaT^kl1w8B;kQDraK4-r*@7a~NJXs&>-(*UzjXY(eqq|W9o{6(G3TidGc zY)T;h@$hcO3FH1~&vfGprUrF6htqOy?5GlbY8O{;zE}}|od>X|{!)Z-;U>?9 z;frEZ8+oob!nT7_Y@CrmD!*-$?~ASr%%%55kW252euh#NuAWAAU@3ak<=HObPTB_M z=JpxxhAmt_2|Q6gr)2ag@BL|;sC=RvE?$cDq-!U|u9q4|8LXB(Mm_}r>kHy&YrY5F z_dt|^W_-h7?-*x%eflOwiFccNvSWWjB0QW=bE*{1h=yW}w(HSZl=gk#N>5tBF@wa# z2V-iPBNbKaSQl|ojOi*_97*tWHi}sSMSj)*JxrgzT^w2EjN?v((y%M{c~XY4Dp(b5 zy0|&X;|XK{u)Bu)j_BflPMyXb+Oa1JlWfVNwJv#4x1+$ zXBkO4XZ{ouXbu2DLFdc`KR0?b1%*XV9>+shu{8)!I$LBG`MaOrlxjP_* zdXzl;MLkO1j;iMP?OdK`gY+Zq-JXd?Ppq#-L~G%BuS)f`rQ+&dCB|vWJC9zhD~eiX z)mr>?23+yT@H}o5Dpsm%(TDAj*G`7+kZ;|C2;?2IBWUC9mgR9kYL9KizHK||ej^iJ&*6=hpm?Dc?d(s-5K`LZW>#pMGJLpU5mHF1+Dfu?s z2{lxdS`aT0JIR6#EAef*Q^LLc|KUu)D+XgNJIm&bqv|X_hmea;Z5mkI>Md`pst$c# zow1PJSYL7;WFX|wM z!&eQ1Zvw=(_3Z1!mNhja6aDNbt0m@XQuHiD^GJFnyOUn#HmV@ z$a=a%s_}YY5xN2gMQFmZXQ!O=oC_>PggzxgZH4}z)r2u0&Y{jZ`WUyfiZt-I#{?Sqi=Y8?NlTHR z^-KjnMI8he=7qg6?bKGHpuZ;~I=E&6-g`%hLuZ@R6s6G(l8g&XY-)kH5fK%%ZbjaMp4po5Usi)Q zLX?2k_h?ydd=b(vn)k~-Bg6PWbA-CPA%*4$_3#(X5$f%(dRqdzPuiAPGSKs4xNWu| zIxljy@m=hzB@Per>@^%nQ%%{dg++==^#y!&?~}seDxMMm+qNn75WFplj<#-6oa8=e ztKD*g`!1G&<2TMZ;6yaf>*=8P1od$nv^Ogw+c}~N^w>=ez4APFkSKiE)7*Z%Nhe## z6L&#dDSG^{VDfI+trV$j)t~AUCA-RZ0iW6(WLuK@72rpQ1&p8EwF_c*Z_C~Cu%PE~ z&+Wz*CW7B88-z9jHh2!OJUT1bV43n&mcc4{3OuRC29`%h1yzWE8;4q)C>!q?0EYyf z3O(8S=ey;6qu$PpM*0`K<&j!Tq{pWmiHyP7LeICxcPxP>8wr6`E~paL837~Wi$}Bz zZQF(H@wJZ{_>0;{jXhPjj|A`+Zrd#zS&7f=dxYfcS_8BgdpzF-X6lw6JfBHFBCCjmSHYU(y0<1{;PRBQ- zk2cn_av&Le#|dYitM|y6=W3N}J#ioeyJz=E1iR-|w(2jmgJ}C8SBGB%?=?$lVPYl! zY!d@)`V3U*}?jGJNuRsoC<&~sEtCDm~5J?g8E_No$&UZxyD#B|- z|J~_1rY(hDl{{!^k-t}NEY1Qq!sIF-I{kZ!yqR#NaLZr^vZLw1PW(mP-OjyLZ5e!6 z?AaEilY3*1=U(He5?pmGonBU{{=V$sRoGw1-Q%tyO7~>Nh(8{7K52ZS*vKm_ABz4Z zFo<1X>C|_{=TC5J5N+SVsvXZHwckbVd{2_`Co8D@`CsYJ%7bxDXhZR+gN6|lr@1}tWy0^d^L8-;QseqW4j_Q=d7Fe$vNw@ECYj=_Q@cVg7;E*WIO#$ z_|KulG~*a6Nzt2i(2)Zjeem129|nsi0-Xcmh=&^;L|^YFa20xU{yv*GPpyViwO`Pi z*9wB>_|1)Jeb=A}?k2X=MevdwP75b&D7vLj@JA1lgM85;6!;EH%jr48ie(Bphmf`a) zd<6R3dQT5Mf4}rphiN@}D&5$Yf)P6i6dUED}XY`K`HKw)aNz>-{CjHRj7&cR>g;yFQFtiV0^ z8(kkYctDEa9#PBu)Rz0H0qm?jV2-ZA-OqU8*y_1iUiq=6$fBwaP=+W|fco&fF8ZO04Omu~6E?#M%s}-m4 z=$Ov3^KpNlPOv89t|@KY#=#24?WLtuL!2+rZ2b`SkkswY$A(2s_F5DHyetZL4_GBy z?(_`SUx#q%kk~{NJy0iJ9Ci<{rR^8l^^&@VWC0w*EhmpCICH z%yfyr%RO%60um$hd?t>Z&ajXF$vH51h}spn zN{w~J@@dg>ZX5D|G@#zUQ0 zf?xMzSE{>&g#d1a74iE$@fx)Lyb5qwW`#n9=(;yMtRm`wr;(=JBQg(qa*X?!;#0e3 zIK|m|T5GMFRQ+sxgQg7*2V#!&2ZD$O(e)Y6iYq)l1S!X9UBuyMJ*~_xN&@I`00*M} zC`{qqKu0M~*XH$7^gAo$rR&3^GwX&ZO)xPCgUb??y%>5 z^SF`?l*7ZSk5r1tzCEM6ejF5nF|yNJD#ITP&sRGbdWoW!JWGx56>&jsF3>`5xHbq& z?{^gz3dA!nd)ga++Uq?O9lVMJfQTQT79n=N;@MzC9#GAxa6Bj(en6hY*MYwX0P)V| zgtmqwpj1f80e#VYZ;LRN4kmJl+_!7G;fwcxXx!4cH88X2y`i^2CLL(`$oGBS)5hq- zN}>=UJrBS}@K&w4@d(Qy26SfD^MHhAZrk4*XN(UlLKlvph>g!Y&DGUdz={%|c|Ja6 zEJyK~2R7L6y3yDfm`f}m*T&-CW1b<#QC5^#yzFD~0n1S=Uba|#9+*okAlJrXRXTjc zb@Fkz-19dpPkes&@i7i6j}o7(4qebEq)DT|Ok(r9jZIG@C$Lo3yc^uG-vB3`ZH-)( ziJbL}gGxv^ql^j~c;dwSp3-`MLy#(DkHexYKQhWtfeVwB?&%5oYZcywCiO+u*zAesNG1J#iS9(m9up5* z$R3kbJ~h9^AB5hhk3T3UUX?o7S+EBKi$QZ3)}p-@kO`4J7L@-{jZuiYg4!Z?QD!ZD zrS=jsSy1n`Q6p*GbKvKx%n@3$uD#$G#T z>oe8mV72;5dH;{ZpkbNG)MEm{~~moYX6C^-g?O~|0&k;T{GzGI>E#L2e} zXE{d56J|ajN4e%}$}G7)Y?o^n#V>qe z(*thPFV>OS84*Q=XS1sr=7O(PE{abWZf%zzmnF}ylsv03y975YKl!ts3niK$H%~YN z-(udA993?yeq@RDBTb?K*lCAuG zYV8!+??iT{+xy#jYb+$Na~KL!FkwoU;e5P2vb!5l;XuDz6QV3K z{wcfcdO*P=1NzSt737qkK5QoY#lR($Zoml7;qj`5b7RK+%a$+!QII>Gef0hac_!Ss z&-{F;%Hpwvq1Lkev@BT`qby^XEHSq7XZOjJ6Q4PgEDKk7%0K8AS|VPk>9Yp?RxIJ> z`LV_9T#~9v2ArSyC%hw$)k3ebhX&;yiBJ!F`w6kewonAZV2w^W%titsh8bbA?U+YlOf_u z-%Vg-RHc4zta6AGs~`^cm; zXR-=q$JKU*nZ|xODc(8M+`o(>*`m$~&iaNKzFej7sJuLs#fL2~!{Vcsm$rC_QsIfq z(@r6a?`#+?XJ=n`aOEdI!@Rak?tQqC$8k*y+0uA@B$&(fily93%UBwZ%MG0VSfKe0 zl4*vSyWE<&mZ>Z`e-(AB?;LL!_sh)j7EuX6G6QpP1z&BfE{-I+&f15+U1kbiO7cS3);_}suMX@qEC zXG8%jz>}xMaC?`RbPG7B$9xhDh+mf|AhM3t9n*itOBB@F%O;5%G; zdOHWm33<-V+%**S?&?f1#0rfYC$d3ZzSaeP)CC)FfLnkq8i>o9r@#fOH5svTg(G#K z*rIVMTl&$`=6+T|+Wb+ry3^Ur@uM!cv>Ae2--eaSL42;X2@YaR4`*ZZs--?m4*-c} zNqrj-AXi_J#-RK|VV3u_2rq_a)?gzYF0uDBbqnPt;&_Q)7fV*kq-eMTouFH*xScWs zgzjNw2FNT{nE^sKQkel5@qXQ*Fvx7$BT6!x4)}}ArbBVrX0xOS%%+JE%N>!$M!`Ti z=2&*VY&Y>ttb9Mm>y#QWt-sgNmjM8Y7 zvltF+HS;zW<5&eb3#cGx@iMDG^Qtl&3g8nV4Wx0u(73T*h6Oq^PD>A|!Gh zl?!Q1-yY_?S^UGOChPlK7x+mk_xlgDK0=u}+&M}_tqPcka$k|Flzr7>6*Lt>Md1i% zh9go}SpF*nl|IKR<-h*4S=EGL&Lm}3tyiH{)sa^pbXGUpKy!?B90;6S)dej9w5ob? z^S2FK#<5brTo5BTiEgn7ffUpgf02T^t|}u;`FNCbNolRj9qsHX9?)#6No9~O@Z&7^ zBY)IIyMH?$7Efv5N)3-$YIuoN&@A$p{O?1~MvljHxut~=^!XlDS}^*`gOi*?SV&L{ zB70{|dG=vvg!vIEqIUJLQKJUUcwvUG6T}R@xt2m6MLb*~{WW5y5LW6J4k9P7{U!Dw zjeLc_NF!gBrIA&SI={7RWSiK^kkY`|s0;k~3T{N;PunkrJK^N)$0r~_J+9G6x+ZXB zm36b?0;>VNWXMIw9?vpXscQn^tAS5zs-?=&A1B`om2?^5AT+|8A@0f@`iQ!$B_XJ@ z+Cq@UY6wPQpQc&HYK5SMy^`)B)LG3j^cHuPYE?ZCLC`&f{;ZPjA#`QE@vU?S5&I6T zQg5Z*lbj=sVwE(4x1$RP#yYaLxIh5vdjWCL+vq8))l@>sU|xROnVWC`1<4I;J(Dcm zJ}8dPijn#CvZo5kXvQ;?<~K~`?S5)lP0V26aT1c080JG(+V4GQid^)rGfOOFr9cYY z@x$yeAFfsj4{Uw%MR8fp+tkm_aP5=6)#@$BmDTufD@jZ+EBK(} z>@x|1<_0w`{ayo2nx1zKKqTa)2I4RBQUkv!W8SDd#ktn*rCQ0@Lg!2|mJv&?>TzA* zM_TYhxfdgs#dHl9Lq^!?gs%#jQ@&C6&t8VV=w;4cs!>^vpYDv7zgOy6Bk<40;$zmG z#{WmEr}47vH^Vthd}FU)X@gua)7f6^wzt~BTH$S`5ZwDF%Y(C=8~px*w^07$A$e9h zhcN$PtO1RX|ERh~`437r^TvOijT0s#1>Ao;!bsA$mul>)zsV7Wa4h}Pr*J6mOuaSW za`#kB7RkDrHbm+2QsSC2?6%Pwb$O{O_VU{;<(;X$hV0giS|caP%=WVF!|B(1O=8iT z&PPQxO;?fUEoXt@$kQb-`!`ALX7*a6Qor=pHEL6LqOV>Hv!`OBW~p=YLBKn{?sf!m zVKmQf7}E(MkzlQeId2W6ohglbtc81gNZe1Bh5N<-6K<7wh9Os;kDT$_46$~`d25t2 zw)M#ui^^(FiDy`Ia+G<|c0t?@MtG!t`-I2TmRB_m&Og9?on(yU-A^r+8-1%5%dJ@jkpLA$!X2yvNiZ78*B8KArjaiHpDCc7wPS1i zo3+IYow?>PAPl$C=-svNTeX0xfDpMm`dv#O<7Jnu{_pH%VvI&iTk44?uo>?+Qn#=+ z)EFec9#J?HW50;4$(UZkUt~-#fmF)cP&-kyc(K!El%B)VK6AeBc$ed*%iRCfB_whK zvd|APi zhxsF9Te(udTUnh+y{~;s>a7}xTjfOQgiO`5)2qqZSL=tHe_9IP|E2SegcXR2E9?!1 zThBZ6uKFKdbpzs7zjUm()t5DRircKzJ~7_`h1P&1uh{NdUm>uNf;W(veqWt#Z%gm1 z8+@nUS2xhL@WKl6wMlwk-R?W}zPf|1*7If?=!>7QC^hAD{*LC&$Ul*4Yu<#f+`pw9_q;pVlPP3+tW1 ztvgC0`R7t3(=+R{->GNT=U68qd7itKQ5MBlLQzbwtQ`o32LUHETzJ@qudIVgNcO*3 zjQmWD7?Jp=nJmsXBOJk|3UT?&;+`Uw*)P`v&XPH6p@bY;F8(6NmbRku@gAHg>IYY>&fVjPoZh8XP6t#H6(n|FJinVQZT7K}t0UPg0tQ zMfRriZB0iEPwgwdx3vmev)0<9_?gw{CCHk!_`IaCIBc&~Z!*@ZO$tBZn^vax6jxbO zWH0QJABFfnpf|P3q30NcAx_SYZ%|Lvwzp7kGHhtFN2fk6ysRmrG2rWSzc`zScC4KE zpa&b@<2#&KnG_k8F7oUx5D9dj8Uq)>FqMbt=O=$b$^bExH77&^6{1I2xfa;K@71o( zGxl0SGSG$uS5+ZRMYgZ$N;EsJ4c^9w4cD7w-A7X+&G)}o8?L7prBs*m_Bve&!%*ye z4!f1eH71T`K1)lm7YwOSXeW2FNRw-jUr34OeD(GlmZB6*!QbUNx-ittG}71cU} zb(9BBJ39y$>q2uGrNm;*{O-%QR8BqPOf1^GC4Gn?TC;9sgoT?@8asG5NeN1RMs_;D zr#y_S5VjURoqAf_&$<#u5_NCb@G~03J9_I{F6u|uDN#SJs{^7oABMgm!-S{H60+Eh|g%$-Y?w=d(yua`&nNt-QAXSck5b9x`j>BJ~A(?Q=bO7q^q@b z|13+oVLya0;z@5d%r#5aN#oVj1V@R6M_UYVO}SUS3^V=*m4_qo2W_tYkjSVlqb@pI zmL4)`p|DXF4!}lPIPBO|77nxR5Axs-@GYD6Hf*wZ-nbS<>oU;Y0W@M3j-U}rSvU|K zWZ?*A4j#?jX@Zn#yaq{`tSP7jtm$4cicw=5s_|;5vOda?#<4EikXSQqNHkRC{v+w1 zig=c1jhxT zb-Fo}PVr+823$0|=y!v2e^6o#!b)Pbm&C~_x8%5j$s;!e9}~O?&NzQ_N|b-JbUm3q zQB+>9Eik~P8Ma>eqA*=cZ1$@>Gljk{B5O1Ys}ojly~T5~ZWrL$Oaveyol>LqA%+co z;iC3>a!N*+oLbct?+8Lq{Mt+6WcAx~Ji!eqdakfO$TRf4qrq2V0Had#dcVc%{km3p zhFOo*xW{~Qz3jF-B}I(YwVK1n%i{2P#bG2LJEolaNK}^ju*Ks2ip3zT#G<_B+rTOzvx~rhrKm$)z=0y$v?w zBytn5l#y#C9&NHgB_3_YIt6IX-9WZj`pHuVSrX-HESRFCC)(98QO|0PlrwT`un=fr z*3sY+%sQIAK{1lBffzBCp$U+E{$+d`dO*Cuom1BjzA<9;+8ta_YbtPUGhB|Yn(?5h@goq-Hl zn(A=q3QHRysPu^+l{WscX@gcxguZZD!zxBAxhUC{X|{&es0)Fxxi0?F0${perGBv> zLefPS1VOsU!(XI}ydO)AlOniH+c3m7?f3>RSY>J!)yNpA3;YNR%KN!2yrKe+oT|u0 zz2U=)PihQmP&{hs;YC(KdVmVj!=t*w(nAO;eUDgrxc^807W=|TKDJW3aq`12@13Fc99 zZbIN2;D3QUN?5}3C}EwCQtcpyWY^eCvtp6la#Ke0=JU$uA7SaPQu|B@&g2944cFp> zM#@<+39p6IW%n?=SxOhAKgVBmzqLDFJl01aRw{#|a z439+UMCdi#Af$c&h8=N-g0?><1*(s-WQM>lK#H$~65zMh&@g+u2HT2IIj$y-L{@H*SP?Fj#BG$0x*5;fx^0;?t-dU-o8fY} zLUs!SEHddo?Nb~a9pxR0iNYQ(%07pUEFre_V`3GA3^saN9vqxD zN=(D9gr`6zw{cr}xu)n+{B@%&Kpxn2wx;~BVa7CB;}%zx3~%ka$H8&23|)&ivJ73H zX?hfu^d9mP5GiH@>D%Y->%B`*{Eq9M+B1S&C!#pV%O|VS+ZL z`xTq$y_^}pNzUlznsEJ^pAOEdB?my~9Nq0W@C;(Yi-rgmqhTOQa zTzr_}o8>#bLAK$HA{tK_Siog#ZdT*znkCnd?{&=*tywo5PchHhRnkIt^9zZdqJv>k zcDt8Qkhj4LC(@ihyIn-c;q>e#bw~fl`(2xYT{L}h{7_%lQO9$dBAAFUzuhakL?-ul z^)R2?tj-T7>5704-BIpQ^oXo6IjxF3GY&4pj%)^gkJL7|Sw>U!E9(b$HSw-SEsdvL znUb>Kg&@c`XS0?4Zf}0Bkgh?lXu0ARHyL7 z_>T1eiKu+{=IYJrq;duP#gobdRS*^oP5dAC{?&v6T$_x zLAd%2cfBNTW34orj(~>P>1nSfJRJ#7OEHMm5(=mYLXrQlr=1wbS`mu;u_DXZB1;~I zqt=)0mGt$iCm0;O(OrfD55AK5Dn@isa>8g=)v!-N3D*WCBnj3W=fV_o>}J{Roa@2V z2b%ftU7-(JTGukaMEv+qe{Q)?H(R?F*n|)F@l1F9&%4|zt=w`=KTLm3Qj;a6m0Jq} zEU8o@L#)&FXxD?`2AMG(PG0eZPC2)qwy2$1qJ&Q6fCNk>Cl}7Xxf~G_4ZCXQ@-37` zF7XHw!uk1HQwEdruI##U!oOV4h?BZl(!`M8seU;o21SJ<2pL?^zD>^lsj^oXTY)GZ z*V1O=KS%;CDd&K%41CC|`rXsQ<;Ytzd?JB$^Td1d%$v5Vz4M!N1%yR--RJBRt{GmP!xpwuaC{w+|Y0g2QrXWu1-!COmBs43j)~*xkrpP)jZv z>q-eOJ>t$YViA@)6ELH z)%D1f`ry3*NtFYfy|I-}l_I%?nbMtCsj2zWR&{3fk_KX#F@3%Jv#sig?h9S51P9+o z3V>f3N^o={2hb<&$c#rUQE#QSF?Ybf55S?=PCK~m4BR0FPB3a^|7q@QghD57c3Q0y zx62?eJaM}k4BV0jB(w?;T=^$;%EmBkmUPMnDBACYgIR_G9SGb|pBCQ81dWjHnMRcE zZ3VSt?>T912P?H?din*|gB3kLLCENtxUhxDfnR>>C(Y4EHeEmI$S17zPvA$IhkL7W zTA}|!$K!45`u+}#=}Kxf9E9>e@1->qtVA9}100Ql2r|IzqN9^t6AUqgkwX?Z04TxJ z@d3KRvOu~-H~uGeiEg5WI9^4Lek`N>K5mc2_8vwOv0dS3n>FoJEdI>dhTHgSVMsxl zpKbK(MVnW<;tVtQXLWVG2|}`#GsLYId+}k?4z4D`PFAo>pLI6bt-Mjcr!p!_*E7ee z$SDV4%dEUE$@#MyKu$&%vE1FxawElFI$V5j(a_TLfIyj_W!k5LD1i2JbT-F_hv%oWU(S@Ht<; z&8kI*Tv7!-H*IijGR&nvQ{ZDPEy~~MnhSHz&nji&Ax1vUIW{eyQd$mL!a$_cS1#(9 z?vTY_Ce@JDc3$^3B~bZ}v0J{m)s-W5GfGIa*X)}8MQL$6u!5VvZEjBQCt`MJJ0-t( zW_S6hsUfHC2Rq-qBRa|iOk^)xe^#MS!e6&U$R~R>Y(geJYuPb}T=cVRnb~58+|t0A zDOxdNXwWo6VAi7iR`{q}sqrFfjKKWJ5CQ?TnsU+Qv+;%PT$el^vA$P`tt@A@MD?i*GXH>;)2^mHTkqQCEafpthXKYmTdfk#O-9 z)jQ&9W|${;sFa7N8NnpF6HIg$mFPlDO%ytguAC09NC(3Fv{}OZR9*`_Doc*Jnu()~ zA`)T5FE$H2WO0|+H`)LRVxGgg*v6W8zyR}NKC`=lcnCW2@bAEm!004z4la(o`IqP> zlsAV@_nmZg4(Z50g9!z50yQ}0Iu^Vdrt^lz-H&I;S4K7LB8G5+U<09_DRrXDJ{ zx1OX@9X_FfY~*P!L>cG0$=fpM_2`jx;4ECjSE4k@8MtQvXyb4 z%s=NEWqc}&&$*hJAN(Rq9(N~G&O^BH<2moDneZ^eBM{?eESS(-#KrG7W`U1#T~fhIwh`XxJ+jkEuBT|1akcw z!+1mm6{NF^tee(Z2qJwKVCMTe<9^Z54k~4*dUKr{Twz%a)Y8N24#BlOOsL5F$CV^f zSjGQJ0bZDd^vh^9f({)htzknsX1Oa_j!sQ+nEiGtBf_+XX8)ad_)s$*ndCtzy*r*a5GH`yKqPWP2CSYqaqKWv6jA$ZA42&p_ z8Bt)1{@^dlC2TR>4~dy3-BgF0NP}Uw(RG(vUhkXHuvU<%Z47faHpJ_iE@f)7bb+6& zf@9?~HJIBUMIuTiKU|=3G4q>eDSv5jZ4VPFTHonxD(0~Yt^5##`{sfw@wRN?PCR-V z2|gpUs=Kwh(^5C4K{R)fx?>XNB2=#L=^PE7HMN`L=_E(jNS!VYvMSQ|G<)ZLx`lEj zal8aD(b3AZohljPMcrCH7RQM9s}ZF^)|I%+Z(Viq z7g<-`U1eJrP)QR`pX%=4LQFW5Yq;l#rU=PD`Jv0o(FJ}23d%p%Jc`kKj4bw5kC6+a z-LH#0jYgSJ;kqrp@L3MZ-oYU);xOi=)U3^)=D4F zPVl3cYOf{~6D$<(uv$U^6@C;4Z^^zlg4L^ISpNTRtfyLM85)3rr?MgB z?7IaFgrCY*k$vm9b7jQfgjm7at7BQ`E*cwg0ng|=iD)Tb&L6v!U!;6nQ{&yO5^ljd zK1$q-MmmwLo#6h+aYdI}rxi)wdUu6I?1uLknB>W^Tbm1ne1l*qg->SGAz<8YmD1@C z1mZu8rIbz;cdNsSE4x%`oZ%1Ezuw(^a!O!KwZ$b(Yf-Hv_YOm}WYqa@`i0k~5u1xu z#J_d-u_>_R+4O)@zLesAUdmMPa>@1G4doB1?g+DBqolKue&?#Y;p@w846gB5#K@Qb z)OQc2MofLZWXy9!w)x3zM1BpV9b^Y>F(~1cQwO|Vlht_E3)5}sTuB@1#3>U$7tHC zs`%#Z-ReB2({8-f;*q1D>(j_=O8_s3nPwvBCS z?5B6z2YW6erorB7j~eWh9BaSV-8vy0>-bFj+%Bg*eNeo_dVc*F)vmR zU9FBL^MT^PV84HlI`MCXt^9+X@?dq|qXv6NU>@^ey}G+Wc?LU){=k+-k&gD7pp8ZD zef3{99FtfPWyFF!W|Nw`v&1X9LLKbW@$gHGgD?qHi5G<-H1Kk3143zS_dDp<6O1?V+4krP_BDhipxaNpf@>cWc2o zQLdmA%j5P?x~s%7YM683gK)^Hj@?5kbmN$L`3D`EHx2cOz0jJ5y1-vF)WzOXL%j&r zRlST@wo&PaR4_(PTJIVl-5uQDid2Nb!|O6I@tfjg`f1Q>)7Z?Nf(}W*P$v zc60ZtmCmifwLMIzptV*mtI)x22y%TndsU{Z>en)E69ZT`2rPP-_k*l3BlPIt3i$HI zZPl|3i;D5VmDFqKf6^O@`&mVRirA1;$f!HriDvv>f5bhple?Aq=3eDnDB0Cpd)4i( z90bbUOI?lyS6KZfL`SKNSMRebintT)o#*HlYK0Zc!1;CR%OUbuM&_m1jqGX}{vx|t zrtB)@QY&$<3Wg7LcAp6`o7B#8&v$I+q|j~8y}AUI-^1L#SKap9qAUC~7Hlo&Jad=( zahZRiVJC4;1Ejf_5;PAJ`#hY>=1Gs`10ulMrXqPyJV9q{=z|6qs9 zx2qai39fF{#ps;qG=}&-s>JDzGQS!giE}Cfu)>xN@MlYK9zuDJL`kDD9tULm;H(t2j@kl zt@=^1BG$3~Te`r7!S5{Ez6j8k+|S)dIQ9qB#q?4YOEqn;oAvjr^S)HpoXASv&qVCn zPa+nKEIE6CyMAI@q=rw;i5d>Xz>u0suoAkqW!BlRgjsbz3Dax`%J~QGax(+NNf1(O zoxNGq)W+=}*}js1_wmFHL44$RhT<=BJVW=Fn$Xln;oF1Vhe~^!qVI>e4Z|^!Q%>&Y zMO~uY%|!V67=Ao`tgi4ARj{Gl?q(3nOZAqj1CcFJZNW04f3qa7UvI zgQ1PQ$M*ZficglqBAZTsrld5e3}-NBA9oK+coVhArS^wKOwM?+!>4odrGPr2eq})Y~whnW*djDux1;|MwNb0 zdFV`Ct!A5s&@V9CGfoNCPkHC62i2ZK zrGrH!S!wWLpQ)@LiSZRnjIZblF2;G57(dq4N{kaE3m{! znWeUKe8FP0GD`(@BrzUheMpSFiCv7y<}d78ViBghu%x_X0O)n)hwy1R98 z8xu$wc>vsu0^XSe?@ho31FkNw18lmyZij7MUjH}1z{~3o2Lo4^*UixkgE{_J zb$gwmux_s-4#*KD7!HgHtlR4#J2DL>J7pTIfK20F@h+z#*ea|vQ9*skDi*OmWEH$g zuvKgpD_CP~53Gl>2l1}l3$f~0u&@WhC+qHwt`xe3Q7c(VkrEJW+eG!`a;p-kj=20 z98x?q(G?aC-49tj^w3qr18n4Wo8#t}%kD3W52G_SwO+6QD&mEqQoPs-YEhae5mbr~ z2yzfs2eZ;a)X8sRCL@c~G1X#as;*FDbQb1zT5w3^cKSruDsDcubMuwrCX(B^%I9Q! z#Ml9J#12EJ*s&GVqLfY|s1(_GHNXzu{x`!8syO@H0gAK3&Kv;ozhn#$|1g3B%NECF zEM;@)JhS#;^~NRsuvRgx4Qd_MKFCZxtkwpMIprr}4wJ=+>a07hSR98HVV4hS!YE-= zch*u9))h+`VOGMXVTV=1rs1p;Q8$!R_lTk{ctEVWlAg+DSt~`;Kn(~24@l7@Scw|N z{VdA69#%`2GZ6FP(uKt=YUx5399Y!kUnXG8P8)Ia5gDyp7T_;hw=6hZ#=2$2BKNM+ z>lV3xvAe(cPE)Opo>%JvKh}ahw(lH`^mSCUNXnpN2hKceq?Flx5Sc$weZSC>xPL~UE`M)Vx|+`xFdcY)xuw-qgqGG&{58p?tLM2)axtv zP~pbze4jK+7x=Lj>?^m9o>FO=Zq~q=X4)Q6n&}o?+rxwk%n>BovWkFaVna~sYa^4F z!{%h#5w?oRF-MUmQe>Nv4XT@?ElspRpj;Cf97{kGI9y^`m0u_pDz?!$5&P4)nS{Sc zCzHz3$>%HG2SVs%cd^?iUT1{RS=B6E;74DuzkE8O(^0wz{Ymev5n_SHz!WpjQq0oe zTDYiTDP|t4(25B`u5YeV%v7ZqHe%}Ih)Iw{%C+Y*E1Ns5VM9rsc3H}ri-@?grgO}} z%3@W1X<6u*vQA)sQr7SIi_B)vJmL$~Tb1HPV+e|Vz$ z^w6wL?ig7(9TK{=T@!zk7#gzoK;0WQj(Up;_ExkJ@zhauyW$mlEl~iqv>O3*(*24u zm<_sLQ8ldoQR~$^YmW12idhu|1Fzm|`(M37OY6M#Yy4IJs4V=+-7+Bw|G_O-FzRsQ zqNvt3cW*-!vtru0ShTjm_3m7NcE?AnQ@Q0DEZ@4=u8Z|ntYa&dQdk38r@f1Qcl7Bf zEB)f0BF?fN6p5ZZs)Fj1xHU7hK>ne^W~W08Viy1FqsuTR|;(c4R`hEZ*(*il8c77aTvT7C1+bss+x9J+KLV z2P230_!p3a3!H!H3eLv>KOcj1y;|k;<9v(^=A)0r2LLBN7;wdht)P}{cfg$_f=ZEv zj=u%7kaf^~NqoR4Ar|IXEX>gr77O&0csT$mOsOwc>T1QoQqI9T#X%TYuk3cqs2sD% z;sKx&4-C5E!B$X9I*+*Lil9>D;cXia&FXnZi3-QGRUi*xS3u5VYV}GK@FQR^@bsVNir}{%RT2CqV1t$xO&KN~!RKNrGxf%jjzqd2QyXqQSSO6& zVL4cGGI%+7j0~5=6*abhCs+kS3$+Rqx3TWHzA$dV$_{4kF-;sTFJ5L1HE}Q6h|85D zPP<23=c_bu29L_QXWTu?(Z6WJS@&_n{P381cQ%(%P11SaE}c)6bYNI-I`2-8*@!-Z zoS?PuHT#%ckmY$u%w~|ltL7z^YWb#au~F8zni?xV&i1r3Hy@LyvOOKeR$Yy+8}gzx z0LueHQmvEjW^(_M0TB$kRT%_*&OfP%a?#s;qGhJbb3&YFph-9Fu2qjy8FBi}G_kF^0IA;S9x2 ztU}!OxMHW9y*aYuXp5za9T;zoJ)epJteuUOI0dnQFgL-ph>LqRtEgvj#$#Pz^j3z9-RBZ&Or+AfKs!Oac4TP=R%NMp5R`u)?=^CyI zTSFl7rJYb=YjxpyR>*vQ2ktV>UTq-5ZYdIAp&_ zk5`Ng+1$sQ_ZH9F8&R10^a&NF&al_I+qTa#PN*mqG2)q78NAt|)XWoBl**c`D76O2 z0ix8K{81{jw4&5igkElp@-$CK!{0nejb^mb>DrNK&vSA`3s0nkU(>`|Ru3bli`*3B zx!!0Ml=_rhSkqIvHR|^uOCD@S{?3Bc_}|r>52BNvQIRdps=upn6~I%7#K5Z%$yNZDIch`BuAou~ zW{k6FH&)u1Qzuxo+MUrujN}157_H{%3eLzdKO@6+y^8gQaz-ApGcwR(1i%v`47_5* zR$#@eL8Ta#-SNAMSN%*-tT&(0f=s|CCyXRdJu#P+>qsxC6k&d#VNwd26G~W=LT2X) z3aE^q<(6d6AaRI6r0F5Q&Qn5QAu|*!)cfam73x(uX;b+XE~$u2iDOMreR11lVAc}m5hUF^+?ftFaRh3=9M zwD5cKJ77?bw|{Qa{sRUL9-P~M z$biPpnm5fI&@8u!$33K}yUBp20~$AN3XlF@NzRm*b$LRWd8mPG$k;s=(?n7N%KPvk zCcP%!kH6@RY9YS1qvwK7eELH#qE6$>26`?LkN5WIX7dL8MHgNl!&^jjFKIcRx~$H` z|EJ+rE}b$=#b30oT@{1tYWTkzs3OploRh!$33ZYA+BcD%#bK116$I0SaPXA$RIlG$ zo_W1pEn{QRo40tD7?HH#-H40ABd}KM-?2(wCh3N3SuZ9mM}cbs;M%V^Iq|#5=Ca0Z zo*5$IbTBrfvP^CbX_rRN>snP7zS}iccIo61DG2cqUvtP_?>jUB{zq?=uV_j^eFT#@ zNVUUE3BXJ;wikVTyJwvdN$&hf^dD1UklPs0RUKNxh;QB&F-BRUWGQO+lHZeTVaIoC+j@QcU{(vsUUnu&57p`|< zqH_Bu<$Fr5)9jOac*aBqktF*s7}#6h+}(3q*o4zyXKy9lBv=Ev7;4O!r&(@zsX0=7 zQj+iKDA8uKdRL8*%kT7D@32Jrg3zCR!851}qbDH4zpht?YWy!M^1Mzd!BcyBA`Nrd zX_Xfb{swZvU%lHiz%YK5{qFI!6^9wqB_DVO8gTNBLx4Wd_(erfYSn)a9x`augZ+n% zoZ&kSU>0Y3<*U6t-(IJtfWUW+Ju<(KCsXWU$h$@6bd-hh4~nQWU`~7)wUaa;`^6X$ z=Fh+n=7_obK3Jf{VoMs{rh_|4aa?&l+!AM^j zbjG`|TZ3zdV+Ec*8MEYUpJ$}_oz)}uu;2V}FR>a8_qQ|ZChxc=BO8dyXSMM_li?=R z($SWm^iA`U+lnOCicln+wMcie8jT|1ETU*CS_Rh*H=!a3df!p7e}5NiMbNte^yKW} zjU!kE0YCffuq;^M0_-@ssAgEQ7!%xLxY88M z+dbrIB0dbR8g4#sqneUsuMBRblx8fIXCDR-Ke9^1Yc6FVa4)6|oANx8(npSe!JA*h zHyM;yP>HSan4HsI&VS5PB@z3nx0-(=5%^Dk z#_Y*wWYp|NHRG`b_YXa>!15rIUh=Ah+2R`GVNRhpMdiz`T4LqP7A3k<)EC~t7&T1s zw2Ud`En`b)+3O&3=t?orfoZdwmw&uZGp@KG73l zke}=#&pdzK`%K_!ra4NZ$Qkc>Pqb!&IXK?)fVhPfK;)1I9~FIX0-QJ48m7qBw?x;H zjV8i&#@(g6ygw0^jl2s@6_|o8u~mTiFe@tK%)_P6*jX<$b&638sF9nK7snX@@lo8^ zszkmWof==1`n0EKm^lvKH{FratybukrmQ!15qvr;qhV&)D_|FtT6YS=LU9ts4=fz0{&8FUCeJPGu;gv z%h`K9P359+FMKlN^9G4>;>TS|SF~#sUvU@6MJ3?f!z4t(#xG@zoTDWwRVN!ca{d(0 zlybxz<~GnMrs~|rhzM9x^hGS?!)S}r8|91JSQ36y(Da;BnR;_LNf5@F zu5+}@RN5)EK37__$S|T(s$mT_aUS&G9%*pOv9^0PB52 z#M;*qYw9^J)}r=r!tSa0;yIO^cQVI{l6$@^$;}8Mxv$>#%qWlKp0*_SG^0XG?nAre zCRmaiTLh95hWLtgyCEW5Vu@_5Ut~pKiJus-Dp>phdZGL&t$SrC=-}AI# zG?QxN&(#}uRWgiqy%ClMU)CbQ0TSl&it<1A+-{hK=T%PUX&fm^?$!TEa&Ich#jr^O!@E!6 zV@z`N)H7q`=AMnBWS64ro`cC(Pqt(^nbD?YxzH}l7ZjV%0!KXU^D5T+hKO@T01p$V ztUj=AMA6x$o|=aF+j*7H`8danGClG?$@ILEX>16Y77UdAt9$#(jbk$6$}QD{mQ)Wi z>a%K{zKveuJom@ogK-iE)zuwXc5zEl>&QZXDEWCpU% zGmztU^Ayi5vYjudigZ77tg=c9UEVSFoF#_m7=c<0^Xy`H+TwTu7sFS&5XE4whu7tY z)7oP^OWQt+F}_pVJ_}T+N4cRxMAW|dB`P=c$v>>z(5D$)fk@vx0aQoVZ&jW_p>`#>xy2YP1 z3vcpg85Z90&(anS0r)W4b<%M$>sVBjtoyeo^7@HhXn5tQov{DtWh7}8_r%hmDd|r& zxU+yikq#HY>Sa$AKGv6<=>C)CqRAYpvCz=TD2m$aS!lqiRq;NLM@;AVaJ)<@OMGvI z5Z~|nJ+GBVU@yy84ti3>%Zvyuuutp)dr`3h-{|Z2t7oUI{+nL?msd)~mXx0RQ#slU z2~z4LVOu$(XyOsieFj{=*>@D=b&`=v{^eL%^7<>ZyoSj|M?KN9rF+>8^TN4B9Yoy3eCVTTm16GQg8)m{^viHkg zS5R|8(YtC@Sze*n{!0yjeL+GmT65Yn(=hImz0Z1Din|#_B=0-_qTwA~YG{jB* z5zL*-DJ7ow%442gWy|xPEYX$Gpw06kEal_5v&BxQzf_F*)k1HfeEZ^!Gty@@0yUJC zk&c*H8}egbO3Rjo>%BM2;y>YojMs+12Ms^E;8|}j{7dC~U&NRoLC!BrkYAS;D>E7N75uAU~fu-W%BEE3e7z)u1hJxauFzRKu)%LFII> zdO;5hl2Z7EGG>#Q3#Dh1#|>|J#AF&5R6ciuQ2}zQGqaXiOHR12YQvaRtl>uYkHyes z%jhtll8mo%<0RJPf*PcNfEiuUyh`5AhS~3e%I7|S5lmvczbvth2q88IGq3xD%)fXR zn!SOF$#6i?n^B?7YrI`#cUv6wxS+DQPh;I+%FT<3uunWwbPtq)nenHJyC5RLxXY~m zr}_l5fSDXW!5kC{SzECYFi&6(_ur~{uLNy+!eLu0nOVd8l-R`yfwQVEKkI_PR_M9% z9jifbRj9JJpVGjk(Hsu*j)NF4L7I)rtO8H@;BNN#7;l<5&dNc&DsOvi2pWCIWJxV= zqPYchZ5?NHFebwpkGHj1`=T_mybURNyIJR=dINh5A#f8$!7SkAgjTM##}$cq+-+2`Le>O-H9w&a2~nT->M0lO?Fsdvt-Hn1YgW zEA_bm@_KT1RC;$YTBA|w9dS{qcRZ`0LtLn!yn`cHML@rCA;|R&zo_yKeo@!kUA)e^ z5xiL-KFm8fmsOB~K?NDu5>|mds?34{xS-KMF0SiMltoG2NP$KE_~d^jhTdM^c`?Y^ zHYIyoncFODqb%>+Eo&Q&pt-g6WVpcEc$)V;tO|WY!d>>xJ6Q`jbng(yp!xNS0;5;j z=dm$a+aLIgtnCkFZE?)n@W6-8Z|=HCPNS$vs<)C6((=ZV<;{BPc$A#DIwMDZ^ThES zc_t$DZc*(LK=CjA(eNU4fuFE~3*|RF!aciT`Z$rS5h#;OyrdNFVijZ}P(gX!6Iq4U zatK0w376ETAS%i^ExZqdH(B1u+rj8EE6dy7%!9hd=`jfj2#qVYG6PR;MCWtAi&ddw z6D!#}ch@bHUy0)-ehpQ+r1H6s(5)pM$AxaJ^0^yNN{`#yy)1x~&YjWj*A@za%xEei zBQu(YzsQWHT_UFy(u{yeoO_BcdA!k~&FE?6z$Sd)iIeZ=l*3AD=4~gAvu*_L zh%9dAZ6YqPa`IP4F3FNxolPSC1{qre$!dSHxwoD;!rK3@=+Q+P?~?HfI@G5xQZ$v_ z#vN}~MV;{1|65Is&$sj@nGOC{HvKgs;WqsN!%EJIGN#f&KqE#dIji^Wozqzha#jqQ zU#loAva$}?SWS)iOHGY`mu+S5TUPc|8*fr*D|<;<*_3wPda`9Z?;&v?qX(@l{~lf7 zr>9p%qe6unU}%K(;||{8VzfqLO^ttBQzNS&O^=X{ju82bVC7oVA!zjt|63W__Z_{h z#p|paf-`4<^k`;e6>4U*2w1`@h=5sg>aE@cF^iQ42#5_yfE+UjLa#gj4w?+V{Fk?@ zxy`aK*KOW3bGv0lIu(9M0j!^ze2@*mNgtSa)w4_d%q39cP(Jjj9f z79R%JTQ}O?y{ulVea>nTD|k61%}BsMEob#LYsH1ofG_?sNJ-s~>L#DM+uO{rZbh-i z>Q+?6%i5OX0>0C?3-MAK`(J?%TvO0DE0*^1woi!1I&RgK7?BhSbgh>?O;)=vuug7q z<4mI6PYtU%e$xo88%vAU)-Mp3bg`suH_FOxT+t>=+isUYI7tobmTo@raDAtU3DLYw z{p_sL%?npHY9>-cG+*>X{fyGhCpLf&BsaA+H!jKSzTTvu*5HFW(g!0GF9sxS-Bt=> z98xcj6?X*#gj~7!#;H4&QjiOl0I&2QQ`R4~9|{|N1zzXl_d@>7df}FWF;cD?=q>An zdF&PS0g+#k9RIa6{D6qz!*15=`ym|Wd2c6)Z!wI4*rJ(S)F1BRcE6(DXm!Q14uUa5 zE6F%!M}A*|mP~1~zCh^Y%a-6T@?}e|gkDM(Jvi7~)d=!nlZJSAh)tYA4BFT00zbln zOXZslN00QrBlkYweMubEz{zF71!|J<>DE)#Auqu6m3L`9>x=2bO{dynuAO4y5(@d5ljBb5g5lwUpn6$#ke z@9S|#z%kN$y{}C{EFU;(Yk+X)8Lii&OVkZ|%A4)PQnKE?MaF3FtwvbqtJX`=Jl27( zQr<2XKjaN@m9p1Wx=JZ(Vh3fjvVEbqsd+0%;?>jyaVvuacQ(75qpzxTmH%cH$y2?9 zU~Gg&G4`rTTFFqHky~bE<{%DCjA_S_A`7Q^z2=OoGWlR;eKCt6B3`DIfoQhk#Sw&P zYS;8!L^NqfW<36ldMhm!;m62=N4@ooFXjA4y$!_Ib{tE}z_BKTyf!}OZH%DX@5~J5 z1w52Wz$rQ~_z<;NgT5^y@kn|r>b$B3J$#K9%BB~dtt^Z4%?QDa0lr7#Z6%LA;eA3} zWAM~LDQ17j#8NWYN@~mK@>My;@Hpk=C%t1ujemmdG_Q2?$baYooeA9n@6T$M0(udQ ztbOF|HRY7C-kHM5poXHPilQX*A4SQEaj?hOmi6g4-g}?f=^wllT2r=*%d0OxS?zVy z^~|u|)%*+F(*76kH7PHrmW-d^^#;KT%m|D%>&rl`6l+GNESUv<7L!#ZYR)VofiwR| zKCL8xDH39t3jFTRmnj!b^mdA49wAT#J_%iM>;$BoT=7KwMXq?F95V^NKFPLOXj88! z;%U1lrXAVd&v@SwuQ6%SDtM+Y@FOj+JBA(E=hT_to&s+bIrcg4RIx~-QL*Iwe^e|v z_aF69h7ff4K9b2Vcu)BqFl#{$*eI0UUi3c9T<_0_gk0}FfQ|u_@e;V+kFc1#-f5bc zB5=KiA&%-26~)lu;b~TiQ4Hk&y60uDJE%393B5at9O=E@cSk`2tL8YQ(OND$@)~ep z%?dOwDBy^|QgYcJ{X+pqk>gcw4I?c5n&r4NSvPccX2WY`95v=jqYySY_aSEPxKpkv z$DP6;k>ll)lp1>zeZ142R{p0SS3-8xqTNkG`fn_rDn?VrFDn z%#0;w96^Z4a|0ss-0;`txo5~pGr)7tvg4Rm7LM7a1xB75K$GX@ylBr|m%$HsZZrNG zJ*PJ!WYinrPV%RRN0^nVtf_L_%plNhuM@i&9PKA7VJX?U^`)jA00ccY`pLQ{bszsg z&!g6Puu*-R9QT^Hh4}}ti>`C_^A!_hp~I*m7p;by<5ynuR*luZlR=W&ck)v0J4?}Y z{F-`K4c|?E!`q=|srqeTyf`5gJ@tk++z|CDgaunZWhTy&lg@}8^f z)_uz4v{?n|`ML>lT2YRF+ndYyWBnC>``(5<7GA3F7j)6MFqq0S+%jo4xCq`lAdP5E zcZ8xlTYBbM6Ex*N0zRgG*0Oz~ZfG$GV)4s?%_g;&W%yb3L0_4DPuqXRGB+2f{76Q< z>&=Ush-A}rG6{dtbTX-eob*C&YU%kT@;xtn(3hPONt#dU%@CF3WAA(Sir1MCXwz$! zF7RXS6?S7by^3Eto+$T!=v^fiYa}YxUx32wY|g77O9nNCS8a2>339?*IM7*VZ~1L- z%d?XP+%68<8|@8lRHM7Er?_Nq^k<;as`ZV##f4zpHy2FpcrLx0>L$OM@9pHD&{$)& zqL^Aic5Bj-UQ2bTrS}Eu8K5GX*3yhH*}tVXRsOla`*^}!B!_9A$oCo!tCSqdD zL;XV_N;;mNVVqIil-Th=UWt%Ox%@wIQ&Vob!|*)UOC1_LZko+T9w*Txp;dyjA~YZMwvrLVz@Rp2lA^ zdBO!@oIE4hVho=0E`GQ7Fj?}0_wUlPr+0(*2T?gpTRg4C!gPTjZNd5SZI036;(nJq zO}@I(`=zL>F{p)DoiJ(4_1VMo#JHMt=@;k5PPcuy49qJ4smk!Pu|*c%1_=rG2Y(vN!^s@+z>MJ#fGUl zH*dRlvVXc|?bLMp51dnkm~P)kgf!jG53{CQ`kd^+pS>LtVzH9XxfK|BIOi6P+TpEf zI6l|Kkd5I~da}e1%Y>~4h&1!8(e;viT`|mkA${FOU>AIy1BmfYa@ORt41wV+2S0*m zIsD9wc@&6;DM=h-wS?+$S*Xs1LN(^?v@Bzp9J2>b?QDp;hecEjlXE(!CkaPIO#-b0 zt5ht5pSX&$Loet)jBgp>XxQ{^+sX;0tRP~OUV?SST!&R=_yKTW|_B?#pRt9<(9#%ZCv8_bZa(4 zKzx-3h@~+hrCu2n4EIy;U`Psvl|{j0|2GN_PE1J+qCg+!yuuLU8pmu6IP=@oE!~_B zbKbEvhxgMacuDU-6alv z^wP24AsOVQ*Wxeo(re|MW1)7;S{(Pn$EDZ`r>N5jZ#zRAWUP>X-m44z2n)*jl$(qa z?%7qB{W`iI6n|(8bd(SIBsQOdyBub?9$kSOwBh1-htfZgtOi>q~bD zTyw)B|7zoZr6xHiH^JNi3irF=%GRn!UOVA!BF`*zhKKb6vS`hN-`(}xgBVqor;!fG z@ly@uVbJ_aM^OUt`Eie7W3sZx@fTUy z|8)JzSBchR|bba_Qr z_(?0+QNDN~>5}(5u~5UMJDzbN5cw8_%c&=F66C05&g$~5ms0K)YgjkBF;E7EW8^AFP6vzZd&T#xIZ;d-@!ysrx$BGB zgTwY$!u^a!4a7m#i)h|k2F<^RqIu2$cS^!#)Eti*b~2bHA}2@i0uqSMksz-#uJxP83-YVS08_o!>eDpjK$ATxwu-+UwmREH&=AJ zdQK(7(Fy^mabo$oj=F^WoY6|oiOT8RrI{}G6IHOK+-`0d`{eIE8iR6pAyE2yRaOq~ z$Dyg;iczcw`MTkim9HCGSuLa{E*cyq+r*@`5--@BK4WXDzxMl%z3Cgaru3oTB3mot zGg*?5(?opB%IQ|r=Cr%BAoJ0x9~#3sbwpT__$j!>aOepV?jX;833o;Ol+&kvPqLPD z3ku#qAdbITxxRS?kBSM&=6NYeqDqy3VkI;gZX64Ngue8f%vutXMA^R{AaSvBjU=&( zEUDNOBFW&|;U-ipZrJ#a00Z=W-=3@$!G>)fgguCrYuMeZAOkJMzk_Rsn^1wUjiJbc zy8Ts#ZBR6mQ&~@AaH+c_Ij33J^eR>eb81lvIK`BlRtddOihSN`%*BdHuJ+?ce&1x& z;Jnr1Mwxw0$7>oipS%|9Vzyw8^m zO<(w_U*oXMPtQpgM|G`Q0{;q<4!HzATSYB_L5_jxOMRDpAJo7$|E&Jwvf!|arYwe3 zO>w~x9V|f$*vgE%-ryJ!wV~8x) zm@JGw_RD&ptA*=kFiD!YP(UJG2p3; z0-J!XY_F`JCE#~h9~5vc-XtL4Dq%(WFQ(Qr!~)h_i#eKNU(kr#L$@DH9Ha zX#>X*p(|+vr%FT_10^mZgfejh$2?F~oh8^1bq{k!SUWgwhJ|);vJ{rmr!Fm|r*%%Q zBWN_z1`Z&hy?2fTEImW^%Y7(ISrC(~vLIeS7W8(ToEGAKMvTpZtPcmXewGD|V13Af zcoSwp5-ccQ?mv?Lxp*>$%-B~KZ}sbUwf0q z7rI8dzQtu}bfwa$V8WJkIJ5vN@PIRaT6iN9Fp}?M7?pHw1=eSUd8zh9Ga`aLQP-2{ z6UASQQqAExi^Fre*5a_5P#o3}Hk);bGHkYvAe$}CVHKzda0nQQLxxdtXe+QjHq1*k zhi7aY_PwLQSE3uERCCxxC>?guwaOFBf{zb}4HK|c($`29!*#V%KZ~2J1T`0%2gLNXu^ix^fA5`22`wVhSn;7$AJp%~C zUfpaozZZ(|BEbp2S5$Lo8`CrkEDfT0)VWmqPB0Ec$o zxymGcy;uhfjnpP(Jq;9sDg1gdE74BGOmHYxgd@O;UW>7a47=pTv6#@m?7=k%9YQ^T z7-=0g41du&Y?!0e4UQss=G!yGMpLVMbB2hgHPz}R?|5C{M_BNC`PNyqy;=8@)Jp8@ z#WOV;^;~JHLv1j=$0}%(b1G=9eQj4m0Y3s0B*@0v9fW3ZE05Jmy?AzKW-~_BgOoLzeq7Zl~#;; zfBjkioO7j?$MWQWoDt$ALr;6p$8>=oX~C%*pd3htRe4rD*Kl!7BT#C&Y^f#k|D)|Y z1EVUsK)rWE2)Ub1Hjo~AAf&LBgg_E{34|5}EcCMUrXYv}1r?)$0)q$$HY}6?ViZM# z9rdFqVi(ZQf(@{JDwcQ7nY(+>-E8nZlJ_TjGv)M|Idi5(7{VvDTmZGqe5Q3P4L*XX zB?zV7KXkQxZdMD-k2>ImT#d!^`&)-vIz;F*rNSAlqVuu&dnqdX4=;#(Aok3&rzri! z(RudP+A)Oh3;bSZFBPTp?V9Zfr0TM|ww3Q;if&@Ye7jBk6}G<4vqOZ?Tyr2?<(a;~ zo}zyDkC-{%9~N#uLDYyNE0PKcox{!AKcp3+%QVpGS1h!XN+hD44>YN5MQVUBVB~H(chu9{&u(`yA;e@MC!C1zo2x6fXy$ zix)!h1TUS3e*nMeZ1Ye&DM@EPL-4c{otJwRj>nAi(xIDGxGR}x^r|7Si}D70 zdZWK#!=|jMhW;a_EwVS)Fv5Rn?Nq#IYszmThqpXl2N>DKjRl z=^w6J5I$`J`*llD5FY$<6F8BJ>=Tu1C9Js;mU5F=dV@Vfxj`IVVsF(J_qF&Sg_b8)EnU`#@USaPHN2JI~xgW)Z z54>Qc;urE!Ir~ya0r~REs^u9Vnseu3#IBp|AC?BgaPOsJ5P7dPOBPkP+j~~KSJ-b> zwdAM(uJ9`N|IVOLUxe31=nz zB#Jjy+9NfNdiG4m_@DyWS1*B7gFwDl)uB-$<5kB*`qf-xMb!y=xR`sF{Y_<|=(ft< zUR%U?U46hYPPqf9*Nf15o`o6E4zzSll5c733hW+6Ex>hvhF`&vh~SbL9srM8{bLbIhqETdl; zRu9DxS;}LC431ncT?;t9QDXJiu0A6AA$ycaT4(<<V|6zzpVCOM`oAnz~V6W){dwGL>o;cTQc!Yqj z3awGJxotF<=-}wXgZ2{THM8hWY5C!z%O?9zN|wmoY#W>44JFcL_F{V;)xuqE-Lrboj;Ay1xI zu+{#Ab~UTjP&OxuHg;~}$5pWwA{)%+eu3r}`mnu|b_+vIGP{Y%Y&Daa&)QmvqemQ( zqESIyy#*(V7N<6ma=Vd{L2`RAP;QGQFAJlot#0f6s9n*jSuGl3urrSBA855t`m6fH zK*0riND2F}QThGgb$93r%K%_4Cqm zNrGD}=$p=%*Fgmw23Z&4&5E&zfoq4RYpj$2i)f+#8ZBpEMc={HIBL5iYygziccf0o zFZ|c{W)6Pq-jJ~$Dv3&g$I)Mr?$K|C3dHVCj#M#gRdTGjBP*p?n}cO_@8$dzjuzrV zR!X*IF;JJ)F(qAF!m{&za!i1Wo`Asu5xr|jjCyMf1;`?ZDmpfZTn)%h$q>^g-p2;^iYqX+yATXm~yyI0Y+vSex?Wvj2hgxi{_t3&)+Ej-UX1G6iw zDi9AnaI?!#rM`a1YDbFQ-xpo4y&PDP;;RQSm0Vn~PKvLNc+UPG?E`b+fy%pL=>dDP z_AX0DU9HQVA1U5DU{AAr4{|@hr%_W8@w`1wJIl(E(%=nbztVn}O4FFqMCuFnHgN_Q z`r)*9p~b)^AS*))KJn;co0v7;(lki&p%?7SO+!;J-mhFO0ryq==;HUCDrTNcT zSWQyPSlc~A%*t$&slwgD2g4ninmyLARB|YDMDZJTI4{|NswO{@)1m99vVMLfI@Z^V zdtSCbrd%OrAF)qTuZR^Hnk!}PKh1iGyS_~d7n7ShazxRq_PdlN;^?dPmfBLrE)7^P zFudU#c}&tUw_6EyGy5w^E%-COn&%gI;>VD(CEt(|7n zkm5g);AuwEE08hF!KBhmar#}KO5Jg_R9f)1eaxk+bg%#llh(aEzljnj^4@SH zX{{N4QfpsK;A(Aw1eK_1ap-)k)2?C_eE!F)Jc^@+sr-_X9W8Nq3%clBoU zx6zDj%<6qkmiMn%+G{MTKC!Pi4QS-W-Sw$`u=Y124E>M)bGEO-0!c;Z8NDsZf3byU1guaDY=gHl;N@ z>6R2gDLgU5MmTWcoA+=bFx)n63&N$>+EfO=e~I(EUs;XOz4G>o5K&vs#EaDb!mh;; zqV<36>3Ji8f?9r;70Kew>3@ba(eD~*V+lU->WIs1UaU=F@2U7jVehF;X+gsJ8H1F)IruiT{3KzrQqy)+={5fVK+1vcI7%M=EsBkUac5SOR(Y%cVF=D~t>uR}Do* zl-P38(MTLVWACaxV4x9btnoqcdbh$0Z1x$ppjklf8HW&0d}~h^Bi0U$*H|g(doOBg zC_i3TK7{OFMa*<0?69c#&R&|l6%)9omoVBu(`olC{WH2cBHuAq(N3@|f8$TSArQhl ztk}69>?Jk^(kE5#)~5OqL@Z3U@&kU6t^6Qu#l~#~^2ois0h$*aI}p9k**68XnjH;b zHJi`dU)RFo0VlVbXqG@$6BaM$g&{_UkH5+WA|q0?{n=iuwKg!2!PtVJ^tOt}O}*3W z$|H+u{Hr}pS`33AE#~jw7Sk6|lf?`cAOC9apWF%)xWy=pIKRcDb$3)L+6b0qSj=UC z5XxCGvKR)^CsAaNjzi7D!elYC@rx{Gwix_}y-iSqxeS!Fz~d6Rhr7kt*!0m47pKz? zItIiq@x#5*5BElb%Q~$Kk$R_f!M>?>JmH^*9HHXypZ1%z^$3C+&lZ+I# zkE8}Lp5Ef`yiF9X zvS(@uEQ2PhaYAY4&;ywnHaUzFJv7OAC0^{_>A3vTU1CGOjm6AxN2mh3yqW{P(WAm* zlI=(g=O~O(hp`6ndt=8|akR=2A*#Y0Ra!pF_j|_+M%2UM45UxvBrFYgbc2=Vns7&Z zt(2jrDN$b(94)S_`~OD)O{W-1{+4&3-lIovv8AmeR$QInu&tXA*;H(ba6GBbvB|j= z{^Hzf%a>P&i`T0i?saL7C{dH_2ov+89IHasgEYkM3P&q#1Ct9)7}ha^ddNnRag7<2 zIGpb2B_S2ooCy;*#5gWBYy^`VgNao2ZkwD+-_0nZ3ByyEz|HI~B(X%Tw8^RTtMso@ zNtQ{$k*X7xaP>BuoFAQAehmc+4y)hT#IaZHEwt|#2IBc^#`CX|XDj15UQ|5qaEY?2 zGf84VqvY^=s{W{#$@&zRs{U8!`M-=J;yElKfalYa=T9ZiYO@5fdYYpcZs^43=w}*E zYWe@iSOP=^;s5>+UI2;7P{LHnE4>OA#4^2J=tSPK7hC!#=)r_iBt`Fwu;r+I6U6Mj z4tNl5bf97wJQ+z~34YUmwP8#@t{TkQuBfvUq{-tin*7qro)k{_ToGbNnxn0DFQXr| zt*%XAQ=bPDf|~f0`gEC~UwDlv*^x>U;nfK;mav-9fjW-c7pUVqrBc<~fj|r<9AY(m z-K9t$n^a%plf;SipDj%k10~I%Z-xJH@iBc`S|d^Qyrq$t-r8{zj#QVnfpE-^j35%_ z4_uUg1`*}-wvNdSC(3VhQGUbdAW=p(3urE1>3sbcYWRZ+EwGes$$l>}Zc3mU(wb4* zQlYL-CPq{N%?zRn>I?vUw79qGO%O3p*!$apSh{ygf}BI#k_BTQDGDJPc=}Bk==Gmj$^ELgMmh%n`l|sOh3zhyE!LQP_$uTGZ}5T*PJ^H*7LPI zunef~7cFQ+e;6nTGu{Ov-R?+H$29Z%Q&~;OmBQB$M8@yG*@(>WHF7dg4Rl2dxNdZM zCr2FI7hBQE(KLAhV&fyiIEEg>2JtMxCq{{Rut{~@1d3xdXbzL}i=-{Nt!le0Ni zO3vm!V0ujO>(Lw597IdAx#;G)0+)1l^hiFB%y7+pY;cDGA07s1hA?<@ExI#KO9})K z&q~ppjzRRv3mKt3;5k^Bbf1e~r2E|Fq`T0h1l8AUH6!N+6+thgA+r`m#G@Ltgz z?O~G$%>i$6aS_<H!7tKxN@9>vKe$-*!FBM1>re}vFRJs)Ajj6g zsLtzJ53H&8cN9Jzz!E5y(<4y^0*j0cA0?H$>SsttuX2nN*+U%_+86`44C4gB<{h0V z!#HKb9DTHztOgpot&SQ2A)Mu`nhfDAfs=U^i86+B1N>qPrw&*$hBF&1hhjLal`F&CT<6V_ z{ZozazV25aA~cQ*V=?Og66MB(-x)TVQvQ;NQ_5n|kQgcU!btG9lo#sNQmRjlc63(M z)Fe6W#9y3t9{Hd=T$~;2_$;JHk}tN>3%+~?L(`>_B&PhbBsueB$`{+`Ir@lM>(4e3 z(fiIc#^6f0xbdYym#PIIbvA4Z%4wn`$=FI)MiIps#$p0D@&d7H8pKvSNiw!F$Nw)) zg`7$H^bj{-cqTjER@WuTn96zvnRs2pd3`|g8p(JC6A-6Ajmf~>maW7ruOsae=ZVN9 zO|)0(Os-<25R*>^GI@vOYNgKP%l?0TOd9h&)GyBWl9J?nFCj_J_ktLf*OnwhC;v;* zLnps8N~E0wMhcx+14&}=Waxw?_$~MKdReZ3o?(d)6kZ?f@q*Axmk9+mQo zFtr#sDW2FuHkegwKrzp@b;O9==qdH)L0zXybseLLq`E&)s`oH%S3xa*bmcIs>i5iJ z;{)rzX|7K#4y0wYIJ89Ew*el;JUwO!(QMQt#Vmug3vYa~bjIf{bv$Vrbtup>qrx#s zv!xiuO3rw!k>GD%Pd7~aY9ji+=SUJ+H-T@IX`qpTmewhHpv7&@(E}~5Q>35X)0{g@ zg$!jmL|UM}e^3Dp>F0WbaN}*2BKK!Rr1)K-EV!O4d4(ef9=y719Y}rh3P)_-cz{^T z`)P$}cx#Gcc+t(au>_w0b(CfC^RO_@rsm@pdDrvB(p!LjW3m0o>fN_El9bXQ8m(*y zO{}`j@rZU8Bb)SoyOH1{yP>er){BX@AQ-%xQe-6M_DV;48A)NKq{q6PsVSbERg8#v zpG10T()^s%*)4ZCdM0neRIZ*|4YrIav)oScGRyKe%;Z}FAsl4ID3HQH`Xq&X(Bk+< zSeO+2F@BMPKPCmUI0`A2;wZO(Rbw2b=W569p!%+EfR=aH8VJo$%;eX*9TT-*89$`? zAB_YbKa~xHcb+W>aBoPeRC?7~N2XLdD_<6*z=;tQaYrf%FLod7#Ky2^J=WcgHVMc=y!6$eE$>A9RiH z+u+zQ&VN1dxJT5 zmQmQr3=EP*PBXRwK7y3+v2zyI_cc4 zjt*)y={^Zg0y!e{o(8nFdTB4x!gV^F5l6i=OYq55$5v*09Sf6A58)T-^pMmk+lule zOj3O@ka#u+_JbQO(jRn`+D`bPz2}GaUM*<85J=KPj^G9S6W5D3Wq}ASa^@s$k#MxI$ZXUX^2%qTOwz(?MmNGt_sth@TvdVHFe}c`!|e zM;>NqX|KvwF>9}*|0PbHXq!cFtP~<)WcV9VLu^kWl=ts*e5$?ytpZO2<1gQpQYNm8 zf@gl<)L@jD^&zyjZ=xJYA?JX5xi{rUCI`9P%#G#GG@4Y}D`pY$CeW$S6v^ zwy5|Rv0;=!`9>_=?`W=l!)U{aQe0$uK=b%2Of+}d8H!qx zE+Z&C5P;rhh})uc)-(pD2jLdBrHrq)Re*|!Gqp>)3=(x=gb-_^16k`VSy5bKR*hq> zI!ouw1px3g>1ogm-j_?KSy1U1KzS`q22fr~lL3?q@GQek(Bd{O;Y{$T=f@%sopSjfZnoRMxgVPs+?L8Es`RlGh+|RZB8t$f|@pN zRrAl^;tmEj%Il1}K2aI15G@m1;j8Jg6~35GtuQ`FBk>-r9(>#ptC+?o-;R|~QS~ky z&v}uNM6UbuMuNYwHN*}Hu!Llhn&TLwy=!2Qfs|tzdLZRT`f^#k%UpSM|SkBMk-iFiAHQe{1 zBPK7pMGz0_D5B(j*0YQT^43{`PmDVHGFv);l-_y!q8{Du1^TKj7DlH;4&E%dR1~?OyFvB82lJhZy9Tu#j^Zu zHQ62rVLB^DQ*Q>+Cn9g(7INx+3l^qn+O7CSioaDVo&{S-!xU_>w=i#7c{r%{8)B;p zct&wz)yuFA*x0WU`xWe0d4TapCa~E^@bT9m`&CR7OpOnM##@DU@PdrLuzVSRSs&a6 zUPE%p29BT&B#IZlaTF(4VJbI-`wXrOLy$3;_gI!;2pa++9B0MI5Ew|GpuAPOA^d=a z$q>%s7a79Yix|QN-4I}piUa$CC=q@Z_8hXlK<-3*>MZP532O-;d8-XE5`2_2$ZnOQ zv(PCe_H``Ok_-$i8k5jcMq@I~xx-Y*@JC~m&g*`HU~&N~L(@rjOE$LmY#C%aNwF9J zMX{J5JbG;{Wq1D%GYu8yp#{G<+NtAOii!^%&Bc;mAS5#$u-BR<+mIw~BnqREI(e4h z6ReK3%r*}TlZxl#7pZtY;Dnd*SV#ssc?!wQ+So#iH)i2}Xc&gTT`9}_&~EZWyGcT0 zarg_^6f#2Ed7DRxPygo_oIoLZX$l5NxK?O)x4a^YHOf+*ad|=yMYTqWF`JxUXICQZ z+u)D?&O1zDciv&1m+nhx4p1_37PnUcRm=rP$))>OJ?ToT8_l<{z&&rj;>8_wL&z_9 zl$6e`F2WOkbaL@;{Gt~l2~d# zj)?YH5-mzAi#Qn@n;;&yIGbvgR)&;_gsN#xbJc$&330VZh-if`&Si+Q=}l9`UoXK) z8Mth$nTQ@9-B{F&?idrCs?*mEOt&(zKp)ewb7@>H4vw^>SJ}kqhn-;wK{Vxs8scEH z8{nGvQ0J6OYzUyKLb1J-JuJe6L5$fkZlpN%SW&E471J_CtXcsVBYR<+Mcy`N^HNh$ z-E3~ZRI`!S-~k=?i=6S!2=PUjbClMXDT2(EE`8~Psk~?8gowP`>;;w)pijCBZ&VG&QO-QrV>muWY;H8>QkT8!lG^DWDPx05=b?H^C&pP$TP{{xovDhtw3Q5p z;jiyTlhK>f!o|&z&J)TbVpNo~t@bDr0NHX)Yb8f{2nA43+m!dT!dYydm=*1ucd4cn zLk}He8NmJ z1>ppx(fKKgR-sOC^T7?6E)PsCl+|eS0k>Ga$Mr6NZUomhUrBH-)K~$LKEv5XEN|xg z!P>L6zhi1C&M$QpYo$htIM~t&_hNn7I7?|Qw|5pBnb16^-gND4bCIda9#PfCIY9LjHY$2SEigpVR{*BQ>C}EVL&y|_ z1ad2q3k$TyZTzZ7?x(^Mj0yg#R?hiay19_NB~49kBN1c=<`M$PrKg>`m~*FMwcYr% z6L3(GQfL!zeVRB`8*VP8V;HPs7#Em(?q-moj$pPqbE*opd9rY`PnF*`e0*L@0P1Z!RqL>;Yp0a>E>`SNs;p5wga zAuh&A?LAU`1Eh?LUOys1oUhjm3Sl;Mn>}9k-@hBlf&I6ot=@k(YU>vXb{`Yq4ftYD zFy^A#5_1}3PR#1$%(?V2N^%u~RLYK@(JMRtsIjrQnoy#o~e6pHk6qT|X zSBI=-2a(lbk8>nED+R)p&q}F%+semI7y)8;FJ}iWAR$3~Ik0P-DV2=W7>tFFz9HcxeD!Mq^Xa@q3KT`+t*Cg_QW^(Ym z^bDr&AlUy~=*%@?H^k7ZtFuGMNgzPfq=3hD+DwW=tQwG?tH8}^K`r~+wqlIvVmDd# z`fkp)7pLZN!^>MZo zMdKRBg=6cLy@#0#dd==kbjc^#bzD5yM?%DtssGjTXY^e<~vSmXUC@#X&mBD$6>Few&qUSb> zQu>K8L!Et8Ku)j!Fyyj91SBMgzk507X*`uIq0AEnvFqxX#^Qsf@beH;iBIm;L;E?S;5u7Ik0JQIy5RR3 zxjw-!?cVBg^$5rYAI~~wSQCs%%GBr%u+m9l2h=2XhFXd}AR$3a z8tAOCvQ*v1s?2QuG{~8uXt9}w*&A#|W=i{tG;$@I3*mqsJ6?bFktP8 zk}Fe&1lfSp8kUP;CmR}-+6uD$FK7W?;*sH%JO(5rh?HT@9afgwQpCIlfrWH?*DP%$ zqm6jV4N=22Rv2L>h*SF-MVmpOHKrB9PG*U5jSx2DE8uc`j35)qg$^F;4E){h9I%&|QO;)Z6QcFwr7tVsA>) zXH`!$z^p2Lth2Ewo8qKvSgOOmNi0&-&%tzX#|!@Aj+d&V&BDd?qn-Jp`)KD%OOy5% zar(WimYUYyFnDmJ90F(gYUB2GSZ{oLTC6tpG~gn%5;YahXpy$@EL_sFKQTs(eyV4^ zMCfBFRRN7nakjHs3_7Kg71tJ1xRZ5Rd%05o7c@P*GJj|DDd7+qOv-{?!4MaE;ap;O z;hp3RS7Zc}j$bUjse$NJJqC7K{Qd*l&DX9WV%kLKab>J1p5)Bb#v4pvFQE&2bX~%p zA%z{sy9(fWPZ(ZPupl`Zg`OnZjddp0$D1`oeWeujl?Ii%sFwzcdW6nwIgpN`zV&~J zcWP^lda^a+X?f~Uxt3NNRef?YHVL4$;wFJpnR1iB$C+}gPLP)4{U}pLJ?@k!eawgfQMVW8HY@q1?;EMU4x;kDhG~ItI{(GQL^12H#AVt~1{xV~D0_W!77P^> zaQGH}aRX%#TD;%17ckjeCDP_NlN5c5$;-(p<~vZzRgfoOirLymvrF2i-@F4D2Q3+9 zbP(Unah9ZfgLH7=ziSXiGs#@BtND~B0gXhaEZvz0wmYr}BB zj3`y4pU%8m>&jALs2XT3zyz8WfoSNq?W=EdZr6sI%k^0Itfna)gepQ>mVn_8Cb(VF-9juod8+>VR{fihD*0KhFK2N0SWNXRHrvrQDv5L`4GTDI%CYj9qx%oWxP2j(>u!Z&?R^I4j4%Nlvdw^5G z<(f5-N^FFg(}NF0WvQ<)PPKy!Hn|e?9`f@#`8y2qsY%zAso_?pXzES$qwL%g89TJo zKROFiXbCa~zi0_ECQB|s?#FgZx2nF@M(#5aOPzO>2I(Lw?{9#HeJ(1gn}}TIoS}6< zQuIb)bSQ0&RDXxkKzL)s$(SUel^7UgUvh5poGfs+s4vNfU+7EXgOK6vEXtNUt9-o( zFClx8j4Y!Ui8p$Y$%v17ky&Eb3TOY6&X~YEkyZvpdN>NZe-XaYKeP%u?$I)^;(Vhb zMnUv8U&&I*zHh?>vhS8ztj%vVm($}Ro4_t`>bJ?rHMRO@vSh1&*2tHwzB;RpR{sjf z6vJV&u!gzS?(OW* zI9y4ly&3Q!_hu-E#pq4WGlNed*iYb(e`^M&u&o)G=cPp}2d=H<;GZrS@TSoEJLs^G z2b6*K551U}y=UBJQM6!sOL1~iTUc5CA~96Vx!;+gHp&)x`{A) z1;`dr=WiMyW_EYBv9`A~0f1C>w+qOC% zRUD%10p~QUiy;zuTiqFQTSGTU4%pUUE#^fJ&g<-khedAcpcZCR`)>MO;J$|b*=%1! zY97|6-dhh%B4*gz(F$3E*QKBCWit~)dkJdQ>I70++^tCNB?uxVFVv8G37&Y^Iq4Fo zBj=7e?ILr#Gcv-2LGC4}`8)}BU#)XBQoVCT?lxy)si}~ztXnQsS#lQvQc(TnHfJx@ zdJ7kO#p(Rglofta>QD4=0_5%i0aC!-1J-+aZL%+lFs#j%5r$LgmP?%;*CnK_`v#30 zz_9wvcVqn|vgJ$XK)T&^_73Nt>hsw$s(`<~jRW2$&EdMsUCs_-`Yz`d^}pHTd~at9 z>z9lc0cJZ^{Y+YHTrG<|2UT$IK=k)X$)sXYwA*>9hmC;Xa=4TmegvJxG)J-eJ`jg9*%L>hbtYgbU+;jrk9!IsaVMy0j=vsFW8VcHe(;?*LGj=; z_F3qW@QTLjY&nhP2BYi8`&71^#`b&4Io-+&h>RJ|0`d1#&Nr;raC&g{-a3h=jQP;Pfuak<0ei?}zSoWk9`g zwmPcNNyN?N!}nRY@G84Y3Wus2bEMO|K1Z(DKl7Zk)cSN_G37~7Qv-_%ukwtHcFv*d zlR3ERUSK`Wb7o)T_F@jLC;K3m-JM-v{hk*i0A~USh^}##SsUdtTOm4?Tv|1^#_=2k z0E?70Z#cVHGk69P02v2gg(d&>Ict@!HZlE0=WuI2FGO%%I@~@yhv2#-+;W~la9uvQ zQeuZ+cJ{N*Lm-Y1cp(D*t`7Vwo;H?eJnw6+zyx1+MC<=2|Ksd#ZHLf&$>c-$)>a#fQHPzalulylVP{LL zgO`Jz*e*uD8Iq^w=8*#tTdOk()6r4Q=8)OLUiw*ZtODV(*| zCfbfVE3B9E6c{;6#nMkMc@qNkT)nI&9JI~g^0%FntrIyS8sI1Rsk6w5gsEnQ1LkJq z-+^Yl5Z?1~CX3_mIJ;Vxa47zPURflj9d{O67x7#gfD9asB#!IyXniGq9xDn$qDj*P z*kI(Gt!zeoL#z+764GalJ`eBH-f;p(x-C2}08yw!wDI2%C5t`pIe)bt;-LH-MZ5yZ zKEKf|GTwK3nlE2du?8O~pl}T4`>ip60)1X~P*PwE%4#0YSlr^=h_J+zT0&~gfme;_ z9xqn?k)37zo+lHjG!^5e{i4jX2$+f`iL#HJ&#D)|9&tJryrdYt6mC(XhwQXYbRgOq z(TQ>A7mCtEhsm z+Le$ifKhQW+tuDWlCz8soKlY57S#6N#&@Dcp-9$aK#wK1HjZz$#syb>w{}H}-#&LH zU1AS{9-TU*6CDk<4&hXxnZ;gw`3aKr4v z`vWWohTBMlDYn5BF2#QsYk%re z?3a4ECT=?Kv|BrK01YBa7s{eU1yoXs)nJjW6=k%T^s_V9I+o)j*B$ z{B5_(Q{A_3c3rdfh$~!`(XaY~UA7H5R`7P6G)wQe?!q`z(nxrEX;_%BDZm-<#>T50LpwQEdZ6Darc12JnD%3^!sePgQ z_upTELo}WUfC>KR`iX!J;&da|fS~S6`%dx(i)$TnuZwj7#}17J7U1wC%RI#Bp_Q7{ z^gwbGOdRpRF3)pwT?yj5`-j(Smk*My#siL~t_*8DCyj*H8B@6M zVv*JoHOg6iFy0leSW9^o8UpGo!+t&ta?sReSTnbCxOlpm>m_I~i<^U6d@V;zW;o|! zVq7Z4XmaGXB)W#x$K+;+N0MCW))|}lS^9t^9GIOSed6V=4= z;XsZb^m9xD(cWrk386~JdE{wHB{bBZYVmaTVm$pN^%pSYU^gO)+PdP!V=Y`6^ zC*90q{g#tOtVOv3n!wkRwJ&sKuIyGmUTkdJaJ`6{?vgQWz#xSuyOG1$`QhT#Hm+SE z{eUE~XpO6-bpR6Qi#?%bsC`^=y}4F6sT{mfVeb^fI})h8Crq4IhN-=J7pcIRBCc6T?81R2#ookkLF|S7f|22WV_d=r{4bgjHeDM#_ zIB4MzeXpp0aO9-&J}gB?UMcFgqysAN zOtFM%9@kjwH4K4N`zW`r_USy!Q2QviRQn>HO==${M&?7P0{|FOHq;)374Jw0C)yp! zYKgnH+NTw`(xFw|QQ%7Jv;jcY3YL#VJY4HNIbzZ}#VfY*WYT(%z?z$R5z;z`r3+rC zw#@c4mL{z~gI}ceXD*`k9w0H)dh@P9w4N`jHl4MKvt3xQLC^F{bYnlJLy-QM4Hi_@*UjTOCmxo$2EG8|N{t$$mV6PlBKU7=!tr94|a+S|3p zI?}`zE*p>KDX1-Vq(?3rm$Mw5;RdCvuk|{H0oRVl*@EEoUhAQA+ajVrxCI~e1KYfV z*Q1rc+dOh1cscyyPUWiCN<gX+*l#M z9dpQ+`m-~5Cka=iSmDF4VY0Hw(XPSfWMblX$;8(N6UJsw-VO~7%FUkEF0}~9CC2!m zb*cxBbvYEZU%p&i3|a=dx5Wj0Y`oX-;e@Ua{GgU0-e&n0vHI8OHa7UsN18GCMI+6a z{JKXP=pM+&=rh5!I_OBVxdBF+stM3D-!aiuV_n2$L)(&W;wdz~ECLM=aP%*|j^*eK zS2h?m*>|Xo#rOBjjuTC%fDNx_xa3F^1iM$j>pbXo&dv|${$aK;!0T$OY!~yqt~Q-^ z0JK_er$7{Z7?{U#(lBtr>zZtRk|)zJFgLK~ZeAp&WnmvtW>vGSuk&PVTG}g^LVes^ zv3r{9Ny|yFliAlO8P?OhtkJW50)}|Zo?knT{%yYO%C}=ZUsn!iP}ABO)ahFwK474Y z4FE8NRJodqBmZ+oiW}Sg9xFPu91&^dW#uO86Zx_ie2)ipyXno%mrZZ=T-O~zo8C?JYkKEybhU=Z*0Oq>o1&9GQ+=k3Yp6#@DKg zG`@8B#VJJ{AZWn&HqiQDz!j70?W`kMx~SOaE>#D2kwI`?11B)0Dc>V}j&LBaO!HYzg02A+2_3h)9!ryTEy6Fd zu0>s_s|#vf-=lSX71Xe9thZsc7OV2h^F`50SEY5Wi4B~;ZsI9qVr#p|o^CbE(HX34 zAZo1Qno3u9>mG(dc5*>*dUunZO}EvNM+S6zmw@gI3@GJJSE_PUbh#7en7a`Z*XNxa zH5m{F|E(YJWa?|~2&{R67a>dFuyjEo(PRnduryi1dHf>17ObDSql+B$eqH6d zDX2XxX#jf|*t1*{f0aN`qv&qe?N+T2DDyRU>UZLJ3K@k~D2<{q%h7qQY#@>bSlcn+ z(jJ1K^R_L-erLL^jy$plrLeX=G+*aRfopKw>s*B?Z4nc^*RVQ4B{zd3YNf1 z19%ZK1rA0R57JAfFcC|WDNMpIGKEQnb^AY-LTL&Y*1K*CY6=_bX9^gw7B%;ujS|ic zu4k8+4pt>9D-iyfo z>P*7A&9Gj%M>O6H>l}LlZmp@uCPc=q;d+jpyqT4oA#S#xCzDAm46Iqrix^Xn!#tU0 z^>1PdO+6MC$_Ui-Ev`kDFADVu$XC3EF#-9!u#O4H`9e7X*@N}?1SG|vQJ;XEOKcMjRLou4?K`_>!@qr^SA=vUkivi%aCRW?zDfXS9ra2)}4OuMC$2XkleGhKnfLHV7vrG>88dzOuYDqq-g4N^*@A z?AFOCx(>f+yc~{7hDIxoc%OL2H3IsP-2Gr9S9W7Zx)%VKc%(ZFMF2-q-V>`^E>9I( z)`Uijfx}`?XxAevB%13)Mn89pb$ga|61Tqq+s3XFgZH=xTA+Y9IXu>FDybZBU7j~_ z%Cw2sIFjol^*CJcB$GSWHP$`W>2~MIGv3jA zV!}jGb+fkGbq4BnH7=WoemmwG^}cT6;K;&!k^XK>$K(xIf;tYp1+gk(jOMnjdne`r z?Fj>pSUtmCn&LI;>9KoO4^X|QKEtr27^R!YkU1;e4fm?#iEgj7ZeoFQx}j|7MusBZ zx;dQjCOihOnf?~HAAw-DDHa`m?)6j{WvxE^p$<&dkb)|{2u9SfIwor+RAtMNtD zQ;Jg?=f$Wki*Q2|ZF7qe8(*HQiBoU5hR0d4CLa+ZibS6`T?Mt#R=w%!719NYi>>(! z6F$Ygn<=<)XL zEE9_?_hg)Ft4(GUtzPOGsE#j^hu5QzxSIUGHxvOn@Q9SdlfxnyUTBDTHC|AC-+RgW z7TvyeO_V!}4<2@}IiJ|+yqEOvACyg=&d6yiX|=6#=(C{~?tb-4sV0r4}`9Yvz(#o~6_4u%-D z7};E3sw)>>_8D6r(KHHh?vg|6tpq$A+hRf*k7Cu z8~Vk4AGtmWu@;+*ITHSr9q<`pNGrUUHKJz4v@1~B@vuvkQfRT1QYb@6QfiM0TuPQ= zl9Ff$*Y8Wk?mK68B$G6BUiE7s%E zCNV+{$&BNYnJpz_0Xq^~zrH#_d=h_?UG#s!6Mm^ux<;4MH4HgP>83y_U8zfHgp|_K z@F|*j;-e`8#paw8n>fq=Z6dn;kP@K@2D9FFwni7^2%jLU!Om=o<@sWZ=&-A82d#!- zGsO2C7vCF9d^Iz}Kz!f0@-9(waQ0{Cw=SplG($^*`#4Z=`*gwWLBVa(&anzOd^hzj z4{WyI>%8ufys8gD_ksIKa|bQf6zHb#{)m-D^8SbwMe_a#Q^%>#0+tua$>097t`$~Z zK;9p5%Q@Finx`b7J>snm106=He*nL&UVUzvxaCLJT&=eO7@PliTM$g%UL`Uhf8S58 z|7usU8plSthp8h<d%$fy~vHB@BPW9dvnPcFEzn7cn8joIs#igRZxf_8g4G9{eZ}aBN+Y$rrwq&Y1fF64 zBaEPBt=(5@8_k7v0`D~ltOf!jn`rxZIn>4Op0u-7+s!ga7e~VeG!dgenA`>)2RNVO z?x4NNO8EJCjq~%aJ& zb!$m=s2J1TU7}igiPf)_#EYk0?t_+&5_Y0k=LX6Oa*{>Tb5k7J z76zJ{QTn7Qn(8BG6U!w*ohx$B()O@a63?dU{l)GsipGlvP^4d7<357m!z>>lC`>%q(>+-`!?K8~<6=TD_q`gg5m-!4eR=s`VD3{oM<+fRZi56aC#qnmtHy>Ir#qq&CiI zvh5|cjeFDBjn)raPV?w0A=Y2&O@uc<47ZBPQumYEEq@-3dyAclv}f-2JQeicvt2 z&wjACoXxz$GH7am88|gKZO+i0cE|;%y}xomoEr}srfJ|GtR%tyRfiqc$FNv}jTs2r zX3o%ILoSC+^S~T)$zf`TK5`y-0JMhlK<_9R_j3KHZU67mZy zognYfA^*pmp+nwbf=tuPFIho?{F#LOGfOAPpXrd*z9vQKkUwLPE3_n527#&xeWe9u zvJ8TX8K`BqIYUClYFx{^wD8ed87oP!2k5Y`W*Gzu46i z=9Igko25A=t0U)>qBomULNR?#xdAEIEv8L%dy;ozDxXu{Ycz>!m{Y#0YFik=&<$R~ zdKiY@_3q%q1!E($O$;J+xA)9+S82OgDt5Oi-kq32#Oc@7@rvXqeLc%P&GKSjSge^l zIZ@1>?H;1N#=(GxsJtvv=D5qWmsvWE6$W&D%30G_-nw_dC~0&_qGFLdxw`*cw@cB! zHwp+`1+km~3dmQ25C2G)w-2Uvt>(KQ(f(nn$13#lv>wCD2N0#N(S0F_vIQlouW>(K zaxHeaut>@@^={eEpb({;#-yxICs{>4^;X~{_Cj|*t$;zG!Q0bM&bd7-gXY|&EPc#Hc{i`uroJng}FF$}1B`|a-XP^~kAO2(0MxBGFen5B|& zbgs7F4*`8CwQzq4xEJ&1Q{ySmd@f|bO1VaZJm9uc` z8cdai!Ow9xCsm)l&;6aM?O~-eo&_&{XMZ^t-^ns&ec&FXzS>_L{J`B#d!1$Yr{FJx zu3*QJTt|PqzYHnB7$r`>+@yU|Lu@X|1OOKmUxg)W91G0&`&zz%oD6SxhW1@BG+%Qx zze+U92C@19cN?Y~KN695z@21eIJ$}Ac_o82>j1MY(qtSMr)NJ{adGe+cLJSnH4$3; zi94Y>>LGWmVoE0aqlji31|RLuRE%K$?_qb6DU~XBdj#g1o`0>}ew+L9+Ld>1bC+xV z{q_Sfbt%9*Jv~TwH`h}XsQR3COww)M1MKCd$hlZ z=~0pm_m<5IsUEQ1ZB?~<7+kW=y9P+xyo+U!ZEhPNZSygf;kV6)2Qb^*JHTw4%xtsTmqiCB>hb9Fnbl&cKt^@M2^&yM7+r zsdnY`y%2f+X)&y=*m-Vny4d;U>If4UX*x|>g(?F~mQ%gNN{Y7^>x2ipf2~aIo)bjMtJ<0$s+9VbhmQbP_j=i#r)XywL{i=t zQh8snbP5cgdZVO?=v6$Wt>v#$inKE92MU1+K#;0}UOnDw)!ewf+85hhOMg z;rK`jv*3;ctyXH<>+S=lR8mWmL++7U+kr;ABDK`2OtRsrMxXeZAsp-ztM|X*UI-dw zAgMd-Gf;MieOLxbC;F_XjXHXud?0Hq%k|6U>VeF*r%Ab}8^Dd2Skj6O*JV;HfItq{ zwJ;S8YTR1A8R)Q)3`l3VPSaa5}Y8mlB0^baz|3~9ym;72I?V1`d`Oph=e{>B7? zpgx!tXMJ$3)B(rb1sYE!wUynwH$)70*X_`17!J}MFH7by>23E_wIQ5;+dWNt`(G*# zH`hB3RsMUiD(8>8+ncM;1h?DAAnd3utTtxaX%N!zSgHFTiYC>l$leaGTIpSrKsZn#KANlQfMp)sb) zFs*AL{(BN^>@HRr!w;rnq_%rbxeHCHG^6xvk7Fa8fxhMwN3WHF;L!sZ_b>jqoe9cK=%W#z&eY z)UG`1TX(jW|8JGoy%m0yscyx0FwzeAw`$_e*@II|^~hSzebA(F7i+6N39S~0EITTfuBZz@ht-_nx(&t-DS{#RDX*O@9m2Fm%e!A6IQ%l66-SRzG~ zRc2>#2?1I;(Ney`0wwB+GFr3O2_2<%9PAgnJOhBc3asrhmC@*|zT6_Iqy9{4YiHE}z-tCC6T-(jy`El(OgF`%5YCBn804_c5 z^LPNR*^NB&m177wS?p`#Dbr3c5PtCQh#jGxQ6jR52RB3qK%OkQIAVre{Z?a7iK6`( z4BT&GauZLw^*1Ar`s)lyLF5p#DdGHBfhysi0UE0kNX8UN#?J;B#wxGTOXwo!dZmE) zDa})*buwdyRbHdwR0*C{)K__z-g_JjScLPp$hm6rt`*(xtvTrt9tz1b@7 z7$k;PdB@@xt@4f?Qr9Z);waD3+N->xd$i{}Z4qOO`dr%Hd!3Q$BcO6cJ(qclemavR zF8pUoqKN<81yAJQmiCnf9=XgL1hMzFA#$0wcbw;xwuRN8g|v-B2fDD{f zXqU4x1aznlbOOsDppcG0=bF=XphFo@o1it=N>-2{->O62z%mH(trGI1=5!tMtv<*g zh-wmK{~*h*~W5Pc<<)sZW)bB3^$SSY5i#1Vf$U(tbbe;EB+>GtkD0;c%7;2w}x= z7^V=Zjb#VPD)JRW%j98vv+i^T2wi8@J4`MddRYc79Nx$hu%zM@pXPZ|HC~VgB!d!t zxpd+%8dh!N3<$oC4#;MEb?^6)Mk|O98O7xa;#Qrstt^B5c-pJ`6iX%gwo3YV=>Yol zy~LaTFX*E+#1DZ!+N%3;050|YVft2GgL!@7_V~qt<5t~xld5z-ZJ0Ri@Z7ImV3=qT z(J~zLOlM}{Koojx7lz42L|zj4Ofg8&7jQWmxrmpkb(GW%F+prCnbTApz0vcOR=_bK+3w+Tzpk5Q(464@RJTiPzSq-L zD`ibM@BR*H6 z$Is)JoX4Lzk8PQ#lclIR)_J`>@0$=BVT%9gJU?gfYxuRCR%Li*#YU=+fXeIZ>6ul% zXp0h2q29)#?0;?I#3QAid~KM4M|x&K5POG~lV?_4F%Sv%vMM;ZDicM<72xD8VCgt? zs}sxR_Nf)-3^}f1F8NPm#pz)_*X({)l0e@lLGNJc1o}Q5^t0xSOp#l-s5?AD$RU$w zcHCTWn0mBadS--vuJ#?vC(K_<%zvjO6lI6jV$A6}ut4i&&d3x+AziyGSCF}=W5Jx!xvZn{1#>RT%XR0H)sfC+mvZJ@LNVRB zoQDLIixHDN*(pOYl{=SR4Ks%+?U=$`aeR_zx^_Jynw-mq>VhJ)>lkQqE(=4w3$)u< zDms@b-diz+NcG)?!HPgQW)VyPcX%Oav6-b~)uybfe)?>~732-Z3!|v7bM?afWIDt@ zKAP$o1aD(?nC2O#?K6tec{UDF-+{RMVi2nVVjo3&>mp!uhxzr3ff2b2JRZ4I-4KS( zQ7tLbroJx&Fs3n4=#DX~XmZhizk<8ye=|VjqF(@m#q)F*SO&T1(IY@j`Y7frNypWA zN%DaW9&|VLe>(F&8!!X4LdWTHN9d%Hi|!0W*lC0$trN>IT=d>7mFR=wL?166K%ai% zEgMd{LufAkBJ`1qJ{9OA7kzplt|=pQ7v11p_lqZ76gDV+T!Kkcy3Yu3#L*cyCCNi{ zl?)#_>T7rcxMy&8WS8qboi$#N{B(mJecK^NCjIp79G1^dkLTq;@#M(fTD@_RXQxHo z4~l>zbZJ4$ppL0EH)kIDTO0?{`?@%_)YDUYouvmj=%2DIbkLzn`Z7m%`r6nYxB@lWGkWf!e0-8oIBGL&>IJD3~YCwAEW$C?x6ulZnse0`q zc&`POYDcBm3(A|F-E($M^Sbe>+lx}dX7j=W^R2s0HjF}x zMbF@#GP^#QRGeRA%`vAdiDr@tuS8RcL<^}zwWGCSt4PHT=EDlC3mGNg*8>VLmr%ll zI$vU)YB|tTnRnx*)}HJLfkAsc)RUK44{7#8qyoo;YngR2J3~rwy$0aoHF?5iqU3U) z)NrTs)uYVaJ!P`}#pTvXmP;P`omN!>t>0eRwuaF8{(==OY?P2`Pm#(xnWxtY2 zjOFpm){jJqW-szl3#MeA^3sIzuuhGrMQ4|4l2@SVCxoi_IEWC(R$Hf8s`pY#Y_kSF z6V&OY2dNOksL4yOw>D%oNjd5eE;(}WvNhaA`RcV02H8kG8dptT?Gq==K`(b=(OwI# zE}2a1CBIyFlzEX`$6C4pANdtKC-C9xtU0VF!H0Zwmwa?5<$m@(f>a?3-Gi~9w$66d zEMUGraZl+=33`00o+rc3b2!V|y_nRbFgUY)Ph1m2XM*8b}!_%Jy29&Eyu$0tR(0KP z2*zF&|6^i*Yy|vog8NnY$Rs{CiOPjov0#F`u_{Dhsq!86orlw>@m& zQ5g|g{OnP%=D&oPsG48-weB``JJ}z)RQwWNv|!jjUSqF{x*W%k9J7AbJ{aDAd}#{L zkG@kKQeL*kg(**4BMcVbTg%cp$}v4e*U8a*<1*r?U+ zQ@zFhx)lD|N$Z$!lmpCGF`nc zr}$4}FZTYb<+qFTqwm9);9b~vcn^}OX=^MJ1qo}%XEreAiJvJPAJ+8g6BQ@T?JXX^ zuELl9Rk?;Gt`E$Y(KTwZ3VpOyp@$G-#Ej{KfqPZ=RDV8wFw57keTtMj+5S)6iMO|t zdB5MjF3vxEU3Ph4`+r-@8m6<4>~rx~^*KK}_~A(Y!NrFv^V=7#rFhR*t*aqXbn8`! zRtFL3M9-W3`(P@$TtKgn>Lc%5JI{^RtsVY(ziYOu7`^!~uUj3gH(^3_ez{qqfOdY5 zKJo&#N8q+Z>m|0DG!UMyTr>X$E4&Tvyk$-Cjt{ddNO2P`$|`%PLZsp3P}$bB^^q54 zHSZ%Y$_mn5?q+@DMOiuLAf_Y$+^{>HJmMYeeD(=pD*q$vp!Of?0`Dxc;{J4d1mAt$ zn#sP=6!^8pjzMujNV;!;D#Rh_f(zEZ%;>8}^O*Jahs{6x$iv3Jfno;1O%09H`a4)f zf2i2LGAH_*&{zsj9Bot!MGI3>J^pKLTIM_8uAmq?j)ALT*3JL3Yz!kD@@l_YtDFDn zBa%`N^G;t{Bg%><^2NMN!NPaE&3o25@i#;%9S-jixvMR*_lzS29#spuyd3rI)xQzIt-G(oMA(8u(`xMFTfef_Vh0FB%J0^} z<{pq%TooQLr~IoQra~Aph*yPg;{CsM+W4)P$3_10DF*E$LLJuL0>ojxpYV#{ii)>U zvkA*95e%1k(|VY_t&4>{ci1mvK`p8X8_0|O(j^IbSaW-x>|~@^4ABne&;4Xl;0ItE z&gAgjcVJd(L%7qDW%ienWs+JgSzjete^QH*K@=BSGWY+5WNP35d6bNhSCS_pAsM~*D58~DpHGi|2we?rC6nC zhry!vOwlSaZrx=ntq$~2FhZYp87amtgO?0^B)k4AxbDvgds?!qO0uh@7A3p7&{D_p zYk&Eo0Q;R(qijF_ooq#NgA7LT-XIx_>exNdN683%Em>ffUGfU1_gdfXC$~Xd=_j{A zd;;zR9vCP|Ot%-0+Uy+4drYuf`G}9~wRqxR)~XdKfX94=>LIKu)|4kqw3p=@{<20F z>6Qy+V=lUCuFJ zA-RfM43D8*(fzyeh2qBrMSSgUeLtT1xZNJFM@v~56m`-}afr35^1O3BqxgEm)|M?K zRhV$ljiY7bc^U%3rJGG##S(N{Mt;<^b%@(0fH6kfE`DK*wmnxqkf4J!)H6EAk74$B zt7)t9dj)hHD2SC5l8T*@Dd0F{az$aW*&QI0Ln89ibD4oIU9tJ07 zjR9T)cvbo5@Hm7GX6Y~bM)LYe8HxPrVmm~NNg2)g?Z+}{+4L&5%0=1(D?FvLqbBP} zm_pUI9S}mbJ%XtAp3~lFZ53Mtzg^WA5xOH0zQRm zN3XJXU^8j6?zXU0J53Xisx1W7RyK@1{K=ZOdTbvdg$mmhN?}h0QCR0>dn5i=EnBT{ zl(lWZn$q?pYF=2&1|H!n(6Fd0Wf~gm606? zKdrIN%G&zD8!5bWvMtF6`oeFH4t&-WTNvSdXS2~j=_5b}(nFY6t=Po&v@wmp-NaUh z%^>_>?>s&*ga=pKB!k|_^(6xLrl zBV!{wOqyZ8T+K@@!cTsi*@!($szm1)hk0^KTTP!P_eI$UHDg5CeCEzaBl%a^8CB)v z*577Z0!Pno+HAGi*Mv3H`{$wb{zDMG@Yiu0O>!*acrYcO2TT+XP$;D@hO6dmNJ z{mV+oj|Xz&TU!e6_gCg{o|Jw+{0SsCE@T4A^B+VLiwXC5BPscjVZbvNs8mGuI&p(b%5V(0p$Y z&y9C9WFL^)l+7+HPc-cfL&$v%y8F1RsZYc?tD>WBn9`bW4wAd|DW@pz5B}o5ro}au zkgm<)%kT6k3KzfHb`^;m3>|u~RaRA20e(??F=GaYaQD>*2O7-zbubyXFLwjpOBn`X zWw^FdcCfUSvVOE6Cl2aZ|j!9_`0sP zL+0qgoRvwd&c+a;=(k6PQsC4e3Y;+j6u7*bt?ECVFFTdCcQFR@GwW?N*f7EgYHf+X z)`lpd25POr`|sVdy0Y!GZJ4UtqNz~TVJKMModIvw^|HnAFMHUgz!taMp0---4MH7t z_(~`p{x^sYXZ5mm{DOmwKv?UA@xi{caYbtE3Sk6Co#inKJaDnxQN^ zI^eSvY(bd-(GE$ra~z|WCWM!PX!969ve;IQwISS~qDP4WIyT{Ea3Rz~k4f_`Gqzy~ zet42CpUoysg|^qO11GwO6r!?cKgPGtv$ghtzAwt2>E(+m`{?^kBl+zc7I>bsAfpDK zHOCgslc(DlZ!^`l*z&?-aJkx&j3jn~u!)`U{NHuLtAU*mbq}I|r0KT$VYpcH85oFS z)%*VzL=*fy~5Xsa-N>~{<~FC`8QoR|8~u{{!o(u~sl@M2qaR+=!9Uo)*^l=wGQ854}PHY0}0 zal5rbb}8P8XUt)lq@{P)5c8s+5_QLa|5PRX6>;(#ZUwYxNmp9c55Pi#*1x^a<^w(nL^9^dyO zQZ{#3peKQ)Y`btgNk@KqJ!BF)5+;OZ%Z(ESbR@S^vg81FYU$dT-`-&B%I4Fy;rU?m z2~CB%hN@ymd55Tu&uT-e8^_oA=Qp{M%p1e_?fI^{>|0U` z*_=V-PTzRx*bY~%FmpM^RqohjOZQ|mwXRjhp0B^in z#he)a(IHzbn@4!ZK|ec`0+$CW5Mq!~@V`oh7nBN5oUmcS zz24fBu)7*E?{KR9-HZoWnc>>P!d*X?7@p;>UA}xTP7@zf+ zl~5MSg}1|@xy;=J+Bdwwd)Cjsad@JF&p!{}hdzHHyzfKF!!5l3`3yUQA6};;lpFo9 zD4;W4Llo4kKOD`y5OiD8U_)uM@FqD(dlY#uE;W=#nWs#No)n7 zidtOqcUs&SsKrxfZ9T&9l5lO}i!a%lu!V#VRN9lGfGTaClxdDq+NlpSiW%$-Z5F1| zPI?JYr5!zAA(9_`)%J?zE9l^5pJdcwHwaPG*%yDOvmXO>hPj2SufoBdFh5Ef*ZGP! zAWwXqaD>_`Ho{MPSEO*CNbT{OnXd7iy>nmuVEGYp_5$2gagBRdiR6c`XEfr;2X9s2 zhtI*LrCHZu`%>bFszv$Hla``<=sDZSBCUW`-e6Wv6ZW8Bn$Ff~BSOs9?fLdkY)$<( zM|Mcdtm36rl3!WhCMwK;#NrrX;iF4uR$=hN%Njb&e*Ox!DlIf0A-?%;;-lWXFUrl+ zXsL3qKHo8tSFN5|g7^Bb?K9XXnEsxv5!*z##QA1jCUMrXUjK~ zIA1D#z5PSR2tM=reHm}nM@nM`+*DP`8JUrV&TBvdUdG6}4%>4&2(GBHwiy}1SRdur zzV@4Xr+jJ~5RR%c`OME?7hERc0afMpSJi_`oOEDL46RMSXN+evXtOYf)>KV^=xgn+ z_K`g8CtC@=tVm{Qe)~(?@5XNa%~v)%+e?V!5Zf6_Z^r`lR`rH$P#Ai%Y#nLgql#zN zWAMYky=|K!$v8D0NX+FC!-XLPlTZxmTL?WV1oVf@9n+_I&z z2S#cBP)m2EmI6P@MUKLhMLCkY7pGjFig@4we(lYi3OxDHty*grrAF|r#WKT=pe?_8 zGzdR@H5e~grUA=OO4#q!*t_w)Z6Zr1f`u6`n+-=vTLl7sW3Ld#URA^B&inmrYsGpH znyAcfqeA3=21;f6%nKWSu?-Jr%yk~6=1}15q&C?7K4fFOF(<6DwKW(3wXGif?@7XHyughh|u$KvA zsOQt6^n5Oeo?-rdGz>i(FRm$NughK}JfLA;6$NxyKCfhYRw`T|^5H{0xbYRZ3N^yIy zf7q9^2HU#ugb3KTY$Gh7WPSW4YcX0nfTqBku$R=TnZ5belJ@(tZ+Vo)O||9;JmHy6 zX8%u-bwXkBsco%n1K}1Gwl?;1)p0oiBE&5(vLMKdl-2 zIT(EBA>-=?!k@2})`CUkY18wtlUqG4!5_RGs}uwh@3EyK-jB~Z=BsLG6pW_x4o|+( zFp^J;vtKgW@}A}G4Ox4_5e|u*ybw0jJulFPApaH4#(PUfo`si5hFAxF_|7}SL;>{> zt@ETEr2&7!j$%_XkFx2sS(s7cu#eGZJp9xWHtMK_C9GQj|*0_r&z9n ze7VnOH)7XGwVqEdhZ6GJykPUmo$+n!g*l&ewg992jy?0CQiNkT>{YF2QLyia)0!~L z7&3V9I-!B^e#`rLa`GXqII8C_fA#!FtB3Y{;s>ySVq$IkOGTOj0lu_XT3yzhkiuS1 z853ef1yAwTwfla4=~vg@?H@W&-0RnHjQm*9kT8J~bruEGSn7|F#!?5k6UMTCPTL$d zm^8x76PMX2PTs-llU% zjOI3jL!OC_GLhw$_)9iGN@mm%Kx*H24jZfh0pO#H)62aX~?1$N9+BQtj_Oa60HXohk z%}R*mzcjNSE>d(X4DYC`ZL6^2@XIG*U>O@?ct`OwPQT%OriHz27+N#$jgjZ(?orXj zSLhmoD>}UIDz*Kl)RuQB?QzzU@E-1}t=U+#AGq_8j32_{5y+bL^9jG`sxzRZc#lfw`Kf3J6>`}r44!3Fkdg~^|GP?kC!YwR+ zB=a;|PMd`}(w1lf)RXp)ZV}11wXz>E3VEm2_L}T@LKD^XOel4|6sRsdM3;E0`KbtN%mx>g*Wd2$lDqzw!>NF>w$cQnxSTqq6Ty2>*rB*uk;BahknfB;S%{ zKV+62$J=ECgVE!BO%ry1ooQzeayBS_Twt7rn{d|V*#GHHeKGx5BFDi@F(9)#gCAZm zA#@epNEA>5EiQOd2cU|KlY_0#z|6_4HED`-(7m?y`j&Qpx$&UPTC4-97TX()HX($3 zbX?%>hW7344Z|=av-LO`Fi;**Jh#7iX};o-p^oRfrgyaOw=4mfIt9hB~%zjRL!>GD&X-QxrOA#N+^*WV8NU0sZ6a2)yt_JZHDX3AA=TG*`2T-QO zUGY_mY`*N9%8|T<+kUc$3$XBydpPQ{G=YzNw=x{Ey*Tm{xNRhdpULwJMPa1{$LcEH zh~d3QgyS|<|F)bU`?n?G3w>uVf5Dp(K~pBkOEcksN-m7G%O5kqgt~ z_~Zqd3G$AMg3TB+5nK|Ah zhc~x$Bz(dY(1BlS)-H^z8E|w&@D}SbOP6e?QTO6!&Nq+aL)K*uXMJ@s7js^GA1|ls znqtzhu+?L^288pRoIo3Z*R`B zL<4o-U2eX;dW_~nJs$#8`KHa8+kD8QhYJ85F_CwkmX@B-c8a`niHP7CVD3I^=h$1v zk#6wTK)>g{nA$$>m|zJnUwTUX!poPQnuwP#F>?75zp&mhly`l?z9?|K*PLq~#NH&j z!14a7F7Oa7*mxhtdszbx!0(%9AIL6i3f>zyEgyjb$GlLl8T;0+md{Ek-oW^X8w>0$ z*zbOo;_^!EIc>iummE(el+4!l*d?lIi5%3dwLi=aq5+(lRr7ptwBb+@d%cj-A&gZHXA{o6jH zA>_SkaRi%3j*R}Rx z>}$;c-aOp?b6wz}U$81XGshm^@;q$A81=8r8SH_{z@Hjq*gbRShdIv(erv{udz??X>G!OgWQ@%b!>) z!WzzG9miz-)0xa8b%m0t8mqdXwEkxM7S>4@%So)GC_pCFBt{yFYevVf&8Sp@4I<6( zmeE{Mfc*_Rh^pPP86W*)#qs9M$vnTnRh{J%cwE*@pBy6IUp!eXYZCeC(nfSCt7s;t zw!Ux!&W|}Z2VlH5bfK_H+AOjaJGAcyXw;T@s@(%m= zeDfac-ZMMx9ip||>glSJh1GW1hZ^i7Lce8tO|`x%=8s-P=u-9$awaUNxE z$&=5kci`mMm#3w?l_sJpN30#&u_5A^V`kqvRFMpy+F{v=m(k!hR_c* z7r)RCG@lY;)<{2SpAvM|Sb86<`nxCXj8AGF4~gGHcDPWPXbR?!!R_?FJwg=RC$f+8 z(Z{rh7%)Y8h`#VwM8<6c3A_7Dkv=|SipR&_K4Px~*9fqq_LlK|L<{O6vNa0nA(kGs zUt`NisW@3FFFE6+6!#_pn7rgH03I(n+aC3IU93a&3a zXSbRUJkIYp9r5e|f@=G__Doin6yRp&vX_2@i9{-POE%Mx`5=&Rx+w z%lvJM^kQF4kzVX`P%U_|@qnRn&Z?YNq;f31K(JSvG~yp$ z%pAt@D7d(On=D5jSIZFsB9|kfR5mY&%EWpkI)H~fUh0&+y$^LeL-B!jOdMEthY41H$Bhq{M(X?cG^*fr!TI zRdhiws1o*A5av@A7{|Q+b>{fEAjsXxQ>9a_I2E00Rc|(-pd^INjRp)EF*cjlQ;U_&IwCgS8>W=xp`PgLl`Q-({}0xB&n?(FoEM&1&e>5T0n_ROyLYi5Aoo4Vo%F(IA2fJy8KE5NyH4b*=tm zug@r;a71hCS8OP*vrp&!=4SoVYu`LQQ&!zdpGAmY7?j?_d~z!9-^`iCj*tp8w*#U8 zJ3yr=4np@q?x9NC*JbX3pz5W@k^8_@9@WrMz+NZV(AG6J<>>wmdJ~QgZT%wx?nhk3 zMITI+t_GTct+$T$GN;g;or(cjTnMJFu5)C^krCu&7{(?Vo@E+{fQDB@{6fPkGA%^7 z)bu0!^q}F=^7{}jb@;#vL~1^)6g?i z(Vl^!XP7W#$l$T#lw%mnXI+JaW0Igl9Yc9S7!!_p?J`EOsiYJgd7OW{$ppe1vn(Tp z7_$_J0*qPWreVyo_EY;S=7DMa!sl?E!yy8WeqtX89rXE&XF&@uG-<}hiWbUGT-oik zS$0i>eP$76Wd=XIeU4#W-skqF=DBHn+nThR>^!MON^gat^idE>xA!_)n7e@K5{^nf zgfQZn_2imh}~jolayD0gvtl zWw=q(dFO8(S%nviXJs0!;s1oMH(mOT=SyV0%Tfur=;UaPUcIU8;M>2mw>F`b2oXrV zB41n7Te%1fEH$RX<;EH9vP|F!;~9-jL6?RK5zjQfWgpH)5#s3MG`NaC+=|zQrLrDo zGYPmKuL>NrEO>=h7|sNsD@`zX!x=_8fnU30@4~hcFu#$nLKxZvLYTP1li%Ct80M4H zWeB4Qs}P35ix4K3n4Guc(Ud#Hy)3AsBmKAdg^u*!(?drvFvc)~F@Cl$4UAyk|Jm+l zmx(}_ar{UZc*qxof7gCf-fu8G+;BNIYY@AmDPWoz6UpXx)A@z(nlxwk{A%$TD5%U` zoSwkGBbDA%a%>Qm-QV)gzuWt;$}_Z$Ktc(2u6|oQ$(*55+V%WvMM~Q&KSOfT(!W-; zEeeGb;5PU)qY^7m0R9&@7w&>9eh=(X=Cw2bwAVDc@!@~kYot6PP`YgpD!NCNg#V#K z{8mUxJ@E%rbVzH*k^)ahfz*NyFT0>cDW2XmzE0c_!6J^B$HXrjF^|m%G4(dQ7c9{I z;T{CKvxulTOs44q5B2*J=+>{E189}4nfkTIl7&LY;Jgtad z(YEq&ro$D#RIo}_IYsj>GYfv#8t)_Zu*k1%u6bZhqatv~x!s^B-hXa*8A%W@j_oEC zywl?eQi#*zaZ!My0pu2mMVKBL|8}SIZSzAIqhgNyh_u0(>-`xa=E%=x$T@PWXhG-5 zcflHPj)Wh+bENk{D)a6Pxg!3HfFQZwLy?P^8AuLZq{=ql<>yN{DlZW_Y-ajIAe_a#aO zlBM`X4gqq%OWoY;h$e&Iqu?E<{^cA_c7l{+%zRMviG%0G6^}Ca&Lp3t-XoA0MPGnU zUtv#UpOOkhaY3Vi2T%cBm)Iauy7%zhI7foHbf&-4!9aT8=#hEDMhsRy$1;om80WCZ z?-8`9(^)}?V_|zSAkUOLmM%(LYR5=S@OPbi)g0I z9PazBS8lmKLnUX)y^)l?1qiOu-f&e?keD`-J`#V@p=z4;;L?8Fquq(HN&`l6#K|1`zXnVlwbq3yh= z3p|v=eeV{tm8&~vt!5u+~acqCq1WCU8|gh9E=Bx7dtvn?FW;?D_6)Fz)Nq;cNFee3v0K*DT* z^(6Abd|?!|v)Af~E?G%q#n~=~C%1BLD7@M|tFKWiiB!_$wtcqp2Tl#ZF+#S^4lz?_ z&X&F)MzkQl04`L!?Q|rtW&{(ug5IP6T|u+i(iKoh?Fy2BFud0q-#|1&jjAb*2q+DD z+H7giGYA1;UFCFB^_~6k*&sTcWh(p2vW3g zjZ{50xf+m)EY-4Bjv@v-`aj_hf#QTmX!sz^I%fztdV~P<%I6Cy{#U@jJyK=HJaZdX)Ncs66aF$sx4D+?3`} zp<6)+Vs0wATn>vQg}pjCJH`=1@pcE8A3CcBf(LX~N#YketE4$0oK?3R$J9V)RlW`Q zsSF|u`l(jBz(cfPS@?7OT6fmixFERQUFXOt-Z{sUNg315Q5nASENSPk#dj6lQ0I}V z*^}S3o*tf6++ZU~F@D#=Co(3GQv9R^VDgg|f%l05mH+^L(ppBEqSY^+gH|87vwc0^ z-pSFN4H6BA(VO$<$N*qI!GuNp>bL2;@ZwWRuDveDA0$x+>f{l1b&|*KWafUH0J<(pU;tBwL)-(0RS04UXEc1qD|F)0>nj|sv~}(P1SiK zgiZbDQOANno7&OCk;~FWYtJkuHnux;frn_phVX0(4*NCb9V^}_&2LS~8pyh83M2#D z@d=st%=N2<3~Z9|giOG8By}+8#&}|e~aR}eq!x2{ubA^SxZhuE&%5ws{ ze=fFzAVb}XjnWmlSW@8WGEjgZNpi8TiB>pZUKhV`z`P!6zh~pByg4_kB)8eB4vGyz!F?O$GcQV&`iFLdC+3b&p`9_8M-PV3?zUi)s_|pZ zx6H%h>pGEh0nB3$_amwUF``Qr*H~o^qwrFL^qmH)sLQ$hF!)VkB>!W6R-&cGTnn$V z0N(JcMPP(?H>&acDIwQ*jpxd^&JeAXi@)0_y+*kTq5$Prfmp@4@`{@P9*&mjS%P2f z)~<#n3wZc$VODLH=aHA-_Drk`Wl>iAWKfWSGJH4Mv4?FZOri{@^BgwIL69M8c~*1wB&qi9`ZM-x83O0| zLVjzEqi?iUqKcrm^L}F;%}No15K+LrC$Q^xEM)uMCX~QkKEy@t%mUE7-^#3RK73*( zC;&eZP;XiOhG3PO1w{dVS-AZK-7Gjy#WNA}v<+fBQ)FIh87xJ#p5IAsjYeQWN4uQ6uw92$q8+hmG@W>K5Y9Njg4ddTTcLX_K@UIy#|2|Em z!O7x?F7VL3FXsyq=Q!XoqFIhXaX~1!&%l8#k(xU&&l9&-$#+zRk3p&Vu(|Mz;EB!* zhcuINX23_oJ|?C2<#Yh>T%qKL8mpQaddzXOGuRDXE{_L%EefdrCM~tC{Y9Fgt^FYi z(AGc+csw9^o@0VpaX!!e+F6ZNo)6U|foPVWAHvjX&6lS3u0W_JmRUEP4b5^;v9F0b z7f^=c6Q9sZ&X=Fi{s4m%=K_8OQx>1le7OJB3J1pzmWYfan)eJ3(Rmp0_7$jcNcI!I za7gx>A0py?ZINS2V8pv%v7-ZP~*U0ES}_Ewq8TsdvS#S&bHd2hsNPLlPA1TFUB!J0fB!Tx?MxF)$ zTt=QHP0{V13^f+sQe%OO7Gxc19OwBfA$fG1U_!5ZofM$gJw9K0T?&cINU>qb0J@k) zb_@t(71^3?CR8zZY*`>vO+^;~-)hujQse;eWxfaq*1ea%! zxF1*`SC3T*I&|?GotpS7FCZ>HnSlFISF6W{f_iHcT8YJDbO5>vk~_>GhhPjBkYwa| znTElK=F~%Qf#%dx{6cf;xge-HeG_O&mW}X{b{r7|Eorna@X!m_yC;6=Xv+JZ$tum0 zr?|@TtFhT`eterlTy}{cQNgWn5e!#}ikH7I861QWcm4utb?yZot6RJUCV>O|;1-w! z@&)VE>PBc;}oV}Exp=%H)NsABo8|1Xkf6}gl2H~8Nj-T`w~Bc_-PdZ z$4=Ww3Ph*D3*Vy-L*k19ie8A;e3X>Euw2N}+L*zYi|y39TCoXR_J#DgFLLri2>**` zXBk5fxLg46z=d*K zG6#Xg$UFeEb&-tBp#>)W0sv|(lF9zWMg072N45#9V9q@NkO(KfsLS5+8JKrkrFV=Y zKFZ^7g_}eFK2flX{(X}8h5migqM-hLC_kDtsVMLCLa;0$d?p;hmJ`|0(--Ih59NY& z;bjTYqm_QiQH~!u0fAEx3hph7qzj)9T_|@lZa(R#X&m8aPdeJhZxK9E7rsz4DFdfA zSF*+!>^V}5%k8Vx>=FF-)vS7!vx_V|{u<;BUM4VlQ^n~;A%f#`i*Vmd)Dh84dZE7X z>!}Eyl9Lw0`(MwB;-d@`%{<8^@wh%LMGBuuScR51AglKON#<@{?M7| z{O{Ep@Ps94v4wAMS2vM0A`OJ%*G8C0X8pw>^ln|u?>yb4X(=DQ^Hx2oG%;&0Cd-oQ z6suU4R9!5WC8Ys@Se7uLAeJRm2=M){vC*U@`aCVS@~6XrkZ|J@zsp+7W)X075*l26 zZ=AkZItgfoPC^4Hd_&Hi_?{*fW&eN8e+MBdTBLSb{htlOn8Z41Xq(3U@(wG3XqMO1u}x8klr~q zH3&4CKZV8!u7-f55gcX38^QG^_%MR&Aqvolp%2iAfBeL8)H12S!ar%3Q=3g84R9qn zp&*0-&nb}M+wY=tRQUGhWk;qt1}eN+g^?7WFkg3pG~XTt(tIBQ{K9-G`yzB(b2U#z zhr?Lzzk+%6>FJE#-%Pab(8d z6+BbN{-qYe>)4mGMoabh_YUY5q!2B%(NgWseVT;l(@_KEOE%EtWOA3cshqu>b=1XN zu*Q#$Em?#o8qQ?aomAm4?Z}hw!hr?a1Tt#1_|^FAYHXMvv<1L;p9HvUpTeW3?;t>_ zrzgCL!|ri~aaFQkFwFd=;-r|JC%$8rBQS_@S@Ge<|jy!^#IjPcH7KER6JZH%3dL1G=%WYJ{_#!5R~ceqyvF zRmfUn{$&Ygv%n_Vk6xrOKNp6DhDGegf_thQ~-Dj@kW!rh5BAbE)v{0U6*j zEMqk?Mm)W$w`y!E$5y4f^DTa*Rxq_Ul005eYTsPLS>0gYX$=0|q~O0+GM&uGp2z+o z;OKkw%vfxN?m(36ub`4CtbZuUzV=tSs{cav&!^Bojk6*Dc>&?#wT2WN(EthF=#V^7 z*V!?agdm&iOXSDct&cA7(7Z4E zuD)vOEXmW7;0$aK3hvP>H;Rq$^0N=wb_i$#0hg-sjupegMF4mj_8xTygGQfh*3ytufE=&MD63 zY?f%C{1omO*||dQ7}-fM;kU~-NrB+X1W4QhOCj|Z*o8n?e7x*1#1Y2F%f=kKA)3u2 zv~lY7q6!hSDB_1@#@0c1;;WacMe#;EX zLWaA4Q#i;rPE(KvVMec%2VwF_1s;SE72+VwGE#vDVW0vJ!oZE-pmC1hK7%mscCVCH z+jS*ct^e7yVcxT8M|tHmXVZAMAVlrB8=&l)dRYu?Rf0_vc<)oKrl)|y{MY7APcooC#Hp88MH|$g+H6S#lc!!Ptdd(1Dy;%YWqfGKx~bZ; z7q?38V>e7W!4g!Sf$4sAB{}#qa!C3S{&8D9M{AU&C5mJ~sn5K$BP?Lt5dfdPO4>i3 zdFeyI{Ww>(1ZC1+3SUElLVtiGs^@s>g_wo6FTmE&DZMICpi_EH{6eSn+Nuyv z>4nbVhy!kUTh_(7f?Xr5pl7rpGVVVEUXOV?F}RG{mE3cN!qiBzELf(pDt3h-8oX&twAN_HofL4Xi#D}}Zz zsX(+)ai>U27t19Th!!e5Xz{Y(Aj)#z0+M1o;D=xa@-t#eFK5jXvjLa9?m2f_c4a=L zm$PpCEujwT2tOkF0Y})l@Y`N+tpr<4_`q+9=Qp{M%r&d!+i{%K!bhz^<|^Pa=v`9V zSIcLJ1TP-lQf9Dj+11&L{_H*% zirrU&uwDn%|iUb8zsZ z*NJQJbwft`HDZXfMKBIJ4RO}=;Q;d(0UBMP#qY(BPD_g|yf?%dVX$<<9V!iaH-bBd zIuqgXt3E@WwOBg>Arxn1{~ha(tO*>FGln^0ga;VzcYdM=R6mLhtFef#igXx$ihFn;l~80A3d znskbi%qeJEd8d)i=s2o(7zda+e^bvnqYL+rbpC3xX9(XoXKC^(5p`^hn1x&L z4lA>NWp9TDS9gfLzD7>MS65{}#4ZzX48k>b^+oAp!E$R8TH)NP>lM0JpaL#DD{MU8 zIm2Lg2|hn=)ujHbBA+!8QWd4vY75YYS$?f_cNIx3c3CVxvm&Hv)L0uhzJzg-@ugTO zwU%$4?92$HF02!>D;=je8!(qIaVtmTwEZ0iS!;tEXHX7KJr0hE%CARwA3_>eiomc4 z2g!I+l0*u2)I9;9Sic@pK(dEo3O7%4HaA&5K`wfTAXVdOIzKkwS(SHszI55b5i^~) z47QTA!E{Pu)6^ukfs~>luH>a>JBRs0E8l!55W4Oh$iN22ebNuwTp6GO6@o1zDww|3 zUj<4eP{EkGa2fkc;0^GrC)kXivJ~WDHJlsm&8}sz9|;?N%2Mgk+l8R4mkd^x>yeCo zR+95~7D6_^B&j$fJ|m`ooZ6CAC#4?nW1Ui~_<&z{3Bb>P-^Rt71p!~X81~&$>=(XH z>p+H@VlaXWbFae7MwYI}-387^Ee~_J#BkiuO8iQJ)6RMj)VR?nePYqbQjb9CgaPiF z;^yCmyz>HQLw;z9vowEv87>EecO#@K$>l&7&R5KA*~;t)e_w4K%V#Wg-eog`;kQf$ z9{g8xL+45G(|bC z8ki{vVr)@qRkgd#D1+w|R(M)nB|nhfg46GUI-p zv5MsNeJ;=PQ8tlq;yRd1b4U6@Vc3)wB1l@La=0fuqvr40KG9)0pwgC9^cYBlb#? zz}>TI5(@!bstp(H;Zkjc_=QWg5$i%M)h2It{{OfEZS6LvlW*JNoXzGDW#NKvwl46n z9_HO=Kx{``5VY>q>*UgC+B(nDC~3Ph-q_7^w!_`~s|6!8s-LMjlb_znk5l>v!b>nT#SMg4NE^)iejI8rf4xp7es+r% zD)EE2^nL)=fj1Ds53eIb&_*(8F>kFv^Zja$#plyv>f77$4M ztbg(_Opwb-sqh#U0OPaHXE*bKN0*^_Q2FP%ib{C_VXXp@tKEw595j})R)e^(TsQ~!QFI`zUW zFFVT`=IssAqkm5tpo_f;!UfHh-Q6Hv>~o?8_2@S?D31<5d_8*E5v7_~Vm4a%u_2Mw zS=>flEy5w(YaYEZ1i8eGa<4fd2hmW=;vAWP>wQlG?xI;c0>|}fI7Ol*8H^_Qza@w$ZepKT%QuTF& zbgkSwc>9m+48v@>NzQZ{UTrm_@Ho>E@6roIM0WrV3TL_wf;`T29mOx4={jx-J=4K3 zyjCl10H1QnxhUv_#=|?M;F(>D@qSmGrPs8{X~aLh4C#_#L`^ue4b}x7p$hIN?eTFz zD7YtWl77A4CXZk5bIn=9fRnt}oH_B61W(jS5710XzkcF`trAbZ?);v&`%*jiT>o}U zX*P zXh9wP@lDFX!;c^i{xhgX2mb}B_B#0Mp~&6dBpo~<=W+0Ypm6YTz&-J6XPOzYS^D?L z&6+;SQfzYwSz@22xbHjXfi?oJOY<*!Er zqr%;}qjCz^69gRHT>yCgX6f#r87@Bp07h)a98vk8Oo8m^;CA`ZiPvb<ui=$@r|{_Dh?#kn0+uQqTT#|z%UppFbw`-v;0(j+n&>bB@-wNuamY&ys4xD@rnxXYM>pdMdVQHL5^Yj zU;==6a~0lkqyq6m1%~bUqykYwg$E^u?Ljo{{(iG`?;mYe?tRT=S9N0tHw;%+{P#j< z)Vp6IO2lnC;N4UCsTw)w*g-;F7+1n4{*Cu(h+bqniKAA|S0&awpf=3&6+=>6vC|q< zZtK*@)Yh&SK^r1)yH`8s6@y(M@Pc@ZhF8xRoZAAC;h(i)c&Fm7w(L_s_;MOv;lHv) zhHn8C=eCe|47k8}ECA|x0CFv1#kcCQg$_ysD$BNPl@6+OQqBlgfq~lDYM?-u>u_@pgx@L1#W(3_v}hM?@?D{Hid8{6cw*&tIt0KiA7wTLgLZuv^71^srmEh7KV=*(_abPONKLP#3%Y zeua?J;#`bx9FWtLzZB=%%$_HDLTCGoF7QZIaDR!D!YcUqT94Np-(inNwnoi1)_xt^oi9-1!9B>jWLcdzmh$Q z*$EJ$ZK2R+lL|x&6^Ql`Qh{ip0$uHEAkLf3JI4mmv-?$^o9Id~k8DLx%k*vGF}zwe zR}3%pU`}zkI`D3yt9|^dLKD>UK1Ec6p7+#;8L52gLpku3_o1BSJT=KBjw+xr9P@8H zov`c8oUA5=BDiKNL;+gcvBEnwT#p*&k!><(a*TkAFw}UG=QnhP+KckSHW`Xe60K-h zy?>hutKmnGu=+nxjbZhBq}mf!!w&ktA$et+46O-CPiQTOV(w)BHkmv5Wt)txf1^}{ zP(S@01* z7+_O+I>6qoh4R?9``A_tuwhaM4XUdJSAfFAy);WjS?ls-fRJV?mr|;cYm31K5Z-Yr z)1yq~r~7V~Q}XaGIgth%N8oWv*6=De&jYpKlsxj`oX2?Dj^<_fh=+47vblaO%juRX ze9qr4C+C2QyzL^eXjE9bnX56}U`7xHXL%E-Su79kcF!5ljuCL2eKmR|;oWV^htOmlT@?y>gbb?+Lgc zn+p7vViTHSkf7OA0KEtb@4U;%AmE)Gt}ZNkhaRqejz!I~w23(6$stkGk|*`c>Bmca z?0iW48g3@;kaMnPL(RFgwU~2biIejVL+Lf;yDlvSLpbkR#V?$9tuURua0XeCBMLJAOU5KV|p6#FuJd%WaQyJ!ofMi+TcTmn!HcV5H zQ|w?+vzTHhkqVr&paLhYxugOoEvTqAHm#kA_Qf3-L3noe2N03f&)(t5{!GenRWL#EGLhTY_BIZ-9~MBCvD(F zU+Va^8I?+~3mOr}jL|t!fP?2rkTb33H(f0G~W0KT8-QMUk@@a=h5N7qf(oiL3{2;CRzgJ)Mh<`I{= z<>GQDR~Lhg{-14zi#ClpIR6jXECP)_O;b=VfBH^zy~c2!(#_SnoUT_K4Bd&I*D@G1 zea6-{%jg;cu+vWOL#!qEu5PXY>?k4bC!V?-Lk!j1 z>0s-)x+%5`TBDaOE`FhxExs%C>IMu86G$_AyEX=%G05%Xn#&ReB6SJ{{bRf?@X#;V z8lFqumYr(l@664K<&9dyl|TLaxk~dV^K%~N9R{Em!N|VpE_vFZG5i%iF9;v*M!TfX zE5FO*^UCD98W`QVBiGdKBE z6*Ec{pv=nm0$F}xHY0y62_>*2f^|W!8mmTJU z+tLU)dd<^Pf^q@J#Lq#$f|o8uM1Y0B>0)i|yzIE5Wy}|`|J7x}&r!7E+Mj23Ne{Ve z7kWr@JCG6A{!kg9?8+$_y9-mUrVcaA8oT+5+39io+z+mL ztQKj9(p1|WVh(7$JA^b2(j|&k!fsd?^l4L(!4EH6xb-uDt%`tFM7{l=OFhgwP;jxa zbX!DQ7kh-1;?Bbk{MvL_@%8T&5mhb#VcXr(IaicG_>gD-P~2|mq00fIxodN>4CC*h z|Jubbv~;#Esk;ac=CiUH?xv3^nHhQfk%LF&sQO}iyLz`v)46p85aHe%+2%ADU!EsgcO;!Iae z{As}{b;<_`>llbmndy3jr4jxx5Ix}E&Z!~P0nr|_T#HQBUYB#+t$lTOPD|E}l%kci z=ey>(Uh{=6omQR0X{`u8YHv=>BEz5wpSA@qF&j=AgKr*WKDH->8<+r3v~p)tCUoHO z%iqj()sE5ZE58hE@^c5`;(a*KJM$M4l8WCS=ef4~KzsKS8(aCU`QWa$lSatr=1_bd z48kYwCl11=+@9;JR!7HpZ+|F({QD!8pE?AKpH~S_7$9j1YN<{d>ea!=q!~^-ABqB; zb`I>8)6VE0D~>mQ=CcZ1HQ28N93I9PX#N;VaueRyjFUl@zVy>A|+i(t}w+!v5i9Fw#7BJOJ711+YpXiZmLd^U|Iu5*3Q zb`k_Ic(ctX_i|PytvWkGDsbQ)+#ABcp5Gg2VD-wTB?i*m$qP5Ql6+`tQQjd0QIws0 z^+s2HALzU&;eH9A_iTl+laJiwYT*OzHAeHNy>fH^FQh37^+PD3jD3MZ`B|e<$PMacTo{C{=BGclRp43Ax?03v61t_a*K0)C7<;|_L&ga93gH76#7hfZVJwKT z_sj8)16{>RzNAsB>|yWcT!Dbb~Pfko^ge@ecn}8ZUHcU=vvNGf#|oDPEBS_{on=qsMGKX znWD$(NNCZ_I>6gK@2bOcNHeX*i~}K@byv74`naoUfF8?f<*5A{K)&BuNQF`Im|zHi zBx;o2(fN{VzB&2;dPkyl6&Mn5HCVE~%=w8;CxT$Wj7pzNN>S<4mD2sd)mc{V2W|l{ z{?^wyse$NQ-pFah_6LJMb0cSy54@k)YI6mVLyG;?H#yuqBgKx_T2et81^1?5-Xrue z9)4F8U_1;Sz?+6KZ^Kv^=4!~kC-9iLxEZRW?;enu3t})nd6*keFCt>G_dAke6=|4H z56CF^-2*ZTeg~+CGz^siZ|cM2@L%1@8Eaup4{D>qB(Bzgx=^oi;pul>F$Q~xKw|8M zS46ZUrJ|=T0LBY`$*JQ54|j>RV}1QVjfZ%@_rRr4#G=oLb5MapE5Hd~Jj)f9{4FQh z!X77xaLl14&L*W8MLy2YUvkCrQngZJe43y&cBqwVH{gW(Wr!Ttk(Ss!s}F{-!yO0Z z#|6?oJY`&JQ^K-}J%C5vs!f|FK9o@n&k<^s^Bj$)NY~6Z4SXnTJ|8%wN0QS2$*ZmuA86z={+cV*j5)-6UxU;~9BHK; zVf3L89gqlL2*44RA{_wsv9V~I7SVd(db)sLzV7PjLm#AgA2+RW-Bl)w`AT^Ea_`@nV?ZJ-yo$Z^JO2It4IZ20GZ*+ zO&ySmy?-LKMGb_;D-T30nirNPuMX8?7X|>Y4Hcjxx#C@Gk?I<_-k|JPQm%nz$cI5H+%aJ5NrQ@eq5l$&w8MTc;b zPrIj2B01330;fn&fm0+m)u)!UNN1f06yoh* z;msfwh!-jl?_g2^>xUHz&erjiGoN%Qxr3%?;55vSt}}mIB&T6}7P+TkU*~t!)u!{K z`5iqXeiO=~6R&+ldpPm>@J_1{>^;H-PP~S6?E0`1FJ-;ZkU0v!l~50;l{A%op^DY) zOJDkpoHr~dwQ9Ir0y^>gD(3oc0V`i68*uf5#=Q@rB1+?oS)Mb|j}}QAb&C^qAi( z?yMK*33oET-&4#nQV&@yr!@-Pnhp?fX@#6Z4U?G0$}LuXMafZ-lwz5!R6V#bO@wA4fZ0^d_9ko><-y$9qgks^R&!1fTz7iy~|t z!Gjsa_oP4=Nn6J|L_1==0CAq72wE5JtX^!*GyaZtBm}XO1QGf`T6ISgcAk`?51d@g zbB~F0$YP>F+jz2a{r+Mew#d5YXQ`{!fD8oP&~A z+&)Lhx^1x`uSJ|Mw~cB$OnvMUo_-TP__?n`QZ+W7wDp8i?ZtoM`}HLlPD>GkbO-e= zEd;kZMe~!blcITE9Y^sJe(b|foN5uxk5qEh;%RjqMZ6e9d2m)Tm+*wHds6f$v$zk! zW3tzsSlKh!m)dIZHgTHwT&x4;?du6nbcwB`0Ew*Ui{c#(yaC1CSBk3DAyfXcjSlrQRVbOc&*@A1#yqAh!n0YVF4v={d zb~--wO}e|e93QitM0!lRx2Xa*(X3A%I_Z8~oQivuol?kUf_)t9BNFT**|RlAe|E=S ze-l(Hj(ikasw|C3E>vKW8%`=Pd4>v1o{vCFvA^I)p3KA9GO^v9?M`ezYVC;A8uPua z9latB3npk{`yJs56I(oD=OUCvV%zlLwe)023x(9mqoxi_x~{Pfs$9NglPU^m=1E%e zNy(1I+Os@9#gP)J0IgRG2_TXvne$DGBUxty2nigS(#Iy%4jQ>Mh)){}aeg$ZhB)6_ z8_u(zbR_uhRZQYxk2@NKHWu)na|lDnBvmf1SP7Qn?EtMVd_OEu@Cj!vE{J+uua!k@&0chu6W|_L+GS%78)bN>#3`kt_qDw^io_P#g zh8z9=y}`>^jyPbccq6J5M{CyrEW+Bg?6j->6YYkQ_J3z{{>@8CF3 zGC4dF=k}Ufz-jgjM_awuG90@|r?=j9@!}G1Q?A?7@tnry5iZ2;Kk1`ZG7tC2fbC~) zJYQbi4;&ozigh%KVgz@=DOBoGxs;0=Bhz|25_Ptk5WvhqDbUJIRxZnd=}8TZ?IfU> zVI3d^m;~)y#?zu zL1-J5sk7xWQx9EE`iQvtsPJ;kY<%NkX?|@O%vp%#_(hRe;j)7$A@xRD~6A%B4jwBS_7Ql%I1xH3> z-%V->U$cKO!jZ_PkXD{4hyJ=`);B=SUM^Q}s0AFO91h~^ZVT|Kqa0~oS`zN%3wTj= z3YTc%dHd}et4(YN(c+|=yH-`7h6HVJt=k>Qi^6SwnENke2|6m zYp*)Uw{-wH=Gs1hKQEWL_QB;c*WMxlBYXgt(N6BZ46&5o=*5ptbhHa6*`7NA76~I} z-A@TYFzbF={KBmJ=@kL8?uL^ci+r>08ZSE*v*AP`m~{_U1#Y5QUp#cy-FnVjjzTXA=4HcMuPllEv z`}QMO=A;!e`_6=KRmtyDjC<4308Ykazv&ndF-f4L+4n#~1GDc7e>5G%&XH1FRv!G< z*oRnF_Gqd|$Zra>m4X+|a+K28U#eWD;5S79O~FY^xn{cfZO0@%|4O-Ls=y1#cu&CH ziTG4USB;fe33%NnWX17qOpqd1$^@wbsTIkYUVdeODRm8KAM;p*XQJ zu@Wo!#u<(k0Vo?5CWJnSea$Kp!g&g#S3|yJaDaAS_|uk0DW(V5w*n1 z1Sux)G|U8Vt{|CU(Je`xbas;<7UNrSg*Zlbh(B_o|KotI@Paw217QABloX&b3g*Z} zkV0Z2sBl`x4)Wz#iQreCII0J+S_BikNbwA-PYMuqtsIgAdV!0si056}@M4P`jaWO< z6bIf`IRScNryRKgO$;V;K*g?gcoqoC9FS5*9rP#E1fxL$6mvidiZYG0foiq*gs;Wi zij;e@KW&keP^5u|>?~j!-ZBbB` zi(i2XPsSItO8L31M_7xy4|x14M}?drrIM00J!X~4`goCV9pb_jVJWQwKe;{NCPAH5 z0fI#WiHR1u@~f<@4}N%tAUx8b1hGI%16t3*Y6=DSWPP1UDcU$?mCX8lkhK#6SZmmT z7}v0UfJzD=lZ6SaIOFNYL@Dw3hZCvEcfb6G?4Kk$l6Qie*mX z>1!RS;j;y8O#kMHUzq;QSrs7tduE+unQ!{nWxeA|wwP!J)4zqPz)dr2;X|i?O?cj~ zNpsj%gg3l(+WmiZkd`+Y$`->D{a03WFmH1Y={gW4y2D0h|9EVCD z@G9TREdywV(-{t0#vSWVIr6NbE)X7ND{ zR$Jd&X+)~ka9nS7fGo(h8i(W1Gos&lb_T@9%SxfI%Z_HQEudC-t-o9_;Rh1}AIJ@W)sqnXNx?k{!97wcjHdqyEQ+mGA7s~7%eV-m7Qu(wJECQrbHu?|;xTC4#F#bMqde&I0hSQB8F zhu8T1eA;y0dDzwqc+%a;T1`>QZhp_@eZNLV6v2*)DC^6# zuFNNHPI#y^0aRLqFZs500e$fr`Q9dFT=eCLLxL(5_-n$wIB~|~wkHG!lR|OgjQu7G zaFX1Ihh2AksRym)ld@V=Wck-Zh2<{deQ&s-VpBe6pu=WG*UERkHx|)~hk7djU;4g} z#-TqECc`3-zS+;)8mR4m?c@e<)yla}1IuyAlVv1B(7^J`>hX)CzK z&eBf&!p_nTB=UO%_~>7bnZ7ykid&9}tS6BkJ4<&};3k^&!6V3t_f$#_RNI zGV8vhW5f_an>tT7!i@H}Ba5vj1-QaFt=Pk5z94w%kQ{|ou5R)Im6JbYKd554xVc>v zAb-{>4{4}wG&n|@;c?0%q5z#6#K+^5;zk4gmgVAi2t2y@&3|(7eCvpdXN#tutU?$=_@9#Cv$tdXTr?F1!fE_YbD6Sx_Mb!=*AS>|nN$tb*TQ4VVxZI6o7>@1u9_qAm`U$=jR%mOc46#_9f(D=EQr&c;!&% zCB{h$F#>Bdd1eu33Y$sFAt<-i7V_Yt&Pr?%DaXa;FV_VK#X0NbVly!l$2$y^4Azy? zGkLdS&e~oiF#XB{tSyu;uG0fgQGfeOA4sn1*oZ??B6&*O?a%XziI zkp@3neSMvL#s3CDfTCRsB-#T%qKTUfh{-*oX(gTIy$Itfl8+9iTZVqg$IzCWfuZpo z|8_j1l(U`QI1pTeb(jZvxpGRlvqLxuC+_GeA`<2|ZP$bE%8)I7$&kH1K*(NE+WEQP z8;U-C1hIHXi{v&usjQQ;UV;;vEA>zXZUM3$5y`T=Sb67YzCIfJIi^CR*2`RJ82l9% zv-zQ(Idr`h(AT>Ida+1neBt+jQJD+n8p+l9ut;aah@pac8r`2!((stKnpF^8GG~IB z46EHAlPc&4DQqDrz%=>e_41Bi8)QYE9@eZbTW14@i#$Gxc1GLrR^-zsIUBIOHs~Ng z$~*QQQQa4QUyQR6J86Rl?CBMqQFiDQcHI{+wvw}_9S|-f5@_>pQ0B&d{xMIj?DS>= zCrsT0TB^zUicU9v?f3ddIMJ=!Q-rP1)vF3R=<3zPFLd>48_?DLUfJ4>=T&iD_DxYr zR&$PJF2XdXD9u%YoASec5(lo*isv6ycdlYx6>^!+ciJF#WBZT_+>M0_ykT`XsleS> zsKDLW4ja&`OZnk9GnI$6aYn+~$J|=ZF4~8@dTnPVZ5B_d?Q9p3DiBiTHzgFZYdiDU zTvC8ZO0jQSKSbV*qL<_yIwcnfd0(NnGL=!ClHX=ut75+Cl(RA)6zi-5yIdc{!l1H> zRANwH4jS+~b=bT?o?4qFT6ofmx1LC@R(zo-LaFn~MZd4%9UEt?7iIKKA3z_LbH;Z` zuCB4;ge_cwQ7x^d8=sau?#bjO>=J2+L)gY42~C4;Zh$?l>1`UaTcjG&saSsX`4Wxv zKLg3EZ{$~pCOlh0QMb-vUfRIZhb7bxCFEd>GUn<0(LA(UvdPM91dX_ZvlwjSdg;MI z0L^>6)8+{;E^%h$Lx6~c!y&4!Z#47UJTtabAmUXY#}Zdn@wj#H_Y z8|750J`fO7sW@OwOr@yI_|lHJ1d9*onY@qJF;#}CbY1TcDWLxJ@)}P3P<4GS?;HLSo>qBu#&JDb1M^C1sjYBnY-28b#{>IH8 zKeRJPZ^Dd6OXo2uI5@nJ;;amxu$Y_TOpX{Wn5Bb5PsKgnM4MA*SaM^HeMyQjhT$Ue zvQ5?^@(NPzS@MBdG8i+#_blIrO>)I&zG&qM+pvaQ<6%~OKuN9nhLOnyf`D0mtr@Hz zT}g9BhZ5FhJcN|1v$G!iiSUe*4-pTwFZqs+&bEH#EyUYA?yR9*;6opG#<5GJxf1zY z0FiG>kr@%0&+X)_RXkUqp$7PpAL-=m8j$Od%>ZwY;`*0h4X1Qgoa9RUqQy$iv z_I99w+r|peB3@Ym4*9)Va49MU=mUqFTwd!bXS;CX!0zrRx&S7U!v%ZT=SPTN*yl%V z4$$XcecJiDZw^_sr7J&wvYWFzdz;ESC82lwH&ua~a@OpJn_q!X$MF-Bl1GR8L7w@+ zW;vI6WwU!O^Zm2V7`Uq9?6b~R5g!P4sAs*V_>-4RfBAB9JGO$9V$ZJdN^7ffVBM)>%=2E&~e0<*mi_T-$^4Z?W=}f?J^8>SCCu1Z@eB zr-W^hc?uC%<|z+0%RJ=)p^bS;HG&(*ae%};g+i)4qp4r6l}P?aUTUC=bJh6MmtApY?LbJYN7HaQi=;0qxknP!VHu`<6KD5u@=$^ z9d3+o7M?S1jI+PS-X{n#!Bq{d*foczjdLcIBJJINoH;ya@i=FY&Xy7+xcS}TljO#1 zH7OOmh6=EeJu@qd{l{uNZ=AClUwJ*Eh*xtEwIW~g3V6gWTXTKscXB<7QbTZDk2>xL z98Z7vfa8MHRU5drlt)c=PV(XfXD3P@)*9(I-{Cn_p7OG@kbkXk&`NmDgqNN9G*wKCJ4ZI_E&HPJ%zW?x9+qn^1Y;A_cdpsaKBdBLJq->ea$&q=WE{f%=}6y zfhx##hJ^3QZONa#>6`*LVG;f?xl)bF$VQ!j3$gFMbBgl{>qo#*$g^2sz#*g*gzUgy zd>eK@Y_QggaFcDYaP$(>LkewEhqWc&=X<>FieLM{X%g8iHq*YBI~Vh&!D>?o~XD~a=!u;GUXAypNNAt39&HTLC&MJKFyJ%Y+_pg5+VBFWXa^phthQY$? zWtPL?^Yqn9WGcg2-f)rMo8ye|B9137d;rf{s;aOq`67$n>gDFv)oIm9DXJ=ZEAQ~0 zvy~mZBFFm^n)v}oFQC|MnvIn17`aty_AF|)xDT^wqPz(gskq+$dp_w5obFAqTfx#m z6X`R&!|2h4_`XfaZ?F-BF`M61lJtjc6@91;|7fmrJj?oj!Qa>_d(VoGoUgFC1YCq* z;>8yB_oZ|?G{bW#N<0hT)vfYe%4Gi1eAu@EZUkI}4_p)CQl4|ECH(}ERQ`L9;?`Bo zdu{v?wAQIyfdp0NeSV9fOX6x1=(yCHsI zrgvj2W_o@<>^yvnysG)cC(hx1lfEerH^FhWa>emcJChsos-HPKv!dIS<72+ZRDoNT ztVcoejnAF0v8oEW%=aq7hvG!O*ML-DVgwZ;&C#NG?sCZ7mXxW|ilq=BOp@AephElb>a`sB!@9l&b4OE zoAVRjI0v$9f=`$*e32?}n=rHBHokAMb1B=V>g4vw7SNNpD&ioiz{D2(aGA3?`<0Yq z0tyY#G8?32rY?21XZHvYn(vl{HF&#nFT{FFVl6|;5i2xMSYKrEq#hC0*)G|1k_z+z zsK7+IJ*hy9P=SuH!E%H^T3O|+#AB}~S1mLKgy`2P^FvOZLD|MS%KQ}(6}BXw4kra( z+Fs@CP61TlwnYk)J@KAtcGasUgHy8sER6}WS`&c z{D3)Coz!l^4{{g0@elIsQ;}22y;xT}RHq-TeMnM)I))0=@o-XsI))0=G2j(CF72PG zAU@-Aa>f73g{|`z6$v4swnYo@!yksvbBUR`tT}M zKMJ4V4BZ(sl0cghWcDDQf zB7pS@;0i(leUubXF#u&HzVSJ&cIoIHZWYFeU#LR(*1q(o9dK3)>IC$Mq*kxUp75sMTkjZ%bdMeKoD(Je_fO6kzogkg=Su-dk9L!O z(N20~Akr@fAYIar)ImJ@esWh|+7BkSEyOn*az<+(@VrCLDr~Nu{Ck1Of9{98cGy|b zujGvm!(i%T^d*O#b+rxr#9?PGw#iO-T_D0c{SYp2)LGpxVdJRtYcIlLniA=wA(DVt z8O;m7z&W_Hgej2%#bwXxxHOa>3{9u=?$8gO>mzIo_ah@Hl)J6yU>)7Ip>^ZwKsUVbD*Dn7t|#EwLr4ZlCp;q*}KCEf61 z>Ne>uz%fGld2AVB6DOHUENc$AWT)J9ALAppg~=`Vxr@%08p|aJ#hjS1SXuhVZmIXJ zm!0pkQv}+k_bTvC7uEZ2ANm$PH~kl`IKwse*e>Fq;*H&?Ufl}wCRd#$`OjCKWrKou z1@V*NDRC@>0HW^|+7-a}!gt9xRJ`>cRwktmnPOPZFUY&sGE4EHdCpS2Yqe%Yyx6iC z#AO2jfB9)=i2z-`=G;KMC$p&2ef_}~j6e&AVv@S2xp+=5y4 z92+GP5bH?BNE8!G4yAIOx1Du^^-p%mH3vmF))yYv9LS{969(nHHoD;KLe`Dd&*YB{ zUn6+I{B5oHg~`X-U4a)MV5W%QimH>}HNkf`_IiHT^XwoI4;Kw`Re_tCtQn7Bonml7 z*EDuXA(x8==fJ4q_QTV=WWJsEl&cv3;BKX29Ddbg`F5+Gg>%Qpc6;DsO2Xce^H{UT zS%e*`%x;;V*CZ8~UqS_*6Kp~%FtvmVOf7*AoCEpMLguf#wB3`@vu-=i-=!^#B>E>4^aWGKuqt_dL!#e7{XJ8>94l= zw>!SLEClKc9F<~;rpyAa1+g%`Ut}JqLh>@rteif0K@U$dt{(3 zMk+ASLInoeC{lre7Ai2%-T|wKIlLc!GjH#~K&zeNLuJ1Maa#yYgY0Rg1$kPhN2_M(tSw1(?AJ?~WT%(?idp2y`IG#@`eht0`CzjnoA0gH*Xe))*+BQE{ z%k?qrT&i;U0fr$Lqv7)(ueXT~%Gevkquyv!ne`$t7*>1i4G=yC?UmufDOy-@^RUm))%{Eop>vr-l2O>Yi5Bc43t|}#c z$piAFDQ%*>7!Y&N2p>?QIdv#{8Q}>>rX`{PM<#F#b>wId(7~h8`$z-S;jTbJ9PuLr zj!oP5%CTuXL4{+}RZ@Us6F}nFL?PAK^c?}mv1!v@IW{c;0%B}h1gwd%iAwGnoA|WG zuJx?iJ`mSE%!p&bN^Mq%sk@w^in!Bpnp)FR%*`W2F`{af?MUGpkKD_kUC&w$` z2}c1RfF}EJvoWaQJ~*sjux%S1RO25qdY>FGRuXP-yiho;HNmBp0&u+8M!<2rP~g_} z1>adbLNh^`IJt!{nxOEE7hVo<&2V)HCn3unxJ4ku(c-E=fuqGW@e479A5^ zqwS+ba}Gx@JF(zg2e-q72*-%XT$!?$g})-=`=OaxCRe7` zS}vy6i(NZ&sOK{ciX}B<2a+nd~YM z1bp#hLsKe-5(Xh{*pyT)n$N%7dREYQ0KnijfpREr*&Ul3V1RfN^t+~B122v-xQ))0 z!EH1_g~4qeDZqX_ns-cvSr-Kqv29MxvbDi73(lEldC`RGy$!*EtAQJG_L#njy|2oBV%g?M7bCp7iDP~C?XEcAGfAo4vrJTz~^I%Q|dNZKT_J|8y4;t*rhd;;#x zp|y52*WwUbVTe*3TIga422Y4$ME$&5TJsL!q|12h0lf|b(+>g#2Bsb27Y3#s2Lc49 z*@In^?18B{e|Cr~ll@9q!N7Dv6}X9Jz4HhH(}s6b7O^`DIR+-}CO*=7RAA`8_qm+6qh17^C72Gg) za!0I5_2R!$^gnoSA>#m8u@ru9UdV;-3bc^w7q$+UJ%$oCX z@oGsz)B1dVWmf?n^p@*6mZd0&R}A5m(a3_e^f$n2m+LiT@7rqUtSnFqc8$}gxT4q_ zqz*>$7Cill+U3LjaGd%2K^d}!9CRmB1F~F^+A98LmMbFuTfj3ivnjlHk@wTQwG;v{F9^U^#w>Uvm6FbC7d+AN1f_ou-L=dQ1WCR(5Zje&ykO$e%9%Mh;ZF`r43S#nA&n){4|7)tNU1>DC4P(eN@E(OT-W3Eta$>rc zZmH=Z&+v@74bRm*DNrAW$MDQ;po#IbGDXRo!!u*?zv@_*c~>x37O=#`j;pBysj#~Z zn(}V%{Ohm^&JfGHtZq_d0;2Zt3!BFWo&{Pzi$`CfoB`sIngNea;&EprJRXS0=27t2 zCLYa3!^0&WdE)V#c(i&E9?9ZSb}T%i#G~Xmc$5>5gX7_GL_8*pehHrA#AE6Nc+3)y zJrm(^Ks<6L!DFp>G=CW$hIll7Mf@ushsEQ#czpF5JQj<`;Md_XLOe3x5dVtD>uYlu_Vz%RUz@Ts-%3olrEYCZhIn|T^NS(>L40-4Ep0eNIu5YFJ%SvY@YX?E0z~)8$XM+CJm5Y zqK95|IJ9#|6h#VKk7XJ5hTV~t_6slgfh$tq^O0m|oE_{%$x`+_$&xh?4Ot+->q?%u zz0EAeQ)y`E%ad$AhAp+XTr8RTkw?t~ri_Jz%5FRC4iA-5JbKGBthD$7ycJND_!7q$ zcFx}XH%aPqesuwmg714Ofr1Ws8&!Yo5Fh%9tEsf=n2*7#pMT?rmP9g!McLbz$M$K_ z;)66<`3ClXzR#@WXdhPLJ3;6aP3_Ga$>u?Dqd6bfr&@U(?w3byJAdXn#X8%-wT^uH z=dPzqi;Gl!Xuu`Z+83@Wg+!Q!V7HKmwJOwxkNm<_kB#u)c^dDhrx$bIp_%q+S z>ay6M-M##I9$(OCz&BRWV&U@`LwCBYdsY|b17|NhtWV$Gg9qVGYtx^_JSUzHDb|qj z7LAND{Dal5C;!#vDe~G+ul6(lY>lfKt45gdn6P+?D5c&}S#W1+F+6Mwj0kC$VBb5P zv=rTT&eMg1|NX`Ik}ddNs6{9KdzYz4{mf^aYt)uIGoB6R_tv}q)?Vj#H^2=4O+s6# z@YR1(;Y?IvJuQjHY;yH_2-Rtmc%#j(I&2c*L22$&yXIb!5{(s_`+;BC3cE5g%smo) zt#o7e(pTQM9fJ9`?_Gatd3^0wSABMh@QV7%+gUvBpR{$!qpcI$TU83pMIrzaC0MyS00>DjBl*iDEMKNIE6nr=xWZU z5Qd}@e|W0^x*65s8&XL9RbX@!Ta?Xg>wY0}%baFMQQ9j&j z2)EWN9vqVAYFD3dy%j0e!MuvbWnYo}eE^@&GtvmWk9n{mb! z&Qq?tLV2?VS~2mfGW*aD{;oH8+{tGW*m6725(+e!?XuTzr}g1{%UM?+cG?bQ6aYd9y_Y^4RN{#A5uKXgdr&RyekF7fj7?VU4F_}At@fdO z$yX3Y=9e>qiw*%=Sp_f?>NN{y4U_H{E6IpXIXGcOy~`1?&K1uW4{I1K(xZySL_7IW zpt^#oA^hM)S8T)}QA&IGlSGv0ORmYRfwu@UsrlD;o?D)A?j55Dizk?uTy~9R?MQ(b z)!<`t`GZ4Ri&9*X124&L(6ArB^}A~@>um>ieb$%pO;_NMSvsk@cHPxcf8i*ft{FAi z7*YXYqmMr7Xn;}cm7}T0>dAUdH~lD&anvv8MQeJxQJN3w9aPe{ zG~^FB=S2AeE2Zks9_2G8G&c07kMc>Kjk;XB4uY*9OrjPxwksG6H}9cn*`yLh`@s@z zC#gWuwgnRHU_jBV6@_d|G)hZ}=2HrymE*BDT}2tKLixV2$rt>WYd9lo`wxI_u(?|zBF@(v2viBzJ1S6elyt`GQy z553u>5*tKnQNaFz1RN~|6dtw=u`UE->%mfEkyy-e(`ou z$1o$0eL=XCCcKy85%3dIDO?n8_n)R2wb*)6j-ss&B-(Z*nyvF$Cl5aPMc#B|BUO>- zi5p;CK}Iz_?-#yvBv3tNr+Qpct?rYkUINIhf)H3oh=X0TJK-xXk3GgSis{vbmM@Mn z>Jl#^tmHZ(nT-|rwBu-_s-Eu{|9mtAo&v{|&!g=6u>gKs?3gF;Y<I=OjA*?&v@d8>VKwa(s|KRjKv5h&#;9IW`H_br+-rO{t(;v( zICR{hU==;(nB1aF^`7bpjY4b8^<>S#S!?|M|8fNgzLo`6k+U@1<(#*-)tty}Vads0~` zH6*&zBayJc7I+Q5WGJf|{;`l8_j*1Nzi_YT6VM8LYbE4)(F7NohaM7_Fg(XkhZ^tu zU2ysM->&6}6W}qXR2*T=hOoC`&@tE$$?#N-B_ms1UFECxsi8Sp!mw1Vr+t z0|=oI&L1yrJkQz_P^8e#qR@?0AO%q&DC{a@RAl{0t)c)RZVLF?R{;I_OAhyfPJEI> z(q1Nq%a7TUL(xtqhg`6+UQN@;SKqf~x~Uo&9>=-T3XpUw3aqa}|{C>k8O z(%$-g1qQ9*69J_tJ|Klj9=yjEX{3cO7r@x3R)}BNr&b)tK2?hLDR;A#{92@O({I0; z|M2~ayOv%F=O0xtF0#E!3b9sc^{t(%)YG>f8QsM(Mh|veQIOrr56R49$7Q!#T+x`r z{v<8XDX$)vhn_DTmz|?fWupxXIRPrP(lP9Oh4{&;MvCqRYE;E2$(>b=Fy6Qdto~HC zgGYOVcc?1CP1f8F*~9~hZXJMse{P)zlK8kaX)oRS`{OpZE+g7Wx9%^P5&yn6E3;iF zpFikAd0wc75f*t&fKVUbE()YRsE-dO(qPJiKEBP~dY}T6J|0f-0cP}ZFq0ZRUK35w z(_a_A(9>T(fu0`j&(pUZm-GBxwTwA_{e8hB@ON063+H9)7+2T=B@yxWxvJFT?~jab z-B_b1TcRjPfA>Q&bMXo3@9}ZQG`5wrKu?Ab>IzR@e?q$Zt~0JueC-)mOLp82dBhuX zUOnR}cGC{@hd0o%`bKfSyT0LIMe;l@!?B|U=gE!+l+o1#u19?UpU>9rzsM+|VbBarjl0RkOoa@`8tJ_A((=jB90dVNN?}f(LZA<_PB-LxvUL zX|0VXSyww`Cl91l@Ha0(M;zYL>dIPQ17bMyqr}wW1uex{-p-S_OrdS(6FVER zyhcakaaQ3J;PhE&Dt}5!QJ&PI6veJIsjAmM#bZ|2i(w5(Es7C;Du5WyQz(W8V)ivF z7gvHRVEahWWmykpORcO?}#E%np!B6m4%H(T-W7)$VOHBcfR^Il%Ybg;gjmB^oV7Nmf!x z8uIGT8t<~;U;TMkfnTL}6(F_3G?4$zlEPM+#%O^MOM@eH{SDLIXTUzASU19+GEG-Ys;;C~nPxE8dVy(%l1h|p z&_78w){;z^he&39GzbWyWR#$ijFzGxoxKE^-N%^Az98I4LBtZJCC4YE66J^++@UZ( z-q&aViV_rZ4N{8|;xc;ZX}OGE^tAF_>_zN!faq5CG&-PuQm&$tj$~cD zc7w+ZGNPCdJy?ki=A#A~Rke6NcaTw=)wk1(4Mekrq{-JkZ^Q;5SlSA%ATF$bmgaeb zpDV}{1{=}Z6a1OMu>9H8POVcQY8e)_kwc8?#CC4+EZb4}q$4JGD@8*97FHZ;qi_qZ7Pp>(QxU-f0N7NC4aMdezD&Icz)DxGW3ocW7H_=M}^j!xJ@E! zO}x=>a!tI6H#uufyg?wE=5O-lo%Do;B}A7Ki{hjQxXs6hj)Sp_QkE_$b{>67aaEj_ z3ZK-coF;ijEdP7Fahwe&%qpiG45EmQxxu6sBg%vcMlCpfwr~Qh#lA@@(KBBSB;rg< zty?D=HHn|Z$Te~xhH;+~Q?mJ#j+|t??Zp_%Ht;vOWwrgJSln;S(@LLZke)4grjem9 z$1+3DhICCV_|rTY8e1P$CyBayo+&1MYR%@jkQXPrC&VwD?4AHc`Csu5f7KZ0XQF%f zRbxK8<*hkuIq^?b>SiEo)+1Qfd2rZOh;KO$CoLAeZq#7~z8Nu15_LpQU)89Cb> z`v$DBM3NRb+bw%W&In7Lk&`i;$2PP>#rr~8lhgKg&~^$Gr)&XO@;7BG47li&4Ua~U z_Hvo<%5S!1!Z6WJPT$6eUxm-`H{Uj@MHUeM(D~anVilgT%K20{EdgMhNrAqUqr53_ zprgDcexakhbp{=Uk;OfpJJqP9P2)GF8Y!i*+**NjBb|K6dT$4QSnusjhW#Y*-p)*c zcse{h@9l^Z^4^Z9%ftgg(*O&;w=?aKd~auBfrbx#o;aDFHNvCpUBreN9!Xg)_5g7I z;d`-Cic7X!EHmMXR(~-c#wqy~p;@pLkDn7gp^#7joQOZcJBE*M%Ztr28nSId2Gq$W zK4T8_Q#=v>ohlW-g!;4k{M&BgIT0Vqi_SJqXg~8SvyHfrBZLMI+twn6r_6zQ?nzZF z7)sTS@Vq(3tBip2A>8Q9uKNN;y=zqV#tUzOwJ&i{K+-wzPtX;5J6!ztca1{feq_x& zct)N}@BN<9h~Hh+GL*xwL>6||rYu~mR_LvlStv$oFFn}onyzebTzZwm0Of~Wbm6}^h{ z=1ZG|zU>p%IUu52b%@+-mO+`MiINTx@ffnYnKzoUz)U*n}^xY+5gsRQ(eAAKR$} z;gedM6?w5I^JfGd1pQ=eFWitFBGuW`6MO3i&dSX11N*B5CxxD&pQpbZ1UK^RFT;5E zTZt8U*RKs%@f`vS9TRr)FTXa9dJ)fP)Urc)I~>sj&#u$5R8Em^V8JHjZ^hMFj4nBM zYng>KR^Xg6lhMUY)&B-=#oZK&0qa!~AH<`xjq+MZIfXzX<{Os6VroTI%n@(7b9~q` zV~`*Cmtsu^Yv2d|)8$4hM(}fQfvw13=Zkmf`c&nh)N|m`FIA|>(g|0ohlxBy2G@4A%oDzdt4FFqy5*r1O%C*M&Ke_5kQ9^JoLJ$WW~ z1YfWhR%!4|?ob}L&uFU;f-l1^te;%kFFp`6BRwrK=*x5Rjh=;m#r+(`bydjhC90`g zc_EeW=y(-b9d+>|>Pyj^jqo{rij>S5wAOe})Aw3>5P!wHI#&-?F3PWb+aZL<{hrx? z7kf9T98cI_tju=<_!eQNA^VF6*l}KBFa7$t0No3|bcinm`~e2ZPU~EnuU&qnIUl^q zDEIFM3>6VTiYV<0cWyRnuq%Wg@Xyo|CC=MaeCZsXz}C+Lqv9-kt1ZSJR!u-z;ZX&V z`14i}sZXjgh{T=`AZ3g5GKfs<7+XRINe5pqK~RAdJMPJOlVd3lumyyzov zeZ)^e!TK3cu6R#rVpgkQ&UP3-YIERl9&9PSONgPL%nGEz{}4YhYNeItPk+#|HgB=( z5&6k<9=aREn@;#a@s``gds~X9zXgm6KRNSW%MaOh(hOBBQmhi&?A`c#)ppWsxJ~1X zP?4#@{fnMxvP(vj?J}B#`|0JG+s<)qSN$kH{qORXg6<1nEMBP!dthe)Bj{cDUg)w0 z4-r!KK9Z2qln?&dXow-D`vD_P(<@z&p;i2a&^r4;nU)-1%IbB{_#}$s1rzP-Crk6JLq_t$#Svt^g_g({{cOatM8XRC$8(~9 zy1(m!j3X_8N8ume9yYGBv80*ukMj1mFQ~S{KlElG&hM~fA>IQ)m33>Dq(@)i@%xN6 zdc*}BaQwPR`3v$;NW){s+7RkP^5u^v$Bl2;7Q)lD<3{iH8&rWvLooH*@aW86f!D}` zRAduxl?QvX`xP+`)NAsqA8F0P{jiXk3*TeEWAtIak`^cLz*`k3KuB>V$Td;{%B>-; z1QC_RE*h2i^p-`#*#iO*cF%YxNDMX)mR5)oVDTvpk^>QjnR|r3`U0*H%yyNB*EjDQ zwNo|;bZy{L^~?$v;g|Rq&k;d^_-(zOtga5p74XzY)`|jaSlJZTGD>C^u7!nz!%3Cf z2tot6gpf8ntzvi`K@yh`>WW{ugi!aQTx$_WX0^x2Q)axQlrPdc{z&<6lUPPCX z3U@O}w6gTOO$5N(@7$CR5(qa6Mfq1!>qYq*sc<)QQ!X-ZVk!230D#QT@ygeX#=e4= zxTMVQ#-qr`kXkSDv82M?49GjL8_ih@Qiqf;UpJb1QN|AE*T@%zpGWA9i?$BeN=Snp z?pc9d{Oj&;;e^(!C^2Kkkyv^e+o^X!?`lm-yFh zdhy%G^fLt%HT_GXz`yB9m0SIpGm#O?^jAb%H2qca3r&ADpy@Ln7)yOkzv5{#U1NnW zD=yIV`Bj0NcGkC#$n>!vnq|d$NFn|}H+!)%ij=Z`xE}^GOJA02`$754RfT73?pI#2 z|LEVJ)g@SB>Lhm7YhIS8=9`m>+~TIJ5N|ssk&280<^a(GPqJ6NEH?+@3YyQbUIYs9 z_OS2{B^8KQR0zBiNCo1B3NO5A@6=6T?-D3%KI^jFngHsPg3S?Z2?0RDUt5INlL~Ap zDt0t%9!$!SE|e3x;r#2vHG+9asF}`wBcO=;q=oxBsX*MKLI|b(t{eoBLxmeTup7=_ zEDFjhN1zaI`0vsP)ky{7g$jH(qSz{}8f!#q1#&GM)@IEV-ED|p!_4-q0|7$Z$rkQs zNd@8-72>4@M@D8e8$fCicd`dJeEp^$dxg{^+KCq0cSr@Ig$lfcaz3d*j1xT=@gqJ;|lSf`Uz2yS(# zaJvWYiv{S;@#h;n!}F@NY*8$;9Jrp^4*Nj9DNLI2uqVxm`eT>918^D9Oa|aVf(P-h zJTyOe(uHV#zJeJRQCfh|n5&Bd6?0>G`rftqbCROXB^nz}BvDH$5Md`uEUpX(-o%j# zDr~M;Tv_T594Ne9)ik`JJvsXZu74`^g_P5HPBnAB7Nh&hnT= zt{5It!+eFEBW)mMbMW-v^?Z2UQt1m&<#XK>)9j^%+*ie3 ztJ?XmDmTH^=led0t-UE5;_#f@I_5+zq^v?cb&M*OtJ-C+^3rkU>_G7K{lE{4 zH#;zbU#x1UMktA`3!N!rxsQvP+{qf2<7%hmNofwldx2gHP7P3kquxv9e z!EDYps$#Sa+__n$x%mzw;Cy0|IiKzK1zg+0Y~ly+pUGw>J8c8kR{_71o0RiHY_p;D zVl)*1z4k4qSy2nQr!ZOq9Cn#gS-xxDPOII67p}p?zTg`>cg)9KCdB)2TO0kJ#T;pb z4i>2lWF37Z%;A<#bDrK;%dhvjDi7@RQ8*nqO1@NT^=}SNegB~S>zBHOpKwkn#^d$<3zC;V+C!3}D zoOb33MoZB*W)OrTaCkvryAP7h+99N!WkGb6kN@A+c`NdV1rsP38B?`pLM`z;ZC}MO z%~JdF_GX^Owi8ID_U|mUe@ALN_AzVmVqFSG>c3p$8RwhFu;Zi_l@GT;`BnZoseByh zjPQ&~q$^wB8wG->eo7G4|2Lt5>IXST`hD#gY%|GUO5o-lid5XzPT_dEe9Wpjc8%}?Msl3twwk%E+3t(Oc7DZnGTnsr&~ z|BGTzPZ*I23XvYA!s?~n3HXLSC-dk0^rV>!xedYU@dOPHM0YbI*kDrWaRfLqH?*5s zk-bSO(GOnbS|)fKTznW@+$Z&!$vZw{HuUEU)vbebe@I`TG|?BnBy@x?0CO{*HQ_iP zDMweJ1VP^>nbP57T zoPw14IK}P%7X>;6K_Q)DpsBGEN~DmeL|T9vHJ${%M22^5}U5V>ip+EikV7@=459TAaI1kHvGpJfn#Gh~=qlXs5 zqDZw+qF(OL04ZkmKi#f)a=2NQxMF>&MIeY;qy&W)`G7HIu=Y7e1p*K%kOH9sX#tAg zW2BkDXsHli*Zw5=P%Q5|%G|~V5D`4lSbxrv|2a~N@=rWiu$n&MPj0-@q#~O{Y8QNA z_67X@XQ5L((ieTvOZrAqdLW0=Q*!7-3kU^N0YIV(C?u+Y7N82Q4h^cyXsJ=6<=a8) zz;wAKS~g=F2xgo@uL;Eb55Sytv`J2(;WEM2BnNHimciplFl`h`H6@Pv@9m}koZaKi z@*4YtFrp0byJdjiNv$$Kfg92Qg>HCga`eA^Hv(9o_zk!J*({JCxd(b^0ZI=n&?%Tu zKm!0E8h`?#0cZgjAc4_>Yts@Z1hu>&&i^OYXRQfR)V&#q?X(+8_b@$+dc`!z^sE?x{|dpNx6Q#`2+$6%+>oy+ z^t>uxQ^1RfdR&$7DWqbdp(kJE9ji2k^|bj#8?fk`$~kbAAyO2$R~hi5G0y4cbUooF z+$7ha3Tr{&(JoDI2Ix|4papzb3lq%v!J!FyLnsi(VAI~oUyH>PJgBDV{;=d#_oieu z@}|5)NwV6FjUdp-bvHeM}a7(`}<~7?IAJc zfNY%}76}I=<#>aS%y%A=8;R(JdFJ*}8jtB1g$96L`Di;nqv$LZadP z>fVVZ`NYL$b=JsV8xUV#0yBJH@yp~J5Xaiu+X(TY&9x=waPKxs_@_x5Av}PWT53M+ zB?%t*@-cVTO__SW$>R$ohI4oit}t)D3|0`w@E*&|@&WsCLq{?cu8cW)y2r z5Tg78H^IusD86_TWK}PaN|by=AZn96)J|?Tseo>3x1=Lcav9gnF8ceo_`2IhIlg;~ zS&DsVr}u6kdY^gd{qm<-KY(=Zx5(SylDBAf_}*-yt>2Wh*X`_G3B=xg4|{`tFyn|OlBAt4@x?!wHKQ&mgzn=hskqgb3NID4<>L>T@vOvc z<>=YP5-ZNx&C2uXAzC56WOF@MDt?x=aoFZ>-8z+c$ucX!F5k_8>jC1lnmlZ$S)0`+ zXwi$R-wx1!8r^nx+W1{&EK#*v7EpqB|FJ60d8@j@ZnL}I<+kiU-U`;Az0KQi2d;Y9 zx#|{(tNtFYY#L6M8h(<;?ltQ~J*f}|)bIoa!-aLwo6wf&|^6m6Av2Hg?Y{bs-UY0&1|upBYG zUpYSHfcX~NMtD%U*>|^PZuT9i#i$b1t6O3I*^g!&?I{28N3$L~Mj%jz!+~Tt>yhEk zL9-!o@D!>3@3`@kSu=!?wAO*&{mD#W_X!_JZe_Zp5ncZnw42MJBwZaiN!u17RUZ# zRwI<#OZ|7g1F!iwqF85wRoHyaF*8LQ&)Xj}+p-Cy?pknS-+!X_rib2}$IWDtjeF?9 z$&&JgB7F$*dM99NwSd2N0(Sa8CKS;O^ZtqEA`i_U^32Em%Lsvo*vDcfO<*w^7cY^ZQlO&W-o6CT)1{aaPizTaEPJ8U0(Mr45={$0e0!g zyBOzvx4UZb1y{|6ut?VBoYxr!C8Y@SMB7%yPA_e@KX0b#$#;4BGP7Jz@?9$_Pv$?J zhkoD5&P-Y$W}bC36MoU`KvdpAs=WPOpPbyPX?NEvNIp0iRhZYgWY*BfTRe?-^E94M zy99fbuiAN<9EhiBZl1C)oAHFFG|AHhU!JU*vEDo__}%^((A~*Lt!EQco_aAGynyY%*K0Uq~&w$IpRC!dq0* zJ#4w8o8(>Th?E@Wl7HVNx#VN_lshB2dy<@Q3=Y2Mj={EE(oIi@7^!E&2Ux{j?DHGJ z9rWFAm~nc=dwlv0aQw=4QqlJUBsg_Fq*mSZ@_aWb;L$t5u__jM+ja3@=0H95p0w-L zCt!lQ>MyerZ~Ql8kWcWAf5T39S36Uk0x^~0Vd}L9W=qoR9+xIg@>^yA<#M5pMPeP}p2X~S>U3-taiYC^HTB|Sy zRO+t^29-Mdt;B{zr+^CMGC?JC#yj^&&UlX?L3Q2=#Cn1I?(SgA8QrXNn>wxXRo?3C z9+cQcuXmiufOQB-Da}65JNMtcosF@!@=3 zNa6%N7s_Bvf*i3h-x`uwlV^n{mW3->J_}83%Z}JN{wWa0r#;3vRU|Q)bp0;U7zens zXky)v0}3Iv#T`{FZE?V|1%(e}i;%yS2ZJrTksb+Xlo=}gEzJ-^;L!|`e+TfeTK`Ae zcLzpQJOTgSyFehDgcNd=TpB$PLPAe22}!O7k^mxBx}X?9x{3mVD2kwfKt@Fb>>aR0 zL?MVBX*RG??4k(RJKyZ=yL)pb`h8x$f5@>ryHj>%c6PSBzsUgqUx&fRGRi7&3Nb47 z1r9?+vSXz_@NYGRU~b}EZ72+G=@=%41rs{BAwowgLNSi3O>vyVq<^lGekJ5*IPl{o zOD)l&lJ!cl0e#A4h}F?qn+;c59Xa9(20;Rv*%01^e!Lr7IeM@af)DTC#tI<>X>Myr zKkat7xHazVt_{Wq4dJ`bkMHI-j=s#~{rG}KZd78YltX?}-m?XW{5&P{SDDCPWxbNfG5^&ZR-`$4Xs4h)&Cy$Y&mc(T-!+8y zPe0zT(jEQSP;KsVGzKcT zQL#%&TVL|Cyq1;^r_OKImYsbtHgm2ww^DG2<;mVfxWm$~sYaWf<@g7ml%s7~dRnf2 zh#n*Ok#OAEbwd5+Hj!f9i11C^^0t-vGS~#kFkLmfSpK4`W*47n=$7H)4vyPHubM%| zGhL!#N=L_MvDcXL`w~ts=vyXkFiYf1KkAnBHD~BbUe(oRrH{O2k2lI~G!MjeaV!^i znh4|_wDBonFydoHnc0qW#lwNH#?|n!4bG_hYOT9E>P0`e!3TK z%xv%GNQTF|IZDML21(a%-U)=%2LH-}^KB5<^klo^^girT$w1UksFtE9_HSunl7qte%N zxEoOyuqK4)90SorRzZl)k%)@K<*b}=oWpQjCzi8n>Tjvh-#S)7{Vi4fJ;KVVzoo1{ zE6|;@mlzCnT5ojv7OS96>t&}_b>-|RtE8Umsb~FJ9HHHPhFTj?6?PZuQ5?gNyHKnd z-G#z!jl@F7#7YUQZa~FrIKuM3zALEmcgPjgwGy6Ri@8!3nAf55pngu<0U}v;W|We@ zJ^B1OIeMA~%k7R1B7@aR2dJgO28Y8QnjFc7=|zq{f=H7=Sk0rbrO44OvVC>3+GddH zax~SFVd(jea+_Te#JNgf6ymiBYh9BPN46!l+$=VNC%Tg}&@86lDNe%SUP1@?NZ&|U z_}y>#C4&-21&k{teB zjCpC#DSgG;tN|s{x5DVb4!o?%$~O;oTp&JY1ro5EgzzaxRBlZ7%+=SgUbuSRYU6l2 z>%hRbdG^J9#VTvD6P$CdN7 ztY>0(%nz+%QW%&o{-~K-H}(R@pE3Fh9TvXpwZV#g?fPVd1(d^1Ce{ne{&Zd`?qxXW z$k|3&pq8OHCChKdw!Fk~r`W;Zh!#5KxJ`$Z$%9kHHdZUoms{S(fjo9;LZ*0^)lhJH zK!=SEN0>XRM|8-aijgz(KQN%VGb7m)R6k{eh&Ag}W!nI(bbyhQLFW%kY8+JoV03)& zSsk|ATV19=x|5Ozc~gVtp=nbcnT%88P$y!Sswy~kI@IZA_~=k4LXu24B*}yq9GK>q8OsWM z4k&$MS22e5D9t1QCkfL!!(k26Ix}r%$C!U=d~Al}iE!i#@C_Q+ZxD zl;?F;Ybwt%pYnXls!4f{{FCyW_*dmImSc#Wl!s%N$^(BbaQH71AQ0&d2O_=U1vC(J znShs)FkT4|hH)7sFDjfVJyWIzZ>g5Z!O2wp&fpld0-lqM*;ma>5LN@^fyHNj!22fCKROG%X3 zaNs7US9CAqzTghY?QS$Axslb9UdekImaQnxu^&ZciEXT!RuX9TIQzl;M$v6|2$a?!rjmq_<44kO}a9zSnXH$8M@Sy`%Ub7&{%9 zey<6XtvIU;s;*Cq@X=kiK#F5j7%%Tu1r(|HY}vs^NjhB)rwZD)tQ&QkV@s5F1`^ge zF4504fdloWqvIqEDOn?}Kw*PHbb zotv7LK@U&1Z`y!z=QoA16I?w5%(Qfaue7?G)=o3(jRhk7xyyG zXy7(9#M$F&;F4K{F0(aqBMa(JI|f0UmmCqkL_A-+Q;p)Cj4I-=KA6MX4GwG7D1zfR z$9eGaGkEgvh2I<-<*(L|_97-o-eFxyXQm%+3JHJUO5-T2pfUZZAB6avU(G8(wwB*CjvUuxOTy=qS9v)HxY)o^;qmR&=0EYH2WbSGa(x zTQr$uN|=#dRtZ^$93_yj^tcr^JmpA^&`d3Dki_X16|@!j!@tIt3?~)K0&b{QNp3#u zKbVxLCr2w|z3CZ;OA|v`TM8B~j8?(INLC@o6c6S}mP2!am%!MqL90!S6(W29cfLL} z8n$e9v<)DTn41&KTy-FG0V6tQT}BMV9I&J+pF8Av$3e@TD7OPoM0FQ;F&3r4YIig+ zst>AB4REwWw>zdrI)b&n5yT&XBluh}ldBk$D~u6@ddF%_>}74q-O@J)4q?}nw)}uq z(>T7@z&L(J;}{evQPwiEZTkqbmh-i}koYprDV$h}NP4UtIz;@zX!J)U`rc@0(cRfS zpbcrj&%wgk9Vnat4Y;FyZcN?$R~-X1ts88A%~2@2H#3Dzemc7uO|YS=-4DhdaP$gm z%)_NI7vk4poi>Qy-7K*&9GInJGaR%BrX|DZ-HtW_{}-SX$rZAIn{~TpYW~e=MkWoz z-*mhuMzUs7nCgSBt9wK`W$G80*tmr23imnsYf;xBT3B|GvxivB2q5`h+mL)$kbDEo zYW)Gnj0nvNW9*aoaSkz`(LwXT-Lino?`ngiE0z4}qTX@jY2q2yjnCH`i#;g+V_rmXtiEcInFm%Z93LG2jWyEv{H?D0C2;m;57pu{&H zIL3*T=B8%S4q9S!wV&9YRmdGQ9V^DJa;HFMoTZD%XSH$*P1YWmIB<|2hkpk;3u{N~ zt*l{qsfoq%i89cwwbG6Abw)dMCIzNwBCHfxDMj1e{KEDcaH1;0nmcqg1k%N zf3JkEucg2Jp!B;U5yRwcV)!OTTw45bGH~rYBr$millnd!bQ0VI^e#h}$>Mm#L0kbbYOu z>-$ZjC)cM5xcyhhDBEMQg!{hR7=_aJ)!{O*OcTuo!Wp(hYrbTm)_f_fg5t_Vm>%U! zgQJ7mx2A=Fx4ldTNDhwDCPWPXpvBneKAOKqw*M+|bkzzHVjmoHIrPMdPd@iSO( z;xETZQN&7#QMbXUmsJp>&VOPQccduPHnWw!1s((}i;5mmyW;#$Pjg0dnIn2XnE!sdKaV zn1LxbjyLSZ`>fRTig}P0P(N&L49sucF#(QN+J;)g;Hw!C%RJzD z3C`~50awnNkrHFlrW~LvHqZg`*l(r;CI@&mlq5PYv5k-g+$(s@?&{G0&DO*svjk*n zM7tUGC8NbIXXWG&mO^5tQ*BX)dcNCZl|#5%wlX{)=10m48dr{`L*n#Bh)TLZPB^)g zM;lF@kV|=b+-kf^?;zf1@MKT#{*yF5ja6|Gmxhc2 zwF9zMntJPJ59?Ab!0@df{2Vw!l`no9)7$pTLByQ$8_f9=Ni-bEc?ef-*z2Tg_4*0m~Zai%*rcFF0ahetFZ$ z)-XtF?v3+1l1qJ26oXSvaL7v-2hVBB)uy z4i&x|XJqFNvT9m5zO8gA)Q=pCBR>+iOSVvc#CNK2foKz9eojd)e(T(L3la=3Z;NUd zK)IQ!`;`$)W+XS}wcQZk-I*KEgdEQg5}FI>HM4mgp5OdLi%p0}5M{o`DVq8o&R0Zh zvsm4GNr;DIdCr_L@P+x#5u$4tc)6P!2EL%D^K4NR2L7v_&hjwu=k{{mBC5l{m-cq% zg@Iq!+c`#z2?LMxsJHVi$TXDMr?iA6eVpfs8DU__ku%w-r{GO_8jgd>lRoJRNBcT| z5I3<7&6MzJL`o^)T2@U;cWZnD%h(O^4Je&G*(AkymHwvqHDBN%1CBdL2Mj->fbCYD+PzNR|aArKdzU24PM(omr_l;qX#( z!Wqy)O*mz&4NW-3EgBfFK`qqu%K4Ntj?Emccs1j2j62Jn69g}i;i`_GTcx=rxrLfr zo+kkqa|<6sb8cbo&*$2u*QL4TTFC^>EsNwYnp+mNXlQPE!sR>=W^Q@I?R-q!$;3g^ z%7U|U?3HGr5B0J)8YNQoswDru#c|Ox4|Eti%w+mK!on|` zg+Y%mDL04uEkn~SHzQ0|O-z`MMNAU0t1YV^>fmaYeMOOtWkKJmJ5Ln zK=A@{Z+YiC2gR~dV~(fKa?~;UD51&VR6>)^An{V^nY3!jMt>OcZXX=!zp z5g)Ps%<(#;#_JHPG{@_dF<#%ZS{kqK{z+7SHZWdErkspx4v1XJi6bXD@dA?5>QT;- z0bs=Gy8)ca16P_?7M1J$64Z3mTR~9%fa|#Fl$o`2PeV@GlZZM`PT4DekyG|2Hsq8o zIYA1h1-+XUyW;z|>X%E``3lu6Y= z`m{vmkyivmEenF8FStF(peT)dZxGat6P?pVJ%gew@bif(3%r+AP;;y}-EN3g-KhJB z)lwE1Ybgtigwm`KMqV{j5yqbZK0V2q>zfrAu$mRl!xSvv{Nfp4OA?L`%?ct3-k6cP7-8gx865M&yi|H8eGCd+o&_D5q@3^-bDZ178>}-^ zLa!JSdWF@R5;|;1=qRft34PR%gpU8Kgp9=oA|?rO#3UhJuyd|+uHXg4-mXCQ>YC4Y zIy8}*Y+8cJU#n!L0j*dq@kbvx=#gyPZpmlWG|hB}p-UPJqU^~kEZ}-T*IP_IFrs-x zPe+$IdOEs1lp&;}%LqyG;E*H_UO*bN`C8|aSXOFi3_Zd-iFHdF!{C(0#9fEq^Wvp6 zpS6_i_J{hjEiqDS=mhZvIQTM$Re>rZcX!=MxLL788z=5!NXRDF$^yeC%}nH06fP|W zw=sAUE}qhFShz2T5iVsSpOmePOynlkB@MQGbzFN?LX_)kam;-LQzr6z22BK?3?_Kb zP0n{kbju(O!V}OUh82?dX*=4&N=awtzK$>?qxQe(-;9j_Ukut~=k zA;=j|MkgtwB!3j0jF!JBIvEW^RyaEa?iJ_HKdZ{h?mPQCT6+ev?&)2bGTGnJ6n{rk zf;;kkz5K{Z=dEF$Ie7L~=YwLgY;Hz5Gwm%$0p`M;F>uRj=RmQ> z#G*c?yCOH$o?;gIP}i(R1=v<;gE?!QHR2HyK!rsQw4|^|y9ZX(IxiKwg6nsvdi|c3 zDjEsHoW$UZM)32VfL(-KX=lw;Tr#g^KwOfOAe*URDa7jclM1Z`b4O94mA;L(ZLY}aKF;$EddY-g1m-}zKqH)@Bk00;y)yN*-{8!H z&YUjt#Vg~Y^rzS0nYV1@wB{>(R~gZ#$!BKi{p95w!G~cH95N6fs6>Dp{>j@V zv$13Be~Ij$UJuUroiXrp*#3Vo`bSV=pv~`)@n}N~)GGvSlO$h%q$fsiz<1*O{pSSte`-#YP`x7@NoOIH zY-&h4mH4V1cD_(PZbxqq{=hr;1b4oo?h2!Ggrm++z~0Rbb^fgC{DkbB-r&0jU(oVX zJ}$U(3SUMm+7XhvUk9U}XsG*h@bxjIeVu%Sj2?Eg;rm7Y?&pQ;9_}lwYNaC_iQW1) zoP5%mb4^&i+^2fC$`_vKsj|!EEf{(cv5L&y%ZHS`yEbep^mLvuh42vwt6oYBMWfNdDZW@by#97F}MDI(bO`^Mm{+UNVv` z|8dHHM$3P$!ha?}*%CdonRGiSg}pFzQLhT{%={t_?t0ppEgq6^WSaND%EN9a?BBdo zRGEeHmz)@uP5G}8!Gu+bhpn(_OaHjq?9++RXF-RtaH9F}Bq(~Ke;j0P_ryb9ozq!$ ze;A}I|0_~hm~^@|98GYQ)wO-riJy3V)$CpJS#5ho7Vw#x;fJBmIoHR%Yc{dsMA-X< zOi0`2yi9y-mcs$ZVD{B#>k+I9dE?<-(9$dWgFJ!Fuo|0R0a%}Rmf-i&Ry>d6@-st{ z|G2kW`(A2%e{~T4de47MHjqT%%NLySf+4Qm?i?Rh{2LoV{4qP6BQ-s>6(p{6T#SF~ z@G@bAW+`ih0m6zl$&mLV<`x~TOf5XH)^(9K08YPzYsxXL(^Iu7*!a4$C*0L?xPa~V zxl>{EF6YSqHoGbQktFM?X=j>gcKG5AXFFkM*mr(jF*s5FpQ}cHNlm%lrYIiykKwMNNn4MV>2CA_P(HCSM`Di)R-0{eV7J}$C{w?Yd{N)B%I zhQF1Maa^1BgM>$0$4CXj|ESvtT5AcICNCps80JewDeaw|+KQ>Pv>u9Q5eb~O=BB}l zzf;>=^wzk2oYcOfh-z&r9GTbuVC*|m;Vx{JXlou!80)w}TX`~KTPcSXyPS!T{*lvK zJ0ZSh-O2sVDoyXwT3HVMrE9ojlKRHLUDBa(~ALcwFbz-tC;6~(95~llm<*k(^ zop=w|cnf$_X-S(7IwP2?*(nAp-*>)cc>tL>{c8VA@ereg zq<9~b;*&~>+9=5X(0Nv)h!1a^7k}jRh>Z*{8PvFW%=(rB!7H zH^sYhQnN`0*wiNj)3i{tOw;Npp_OT6sfN;%~DvEW|sOoTXs+5m`@Vqed@eGCr|d8kQfe zP5}F7*v!qEmF;$)t(Uh^n=mExS6%LDpexKM+}fn3C-wlbturzN0|Ok>c6#eJGJ|kl z>xuofufk{k8 z9EB(n{uq)fIEn+E-0jvByYj^Qtm|VtJk=J2Qd`i$;PA!?JOlPk5WHj{@zx=D@M-m! z7}%=0Z1|z9TfTEm5&at{I=U?pt#UTF`xRM0#$D6aH15L;jEwt(w#v9aU=@Dj*1vBHL%zZF%#W;=4CNFKj^DcfHVozQ zws6_E&Ya{IB{T`i*d#>PcO6JNmiQ51f{5;7C8T@?tiwu5#Y6Ave+tjr% z)ZSlf>Y5t|rbKX2ynkQYQnB7Fg2amIvo(Oz(XPs>Rc5)5oMmex_5#D8`Si48NQgQw z296xVo9nsFU8UkF6BqacjaFeOsChCK7oHkErqCh=XNDJfI~gd1ZzA^#aCUzQp_TD7 zFlGF=q>}NU?VH^ts51Uf%w4Oj|O%lckHzc(ti3!$)hrPB65aOQlqnC%7U= zshrPI(+ZK1;@AC0BGdgmk87-Yo~d6;S4skWcf{2U=Dn1;S|4mvOGNxjOT?+Jf*2_5 zePOfE9vypF@{(f-lItBDffKUgxTS%pBKeQG2DN@>A^{#C}E}N$O1|sSlK-;sPWEnbC#maP&@B zYZ&mLyE$Bv>-vw+AAzJ&f6WH@=efFy*BB)vsc(ZN^|IpUMJcHsFm+X7HO%eRc;foY z*F6_k)%&F}aBhc!c8cT8JzaNOI;Tb9rcps>k)385wiKS;F^$cdz3|;3`QjIo9&G;D z)gQ2v7&vq9@n%rp+w~t`79!bMveKf~v?%N(@UQ7%q?Wm40oSs0Na*h>*HhC}KH|;J z1v6lGLE{PU9Do0E-R)Dh`rDJ5!16^IP2lVPt{0*fAXTvA(ZVcoEhCsDH=j#xSs2M> zT!@zWSD`EOKPDu|BCdjcc2~N%ieV>JyDL~+S15L78RB}Q$hBBJ!CFy}HLuv!Nj%3& zWlW|$0e=;{28KeC|ub^uHJknGJky`&IKMMgPG80{9Mw#nX%U_6j zU(bS$;tZpS#^Mh?7R}R1iyQO-r4Cp72!_P+3z9*JHT)5%!>Q>(I{c&J=(I5?@h;a| z(L)0HmSr;XJvyx<3budi&K3Pw6-CPk3(t=#Xcy3^F=Vahq^q}mkTfpr4PT6kfv>zc zKV4c-&C*1K81M@-%Pcv51jV8`ap-r3zA^W zGyi!~Cl@>}9qJFeI*4(M8fh2Fi)8_KBcm0g_?&)OrE48LH@ML}hz^DfN2CYHuwE+c z?rPVoQ9F?s*puezAa*f2NoqT|)b{*~#%4Z$5@)T~BAT_dZLo8w%O zA+e{W#CpK~jYVxC?-Tit#eNoaJ*V*mc*+pq(}4n{8Lazo*LzWIGf;qeJv{A&4S)Hq zMowI)GNrvjmflkikQ7h>{=dm=HwB3vx3>H@Uyq@Qh&5o3#k0pjC4I21qct1lzB45 z?TjH({xysj3?1dz1;iXf9>JL7mM4!3c;r%dMB&ED48vFB55N8pJ5L9*bBn>wQaM^% z#Ou6)-1>-ccGF++_s_%y+nzvq?YPLb6F*3`aJ;L%_@3bOg`C@^w63CtG%8Ed2ngg^c=uRDs2$I?*!BQ(V zxGDy1HhO`{BMWX9SF=_WnAKnA$`y-PDNX+frlx-mk60pC#w!(3dU0mJ)J60C`O{r> z+Eb7?1GVuPMiOb`6I{miO2z@Un>#Zib;OJv$@OuDnB@AFEa2Yt5ksyIO1Z9rtFCN3 zMf}u|&Vzx{+5BEFd>G{l*S@H@EL6g8=G!}o7Wj)RAwGb#WvOr7-Uj#S!mg(to#W~l zf$~|RvkbR}Km6#Wn3B550xl+e_IW8Tqwv#P@(pE}d$nr@Y@6R`veJtD{qs0-eGV=d zKb+^HtyzrE5_W z-)6LseD^W=ejG-=w6gzu`$+*qZipzfwCqN%H!m&76!;@hwkKr)SI5^B8!sEOZ84*J zb9nrUf`!7;&TJ|LTzeaOM8OKBe057Z$glUbfxHc_?0_bXB4f-jtw38r;<2@wNc3{VEU-P(}kj5 zpq!ozmeVrD!V*JH>sx!{U5xSkQI`cd$wn0&zm%cnDrj*RW1Zc(f3A{Je`2!O_?YB5g_&C zC9;4^eVoD5==RD1>{wL*VjXKXeXzGu+{X%N{z3>fe{s-85%L`-L0rg`EQx`FRG9XN zD-|An$aO>1dq@>bFD%LshZub%?02}ZKM5mjTsoc;fnw|X+pE>keuf$OuTK6^7H|pg zF&KKoknj+>#y@pO!7%t^bEAbfV9rrM<(yOikUNh-hlkvZ48tuKpsMQ9)v>k_B9BoeYNBcTkF%{*-H-7|WW`-s%23 zi*qcKI^f~I8;U!NDXbbZBIET-Id4~VfGzbEffWGIzMr zA@AVvXqdXk^-NS95+M~eTWn?IkXWB)V%-%+tfr1)cP-$=Hp~r1xKpBSfl>QiMPdu1 zg#`VsEZ~BEobmdI5_BC3I#v^3^R|s4)-M84aj}kRKe2a(}0%bcX0}U429fql$!CAPczVCUsVp+oH2l z$~o5*pChVxv&N9XojUtOx=i+uGU)AEJO+2A1=-pmowy~kTbX>7yN@HkL|8- z!{5hHh|`WoE=27zc;S28le>)3Lo&Qo7H}C(GPs*)$Z*dOuE{X(m&P;fdrSmOe08>; zG5KlP(>V$%J}Kxc_Ax?9aJ#wS-dBPP$TMB>t7~!u6NKeeM7{8{f-VAo_~#~)(Ko>| zddXm6ry-*|e|OD-k$*RyjQ%tcFd4y~7eL%_+J9jvoy4LVmcZ}P2?yzpZ#obwp_I+v~p}(cAb`2ynahHgNj8+of zJSM!QN_atg^BWI1Fi8B%)uZ;Nl4h{JsXLO@hc-vaY!0J?WVS9?W|u3O&FrFF-0|-V zE{Dq4#uFUw*5R1o)gLZ6RJ>x%atKvz?9T-Q#0QK@lGb}nTA%%csttkZU%UE2<`)Co z)_#Mot@7gHi1&f?x4OXe&s`bfEk+f|?&o0H?NhRQ(~w`8EU2xx$^vfUg$8H+;F#6jL;D#L zTe-W6*{mI9hvuIw$+67Oj)KQdmSl?stlB&;GnX@aQ#PHK377$%Z|&|8!3?0!#y;gi z8BU#4q~tq;xtihU>U5^xy?`$^{Ud4zHh_|}LAhclV}*w71af9I}stnR~`y?nyahxlo+p9tnrrHJXRfzw`Ic zg(m}2I4%l%E6x|3I-U$Cv)oTcweE_tw3Q6%FWTa-fJLLVt5W~WVHrtU*M_x!Y|)@9 z=-$B{(HZfiuFB0MF)Bzq`pN>X^DVlnFf_I+9O&r&NepByaO0^`oW%;ru?+00p5qIG zYzJc!3vQ2dbZx(;?W{t5r z`Q60AC5KloV&KNK!p`ar!L;7)L^waKuw(53{9ao?c~`wdH@LI6ySwPrEzsVycKDRN z+sMe~b!*t(Xloo%w15r6@P@(mVFMzbuyTUF@IdrdZx1n!)%qtKe0;!UcXGGT`R3%TLD)XBbI;m2 zaI(cagB!>CHVi@KZ15*SV@4?0HgHcZ+ zJlt~OfG*-`hK9nqEsXIUYMcWssB(aNbOaNvc5hO1 z$#l#A;J~6mS>kinmPRz=xeq$xr-zu)%mB&*he18P0dRvqg8=gdcv)&SAk_zZ^2R zfMKBHK4*SAo&*clN1h_Ebj*o@f%%1Yfj|6|kSnVQ=B8baidQpW>^bfpuzYUMW>C|! z@NqGcH*E}ec7ejAXXFH=O6k^JW~KYZsOu0TBpw}9Feua-+XX|d z1+SeJa&SMg{J0=tL_Y&r=nmfwei{QIlA!v-&g z*sZ3yBRS}(jfNA`Fc=ukC?KgV3YOXkCAISnsm(pVaGC(#O1@9!3BJC(T1nu1l7N1( zO}>6%Jo<(g+Rc}#D&;+7^)i)LUB;$I-@@FquR$F0(YLlRExS{;kS4hCS~ zaj5{ncO!X<&15cJOM?8R?lvNc5k*?mR~B&F!!J-RK~F&MmBsdu2G|{r zCfi(^JFr4J7`=H9`Iy^T@XkagA6CBQC+z z)@3)jBX|yivprt1J)Y4-Y~L8n_E^T-y;`SLv3vv5FFt<-KrZ#hKj|Wz;LH0uZ zZ+&8*|Bdb!E%A96H%`U4F(EHd$Mx7eGYrz(=8={M1=tifX1;zh4eB>lM!|w+-$X<4 z^un0N8+A)Fq;Kqd@vQ{@2n;B5WC2(ACV490)ALMK*Nar4rbFUtcmApsr=ro+@p}`f z?tbrx55C}>kq_6zrnl8j!or)~UhNw-DbSOB%zycwAgMW?tDfw;`4;y|{$`1K(CgHP z9s$#qyU!KZGP33Sc~$ex0$*p1@MNE%I^V5u&k?tq7}V2TYx307Tq{v9@{@F3Z*`Z7 zEx}Na<*APr?O+vI?+-d#dkn^`auApe+-YEKosl9KlzQ=JPM&=6=lm3U>BlV}VfsHoB_ATp1-0ohXi;k=*g{MOfU)UVd78GXcJ@R2_9NwAFXCU+pQTKdinD%^nIZOO0 zgLuRU7|08qUJrRc}nf4ow^Dq ztE4Wl($|IjuZ@Qxo7@$)XxSlGfbUKD04czjYmyS_ zDI+n3A(w8-c3Q&n#x)E=zL8Fflft_6iCocCopPOQKq_;+{6#8rJ&fJr?qp@gEuR#j z*AGvl!`N0e7XIGihG07{g1zG^1bkTM7SKG?g-@~77FLS87)3PxcbEk}VwOQ8sN7v! z-AQoSQ||fVX%mB*KDXc)$?pd~))P**mmlwY+Fc>`1Vg>fpyWt~A++XE8cBUkPnz$9 zf4*CWpV6svw`{gr&3Px_(K>gP?NNz>4-YV$H0Q}jmc-Ajluo24oJ#$#4~voYp(t95 zA6TzDx4NGaO?n|UMh2U-CrTC&dB!Bio8V)Z^F$loL_TtBl?9{;kM^W@FsJ?4W~QZg zFZ{$;^NcLfm%&ru-4k}cfKkKI%;a?Sc5P`dIQ?jK&$ttkIyKwLM+on3k)!2GSg+{H z`q&BhT2g1#$Aazdj=HrMJqW2KQ`xHeuTw#ODl?8zj?;72oAv^D>F&bsVc;%G+~!An zs*_B1jgNWGgpDt{)9b#icMsIWa)vetyqTInmrC%5#0CZ^#TeS}I+M7(7i}^6(q1sM z%2UPwjUI0_0jGUe7^7Ve%U^OoBI<)MB%72QU%|T`d+b_Krq2xN*Yb>AFzYPq!$?EJ)I zg#tRi?!Hb$^+rm3TQV{-|DRdlqkmZ=p}Y!8-Xc{Zr{Ai#awy64S3Q**26;_VZ;A)> z-+Ph2XlMG17Q-%`GHvpN>It)Q$4;9zd5+;Y?C{x}Zig*NGQu6lUrZ&)aon=G@R)F# z`~uyPr{~5hS?RI(frCNY=N=deOOK6>3Wkl@@17X|OEK-k``tO(3^=$S4+qU+O@^-U zOwgzGHltZ>KI}N)9@_FxNiSyrNri;?PHhAFmcgqn1hkAHATP9m70_$E>tq3Wp+9?( z7uwvj^i_RZZ`=;>bQCWza0<7#G6MBid#iBUE}@KYdwKuL{@T-U@?CeDc$&2)nP&7U z?I1p8rF10Z>E5uipfWoE9NEdnue>$s)@q9h?o-4X6Yh`S+HjuE}+XvpP{ZYl$_yD5+Lg^?)QE8zWY+qkwFKqOZph= z5(Xj#rFF;W{Cx)q?0rJzB$p*@Xbr5030mwZ929_(QXL@#w!_ceAI88m10-i`c4+|4Rwyr0D4Dhy^>M5R{5DN_O4xCLuaDrt zpxYQM&7dZ>I7Jp~4AZZ!NU7U#)U7ws@9zT(-}Me+*jt3c)0c55&}Y`}R|Vxts;nV~{_Le9wuN81SA|Aw7k=d)DGoBWC`5bPEb!r9wx$tW_v>G~ zXIaB^Uh_H1N3NUp;t6M3H|;)-5%SM)@;FAwpG#`EFWGOBCnMy%x=DKrn``0>D<;b| z-}#H~Ynl$3@0mU@Z3@08!rL5sVPHGhaKgP>&yX97=t;6zGx8*9eN9)Vck8Px55LP-vi~#% zW#lqo@W%rj`nbNZ&{F9U;~9lg&67vV0vZ7$6EUW*nP0H&4%4gQo<~FJ5AK`AeAb~f zXV#(NL$2xzV`q8Bi{%V52(=N}EJLZ!#;3ut1^Ez@HlwR6`oi=>p0ZW}T>9wgi-GEG zc8`^*kQI5OxkM>pmGxOk16kNs`HL)UD`E>9>J0hCy)ta5v$_%NrTW7{J8b{eeX)3( z$%RaGpIKlv7+BUwDC1z>2l&Owl8*~h;BaMSqWm>X95)ftqDuP$^8Rr56~D4_S}lLk zmwh3+n6qTcQO8c6o!|YW2lSh5%kw_G%>S?sg#|)JuTt6zufV9 z=YH_UUv9VUm_*GT!<&qjvg;~(!RWu;li;!_k8y9I+O|8mNq0sd1shIQAcGB2CJRVG zcCX3w{9zg04_|nCxu~NU%OGj`#Al3}c+`y!e7r)_J$*!H31j$%GTl>PIUifoH$d@+ zUo!dMdWTyUVa>)h1KNx0Sq=5OkoCJfwBH`j59$mFGn=%~&+mt!1b+RK_wDy2t%jTZ zTKz1cLF{bRDP3O^wI(+T*J!sCCu(O&e0bx;c8$>bsr6QgEGoA$X|XO;j8f9n^A#+O zAz9O$ZOYoP%vb7GMtg42#3v>p5FYX{AY=xV&WcTh=bC#Ch#y!Jn&-{Vjjtk{Qbf~& z>u^7{;4*;>3O-aowAeZX`-P`Me?`G2hrsUYCu5Nm=y9@el4#$bjh6IaCb$ttWc0@+ znI{*P#CgsZy%{*Uu@Lb5{>qKXW*7=F#Wecc#WOcSdZSLErIn*~1f%OZR}Uge6DJ&AB6#dDFk-^2hi8?4=p*U3G7 z#Z#tU~63Q^L?#vk~^T@{APw87y`3CVoNBpNKxpY6ik!$i4AGa1dQe8W<+k#HKx=v2g@RKq5Jk!siq8kk0(vw6Ztrvlcep|1ClUGSxT zzFFWy-v}XU33O}cX#rD@7L88{gQ3O&3vxVZdQO2)rcs%m_S)IdCDT)3b4Zf7^m0ua zDNYS~*;kBY_2?z4B8>5f_!Myg>y>7-8LWVo&r@Xq&1jASTs{wgZ|^DEW4XD&nAesw zc#3+L7O<%I_5v04o-LvH%yt8|rCcuhc~$J3}v7_GJrpvf2= z2@K!0D|M$ZP4a2G(#2|PPe}`T;9l|2jB zCI(48ES5c3Y1ijAR!6-oHhaOhTd>EotYH|fxv)?} zxEUJC^7&q{zDn$5RcKU0@c`t=LQk&P!^+L85wA=2Gj4($EL2ZdKPw@X!D7Z8pRVql z?2<*CfSm{{uh?;HGLvHqf!xmU(mwjA{vHrNn5B44;wZepgr;j|Gx!bg$XqotlDp^@6$GEcQw#@HuQztJr4;a|2Q;$^TGc6YFkw}$Dw z<_X21b%UN2H5V9G;tNb-Xu~@%GWwQzl*0>shJ0Q(XR49 zFR@yhuIl+1@3pHL@ev8d^FYtrRUYVh*4)ekea1>D4}{>92jbxV*-d}SuJS;+6`lz4 zK-FqNssMb@*V<(ohqj17tmic!rAEj485{>1Kfs^RfuP z?vC5OC9q~F2GPsR&ei7kjVQ4{+MV3_3Mhv6ipbC zYZjr#Nb8%7(pD*&zt8q$Xs<*1a9q$XlD%@nyNscs$&F5u%Qx-CTdWF)y$VKOABmEe zz=QqmiDIAGYhC`io;Y0`GfTj4<=V;G3p|~~X;w!zexis?H-DfI@$-h_bqU37{OclR z<6pDpri~{SBe-EqWa9`Jx4Vm#Z>nREL1ZQ>$fpc4?`OTT!DXL+bk+PtY!K-DBqb9i*3$02@a z^pIov*(~s(U$!c;34FtJ&mf4e@r<{I>Aa>{iE<&QaRAAM)K2nb>1|4&{Undm)~v*5 z0>&isgGry-_<3@YCt4HjB%CifAm0d~k2`c_rDS{UO4ObY2lsmcy}U%t^-k7|{6J|5 z^8?i-$`7=WP}~m`l_)<@#G0FaU_2`&S`eK400;N`0Uar&J)bdCFZ!=@J<5G(T!x7@ zz-3&IVwW2|H<%`T0(ejSXN zg^TSc7@)+RWC9vf{U*qp?J3vSm8hk&S#NZ7M~Rx{!;@po@=RrXDs5<8mGwhO0$J2Y z@)uduM~E$~MO}G?=gv@z`gk246aQwuCmx3d$aap|Qp?0QR-=j1WB;F!ho< zfMqXBSuNqtRk*8JIb|<%vA~zTl)rrh{}XY5(`s00 z_p(^r(4<_JMfS@Bj_*v_OK)MEq}|*kTcnsZzEP1JBSs^4IZyUQnlWGgBF&gTpaIQz zX+gO7uXZ7Zejr=>Jd-@3w8|{-VU9HP%exyxzmwOa9u^d2;75ByG1S~gyxH_y2Kc1; z^CFDYo&oE17^&SSTX4axFuPDoq`cX#@nQ!nMT3nfNb}L0D4u7%$~;2d$K6Wr(ZpU> zOgY49-(=#u#5Z^{wL@UL5#zNF7zFw0_Xe1LTKfzR+=Sb2&qyG{O_wh5v`^k63wTtu z7xg*cnHq|4bBha_!_ncD?X^GQni;P7PoLeZhrR4J0ovMKgKcy{u{GEbh!W0jPVkk2aUIi;p#EQO_*rY&gF zGe9(Z*%%JCL#fIJag;%%8jvBRo|tOCU!23JAyVt7*$XfM*J6dIpBTp~=@{84 zPUU1t<#hXqmZnsUAQn4?u`}#FdGGWjNBs=^y1})qS5#7Zk^@HG>N%H#tK?5e&zuQL zoNwTr$Qfm1l#vdq*j3WrT88GD2YWhxx* z$RKI{HX)60w;hx{;7Ox1x|9RQmNEyfl*@;mw0CtzGA-4Lhk{BqlQcXeu9X7Wi;RdTt%v z;9$sGfZ44uo!4Amrh?m4{sbx#~i`24Zd8k^_ zHL8?{JvWEy<<}46(Sq)>H4iDW%>p0NMmhAneziRgPAx;_41=M@Uapk0L%A=csCo=1 z=SsNjF^|J$mo#x@>|_$DR&IYi=4q;l;jEZ^9)09%Br7GKH@sY}+&H+oa+_VQ{O=X4 z8TsFt<>tJnFDzFRbftviE4QiT%KuJf%}xIctdwX$aPq$#-0y#Nq?A@}%brgAuPZmY z!GXe0jyuc59k6_R7G*D&Z_kK_C8GjqpLlrJMyGnc!G=t9Mc@1dK=1D zWsP?rzhqM_g#D(*KM>XLEfC= zWH_4Qt%0j|&}k{UQebzeD+T@NZ(;2X6I!Q)Qc=^_q3kZh;j_D*+dUoeU5fLz<0Q~m zw%~S`Wp*L$?m01$6-X_ouf9!Vg;L42iI7*12_g=RI$i}4Ocp-=TZ;({8*LpfJ!Ic4 zmatMXzsz#w(bWO* z7VC&kG3;}wQw-Z3DumnSP$3*6S%q+2RLb_yL-zMYh7%DP8ck^!lVjs-SSp-)$K$OV z|A@VtCi(?|Cx?Lda;l7N=4bY6g_nVwV>N`8%CWK_7)*QI?hb&L@@L)0D*3ydD#P0g zvi5n(lS0tv!L&md#&&l?X0+F<;WUn5tQ&)=)=rh$-L%<$ow$k7L%z)H)re3R8%*ul zV!uMHW#E3xxQ7*z{;idm@vVrLhKM9NQlvyicefc#EGFvGLeRA~JF_Y}qn@(A1eYB& z&rF(aS}MWps>5L#r->tGTRJnzcsC$FG??j8ha+@~fs=O*>G*^}?1#Y;H@Z7S61TjI zV|d_{-J|UyIA%Ep9AgS7sm=5fPA6hgoB1H0Gd0{;m9?7-Wk?=8NB$xYp5qGj;1m@# z`_Qv7G%CW4wi&`DTXPRyW)}F6F1s_b#2b0AGoN@`!KN25Dhh+4W|)h-Gk&}>>##@O z|DJo;(-m*}K5*D`u5Fkki96>KlSUO34LstRu8AqEn3m1>7G^Uzb<~rM_sZKI!)5*) z2H`(=pv{J|Z;a!|`XUz{k4PLZA&t-%e?8F*@+$_kgfX9Z{_A7AJ}IPWQy}eA&$Y3P zTq~5F9@ZZAev0|WI~a|qfq3-ey(+3^o0SekO<2U$0?s(43Mmg~E)IWEMtdime}>hdZhS$XnTL)(tpP+C z@>=79*dO?fQ7cnnpP3m(P-Pt@i6Yw`Eq{@1k4DtN3vsgT9j83<wxGJ_smn>5Y<`worBYD&u;H4xRP6@! zJ9Da*Wer10&0@ET*rvLJm+`G&%oQIe4uA{d^6x*vkT_4nP%hj3^aRM-wlND`V6)N!iF6(o8P!mug| z>f&Vqxq`)R3hI9P$i7L>@xX_b6`e&c1E-j-tB1vOc;1bU1Z!@HLZ!jqdSYPnm-a>C14dR5qedY1p26szuk1_2 zHw@fw8b7c?GL3IgmiRI-qtoc?D}xc)Co+;|GGYKsG`ljQI_o#~eGu0o+{hV0Q?gf$ z+-=|5J8Ghb*Hp_Oh79;__{yKWTypMr$WSQ*r;!_ygja`3T6p^kFRLQ9N)b^YTSkw? zUNt_l=fLqX0J?b9nTn3+d}RQrBh3<$nVA8}1fU{7rpqbtly|;r%4+B0T4IhN(D5U?fStKO){hTzq`eaS_ZqxL>6|m7W%ncvrC8e`Q z#vL-=i1@iQ)BBBZGb)1ksb*EgkK5oUqz&;iCJ5YuU~sHSQ8G;Fx-B{s5jC0-)Ck{x zytBQxXDIYFo$xcO>nwOP@w(6^3p;p=!ZyhfwL#ECRa}#zv{3l{3!|gp!X`ys#e?A* zAuDaDb(wuiOF(*Z#B<@`Zf{zY8{BzE_@!x4XYpn@_^YCe+6KS}jd_wT}HE_ zWKDd=x}@xwEPUM@U!4zWMZHt#jKD#?WjR2vN4ewy7+xnz^G( zQI(Yi9KOiO2wAGEe@c=maQjRCqQLDhL>4x1yLO;A%o+K!2YH7IYo)2f6s{$i1wN#a zo{^%Y)mOcWVqri|(RgbZ3^g4pRU{TyNs(BV`BYQ9`Bc-yv6C-0UTW$C?^JoqY#k)A zJVt9_QeT%}?d_w960-!R5B63HH!E0q-=M*`YdTFnM#2Hj?afh@YI}1GYb8CEymvOr zYkWYmrcyboJ`%`qRCK!Jyh^pZc^+#`x<}6%Enuajb_h=*3<50(p|EEL~W${){_9}MPRy%a@yG74CvYL z{dZNW4bB%>ujFCPUX5MJt(9tnb1#FWoSF$~Y;f*2@l#$6Tgnv@Bh={f8558WxP&Lr z*zjZuIn*c{gdk5GuWVhUQV;COuipr@w3WkZxSQTnR6-0Iq zi-eLWCb3>IYTHz|ew=rdCg!nX(-ADKQjXweR!bqvk}4Lm018vyRGA>5xF@*2N_m3o zS##49JjP1N6CgNw0uF9^f_XSHm{&-jE1QuBjaw>=qX4VkgCilWdLP3>F^JiNalmhP z6+5$F(bd!&(5+$8bE~9D8y8ikTwJ3_OT-qx%-sDt?m9WL6~v|L>@Xc;vzIOBK7Rq9aw|!9S@|0Ti9hD`)6~s5Mei zCDpL<;>rmz3^0gJNsCCVVxvuG6`L#mm7^J8{V6^}4rN1vxLQK<9;z&BnxZ6vtRCc`&Rc4~CuR7gtzo z=Xi&R-x&~Pk$yJ%ZZ`P;(DvQ|RUS*@aGvK_khK89u~BV7MFo2~aKHkb2H1@i6dU$# ztQcd7qGDt1B{3SKMolAKO~0v{o}1i6O}!eU-jthW{AOqOuyYD|?=Sl0k8s?bowl>H zv$N&Vc8a*6qF_^I6pycENn}=1i@2fIi(5QNYz?BeqWwA2Gp^0?dd9?s*)8F@pMDFo z2Sx7}oKVlWp0Ea|TK!-YCvatTGiy^0RZY8?)*D zEKa5@E|4tNA}qq)`LqICe8hOskg6!1pIn_C>q8LSYcrnSx7O`!10f^as|7U2Ge+53 z`M_%x-tSf6LDCRacpv5OL~s>055`^c^6Y+r)Q&IDPPP04sP(zi)`Gq6ORWpX^W(1& zl9u-cymxEXnY2RY+UJpBkRh4#83yp_%9fEuT18&opu5HP zIb}{Lvu*(7wOqdRd6=KAYX0<5u9`o`=gRpr?JZkG`N7GyUrbg+I2BV2u_Kjd8p}^? zf;Dh)b$d&mzcKr3c30(1)Js;2MU$Cq69L3oNi(hXj7sxx_JlWNGj>5bLDwrp3qVuw zB3F6aS+>OnJ3;XI@v3Iyqk?c-o;Am|mpxCQy~C`vnWr4pTcj3y=r!6y9|h?la8%7B zHHV5KP~m&$*?I+%!*O;Ms&SnC$CsWOXWtW|mOlWtl5rNC?y32M`n*S zw<Pcl z{v8aSud&7Zz=L~%!|gZfgp%Q?*nJi|HkOBl)^5RzN^FD88h!cMquB#k?Y^2p@o_Pe z_2o++%FbkrRQNfrhB82}4v!D+&&e>W^yLZ7`$X}@>ui6p4x|}=tSp(IKc4Mm$)wy5 zo#HV`ql1trgk7?NedK0!IS+pXa%#{~0xl*1ZnPfP zDz*6bBiR?(e8Q(+*T+e*=k%59jLglpi);-6Kk=l)%{Gw&9KUP$_m5}WeE_{qEy;4Q zukvb#NHg?m_xC09&Lg0jAmLYYB7Ll6ZcSf#M~?D^CE*koQ(Y99>MCef;m>ZfHTRJb9Y)x8TQ_!@P*WN?@igp6QWpIzLLpwI z`dVll`Y>Aeq3R0KhjKfc%$;&On*_t&Wr&KWJ=XYsVEVZBNf5tq?UT^2lC{tB=d%C* zdX6iVx7};2#rN*Ewc$UU%pStJ3wCt2XN+6_+bhH^c$W*w&a`$8L|)|RCsrIWMnCU@ zLp`7y0s-)@=Xjf9BBHzmU?1R10i`U^0*h9}}H;Q%$v^3`Kpy|jB@iY5u zEBJy}a6?=K8PVU2_d}e8GQ4#1e)W^c<`g54{!kKm+>A48xb$#JwZT_!lRVJ^MMp_JF27~ zY%amWuap3ozj}>+mB#7q>LSpKe2sp2Ke1QU1G)t-2u>H6vNNKHnsggp=k@IS*>#PM z_sMYPMu>l7uc*B2uON#!t&;Ob_Apkvzm^%pKHVbFg1J?&p3o39{&j z?HEfU=zNK*^ig7eN&HI9)K^(5ffmlA>7kI_EC8v0RT3zwt^%3^6rXVvw&qIHU+|GNX0`o6Wf%%uWp0YJ& z7f3DUU!WHAFV8{qRL6MsI|0DF&VLo&8Uys$K)g_)b4K+@E#ie*FW$2~`day(>$b@( znLr`(qyduYG*W@cp+X~flUhU$wO-_yGzy~bqG$Wdq|yET(T9^8srC4&kFx7|KYuit zU%vq7m!1`JQ+NFUQ3U4Kz_YY7$`ygq69`(Kf#Al!2;opMKo-BY=4hntt9%zm}8-Dou?666-+L`|tzzcfj zH4P<|5MgyG3o(<-R|tOd{Q-Df+=sx@P)8?=AaHhQLPPvv{KJ-NULGJXwq7Afk>N`O zq46s+T$3p$HQ1yKX1~G?K)=znL9WM460md0jqfaFm#)ZTwG4t1oWQDxUpRqP8C3ZMcCf#kz<&BOdr!~_Y{xCQIRH~i zH9qp3t@akDV;74RjOoa`(9=*Cc;zX%m1JjGgHR|+8YG=}?%KsO#gB_RpBQQE54 zG>f22E)~WPl8$^3C`CLb(ti-H73z_$_Gwh`z3nNMI9PW8=03EgDA(L{u#DJ?!W|{7 zD*;Cb761-kiivRaFhwiyqY(l138KCW$4gAXIpgTN?(m~TOjx;p(pvhi=8+DMVU8Ot zeV3-JJUE5d;Wrsc721(w(PLdKctG#9MEpYUwFCsKEc~{Djfw9kK=@sqcdO?p3+lpd zQ4C&z?fm+|BljsmvT53sHVRMnB=&mi~ZH9o=o~iF@jl+KL~h5mZQoLZK@*6Vg7LkUvdVP zIushy99l{h0{*Jl7DRyUXbqsK6Sgr$8byr*$l|2F0cJADUAG~82rUt8YRiQ*mPw9R z+Bu#uP1_LZW;J#7`7#QRZZ`hC`7BDCwAUZ0vEi}y6D**Y?Js_zm+e2Kaxc4Ku=28< z9rp!wu)A(mjJVL6%J_~^@TIC(yEyJ+Q;4q6%NFSZuT&+smiXfOsVCTSO-6dzr9-5{ z+C(bQVL^rVhWkh@IxMIa4h!;A$*GPB>?u-@e(-UH_El1WXrV&;!4F6+qJ>)YgNxvA zMc(5IfkNb$6!Pn&0+B<7M$U%nVS&h@){7jSY!H1b?N3Wur?dMs&x0qLlrB!r$eREE$=0*Z#vBcMHo z(C{NLgf>?V6&a8wY&EH^h@n?d3Y&+@7@AVR7+O%k7+U6;nhOpva-8&g)_&?o_MD~t9nYSpJPXje0F8ErITM?PEop%3ci~SD?i`QQ3yAM{6Hf#s0xQW@#6y=J?aLOHybA6fi~r} zJEXRSC%p)s;C%K$KHKm=203Q2u>{@~3`kmkiXVS~!7tW-YLDI_BD`SVqnRHNrg9n{S`7M}9OGi15vg*V2@GweU zW8C`RUMX(L3tm7hjE^XEtYfj7f}AuP4wsW=5~;um2rBdh)Q!~Q1O&A>XxSr1+N6L$;APn2365#}wW)fp(oNLiZ`uUssuctW&Q;4q0nSx7hGEVp&XM|& zW#4c$RozG6h2MviGb$y&erzN2DCk$5Y#%Cs=uEW(n&V6bKYVAZ3XgBTG+e&v@CpGz z3NH`}X9FqVlMXwE%k5Q)UpsuRQC4&os0JOrv00$+!jBgiq2{vTG67yJ%fv&HR-!V} zSbkA6H8=Hpeq%N&9G#O^xY}?G86i&$eU_Kn*I-RYXz_!?$B&SymdX7cAF+-ET$n(F zMz1`6J6>>?gM7tIGzX_f02LoG1hB4y86)_quC8no*h3$z5i9trBcu<8Z)?`z`v;_s zVq*w1e!Qy(BMKDndk3cWXLAU+AMXl$CSeJ_24RZk!Xay36kt_?N;u?NK3&3d2dCz- zG6Lf_T9jKSjmjaFu) z&3WwO+ZgdluzZ>mbg!0C>qVL@Bh&TM{&Wr!mvwl<{ zCq-X?f<;vR#t3ifW8E@Gidl0cKfTOR82yE4LLJ&$8V8531Mg;0BlUQJUiI)gQO#>fU_ zA+~_)+&f_sgZC}*%Z-FxI3u3$M)$6~PNefg_7uT^-a`wjJkH}I%L_hoPB6@mM)IXq zU3Oly8SM?3{(v(5Wl*MVkwpPG-x*mp+}V)5Lx_Wx)p5xH=(k2n-<$tL+C$8euT2k6 zwXGikM=}{H#hi^LUmjBpKz3U`2F1o(Qb+O6MTZhIP%^(hQl46Tm5(fQIE=^t3ic5R z>tnr6?#Q*0QRDRiYUFvM+=5^9OCIqH{Sw^X+UjV|?i0ZHwfV0&KJazCrYn>`y0wxx z@aCT8D~Hin$6(`#`p|!k)&*YPZ}z?rQ0mLu+?l$8E!N0o{5L;e-WQq!oz^6;9`C-( zk#V$9+BUVk}npQEL5iQl)+F(`Vrz)0O?J|Tfwi#wO34rD))Qk)4#`nS8LAz|yTQQX zNptX-g=Tbtc9&+$0(s-(l3=F7TV7tC+O)1_Sb0mcfM0vS5#vJ^$0QydPbYLL*!+1# z>K-3>FPll0{vZWjei}#`B7=P?gZYv{Mi}JcPC-!i@X`m>B0BQ`L5Su#&O9fNz&d3i z;lr=T)B>8e!%3i&HW5!It`!A135?9gNnqNK4Q5&ngQ(|g#3it!1pe%f-lNS!RMc|N z?~$B#wTP%NbDh4oPLg>)!pVuC-ad`RJ6elCMwvL-T_6)DYYSxJWOaeudnCNmM&*6h zr#3YC?~m)?S*xp_bW9h4ulKS#;j6jjaT`->8LZkUZK*hq=te4dGvOQD;%wu~n^MQK zdIVgkmUNyv&Ja0DCND%Yk&OtzcLVG|+-b?&lDf%Y9SOn{;^cQKDLB18C)XTRg_rQu z7Cw-A($VPE+gvG%-Q2CIFR;M`85*p8TWWL5C_q`Wjy-`Dl4>;A{84&D8B_T2Q;rUP zo!BbO9vc}z6zK3Lx2LxBA&BDKO-P8rWWeUybB>m^2xl;_pXw3?j+20jGyfKWb?VO4 z4nA1*xO)()aoimt4N;5-v=|X6#9s|MrMJPO${0(kTFt?)2I049g$j3tanCvrHIO!6CnaulK>#XGTUWH(qu0 zWxYr1LFeb78px4Kn}|b1{IgdbKbZYS%LSIUKXqG!f>$iCqR4z!;VE!N%&`^;4ls_H zD1KoaGjVj~>#LFZa(%Vob;vw@)kw2%?8~(Ag9^0x$WJdv9(nb?%>z zA#xeD<8bN@wnJ0EfW+W@>DvysxoNcg%5~nxHr?4H1W1Gx#xY-@u1%c%+3N%d_f}pR zErXJeNd*QaP@yj(e?w|TP-48o&%Z+$xZ`+gKD(_@s|#`ep>WqG6^I)uH123pi@5*r z#r?{|fV(3BLfk2ZlJB0R0&zoy#@&b1VlV}@n3CHhXml?dY1WGh(tSl6!Jr|YS}@uh zPhI@Tk!;N1jXrjaj@~GgLF1`KL^~Kyz4=4$No)b34aV=`>F&b6y9Nb&$Y=8iLJR_i zJ(0SVttO@DGtY&jwSeSQ-lwn)QbsDlt#sk>X164BW1;r`=H5d2x$PMOv?89G{#0s0 z#66;ju0B`uL;rHL^C5}xN&p~b72hly`pRlU5x^AneOcj&CnHxH%_4 zS`~6paExYG6Uvy$mwm>jro3>gO}#>gBr83!_@u?L}| zxi||QN>E@%W9t|hysjK0gV(#q$aDr_Ri-l%IbO#8_L^gcg?&rVV5p!wRz27Dr6_~%-X^Q+BckuKHxaoa+;-eGhJ}y-0keh zJfs}l{A5DK%Utr?&h9?oT9ze2z(JPC zEf<}UK25Ydo0L3TNK=$&1C?h_CGrq=>y?LpZaQ205YzlUMu-S;EYKzV)Vb8QKJdoR zIZb)&`BWQxygR>&GnKtgnrYYe3Njd3V@nlv@|R~cs@k0Ahs1`P?}JpcTxgezlsjM_@m;0*Y|vE3g7=P@hkGwYn3c?waHD z002^ISVWRiR1Sdg;;&OWQ)yAlMiR>Evj ziu#_+lj}I+e4w=oRt7+qg*iL;00)y_`Kt+9{ zSL2xV(*z3FDCK@oxHNm0K;aVSZRjwOFFsEyusKxdCC(L6 zi_53Cg%P+-F9*0Z3z?wp2XR-KAaPqs1>%MZjk_tS#pM&!;__*Spn=OLYY=r8Z6A;O zcd$#eG|?$Omh)+%vjcn~CcK4nV)S;wFkL<^rxJ{Z6O(&>>ph+25ZbtW+I!#hn^->S z{;S1Y1T`+CCbn{}W5Y>l#frcj2cGRy_+rEaQmg09F%w9jGIN4l67&|JzALF=qKK}f zhVw(MAt0kPMc5S`07!WiD=D7;WbG>DBicAWH`sc@6FOO3PH|F-USU1|BiZ?EAT)+- zhXSC>r?qo7@I~&&S~ck=DQmb^c`Gb!wt0GjT&rkFRIpFMh1SbMIyzy&@-|^W3-KW- z6+&15jIXPk_Pr0hA7AQX8YP5$dAc}Hm{$V$iV741R~42bJy>v6ahoW>RmJx46{`v} zwn%Q2#uIRi_M(f3QM4?Qa|AI8xvZ#?%lHkB~MR<{1SKL-4*A>?%$aMvg&1YTF zvQgUSCMzIlaB9|T6YU8BbcyP^Agj#u-&9o;5W;P8*0P?REm&UC^9{{)|AE_$LiVC+W094-wge4kurp(S}DEC7G*TA!cEb>7a} zk%rpIwV6ol*)|cKTokcqktKaN6Xib9f_7>1SQ){H9f0EOCZ&RoQO5V>Luhrp`yv)0JR430D%9Nsy$*4iF;&3y zAQCHjlP1c&{;52CFoa~oi)4@+z}FDaOhu6U9^n8p3>sX8gJ&kHV-x?Gh*2*4ku*Wu zyh{81&mgubV%@q$0hqtzH-&2}apD(7x#K2P66GEl1@Uaaro)lZ&O@x2r~sqfg}T5?wB&)Cj&ig3 zv@y=zjBDg_zhM*V6~BsRuAd}BTMSx{`9Ye8C&|F_SyF+4B~<9Z@^w;+LF-|DW;_I~ zfE%xB1d*<2-6VM^Z0;m)QvUh`XD8!3-l51jHF}-ENTbR-2?;zC_7f?a6B5Xnl`oy=Y#ym; zhsxO#h;V#!E`SZV+naH)cC6MkTV%kh0D4 zr#6jJTO5R%kS!QB{?t5(Gy+6JMV3ioTm6Y`ro`_3eyU82}efF8`vvdBmKBcrS2BB41pYfxMosE42!?OXmP0`~3{dYVV z_!4JlA4rVl1MDEc;-^0C9A~on6yvkbC(PzkWH6pcDsU2OI)zw!yD2ijqSlVb7UL00 z2IFS^DLA{tYG%}}3c?Ho-}sJgn^9@w4A!4e6$71En2L_`rpQ-YSE!RoKB&~HnteCXXq0cH(D*C_zU^29)@EF=_8tP%a zMW8kj+S}GTLo94R!Gv@4xoK(b*b!2SAC>blCN@t^k?H^ENmJ~z z=V+h35v0#BDAsJoOAobwicJ4g2DJh%5GrVd0FD7Z1=sTY=m&0~JS{2_C1k1;C3LE` zbQGl;M0GuTc9WU($f<$mSE(o%-v{TdC845peU>{@0(on@)!ECEHWjYm%}&c;>7<#C z?rn<0YN+hNzkAnZUP~C{;2Z++eHd6#Qpps z=S_vURCTr4c7h(m+&U#`Q3g9giZRSREDC6tOB-UCdu(mmQu8Sg|NU%Nv<9yx9XSP; zVeY!Lfd+e((7{ck^9A;+>ex;IsN~IT*~IO^h(GzoGzt{o~{QAN>_h6k*;|q>1KV2PZF*Qq(?x$>@y2jlDs9VKll&GKOD9}&AZHTvZ0=n!;F}Qjd@X8~M zF^*S|G>kIs{m{4~G<$+bfT5WNS6R+S%kw`Hq1gvBWN7yEr#duyk4S1<2DGlVuqX376aWf2ulLD7F>hRoVxn$ei4jZOz;HAt!GKhu~ggR%h1f6kCWnLsMy z)&PKi%#cCZ%l!Cf5R^SC;mAy~p8XN@ja+c%&i-kJTwy$C%6| zeql`Jni&w2mBW24c*r3j#aQox^B5~6;$w<2Ul(`@mK?jecV|&f+{N~jQnZJ>mycHEAAbXf!;X+D^iTWwly9BQe42pOdHAJo|8}V5)k*?C`BGZ7 zn)@_Ke2=RQzwuJqKiM0)SUw%~q9{P&s><2sRp@bXgJtj~=Op$o0**O}0Pug#lvXU7 z2`df&cnMSt=lbhYhJYmQgbHAO`u@8b@Tni|s#>0Q*}2?c*9lG3~bw2SIh&QNi#M~3D zZA-mQLu^XkXiNUpxt*OQ_;4wq+o?PKv>mPurhSn1kikAD4RMA&m(VT6{P!$4E&(5v zzeH;F1pCb_9Rrv@&5{%B4q?J-fgnC$QMX95pdJMHoWFkE8Sg_9_1)cYbzy9_pRs?= zAN$iSdKBfE;}3HzCo1@YtJe{oswyx9o7u3e({tr}~%kegKhqvvJ;^N6_KCkKeKhfSxs*O#FvP8|*XOUpzrdapFHTTkbCg zAUhy9*87X5Kn|`mA^;F#axWl$P-qI=M`F31@r$Fzv?U{b!Sk3a*E(D~ zS?{#0CPk0+KSC0W1AY*{Fb?JHK!`5z61@fY ztux_3s;h)G(a2>i5I09=V;b?(aV{%A_E@Hq7u9u%LzsAat+T8*8_ki)l_1;|HJl^k z1j`)nb|Kt}j^WQmxT<;cDnsGGqiaxfLqVPf2~`O{7$mSOX_>5$l%k7Sd?hW(GG$H` ze)LLO3pR~ZYacUd4)HPb=SUwjRDdcU^GyBB=4F3$tdTr+!lbctI?gF*+ip~0`*sB# zIv0#895bdv!Prq9yL9c`VN{n6ol=s=c24dzs`IFhoja!h@7L;c3>`p;wfXTUGpm_} zKtX&)j`E8Bw?vSnG8Pba;ndUOQ1Wka=!tC?1vu3=*TKMm`0Hrb3RZ6}w5AEly1Kwiv}DiC1;pvGuJ>3Q zjaS-t%egWZZa!CTweS2rEsKBFSPy_68UXjpgK$>VY_1#twdZ;Vz~KZ}Yhx_`IKeeM zx|yI!4I+#%fkvMempP10C8aPSd-&c|dh5f^S7oqlp2J1`^`q5WRw^#I=*0O)c+yq?As+R0|RrsXZb|-@$6@s8A#oOxnP>r|M zN0DmGb&i-vI%yK{1Rpo6<=aVkU0w699^n-fhlkl)`cTAl=Us$G1#{iP?X7AN=Ah5; z!unDvi| z^5S{`WN+24qC0&1RrM3}tGGR3{K-#tbvaD1wcv372G;=#z*@d`oMW|nti)Y-eWCI= zo~Y|WV(EazFX@2!^zN=8kH>`CTu%pmKk(4aIaZt)r=_~SWcBaV)`qc6q%QEXUUG}5 zHQ-^5>~nc+wszI6?v%d#cKj>z8bLTHYJR73*LQl|^_mPqs?j20(Aj);Kd{Te`?%+G+L#lp|jd^}}w>E5sAGig;_}+MXtUu<) zymYC(1G_sIe4nwi5(DASB-lH#GCz2DE8=pdD*(HjJ>Un3jHEQN=U0OGsbKJVP3_Hn z;4vTy6QER~14!GYO+4!DHlk*)t*D;zSU(Xh(9Ay-ztGG-y%Xb%pkLSuyHma`@V3*n zCotqFPj%Jem-AdT`CBg6c=i)v2d(y+F7R@4v!51$F=FSt6YWp1n)5*bHML-b9Wr0; zcQzyyc#ID!^jk%Vq!xBPCmHkQre_uS>+B_MJqX`Lmif}wzw_EUe6S>vU&?bu84hmr zaSe#J2+Xv5zSrW*?*T@oWcJ{;zOEYlav#?i)|aq?fy%nD-hVex@#-a#=k|kWC6}Pa zXk|`6*IHIUO2O+l<&)dmTN@L3et%aIn@lRv=TDeVrm(s55)m51?f$dd=VjD`ABY19!yz{(3|bZcQS5Sb^7GJbAPkYVMoQM{LX*NSkn94JhPP5R45kQG6mc{8kiTY-pK}vElJ{>93g8 z7I0%oRx=i|0BY3`z%8OG3rLqmERg95+GXpzxVxCQE#Oz*&x~fbk>;3Li0hc%lqHf< zbi4q*p{u)v4>mhurjbr1jN207Jz+fq`Ba;{n+ zgB1!cx-Ed0<)Bz``W>?R<6S-KYWq~YPFsK>2%9V@NFg>Q{Lv9Fd>XKT587xjP#1es zdpp`ju-6E0zUrte2ieODc)_f!LiPy(#DG~dqaOVENHO~|(v8;j3e#YM0Z)tj_S3OU z2%Lx`^ZIe+4?Wf@3qeSnQL2hxIHOcuSjo!uok_vcH&0D=&1JEoHC?$j)CFFmH=DjG zc4VdUkxqLluQRtI+A&i2*+s4tJSc9omcQ}Y;~)$aB`uV*K-5BS#4~a_gf9d5>gkY` zNfIp68K9n)0cU{n)-xbJVk1Z~x+={4j$bG=Pn}WVU)8LkrURod-~a1M6M8Rsir}t z{L_B+0hGMv_%tC^!7=1=G4VuuL&RAz0mz5y<|?;*cz}H#JEx1~?v`$-P6d4m13~O= zJv-1oon6!5nzLVZA=fj=wS_X7s}ZWH?|Y#g_)vp*Ls%deiChh&sD3Pfdeoy_gSK!M z0a)Jp4ttiBSf+P$DdYB76BhwE4(S%+7Y^wbiz*q?cP(-42#gGii`9m zuG4gZmvYIrn_D=c1%I~GHP0FZc~RaX9J5AOeqy_82syE4qyV$1J4FFn3mh_8>AG${ zwMd2=&k#rqH=ZD3nJ+Jr;Rclo!;ME5$#COQ(p-ldpOR9Xh5;PI4GNCo#ccn6~EBxt&0P#e(74* zji9UlTk-XP;}h*+{E4&#Fo0NqDemPXET;nWkvPs!@e z29OG|)G~VVge@+&X$T zdkGLO^L8t=$4LdEg$lf_g`Yuwj?^OV-4(b~cEg)}pK#Y5>_Y;CxZhQ{zakZg8!8a@ z@%J1pLP;f}eiu<2cJW6(Fc74hiqaO#(4qNaZ|G2ShpU+xxrDdh;c`c(39Qubv>;?K zxxId2yAWQ~uG>Q_W{EZn5%onU`ZsP!An@4hp1Jnf25Uu%F{jv`6o}Dh0SNxeosfQ{ zpkh{x)ihLQo6vxOKIO9}k>v~L+b0+-mmn4F)zwXvcXBP^;az%n=6e(Ch4LHwTp{&* zkSX^A&C21%iea*G1S7hR&llUfv8kj~FmH_G=k~iY0-=xJZSTUC`azrHmdJ!s0CG$y zZSn&Lqo`fc>NmHmyJS-Wz_Wg8v7L%L%>ngZ%Uvun~_qqTL9w=*4op3 z;L*f8`+=G<#WL=rnElkEjs`R=mYWTNA(52U;wet60xDRvmG4;(c@#F1Q1X*ZU8x$X zBpbWIzM4%V;3!$lM#%cjBc(zzbDCn8g8Q+n&PGmF>?-nJcF%0GPdC_JLP-Yd zul1%EB~qAyieupW+=-D| zPs$8{6#ugf_8llq5JEjo6#&1p{OU8Vh6a0|um~zrEBAkqQtW&H<9XZcz5L-D^S#k? zTZj6Ao9`=)QtW;jjggl4j?(DP0F5faK%@AklUeM0R>HW-&z^!n9nYZ#hoOZ2ZEtXa~D4IxCnk~fy2;aTSzKCV~pWvxWOg8}|-&(SCUJ7rM?X_na&2$Sg3n{FZiGL8e1x8#OKlie$ zFT2~1GlD}MH>FMR9!B21_P5QAOXWQbEy(RsO%xnRs+2gHOTA%}nvXr!LxKg2`yLd( zFz$O0v{%{ZOcEE%l(_pf*UF%A;QCvzn7Mkty%RtDx>&9d4PjFKlrHefQgVw(hVbk{=8_u*OZ-m{jf0Ig#1wRxP;5Oe~Dr3Rp^_%r(#$DQ+Mf?P3>;OYL zU;mCyyIjY1#=GKAcOF)6QvE26+ACSnJJ8YMvno$5^+rv5|K*A?+Vb?TT&dCTh!!+x zdRC*5i?wM-?DJU{!Vbnu&-l0NNFXp@-tb*lHp?WXqFt{ zBo&AkD)hSw<}z(7h#YFY$i+dC%9Zqly)ke5gR6N+TOcsLU(t)4+J^2cb<}tyVFR}x z<0o`$hwH+6q{_D+p0MXcbr1}qgXk!Jp@ZniCx7i~UQ>Tpq~l$DdXguYq>9%UFS~l)XQEncS4U1HNNZ)+>sm&hPYtGG_C$7hIj#N>Yw0pS_Hz zd<&^Xl|!viIeg^i>Lpj-sGyATGhe!#|Cg#&eBX-@@KtpbsnS9V+)eqZaYj;g+j+s}FJsSEyof$d#Xa2Xf`w5vu(uAjV_fwfFX+y7YIK!xFN*3ZIsf*qDVb z2QEh()omC=d_l#9n+ zhpY~zgu1*@oE^eXerS)ck_V)C{&9O_*4LkC4kbEF5@kd{{{5e>#=+(5{IT5~NcH%~ z_BNJTAmsUv?Jd|Ge|j@0z2aa(@{mvL&4WqV+HfEBp(hqE(E;k9F$l&q^F9SWcM?YY zVj8tdB<)mQhv)vw-qSe3i!JVK_K+Wfx|*gnd zb+g8n+q|ziZx{>jKfFqa;gVVtOOyfsi_3L}fj?K>{S`Y$+Ccv|<>~zzROjDaus1g@ zmep{#;-$>(eH+*OmUhF>%W*+li*!2-qO>pV%}K|r2O@w9pZBHR?nAC(NlTQX;6Gh1 z7i4M7-IqnJ(8Eh~0@Gq8@Ex_?UG$-Q(N660Xb6SyV}87m+gkqg*LHYvs69c5HXnbf zR}Jo{<*r%wt-XOIbww2({jEKbKO3e+@4kWzX~zn=mM5a~wsqXM6T#Ip&OnMU`nTQT zLo=A*3cl?MDR}-x`!qJ5@F@f*dQxk~F~Ep;JVG?{m0RIca({ct-pgPs2tGgiXe#aF zE=B(3%P`Gz0`8~xW_&?Cs&~=Om%c)%=+C=iw;Jp*f)Mo{J9=mh-sP%2l7Dp7-oQA? zKexKu@i!Z2wLeSM{(2C#*QxJrOS)Ux`C~i}%6$k1Q@Vmap`=dw!Tu<_NSO3fx>_}V zqm(Y1iOi8UHihrw-*o$NX@i;su*4>}E{D=@7ttC6O2_ze$%I&|}+k~2T ztd!XXt(LZd@H*Q-7NHeUf?UUXtkVP!7$Hm-zc50W4kAIeAxcLGc-s}X;GW^9Te^P= z++e-l$~}v%CIX3|%d?U**=Y2ZV&BRDOV)hR*FvyTKSDWS#|i1 z-cyfDpcJx+(ljaeY5h4%+CiBvPnWtF2Rob4x zNL^$$fyT|*ZmZQQLbGG>^c@&JuN{@n-_m4_%3VCUQMtF^gW}*OlM_mHgSstG1hD+g35J=yd-h3X^ zQp4Snx6RO=_Y~F0TT&ynh(^?0Pw1%w6;G6%k#p_knDlup znt=OJR^Scpk(5O<;r0XYomeH)+YhbcXIWOZxif%8g=rfH7OnE|nw!w|V^ghFv+t2! ze>j2k<52C54N)9I3-tP$LxpM^Q7@*LiEZ&vhdb9whO*ZuDtF+CS|J!fZ@g0cLT?P- z#NiHd>c7b8UK{9#Pc4RnE)EyObbE;~=!|#j0x#i`jkmxVA8`XCi)UM)T6j{?8)oay&uHL1%)Gn857f@`jp`^f<$kJlMe zgP$7!^G&za{JVRyZf7=sl3ggt%pfGg*JL#dO46|=E6ztsa7{VU0nAbL;Pf({uz=Ic z7*T-J%R~3*>1Ek!IlU|=;Hadfl;ib5IL7H^(P}xpEF#VI^m0Eb#l21d$Fn~aT+c6e z5^$Vf=B$?U%NS@T4*!f=E$0^^ES+EY`p)Uku}=vWoL;o9l+*c$pD1w0@iQxJEgtWh z4xe)Vku=fUkbjU;oE(4TF$Hi=nnL3|Auf4G1W>susLW&a)@TDo&ERX?aikQtI01|= zwZZXhKX|nzn&Jm<)>|Vtxhc4?3}Qn{+Q>C>61WPl@rg+wfYHmV@i?=2aW#*xo}F!e zBmn~@dY_*d15xQj!VCI;jZtOT#;uY5e<6WH|F0p{y9IYD=AZ@oe+{5ey-zv;{Xgk@ zel0vZ*GgQG*9|Lg=CR%{7(oAjK>R}ge*j1Yy?g%91oxW22>?zy-oZ{1LD2Us~@Q@^uD#^7(^UwM5c2=Ssf*GT{U_!_VO4w>SPGk)fYQ`{NR zZwhv)|9(RAFZap5mQ*5LSrTckU0HupimnX6(Uno~3Rh;{ScAtiV{aGDsN(<7DyGRd zb5;poYH??=IfM=l8I3_ji!(}e_KnBPb%$7ea4H{vdx=cF;T4Rcxv*F-C75y8YRoFg zD=CrD<(>0jlyhB-yCXe-3feHP`Z{ipFkKaH` zLH)0MTm=Gwa) zBcMgSlJ+4#o$iaxjb65(hJRZ2B>Fi6F)yu31x)`8Qy0?`36`ug~ZXha4^I^q>e1 ze`Bq5NUeKz&t{PX+?Q{KJ$#+?M>m9adejY|{s-76+#I+3y0!|pcbp}2oW?hmK!3TG zc&}cBwjZnN15fGer1u&?Abq)1*4I~ZX+i^xcr=>|)0aez81WG8^W^Ce@sM%jbslOE zdaR2Dee_sM#4q$%OMp~Rk2R{yy(Q3NrE&K(ww1_%5zl5_;3Zm8b_+b#$*r*2bxb3d z9_uh@Nvw9CB^BtgphB;9UnjM=+J#zN?H+``-qmgp#)}TDlP+uhIvD4iYzS}Ww zr`r{MK%k|LY6GEzj_S{y?vL3|q!gp2+?U{dWv$(ixw^qqce^_DFrd)?KHpLph8cajg2Vto)DBY2|1{fCHwE5|m3Yg{?D z5(T(&Jg`nbVB%P>9x!nccznPlYrU2duFmzj&kfJFYat;GclzEsNoG$3Q}3792@+iU z+1AUoU#su1%6^wPJc7Cl%LJc>Bw?PMYtoU zKOCc7`>;EfrIPaL3$g}VgYZ~nE0wOMS*h36?0m%C#F)%aJ>qVhG6hh~F6vqxqNFJ` z;eR;FYyvMGqPG)5;D2H{o@_hya~eY>OEr15qA0fD>FuL$w=Nb<<$NH1$@xI`2RQ)r zRU@9VxUa`r+NeV773dymBm`)|;}66%v6fVzTU&u{Z2-ChR&iKv9H09*tUC?}OsXfv zQOSet%iTt;1ERT?aen6QhUx4fUBpq%2YA7A?jAgTcEeE5y}HuN+0E{J#V_>q=AP-E z5dPVd?mO8FngRzm){;*%EZyn_pq2UA3WZuRg-YCWSRYc4Xgvz;NK%1lp#sq^dmcER zOllD=)M~U=zT^dWFSddJA?~{r?#-kEaYF^p`e$BrH)HpbTEq>t6!+UNxd*VP2@v8g zSGfN{DiAkR0N+-g@`}3&`;gQkZm6ZW+q?=}K3544;{HzI{*zQ7Zm2+=#MiPUvYH!x zd(nhiio5hRh|Zf4AjF-pQFdc{Qh~Uk0&%Am6veX)QY-j268N>Zw1xcZ4fjMgguo!` zfeQ6_Qh}(U0+)qzNCjdYNU+x91KtKjuO~2wb&bNhi&O}##u~o&3~bvUCgq3}QYD1d zXU@9w*oy=Pk)BdW-ys#qDpVk==ST%&J>|s;BSl`?3py^r#sAl{v1-w~FaUYY`f+iL zfQh%P8k@V&a}Vx6zDrT2Sk4Mixv;Ih34V!xuGn1U@Ky!5b8r{F?tG6ZP#zJ($yOhL zRn-;9yneD%R%0I4ZC-{Mvx#5%z}nOczCOM z9eB=1?!SBG*y|r_n{_wI%f{UW6LewK5eTJz^T(aN9=6MBaMk(Oix~)EO ze`l~hgfK3n_x!q|4ZDMs;xf7qFrLz@Q6PBKXW(=v1_AH>Oy9Ub@c(=UhP%iQ+~`xj z?sNBkUuH1I&J&QRC$)7%rGOaQ!S}vfy&c;@5MrRcRTN+d@O&vh(XZEde&vF@fIUv& zGV12$m=AB_8|vmZVh@uF3`)bUbZKsRZ4(6M6T;%z8>AX-=2c=d9|X0Tj2gXS>T34Y z1IIuw;i|i#54{avfmKolKynAqA8S-KjtMed_^JMuQ1i$pp7CRD8@}pm@D-NL+Qd`olSD19fgnmk38ExE1r?I~5k!)xi|%nO zk8p&NxHro#agz!yNugJgv7{O$8ATA@!PjIJ-z#K@q-IB799Mvd-6D z6BAWULeI(*=J!e9XEs^du*dKxm)Mn1@so?E?{rBRtm&%}_n zn4W1+Mx5vEW%$0V&u~4zB9~fe<8A6Qsz(8p*;MQjRPPt>)>) z_R-QEy%WtXE%?c|c1Lfn5^kAVm-&=d@VH9zc>2|x4C9cTaL%1- z&kUFw;n0Ht)?LHXg9bw7Q)+n58SD$nT=UGv{P?{&ZP+DJDzsKhfXyCN)D&_ICA)d) zsNa(Ku~1K4o>S8^*#`%vm-IZ7B)#WbX*yyLJeJq~xIr)QpPuF{jZ}%q zjCB_U7@6hq^PN30{A8zERvy#96K2Wb@L8;H1~fF`Z+I6=11vxfH;`b#S*9N+BQKx- z4`E9O$!Z?w8Kr&GBa5^Us>aP_nzTC?)?zDL(x7T|08kgg2)rW-N2f`F@F#dnGKwff zE1n;Y^z@0^BpP5EX|wo+X{60OJjz4wNQP~aX`ct9Ja-57{Ws6K!+6V7(AZ(n)QG7W zP1sSwhUogJL%M))V6W$iG55(D})g=jTcFQHVvW?(lNuLJ$vm7QY+@4Tq!|^4@EIWd3q$B3wfmwb>u(5` zNEI5wx1xX=Lfp@xa7eVXS%d29>w*6J5Qjo?37c zTO2SDg2+w7cX4?|BKu6q?e#!gP&L0QTlhApEhwO`h(u@$7f3;cEz~1Ap)-llwl_<>d+ zexMa>B)HHD))On(S&0>pMYdaV3umypdU^zwuM*{5`0)ZG)SSC5m`_j$W)VKn4yKa= zw1aaWj%1O#P%EGBY!5EsZBd0?e@6Vmu0K;r*N@{nI(SwD_W$^fo`fpjKyyCwRmjr+ zTT_GQ5S)dvU+Dr(zQQ4FD!3YHp7Zbel1`pz(e)2@@-$5O0}%X0*XKxOUeILxyS~PD zkWCF*?D}e=KzDsFOM~sIuf-4SYw-iu@(H9d`v2JN+W(uawg(P*zr}oC$zP-G0q$Sb z)Y~rIf3@wwx>^BQ2pibdw~+$u>Z=_SS&UXf5MA?v7Dhuo@S{cu6xjPC#V_prk-VU1 z(7Gslc642&PEV6it|SOY}~@wbw#qzbKMizv`mLe~`!crS|faw3ojQ7zRsT9}Kh@RdYaD%$A@QqkuLNM$lr`lY)v#B8q54cMku( z2P`Zuiw0;P--};pAKzDIAHVhVlm*&H%{Sc*#6Z zHg(nbXtF6^7vqz~BH09w>n1xrjTmV{a!s=Yhc)67*c{SSZAhVXL=*TnNo*rh?9l^Yqf=M7epiPp#mrpRK!&9+wq^p8i1W&l9 zNtX2yfeWqkQSl3{^U)o_!v-J;;e2W?gtM>n;#^2Byh#`ozANe~&$Zw&eIbs$4qY#t6TATC?Ca^q%$)$L=0TBuf}?QIW%8^l>CZyR#P6~{F9z*T z1@jHz2K)0%Qc&Sz;)pz2i4`L}U-oCR;12sUMf}44Oxamkf8I49SRP~jxtuUQd?55^ zHlH%k(~LQZ$T$~e>VhDwjKxSaW2avvI(3kzk?=MpgFFpVh69Gb=)$p5dp$KB(S^yp z+F;LiR!B-gJvk&DG+wqVAP~44i8-%%q!fF7wkV*z4k^(%+3Txzs$PftqC-5%Y%OVv zsoK>$10s#Qm0d_P(ZwfoIfNT|gSu9O;=-N!9w1 zo`c+4KQ4-qrt+M@8`30V{KtCHFMC#D3t8ZyO-c5)saO7kJ#P z`mPGOg!`lRFhw@5LLflfU3lKro|Pzf_$W_~HCDi*a^u7=RBqfZ97W_KL#R(_KAYr= ziZ@ObM)90_4mg2m^Hkx-hI?x8?V~-}m8-rJZ(ZnVY;@vzh2S{55I)gycF+Yx`@a=} z_Jda~8sj-EwNL7$_S^2l0U4m)Zb>!6EXcwlRb~JH%XPB^5@9LuMvm}<;M|}TFi>MWES5r-qXwarD%%X z@Rj(5-SCy{2J+Ge83p{rR8J4frCsnOU1n@EcA1bCU+^>ky-WDa4F0bUH-BV@M#*K* z^(yoP@opu@Z|?Xk9MT!fuXcrJ!4J*wY_pgVyLtGoo@2$|v!{BE;%#fysm-S??OK(` zot{^d@0sgq#oJu6B=X|9p3zmh?1osqbZTL9)(w7nLk0{QJMn9GdGlSpcJqQUz1!6k zR-*Dx?tcW%e_mz_G^8DTVN}$&%@EWK6QZcD4ADp}^K$p#i1k_KEiCc$zZvbM@|9~nEm$g{i`psh z*G@OWeP`g-$ZX5kt%Hs3*|h1c(9;ZGN_3RA9TpqPFPD1$U1cXwIQJJyHGvX#xW+~ePPdz#sHD>TbTZr&yPl*ER&)|?`MVFWE;Tu}?Zo}is=jE}t zNK-r%kw2-LlYKx+MX+xHFuwPKCBX+C`se1y?(4psQ6=wvpl59!`xTtR-!rvaEuLKL zvGVm>J%_4P-wQh5-6SWO)qr2#v4J|T%2V$1PAqlz2ANnAUX>FIJe0lF6UG<)Rz19| zM(oWva*MGSlDwn4He~Rlf*Um6W}<-h!=FUj-&H?cjSsKNPZd`y;GgXAh*u47iBIe# z6w$*3B2=Zx7h8w&w|9F!H}d(hJ)R^sim;3d96=N~Nh&ak&deat!y&LI-;sx}fvK_f zK2O3;*swWdFJHA5rjQ|o4^-V^f7K0=0`=c3thY5kS2w!10r#SWkWfa1e0;yBx>4m3 zXwPFFsMd--Mo^=OCy0nArHDSREct+E*iFb}9OXR^db+ctgf5D7)?cItCHn_aq&ECa zv+9%BSESX_`*NJ@GAY1?_g8y)$_dyrrI5E|C|;;whiJ3B_^>C|Fk|=ey+=HqS^Pe2 z;;77Mp7Er2z_r{LI4_(%>KS_z$~5cm<5wPng-U%w7`15=1$1mh2~K*L5&NWj8-68c z4$C90gnKKynqy;wNg*b%@_6zIPh%h8TcS`;1xHe$<<}ne(D_MFKPny|MhI*VIO&_a@%PSEapwfP!UkMWUqNI-eHWX*g7kkDoEm5eJ=dM zLsvXub2Zpbc;3?_x{0Wz7E+sVh#5;!{0#ktW-p6A&i0*1$e@4r``&Ay*h=(E|+-mCU=Pm*ffpL_aV zvY-18=uB~hLukxa=33U910G`Asz~*)bJ3jUqL$fQD7C~=DT+juDk@r9ZSAGjHc_ose_G#}GxxnY z_r0gSkADB$yqr1PoH=u5=G?h6?zN3*rG^4PTdC*bpjoU7K@*7-){y`}nP@)0fi=to z#WoAgYEaA4|6O=1e=H!84J1U^W_{l!Z8q{<`Ff351ir93v^1z{Rb><7%WWbazECg! zPEaS4Y=~>}I~hIgU0LylFsl>Co4tqzXwD1mdN8Ao3nX%jW)$f_?yw_zFMObz8MR2% z025M+#V<@qEq?cQFE=hud8jfk`3f3^ghUzkR(zc~nte>{A##728x_DU`ag(xokjkF z@xKq0DZ@`qeJGqyIRfD)_|0Bn;#W6zP)U_{)$HR5-(+@W#|a$25Zw2!jCFh9FT^@t zc&u*aNQLB9*|i(WjaU~W!yKuY40CJW#V{A8!kpzjFervO_8vceG&3!3w_r^}+d3sn zq#;uv^OZS@g$qKr3yWpvy@fVqt@13Cu*L%sXC9h1Ok>pv7{6FZ8EF>#q zJ)IP&?!OS!!tT#WF&gF-Vwk0V4I_GgxYFJ@6$|8HM5OXCB6cmJUK0u5s>I=#`l6}WPK0G`syR_ zuMq~RGhi58@>mkPO~1w{nD#zc1*2fP_=Qn0{r%fTL3s1ml80Q$jPsiyzsGBfA+gt) zulfbvavi&pxry}``WUeQBkF?+;0{msdQ-AnVK0ci7AXpflw;Fs8kOJfj1<3aY zQhY>$Tj+XIUyJ%D6lIG7Qe773|@Bo_q18>-~K)AJOA9K zkGy@)i=NJW%{(}SqoHOElvg9acMIkpPmtBlEW%f)6A=BUtFPMF!umNdfYO0_1y|6d+$HaP!48 z@ckIW^$g(rkvX^ALd|`}O4$*a3G(eL!I%C!ewp_ir|fdK|AsE-_@4V2p#^o|M~GVJ zz_`ocg%>l&vC4v4O?0er6TOKe35N1t!qVNUq9Pc|8wv{a-xTo+{WoR#?frM+GU>l7 zPEM^R_ZbuiTZjA3Z*!RSt@7QJIxsrn0W=N;!UJgZZp-=Uk9+pW?4%0ZO3vGGZ+;JF z4^`!bHLXqfxRF6{bD)xd8%v`6h;$8K&X>X|G90d84CAHihWBPUgbW?%aWGG6m&m*y zYbWvX;Z~6_MvntH`p;wV*T@7!`W3+^CR*e5wB_g>aCzhCFl%jXC7&N=wZ#n=(x^Xl zAmVY(i*F4!5U6@0SR^ch*f`V8+k&F}N4-u(#;9I8zHDWypOOc`AL#{;!N1CvW zDeTvLZdGe88{|z8QaL-4!%9hkV}6(6`jrnV$hS?IC)77PkTzx<^xy`KlrSxYpbH0p=&4sBe9Xr4lq;@HHR+wcw*r znG%>aq#VzGCaA8~iEGKweYz03tB=`6z<20NJ9ca(_iZ~?$b98~QA?Q?;0+pD>s3{i zG4ho}5QG8Sb3qA=fcVme*2lEbQsNjQ5z}oWsmMuEWO*VI(rxk22X&46H=+E4RBKz4 zNHDsQY)e`plWkR2$Yfj83OrAe(FOo)BhN-W)ZL#9m(Pq^B~-_*yjuLiuDp81?Yc7T zy6ea{Hi0V}eDZA3O|8?|Zej?W=k8Phx9EBA-dk73RUu5W%ZN9!W%&5q;W50MW}U*0 zD_L@$@EsUlEdMT(0x_}BzT@dF;O*EA0>_Cd5QvF|c7&(5w2okvR)R$g$Hj?91$d1q z7$%ScoT)$oPIZ$>0dj-_oT?mIA+LM#V-MG1kSdaRueGtp%Ly*Qk`vr*D=;vTcNGr^ zNw`282*2dJ3bn8Bu&5agQaeahak7htF6QqY%_3EayM=^CIAVOq40*A#@MSs&2Yvw}NKCOoMCZl&g}zc;tR$<&13 z%Jk%yPnQWVDCl4f*VtkuN8S?lCbXBxEAW*vukb>KbsQ@oSi%pq4ZO6wH5#(ALDkr2 zq);5R358cXS(~x130xcisc!(o!EBbF8g0#F=SV3G@y~^cjR*6}PI#i#u(8>X!ngll z^Tc+x2n{w!31&A4I-VwZT4>OWmHAK^4uu=|kpzyyPp^cNq3t!`rn@rXtOh9s;eGPD zTbtZLf#!sSD$t3*sRCI9Zc-q3Kzt>ZO-ez5k-TtWeBy01&_Q*W(ZumnGXm?mjXRAn zK=xoxAckl#{9_abadMAf~dLQaz?W()2Je$xWXDC2l zm`@5YO1mi*kpee`a)wo;R5*jSg)i-I?db^#0Rv#H`HUdp&``9BU+r#6HoY_lwyB?QapzF0x3YzP@r7lFH-t1uApBx zxK&u=%EzvBPz)`%LAc+*9cqmZ5(1MiS!52I#^dvNHj_3^iNP$U*QKZ04p}b)- zDZQgNfc745(A_4UPdK-EdZVKfOTSzJTgCG+-Qec$8Jf@#niz{y> zw_dT%VBZm9tWNIGX~F!!W7gKU8~2W^5mS*4JbBo(a#6QojjPs~E8Y36vXiYfwHv&_ zWNVMOJTYaUQ@~kd4uSbCu?dgwpNe@k+* z!JORZ%pgQ>JcbreE^Lgyk4fN3Ewfz+S}3|N*sTbNoDDT z29K{#&|B4qqt0i|wHl`i_E^i;J=UXf`5QtN&->xrKg-mQs4j@<3Rnm%{Ig7LlR#Wq z4_hl&*29TBv9i{(iKy{wxjo7HK)4^ia%D~HjVo&(OmBnnFaMeL5PP0T74KQ9Dmo*V zMd)A=TU2Iba>4$FWvp;x03k)AE`d5G{!^wsgCCyBIJ(6q0`Qij|gZp?N0 z9b-(GUfP7nEl7v&tWAS5IVl>8$X7N%8KL=n+%Ve{ER+;@$uKT%3E}zg-J!-6gL9f` ztQBE}W^I-qz?ZU|=?s2&TEI()aq?>;6cX*m87Aml#0Q&jqGW{3X;)DJR~e9MW3B7 zGBc@sd{|CG)C`3}ePjW%jjW27O=HGLRmeDa6-4pW6Ez~>{JpYU3)Vht>!q>fij~|h zhTBHg<;!g&8%QZ;Yu2I~MuKQtzT6aGjtgSn25qwkCWVEth{!LyXJUbmiL_pMWog8M^m=F9yd zHwgnwk}YW&Q(KQ%$F&GsB8wtqXn;!VNQNu{HjRrNeZ&AfA<|ZjRLVH36r|yS)IQSE z#O}Nn>*VgdRzw=^&TB@cWvr9C^Qbi3ou?YwBrSp$AC3;vL3HU9TWfv5I&QCFtHB0& z3+YFNjPfI7)?#a--zqJwX{*Y7t0ayg&0S|44KdqW+zcvio*!{|HiW-AWv_-5I2DJf z&cbQ7P;Y2GZ$LCp*ln$8f@0^zqchhK6-DPYp`nbKZ%>OiK{31*-jVLqM}c0tiM(X7 zV`mUXCH;E7JS98stulYHbA%nb=;?LRMNg9g<)SwX7yTb8MHl^p8aQzM9bMEo=M|)( zi~2}I7mZ&pU9{SI)sKXW!g=(kS6byKVDPnK=_+euQ+M!kP?Id_ppdu;TWM{hr>~d( z+0k1@Ili-wL#(a{^`UpeU)Hg`i4A@|H zP5r(NBvw~|^p@D${4dedB+ZDPAR41*?G4g9>v#*PNrg1>BgD%;l@Rn#-ztgd*?of% zJ$rhK>q^D-_9MufFIir)I+2I;LIk^<$epKg%e`WY$3 zNLoaVeQ?7aBWWG!t{@HF)khk->v_XnFA`}u*q@`)uK8(NuUKl5X1FVeMt5Z!rMs5j zXzmkQIi9`W2-kY_M&B;s<*iBvdaG}Zgts=_Xn1R?x3mUCT5CVjyqr}@LuaMZl(Tw4 z>oG5Y;j9#j&RTftsa9+t(GdNVqA5S6Q1sLBcceoww=qP$>Gk z{Y3wAe0=Sk1byE|{!;6XHQ50|h~arJX|HcL`kURSZ|_~L8Z1abFZ~^d8^5Rrm;W z!8dOe#V>sGR`H|Ty?MKQ(7M9+-P#YuklJB&1U-GXR#O4oV*lHBYrNUl)|ITi5+h%& zwf;!HT5JB1e6{xOVc5?0Ai=`yY1T(1dpewyVjek*ulpAA=#LUO=IMY+B~PCsrT>yV z)n-X%uM>1+HVai~%9fJ?lx`4wMBr`$l{@{El-?nC>ek>}LgHqq^@8jzfl~#p5x5&) zB~Gat-S0Nt|kibz=zwWDnNGylGuhfN6AtpgDoN2~^s&6Dh^CDX_z|soN3o z9qS;1g^ti~lXQe30~;pTrb=xOH$00Vg4FH-U17vIYMS&H%OYID_ss zadpB0`9lGELkcOtEV`Sb9Vu{AD0k>dO3@tznaHApJK*khKk>=cjAvf4&SYZ*2CCf_MOCf^T12`1maCN!SpyMC~MEL@Hk$n3i?t5^1YqX5zDyO4<4 zcPbIH@4pww?E4=?Ant3sMrCOqWBR?4FJr#$4{JL{*@Bg=aXyIN7L(cc_>WcJ!tA@E zD=Q}ugwCCPpL4@HRAbEuDO$DB$42%YeyHKv?I2wV(1VT{c#1A`4_7)E8TjOnah?`g zPw|KX5jX+cSTN*oYX^;uQ)QTZ*IfMOKh|vKB5>gnc&0!u0iw6MK!V7>Q*19?jQsnE zf76A7E^!4i|Gvyy#ycO&{QEnkz)Oaae_wQG88ZLApRhusehzJb`FHr?X#+1IM*e-5 z6cX*YCbYlp(x+s^OOyGcxla$tN@4QgI@g z`Hq`qX1)_C#kFcWYGGvNZJXuX-5fJSW}b9yBQxKUhlbjkGb+xjB@M);n^j^yzO%9Q zlh}yVH!RGS!=?}w@x#T(1OQvKS;5sXTPKaZOi;u^U3-zw54Xj!7YW?6PS=*@MZhQQ zACNMv`FphH>t)RusX3x^$L@)K0afQnG%a06PqbnbB*9XW%KHkT6cr93^Eyfx>VvEU# zhv}iPX~(_iSF6ge*0MD=Sr6Cf{-og=ok~+{bT4QYL|o?`X>pxSX~Ees^BJUVmWj`2H_N1a)2g-$YzkqBsia4@@QH04alr)c z@lgHwEi#kz0x3lweU2De=UZeZiTVw`Hd0nLQp+F=Gf9sUekctyNo%*r#OFFvie9>! zNYl3ZHYp~OZX?V{B!Og+NP;hcY&C2(*%5CMhp32?z9NK=l78T>4_{K#R*m^qN2HPd zaJ%RYZ(+X^VY&q>BoevQdYG8^tq{+yZ5v{erd*Wj0ML5AXy~F84F?r`V^nLa>O|HXpI*CHP(n+sumFc8~gb=-c!B!Po^u=5KjY%?} zq?)d#oDLFc?tBsfseF?D_*R)r8@W~Hk|v@hj9d~KoMbLZ9I+ckmK&ZSs~N6sGNZl` zRlsD@x8fHjlfK=0yJXV+skXO$l1ZF3vi-?Qi7jw@{}lyrOa1?mODgk;@=RQ6T0W7v zq+4L1yo^YWxuj|Y3sVTOpO9Qq15%2~lvuv54ZOQ=P2jj%1uB(7$Rwrzl0ty{N|9MM zK}TlYP=%&!JSjlw2ElX!7X-j)K`WTJJWt?vNFBIkFD4`=*{ewbmA#d~mF${u<~VH8 z-b)H`sr_$Tw4s)s!~wiJMN|Ap7@#^}SIiq+B?Xv8G6-%FxSK$w4a#p*E`VtRV25b~ zw+mnvsW!nv7pT6CxIhz9iYXK*#WYd}Qh=hNK>0u~Qu;4GpxX^@qX<57g91$9OeO^= z-%ar(DR5J$G}6nY^bWq@(P0^(adSi+Hj)C94m(MKn?mK0ib?4m-2tlQaR=RP<4c4C z@`nQShd)UHc5XLC(00}2ZVKfP5u_9yLXe3(5;z3z#`F`LT>os9yD=LRVyw;`6G;uX zlSI;OSmSQY^IP4!F_+qGbs(quh0T@~_m2paG(B`tMNawEpg3TTPw!%PpA(CJdtgQC6rgkwmgW(+L>W!mQ9!1S-_B0GiASQGCn_y$&Uq6?&7< zU{=W9@X-d^b~2d0zg;GUvIM4iOJ3>#ebW2r1h1FQ_8! z$b=uBe1vk1&>afu!N;T!#TUwlDuUQ->#hPa$n}4LADskRC!6! z8|{$$G8>TsrBqh}MSlf!Ob$_WFP)6!P%>cNNhg^d8s{Yh(p3)+vrT0#0{4<(B!@=) zU&xTzp;rknwC?;JMs^5(cv{0tijf_fC#6LDx30<##SpJD8isfWNdkRLM53)R2~&a1%;%)fW2 zBoN;|(N;E!ScujZcW1UI3gR2>HUfal5Ex%@cV^8;ZQrnd1P@o)y$j`rjozd{EwjfJ z%4PNhQi}B-OX@#W)}N93%gvdp_D1FegyAaNM;NZMUoMoZ>{p2}vC7uw6Jd*hg;DTW?-6#nwjOR47wHAA5_~NJQ-PBLXu){zPCV$hSUXnf-mCkqJ8HE$t|g z_LCoJmSM=1@MbcASlLF6iHWof=I)J&?F*Fo5N2(2{}G0%*$0x!i{RzWyLjf?tvD#qNg`i}n z?@r?OBX{~6p=3r#dA^YmBGTL$Ap#;9p|qVcBh+vwRvv~nSYa6nAu?9UgwTYysbQ3C$uHZS@@6f$E6KyPAc_~wbf#+s1qrX% zI%}2!Fv+Z^^`rggX{oOceAOimG|GO|^(pY1{;KOU{8PuZNeJB_9?ys)JuU;%B-b8N z_#75IJIU4103z}-A$AuWKy0g|7mo^0z#~FDu87A~@rcZUM~ry1oDPq6;!%4BJnD3Mi;6_4N-;89ULUV0H8uZl;l`S3^*kGI9+9r1|d@Q4wQ_rzm`cr<ek@{c$ggUwE-u$UE>0&r4tXF8snHg&pDqM?5%kyf_OFkKjv#zUIP%*TgYX*gvuV zxw`ceUGY8fz~h#-i8Ds)c9 zj~o7Kj|AhYQq_jj$H`U++hukhxX63fR$C*EzVqRP0G>1a{#bqUM5%VKWoc(veQ%Pw zl4MEqN>Tji^0Z1(yC4+#Nc^53TxF|WRt%pocHH7&oyvCM8LMp>tfz-zXPzE!ulq{j z#ah;G3MhVwsn5Je?{+8~{z}-1D86=Gi}JkqQ(MF&J2lR9KA{2TrJ^KfX(*rYOzTZuShG(7IwU5ojC|?jta5Wl|meja_`fCmD6vTizn( zFUYT@y(XGFm8bN4D2(Sm(eiHZ^g}x}ctNiaLX_CWwe1w+aiU6lvjagmz*7YqFtb0H@D8(nVo{_{ln$<&Vw$|DU_R^lP7`nRC z*4Ps8Spc^#s0ItTXF8SV3H9N0r}njGh4Go6+U}_)t+{oVtqp5U^iT#KETFU-wjlLx z`kB0sD7TJ%H+z)OJL=l!^O7Q4Woe(N-*J|mHe#Q@`*^^9qsd~NXU9Sn|dg1*%(4Om7Ih{QC5M0q2`seVnJU=iu zOf+gDFJ<=1e96X1@jPjtZHZ+&sJ~#wsHUvYyQa`NT5F%En!>IuPjjxzOo-+OnY}yD zWmWF>lnv2Yf<6YZli=3U1#^;_`0aLhtZ{DGXcp#OVc7rdap3hvLpD7K)2&iMzOJo( z6Py#duh`~bHwj#|;h(BzmZ06T4bfE{GX_TU@nv#5Mz}VMzDu2`)My(jO0|s-`p;%n z-ED&_V!S&E0u}sY+?}*tgaCPW66|t1Z0i|CgD7Z%se;WAPPb-e^UNNux;(dKI$XjR z4o6<+91D6>;y;lMwI*9mQUC-Jr-m9kaamQ^8u`r#h&OHjS=u&ZI* z81WzVtlmnWyc4#g?11{8OfDYqCi{Y*;pC#p!kM459|#nz1%4uCCW_dYD0mYWY&s?8 zH5Umr1jOo`ow2>EUE^!d*!r;FNg*~wsNSlLes#A@Ea5PEYd2qarek9Z)R?;iMUP5K zdZ1jjT;yQr7IF^bQ%F_2THkJ5AQis{tVTyf`@6krg~SLb_KgQXa#qHuf~cQtbv4$) z8@q6vrIy}gkIWc1A*I@N+cb-P54^>61t&5mDZwhHEC_6?S$WtW?uo*HJ(xNZHOwo` zZKQP;b|pp38})GJ=jRv9zLkl z*2h=iYkRo;rY+edOGP>#{T2$=sjtj0EyGiG#s%x3Z|Z`c9m0gSpqm@@$W?d~erXk~ z=j`D_^18L-CpQfZCJt)c>OxE=rq1uNGv<0p$BtLp7;k6^-7cPLainXhC>K9g){+a- zezT=%%<{RHH=%#rGW_Ef5rzH{`?=vC@n*U@T=<7x<#W;n?*H86AbKPg#z_ykB|U@) zkRB3Zf}CCohxDaAJ0_74Fkknl&CYt56@XR353#i(37R_yyB^@MCD-y#P_U~(lw6H zKUlq~e?2XhqdE(0OfTYu(mhn- zH1h9C_BYIn_3SNOTJsa(_Fvg9b4}`Soa_}Us9TG9tL}M{Y2`Z(m4xyiTF=U2Un>b} zvKQq?uInps3voBc!8WtDu#0B0Ui!Jca>@s15ZAC*;kI_Ox-jhv<+R{lz4X5&l74!x z+@WiKIk`2fV#b1?vqGzK4uOH`eRNMwn51=|c@EkC_V$DMN{r+1?l^1?b&U zaAR_8r&$j6rWv)D&J8Im%ms!NE~G#NO0Xxg0&k4czBwIX$!HRi+i}KVR&2)XrSCU{ zoG=#{LiUrYT=B-hssO!^0w)rje&HB)*(giiEEnXsu| zN5F8`0{3g)#u4FY^Z|U$F9k-f&+fMCkC!PdQGZ2)M-+Q25n3aaliXVs7UO2Fyb zU>k94dma0A_5e{6BB)GRSO)J4SorL$t}L6BVgwaA3w_`|6+tay_Q?gWX5;Pa*$3Z! zw#(?Y7l+1%Xb*5leS1BVa-M)2H(e-2E9E3w!VG^pdyxQeK*fRnc>%?U_0?W{M?T@V zDvw%Lfd05O;X^Z#OhW0)NnQ1i;5vKQ90XN;siD1z{w|imbw2i>`oU&uoK7b2AtSUv z{jGg6`ai!1adM~ks_+X3$t=Yv1lcML}EX3 zT~Ygac1%`0U-QcYxvYVite0MQzl@x<_RAm}>U8yHoxHKqy|CcMrA}<18O!LkefP_K z@1Ye_>jj%JdTD)mb~k$}Uox|NtX50@hUI+qNQLJ%mrz^v+ba8weoHDS`|YiLs^5kI zn$d4x6ThnL=e9QX=J8SDAL`*6k;m8F$Y{thO|?jYxkyv#AMEG*i(y*7k`$WwgAhRJsdKh@SA-?X>ah%d zc)AA8CQm(FzKJF3KmZS$s@DoWpi0rExK@ieplqsFKOom?f_3Wn@~!nN`{gb#%6VO9 zdrwO%V2T-nHh#Ibpjnu%w%;DhN!bCOUt?89HB0Tp(n*J3`0*Iz_}qKaY(qj*!eP&SLk6M6p1A==6JeG zKR&AmXwh$1LE&DLaJ4`(jt@XYb;T{VZ$fi`cQhy@d%;V-C2+m+OIXCxps0 z5EC;)!U1OA_6Pgcuyp$pLdlG3)mab19h*FDa$vC5g|8b4gNS$|+Uj20EpkY?=s;pyvvN|cn=P~GysTtX)so(DPJ0lk{YKqsT&*V zmo*%lMFlLzzpmw;y5u%2En;!k4FeW-Dx>?X~#hdwlXc$4fALz}i}*}Tcn7EPL^ri^Hw(rjq+p-r1N zPaQ5g)KLA>m%Q|=j?LL6BFN)xl`08(v zJnJdcG{Ty&lHT>890Jiyy$=dAHPXu;YK_0To(Z+;{{0nPU47?|MK4I9i-9faccDf+p zG5d5)`-m@^1UaMvq6u1W1GQd}vflB@_R)81y|o8nM&sxe&)|n2^L;I#G^(vK%m+8P zO|UoQdrvqT^KwtvFR=539>adssrJsSgg`MgpXb}B+FvzctH#>t-Sy8J7Fr=Kq=Uz) z*O<^fRYZap3+{;Ysq70PB1QR&NISoj?=nwJw~sT&M@&M!GQ&QWr57t}fbEm`1kKXQ z+EzhDw8s&7`aQ*+jJ#ZXENowh%e6ORcEz5f(9%U(t7tz$UAE!?UfQ8zEHBBm4`A7Z zZq^HsT^d*{KinN}E~uNgDX5+{kf+bKH)qpH8AOM+e96b<0(t3+c88@r_{6RC)v5|U z@KtOSFIio!8e2dJgcQlBCU5tkr4n0A3Kh5F?iD-xa?4#?wHn(%2;4fScDFSPHp7X^ zHTnFEic#z!K~R$NOM+_gia(~;^A(ryioF{9kx;qCiR*r&{99KZde)*?uD|TB+G8`@ z3l4ar+~4At`1k2oUERciMdG)yNo`z+`v4*xQ9^i>T_vjl%Ay9_v6kD;} zJ8oZSuO7t?0T`#yA>tQKp+gSIDfCw1ftX%}j};F(M)BXDvrqQp&RO$dS-o$r{Xtes z@KDj%@aaSa_4xFxyZ7mn&)bIu)Bv7*O_$5{D;cM|Hc>)|XZsQDYJ7-#b|*rI&6a*h zdUlq%K)Ojf4}IAVZt|i%oMjUP2=ClLa4Z-X1U_Z(8FxS8GC%?;g~69SXs z@0$yV;;q;QQl_N%ac#FKbnQKa$}I|A+rN3GYsVcTt}U8Ny7p=DOZ@A0ZSmX3wV{p7 zu3c3COs-8KP=>DE_z-dJ5uGoI)-Wf7S$X%X;XJoPP&uCa^h`UetVAfMj`Abe75$ZbVK5_+l__Zbh8^y7 zOeVyRe2CdeU&&-u?XO6(sY^Ck4nA3eW}# zriTPhqWwt2+JZ^$lPWy&n5-P910Zk@uU=)L#dlNzOK1V7|@P8W?Evt z3gCOsk4<0%i6?#xySVQAN`>W0fM$f{w}mu8C3bPeM+-Qelk3Xy56G0SSo*PdiH&juWTK(&=e4+C;|D(v>s*)0G9Ey0Bcid^8?;|GfQ+vE# z=?Jg(Da=A6j)1Oe1~yC!b;_I4)z{)}K~LydsR zr~04SZ?aZI{!(FsCnj5J2V?-0m$r7)W}Qj7uz=Qq=x2B9w{VZWKGBcKS!gT%^&a~Z zCK3MhGqAn%JIclq(dasDW;zad*_qgrn#b z+@25^9P*NY;v@xzYS_#-vLI={{g}p9o3X9>iX(C#-wILymbB?bM|fD%tUBydQV`bG zFhZ#Lj;fY(P>k;a&U=gb zk%+mf#K2pC8WAo(Vt8U{&lr=Gt7RPZOn~$w@S1((SN2Ct(9{I*o8Wypoms_ils991 znPmw!p(2AlU)#5tpcBtSPB`JuKJ{55VQ@9hVKt!vaYqvXy&|pZs3g{y&5jzs-8Hp8IG9yiCJbzx4)8AAfc~4UK|znB_8)ZSA{@aER(-@b z(n&^;0(6oY-$*CPB?agtIeft}clL1ZH)baZSFLA!(hmIbKmZf}?G7hfLivh_4=p0J z!M3K@*wzG4FzbYUgT^)ydbHT7Q31(pJAq;jXA{483L3`;J7GifR;<_;`{&aTy(xCs zbw>s}Ll8yl2M7#4A)!|iKUm_3;LnW>sNhTWn-`S@sQ9dklh>J0Jt2V%50zz{BDLl? zJZuY{oU5_WZ_UokMLOOR@@)Wrz0%|f41RbbH#l%_R-FKZ_K3P{#iZv=s2F4it(?@= z(hN8qdcoCzwIGBLV;l0)apBGMCf}-|2BL1*C3`>8?#7uVA>Z;Dm+ToP3I1wopwpVB zSR5U+VZzJ2T=?>3dy0ikBub$RKm4t9;fF~9dc^h;`zLG;fnrz&bo5AyetNp27SHbx zT#qdz=knOBROjcjE zHb_C|r&7@QDFB?mdcm=4c3o!&i8!op=$mbm*tZ0VJ>VdJ>AJmxFE-A1F8X56{sUex z`RDyVU+k%W+CMX4dm6c_iUr0I38WtIo><&q%Fo`gkJTzKv^(PX!++VkviPIQcd@l% zj`Gm|*<)D@DZtA1`Ja6rYe=A2*%+RxJ30{C)|Ix6Ix0`02tUdbYda$O<(u}=S`U;v zwa(-WX7^&GXBu)dNr9C6k9{s1N}wn=(_3zml-tcq?!{a75!wup`#789#Y4|EMCOtL z6gft7jAaW66h-EGi>xO_=17rRxF}EMg|!l5Nn|nXL7IY#{-(RWl?IZ-MKV8Uaok{^ z6Pei6b{&;nZ5JuP5kKu%Kvm1Jqp-L5SU@5>L5jtgp?`l=g$(_|Q5-a2_E;F?s7=}` zRaO9mhz=SM`H(;_!^tEbcqykPl1h$t8p|eN>_C8z;f~^~ zaQ7%d_k=qj!Ei@O&=K2z;OfbqA|!4JXmg5=Hm3lHTZsjaMLDWy>`lTz$mFHJ-_PPb zOQXipWP}(@Hu1xy$pwunJ9=vRn(r1m9I+gA*+5ufr-1t^V_+_xPvAHSToU6*W1kVI zyRuq7Zx!npYNEhd-`-e9XZ9_jz;RzN=Gy2cF~IpWTeGA-Y}7P z!X)wkrn2U%z@6aqJZ%L}sO^a2i>f+ahlA6WR)-k5wWgy3tMI+YnK(88`<`E|=4i?o zDS%qLSONjKE35m5K7aXAHL?@#gOQt@_f#S6fUnx;J`P1x>!(ELR& z-sPVM0PJ(ADfX>w=Ap@sXg+S!U+?f4^&AzLD0DA{{RwO#1wP{zDBJCcx{lX)%AQBc z@X-4mVcHrg-j?L($uqy_pDa%F)Be;^hZ?qvazlV~k1kiyfO zJ7P`Z{29Q&t`GbmM(8WP6RAA-7*pI3t|nYYBq1?Wj`Ce)XwltcOzoDAQk^X!`a|`t z`ddH9G3G5&fb-qbPA%$KHvRw$``)#xvrVKJhxzri%7yTeK3qPHqoU*SA#}pqMOGQa z;Lt?HsG;c_%H2J_0|^dIlmtUe&-RWw>;fUdW(RZ}nkYIBO%#Ar>YiziMLPS3FhI7^ z9UTK$&@tuV*j@kO2Rb^2o3L@rfFYm}t4y%Pm;oCzFK56ALwO_i)J`x~B>7_h)5+1# z8@nc-HrW!vkMEvYm9_CADK9v?gI6y;p_QW-FE@021#ceJ;Wa1h4Y7KW>;D+d;G^IR zT_KnZ@j|x%8ej8zR#jj2Pj&;vAMwJ6>bK|)!wuz*rY-31Xvdx;*oJ9sJsbl~*q&}c z9K4;|gH+2T_H-;^ZxMc?C*#~A)-$*0>`R8T-`9=q*2cPkP<4qH`$FgL`+Rd$m$FeZ}y85guqM%A2 z$3q%_sk#F$X1IPjupqvVV}ZtEk9!d17Ruz$R+r-!AB34paZN`BzImXdE~`P1uw%v^ z=kxkG>ibfk>*pB4n)*Rs(%(_t7yZ)=T#t1a?l{OO6bx`MmVPH?3P(6tNuU3PX8kXU?-a%enMt3BTpzVMGJ+UP!`gwolt#JGUPq^GXnLT@Z?3O#w!Qz1OF zcZqzTgvSrO1aB3^@dNYV_1@{{w4v-05hB!=Zz<0UsPUE(zh+9C-{B=o;3@p*s3t3O zia4pr5L!-=cpP?0#bf;7=+;S5Do=-C|MM1@Fj^1R|2!!_M?4Q^cI$`7BebKUJo>d3 zP^Dj!f{Ak-YXjJW-pILWPciM3>_AzhP>e3x7=HC7nB6=~;5fL9rj?mOD&zGcb({<@ zz?bj1=}Kf&0EQKK?{8->5cVRhSOos&zg=z16MUGY<$u_rJ6lYUu{A^mbRf8TXht)W z0Ocm@2#s(Pxap+Yt1vhb_Ht^6TOL03#SUHw{gGlT<&O|-Tn%OM&UuauFVzcML?-ac z0b^3wd4liJpQm%jqb31L`5S~lD38{OUf-dQ2_M{Ae)~dZx`y>_iUAlg^+b&bUbXBP zD}U{EM^iogG(Y${grmsQ%3mSa)a0kij;YV$2-MSaBTw_SZ@?HqNt8X335l?W4(K?? zr05=P$wb7MPllZ)bIdoS|Cnna=9qfVQ?fU-2G@n&pwGizYn(Dob{cRHmB9-q$FWGV zF-LU``FY&KLTTIpIZph-4Upqb-)3)b%3{Yr4f7 z=lSQ&zQ^s4xevn`ZZ9u&jAnU?yWIIWB(q#=Vr;ia*TU0sdExhs^E;^r*`fm!7qn}-BC+SE7#4EV}DHdKJxW3wHKagR-*x13L?oG+9dxyirUy;C{)>@2T=s=K+%*PC{)-%3qpPK7Cc%@cbnp|t&S^f0^x_I z7;BhfEGYn|=w^BHM|h<&SW9G2lM=MWY;Rl4C$`Xj3a&|PVeESYDY)jPQgFh$j52qx z8vq+EN3qdz6o8d4+~F9^C{$UlkZ?xJQ8Xm3SLBE>5u@csn=FSnk3Mlmj)0?}hl=^& zaM8!aeDxZUfisLHwTCe#fJT2;)71)Rjp=IWS>lXhx*BqpbmN$_%B^s^S{6%<>1qI_ z74uJ=u4-qcdZo~mZuM}w+Ql0kH~nP@DABKA?H)(0#s+vJi=9BM4}qf5@Pbqd#Sk@t zuiFbD>JfsCA!;10TMnt4n7ziSE@SLlq*@{_`1~km zHD3-m@qF)&9J<6$N#cVKKwgnD#~AZ~VegEyazZp5-NKjoXxLfRCL*H9wP~vWFbS>?)}bPKNMfke?OQEq31P_c|MT#1h8m ze_fKmx7~Q83J?9-k;Cpgr(9Z2#oztbtXt+MgyD3Oq_1cVSU*kf`sDw@zdWsnz6A2j>P@A_8q*|m`dO{5$bnN zPK4b0;fETp5G>^SlH|ISz>(`qf@>6C+}G8WttExX`X$9$%(47iE$_G^*P@>@W?00q zIK$E|@I%KPnPGrn%&m@#U-~)T@Pxw}e@l1)om^caZh@1l0{EOYR^!&Qm~6# zrpk)N+>dL=x0D!hjf zC@y{ie&Q?6!gQOWLt5_zJ>e&r(W_1R&;I!!g1wAg`;`I842+|=%kXy%+X4e!;wUUYSu$QF;w5;Mdh8fd1!Ejjy&a} z<2N?iOkmZA|0L!#alr(RQ<~{N$tlfDQh>wwG_RV&u7*RuI+|KU#W8cO)GjX7=Cj>{B)xo8SNf5HvS%LyIEZHk6*d(+R31&l&*NFFLQ?Vu0-Np3%`RN^S3v;Bk_ z&SXAE1H`h=Nda2mlwpB0qyQ}d$y`(0YgcY-0b`#!$UqBF8E63tKnqX+S^)PH2cK8I zj2571Xo0oA!Fyi{MPl4y9Ct_Js&yxIG!f&D<77gIGap=u<($x0VDs*%p0b2FB9?Th!jowgywAPOI+dF$TB=#cXnid-;u*D-MPfXLA0$t z0nY3Y8E)B|llhnc=N4A|g6bF8nX6uqE3~Sl0FAh$WlU|o*#&vkU<*=;J-P{>73!qX zyu$_6!s$`jHR3!iyihj|VeL^>HZ_REH3}7}nz|1aTUt(NV=iQMQUrSJy*db$uU0d+N zUhrWBG#qB~2Z&DEg6C&z!Fmsfy<+Ln^(SLxw3i4{<;dHWpbIb6GcJ-Co5u$t6)7Dd5PbRO!lKCFDi3A?L>D!3|IBYxqkXw5~RRgswgCI;4V9fNfHUq{At zh{EF`j8F32JP#hg8wB-(2aJQ%4g$6~NUcGE;JpzZo`ci`gdC(M%3OGu$}yOziAw=N zlDHJ`KRKl;-F!?7?7M0q4$Hu^IpW0e0C<$aeIlEVpUln>Sy9ZdUJz4wSO>_H)kLL% z_*Z$d+O52V1Ct*RNZysBG)pV5j=NILKR-C zrnBGw``N5v{jNsvPis0`ls5_B*{g^3<3npX<1DQ%1@NVBCsg)ASi679BfR9tF%|e1 zz2*cLq||mkpw;a!>N`+828&0wcnlMd;o>n;JVuMh7{2CyXOBv%#>NcY%CEM8s8||1 zys?N_qm!v%_puOwuslO@9e2Bz9bIbPT@mdY#XM%B@|8Np-()V zU`YeCs~d);mJ{lLAKw?qPsh~l%wKBY%wXFDBXr~f9`=YcL;CR+1r@*0kH_DeAHO^} zoUclDexK=&_rkm7&4qsm*6q@q&3HT33?Z$LGezp<4tlwM^+h#r^Z-C`8tHvT97g@G~)S~hXk(DX`| zN#COnzZBg#*kxq>gt1HnSyo)XA6w{^bF2o}$7=lqLpAi9BZ z<=IJ@YZcVf`|kcwdg6EM*-pipqrikiEm}t^pj)1+2r4NKqhFBje3>0p2z)_?vo1e1 zBe0%+80y|VqlZ?^i#s@@fH@Z95mmjEzVLX`CWLpA1+5@`Ba0M6Lqb*PAG`B2Y)YF-*4b01Q zuCq+K0+*NU)2rwMuV4}`gmS`;7^hS)-i7+8@R-&4SNRu|D7Ol4+MFBNLIsy9K(;WD z=kC%2qd62A2SrV;>AqL?g)97OQ1^5q*0?*?M{GTZ^DJ9wW-o7=j8{6Blgj`?d`TYa zu-!~(4cRIHIEq8}z{{BqWI4-g>^n1J2G5P_%OKkY3B%ZsBdYKcKRv8-B2TW|u^fN; z0cW!Q^A+xR41#Ql!V%qaxPJKxiLW=V;1Wh_#gFxNHVapp8?SYafIZ+VOh1xfHD8WT ze$W}OhyBbKKIlwj;XgwajPYJb(kgPtP$%4RC<1x>&u&30`#5V=@)g8S_i=j35!XR^ zNfwv=^y=$;-waOtCM#3_3VcXpCk|ebxyD`noN$PWl_-UdT|A>9(|(pIiteN^WuUXW zW$4ewM=cML60FM*QkQYEE*9wB9KUH%wTYGu-u-83HX;BTeySsp7r$ajW=|6C*u}-E z2S6jfaSk!jV58#q<*$Ki_sd?;whA4T*hc;i^$3f>KWv$e8Fhv zoDf zC-j+_#2T{GTel^TICrq`&1e~TT1Ln>3JL*K1Q(GH@&cRUDjdCJf6UpKl`2XMs}Pb^ z75~C28bOt~Sd44~lT-|^CJ6TVe63S3kDKg_)hm_omXnMKe^yVEF!2wbV}1 zQs70&ytGR1B-Y=|-x|_K0H`aipXw}PkDAe7b7HqL!TJQOF`Q0%dvQW7 z^mI*z7Q;&hM4h4drc8xB{G_uL`&Cp4%>dJom)seI5(O2%FoWQ_+ePefj+wCh_nZ}Z z&Qs2Vnf|yxf4AH*hroe(dtPCIGl=im-7KOY@EPYoorRXFx@k{jRp&1~=WNF+6KLXb zr&SLvm9I8@&?n4w_F+l>(T$-UXn1<-ha))P2J*hoJF{4u{~Lm6-g=(1CA0eC795-h z3H%VE3|!MAhU(C%S=HGPLXiDW7An8#MUYDH`GOTrYkWn4N!LQu>U_aFT_QPN#y+)F zCQfn)XK)0o_Bfxl7ls7PnJfy-zRR_dr)4UHm=wT!*eS&AW?Syr5gscT^0IS@MO(_X zJm*M#X{kK0Kc!RWU|xQ)vs}T+JZD)At{c6;;U(T)QtydtoWr!wWW90ELut2uVGwao zzvlep?s6fb`Z-z=AM}RvepW<8E!gR_g?Tp-T)QkxjtBN{g?14K_K#l^0b58i`ULPX zZ#o}ge-R$&)4^{!A7lDe<>|tw;lAmkZ-IYN?4mcata+{K-9tO(Xn&X$)NS})f52I&51-Y-nV5H^q%NPo)ERRx zhHk*eyyL9T8W72%GgNX20PPG({OSsb^!HztMn3q*ptAg>znm|!;e=GgLy;P|SE~*6 z2%`oYQe$jjfws(9PSfUbw%pmAy+~xE!R8W!y(SH20fTXERi6atm|4;MR z_Fk;^G=Fe~vmtw$h)1if^tRd@S&>}BYF(;ly~nl_s{hJhTRn1w!3y$MIVWiW=Rgo- zHnQ5X^F$=t33gt29P28v6JGf|eyy|Dy;$cYe=;AIYA1cuRFg{ z;B3LV6TxWVaRNYlZ5LUcj9+E1&CSco;@O*FOrK3i(ah}|Zw}-gc~&c`d)Ofd{=vw5peoCzTW(HOPuMOj^0p%=Pf zj6328KL0P;d#1-gw7qxa^$+H0JDlGKTm?mV=!LBN*)^gPwsHw+<-f6&Wo%wIB|3^* zi=6H5r4L=^nLA-Px=e&(3s=16)xxmLL^$j@XyK!s8uAstWDVejpF#`Q5SX+hO(@B7 zvU&uHjSFb9aeeSdmuB^5ZN2dI8rNhCQ*>-$8^IJUY!RHrAxa?xm9}xV7lB}%IG|H( zFoBCYhrjMU>L*;2?>(T>Myo+;z<6~5lNZmc3%CsrrU&wZr8mUSo>6`#P_EZY<%^4q zFPtARf&iOwvfA**`(=jmwxz~{5q`o8c%K8Eh=xe7Rl|GvO2R;Z_FzS6F<*ds}QKH zb$>eNTXsR)?wH;$fe|Dzi>|J(ye8j4tbL?uFfTpitX>&#jW-YRzrio@FW!s5XZF2Z zi`%|(hQ${N6dJcy5!v!Jgx9RDhG0d#8)tR(2o#5j8o%-H-hxO;(M8zc$NwIF5A!-~ zqOv^gj3bC85Sa0+`h&%No)}0Ax1dn*3s`=o{xXHk{yTwP9tF{hQ1HXOn`7 z>tPiJSuqC_z(cFFpRtFRcmawxVA|H)F zG0^@)essor(^cmx`D{g7A(FT9HD7*`K$}hnrt3Hhj7<~7e5=DqCfjP@$J0d`GSgBjV;2r@gC79 ze}}}HxJMLzc%lKe6W$}b28!Vx(V8ru6k|iJqHMR2hQj3UlYG|C&PYDtc}tnwaQ@28 z`LH+VV#@i1U(T@>p*OtV=xVv{=JTgFpWi4S{kn1`L&LNZr@7h?eBpZCmjmmuT*6Cq zP5D*VbZ}bHPGiA{&`x>=wwIAfq%jN_K_dFYa=}qF2&<-(8|vC$2MBJcOB25^hnRL< zZm7E=h6~IgmK2=2>I~L=2i4STFx2)Hltv6!gX#kc>K=CHEx+eM6}~L_74~QhIpQqC zx7W%J=hc39_F|)yEIG!CtHPrEXy6)oT@JDl*PWx;3_^y3?9}UWkev(-Wg2AjyfI%^ znE0aKuPmPbr*nbDb=??a3630N?bp4=*igVV#@J8AFIV1Q&eriG#ZNk_I+Zpha#U5z z_`RwO)0+5(KlkCFdl)5^&C9dhgguUuCkOz;!w&+0;Q?%o-!LdaeqA>;xfoe&5Fl2C%w6d-g6+}(3W2_!TzbOk|03F_C1QUn$h6n=I^ zn&lJ~K~YhVCN^wfS5Ux$C?fC7>~r_bT@L+x2=71SnBAS3ot@d4oh{Grr%V}|ai{vkY3>=T88VXoyg!um=dl7y`pZn|ui&K{hPAD`{4zQnFE=mNI_pdMP^`W1 zP?&BKNYYSnk~9=S0Mku!D7ndPj2RjQUc+*e97@t8H@W{m8{^1uVxyj?F z)%5!bXfL|Sk5Kc_O@^JZ6cz12T!sK;2j0cejucH#IU_53mNgS;tg7EdYDsctlEb{C zK-t$;a&ZGkhcMJ_@{*0um|hZo_-(@PCE9spn*K~0AB{(*V zw;9KlgL}h*`W@WEwRUiQRb~^Gj!oq~O+b%6vdCDzEj|QscwfCD(Xmwg%o?Cq(|$zJ z4%EMeK?-nc5r0~GMD9=jQ@KB=iJzN-Fr;l)k-}=ha6zhiRHqy``ip1i5GU0FKjA^R9 zBM)Rb+KWA`8ad!ye=-OB0gN!bz^hmPDL*rYWyq#29dU8XunEb}JXQxJ=?Ya1l61~% zX-h{koP5~S5_b7c22(rEsr{v>Y1Q)0Y)A8ubjZVSI^r@5=*SkutdJzu{Vyi50e`8G1+-6v zES9vQRIm+1s27|F^&$vh`biEYKY1miPkxfuu>2&4T7L5S|7=Wtk~b#NW&UM~PJ-xi zy>;6=F4x3bhKzJ?wJE>VtiY1rvr2x?vqF;J7B0W-7nYxStPqHh{5TPkUl70y`8X8h zkS+5%L6-P)#smqGS0f=F?Bs9@4kaN{=yviy8%K9`#M)S6GoL!3vm;aJXDzLxgbJ&t z(lI}FcH9v_nucJN8UlU&pX$Wb6Mw2uWhEFqhAPWZ<1kd|$OzE%(GCID^zlYm*;#YN zJ&aW)&ktK7g*-~pN1aviM73Pd!_i&qkLAfS?e?^sDAv~U^F6TwOz&rvi(gL6DHk8j zCOSA_lk=u~uvi$3q~h0vsDyxuChK5Faz@?JO=b0suupMca63G6oNU>ed18$tl3GgN zM&4hG9qa38kIS`v99OXV@ya#>>sRzEwsYU$mm&li7=Y|RCMW=T4S!Jp^4i&&i|d$v z4ttHo^*`bh)(0!>_|Ss-!;YtG7j{&;9aqZ!55V_at{>>A5IW8yxF+FdP;|6ir-_S*KvZS!%Z>1`0=SMfy&%khFM6qaRL<**@Ve58hM5$;T)JAXg zw~8x#^(g|$W3{aCAt$Kn9UHY?qA#mTAxN*kRS06R0t*L}QV23WxRgQ=D5Vetn4u6P zgyc~K6oMQFi=hyNRZ=0y!Lz|32-G!0kflf$|EoffpT`_)DW4nIH8%MNtinT(LrnZ; zA{}>GS2D(}NqjAX;^d{T{9En1@#?heHh1{N<^@1!riTL^BBi>aJzzGBT)`Gr$jk`66ir_eD6rQq1 zf$}2nf`wvQ`em?V3^raw8^mCv4cL_? z1JDT3Reuh(bZzH9%HrPSZLnvrv7YT`J)`UX*4$-=DjfO3FC4i6JdjC!%LtGj@g~IO zo@*TmHU>5Ihz?kuVXaAzSUsgjPhaP#3Z`oALPedolrS{ugn5q2fX1js@Bu1obXKa- z(O)DLGDAYIv0wi=jEt^_u~n2igKO4HZS94p`4-d{rY&4iyXX)Oa`uznJ0KOc)Ix5hqU<3^RxJTx;Wf-h?{sVt zkF#bJls$Z&qC9P_+_A)AmqmXJ8zr^}S9&?HQc&dhQE>G`fz>H+Jjp6qLErJfn&%_M z2oZT%9m}WVaSJ#tq%Ac%3Og&XP(bO-^A+IQ?6xeC8C<3Mw<~*Um&wi7ItQpOt`^-{ z9TGuj6aN5KfcRIWl;uF%bcfMZ3=b-k6qQ0t#H_D9ucFcmh@Ya;W#`SPlvPqu>2>FW zqS6?sYeuEFA>Cy%YK5a!(h`L7Ky)6HY1s?`UAV(;@|zJm8eM_x<}F3Gk(L3l1(4a&yUR97WO&*A>Y$>|3QVNkeX)=BH@Bw;nO>Ta`=nw|#qQY&9RddG&2rM}0NDLrA(GjOe zj)^wkIFvMrHs8iE`s7-8HQIdR0BC1!zRmu(c0_dMBaTS{yisJ6qRCjhr&x!V4~HHw z+Ik;()X`fL_c3fFycMSKRncAn$n6 z(N%CLMFSr((j+%tgZfXWN;s5+PTOTa{%2!K1M^*1=`>!N{fX($O# z=yJg?W0Im6oMcz@cz9b)S9;f+6;dFWE*HGu3j}lZ3+kSE4;4skKJQ5uf}sH#gS0;K z)h&?V>&M`PzBfbfQ0VpBE|ZIQkI9a+G~2>{s&qutVC)$ZuGZC)$$Q2m>63NYb|2}XZ6Lw~=8 ze$)CftwW+O-UrMA`k7NI6J*hE0NpL!9_e3`bsaIBg7r=|8@Vb!G`I z%+g#6idj7s6yMy?**iq*-y1^fxc_L~SlYKa;sTV2xTg=?G-r)Ncm3=(M^OmUbP2c< zYaNPl^`W2;t?4sE{r;nMf;_+7kr|>j9r_;mZ>=}ibLIu~nAQQ2s8so~Y=1^9PP{aC zoO#VLUK7;}8O}0kpH|1n^s$c={(Qq?DW%Vw9C=F zVNE)6z%EC#04k&d_wRCa5QiCN)BznjPxB6EimG4rwxd8C4^bUwk1*^ET-HmFo!)VD z7XO5(b~IrmT0vHNi%}Plc(}SgPgOY|nCSvkPQ+hRA zRv!d;a6%-HAb^=L;!u(Yg+%u=K1d$C8ihn00PW0>=;?oJS9#RYSnfOI7!bf45j{Dy zZnzxqzN3eD_1`eiFrJN=5F3DjM#3OL(RT;Hyz}QneAO8Ku5uUabv3!;NoTPhuE}-F z-Q&bBj0ApYe!jxO|Hq*)XWt@w!zQV4);h=%IXtaJrTg!n*S-RhDNe#fOfEOGXM#QGDRF} z>Dlx;O3!BUHkc`z%KCJ@>XTo^*b1SUQZbI4GDRFPv)FEsALWJe5~N^`|LTC7 z7~eVih}dAdblf!r-Kv-fd0=lvlKkj<$Ah8;YeqYC&EzS~nZM$?Hc9Yd5Y6L)i_w^h zDGaU$pH>R07nF^02e)wW7CYvR7;3)&ciIomQF4Epqk|q7A-CNyB3-bGDpm1k9a;Hg zdA{`DM2U?e$odg$Hqc+{AdN`=IerJU8%)B~fES_gIF%rwc8t@hYeF(lzTIICyQOo|fY{9Y{ zmbEk&_*Mg+%GhOrCE^JKJSvsJNz$d5m={Ygc3Y22{qVx$YwnpmV~#H;K;s((FgGbV6b24XW;4<_;EAk;Z*Dgq43|T` z8rD{@a!Er^*_67GmR^(I@M<&$dmNza^CO*C24JB1qX}zFBhMStYKj9$`kO52(@N^; zC?{+b_h5)9=o_P zDSi$m@y}zVNp8Fb$*pIMGevMH3Ef)#-}9dsX!Xx9@YVlX)|y1m>ao>7gPN^r^}ppm zTd#<7_OsP&O_sOwKU$j$_?oS00sp~&v^E#;HCxjH{`-GxO)AG4N>aH_k$!`x=sv8j zitc}jP{G=X2)Pc!=%)27Qy@3c7y+gmkP9AicJQ`t;yk2@JXVnc=^O^2v8OP~Um z0~&*pX371flUs?o|Jk@_s&lf9q2x~CPS%?AlhspBfdP2K)&JIzcqXS%vo)#ahW~6$ zPJy*nI+9&a=|tmtmQG**&tnCD0B`5P8|*>(ROIMSo+0+5$N@$0U*a!{;J<`1hX`J< zO;n5@)5BX`!9XGZ81_+yCrd-%uytTjT| zv({KvMfc2s0KEbqeUcu!lGPC%YY~9adrtNHvm5NdEk16Am#OKZb{XFKap6DP@n||7 zdq0RL#OUo)`FLsDl-5w5uji^S^YWbygk`29T!qY?_BJt;NxLU z@xw<8+Gq zj~NvAB0~6BEs2st$2*I)dt_x-=Yw)kp)*Pcm7aNK^dMO{tL4QRBgyAB{T)AUZL$+S zZ1MrTr+QbE++6PNE4P208RfP0a7Jm`Z!)3KSztTOnI)n8!i1tWmE6bx~_z>p=`Qc#aQ{nFbM>6&mXJ^|U&KnKSECs?(j}UI`JIuk@rUt`%Y?w1blU?1HP=o(8rL-+j zO8Z~Sjq;vzIm5N^W;T$}-+RI0o5Qa_1x~kF3asVIvN6u~N`GU2v)ko}zRna`WH=M$ zJdg9@o-Z?JrevEuIn!t2hnNsWW{J_2iuLDG-=j#TyD2Bxxq7esd8;6 zh#*pD9ZQy7KWJ195hyKh z>I7#!E&P4pM4tQInQ!}$b4jv#kIU+4u&k<`r&`N}Mb3+RQ&6dwwom?Vk~7D)kJBaz z{TeKxJxW4vEA6`HO6N_sy3x!kFu;nN6700YqsdL^Z>!F0ccHr|(PrVFd^z8ilBms; zizhq#>Qkd+1`S{k6V<|6J;O;0j29F7R|3&5p5vTtJI!km`d>`+ z;q{ry5PB%F&^P48g#MR6^l{fYC)ir^T7D#}#_^1ApW4B=!3M^P1{F}YFyg8S6UR>p9;zd9S$GS57Ux zjg*B&6C-SMIqJ&hb~nU{Bi$C}^Il%OFrj3-U`w_}$-~ zP2}!7oC9r%j0~HxLQt=2(m>5vtFm7d^3B_vd9urFXOuj$Au3kpO=&RFmdA0C9p*Gp zcG!cLkR3t^+2KH5LUsrxblABiw1xf26??C^&NhM9BFvR0=Bs%LVTKaIynvSwW+>s9 zB~5+z@oI#6g^BucUP7p$#G0F)=f#8{ihcNL|MLPur0F9GTGyC9cmtX~G)-2nagLA0 z+G@`D8h<4d6ITxesiv=%5i6Zf*_t9IAMa!W2@GOl zTKH_OZLg19Ts|>b{~Mg0G1j$z#AwR(l932gRU_LyF=8EUgxX|tPj!SK)G+7vlc5@ zbHwJ%(V}fLIMD^d=%<|2dJZNhwYHvHL?M(EH``nNkTVV6L0|W4qub#fpjSr#2 z_;sZ$mi`_L^-QCE7zmf1;n8=*$f1ShNwysU&F&hJE>A|smT1T1f=8V#Z9nl+2>!-v z@FhM!(m!J4=8TGtT8xaDSJ@v?;;Ft6C}Vzhx6&KL${lyRGiPTa}LD+dFV0Yx|SnUmuO3{TkaqPSfx3MLz^9 zVM-8YNAH=ZoY7(0G#RncnQNQD8xf-rNBJ4OPBAL8H#yrid<2=HS<8GYWRje^$=TgD ziKE#3)woP~c#|{RwwQxSEhowH&Ccq;`m{)?fq6XgV4eo71RlO05ies_ja?VEDYlM0 zb*>~)&N!Ai$-~b&vsq8fuX=5fUp(uqux;Te z$iSvN2kXv{IhcB~MgIL9q>lpX2ld3nydkhBOWrRZkX)m?<($A!FQnr}sAlxUQa|V* zp1Q+vhCP@-Q=-_3PZ<8e2EF~Xyez&U0BFWf#a}ezr#8G$==9c$&MhJ4`R!YspW80S z_P$w(=J^f`Vv=3>+$EUj_f0>RBCC3hO_cWzai+?5MpQ)0lviMR+lLV}r~Prgx>6TS z#!NPmPf?`HroeH=|Htctc#I4$xf<)iN#Z!^m(s?^S1|ZFY^iGlS}`-R_)Z zySqlUJFIFHM1&9yazzfLAGEIFKzIY?Kym>ko~E+aAlOhjkgfQupPc);vwLzW{^sFC zJ_3A0MGl1WZno_lP8p<%H=MP|WcQIYREOt|jkdkQaa*g9_c_>_lnx@8CZ$pt^Op08 zu#*kVMaVC_0i{oVZfK?G^uJ+XaR~zbrzME~V?&u=r@W8tTiy<*O8qM+!BeXT8!G$R z2mk-cQyj=C*$fWvseX57BeGGS5n4*6w<7D;^$NVp~|F>g`rlvV;pzQ>$@kUBeQ119LSFC<85_0?E?3!WZ#Zg=}!h z*(JFge{)OdivXX{X*CY{)bDMtaxfV}UbU-MhCni}*Kb&T+shocWeA5j*l!570|+KV zzyWx(Vq@5exH>Z3Xr5s^#ap0j)_;m)mT)#sor{3}%b~rex7UA&Qfbci!yB&`*Mz@Ld|T=IabT6yK}H*)m;!wR*hPOR_%#5 zt$GA+K~@ctw|3&k%N-}29m7Bl%BbN{Y;tddc{4KV0Z@WQ-6dYmtTVO*zA->H9l$8r zG#49Vi)?xgq9vPt0DqB9KM;Q*n-2RmlugUyzdASAyqrNY>1PH8*Y zjpTQ~JNww)WMr60hoD~d2J{Sl+>HG*>c~TZ$MT7F^1nN^l^6bb$Ys;E(hsD?aC?!@n&Qd{hH$t<{_ z7+Yi(s}V1m#TxuYX0gT|!Yp7y!_PH#k!`|U6$z9=GiB^U*(M4u0Tt#Kg~1PRx;vql zhQH|8TF#@0{2}bjngtYg$<~C&&YLk zT?-;n7J%*{^%=*FA}T`8iF9=lhp|gU@Q~a*(dZ@fK8cMQ{GkQKU#KGsr(SF*Y#w9V zA4}@@|WDLmSQc(J` z1({i4kqK~JreU+@A}S$BCPlBc7jOW8PN$9eU!RN1!6_zXllrduHpT#$5FSzE5TC@? z)mkR~)Dg9b4O~NYJvV`lsA;+0w1%z@Zwajsn9=DmHuHBN`GmXN6zg%`)_aI^i? z<<55U!A7nH7j;I3x;<1IB6r2RI*B2SSnT7j!Ev(?z{h4_g4){d2VCHJp-=6u)#7&E zY?OPjOnbA}#TlGpNB^Hih0a=(Ca6AVDJ z;7nThRZt5iwx)JDs;R4}HgbAG_DXW)h$k3XlGD2g;BtD@?7>5(oCYPkPRoJmt|;vg zs(tN6^tnYKKtvTU6h+CbG}mc8vavj$=xHmW8Z&!A8AUW^8q}yU$tVnDB#T>@CCC#q z%InGf9(RVU&Tw7aDIRka^~SPSGgoJ!GX_XnSqR|LI&XI7ZzV17h)h?aCc5x;FjX|F zY7s2vPQX1J$kU;rPYRIrGrzP27NvC`)nCs^kV_^z`{*qbFjz4UTZFJ^Kra`3VKk+$ zsD@2%OvhoxOvVLG!9~~9iPEPw#`&f=IXRdkj`zZIN39YUS#tXgt`TbPsMpFhN|%ch zZ;6znejB$;U*1?9bcMfk(DlRvbECXR+PL65HZRHF+rntP!ux~j@FG`-x0E_)SILw- z*OeD(D!|@Y$R`)&!~FFeBS(Y(F#`DDZ!yPkBk=LZ=v+Cdool(=-O)0Yi_SKXpvLMy zS_Du@wDt067gs--meV^*e$c_SH@s03m>*K6RW}oM_~rMvD4d2(n60EWQDjkk%Ltu4)%|0~ax!(W4o6GMCV`Na4guGFQM~{}_>=?g|#vc(V(Yrl7uv@s!CfBi(!C{XH+8TCKLIaJ4%5zcEqr z(Gu4#?M*qoCpe2;j9-%2PA;*7N@8GeclC0Os*S;Imuq{wlErpLj>PkIuy|fE8Q*G( z$M@yB9rBa@mrgvtTU1Ov()ziUXnJa*T-M*!N2DiO!$@LDPGqLmI+08b#Ik#UYwpF1 zWt^5M&kb~?izbX5iKRONxOv%uB$`(o@PX!ac93hU7|NTG54t;e{u*qx!;b3fVIK4Q zAee{A2Q6)^e9%3O|HB8}4U-ifA}Ai}S`-+F;(26qtJJ?>_`lkPuQ12=lKUsSB4u8(`&#k5ML{kI_l&oPAX)Vs zNcMRnNxtfG^$wW*>#h!tRSt*hKI4%X>wKdF-?MzTVp53ML|2)K8ghI5BgU+d@+vsf*{J;TI( z6DuIxGZ^m0tdMX+E7rHYJ3IClPp~?K`4JPdmlY7^M;PWeSRrACRt$6ITY&j^5hrqcI+v}GM2RrPli0{PN^do$91eLNAB&IsZEjJ zUFm8jrm<@4{xBx!RY`2-oD1EAcZ&ouvpEvEkdc#JZ7+TfB|ERLj|GVzs4Pyp6Up<= zjA8uHdYu-9OBj?^JTr#6FLqJrn{4Wf8nk9)XJv=|Us4@eaVDvyc$g8TU_Iv4WC35G zqTE2y!0{KG8}Kt=V+@$N0S*DlP&Ve0#rI;S>x`zqous0A_)AfJ(Vn6x@5fiW;LgDb z`S~nYTXBka90S*%xK5l+B5xYcbOIG{3uwo}UNT=dI?5BN?ilI1rdF|R*bguco6|aH z3-}QjqeUkNDb2UQ5?-bHN@{am?}>CQHxpf?Ewv3}Q<9Z8|0+qX43B_W_%F8Yy3S?O z!utYE*=@J0jp)y)Q!G-NY*~~BZ}iM_wGS|;^YdJjFW#WWhLt3nf`T7bzcJ%75dqw~ z3eApm1C}r>88T;%A;UkLZOAS+U%F^*jzxun7@xTIhm}TocQ0^t(6n_cZibBHLyTb( z)q`AAPm`!Z>RFl6v!CWeGJer5wbQfved2>3f#Q2LSbQtZjx9IESFta>o-F&u<(Av= z*Rii=yTyAP3k7*QP=EO-?6=VPbI@y-Ai!I@7OryAJ=)!Oxi;&1+Y~hs z!C(JGBwOY5j+67Qcjd^mn~z1xRf}93!=2C}ncuW)rZ9NdaAq2oV%e5nkwP<5fN`x^ z=_*82F>+d4Sfby(GPPEI1NzW5Y%oar)WM!0ecdc?|h{qUpT2$>07U9Dw^5{lS38*qj z@U8n?JH;2g)g=?zr+!KS5=+a=ijs@gxQ^)&sdC-}u2v#4)f#scnFgPseB5Q;+@P#_ z!_=Bex%NTV#M+8YzbsYmUki)T%NPqJw@d_Z)jMY@z+a}|PQ({{Dz`miP575W&9si# z^Aa711juaA$B;wb@UZKfuraB1F$t|aSZI@#(BeYG7;%FapzicaDs{}MzXJ@(8y6O2iane) z)Z1ObL-0Wey`{t>va?UF~Z-0fZ%|nc{;Vem-ahC`JGmUn1~=&L;sFMCbGBih>!!#hX#2 zk`+AT4zt?%q+vxW;I}DKX`P}Xl@=-g5vgRsJcQ|}buYR$1+IN49kp_+>vpk*F|`0P zIfGVN0Drov_A8=Zvify6g6w(Ob+dTZq9AeAAGQeuTe&Bzi+GKdP@-T{np*a+Pg6%! zHZ^YETO4M!sQm}fK7VYT9^!jeLhV1W+SA#U5S^=fDos}Y35l(;?XGeWk!}qwrQ-B- zx#Xph9YrHv@UAOcu6-djN1i+YNstU)1nIj79RRb(%FRQs=_K&CPiOQ0HazhmS&&C} zxsvr|z=@feXknvV1e{TTRbHB0aF;7hE`HrrS1(GJ(|?0Z)W+9cP4wb)m7;hG`_1)l z1rr3NDDvjI9u|EWFSJg}dc##AdNb&fH(XbQ4Nr&Rc&4O@K0I9x{cU8THeBYv3E8qr zR*}pP=3Q$ydvZD*SFT@#wN&Z?mZ|cUczeG%17XBpn7a2f5}wV69k`kWZXk*GyUHqJ z>&dCRT#Q5N7hpJFa`gdTehlamh>`w*Wq>wY&L68zsHuqCGAtUbm1d3wafX z1TEwMDG zM0|!N2eOaY3}qk9cmdi+b#mR-I+UI|;OZ#yc`2GmEC9en7JWRsv%udz*`kTqFTh25 zKO;$h2)GGlBN;OP@QKX2bWVCm2HD7pL$0QJS%xx^t=M&LB9Aaxkcq(Be3Ni9UdTlL z_r7baa55;Eh+Rg0;Btgb$}sI@QiigVNpjf-uAyQEt4($?HN&zK?K-*cLr6#r!AfR^ z?~4y1cQ63~+(xQ0l#SFVmICdgACxk~J;r~V=sR1jyjENY+B z!oChklbQS<{vtE^zl;l+NuR^6T_McG_{6ndyoBw!nRqRLkM_cCmtbvsd_KIm(fc#k zE#ja>LD|Y)92T^dBdi3qUE7QDP&Xj;cQTm0oMAP|qx=Rq$fHCwvpPgLezS1E$EXP( z-lB{T(b1~6W%^Oqts;}*Ae%{RrfjAiFYwz8l#VtDS$h@_4 zq6LC{@+Q*>$wmf_b&|G4#(wP@0Xv&hzIJujM>kWBWXIR8=K7ds%1YiwL2xU1mPv-J z#Fv73Nlaw4$y7=+;gCjkCkVH2bQ%ZX8OJJ<1)ciVRUS5{nQ1|DnkfsKBX9f8HB!uH zwQ0dJPY(Uw)m730?~Z2VXvAo&WLnUt-@7~wXCZ)F(6!hqUsjBajICKXn+oq;e6lV% zo0I_ql_4=seHvRetC{6*>`Wy73U8B$O>^3We2_V9#$RMkn}O-jUT5$z*SbNWQb12# z0y9~>$W>2nJnni{>_%3&WxizreBD@h$w)4m;chCQ{@Jxad})!9WI&&*L7@-u9&Uz4 zXkD=pe+Ab*U88oqq#&?irqv%Z+4`BL$)>Rqa&q-Em6HQ%TGEIIwJI3|mb=*tzi8?8Sez%@O-7oa!Jgep@jgF^v^Qo zsSiCvL)Tfp!02aZW8x#Q#{pGzY@Ulzk@%5-gB9LC~N%>b!Y^Kv<=|zFrbjCzcM@G5U%ei-N@P z*dBspRqN*JPD1sh{BW5!_8Obq9bt?RC9EyjYg>K!Ao=Rv2a;q_WlXHrLvD^U%vTG# zsNeKz!37BTjJTitBGQOcmdvUuORm%0vg8D2$&-*1vg8@f(K#l_m+KjYNv#pg?KzTh zOiqz9qjMQlnP%PKhO=1}FwGR1b~JmmSjeDgnzlO-K&Dw2IJFs@#5z{x=oa^2eNA)q zO7;@^(bJ?8I=0)z-A_$Nm?J@9aN)Fu-?-{J!rv{Dgci+)mS^llf)mK&i;rwCG z&mzFr^97Zo3gmW|tBJhpkv=gHs=8kZZ;}OT$^$Mqnbj12`5YQ;q$gytiK=;)+DK=e zlRX+4qxHBfny2gytmZzOr~+x9{L9rxw?Q48sLnEW@tNphRvSqJH3R{EcHzYV`KsNR zqg^RGCBR2uCiCjJ)qe%&aCQg|M>IAvk}Rz;FV>G^cvdzBYvTZvv0kAVhLhlxDMpEQ ztK8lM3~McGN9?W%X4m^{q5)@hUtkqUyPhLP^X2xpBZS=G9+B5{D^@x6`DK^gUbPXA zC2+ZJN-`Sho3rH5eIruDW`+yYBtb?b8`}b)#PJ4`<2A&wjtcRWqu9<2gpZ2l3QlqK zc&CCsvm3fu9a%QEps9CnsdU9w8%}v= zCxh;NU;^Q+Qolbe^$UqZso!fs>UU2^qm7>0QmNm29gWhY@3G5V{ob%-AVK|7WX1f3 zvC`W2YS|JRn0C$fz49!u+V_HbYTt`Bz|d!K^3GtA&8@a}l~$spD&xdA8dcx>^{!n! zwj#9~hQCPdhPAwKguK(#JEQXjBIH|Yt#`jfPhnj#Pu9+|KuYDNv}Cj1B&*cd$%VCN zBu9=}SkNoV!cB8sdxYx1>7TxG!NO|!e*opyYLq&#IAo)i197e zM6|WocqHURbaSm0B25nNZ3ua;#CRk6OV%q>HGZ@}N;SUZs`0s1>g(^qOT^MZao$3% zbRz_{s(+Mjgf1f8_$Wv>68jk0dUCd!U`F;adL;dWgt%^e!YEt10lSkkqq3o@nIBTB zaX7efGph<$4TjSvDq!AHjqcctRHFy}BGu@TO>;#;sMR#kl{4?_SZZhIZ2gGg6guUt z(;iK3W*^|kJkXDMpu#LH%pXck_e_%Z0mh>tuY#_xouK(7L+2pEnA(Azd2iF z#pw+FL#!6{Omi6B#D@${XS<;RZbE4{ z%QUA^E>5y?LU`On_zx=}gvSw~UG}J~N)xtLmfQ&|w4$vof0t(E7m4Pq7G(|7TfxoA zm6;txdsaeJ(_8u5Q`YbTLbXnu&&f7VoU@uL-!KZ~<~wno1l7zWLj{t=|C%Sx7beNr zR<5S<$Ki15d=^&YraOl9o6YEcI56G>Wz8Sr!-qv~`8H zH2KjeIC?(Mf>W|>#e%RXc>Q`}xv^BRHWW^zSj5caBO?Y_Pu*VC$b0i>qeK@g8QQMn zjSTrqg;6BdGAJCK9IUOB3oDJ3fZ7#M1miPtG8oPA6;~K*#c>7>!qU)>WoYWCVmWA%QP&M}e)Y-GupsQNwSmMe{MBA3;rC4TGHDuL9R6+i-MvEHY(`h;yiRzUfc-mO`F z#nGDbD_Vsto?>*@ivb%vO{N1@N)~aflq?DYB*?B);lLJ$Qd*#8YxTjd=B>T(jX19+ z?qpmL-?y54-^vOo@ipY|^u_xB0sS;jmUx(z!Uj?Yx&QX2dHPz`18sxcKhx--SG1C` zh2=f;)vf6PO|hD_q-z{U&S$j_d$YBA(?;xK#Uz!T45xljNhJ&{TfJ!mSYzS6%K)sK zPrw~0=mrUjcY_4Q0S69&oxCyIcwW9R+t@EoGukS_XlY<$r8~SeEkWbv7&An8j-@EU z4b2aW)o56MuJNpB7}PMO%A%N3gQ6X;m~@jBf6a=}{NqSpT9n7HHLelu88#Zr+#IEY zxvYT3vbtxcTOW`kXJ!vi7lT+SiM(HqrHGna&Rk%0#9=&OjBTg)29&6XfSTmXQImXw z010y34Mu_BP*TL49G@bp??PvQ+F?pCwzbM&)`wxo??SKU%;C1mDg;qJ^ozVYrUaj}`qGek;2=%4Yi==`iF$1;#X!+&@G{{d$hOlv=(O1y*T!e(cmL05kz@^jGd27g!?6E< zFr#w-N%9})2ukiJ#wDiuE-I9P9yF;_goT43y>twS{! zsI8GlmqUC-!Qd;b4h3H?2Gl88VvH8=vpR(5fE>CEtm`WV$F}-`HgZ8?xn15^Fs+$5 z#Y!o1gHnnIP4Z9P3(hyHt);0Ho<+1(QD$RSK)9iRo_M3EFpHHEZYZ^I8={bvQ#{zU ztr-svVkJbdt7@sQX+yin@gb!uk4j@%*pfD8B*^NhNN`RYD-w)>YGx#O9THn2JFNl} zy9c2>@Vl1DhXTJ(@#%nS&L1AejfoSrxVq3mq80_7*|>p`uy(7KGbrsUEJXlW1t?W< zzI&1!x7sKO&j)WMdmOzvS!`l0Xx?AnR?YkCSpmf!Z?#p^G%I8>V$`1l0$RiILO$CS2MD;{lHRV6rR{5;A)*3H~s9flr z8DkOe5xI)@2v$HoYt#9xkzpCRW}J}8im3-_xmFMKwz)K`hQYY2I3WqJVjlqesd+|I zPL;aAsR1BC-t{mX$mUS$LRfBK7r^bN%jDB%!V?u6tj@ci;O=H4wQ-^{8Vg(brgf`qKJ0S|F83yCx6kSo7?`RaU8wsfDX+>GZZ4rLx}4R8`WtipZDbjB9>llsct{p*Gg@Elt&43Ce>9NAhm6Z*TGs|qNu7{5?}CkSLrWcerAzc+ zP_U!Ha{qSYqTM3!AUGLtg4YWNqd*p2h5)kYrJxgkI3{`bzGlShVj8PR6Kz$#avfEy zfF|0(ca3c?qW}Bw*F+kIw`WAmD1Qg&X7N^#x|NG2gd~`MG!lFBtq1{ zo>m03_vXu^zrqx=pJBK7-@`~8R{RS_LjL@Y(HRNE;tHA*pcOPolUxgzCb^a%0GvzN zW4vKwQ1i-I6`b z0_xJs2aU0ULkVRsx$b?iw(U;H_l;MUcXEy%rBy0Y^c{{egqOfaQjt2HoyBil1sDk= zEe3?$*3Nv>;SNq4MHDmqC4qzn)M8?=F{3o!ao`Zs9BY|n_s;kb&P?kY+Nn#^@E0yk zCoezWxR*?u0vG8vZ40X-KmOQo$Y(z`mV_UIj>Tq_ zAE4{gKQYE%q(p#E=e;w|N9ucl)iJ{xi@l5iN}m3L06ur_mODO!r0lMCcss3)JQA1G zTi4sGD{BD6t7q`J8B&Ls^^K!Y2zc`hz6%MkQqsO?56P{gkSZjtp36% z3G3M2yd>YLJu@^^1bT_DeS39FeswU19HqJ?&mq1Mex-JS#M*C-2`eVlZ{+>usFAJd zBipN?hQI!y&ifHQ>Ur`jwvs^EbxDz77UF zPSviL^}hqnx}FiH-0_15-~&6?9K_kc5#BpYeXUzPnfASLOgzKe!bU-(Do1eRO;%&N ze0UZ8-+Ye|ghH1OJ?+)yLuY$-`7p%T0D6@ok;jZj0}YlgAKr2ta_?suQ*^894-4Rr z7Hjo3ewG9Q4w2bE8()h09V``uD9ya06xBgpw@Bip_y`vi98DP6NS1xxvVB-i2iVPc zC@EdEWz}dM)T#p;{L4E~6cpqsm#k{qJ}e3_tou8=iGUx0Q5HGkvJT1-4`Zc-e=x^C zDkOgL#Mlq?#5K^PCx#82BflCg#5D}N-x2FqaT3)XD3S=&U+~2L(t(&M(Lyf%-Dm;Z zH!u8dWQhAhl3BsYJWOQLWyQ^54FhO>aN1~xvOn;gBN6}RXAh5;N2W%1&|a1^;C#B+ z#*mYQwsO3?l!O8UAv&QR)nUae<$>~{D>ETy>exA} zs#a~iI$8s2_YEkVrQL)?>Dc)TvR#CGK+;GA@R2NKY|(PfH?Myw4;4S%P;6)AwCeey z_^OLt^}u{dvW$sU8U9xoZYvA;K7-OK=pX`U6$Ij-yvDJ5?gipUR*!h z4T1m(@+3URChw1Sw-daG!r`wFU%sSs>jz=<@w;UEI;td7AI>8tnR+3>*LzAbjWxS7 zo>#^0RPgRhyHIy@IQotmLE&NTt;CQEN-^EktH5Fm(@poY+B7UHIb$>|&&9cyg>M0{ zjLq`c<(={FC^@x}J6b%;+ajl%IH%hbr-BJy&W(4sN!p7eLCR_#S6|QY?1*;{5rF_W zuKt9{{Yu6?rnR`LS!u0OOH=Gj$}m?Avj2{>Xqq~Wzi65|T@YfLqVFKEtcM>Htl6yt zMPZ$M=)&rNzEHS#t}d@?^=KSe~qjRqEqy zVeMb}>>y`kxMJm|HtxFWsn0GJ8THg>2)b3BJ4t%#vww=ahv>^&V9M+QEpR)@o1N-z zrisz43C*G-I;qW?DXah|UL6W(v&NI|9xbk8rLUAZ{Jy;|JMY7z29 zCh~QxfRIB0A-_D+{ixW;N(niX1|X+hu3fAa;n)c?I($A)GvwMV_e61ol@sw#P2xYZ z0%`~a#YyA3ioaO_(S-sZUGgXw5T|vnsDCFj4ajOLhtdd`^QQr!n(0MaT@JtSzrHkJ z|4u4G=!{jkU$HahtTbRQwy%)}?0mVI2JFg;DOChq^oNBR9NHIgC9z?xfzMAI-qzB5U`erDa&rf>Wdv;nj>5 z&cb2_0?0jd_7>&4%QbNit3rP9&dZfwypt7Ba*(b)Jql2D?dfq=PSSrkSo&K+Nx!g> zQLe4Us^+yWphrHE(<2|r0dxQ*@6Y~qq*35rE)Fu;hkf2l<@9p zS63c62A}_?^lDjqcMEy6tNTX1NoSQ=ZOTyj7ew$ql2bk0<~6zIoz;4%72;OPEUUZ2 zjn}x&DzO^JP^c3_-@r%XBYL>Y^zNNy>qJ*eQOK&$pmk*g`gJC25uCt{g>DZLpcP#W z0+d^=?5uLD;}~wM2V)q4sj3GyMxc{C@s4phQi#RmDyKlnRS+m?2Nx)52M3ULtS@mN z7fToq!HN;7#+NrF#c0;c{hoM`HH5sXAs%A@I{A?YDOK%3xw*HyX+UkveUU8SO?_5?wz6VQ%y7L`7kOathzya#3Tchq zvI`5s3*aIy-W(0+rCc&QHb>6{?6{E)R7in16;hxeK!U6q?Cv8tl(u_C7q#6BhL795 z+5)*`2+RXBE~j`GzGnc_0_3VO`OK$ZQpp*2xU#~kyO@c`n^;#!qbTusBk(tVc#*8# zv%<^^*ccmTPMSkt5ODrq_)_f_y5t1c4tM9OcRjCjxQFQaV<7W_Q4{emz3Z8ZAKH1) zaQ_?%In99$-N#@KJ`L%fR?HeE=Ip+a!pppX_mK zW|VjA1b1gmn=e;SbaxjE7F(-y$LOs)N^F(zGjHD8A%{_(U7FLYwM)))eBGT&N zAG*kF4kZN?_cNsUCu9@R9BvSX?}zk{;O+ZE9aXc{$H>iN91Kyto-0!2Bk#Q zZUoR0=$EeQl;92T>5+2H4G^RJz$#Nb|4la)qkO{(C`kwdKu5R2x&tOjC3k=; zo_dpez39a_qCOOLSA8gA1=NR8W*kQXjg5D#Lj?Umqsi=Dtt9bSL>#V*mc`ba+61x`<$aIzirdyL*HWfJo%M%iKM+ zFT5ayR+`ww`a>voniAN_3TRb!GS#z4KLQ=Vs~TUjQvdoz|D4G}Ki*v}!T5m2-tF$J z9|k51%ag=mh69#h1NHD8a>w273=z>INKf=0mW=fncw7d*w!!fpy~o{FJ1k=s!Fq$E zrDYNHh=k62L_+5Pib3lwc3&epFzUGYNUgH0N2t)BHH0YsX#4JMWV0o(V(!P9s;KpR zgQ!MUb8~Ufy9aD4-kH`$PFU(*C`PbGNUss2XEt#6Kp);o=Dn5_rT6Y3m;5oZIIafT z5|Gk$ql%M=J2LkA{$!@liqY4V=sWys1QQuN(^L9gto|vO86>B*-8i}B%e38zvGCmS z+U4%?;(o@V%1i-YFJoP zv#M6RGm6#wM|anc^Y;8dcLQA?rJBTtq$0OI?Cxi0 zzQ@lpxH`({UyUqNMt>Imq7?kBLQ282=T#{D@u>|xuhRHY_d|heFgj+SKjywm+|9&5 zQOq3{z{fx>PYdB!9XrUfO>i{q&ZUWQ@}tMyZ-|F2GPD_~uPs!e%<4k68~HM;MWMqB zh30PLJFJAV%`bpj!A)5m+Eea0L_ezT2i*SM$e-4`vsBE$s;cDiEx?O!dpUv9#q`*4 z)k!2up~IO%nSZU@EbcuspJ%f2}gUAkvoN z9HV8$81al2O(qQyKw1Gpz?%r(J)6OMi9A*jJri7*%6rD0Byt#>Tyx(dHTU#q1(dHV zm78A-NO3!hl!2c?&RC40m0(RX$C^{5+y$pY?t%lzU5Mx1d&De86{qjys`>~ap_}Pd z-jH%tW4-Reuv?1ET-7Z_Dpv)6*GzPG6AKwe%2nMF+>aGS>M>2;kJuO8T^d@X%>?bO z*i;?Htyy>z7WR*3?D=w1a0?ro;i*DB3)sWN)Q+w0Tg6+9HyV`J<+_*Lsp548r>NuO zEKg|wlxD^4fp{rN)J(xPRccXs!y+}gHz+cn8e?clSb6f;?N_n#}$+35e-;#7)JAgfDKA<$M!7a3!Tm|RvY;eLlB_&k`=GH_rq&q`LDa- zH8EZh{oxgytJxvAB8Ov*qZx6GV|d8nZ~%pd6(*}giY*c1_AIx;R&Tn?#6t{~-@Vvb zHQ(e4iYyO&Sf1pq^Ok!^xW2hqy~P!}ruUWI?pC^Zogt?qw~h8f9J`xAi6rHRUza=g zy7Ou_N#Ezr5uaV4$z%K6`8AvD&weRFiv2L@oVY-{yZ5^@1KLqe#*(vnqxRKe6={`C z?G`0RA8N~BiwXFP{9-~$@J@FQ{XVDuQc|s!_W}!eDMt8+{gF#e~7Ftbh^*P(TTTWvqa9d!c|lHt<6pJA_!O z3IQv6>=~cBuTsvM)l$y7MM-F9{Swk6XZ?DKa@J3M=AM#Nh+yulTQR=KSyO6jH-jpN zlO5b}7pr1<-Y*!GCeu$5K$BK>N$~3aFIJh>g{OhlXJC1CniZh?)f&p;@7!6UQBO;k zXki@Flg+;=J=OgCI<{t>SGV<4D`P-Ui!_d&ylxP{T-|dhd6r*MF-r84CCXXR>fXgz zqCN}-V%UeFtbqCeUs}dKOlNTF!(`rvYcJG?E6hFsdg=p5Pkjgin5%mZr73)HPqlsG z>%{dxx?d8T7*EuR^=2p5vjS^@z6*H31^PRz)LNjw$@_Dtr&^%%F`)(eYdzHh{WXSz z7U;)&ss;MbtbpY7BgcCtgq(1Jt^?j!+_>a;X@w45BEj)4k>G*=3G&*L?oz>_B)BIm z!BI%@6DkAbx-q2q6l@sRiyxP$kfOL3(^EVJ)&l`PE1-~KR4)}$jOJC*d5?hG79Tsh zs29yA^}2vc!!dbG_SlD6&3%(;6&M;lRyqXgU|`Xsm&F|h7R#+RYBjr*b4N$P^8awZ z6}}$8a_ts(f!M%XAd^pWCSM4_WZs|df+TCsFe8jd8J?T|bk7hRKvI6l1rhacU|)mX+ft&Ug`HD#PAv8brm%R-Q?D)ugk z@I-6E!z#n%k)SUZGJ4v#P2`aq>$HZCa}KQ!*}AgcLC$&xYenhuDZFC5Ec-uA$S&*P zg5a`xo(yq&aP?aPs(Y`E@`P*R!Qfi=2h_sdf*XW4u#zjV3gr7|ihY4qoRH`8^@3b{ zNO3?9(Z$oJiF@@n4|K7b%FVax?RWFJ4WXLp+yBO2*s82sSwT`U{*OEN9L5kjcQ5Rc zCTT)1wbX-_;-8(HP^+c5UkzlNgHt2Lc}CU>4H6ht3Jn?|fF{M_-YPVxYy^UC$LgUo zlG74At>7#LOx7?r$9uZVdlEqT55e-(Geiz;>?zS(mMV{YlihQ#T+@U~$&b0A0Nx&! zX~_g56q^z}edLcx1i(2*W~6v}`cb^z*mGFi62yXDU8RC*M1M~OIRQB?E2rm)iX(_K-8FV zKgF7pLvPwgIrQW{me!F&Z_C5V;<4>@Ko^UCoTDQ@4t*d&@jj5CIACU` zXN2GYlF>(jGLp?bkBPC2E0WRZKI(4dXjVXaL)iunC5JV#kBX;21t~0mH=P@M%&?$Q zsdBurr7A2~#ZZz3tU!Rz0w^qawvP%6p66B3<8I-?+HMJpULe@eM1R zVo(uiHZmVU`-joHDc3VjZ~zJOtjXz*j8n`n@Ck+T3q2SkewS}&)qGyADyGzXAm8(r zt`F?1QVSQTq;>Q>qv==lRbQLALLMjpi=M*C;PH+td4I3zOBph-=98T~?S$3e6q($` zQz(mYV}?Q1zD{LdwK3!MUhaW?)Fq4ruCy8f$3D5GsuuSEQ~sTq%D!r6#;RpLw>27A zgPj>|g#4$AXJ~XlH}McyH@UW~n~1ljX1|DF_QjVV?AwtQifMM>FN$e)Kp)}jG(7fD zk7hpC&9gA%qnQt0g0NzLp(jqB?e2M1e8R*-PbGb50el@;c!@|>h#xKF>Vc#X)T({} zk?gH#D)$$8JmNfSL5cXYeN`g=4E^nbFOl0XfW`9r$3Z9PJqK1(?cX1e={-G_F;Kzu z_&NRH*KxVDr>9NQ4+!P{{t)Aa7W30LG^!(GdUE)MEa<;D)(~)eIOdk6p^3 zG(q%40L@qL^;K7SMwNQDi;=9Ja=ZPMyL7VxTm$P@^;6T^ELK1h$&7w%BDt}j@&!5l z)H^;?03GgZyZfoBpQELzKM0T@AD!d5MQ|uhFHXRN6JgJOY9cHGqWCh5mve*5wPz9F z>nF|22TjHg@v1m4@8^tv9>n+_#khT!)yk)|RUkoHrM+P?^(h)muDnM><$NmXkrmkjfC3oAg%_jO=eo5SM36e|QIJc{Yk+_0QF*psBjFPh?R>L0v^_@TcY3=-`j8Y4VA zL(X=W;?(B(0j^dub+o6BJUP;HLab);qA72s1@JL;NluIU=-w%wvM8u|F9gY|C;Q9F z*DB%d>@l7z#17Vi=Dk;-6tBa)2;UKg%VQ@OjO{Nz4zBcmU?sX(bBa}>jOkB-mDY}h zZ?Z2Q>**ls4S*ptCn=&?X8@z=6zRd`$*Np`5wsOv)UjWnSJpiIG~8#Pd6?By>#wE2 zlW`XIIe{G^%KE*RBMDAVZn@H;c_vH}X+r(fln69A>D?41EBaDNM$;nw4pt37+gpR6q* z{e6J)WWTcl@?^0Cl_!fE2ppP9NuI31Kx@v`lLxAhc(7b|lc&2b1}aAeSZNKzv63ST z0+^1BLy7la{vU1c9Uo=!JdXQ3DMI!r=|DO?v?O%t3B4qQe$U-=5UOyrAWAO@y+bHj ziU^2eN3fj*5l~UFfel4z7En=|y?!^l=}>lJEx_am`*0C1*t<(K)R@VV!wYQh)3UVFF}eBtYxVRhgOU+=4155DlJrz7GEU)>o|AHMKa zl~2VNK9pgm!x!Ga@1EWmKJfz9iQ=+5yhHE0xDf;I+~^_>mE#Q!G2-9>9<9A9wl?G5 z>P2E#5AK+%CsrBda;%tBW5o7^@ThSPw_c3tn|amE_Tma+JpiQqfJc5f9i09?Bf@w_ z2YWc*+tLW<*Ed7IrsY9y)W~1_+C%m(JoEF&h`fJARY|D$5>0*8gd44d(fsh9p((uJ zReL0VINvpj8(Zy@bAypsd!rl*hqW@ymZ}mv_Nc%!_S!eI3VnSIUvvjIt2DT~z2pFlia^LuXQ`JG zBKQmY?5}DWeC~dGI?Ez-h03(XqM%&BC~IGBVev((?edFo_gAMYcEDy}{@~LPc1$N62`xtD3IOdh>Pp#a^_BMa&@=Ykw&AK&uAC;N{tmtDI0cry?70JX z!YfeE+H3lk*dO6a<7);)bYimuOW>Ze;rzmLU|@s_2i|gd=7QXt?1F}ALs1+Jo`F9E zHRiSM$zAV=;FVsmzo9+OKYjsfYA<07YwFSeRa4K?nzG+))$HN_yaX)lAuM3k91{Rq zHM?ci?6j&T$ z9A@b9cPrju^N7lf5EiwS7nK*-9zU0=-|17mI;96)GM>^KkS9;+_01E3hiu-dO7)01 zI$(eX&?C=-wk_U$o_xf}`2r z-0hLtSn=JzTy*E{>#LZ6WK}p0c_TN1e^vZX)fh(Ti;AwPXXne%&DmeW8RDCoZWjTtTrb}5!mtb+$k=WL7G?@QOy|IoJ5`ok8PxD72;YCg4$)-+ zKr`u_FQe$4-?2Z*-XZyR{R5XFy_t`(2iuz}0VZr0hOE`U27QWq$}gxCu6<}9t$it! zR$hmFHD89+x94M69hw(pPAVNfw~+>Xd@!H}Bb2yy+#b&hM}@=$LWlbSK*e$&Gh7Rb zwDC6BXL#ht(0}dEm(%I=em-?d71R{~uL>~0-ld-usT;{EMACEmmE+&!_wy4+@6b%E-fB@*?P*pm%T#dQQgK%3hGtgsy(-)x60zjzqTjy{|2;*=BvN3 z_hRoUQltY3!hri-5LG-%GUK#;4*QxE^YtD2xqdPj`~}~2#(o$3J7}ig`^jy(5&c1B zYQmMy^B>U~>X3?ib*lxY7Dk2Sh*aFL`vusJxSu^JpSsfVTLq=iE2;%9=i>KRyH~vLO?Hk%JeC1^lAO&PLpW_&y*%cO?emSPJZ}X*qeGkNyL8SzVh%t-e2}3 z-TKSbMnI33>y$yC`d$5W{k8t`)r+Hn_>Yu_|G2`BFJJ)vNU^hp;y>TO7|8A-D8a6+ z;~|s#%PwmuXb*O8zzf%zKiYE`sRm(9@}Y-VY7IX1^K(Di^W!QF008zNmBknKAe9GT z4`QP|h&(26=CXZJkbdKlEB1}7o+xiM9@THuQcz#NvGwNrjnr%QWvr#bO*)Do6x}UA zBGFOwyl$Vw`jBF(qv$aJI|{wa06c0}YS$URIz-Q8qk?8HklD2^yk8{)&a6(>(&EaY zJViJqtpQ7!woeMkwx0}Gy=}j$C?eZ_iTG*_ubtQ%B()IVw5g{G0BPz?JnMh857%s* z!qbeQaG9Ez?(9%tn*y!j@HTX2t_` z+u8fHp`vTKO~(~P`V8+10Cp%)$@rSkM}OOouuCK#x=j}c$R(SLBmugIp4xwW_`mjA zOdIG^BRWm`KLg6?dDuYg8A6~|O0O2xigv#xP-2x>E9MvZzW?mWEPzx^ezj}sihOLQ zk)qcc$d_jtwOE}%s%Znup_(D7>LtKdmQgplEKv~u{b7l^5L8@&Jb!+6Mc%5ZQB&_e zkUN_iby?3qVqME4Hb4^7O88aXXb_YZdWKX&SSAK=L<)Md-(%R>hu^ zFNp{^D>y3vUh@_%F&ytc5doF?AIXWr{#Bl^6$i~LTm5pEn%dslP zW@d`=bYR)}dv@DC3V18W6$nvh@h4xfNARLZBbSX=RMZF)YgbS&ZMU2Ei!yezVwEI% zS8D=0m+y);tO@K)@!dZzD2_oK$BK!7q|8`B3dpfyz#uYKh$3>V*ekv!ax>OwkmMHM zbgUR80A#Gl;23^+hJw{laX^8|Q1Q$lzV4vCtRb(BT z2Acc-vnR1KH1}y;EAkhUjYO>tKbZ{goVE)j*}6QE-Ml1!NHJ>11R)77bg$6zXiiTB znnU@dkqEC_YUIO{he*}rv}Su z$5R9W+DPie)TY`O68jmFh}ch+hyB}N*x{h*!i;bYu4YO%I_kH<6Sm@=TYZQ!S48@+ zL|Qf`ZyUn13e6T8bid-w+ouNO!v>UNoN4SOT&e-#vB7dc*g9D0R_r`zPspQg+X#Sa zRV{f;W8*06PqG10xjx782o$S*UE{n+KdA7{LdFb%OR?M$X>2UbFXBI=hLqzc-6dt! z2cdJ8>{ixZQAR@uX^5MNrbZwftIp@AX)E}$Orthi6-a(rdE`qadA>8tsF!pjw0&+H z^bn4wMm@GKkoM!{(SFfa&DV4zJ@J20=Pxxgruzx*YfyS`KqEYWHbYc}i|zKLV-=mZ zoLk1xA;nk!gJgK>nqVD$fa~H5eSqsj&<9{-aw)K-h1Pc`=JB~LjUn-vWQ|f@lvVP= z`2LProkHNl+Pok@V)H`dzXbB%;XmKz1py(O7etzjf&q!NQhP%ke#Pzue&r71#*R4o zmiBN(yK+naa6c?HWQ!myMxCD%u^0^VBnu}BCw&7%w{IWBBRAWNLO@>L_}K$#Jf&?$ zL%zPP(ZrTvhjdgyx}8Th8Q58_{Wl_D$RHZqD))`frsdlIhC*k>(s~d?DHwSzoVR2}8Bwhn|IPh06omwKX`=(cY+M>qS$GPYoWSceBe@c`b0&d7xb! zipb)J5@Rd#k2)ANqS}kXIPh6lm2@cWXl(MQnB8kwZc>?yR0(oFKx!wW$W}8hTJ zuFU&%Hfj^;tm}*y^97xaS+>O#sSqz(F=^#2h6;y^*5c=ptX5sSAv2%yaf=%KR2O4q z$ctXKhxIfVU)|M6)eiH$UBP@_C1pAC{z`egziaW{>8r>}{A4$yCgI)cF%NLo9e6)L zkp}Q?<$V7C1Mi-ZJ&byq_J`oK20z%#xSc=V)2L+oi=s!Ke=CpYFhg1s^88FMKc1}# z+)w=5Ud9C5PZVhY&sNSW{}<1(ty=QbJ(X(^OSGzr+7plbeq;yib8bjc#kjdYueuf~Sx3dfc{*|-(|WPmY9UulT#bBVmjRWVh* zn7a%)hU+?7MWtwPZOK5RSp~rs^tG3GWY-Ga`Q#OjO!kOChdt+Ro;Awo!jJDe%yJb_ zd||&i>E`-PerVLSINo=#@sVv0!OqX$4bK+j4>4+mya~#mGB2ejJEqbFOL_WHL+(y0 zm^|{v0%b9RdNePXVKnD&+KtMLu)xpTjZwJ-;FEawjY=%Ga1oN89}Q!Ure87S&LsHt zJ%9IJlQt2&gK0dY$2$1Mt>C`IJ5+u2>**M&M?2&gaVc<&NOQ=YNfAShIXAQ$fw0Jd z#W;NAu!=)Ia#)4%QL@3vi*7CebaHHS$W2NWfkClJslpDUH?K3?F!_@^47>Om$GQ_N z`*#DDi$c2;OBaO&x7CE>-`2gppeo!k@Pi?D418;l9RoqC%zY6o`mLbyT`xgY?va$m73_kd+0OD7x0*q@{r*hDV>Z@O`_&Dzv| zQ>4(2UU0}QZH4x_HePG0k;sSMW&EwDIk`F2XvbdV-Tbc8^hqB@m8Kn;iv!YO|VCHn><|RW!IK zrWt>-0i@Wi(`LRR<)_WPW9mkDN@p4|8Z@HEW*K*|IfOo%=8W^EmZn7Tnad0t zZ&z%Jlb|)}nd|0M%M8DN3q|P1kdB zl~DuU@gl`;oz|Q_QdDa^C8T)~$ z#=y0~NN4j252(4_fts5m#hEEJ$H%pG_TU{h86EhQw$4G~t2gryB%sH(cUW5r|5oh!e9i5*#@Fn?k8L#)w14@9tww!TC6GLBEet~5UD+kxV@>2wZZq1m zR8kE5rS#J0!XX0Wk`J>s2}tBcNw;GvKFr!KAXO9%PXypSBY1XL!+0jXz0(b-@AkZ4 zP@{yna#(^3of7q5O}TE0hBbypPWz5Q#s%kFfn~;v;NHl|=$=dVdgg<1R!G zc&cMHHjJ<$tS0Gqk&%`(RSs}GTMdcjXFI(R&Zq7&hVg=3#(XwWW#9oQtSC(x6dw2e zMmvqoF2AG|eDN!(?y#iN0J|7JhT6lsukttL*Nj^)Fk=vLgZRQA;szH65#x3Xd&50$ zXtr4RcWBqbnhPH^*8l%G4Qj#v9(66!b6}4VuCXVG_^M$%qM*Kpaf>Elk~+WiurY`o zP-Hj~$7T_Pxcep0o7e|){t@Fb_5mp-nguWXqg^8n8V(%T){nVx8w|(8*xv`{%&auK zOwQxA9mAMD6e>i`zUBI-{x2XC*I-r+OvU|mkc#{3l1b``?~L)H7;dctUUt=md!^TD z4g0cIBo{VjM?xc5okILw1JdOFy=Frt{sAOa;Mbb*{rikQK2eiDFp}is91}=R)QsRW zWb9D9W;=#|z8@CEX9ecL3(Cg&P~v95pmhLiipHiY2SKN5k@u3^rA+d3=uK+syP-P7 zh9J>dR24;JXYr6AevmJJ#>hx|NkC~U-=k{Fkh_#|n(_o;7~A%PfdwB`Ibhn!2G3@P z6+{M8@>9biYzGAt+uDOJx#eb+$M}SOK{9LaJM#2Thsx#CPf5c0H(*Cz!PJDU`p-k< zb&$#t(OKG>6)b?C9#CUmhw~-YydaX)hUr^=iZ9rr{dHfKSU9 z(>ggvYjJ%4VWVwy8852#Fn+#+qXi(w4HAGDx8hO6CA}O2g+RDyNd=nnGOYdv0OI+< zmyJ1oP^e97=ibMF9pbzC2SYvA?r=nE5rj)rn{${{o0BA<+EVAuU87GQCe=2RqzbiZ z_mm^tLVvAI878$hg_O@eW;EgFvg;-3+lFzigQF(p2{pH+9OMuAG$&RTwJAL7H6wvh z+^9GZ2^B|0Ld8))S|`UgO4z3|%`T{C@%-a8BSCF)qtK+I#&z~35dw90#?svxk^s8< zTK{vHe82H;l7MRay&TEH3((l0L*r?qBHHLbTYCGMAOOAf){_f(WT`8Sr55;Go1R!u zjvY5B@S0oZQ?8~0Gwdu)q@sfv*W{_4hP2RgAn#A`hFgWaKy1ewNiu zRRYyLNV962Rsz;`03e=sI&N%Y6sqd{^B{HJslVe@_5@)U>->=dd7;50Bmv09^Z!0D z3`U`dz39#E;UFSDX7hpQuB}%{-iO`_mObHxGK7g&Nc5MWD-zqXz9y()Kqp9nhOXxh zFDGo|L_YP0hVrfB9kmnH;896BU_A+@`d=8M83p*NRqr-jGT&l2GOxXa+E%ZV&@qTG zj%V_h6B7O69C@)pGkfNoF)qMVdpMrI51xk~J7@HaqXVUv7I;W_vSP2GgbVxcWpwwAAqEulyYZwI`OqfMy z?Qmeh0V;>(thp70IBRzbD7OE@!_isuth{2t?Y4_aZtO;jM@YA$m?WUvac;QztiFAO z?AUgYRP+qC@hKG@<%Opn0Tsi|rh5Jee(0nz40en|X6tHGpocyIrH7*g1w{UAe8?!k z*OO@T1TMG-VyrD>6SR#Ev5|jh_J1`*bEB}+EqD%1W{}L&5B%V7F zBB2+0eT4LNQ4|;}_H)>C+bap@16wP>LGeDUb_QN97W# zvk`!SE0Lb({xxiH!4Tm=m{YPcCu_?(EeShq=5&nq^wAva!(%tycAIva_~#xPfFxQW zu^tO^j1&QVSnEnnk4Wk*#|1yc$`Z8`!`tDyuJ)O#M`*}+Tj~q}%F*u}AqTioBjhN& zfiQprTv2=%#stu7-#ET?T<3U7-wWDb>8Q{4kuo^IJzk#nUsT$!y57-Se|V%EiXTuI zyj`gqni3AhyC9Dkir0-)oQk3NqAEk0;@4$ZZC=IkaLB(SLE*ng)n&Jh3b2&F%i}d- zl+RM8-05hLsA?isYW;V@K&ME@R7L^VhSt4bD_pbK|C+E5JH4vWzC~#l0{ho~gY6CB z(T-OR4ia(j4R2K1GK32tkOup9H-LAE9ea$1!%46jMIJkx}R) zfRkRF?tt0N`X+7JnZTSl?4R<_iP5QF19PI^aeb6@A3{e%1ybKa;L)!0;`)wuEQ%ze z_W-4Y_u%DZt=2G~H6)o7&-F%2{C5PV9uKY5NEBqwL35mDzQYO)DMo5mnxQ1zj&$Q znx~D{Ri1*nDC1I*Qqra3P>Wuds+uSwU8>`P2k|Ec%X!Hwm*B*7h9ffRNs)#6S6c-@ zR;uM+;X>&rLn=hJh=q;u(dOunzzvM} z2#iJ&ls}R*M*1TuBvtq$dcv4;9ES8U(ib^CTKXdKW27$j6!{`oc=HHFW#2@i%0f%Wbl+W zjxX6V!Ye9ok)^yvBmtF&VX>W-^6n?8sJ#2i6Y=o?zF&z+Mg;Vaa!l5#-!f9n-g$Dqv_!xz% zHWLciRh#j=*vC;_W1kRivC({B)%yn|K{T4u=~WHwGC!W@sKu_5G_0N<%B!9~v3gKK z?LtH?UUh0%75!TvA+F&DQYaNAg;G(#;e5x_i~>-gtIPU@YgC@=ENg6l1vefmqkN4? z0-(2|d=%=_5p134HxT9#e~rdzh5kGI3UB=)?0gqz=D+5{M>;b3)#`&Au(1R!jC?Y} z$3_dN>fBrMeuEuHSrN%Av<$CoOc~;s7_~saubsK=wq@=oE5L*a%&fSwv${UhVtpnl zhpZoOToA=5^u#3xtd3l-lF4?FyvR=`TzwQv@_Jo1_ZD8?aE$arqckv0Xux`RV)R%) zvGIO}Hv`Ftz$SZLK#AC%aZX3Nrhf$p#7zy~kV2xt!P!=jzbP-ctXC|%xN>Ez>M!u3 zhSQ)9@g&G;f(Bc4QA*{``t9T7#I52uWdLZEVdKi_kfO)oSOr(Cl?-$A(E&Yn8fDP0 zyJig08uIxCjttf~5PN!g*jq{LqR$W^41pe7HAOF4b=+r4991`?aGnU4v7omPX% z#u845;R&d$0S|Z;-)SKW##v_+_Em8-3Rw<+;hb?LDUNDdTAm=Ad}=DZ)6pCN>`2F5Y!Sf-hLl$}XVEz9di1$~@moi%=j*YK`!xOVINoovnZ{lv<&mRT%H!x= zA4glpJL*I!j;uZEFY)8!9sAfz1YrO}Rz{CvsN`c;?<9rEl5M6!0bZa7g67l4$-ZFp zI5~6wdNhYU3E6Sf?ekRuIH4Isd$LMyWs(?w4w~6BX|m(KFg?MI@#mDFd3?@hExzmV zIvwMvm+GYovmw|7Q7g>72@H!5@2A&`6JK(&*;KHClg*}Z&=Q{F2)Y$w3(TX%R)~+L zIZFL^spEA&`=>h|VZDh^(3riqgej=km{&b`Yi6d|eBMk)0dpt{WLnr=LA`X{21qET zh4W`Q=CMMRK{(;o27?K189E;8mZ9TAvmFE2vY=TP$*gdZ*r7QNxJXQ8q6F1E#e@uH z<|(98lh2>$$VxKAH=UYv5dgob32r@nNrA;4oLqh;`>vbX zP7JFC+5EjCN3`vEg&Oz&#CWt~M=PBjQ*gQM=Pdz1UPEN`#jhl84LC!}`1&o|=K_lT z7StNv#_{VS$NTILk{SJyU)<6k{e>jp7?5w*8tawD^Ai<@!+x*vJ`HivmB1rz`+2#+ z=IY~d90&oW^YgD&Y!IcSu#PAF!mllLBrr-8J(K`|HCLffIijAa7_PZx-**KL{EPeH zA7AeHiS;6UqIliLOYypq1h04%`N1(YYs30%;Yvq3E1)@qi01zi(Je*Pp5>EE9gU)u zfYu@$&_y4N(nSda0P(!TYR7g)p~`1~H#9l;4EO>!h$$kn`Va6cT&K_7(ueqzXRmdP zVvi8+(Fjrt;E56e^xA+gBCEY71wKlOV4WWMUjiTZ30!5pqmNjd<<|NEdyyc5c4A#O z=Mgz_v^_j~1NIogh6C zSv`rWdaS3eDids;QpZk40jdI+pdp<$?N1a$|J04clYa|tcyve_f8|_a7~dHeU5n)r z>^MBpM(eGTw|KiPj{VwjetC(xr z;_fRToEWb|9(I(n@QENZ4XWaT?L;|T|2shr*9TiTBl+GI&UP$0FgpepYXsz<@TlW% z)-q_;rYfsg)Qu~LK{dW#2f50O@1&F*-#?u|#&=Ofj_)G{57&90CmbV_t_Ua{-%lxx z$qddRb;e43q^ghQ@jm=Pr99sN9 zRzv{4#vTIMoIFelPoO{;szQ*1r`EaCtW1<{s-yjKDU7YK*ulV8TA>{cDf#YoC{KRsmkyj?l z&U++JebdoiKMjaQSOW;)kV*;QkQxAp^L+H8BSvEsj9q$u_JVM2q72p?=KbDtWO$xA z;Hajtx|2XUt7(8NeYHtal$r!CMA17;k}JubNCL{zZc;h2^qS-+OKZR^WT`nx%0eli zECGOce*KW+ZAPKK(MeC4L}Y2gGmgfFc~&2BOx9R2;SVckt|if2l7J!G9j`ey>RTr9 zYjt1`(l(NcV)63CdQgg`kAz3l#oa3#Cdo*`28u!K0Dalg*ef(a1iW7=5A|FA8UxHY z%cqzzb_XJ%IZ%;Mg#mzg-sdgHuZ%)bh3B3b77i7Sp*v{}yz<+Q5iE4FpE2a=w@sGT za2rXu_O@dIOCSKzU~Sa}05`$M!CK~L1K^g0x563UI|N?1EvW3Q5}712khm1A`X)GQ zXt(jKkHH(J1W*zRP}TkqW%@zZmvABKTI#=OKZ`p`?p-VghFW&)%d<|9dVx5K6muhS$k3p!=O0ObR|&V z=%lshZ=P{%^eX}ygbQiJ)2fP`wVU9MLfDzGBDFF9^(;(T3JAsk_AKwvRVa5KWFAS3 z(C*;7eguF2_-Df-i69o{mWBAZs@}AapHDYC@SX8>8Op@}JMS2;E#u?Agc}J~5Q;eD zmJomxYI9{~1EBYY`j&j?yuVxW(yttq{Yrz7RGrmjt6$<%C$QRwjJB4#Np->TbML+z z{WP_-4A10m91S)0CSeV`@Yg^Y;>Pmys53#b_l3pYXF@X* z;CZ5??;K9{TlwV@Wx1bdxj5eLdq+vAZ3=|KN}leO#wx>?ckoo^5=)>ya|waG(wPY; zG?3K`mS3+tg%|w*duC|%0M#c+9wVkmOa4q)301u%JJA|d{b5TqYXCTS*)fR?C9I(4 z9k7}H=^+WsK@z-;{L~fb$)=KofJR<8#WxUm`^3n5M0UUK=|o*;0&LmG@r+WzMos~$ zdm3U1jGRBn_7E13>HDWhbGe@+sM0%V=?wnKPjF)BZITmFykW`x21)SB{ngKoHtZZp z2$1`95V^k;+5O}e!-5WEq+ds{q2QD*vW^a%Kj#g8b4+2;cPSG@&a2!dYpe=M@N(Ys zcSk2ypCkluUgxf|HP%36FUvWQLCz@|r^ul-S6)By#o zxca(1L}8nXD7Y=m>F;+{oa$HYt3#dhS&M+uS{6TSb0)GZ0{5!!#W3es){7(rsIL3e zvIg5nWG`#5SyQFzC>c~81t__jAm;Rnn;Kg?PkGvAy&7C?CFV{%qk?lOn@ji-YS3m% zL1q%TSCCN^ods+?NeB>RZ4f~=1{Y+eB?u*hf>3}GWSV~!oM6sU_Bvq%IX^5pKTP0W z&SNV7}nW!o_*2)jV4AT%NhP>R2&tm4Ndf6wj&!y-*Z^d-eWA zl5-MkND=~?K>d5l^g{g8RHZ9{Q&vNCinBTETt23#dvNk+s{wPN^x}U{jcc9r<`6lYB~u>9iv$}$o;SY$7&Mxcahr1GK~DFD@&zoKtAoa>~)g0z~>=h#xh z2X-P0r3M!gxL1RVYdPKg?>c^#m0MR?)}gveTcSLfDnCQe1?YXD)Rr*a(mKvD?Dg`q z9tonEH$?WbngOh+87c>Ah5~#BrWZ-o=!YRxCl;v=!mn7QdSaqn(|;5~ed6?9_%vm3 zLJoO)FGN6PaB%{Ud}H9lA!*aBO<%Q00o?SJGEJCSo3fi*8c&m(z90~cM$N1F_0=a44I}lgk1-W1VlyX1ZJ{>JF!?2KPIfoO#zu;rgBq&_>$`jV+2iH zUl;>y!KQ#9>kI9gIG+o;@BG_JitEX3MXuxpy!Y`&dOY3>}yUJjb+1)3?2tEG&OgJwVB zpZ$rJ&ROiopgF&rCby0M6_|>9yCD@XO{h2>>f8z<l#&Y|(|~W^1_x0@E`YQW;lL4r}vuKLt^nuWfk(ifwqtG`Za%w}Z2UO(2;-7^Q$+R{$WMhvqo5{j#YJZS-{P>-7=S zIc_e9?CjjZ-XN@@Ft1v|yh;*Kn6s8J=SczzbGkfXE(HklnI+7tQW#1Bg$V$}^G~`t z`!EVs!W;?^=5lxEdRB7=RG3=x$kUT&$eKwe2`Ee(I0Pmhvuj5ZP?*->H3jX9yUp;g zndX36ta<SUUlLc;0Z3^Jzw*s&=Ny+7SnVhd8ZAR)&Es!&s}qBb`H>IeKqs1Hu_- zI#XGoat1O4)Z3BBQ}TA_XId^#G@P|rUs6WcAS`z5H=IE(5;11_Oz{2RhBw!{&y@Am zogxqmR8wY3>z+yz1m?-*V4kZmivt;2cb;v6&s+xaCJQkSM7*IK#Jl_v3zl)^i(?)>9_MTpt@x`V!^(AL@i)dfPqI1$YXE~*&NM;B+N%W&;_g?4&Jy=4 zC8yl|s=;*6S6}bT`U0EAwsR<7kBFn=FR3W?=;d_6nb>O-AG|~uzi)Qy1kXbgoll1A zi)YCj8G>fz2k&z$Zq)0cZ0QnkQ=N;ntPAH^%`7& zEFKkrUwl-c<4os`Ju0B?q?Ok?4@C4nreSLKtGLn)Z}?YdE@2KN_%9OmHk;sJ3V4#E@jRu`c2+z=%v|R-j@9GeCLyzo;q7z zqz%7tk@g6_^TN;w?pff>=es@4>xi#$S~s4y5CRxIW~(|nywo{T?=l;`A--;De5BT& zM=o+cdxKY5dRgnMcLIKf8P!-PLM*F-*^{5+dRX*m0i|w!``LJnuhzzswZv)DY%^4` zS@O|{PTQhuhb)*4=fz%#s>2qkbdE92M6E_W_rgguT@?Hko8JStGAd%QyN{VTwGXf<2jzC3@oJ%V>%={%;tI-5_v75D+`=)o=zK`PiuPL zIkIuWZ{$luC-ApQoj*ZL?q%+5$)*z_(2}RlA+52P@7m#PrjMLm`nWxf7gRIr@$JcG zB+vY~%gq|Ix4PjUiERnthjbN_Fd>*MX z>LZswdGc0riC6JIpa|owwPWVUMwMYEL!-J6`n%ZsoZGbbz&V1h?l|EHmHQ4=?kQBR z>>;kaXTq3r;YwY8{KTc(d7n}B;fDBIs$^i_((#*wE2ZNf0(JblCF&8W<4s?f``B%B z{Y*YDx_e-$e^e>2g4DIXV1Rh7Z=X4`-SwFBf3&;qfK8nKY4RWh-AM!Ty#JsRHY)Zc z?0|l)gFjsr)HmGU`c(R&*jV0%x284$ceF_0mrLLgD~M9GFRT{yI1dG z<1ajx(v*!OWly~190bQO@y_1q{_u3Z?trrqB#OOVyy!^PaNco9NF-ZKvVq07=R2RT z7{-tHs?se4#vT6OQz^;%=(!@8md#V|sSy$Pzqs1`7;IkNO)vsO@}A)xbLBn5`~4FK z>X3l!zT%&NrL-Nq;0cH(?I3AjZPx9={7uGuR$i2>CN!>+3yjS=%e!+jIUJYc>uH`)6Spg|!w)EI(N_ zoaPGZYdH7as`2R0Z>~i1@g6u!+;X0DJGv`!R>K+DrERPNdU?#)rGaaZ8 zoF^@DjDLc(Uq}pSICqn50z4;*kNu{9*k*KT5i^1=JP>`c;|fR-SYY3vlCVjph%aoCDf7#3 zl9}^lldN#md9VLW4NtOOI_kWSwHBDlwo3)|wuzfP$*KmlbI<-=jX(9K^G?=Xks<9- z0ll={-9SpQ?)1u}DpCBMw_tCIOXU*nQ7%4d@VL@P;A-!jUnv3J?Zj{K$b4*bm0RKD zo!)k?uhJ8e)Jo1D@=9rvUsPjFJ!8Jl)DuMsY3eJ)m-y2%^;OmR`Dg!*=g+?5j7jPy z5~rSFxDsJ|PNhPa?!u6@`Umr6u=XRBBI>v~FL*mN3$7i& z$`O%1IpUp}FN44<=Hm*H_KwJ4U3v&aM6}zVNcO6s4g4V`2}9%flOH2y&rBM;avTco2DQkMa&YqI44=$3Iz1UT5viVs&O4We+HA!>V*v|~ zaHVnQ1!rp(qrlRJ#Au+~iuvUW&W%9|!3ffv)h(}3hi_q-lTcD)NR$$hN!P0aKk&Nqdh7HX9_@qnD3^tfB0;(RV4G>6W1YWkw zf?^y^;eF55KRBCe_wjC*ojv850mYGZ&a-#1b!K4TkIv0(Ho*<1l1C)4^20KnkN}Si z^yce+bLPa9!Px_FW>@MJ!$Yq)-_^EB?zi#FSDd}sPC@~>-yX>QqdxA_uQ~I8`>(H; z<=#5Mu*u84?YeUwd!678;NHrA#Nz&uHY|{LD~FHw`+ssip?xEH|AtTa+1ZhOPw*q} z7Xx|!*~j~~Uz|Bado^Tbe@*TmN?UV0S8l(xXY;-m-110(!Y{j{zzDJ({^Hm-1-znG58p z-+S=4P3bT_J}!t<0$=vq&XOwQ081Hnh7^$QOkcoedG1w33F*!}D!#^Ta+)oY#)wbq zyz~bzidW}kuz!^-7VCO5kIFr8BDO5L>Co=`+)$rmB#g^#i%1Q zZJ~5zW~gMMwYw?m1q*#z!~5z0v$%T7Ru(gQGFul)Pv%~N8Ts8zk?xWF>QEKRl>yA? z$`H)NmFYncg6&$aOjpHN( zHiNo(yr$U-u2Lx!mV!qn70=diKNG~mBa<^~nfI|r2x>9r5*e-hdjzcRwu#1@0r zO+>H=!*Cg5nuD>4zM_*D2%X(#dr<`;DwNnGw&DE?kIf|QC~w)uY|oAo(%N#E4_p!e>h8U|SZ+@^#M9cEkFozq0W_!7 zwpAjc?+YyTw=AU}S}fmceHs65#n1Js%Szjuz4hITix(6+h z?)}AVa}%3DN`UsPSS8$OnG3_Ch*j#NmhiNJgJD^^v)Pj^3YxvhKf7ih6wCW`f$aAN zX2!f@N?L!` zQt2q41Y3f4;`9_iET$Jg05|^<0$dwr#`D5aAu+5Bw9koFRd|!vjpXVZ7jKkjv~Y^y zmvOn*{|#R%w`_+jmAmQN=9_P^v4mG_{wU}uOVCj&)eKGmu%p5!`@lo2AM^AG^|##xa!o z05C3Il-r|{m0s_snDI&iu*A?fRFJ;%Y62a$K!4T zBNy|*E6_=b4cb2}k#p|3{^ax6ECG;xgr{h@8LR1=m&w*beSF!R3A& z=O0++Yw37h^7>`i(%BkP67`ij4uZ=oAytF|X7TK&VE!OD5;N2j{+aV^?hLs*p8H9k0bC#JCk`7dQ zKhVCtyw$Ysa;{Ap9OKEEZSDwTTLWpL??9 zs`ncLw>RYQTO2D;bby5?EJXQ_WwCeKgb0es+TB*cXIaqox)^NrDHgYQ> zLCQV1${egg2xs_O6CArMb3*y#>UTF~-2)L_t$sJ-A#2QbtP4pBs01q@&}oINg!U`& zPzVoMYr5bC10d0ZO(3PQ847!+Mmor zi6y4S)(686(Vc1Q!KGhA5(8Mb?p0c$aKdqsmV9T;s5r2&(|(Er4FLN}Q+H0?uKKU+%8PVCb_MCZEnW4swRhp>-HQhqw*9SeT5d?e_LMNbV~e>!4`0d6 zsYW|iVWl!V^l>*tx79-V{`*?Zq~8P>gE2X_7S{#CI(Xsm=(+ zz?!$R0)x0j6`+5MeWF6C{}1jpWBBX$noU@9!f3Ecs1>XdVm))Wo13-J-cXpIm}XYz zO?N;$$PdJYJ!39^bBEcP<&s2E6QsYWBWd&$>dDc&t(0x#{hj9M&_W-De!I+kb`L?~ zYby|8`)d~j`|cu%0Tk*=3UFy7r4X^(EC}7?qp);0M2@!-Bt8n2I6%Fvu^CUh&uqp& z`Prz<1l&6h3Lsfel7w?~lw|V<&2#J!DdnS~9pIDpnAz+ANen<~t&lwLL+NXfWtEvD zGPULb_F!o`z#gjctcPK${5_!@%oG{~Gle+M<%i8bLs;ciN)tYr^oUiw^Ao1QB1kF- zRc3H+EK!HAl7qXaU+vh71uV9`L+i_ghw?t zHJF5C@{u8VAO&G2kaeb3jHktOrmpcnZ51NLXQF0XtWa5l_&g7|RjU~0N51}dAuoE~%nX9#^z*RDu_G7`KKTXnPDZE(dI8NO@5Ms%J>&dDu%-)_z<>AM ziA`f6P(R+71IEFR3I;F^{)YI%IQSc@WE|WfVqG}Taf!H$h=b4O`(A=LIHt%Tg*P7N zo&@^CI5>P*ac}{`IQVga`(60Y7Y7#*5(gJ)Zj9N@1{I4VeDDiL_;PN1P9OrvGIm?d zKNtwr(?Pg$onc13*g0Rw z8aaBSTbQdg8~kd%cQ*JGxLW(~>)V)D{U&K6tFbx&5ze#XSBoiH7SFtpl*ChCHCbFx zRL6Mst7hE_LeIeNX@34>LJ$7$zQzq%8z0){T)S%4=S6?*s+-qJLB$saC`aCCfYLe} zSa`;)!1ujo9?lJheeR87mnVDxc@_^jYCgs6ighVa>c-Y}lZFT=4d_uGq{o1(0Ap8& zZAiOXkGTV}9N!uOKBhRzG-kD23TXVMd4o#<9Jzh`O;`r-V*`&rQHWRdH@6HR$o1uy zJ^^p;>K(OW_{*zODtOp2^N^;mT`kW*!7m2b4(?MX#%HP7xfEI0b2z^Z$EHOBq* zM}P@&%xUsB=GUBk4Bob7!dL&SU6&UvywM=6;z|ETk-~F3dsfSXO;7HfXya!-G=B-L zvIZQh9l7vi>5m_o$t)87l+7J^vD8&*jSQp+b?FIfc)wu-n}&R_8cxK2F*=?f_-jN( zo;u-L1zzhdpq<3ct&xa& z9mL=3H>U~z`3v)Lw!&Y=27Fz|{%!jxpb!>&zMCg|gl$oHc~-1zRNN8;@Dg%wUL#jz zK0Iq~WlyRMvI@@53u~l5wniwixBk!?`NBfxd9y8hBQWce83~PH;^>#N$(QB`b~Z34 zBK=%t#jAzN;SH}ATAS=@9J&qA@X14Krr2m!p7rOzG`$Fr;e|pet~ymkM!9jzwidp& z@e5y@?UObOD7C?biY>4KvF%(mY8EBR;NWSsZ0ySy1eUI%vVn<-+25H9<|DRL3T`)Q za2j9rEet^iE}E&VzDkqI#s2;5B{M=#UCUd2Yt|25ygqC5KTB5m&g|e{QuJZ96wB7L zOO$0ClV9L(ePLryTB!H`M*82L`C~Ymq zszbo$@WH5P#k&=d1p>G}MF{Zy|C$XM1r+}V0oaL+T}}L;`yyO5`M7$n`s^!z9_sU| zCnM^{5)8hEy@0Q}ZkF0;5E(E5l9O*2<-<%Ria_=@q`#dU^eH$oaK|yVzB`X>WR8UKV ziqsMXfR?t|2mtsHapZORch_WH{pr`|D1itz#L^Nz`{1AbZZ7mkhHBE*`P2mQ-6o#; zf12HN<_?M-4QPy|pD`+nrJt)^Th|Ynw=RsQ4X#s@6{&QopgB}QE0lurXB5;W3bJl! z2QsK2LPjcx0zg4=o`3!|FKRXdUM&q^q?8PHjTdXK9DOqwzF0SbH8;&=ZJ}HQmMykW zzU9wreU7c`sDOG~*OcD}y{3N+l`k&Xy5OIGwEiWP?W&Ru?;SeBGs9dx;!deT%6iw} zW0(3#P^wsGI=W7-GYQ7Ts!mc#fSn>^H3Zbl818lLf4l3I)TS!4mp~ql1=a>rKIQ(` za$=j5&E;Oe=T~smw9zElCv+>3eL@daNLFT-5@PNBOZ+>9MAa!+0aSvS507wlVH5z( zz7HGgPr+*OB%4ndTtk`g#yMhEJ8iS)HD zL#6&&5XY;WGl#Ou>p@G@d%>&`u*xDFILNBD)6@-`wWi97TWNY#cXeVNf@W>AUfwC$ zConbt!^VxYHoT~Ys||AmCKfd7+!+$H5?pTg zac&w9LGb$qH`iZ=x)hhuLABQV1bz-V4mQH3^I+>+Xq)w&< z>SR%XPT;u!pH2Wj>V)8zI-vlR2;E2uRXTatp9M=NG%sSa}of(^&nDe%5RGlIZQ#-YBcNw#s4&h1=OW zZIs?{j!H(M^bQ+|f6!;6&-QUETN^+swz2_otYd;)N<#r4O`PY*9j?)ujesq)P21>a zw*05It`FEke`csS^DS}at1Ol{sq^Np(YFCZ;GCi~rH>hbZ z^Qs+P9koq7zoRS3wn-JVoZ{5)>Zj|kSZX?~lBJqnrYPSIP}3$5Ztaj7{z#{EbPUiz z3{)HuLn@8}&KCAw6Atpn5|;XQjY$22_0kWG z*%V+Q=!ZrMsJACYKlGO_u08Mw!M$Cfn`-P|X0(>huPuNs?_6qhGKM$xR-4c+K!-1N zb2UjkA-Y!_NUY5hbqI#A?yk0s0?=#BB{{H%7xP5FY^a5(9@dK28!@8@tbKyApk1AUDh`d-bx)Jfwvnvwppl4SszR?E#6nOamX*GK~OV$^lphfo*+bn)Q{!ygp4m;;e2*q zaQF`j4pHRidDdPREQf~2Fjb$=i)3M2tESzk!)mRLTCc8$$HG1bqxZ3jDABv3ByOzqs5baIZ+8d1F16K>QW_*JS z_6av5w6gAUSnoOy4=ob)$8IY>o4$ zh9Un3rMM*G={OvGvCs`bmLIP-KbCKQz*Uidzi4PBwu!KU8Y>|h+fj={k**pyqrlaC-6&U6wwjPe1@0FBs=yUWBnY|`j&{AvUZ;g_mFkWtI{MO5 zdGy3m-KL$xZ2YaUuAY3wSl2FSX^qCY8nMfS3)I^8L~FlGt!aaK54UUd%_!;uzk57T zyFjR+q9S;JqQ0^ONE#NUS%x-uf~$}vi;Sd)yd{Q~z)S7|r}mt`qF|BC+aj+_avj&Y z@)&hjAu8@kLOnkUEOX*YaRLDQ(O&LM?x93HZo9a z?W7=gaM?6pi5|LyO{b-9m3`gqBSc#z&;6`Z1YdcN>onXeF>V^Lyps?|W!)R7tVfBm z@=8+T`I=9MR^;a#Fg_ic?y7q;YTL}8m;q6j&4dS3+krr}ZIaTgx77AR`=RUku(_@X zO^(91#KzwB(eTsQE2Yi|-gS=ahtS`EE52gR&<5-e!Z0fBmq4Y3Y(@)%2HAI>Ys}5) z=o+6hAL{8EA&EMQ-5k&$FH8O}Svq>Vc<5!8E;5nE$i*(}C>Gf1)#X!`dq)i@@0DLI z-NFzkmTtAGqR}Un-rcRCW|Qr|Q}gtMxFCbEn?aW(7H|Jq=(;zk53}#4N9$31=wjC? zb{7#c@|zL{enY~2M{rz#5piMlM~V?JdnPo8SHSx8OcUtLclvE_X>7X}WmERvCBH2;2l0eaR_=~2&4vl-Q_+H#{RodH% z+)#)348#(VFGs&;i{ei#{Jf)z$l8Ca41aUBxaMhJ@xQh}zyA%%j{KbuZ<>bVL%L`k-qGTR@75&R3teRW7{D z+A4R>9N6PB*w(;YrI5OQa0~V@NdS9*tK}Zi8tRaWYaGu7rWQtpwgIV8sea>a)o056Rvw$ z^=&@7fbJ02I8QWxV7Crd(+hi~QHIVA>Y@;{aCVTmY zq?G98^+DTY0DA~YKy(8ry5SO?_BGFV%GFF@!ycYu!yX=Z#~z;WE_?U@Ks>x#;Ywu` zioH?lx!K{cw2zAxRedaiN|jZliy%b^f`r~g6r>})gVIZ|p(5~`nSFOVce#AO-;c?UKf=4&-I>|h zX}fQCU*mQ0v&0<69!cpFTS}kk0$WP2eG`AeTnCKcn(umDERXDr?{9w1x@GK;)l=hZ znII%M+uOukWeaH)YXm|nDe2Jgsn67*;WMn1P@do@f95E|Wv8=!${VZX*p2bUg&*4X z=D)V=pD>Ih`+pclGuIroo@&b;m`r@t73q(yq%6?BTtzc_jyw|AyQC;NM{5ZzF$Fr$7FCRI`yp`@udxO>KwWA*Z5LmI%_~f@e%Lk9FRrQ3pInl z>}Ar(qz2{(bCeN$z?x0#=cpzVr^J^r*UeFewVsud=)UGicPP=J&X8d#oc5Q(;79e} zL6J_)QATx!qiX3GXmCtFdk2AR3fj`R24?PGo4F?(BU=4G9A&P#zE0Lgw2b65Ipx3Je*Z zwZ^f=R4ASirm^mg0H3jLxIey<5j1kH{UNNB{JnF_x@lwrKdA;>hbsvk?A@+lwqRxI^*JVM@ws&5WH#n{YD1x;(d|O*oI#9*U64 z(7T$}NRe{FHuyw2VVilB6BY`T6Lw$P>3qBqFdJNx>G^k0S@m*!sEoWAe@nQTC@2wh zXn@CPlCy}UC6Y99l>;^#71^+m26`waB!X;kuMWJyc~iWnD@aNK-=3#Zz_IgG3OMv? zd~Y$|zt(3^iYee%tU#xLPzotvA^FqK@wLQe|0=PK-)Jd!{^Q94$Es(_0s{yL+0|L# ztAH$B7RXwuEU>4Hxei$%R#sWyO?-M)es(>+N>m~~^DM9r0(`PSTC}~d!7K~x?ce&2 zu4ZR}LG!)%R2KLQ0?5tvo~N?F7PsOjisGyuv#!R&kvJ*4%}3p93hQ@5pB6fNye8f)+Mk zC1@w^#ixi-j1lU<2)hF#bb;N0=MyIMmMPcTM95}uP3Ue;o3G;T3|&!mWeV>K#4Eci z6m};AZMZl_OlFNBl$VnQ=0)a{Q~Qb%a3E*LukoctDyu;`!di|N&f@$QUn>Z7LZt`_ zuL|eJWEuN=d{gtZE$g!k6S@179Mdme21(X{2ydYAVUQB;$2PX7{@5NdY-a8SDw2DK zZt{Ezy}Y}WqJflYD4CSiQ2GHPK@Efi!-k%9JoQiaLLQ2qlJn5VOFw1H&f>N zO*;OrK8^p>IP~#bj;i7at4-V;@aOKV;tqCX%r_j>Belb@laRd(!yUuXQ*eMXxXMFw zFn+%wevQZIC*huO*vn9uI~^@d$Wb0Vj4mQ&kfXCH7Rp;ej_xAwLOswFkLgko&6Rx% zdG3Yk$^*KFyrariGN1yV&urO3MEm2##h~!OP2`c2@x@Y4WOu|GX4Qpi%Wc4#a%fJ+ z8={df>XtRU_v$7T%LOMtZQX%>ksG(K2Jt~CFOMw~CWq&895CDcj|7+HcC-!W5x^r( z2s@NrxR4pjF5LJ;*@b&y#w$+X;%UVxw{T1km}6w}pdzg}Ex2|&m+YIzabCR1WJNi~ z>l)y(g5)eC`BFZ|b7Hclz!sYV&`tON0z5;0Rl>pXOiNZB}`cQTVb(D+x0H1lH zFaiNSi2}W=yraP^Q5f#u`lhaCCkoFj^5RpT=P_0x?H;~RB?>{|Ah}|!9>v*+MJiE< z&;@p!jqd80WY%1yqHAqktfFi6MLJP1n=Vpo4A(l|?GLR$+}GcvY2`nwN_* zdn{7h1ADPjiih1f%6Vf^)VXI`9&y`AcVNJYpHsA|@hR5 zpUD|j8HV8~t4_QgWW1j9^nEdqi`4GJP8;^IwhyW}>In|;T7~gF<90pc7T)a?;vUG$ zrnIU#+KJ%BT0tmFpjSHq8-SK{a@Q%ES}WG^r)d^mOyRsl232hbT2L-rS*B??cc2~y zAVyG}t%e*>oQ=gNinFncGoHl{ms4vw{tXymS7*U29=37hku$=gYRY%&I97;uOg>q01 z^RNE4Z*>Z{84%Uswhv%Q7j9WA6>gg?R^b+Ft8lvxpZdrajUAPudg3z=w=EIi6K-*j zi`b;WEZny6Z=I^E+2Qt}hLEv}9}z&t+9Gv9Q-{M4H(3=5AHOVCk@go|pu$J$!9GLc z4Ab~R9UBSy!pkeg596s4BYhYPCoM)^x$t>MZFAjX^^J)~i>f`#zvUr1c-Mx?F;SA7$Z(gc(vg&A_UptgW7F|K?`(VpR> zpwyb-gHNp?kH$Lrq(5W?ibZ>w8-7%;(5sL<+^J1o+0i|uyz#PZ-v)y7Fn^4LImS^Q zjN1k}nq-KvcF;6naLuIlWrF>&P2t#Jsa5eeZjhr%5cE<$IR0F*JgmDP%aH5t(lVt> zn;5Z{;Ub?#ANYGDt95Xc60D7q``8YSM&LcSbbvnXWi3fc-*GOEdAO)H*zqj9)QF06 z6!*bLaT_#;;x^M96}SBW5i(y#M_Iw46t`U+9hJo+#t6;QSv8N_NoXM-b#x5#!Jy;8 z71TqRHFgUMHZOwp!^vRypljD`sSP?iS{fpHiPl?E_{b$n;Ujec&zI^gQBk~sE>`(c zoh3{!TP;y58K9T6a#Lf8QuZ3Gl{b)^eV3@*(!oke>b*J6K^iCJmVlFDImbzYhaQmN zSr3%pIbd23$5g=qI#-&?*dUp+YE0(0dO9kl$Izmeqk&lTf5gzsQ8zt?xZbdtZr%S4 z!?oUySbq!y#h(9L<3IX1I`}m9DvenLWQ(aaC=BL)#yM1?7UqwORrd44VwL*+%?MHI z_a_3BLj~=}cXy-v3|VBDVM~>l3}33XjYhcOQl>T0OTAiy2kXpyOO@8-W39A{thY3~ za*+*KF}cV(9BHeizAh4wl8fX>$wl@BeB>e>44+a%j&G1+(&Hl)kG7A5AHF`)9Jf?< zXam+g!5`-sjx*Vdle}a`IBN$j1|F+-DqmVG@yEA_<4f`4BR>gUReqB7nfu8-44KzY zqV!`sKz_{{X-8?ESt_@7fR3GGZAn-Dz)L2%X7_IyzQ@sXXs=4qw`Q0!_ z)kvL8*sEjZS?m0Xjyic50Nf*fMetHuVmA3&A~@|%tg=_0g?I}uqq0Dfqr6~6lKjws zBoM8ep&>uSs%a_7zmpszeK2SjZc*MfBj{~D{L(wb;4b= z=U;a$2$=tWodx-S@|gJi(t6X8UA7zTxG45Bu~7d1g9dm8BRMPSb`xhc1(yE@pqp?8 zgoXKk_qSlN=mBd+%WQYQRLg8Pzf`&Z>M^j)Hh&B(v*lg};#LVZz59cs%tt0WqU6+N zd8(OEopS#S2{7khrQy667wleK(#5J5 z=lpwd%dZ!wR4;bfyCJ0+7u`yC<4YCXIzk-`ZcUae4~?8*aQj%dQR+H99cQ^` zIyM?B<+n2()x;`Rofuor8QY*3GwR4|A3JJ9X=|}pmX_$&U~7kZ7Z(ho0ul|-L0wPM z0I_PiXR^3-IP&l!6(5&LM=NoOp&7@zR)_=E{q{Re5p=4qqG1EB+1X_YAt{N0K}<>N4l;sIb)M zzI2#|_*}Cs*Zkm$i&}&L9)CF#`h;`P+7;R9>ep`=0+I&Z`nqO?y7hI(a>swY^%Xd+ zpT~zdoowb1kDTXcP9{74b@WP2T~K*IBE-Xr5^Jm zJ)HJMrB7BUr@!FP>mg>ImFh6_T#pQ};zCOx3w&T6 zu246T{tjH=O{B}VJI2T-yBxvrDNGoN9+_amj9ux)jmO=L2Xeg2*;ZD|n?G2N-UaVy zTJCa8hR-z|+66JEZ$RPnT*-tp5b(h*u4dFq8PnETRzBJ643TAbJO1mbWs+1kd2Kh$ znYwZED5=-|CDqyPO&qWUl1jb(9jLzCyf;fk^}a^VMWqkl9{jwOxrSTNG54t9QQ|F0I^+nrjf zBqmqwcO=Sx4`qqKu4vp`V3&qh2$oL|I*w$^^A+@bUrwvM$OlgzSL-!9BUm2!1zuw$ zzVv!Aqp)m#%287ZtJ#{`;c{M+7jny~Ijw>+`begPW#;%wUOwVzC~|NnKw1SWB7j?B z5Hi%leC8{qUVk5Tz~@Ptux6PwN28&a0GHT~pGya));ZzGXBY$IvnL(R#EXn3$*Wn( z{IN`0NhGZxP%Y^>tK2RVZo+WNF{d3Bgp-p+3BBzvp}wjEy_AIHq35jb^7I+llO$Qw zn9^2B+2^d|1u>sP-*(0sQi^l1xWQ|KQ+!@7xc#5w3%L-u@CQc@_|k&yD*Ih<+<+Ig z9WFX*h@*@Zt%3)cP~mMYs35ww6cb$Alnahfx%HIezuroXd7P>RwUY#5d-UpU=9V*n&v9G|0)EWbkz@!&skMO z`c)5tYU1CEF7B;H|`$j14VBSW818 zMwcC35Y7bArR(S@=+gB@ckWk|$@eqmP>lt$LmI5VF5uKre!KnUH zDb_Tz@;mNJgv)Q(v-N{z|KA;TW%=J7$=RL)RT;9>swj-r+N8AL9xK6-_KDS6a;qPj z5wiFfaBjtF;LIT#KfPT@=Ks@?DINS<{_rPWvA_g@*DfrCaRxzL1R;HY&nMbzy$FVD0PhdqxAG9iq-u~h$up|h=(NjBkoBfrr zyjfvW<4$3DzYUyPk3Et(zurZbd<;{yE}Q`r(`)`>>Zm%?VYRZ-GEW?f<#xlF1vxa_ zk3(_-)J(VF_L@7!8u_8&tRdEN?mWq$v6=~Js}>N%mTsAGUMuACAZIPHg40Ba9P*b4 ztRUm?eql>wb2euO`ESlFk;o-4Y9uUmBgt1eL1j~APoezzEGB%&Hz8Ju0dL5PN;*uMt zC70Z)dyL#s%@r-D^oBT@6+$!OWuF2tl<}Mql-YQHnf122)B~8qY3z^nTtmditXXDd zHeD0oG9$J7Ce(QaK2Y{an6tXr#%OApZQ?TfLCY)zwe3}T=<6=>9 zIqqvmaakbPnNJ|xJMTfMok0NCw6%7pQf#ShY2_L&?y+W>mD+7hfJ-d}KYSlm)Oo}# zv__^Cg%OTe!+7<0F*9@xGt!tf+(^4-LSknAHBv-5D~SA@DoUs(0=R_o08#i*3j~v- z((r|h-{V~CL~GV6vjS?R@SC~UaQ`l2Z&eAFOQM}ejiGW>jI*jpWHhx}4dL<`t>i=V zvNZz+MaYzr&U%@Uk}*hrRLWUf4C16wNXh;}8ej{_jY2vgAC=1rKX1;pMdS7rP4vl{ z!Lmd-=hxZ32R`JU@vgFBFK5xKJ>PNZ9Anb)e9aoB_~Ts#WK;!brdE)4%JUVRmBdcY z1j^|be>rWl<+NET)Bg8dlVp>sSt6`IZDDQp71oYdAqVYI#kt9h{#u4s1ujc|9mvp% zf6WZ7^4DHNt5(e!mkAXzi+(Lj$2!Z2qMRzqrU?SLp+x{u{322qaDoo}!$q#wL>Ja9 zvzFFT5ir8!k*3ZTp0&udCIj-wpKF3?r_^-52`9g*)N)o7Z!o&r+D39AO;keiU0|z~ z30WDh$_90urNpb8Hi}C6iz?9;)yrSYqyh2OWYbjFT(N>R%dDurv_Q1y>byY3^(&s;muU zb`{n#v#Sf3V0Bw*)c9#N!)1rd_jAhvyJ64B;h$Yma(l5mIi<60rj{SfGHYetDb7ey zhBJgxYl{FbwUVl5W(i;tE%J?4&RZg$HOs7;_0|MV;| z`OOn+)iLg4Yw;CZ^U#C-ojU{-a3{gmwYZa@(X6pWvZt@K2`b%%eVyw;5~<+4*J_FI z5rtWOuK8^6mnM=_29{yoO(hwd`xg>U#GnU*J2&BhczQ3!e!jfF1h95 z*3R7Wt73PGWZD#B*C|to<*dL+7wm=rZVFY9EwvP9RFnm}J6DTWSR)$jVF<|j!47(R zU3S^|yU@b&QoC}!&5zcpF`vrF(+VzNGJ90KnWydpCz0uuKAFVU(UEGP7FE-`PclSz|% zhsh>=onhjZZD#`}Moh2vTL8!!79J%r9S!cV=d(+_)lZIh@hr3g-b;A;&j< zs&J9@>)bl!8K*m)-Q+~4bEqha)%9EbOuapg_(o+!Kt)L}72cjUH?lPc8nSnFcMZ{! zQPYmG={GE>JP%0hSElzj^@J~#VKlik>Oq7o+dp&Bx1qe&A7%#)IS=S2oe1E@Q_t>4 zZQu*z$X^4T?}=AgGkUGCav;nC-{4Sqtq=s&vwuvMG|kHa#Tb75~#!uFYg!8_N{4+_XWgEJ-Vpd}!Pl-qS` z3V85p7_Qld?n3~V_vd!k7TEHx^0M==yp@_xa7vZ=KMLxu|B&rek&I$ zM~#Hc%wm*DaEUvb#WJxa_=;`Hkj#tC=qbmJf>gRECynm!O@FC%XI<&C-kz$BcJ3Ba zS<}qQ3qDBUl@}1<@|tqHSg@3Dfo;C{mUE1eDzCletSmM%;#$|fVM6=XD>RtWmX(Lf z-6(POJ@X>+Stikf1iLl4# z;6&#~p!f0bI_ro!j5F`(m^D&am}-{Fa=q$zi-pTM?>U=gB8{(D6^MEkMYEOfKd{2g zi8IH~d~0TTwP_NIz1|7kXcq)<|4<27!Uc))z$b>Sx84UWAIO?zQp?SLihxmGj{jIM zNNoNZR%}WpJNLmo!FQ9LHN_N0lB5?~c0epBK74|{fqGZ{sS+Mdu0L{i&xF+AZBw2p z&M5I7r-{;8;V+$cZ0U?A=~T(y(=?uWMh@NR7@j(2sx#WiyIrGL0lPYDZH<;cPIDd= z-)p$s`Hj1YOxuw!r@TAexxn0>DnoAdDZlXP)n%0L7m*VG28ixh+{3LHM6?GF6ZVc5QpgG_H!H5>5arWFek9)IJ=2~{?*;O zy78QJ&2@Ikh-T7q>)oIR8z736e?3|-#^g@ZDrrVe(ce8Qie&juEe zJI6XBWV!jyu*kYt$W5^%0_?1Me27&o_1*bSxRB^m1_on{ld+4O|MgQVuwSO7+_4DW zn#|%@2fB;P=*txxVikkpbT7{e1mFmx%#DX#2c?!=?1T+lds)TmzrxO#@8I(ZYkL$E z-?4(2-R_R&c^Io)uJYm{D*yu@V4PKQ$DL{B%?)ZQ2Le-HRbGm3T3yc^YVgBcs-)E}J{LIV+^la9P2 zL@330Hn)u0?~F9dY?KZ6!!)X#A0e~UM&_@oYf7CCI7l8F zfU~sOcB8DmzH52W-k(5gPN2IY09UlHUg@kH5P$PSz%GamZZm}| z(1aL^wdq3n39@--Ymi*E+4;JEaM>x|W(-nX8LI&vddZVA9ak#DjmyrL#B_~Z#gzcm z5~e{9@I+vr#mr51xL}o3xEKwi z2;rgt)UdZfP)`jEKC60AfG8QU%sfPV>f_C#)S= z!6O8a6~I`)QL-Q)V->nwpzc zzyXn~fTJ1CqZkGP6mU2Jzkt(zvkExR`;%(RN%c^q;Ioobesoq04Md0nPC7!~fMX1k z4fZ=@M3O(9mpPp`ymUH33<*ew!VOB!H{8qs2!@-F8UFDjT>}k{e!fC)9^WKWRyr#M z#82S{@cV`v$l~W8a+Vbv8G0I#Z#e#Mz3gv13~@P-n8-xzel$F`%5-I=Ik&2WK59;{)PaL29h5R*`oY#=oYPm#DD%ROrxTUQf zK3pES057BWvQqGv6(oLh1FNhV1)o#*P}q0T*;ZWPRWTr3uqmXm0-^u~Kp{ewC^5LC zc*07FLV>8kEg?zpArN)N*;Pbr)mr8{WOav+!%`2*a5(lLbgTMcNKICtnTJvjZaR;i zfq*GSjo)I&C{{_us24%QF-AcRJ4U&X+IX4!nzK^m7=-c|^%CnP#i()DV1o9dFN1ON z;K6*EibtqS5u9#+PQe>o-egcR?NJCI(+1U|51;qA>3mH{R*z!KjIAoR%wPo+Tb6HC zv1KJIKu-X-}U@(s5hJj^@aneH|u|Qb`Ts&(WUw} zb@h*@CkOw4w?FSQo@h`e+C7=b3Up8As-Dbeh18SJcu$sP*b{p)12m{7oCfuT1E?pz z{N-#UIFx!aLHC3%G5P?|bQnp(g`k@mhVPHW)i~ z=ER())x(DliN4)-)yMkVy?w;QfO|Je449kc!IBb#FOf$|43^;&B?ilYf1_ua^b@mI z*{#I%iNT}n);zI`^_6C4+cdyKH2Iw@$PA`txAMvvgN>qcOHQkfIHJj5X3(vgzQnpd zEq1nU6Y7uOS4!kPn6>V(fy;%YA z2L(w_t#FxmK36$0h?Ob|eVVm|k2O*32LcrPGmsR;{$tzi*v~4d*uN3X6k|Wsuw(x$ zBz8>J53wpo9!4mS!JD-lQz7;z8)A+xZ*lVC(7Kt5`=ly&Lan@cKGmr0X=u?fYm!)@ z!D<@190A0oJq=|I*)()JYe!yW3j)ZCfJR}au+$2-3~`3lBZqzhK8uB`QzuvfIP|tb zcXwomGkC!<;yx=u?`PbWYl>R--k-l=pfFVc!Olt>SE^8g=GR{K1jKUu^<0tu6iUkP zidap}kexC|QLBLn-3k2KF_V03e)w90_svPvP9g&zk*ihAY7!cNhzc3J7Zfr$fc)db zVpggTD-_C)VVA1QPKQf|n1?}a;j+Zk(NR{4A>tTcC@@%?-&xU$6zv$C0^s3X9dgSP zC9JZBTRtuUYl!_>4eF7_docYL^kSD+4&!ieMBOrILm z?w`_DJs&8&I(3$@T8Lf$YvahW)`vcgDa^Fqsd5$1P>m>O{c4Kq3>yvARW(#s861YH zl8hbNvIGc;zKQji6=DMEBfOluyxJ{cOJ3=MdYB^BFkO}7D_fCy83}lawyhYpYs4jXVsz zLdNuR#K`EsdR7)~S#wGxV*8oFKBS0&i?LRO57ek`%@%!F<3O|{WOxnhSOC&#r*k(A zW{v*`%7*ZL_@fk623A6Wol=hSi>4(eg}tWq0qiAeC{sI5GFv}X;T8k zVvQ#k!O%|$&@I^X!567 zkN_o~0NvWr*2*QHcC8yK?>DwAQ9;vE>mvb(CzOX?VX~9f#2PJ{vKEx=H2jv59iy(S z-U70P`8Aqnmye2D1!SWgMMC6)8qKre&uXHFf5Wc64Jk<)#wt+~GMHC-O}xj-iTc~$ zs?_LXRzMA*KxZ$Xvr?74;JOP`q4cHhw<>+fpzoBvRQlFVUsxrTzJz?M-o`==JAFBV zPx#aGHnx;punIoxllYt!8d)9-c|H@00DJstE#uI0)^c%@LCL4k6$}?S6x_IZ@>`kb zoTI*++Qw?^(}uRDSl8?P*NcAO1#V^O(U^RBe$s^PJm`K~%PIcSV5zx$X1DGUZJqf` zR%&n6@~Mqm4k907bCN|i<);}L%$nX3#ThDc5ycQdE&{ZYTtxld%0)C}RVk3y-OW;y zXLqY*h9lpq`CrZ5YW`P^wW9f7WhlV;U$NcFHx!27uqRt^*2p)oar2ldS_=7wF^H9X z!&rPG-!OJ}K;LjJ;Du6?v%ucz&I_>j9P&UH>!$dW^_2X~#~R@2Kyp^nwf)ScZdNPt zrKY9)OaS5uOF=^DXTIxhEf(8Y3$pZ0yVay>{cbj?I>Bm@*&p?*6`Qj~UvZDsLR`iz z*|`tQ0sm$2kgLw_@Xc=eG;;8FFle?(YIku9R0x-8Jq+miS}9&1=Ts%WQ(mb$D2~s}IhYszaivDS|D5QnrF+S9P@*Y8ZK!W5wvf&eXk8E%t3YJ#F**kA< zyJ@@C-l~}|TI2kajK;F>AeazDAtIh+6wv?=p5)}rIh~Z3tc9Yo#;XiH0HK6R&>1xJ zI)mXxsA5Apgvh#stq@uH(*^|)R#miMSjb?T$dDnB?j?rj3^5wubC>W85R>j!-DB%6 ztE6-{Y!B&fVW?s2?l649pA@ZS<9}`!lP6!cLLw_+0axU31h7b*T5G7a$q*wL7)&ir zjyqrbzb-$34BObtc&})*wtfaBS@ZM0!@%}Nz(YyaK#{EBxDl{*#76)akw9x%ua)+! zWxcb9K0+J$HrA%T+3OXI8e6Ye%8*j{U5o$#1>YM)+;vbQR@{O zSV71Lt5eWn7#UixILb;Wqd$nlYQNezw+EwjNol{Yn0+NgB_{q&KZnoMLDIifUfS3DUff187?I z=yjO!b11D}e52^mWN0yrMDAWK4A4j1rc?8Kty?7NSOj<^O^Ht2_bSop#Hy0y;LXH1 zdoBdG|3Nouo5S{~sZbj%ijvK`G^`xVn$b+CIhNToq1f-e+~8{Wd#o;T^A6{RR=b17 zTJHzV``#YS1*`$_G>7rD+()$ICRk;PYtiOaUh)%-0Qa}zN)!W08rInHRt<9(+^U6x zxm!1oL=h%`UMU<*N0DiKdWv%A1gpIdJsK{!3e_v1ceH?TrpV2OvO(q>JpL5j9QpI? zKfq9uKhJ?r#+P%^9c5kN)`G9dhJGgL3Xx9 z(ty@SfM-C-Yxmfzyml{El?JB!UN$iObPwqDWaqtVdip$TMbp!EPyn15_2t6PtQICR zf)0Bst4EA{$QdEcIy1-GAiiMrK;`Y%lM5M?q(HAHIh2$wt!hwi*=?Rx88$$VhyTQ8 z){gp=%KP*k^~nz6Npj(Qt4x$089RtGA}f^IF^Ghep^~h#z$#;$mwgw&U2hltDW2sN zZz?GoNpkc;t4iemL`;6W5L`Z|MFTz07Vn2zyy)(^Ig`6*9>wE%(G8NjkKPA5K<+*U zpUBeRe!xbub>3GJqCNNTGrq4i@86d%1FjRW-5=KJ#!;lkuQd z+#WjG%cPYcfaR*nG8$1odT5;6XjKUfK*N4D$ViZf z2I5|{;F|^u4j`L7w$Faev`=mBY4eS>Tf{ML=q*z_Iesg?5M*#ICbzu29>mn26;c;0 z-i4vwF8GNlmx`N!T8W9%&|-R5iD?p}L9YQhiRoSvep2$1uwMf*BqSvtl6Vs0qfJ(K zpU#q~TK}jH5FD1{Hp8^-TZV>&v|Xlcfs0wcn%uC0I1;ch+-&-f>~*R|32`xfIZ1ds zgM)-)WbBR{!Di86^7vMG!}uF3#Q>D2$S@dR+GmkQlBh0s?9CzMsvff;)vSOGRSqGi%v3qDO!_ND+wL*Fu9wbOcAbYK+;L!14|6x*-@9|>ICWlaz+R*Di3 zS^^HF1m`+7xpGjetdF~ZnruM<@^)Hmlo{$T$ zN>^vITsS_d2y7mJCyK!4fea$>7e89*4vjRD{rAHN7sJ*(0!L_ohkllv9DzGlLu99% zujZ87%D6)1f*swm$@+J!eCo#5ikd1#T%~)NE$BhoCcwFy*S~f3o z7?$IE`q%2FYf%&qOd;tAMB&N@>?q9Ys99OT11bzd4Lb}^#HY>D{zIWCePLtyS#} zW$$5(37VBvIA#qp#AF7>5DZ^l$lR$Ck8tzmoupC2BE#jHjjN`h;4M==7oK@vn>u$%BJ~S7nOBR!@9sxKa!D}q#Yp`61I+ajkTjR<0=BkrYjs! zJCrA!wU!CvAb@R!Cztm4fO2V%83GEMm-e;DEoWc0%9(`@&N>hKXd+ls@&=)D%?-~R z`j~^VbH!e@Wr+(`H6{RiB?gGl?2Hp3H^u=pFFAGrUOI9p`S*Vgs0834h#S8&|Ky^T zCb}?ws4H;?RafFzfnQe!s;&%THK;57Syx^O+!cGD4iKTPa3a(d4xp~gx@vXL%b;pQ zO0*3A@y+MNRK@|u2;7w-SY=5lPX7!UD~FP+Z;#B{o1{P@zp@8gE!e43*J$VP{q| z*wc=08(2H+n%U$K%UnAgQo8HDXH{qR7N(pS$G-ZWa5hXR2&OHJORG-^M`ds>|%8(j%_BJ%R-t`76pm(ECK&NmT{$-UCf3i~09{UsyRKa(n9s>3Lh6FnQVXcqEg*dDT zM6m)Q00l%~_CG+N5-ar*FoZl3?NZkTC?ZLs6|aadcbnPxyRZVn4+ZezxR8AEFKo!O zSgFR}%pZTaEcyiY_>AJUk;n*}$a|~+i5Mef;!~@M_?W>7eSt|$TBb+-d^49*tm1VM z`Enci7FIw#fCB2l_S&v!v5%GN9xT^H%uQe}upST|P)80)dd;`$ke!OKN-7nZ2^Nei z0#L(FMgBsHtK{fxu9}f65Xx5sW-*PR6#=|pT|Dt+GEUCR?)tCm!?e)iF^Xd15l21H z4PVqama~QkJ)+f(++P6%ko#M4NQLRiIpIp_s;nNyw)_>f^_( z6c3ZK&dgVxG5(T9K3ADg-4#1o0s<7RIRWYl2T)g5Y6BGj%q!k&O{wm;}XRRbZ2TGRpU~Zl~QMF%I3vAYS#RyS`JD#GWk?k1rpR5PJ%ka z0o0kB;jR{fL#Z=Gk(Qs5J&bTI7q2j`s53+D&J1M*x-;+EoteZ+an*)(WqL+ku~R}I zKwaSks4E;mU8z*e)m?BXb!D(`SDN32%axyxbV>0o=LxSy*=~1bJ1d~B&=nRZkKz>; zC4*TZ4a;%Xm#eBT=3fxaCRnAJ#n|Z%kf6?R64V(Epw0{}0ZPW9)EPJq$;XAZ2*)VJ zqlB;kD6!GK1wr(U5!_o+s>J-YCu>On4@s#~)nlNplqyxjCrXv79SfK$4U)S`y50=9 z0q=t>SXbAdy(s=~mmG3r?Z~P!q%@3NTV#x{D?FzW~kvIdj{!O2*~0wl?3!YW+wrxl1c)a9#csG)UcC)!}!!&{#(gaBeDlR^CX}JV+E1` zSbiK^FhtVVLQb$E`XFa>|Hj934f+CPUD<3!?%;5S(=)IMJ&q|wy^BpqQSadsDe66? zr~$WmH9w}dd9AGKN)D*A)3ZQlcZ_%tDWm`Gl1-^=Xsm0g$n_Jj$JI5P26%dvoR!3L zs7b@^>aH##Leo;Oqyi962>(gFlDbgCwN_MNEl^*L3i3fsR|m7qPfT5(^{Zqyhf-A6 zuB?F66$-Svx>%`JSExej3KU3PGhmT&)*?UI>dGo9b$z1LwJ_AM)pZI!;ZLrcwHLJeD2bZk;Q>!O^ z9;X}QlGJm%f8)-&23Jpplgk#>v(R8{Lh3mLpGZB2NY`_&vH?Boc3V52Jm-2d{ldx4 z)~-**M9qYxg_H3b;31zS+SKgc{V@4aCsz)c*cPJoOif0qQ~05p zfac#h5kT{A5HT%>mN}u8L(8$Mm`0nWPOvq@>L+M=W8MdQgcE6Ii4$r&Pchbtw(}H* z0$iBQc|t7?W`o~&+Jv)487~u#N8NDPN!t?;D{1>+d?IZhEH8J5FZr zX7U!}g4U`Qly=S&rLl=^JY*)9qJ#dcnZO{mv?s4I94(qieFh*Cse=GA5g0LCp-&C! z=UQW$-A>A#zs8pmFR%t{D!TidT~2C4F)Vp`u&Y)ObXX>hOln}pos^xM#z%@c){3UE zX+4U^2E7i|7Ir8fEk?6qLi!p<`VJvAi=ULP1Xq2;N!ttqxBGbU5jb zGr)~^oXy(vLJe~V&}-DAl-T8uXd6egU-vksf3T;=g=Dk0tK~4_Wa1E4GvjBuW{9hl zxW*8XkGaASnQ150N*%}!&h*#7ZgQ67rI+*8GIO0$?kf0{Ru7u>=aAK3^DM@M!TTCm z^Fx7=xAMo-Yz6RCSyoGQl@V3_5mjV}>S;uut#q|X$5L9}kQPCmPQj7+ygA@Ip#G@h z7^=P+Re?8M?LacaUUfyK(+d*(@KZ|guQ7zE6~-$J;kZ-sNYV>6N!2nEe9$Mr8=X#= z%}|lNW-(NY6>o?tW65u^CBMxd6WosJmHZF7ml;d`l9K!te?%7;qB|N<#*)u=I=ej5 zc67Pm)4s}Jny0l%ngvdKwE-m$gE(tzd@&!%!%|L#Srv;^4rU5U;jA^71BSCYVEoJB zvhSMk8^alQBNWb<6Z3=?^!PNlcpllKa2AJ86wcyKXRv_Ne=K~MlE<@YpSfDe660K> z#fz+)6wmr;fQM-Egv`Y=ds+XEkPF7UI*8Xa1&VBi0+39Aw=5G}6GSqrOEGQIX%*An zIn83)V*gqTbS;W$BgE zT_we{tdLMPXDB-=l;%wsC5%vjks_2oM)Gbio>AWIC0~pK7`|5-i{#rBiz=ufcDN_A zY0%^|wsZTCVIt@DKEox?sIUUvCFcgMDXhT%bekuImDPX}HwCQm$MhA$v{_-oUXpY3 z$An?UJa$ILCb~+C@e;De`Vb&X9NG zl1J|*J5A4CNfct3XzxNn#AF|tGC+CI$320=5a{E$8j_D==HPKR37~&#HaR;LItvO( zF0MH~k&A17HUk$I_L=Jye;2n+^u~s^l9P9PK?6MGk|$=3cgrc$s=ybVd(L%r6)$Nr zDtQk;H(?O;1-FQImq1UnvjwUlm4}4s9MHInY6&wB|HN%lv@uz zYkM$ONqMl&XO#zo8ny@9jZcGR*dkYz$U*qbJy=)91bHy}Z00@&B@fp3^Gtg%Tcodz zH1dh>Iev6t7a4#Y*f|7{0|UuYl3nl%SBPQ$12V#t^Iz70^5MUr-`@S*InF5$23?or z9)3ToJlOB78F?@(Y;?t-;^%BX5q%D*+A2o*XXH7CwIXZ)!Z*c$l^g{i1t%66?2nTi zMvHUGVYKo`*^Hx%Qz*^dXO+hQl;nHhfAT$)hz^wFS3n{<$RAUGj_DPJ2@dqnUg>IU z0)mh!J&Fq6VQuDVoMpVh{4UUgG{yj?7l66bed?zHhGxzOi_DzqjK}U!|0$JOjZBiA zr{ELWc?yh1z)SM(tab&sJ$GS>>kYA&b(W0%I}Pv<&64YL$K{7_VvY;FlU@Bidrkggn z@`^efKU#Yn1CX`1M*vwnh!(AVRz>&QK`))RC%=PPeKPhJ&oi?eah{Cbs42&9b~P~j zomVSQPS%K0^}bMmI^JF`+~R6swt=6h-kdv9Zzd#F&=08I z)3^P9T>6I(;D*W7+g-cFUe-}%DjMMFK$a}j63Nepx{J!scEaY6Q<{uQ{lC)y58Z^5 z(%Jx1H*#WdEqoh zdn9;9I=+Wx|C0#yF)-Gi3=F>%EIKnDam7D!r+>RRR)ekq8o&T#B5nkbiR?VDO=R2! z+e9X?`jmZ-QDUH@3CS18Ld^CTDEl@>W0~5m8vdGY=p8hmkoHga*6=}TsHeWPVY)9+ z@@F^^)*^y2%$mW;hbfI~rfxmpnqr7=HD6m|i0fzZkhOv=2KLP29(UcyzHa$9 zXcV#}f0(>+)U`!qzX)>nXdX6dI{(Gsyimt0eULcrh+pvPYq@2!pIoa&IBSB#8=8(p z=tZ_I{L6m3BdWCM)q?gWw<>fyDO)Y^A%~(8Oq_MzRU>_6=XqDGn4hk)ym{W$I(_Z<3xH!y zfZ7*aReWmGT{pV(_O>m?ynSa$nMG_jXqr5Am=wSD7>Piwjk?*I#pL{8cTZ8AwV>Ro=p~gqMbQ81T7?X- zQ2rz?+3uZHqWsBtAe-NCbqj$C9`BA%;*wl)!__b{7yjVx{WmQbiS9kM%1zfyLv-d0 zVgfa#YDuUM6Kv1P+iGzc3h&Ybgdx&-*gHm+phX9HWAUQfUaN&;Y3-Jc4M|=N9 zUQ!zwN3sH%2bI0&iZ?!z@7#0s5>r_r&4Q9Iv2<(pC7K068g=Bpt8b_iE0c_D9}Fbu zGKF*`;1oh`IU~(g!T4HkO>-_1Ya5~$(bS^${RS!sqmXOlXp+oz_e|1$h;5E~) zuIl2HKb@aAohx2Cdwz4(3P^`G0CGCC0gwYASBNu*gK%*zxZfqUPGSKWJaZCq8ARmK zc>MHRJ_LA1>&PCfj%@U&Ym`~}vW)80rXZB{US{&IciAKVgAZM`&9awOx?7Sp zqI9vfMC{vXLkxEvv4>%%sEoJMLMFA)a5omL4SiZNDjn|EbaVKS zWOCm^@+H$f+_)q!nC?>IiY`@GuvHBLk~cXN1Kt(6Ey&%^r#40+Plm1tcDg!JOsk&aVBNeNpX8QGEXFN_s zpoSf)X5dp-**dQ~HnI~w^GMZ@aRQO5xXgFD$m?Q0gOcsfK>&Fo=ts!+-Rj6o5m9;M z;e74{a})F|u6IeXg*76Z+5oJ0m)iDRQHx^04PHfEN)~uEdwz4>73GyuSX=T+UqJzS zr8!rWSNarw<1Bm@tEiG*+)T=P;TdQYIH}rGY(c8_%vE?IReR=Y2C5bx>Yk83`zagd z9xIAqYpz{|G{8eN`NJ&8eui~*!kqQC3znPyXca2|DCCZi@9!Cu7oSRt@|vnrwg7A- zl!N}+%GN8GH9%d13v!Yo+#QTM_+LZ%dR_)7NYg4_wKa`ZQkquas?s#5VQX3fk&><= z?%I*%@R@5`LB@yHwAUDvH0@OckfuQ=d^Bya0lh*+o59+kq8U@LEA|C>bFa$ktKh5M zN#MGT$yi_?w|tMaqE{C0s8+PQ{#CeY9bQ=&i3HR8>tAM#l)4pk3nmHAz@x-T+fHBu z(zcWMMA~*TBW-)LgxmKOE#=zPqTM4!8Y4`;?2ZO_h-S$v+9{*pMzd8h?)KuTrl2${ z0Lg?Wq*;-2c1d?{QRrvrqHPl7#zKB3H)iCONwwVJGPRVup{U|tse-Cx=KWdiv&?`D zX`k`4t$nPL(!T3T`$C|Gt$n@m33iCIEbFci`2;(|)$bwmyQn!8dQLlfrnCCAsQJ;)%&pG(SuNT02BG2$ z(+_@D4)tBuiX7_OP=F5g6_7fdllJM!7Uu228;DR4xzqt+EV1ghUSWws90B-wZ z+|e@1%7M;UF_uFys~jn()pxf|Upr?5cP%k3eeI7MxTpKnh8*;HIkurYQ#Y^Uu=;#? zZaAY%OQI4VE2AQF_;xVIJVEHLn&?CZw<|H8#mo-{tmASX^%M$a9nWK31)D> z-5u8c3H1U7*QlY959%qoM&^{0+PV9Pjl4eM|HfwidsaZqLjh4Z&I&XIDD|Omzk}N; z?(wRK{1(XViZAnYExV06__`i$jT#zxP?M9%U_dC)HoRs#8CFR-nHYFEf)fg;VLO?6 zNUfo~-pO4pvK~UYk154iCm-YP>^^FUCcYfT$xQ6R)rxoab$1@okfX*3+m!*x0dztD zIRMZ6Gwi<2@y{+p$uz&hEympj0w^)tQPzUMOF zPTWJ{0OO5f>|PD9S0+Dy7!1v?tOc3;z3VEx-ny=A zm()M_2K1W;;T$)VV<^lD$hM$>Y^y9Q&;|gdXaMk00~nGn;Tdp8`hVfNt^cf&(*NC{ z45jbIo9kP!?)02u*{h&F-`ZYU#2X7$MkCf#60FbgD!8=<@1kVjr{ z*D&9?p{!sWYeiP@78GC<9CAZN!I$7SS^(#dEP%<$qmrm96a^0GSodx{H2jAYY0Fs;URPb10Y#LzMIfH zrsqbm40!{5$KeC9k;YAC5M});nkAtW&t%qO1!NFVKnBr*6_7zp4QSm8iw(y8d_Rym<002)rN@#)2j`fS27YN zE|0#V29c56Mhavkckqdfsqd z)UY+V2R?=0l9S(YSB?zDA6$E%ut6p5H7B}f8zP=@Nb{!y?YcD)12`1tPw~?A9w=10 z+9~hBvfjw_wX05YU-79;^QS(ayD~L@f>9_W$BZ;`h~A7OOq`0#=*tx4h7%5$7(Hajhwet^3i!qlo@83V z8qr%C+7EgBmf8<_l9f_CI>u1KJBT$Oxoev}ZmI2%fRf(vr9)ZZUXP0A-@xUEJxYp4 z{wNaktgog6)CyjoyW1flu8FgFf|iAn|r|ZaHXew-|H5ZMkz;d>OHbk){sJ z;~iM3JMhK2ZskKYIs5MY&u+_0>$*9`XABMXV8}P!>WEz&3dUwa^~c|IYwT0quOBvI zsrxbQczpXPP1zP*YmFODS*OC_wz{nbyC!taGuZeFj9V1>Z{{#ouwf_vo%0Sr$baX; zC-UF9?quM<>nw1;8}Md}DOs>m_Td6|VcG4kYBlA|h4A{LB(lQ;LU9f7^ddRS=vMsP zJy2BF6jW3QKr$f~go9Dx`Ni%$vhiYfoM_FOQD|s+M}>x_^go4$LIF|9HLKk31=WPz zytJK<)lre5@Ew)(Lk&AJ49BOM^6V0K-N;yc=7FIYV*~<&eL>1w?>l#k(X5Cz_Z0PS zJW|)-r}!C8kJM2Fq&w5F3F*#sd?MYMu5>5h=ANQ=)aIW1%iQU{gVji`U+x|wR%kBN zG5)0*;Gv({?_g1`9J|szLTu8=)qn?}mavfq+}_-Ch_#@x{?Q)mAJ|w2#G=M}i)XA^ z9W~aA?6HO#_E`UmPg~^O)$Ur68}XTs^i<2h zin926cX7dx(2j@DGT55rX@3Q->|MPFAu?SlV~*Y0+k>${QMDTaD5`?eP<~QugF9Xf zVfAQV)1bR*U(+B~fHwe|WACbuCyi$X6s6v}%fjsByObjYfr8K-fMJ?nJDLDub=5tm zKv&)Gm^rG9`8jlUkGq2S!k^4SPG+?tWBevm(oFr+QQq#n)gDfOs! zPpbzeGTiDYkzr2HPM|@(By%tRLOYBIx=J zUw4@>0|dIJY4v77@Q@nQBchdoPjdXb=Cx+!6D}a~v-sz7D*U+se?}yH54WbjHB%M7 zPX&`kBviA3RGGH2E`S|cvwBuC;s5bf`_`{NGILo|r$g@gW7!^A5D7SW3|pMnSA4_z-mb|&7;O4qwK#Y@uYj<+ZHMAv6+#k+#&a-ui!E*H9v<_)|bgD%-{ z;K5)z)Z7_Qc+ug&9eC!44i0U{ZN+p9;sNesrOmMQaTg73HY$KG(hFVf0e`RKBfXiw zhHn<>{bUTT|I2$I&BF_0)S#->R8Xm z9hp9R)mK}#34;fio=FJ4D?>i%*t2WZQsx^69sEJBadrd>Cb9^K-c0WLd{( z!x_i5cKH29JeQLeMKkEpH6#C$1HOf?$&ol zmiynk@&s&TfNcK08J!E+09uP=$g{ax%RHytHN;RakwMaR-Q7yYo(&0(8?2%Dgq$Z2 z{I5nbK<-@PC?OA@a|@aOwEO$#17Uyrzhajmz2QU?Aa5*l-i`{Blg_}LC0X;YdKKL; ze{j@fg!0^tGa_AedlZsslU}Z1-p@WGCas*9=Z~b>YuSU1**FO8|Km1SVDnkQsLJT` z?*0Mgu{3k?NG#K@eQN9lce^0-+xxP5oxTI{|CoZ^-SX1Lj={3i756<@u55Z0RN%I6 zKg-LhGqN=_t}A7m`c?K|nYQBX5c7}w@#}&+#<~K~2kd=DU3N?bw^Y`J-=5AHxjhKE(A`)wos`#hdM8mQKutVH8w7}D^M)^nN&41un*h~5Dc!Gz55n;`-90iZ z78(1=%em#{Kiw^`pF8`)+QOOpa!q`XHqx3~B3L?ayMNC%3b>JPR_#|?yy452J#Zrt zL3ODIZep73?Ce$}CeK}1H=#IMmEP3a?`#G_KHHA^_B-Szj4d{wA8CkzyH`(X` zWK_I*Rty5^Cfs6#qX5kLj6#85f`Vno-(acp=QKI)AJ~c6cJ|}^^7WDJ@``J|T-u`n zyH0&aBaMy5gL4BSwmHm=FBM08U?H zH&5APkgIjSE+QN&*+zvCVOH4dmxn)w$enikmu7`J33zi@K?M^cq z%d!8!{-LJ6OxVI~h^@J5w|$^h+at_YSs_ECu3Yu6yQ-+m_#hGX@fTq&)uZYUlp1e* z?4Brwu~ynIjbu<%;~=OeliFpAN?-p{A2`hVexUk0U+7vim=$E1#t)%>7}aHr0R!Z5 zJJBa=2FrH2`UT5MX206S?8Kia-KzN%t*+;c7|WRs9W64FQl z0RkbAKtkvwNG~BEN-yD7La#QeAc%s10xOC>P;7_@7NVdupFBjR=(8i`=|e@4prC?8 zezUXZ-ko#q&GY*S{`@0eW@l$+XJ%)2XXl&~x>l1PB#_zuqo3b~O236C*S06tiv1Zh zx9^kEy1ZX)dj^Yxf0Fqr^{z+%ERU_YRHyx{riF_5hRPH9s`fvI@{?y~h5c<&UylIx zLgf)eIHB^`JOQ984+Gg8u&{+d53!KD!tMWL-AOkQbGX>A#qPH5*Se~{-td7>KSph> z7bf;MTBnhHw0&Z?kh*SWk8BNIqAoV(MfpvW&BgCZ_AuUUNG;na@t0a%tl_OncZ z-y3V+!CofaitE}3>)U?D?6IZ0=&e+#a)4ZSGotk(94Y#~8H z(sK>cD@lWov<|IG_QwedGJsYrzS#0J7GJ~#v@g#{x38%41SocS@N}okF~z-fC0!ruM5^Akw_FTE6K2F3`E7#`) z3gau$kN+Zf)E4wo_Co+nv7^?G^NS7b{aBTy9pF6E-kMQDFq#q`^+t~y*l-LBKcX02 z;AM>*u!9yi*(sNl`@u-M@zV65u<%3y#fShi3LY|f&Q^E{GPrNrig^Hhw&G0vs&bk9G68+4gn* zF>iQt`vJDjEVL2x9#T**>*bH%Sj;PGZyyFH8+g~Ot9o`cY^V#ZzZUgPO(ATAX6eH@JL?T#-3Z} zSrE@JMvz_@BeWI#cpLlhD1j_P#2~@=S>B=0-Y#XcfYK1Lk`7sf2sooX!-f)B@pv|t z07P`qhVtZg_W346oYM>LY**7c4W2S4{8q(?&guCIER#Jrr{@SL&S~%yoYRk9Hsw&oYbHnoYeZ7%kmCmmAS8+(E18!756H0F3ZIEo$zl_=13$albGn$ zJClSn<0L*M=;I_lEq>u7J`KVIp2T%Z?4f)_k$s8(OwKB{Kftb-r8Q>qWd-%}U%vi^ zX7ajT_FMVq_4Qc3uM{MLLva+h-3(ie&|hH?>M&{SWdaCL9`dW0&BpC+D(Qx^Igyw3 zgNP|+Gek=Kjc@0vhLV~WVL-`mUXWgL?W_d5!P*%uu;s+)BYuVb%J1u8&rb;v|DZGD zXQe@|iJ5^X=Td>D1}jg_QL(IsP7g{Q5#C?Xq(1LdVCnO@_l7ejfavm|OyTm{0)DZ# zy&=2DjBPAp^Q0bqi6U(|Ki0?I+6F@xKHpk28_U>iGXY~6n;|f~@A>&vE@NW^tScj8 z6UQfN^E#feJ39V5f(1JMLGcS6{~-88wT}Owzt4YDV&BY8nPoM6{!0b*vc5r|=Wyuk z!YhBd5XGM@wU@D<6bG_!1>jqL9$h_!KR?humDT!9ISnowH~l7yR<8Xj7p)V6>^)hE z6|3HFa&c)!8r0$ft+*v`OImSVfd*VxfH=Ghs~&H4tNj)>kYJ$*{SD${NP{8{tw?+l zX+`4D;3F=+NLbC-)#R)MmHACh(n~H{pYVM{VbK!Ea&A5*7+3OU!|Vkq=LM8b&CiG# z#MG>KVVJ!$e7Kkht2VaJ6R23aY=9ERFjv0IM< zWBSp?wDl=}>_(&QIach(e9>roGj`D*J7kQ#hZWmMiQ9fxPKHbLCjR>vdzWgk<1E;y zm8i(ZNhW-`O|NluQ`4s&HQy6zTr}S0n?>rzE8iQ%m;hqDgBgWO{D9w$C4Qh8-&o@N z|4x?p5x>hN9=u5|@x6bSOMG{8U$_$cWE6u>BjO65_q$x-Tfo1?3Qy!EfsQz#H`<6< zkAZHDAdi7=t@wq3ZY{_XIMBV~w%_9)=uY?Q7Qz>K?DN<*v#>_A+oGUe{>vY}p%q@3 ztF1R-7s1oZ?E~0biVKN&0eF|c3F8xs`>~>-L)nL<8-|-BzsrdC9{yiea92Y`#g4r| z#V>Y{UUFf78q6gQ#R6LfkL%*sUjFtZd&`tJ#c%3;&kBICg5$a_GJ-7Vih{!Ik?Z<^ zX+3MWuA5XD8?Gzr7x+SU+ubZlLCA(SK|s;lL7Q09lsOGjXDzMB`+A3j>DgDXuqixS zwZiq^1H&^ozD{Y)bbC|y%ITizkjL$&P^1-eR|j>{i>{EVQgTJsLSN^nXV~*%V?_^C zTaY|c0ylBN7Jys&58Z0>Su^d8G#7ttCd4gIKyD7oZMu)!8?)>=0lDFumB`rmj=A;( zKGk8X%lx1dX4_|&pb)rv^RX^1NY4T-iEVqr6*;Nvf*7J4>S?o(MwZ}70reUHzj3qg ziY!h)V8+klsKPyTQ18n@>DPakCF;9?wWx{OY3^#ACtfiGdy)ty3Zt%AvGJ($D;2CP z{I)jy?KyBHj=XAiTlwwpFaiawWrY&}_+Kcz)wjV_S^SnsP{HqwVWnRsp3&l}*E0sr zx5Fb6LK5^0J%bl zaCM1a7+hU2oWQ|#>^=TDkoVYp>##B9d$)pmx!!2{!w9K~{QP431oog}K%!{?w&g2e zK)z`D6zPW1^dDDcG~Iyzm(jEuDk_?;0xEvdl=PC(boNylO$D}$rpLsuRebAxkUv-< ze$!}rhXAN(dWn5P03wj`^n>kUYkplP)+1D2s8PE5k)m&e(jOFrgwpQ>6lXH1QkI7< zhh_GrKa{*E9){9u;GC}vNe;iJNExBDXobCr9{UHs*l1V-7H95kOqS?B$Ye?TLr#`s zeEx&>#WeqtcYua%rY8r zZGeE9w2{zg*k}4AV_;Lvow9iPKPGh6=(z6mjjQ-!dk5Y92R_gf?p7TQg{4nQZ>6s` z=sv8P$-1+W5`H`oVdG;Bzy)4)-dTU`5Bb1qg_YdC(k5mx_e*N}F_=E$p;h-E_(cOE zrtos(iw1TxIU_EQ1*T%b81RQutcc4$Td^@NUl34}V!N-0xEylL;$~1+#KH&=!?H~Q z4DC%_Ik8o(WB@}=?9gnMst}0&60Z@5YjVx&a9=%U&r4AbXGCYhgE!k?Z^I}+Et5B0 zlcT;sMlHfKnQkOJlUeT#lp@KQoMi&~gD;Hp5p5D%#5NLU0-AR#bw*|3xJz z@4RYGO?P#owyTf%mJw?07K>{ZysKFuvZ+lw$^teB;ZYmw_{FE}B_-<>K>QL8w|q=ZH~Y?qqff^3 zr{`ac;T_*=l*o^4wlB85cnzLITU*>B{3XJQ?+6=}!M8sRTgaUXEJT76Q!TjVc!{@t z#y;4;&$^fIX~hl&>S6=>JpGa42Ifx1ea7^U-6A^BX!*i5`Jg~ldei9m06Hk&a!uCs z^?J@eo1L}ttNig^mg1vnRMJy2qI2DfUeDXt>+I71?rppX($qWpoV_kzuq{22FWzb& zn&%on(KWkZc3I0-;~cG9mE{+fjdM7i`DLzg1#R0E=8tQe-zG2DRhZjm9K5QhurSZb zBVL450U^o9yl9`Thg9*rl3|GvqycpH()+hh*Us~)+w3j$tSY{7o4pTFn6Wx0SBcP& z!Yh;KX2+TO8&PTtANG=cRKhwnSn&%37-(PCV#5z(x(Se&ZmkNd04pE<_@Wp{S7WEsROiBdU1iD{#RE za`EHuHtNTxy=u?myWfB^jhTGmVMjMU_O*D{Uy#OWF;o2dJ7&RS_gswPuGj24!*3_V z`I(uwrC0RYY2TwWuHZcS4f|Zk2d#X=-kd!};Kd0Jr~VHdQ2W?jwP14A#;e>(W#cEW zDSxp_gy;r*>>^tu#UvJ<@;d@J=@TJavdsraZv-evx2eRM6(*E?h6*t7rKVW|_f~Xky;L}hS z4%kPqJc19t2`@D7et#%0&2V(lIr#lKJJcAzZC{`j!{aCRWE+s-=`ZwaWKzS$wT|BW z^oKixQ>+@kU8$l<2DdKn*blK`gz2=M&XQDR8Y8e-JJ#h>+wBReSa;C=v=-r3-MwS+ z9I{VmQxsgxGh-~x-nHMNyZ@A9seMqd!w1AKtHU2Z1Q$QM-nCDICtbwQG&k>c*nT%7 z#5sCHa&Cq>#0H^G|uS~Te0J)y-qE5hVT})h*h?z zBeNx6{V7e?@MHVOyjQQ72oAsg!!B4l5+5}J_*Z=DC-(7r)t@q4u6jNk9@0MwQ7HXW zdn(}*XW~=g{M0^Cr z(fVqf$&#pv1m7RxZo%h%VSfldxDxfH-5F7!2zb5j$uI3gSw{sYUf1V@y{A^dqs~Dk z({m^6bM=1L`NbplBpZ;Cb|ds)vtrDk7@yrzrBHd-@iFzd7K)2N!9{K#PdjPfrA_2t zoP@A5Sz(CS-hg*JWzT}Q-Z@X%v)P@b5n@t4-`7ZMsn5EOn{WRpzvw#VnzcQA!D)L7 zV%hpqs>yucX{a%vEOD-guUPOuzeda9G?~mlJOg=qiWp$52Gw#o)`Wm#1)Wd(xFCsN z_>X;s_6DE(HQ01F85Q!6`fsh~>;QqH5WD%%Z$Jlr*xSE>mF3_5*zNyoZyy+&H~U_V zZ8y(83wozy1B@+AYOLb_GPcg&+7H-*ZwltN@9aGyLT?III|LcBXMbmZmDN#j;&69; zZ(pm2-o#gDIO2HYbN0_|X+UW8dwQZ4%8NrCusP|lD@OTOx|FNdO}u!WqxgU8{Ocd= zk7^zGydUkE5uFrw?=(32Bb1YLQ*a{H#`E^cdM87wMnBn~u?_Z0)ro)ilf4ro^a4$T z3@K*2zY;U9unn&q7Mets5@QC@X)Oa;>B7v$w!1)%vY3XA*c`LqP`Ct-&FFXB#HTIx z6m?iWtHvi2?%U^tn`FrNYMi}Of3pv&*;WwcuCMLqJAQ`~{eHq9XH)vKvx8#p`&@LNYqEU**uW-8gBnzHa*`wlMwmoA{=u zruO3HwG+{ZJ@}C8_Kmh~FvKVJLPcT^^AL>)-?h4NmTG9ZTCnRh%G?h(bT;(uIBWBL z>t=@C$hfu6JVtl4WSxmzYS`nf!|tF-i?-F!qP)J%QNd=DzPP)cM*t$U>$5eU`?Dj@ zgo&nq$ZPsFqzjsURdp(Pf|wpWdPT6KXY6{b=K({sCKXK$%MX2q8rHO%oyFSg%BrFW z9HuCQ=Dzw9FpnlWGW4}K@x4c$NI|Pd%`IgbguMqm#k{CaVpzZ}&ib2p#-2%Ke0^=l zEJk7q-@o43k>48TxEygwDF6a?>Fk{1Fa_bOr#qUi+Zmj#Ujm0%>@4Q#vy#F}Diwxz zw^8%gtzvX~g+=S8IoOO()okq(0&psi(u4Va&6dpn8{sHoX{6u&DGo<`;4ZxQ)U*_S zFw*fcDjoFkvjwc_8Y@HgG(7+9U)dGC5g^3w+$SyAN~Ktf$>?2?t!WV~X9 zY@q)DPIcT3^|#u>14h$#bP-MSBT%#*p;9JZyyv!b zzA?p7yJqp_HlCa62-aWH`Hp*C9r?FOE@yQPK49p@v$k6-ZwHZ?IbTubu=+a>5DL_!LUCxtrymT)~)z1 z)$xqRq6MO1LEIZ-RwI!>F@Q$f_@*jHvj~Fj-PU1#Ae(ehM^nrXKv&po-fQb%llx2^ z0Qn6ZP7`Yg#w0~z8vwYtTn!|2g{HOsJfkgaQbl#2|2|`cO|8lnXWHoOUf+@}iB(Ff zCAW_t*?XCebdzL0ou>Gq6P@x+%bj<#xkOsfLP_{t0$|K1KJCgxPsMYM9S1e`2tnNc z9xPC6Y&`mXM>1PO8c-+m=NH%JNlhIMY+FGm(|QhX#I_L})XA3rrIXiDC;9Qz`9P?b zVU{fqy_xU-fh7_}L`g+}IC;0Yl1$>9dBTw$PUNc+8N-Z<_-sd##y%u6VX8(c%ea&= z^@JRB9N*pCQOHhPIub1#F9#tVE2ic+e%IJfqz^h9)Xzrq?Y5#Y;`hd<^+@k3uHn~x zphQAjEmYQ3e-Oqw#?^vv$aNfNb!w@pfJR}pq)`}YD2sOXwl%B;hk_HeGFT(hf~Lse z866w}cEBxb1&VOTHwD*^QJRXC%4hs^2S-W-;R;hNdaA30btmj#;N8|Ow1sJm@95}A zWdvO&r0V@LqcIyodf-HcF`;Em=wMlM|0f&?d`@Ra7c*2OJ%idfa@jNsRWq9CyuA&C zCKC@|#&pqNc0T=DP?V`N%)t^ko`P!gcDnEoiu1)fn#3|HW|e(r}xl;Rsi+;Z72EKErL6h9l_GaDQ}kyviy`4>TN%2@PjL z7lyL{48xhALiee~chu%};+=&oEJ*peAni}#sV$HrBgB9{a(WjafG$j?j%fSQkMa2M*SJ z;|m2fJYUH5-^?A))Knhtnfl2ZAKxo3-t5?~>*L`P=lDdIZG4b%if$QECz4NH*e-~t z?Y{%QAywa*$WM=T1oNV9jxgT*2U{~<+0$XKwGxKUS51MF-)f==@X36>U_ffF25)Q# zxMz9{7{Zy_ys6kT0A>g>cykck38bEf=lauctI-Y$hBXBryI&T>_hvXV*fJuXZ&8eW zQ9$XzbP1%5#hH5%m>166{DoPL>1;pgTinK3!lw=#Qj=|+PpCbTi?)atPXyN!M_+g< zV28`md);vu^Ystzh*K(GSK?T2`wk3q^vE4e*f}bTFUJWV1_-QYcw#P~o^Pwc=FKZU ze7f$fQh24ue~2hbrNO}#mBOcOQKcsgmF^knDCegJJH$od-=fWgU}ON_ySHkSulyl7 zjE4_)Y}bo}`I&6+gPVnT#*Pu)6m!H~f>D1lem8;r`LPj>)@C>T;#S9i8&IF#A(+>0 z0itvuqA2~1vFfj_F}wm^Im*$JpTFPHi_IWi{}vril}z*knE&DkFTIhU?$$VrR}FKV zvppIN82{+sjBTK-ah@+9kqdbU;eY=6dnSPX>Wp*@y8-=aYk2f1$cC&Tf++R9ZdKoE zLwyel^_^kwlU{#|=H4|l_n=vG5J1ED;e~g^@W-=d?0i)JC74&Xbv9y`sSLh3e6czm zUJszd4dWcQ+=vd(^GEEk$2m_VQ96tcu}tA}h7P}#F1T-_b20zX{rAn_1|c#;eCyR= z1;oO-nyp_5Fm`2UvJxSY->mHuQcctw8WJGtfy(muiTA5Q;c;I_(hVrj)&s-c zgC9PzP<=((=HM8s_HH&tR}>=Gl&h~fC$f2@D_;MVS(l=_RX1ZwLU`+{jTccakIxUU zp9JOG$0j;@>Ej^!`x0mY_6Ox|bPrBBfRGwgUL_ZGQu&V1Dv0xDDF2DtHn*saSAKihU8n7q)j5upddo zK#?sI4Q*W=*j3U1X~GGj0aAp0^-sXL9`MN569JY|-nTk6L`3c3&3r^JHH&Kh_n2ku1jL~mmr z;6Zh-wPOo~Q6)>U@DX)N&wI1_aR@xi=IkHWOLW2dzuw{(*8lb9n-(}4$79tFKB10o zg1LabA<~(?zuob`{|E0G0Q;RVo_wd{S!P#bf!C9R2aQpHzsZ9nw`(7Sg!0pOIqqV2 zDGprtiEVahFwYwo6vsOs4r$8nBhBbvvqPn~Oo!`7!&~A5NLfBDlzTIvO?lx=M=XwV z{H;#r^&rvy3RJi99?IpaGg=9(*%He%}6Dl;Wc8j#r7yLN3R)S z?YLWEP_Lo%yj}w%L9h8(bV0BAMEpXpfp2tI=QShX04#F&^GEfM<^vWwCNdIuWFlX` z$1$E=P?AWS|DXUqn?Gn)>-tdc;#731v~Vtm9=@ZmpdZZ8bTHmlv@b^&e|p6&kFzs zB^Z20i}4|X>AGb(S_mZ`9}Ndx95ONVN;`RSdGO#O@6yv0gq7CS*uFtzfT zbcnzy+q1PXF&4g3^fFTa{G|^Zjbfh`5Y(OVI2OoI{M(FF<|o5TuRF4Be}d&N&eI#Q zo5G-<+UYpqt;6V$f%%7p1>mpkax|=te>^{W)Ddh0A$W!-3|`S0+7I43__?RC-XM%m z?dxvFGA#n=>0#CEvRX*y5p?jud~9C*#sRrw{)diUq-0I%06+pimNPcS3>Enwd>FSM z5e-v67HSE6(ptxzrp~Y{D}k3!fePF5eS_hK`7JQRKzECZm)AMm8k@=NFqu=N{L!Z@0K=zDP@hkQGBw}Or%Y(VA;UL1CWRAd70(zp zI)hJj-qnC5k=~g7%YCN~3nPO?m%e!u9N7s4nJ7hD1PDc zK9TYLtEMyxr@KNPy~N|@OUL(57H5jt{;T>6&p6hxd&w|yC$~@me5?A}8(h_kMmi$- zlm*U**ak&i9s?d>@@{+$;};vdO4+Lf0oUy93IUh=ZCl`q?|p)WtMDNvm;5hC19le; z;xzFcX%I`kb_hOf;po7p#)m}fz#Nx-Eu6TV*ke{PW7)4mS_DHVw)S<0vEBip<56J&WTnFBI-k0lA@SW+N3;|`!xxZDBUyWP<@^cllpa|BLFvh*ZL;}FQ!*~I}y#r`(;R@%MY#~9x#b9o@Tny%t2Ftc#O}N}P ztRpBG;2sLcRntEswvq39!%-04Npvvn7@Puvx;DOP1nhA=@MDi_(d*&HTC~f`dS`X4 z{~3TaZWgLxZEO~Rzjd>4B3y13PFi_?Q62B^kaq+fwy{?T#2ohuble!%DPZ9mX9=SK zy#B|S8XN(NG`3I}Q%z_hq(8RSnd09W>uT%$WoNwKqa-mP-xbbRFZ2{cdM0Ww#9$Zb zVIABsi7O{p7DYAoHa8-2F5i6NrY9~st6-6K1o_I60eGoM=9uvRYw7&FP{||0>qdBB9g(eG3tFV`k$n$C6L8M%0QMt zx?&)UjjU$-pAjj~9>)YxQzSbpAoT3>XM~Joe*7_#wTm<&SqCfc!s>W;55yZoSv9}=M?9jF;?ays$)K0GLN7GH)2^J?ikDH$T5~t0LC&3P_b+&kqTp(3C$PF zOi;16#aOofFFRu_qn$-8gU85mZsKQ9&qc^9@oy2P-h@frQpL2<%E7!rL`*}BY3~bZ zFs6MVeql`e08|-xN4fA5$Griwi#HmR;0B;J-}smjDq_nNNL3dvtRu{3R2R=x7(QoOUh@-9 zafb629`+5KN}f=JMVY@*VjO^7`Qvqr662`QM>BM#OR@KVTnVU7hUB1C=~p~KfTq);g-iA9^c6~VmmDW*MkO{homn-Zu}KD>rBalojBi*H-<9>wC1$QAtgiszM*8szO>;KW*m#11DFJ7+ zObIwi1Jq__^L;x8*0;?C(K5=zGT405jNW{AbTxB%S#+SeylLN^sddZM5RB)WfjjOd zDRpeieUD9eQglm-+Xui$5%XkVW|2Gf`w6YW4olr`p?mP zQ=b_b>=J23O;=W@=|2N%`r<1ksj*7YM%^{=KGVUG96@+{Q{i=Ely8e!CaRcqz{gZL z!MCQuvtnc_ycy|_0ymDS#x?R|&@~u|ar|nyvq3;{(Jv@_^a~3hfp3a%7BCZ3n0646 z30=a3AzT7YOQC4mPtB$^3Yu>x)Ns??K25G>8<_BVoO7s<^1(mX_I;C)_ln9~} zSo=gNI#G-9Oh52ND-yn5E51k=dabC<;74Pfsf?hLlIFdnhtQD@)KTdsbaAC+0T?CC zCa9Qp!%nRl8l+uqCYWpmqDqp}&lDJ>`X_#Z5 z#zgCbz=We5IePiqd`|;sZ?=k%fMnE=no6|7%tI8S=>uZnVhJA7-R>M5#w#3af9A<$FpU4cT@gh0@=@t@?YBjBSh5Ur>1pR7CRJ z`HrsaJ3{3~RQO*r85+A1xpGupH6_tGv0OR4 zE-o4VmkUY!csplnlY3rk?(D%&u7ENo@ioDksy4K)tXU2v@}O!Lgq8-!2q5*$pt`c2 zQ?Dy49z$9>NAoGIoJPraO}$a?BHFe<8)#}he~ z-kjCxZHB+z#w96#6S`w4tmKsI1d$J?V7=ey6W9lr_Sv zEQo*bZko2vBTyD`p{=tqJ3#q~IlKMqak*M`ntI<~Q+3)qYf{fGBA&jhE?;klr$=@X zA$(Id_N0JP$Eq-N^{U}mq7s??O#0r4!Y&vJd)2J4Dc#$J@vEJkUHHMy&gHhmIHM*x zIWExDOo*#yH`gf6f9U|t74qCJ&Je!zbjz3%mD@Oy6o z7W?wtSXmiZ(%rc>;BKJC-*9tQaW&;VZ*|s_8xdMpO1jBZ z*D|o5DgnS;7nYZv7eZiG_;MT{@R~D)Z|~>qle$TOspl+L!qU>@Dg~BBrVm&_72`nL<= zJoQdTD_*r8^c*$NIhM5)LV54mM1gX)0{k70r5OMD0X%bn70Nvn3we#uH6E`Kj0)w! zq*>%_;f3-GM?3rJo#TC;6c<3s@=kpJVCO5|s|11}ou*NIV5hlDutTT0Ctf;D!EN9) zodlRVO_maiRwm!Cz|v`&SUWCN7>3jAJ1~)KNxC8;bgkV*(Zrl z9O3k^4;2d;LXM#M`f7*y!jaA)?3}gzY`hFHzmo{*L8>1)01yD=*yTYrMaC@1vvDdW- znslv~t8uMc1W$CW5ed?@`iygSOnq03kh<2ZYRIxAiHq$fvlEeFS5U%R_U>83?XO{; z6o)gMjU{C9I{pp@QO?ShYJaAF)%L!ado>IU>C*yWN)+A385LBH}lMEtYg^`~KcrSk#tdBLx?_1d) z`d{on3BVq&=Br_ET+M?F)~orS;5DJ*YQECS|HuEu|ElC4PKIyX&Ib|zQ#f?|m^ZTk zj0#c{)K@`TuO4XCm|2)SGogv(8CE4zDD2Bh;KN>EL!&Br85lxUC3hke(N)^jldjT^ zG@z@Xol5H&b{a&Qg`4Ol^{Uy7j;!bJA{HANMYg~iUBr*IDoUPNPnv1AmHqVU*e{Um z{Y@03OyuRyGiEwdA_#kL3U3`@=S|`1ATB0i3BENEyQQ8?#BL@1QCrVdC+-lT*06I`~r<=C^3gBDM zAHBi#d}C{;QH$(R)Me$HgO@FY4cXX4j-|*8NV`~cwK=|aRf+rvLBjQSO`=@ypCJvR zw=NpQk>XX-fb0Dler&O1i$%yEkap40_HLrF)_+M_1TXDfUr)Sp51_8{F^S|H^72w= zu6MO3$a1ysl^A#V?sJx=juFDp)xM9CPOkPw0dlnHZ|n#~fxc0I zoT$LE0QuO_I!sIAQLi}480jN~!vf^Un&o^3bF?_t9!C43IqVR2xIty z70wf^Kf%C=-#bZ0{NAL&ygAUu@|=~Bz8*&~FpP~(swU`9Op*nAwM7rp#vo5XP|HT? zF|fy|@5de&oW)7Tg0sZR`=07}uL{H)SDb2i8@mD!z`84VE=evoTdd5VsgC)pl6eFj zxUnSvQ;bmSPqDF6%hC_okLeMqFj@M%I5u@{SvO;Eg=6)*Mu<}W*A!5;05vA0K( zyz_xK2jiVjE6{|m`k1<-FVM!*dE^bWFpKfjosbOffT6aY_=TaiUUGGzw#j!k?G0NagEdm1*!_*vQ_zI}sp1RG0mFxrhwHlp2R z(juarJ~CORUW$@sWpMzx%ey3#aJS%9NC$uy$2{jYhv_L|QC5-b?^^%2_#JUX4#VFo-(Q@?}t)2wjX}Zx8?; zb9M><#xT$ZRvjN9C>X>JC(9sqm^7G!n0_W%o^ZY@kQ1r5HghBnA2zo{9m~mQqasjZO)`8-rLiyp13R0$77s(-axR zvaQUURL8tPGLN7GH-cCo?ij@A$T5gf00uD%P(kb#A{7QP6PhoGnV`NP=KRaf7{q92 z5yar#%s6ea>Ubx3j(8E*D+t4?WwU7hGHmtL>9 z(p+@x-8CNH=3E&td3d9N3UmBhK84GbPTQSR*egUun2>%+0lY(4{0-ia8)Q z^M*k(Fc}7)PYE0b{}fa)3@bs=r@f-7xbIP;urc&k*6 zWh$Y4yU>;R*4A47&Fjvt3D{z6ZoOphgLCkXE_p>Z_+fnfM}XktKWFD>m3I=<+lxPa z#TP7ki9gH4pC#hYQSs+}@#i-2VSro2pQhp^(2d2P(c;et_%qA+QkNvR3`yOGWbQ)} z_hI+@u#!b6)*#n!6@Ta>utdBloU8?hAa}4~k#Ny}u9vxu<)%m)|OWt%bv_ z_!b!aAHM~5>dhKmV*B1wKcBom8r&C(F@F%R2FBM9cNK5u>?r=cC0?t7?{pa^o{`0O zbDR~w@LdXX#6ytyXyr)pyaPT{^p&WD#|r#AMDZ^c7#E7#v^?==nYjAEo0t}jM7k35 z>o1F6m=5hF4mEgG$`Y{*_YThsFMg>aYLByl#wH3&de^8nPUB0d<5R_~%(H>qe1{{U zfek#LPnnRAoJQWQ;hUrCO`Y&gxDO(l^T-X)LTvCP#Pdn}oRiqnfIJo(JYXzl9&sdF z?&I+^-?QJD6Ds@_G`p8acMt8!+aGYYXV3bmZ{iEbx*#v{Wpr4{W(5_$#CBqNS&cV^ z_?5KXOW-SM1q(9Ec+vxU3{U%ULeRQ;uG;*cZ#&xs9L;}0HkPK!}2joR0bc=Wr@d=rmNVeXPtKSUy1 zDxbD{a!Y>hUFUyvR-Yd^>^#dN>U;gru%Z}YtfFEZA8XggTu?%=LKg$T-69~%Z=5{z zKHUE|sL!K5a4uk(3R9_$5H`M;l>UDqJo$)oiPnx^KH_|Ub@&Uq#_N3x{||I4Mjvy2 zrLjSOLD4AHEs+%C1FJwh!O{kvcTNxH$2!{Lh>sW=BzBNKvfv}<(TItPH)s*RZ#C!N za9uQ0!G-pW`sw_So&DjvInigF@qBNSxFo*4YJL!}_}Dqwwz$4gLp`xRFH3=UI1tKQ zcm|P(8Lx*WE(l&5U-8{1&azr;17$7T_GoWU7oPt1kSP6``fEqJ+Op>e2Kp|RFl`3? z_?-9U`oeiz=~uz$8c(UmAJ<&%W6PCWMMx1gRNVTNGf0mhJiTgIddm4cJ484sH7q#o zT%~OgYWT+XnK5qocg%mB(@fG^hHdclGepGK&T|o!ij!A@%x|3K>~{qxhB*0+vqY=( z86t&``LA<^Ei}!rL8V~>Ley#liNqg6h6cN+1@Wk3Z=J#AOPz$L5G68N4&&LaL` zf~zJk^cB*ri*U8K-3~IXY(F@Y!4G3a--O1FeM|u8GBGnvzSeXaFSEH?@~^(0R-5pdT)Y5uGT$HJ>dn(n&5Goa$8EtCQNKIu zY1${e=@n-$_8AdD>F?iEfB%vCgRh8}U3E^ZK~~i(n(Y|q?Bc+|sSJLYb#}?BvkwfN z9Y&p1T<_|JH;jj-t8RanzTm~i+rwO4^}`l*<-+??r(SoS(^{?_;cCb72y3OMoOI%6 z9n#UyXzc5D1KQG>^2{(-25U+VwTH8G;Ji@@ z{6fw|cxQER85O>{iL<$k@0Y2){!t*dTX0O=4y`&wI&p2mnLxbPfv3`FX4t9&6b~G#5ee1 zQd;a#0ia6DGse;)Ll##5de}3NuS;}oWfMu?h2G@bSXXK)0cyx-lDeXE#pP;)b0`GnR!K7a`2XF>JwDW{63 z8oHKhtcvuz*xJ>UpPm<#tzQ8g_@I+^nP(Kb;(64d^4nNk1LYz1c}k28&0Le&U1pr7{Mg~_=9)qLKGKN9X9MwGY#jk3-PtC(C-dAB*-K^|Lt`%( zgx?~qg0Kz^#jV|)*n6Y_NxxtsJv86Fh<#(mF-V^_NdHV)k+f(K7w$JTG+AbXcG^Vx z+cxe6EYXb9luun;(3~%5?`p%EkS5ec9AD7Z)sYntxR6+nYbY!446oRi?;6ia%t%f7 zs^`ZVbVrgVl($bqsfu#afP|qz)ErAM8qXG)+oc-dGr}nCYSM_(0$fP@4+2M`^C{7I z-n+B=e)hTUyV(RH#Km`ACE*?cz=Z|kFn-voYd_a_ zI$J^zL5(H)J(===LgJogq@xGDKF54f@;2mrkK zc<0RYify;JoErOv@Ef?nQ_6lMfc-OFCE7Rq(5s2Nl<9jL@m2FY@KIbs1P$?)8iMv78bVB;{Uayz zBu-P$I|Ah$+97asljLEZ68KgED8%>x*BsEdD7W3@c8#gUE)mA4?Mg%2m9$}^tCt?y zSiW>1tg+&Tb3M2*321d2`_z4Ak}H#_yNMJQ=;K_s(1)F5o#D0lgvqXkT64Z~GPrjO zE2CzVQCr1m>l9bBfQ-Zg@QgAVTgwCC>tS09Rziqx+6Z$8J*Fgw5d~p1Aw9j(BzZby6xeJ+!M8w>*q!3lj8Cz~^~2#Au7~wyjrp0>@??J3 zOxR;QNJwEEdVojGa?M~55cnpSXDHi904VhXjb*aigeguhDh3%JGG7X67R9WK8}q#V zljADVZg*|a*g*?H?EsIv)3ux(pzzx6vFtMnfcanp3?3EPILU;H2Peha_*VHI$y!^? zbMJQbBc5)EMpP`rn9t!&}f6w6e;myz=wfK|E$YWT9#`@oAOsxCab<4fF|q z5unpg^I`VJTky4O>lV3^g9M8i@I*jfU4D3hs~gMmL*t%>u6F`Z9exi){`P+8f-1b< zJY|t=aj+R#ykNC!ILjanf;ib9G z#g9GVYRIOMCS1QK33=obK5{E^H$2$xDiAB+#d+>VWB{$?0EX~9Zs8$)W)N!`MyR99 z4B?dO|?q$>*clvS`DKEYP4cV&@S>J=b;RUA&BMj*>=)HR5%+^E?ZOV^7;cCFbnkwg#i+)ozso{C~ye$FEQy|S#Da}J! zs43lykVgAdO8Zc3+%@5w^{?MHDP8Z}lxGZ?l*x)nSCpzFm8y?Vs$(8^6Ji^$R9SKz zCj&>*P{z?uxjKdufMJ!po`RU}A>7d_1dj`=@U*SqlqRS!%6XGfnm+A1#8wbe7-g3= zl~HyXZSYxTlVO#oNGp#2A9VaL`o=FN4H?#tjmnGuI$DOJqh(Y?o7zl9wCSWT$~BqFHOD8HC7LO@aQUQ+&@>c) zrXc{sG;h5Ev7q>4V7h@cahEnJkXga59LhRgf==8prbQU zbjvjFk}bn;G3kqPbs}>0RdQLvuaXO$i84ZGqJU|8ToV`tph0Wzb>*`0ggY9PqM<=w z-3!G%6pEeGTX$~G?*3n$k3ZpQV(N#s{K;oaTukTfhwb4;LIw@GAzMa=4YWZRbiv0V zO>D1b8?SuZNt#h}FB8q}Q<}?oqMQcquF|5w1T9LLfJFzfPY78wCSanDDJJUJ0!ZMM z)8J4{p=fiJsQ5WsCMqrw7MQ50B$EG`4WGH6*g8O_qS!0B@?^|ZP>w>&+Im4wWh#76 zQ|fnS%Ex>>kd=h$c$+gbn4ejujbjDP6-`WVwh{nuf)gIjDB$T|Bp%gDdFgww*&IaB zF#?t}Cy{w1&wF1+=Hff2wb%PJ=hN<m3&ur3)B&So73w$IO zJ~+LV)`yoJfn9+g#mXV|bM;4>^NXV=X0S&IMbL8Fb)kB5eI22yZwAcG6HwJ<=~LPX zNe7;tl4PO_34W-&zAwFb7$FC43K{b8dYFE5bJVETiWeVubw!1)o}&+E9}{d;=!XJ8 z6q;Xg=ZCJYVeBV@h-9&B>RfX<1t6G3f5V%MJ`*X7KXpV50k$Vc7vo!+VM@l zg0~DMi0HHJ1c3N#PQ}vST;sLy@e0w{fu&x7i;ZatjL9_k;>*!1u5JO)i>|tQutgSh zeS8aCxdP+Y<(>X;wPI^6oq)%?f4DNL>yv#A`aJ93r{bDx79+!uTS2@xd4pi1CyeJ` zR>8)RVq5H6D%A*Y@LibfF4o(%kOdtUyBW&%*{$<+h$`&A7IwBXUc14M>g+aBGW<%~ z?HWNuyL}}9#BLaCqIue^TY@TXtL27|Qbn}%(KamjS`ci5;}lq?LnB&pSFrmhM(|}# zrgFzyr7U4BWpKI>;$9Dn#(w5b;ZKLUJFI;6YJ8PB)4v%t5?*n3O1&Ys}qM&uJ+m+i>P~fwzEQE;iXh6{h6E zaCZrtK;Ral!zEF-ndrk2?t8TdR=KdmtrD|0=M@8l-$4`%tWV zzs4>S-a;nZ`Ibhcfge8WiItJqq)ZO-d!82$MaH4I3K2c_d(o44Yz{A7(mJRjIKe$g z3r|$ohO_p4)7^t*D6kASiF{ZCcN<2~$qBDD!4^{MiMhO8lKX@SU8s_%YK#;*K3C4` z?+uk%=Cv_2pO%`ZxMOuT#=_4wBG=Fo{4i;WFmy_WLvqFbA&zg~f=<-5iD09{E#(s%x?3vHNDaubZ$f zI(5h)E;e)uLq#_fIwkI6C;|?^Vga1`Q~R(O+^J#7MlWxK*x1n%U#RnVNCQ%`WU;Ez7 zqn3C)JhiENtF_XuV?|UmcYlr5%L8Pi(giE+>MDS*((b7nE9mD?(4WHhHFq<zd`Fi0P7<6g%unA;7iKNwW2NGnqPK~iO{lrJDv=s*R= zBDG92l0iDXl~hP8(uz8T1}xbtA`ODJmd>>Y+{Wu2426^)Uw8`}W=1sV-)hizlUAfJ z8bsaREYg7VZ}q2-Wor+b5e@qH8}v7jR-_LNs&s7&X+kS-w^$PnNF<6j{FZnc&uxmv?pdPH8Nlw0tdE*|6ehS9g1jog~7EgBd!yG5*$+j#g8*kCybWrM{%uGX@+ z$77}LAk?S(sP7x>ZXS?2=D#R)%zs$`34C;KPq%OarB+!*M8K>y!GjDfBnv43(^zov z+aKm>>9GdUdS>eiD7aazvDXM4)bS2O$2&*^4*p$Z@b8fZRPDdW;6JWz@WyvMfI1GI zQpdqt07hXGh34JjxsClon2U`9qZpWAoqU`7850x|1f?t}Upby%zx}s*`kT5~@{Ec3 zGS8Syh=@F+o{;ZL55;KtGSB!KoI*rJl=3R$#d%ax%rjB|8fcrzK=R`(StHz^vl7A> zjnpS!PJ}+R!Iz^SmoIbl4$_M0tg%YoXnk_NcNSF6b2lb_YLxu}56tLN9x6w_n9#55{lqhf8AV(Fkqyzo(aRC1vUQAX%O7C-_&GR@sQ zoIvUPIY5NK`9tvJ{Gk9$w)X^up@fal+T81)0%UA%0WeAj7W(1J|Ekp36WhekGbJ}c~JrmsL*#bfaEi55_|^seXa+Eg=Nj9OISfM%f_ zlvxH4(l}oL9p?*0H%Btv-bP+sJ4s&@tBi;>MT!+5k}0{+E|d}4#R4$wLZH+xD~Jqe z7lJ44LIJqY#Bgmf-e8Ftx58+>*-DD85HG@=6jNfhv5b#_UX zaSS-1T_^`-m+uH^v9~wi(1061r#>z(jRXOjMTz0H3kD&s`Kw zpj2It5wfT*f+y8Q0T^Anfrv7?_-a_^D-Ghc?AL|zTJ~$w3%wJsWh2_kYuP$&l~*85)|OZ$ zu`PP0u!^{s)qy4&!H*_h%;vR~7qhJiP2a_AOG>vBV2X=bpo7&DP71`HHBggeJ5cg~RRyokT`n0p+fOhksTz8~Uz#Yf)E z=J2;Sxc^{B6dWsAZHI+q;$jwl_|CMLepWOyCG&&4bhCRf`!7KhDOGk*08mjs@{L>E zuZI7sFzDR)Q-S3P{8yf_2{sM{U0#p)asH*P%po5HCGT|<$~!$jthZq(aHm(dV(^ph z`WkE2P7O$$m28dM8AF91rlFE8pz$O{gLZfa&58*oj6j~6L13M>a7)}Bvl=+0pT zUtSSxe-*wtkV(*m?0Q)Hih|eN@me+bZT#_h)lT<(6FOdEsrg`(o`>)=2i$Er-ciA@ z1L@aLiqDzWyzb7@*f z6Y)oMTU(;`9Ur~l-Gx<>alyKn52X)UOYv;U0my=hFLlTlwOwtGkGn!PaK!<4S2D&n za*XFhhXC-ia_psJqid)3eP8051oasV(&KG;(F?W1;z_R8dnF@oM(`piqXU>2FM=9~ zUw9GJphGnmL1U)e9>mZ86Ru#$dlxF;y$i5o>>#?+i=aXU@N&J8mzm;Y(Azav0$-N8 zAc^n(7hFL1Q7qI&P+S1U<-PgpL$IEXB^@9EZzS(Wc9543lS!*c-fJWI)T3})GKauL z+Fpka_{90p4!pR)GmWh^BN${?8)Tm%tw?sYB)fyakt}rZk`?d#Uw6cP7dvc5GDsgZ zNPk9Jk@P`H`YeGXY3Sf3jc@M{sG|&*NJ|>?fp!6ca(mTH5rBB@BYO%t<=p7^{rC;w2 zU%LOLvF@Zd7Ll#`%H5CkCs15wx_9I|wob2aLdT~W$5=2U1VL|gNo!to!rhv`ezj+$ zsV6du{KegeO|x{@y7S!APRx7Yv43_al zU%Lw#LC4^ps`y0u>CL#ld5O@%t^QU4z-6g-2l?Fo9shMF+t^`(h=IBc}q4@a~2(64w{-iPEXRxtp?D zos^Fw^_w~o>XDti)bY9OK-BR-MycbeIFpdYQ!&Var(%kUr(z2rfuA}LC8HFI5BGN_ z1ce`(Fn~}3kH6slF`V?HMlU73@ia~F6TT?&f(KG+D z^GCn92benJIsR=hnJ5O`2mcojf&X;Ly+dQ`2{m+~wVk93ttAa;*%zf{Um|d{>J>)y!1m znc||({LED|bu{N)gesa75Ye1Pqyf!o0T||_P&DTn(hqe+F;GXdgFUY^3bokuxz5t2 zTL>kz=`(b|ucA#`g|EHK`|dq|>l#m_Q(gmVdsdm4<2*l1SOpdu4ND23VLO3DhGB89 zUwJ#!?7!7f?%KCPj2D@q=Q|qtwkpB}my4?c;9V{--!|{Lx!>99brE0i4Qs%Xx+s71 zWwPSC5VL1?k(n$Q`^5>K4th)%nRSaHJyE@J6Fv+n7$#GVaqbbRWek3v9MoFrCTO=VRH$mb_2-Zbv^=fCORm`_NPS8=S zj|u?MYJSD^I8TpY_7*`zx|nZ!ql*lqZ;)1;cgI1MV%~j38cBzoPBZD`W)K!tC zk&L52mOpsvmK;XuV?-&c?`g(wy#TfM_MHS1l;4!3df^RJLA1Z*((IYoZE=KDziOZ^%o4cd=%UWCcFN8M_KqtH>IlZ z(R9>MPKxK<*M-=4-hD&-!t?GMpgQ;xh=1YZ)E1tN^r$OdG1!q0Y3cbl`;ZJD>mH9N zK&mk_mOp-jb&o}zJx%!X=I&VT&ht3f8O1^!cjE&vE9wqI`sZh zBoDno#l*SAOY)!rKNTBG8t@DW4Oq>0ffp5crnBbe_NIJe_l3>j<$nv?y9!u)(kKq5 zdRDQd+KV&@sv5kwp`E9negU|8&%9-39OKM8${;<3v?6I}K!N9y1|&VoM;gz()hG(j zykCQk|}JrgimcM7(0SM6W8Ap|6Ti z!1Yv})8e|yb6NuFD}taF%a0HA7$tTYT}2Gc*Iy`>=QJg>@j8BBgy%HM2xDx!t}@1U zu#zt%9`LuV#^cxV@qn zxFuf8bh8BLVtF-WQ zqyZJb&rtjU(tvi|LlpmhwTd^Yvw%D*o{~q!TL8v(nnJO_?;PQds-qY}b zP+cjz_P_dJfgkN+*?~vhEO+2BH>>G@JMhSx$-16$vpiLSPvfadIh~Q1p&VKc_1tTf zvH?c}w<25u4w2*Ln^F@7)}9u2FzPqGMt)$p=V_e{Ar#Tbx7;j^d<$t1MusPjw9%fX zY!ZRv24*}R=H(ese6q`vWfB_$#|6SM(0CK1YY@sD=YA;&26JEgO{}v}ir?egX#G+# z9w4-@B`p2Dq-fjeV&iDmpquh^Tp`i~z`H`IqgkhJ#?h<`>EJt>b?8Q>NAGTUG}B(- zl@mN2^+NdSqj*fckaSchv$AgTWM(I==!jzoNo^9pILlKY7LonpWCkSB?E;g$*C4sn zN^%h;x!R8;p3Epobuw#BNXb0`oXp^Tl&coPPB^WbJeUcc;=$|y!A70#6#%N!ie}S2 zn>FnOKRUxx&dv~gq>ksalR)-;ctzkz(u(o&we8fsIp(k_;g4kdlz2I+%*!U zK>w||o_rI1w9EEm^@8~Ovpo~EM80yKr;sIgS3V-#UrXSd7Rd!Z2H1$VDuA)e?(htX zRlcvd;Ad>;DDYtBhxr9aFP5!OyWs^`6Q0krvxpbG8tCS61 zL;K0oQ&2VHz0i(0peZCn(H{|S5C=5vnDoxQ(mS=&IQ#K~jr-s$-w|}PXk4W(=s6^W zFTcl=uYJt--{VQPecU~mi;GnKy*;IGW%H7-)WAcOuEbPL}LiopH2_y}l8`OBgF z%)i`ee7@_)5Wa6t*D#`RqtNbCIl!?aLZkf~Kf*>79IjZyQd2Z(CDQ9tpexZERM zqT@}Qd^P>>$QjuKJQ|Ojb;K_`a@Oe)@W@%|f7pCdFbzLbb zz=bFjU@{Zv;@jx>-PcwtmbqvwH;F$)N|CrI5Z`@0MGBBO6!?kbs^`-HGUy}b>_dX%kP-bLHwqR#3TW*E)wUj&;Nmaqu}Z_mPyO|U*|_z z)0|%^g66XAnu2f~K>iW{96-RtxNLiNQ$FNI>h}-GD3@)~{bgW`rUlmYTC4tY+18q% zV2o_R4{r4@+q(3ZqsJHho zd7Lg%^0<1i0nDr!g<{rhKH-k@CyIgd%((6O>zxE@F8A;t%oadJe- zVBvqkv*@GZ_V-%JF8hZG<2ijiRB^@Mba!mG%-hlRf%BRmP7EX+2z#^aVAD zX&rQmK&D6wlV-rv*?;wu)92s&nM;!Mgb7B!vjX6cez+t_FYC2d|7(C;I{ZWMQS*OL z&4=*3XQbwF>F~<{UOb?nKl_1H!g(d$I(2z~%(a{alZyEj&_L-zgGecM`CA9dXgP%xU>hb4B;He?+8`1M%6rTOCXnS<=7qLq zls;Mwb1lmVaba?}=IhY2`J*k^c*3Lt;eMnh>|93swmz5NP-oi+7?-QN2>>~4^UXb+ zKU%Y5ibE`lg?Z&ZWg+f-)_cRju+sbty$$G0Bo=<}Cld=~m=xo=d82}5lvWnOS>C5Y zDxBq=6~AzncXnW80^D^B$`y_CO;{YqMgiG?2(ATZS{zoDsK20!BYHlEM@ zxleuWeg(d74IZQ%4we??gGH4vHmVJhlfIg-!7T;nUd<2ZgW@71xccw-x7w)xc4Kjb zGR_MRG?@msqP;D)3l@dN!hN~;JF!qpimrkm&a^^+j+|)`EIHHqejv`YA_a<^X$=&= zLI&}|*Ymq3R1^Q9Q>`mhpYq`rct7iJ=TL!YPQm2W={P)(R$zHxcqrUkC*DdW_+pEE z2w(JO{&hYIX&R*N$^0;uN%)EVd*1hC{w!8RpfZApH-!rY6x$XgCrY$(>Z$xY^reI3 z&1ok;hBW93LIgX`az5&GeimC!;J7GMbj^ofN`;wv#Vk~aepfUAS3cys;$aVg+xVFiz6buDpKsaQ`S2w6+k_Uj=~Vfc11B87DJLAjZGad) z_T&5kj6yM_qu*o`8HA24XgG@JdRe3e3j3&y`Il$%)7Y*5QdwSfYpIN!=e+~DSKsLA?7#I8-p;Unw*{niI;yzsZlVkip5{@21kf zmP*%ug;*qRM(C7t$x!@3pUCMD-n4GBCbHB6|;;~69I|g(R?JfJV5M2@kXn}-Np0x2Iay_!FRJuQ@knthz-jdbRCb zZg-tV*{)BK4D=>L@ZDOy@esc2{-OcC7pl2>Ye8#(6)#%o>cPqg)4YIsR#EkAMfJ3C ziQYHN;m89nk;p_SuZTPv`#?Aa%ou!fG_arUTof=kLoj>@oYZm{$I3%1uy1uA7-x1|n%I8J9Lbb<5 z1i3N)iq4YnB7bbv8^7{ya;UFG9akMKC>>IZOab3?V+}IntWSPAYegwErT9pk>i{DN{J{6F zZrm5|f+xX=Na%+}nxjkBQwkaw&<@>Dpk2g!Hg|>aNpFSJ;vtEyEcTjW0UzbNrbJi5 z(>M}+9KBF~8y3D-F$ABU(O?;mpYy<;T>*~Gg^3Rf8k@DBMhOT7xYo!%` zq!ov;nnRUIVK6hPv!NF1SCU=z`MG2eKc!OihF0_jDXs)wGsQKE^{5oRi$vGo&ypAJ zRiOgdcNovhI@PPicfOWijW1s9N~w7Q+O#UTWa_jjg_Adm*~#A#wHc|;!7Ur=2f>}r zOi$aC9vjL-ujMDjZpn~PJ znu2{ko-Mx4aD+|~&I$-cG0X53GRbg4oLJ=xn2z6%v^T z`&-|2bKhqLqg0a`c{VvN1BZ+^_6=oMZ9?&gmY%K}73$BScxnNK%2_xehF@;!=|j|N z?y*>!e?FzK6(bPgSOfW_X<9Y?A)qbxxc>t!fg8bmYdW~%G?ttV%JxTQF-1nzCT2_3 zCaO|Xwb^5|mU^dbxgp#|6)VMd$R>*IlP#BsZcwmzJ5=e_+-Lw!s8=F;OO}mJbki7L%i-LR&d%EUmY%diiV4Md{<2E)t+Z|>RyGm-OgTA1Yp<>#>T zlr{)gUg`+d0Ugb0K}U01AZU*|eO&ih>7qGnyw-6X`;!tE=B!wK=c&+Oez>ozm$eLJ zOX54GxZ1I>9II;!0j;Ai1g)se0& z{i__gDfu4wl-T|gqG4vQEy z#8xVZ+_p)-Rx^}vFrT_z&d*JD-KXtNRf?hoXoBqv(jyt@0zV$ zlu|#H@9M_BClmy6l=>3Sbh)OpOQg(3-TW5#D@y%8diZd@c$zDgH*&lBuv){dej_M{ zMF7x$zIQV3(f8Ug-oOK<5^(=iz{bkFX3aUAD5#E4^SWG`-qvJzYKE&5>qKY-n$q4^ zuh4a?#@drY8w2xO&@{>*+Sjw#^|i)wNwomYalCYfE6F)dm1S}a{U}C}0;30^M#u5I znXWyIR6&mEK#%^XY+Oh@6vnI%v<+LIB54vrJy zSigE#zXBecFxz#SJwPP2O`FYcgGv9$gtG+GGW4#)WSD4%>@(nP4UA^u#H3|*4mvgy z&}3QQUm=Rsn%K0i^RAEpH?7|jzi`v~J)SYomEwF{AmfexPi6ARJMyRVkLI~vs<1Zo zeR;bpSYww-Q`F-0l7jkKuR3-^i__`6=0evF_KzYgV$_uAN;nyRgDJ(5bm$`23#|4C z<>25*=AtoTggi&skdzkx;~Jqu0iGjlO$xADQIw;XD2?nqJrf>?#WRWn?MUYqR%@>J zHEE9~rAQkJkoHtkplCy>N&9LFd@Zt&AYtu!z!X-|x^o0Sm<%rhMf?;N#f#R(w`1i5 zRW)(FDaLM6iiDs5#dwSqC^4Ya6a$Y-E==e&gq^TsVmn_o8GJ}ekpUDSgRe+|VgRL- z!J>WHZg$hi%8c}v$snARA_FKu263c7F@RE&0iMaM!b2)svEKv&S6H!=`XY2R)GrLT zuGr(qid|5UEA~M`wwp%qqBX9JxW9$l(k1)X#E)Ug-kL8Cb)99|q&>K9pV%zrI@j&k zUz+i3)-jk3A!Kp!p0duR!$T|tETT|ct^m-*yS*ZRd;{z*c&n~wu1+h|>$1r;i7g`a zz*;g*>9~C)WIHDes>k4mWh5fvn9FfH*$20l!<$=N)q_weUa?@iBt7Sk0@V73TX-W>G7!zOrh8Sb$R z8YR~^gGS0T2TIN6@xqi*zS|ylorM>J2|Y1SAm%qw8xjndGp71}+v{2u#JmJ7-3lg- zwG<%=}Sk+sS>UhSJ>)`DTBUz6mK=vmC2TqLLpIM9N=0*fX$$$m zXIypo{&pRQ>klFM9JY^C7E%eyjyZ+^k`h~5q9$MVPebnM462n9cVxWq*};woo7NSTegdF4zOO5Hc^sB0y>lSXO< zC{E_xUv$lOPF7`^9M{f!2X{-^^O-j=wCf;R;9S7rj9dj<~gSjYd-|i=p;yhG&xVg?CeNN6p zwFZ*#fjli#4kesc3UjinAOjIJl#*TPT5p2g1{|I}3YjW8{Y?b%4J3 zT4tCX31?_oCh19}6iGt?PM``%0n)}bh&YAY zL6DHtkuJBl05MC&4G;TBAqsGhDZsO&0Bg1GemiX(&fuz0Y-KaJ8bGhY435;7Gq}s6 ztDeCL3UUT_QT(bghUa|f>Jb+#{zGSQSCw;dn8Bs`KKjtL+`%pjJacOur*Mn4de=RL zLudP_d8aV;ts?7#DIC+7K2|XT&A}didLIV*e#2?xJO5GWbWT*;UZ=H~6a6zrh9^=< z&WZjGwAnmqNu;22qBeH2IQ2*sP@H-|C(u53?bje#{W;|NhEjBMHUwwjc717?IgA}E zXAT#~@a(>Y?KJq*@Jkp*@cQrGlmbkOv~*F}OHUmux6oRQH77-PSP{+Ly`@w#FJbO&tYF;qywbN*6K%h2<3UwP&5rij+xV<(qXRsR=ggVZ zI8JHY{A7kO=gYrwonsULF;=E|w2iX;OJ)1@7Gq^VCiap68E<$cp6d^bB2HmM{z1r% z5&1{)3nTK6ASE1Tt0W@-_?_!98j*dFw9e9)a~yF^vEz#g>ktL?vt9M{4MyXgcVCU= z5y3_<&;B)~79VxhmCa%mAGt+P31g%FI2o7w|KNI?rO_H9!lvgIw9sI)NrbMRq!5E2 zJhuEh?B5L`a1}aRj>FKYHHE9)WU6~Sn`XyM?@%v5ekLhI^0!LzO9)(%ztu_}UlzQF zU}9|L&^D27H)UAdd*MX(I6*>kI6mw*+jx|eq7eI~5T^)S2?4e6Y9FLOhkb2FLegKD zq<pr&U^;G9BL=~p2R!z2A8C*nwz~eGbxkMRL1^O%#qPnz z9CnaEaqf9Q0O;-msR!p3pDjq`WnhuKW_=oe<-5eUpQiYT>o{OEruV_NhY0Gna&}xxeut(v7a1uKXMz@P>I@1*u58 z%(47W!V%m_?u@`q87G{E%lWG+q+@y5cu*J3;U|7o#I#%FP)_Q|pImAue-(V5O3ccTW`3lJZT1muvOmmJW+Z)5i%fWoxEgWAWNgpqFH@eZ9 zVt1qSc)7dLWV{^78;>_f@HEJ7o>1?yT25xa|1j2B4g>$1S zg&e|_83P=T04sdQ<55)<7`yd7v^j@VbMR>zrCsxY18`}T>q=mR3)+D=gNa$DnE5j5 z8T}mWV+B!(uv&^mgj~eGKVIx-4B%bkjosQ+elFg)jr~Ha!pc+oksnAfIy!$;aMOiq zH!z-JArovagww$v$BTqRH-3)m)d*YjbpK`0gE+YG?Rfck_?bjwkDd&dr^Oqwd~=d9 zi8ZBEg%BzHd}9zIMZrxWo@!`3$GR#o*{4gHP^l1R+Z#@>3Nbg?xJMst3X#^>7{$g@ zszL~u5eXs2Dmd*-1qw`r7+bjz<{^oZN(f9CDGQmZx;UO+&6(K?E`|@R(}_OKro02C zkT0r*et^-hrrE1A`L2}d{q@ymkC-oegx(nJEv5tiF3PS z;up^Cj!lpsDv+d)pe8<4c!y7FZuE=B5*cR#6kpBc=l9RZaJ-u7|55>d!QsB9U$+pH zkHeoC=7$Kz3HZ;-8G)}3M45q$_;=tNiOX=?+&jFimC^h9P8Q2!=pD$W0LTbw&V%Aa z93Hj1AhsWH3;(iMu;EhBA%?(^apVgE(MYIP&LjJV^yjUzvzxJNLQrh??>y&G!~Bfk zF9j99L`+;Y|%Ut=9L8_gKh_vwhUB)0I zo)*Y7#hZySyCvcATw>xej3O*&43V@%pQtTBThfmoq*`GZ}TCsgaS z<3g9I{8WGA2Npb0RmV^xdSR_hdv(V|dHDXgQVb3(c<>yYRUAAQhsy>T17NEK64GT^jm5wqxu!B}Oyhr!2)?D8K3{Fk& z$_|s#^D%C>C@7s;lBt;j9H{G_#y%iOLQL>tBz?gOH%Y$(Ie``sarf7DG-N*!6r>NO zlz!3u*#--nq}&PBP-Bu@Eyr35;3!1G@D|!6Nq@&!V*qPPFp$2eD&^l5?=E7!NI8=3 zVUo_a7MQX_Dau~>V0JRgB`8Q+)CJl+VuG=S%_gNtd4@@OxwXKg45g^>4Wtx_ifTmR zf9=U$z#bt;Nc$m^_A}N3pj}WBP)LtFBas~^7)W1KCG>HR;ygh@`k$KgFIx*t*`X9= z|C^K|ZBb3qKKNTfG(RxK7|NpaY{rbrlg3Q87BuBWB_MmAB;AG-B56@eiCx~zJ%SA; zI4E_0lk!+=fhjeVX0)B&olPgDNLo}grA~$|ukgB#@oX_cLfZ39+H0%@CT%E1+S^De z(iYVuZA=7I5dv^S<aTj>1UNk|UM31DFbXtwn#f*S2z}`T z0?=M|XN3t2{}H@Cd|iRjmlyrDCd^V3M~@?oYgXgmem&^A2UHBD5l_!|I^R@6Opu>n z{Hh>wUMp7k>?Z-m6+W!#e=$;cL}+*~-=z{`rp}^ng)%i0&eFqg#WgewCk4A)?uPOc zj1+*%PcWL0@{Ik)R6Y4txhEiIJMcVI(rlx>1GFu_zPKVpKvkP3Fo2CX%WPqDeu>fC z4v67lbBu#dA`PtD#5s_}-^R3H*+d9AkB6K`MH1`h8cQwEqaPRzd9QiK7M@LVrC^eyySGU?%i|2ik%15OxS7 z0O$*6dL%dC*EW|_^L1ZpY=_G>2vgJtezNf~feL+SZ}YXwjag2D4c2Q^*oYs@2HF@Ga{X&aTDYQ!+M*ieN|>0 z*Vr5)CVJY;$+FYWBn7C87cOT%$L=Cf)CHj9wP6$;!Xmt;wZYMfZ6oL+HtK+m4`)+! z>Bnbpslo5sWF%?__})!MWA+%SDtuXcR4Gq?ZnE5G1YiDcsQczxN*(5@Y~X{wO!;6; zu>oRuF*jak6pG?RjH#BVe=?aLd;;czXNf3a$|>4MM3k>5%WoP)d@KAhB!l>wdEA5& zUw7WP*}_c(0Sy*kU_73Ex?!XU1mX)W{-q=5cNRHCIV4&qY>Ko_7%4!37mF9S8&5H} zHg6`y7zi3oQ4v{Bn}XWYUgwGT8Yx71<_pEZ1Z_&0B;DyA#`+VoXimUHHB(GfGX-R< zao6QNLvo53g`(7_zwgL+L9IUVJnI&BZ^vYi|4gkuUD#B@NN8NoBl2s7eAh0c9R@OZ zQYt|i-#p1q*g(9B2v4bR;f!%N6bO>I%a2SwALL89-*{PLn+bDN`bJaf8%cra626^L zIXyJChk&t906yxE;;TOK96?7V0y_2yimpv|7qF8A(@z-HO)*j36p-<-ahOqna_DcS zNQeHG5JvTWP1XAgsuu@rn?pB}Thf#`Iy42KcGoHG;^&B=`;2ZHYcSR3&9PIZH^-6! zkam#Xb}C=@a&aTpo)n-Tr%fe(+;b}WF-j`Z>co?qN=bnMT7oiAmKaH>qa^?xEkV&i zp5}a_$K618P34O{?ncZ_s-aNRsZg_|P|&%af6SnfNr{9uq&(1uHb4w_J#HLg6dEw3 zwuv8j!ho(rBtbiFppxvGT4iK1AE2hh(U25?hO7$&&2EB*Z0<8UY3y~v7kkJnrXgP; z1wz{L*0WmbXQ%R{neHa+94SP-eL|)ECZM;RXN(ral;%swzykF~S)kr*fEcbnYiwW? z8qk{_3diL{M0ZY8o`{MInMV97dRmo=YcBnYQb)y604naqfZ}|`FBq#e)|0SAopqfi zoxdw7kdj{Rl;RjZ4L)3RMI^G3q!_i9Lq(l9EzkuvUDX?rc|n?#v@1XVrV+;|6V(A` z5!%=RKql+}6dh&S*|~lV9=^~WudkfOTP}1bvAaoKl>>;weKXyJSBxbd0J zz9IF{q!&z+ULXZ1F3!^b0YSvA`8Q2h&WD=&i;5dMJutNqA5{~Jc9zm!kQSvpaBxl} zWYL%)4fYs{i8{6c%*%Bt6eoP@1JN#ov>1pO#RZZvJo&V-%mVdOsLnq*ZM0;W|4Jd@ z_Zq`1Qn>f`8U-x(Un_t2mJ#bDLYWK0Q-9QG!iq?3uo5JA#KMpu^P_J=`kesGg-Q0d z8i{Plzt+a~|MZUGwviAk(<>j==)pGr??{|1$w{$@g`NX5B)8+C=`b()GN%jMLr9^g zKQNudttX~q+%hLdb$RNskl^xDp>_G9(-*4qq7RHvGFLL6O{dKc=BHP7OR&fQW}L!a zCtNExKYXq|ppxd}!u%6byK?=52IYl+m5^xNxK}&&{r`qU3_tf|wFry!*mplyeHSOz zD?TyKvs(G84`SD?nJ=SpO;Ui}sxbjzw*pM;RumJv6$QYYcLk#W6}2+*`zIlh{4*2cIAJS?_VV4U9>Ec`bgCS zADmiJK5AtBo6twa0XmMX6dlFdxzUm0h;+fh&_+WWvRW?Xm*5mKgQ(YZkzO9}!Ury3 zX#MVzWrC>$LlaR>Xd)XRhTmQ8h-MV3Ow^UgfhMA8XrdY1(Z^C*D*5T5)%Zp3SOJ%v zEdJgY$8rcEj95cxTW)bF4?n0+geTB`>)ntS9?ghIFx0ZHmtW%n-9UtfZ)LS30f)c@ z89o79?N)iR=%+k9Sp-LB*8Oa>mLGMkA;MrNI*^&cLIqH5iMHoG%X*b*5A(<$jTE+* z)WEU&K`Q=}U<&cHoY+zmuL9i<%^3jS{_h~QkPlw%y$#-564y%K?IMzmXaBV$<3{ag zN-7_0)TRfqKkayU&goYmCf?}zm6W0-aLQ5BkW-FGBcM8t%?LAyN5vYd8P+LBf2sLj z`SX7njhuvsIl!jglatNT2yxk3IHAUUe?!8S)Zp4bMkecR#}$om02;q~W?=^lzH-Kq zq>^w(I5Agt%@|n`J5k&aKfMC>rp@jg3o=9#nFo(oPG&asN2SLJ;s``--we$?Omi+$ zRB7AqRABS;2uv=tMSL4vAj3!<(fWqGZjie*+hVUGR1hX`{YisS{J?IwI;-{jPXzJT zgWLlwgp^wL5<;k!Mf}BT?*0~Rh)9ijmta`6K2NYkL;@jw!S1mZ?0{a#JYleO0jif^ zo^}>)YD@@mm+-I<_ipwfp^Y){Y>2xRJ5Qj3qXW?Rfvq{c`Q94tnsow|Hl_NXk^Y^k z_D513-Ac^cAWp9fb;nvb2Bap7#vCd2yWr;KQ#$e^&*`DH@+!7O?u=eBJLYGyW9nD) z8S+PtiSp=G8#nYbJbKku{KBJGZQb%%{qG`!j^Eq=H9>xF|8bAQk_@4W{B3_lEnl`pxsi^6w(ux$G9jLZ;#?;c1L> z(^Pyhse%bWFBFSZyvt2e@hk0E%N3SN#qY9XZFkEQ=zeQ~nM{OINUwGaC54zv1UR0~ z_Dg`d`1c4F%K4T_`wMGeHomXwf-)Q5(pNjp-As3$RKlBM$ALrc&Fnn|Cd2YcKB1j^BqMb=j8+5K*904f z#*=(vd-wAeL>y!=VIQH#UU$M?1l;-?EloS2n46jV>IKUEaNwJi5XP7Q;w%*cFuuQ4 z-pT#2#u{3Yv-E@lIU!6S1vnwZdlNeVR3_~^k#d|8wu57T;?6`&+QU7*-Q4XRU=*3O zze!-zq&={~RR(2)s|*_;MqZdmpwv#2h!C==%R*Tw0pe2QR1cWd5DGl0r+YjrA!xWn zp%~|Tx(8XR;Iyger!&cH+5cEiY-atM?yg_4a*qsmGAsYr%D4$ZMFG!&lrbn*Y#`PJ zwTb%~pYG*O(b%(u8ZfGuma_rOZ9xh}C1QI2cOn8RpQ54B(#3_01WL`$3T+;aTXF=MBZ+zgLE{vPs(eDJ z5>HIj800>wvDQ|SSy~I8mg$aTEeIUN$24{?0>!Cw3!X97hOHL!BM3IehZa093nrnI zwzQHziLK`s@<%oq$;=>C(Nxn4WiLB7C^rfcnPT|}XGFgp>TXg?St?4-6I&EYOHn>( zDH|Y$Z^?FNTExMoM%>fA8Cy>zKucAq?8|}PM4_tk?tiWP-OJ!69rq2%*%8jmP z2oc-@c*@iPZgRa;h+6=lgwis1?>MCd^TP=$7;bS<06IidAV>NZZ_svjCO75)jw0owXt`@t>aZfYWQJZQz6^>|Vw-nwT$Bz) znc$9EBSKdAl77)NGQ~tA+W;~A&T()`oD z`jPSO0SQX_+S2m~7k>twfW%@bOTVDhj#rzORa+S3i^z39ud$hgH^#N1A~`4(kpkgm zW(NHZ0v0~113qr9QGC@OHxqQ!A)ueGH8qY=bj+adA((!`82l(EYTE{g;oYXV@3jzA zj{QoJbnN4VI;!|3qT;s#Dz^ExdBq83h<;50LcuUU1B02TLj2=~Or-xw7^8lFHTC-| zDFAr~={1XGB0aL$>do-}U0RXp4O%SE^O}P_rqPug|w{R(nNRvMeL48Bv^hbOSh`;wT4HoDC4ezn|s)52H|} zxC^G@z9yoe;=WL#=s#4YIP;JZC5?)s094!#LCxm>+vmFB{6TDq@@7!n3@MQE zid=eXiJ41JBgGigTb8Ifuimu;W4f61id;HTo_SmXxL`M+TvRv6A;hs806KO9ijG1B zlIhx1-eRG*fWt;@AV)@P-yKWc12pyu;ffYLW?J+ZDL`RyU;85v zL!{C_A*HCe52&ygl;ZGyaur6*V;sN)4N95dDE$|qi?#$zR58Uw725#jq?tl-Hl=du z(KD3q;(Uza0?8PTcP$erojErlwLwp2GMgaFne*klU@}XgsQSZJ)pN{*4zW_q(g)6v zeQ6*mK&4D108|QKqEaYk-WNuTP=bhwP>P^D?)Dkd;}#Hf3?p-S-a6>`DiM0;j4Hg& zJR3ymqt{UY#*%)5WH0~ni(?w}0O5;1_lVi@M@Rv-{1^dX%K;NxPBGCPYydM2N}=cu zm=M8J8XU&9kU14LEO-ix1W>Sjdc+xg^dtA4QTpEzXzFC1}geR$ZG|QB5(_(vW`ck=eWlEj z`f5VRp}vwSsW!9xE8I#I2G0POJ_y&lXWEGjphQMVBGfasB^FwpO?w!=bV?-pL0`wT zYy3>vHJmd^*Z3*nmQcb}^^9c#N_s{+U$edL>A`HL9UHT++h)mFxs8;f-w!RVmJ4>J6o_J9+`<$HMW{^Z&uYYky?je_PIAYqizeh zA05}~E3n$I)uV2c*PM__V(lqel2xmDGLEu@@Yl9`3*V$?+)aX&8}AfsF4F({_O7AcZL|O;yI~A)Tx}$RjQp zdH+TC5&hxY#7&;D{E3&`z1X9Kx)}Pjy*&G6_dd3lzyl^Bgu6+?58ftcd%JIw*N7Z_ z#l2BKi45ZT%vas**xQ7VU=Vg10RBw4m!EpYUBEwUJq$jdBZ!r8>@GRJK{!r?^nK=Q z?r(JVJE@G#_!%y*aU1Ms0!KT;?q+q~>P`2}jLi;sDo11g%=f?P&aPOc=<@I&-uk3F zi^W&0^1(@W-%6^8jp$SxwgZIWZ~T0wSw(#8kQp|7?PtE@w7X?R?B7qj$FboyZ2f1m zGtnkjrbp8yt|~p^wI|AFOw;bVP2Q6azJv3S#24Z!@vJsbD(*eOzKIEhZf0)V{48nH zEE%4cK`0fEt;6jDc<%|xi;(2IB@v_oHQsx&N38N(yRX z)X(L=zw7QDjYTru?oX^6Vepl`xcDS2*MIQ|{1Q*Je%0~`LHi*53EX@lAmru~QD)$0 z_`pHje4@j@;z89eH+GjtNki+m{m@7HijP$Bo7dhVK{f!gy8g#f9ndWPPnXn8{?kY9 zZ0FZPC~V|^XLId|X}!xIeu@ntKqwZY-l~%8K2jhqIoa^%s`|X_yG6;o=O^yxoWBwV zy!1Bj0G@a_H#k;6(G|=G%D+@-zM@av<1}ZrIYit*#kfF4^L{Q;aW>vp;v4yy`-tYO z^)J=UyRj_Q*CkDXYY84rtj7)RQ&olq|6ECyS69Rwc+i5V|IzQnP2(by(_H0XvjeEXD}cixOv#Xs9yp~ zFtY?*c+Ma0czz{zLGu_3N3(lC1^&jlvGsY$m+tA&|5dsczi_7W%WU*^?H6C#1$RHq zA!-O;Z!=DC9u0p2zAhld*F~9uOrbG18A)>j4p^&vf6I=%%|-VFIA~OM(cMd%FXT+) z5p%tXjuz0GtB+4k3lZXgBX5@%@{CJbkixbLO6aPbpC9HiFXY*(pyC($YVi&EDt~tE z)rNfEa&I1wSl$+`GCiv@He0Tn4KJv`()E9HwC@R}!v#`0F)>;&HWo0g&c@GtIJdfmCaY+-%}R)4N? zsK{&X$$Io$x!RdD*Ab~F&y~*ukNeHN{{O$%3kzcl5*$%;gUeThq%!z7;J;UYcW2e= zC;-%|HRs9;UYv8~gQN-dJSW*;Qcbu$8gNpxl%_I_`-ioN+7NXwT=)YpjQ zt2Z~eA)y_fx#oR4@WZOgGP^2WX8Wc|Rr)&V9>}ZjCiO6c;6*#%*n8J5RoSl`oXOxt zJK%tL(avQIujMoQHP4>Q9l`i!j=X2*n`)jtl}3`sZYYv0;wN+FxALv6 z?rE>F??@9P=X$1OT~q+kP7IJY#&2HrO*i4mOnyXzyRZ&d8Ni3DqdCIi(r*5@r=-W zCXIlZl znbMbYeMzlc_iHSN;DBz;msN+{F1Le*kkT{d9`nMKsQ{H{ucni7=tb@Lq!U4D`sCZy zumo2Els5IWcYx010W2l9d1E;6!YydZtGK*JXlL0!coizYX<>okp}7y%}@{4zCy%M zYCUGE^%yCIHVoB2y4_3zkpiX952*APP@j7E?ebKVlH0t*6L`o34q)b7bofrj_ z=74eWKvd9ti0Hh?Rf-5WZ?LPJ@j?tIf4^$9U-4_YI7zVZ(}c|N8@sx(KK zGzXPJnu9>3ITCBf1#8M0c&2Jls^=b^4IyGEYYd!k=7&fr>LIc0wgYS;fkGWfC(V~z zT?19Y9Ql|Z+z^r)s-Wg%{|ke`QUQ;1kSbhqxX;svEwxt3(gyM~eLS&@VhhWK5dZ`f zaczz7cze&|aJvqnux<=k5I-{9MWEQ)vcKW3&JLYD&si#nDP4kcpGc`^E3fmrV{7wM zGe%b9)oMrABNijTGrqZJv`N;Em8+U9DZA+_X8nl2R+}z(_LeZ z1r|3q;CyO;&?o4b0XuIi|!#qfivef1GQQW9|aeNp81Gh0$O(kxE<6i~4)o z`F$i_nclqGiLimFEMC+l5E7ODQbxy_Fn&?j=XSY6*A~LC*r98U!2&+2fhQ?r$mnSa zb2)3fxAip~4SBU)Bv2YJs$!H!jI<|o4?4DkS|DEZ1ioIj6({so4Q0FlLH3wq8 zYtQtSzP?#7_hVlYYz!2yWP94M?+8?cqA-Ex-&qdjSC%^J+H1~d*KC#aFNL0G#M?0& z^81E)+Of!mmi~~XeaTx7_w=w}qh0SA?wPMQUdZc>@bqRklUmBp8ZA^kK}+LWuBQ>7 zwA2wL%$hUOGn7Of^Y9UEP%r-3U{9~|QJ!!Mb6Y4dEB<$Z+`9#x3po66G^imu71F#698HsKjE6lUmWXcX2BLx60bFn z2vOGJQakf$zU71}&d-(zfZr`-Hv1OOeVV=#9&8hN=le(nrS5yFx*rkhZjT*EB%ik~ zl=_mW$W9t zaeTcnm=|R=X~@2@Q^xt>1wt8~X%hmA;lF%pZf7B|$Z0!(FxLj;4sTavQVo zMan}1jn_hX>2yz5jyoWA7s+!^Vy<~)S}wL;5QC?ZFHiOicC-dkY1vJZS({2pwIZat zNm4?OgPthpj^bQ>w_hxy4aOeYpnZBW8%79<9*X#BnYl?8d{q3R%-n8{X&}i9nb4?w zQc*Q(3X!CQG%C%V+Z#zY$jXhgkOselFKyOWYaUasRBnl5SN|BLCd=6hr9HL)!WadhdD0W|o3ZZ+Ct;pC1Wn1yhZTB0 zw@?7Bn(q}I6jH&S@APJo`p!ji_*eve04}z#a^#2%&mO?)E>>Q9wAhpNFJY*O@91IA z7+p_U%-3CX$MLdL4cphD;Ui!b{{2kPz-Y@_(=-@tSco)Io$i7)rjdGxUzkSf!4J;z zq(pPkYW#!~w}1S0PI>|Mkh5;{yin<;&vQ4l=`$DJ|8SHj>&g0N);_jCA&4ox-0RWi^5XfPOnug3 zvemPxQp|M$Ox)?&N04xLUkgCEGAh zEM^XnL+-*52avlkS&J*%g^6$p$@_=hbd%9XNaNz$mwS38OcPML2a}^3DEDAm`kLM0 zS*x=_qz!V(wA*tZ8%CheGI<&i4)y$ZrRT*es!XY@iaw}R&Ppj8oD*c*CG4;2&yg41 zE>RGUF?f*xVBgGM%wfAG-}m@xPkoJTCx|HRk%84i^)01xIlG0F;)sLa%N+!$+_QO{ zln27DzQ0t>+4Sd2NddTFLjgFr;f75%kpR3QD~6y20vj-u8#bg+E*=Ax(5CP!TRpAWG(rzs zgoe14HmL|2FTN$HUs@7;O;`S8^uPuQ2=&DO^!S4Vqy1L zLd7auirq(O?kMbpkw9jCwMO`uyBq{!_MZczg29yj?xQw2%1Y%Fe-R7^;sEu0h~apE z`c)zr4lgeWfPZ+wN7B;Edac#}yHqYVzaaQZzvpN}zE}FiYlA+4h7Bm_AM=5#s{9us z5UxSqT`C292^`TcAg)1TmnnBe0qY6?5wM-_?TL$JOj zCDNJ1p;o=mGVXc|Zg=UY>ZxUj-fJ0g_3UK(pmfR`Q3ed=xE^|fa2D&KI+bGke1|=^>iRL@5Lg9O zipWck!79iy+cRATrt)~0?nA*4S3w_%U$_eT2p4cJ2{Y6i@ zM3NJOfNJ(aw-m?f_RjGitAk&7)TqVhg3CGh6F6!lAmpf#C^K-`b%?Kf#nVDR1oJ;} zs_w>*=Y%I&v-z+`__^2(!xU$hn1PPqM_=`nI$-_Bi|(I1gr{a_H+9A=hZ1aI4BYFC1Pjz1QnrFv#oKi`<+Z!tgbmZesdBVdi zBFckl=N?Xv;)!nv~RK)p4j_32Umh<9e`RROnwY=+joI4;Zs?BMULF;5pu2eVs zZcH~mFwBw825A^NJar*DvLE9Z!KCLZ3 z(pXE??^%vvxYj>G;CwYorcRqu=*@E#Y&0HTE>AlZMYL!9p4UC~_{Z;f#$K;SEq>QC z9bVb``dv?FC#RC+yf$@6t>^4E+_+qxds+v=Pngn*|MQ;bQRit|5084{gOr8#%5SR5 zcvxo*G*MjbB@XL=w$6Rv8LZEQ)_JD%*NdR+?)(h-A{Mop*&mI<Q0Ov`q9 zDMH$NuHkSIm7f-FxjcH_v&FfbVhN6V=^eP;;@m(>M14^rc0!!HXvz7>hM|@6(hH`P zI}0~EpP>jy^eL0*aaw{zMG3so?0k=wAkn9gsMcQm)3tn}9ur-K{&08YbmH(@yzGI( z$PK3(hVU1@@`TiE3MADl&HwPyzawfpDGd$|o}||V-HH=0`%Bt~iq2G*yTA5?MvB^U zuO;YC_|^0dzRGK~PDl}88qy+(;Lyvjg|+l)7d<~~&QMX!Kd|HlImEa#)S2M}kw-WrgtDg2&{Isjnl6ZRb;aulvJH7)1;YaTp5NEA% zW=TmhpEPPvQ>V*b10<^cqn(3l!R?jcfAynhtd;)x7YdSj`mnH@ovSOszxtCW*@~~^ z*-;7p@t-}3R(#dsgLZs>i|d$sH_h+l>0P~bxcI)y`Jx>gTD$yLPq~%4h|TfM1S&eC zd6eE_YRI+S?mSPa;gE`-j-C}@TwSEx;e(5)o(^*UMKRCMa}UvfyAxN-VZV_Qu+*TN z6ZxC}cuwlISK!x!&gd1y(;?hV(W6#WF>)oYkc)|+J9%Eq!Y+FF3QW;C!zqa~-@%23 zM@BVhqjy??Z&o|I&|>7!p(+l26bF2~8aQB14LES^wQk+@@hkYQK{Jw^xfN)RtBPj6 zqFK78q>Ydo_g5-PEi#Mx;uZLjrgMpnLtBoy#f4R|Sq1gPC!0b!;*(8ab2YLc)~cMm z?uEmJWyI3mNiD;V&NiCaY=y^VnpF3GqHlVvdX)136-f1$LllfX{s2D|>TP4iM}HQt zWI12A;|B@C+})_Ki?s^84AtBD3B?8v90G3x-R<;tx1u8TpPk-koZnM?A&mp5^Wt?i z8(3?A{C%A_tt75zivDi6cZd}g<%puFrW_|~dYf2LQI5n2Z#!o)#WzVm8sY6(3I3<$ zCEc7ID#1SxS!p{#i=q6;w?)mI1MHQsv6IG6u5V?NcXoO*e3Dbt);Z2z1Jqes%Ufi{ zw}l7u9GS&ka3p{iz_w}55=!&n)uI%>X6g&go%1MIXh1Jn$;+aPyHu!<<6LFOh4be} zV!R7%sNy>P@3)ma;JlaO3u_44*r}|-Kn35>pNi^g&I6Uz*t4S~*2==x@>(*}XK#5O z-y5;sFfHsjAqs2QcF!mB;CS!7&eH@gR)yVo>%Mn|@Uq{EmgvV7?|;^n%7{^Q4zW6ubcYXMS*;w-Y}y!V#+faHo7h?y*Ggf@)577jbWl z$<^8{H*ia${01rl3>wq`Rt!$*Ff)V{-gmGA74U5*U;59)SM9 z0nTGM2hw8X(6=fM!xabIDgzEV7Yge;EgUegLGv)M(dNm(Mj_@oz)4#1y*j`A)3r%F zH>miCb2gO-1r|@a>7{q^)2oeE&ZV?iYwew)FOmY+uCTybeOIu0)-6g6v*xv6vw4Fw zZ!0T56;AJ`e6ZWhz6&>Ytrf6KM>L<&*7>Bpf><}U@iw;NLu5+kr+)W#b-r2&{xfa8 z{jK;I^gg7h81!cIJ?$VUS#*W6w|*WbbC)Q-U-mp!+|pVBqhyZ{_f_ZJUwomv^KW}C z2axC5+dUGj)l`#f-c1}^@WC2q>a&K{8aU~CuA{f9Gs#{9l+?46*M^TRIeiRT(zX(O zXJ_wFD}B}SzLnqyck!lM@v-5}UV0(hIl2;jkSDgf3^*WMSMM;Vs}ihBUA^Nfp_(35 z+|GG>Mf~#aUc-uRiz}v6(hef;Jpb;Al4#wzfs$0g{T>Py7SJ~Eqv_yXcKjUYK0B(u z;ck93#yj7J8wl=)X$1`KPyvIxmADG-XY4gVn!0_x1hMNz?*&AMmckbu?G3+8C zX@>T({k=1sR|(u2+QWF$0p3CS#k*yEzh^)U<9l688Q(d;yTqZbg5yFb^m=gfV9$Zx z5+|i^5A})C2`rL{P_G9;#1Tn92=kb$`go96)0{0_n>6fWqAkd z`KvG?<}_%D2=&^uDrnDK6&On(FP6+BW>l*w7+|=!Fu-sR&BSm|n~CAxX@NxMO^@a= zIo^CL`1~}OOg0vhnD>kM2hYL7ymK_?ekwI;b+6Q_b1yB)yE3C0FWVfPpucD~_hnj) z%{^L0b5B{C+qjk*Da@O+fFt_7m7~}U5HD*wzoeXSGXN@x9H3Q19LuuBwWQZZc@wqY zdE#go9sZ=1QOsYf5VP9qfK^WCPrtcRG0_edF~xeqDhJx(!Wi!*D;VwYkkt->oSb%9 z%x-$=XJIiZGF~6UVqc`>oPAakr-vZXo8!tfLx9bdDOZWPiL2$TBahY+jn*fuu3}!} zR;|Wa$Jo`FpmUC-Bw(*{h(2t!Oy*>)Rx*mLoO3fpRWfd}$=J@;#blkt* z2V~)O59dBwENwbQYpK5sa=|rd&R1zMHtof#ns$aXO&qIGe%C}so_&1hH18xUM;yCa zPWKi#zoMKl_V43APxlVC;;R|W?{<7$HmP>G%Ns0ytKAE>hFH}ky~_o|uBGuPO1$Cq zIOFa3VFJ;AzIzehHQBqEHweiNvl6h41ZJxrrgFmirjD<=$D5`(+fyc>_!e-5ly?a{ z)%2qmmWmm)6!Z?e@8Ywm?rW;>tHEn9gB>LH1^MNZ-u z`16feI(;SnFcF|a;Lj}MRmh($*eKCfBFYLZUNOr^HH)w^Zu3LZ>Lw#a{HZB6S8>Z0 z37!{J1wlhcs_$b}<3k?*!qkEMbeB{o-Qh#ES~Kh+X7k!Qg;UW#^;ORkEtO=QB{Cr)!~f>@$@;~ zTl8~CIz#^yeJ73Y>=@MmJ_1Oa>uu`*mGbbU1)2Qux!xYme*)6|wuYn~|0H0O#VXfz zr=t96#}m%5wSLioT_8Ub?-XF%Kr}D$p!~%w$h=G=Zoc={>r5|g*#0Qv_tskw!zZ1F z@6-R9?+p*5T+Ayq=50^J%w+^5Efd$8S87=C@JfwGdFzGVJ6MJgytnw%mmgi|9b8Mb z#5{)8ZmsCPad@Lfw1tpqYUf%$f04H+`nQTIH=qnt+(6ZrG&-ga%+Yx9jG~KeMhKQU z@F$Sq77&u)7G(yqgI3&R#ICj7r7>xDVk6#a{nZFQXQ?+ypSxE0VupSjN-G`4kpk@( z_i8vmG(M^Q{7jBlYH&di9eN$tp7WYlYHUP6Wb%#3%^R@E!3<~jU{J?eV!w33kR!#qQt-LAYTd+Oe zlmTD%R^u(7DS`)Et=DCwZh?z74tTuv#dR5xyy#d_2;aWWTdqfy$(u52mnlEV3oDSX z&uJ0-%r=-O<8_?Z2F;Ju6Ut-~IpVum#=AXO7|rKx@J_tGUcO*M(X|lWS;p6G^rkT< z5ukXRH!CVl0H{T42w{5Z!DYO7llN`bmsE({SOCw?U-l%kAq1NDtv3tqoW5KRfU0@r|uPB{AveWxy(EA`8-+9ZW zXdW@Ppb`6!$gceJUAq!LmrB%A%XrS9q6x5I@?Ot{B+$JUz;0T<8vK#_y)D=o!Wg)KRSJ$-Gyvsx0POJ@K ztaR0ipMS{Pm18&VwoY_o;cL4Nc~g1OmT!~z&L?_@-iW@iH#b|y_ucPp&YBSsP-9sF zKwa%-Y>b|~PP*Fiz0flL&Hn#8SDP4MfQLrR9_riws5eLpS_$It9UBYVvb%|-N?9;( z4k&ArRF)&P3|Furn;6AAy8cp+SRpKwq}8;u0J31E`vv8 zNVOaFFn(oZYK;IBsxp3RCe_c`mcCrv)2fg z;HbUKufF2#z}_ctto`zO`QX}@qyQYhDaQ}DpcKEW5^}+w7ht4|6PSt#|BMUk`5ln!TY2`VZnb%XrkEQ1svaZvz=mDo^Hpol}MpE%yhQ-yVs z9w=N>(+llUXOqt3*(63PaOe;X_2KKe_F&;HQ36|@MOq*@!++)NJBEPMNIX)h3FeV_ z`_7I{-v6+rL|`?+x|=}71WRAK0q$Xgo=MR`5I8B@KjAuOSkirY%eTBCY%$>{=JCE! z0M*%U0tRhn#oaFe*evsMA6l{K*@D)5%Dd2?yT0qKtNHkdcfBLo(>5Bl6b&;W^W+BH zd5?KaVfuTh0m!`g-S+kQo$q-kYbW`o_q_S+v_iyn2_b17+j--ELo)3H?>FqLs%e=w z?tCt3MOQAKIF;Q24uvMh66Kf;qsl?8=6&Ri)0nmqlt{uPsc7CkL@T0JYfPL!NUyz- z7kuK)V$rtxr1|D)f~bvBqcs&~MU8I#)O(7xR2X(unxBC+m9(NOr=^-7uk30{L0SQ8 zX*lx4hFH1vk^9Pn1QhppAVT8zg#SI~t);Pif?et>%+jZ9l&O~~ssQ?uI`y=8qr5YH zi7MwXVouc;LL0=>dpIpywGp@6wFUg(Pu{Njyp8fIf_b#kCxs2=F{j-d@t6~PfR+l9 z_fe7uD9IRpZEn3}K^IRq0bO~z>G(!G-NatElX``cdPkDd7eGLR15I$xS=!g$I95SA zJkIp(MtSG__k?8eiNdKGrT7~liL*;U5zj7xVB+kOg=Eq{cjew zdZkYnRKm0{xv-z5UY;;<`uAS9K4z2r(sLXkvM#e|iau%+@tP@{z`$zP=;-<2eVA3@Tl zJIEnYhZd6PMj$`B5s_cI5e4|&sD3Ensm8y*2{dPT;ZO^faH7-AW<)RxLE%K{ZD2lA zvs`&#rFCCuKBK<9?j)ApDWf1Qpl)eUXlbnFyl&itPR{$)`~qwh{I$Ws$^A!>%kEp)P6u*06jE{+!y>tiVMMnW!)(gNL%bKG3ML1!*9c?V zRN1_^jL`DIY;c~&-nZ2uQz-L}C{kxF#ArCC5)SR5p7QF~g|jvG8=-{#`6uZd>?cy7 z`m=Mh?9btw1Fj>-kkHMjBi z_u4GGb01P4yK_2~EemCO0g3xI z;{geFFR28K%)37C*(~L{YqOFIKV3d=MK|Z$XYGRdhBqk))`ETmIA6$Tw`PBkdMMj3 zL^eHWi@$%DHY@0mpdx9COve78YC}MBKDnR;BOs2^vQ_hf7Oegj;(j7pTF}JU`EK(9 zZh@k4E}QK=E8DC0-zcB7APWw$N{4)t$iG`w-pV3)7ts(Q0p{Pc#4pUhXYssN1u1Nu zSTSL88RpAnh56i(TCl3(X48AA1qa!5(hyB-HceIl|H5n4)*ISv8p?ZaxC)nE9$9b; zyG>D-yG@m_GiGg(yG{4EDR`2tA~kR$Wd)Rq-KJ$*IBp^BCJ4BpvQr`8eoXgG$z#}a z1Pk|i4)HVX3p%jZ2^?!5+9EFiTF{{&nSDS?!D-EXBtXGE8IS)c~eRtx5-Z+U}R4MH0erf+vG_@2cQC}=1vzPU7U`bT`sPT$!!bGJwHEQC&;rR%CRa%|V)P@Ht2|M4t6zEwsw&FDn1`2wM}XIgwl zxv=&Y+_QPeeo4>J2h9_+REpJ(D}*+XMYPF?WapxbMv3Ee#yp%2^nCDtxY|$a#}PW{ z?dORVln4-~01ChfIJ@7|QHBELTX~!y-l5X@1fihu31U~!Y1K`O%~kah4ueb>8pP`PwXm=Sna|K-}rjrq~!&^vw)98 zpcghtFAxF33lxA}sMRrJg+ZZc$a=*P?@FY#6!ItRY+qTgHBZd?)#u68D0;pUzcMl+ zIn)yw)^gN*zUb(dgosc1urZ8DR66>p`D#ZuVAc#x@Dnc}Qpe7oYtbV7+*zUiwav$Sl{Bco0^Yb431PhKM| zru2a5p#XIHB%-@r=&o0vCzcp84#^UuOeL0=@e!{>Tplhl-|}C$#C!`%!bK1MYs}_n zGCrVdj2j9XjWpvj(HYm5ix$AUzASyr^=0?0%mQ<=b4s%85%6)#nUNEUvXi|sdKq^t zSz@&bAUy5%e6iXb?Va(d5w^ezKwJ(AE)c6t-UYn2F~q1$5O6t)Ss?QI^+^L#LWBL= zq0Nm1(qOG2(28pa=UZtwJbS_H1B^Zd6`4OPnGYik$Q&Aw`3s~0nd7$zEZ(>Po=$qU ztMN9$MBZ;9??#~nj;sNWtXGi+OK)iP=#9MVEX?5eid$-j4JJNv6p#hnnBMlaF zXjPcMtY>Bz_XsL7|5Gy0|GrOOK?5=`P8uxc(CT51t9FoBz*YMm1diXTO$fxQeRjTB zwK=v}wcB#Z@Fex{jFwTiIh3y2=dEazt2SFPJma>}QB}7qJCopekcuhBY5imF?vD|YUfV#>@_IwCSutH&(M~zfMhkN0|g)%D{83c+IpVar+j6#`> z{n2;ZU{5t60J^^Np2+AsT^NZ6r`M zV&(g6!)iyAKRVjHF93SX=FBk)I@c=Fa;?1Rk7y$m z)+6@ijMjSLg(8nqn9$()8$USPbfL)MHm9w8(QQmPKDkh=w{71SFJuEtoHQaqWX$uvO!^Wg!!0KG&b4F`0(yx&%*2Hv5A&)om+^$lbc+k7VSo#!Vf?Jas>D)o z1^*K6M}#H%>qEkFgYcKmt>bT0155nqEMgq`y!$A2l$y+B~Dh&tgjjEiC7#YZ5D|^ z(#C3lL1ItrdtMvB5~gKTH3nKOBG1^5YMKW2Ko!a}K6-)Tydcqw5Lx46(jqZFCev1) zXPiJ;&RC=l5a5Y9M&Kzv7rhMF@Vdrw!Y1jdj8u(s*=TXWR10vyoFLT<0}(ucfk-?c z0+9l&KvbaKKs-TI!9Y~dcpzeBLxFN)tZZESS7Iz}_z({?{{DA5UfZB_7{KA#R_tK_ zQw%GBDbxz!O4%ZSs}Lp_z!kDd0LNwr3*c~(e4)%SfGGe2xHa@9WJI+;+_7^r#%V@x zA`nCOnQRfd&sYtf`MukT%$d49Tg>lHt6ciu$V@J;$Ycj#~|idu~bh+_u_oXd7hW8EWog0LPdq*#|Se&TK zEVe=mGmIq`lc=b)SalDuL-$a2=pN7=-9vO2?x6sT)cEBYI}8d%7ag-)gmstwD>6Fg zF`g&Np^N%177^6fYVf$oy*A?){lf?l%Pg^NZJtKeEp>LUAM5kPiAW6gl`7mFG2 zecH;yXfENXe`NUy?`#2{xJ7{f=L{a%DP-4T`DKAUzHD|-HeU-i(0Ls&*g0VY0B+<(6c!&@Gp~D5&&(F^ zc+3Y@XyDcocd!Ks6t|Yz2dwwjj6(`K&RS&&CZDx*z&!E^3`xouFe|X`y}+K@0nl@M zWj0aJeYVE(y>4QM8y?enNi&`%%y1JL&p!ult;+IV&Tbzt`{>NNZ1RqbmyHxcg9eNw z05l-w1GZ-nY}P3zdM37iW({K;K}XL3I)0m+qH_a?9$m+6UD&O(}|E3JwYyDZqY~ui-L94$b z0JQpmw3=dCR$nCOXf>dt)fC;w>T*JlFQwI>PavzMwi|`j+FEw_i;Rx&h6C7I!X5i% zMqkY+|DhG4fee;kfhqf;Fu3x5s2s!+8Z@{G0ieOLABt|Km}oHEr=5pwJ&;ku=tOAH zYM?=@DUFZS@?HGeu=_4MG(iWY0$D9pE(NX7*LtxJ+0FK@4j!}rItVT>UL(@IW*4#I zMHVe5vh{~D))`p@8x3Aa0BCTQG?-$d!80=;uGbTEv=z|NR*LRpt9-lvU1{sYz_v;~ z#|c}FFTZ41a%bA~O#!@0Wkm|BZxp;{focqpZTr)maY3Nib(Kku876(*IA}thZ zh0I$5N$aJrJf%PR0X$Zb+L`1pL*36Ju?FB|llUqpf^<5>HtsdRgMh3RvPUj;RycEnO)`x8qo z+p&BwUPYIgp0OON7+>RR#$_#w6}^@bYrIEj(DvC>(GO5j*#9)Xo>8Bqz^aQeHIoo$ zzm-|tpa2}YxJB7Y(DWr5NG0t&#ST;6`3F!OcM&+!4O%8L?2||XguSeb zLn~(3+b<(Ejrjx>dBd|eoc9U>N8U{Gc9RC=ozr`4Tg_r^l{5|$Ok{mfus%cJ$oimU zeT_6&YC|hm8=P_YpNvID-jA%_#Cn7Fk*M$#B@M_H8nE6FLmC9zk88GN=O<>utJmYh z%Ie?`R2s_}%?L8GZzS1wAPvYK8j$_7q`|AT)<_kAC5<3~fF+G)V7p&QgAj<4M)Wc) zX_VvGqNFjIOXvTbGCQp!d?jdF+4*rHS{c@9ct+8v#vF~-I4W>}7z%Jc!Y30-=FeQN z8B;GqFyECYF1T z18B{|hmEXxd_?GQ!o>XlIs)YrCWONDLU8i(!^RnMk3Y7paHicK8z){1L;7hh!20dWnk1-sPg=vCo&yZp!A6#Rf|r zzy?bme&%7x;}ZCSmpm>Lp7^ZoMauJcug3;PXEp<~=0|5nDh|WE33LzUO-T2Mq!tBW zQVS~{3e=luF0(=nHA6x3Ry-6aC&u?MYW*uQRy-&%Zbn)WI^2v<4AdAa9u$fpf)$S* zD@4M$Ct-pK8DWZ2MVZx(V8_XuQ$dpB5`^q4}D~lbJH3lyQVDL_Wo)p3B zj+>kDie}6s@-S|*R*JaIvKl;-J61b3t`xz$*=on&<(CzE6xDVztvNi!CPQ~MsLexn zH6a1ZyXrrz6xsaav;m@4J8JRLFRb)T>fN5qY^Vb>JOxr_IPHPrIPDR|MZgh&EOihF z&_H$pUJqyi8^!L2D@1t5b#Cj-wwe*S%8EerPw7>{Kc%e(#Xk*K3I8;<+Qs0mzluyl z39IPfhASTSw1ug>E}=mO^BBa)!^|D);hLI|9on-3;%pfOw#wM z{@Ez}vysqv=RUY}U~#w1ipCk*$bEEzFw`!4e8hJK8uEkNhF-0k4}M1^Wp)mEVzsPw z=&P+B$D{t=gpY2n7NsSa{_qRRppqzdP~G?j4~rcYC@;Q4-N>?^hK{Dl7`)&$3|`_j z?3^$H05|&9I@%EaRwAJjf#No?&1zBWpy)Vd^&^;k%F+Q7YaKqAveuE|gAVuW5Hn<{V>aQ1+s}Aj>ag~$GSM}2H7Rv0B{Zo28Uo<@YfIVgL9k1wi0Bur zbnGJ7=$ECdMOu`ibN!20YRF0llz;|gHes=Q%Z2Kok~cLtu#h8HCO>^NhMNd8ky%ks(u9W4iRObAnSAIoL6 zqX3Juf#nklJ!NQt4VMc4frjfhA%ebu2e_xKW?*k|S@9T16bNLrEFbh+Ln(P*pU@fM*$%Ygw>K~=m6ceq+vPUjKM}q+!4W{Tm2FtR?QDQKt z6Ubnx>@GCe*v4g%$_EefS>I*YG^5s9D_{c|E$ax?){6ed(nm`|gO)!@0BCv3wIawV zrq$nA`go4ep!q<9=2IGOKACD{>7&_NQQ-omyrvT@sd8m#<<-m>E(mQGr4Md<^6`up zG~*qjg4cF3QOFv^3}zdhxx@I7V58Nm2mr1Aa4lPL5^mR`m_8QB+DEpuU`AjIq~N!N z1={PZ^~;$Zz0oSFAD4)9ukyqTvQlwDb{tke?x-}>wG#c7R1C-hxmIGG6^ezNTr0~T zd=BB|4{JJ>lPpTF=e?rq@&ij@z})%!NbDT0Ztk4x59 zNCUEl2F&!|B@M_sr(8?Q+bVrTY_MVud53KfYL_Ps$Qv4vcWu&uyzxpbX!R&=z0T2| zpd#}&l6g7Rb@RvMc%6=@13LpRfYys`5*Tc)<8#(aSR5F8ng|m0vxD z;A1^SOV0WzvtKyJ71fmcTqVt^!F+vte{EWaNNit!GMxa*12^5V; z-YAMBe&}fP%RcB@GK=1v`LaQ=xl)mqXJw6qC?#toa|ti#da+g-SsaRM#YV)7NjeGC*gH;kg1F=fdZ;Wtu4z!vyOjUx9z-jjU@NAWX1M@&)zc(M{sP zdhjB?8Db3N7_-^i-*Nn-H-$HgK~k7dS%akMW-&;b(^fu68dIK6!u=U^kN{6C zl>kpsD(Mewc&X%hUp9Ryo8cB4td#&8td&sJFciTD7>dLPA`~gW3PlC#4aHeh7ruX1 z(0C}~yCDjc6JxRD!+#~lVu=s&Kx50l)A3>nrNa>ZlF(rYQw%GFDbxz#li)`l!lwxn z4B?-s_kV>zfKnfy2z)|VmP;se3}Fhu5WWpVLWHm^mxOPzLJ_0a+#;gav>H4UJ(f$V zZ4ncF4Xa&D^i{Ty7;dmdjo}JgL=0CTRA7Ery~`F+5J;pAJbXJ5c3Lks>ok-~z;L`w z0J682pb|%!Vbp={7|AR2=eIQ7B7dqOVmR5ye-}Hw$-4xXO(o% z8mnEnX9clGcl)?!sdUd$LWS=6R=Vd1ZQ$rHI za4eek`t98bs*% zRsr7VvveEj)eY}W3#1!*naauKw?d+F&N?VGG2T1J>VC)y};#W-N$06t|LU)ef&*b?I*V9F4U$@ z(nju~A1#jBFJ2Gfh71_uQ!DFO+rx{EpyN9@6y4__A`3gjFj<(IMVR59Kb{w+thkkRk?C$ynEHUwpaClh z01fy6I*7l6Lov}aSee>R(9tu1j#+Dp&J8GH=^<+m@VaS!o2*QMPTuq?!IT=qr%LnN z+89%~EId#~;xqgDt8Q7Dxwp!tY)`t@ST3=wRu%2RC z)>k0tXg#2#^%UL5dRd6b%aTfatOvaUSueHDLF=_^EUJ*LBiKxUSj&xrg$hRe#xuC1arb(El^&8G+eZ9Xb(rkH3m)~0R{bTk*x(Oin|W3DV( z93dSI>ICX&sqA*NH)QM9d~8B?>z3l<%MjzDFjf5%D^>$pEGsFMKOu#wW`qXKZbJZQ zcC$}Jd{a!TtFbWElhB~;K!dhZ8g4t8YUHOT8-F4SQ=pXBZh|FMt^lpPFcrlG;rOoX z9p9ob^)^u05m)M6H%F>m_8;{6SrQ7koL0Ja8~vlR;F&LG}N~eJy$9QWPucuSf`|Kk8^(L+v*%94Hb` zkj0)pq#?r>bozZN&a?vv4W?}Rd`iw3!#?$H5%@ksgL$EjEz)?F5_u|A`UGIf&$p9k zE8j?uqb#RcEcy8sSjNTL$|@}RF2d+RxIou+WbuWQ^J$-o0#&O|x#ttmbSzNqP_f&w zfkVRsm_D(d?HhPdtXq9s4dVwwf|h?r)jTKE)b6wN2DaKH87V)}c!*GAeTo8b7-PEg zHbLVf*ig{;`Fd4DTYDAC&)1lhEU?Y$&%nex8rd2t#5m^45IR2Q6b!yC#`+Z11kWB{ zOXq$noC^=QVZiO~u7@g#XBe&WnoE-R_7shH6$jtZ>B^N5*Ie>n;+o5CLEh0xX=V%X zj?R`gu;pi+7Qz)fjau5e8!uRLM9pfj1@H(? z8?{Z;tg5!M%`~Q22n=f(Z$K;Fc)3m9cu5ejrjczSVEO5#c-sJDJHbLWTepc4(E-wc zjKR#){{*%Wa}2GI^W4?b5=c`it8xq0O%-LJSr!nGDz_Z@c82o`QEu((-MG zU!&QCcDANbqc{{NI$0JONConDN@~0FJZWniVwjvtzITP^p4}HKiIiuCy6X$?3Lbq&a2Ew=ZF@^=M%Xf7{nlxUlx zJ=~s{l#XCcdB->xc>jVmMmKbT# z$wCvMljV^4Dvf+};5`n-RS8BAzcZA5{JMiS|*e%-1*RdSR^KXkM=4pW^ zK4VOI;&B*Ez~eA6L8OEz0FxE?YJ~#z=4q?!AR~saBMKT{M~?Kd4N;)D6f_}pxD@!( z;Zi_>xD>1dOL?YlHRuj$c=k&_+uufi%8P#+rS}feIlZk0Pv>ABbJPxz8+p-c7l}IO z4lYKg;91(cX<06uekws*e{eF_6uka z{ZclRaKjuDv4&x{R2Xb~-=I)*(X${_x(GLcxG!6=UF=WZgRtfMlQ}TVacg#iNWqOL zK0I`lLp`Iwx*xURP7#2{PSWW-1C*cHN7&?Z{l#~B?Zkal2ycsI-QUSu)A&b~CZF#4 z3;f5g62A)F=1~qePi=@COS#q@swh`I&9*8}ZveBnqsxl1YiYJ(MqfgUdA#R{jzffw zI2#_^{7Nk{&&ZompC;t3M%rQx3b3|OFB3G}2`Oki{F}kId;N)DNw>ut)BhK7Oa^?* zg>u7Tvxt!3u%Q^<9TWv(Ua>p3J&uJBtr4NO-icn;=fKLspYkCyqj<_Eo?jHMERmMG zaR>DsR|0oX-}7I%gZdsk>U)bT%-}J3s-@t{DQ> zvv0esk74DT*R9DWl$uz}4BrJv=#bD|jxyXWK@?AtQq z;5*m*M^xbXSj$qNF90l^ERoW%K zlbxvGO2eijgt(i@U^T-#(n{Y7Q=TKc(QhaK0@wMiTyYOqx zW@pMq+nfrYuZPbyYfrJbH((sac1ej~-BO!BVwe&CnTj4-leEDBy|m@=yyS-dDwAKg z?Ghhvwn2yB$D7Z6(k+zDoML;RXTd|z9UKkK_o&?wS*h@KmC9OO_=FbN-Mr}0JP?Wn z9Ya!6GSicXXUtCf066wdiDT>Eu)X%Eu{2?kEmMQ9*uH72ZqB6QllBkkT4alF$4wVq zaQMd}5&G0!_$gO5ea!Ru*@WY^9p-+@06!p~&bVUuO{;Z5H1`-vnpT*dX5f3%yq_WE1qqE4NFPWZ^SyJswNfE5eOes21qP zLc4w9|5swwMd3#Gw>|8|G_wLn^~_5Di3|1eyTzAIK@fExd>GeYv2$#HYaLnLEL&r< zGZpQPKK-fPxGVDyzh`!fj|y*M&obMP$MIZ9+ud-vz}|$aCj79>=e{dC)Yo_M(wvsN z#g~L%nQN=0vD5F{LUowP{~MQ$wq#J3!Fe>){oVqbp}|FNOWwCNHJ4C*EuUov^VwSA zGkw!8enPFz&dr1mv;VWu*6?xMr!8PPi)?kx1ymVy-fmy#&6S2_3Fm!u`e(al9;I~u zjRTKZa)<-p-FYX}{l|y4(wg>wg)OzUFdtIUmjCVr^I!fw7;`vi&%DsRB+g2bD6E^V|npU_WVb-I_95LCG=wHJwC(tcWK>C;YF6V+_u21&9VO5ky~Sr7`Y&a zc#*YE?jOn?uC)E5^<)oM*&3P8Qqh(dd+Z4^at9JGYO8ydWYNj?(yV&}M=6%R##ZKW zyr?JcVY!RIjfqqzbfd%9jh%&gS_gOZI$KxGoI*+dn>c(`da%PD=|MLv9d$Kr4NKT$ zt7fjF647z%?+uC7g8A(e;Od_QF#NNj)P?_+br0bYLY8p}WtA(ysf`fl)hc zH#FAuv;T4hX}DJmU64V1m$js8s5@k@t+1BodC-dO9N=thCR2?q=k*Wfyb;8C_WaQ$ z+5NuGhU~36oGBHF}yk3cfj_I`4d%5J2i4};xPh|oTfeAH%stPk;Gb@faM%(1;-BB zx|o-V90omGo#ialnw1D3KJ8cN?X&iBZ0|R=56r(Qoqb@&)B63rnCmyq&q#E~{V*I` zc(UItLtD-dPD|r7`0~STaJlCt7PCG@L)LXa6RZ=KzbbR>=H@GRK2->(2-0W5-U|lGv`*yTaJF zCu}L^S&HQyoRMcZ80`oVrFDfH|4g>|2c^W5cy^V+hQXmY{vd4a_eKtL=bo}P%3~JV z2XN08==_)wUG>m?EUB&|DlC+=h`R^e2hZEi>t-}*U=ufGR${hc=`m(C3eG(>tg9Zq zk9`uF9;Xt-<)+5q^Y3OeUxGZGGaFGcvzbb=p<-rRvkS!rvylBXGrfh1i|qe2(?2x_ zPy((`2(V}NS%u516kx%Vrp*_bEB`~G^e!qcYBGu9dNes$IK8Thi<(4-r#CQXQv#1? z)`h3H3P5l=%hAGI7Kk9}nypCy0(g}mlS3;Wp2 z682_(1WD#!fpGVfOdsomJ9T6XyRpEr%q;XdiDK*$V2%&Hs@ed7yW1^WDb0-brO+<0 zJ%8HDsSNY9nZD4BCvcv&Y{6omoLYd*ylb1J zH~E~+ib*NXrbnfJ7SjFmd~DX&dT9>jPY0QlBlA(FP=Id0kG$sJC+Zn_;QvWO>$npi z*wXWwFHY%gF+2QGFbwQET>+&)`r0oJGf_*H$H2Q_3e)0>%sw@aK|M0u1Qzn$G&> z*MSI*)Jw0V62Q=`#J;_k-rPJLh+td&^!6$Nj{BPw7lRD6S=9h$AjMIre(a9IF{bu~ z8kKbl&e5LGp5Xs6t#py{+H^M1u-8$^aoTA0)0+IOFu+M*oy{W9$&=Xz?>C`NNbrs zTqW=sZ!%=*Xc5!i_05hFy19ZfwWhrd6wLciTfyEgVQ=n-pJaX(0Ci$X`zt=E-bwEm z#m9JD@r9W5R9&n|@7F*SrJqcnql)k`T)sx&Yj|+C~2@&!(WAuo^(i`6jJg_IR`>}e8+UVNd@@Mf$}kKMKzoQ zT`&{znl8+N`1aX~XnP0EY(sUzIk452Sok(u(U#;q!;;LN6mmYv(NzarUjA2c_q>=^ zLxn^n4=urFRkU|i!5etL8I|nuW(MWV`%Ohe`a_PSDk>P~-+^1>^RlSQ_P4c3Y;9$G z2XivzB@UvKLSpp^Uj{kF&-fA_x5>lz#%$uJwM(#hBhyQ;jLP;(ta(*?5wgt7M;R5* zq*b-IQ`JJVqVM*qWiFwr_?rceD#Z?;HHrkF|El@elB`gb*z)Gb|C`CgyXhsfabcs6!J(dwGFI|0 z*R-Dr$@5h{wjnjNf|>6t64&VQ!*7(0)%CA}cs%?o@leEp&sgq=Va@fwp$FiJ74vT@ z9Xl64?pEz9d<@2{;UgwRuOcM)FRl&P#Jcu|Itai=Vn6`ye1Zt*A_XKW0t&-33BmaH z^5f4R!%z)KZkhSCd7qjDXO^z|oiD|M3YTD*@dp*S@A-oY=9^SH1WQ|nk5NqFVB-7+ z?uZ8VF`Bv151m&R&3P1z<7Q^<#0V9PuI=7SE6BPwvR8sD*c^@Q)y>TcWmam6zCM`w zJJEdY0DHT!y%rfC@_}?&ry>w!SpnN04E-V(^fxT6`5E4o3WWQY*B3cL8rlT z-nECb25szp%v2(bWSIi!kTzt$$THP!Yu{~-rF58y8NFYmf~L|I%)~$oW@6r>EtqA3 z7R)la_LD5r28xEP*GSg8XbZB27G(VmZ9&%1;$e*$rb`rq)50-J>uB$ygKR6o^f$#q z+4rSv^8oaPCq03(p#^1^p)DvIT0F8Lc~*yo-wG?jY_lR8nDr?x@~?Y9X3%I0@`o1W z-;K6l0;?{IaC$Om9`!pW+B=)WC@Qi~k?dcfEyx~P66z0aX-=js$Ua47kNL460fG6k zVc;|+KlU)Zm`MrvW+_HbgifXjvQnH*B*->$9r!=-UU?S&;kC-lh<8Lp4&f*?Th^Te zWH-38d)V7*=2mKel_NX1w$tO}$gJT~fOTJD&u4C-VlZ1)>KXf8^Ggc0(qmt6Finps zwU;*M{Rt{re6xo$6~nQf^mXj<#9g=wv63z`_eNOhf?%s4+h!NryLXy>~1{3@Qr(GKo%EK3lh;c@sua}MuDJhSMByUO$7|LC2AlW zVj5mpg*B&*{@Vd@jycZ%DbF#-U{c^uB%2>nDb|#h&B2~2jUQy($6fXbTFB0W@+7mH z(pe{&?ZM1Ga8R6NxY_(9v-O}j$!w*3F!XmnTfUxt;UHcmWL~7r=-6|?B-{{=g-v?= zOLi21_pX2drmZd4PS5uZUIAnl_=ZHIS92{7OM2bj-2Z@7ghfoSH_$8BZ_BraRw5C4odt+ zIH==fgP# zo^%ZCkPrMF!f(G(J&wo5%``yp*tp@K2zU5!>#O!QAw1IY)c8G>ZbkZG4pt(4>STK> z&AjY~j;F?p6pUjKPmKyV_qM$Tn>q!KZGW*%Q|z_PzZD{w9^ie#z=jt%gpmN9bo6z5 zELp8(9!-&h2Sx>g11K5}jC%AT)~SiTqFLdP8to~1)S)0VQ!TITm2bk4(VCe4KV**| zpHPsso@%e4w>!j^9ko|6+xscdCYS=Khw7$D?ZI0tqo(1rr9f- zX?_Z%22;T0^+31j_G;Dsrw8y+^-BDpw~eiDYL8^wr`uPXN^kIWMmx`YTD}Z$_#1JM zJtk&iJjg1WOxScoB8k5dKsU`KK=CBIid%#y+130Po@7^p>hMNDfRpU)nf8SNPO>Lw z+0U7uQ{Ui8b`OC_xzm>Y7bn@+CH81`{at&qd6bAC=hpy|)4qqE;!jE3oNeE1UZHe& zQo3|V9K`O@7Cb3I3m(MseG5i-j(~X3gBCpKT{uL}ujMHkXRVcGNek_b%-Xa8IhXxb zaBfap@C;U#&D!BP;sJL&!uF(CNZySZCOg6b*PH#m0?k&BNlr zRg<>hf`n&D1#BHDo;obfk{uN)?}6*d!$H=Drw?Q5KLmP)940L@mIkZ)m}q0YaJn@2R&2mi117`+Jc^GMIq=J zz(vm}xab)Lf}T0|j`Jl`0b7U2UX(K)A{9hlHev(&vr}6@ z9*5w8OK}DsxE9dv!~@sdBO>76fU)Zdcsy}!qtY?pXTCJnFgTRNdjog>L-tjgdDssd z4_pT+7{@XmxD>GWz@=aOj%}V|uVr3RsCXn?2x54S*YIPn+v`SJOIk6Jj!^{RiA#at z5W+LZ#_#OWdV%lR(eI#87y7+#B<5ogKL$Gc7yBNE5xe%iz1pKm_nx`5T5Rc2dsVZJ zpYR$%gg24GcOSFY`2Q9@D>1zyi=SH|KkM~_JqErhIpzo0DE06Yo)|=UKPi0nk8sxe zpMH0r_|aZPGZn|<;c7qcRC&1C`W=R!Ug$8sY3;LP^Bk;-E89m;AhMY!?A=Se%T>p7 z)olI?&sDR(4|c8!fB(h2EajtXrP!*I_SXWOuwFa`2f{Vf9eBc8K_GG@Ok4h6oUq`v zva+oE8T&|cI}u@>u!;weoVJa{pS901zoQg*Iyl6V&O@o~!1w$+3nke2;<3e8_rDzN z%qxDVm%ONWA_yqvdxj^1oj~k&BA^7K?z9A?(z;VPrxRy`l1Jg!PWIf-_GVGrIFz0Z zmJ!{=gW2MZw@6OpIR;usgUmZGKi<&*U4HHtdze{1Zv0`~3_H78q~1IOM`3X$h{ zpxIfn=7?i6*W?ZL-*JpTDmIGHLF9;FSt^eRieTI*st}$t>B;3Z!Rz<5B=_O#_DIcK zPE|q+mq-hj&=#~1j|mFcvT(PsaIZq-wQ%SEvhd))SSU{lieR)*g>VZOTNdg`N3GqX zmdG30=q(YJ5Yh~siEC-dF%rQT4$=2U8wQ7Zq5<}f4cPiKWAnPdy=9-OnWg+la6v6b z!PbJRfMG%H0jtTq`;fe>qu}!`VU1%!Hl0n5i9B}6qpa*-u$Wq%FHZ@I5L`?Z2=-FW zlT8Y;t$*3e!-{hJFIY=^_$iPWOo4uu0=WyClERIrmgxfR&RJ4*I=!e*ov^3`5aEO8j)iy;UxlyPpkTaNRlqe z4=*#cqI7&A*PB5zzkROJ556n;vwpZe2(J1ROoksWBSPIr^+{M~`4m#|=#l zprsp{#pa;m2IYs((S(EVmHiAS6Z@H>Kk^V`or*YGMpfldx}PaRILQ~y@ZIy$NCd@) zG|v?X-5Wpo$QN(mlV(c%6(}MOKP9Lf+|_(o%yG-CM#0vurYZ;1U5!GX9654~*@9A9 zyPBpPjO!Q#vz7IHj$-4Q|MZVySMxM&v34~I*t_QInQ&)1zi-8^Pqbe2>u=(gtN zAH}u?`iX37EK}vSMv;t*z6#-ses?aXjo$S~nfP2n)j{*JrFq%3#oE#+V9UJi(!8At zmDjva|Cf1R{fl{WPoqdi^Hc~o59$eEp4QcUIL7f7q~obJXx;T6MRM;tZNcPT$Zj)L<&4Qa1rh0IRB@!63K$QUS3KP%-h}$Hs-rKw z1wi?sRjuH;3iw`=*^0KHRXr&LtpZ%MO2I{|6bNdyw}zvG$`l`$Z(P&S%*>#iVHm+% z02G4s*J?VZt6-#GR?E@GoItUI&=0QdsHoCo&a?S(k@M^d9mMYhY`bLKd~+$~$Grj@ z-0pQ9<;}&kA^C=*s}JPN(8_GxvyOV^Hj0S-q>ze!S~jk_N{<>Xv^0X9Lu0%eS?k0* zuL)b9tcB`LA?{#H0n<6cu?acKxT^>!5NP8w;eYXhdNXmy$Bu)}Q1Sfmw~ZWK%!))9*;)k9A+5qs zVr#Lzv17K`l+xkK+z^`i)*|jF->pTGA8uEIt8OiZ`{54xNo*}%q%ByQgcjUOyhdC2 za<4-R)^)iqe7#>tF>t+~_mf=jSJNgmWS&KgDU2Y#z!kqTP}3EEB7bz25{MLr0ea9S zKZ4VVCI2V>tMX6mQfo(}s0#cabj=Ur067T7fv$_PKYZ$#F(|>M^a>* zUQ3@4D}HI(g3|%!F%+!7Cj+X`!uQxnwBa}OQkJn8YVCluw~jLVcKMc$ZOh!V5ZIZ7t`cI zuLwocR0ub1uw|O4npWT>iCZ)(&q)!Ad1wnRYAVFLs6|mk)JQ?J7BvNon-7ic zc^>wp-49oYfDp10M0)rMaZdi{Cvi^x3+B}9i7Z6M1)w) z4tMU-yf}eM!D+9Z6pPu517JE^KoA(7`QGCm?*fk`p0_(nzy-Q>nwy&`5?@2$JHZs` zOy$UYtXi_;Df1x3#3kjclVS}!L0fPQgBD!FF4GoV!=Qz)VICb~^S8;%CJc5wXKJUw z2+#f)**}!*3)2>44=u<(lC~gwXd&#g4h_xAE)Q{xG8<7$9@dncQ_cgDlmiatqPm{lH+G{ zJ;mnhgSMI-8RIAywwg5LV|zMPjb;NYwam|6d@#BWTYsrTX%>Dhv?2>{-n=YZ_Ohe5 z_EpwcM$L7d<@_VmhhTPPWV5Z4mr}Xjt2Ue)BGWi5^P`xXJvgagbshwV=v{0 z+lQIG%2(H~oyM>0nm1@OJ}Ys>lH_0AxqDhXm^_9}nBk}oSAj*0cLb7gEoE<(|G9R}nXYj~QAq~zzWOuJt$!z4u zw_Y&5@fKhFx*d20zi#K_o=I>reU@_Nt2J0T`c+>m`9l!;>eFJ&Lc5ybmPLW!0zY&z zESU-z7x)$2+imn^r$u&Q(`$}TbaOgY0rwnlp23Y&*qfw92Gy=PWsmAh&*0_y=0~L6 ziXQ#LV1C(fMm!$`{>JO}7o8DNvxxG+sKKXS_MZ_?zkE%bu}8lQCgGUyyf%g%ndWG& zg8+O!2n2}FJYPQ}0`aCF%d5dy-t)5LLC9HR4ar|;{N{7SS@C>L(X(n4$_J1NpA8a< zkwC{k(+IA?uRwzsd=^F#gJA%jgF9E+IT!{$-G$#c%x*kBulwa$j;A#x z0lOmw^8gG1MAj`NZ+VphFP-Y^i>xKEEwdeMRaCrtCY_@4Y!9F=p5v&dqM{yfl8NMMt*9JK<_;H^`$0^mDYKz!@csSkaL^n|nG?jprQu#xQ=IfKtvxP-`C zTok9nIn{H8)Hcf0x=ZCV3g!ms+s=wBqSOjy8BEZLRLnP%D!|}qBDKKF83t!9JyR#h^L(EF&NW|yH zjZDm99B0qBAa>mlp> zyDxqSFcuS$A^|CI_~$uKBaW|~Gg;$}aB}g-$6J(21iz-dE~fYS!ph$}d?QEcQC2yWzx?1R-+0b@aB(mt2~N?#!H z&wEKlMEbg)J36XhOg?=8R`5ijr#sqx;fT}BR+J%jN3#pq9cDAyV!evo&9pQg^7{FroI~wBYfq(nkT4Ci2e;^T^qe#SEt^z^h^aGAxRn^eA#vq#-x8-Yx zshMw69nrYAgmGbSkro+iI~zMsX&%kO%U@4A!P+*K( zU4O-Kt6TJEA*T4xBn&}uDJJ6QAVaY{(9x|fh{3I{A_fNvbP&b@?I1Bw6bQxwCTSHg zE)@92{!>&#KDn9-qBlvaKrxiw0AJBiYIoexUNc8hei%x_eiqZ#Fw!DJDSF&1O;~uZ zh!{37zur)v{Ii(ArVvaLRg;2wZKmZl-1dz7Swz)1$_JwgPu$CY76+Y`v>BsnSuhEk zf2OBx9R%R~r3k=o0b{XSsIj736bN?9o->YYQvu`rHRCMIU#F;UIDaXKNZtG*ewrbw>%`0WVal<;5ew4z9>4QETyzUxa7qkAzb;QH-xb> zie40*QIzt*&IlhFRxhOGMfpNaYuawfX&y{YM@tUAPy=#ssDm6hOigSVk_a|qA6YV1rO$r2~A?m85v#Ee_kY` zqNv22pegCB>18ngNvv7s2II{T0B{)BtT&UDc?L-QnQxA zSS)&-Gsj}l8~hg*i{1b|0>62_>bB!k|6&naeaG>mxtOYnwW9Y4L^^8P=KrErl%6N2 z8ryNt@v6C=h~N{wyq`aS=lBh8}MH`SYkZ{KO&R@hQgM&B-ABWfo_V^VFD1j&xy!VSwp@7qg zLcu65efh5@Zz42S17<}X?7vWG)Gejm|%J( zzw@DPPNi^^%s+h*`6dU`MgeJc=d=>=m{0%NX_c5}I0v)ChBM53 z@85XK?7S-SCuL#n{LB9;cK$KHg1VkDh!P@y4I-hYB>~^>1PQny00|<&-S$_p z?|agZXF@QZ-7KCHXE^HVz!SFv{#xU6Z03Ivl+_-TjvR5@IF6+~QmZ51-Bs`R*-fJ|`%bIt#O zK75R`o=T62?_HD>ceVbaGb?4bS4lA{&Kb?}vX*t63umjP4V&@w=>$>|?bS7wK zfy*RPaTMjbEJjft(jrF@ek42kvKU1bNV^zCQI~_nc&*FoC@OPVjG{7>h42@z`?UiJ z@X2hmJ#EHO)FzmO?v@1nel|$JqmCj0LlMlwP^9LGP*floiVDOE#nDtR3`G_3Zh93{ zfmj#gPyOGd7{xnlI?Jf^5XCZqx#0goU(4B2rN<~a@&sYV2!=17YvM`{iED=x& z1pWI@1Lu>b0>-mJj>jlBjLc@5*@J3@1||L`24x~?kp}U^mY(*TIQEVt?IZ^=ESOa< z{N|m)@z|RJM)CD6h4S&PZ`urIZ|1CM&ZMn4FsB6*Fi*IR&s?~?fdIa|X(_NGIorbp zWw|Y#70k^(4CTtRJ{Z@XmfE=T09Rb#{MF_Q9K7IzQjQ0fax|Ef3;t4YeN&|1qypW8 zF+jUV#DD_97{Iia0=Cjxp;t&a;>@BTVz6`ub@@T^C)n+Ho>SLX@ctwOz zB4xotDC>)7>*=GfFl{Wn5io|f;^cu>*uM}=%4GOTuH0)_&!~VX+$(`7kvv%dKQMW+ z(1(4BJ}(&O^t4``16cUyLp8?rg{h zFjri7r)&s!xph%Ut*fHAQpb;NjbLn>c-dlY1^j_yOYsFCTV^L}K4v1Gx*~$T(G`&~ z;lYk?HxH-ctzb{(U?tcGJneizGbj0>^EaFIaaVD!HOJ9rsE~9B$-0`4C7;R@W4=e5 z(0#Lm+4+Ij&X|R1m5W%%JNey^aqPyk&Sz9%Scdb%97BcT6ZMClb6z%gQgEPir2L46 zLXP$R7opcC4olEd*@oWEHu_#TCH!Ph@Hw!06FSNf+VUqRbgpw9FrjmU|H6dMjjO>D zIv@0PE(ws(ncmNN(9D001STeQLI_0m-W%+WcKsL*Lz(PS(r51f=M1| zv64KaX*18oXuVj>TB?}(?#wKTkLjN2QqUsWf`Xt09}HeYTTsSyONLfS{Ep7lVoC(@ zBj$Zd0T;i#4MlLPSx+-_DBK#aH#wN*eH41kjpVs* z*&<$n!4H;b9E{Uj@oO?SQl4Vs2D0pRv4Jd0T4-*h@pW;kYf9S1sjlJmAPaxn>tf+Q zc}?U-;;xH@KaR5S?j7~M*TvSNKW)ajvv)8FLoErooPh*f&On05jf}r8ma~a|JYNaM z^DT=fF2ukSw~qc=V{YWb>moO@)JKBcp)L+4W*yM+{R(#u&y9c>T;CKixOaq}!M!8x z8L@X%Ab22EAl8BON2(ld8x=&{c4BTs0b99|-~JEum>W^(@l^SMlH#dS!Ld%23Rpc= z>VU#nw26MkCiHfA1g~iKk`j=ap(+q z9aSbr+EG<-7{%Yfd)!UZKyo8mKNd3)&PM}Cvlv8uf@weOhB}Cz1#9>L>{-e}xQnMo zCfpFIkx8@}2hq4-5~f)aFf{@aFg2n`z(@q+FcRY_b9_)kfnX#m5GxWlQ&NmX6_KY# z6o{1?`Qm?*VkBW|M4`7*Bgg+Q^gK19&|?r^p`;kZ3XT=T3fL!z|E59w#La*~{8z9} z3cVRDh~*1)iewC86~gc92j(({Cr)$jHS1FyFna6W6pKJz(n8ZBoo~wHQ&)n30jzao zM`kz!JiGbaO_3IXRT$GE+LIhH5?*}DTNA$beB^CsS(AzrGn)cI_hM#50rSHyTpk46 zP=D1ol0AfH=ei^uyx{ILa{Mm6+~3xbyW%L)LrDdIEcU} zrTClSA%BAt@YMZ1MByR~qQs%QQI3q7CO+&_^ag^n z|Dm!Ci(BYy7~+W<9hl-O?5DptZ}(wI@56b!pPztU!33nD0PY`L<$=HVxa}_kkK5yN zL?=w}6EZfKkf~lFo=)(3hM%^z4}{uF{5WO@51Bjot;pTZ9g5g7JMCgZM0`Ua8xKAvXL=*-(-Y3SP zB+eVS3oUbw)y;B#*m&SBl`9V1rD!uAxMOqWfx8}U!u76BZjhjDk?UPi`H8!zwI7g= zvx2y#E1h4Pia0!S`=J)2Vyz>0FA5H{g)b_qG732!xg&DLjPV4R%LrvCi4H1b&{*a~6{9qIR+K>zoN8QM>ZF zW1cJ7PUFAW#3}lv@zv61an3XNpFW?%pXd0Wm@nZ^6#N;L_9YaaUzsh?-b9o)u=$Nq zX?0~25{K;ql1ltfdH(0{Uifp2|3QXHoGWLTR*L^g+z)^FC&b#NZ9fD*_wYYU_=Svk zzhgMR$_Ve*z*qnA!h{U|79hS<_#Q9w<5L5F^E^Zde7a`mkZ0K8W_3-L-R097EZ(fx z!`#9x@>FMejE8K5I6E@4STR;>e6<2BZL_ns{u%VtZzEz^_V};}mfdo4s0m1x)9f#% z_pSx50yi`TTho3X4}avR|19nn0lacnsA4C!Ym2j=eim6L=%+A*AzRQGzQbIDZTQ$( zzX0zec;J5_JO5+Z4(#vswQCv=z3Sd!xwoC|SnSD&(8T)|)T7t5K98Ihc{k!r307{a z)7>=?-w}_>mql!K7G>*yc1F9O{=}K68D)R>I7iwN-MnyUxiTC|Pwhkrw&B%LC0MO( z&Sge*LL3+8s=)r)=Imv}5h%E)rTDP<>7JKrvZx)-0_?I^;4|-#7b2{`u+~nRFR66jsB`G?HJB) zy?`h*3p!TPe_#T>mb4_ri3 z&@m)6B{MyFc*g9s&A_W~N*r6T&)NUcJ%TDm!YVucb7v*v10vnqgGImOP#Ri`erFp( zQxo(Bzq8!_DRtP4FPuLZCn+r-VmvI1j`5{EZqeG?4oT4Gf_?nbgz(j+Lb-p=A0OFC z9}l*TOnFLw85-XjmcZf*mkupKd(AT`jQO3#>`YH)Is2U>)Nb8yV|a7+!2##nVHN-I zju)7s4u4xF-l%DT_;gS`>*IVi^@@M+N39ZA^r$kSUCUb--l^f0#}0^k`~#wWjd+VW zgHEo&Y+6XOk^w}fwf+On7FtMIw)GolypiZjH=)Rg=EW_bM^hjZ8P;7_Qi`*+hnxeA z6bp+T={l;XKJX9Bf*KCeuwji08+dNgm_Qo1k685FGHo^VQD?m$2zYB)v#jU!k|hG` z&EobC>&F&sbyW;c>kh1}1m!};@98lJ8RN00m-z$plPrEj<51S!7!}I;mG565krRt7 zriXm#RC^|Cqkq{Zg6M#wH8SlD>zTbqCA- z-dWk$Mc{j`yN2l7z*t_k^BaQu|G;fh7%H}*fY68~?0h!5>38eDt{jqgQBT_zHFJ{n1%MH*$TX;v`Tm z$E&hj0(`02;1kX(#y^A@I-~*{bJE#NFL;Z6e9{RY^uFcoMm}f;>-ld5>6YTR@Nry& zbPGFu%GtDtrH4#w{lluAcD7aod#AlfKWw6PF5?#}8I6ff_G_+0vjGRlFyyDx2JW0Q z&R6n0n$O*^=zpv|8ZF;2G;p8(#i@rHU5J*+7hQ>Zhg*19FglP1bohj0`KyKuyd@3{ z#vsy+17ScgkBQcgjS*b5t%QhzwB7_$lb;?}}6o_|x&a}T>pGFwVWu`psV->tT)6zwi?%Q;#z zS6X~>8NQ3L?N4VLW1|J;>qMfql0A1Do^SInY%554LKlr1U zzUyos0DanBXCvdX54yhcme_X@ZEz;VeOHv_c$xlEjZaQ#Ro8v`p7ZTcGyk97ktK~s zYYJOnG+xjDCrj?@s$&p*X74>J(TE|K*b9J(sR)88IVa|G)nes~xk5GEye4v{$MU%v zD@^$q%=$68773neB6vc8@!;W4xp(DvoyuEqPEpV8ws9}I;@k(rTuSzonEU<%~sp%SI z*a#H;F`Pxza&=a)y%v(-FD)z_VhP+c)zz6GNR2w&W)sT}P0+z8$gwnL(L2l0F(k3- zL+f)R6GH0VhBW5+J}ueVj|Wk-k{*BJtKM)%hif<7bzFHh_IX`b1!FZa0?(qwVqH^> z%>)YWZppuK0C#Wg)AMQ{v)ou$F}U1kQ9V~_RzA*^pYm`6k9?Z(WpMiaguXnm*;UVV z**Fm#{}kfut8a_l7k{^axJo{JlJ=)?QS9Dwp*qYef&3-soM)gF{G}zamJMAU^~67U zp{$sDK|@z;9;3(|E5rkZS&VRIp*t*T$&0M2( zGtR<;39DjeMb@p2E81vkfyMF`$BMLawJ-=e!I2Fw}hk3Ot5 ztP=fw(6u<0)7ll~kByT@ra$&K@vfTw*f{S^^vC`v!SzxwJKrVfI48%k{cT{)@v{?| zFD2MGw&K{jwyxH}n7awOWX{@wy8<)cPp~~s#N-J@4>WS4MEBRZBL*gfL7+gBL1I8F z1e%`z4!haj)xjHSU7vDgg&2A6{_jYWYwZ(vMWm&4b~Q7K_|jmcJ;9+O(ilWqU3Xj; zS9jg4Xd%mRTb~HwR?`AwxP<^7+cUL8IfD?0fE(4#)xc;;@VT$TIGSg1Y@gN1)t-%R zvAs|LaW^-Nk2bmya^5j|#k(vl$u(M$7Rc3=gsY?P3Ri<40=Zgx>7jJ>y*n)as#uz`JD zbq#_pc4q4cB8J071<>j{#t1XBw-Q^px+U~2#t_00^K!{-HQklhGZ(H36xo1Tz4#@}X>|obglVD3L zqC2S%ukm$f1M=(*w+J=+$qL#4t zt_&-%+ZzW2OM2yJXyr=aiRh;F`XA$$CKw^uD=z6BOx_b#hugJp=IGhE0AHVG}t;#-F0WovA( z_g$mX$@Fs6YmEo%@7@zh<=X9DSQ@h99z2BlwO*P-(WR7epphCY44ruohZcMoJ^3wH z8{$mqi1d5tOk+6L0~49CEO%GI)?T*`a=HG=Yur`U^mD6>@>|la7sj||82Rp7k%?V_ zZoS1hS#FKur;H-*JY!uAHM68eL5FmC3yi+iOWtRHzT&EH5PUH=J~IwB#Bl^2=SGg^ znH%ja_c>QAt2-Wc-;_L%3mXa-7Q4^v+cN61(i2=g^u+t@d}LZ#_QnL5g`f731bf@) z$*yuncLK*D^87^CNMi_r;)K)ve!$IBQz5p?eX;ZHcwg*%znkQmrB9UNC%g)K`6)gO zwO57sR|y=&=iKO&how)3!TTO*!a@Bi%bo1XG$=_RSIGVy@1s+tDXs_FRu=s_xP6B& z>rdIv*IfgRPYIll0C(p%T6=SR<#k=&+96%gei3XvoG(JxOH)u`}!t{(1z zvs^88eaHibRiPmd@-h38kYrYVNY7A~XO62WTRq#gQhSR%HwO;;(~03c0jj;pZI<7F z^UF;$VA?mOo{|K8Da)1gh%N$k`)IGRVa(OWc#SCHjm{z~IFwe2CUNzeuyZdwX=o2b zp{Vw!u8YPFO76)_^IK&fN3~BCVZ5@WjdkbFb5+pvix1fOnnPlYOaG6x?+&b@S{`Qi zCIqq@NFkx6hlG-l0tvmOL1+mHMHE4U6fuAX&26DZ5y2OMC~y>MK@>$muw6Sr#EJ+u z6cq#5C`w{`APV1{IeYKU-XiZKzdwM>oM~rfPMOn|$VL0X3q-!{*Wkr|=^L&&#L#}n zS^JI9r5z`V==PKUcC#Nm9?k7n8V29Z_(C(_fK3&%S=kon@|jrGZ=&twu)oE29taVJ zV_>-9Y;pCFK(_HdTQF0$RK&4oYbze|8wg6Wn%XXL%3!Xp*i{kB@%{hyu^d1AZ;Zq? zWI3L<@MmGaq?*-iuSj649;=9Jit~H3(OWCBl-@)omtDhdbhm4!R^5!hMNrNeXMRz= zL#Ne7Wn2Tb>R>S{-@$8nSCkigoR}|n!a>NC6DAU0HdkDOZM4d^`h~=VZ;Cs|+Ss$hW`7w~!Pd zUnoGnH&QTUpQ zYnxVSTg;pD&>)z^oa3Sk_^;ppfybR@?+a%eUarWGKFx*EvEfrHo#lK#DUGGRQgKT8 z+o-$f-|AycO&A*nv|nuyeUXUZ+og`U*I@0~q=C$_zhZzFbWFGBxuMGgFSEwYFpYK70}cfBfS3CpAn2Mh z>kd@(^v3;8^XfUng)?IpX3tYzCmeCt_7x7mbPZa- z+>5hkIv#x&raQ_P1Q9n*KfNqAPCq3DaSP0&<#U(W-2dL%Mfrsk;Fjqb9xmR_4qUh_ zwoIX+G%ItR9guAPox=1gXiG;R7Pm~PSllw*e9$jlX?4XFxeT{V0UfglijI4ry9ad& zN9NkNjlfwSRwOAD6|<@A@iS7DE`&4plmQKiZ#`78SS7?XI{Oi7?l@2Cy&r+wJ*i{4 z+ecl6I^D>QA2-{5wo8h91Psnk@E-yr@LMQ9AF1dgDRT)o^yHi?!jp4I0ebS@E5eia zkplGOJy(2qvgXSF;7RS=EQm!NkB(WQgm+jwX6KX0|_$vB74~^*ghjr zbY%TZzf@%(fubWR8WKNvwBja}Ks85Vckl_JMn@7nhScat0@bL|k>6j1I^Cc%He_^U z8Q7aT@~>kRA(9ff4G@2B>J5(KEX#6A5edC#^oR+*Dr?trDoyBYYWeHlap;58- z%}7wr6Jk{OtS^Nx3WZx4;;tDh-##P8tHu~fR0TbfJfJ&vpIbtAeeZ6&=u zVI+AF$2_zk!$7RNbiHsX?`v^MsKF`+${$=7Ydf!8W_xDN%#|;T`#j1BA_+&`0uFGF zy7&lV_Nv^K(sZ`!XBd%gCFp3msgjQtJ6H17VyoKcXUR89tY&RxfpQ~Z1`!WuQ*Q%J zua}rK6e6;K9XVf-YjS|5{6dDZkzk{ykGgB>2yCqAE-B9uL}bgCqLgPSlpj4>)x9Xh z0L6jk9nkG#OBdxmf{qnE;H#pac&#X(GLTu1w$)6OXk>5vT^6qzAb7+HGu+ceJaz^I zPjm*=|E-AeLVf5DSjxC`RqB<0R>XOs#(^bB)`Rc=OZEfznnx)ySEb%`p`wo$*_)z! zt1S3p#Y`pRDlF0sZqoyQhZZ@HV&upUn4iI`4+@!TiaCDpet($sKHV}f!jSOjVJ}@j zy)a@L*8;DhOy|Gw8p?E;R>+K zuuM!tmZb0meB7cSePI`C9@MZ z&C60=B?XwoLc!dp=l56MBLxr|BB7U_Vs(DzQ7+!_RklgWNrH*Ik88XeNCEPO0_1&} z6d>>5s9AX~&U1Ink6`J)_kyhxlOCSPIm{%qP9z1$848edPg3C0T87enerDYynAVRX zsK|Vn#(W|vK;}>Y%p>r7Y|2bhDkR*PohRu6<~k}%BD{FKtXgK$cKak&9cUin%NxfCKtMi~WU$0a)8Fl7Keb}`x_w{ni z=hqYNc>K94$lR;tnsDdQKu3_dle$Ys(&jSQ`Ms!vF@ZJ#9;^DXMWh!3?6KZ;Ban8n zS*^|86~don_d7W@&FVop&Ax=8Q;B8YqtHvtAa z@+O>-Iv;8d^}-(OqWbCK4WU#7U#592%skKwI%fINZs>A7#3i2xxv8UN`RN3m>jd04 zhnstPa$g%^o}uItY)zNC2y<5hZ|r{gm7*x!uKr>oPVB0k%q}GiaSWf#0XW-$mQa&v zo5>DK!G4bI?ac2;$~=ON>7mt+?fI^vqhcimIBKu-6QgzwDZo+t0Y4wplSlo;^n`II z84~?ay&hVkZ)LTS=17B7J)hV^MDmHKWM!L^%tjscNg&l6p_u1WsGjG4Kse(hkfI^+ zsc7^4K?DlzyRJ`oEL#_2PFKDm2sA=JD%8ib(e!+)0K`=VZURqDRU<|mCjU7>KvEfjX9n77HwPQnsH;VFO7K%XK7 zdfva!U(5UVlVS{ry}knCL$3jWdB5IFwP(OUIOhFSxE>Lwh|IV=^JvLmr2Q0Ij|dOw zCq2vs3WbVx%G3UT2xp84iiRxD^)z=>2~-;FLO7g=T(V=`i>1T5Q8~qDnkezw`3rxKUVjx-sbxZWN53yRRO8W z1VZaw;kdrg)lwTE@!%(Vmn*kjm3VwVZ?#?1&pcb1cU9u~{mn@R$$CEiz*UJY1I#I2 zTpY_+b~X`e?=H3sG%qoT7G1^`(0dOd_HMEI7yN?_#Ck^bgukl?Z|q@BWqVImFy(W? z5nJuYuqnic)sIPmYmvuvrg;G54pN+Qjui7&3lG-D6_|aUbb!O>xMF7#DyM8>+-Jj5x0LXAD$b(Gxuh= z&U3pTuAaz~VSe+0B}bm<$3jj)A^-ZhLMCMHnXn;C(5GZodnyaVmvbF46TYAS!c6#n zmOUJri(4Z6t(P2_jW91z9wXJ%bKp%n)RhC@)8rhu=ce8Nm81X`HOjn7c|{i?GT|3_ zG(#r*YyioGKPFh1_8o#S;hAtfDZsQ33NWYqg%m)W*0#2xv@vP%C=iZWHfF*BE%fk3 z-li6UcQ`3P-cW$N6G(y18%j0am`!@IUD=)hkxjz=-cC#%Yff;clmuC%l*$-pQ{iFBr8q>sby>0?$Vu^<~ChF?byy+GlEV4Sl6Iq=n0cJuK z-Uy!B2B#+pfh(^|X5~NLe65cVz)=V-YTD8oP9PfKrgZT2=IbQo0Ro1WT%@ca0NzJS z53u$VVQi;}t~@ESnq$-a(@jh`OTY0uf5+Do&2TPtr_P!h^93C&lF*&(-AU#$FX(8> zcRbO5o^0Nr5bok+`j-R|YqFCKyxE*!K*X`BK5oB1d+=s+Pvxv9Nld95iL3HadgZkw zkyKvW2yWR@Z!nl7Hs=6L5+T5+Or1aT#aqn%C8ZO=!*MLOr5MLzNdYDzeOih{q#r53 z(V$mLAEQBjOEG$l;gvI_hhcgRv`>A2SRB2mSbg3(k;uf23P8uPgQDwWhX)iBL<&Xo z<3?}=VU1G*iiRwA-fCW=5-1I!rGy%1B?M1QJnQG0!@N-A{^7${p-xu}>|BXNR7)`< z=>Y%2jKtA)mN`mNUMJkpl`m_qe3=xWE01Wd{Dc&sD?jq(%5VM`R|boT2#7^jQn9)# ze*?ZB}GG)wdLliDuHUQ#O57CsL_=KkGPUR zHEMKa##N}(6+$TbTignMk+{+||7hD%%s-lg)%pCx1W3$2RhdSF@J6jn;Q-O7S+UuC zKwcEcYJRRrRH_IjdUipek4E~RKyQr{x0vj}jBhcS2{W*aw#9U3pipuOFwm7uW5ueR zqP#>%P}3KTnr1mx+RY&*FG`jC|Jz=f}r&0PRXXFn1+*6x(A+BJHu z9p6_9)w>|=Ij#@c;f3bs6e`r!<&yD6!+wwGfNQg@7Ms6OgA`W?(rzML2aAy=i1oeK z+}R5{ZasB&LzjaT#_l#ht`PRFF*}9m79m=on{FSfgLQ^9{podUKu_Z?#!g}bp>z2JQ0-;zS+gH*2S_GS&~`% zUtGyJzb<9%er1LCn}J9lwvXSJJRv?yQ`;}#^TZB(abtyGrL+L9+; zSPLOwKu88BS5LUsylXnXu-5(|^R6Oqe5YSCU)FfWlEPNJV{OiMBrFJXOk8c=Bda}# z?kwkHOB`#t-kb(EP5Q1k_fQAXQt4UCEpk6qj2=haU+NmBvbeqTGT5?*&AFi&oGu0I zFj5jNz6bmIVd&*NrKLY&9w<#=w?AUeP^WrGyV;ktIVi1%bOT$t&bz!*>&zFu$iv#* zD{6P2hrD}y$*Xb6yK#d#E84Suz{+_sEt55_F=uvIeede3)%?}NuDsD3YMwF27RRDC znoHGfRE3-pTcOm09o=Z2X4L#hKTBbhhfEqCjy;=T=|bI0*`btJSoBigpD?Y`LyrpjOXGSZJKtD3*Cr|AYYfR!wq+?Jj1 zKDz^JP>Q>S>B_ed_Sg$dD&}=CYT#B+4VBiDK|RCS*}n6qZAh1;PuSvZX1i(%BFz$O zk-j}N$rKa>%Ll#MbXHr_a*Sdn$VU{n58_eW!w;$eN0rjsbS0W=`H3lrJ^qxr+Kbei zwws5UGC=B)2g8_HvWDBkddX=*bQ_NbG!O{)C}BO=;>f@xuVSSg=6s`AH-l*! z8Vn|-!uf>k?cKVVZVU=|D6XNiI+-ely%VZzpTEZYalCq-dqo_4(7aI z?yYX8^~NxGLii%o!xzu9&99k7An%zza|nCpMRQ=r|L=p0(|M1JiuN*X2?|)dtVNm% z|7v3!j3C^5VQ+It3h6301@R?Dcy};}HNI#|Ws_bqFIJCHx{N)xLbka7E!XI#?rii) zb8m@=`OchUdW75UKQPjjuZ;<0J6t2rfaflB`{s?2+g5LfGyXuQj|hQ(gi^OV^D_RN;rN6xuR|t4VEnL965+ znk_fqWqFAWe$yN%^8vi6W`q#zC8xI%?&2a0c8r}J`9_gw zP!GiA#Gr=oIN!W=AglYp{IPtg6}#gRbGrJEhjtfzXcy2L+nAXBNaKiq7)vDl;yO}vZU%0?&^z7D zH&Rq|>f48jKBC#9~#SF%j(iPvi5O9*fO_Vai)FE=q+TZl>$RA+!toN0{y}&2*(7#kFL` z-;bZb>iDm-r_2-7K9oz%LYS>oy3ba!f^qnh{zB8pkKicieCQbd)2j*|I>xy|B)`ln z&kJHlM$aGFmQE5uF`hG*0dqE`b^B6w=m)dKIE~DBuChP-&yQw@x|r$&R)(!YcvrY+ zJ^^d|suwnKiWw80-=5Wtoj+4uNx1X*Pglkd9fx}nTDF2^oH4(zK29lMlHG;XFZ55A zYlCsSRNBDyorBlPgU6Izr@rnT^<|1$qJHLqRs58cEFYm*5$x>3*^||uJy22hX^2MH zgjFwj6mw4SJ=?lQP-#%`>}<7V2nnCLXYFM&5cA``PQ`Dpnti7lPqFkmMu!MF=^n+X zF%<7>gcF#9Xfev*CHx5S2B;H1;p^4B!D3JL+sCYNt!tnr`jg8?@X2MBQt>HvoNNsi zyR%;vS=)zl8nGQan=1hSWyJ%Edqu6_aN0iX)J${lvZRTb_?=X3?5=nJaqTl&5n|cJ zLFyfpFHhPWH~ndzA*odq&f8$rVh%w~wd=GVq-^vBbFsSeUnsSwfjud^T{M5EZul2U zEh#rpR^2jxp1Ow;RsCWqRCjR*w(J$bcpBAl@RIovNj*q0YyMbRD8Czm%lzuQv;=0F zMRI)z?lr0>X~~|1%4za(2s3`U&10ZH7lQj3(rmW4$dVGOn@jry`n#;=3LGFa$l5n& zem5f|L$XA$wWmtQ2T{ZTc$ia-Wq}{eAF2k1LiJqJ9#{=rTV)FLU{db};Y&ZbC=*G^ z`J#*)BA3t4A{oJr-^?$R4}^$YW^c06ww5%9; zqSwgUse0Gqok8-HYFH#KJyjg9zDzkl#Wcy~vE#b2kIt90VasRxwK9r#5+^9`v><&^ zYs+&+bUuqD?OnTHYcLRB5Ocg9Y*{R+Kf3XRtquNa&?&}3EqAJ?XesK!H#^mf6wE6j zp9&QVTm}M6`*49PC`?=6Y8^)69|lEjflCR)2=ZLuY7d021uoJowF`=;SZsu4h*3?q z`fHem`X9MM*JrwuSsK(H8P)i3o;Omfh+^3g$s10|DQ=4x$7B zETnu!kvf|qy8;>r_)P(o5-@EIc6PqHkPn zY6BI5_4pa;5pt=xg9<-LC(S$GeMy!{s@#Tv(HlPl!(>}dn65#*FzM+qam3<>Fn(;m z4NK@^=_g0G5#lSmSn|~bcV?#8Hkx?&;U<1cS4%fFi-Ng$DV9myExAN`f{-5B#vt8M z)6LReQYX06o5ngN!Vfozg(;Sa>TMK^634nr)LsM~txK$`Uoet%Kbk?POB@hmpGrYx z%PD)e&`k0YnpJ1+iD0wRE%Q`HDKRv|GAtw1O%#m!GUmvzOfcfR^$*>=NWw<&NDs?V z)j?Te2e_dpq`!M9n0J7154&%suTDK)C3d z2hb86Z}_cv)3|WxlHkC!dL1pt$;y~;ACr~RaOY&Dc(5gjv?}e*KoE(YI~A$TRxDJC zv%`{s0Q+i6AZ9BD2u>OgWm{fTjbPsIG^7V~Q&&;$+!t<$e9|{57kp!&-!~BGjn9p$ zTL`B$jrZg;{?e$CY);}mag4t?DnA>}rd(ds!B~vS;tbOu3}={q!$r6ACd@RQhmoYc zYlm8LuIf0ivk`)mX;?|*cih!!6c;O38sQ^8Zx@x*QWVm~YM&1=h`scP z^**CmbWuTsICa$vc!58pr&)S21dbswTUcy)*R(ML7KQ%F?ZBp%Sn}k@BiQMW&DrWU zsx7WoJ?2Z>JrQEvem47Jj3uA6rop1oZ-#Q1Dyf?(OKiZ_v6dmyd+hbGmOS+XT8aYS z@g?vxm%xT`mZ4q+O0Df3WDuP5@VszVIo>i_{y9P{!=3k#bJmxfi!M0<6D-AE<+#lW zv>LCE5Z3^TOG8?+%M&auBBfWdyYom5K2vMj23ym035_(nIY|aZnI1b_rUj4y6dXj9g8| zIFDkK0mb}AhI$JvM)pvmvyWgMW?NoR=TR(OhEDx)|kh!?x+ z5yAK?1?p~!r3>1j33|h$7zIJG>%{`~AjLsJP|O9%6WWT!Oz+KrEM|@b=Xxw=QYyZf z885Zf*D@nHiCD}0i_7Q#)xH{6od6dQU>f;y^E*PLptTv7HhXe_vwMK0%^%ff?Fj@| zHTipl*SbZEeL_F8B}n~;+67lNXPPa2B(*h_hxtM)4xy`>9;7VU3KOfSf1%V?H9aUD zciNyIQIjbtCIDycmT_uN3I_KV%E|4;;UohAPIz@KwRKPrS#0n;OR+kV^5pf4)+rUy zlT%79v(20jYTg8gs4OLFsXK>Ior89feiCa~XvvMZfnb6SacGAFbmd{ix zL10`N!bV!JKB+5fPtpLL%U`7S;*_N`JLr|k(tm?2Oi3JC?%43%oTO8`M z6qzRi@XSQXG7G#)K?`t(^>%wP!+MvN;0)_6@RZj@;E&sj>EmDRSXGfFnbbH`n12^L zagU{=Q5Y`17{ucod2gJxuMrW0r+B6HcC~@3#Dm9(i1fR=S=$@Id;$j(Hts$+oiuli zC3Wr7clbN1ms(~?YIq0I7SS-U(!CZ86G97cezkJ-O)c4D%PifbuI$h4i$E`Yu1wk}!n&Y|^md=uTKjnvpT`CN_losfVg6k<56X&I@ z_F-7$ruf>L;4X>_)f9`|OTor`O^_0hHNiScqzOQy8}QNS1_&B`+(VWOBV*m@$0%bo zx+ndkt1W$v^k}(zoR)JySVlY1}`-8XuL!VFd8vk59_F<>){Ly0z#sJVWP;tnXq9p7vBw;LRWHzLMeV})0-H1sH5J21nj>eYB}r1p86@zr zwV3VO1&y|t7U0-AGg6GLWwZpF>kM86U(K~5($!q~_!_1wsx876M~bkc61A|qpNevY z9S~sHQ37!zA$xQ{qP#JZ<*b_*uWqKqd>KJnuj}b~l6O1X^Q@((3FgNvZpxTWUiHM_ zHHgLFH9)ZCuX+yVEe0?Siuw!flkVz+rzc;F~4z-}}9fvKJ4^O3Bv zp(@ufy`)f~#T8eFLyoUJWa8FJRUB!jho^ zxMT%mWlMH)uO(V~fk|~>N(UuDQ$FX*l>1z!Y_|_qxAmr{n-W9X;6V&&0|Y~Q|31rq zRRb79`co3pX>93!%Nq4psvr(UzeI_l=oea|&jgyo;~=TpOR>s)0IRA7-XUY3=nhxf6PQRg7Jt*&p|2b45}25e>X(FTfiSQF@kY6aW+aU z;6K@3U%;0iZ!cELSF`dDAoHkU`#!Ryv(nA2Gu20^C`{efa)_R~^LraqS zB1K1+KI_X|b-GJ&A%7QG9PSdU+bIiN$ln$%R+6@8$L&1pyaFfmnj6tzlazy{EZ4MW{MKs_&8*>6?TX-7cJMPxU(=WvI3W34ZhQO@(#Irz)GVBt zrB0;k&c{#T?#;@n!Gmk?RGnL0NtI z0k@5C<(sZHxk9QfS^54C*Bw{BtNAZn`L2%fx$^zemzHTBE8qRu)MJ)K>f>%^&`yWe z60oL1wYf>BL-Seb$1TFxpI^Z??el~?S@`xMwCp+XAYb@q>$}Zp$-e&D@__n2rH0Ve z7Qf#X?%TX5sH6NQ#3+Ae7T2^-df@ZrNa?s2{BMU>`LncdE!pZ{9z+eTN2W+IVoA6~ zEEvVP9*8QGzaa6_lH|qkB~$sl>TH>PFVW0@`!*C=}rE7OoaDp zlZDO~K^KpOPD&+CZLW{eS328q8nM!u&voGc#g)#r2hPDM+EbR0D6p(?k#i#lI4cE< zoT-l4r!4Jcbp)*hrhjmor8TSj-qKbbL(9Mrh0+L?@q;DNNEGtX`~(*Blck?J%?p0} zAK|QlL5PlTamNqhh|UfDDz^ALOBKsLZE5A5K>%BF+R{^9=FSDQ3^@Z!PX?*5UOB3N z6Qg{DT0mvtS&B(#EuX8k6s*_pDGEmW)v`a%SymeHaV2##N5%DCZPnHw36~S!q1qv1n?fEUH;yUj_FV#V12gDf2F4GxV(}>$Ht!G1Y;`o{iD}44mh&ehf+J}` z2_)!s655Bcqi2PQpIGV5z zOu&yOyhLk(0rUcgI0FceCVUbnLg6!ti#0y-Z#Di_uQ8w1NFRzCmk;lmqEJqJVk5oH z3;VF$Q{W?aF90DwJ|T3}jwz_|#Pz6XOAaB5X0fU(mRIG3_%(y9X=)K2I@r4$!K#w=`(aOKPES zbJh)3y(%Krq8mev?p}y`N^<^U}-WU1IJL(Z5 zD$W&t_CUq0%hN{G6RNdT^-lmhIfqMKS1AFf2;pJQ;x)~*)6r%8vLBzWAWOj0_rl|x z$Q%cELwPaZcEu{sSNl-}WKtK9o1)25hk2Buh+YYNKGIvgjus<#D8aqf4NxzSKau0Rbd4zu=%TEU?>jA<`j*okb0 z*GBM;zQNkBY2jGF&fn6pxq2UEi^FqHxOIv82nF*6%BY7qgl?}IC~>&mNr|u% z+Rh=^34!(aOL6R(cS=fGLs4aOHZjtwFs09;1eP6fNnv$2RtB-OcGg+yyOa$M#&0Ev z!T2p&g2~s{2_pGAPD`*qI|gy*bz|=**x81MMdc+4xUm z@?u@>Z3&Qv)-}jO>lz?vUEDV{fb|`!c~mXv0SZ+EBGThVi2;n0onBo3TuHObZwb~@ z>SoFf?Xq68%X(UZYg4K1@>;T`1q;{s<&^ZZ-B4`t62|5Q% zlqC00WO23g;?#k(7<+}ji9ULTf<(Pnm~nSPn=;)i+AD1!6BiDtOl|*gGL-|>6??Zp zfRRoK#0H`Pg2p_SW-SSKT^BNxqgBh&ttqP2O-!L`Ktx7229Aj|f_1Mf{~ze_IIn>% z_9d~2T3_OTzND+9?xL*FCEGQZY^NpYlEt3|bT+-22rExt`^Bkm(Q@=joiCpp5zA!J99Xjc&@z6pR6GKt%et z`&iSx(Cd4}!Ab6|#FGj7!vIEqY!m*F-+(^edAwSFH9^d>x5Eg>XW84JkY_P@R1S{I z*&N~=mobaEDM@58r4$$4GbzbOlPODbH5pu&y&hQbb=h&01+L4MB#C9?Y!)}znycxh zWiE_jqjIa=l*?ihv#poa9Tbr}R2;B=l7jJowE@CMGPw>k;|HwYq_|kQH+)s@pk6s# zp4Gbp?FmAIl*jX|Of^6-RBp?+rm82YPz)6VB8Ccj*#Jf_Kd#wrwaadpH5q1Jde%fI zj>Nrs))d|uz?d~f@L!lUMRfL=HSI32-tQ%ATG_MMpDi6`U8<&WF3t&#o;oEHu%<`# zvTIMB@C~G*4UL^xhY{9!>L9{hPomm-5n48|v$j@RKP=y>j-!O&2W^?Om{m=M$qX)& zj_S-BpIbOfo$VcUrj9C&VteKQS?nEBT!eSoBwNS^ejeEZr4rdfQfEC|h~zXPTX=;3 z;{SCX&4igrfwdF+X{$9f3hHP~AG&aW(YOYZhE7|HJ{HE?kKUU>UzqT zoX^}v;g~?|P0qN9lsysprHQ4qTR6 zv!q9uG~1dIrdvxpUPR*bhH#n?fQ!A+z>n_|f5Cl} zYwXEzRIPh+w$g?)ZI>O`l-sSv5f5#L;aJ!ddXWet1FIJu%3kP72iAj> zP#;*|<)$7bztvTYso#0Ws&`@G!kc$#WGHZcFLG4!CavJA=iX&%{?b=^X1oQV$+fbHd&`hFm95fR-gbtbp zQhd7Mvr6lHS@{^Rw{$5}$F{0wZ&&q|?nQD<2`~i!s|M7zV`yzO> zt<)3WQMcH7t7Ig=y*j-b+6Zo_23p|RyREY&)kc}RSwLH(Fp%O1UQLOx&sxqQ*k`@a zm5kuqC?bwik98B{)MK;+JE>Q@iB9TuT7o_B%iVk=MDKJH2~kKlv9hSwTI-=e8je&3 zX*g0DAo>_?0P7>w_f#hwsSJqvNM!)yNVU0}IM%ZP{&kJtfnX|Eh@)MaCkwkYrzL2Y z=wxA+SXzR1iA?rkmu|_v?4qUdAPwzekcM_KK=cvZ0M_j?jOv7TF(B%8F@Vu7rexhN zu7rABH!)H!2gmY+dMOx*zpqjm>51pYX+(}wWxD55@u*HbVK;RXms!38Y} z{-U^8yFY!^&M(Cf1yOqI&@yU+6db<|5OmWwTE!3Q6~~m=&?)FCG40Zc3G|e>KlH6) z3?IOM;TS$3#pf6vyurG~%NTxf1El}sIRj{z&G?>`K8BYNu%<%w>L!limp3$~v+bL# z52@1#cYV+f_ad}xD%-c&x>~KI6gXNRem^;d#l7TAg6~Wb1NMU+h{5So38Hi-D|yqI z0(%vhLdNYGz|CXarc^j?Lt0(3)jBemV~Y`cFaI@z?bvE9ikixQ!ynh9@I@TpG&zpg z&PNDeRS(cI9JW`EUUJ7*1fE@4$@Y=&f0bl$ilAOAPc*814JM43}C%$A5AsFuHAsBckKo+_8EcQ zMb{nx|GI{}3d#?yQr?~IE3`){v;d8=Of$;;v;>W^)R$3K`!I?&g#l4$lyb@ujbec4 zP9hu(I|6>QC#DlUw5%i3*R+)6Vh1BS{tA{;A7tRR2IhDNe*$w z8;*I+QpK1jr;?CEOI;S0@=WT~R52>-g^6X`%=?py!!hqSp`3iOyBPC?V%nJ3 zmr6wKdT|KR&iPCSMbyW<5fm(*>7WpdgIl0>_)G^a!P=Fk`k49LE^4Q>jwro#Xm>~r zV#PBZlsS5;AXSX@y?_^t^-=?OPOh;Za*cT5v`cgufJyryUwxdj#(eb&{tL&tCsJ{& zQ|bE<>`0r1@uoC*Ct}n7*@GgmNb6*s9OG3M@|HD6j#nKaKP?&}nc@MvYN`Cg;4Wp) zaOOMsU$60(R$hj`^v}-l!sS>%J~)HO_?~MT+xNCLh0A{E#1DP?{U3a*q}5HvhhpKV zq?NzRiI048-O8The`W9s?RZyyJwNq{he@scAO@c4NWuj{{?|sHBVxKaiubl9DQr*M zs>LR-5nFX}LmZ3gpO(ztdlz!NQ``b*wr^6&r(Ws_7!Y`XR!_a==>UG}<<-yOAjRJq zX>Hg?W8hujAK!zcM!ymU8t26}e^+TESU3=h+5p^Y!?VMXU{b0ll%xFESL;mm7`tsf}Z zhjG_+V8w^5!y~>ScF{2~n59NX<00!%$;2rjmVfNgn~TnbzwRn~2eezTx{O1X-&F>G z!~eQqSs4n2$~7x%md2xD=Gtev_hy6phK8{ftrCLSKc89ySQ`CJ!TZU{uApUrING4z^P!hpID2EtU7@I`o9R7OIsV;uv&IvHWwfWW)?6$A0 z^#*A*zgXj0`FrYSGPH*zqSLP~Bk`2= zJ}IB=JY~&Sh7!&vA}dEr9*nidIq2UR!>bSj*x>=D@JNqp6H784IP8x2HvW!<-&^5x zuhWV6#;FiJhgMJPq|6~uZc=GFTlAxKnkRPsjZ-@*i#)Mc{A9h$6B~Kgcw+B3ZH@QD zM&6HkV%yJHr+8uqoV5;9Uhu?z>a4Y^0h>n~v5~eT+=Q{XyHG1%e|EU5f`s*mEc!oAWtQZ86!Ss6%#V8;=?UoKLH5Gb1S zqsu$ts|fq$3~3-s{|CgeW?9s=Ww4vpyxnmci0TO$%wt;G_~|(_o4XpP8Z%t&^>O^qMDU zOj>Lk!>WIiyE$rG*m_Iyg$(?{lyt$76KE@tDvC_vX#v`h)qeGH%@w(mAA2tDq5|>opz}HPZQ%HCe_wr%`sCLt6$K$Ia?5J z8>PIUi(%mRZulXJwqAsnJ>LVS6Ow7HvY(KIEVWPbiH&yz^V-@zP`)H2jX&DPNuRMJ z9c{go9|=6}=6U1f&w7Z@-Ty%fYJRZI;stp2{s@~AWrHWr;9)$aRZl%;kvg!axRanE zeLG*dK}jM=T(lhD6E6cOnWO-zp#V?+uL?B9D!HT-72u`(@IUgNs@zD*k?jPH?QNt0 z*+PNN)=El|EiZMkjbQJ`*w!ek2omzH)_89u1;`r;T+g>DJ4h+=hEl?NZMRwDlmi3@ zS?|+We?kh7H57o_1CfM zD~pts1b~z2`y9J7Y}Jwh6Q=-6IVMfIsIWafZS$0!gjdGVc}2>04iN5Tt1@j5U)yR! zGAsW*AfNr+#Z=&E-OJWmQr;zk<`&wE<80R#=d!?~}wZJS)5$)-$Sn53N4 zi+MK;9|rLiBIhz$Z3lbLAQB?bF{c+b?=2t8Wcv=n>hUqc3?tDmON+$jS+3A!7>RP0 zk4Oy8@*0Wx(lNHLzpbM|#)(k-I9^e{o~)3HGD(J+1qDEMAJ1MHV7sJb5>1>5aobIs z?v&xB(c(e29?AfMpy$S!St4VYHQ4r?JSs~}Z!=l{Y}-HsOCA@|dR%BpCQ-$i8%O2X zx|?nT`|#XYx{ckM18M8+L^g)rELNUp%MH^RYU$6dSz=j#8fe0w)!%ICNeSsi0+zR@pkCU(kzN3+6RxYjU7;AR z{wm3Ou?Y0ey?g|ERxb>6xAr8>3Qm?2df`3*d}Q>IKvwYc+#BtQQM| ztoCJ)Exrx1N;62MFbEMTnmPqQogy506Ks)^Lcv%mtFuzv->HsnH^5Sf@+H-fyZSS& zW}oQ=kRvTvoWX*v!NX0By~N8r%5QqPsM>j7Rr^O&%`m*y-C|3X&uSHeX({(Kktixg z0qCr%$+npWH1sro9bbv-t%odn+JpGjo50f)ibna^U=()dX4^~3P{Iqno!eW4f399Y zZE{m@%_gOKxv&`5DmIdGw43OKpUSMVy=hn$CQpL*v!WueYCe2 zq>mD28GG%itoUXr+9dVS9BAsJM-h(HSA59|>f^(KAZdzZ@1RggI8;NO(W9i!BFrfO z47)_30F3b6cdD667SRnOoT7-oK}?75lo%7QodKR(z&nR2wmot6Z-n- zN;CR;ns(4VwsF^JS~;dK>$}9(U5O!TaNCCEaR9Y#WM8rR)xNJVZr;7NN>;th7ARHl z4YUc@s=+wImzZjC^$=)a_u1a_TL_x4n%XXL%3`7<+G_E!{B+5esqPo13d`pWTqL?Y ztA4gcvu5nX7JEATsLm9^8eYG4C)?P<`)wJDji`mTTkmc=vsTADHQQDH$M&MSTPM@T zqdTf?@ybg&nD2{<@krXu&Q{w}z0j0TuZ&mT_eLY{2FvgTbs~s0HL&HKq$;|*)^05f zbiA?BCQ0y|aNR1%BmN;O>2ZD0m$L%;dB$~&)jp1;AGzroS0yT7QT3MxZM~I0h$`rx z_Wj&q`&X?}=QaPBf3v@;cIQ~mH5i;PpsllXuth zl|EoaTOj-Yfars^KFdrQ}JsXqp(=fQ_wEN7Rkr(rq)rkin%29rDWXZ@bC zB`KYV4rsAq96&7=Cn_aHvxXO8(O}?qTct9IP&LJ1H)sZn?r$(y?9rZq?BN}@{ib{R z!}iTlQ)lH~B2kaDDqq%G>1nNok8C|z>cr+PS=8%4v|tl!+Xpsf;4>`%)oNZH(lL-| zh8C=Kw;+6tJmeHifULrT=H0g4$_s?5DHeQIv!K;z!L&&*$@+O!VWgPSrtkeBg!Qc{ z97F#5YE5BB_*Q+xb1+aHC)()NJ?6{0KY3ag#;G0*#I$Fl9x7~_VLu1MmJjb3ufPvu z&-s_TWk1m@dzf2xkFnksln4Ulb6vUB0G9I-%rYo?ljj7=0MYgjJ00PG z+3p}oDq!iaLc1MKl+Z0aWPpz$Y3u;cslepdY*VhWxtnqZXrmGQFxqrF2hjFDNUKQy z0b(?2hz;>)b&H!%QS5}aDKTpy60nwR%}U?0)hHhmf~FYjBh6T=!5w5w zNk7v)kOgin?7+^w4f(-EkjA2(Y@V!KB64->{nwZE{0Djl+VOX7*K#Zr)70Ns{d=}f z%5OvqG*{b!ZeiA-)$3<1%nm08%vO>)mUbR;&kOTLC_M=P+ivnewrBc0Sa>D{O>Vng z28y=Jb29c?o_LhM@+HkoS(?VcgYm#WXXgl#0NRFc)GBoSK+%TFs|shbn?7rDp8AmBD_swBPg|}tqfcK2Luv0%ZGTFy zv((REIN3`SL__U9>6Z>io$!%1kCl@5yx0kclk#r^LRt6U&IPPF@7JUu1wPU{=_u?s zIf!0pxUbv|_q=AfJ(}U3k^OF0&J!{iRub8&%K=@L{}L#M=6NkNDLP82c3+}7r59!AwZaV*Pou0NSmJPo8`jDe)*!axq;0(NBtb>l zTL+0VDKC-&CK)z65 z;9L5mZK)DESa%KbZ8ccv8%qk1FBBl(R8oL^p}@d*`!Duelmdc<`XRBYt#7NPYRGP6d>P+NdfYO0w-U793|XKFqTbV8Ru==;L-A` ze}da61VbD@$sS}le$pl!Po4}7f`cV{xj1}=^BuOh!B!A8f%}2>l)1WN@Q_KWBec=> znxuS073IeyjuHT_n0~~nezPq%AmWg9+6~bJtXOQCUta?%uEJh&Lxtmx+y1b<>4_MW ztp^4djyy|x`ehkVaU4wFa`QDV*kY?~r5q$m!J&?57JH)WO-c&UfS>G8yK(@Y?3geJ zZy-80UbLl2N&!K{ou9mHv6Ysm7ic>_<(F&+OgCi*uoHO`2)eHy6VnqEoIXoKQ|fP)M%n38+s_$nrvjjH9oh4#Zv9m-0xIj3~&1%7BK%gVo9c0~Dk7+*RqG z@UzDn=#Kc=i_}gG8cPeVtXHxKFAUL)91)@!dVvU0$3HFXs$?3Kqs3^Ejv!)mM2?Rby*|flj7mcp z(E&1}!=mc!%+eF@#{DU>$~Y3SP4_KsXMey}L}=_%Q!m!L`+)rSBNOA z(u=;hza_W_(U#DRmCT)z?Ir-5+Seceo7!=A0mpm^_(=%xY-(I}+{L9W53-%jNzM_L&7)J@maWimaJqEW+Hxb zwfNNwv@Uko<5RNO;l}6~)^F>$P*yi9r~@l|_l6ryg}GWtkJf2KNRQ0*5z;s0dJSp0 zAXn_P7Z6T*e>fKep_A?+#TW&52tl4poeS99XnR)BJ2VQgKjfmY>-7+YUHqC{5!%dM z(nG!^)uJSYNMhKrlaI`KW;BvKqBXaN@R0aXSE`6M1S)6^PtehrbjJSr|?fsNS0>vo=%?7(G5)ML(SE1wpU2Ld?U_nIo*u4qd%zb1OnE+nA_NL7_MV37LGm^}G?DlA zIMdQTKzy3r*x4TKDIIol{Mo|4?B#OTJl60R@Je=<-r1M*EN{~PwvUVUln&-_embQq zi%YO~Wj}Vcw=$@M#v44oO(fg=lkHzA zQwc-SHT0O%OPNKWT#Pi8T}ZJPcw!$uKf9B%z!UpScYCoXHlC4M>4|+d)jrG}yGW^Z zLzJh2WqDnx&b+QsdR?`Lj!0d#V}_}@q|-`sWM7=h_iBGT`B8WfLjJvEor*qMj12FgpE2R(gtb7pocub7v|EeF3#a zUy#}gUl;({Fkz(tw~q3Ye9=*UMiu29eLwvcl!w})t4uqG> zt#Fk%qrje^3?+r=)LdVJiicqP@^q>Ug0O{ALFiSeEP9nxR(O>Hu#wy`+@7OQC?+R1 zq8v6Zih*?Rf8p2GK!=`?h7eDrZksXEE-M=dFKl3sXr6dPFQA@yLGy$|FBYD7&X7jsp*HQ)IadD3NEmF|!6_MR%yLOZGSOR#?gyEHiQI6y1{vCTKyzc;-wRJ#G= zAgCB(&kgm_tLz)JK!F}>{9vnWD!@KdF_8i>Q+PkOC0m)|-&yWhAa3$T5folS z3BH$VxAzb8*x%?}fE8>*(;0CDuR4fTMNW%uQ>IU<62-+5&|~v-`>h5&+@_iu<`r63 zezB}|n*Smtk0^&Th{JJ%{n*|#{~pRnQp6)g%43Iag&8Cz;iAYKy0cJcfZ!d&S^ccI*z0!VM}k4<4$w%+FNm{o2sm6a`oBYIKKHFgw;Tw@nO;hB!K z9lhw8l)l93Eig5ssbUOd8YIurzGc3J`I+rQJY~DGEa@=&#ca<~K6V#<$cN~!y@-Ys ztBoEtPSIe44t@O7{!RGrLinHV!hiJx z*;~m<-Y`AHcrbMv41j+LNnUIS$!wmRjVDkH$-%7EB73evvAu+3nh44M!!RVfvonkA z6-qhbg_q=Y_oZtgJdAHc_ZBwjKg_EQG}e7sX%*;^$$4Uu4X>~4Z8?}5fnP);lgh51 zZC6|d`&;Wl&+0uWe_qqD{$J8{eo+M7A^~yEHGg_6Glj?~J{{GM3nr zf-3lCB0QnhtPJ)cS?vuyXRs@E)57`wWVz?o4mHwFC-7Y@ zlRO;qm4iwBls2RUH^SuMVq42ezq?)H5G93RA$=F1&$z{ZkkXHoAbl5|9&c%Tseak_ z!}u-j z4$NBbvZS%o57_r8G!I0-TqUjXiY~JPHMfu)cgA+b9I4?9%hz6|HT6^a(FY?6ND9Cy?JH~T*BP|r zIg#`@*8px0@~^C}2C4id!y4AW?9-I^5l~mH386b;IDok0EqUMwu^cm)pyCX&{|Fy5 z$l)Wz%`93oT#xAutk%L7R!_o8pF*aO5L3t)Aa|*l&WcqzMX?YH)blPkJ+s(__4XR& zKLn3YAeH+FAS7vi7Xv_#pG}|{yf3NL5_GKO249tYT2wNKR1$Uxc>qP~4%9w;LY4S( z6O0oSfNARzt?qY;y2~}g@niA|ZA94l)5cFc#XJ9qlU#Z1{7>;;*!iCtAs$rr()(}Q zVz2V-`0scOhJ(L}8L+#*paWdpeN7X)`}14vE0nO2plLTgDpiP{zV%4a(<>w0kE0~J zqjq*f#j_xJ?pT9IiZdG}qyW!AKmneCxS15-83-uAGZ3HxcJ^K>Ulur$clJ*@`+0&Q z`uX4B+vD#o$Y9zV9P|*xQZ5hs`4z0>Y5T~iKn|ci{2#>H*uy)1dfFZ@scUsj>Fu12 zI#|DhAg>+C&Q;sGdm+LrBfGs3No(2tyX6qj?y$KgzeeyZ4`+ah4)>R6`UbG`VcfqEWia3P9ksR zXCHcx5?yLvQi`KhmJd03qePEN3&e~iQ>JNZ}mm%kA`{#E-yf3fNwws9t!xD zl%V6_TSHz0mie>tJh$C#cW1hg^)hByi!yUW1X8xArs_C~tPDDWj?ypZ87_&@{(A2k;SAA|)4 z9|;Q)d=%gezUJ(m=lzE$v7V!UZj>2PB8DECGND?S__;)>o;@7cdp zwh)Hc^K2~CqE|1_dLG(0U$}=J)KWAmJ0xjX#OAk;uULDg~ffmw#mMY(Ud@*FuZ* z&=)=-+=NfE%we9y^)vkf*n5Y8Z>Otrm~{k}ZmCk(A3a*A_eZWJ*z+*n^Cj5hFeiY? zsr=PQR<&)xv_K*QhoW&D;2erDovHh=Tcvzw5i3coOi(HaJ~rrbw&yDdp;bHm13gzN z7Z!;m#pvXWeg560*_( zFYJ#ibp#Km)2|T#PNyjVqpV>_pDyyJT6I4s=vdv4|E;?9zN#A?Rd$SzuqiOakJR3` zrGn2Kv(Hf|09)tF!T?X|2Eg?cI;X%XHJxn{=i!vP?P!4Dl)4@Ng;VNwqkT@PKf8NT z1bb~(Wd_@Ha$Z+f{^i}FtoX6{Z9S&h+x8!~OG*aksZD-yn%!Loq-m;DZ)nmqdps*n z|2>2)&TZbFU8%PpQ-GII&Gh&{6(;k`JWo|7R9>bkU10}^C4&9q-6vtMdrLz zV~!TdK4+h#q!BD+o?I*}GLRG?b11+k2}hCw{t8f zsKMOi*v_>FPP^$oNE54FcoE*A>#U_hnAPmn!FnnLGr%u@x8I-;8tpo^z3(+HcWKQk z_~rSk@;s4=?`5aGxX9lz=}-I1lJW&9!|t)XG|QhAT(Dm+on)IYKtA;y!N7sI9^Cb| zxu54~@Jlh1>hJE^y6hQF;#{+8#&)T;!C_@bIS>t}y}yP_o9++;{i*WS#$1Y1sD$xlI zS9cK%w`xdbd$#DZeVAV#C};COKi7p_DewzA$Qz^- zNAOpChmF-&*xJp&Pefmew#6RGr<`tMMGjdpHHE9K0oQIbQ6Or;}lAVSxFy4 zXE+hwSUV!afUY0br%X_DJgh&0aPpx!KdeuQaRyb%T_Exs$@*e&B|P+b2VsTrI%|xG z*I9ajh*vEyUpht$*kw9`$ZeL4@zK#eIL3R#%8SQ{Rh7kr6(;7}K?o-1J4gxkrce43 z^5PiJc*V>dgkWY)h3M_#&=}D!4!a9F=u6NsFM_aPfFPclON-f&ww2eJeuX;V@%-P7 ztY=8RIA0c=TNzq{mXjNpM=)$_5o5Ks)^4mG$!MiEV|}_<=GYRJ>}U! zeKsrvg;92y!b_)J9L`ef2840ik^$0bO9(6FPmc_c{&av~u}K~ZC#XU; z2_sD+56OcdblhM;R~xs0t86)qppTykl=FHxIq!vRda?M_K@ujF;9qqd{|fv^9LN8G zNKm)3FNG6x6|@%T@o9DNJU%c-|Dx5A{sop6>4m985T+L>09~YGGv~uLGW0Jzx7}o* z>H^Zg2sbQzpt76rLu_% zkIz+VV|iXDXEHyR5??oX0$4CGIAn<@E49(0R3G?)_u*4vEni^G9TaA4nIUZxFpiy`Yd ze7bXQFXywdFDWJ9sNV5THB|H367o1w*bnE_!J6} zwa;gihdA^8v9x&bnYoMnd~dkBX$!Tm_NhVEKJ{e(dI?yFlkQZDfTfQ`8L;%h>&a<6 zcSqIstomT(n79b4DgeGk5GF?t)vtZP(Q>dgFKJB*;2_vyF#1k#P2kDC0nUs7*AZ8A z^(KSm8G{Cdmp>`0rwo>9+^U0RR@4|QPSRRg(TSvpT(kw~+rDCGKj-Ta%u5LIn5t_q z_6_DD2yC>|(S0lP+;=87cC3R+7T!In8QVZ;u##)SRdPF4($-w51D#E)t7zCjww8;J z80gG3h;%C_vZ798d-eno=zqM?0mM8xDY7SjYLK&Ph@xAPBKxox!xp_YIkIhVbq~GW zt`h%quruHB9_teVb;ALBr;ta@IDn|^J5yr~*pCqu4uFRQ00(SnWE`+F`bNH`zcEy9SDz;I;+%~B zTDaQ33olfOhv7->A!&z~L0=jw*T*jrW@u;3SzI1!%?-XMXc#sp!do1n)8u~+l_?9m zD4ZLBC|pufQDRBSP7>y7vTy<%TkQEB0*+z}^}ta7WT9ouFtCi(@6c3f0$?-McCYhA zb{nC?9n>BKfIFxZ5HM#LI?S3g3@3$f&MSt)g(XI>@GaL+K`4Vo-0RlJXY7qo(%mD&7=0FA9mJs23SuZ8cwA26-A6Kfe|7 zG(?_U)KWm+3Fk~31KphBN&CENj?oQ$&BsJx7iTF3{5g%gmjPr3SpT94{yyJAxFbP zg_gPE>ETS`8X-r+JCuX?M#Cv1)Ey(Gt5q5q;A-$O_s~Os)sdlHP5%SDR$M&zg-FG5e#g&wk=h8U;eWwa zehsaA2VIG5RPz=AAZljtW&54avHpY(hxvX4fWtfmV1well?hNsaqnOfA;%US7p{(l zvW~HK-@$taql7zQbhge&QJGr~ItMWdz$UwEq^$cbz*P+Kqle3T2Q%{?ju-$3_oE8%_YUs$o^Y;V?&NaYVr+7oYi^fa;=*9)rwsTr2j_J!^8Up70!DSLTHtt3Iz%+)9}+ECWPHN zagLIKp`Iv3N94((R3Cl7C@bg@uDGQ%fB z-P>3jB}e6lo_D^&o+td!D#t9V98(BtmG>;Ge4xp#Zs%7DsZQwyOIqA;;=I8K$}~hN~`|#?25Wz{q2LVU)_e=S}A* zMgiEAJBR^RDFfhwl7hBnAtrtvLOsE<;K{WF-i#> zTePY?^)qJq$Z2e= z;?9M;B!&=|zXhshLYF!xILxe~@w_L*RH6Xz-@`ae~3qzK@QPDT0TgLSu?L zmyOXA6GBVjVDKcZ2wj8uuc4RL<8kMlDbdn9&RO2kXKG}2GAL&Ej`>QsoNw@Y74vi0 zmkKQNtN7WEO9U#$Nc~G_R`J;nN)FcsZ{$6Go0)IsZDvG9vd@S-vGr5&NR6zUH5QW# zm9Tp3*I&WLO?3i*@hO$}NXTjr9VxYEd<_Rs^U{Q@7PewI?qi)Ald_^tNI#-5a$Yd~ z)xyZWtWzlZy|W^-Z1kA7tt?2fD_ZAygX&W}J2FLMIfNxDhJuC?s89@M8pkd=F9lOq z+tRH$%MYf`y9^l$$~!=*Xt{wxmAZ7<*@rD8tPX!aFDsEy_&QWR)Qy+c&GNAIgc^2k zZs)PJ;wwX%q~v>NLd04?^76gU)RMoBR&;`|wAagO#rBX=@L}feJoj5Yf)}6EDD9TSuhi62bNQ(soQ;emD4myoa150BkhfVF zUn41~2&oQl^P}_51lk9n#c-an1$vEmjpJpZCc&TFwVb}i}6B#H`l&QA(5j#FL`Eu1Af&T z8L8`ea#$Jln{!a|C7~!CR^BI?%R~L@t2Qi8RTCF0=N`T5MpB2qn2=*-4WkKP+zS5o z-dm&j$c3o~5bhzGh)E*L76A0QOOVfTy~!pK z3Y;E}BLJKpQUF%AO-XKLe(1i)W)2tVcWD_MrE-%(n2uN=D;vCNe_x)Q6zigde^T7K zbyl;ws!rBB8bmT|s%I~YOko5hPq}Pe7I}|jyHAhuKs~mF)8i4T2P1m$+(_45*VE$R z^sFv6Eif&Tnjb4 zeA(*AwJd%t)WZrxIOC`~R&HaY5(I8z00Oo#AZW+LG-9m@7WOhGRND}N@0D z1pPpaBty`l^^s%QFrp?#pB{@-Z#ep((Z1XeS&I!OY*mtE27%(5Z>j)bcZMqBQnk)M z`#s0*C3Kh$@Q#(|jl2YbefiunM-vAhYaK7$M9|ocH$YQ`yj!#jEZ%fpdzK?gSP2q1 zT3RnYf0BTp;jCWl<^5~Al46Ny=*)2i6SLTpL>!)t0W}MI!AV_0D|>m5TG5TP*ZJxM zR|9s6lv3w~Uk#_}J7e*@a4gXja_8rlM%9fER&}gQU{Lv()}a8%W!K_=ywY!$O-&2~ z=2#2^+En42op^D>n;9IUQ3uA1abO#(D`5Lo764oO_1zv>!cqwx2IXV|z@SV4*pS6< zMKy6`jI-X~?MUcx(cX@)Npgj_p_MsKhGV;R&Xh;it*fkK&E1GhXu;T>k+(Afk_njF zLXMTTs0_ScE$S(30cR*kt6>nN{fQU>7j^T6`WOTkh+h~47mN!V1Y4%KHU!Rrx>Q7` zx(;e=EwKa!yOj#y4|e2^ye0Cg9&4GKW$KQ{v$4(J!UJmeimKQX0bzmP*cx%@{9ZIFNca3G=5yXk6u4QrJ zlhLKo1q(Wlo0d0w_WJyP^0+it4ef&D;}{QywOlbz@VS7}Ggur&2*Fl?dK3-?92daZ z;x1%1;HMmVb=H!gLHy9NyRzC}M}67^J4auot z#EY83EIx^!^Hgf#GwWi)0CfSg;$HhYg248)+M%4leFgAF@61_Qo!CKw#f^Aiha2%e z52$rIvY5R@sL%sWjwc@QHo*!H&;eW647UG2r3f&Cc9Pd??;6K`B=Bo^fPUHH6Eh*e z1pomKn89jMgplkj(U>Ac16&?&`M|L`L*gmF>$rfQW1j$y0)aXVrU=ePH z1H3wcIKT%4iy`1u9+wFr-~xq%1#~EdA>a>!xP}90zeqlD69d}+7nGjC>QRK~e^!B( z6fR8v%LEz%x)Ahr+TX`9n-oFw`BWH15k!Tl6z)?2TYmw;T(|W>jKB5a+tX;)b%X)x z0%pa=FDD2L0ak&71nw)K+WuLB#kL1_wh-{hovvc`HlY$8puNdca$JdW4EU5F(E;A% zsds||T&8g00B=r|4iGU(wdge*K)-2{j3l)Py{Lf(mjMTZ^qgm41Zqr?q6u!|IU`&h zV<=d(z)h2=6Z9nL>o|d5jlrZ$kQ(DDQUn5@^0O$yrwF=2F~MBV6`)qyXjdPwJDPSg zDT-|hrbQ>%M-b=)R)He~?kk|2;3UDK697BE6MW{{$UYzh*#7T`7JxoZ;G*gEcdRD+ zg(5`T0|GlgoBY4Eebi*x_VoxoDh>#Yye%n0i1wA}LJ`8?QIoBf&mPe!K89eg*YG}$ zqevN>4pS+D>ac(!d^%vG-$yXlYjja1?Efhz^U^fSvgL$6LU;?zVWAPJljfj5w~AdIcsG|%K2`;yw*A@OJh%vqSzLP zLCMrVqi$vJ!@vGOCwh?pa0lWrZ&BzPVIve;lj_CDbo~Kgm7WO?D+a!WU4FYMJoE6q zbt<;Ci>j`%ZxjVb5nuAtvt4=YO9Dq-t`dMncy5lXj*T!t7wZJof3L4g%P14x@o1E< z>W`L5&5zuN=!J5` z;i^mJh#Zkjipl;5phn3>&(og`??qa8;zLcG!Q zM!w9y*keb^nW%Qe&u^BM{y%guC6n#xnl;REkY2m)=; zU}~6LV)|5>OC&bnsddbH#PO}WqaakiUP^dlAQ$;T{m!X;O#(b9a5urK1mPXw#18_d z@Ss3I_{IdG@&%;;KEV;odu()dbxfZMA-6$xeKs>tz2c_VN?}N&c;lYr;VfF-?sBw^TF#}Kd>JOGt87wBhI zZapxh$eeH@M@x~{@@v09%ddm041Nt~OnPjFO#l3l;^%}Dzc7UOK)3eGmu^kPE4QXl zbZZJwZcU-+*44gyzBAiRlt#CvWXi266y5sBb<3e!({kw6-`U){RYjlet|}UPk8nf3 zJ_`?k!gI*%EJ2`Oe<%I=5`km5{wAE6e+%Q+WWcgMZFH6w?sO&DL@KwApDx|H=5*De z{B8{oXcry~wO>(hdN{8RBfcg-{qMv`9jXs6&vbEgoNl@HEg{8bgb~|IioKR+`|1pR z2O~B$w2Igxrpt&uDx`S0r4_Q)lR}6O^lZO;>Dg4g@@xu4&!zz7*%XSNoqXH;X#T-I zSVSx%ilci|TIJppitfGTy5-QlX*qQ7e^2v8?TYkATn#mLoG?PqerCG#>}Lo9XCnUw ztBIM&+XR7|VQ+>p^SSBQjo3|P#0Hrdv8hbu+CN*a{VNfyT>Hl`(j#Vsb8RvaQu6UZ zCC~%iI%$UG)^%ru>P@wI+_Ry2Q&TDOT5jzZXt{N8jYYuj!84CS!0s7RdiOBW`-YGn z=+%Dl(yOU-<<%65UQGeYt0@${`p}iTBKUtEhaArgqBwdrrBz-{q3G4c*DZHQuN)Uc z{6ILh21lq5LQVnS0hiN}Ry=8I)URw0;fKy$K0`WpIYFRvKMBSY&iyn&pmSG*vGzY_ zT-Uj+Cmld0IyaT6ocn_rGH!oF1fz4O6xVGNM)sGorLR53R?=}UQqD7*z&xpEnmt{j^}(XlB&IW~o&V~?mC-IWa>Dx*(RGUd}0iatHzy5%rZ({kw44~V89 zPVKvVp+`)Whoi2*T2~y7x(JyC{~J0Ri8Ne$ZV-SL;uz)*4r|ZG>xzG`#=Wm(O<@NJ zDV~aWhyd_Z1O=eS=6pD!GN0MlOwmuw@WdNn|X9_ zy=2mi)~h2_@}(wbJ4OLGkUcn4T44jQwXA@58OXYvYwjb*L+ZUioPS@_=d0f}q@X=Toj` z`Z&Og<6QGk!EvrMAwNw#2XCcA5|u($Zo8nQ-()sTf%)HYoU5gEm~;x^i-*g-XI$en z<|1HpSj;0W2HRjB={|x+XT7%|%wls57z@s0#f}pt{5fdMBRK^Kt8N_(ckw6x?Yhk- z8>2?^w_sJimxvTm11_Jx{T3tusHP(8loZ64R#6>U`zPUtN1mP&0PNq;fbw?LSyv%@ zm(bzJ_cna#KrC3^CI~bUo^<*aOoU$=zevz%qOZf5=+}@Y5=WilRb8w+CJ4uyY*aV~ zU<$w(I^%3qLz|A++5c4_JNt7WQ*`!Y1tjFPECdT!y$(&%TmWn)dFFlBT-KA&VZ7^3 z02uEm0Bv)zl_LY*p-K7BmCl9|YP8J2!Z6M=wopzDi1YC5k6f)t8(ZmZDsa4J>f`yZO+s}HbDPC440D?c!-lz`AGRwzA@*B+C3;YV z*l#sv(cS(mg1+9SuaD(eQpTo40Yy+HJQU$m0ylk23Ff++zMz2r(1-3b?Sq7aWm??t zf1JQ^*Vk9zIfAeXs7>F~6bYNYLJaQrKL;&Y;p|^Cg!|>6;Ll!mEo0x2ve(-5y#S5r z-}DX1uTTz*4;R`8#z=W*i)S^8O5|04aMjSO&Xz-DrypF|$tQ%9(IIlb@;YmXJg7&^ zV6|o|r-N~$5nughR5O-Bpkmz6Yt5E>z?A$i?*Z3TQmj4TTNH%s0cR2@j$*g)^j}>m zj8bF3#2w&4vtf-Pc7TVFVz8!>JHYyY*l9+=O+`&(6%^^d%```bx?=*SD=$2-%T_Bk!^$6biT`cq$7f3=1#0w-;AP(O_q{Osj@3)+4BKCe&xoDXR zA?18~zh|$y?$Ov&q^M{E#}QBy_kQ7rKWr%vdW}HQgO1GRX@#(%Pswq^OX*+@*Z-J} zNurtu6$@W*&+o+JqRga0_&%u$M>NdDWJz)6Zw@?6oYY(_S%$7Yxnb)ea+yc%atgtKe<=dI* zWqk=eK!mje+~=Ai&Kc%CNkJ_^yurT#d^l=@j#oGM)u`-xYz`5O^G@6iHVG8H1<2%X zFr^oY5*M^~gNabzZtzyZ4tlb+8@zFj=*e<7IAOgaQO+`(_b+x$BHO{LhSqj42n*T{ zepay}+rckF4R9L&GC|`^?4PJdi0$Bi!84m;8gCCKVj3T>6tQ-BpPj?cEP~t>6&}!# z7Uh$$x)a|e7yH3=U$z!NHltb7&rT4~#+okn8&Mc%s6Pt;&QMPj%1QgV8qvSAYIBL3 zid|u2uAHI@O1)ztj^i)cbOi$G(Ww3wLEebRFNGl2zDr9;}HCU<~ zq^V>~Pf-Axpi&WMDbXlnKp7Qkg2i4rn9MJI*C47h9?CzQu!+j#K{mu=&VaM@S&t3 zfsbur4oyIeTp0P;E`=8*PR`5Jm$t5m`@(y>=2!}YMadHVKi*O;ef_BQ`Ql=K-t7G6 zAxq?j>oWLH(|nf@J74_yMzH!y{Q0g8{P|k^8IulwMv6Zr;*UrCIV}D>D*jx|fIr`e zKhKH_%&G8aZvKme@iM`5`b|rb<5J|d6ge$LE=!TaQY^i6Za#$Nu192;6ktvml&r_S!bbo1#RFKXd8^xU!et3-pY7k>tb zdiV2N;B)b-M|b#hyZG})ANcbx@#o52@CUz#-8371;Wy!GiT73UP2m0F!AN|L@=5Vn z6~2O1RlL-IkAjRX5ua4V&a^epYO(EwA;yb8ZvZOqw&<*;>h#%? z_5jBv1Cu@XBmlsy7I%1WBA$28FzZE&A^_jZ<8F_>gYVBUyBh!TtMO(LPp=AHtj&9I zF ziq!Vcz0Dw%EE4gR+Q-t)W*@CpQO%0`dzgmCMks}ZeI`Uq0019zCMA&{HRjjjJ$jn4 z#w0~#nQ2@YGZp&HR6U}F;1u`Xyx!H7t*mRoBlyN%=5T`u57OJB4APtTc({2}$EtZz z>ryW^G1gGc(Cv%6d6`fyoww;bK8{bl-MqmY*~%9?Frr0SZ*zP|&)@wwd45xVu)ldT zzxBcC31t(i)TroqhgnC{kIdt#8_kK1Bj6F4E9>U+s^jWb;Z@E!B6+o+Cq(n(7yqcv zuNEwb;TLwe*ShW4@$K5?weOfWcKn11?eiv%&FFMX$M$18weOJLW@5)S z9maMXo6)gjI($}`c4}3%y4u^kZ(p;m@itXRxNh}d1%!6(f63-NeYSd>ei}ONk@>B7 z_PlwO`BVMO9{i|2EtVhdXAU;1%=dS7m{38Kh<`MY6`L;>Lz&3t)47>&t6X@B_!}3sVy2BVCK53sR5s%mAJ94{hLD~=VZQYy)yo6T<%UTM zLKkhy53v?$+I(KZ=E3*o2b(jE^+6=7ANNp_1b8j4RTpD_5M9oUS$4Ygq2>VNWDwn< zBgju=ca1lLusIKDE%f8_cv6t zdw2m`J25h`5{x2K#;?zx3@l3{aYz}r9>(sHKdRL*C>IgAQ?-8l#0Yb6bwMp()vB@p ze!+ivPS>0c$zWT1@5r%fI=iTK$i7iSFp>J71fsEoPi5MYxgVAPto-o?XGU`*D z=vsAEach8~#iRI%s7bAOKcizHk9ftSlAQ0fTOjgUJ!=w5P#e2h z_I$j|!8d;}{gjbK2xL!JtgLb4F3F14+s}$0US`(e=SJ;J<`;)W*G^J}Ej>tGc=1@% zG-gnNCEphHV^al0YF3du&Rn4x%P7s7A3Xi^#S3IYWU<2F9Hgwx+?I}QV3$k(sMN&R zuCPV?a0B@0&6Wjn*%ve&cxVAG`yAjBe064Qb7Dbj#t0&D?~;lWSmA7g!Bh7e`>Xg}ke!rTuyuaqWY_fUK&g0StW=Qe~Of~FaVIT2?xY3-dBoGRwST%%*B!lg)IZPa88SCS4dNeU91JSWLmfFgg?v8M;_n0Ft}# z1dPEcv6#G-l{jKV0r3t@2niSGnr)1SXd#~jY*QkEW1A9y)u!JRnfKcni@Iym_?dZ- z_W*ajo!ZZhyeiS9zL&)F^HDI&ek8kKp^fo1Svg6DZRPa%&4xyXbtIh{rLG} zvz5`0vP4(G7&DiGMMK64LRi)|6pPd@y#LqkhP<-Zti_MtQ90Jm1=l!1^6sP@aRmEe zq1l_a`JqiTzqrsGYOJ6HxQ{~2K1YG=Bw4>xjAQa%ZiT{o6~gtgo~F9S(LkwVGuz5|V{SaNp(q3brP0mtr$OZRM3F5UZ6 z4%kO}6jh4R`SlB9jk(3F zbp=jJJnyUs+-ur7$zT*kgX`G^L zFmQ{{6dGqKSOjkPT(q_wmR-U0Debza8D9p{JAjbye>Nvoh^f2b{i(6`qNwqVK#gA` z8pGOMUxEMcC>QQUPz_kP>$B0SNn+)$&oud&Z1e7#)Df&soIitmcbZ?=eI)%cXBYnH zF7u4h#Z97tT4{GAU|%%Y@Rz#ONPg_8oM_%-Q_cY6F2bEGutNyVzte3ku-89m9x`%i zL0n*q$F1~{Zh86)zC*UxoMy}qO*My7S2%@AMUUuTnNJUI8i4}^8bb6 zkpDY&{yAq#1{l>nq_LIxs(54-Qi9NE3_$yzt2A0s8WaR*S`m1h`*!0FN`-=sS8kD} zd*tKX#-JcHnzEPVqz?t_!y&SS(EcFv4mlmh#q)1ldSlm}Y7)(lJ!VEb`hu&Ze>yV7 zpye>rptp6)BVyUT$HnlNEoKcq^^0jS)uDuyc~~ek5)4*M&u^U!PG^tr?QQ0T%tHkP zkvf{O)K(F(G{CU2nu0NGEak5rfv^!wk6~kH2>LS>kc_a=L#*h_-*4adM!t#&0USGE z6=N}#Rc)|)ntt5FJ%inu#&Z;dNyVoG1jo4uIb}NPk*9HBHO|jEmP`X(dFyz8=fXMwA!S z_DzBU>S}!l(BZ|pCWNdj^cchJ%1?K7)J#@YvaDn?@#=3qHQ|tjIaP1qIP6~;j-2CWGn zgNx*8eZ6T$1;t@MJjlH-o3reNghfdsS_j)~3gDE^e8v2?@h{2}BAZyqGyd?a=6vH6 zMFlXmaxyli=otrIGe6e8;j3RavyJa41FVYihFN6%NWthB-+6iFB~Md(fw)uVC?mR< z_%*24Py3F)bPAGUfxH{?DM!wv8?`AtTIf6e=xOs-J3V|nHkGIRJT%Qnqx6Em4!U5P z#U>!YNv(r+7l@PAuue5mi$E^*UsHSQ<7LOw^Sqc+XyJ_7Y+nAh*+u$dNwLirwV47Za}qiT5GfbKCIB7M2Eja|_!6I; z5L=aF{Y$E*0Hlu@jsOB_^w&cUcP@1XG6Z^T}bb} z{6Cbh|DIVIqWtkSRa1@k{)h6;_aO&j(;q#jO{1Rejc;gq;W>6fwBMo+%se|7b5?^z zb67X-ET^bA{Gqv2Gpd&mcSnDyQX>7K3dMjw9Mqea;O7X9G>SPf&E2sqT2IrPmXO%g zp#;A}s6%Wz6SJ_p-mnBeK4>(gMKjOCBs>emr7ui1awrCaU0=#@c!}S^&X;@I3Wnk< zgLa1fZ(T4z2mR6AZ2F_S*&t}Hg8!Ny8#XYS+xwZ>-dIQ#LUY>)(-*nN+KXall$GF^ zC%T@&d(l+q6d;+aPG;z2Cxu!UonFENsA^DRs9u5*HHh zLmS%&vHa8(?pgNoXy_f%&{|&ECG&{Ul`=vDcUmajxD&-_?qYaydS10V9RnB2m&}d9 z6ptpkXCZOq+=YI>(`tI#=~)YLkkx@bTENC0EntIS4ffwYH^H!jF(`@k?jkB4gPNUC z1hsnW-0Al6Xn~A{epky&gm0Gb{L%Dk#zT~$u!LiesA}TSX{sJ>6aayG-mK&}H7I1w?bgZKf@Mm>cZ$0Yh6| zYhrBG=4miEoQA^9HZrHMsAv^9W?XkFE2w<@Xs=Ae_Jb*sIHq|Q^hS}8PrX-Jfa9dC zu7LO^ZJ3bndaoGp8Z%0Ye$n|};un4H_4@@*zB)iDn0y&+X|c>n^ZMzn@0GgLg%U~^ zE9*X&lA}Vi0u;)q*i^}#pc(g5O0X>)i-ZiAv4nz4>bRQNA(?L$W$6!qZty8kV+W{qWGaldfsImr$WN$iM`@#W$7~o-7Z9VTu%P@Ka_8|CW4j4x-;xNuxH+D zHTf*ry6gd4bE9$uc3Yk@(YAtnoYY;_B`XjUfW>TONvj;25|lik~T( zeup-Jm(+CQ_c-GCj&6%$48T}@5EO#U986S7+BHoBWqe;;`o!z|m`AAmoX|SGN`t$2 zvzqQ9T8UuaQ}--_&mnnp9Blx3>9KL?(ZT?b$bXUdPjI`9?SB0>Eh0Jmtpsc-RXX9u zvv!!n-?H~oW&YaB^Xl+t65T6}M~MiT3_l?+FHMmaJ>4B6g{Lk9%>9HRR zWj_^vJ_GVYP42lfUg>YG{N7q5B4rZ4SjXL>CS_)sH2(l^ljNR~u!)$$k6MI2sU4`e zl;rNMIe`YS9Xij5_w!>aK~y3rl&Yw1YyEi9H1E=vm>J)ACc;A#5yeoe(20? zdH>n&+seAFXZ;jR{KDOy@qf`%cGU7z;@S1x&u3+X;O@O~?j`#!!N%ZmcXNKKmM2o4 zmOb9UU0Y*=l^|X+$DNftNC4>03{{2f%uHO2J2PxDVUS+glckLp_PqNB{M4po6~iu9 zY{^iF&*XpMMz&903ts%HyB40ID8-AGzBxDo1VpD2~I zz5IL|cTdM|(Fn`o{Q5c8Ifl=i+boj1)7|enVwXg5ZS(Zjtm+a~QNO8mwnR?Z(9Ab4 z5oT_ypI*%K+IiqM@=<8@f^SNy@sIvY`kQpuqn7ZJ_U=|Jis&N@AKyX%XupbBA~)5v zC1~`D(hPS!*eX@!7IT=r!5OQs+&y^8^FyjR?u5#sU)`;UxT@?Ow6cSi;Jq~MG|%be z9u&Vgu-R{2!bjIA?iWH{%DUSt@thCbMf&t5Jojx+FE-OI&bsV8m5N&c)iyot(6*m= zvO~(l`>>>b9PJXMSyy5gaqM=t@PJOdO}5FzuXOG;>eklo=jXe+`+)5*c#8wKi6O#6 zK5*yhvpeMRYCR%j_|ygms_{p2%$hv8yF1q&VQ@q5WOw&x?3BH_&E?72R~1y)665{G zzaEiW@YP?rZ|27bn3LIuN`z?E=JL>N2*LRufG6OGTu*1ZpJU&XaxgqKW-eeAQAg}Sb@p&lcoqIcKVUsxix4Tn@0B=Usv-9je(SDsJ?N47`Bmy|CrmLJdi z9|oiTq#igJz1RCM26Wjed*s9#S&H{!oc>e{90>DLmaE`6aY`B^02tt{L(ZfmuR7R0 z9TMj5!S0@HZa~R+RnppiD_kl!31=uuU(Cse55Nv_4~O{o{t$OBR;nma3&P9Vgj;$| zUgw9pv)~&;ZHBo!vR&bMSuZ$jzaFn-UiD>`htleOD+L~=?9S;M7dYcR+*#Huih z7kAL#CDO#~oELvz$YKN#^Ew~!l0)vsyjo0^UKL$Oxw~oXhrj~I?~IDkFD=D{A-hDd zhgZ4l%RRZ+Ww;H(sxAY*)>7d7W9|tW<7cM0lli%n__}g7ck?ot8M=EZZp&$~>Yd{5 zBiM_Cp^bg{a(9bBKqB9s=N@MeEf#b8rX1@=bbtzH1+#d6th><80;du?rg=8|Q!31|}n>G*x?&QTO?nq5GxPAft zg}gYQI???*TS8R8mJiDBfYlB=2o~F6YoOu}2eiXR*$xYr$#$UZ zu^j>ci5&N$2-Io^u@}YOAmXtJ2ptD@P`b;M@dklfvpH;nkF6&7lyFf^a4xVW--c}h zYg>?rkxf7W*aW!~wMv>78JDe@-AFV8=8UV%bg$G{;{D30{q3N~-!C)h@d|61;MPKS zE^DU1Vo{tW=<)D2rI&}dSr+()$){QNw((^#cS)282ezwCXR6V83;6oDs+fgXuJkH7=f0ctSxa$ZGM@e*WXq~qC47F-)N~Jmx50^$ z$}i4JzhGwx7CUH)$GuX&0=AgoY0Q2gSg7E5{SvL))%)fCAVd}1AN&T)^4fwV;~P~9 ztS0sc6PM%uAiH_F@=@&YHNlYXF49yDmiuEa?hXPwu{+2JJ24+=1~hFpAzoogg3l(h^yYJIj z0b%AhG~6_ZyAJ~4G=fxiUb zlh(UG(%39J+uOJpe;qSKjm3T;{P4|nAU?u=;Vl(UmAP9x*jk0ad?@d6wQ5Wa6^5++ zqLsiX?!l@xc>ZR0W40r((5>4i#l!-QHBW=$y!`%@w2Jy$+^=ZHVMT6P;^u9@j}+;?h=gn7~-y_ph;C;G^UV|_=1_>vrPrk2XF6S}3^xBUY8Xm8lB zJ-Zb5O0|FU69?Upr{7VvJu9}?1LhDZm13CNZw#F0XK?pE_m_?>V8+7}W9qYQq!5lm zo1pUk5q9qie|YTQdSMrR!wMN5H>gt9*qu9JUIvWp;-(fmp|BVt^=B#1S6BE00p8Bq zz}M_|CmF#k&rOeQuYUs6_jnt}1hPC&S$=0{Db&QUOL(fV%hnKHFz>mOi@Be^a)q?4 z8+gGkw6yF ztd(d2?QZ_c*?hyDBD@zly6~Y`g-?9^RE-c*4Db5%RzuYw_*0 zQo2;eN;w_tRpGwRv1lc1>HN{NHa{KRw=%z2;cgtUTvVpb_s}<15LsA{WwajLUylw? z+UjAw$i76@V~Jv7)#Kd7f(U-`vOA3(P&iqcC49tF?g5OH39O98e4(lg%;7o&b}OsO z>4ZOILc7VvZnaW2b~01|8e9MOQu#&`Svw1 zU%1%AG529+tOD}pg1oIvapJ24(F*Fz zbCj$%m`l7V~(36?r_rm~I;y4rQJ|QWWE~#FPeNQ^pku zb@91bcZV4b+2%kB6b0pdqA=4J+At*3mkexVrjL*cSE{c&R>@4CAd#8Am&7mlFRy*e zj5f(&V0)&ok^o3ourhtH1Ja+*JW|}9=l1Xp;lID)zJ?g*H&*fK z{|7r6gwhJyYA55XRdOfeYf@OPy1oE2`p1MHSK+Eldx;mm;U4xEw&QN+t>2s;se^jB z@j=wX9-kb&I=~>WD&?$9W98HC2+fEWgg!&z)TZE{#cf#~1?Fgo_|^QyGwv~r(4(Zf zN|JTFo=Sq~xHP{;#o;&Iy&YOt{_|Vz&?FuY|S$E#~th=e591~3` z)9O{?%<#<8hpmSF8c!x0LCX3quMOd;@4~!6ZG}!)jnX4!^>Q3Zw-}x5ujn>H7 z(@P*r+-;8+IO`nwAFJh3iZaKgQ~)56?-)6tu0fzy<0gF$bLu;Za9mFkI=PfO@wvNo zh|(8N7uRPau3P%4FWh&BDBbo;cPBRex~2d7B`o-yJS&#aLdhob~5=G59#qyb-ABd65R zfSA}hvPMp+kElXcbjJDbIm;zJR%n@a_>l1Y+U^uO@WlBq;VC*tGhX}$411t}$U4wE zpqEfU$z|xy1Q0ZDtFhMR-C2R`5;?!(9%*NRp*iJyXy?YHH2N43C4CIrnL@FhJ6*RN zwlgiK+IgF>n3e1BHTG{my1Q#^6k)3xd)Qjp*uw}G8~f1J#v}B(YkB`h&IW8A!Qu>g z_F6JnmaLUC{g-&oukH+e=31Hb0M^(Blr^?N03ea~{LQ`EAW#~H_Yl!&MM5X7xc_(e zI7Xp=5hlYKY>_Yl^u<0r9DD_8 zDAs^K5OOrjC2E$d(k!|a#q@8aUD%hTlvYp9V|#p$N|s zek3}wN{I3}UHK%Sy!JBxEzZ-Q5pk$zlA2^B%XTJuVp2xyEbIkmAtyDD)0=^tSnh}q z{E~@-U}r5J=`5c3q*^>Ctp_kJ9+Sl{Ts$VP$HgNfi$}pSwNlgk0pMxdpP$w}0ddx> z*T=Z`VtHP<_hRe3a&Mp(=apMF7Q7q4AOGP{0U?J&1x_qc;a!i#@(mG?Bp$Zq*|j`3 z@^*yp;2IvOtWw{8_y}6>1#yr8&qFxGygquBIE`8yEvg0BulV`1b^7p>C2d-;;X*a6 z=|Ems*K?bEjCF{DieI9$mrlCzH8Gq-{yr-d&&4;+vwvex--^~rp5Ypsue9Zv*`9uN z^XCaj8ffkNjusV8&XF!%FVB(QPdI=Tvcx_{NAN{_m~-T=yc=mFp&$nZBl&T6K{O*8 z@bY?|@geQ;7hdKBafR{(>3>o@m2~~!dU=BM;Ce`?ixZ^B%0@6gqCrV5@!Ur&Fa8%C zK&;%LB$of#z_V6+i?3}$6VLlBdV_LiaD=SR zf6bl?^hz7#F-ai>jsrSg0ArrndP{%)Ky%M!tuN3P;N$$KPaHoU|y>#re!cQ!(+0iNLdkWYUJ+?bkGV?4oslGfbL^G00SKpUvAwm zyjZ^6x=;M0;D}Q!;LY=@-ki%9b@D8vL8Kz?7EhAK^fKl0U`6Y^=$}eQAE&?a z(ki&xh_Zy7K`bs%8osO=LRx;cGApIorK{&SYeLFp{=+j+Z%`)Fnf1zKIunn5-b$z- z3d4rEc$Tqc=sAqZrCIwCer)D5G3-3Qa0XrPBfQL`So**>Ey<`Eqk0I32vA@DWrKWUW>qV1vp7*g=8?Au>G5U!d_Pai zWN>PGfcQ;uSuYQa;y6@JRnGPdxv^*^x?D8>Zfu=M;{nBRy_~)b$nm_w4k@rT@i{0U z7{aV`pth2DV(}y?biS51%Qztb7;LIRZ-l2q%JyYMRD5)gr;o-yBE--(a+6+rkCzPe zB(e7h@=_n~YW*iJ7pT7w#F}3{6SN=rn!z4xA`y=ZJ>tGvMCvHiFDso4_^UrJ& z;dWP)l(sLRb}!PF7c*VdZWo@z+Ot>e@t|p9oec zE`=)?$zwco^bH&Nv;TqREe{mBE}YPEB9z{8iHi>w4?N&~SDXA0CbEH;-zam9U|-BNe!LNLjqGE>1?)LkH#W&mQDu|gHM!^%dd#LUO;>A^twZR* z8dHvxHJA#nTDZ(K4fGHxM_a9+n*;(9xo3(e-v&je_dmD8dJqNCYQpnv1)%#S^5^nB zeQeP3V(=RAybQaCaJY2QlVu~r!XHlcY_LJmItmoZ3-P_tG8cdj_zr0bV>MSSX$6wnYQBgM2Q(I?Sh$701_$KK^oM43) z>5pxa8R{np!tX|h!`0!~Cc7IQ04u;*M0S91K{q;UxzRfWfo}9xIM$y8xDl{MH=?Z3 zjl{V`9qNUCWUH45w*-LUHl-qAo@a^1qBbjkMo+@C$yEu|??igkW1po^g(MbPU*-dO=pD35 zA!3n5O$<`8>RZoC8q1@ah~BX1qGv3dLZDc!yv_LTQy}?h<_baC@-j^6C}Y1uIAg={ z!+I%f)Mj~f3SJM3izV8@2#7B-t>0wx@row*ddhXSp9od%y>GL0?|lRd?p>d+-0B&{ zd${58l-wviLp#Y+?}M260wMD|`*X4#f=Bw(o9)hi6k1X^`%%IL+c{-=N?ZMl&HU2E zlKSi`f<=%2EFAyuH)G(`w(#^Fo-Vp%Uz7K^w{@iWPx|*I-F0J&{KQ|CEy{gyjuOMq z?1Gd}=p;w2E&h;PGI3#B?I^#r9A-dNan+T;hS-&CHWXcn0IaU`RjH?ogLNgk$OM)O zWp!k>)K*lyXI61&wMW<3T>(Yw<*TCBSJh}yNMEe3QG<6|>zU7nlA_=M-QdvBa|wJ$ zn`NnLhSD%dIu5`39%vi*uBQ%R6K_;RtoIybE<3~9%IeNy&=&Z8^mzn_{)FeX*KLt8 za|6Np+z9s4uF)Xdx7b~2#TMyGD+nj)N?$f@rdNO#@Xix^l3=mXpSYHc=VhZq70#8z zObSF`{G=jOqt63{#5ioLs2GO>0EzsoO`gd%C@{&=;4_)KJU#set-HnZI{TBTtGei~ zmPvmlSYH=?LQmK#OaL)I0#wG%0g=f5V7}Z-f5f~1e z$YwavL;-+A?%3s-V}oK7{bX;VUb{V8*dC&(zlj{>TjeQc20wi35snj}1$$uSL7_Nw z9-2Ebf*%|_t1Ww)6hMAEc7MrY2oSlfe9+U(#s&3zfXD5%T*$xc_@-QW6(8;0NIwC~ za8w)%zYE1X@k4p=48R3wLQBbXc)gyH1*}-8TRT5=;Z1e+ z9~;aP3ggaCw)llRKiN>3JLfiv9Vl{Qcx(_dZt~dRfdigWnqA|NUF!-DpLjlElkHWv zGHl}&)SqG7^p|!s`td^#U#iKAdq%=Z(c>ip**qnJgU#iQ?3y72=NIuYhdpQ63Q_XAJv> zP@-aAg5$skj@WMm;b)leQ3M$D-(BpW7*$ZXi# zLi~ble8gKNZIg=xn5N6~RBKw zi|m2|TRE|>1cc_qY$fpxT)7z7ZMdOWG5 z`cjXtDUeJ(p4=`|kA#+_9zV2`Td7AVgQ>@WGFj|mIC4xqQgRqKI0a2tiD6$9%~Q;j7Q`3YCFQ1weAi~%)plub3gIq#4Djy<**yQgTFD_lgy|n zoL>5Kk6H)*%zxnZmrj8)+lQ0c(=YSVJMacfD4CdVq%uR<#Zr;jMXq=j$UdMK!N1~d zRsNm_PPY{j{m?=2DC6`U(nF^cEPCj&9nwRW69jtbeX?4?sf!If?+Z@`SP~udUMMdd z6a?T*mI@FK$^roLKEDkbko0?!Xo3~Mq#tFIdfv0t#sOOjQ+BWKkeQfMgb8}atKnMd z9e*nc&q!9SWaU5?*Lq)~bFFlnt)|*IFX|pT>^*2L= zpyku=m^#f?O4)yGxwQXyQX1`_8?F{J%ER+*K*a+wLET88Q+7CEV;l?q!)Rq?07 z$_P}X!r)3{k4vzG37{U$_5~BBUG@yL5&HEZo!rWj++Xg`gvIcdS3FU%L_=RX>^Hju z@rzSCMpXQH#RFHN-y!0$8H$sJF*xOiDU7!W(zo6wDKY(0xmL z!KBzN@W@cPE0uK#WZN+u+uIdekq{GXapg_bhK7PmTmu@Wfd!$H)QKTg!f0i)sMuTB z_B-q?P$(pc8}jT2OFFaZL^a%7pk%-;k-z*0T=k$(wK3tnZs8CAgr}y13b*-YdVRL$ zI)!WT$&W|G2N!Pja7hQY>pF!&?T1V5vlYfD_hz|2%3*>nTKAq|FA-)c$er9N{qrQj z`uy_={oGFJl^+wV-zz^1*Sufvw0q^dJEd2?OSmYnjMyc;GIE#QD>a>$RP~0)H&xqZ zcS_0La!UA*$_O>xB{M?J16el?!@9jvy$2K^@Orkif!{b$D3(Mxv87AqkfWs8Y~=p&X{4-l+~Bich@WK{&171(1k zl(I*&rp!o9(?Bti3$;~MSTz8U$Q#FbXWO8{s@i0sgms$$EQ>EETqc?-qkd}{^;?1! zMlG9HZI~lwxAl60u{*#oqxqV8q5Lvow>8L@)%3R4A_SFn{|5wNm284Ul>z|rDFqu8 zM)@q(nW%v3=e+O*i=kSJ5QYyaP>yJh3wCq(uN3IB!8YQ?`dC=Th@9CNn45~k-gF`i z*I4-i;9FzCU4jgLsDAAOj-_CrxY)?X?0!-J-C#)=1Fe?^azG-0$C-I|!h1=68!->z zqLO}ZO2CHs|-VbkFhnbP9$^J1#^sEq@*-6>N0qpJ3p z+9Zo(lG>zM6w+$yPM?E@-7NaZGPCudw|^`%3J9Uh&EPg zvzLPUG8?6T;p1`r)4k()mUCJ>Ki0(Cl?_(hNmet2%=|&z+tmAiY#J#b(q#}G4!7|3 zg{OWmHTNd+6i?GT*`h!i_^gbdCYNmuM8ioCKiYbo^6@~LLr9~K-y;)iAvN4X5^F<& zK~Q3il#+?H?t4^Xt(qtz6Km(iuc7>p;!$*Z>Wu3(7|`gN4| z2yh`B|DYW6;t3YVyy9LBhv=;VD|Y452^KqaOMap^gpANzv0WbI+D=!7wug)HU2DeA zXL$SQAPM8MO_GSu0RWg|cJOwxL9w4!6C!)+u@B0#L~sI*!wI;KyhruOn|bR2o}bw) zqNN&uW>__xL9n>Oy#GPD!Ym~StQq`q-(Fu|#P5*I1qP55(Z=w& zfv^ip1>kxw0AOXOC^R5D^$5{K4ZXGk=RLLf2V>m@Hfh*$n4&tiSEfi#5KibR&xWhh zt2R$bRxM>cIZ33$F2@9TZks@4ifZIuxhjBYf{QnNZ}NMhfohD4R%2WwSZoYqpKOdO z`;?1gW5n!37Y|Mq*5Yv^y&33i;){Hdz(6#{McEis05(PdKt4IiC{(4Vx)LQ&_nae9 zEQY9zGa&Kmq>X`Uh8(!!AP)E4Ll|K*WXakDr{+iQqaBtsgZ1nrQPgS%0+G$|4QU4d zhIowVDAr!{FEF-?>FAGp5WSU#?x4 zz#<+BaHE?Z3KJ=-Jml-s->+NPs=D(38gkbBJ8w7E+a&gPrHpTsX-H&%mt^U`LmO81 z)Zi)OybTyBKn9o&_A=H00|jw_2`H1r`h+6ae&_!k?;UHC;E$cebF2#dOf;8=>EE2- zy)QObv4#pA?^Lq^UpCR(h)q^-96PmK9zDrBfDwA(Zb74&bsd*TlN$*?SWWz?YGPas zkhz!OXB~8)b3fvXYBf+U)Wg-lPVoy@13Mp*S6sub)h=D9`u8*H0#c9q@wdBZBij_~XCeDj?*7tH9;s^(Ek+(%Nj{m}-;RQ7tiOoM7kK$&jM#X_J?!pcGSO=fUUzjs9eGYsL0{e~C#O04Na%<) zeutOr^n$0o7Z;QDzJiKhqOX_ExbbrwYku~&;O9>MKWpC|7*+8+{(0|0%O*e)l28%| zy{FJSgd#lzK`EjHrDzNgM0&aM4g^5~1y)39ic+P@f%GCOMTm+NQ9u+y1cKN{e>-Dx{B+h*JDB7EfR+lBalM>;?09*o7y|CR;38R1Nl98QjRHsBY= zIScdh^|NDqFOG87)!1EC9$Cty<|V=t{uHTnNPJhj8~MfsP#uXNDa8u4OKEX?#`%kqtPoyB;Y zG0y&aYSnPGTqBR`wzf(DRRvxn)0@L> zq2;Hh^B$u*7E2xaRL;<`4aW{jsrUHc`t=4iXguig!9#{L7&P?phE19_Zt!@M2945E zhc-@a^myaP8#Zp77DTVbBZw5xD8ef+L2dc&|87ek*m9<(4_+hB><(T7hv!}_pT+lm zQze|YIpRoIdg6`)&YNEUBqxd|9qj?v>5M2^gC|`t7tX)m(W4-H*@1Rt^ykH;snFHV zCQ3@54F_cAz8uzEp8+Ni*G-k=xl#JUHS*|g=PAx<|D(nRyqtTlsP2UVyf(Qp^Ag^| zz%i>u0(C$)JpFPR9@v=5bDhq!Y&Su`%DJ)m6c%kqdQT$hQ`g{eTzwM$Z=S0J<%x5Z z`XDS}!op`CsI5P`hUfK|+%=vW(yZm#13<}mvhtM2xiF|bQ1FxNHRWhdyn`6zb$?@7b0U~a=13}?f z<}+*+fkNVMn#8w}3?vR2K)fY8WX&+?id>T}mJg3MerW~m?KlfMO?$jhD|VgaAltJF zA2)IZw}^~4y||@c4A1?{9VEN8p!`DAGf9jfipI4PjE+ja?0h^L0L)-h z>2>f6;fH6ZB!Zc(Rr8*zi>u|K#-&c@8dhFl)e^TSn*AsCEPvVSXgLCgJxhZH&JS4~ zl8W`)hHN(b1lb43(ON_^g$RQh@g&hk?p)w#zpe;BezHdo_JGQl?p#uD)u@IFfMWBWQy-1zBa67&#bhhV&7ED%_-~8AwFyVrIRyX`DS6(j&dKZ;(dr=W}N0GuPovJYuHGfPO|i6T5GOyD&fAXkt6ZN|3r@c6deh zwgQqRO`TV$rTzvj>85pZS*`RsfN<5v}ulNyW~zNb&|} zGnT88(IOBW-?!FT)e64+Ts1T zORc}d7jJbw%?Ld5A#QH&l_Gqkn`?>aed188X86F<-`7|}LLZ$x?H%dlX)0s2yfiCm z?%0j2qe>R?v|re$9Mj&BZ);E#SpLf$n!)xwhqOd>l1A0fhTr3cSX!m$Y!VFe4}q6zI(TGNZ2CC}emyBHlB-n>K3w$Z9dDtIk}ui5Jy z$OvP*QB6Q1uxZp}!KSTjx{`hM_Cv48J|hANt2$1;BM+QJz>k7n8q6vl@V;=s+0>eh z-Dt_ag$6l(0JK3L7Hi0EDl}5U?^OwZvz9PHm9VS~3lYXV<$dQ9R+iYD?0w%^hZW!8 z7Z4pjmLL|4d$a%I{SG_RgOHdo))B|QJnSsblKvT;r#^62V}ylJyLsy5c!6TmzlMO| z+@jqX)N!$%u8riFl=(8uDs!Og5Nqnato+Oy;4?+4?BqFg^3`5;{aKP z@f$79XBx4TNF_$(nLCP?^u7P7bCIsq;{!j3AYcQ6sH~W}QCe|d)~IN0BN`D$nc`x@ zQmTfS&&Su=l)ab=?7Q{AiKPL5v{S8JVY60~i&%=lU>WqoQb5iLBS*w&xeWa(cu~uos+N z*e(U4nlgR6X(}9)9p0#B1nIRid&QE;fcdNjFyhG(ncW!Sh?0_i*aRh#n#0Yi8>J7H z0-pdMgtv5{J!uH3u}uoXw}sU|*k zapDP|G1(sgmnrjQ=1k0(F(y03OhjNA(h(R{#OIIIGVTmg;KhoqCp_|h69g=6jU7SU z`A@-5hwy>8Qc>sx($@2|A7B^6qoNqKgogTXt+UIFG51%g;+N3d?BV}5wlsuejCt-2 z=VvTO5ti&SYd2yEBC!te=xScLPT7+O-HY6E4*i!wzumW-?IS5!7)6Np+*8Xd?4!{pn5Sy`8{AKI*#myJxF;@8AY>QVRJzc~BqXRrpEPr0As`M)@OI;H`2@rrviXQdbQ8H(RSr65o>du9{ibf2aq8{Mbj zmJsgKZi~D-U=Qeyglk6&xoGQBmp@v{l@ZAIG~sE_^4~{uIy35JMWCk zeD1PeC;^6Tk)uN)KvsT_hhqX+1FE>YjFuU76#!Xli*!t(D{&L(OZeAZv4Yx(D^}yN zCdn16XE)=DRV-~Ppy1e(jrR2{)ujaXBXj@Z=!Tih?&k!IY5 z$ttcmK`yQgfru!-7v<6qTqRcD)MuAhMbp$sn6bWLJM2q-c*EE$|3>4JfFm}l08 zaPbwI4x|^lSvyS;#zn8-4j>o3O4fBXDsckLt2SBx!twS3f+afrO8V9j$aN4)5Kr3kD#PA-2j@#_$ z@dOOVJ-t(1{aFo?ibD$x!^{~M!~QX6>D=1i(tdpR6J1Lg&RC`ksKX}Z+Z)g=%b10n})(E4h)6KVwn4JmQaxF;xOo7W;xNzu;J zo4ej*UswrBCn1(HZ?q)Hn{bgzdrT<9JoWU*yYg_eT&eogP7*iQ|7IHJH zHgI_3G_$j-Zy+=hKM)Arvx}>P1=?2N;&O%-P++lC#m*6Ws=!~9RJ7hXu!2~rqTqrJ z@%5+xHm0xtZ1r{AvtByG)lg%RKIOB(#=LR37$5YgD}fawnc(VhWp5AH9KEVf9&xQs za$%e|Sg-60;p%BV85W0j2rqA~;FE_XD-a6WgRX9l&OWm$btO6ec24gYioruZYh3~c zcwCY)0A0y9!S!MwjyNw#i-$EVcd()!+5D&c3qJHa+E>^ptZX6PuJZkGdXU`6LyctK^*;O!MLL1*0gV z9&=?feY@2a7mCHrb70waU@Hm@3^G_L8#Fg*qh%?yvaBUl^lHPhT<2LWJ0USpD6e`S zb7L_J@vO&PRajdqwG6E_|LSp9Z+>^ED;&-S2<68p z+GS*gZN8nS{W7_&@8T1#L8QuZ3{e7$L4XP6<$y;{j}@x zKwtxXN3gMPV1d(jknG&4Eo7pII@aJb&c4DqC<+9^`Pv3ZJ15-Yy-G z78k%X*>5&TkbLn7S1$`)n*q($*eq#4Z99ked%Kbr*)%Y99vpq>r)BNZVdR0W@s3=VC%770WU;lRCLj^tY)NbEkmr-kQ6^9A9vS9KoaB03V;>VS(Reu2 zJYpLB2+4*1w;nG!twv|Zl^qcOKOa_+T_xG7ll&%B8Gi&T*BIBpA<7svp>1Vea&(~* z`o$gc+|m(gPs&oYoR(D4a?WwOUSZMiDR0I4*4qUQQdyD;Mas~l-{Zf#TrDl&LUm+> zZ{B-L*Jfs-X0gY$kToNzf(OwHXx+?>U;k25^f`y@tzzn%^*}@yi|#2zCW=cEX3k7gs*{S>xtx-}W5NkB>efXlQgF|b`i@)SbW{nBF zUsHPhogvzW^qu~}W!lTGRMLIdlnqwOPR`z)QkSI=y3l-9<@bh7uF3k4RIK7j9lEjz zNQBj@Dq?N21@HO8lq!7nJXaaMuVb-D3mxIYfgEe^lqacbFL145BLf(~0EXb0kIVxO zI`_WbFs!PvQ%rbE`4%p8UDLD|xa$?@&*u1C19%d$nTx}?dhBlYqezpw~` zT+b1*QLnllW*bNXYUE<6K8){w6@~*87VCPc#ja*-zZD?^u5Vej7-BpD&^Xrq)CR3T zw^NR_DY#9qro@J+*Iuu?a@lo42W82B-BpL(A*tBzT<2q#xE{1XW8eAn5^%LbyOe8U zQAOvhUk8iy|9WB45Dc5#<$>EL$yMBMJSTE zw4@|h%WT5L`L}o)x>B{p+#Qi_7hCL(s1O3h4CdA2=|@Y(_}*CII_uDT>{6R0{syld zU%swt>o^(&ERg3IEDiXt7#=EQ!mSd+#4p?`F>DuZm59$5?FDX?z(BrP^`V;-PkFUp z<(eOK`x;q*ky>S)hANQP`%nz=1eZbsAb5MuOxc(HCTF|o1{=ee> zD4VOOtLT1g5T4m{_`G$lJoXkr5V2%^#V#3-U$Tq554MLuVd(lj8&u^DFs%QaKq0M9 zcFEHs-;fMMhYSqc|41`L&^xI@SUYW(jCmJG&~ibQzKrb#vzh^5q+MjUq+Nz&AZ^IN zu>F)qBdW0KG}j+h7a$_44jeG}9aKNNNbvh5kTW3oO|WF}d)%&|!Eb>qgWnGcY2aU8 zw&{q}#5p3JuB%N{+K|C-4hww!_{eRpuh=7`AlL$J-2QX~Z?Vl)pXdHCwm84L{b|N~ zeCBGyo*02%;J%j{!XgU2HaX<2YG+h;Mq&)i-8> zy)=&iqG;JDXVJ1H1VHwsjKyw+*j=uUyy!01AhwibVWWxj1VzEzXk()g>$|hd)yTot z6Kqr(KAih5Nfpg@qyQ`Efj9DjC#O8X8|-(Dx1eJ?zVY)Zsq6zQx_NGT{chg;^pxrr z9MrSgCHDnya}Wl_UlM$!=Ch&H{GC*@1AK>z9dj|+s`Tcy9qaiwhg<_KtW|065_Y1r zI!Joy{FE|0?l8nCsD^BA5w%CUMa&*m^OU?L_JnYY#68q4qJs##_(Rud3uECGi2;Db zrsjf5Ya$5_?plZhY~d&Dk}E35j=0)stUm!nufeI*!+Yf1`C*caq0D6y^by)Kyy9^f zbv#Qlao}_E)nVe%k>GV;D(DF2QTju><*+$tj||)cD-1qSR%!}mNflG5HYZ#Q*b>4S z&6n`qlv?a9k}AxnE#cEo!VD?^I{zeubG8RU=j1^=nnK&^pm}tH%7pW+7N59Qu#k)$fqkH`xhSMgXkJBbfAGBnKv!g&75zeNC zQ+{Vj6@It*JnYkP6M4|aQ@#Wn&m^hncWxg0m8(-AG>)?u+n{y#UOCRD#BGje#@7SZp`f?G zz)breATYCRUlD$(UH?jK1wp_%5068H*7&-8{)!KQnK+)+X>?Wn)qS$|ze-49?LP!e zFl=&|MP{oPfZ ziOhmo29Ef09hu4OagvJth?u!M02a@OSdh@&@p#CyR-_EEU-rKcS)nXs^%6H7Pq#tq z&Gw6W@L04yXgn+0qI-!e|X07pt0MMr)c`1!&Jjv?eY%3h#N@S}=DsWN9oykS{L|mnWn|xVP(r3C~yp zqM8%lBhvjPd&bJ7Rl^0{aknm<^=Jw~)9i9Z;bS%+1wz&jVC)0N4>@$#-!pwI+TA&h z&czF~JO?6K1u>{tE~LU3)GOi_#-Lu|6=U4h;(~>sV1iN0CY+K139rzS}pga=sFK?T*h+8~@NN_+NjG!q67TEglEg<;$Ks{4*z1Bf_CZg6sc_sp` zuX-Sy_pj`JfETOm-WZk%<>k4}r`BQ*l9Jzk%xyk;mvK<``m5~c9tIqg=N=xpk;wSP zD((sY;_yR(UiypclpI|^#LPoInlbp{chWqsJ0oVKNT4?Ccu;OMZ+}ppfT&yD{WUWP zn(%Er{BUx4?|)O(ERyLi!cH83NEgbS1?QZ^ja9xvwcMH(wg$NKbsMLquysTZrN~vG z6uAu*SACc#o>?@c&h}+MB#nU3UZaCJ_xa`=Lmn znq6)db&082c+)I$>7+toS_7VvJ-sM*oi16JC#3ij?{zO!oR_HQ4%cLZ@_(oFvqTb$ z(l_o-0S``_8on^ieKE{&2=soky0bL@GtC{t3c2*VJb`zmdDEUL74yp0lWYP~Hp{q@BqI(sH4uQxo?~K^y8f|F@P% zG}P@E#uZ!&_Ek)#i!bfx$!1eYQNdQ`V$DRA>hF#Ik0f}Ay`YG5WGPN!#06oQJ^K*P z+B6jwk>fHqu{Q|X@>cHN`qD$VVgrxmrniAEB=?}Z3)^W2@>zlK4zN$HK;|=&Cn)4l zcHIipTmKIHSG*wkyEVhahFo0PDe}JZefLTC(*jMbxfDp5TBPj&mPCNCC<*UN+R4@o zlQ!fc?G_|g(AE-oR7ZEW0@CF=!1(+j0)wP`nxvnwX4K^Q-lytl@AICuVc}s}Qf5Uq zia;Rwo)+@>uIBRu2FXu1$-iRFsL5T4QGz@Q{uaqZ%F`{BFLZWyV0#G+Qr>A&K5or0 zbpp94dEcra`4F-4P`eHDOc%m|dZ)u;o7nGO-=2S~uaDA+JosuB%^zQCT`m=}R z64$KK6~g(l?(XVQ0#B}P6*~;S=74u}pISFzwn(O}%sAyPzKR)cxJspjfT!a>93zdj zBSsJ~93$=N;XcL^NvgkTN>s?^nGS*s1AlQUBh8KoH-?2rB#Ts>LySEnR}wls=&q)* zZUj0i-jktsIxNG-ok)hewnsdBQj**qHu$g^?-@$q(*JS~(H}n?qWRA~EJJw34&w<8 z{jtMxEde-U_>OYSOZ3!^APEOJ-p_OLvU^U%T*dJKS9e^zqLSr^6t^GDJuI&KjpZ+l z_S9emlc!yASK%pr-AQbX6){5x9C6Qu9lSl;6$BCwbWp;gt4~mNGMBJOS#TiiOX=@! z1h?%Fis{$gmAG29{0h`1ju>7fAkc~q*3XAh@b`yhQ~~@{o-R~Un8!*!J1noFx3OKT z>mTr&*P&SrgWC}bTvjmC{=+v7b2pC(=*x?LfV}i#hwVp3_f2ja9v#S;r)Rm#S;}iu zlqn)rR9=?5t={3VT>5AWe_`o^Po3m>pS2`%qT4q8K)P*Hk|Erdx5;;J&>#9h-k8&e zWa6ayT- z&WAD_4y_ligO&YIM#9SyDp-TFN=>ZgX#b(vJU&3Pg~zqMACt@v{ceYmaA1NFYRUwy z2_-~p(h_2uNfKn6>8m~34Tt=mC32uW@jTmPk}B+}JPw`_uYhR)6sR_HUQOrJSLGL+BUHhty}$wi;Jbw6|7wfW3-(`T*| zD#~YKKQetL{v+kj*rmpN6rxM5_>t9LfC2goWq|$yr2~H{7fu+XyO7eFUF-(q?V* zzCuzA>124iZYCk9N->Y5Vku^RgqJ}w8+a9dYZKgC^+phIJYHu5Z_nNh0x7P63_o)GvWAzAYtjWnoWb2*#qkwKC1M63(BO&V7!$>e?&I= z?Fj`K2UO=Jmn0PDa|f^rjuA)9ZSc7SMl=t>zQbSb({qNH0+Z!29%oG%l^u0$>Z2B%W^EX42nor@u86{R4sYari;$ zV*><6!48WW1&1HDgm`{xk$W(sspw@xUv+1)?}=Q(%VG(b8h-F9i`}nSD2VZcUK^}0 zw$PZ~!;`Ps*QU~Ud8;3lLy4LM4sBiaXb6w0 zf7EYl97a?;Dm|(qp&&+|kn^_grU7i3Dih z?r*tUu(wI7uy2?Et}m0&QbpF5glHIO8dL)bFYAK4}V{w9Y-1 z#T~QxX!J4ZqtPS-t8&R(O{(d&AXhXMb!e`bp4T`Q!ZRBk^S5=-R8%en<9OhR5e{<+ z7dVQ>Ba(1D0L!xCvfgfl4V1n;9<>8_ysVeP%gcIeZgf{;kJ)hezL`Ckc1$`F!Qt3W z*b?G-!Y0r65B?=VRCFP+H4M`(0!n;y_4!W#B_XKN@hL%onsjAh+CuRs8;Kc zykqq3V^Y+GpgU7kTok8q9=~{p%ti5hMNo!5a8W!sidYm+@E!5F7d!O7j;TfQ*r4G2 z_)b_WCZR3Az!0+auNB9|9tW9ltvF8n!nNYKi<0q-bk+NOl@1(d?91!9`{|ADg>-0#5o~@(z%+WSwA17 zZ`NAzQ6cg8Al$QC9XBs0`gXtjL-r8ClhNMeGA7=g@Bg46CO+H_^pq6{W8%}SKxUNH zZG}wvsZl0--3r-TUvyjsuh&{LBnfR1-+vg|@Es&mglGj8#>G+6XV@nsA4~GFN%f*N z!=(DLqWQr>V==V7nVo|YX*ek3AhZ!S37PC#g`O#G8CUL1W4!o zPr2(SKuxhm;%gFTfk=ER|0nCJ>=#ld(S^wym}=OG-yvWat=CVxZ?dox%Juxni3-__ z))QniT3_0Zh|&63k%}#4jpH&}|IS%A+=N%3K;u9)<%Aprq>v1p>vVmrC*VeDGp;yjPIMnGTg-&2)Sw{T+7t z?}nm(FpxeDg(-a;3WG^-C`?U)Lt&C&4ux?!<2xk+UCy|rl4YO1Y~KJ*J}Ovjq9**@`#;RpHRGpNM7JO!4@-O zf^o)^9F((7QKpPkQ8>1*1NBnOLTkcb|7ym3A}LnuxhG|{o=Y-t{@DgrGvFzK{Ct=i zzC$vxZmf~z3!EBm=Xtl?4GU`aTPJ1Bev9Dal=Gyd`w2-$x*vz4dp-zVGi>n|PyNZ= zTL0;!T+jH$PV>i5w)jt;oQ6O>#wjOAi}j33i}eh2g!PQ-2xkhm1am=yrsAv(7c^?* zS!+ui0V@~?W+mdNcL_lySD{a= zUgiKWxO=cvS)PH7-KP%8Q0~*|6X`x(NG^8c4}21$aqj(z#dX?#B3-8~A)s6*=M&R)M$l{#i^vW| zfBYx@MnJd?ESlv-c*-$KAH4?3g#BY#y{;-DAo?-A$ER}a+mmEqN7g+Q zr?Mv-V<$Q)6j7%nDn_K(lL1xi$*8>O#h@_s;u3^3 zdNE0$!P7Sg9C`-^PuG%EZ2Sb644wucU~9SChM>K{KTq;hV>ama?1T+ae*=mv+?zt$ z9Laohij+VGProCyQ1)aIJiSFyh3xuwpYpwH-18U(w{a*fgG!VGx@rVipN_CbRP{_{ zWk0hyY20VBMT{dE=%uc9Rrkg?orS@(sSgEitV=^EX;z2BOsw zz@2p9gw~~;aGYXGi03zIc+we7#eEMk$Wy$$RxoJv{ZZ3XSYu;|bXf65nPnP9GN4RX z^%p*q6=Dv_!1BzxUwIbE@)QgkpZiQ!x912E+k|k_XXb=(3xUCb2s{TBT5-EULuDt_ zFPIccM&_gt{wbIgCTgdoSxyt`SPZD5p{ZZ8nneeSI5DK<@J|f2-zAIx+FAU1KNf{f zSu8JDU`?kiu%?5B&=;tM&=+h8@%&nS&r^)1Vr6kQ@FcUkr<5;?$`VJw=$JL3p{Gh9 z3GA?1+enlSP6FDG+qbmx79!}ABTyUEC;5YoJ#VqWgf6;d)+t%dvPg!gX0V&EpJVbV z=)MMO71>mhiw2#@FSYgr*>yHUDO!tl*4M`J^kz`SfJ@#|XSr}f2DM7LLP9*h+sxCC z(bPfBJrA&T1TTGtyGOkGpXjqd85A9r@u(2i+?XV$b^e39)lSG*ek_CzL@YlVGR3mP z1w~&@?J?$aUZfVpeB`ximCCMn`~gaeiY#1>{YkJ;Nxy|qQsK|h8y#Zi95s1RXYD7{ zQe3_wK#C;~wBC?qzzg8cgOZiF=Bd{DpIe+xK5rJ0DpHBe4SacRJqsOS8IaD0zxjB1 zmPzo0)OxqiL-g+brP$C4OzG&U60IiPm1INTiEruXsm?kPf@)}#OHy%Y1YmM#6abGy zBaaPU>%@n3_SCmfN8gwq2-u;Er%nVR3tjVYc*TB67a0G)Wd%21LG8p}>FU{IA#Ur; z%rdqo=onmFy8G#He!ZLLOSXq(p=5_if+%vNfGF5_gK(m!6vnHZffRSD|S9Qd!*>tpT2K>=A+|)(13r zckEG5H@(+sd2d!yboDN5v>j-q6$sC2%(4SL=Lf=F`@v=5xNE;7;07!e5CpkYQ0KIL zsX*Y#rGoAFi`N|FNlAbbT9*n^M1pA*Tq;m!gZ7Xts9(_H<&9wITyRA#{Ff&@6W9#`i~Z%b)3U$3Mlx_%dNLxVk6!4EoP!iO zqol@0)o}(J)xgMK6i*xFX$W`qx`uk{YxjiS%}XI`On;B#SIqL|e&ZgrLx9p(o8wp*^ee z&ycgmcsg2;QOW+*3BAc#dDfyCA&1Kojn0M`t+YQYmnWcg!R3j>WKm|#*5MaO1~yD$MM7VFR#xP-Bo`~f+o1~bE@)g_ELKpH-#9C4@*9K#26K*^q)(6x zBz-g#>9aveo7ETiK=o~<-##mw(mQstw?dJa#2lT<+3H1 z>k>2-$FsODQT3dqZe_$0u!4a?b}~=*dipSuC6^@{+mPc3ghD>eaan@oarB4hLE#1d zP%xFzF3Q#(=LaWF%R%8WX!XT(CfmwRP7T;Fkt%yU-^S-WwKaX(Iq4+N5qPwuaV|t9 zn|IFYB+hfvNt}d&t+`))&TQ`25*Tdm-wws)-E-FFUUD)01^)3j_xka3a#i{Sp)Gwe z6z#LB1lS}4Ic)H03H%Mde%qvf$4>uNDEfB;>7!Rt`ob&YCMlBC1@K+#@#o}de;5!G zqkU;ubK;l$g~b!w^OL^E854;G!x=GG^=+T$DXTd;d;$BqYLqR-uf61nV;u>qP?Oe< z=Pe4k9M$s+G&a<)J1@gfO|_@yf=g>ct<`)_as)}B-O?}ur@AEy?3Z13OC*bQOB1YQ zGGYms(jdofiDbzdIP0GwSK-hr+K?-8yu;}Ae?}qY70=^=6!yI0sl_(fD3m6QQ~{vZ zk})2Vi|v5cLKv&9UK`9}It5Mv>44X-NazIdrRlR)o^lEp9}4Bm(v8dU$s z#Vt0D8rk`L*;3B~aR?+Q2!0Ni56C-gE*~)Ou(=G|VBrp%@9Gvk4@?Td$N%iFNFmSu ziafawGXH?QrY8RYUQ^TT|LTI4;&rU|4nRcUS+S89PdZn_-Awoq!!r^5sTc2YoB<`m!_MlRPjqx{@FeL^(IZ zx{i9+^YT63Rp+0GZHUB!`I74G>Wd|#8;B>vDU&k8n5 zrAzU}JG-!*zUOLB+k`G66Gv%9WK@Y1%eP^*XSN!y7zN@y{t@;up50AR6D_v}?K9Sr<-bswikkR^3g=PR-Yn0j@$jv1Ry)cL^Vn7of%#@DG;x*eFhD1q4|^$kh;~=VmB{;y zjBlv@!SBB78KbxOQZz5AJpac7ar}#&p7Jru8_fGJn|_IJ4J`D*-hgga;u)nBw0S6b-#-rQ29INR>&rT4!NdGiuGAP<{XOYwn~V&eF|zv63XCHVS1o-*O7^T$Yw|G~TO z@XXc6+=rI=^vW||ia`_7is0isG4-@0q{R<GQ+eT?o)`4F_aRnYvVDP+ds*mm zo3AUpP*CnVyFKsf@7#xcT|fDPa!2rqdpz~DG$Csp5EHGGvA%R;M!ZKM!9h6q-a6tbsaaTnO)|;{$YN19)&^htF=(artglFIyV$g35@~xI%W@E0-^GtT zaSoPCM24;>gW$9dz!AO^%Uz#%ribv7a-Vumv6)tqrk6}tsl-bj`^*#OU|i)%>s6@J zp)il%7*>@htq)`T%ikP{Jol_8iqE|{yqv!LE1o`PVoUZ0LAzAS7_2WPn%37tLs`aX z%_m*;bRqigAWOyh%CnxX7S1+xn}8O%`KWJ7l=4kF=Sk7^kL>DBRHo`EnNVE5X(>GX z>-yzVn6J~9p5vN+;VZuUw+Xe`C0dFCLnYs-|Ekf8ww89rUwbkxstuf7eIz$zOYV>QNW?pue1DwX^*DuRZM;At`Oq z@3JS;QS|~`UbgFrWLBM!hMF`)uY5sOB0cQ_*DiY6@VcjsaQ@Y^gClwVH=d|q;>Uao zN2Mq)p?#u3vz&n%#OJLJe(QN&(|cXu`{#~NVGmK6gdg;zG7Y>C)DJSHBD?d`S3QSV zcS1r)LaKoYNF?!<{N8gU8Yn_?dfs3g7< zcRVqg4zZ7Ke)6=Aa9s4eF%0^|ir>aDLmRPhm5d`I-Eom$`q`5lN#Tp|xoLX_uml2& zBWoC%GNAwIFR!|%;LX1 z53%P7QEXt^-1D@7H;>)-U?}zKMQl*?$1cjlhygSfj5S8GbygA&@J5>Ph$IomS82w4 zeV3#IY5jDgUSKijT+ovoC&2(czYa@cpAdSgi~pDw_WVVjcEr<)SFaxy7o@~*Cx#iC zg^e&3>3~hukd^?(&!R`*$4>1k#>Zb>*1*@Xh*4Ve-7Rd4(DdIfhVGF21z1;hu3^QD z%^^D1qs5F3EasBGPLNqeNtLRc#CJ8^D6g}MDo=R%1FR-VC}^QX(*bomfp=T^cJUJP zXBT^B$k4$fhYxyc#QbbqYeMNk>y^U$7dK`WThP|r=Eql>(lN?L0Z*xl;0MeIcee?>?tVd44a}hz?r9Dse`43pe4Dq@Oh9qz)h- zZ~HUO_>}D@LSWOdtltBL`H6%9g?X9%adAAcw9!gC$_JDNLmVftXb89h#cznyLf~hJ zgxS&t`!C4`jxw^<8WWOAXinlLmNjnZcP@plBsr1^LB&e4Fu|A=qK+&}FgCH`Uk9rr zOr@$i!uKW`KeGgtB`OuI^JAq57G(K8Z@&u0Yg!8brGhb$r4a(yM?0$+WmprEN-J9F zibg$qCrT;cm|$x~W2K(8o>kjhcOQ6!ZL7_6746hOf7g&qdvL3~qjXf*!((NkB?4v=+%ly&Ie%j)~1 zn(>Stu|mmX_BM-Z8n3f8Dp>@APG~E5RBalz2yIU)pVutd^L7F|O!`kG`?MZT15)U{ih5<*MYOflwY=lG5kqkaU*G&N8r z)#%8IURE9r^gHm4sYXry=lTsL0TFZ&$BU&w(^HyPY+{si01;li*X}YFnMJK6quMD_ za8g*=|1_>=ycnWxovUXIXU&Nu{!nFwCMuP$;bj~e>3ZZc znkS>G_2+Gccp4ia{hr8xbTcV7M>}Ban8% zakh6d>PApLQt{E9je+bTg3_~_@c{q0@GBkkn%_v5EwS=IWByPVqnkeD8`;J|j_3(U zO_>v*g!8hd)az(kVZafKB(e}wO2G-aNv-;LpkqQa-5qhl@`met?5Fg*ycvE|TC-yViH|ZeQ zbb`;2Y~<4I{#*`9E=|4_)93`AUv5h6`zvQ~eX7(6B|byNXTA8W5ucYt3FnBt~6X(-zDdhnSYUgOy@&yIZNsX;k4=VxT!6JURePbC3SL40P5&rI=|AU)9MwH2tkO+c)BG^`eAv@b;(8f~a)H1JAa<`bgF_6hr{MaItZiRi80ihFa?93aKQ)$PlK z7al!w%rj36nV;Q-zcAED)Q0lZA;wzvi5)qAM$f{Ui3@TE!*wiyk#63)9#x8p$_ByH z<28zMa7810C$4QLDV~t+sitOVdQA7)^mFrnWlyPOp_~l37`n}P zqh-oYuw++rH9k|p5V;FfQ36DHp5K@agSIIOP}&+6{tNwokSd9!Hjg&GV{`1J#AXJ4 zmMjdLMRNCVhtPe=zJ&%k-nars8$K-7kgX)yJ=Yqr&ggNZ>dOInrl+g6fzKOjJR74F zY@SF4;^qe#ZFGUJm}qng0)Ap_lSIzW6|2mC55(Ct$;hzc2&Ya^ zdNAMZBy#d+CmVy4qrNk%D0pju)y;ha1QuMw=9Cqt7#mp?fsCzDLH#e+fN9@Jr%Y0r zW`RddHTJPaDp?jdiMwapoH9|t1aZoE<&<3%UK&JHo(-^*LZ|F23&Z-7 zTy)Ah9%G=E%V&FxM(i1qsa$ddpn^;4lfM(2s_XGKm!l$i$sJMQ{P^)PHA)eEn>#On zm+(=oFR$P=RWs=%*W3^;~clypuGa@y%j_|>voxItY z@ewiY6L{BRkxEu z->rNVD@Q-tIt{z7-iU|KtZ^0$E(DJ=azwm=OuHE z8pNjN_MOT+f3Z>40Ssj$TWp@un>|WM3qRIDuJrLn3yUL%C@PPd6kV3*e(k9I58B$B zch;5Vb6zsGMUGP}zbzsI56`@8)Zt$&fG~(`sxam-j{o+u(IkR`+kMcyB{aaF?&pJ5 z|A7ytFECzZtCXCw`9izBDeV^Vrph&)aLPhsK6_6kV*{!KywInmFJ7*Ig0!I3l^1@j z07JB(_a{{YNxk@rk;g9DNnvTun_hUHVtiX)H+sMoHH0gcF?Ff&h~Dg)TqbToa#i`7T$6R|fq?Rv8`Dy`w%q6+ zL1>%aFk`vVmJJ|8v6o2YRaO{pS;0lSny3_K5~e;axA66T!x$ZB8TXnICK$Xu#Omwd47 za`FU}d?g`+?aGR4+A)L*T90uU%bp(qb~c;_sY$&0DqbV2>)Id;LwGlC3%%j z5mBTR4WyERi>(x9#^rxdistKKEuMxOi>W!R~XFW*;H{Fp|BN?~;{aquU?I7Zb=_sjxO@h_G zOT`bR@p(R&KOPeXAHebm0W|Z+rkOt`8K9y^^l!iC_f8r0*>@xZHFB9~lw9GCg7uY~M_@A~4)GDC{~m+Z zyXLY~F(8!HIn9g`f|fjd9CyE>wciW-?;bXbRx*ER7;ky)$)Y^`jM1JwLIlJ@_LYU~ zOVSGp*&bHxpnR>_D3Xb#8cs?ziIl4Rq6bU!M-Ny^)k2o4Z$PQcjNbpSR2>f*7ua$l z35x%^6#sRSj^ZCbWHbwV7gBl4ZwANn@=XR6=c(_5g?t1O%d&-(Wxp&-lfy<$;%zNu z30@BL2bEU;csdNQK}XY{7sch2I`nsxI&JA;etrNnt=8W~k|g zN~Lap{X^rh=HQ!-Lz8@QICK=Beq^MCh5rCL%39Vlo+lnLVp#;JgZxic;4+4>`1Lu;lW7u0%4A&nn_B<%~G{JWmGAp zh7;z#=xIL`k=MPz55Lt!y9!~hzfOUFY$EAMd%dEq?c_HC>V_QN6;~LPI2=1|#P?NA zDo1)^6O)P~%k}Y>Mz8n~Edj4k?6rn` z$@O(9KL)Ssc~v~*Z0O1R{W-_L1H{e z+}GTWOHg3(MI83ZzivDi(tWeu-d2vU{=rxf_k*xyEwNDnf7KShU@jSTXk5DfpDX6l zEY!1trP-Q7lxpHrSwy3g#Akw-1&tM-??r#|o%sAAs`szr(^6=!nfO!`XyxHECi?^6 zgLk3Ae>0KP3?wrXNz6p_nTR?Q(PoaxPAT%APKbltv0@_kvO)ypj?-o2j{Q1v$My=j zV+|MFv)kOj^QT2ci6J<0Uaprta@**}9u)bgj&6KZA+Nb!)0jpBKCjM(Tb@w*Oi z?rN@n4dR1xyotDVATEf2*;zN`ihb@+#uIVf1hy=f_=RQ$05o&fP1DT40?!jya|@WM z@bRA~7AgMo#F&-cgS&q<+zz13+gw;&*;nH?YHLGYtQy?7qFR~^S>*qB;R`v zX0XRKZ*lgfAdDq>lV8!i3zFUw2{nb^lB@#m**k9Xdv&K}$A!pqCQoa`7j(SQiqCO) z`?6DnIGVrB#NjMXB@(hlc-r0rPsM%`ER&xK^Uh}S7 zl9Jbl`F<|sy{bjrqnZ0#!oiR5qTZKTkz1<#T0d`V-p0oY^BYCIqu`#UfyKP18A0Uf z;TFDSgYeCJYg!`QlYjfuLsesc5Ij+rq+GnB%bOd#puU;RyVAiI#I=f!OjCk^OW-NT z-)}8$z?!ObtWqMb>i}Ti%>2bwG+sK&+ba;a5>NSYaWd-~1Q!l*R*Lqz8R2IyrWto6 zWsvIiCC7LR=@CyTsyF3gY*wtd1$$a0n{^*97Sf*Jzr=daGlFC1RwqDXH|1PD^{2(1 z9n)?V;i*r|@4}uV@VqaB|!lYQ=ckr|d-UMIY1aB=ZVg~_`I@pltZO`_rWTgXr$1T2T$fSylAfXZn z|9X=DyZ7Vo1OENAh|7uxRsVIBtXRWyX5A}#D>H&)=WNErE=bOCK}(KJVb6pBbrBEY zY16!eE0YAJH}MOrZ8PXCZgB1SCGa>+Wp6!JE??C}TMajd%cT{B=@gMwyr&~-(quf; zl{IyI9hRn&i3)0RUe#MA2u@OuX|-6p5I8y2yj86@YBcyzFdV&RK6hqLYhguF!VL?C zq}Ak&YIsu_DG=JHvQo7<|Dm%Xx_LQ{+Pr^Z$Ey*pr9T`gjzDlYZX^(vW| zXeHd(<{caa2gkL0gW>2a^Z5q@r{yxj$gaBnLD~Z`Vlh<*x6%E*>IMX%ArDM1s^=Z1 z!CnBNI%2P^APAD_{$J-c(SEfttsBf<=9v|1Z9>5X4ZX;193)f=hMF6|9&2Xs{)Z25 z=hhZ0239>HSd`cs)cD(m>6UY9MH+h6*G>mC9dF7IN(y7!&@`!rMom zgoMlStd`y`Y`l=)>;+)hSdTC3?=8W`id5|GNBgu^-uE0jT&)Gew{rYUy0i7S$?&Z)odn7DBCaXLz$iWKC)3ofmI)5>rSRL3F!2zaj76-uo~+ zCfJ!nJ{*;a*>&tkDphHMm+t`f4W6~6gZBe=Sz!r7W)PL{m8u}fQspE;G4iYYeN?$N zjz?YERg3>sZBJ$GKV0kYP1L6I+w-AIy(>7{RUfTX{|Dql)p(g-n(nQ^Pn3P_ORbC~ zu!2|QV7s^JQaj-%YE50Jc6jns#t@7p9d2NkDdr#0v;QKnyZdWBpvAfqbuXFWD>{Y(RwAT{C z;4q?aAgQutduJyF#cg88-PG{4xeo0Mf_w7e*%itMJTGio9nhpuxxOsG zzg|IoCl;P5v|#Fcf%vUzWy==XFGI@gLOFw;9Wov+mcb(s_q9RyYNi+;-R8?Hd7lX3 zw{Jh?tx@2PCAzGytjFFFjZ{KG1&h7|g50Nqm4JLz!3sa^{Z3CdDVQ~^wv|G2J^qfp zhLyO3nku|S)MlxH5aMEc7qpuBmJIhU(b+?Sn^GK^7j_@$SBL@;VEXSlIfv{RL&0i}Q-rQChUW=$WT@43D z3qJR0t#Tp1ptYI;6C1=e+o{=B+~)fDpRk=`YCx9D^SHOXrI`vYB{ow*vwS6Hdb9P& zZAu{p@tmT4UTeVisC4u|jOPF_f2GfB+=ew*Tt9M>Ac(*RY*n56f_FS43~Ynu?!G{c zn*p-96UK!3UU|{`xg+ALqHE637QY1Jt$dYCYRFaI^kr`YMsScPvGR^Up7*ozfcbta z^OOD8SJvYB@;8*3OZ|L*Ge<#wfthRgb}sOC)Zm#Pq+lAmu9ZS_7!_u|=`BSD-%&pY z_DMl4%7w8j1kDnDD`Fen;dRC#v88ykA+MbYG1uC&$h(9+E~HYOmpRuOs8UHqIPxmg zxu99Tu8X}7hOr3>&0gm&nbsia(i$Xzu$sM0S>xj9mnv%uE!KG1s>^_ma4zI4Yg}LM zeOH4OTxyMVRtn9vSM1i9`?F;X9$ZeWb-}Z`uEZi#^vvu8Bb(hTz4i37Kl4$`y=_R3 z{ds|)a+t~Un!XjsXTRn3YIk_l+ungeM~eS7b(t@bSMlBd|Cnht`KWiiAH(2PQZQ@wvsMbt^{ij)!_B_G{6lA|LJFkRA%0=4 zuB3w~{uvz>=WT0o-n0r6P&Jmz;$(3xe0my8>T))F*A>$a`ifZN@IN(|i zPDxGVX&YxZ({}TuqcE#mEvU*Vf|}JW|3$WE)ci|?c&fc=nJ#A;VNX6gJm;THGO7^E z2PorLt1^E28)e*<$|#uS@d}^qNZ@npyk2J8N8Uaff9-&`D4*$lJ(BM`wIkA+QA&^b zRmN6A&ITu%l9v1xJ!lo5G36roV|HJ!%=kdWwcb%$pPMve=RCQJT77_&>pMZ;II zx(~|RbHbm=HS>=P)6CX?63wjtc;iUE!)eV*Lfg}+wUQ0*RjsuAxcp9zx6&%8RwQi| zefiwedaY!iz7VaL47H*J_%Dgkqia7aUnbm)+g4*GYxCb+n2!GWInj~Zx_BgiuU1EQ zYXwXgFJ@|V)aQ743y!bV>L{wMqA!1cf{tdMj*ow}OLtt_TJ3zs#7R<{T04KBlP^T_ zVEn~dRf7;-yZHi185KSF7fO-{nv7?-I^CBwxY1Bty=Pj>yz?v1|TQ z-jd`0P3TfY<_0=C^!``nHTQphxc`R&t&`P2*4(%1o&QJ9=hF%MMb#%}z! zypR_Pe@|*rZ7C-Vd8&AH`wzsTxWEe|`2oLcysjT^BtYr{yTDg~y&pU>XZF}D3=xtJl$ORk&ZB)UoC%U0xWSc$E5 z#t%zJ@~gC3TA>v&!S9x_T0-_y?Al zSsnVZ>yCbCARqi1ZkWI_CZFU@(vz;s2yTG2D?*iel6R{@stHOX|1bO7e+1FGdxG71xCuRm86<*f1B&U0({pwRT zUeHFH0!k-K!UaiZ3 zg0Z=O?CZlBwDo!G;1Hqt8CCbBtrP!vrY|N##Ydm%Brpw;CAT6~-UZ3ztwV1geP$He z(=IsHXg^3v(0~vfX;;xE-{CTglH_puY<92J?D06A7N6Va@C3|upUds?#ty&x%%fb! zHD_Rp+QN0MnDxJET4!HI9Qaf&p-DG4YQZoaHfWnTY2DJ={Z{_kGk90JZ49kIH+;LRMj1J%n9zTvzdbB86nvvdzEUd~yvFs)ci zN`VMXZy0XJEk^kT!7DOef!!Mew;U|Y=m(3}rcUxq zFTD#D-24M9XjGyJg+cqg#n5cH6o}zppoD*c4E`;LBsE-$Ny4R-xD45{Om-|kiPnEY5DkzsM|f6aGb#kj?lPR`A`WA7D|@&NgNDWPq~J{KxVO zU}2>$wxv_>tw#I-+3*G{hPUwc|8?i>fs-B3>D{|BTkge7knoCsK|p#DaWCzkZBqB% zYD>rlcNG2ED>ymZ_|@Fv;9B7awO(}mcu)?eZN62X;$Osgk3#3+4Y!?=yp&CJIKB>t z?$GO4ANEc(JgYE{1}zGW=m_=DqI3^#J+{P@P);mg3jW3k+05etOYj*Xmw5oJ(tC_@ zt-;BB_E|Kkaryh149yvGOF^#M8r^xzv<5}gowse&4QUzy(bkqb?#R(RQWSzBLV3s7 zVSBK7Jz*%r9k5%7vib(62_u=OD$j5A4UXc5#&Y`wujMp^gRTccvK7{+B^<#IJ&R6d zmw%kev?GhiD3tEHWtc^Sri8Ll?_VAsmNEA%-3B|Ktvb761V8(%ybV^>72QzFR0N$* zw!yX=6r9BiE14>Ar?yf_=?>auXXS0Mi`9~0 zjpH*7ijzCc7~T`STCBIYSE&ItPSTJZCP(rbSY6$_6hmgcSp zA#|n33)>S5p1MBRJ(DRYv)@T|G`g#o>0)p&un>7`D*yI5k_9ozn@UPI^J+-t&Af+h z41UA&pAlLLn1vyHm@pbY=cjTEoT*`y+1JZh_ZeniukedX%DDYm<|)zaFX*vbg1*Gk zWJ7P$KULGGrC*sCoRP`YouIIr<^E>bVinfq&*Tc5U_i=j;pOdwmQfhfPi_NRxu3{R z+$-f~nN7TEKTSdxm(i!GPt^d9UJO85 zVf?D^t-+N-Sf!HtnC#)LWuD?*%Yb5J`)(#vUhcO%Rg{PivJplXYg>TaGc) zsP>`q+mm$4_?f|4lVRU0+1NbP;%m6X;<7t~lY~}(Y21sNLUZ*gV+z7uU<$^sD(?z* zm6g{6;eCU!zk<6P&N|WWxV>&87tDrS)$HlLz>82>d9b7U`L-JW-8bg}T&Mo??VafG^N9M#%g$7qlQ;-d&YfwK&~SG={DA}BKTWlxLOtZHerLV zqK1-&bnCSP|2FPO}O8%_TW+x?RQs|teu{0;i@1gy#YGDF-Z6I;=Q@K%3Q5f zrR^D~CFwQyh%r#JZ$t9GB=6}f>a}6yN?W+qa z8*}mYQ*I!UFYaKMUD7C7XY_$r#KG{M_gMZ@!4({LlT1wA?0PLRb+gMaK`l-OTQTDI zLHl-r(XsK#kXhN)l0=Hqjfx;-$6iPy#{w-YtZ&WN$npB7V0VsNtC3@smYB-%P=Xxu z(Y`GZWaJI}siH*^5ms*{A|xy+zYf0g1BjB1 zsl07GHM`Gc7VFUVscTBnfoW@6qGr>9kFnF&v_+O3FiZX7gXcqRXD4@n|IgSNY=w@`SW|@ZXRgUX zMZ1C~^z6=H2ULG1@KcU|y*>jJd;QK}TQqg%n#<6gJA*CGm!kQcCBY?l(N~Uv85}yk zAvD@BW=xK=N4$Z?4E~c#ko)&V*D&7litH`S(tDQ1TgY-l8_lD*3&RwA+JbC2PP98X zPY^k9Z5m@tbnzP(3rJ+h6GF99)!hLkjC7;ecpq7Q{vN)SQ4 z_60xZ1C*Es5wDh*I^Rf+1QBK<h<98Cl$MiNDP?qXQV2M`# zmQb3Fj=vTxMIXKvoX5WbHGp|BySdaxS1UE3^=BYT$zu}#2uJLTQDhZdE(8VG9KgW9 zl9dL(S&b=+`0Mf(T#_K1BGV1S`o?i zGvW1&VfAta_@Op|7a;n-9qca@Fi&xLK9ffuydAtDlPNAw4qB@$Jxy6^#G`^m(Lveu z)k@SHHFoly;CNVRQ{UmW&Jp|-JUVt{iwW3P*g0|}=n-yW9^iu96{zYT!BLr4sLvA^ zd4@7FAQdBM-O->oiSpaN8=R7C*l8Yyb;j-Q2H)a@kjev|S#?Iwz8`c5QRXS(IE1eF zASh-srDcwpI1%6C%{Y`iCt@C`I*iW~N?wY47|De3R$u;kJ{~cS+9Yv{SdXqWxa+*=4F0#H$`}kM3 z2wqleR=MUUp+SafMmoaxlMu$ne;#yjLTi>1_vyJWpiet8PjR1i$HhQK2-} zHBqPVB_Afr59X+@8ZnFSnvNo)VG@6N^WVX5g}WIBbUOcvw#ih8SHp8+gT4xO;)Mka zC0VcUP`jpFsAQgk&gnOXpK90mxdrIWZ-ZqTI?qg>_oG5m5Tl?}M{4nN||~ z?;8UKQ;gF!Kag>n>>z#>xlgF`=!3X%V~5)ZuT+Qo>Bry<4q#^qF&&{l)e_4N$Gwi4 zpA51m9rl6QoZkSQ#?{VXS5s!wx@`GUB%TVg>3x%Wg#Y-|867#eWNyAqlss;S#p&_b zTvmtI>vsD@zuD`P0#5kgELqW!CZUJYm#Y0G*p};pq%(9DZaDB}&~1C2>Y;*vA!Xpr zuZL>;gf17K>vc-lSi0;k<2=NRKip|Bp@^?H?!l~op> zW~1$=g1g}sOAs@~EW0TcbBat{7dw4ASjchnFT(an}i~!)McEA*eJl@rL@s*RJdbW8~rrFMqkxv z^`K6x7i^=2ic+;}LkS9Ng}BTRY|~%-VrOQNw0V6Rn`rvIrfDb#U7Zoy!1t`5JpH!N zM!U<@b+KvnVBWxA1|&m6V+=EPmyQHwGzcx{OMoI-x;;>#VAAbgvJ_&oFY=cjt8Bp} z-OcOE!I3(D7O=)T|Am`tPerq2^(T$F4oPjU6^7a`m-VNy*?b#>RiDG{aM=TXt1aMl z+a!<2;l=Qds<&&V8dl4-sx8y0 z_JVD8sG`|4Hhb7mYlmd5DZv$Nb_-f?^syHFHz{oPM%w6qWa>HuHro%aZXPPZ$G@`B z^yZ-u|3?Z7zC~Zb9WB6uo4{&jG7I)A6pRJ;gv*?WCmPuBA+4g{&?)-DZFsbz>GQGS z(v&vL4{o5Jybo$%kQsQa9<#-42?TsDi`5m7+&;6<>a&S%(d=~kyf$LLrZlC{)=f*= z@e`m$Fki!@U?vr9Tmwx~a6{QFNNxdikmZeMMw_ zDV96Hbvy@|+J~Oy9|to^w%9R;Hu#84U5Ea7cu7B0+adHb9|N*v5qE)}>`cc{9sg)b~;PZ>G{}cb!t21U^zs)$n>YIIVH}zzg{xWWEMq- zJs`Oxx5MhOd0mp#>u^Kr>hO820UI?_d+JieOu6=mGsDmd+k@F-fa>}PqSCc#s4>;n z4fUq_r&h0Lbb7sDQ&kSI$=_{~W&Az(VF@Z5+EAMqJl;997j6LrLD@ams*D?`jFV(K zy61YYIn)^S?i%`>yGz!Q?sTn6U#F)JbqlS-I}oX66HeEvq?;8|joD5BAU0U{Wm1Hp zASDwC1_P^XB)D+1eVDdejhTKRD^q8t`?Sj3tyAWO2h@Kn+9YP0 zWYzKE%R~5!yMBtx+ZyW!esg0@IEdZ2a?LW1AJI5@Jg83(Ck&S<>tde{3GqBP5gi*E z8f!SS74#I}uURvjTuM@K-g)BNm)>U%#di6Aa9aNvXf}IVtwm z@DN}pt_Er10fa1=HYf=>g~ynucyT)eipd{`63TyB60!?1U3q?WW7PH0H6@u$@q`uD zTq-NO1e{`pb?eB`@+2GNZW$H&Rrr^d2f8cjnEF)xT7veC4oxu`zEVD<^d@JhViU)N zHf9KasI`!7^2~P{E0uz&P2S7LJYZTrb3L(8<=lCjCh?CmS}|oz&q??XD5XEb3&EAp)k|Xd#LQY@=oZ$#L(VM{G3Xa(8h3sHn7pAv8K`SqpRdt z{WfiSvI;0>+j4{3Y;4Q&my=eO&7e$$2Zd>WZ1#APDK;Q!Fd zbV|z+`_IN)92S`L~CT2z@XEtX&gJ zy_|VU?79!?I61UAlPR5GFH;ijB?dOxte!BAsSQWoWzRln7Cg*D(!@B_ct&VUCQ~?} zi8~UTNELyG%_I?soHP$pz0)n9A>6vLAufPdYV@h@HKrl@;F`4^(4jj+1^fnW_pQ}d zBX=KPDd@ivFA(HhmToICj5Bf!Dl&ctJ7~zkySW*_nlgtalKn#~**jX6SaWta8JLR&KUk)%oE zRsN6lByB1~MH&1=AW4=BeWj4Zb0M6)^Uh4Pueh=gUzDl0r;eG4N^XbcW|Vy4ndj?@ zmeGvq5pTAkDaKaSgjRCGVx~3S2k%o#H7Y~rF>suV2U&9G!4_?&Zp6(Q`|DG3*T@4$ z?AF=?B^>`crKVB#6)iP&(`OUZ`V>{`dFBggMvX?OU=@5+xCh}BNWP)qH?36v)$+yq z>IschuPi-K!Ewz{?UV3nmkO1crBMkL>U4roCo<1B_850KYO~6Cs^QAgPc`ho66;?B zR)=PC+!)Muif_K{DU8iXnYu1!TO0a_gM~IMt>M+j>bh5|;PkW))0LOg`TBNi`pTd0!D+ElsS64v4Sec8neDWw~D#$KVjjSf2Y*rlVGP zTuVo-@KBaMV!cdtc%H7+#!v>>D@U=MeWB6@+$*T;)g+7akJDxk$b@yVdas3w8p8T7s4d0Lk{9%3 z>)r{CY5-UnKsLru(Qhggny|80Ry6-if>Awcpyl;CEnoOxzE)9ls=<8phoL7pp+hsZ zPs!5AEt}Umg-*;E9p=N&olbnMAbLU5$DFH^BD zclgqP{5*1pZ&AS?>szCPpM~B{vT(BT^U$-x1g2q-h%TIrQ=c;7^3bu+lx)LSu@T2Z za82}GDw%$z%`{o^W4Jlvc)tN&k!VQ{4Yv6zbTiNIqtrBB?$%P%c==Q_5-*uk1{=_z zZy`d{X^%0x@^L}KcPRHep0VN6VH(ELreI2&68*L`BbS~b0TdWoQGK2 z4>kWWbeX&t;-UH#z3`t`^Vv{KvTq<=^|c)NF*J+s3>3+7{oV?NCOrJvjAR{*?!Lyl z>)5DUDLtcc^7Q&kGqK*~;0t3Rz7fLMM3L)c=&&#bM2m-N;@0FwhjGkPGVvaR-ugLY z&tys`cy(U`3nc4JRsRiHIANB)%9*JBuc0q9XR6N=s=Um&%A8o_x6nRLh^nN_;p}D1 zQ^I=`HT^y0ODs)}z1QhV^HG2ge0*J@zW8`yr>-OyMZ%fTWBP*hPK>t_OW%1mbWbM3 zbAq@748$eLnz7;k^Bgh!vf-5@`Tr98Q_jJhz^xm5?ho)v$#Y_T{tCUvaS#O>R49{% z#w|3&)Ny}pu1|D+Xs$_g44I^hriSm(PQJqM`-HuP-g7O$5@DKpuBi>2emR{{5#mN- z)>BLzZlpTBMy`RnFx+w04y|oa(G-1BzamF*=2_e%TwRKx{uX_8vl>*~&rQcv#v{F7 zA&9$jiyL?Kg0xik&E3*MlSUakvdK`7N-&>{2EE?D_4dXU&U(UX+=<4MiRl++W?h?B zY)UdX*e(LWtb!%+5#THnY<# zE!;N4eH;^WD*ADWO_8h2nzU4PtTvS&UT5P!Zh?9oeWoarZHZj+Q>4x<%M!%{?SPrn z`^@g^STUBl7)&KxkVr^ogPj%@&h}biqmBgEnYl%q)fbRppH9Fj1w0OqTZAp=PWeVN z{>ql<$W=>PGhc41Xr(q*s2f7`LNm4Tip0h#*W^O85iQ9|VX@KCvT!m|KRW!=>el(` zc$e=r>kACB_nHlczv;bZS7P4Td(Gg1e6QIp_zew+lk+Niokv^Rd(Bh@#1+L_C63ZX z%mdZR@h_5TEvip?cCM-7CX-$C`z&^cD`2r(tqwRH;IKL@9+xOOT^^^|fldahT5tES z9A7WbYZu)C=tGOeYBgIWr`rQ`R*UHIctoEaad$o3I(BSBRV8Na=-1pmxzJim;p5Z*yB?C#$Na z)ib&MX1miV*__UR*BWryT{hSg=kbBFx%?iBh-x#Vtz%nmeBv1{&+Bk`tTs6L;r3c> z)_}+DktCPdVYZ1bzuAVk=^(EdSpEcOO5L&z?aSLQrfs?GswxTX9SyrFzwcAgsn}*O zHc!61_ni|8=gjGuUnsh)U^`x`*JHI?T|U?;ZSw}~U_(}~&Ed14BVU4fh~|o$>zUFV zSpmgXWXFyTs0efOY^i(7RR}F#J?f^3B_jt9xn^P-6BV_keW~?lE}YO4y?l0ajwzjJ zWmQ$3QS-Z3);HM#cC*#zw>vC;msNy*6D7L@wrUf-J}^z%#dfpTEBSqXpU>m9`aNzp z+yrU0!47jUU!Q1?9hp$Imdo?IZE%*yVfA@jPOHTU2PbUsTCxQkPKU#Xj=b@3Hg&f& zt=iD;VHG3u)3oZB-EI8v3c(a`TSbfAZ?pTX7OTT-c3MCLdjJA}7eYL2d{_I@>JZ(M z(<)hDdoh@+!wFXE60H`9Cw7wJLlk_lFQ*2&3?B% z;D|x&0EbK0>~UIb=2(lDDkzFwb-2S!|iiB!9)UHmm7g6#>ceOP1`-FcxuH6Q<`Rx zXxKG1;LZr`c|?h<>jXw&TNqYlHDMV6j1ZB}p;qkLA#dPB)yHf}&=(-EVaP za}Loa`7I*slr}>=KrMQ%XdBz>Tn?5ACsOQorw6W=b;4;C7x)#}rpxMq(^g)eEe1Zj zo6AexD%yMZ6BbkICLQvKwtH4ZM^nIMg|>Wtr^Vs1!qv7OF#t;UK-vMBf!jxA0JVd+ z!`@gk49hm3=z>!T0h`4wVl#$t2gwM82!8-d!Kp<%2x_&tydKyN?tp;|xPbxDj!v#y z**eyI!}6yfPNZ%Y4cfax%1_g(1&d)vug|L}>S<=ZOL7K0UZ2D7^4kMeNNr&#^GT3J z_}ro!#@X0$^OhO)a#NlRLNmNyw2qw^w!D&?m%3Mc+7T&@Ir_Dw(`d{Nu9c5wy;hr@ zms%!NFrlK0Jbu~X#E8cQX@xo9uu3p2nXPW8-D&enaOz2NBQ9$>8N?xEf+blkUWdnG z_QQbh^*9}NkJaIHTdXh;*kVu;#xN&1sR&isCCJ-c5QqJa0OVOti_2$mc+tL(VW1}| zqbXg>E2=B5OVcJAc>Qv?va6<|smWz=TfLGm;Ds?2G9;JFY`0n*0SV5+_$+RxJPzkU zvSRka25z_C;RJsYT^0!B7QY3C39r|TN7$U$z?+vp&E?r3g7|$luN`trmt^x;t$v@` z9qLXd!T!(o?vFdo4_e#j-=kkP^+VCWgY*Y1s-d~XFfmM74ibIna;|Fm#zkdx@GP+Rb*a&*SvMDLMyq z5KeR@unMyX1E}2@kcVXPuPU&w)Q6YQ$;(!f;VS|;V#>~OYMmyvMOt(&mPThj;$km{ zDzYKFN+}skW;(9ukq3cIv^sHK@3Ml>ZpmfyJ0v*u0+)e{+Pn(l4@}J<^)$P|$}Ap8 ztXyy$#$yRcA`a&`M>Lr|aG2Ka6TLP#+6B1{7%`4qHarA~PKP`vTQ@rTPtKIOX&-9; zY{lq&m}8`BmF9>$pRLF;!8{VSkb@gIMLdZCr?&cWSch2%jG$fwiC^p3{H*=Zm5_dc zQ^DvZLCWI;zI-qha#?IXkKZnOV=zwv^R$?)FnIYTHx4Lf$>)~r5LU>MH5jp7F_^tU zikPldso55Dn)c9)#t%to%Zo503qUmTIV@hM4TdHMY=w8aAYpXaoE8b3Tcqygf|1&W z(^j+7W);0~2-GK8z}G~a)jNUzyB-Gqtq@s!E}PG42jxS8i=Ec#mtYWvS)P~Zqit-R zv*K|sKTWf;kL9On)+rBQyAM`$F1A{WU5uAmMTg{v$*mV}_;269Z*)$R#wc~^WE#CmWEOT~RgNi*ROt8vE9fjtf@B1SZmZW1d6MLX zgg;=1H2^%i!ZgJlt6i{STD?4*2aXLtKIBD>w7_fIq_8O zLRc;Ez>Jf?2~VGqOGr2 z4Kk(X!Y7Xf#qU)#Hkku%m}h~B`W+T497cA*blc)GyCpAVwiXBNRhW6g;ZC>J?e)S8 z)GETz7x2Lo2qiw4iQ=gnSp<0krZP^qGlR7MP4W0HeU}cR{w`6y3}2dbl06 z*EB8D<%4uB!z@`s`JYvEF+l)xyF6}5#3Pi;=^<%v0M={p)XHoot5Yx7u<+!wJLvS%+njV2(wU&*(t}4{4~v4 z2C7cO5 zVBG?eFwrc+_yy~B5OTw+y2Jns1y)Id1rrgLuG}!!w!usY(tfiwmjC(Y zbuc9OMKR#_S}Zom&mg)w19pcS(jL$!tgTpLuoU(^m!GClA8LH6VzkMevOzZ<6h!po zDHzzu7yyH;8{($bZgDt0W}nRs3oi~a0C6RD+ssehC?pVg zv2p3zhuY^sWOKo|=5^a)1xb`(Wx(r$fejXMa88Vl%!SGSmNm67IKv{o1!k=t3DOcU zN?8ANNItVD$ddajIuS5g)u)YmTxe)dta-sEemdAxl zeew-)msZ8sKmw_|NjJo$u}l)@)n&;vigU)j%#>O%3tGSLi_XhhJcKT;?_XTszqr1i z@CiznSzcVH!{`S2C|T=|rP5nyS_a)VP27~HQlI`PFz3zD3q=}|Ads*NG^ zH5^dEnC1=00fg1DlOI1blxso$*bLYjBTBcxzoqNZ`qF>BWS@yoIpCuXD$selGZjlp zXQDeAhC6T%qe#PW&y1|UWSDdAQ}jv0aMy-6z-hvTB|h}lfgcLcI}3mA)o=$Kl8M8d zXOu2(iMVC!Y=MWN)o>|L!@r-x{b1ozOc^f4rNdAP{#6mqH)B2t!s8bFi$Fwf#lOhq zXV2naBxKHm(8)0R^iHf&SZ6~;#zb^Jpv?6ds;PH$Fe?6K*l2YhDl@!w+hO_FNU|t|7#Nw^9Xf zCbN1O$N(@+Iepa1G}`~=u@14xh2iC#us|&#_Zo(jVJd7PS2*uHDm-2kzKIhaW-2_{ zBV35YoN7^cgn23(M?Jm?IPS?V;RiJ&I(b^j&7;)Km(5%cCZ z%iU=Tm7v<~d@Gc14bKs#sMX<42jeeV(@nUGd8!zH29zbB%o-xxnH^Qdj*;bMxJ1)$ z59h>0dpOK<3zZ&mGG=*g0!>Szqa3CdMpo1`Z(~RFo-6#Q@R*)Yox%H))SN~^lUa0U zZa-#Pxz%P5Zc-i;(AH-n>^(5M;1w7Jz4+?oe&NX+_pwY&uW9&DOH5CDA8f5Z?Y*nD zd_bAGoG05*8R+=dNNKWH1Hx-fNz9CnIz!RPiLHB~w+4p$3t8C)=9be$ead#hWo=fK zCVTf%n^hfS*_VfVb3&0yEnC+t?(rT%Pv)s&U3^hC`t6EvnT7@%7h@>Za(A*k5koPt zPn7P#{F1SCDbt-Y-ZVcJ@D&*-%Tbsk<4!GsS8AsoxH1gLbWq(Mpe za$#c;Z^vEt+jfE+&}p720nA@fwV>vB}&4bRn(=#2EMBu3hao8V?d$32uh{6MxoGzyB%%x*T+0UwIzc$B}TX+Lt~4_ zlakS?fG&IRt=j5U*1Rq0XXSoD(}M7&&+|Q@oc5YvRg{~kDBas??iTFQRuAseylq0n z7P6qZc+dsIzid!xDvV09%0d@OfR0?hF_t!u^#BH{T#uY!9upE|9Vg2gzeW&cUA=G_ zKdWtW^SF(+b*D^NhdzC7;m>>pP-w3RQ5r7OPZ6xXLm(PxTahF%&NnVBZvFPHQE2L?qJ z3h!(Al2^Y>N7bj;V09f^hPL`Q!rH1CHIA*iJhGD$zEsQOwXh1|d*%VQ9wZKl+z5A+ zhKEEBYD$wK?EWhwg9Wag#^8Vxywvg~YCAMCQ$s@5s>qsCD=i6KY{P3#K)3sSSe==Mn6aMCrqc0N0nbi^pn$q0k4jWgM&>@JbEV_TdqM=dY*KbRIEQOD#uh zZU8!25@A6U9PMPEWhaM*jLXvq!&gc$T8VqK6>2sz@`Er(tJJ|VShMOlYmM|q7AYSZ z6?t8#WXMV9&K(^o78Wy4)nT*}H5d~q)sW~qX}wWn1y6l8v<(kr7) z+lDmJs+FBgY=c*7r|iBqvX$eHYCGkymYR0TE`6tLYo{4Ojd{d#i6X;SN`E}3861c- z8SUdXw(t0oAx+vRHL-KDH1TobiB&g68uF(0$%lzuRL31*x*}s3liTFmwU@7;tq)Bl zTtRz|S|7ax5$E{AA6Q2;P5*l%#`8>Xvm*vkz*t2A#K}e_*FXv87_Y$4*%a@K@EQCx zpih=v{6rg`B2(7I9=bKME`y&>nl#QV;t0$N$-2pruX(-(NRka8nG`~3N_))!a=WZ( z{<`-1gsem^$inLg!?4_pmiu1#K=O55&1m}ch%ejF6wx=+i6<#IF>h$q|7vpeAB?M? z%*}_*j7-en|3#@cAn8Ak4cA#OO-SELkpCc+|NLTH5<$k@Lj=LNCtP#1zAU0F;$?M6 z>O@W86)_cT6DBPsl^$C%A z5VbG1L*-O~eWJ=-GmmHnqo;6FcD(zf_Rud!+bkJv+8>wM2Avlxm zXR^$aM0qQgM)qbKE()VNmPL*Ug&lR4Cc;ODY?Jy_%?i;j6q#cDDt6iO$VVB1OC?i3 z)iG1$I6fy^Jt}BhogI5*Rb(8WHB_aCFC#6c2MSTowUM5}NcB0ccLYDQBP!m!CMqxl zkk`O!#};XKKf$dnE`K#8m4l-btf!k$L7=!jif&vp5KXvgRhFhAU1IVm?WRPgGd4u- zt}oojv_=xv$DW8hA(Sys<7sgtw5l$$kh>3ce=;&jLr2ml@=0x(mQK!%GoTGLadERH z8X_H^j~nqx5-65))!pBGnz$8#uz9ItJmnxG?oP~vaatRLS8BNIxiPXJgMXh=)3|U{ zOHJd#o{su>8S9uBFO69xA3Y3T#U?!)Il~F(7_F(gte>m5Z9LC7huS_LaV3(h?Z4?t zp-mE!yzP-0SxhTnp6dr>=A&KPBYlMKTA~rq#Hd)LPSb?0vkqQhXMObo=`4)Q!i_?; z`_-YX1UGKnSHs{H=_|5cbk)wtcN}-SOia5fpe3eVH6~ZzRl{;MA>6Plk)dz* zMIPr4VJh~%VU^%pg+LRrAJ5fC?3!HJwAqNwYDQidXP+pYsLTvbpcZ!@Z;jR+jOvND9#XDg&fY? zz7c_aGd&o3;+15hg_(J(P7r&brEf*vP9&*06zL}nPD0Y? zuOZSIspA5T^oLIrBV7hCLi}Kp#zqHWMvQH=KfF?Hbi`*78$W>(QyU$pC8jodrAcq2 z{Y~d-qsHL{6(2Jm4=SKut!0+Sd8R4-^~WRo8}sXc?PRui4b|srnX)dn>br=u3BQ#{ zYHWhj^d#5(7FpGp-v=bg%x|$m5;wo~4ZrBcne^6IZaNR^GuBeXVJL&mBo6J&S=iNw{;hCl92RmP}xgE zqOOuFg9%mydtJucFo!y-1RaUHR`ciGHTQV z@`+J1cpnbrE~@Ovm&#x%#(hGPoTAjh;*bU+lE@L#$gx1n5W7G*UzQ`jq!+t4v+~hK z062%$AWuaP=LAg*?2($ByifJKHea*2w<@13?&Um$Yu4jS&Br3=X;z))VCGbF`x{?_ z-eEc%`b7B}L^ScfMiWPqYvQo1iTKhU>K9wwF}AL4Ws?lPgy@jFACb)x-^=ReKTI&M!-={+ zq|^1^_*B%Ea>3`x>pzC38GE{Op@9L)AW~sat z9qY2K5B_y0|2a{Bv1#9`uVAdT@@@Vnph#xf)8Z6ZKY4M>eyxCvZA`#?mb_=9M<%PN z^GU2`p&9M>v_hhz@_C_Sp<;IGbc6d44RBVr*H)aus6KTPqr$j7uub>KaCP*sm4ywsA2E4~;o~FP_IEOMU95C$<%bQpzZea! z+p{pg$Y@YFp{LzBuCh@BzFDW_nPfwHr0F|Zk#TqX8jK4dp1A}Yd&@xKuj>^4HwKcU zipJ$n%9c=*NIXVCdtgdutv^h{&Alzj{!jJ2OMxT79y@p1Y!S+ffKn^RCsw6Zu zwifS>+SdhLiu#{eR>VIH{m*PaUXD324n<4hl`_1cy(1Uig7%E4Y=C~hz49G?8?A;$ zrLEd(XjEF=Nk7glMaQTAUyO5?#qkUi#<|Zr>BqT`<8sh(4z_(+(K}NsNAagXh-8D^ zV5;d~WNNba>wCUYQS!uXn4SW*eHEig*DvhHw*|6fL)_>%8CH!l#GUM2QSxA}MqsWJq`-P0oY9EsDC@>G=;Zfi^qtpMa zbZJWKLS0a4Q>joso0DWZoc}RNx3+dUIFdJajt9BX=e7)Kf;ljbaXsOcCdN%f$3Cfi zmmf|m*nrB8FCDI{fJQfKXMJ?*iDrBWSzg*%dlCsIeoiDv@XfmscdU}lt7gWzPKanx z;5(VEuA&O9l&NV%TT3K0&eu2SDb$Fz8OV}Fv?t?aSRHZq)T!;d6~9#xlBl7+Vwz@Y{}wH zJq3wr0iZ}`BL9d}pc&UJR0h2PUG#%qck-T{*9l#KEmoO-Bb@C~w3%Y10!CtO9E&S*@{&pyrY$)xSmyeQ4$TxYcYjl~#*oy^8g^g%^@({AxZ zh3s|_x+RS(jo_7%sl;aOSlFB6yHaWzSBkXMG_Ex7rjILdl)7ov{}5M3?J|xlqr2%H zWJH|lgt$@)tS7S^JJsr~GBu4W4-jFE6P12?3N@}&0$H-Saz&gBD?}NEeBJb;&Pc=D#^RuG;!rfHxgHv{NzO z0>J4$sp{6#$pRRg-GJUA0Tzk`;60+`^7yR|3}xtYo4pRdUB&{X0LB&{fMz?K0Q4&X z!lB;@UF85Y6M$(0dxg$a0gU}A`^c=r<4I$lI&9T6it|uhkv68(l7UHK@E#`se!C?= zECbL-xSbY&nE+JD>TsFCG(@)~-`y))sN3eVTfm0>PC%IQlCBc{0QL;v< z!(9L|We1g*eE=M6cZvY53lKqeyUlEKNG=D1ot2-aeJ5)FebrdN2u|HL!2gP9*Y{P; z2udg*tpT34$A`fL0pSb4-2fBT4gk$wABD*U&~Ik|{LpR(M+B@@C@Z?`4uEI8K6x8tOimmS=F_toyDjF?LjaHY-@;VR+l&60bE-^^#V|zK)`RN$h)$)0g5H`T)^#+ z09_AYmjL@q5?y#y0MJWYKt_g@v9bUPI8`5cwCGo9j8o^EX_V%Oqxj^f5skW=1BNhH z06NR*^8<9V4Um*PcE7~|&`JXHs9&>a zlRSq6pokV1IFJ`0b3Fin=5PRtz0YlSNCAIr-;)&}3Basc0LL7p0B7-FTz8KI(2EYI z4d7G*X!MSXb}<66oofXcd9Mo~3#|Z%4%n>#QwM0K9={hn*M@2XfQ&|Pfb&zg3j;rf zwa-u8aDZ5-hSz0Q$=V>bH5A>&rU=d?z46L(fS7 z#q4oA0UAt#A;9Kv1J2u#CefT&&EATq0T$8=(9HnAXu$xP4vWnlumFa-#qEJ8B;S-S}0)q}PZ3QGu3`Pp5r2y#$!QSDgg8@Jv`@wNUI{>HQpyRZ8 z0nF3`n1T>-EM5v44%rq2RhQRq2DCqbEeD`D5kTmCZosAsVE96eR4sd2nr6MIy%Zg5 zO4F^{2-klF!d+9`ShF#!Js0lWZI?T2&{p1C1t`rVK$+nj(a2)8~592AvV#-mHq zEI|x6rD+udj5^SPE27yCH40&LS zmto!|4`dRADVU)-Z5UA8F9C8q0G^64!vH8`faYf1D^1&Ow0vxIv?*QNWO8$?TZMp} z*G98oq9%!UKuWX+fDiBu0Bpqb0-wVUvrs3%qGn@kQan!sf3f)hDjsrP8$d)_C8raN z!S3?{bi6Yr!vebkvjmI8*okm%h_pmxh&A{)2rf>o74?k5DWlPz9V(3 z1Ql3B#S@~10J94CUw)@ulwdk(511iPxB?IhBnfih09^Wrr^SHAIiX%Iq<)YB0^Bl$ zI=ckvpigu`Y=a&E^mh!hx|hqtS%~PAAngKhNSOSY1K_?A0J8$fqQetAz81no+BPxp zqY2O@Q?(~UtnM9M1s4SeqD94KYcY%d=z$4@O*GrA0PzYA=7mWkWQI;By?JsloPHm0XH*J21$%D7rMQxCDJBn-^5IfkGF-X=zg0o7Ucwu6 z$hBv?@h^gC3Hq_IE(j3tQKVwJ(c$IH3(w z_4;kqV+0fP0NNVCx9Neb3!-ZhOG*YMBjvi1+=-eI9sh$lC3qjLuAvRaH-t0 z!Du^PDACo(U5z?F6!m6Ztv>HgZ}a-xI=PE5QGHJJ@@1(IvxTEkPGD$|j)@#YCUVe- z%II{s@@-FLbcXPNzG`v}|2;hjoL8PIP}_vMfWv(aZ!Jb`tD>u{3q9D%alqI@lcLe9!9kyjMn?$GsO6BZ!VYqUb?Ga7 zzdGvR_MxUV(SE{#&OI61zSQ?E$@n@Dst(tmu#$%FY zVEJ)>AN6%&9xy!@xBJcz7+5$k8`CiEKStnUxdAg%0$d~~wjV{aIN=KB@xD_vu-)z6 zF&1Gs^OT5v1zNZQ}blD$X(H7!I&UZcii4Y&65syA`UpFsg`czdEs@Vhvf6Yf*VNT6rBq)P4*hMIIqC+30LlF}uM zWv>Ou9KNO}NkJL79Muz+CsYnK5K;`6!>^M`4V`FJ0;z10(ci9XjDC1FIxTaHDpYqg zF@XHS3+fYDXJokD(vv~GQF&XJ&_J9wjC#YrCG%z&gEl0Rq8Yb`vtu_uAKjA8f6^1< z-rU9nzQ+>@s2&L7&G*UMQqXdk{vaLHhIznt5NdH~XBRmALZG*r4cpj>6VQwgqVYSm zG8^?u?l1M>o#HR3$J^0ET#-yny`_L9Cf<_OOYbf9dnI~{F|Wj1lGttC;piw{7>?Vc zPM{4vC2ia`wWQ0h{1lIV6Y$bV(;+DF}5FKt4V$C@SY&{xr8&I`NjH^ zIJw1yS^3ZrI^6N4=4ju^=;=&5JXaF+>Gz|e__Z*WV*R1T+~S1eFqtgV@-~Z2-=YsD8PrCfioPivMVlTh zFKv_TW$y*$9b(tqw&)2?SgFz@lD}_Y9*`7hWifiXbkT2`k~jrYQ<;(tR8porc~aSP z%A#?+u#>5h1CdA~%E+iH9Nk{8I_`mp;FM+cj%Qje z@}D0f^j6JCZ`BRqoicF5UaMaX$FaLmYU+udSaRZt&3fyHj)uJxhYmwtAl`hl}V`1 z<%DT!EhOn;jO}&WGfZvr81Y(W^&dhRLrAP@4(iyndYdqZc~0znG4p`f`JCSJ-9~Il zol(4L+;sL6y_#3^!qZHRq>1O42e^qWTmrh9+^XLMomi03Hj^Qu(_&kz>U)Hj8B&-Q z4?$;JRo|2Wh0%;*^>PiU_Don*A$+8#x-YwWDxo@Fzh5gfwa1GM6S@3}AtD-k8tu%f zKA|b7)5D=8dWhNDR=>#!4Mo*3%Klq3wh8k$QFTKRz0kh;6HP%~6Ym%_f&DLy5xtj) zLIpcPnd_u7Etr}3s*Y|n6ycrXis*~n>KH$gQd3X7hNUK+=oIyyD2j=m$QY~Y71R?A z-=Sgo)ghDNtXJ`v-AD?oDn_{l)ei|lt&U|F2d)hLRZwje%9xj+XF5Zkt3FkELhB2` zQw?7!?fxLcVh!k2y;yi$tptxBh3Htpfd**K*&4I3iFri~>v2?DRNY%oGDg^&Sn!_C z)mLf?>dfP3Y90)uWW+(!UAybYO1e}(!wDZU)e_du-f++<9Almmu0D*t(5`4Y10{wKUq_OO7 zxbY;G-5K7gmffhhdIvw4Qd7$w#8P9+=6azSy{lPlwa$_z*)wF2+O*+2G({xLC!~6J zK*iddtS86$#mDk9>i}@Rd)bmXOS+Z9c~N_Hqx$HL7Zzv5w%Mzj*XJuh5bZ&IHF0l3 zK?us_`s!j=^{d{}gkMf%XHV*@B%+>V`q1hoP53$>(VoUuN#dY5MZU- zDj?Gi_MM-FUzxgy!w@`ybIeoH!msGJ8>*$m(%0TtZ5EoDRR(G4V>ecNHKld@lpF9v zLOsKv>H$g=ilCD(MDSe|7=d8fom-1|JDhV=5pGgf{jkClIJtgc40pQ~=d9hDah zwj6K@=&McDeTDCEH&fRF3#EhP*XmQ%22suC>M7ZVuVO8>RJYF%np@P$h%5CUG`UD< z%RI%-!8f;{51y;uqc1*2=wVQD#Pg6CCRCg`btAwr8x$uOb+W~EZnuH<3?l|vV=yrf zRFM_8doqrcfsx~QuO;qs7>-%MY$Wlx3Ghz!xQrduFY~i0u?)woAtr9-ha;CKgRPj= zgcv8Udv z&Tq#bCh{7)Rug)otU_}6Pu1hw^2dNAnQM(#NHngs!=iVsM=Wwe$^z`Ls*{Hu_KDJs zv6{v;tvMmfsxxN-v{bZz9Tc;ntHFn;qV%#@454%~bw6N=<|M7?zq?TYszG+U(Zl3ng{dw<-mP1YkQTdbg4{P7n^UcXMYOI{_AKW*_YijX());F!pP+RXNlhzSqxJXJ zEJ?D&HtfEdmxWB5+AtWjJc;5P*-+{IHBO-s^Hv=o>Z?x~yKVkJ&6I4zSFzd$YHs3$ zUMiWq?q*{iki-c-1L>YOf%?q*^blAVruz%W01K5;q%c6WzO z<8+g8<4K(EHh8Bx-KS+W^Y{u%O`Wcsr6x`{-KKZC+iV)AGvrX7WE2^{0|v=@Qf|sS zt+;K-T~U*8o$yv!hWNc!=*Yn(bMyU9H=HJhv;Abb!N*O<%dF<_~UpavhJ*6TGmv=3cndIjN4XQwZWZCbQrK6;HM&4iKzTjMX*$+wzlu=VY_aSyZJHWJ=AfbKU-$o9L|b z(fu{)ZTT`FNtUc+HB0cw>tSs5%B(9Akn zRmrI_`$XweRP#;ErZlro9?kfASuv{owq~L567EnMrIqA@+ks|$2f4)#=B1ijY*(K$ z!*iSOA-6Dm6rmr!HTfD6+$1{;Vk$-d3NJRTuK@_El8zSB)qzG-Q{sptd#_y}{KE%h(Hzjdo?UUOKyW zCimmgpK9+BPB0bXUSKpdkFxkZ(U3xnF6C<<;Oo0k9bY?EXz0?IX(8(Uz?a2BQ|2kL z)rKy#HKX=YO>tsZ`35D4U9lBo-L+PwnNJzZaG`=l(LoAlu{rf?b9mu$rb@8#&gheU z^Lq)yn5TrL%PC82al+DggOY?Lwxo`wGRjhanI+oW6!zgoZyua}a35_~j*g{}z z4tLmPXm98I4$Sx2xQXfmM9eAF=5fM8hELtLqy@A!mXZv@%mc>Ep$kc(A4a3!+Yny} zMtfsxi})v9nvwW%+-8zl%OmiP3~ZyH3U!M;-n8~y6MjD>r$g}`mYfX5PrLL(@gpud zsbTjy8nZ1gPZ__9i?kh;y#a_pGdt977rtQ?h6CkE<^l2BZ_qa#YX@lxk^rxMip%Ju z+IyTNx3-6#WQ>rVSn!R!+9FLsY(z|dzi7~FWCQH|rrK>nFQ!5gylu<_!b&gn@BG?j znu59(UNUHbd?GVcA}TGc#cM|7vjE0?9p6V|3^!p0k{HAF@J^k=zS*gE1%EfCrnWGX zr6#s;OCP;0T;E5NmKkzMzmplhL(RGn3G`_hw-#;fQp>_@tcvqXvoc55+A+EO3&3)+ z#iFBBm(R}(I2&NKLNc%-_KDhkad$b_2s*9q|FQSoVNw)Z-*%I?K?%DH5_Xo1#GX7O zK~PWumt+J%m?$hD3ldZ$DS~8nXJ!i)l;FL(X3&dc2F%xhpcpV9V9uh~oW5UG^-Ndy z^vufj{oePVz0Y%Tw!2T&sZ%Fc)hSYaUHRCeNXU(HtbP=*qh+RO&B_QZAsBLcT&SH$ z4m?lGGX1#*Wtjq~+lgX(ZVyTbqMob|WoKP3motEpvM86!YuNEhQ+TX;XlXPL%KHVJ zsITcoA+I263A<1sFU-qo@uq=@SCp;a}A%8)1%hVqHYqlea@s9Oykds$I8 zTeOBwm#kT1Ck+$jgKd!jYBfe_IaFuJ<#y4kbWWc)jFN%gAc_g{x`{h(ru9it1rZgg zd|nR-f`oE?+$MazAp@6F|%8aPp!wl|VLW$UY2+9$ZN`0vMoMVzA#%fbFaH-SyH43NYAe-Mq4>8YquDr0g zhN1aL`?rrxCLjK@d|0jQ)yiJ2>{(fe|8KH4bI+Pf$-e1p8_V_knol$9p+}uY+=7c% zl(5sx+y7m@wuT%=DH&Z7&nKbh%hwlXIV{T#H?!_ihnv|S8HbyjbnJ_R%IpC1v_O#T z*>}8~JRS#xUfI;U{sL^*UEPWdI&{2Mqj>2UY)V|+_i}Q4UPWKIbUqorue`nVA(_6f zypJrq$<6!9-MGZ;;J$K~+@>$dd%3*tBHH$f((yRPvZ9nWwt_XXqI5oXaIGl)5bO9W zN@b*TSCrn5oX3jNHuQV_5VQw>ma_eJUiyojQS#AWY%{o@{$g8ZPp7}wmc7387u(Iz z55HQLvNfsx^dZX^4WPds@akuz>wtP>&l|z^xO1>NdENf$YLR#N7d zcV~P_@{g5wY9cfVM7EvLxR~Jla@RcL=X_InjC^>k{5?b4gU*YMXp156h;z7hhFTa3 zIWW4Skf{IJG*mv+m-Gq6hbwQJ+9m^E9*pBevn%Xm(xnZX73s~jz)D(NSnkUi`d#Xs&LP<31}tSyJ3W<8&A; z^ft6})AoKWL6WU4b~;%H(#9?jkIhB$o-fKvC1s?kw{|+9b`)9w?8_EtI*Lzp(xv9U zBjiUsM?A&UgTN*|`LslZFDRQNfBCvxm6UnHd z7bxYKAD;4E`E`a5=^S;`N35M|7VrUUu*iuXA(n6N$1I3&FiQv3P9KY);>qEM$o?P7 zrwGJ#WemM9j|5Ro_SL64cl!c6IxV=KGphOIu>5ik%m!sP!=|y&dKyVlqs<Umq z`COnN)mw$1=nq7hX`i>bG~2svd7ImkcH7t9r_}GSOA!+qxj#QTEDJA8dSo2OUFetV z5q5OANPwe)B2ZU5axB306^;(eJ^QmWlmdWu*4O|*?}fLCPcnIZs^ReP@cv>RMLCz^ z$Mp);J7QX52ws7&Vual=$j=UkHE5nkQ33*V`CJ(JlK$p2%8>qkCu`02jmvXuNzcUOHJ+;+vBF^ zsYVrDlwJCB0)}C>rw%?QJC8`Mt)SNA0qWUoP)j~;*wzZ_5~ZS>a>xQozPmp^@FE~c zD1!=ovx+mQND{6i#V2VtpyZ+%+2Q3}so;dO^b1j&RE!Z0IO{s4GP7|_9kBz>c>|a_ z5)L@)pj8>5TyXRQ&aDRk8O`V62b??TPZ+&P(={U%X@GuIRM3<+XSAQvlsIp>RV^!Z07DA$1^7Wy=i&nv6xmFwwa z&hnfA2GO2HNo6hCGw>=c+U%IKyjBC&Bzu(r%p`l>0JCJz7?3I1Sx{v~0j%F?+*Z<* z9!JSfKC^$VLsoVPvrM(7?q-z~XeTYi))<*OiBHlaPjPce8~xa`{34$P;oNh20!xZ5 z+7}u6o$NDM(kT;`b2K~n{DnTKzMPr=qd(!y%uefnA#igi9kFhijT_jx;Th)8QHM<( zniff1uUDPmSXq943PtWK9D-FPftF}=bT|+CuwjR4^I%_z{CBdGt4YJ2*VJzURdMD>{3?To7PEMZunV=ri~kZ zmUCRigU=&NDt>9aRY$Wg(GEV(eD( zlG-Xkyi>=mg<)}rzCe7U^TUn{D~v~W3kMo_r^P`1Ta$m&6t8q8c*?~U)8#%Iu*N_= z1z@HGTMaaGP}6}Yqy();k?b|LqMfWO|pSMEIeR++&7S)H5I=!aZc*^y2vL??O4;CY>iYroW-S_5v@3& zd?esNUCM&@^#|0dXqNS!%PXc?ze@I*T=A5o{H}v>0@fR(Pcxg<-^m@N6+aq2G|}%N zjeY_OoPPXhemkMX@+&GzmCnKgM!$B0$VD?M?r9=?DP&N(C|)A~b7N%yt(DeoR0JTR z$GAg{AS3GFGteA(j6>_5N$y-y@q*!VrVENJzU+N{#p#AG z(eMR|n)zk2!_o?yWcbv?h{rOq*BDV4k3f5M8Dm6tbob&jQ#{CS)xLoCZ_R|G@rp5F z`}s#tBkPw}yeXGyz#0!u7l0WLjy==NgQL$hcq^9parU!WzXN(~ug!O<^Ys~f6RJpg z9ET9Mj$3+4^SQ@U*&UL?UfZD1cU8qjvV1=VVBDafJDfjjRNcWLtCOP+-h7@!j;yb6 z^J9v|KR(c({XIy2iV;HGwV=1tKs&3LZf9e8ML$_S2oU401s$X?4Z@W;#;>*_bnBEo9``M8)rlbe4gyJClnq!Lj&8!c)fA(ph97shDE;+{A*XX&4K= za~7;&8vA6NomI~=Fk~-^j5R}c$E&nfBqI*5bjw3EV2vTq7JwN;I?ggPWcRcFhZxeA z8i|=9&t2&pN$y@X!KpdA*+)QJyKCsB;UlwYt47t%pfnk zRdJ}Dd^bR{@m)RbxZsMj41BkYO#0ctcV+y&xLH{dW}Z9o!UJ9R&|ge`ClmX@C-cd_ zeyLb(vrLMmzkH1!m|gR0#Wl)@bV4=vk{XxdWBLP&POhlKlVrKSnoSP8{$z_}i{C5S z%8h>$8svWI_&+NWO5MSF$ILGscyLF{#3iwa{M%VPc_jdvl2;{HYh)GB;MOH9#Wu)| zZF<|9D|}kr*ea!~{+O^X>(+~v%C^CztX`~>1<>Alv73~BW}tiO#}-o{wLxr{BJ{+) zAa-VVv;f289iNYA7+YcZ++;B4TMwx)8EO=pBPmmaCgII>CJmL?5M`$Dlv(g8GfkpYq%BMZDQ_EVE0^9+wjEy8z0eXrZrVCoze|b6nmWKGee#J7<*0EehXrg* z5#if>D5-N}$zPhqu5Bd$KA0s|iu6PIy0NL$Nc_uS(*AwY4#vj5WA*9skAn%_Rap2w zZLrjjY-;JmZ&TLvZ93K>gZ#fqaneK+lUu{tFSeG;CnGKB>x8*BQvf9_cDiDz`iDyI zAzA0L2VSwc)O73NqS)zmq!J3Aar{ds!iQSl!#H$xa&w2+J$0nZSg+(raf?E-b@%FG z;S87#`>hFZ|WrN1nn@g*AvqZ z-pS_-VUr;{hnTsp2m7*Nw^HFuwbG4}N0^Hm4vSe$#^Lm2umIGSn`N7jnXPx{Cj&iW zaY@-O^v=BHD}I>YQ@KNU%7lMAc~OlG&F{uj#sUzcx@Kk34y0?JSWo3qBN$&8-%jrC z6ANZ`G|(}T2JlpIMopQFpBN9fb>)F4g$2!&(rI?N4GUF&N6|gbsu}kEVIyt55@Z1&kqbXrcL4Vv}XC1+A>C@s` z3oNeS-v~qj9P@2D3-g>of_sc4xHCHmsyPYLrz_hJitU%52Y5Co@nWstXE|Usxw-qX ze&pPZMIco3mn-^4qL`YnSmda|5Rhjy)iM4v1_XV>AsRdW`Z@oapk74DPBn zQG8{xN1ln`|An?1m8LjPmsv7xa^N{J6w0)nqt7o>Pg@&*P?wC_9`h(&g;(4YI)_Xj z8XM3=fJx6IIW zW~g3~W|Ji&WBG!6G>rr<{~vLWmKf9u8`C4kF+C_CV^S--_?S{^<$*D=v-9OQ&dIJ- zR%%2)c#c7<95{!2M~~6=%vxm^9jehgx{sptx0K5D!t9Gmg%LnG*D$FK&&@ii_3(;K zs^%WuGbQ#z6S*tkvuTx6w0awzIAnFQ+f}iqr^r6mrL`XMm_c?dkG<1GJ{KU_6v<_2 z5Q8FVe=ei5)PyXlj)^7U>YbaZxn(+Rfyn=bB5A0haqO&IisVZYn=3cDR_`vQ6qtN3 z)t~G8Dey7bd2zjbGT&R2M+R?#YzXi?8rxWv--c}66lmTf(1U;M^nK@{24USv%_W^`ak5bZLcRP7B-eEjANN9U}Ms(llfTEn)S}u!G`im zpq9;FyHg|f@}UOJx^yV_*UD&nX3aWzXr|OhC{BXZpSZvF4`JFfDDb$E0*_>;z=NCu zDSs{5FB$7nM}7P9~#Q~W98@#~@tYw_#gM2dNJsC{*pv6q= zGR?$)p?|+jPsLveI}3U7jm1yJepLDl)7iijceT+5C%Q?0rTO-}Xu{3U#KtH?h346^ z*4g?4Jp@Qz_H67jNx4{m$2I$>&msFZQFzL{%ZrEc)S>vfNh76dwurqk)CU8Nm$YUuP!`>cLL%_My^FB?bmqJWS|AN`w;CZ&&(-@Y7MmM4D>{IV&e zGc`8(WSBuAeTZZX5@9V5&<4#4>EFXL71A^M$f*7QFEU|$HB2b^M1`c&!8SZKt4qGA z9FjLY>!hBFS8P%>fA7euFaJLFW*vM-j?NoVZ0N(}S^YbOslaY*LrTjZW0Pg& zX`xMq-DA^lYDhc};O58~>+07d`+kNC`jYSw!}Dp<@0ZxOnZRXhKkTl&m-+R3zs5c` zd~MQSFJvMK9YwFN9P@i@a)GFkbryd4_t;`ZK2N7EQ@DTXz3U1i`Pd(^d|7EKe9YDx z=D(X?L~K&LtI|q%#k6kI^T;+SZf_#Mr2NP~rFeIxyAgoL^Z;5a$Eyq-F{+MyGrt4b z`bUF$}{PxhSCsEMI- z6P*uebQX!kO`P~7P2#kkeIr#jDqW;t&Uq=#!ZrlVqWD?ciy3&O+l$!^;vdUvHDJwN ztP+5k^E&T5bN+e;u@}VkRTFD$*?yEx*6)BGOS&D&uo#uJ=ECE~;XEQ>WHJ~J^5LWn z#!4l=x}p5mdD#udry9}UIL}}(4xYzUR^cAnpxIzNNXKi;4eX*g30mvK9oS>S?3?Wc zqr%B0hDlXQvQBD4yb|rj!j|!Ab>;4W&t@-rXoVcQa>(lB74To{$$eRu)?R8~GsqY1 z<74W|!vT`bJe-#XF_?!=CEPqTEis#ih9w5`uw?Sm?n*s6Zh_MOg@f8j!{g84OuPy# znKHShTfB|bc#+;+U$S!**{CenpYS!^d%MRkmlu_AKT!DIyo4M`cdL(pDtof->N)k2 zPxOeNBRAQuHx7li$5&8HJiX%%{XGL(gO$y;3Ua;b5X5owZYHaXylZ&eEP$8@UBChvRV%}B@_pDi~TK@NH2=UYII z^~I+t-Hnh#NP#~-lmboi$4eEVJ2uI}#^FdNqT2e9C6|$hPLE%k#e@#)8^0&ZF1;rG z;{Q+r0*=hOUZy_~tgEemybO2X=J|X+hjTh+WpGr~% zvfdB|1N+5K@CrDmYF-IlYd9y$pK!_Fj9}Kx^3=$J%&Fv{5wid5oAQfmLY<5r7Jstt zyFic(`moYPiqDPLEiU~Cf3L1HXV#Q>=_eHT5v`HFMeGXxjCmK{y~A| z8FVsmMEuP9EF4Oe9bkW$%MLu|&8GvUqrI|pH+EDkh_9}3sPWSLkz_`L6|Hd%%Gaaf zBV`miqjd_TBV@+txTnD`>~>8RC}>dn9=0#7K8v#|8Qqp=%+#&r&O2)+7OXrgr zW8i3Y9!aFit?os=fW(T@^*D~VqVx#1cdsa=4Xt1etSG${Q?;V>H+bADO3!D%JJav= zA_ar!K-j*mGwCmO;_)o{i)~#WOnN+vJB4@l7{%nwf`|2{=r2wIvSez!O|s+V@dqX4EBym< zG(of*uzwJqveAut<`ac%m=bpx0GeGF*Dk?sI4V8ml=OoM1Gu3ye!2m`gljX7>t{J| zO#;{FWTm^%zK*6tc*=TJ>&kg`@GW!83_v=ngROw1?&R={_=TAuYT-InxhMCh>Y4w`GiDkyw5ifKu~JJCVA zWPx?=IO-D2Qgd^2DeqP>_&3I?`iYAT-_z+5s5gp_NyLMn#ol;*{E#e%Mzh1Kf*_5_0ANJOg6_=aaqSp&iG1B? zL#V%q;;d=T%rL_$tBiF`vDK8l(V?@j6^#}SS!&Xh3 zfK~N%>*60NZ|h%}t>$7*Z=ns&bixC%QB83z6UtI_Cx3K#yrcY+k^J8q2`G~PTfAcA zXWMJ`R>U{T&BpM#)2M&)m^5_==1!yjFB#PTmQp{RLo2YvnNZ4iw0xDO{Cc31-gj(1 z#()9^%{Ii_lJ&7iIt%A&`T|FQrLt!Ho(gX;6ji+rpErVHmMD1{2uJJ=pTi$e?GAs$ z9pLv=)c6&XZz~L-ABkIo4G;cib1v&|}itO%*;$ zTJGf$cqs$U$hF6hIdxoy(zL43873#ymRnM7DW_U$shHed6@OmdirGh!t)taQZ{gkD z#Nn!wzif*4mgJp`U&dHM+-`&*TW*TqA@2nMGHk-$W1W~gQUIw0+qMSBaLu+x%i_e5 zRn3H>M@x5QJ)7GA6fx;aHq7OmC5sk?I0{8vkw|HNr$kI@#Dhil- zU17U75cWkp4i$A*{h_eO=cb&xqA2%AWamBcQ|0{gv-9a=d~D6g-hamRUER{j^lwP@ zwUx~TPW{P9+3!u1Jz-8wrU=UfHM@LczyCkuqJkQ9zNVn~(jnRH-&;r~+#25@PdGn2 zr#{EK8^?jGlk0DbcbDWV0CCPTYfjx~gdq0YR(bViCit`Utqo|Ktm#5ww-6!HHGNB^0Nqvbgn^D~RnRAlLe#i)wx2?x{&>J*1jJlg9E2SO;aj5@|% zzdIZVbN`^muNY6SMVH1M9chzR(m*@HyXu0}0v)@3<;DxlRY_){5kX7L0MeqC7va>W%mL+^$_j-J(G8ThL@x3uISTZv`5Beu8Z6vgx z8Nrv#OO=t(OVG__BudZBm9$UmnJMG6jj`&IByb23{5lO-i{Muqfwc(!s*4z11TVGh zB5~Vf780=BN$%k+$sEq3#^F3<#7Ok_A4m;H^Y>4AH$F^$6X3?3AG&1UsL}j24p>dz zeK&re{3+{jj8$&0WUUF}s|I9H&yL-+OFDiAWHweyq#+Hg_R2+MX49>GQB}%xBi#cR zvG4vHR_l2*p03CB&Cwkl<(?N)p-FSZX%}bZh%R^q1Ei(YRvn9fF3UqSXpJS#G(u}E z(feYvsB|IQj{l{kP7N0Ep4=93*2QLvID?PDXc2?aP|y|hIGz45uKMt*!4PgL33%)g zuiG05M>UVF#;=$~T!k*PS;Sr1G~al!!6M#pvDqTdpyUzvQT529gcVXcC+xKC(E6q# zmhvLHl4n1U=VL>)IUOcHl0mo!Q)m&qS8*0HvcPn$rJR%po=|oRxM7K9M8Tu_1HIK`$scj7_PwOPWBGi2!KI|G zR{TZ)=L;yp1HHY(7m2jS-#_l|j?!laKKYpTW6dWY;FYfMhs%l1_2oKaxw+6d<)pC& zXpK|8$l#O@EI7pyTh1w#ujr82Hke*Au&O4UEDh>3E%<*>(yqR`@u| z@#)9YX z`X(O8GO6?XB|cEjp~z?gK~-DJ!TJM{GUUMey={`8^-p|SN4Ze{#H``o*9b1O!U--s z5S!Hq{%MNfw62gei<3*E^$a7q#ModOUg@;%I5^QnkyaUKeWMXrqxI}@W?D}hX9#sH zvE^j8e)aY!rmHjjv0Z4_SY_?L6waDIwqxn-Ey>}{iRPr|m_%RM;UqgRNc14zT%5?O zmQPP3>&{O!miE!{X4DYUbyg>>WX=n`-)get>cmKL#RZ8$TB{z`&FJ}w ze!L#Xk6RK0E#IFjy~k*4S$IhAu(!FxX4fVm`>&}bP^s|FzT6xDp=;}mO7A`6A~F!9&ML0HciJa zfluO#i-I1H>JB)(xDd}7bp}+dNIQKIMLKYJODZ2SQ8{mCV!ix*4k}-vA@Qw7qc z+2f63eBi10!eXbxXZQM@DlSR&xIC)E7x71NFQq>ci3U9(uZu0!+iLoV$#HOeb~(OL zqvAx0lpx3B$+p>0+@t&}8wiPcR5Mx#e?wDoX94fOCCk^PS+53Jt}v5q9VeMljPJzU zXG=N6w63Z-peDwT=HRc5W(X$6FLM5})QMYD5R^&+E&oYrSt8_x*BQvT+C;_^7va@u zI_47L{&OuwSgtd{>`I(8fz3yny1FZ|c3#3)&(+)Sa8Pfe1vxw~(V>pt?x5bpD3a?f z_bTMJ6SB|IUD_~C<=r!nVvVV{R%F062}SnfQuO(W{(@t%|LVkmT;C3rd!g%WI{N{0 z*YGXInVRDR)jf->qs1q^<^Jd`TWV@=syEX9dVx{o!U^W&)JgPqdOhAg(ILR-u3=iW`L4-Nt##ZY-|xE2fE7 zpv!Ez&{s5~ESq4+g>OU|Q(A9L)7u3c|!(FJ>^;0|r9gZzAN0tD)D^l+2}u7O%8cL)|Yk ztD&x!8PyQ;BF?%jy8`(^Ltr2Wtk%4U3jmT$@P9Lba4#YZh-_X&9j!9iz{^B0LhgT= zIUwkY0STV(2?}pRL)|xXKp>M0YQ_1Wjl%2pV-3R}#iE7XgQfjYAQ;6~Dj&A0;?izU zkZt(8u_*UfWXC=6*76Q?m`!w>Y9zV)vb5+nd#D%6$(nA%i5n?W4vhbn=;mqt)+oA1 zGN|>giMN>O{+xri+Gu_Kpz#)u1M((jXRY>T2qwC%0g;Whx}_luto2<6YrShE>NO(ENK+8&aw0U)nk-~H$9K^IKbi~BJqlm`jR7BF_=DB}_Q{JG5 zY-+$6w)-5aJ&3KxVRy(M!A9h$%NYmZrjav#F~)$tW;X9ZAKc{r$Nza1pJ)b{v?; zG$m!Fq5yr#*5{YDw9J5|3bD4EB=VZvdXm}T)y1#`gC_wkk)9{6 zl~M(IHLYY5OsGW)4Xf6hm(j9>8OHLe40_Ko(VMy!Qh5#ZUZ|08twwL|UeN4&Hi9oT zK``$^x~~R;uS!E12)-(V;B$-w7s&Hhk`(K63by=V2GNf3aT_GNI24KcJP_@$HxhNZ z{4Sq8>h_1Dk$_hX1e`8y^I(l%QPGzE;Dp(8S{6>+pb_TRNohX=TjAxOCYc?LV@ATf zXX3;YPC8a-9oHz?y#r>+?h(k8Z26o(b_;e(sxJ@Q!_rQ1rk?sbZ{+>v0PW7DA(UA69IvVnp4DxO^k@vJG5|iZzIeCTRZTc$0 zBN_s`H1Z0?+sKk96PNIm!VOO*CdvQKLG!()X2^u65+me8IcWY|8X`sWqrX1TOUfYm z<^X$d*ve&=>;mC|t_hPjJ(GAuQtAiwNz#wro-8~~uaMTkxBUFI2&5nKEzSy*zHYFI z0Ey#=ybjOvi8~aB8Ft_kPDKimzAq&D8*tRS8*Bzq=^1f~36~rtgBCy9n{0jstKbh9i95n}zy3hyA^M9g zRbx*`>)kDqOI}Tkm6WISPt6OnUucvUT1$?4Em0;buLwYl583(rw}hu@K9pV|^WFqo zWPl7TD!1olftY$IF)b5EbW>6|0tweIZ%?$Q(5V?*ir zPQs;h$O7{4JBdx1APg~A7Ldk=6A=T5iNC+fq%z-eA&_04L^A0;#^1D9I_jeA{Ziiq zb_qqmn!PW?E1kWYA4O$|dPfrzP}`n0pt1N&V*?tCPY5v<7joR#Nq;P1JR@z5E8FL5 z`6|tefAafQ?C&S)$jT;xglsO3w12WbS@7F>hjNSXN}t0`c3FYc zK_6T#ik<0t>RBrwX%lJvNn&PZKfhi4lutR71!UN#i9QApwn63APZPH*p9>)R29+(J zB`TUwv@lhyVq!KP7lfo99&W6ltaEe1VabaDp zT(K})xw!D$FBuoI%GzDS1})o(;$Y2&?eR)y!`r_~tdj?7z}ty**OSBZjIbI9o)$JM z+4f=XyYL&T3IwDDN%;%h*CJK!+#FX(rKFjJbLytM7cWl@fN#V|D&HpVljZ9%hHOcT z)*4+GbI9uCpzjmc)RE(C*w*`DyP83qKVu9g); zkc%Vcz@lA5lM`*fPq0qq&61x;bt@-Y2LBgmU3oZMHNg^lKeDH8;8fhGdI^tSdOpdf$R%n?#2&6$prjwl!bEMG@0~8{S*1%Gv?1?82O46j| zDNRe3CHosz(!H=|9+k^8=)KlR@8nO7Dxa66JF*jenufq_X@cKL&LCTxR37H#?aP`} zww5H++e*>iGG3WuYDJ7!4xdu_94US)zX>^ZO67j(g}*W(i_+~GCgdL(6S6kKeN^$L zHGzgq4-^Uy1U*2C4{!I9cbZqalwXB;gh?Jz@RR;Phad}ERDPs1it2N2+6cd1!&-pm z+y8_IdUI(-RGCuUdMWWPQG+4sNc*%lM8$Ze8zOe$>KPia<_q;R0&AA2ThwfcilYWg zWQjA|1ZcB-l^)KP)Nst~Dor6fXBw*AL{rFXM(EK~E1zjCUkCiN8KGM>5-;MA)yewq z%1LeH7#p&+5lUUZkOnzCs`BR6@+|<#W`xFSwR;yuMfSsWEWke_aUIp@rdc6@IE?$U z@Y3Yz86qv+ytjv$Li_nRxxFF#+dkHm+mQXuKY@p2LU8o7AaM` zJPmT&+{#i(9t{vore(VQ^;9op$yJr~80wM__Vki2XR2KY1@h@@{W$MmoW|d;wkFS# z4Du}GgEY;X-$IK71XAh9@?$2JuhRNgZXo(- z=^FBZ^kCTG=F5y&i97u+<)caYxXE2BD}9aR1wb#`(z>FRsl8@$D&@_ttDQHQojGn9 zq79mhu3tJi({f)zk@`EHYF!NxN+C-s>`YVPz;pNIn$kNt5mLL$k{6Q7i|WWP0X&;& zx**jzhs1foO_k5pkq@&TtxeNJGsuiBmHq0-UjZbWX_}e_5lxf)EGM;me+FCKX+h^| z6P-`EK1oSQ3Jp^JQYB9MSxHv1@jojcmy`}u^hssm{-}-j`;_j&)3k8Q9j1_#w^hEB z33JAU`EAM8>dFpEzifc*Zm(Qw05qwER2gOgSAI0A*BzDbC>IFLGAx^Z{p9J&c;P9- za`BxHE9Ch*E5~I5uwh+c3Gn`1l|ci53AI$2XA!l(ps}teqhH%j*AgM*Bjv=Dl(u35 zUO_Rj_8HgVmF_bp?ydY%zDEPrbk?0lU`=O{DdzmyIx>1^WxKzvveuYY)=2rVaWrom z5fatan|w5Bb+z;U%F7zbzf8%lt|~R={c(yxUHxYYza!!ZZP2W)-lQXKYr50b(A8vg zzo!N#Cp}Y{&~7&C@l56G5;C)B#!l9MytIR5*!`KQndH^aRjPHQsT^$U?Dg#}L+&5a zU^nfR*H8^b}P*^7o90d1oEG_8hbNEf2PJd3G%1g+_Yhp8iL6D{HC-e zJv@aBl$I7+9^|aA)le`t%Nn5vIi-6|jaZ)O%*$+qs;$GyZejH7Fz2(v1E#FlVb0y9 zmWMe{&TJL~Ww_D9oYLDS+$>LZHnnJkpX!|PN@cSK(&x01%Z2lt`4#|Luk<{p^sA{? zON#W#Y=kFxjdV^azcb#hyh~|0Rc95@W<){0{y?8UOkiJU@6V$JrD`-9YY=ziUW*FFoKVKhH-fwOc@345c2OYTkr#>(orWA|S~_c;SIS z^&THrR$F^MLYvw!?uhPt!9DckqB*_5{TI0^kjL;f)4x47?&NHVOxYHU{ z%AK7oU(xwsi_NpB{!b^r^+A;z2esCSmguUi;)6=ND(`+@*{y+mH}K0AS?zf*0Okv-Ft0%K)r72-;zN68}aI*!sKx+EI*Xgpun$?RtfnXnZia1z z{y^`L{$d7h0@=Ixp%%#&Dj6*+Rr;q)8weGNCTjd6w#L1VZye-FNvReAf`J!pU47yikEy~05&@;nW*x_^CBPVEh%pa&6*bTLKcv0vz|C= zosBo2o)QvNuQ;7_l7G}#UJKv3EeEDXBX7`#|!KM)G)E zEt+k6!y=8~s01^d&~+M`L#9Ophm*Es(u|e1mS@s7&EC%Gs5? z5+>i866=kWSd*O+D>)@n-cGX72y#t5`7Xd`b9bK8dcU1RRwo-=K=SL$kFhSTGs$n6 zL1N>`qF_N8D<7sX+iDfCTgF!gR?hHZsy<==Vs178}WN( zRtHH?savK`HFbCjB>lliU1-LK$h1zDujofi`zd*tX{|h0n=;0ymOe_;JZ?RWtua_u zo~s9kwY0qXnXue7xjI7LQu^ws6Xu$nB|OkwlfGq^u1TxRwlOw_7c0+oF~`f&BWY~` z%RQ0{CX?xT^5tcg<++M1z_cz|d9HamNO4vsEO$bTbWQ2Z#j|z&`t?`;>Lgc|8A8bz zC6%>)U5{5FgH{su=p3?3zE=a*{E@qiz?yp9P-f=-^%#$^L}!gDb4aXT4Z6zGA(0QE zU1Of(b&j*>krXW;%gG;C)7?4GVDbNJ0cXJ-k-sQ2r#N2Mu+}yx2&i!{M0g-b%qR0L zah2K;`(lIh)Osc(uL;#>h~oxe>BP&_vR=;{C4y z;*VrO99LUg(0O}q#Ixwocb8ey`BO8xA7w%JNS*KMldU%rKk3^OIRBXi=ie-G{%B^V zofin4gO!sjSCTf8(tQ?KQF97*tRhv4LwKNXU1qmGcb`Q@AHS=$0mkH6E;}*()p#wb zEU>g|B)OJco5hPicO99gOcC&;CayTDKhOm>%~ut9r2GN7MRMSJ(o|OF>ED{&__#I# zu{rL>zf(c>NXiWYD0Aa?EIp$xc_~g@${OL7?#tgmE=`d61~}~IxJ21v^>q{4Jk&DX z9)3wHGVoQhiJVTzS_8O==9QTkbDJR!L034*4UAz~rf$Mb@X4QA%;)IBk}fl3pcjd}Y=lHNq=2kxo9&zL`vw$UQr6ZArFXwX8mQZwtvM122sACimPz3dsJG zvp9f z1>5;bo`P*g$!ZQt8eN&Gtm@OL`8z?$?E?2(^TI>}FO1L53u8Giq+$~Cd^Krjn{wsE zaA4NdiBqn;a!#bUnEk#oG-FmI&*}2Hd}MFe<}FTEdplGoDl6r=Rfkt)&l=NbF1OE@ z=kzA^6>5C zax9jAsnPx_PB`pKzmuFzMqNzm7EwBl7l}50;{P|Q=}3RS zvL)M~O|U^*CF`fGZ18`JO-E@pC1GFE^x37Y##xmB{>el_VUIXW!0M-q`TzcpxbWV4 zNa6o30~V$vAbvx9NgVgDp9V6NZl+WmW2uPhYS&0##g$8{So|EWh~&VPX45m)LJM7F z(n2R5tbdeNLwq&D(rl6AJ4vPTs?ZtpT=we^EIgM2h1jPo4Rp%=RT~A$Puqs^8KoB2 z-IlR>u|_guiwvHvC;XzrTgL01GT~{w?jep{q*}?Ft!s1^uQwMSFt>;;CFISvjMuwm zwhfvv+*rKc1wjXLWtQ=JcMDh^ufLtd#q_dgwq?BD+X77MlEv$1^DZq(k-EfOASL&` zga`VZl16)V-)o<3S0_0#+u(ZzDXFY|uZegCGHCI7=@Vp~yifzy;`RAPV9ocse70Et zCSp8-?`4fC^}TGCuhPEPc(T*^FRM^Zu0{{W$o-!jds8@k1DW^?8AQS}usPvz0edYb zwtuy`7ml!+DpCD&cBU60Aj(4?;ek&6O@d(vDEQ+m5JlNEAJ=Z5D=MS-=X zpYa08wx#^h7sz!=i#a+HR0$L`)gK5L-}NHNla==RJ9D^lm4>kh&cYS)ZoQ}SlIOil z-jI|&0z8XZMjapn6tD1<$z}17;R^ZW0J%C7VEwz7*CiFNkaLxxR!~XTs{}jN#ePgd z$~BpIa>|N`>&!p>wX~pAeh7cQjO;wd{CWH9dxzvv6s)DB6tB`!lHB(?iAgAV%3w7q zS!M+0QiAg0%?=T9XI<$WgOFHb$pRG1S7{+xL-n#DKw;x~C^a6oEA;^*PU4Ee{d_>_ z_+|Mkn8{Z|($?13R>_t#Opn!at{vD; zntD6+Fy6L1miluy{qvK<{Li*L3hDM9jY9rE_rzk2*C;W@SRPZU)Y#?~Qv7~;`9pqr z4v#V(p~Nvq8TZf0)DJr-f&WgFu})xLs|l4G%{3_U`g60gXdS#_EUF#;Z1oW-Cbzv> zfPnL3(u%zNF{YyEYtoQ3|CqF{pXXA2UN?FCBhr$*fBU)uvToeA`t|&7zpI!8X5Zg} zlzl?#lGvPo6_WMiw$-bLpv2)Odej5C?``<59(oMq@vzEXE}mKPfp&4TQT=9-kEVLMq5d`A-UMh#fAg_TBN&11YS zg8Kib18Y@M>0h@B%rIgh&x|=vX?a1 z>>}>5m@t97+(i@~=nfZo{AcotQg@y{xh4;>abq5l3edUym_@&mg~iqQ1>s6(T&@*!jJL(T~ER&!7Mpo2ST>3l0YLBdYr{)V$<*E~JQ6Yjiftr1Ze93x^U;ekHdv@g}Z zG3;hF`L)4@v9_?=6^J^c9>3d-i<$kXi|h7<9Zp|Bb=XzAKRM{RjWg=nqK;?)1~lSy zIlL~f!+`?Wo~YC7w}<>5Z#0-}|K7b@q$0Z=cRHgow%zH*wdM9m!0iq>!>TVFa=Ywa z^39qx1ba`uu03V)Oaz;Yi5ucSnJyJ>(3!L&1nM z;D|aftVoy~kFLp2s*dI3>lV3HHR5x5J&}mVWp}ATuhZ#^dY#dzH|UADllXGCWK*Ml zuNtx2T}UgsoE{%;IrKQa0Z%CG3wv<&;qm@et&&@P%WsoxxqC*!vgir5*qggoCuwGT zLM0PgZ#butA$uh3bh$t!+(+zDBYt1N<8U}!;iUbS4VVspFcNY)RG%8~xiD$& zU_=GVK93()BZSmI68PGi9+_i&Y*+2_g$9TqI;S=_-Bbp=%wJmy9*M6WxD z%F8HZ5)Hci5eEoNq$V3uvl9$ORj&gdxP2(i914UZc8Aa552$vBKLU5G@!I_4H^Vlp zk{0EjA$JG#J9O08i6tWk4>@mQZpL(*zV_rMoUg-#p2g(pWy=eSYZ#fA?ETk<(`5aHzu_jC$>Mhtm;+{P~=i z&DopSY+hQ|hI=|7R}MS4+3yOugML-@yP{FQ+o6WsDzwHwj_r}!xt(yrLzwf3-{lHB z0zrq{84cr}o&c`iCWE>xFG!YMyzwrnUG9GE=dQ8W)FU}Mf1{oBINQfXu!?#O(qSK*-_o`n(>*G+|F5IWu%@M%{K!2kH+8Ln^8fdtG4+ zC+v%O9BM!f`caKI(D}B)SnUM>raCMe(5<8~}aq1SdHB z9s&ws-}rlze@2gHtHch}(6}kLC*zI*e$#`83chnbj2JH?g+@LS)c9NNA zRuv?hZr^Z+RGhnauZLT;+&#Oz+^R8Y3wTkxD&mczQ)+ahu)yvp<^|fz4o4$-)Ug99 zkdD_0^WgRRTq>=01tE30d|rD1Rj;4|dv1i)efr*NshtNC?ZSn`PN&o5$D*GLlM?j> zpn{;9$T!h7rzVg5=NQJEyI*2ov<R&fPB?hlgA{c|+IU4tHp)t*b#K0{rlBoav!*j?I;X0BQ83^OMP2S7rpo0D zxcyK%5vS^gH{!F0LYl`CQK?l8!}*H(U7m2zABN-T33E{{9xBgfaknd1@%BIfGbL0Vl}bzX4|eKU#cL%zIfL!%;x#|5L~ z@dq$Puvmd86nYS%7zn^T1(OFR!~4RLY{(gL!ch4!@tz1+7&gJ<4LO1iZ@`}ne6?W@ z6g)T*M%wL#gtI>NY!0)AMSdtY0h+yoagcc(5UY_{B;f`6!$F5a=GF*&>h zJ_kg>t9s!>c|1NBgeu?(23^ibB;tZQ5pj^?uWf{aySE%3vDb_0)j=3vuM=;AxHiuf zjJjYjFn*sSx$Uzmc*G7|l;OhPE*JhEa(I1F_#1AjZgH^&tp1WS*0!P|2ieTsar={R zv)e+s`y_TR4BMmAt86MR-0AIdPnn%|CY{c(I}nK=%6a&*- zeQ3r=1h*>S+CL`>=u!UkhhVfp6qso!`s9JF&@<)OhUawz&y~qxZV-2y&eB?1pE$|4xbwl1#XM82a`v)EPq_Gv*P7db{iED%1y0*)uxom!+uB9EBKAY zHS~{Zqw!`9T}P;8_K<<=t4?d+w)-8u-5yf5zN%%BI~Z~X>?-cc#Oxrzgwy19B1(gX za7M5l=W2Kei<>+#zHU3*eH9L<5vRwFtO3Fps3&;F2nW3Ip~>E*RfWkTXDnYSEy_Jh zs!_Z`Ia$(W5=JH z8KUV6Y=%N;3Aaj(BoRs?hoB;QL*N#K0`wx!;0RDA#jYzvK*5kBnnVCZGa(*0$lz8r zfRILYhF~2+0VF{@h)n|aAXT?46M~SYhHf=c%iSxSJemoCs5K)m-d<(1`P_btAQ*&> zi$dHGromP@5$QtpM?-!-DK=y`fTl~w+#ny4|)u_zJ^A(jiN zK93U$(St}K;EV>Kf9wG`Xxt6sPH+ufyEP{`ch^kReB_<`s=7At`yKY)2pOoT*#iEc z9pRye-Vy;%L-mL4aGxOX$n|(bQ67KpxS1Mgg!fJ`4^lx<_{*x#?}Uh|LAL|0N;o7Y zMRHG;(hlsJrGRl7jUmJch_o!nzKgodWURRrO$2OJWDhNg~303Jm0o2^ygIH<~?E9k+EagawRoPPwFt^jh`@Z=-m zD2?c#-A?sRKP(-bid8+~Fz&K(K~IKNOtKwbKb&mXA2bp2LrK!$;hQ_k;X}g5vBN3F z^!i;6*gDni#((@sjeuli+X6bhG!)(YU-KVII^Jg#zxSeNUGT*o-h)S zzz+T&FoRi*V6u?rP8o&(OmiTLd;`3-2omK!Xosi=IUZaJ81W^g9&ja#aKEq{PIc6a zC?57A5P(5&*pc*eIgn{hV$NX+bN9!s0iv{={gGzR1OF>}W68qdcTu{6&%6)}SBNe# zz~@5dKN^586jKKtr^DeyZa)lj4dk6cEV;lp!-Ydgq(tmV#9qLUYMYQB4vUJ!2$YM@ zj)Wc@I3F?;P=s2*>01sEUtB|{%r*9qJ!3a^>gn*FmOpU8v6Uew<7zmL#vuJ7m+?6WTBokpnp-ZB$szHB*nhK8tX)h*q4@9aEgu_?C!YDKXjIYlR$HnJ! z1j5LXhT*yKeEyDco9>c|LUwxq%a0M&8-;@cHdnzo%<9d){8&ny+8jTme}4fHxSXRyiDk!l0{=0Y5?}mpjDNk>(N?=kD08 z#cnx!M#h7uNtzaH?9{{O6C}eslCm_6~y=_J?{~<02oj7s$0Cw}d=DZm5Sh zY!6^74(^UYn8Ua66hW_0HHmo6jomMH%pf+vBBzR!78VJ}=!ce{nq2Q$i|7+sE7;`# zThxKH`y&BAbO;qxEO9uvOI$;rd~q#zmr<5mWmc_2Z)b0pSCBGaz-h-yD;8I15&#}D z+>WTz6F`a-@v`V4*K~RJH~o>0EdK2n>{`x=F{M0e;L41cEhovs)U0(NKMlMs-&WJe zQfq7VkWGw_fU2WDRRD@I?85FWmXpL{57u-esw03?lCTqCVK|9VSaKfL>{{-=-Q2F#)OR{!D+-2!o}dd0 z4v`?jPV8O+14h7*s)}VmyRf8<$iRcd5W+NS5!_ywkPvJ-(&*uc2fHiC-ZJDq)*oL3 zKJ_5Qhg^jZD{Dw+(nUh-X+XGuAPP>AkR>V3-MzM^U1Qh!G8^+Lv17tbmwnxCiYekP zKdcvskBmRo*tM-qEMwl5=3^l`5d;J-gqH!h$WVk>Hui^uL~XjGkZ&R>a=NjL&W$Vu zi&`Dn7-RQg*)AAHVCc5<9K4pG%-y-R7Jw)*d&fRxyVzO)+{z9;UA}$JG?II2 z+44ec!N@T%YWMlJE!Z+}s4t3~A{K)&wOFPKIuOWW{mS9d7K5>-gTTKVO+6x>cvC42*+Jx*co3Ki7)tSm|*-D>%o5H#sUc35tWi{y`Vt{ z_TF)))DG6f>2rkq_9*tLd42u>btgk~5gf}V$pZ_qYEYEBPg30IMu#nTk6|HI0&fwt zj9?`V32;xCt_+5tA-q^ikHQ1flprEV7wj@NXkn?she*dCh4bmPBfgG!aoH%_(!=&? z!7U4h{dVY27C43s6 zYKK<{U(G{yeudRD*fg4hMDXiyIl?fjSX~MS==R@e7|sy3FJNu@c4Tb1Ma$iBD)C=a z&n$<>693qkibZy;7lvWcAn#aSb2=T^t8k@LqwF;YTMr@_dIDpX-1@?IwR59If5tPYc-9 zZt}0)V?IwT2$%WcY{l zWa}%N`bZCv{jY3tHTcKah9|9V7bY)0`DNQi@zO!#@MoVgVz2nJCHeK(@l&N8B=G8{ z;nFSS?pHT;==JR7c(2Tz5}DU)R-|mktl9C>AE)9`<7t6lWLhtF4e6Ef(y!^W9>o6P z@m?*LU4h>x&zLiN+LXww^cM@sz=NBLr4R`m+|*XOlq@{B>9m3-xCm*rLNDj+HD!9> z@(5b0H-|iWa8sB1#kj^{bs_oYBW@n#`YRulD}9ds`i1`bH~lqcI{tZ{{$iI=zd(OUW!>=ai}WYE;_W5+ zi`^@?kN#p8fV@n9b;M=m@!KvW`%mxFqakG^+)@!I&4x5Qhn(`prh$z=q8~9m z-YG8`@xJf`@90%#s{?&zPcNhYk4~8uo$H<(=tFO-z-e|AunFTJZ6F$Sqb?FV>u6U| zlh+eO8D=jI3X(||?Py7g>)hOsjM(yMebVO5O=VL2|FQSpaZw!a1MqhjP-L+K8XG8B zVnMLC*rLV;*2LIiutl+Jtg)biief>5QMo&=a3?YLwsygis9$T0X(mxqO=3-=#uR<0 z-OlXXF2=9F&-?!I<{vy~=9zi=^Gsbe?bB>UuI@Jj4p0RBDTe+8qdz6lpEBrADEd== z1~~Y6cC+p>`cDA*6NvsO=uZjsr!@K#g8r0)e@4(RZuLa!kH5n98zKjN%cPq>`8djb zXwnZ;DuKHd=hO)^AU5&0>0tikj0!-#lHIS|HD7MP27zFEo7lE~@P}HpU%3tv`UU1M zl7FaG6JZhs|4d2z0P9R5DoLF}H3(NF!cjqf)Qj^1QSVS7r$BmSN);(j9ey?Yc%U3N z13R4#+9z4lMm#_Ni-D^*vMZG7itxkoM!(?L2Y__w=M=N=TKtTN^`?kUj1g;OU#8)1S z8e@G4A^hMe0O{wmLP5-L*#Lk^UxDy7 z;J2dHE%&nz$;ww;FZbG7;>$2JULc^KlWu!ns8%}c6V@92B21kDuK(t)sCIdj9Vsaf zSPLNZSCRDh%RlU|>z~;#OTi^(GPMB-UuO1F!dMBG1c>pMgX9u3LC3$dyC__H%+|7u zp2}qWpqZfR>J{zGXn_{ki<1Rqf=(8bCN3Qo$(Jxzctscq75o;EmfBtfJtLDFD4jT@ z5nH$s>JqeGW-Vr5Y45IMX)GyySuvP6*z&qEh$}#f2$J60uYk(3<<(%W?F=AAuc-=F z&2QrmYQ>g{QN|mB)$_C1bweOcjASf}_Qeg`F8rkKhJ2^A2uP(YmBF=$vSHvtSV}ne zF<90|jBg)cesx=@IxE1kSdy|xAFJLCu96wCI+|llBLhIkpDC3k_zKpgw~XyP(*k!QMOvj53HDJyB}-}?%g@sPvM|MFEW78!VgLKem2;0M3SDE@_mp2 zAX0e~?3b0a)Rd-!($^2h$yH|QzV}#h7UPv zuSZZc)(IR3unKV;;1A!OuVDF7-lOOGP7WAzJ;#UZV3zKicRbo`V8rl9!zx4x4skgU z6Ycx2P<1FZ-|MOQhC@i8<{F_!`vUBLyC?4olI3@B0>gbYmHDAO!s#coK-F*HM{{R^ zdv4GY{!{zLXh~~K50&_WFY{J_kX8bcYKk%}- zFk^DGwA3P=t2QXvb#tV=SWO0+@cB-UwtYI9vpKdoG;Nd%xj);jluTO z$><~I*fj56-xetafr8$a$}r^PZ!;I2tpNc+E&X8?R?A)+7u8Znbg)E8;K-HaV0Cy0 zOROYCl76V8kKp>jdpjPtB>8N;KLVXT;iYPiI(tBa+H0nCN@MWdCeMlgPG08sVKsZ|wjBplv3 z(e^aLkxP$4S$f3r1f+MfOni#)2Y`YRp&{V?xMO3(4f7tansiGh-{_n@Kl!M#fujVc zLAk7e)8Ry22B+SzlnCa)>EtDQ zb#e#gEu&8SU}Mm7O>!i7=a+#cbt9t*45u;+e9@gj9H1e?y_y}Ds&jxB2EgF3Vva5_ zFGGkKtIrZbBFVJW1DVOMNb&{>P5oXj2aOeI)g009Et#Y9d;gOHfl4DR4@?r=njPWfXT%E*g zBaDnCUK3Vn4nzHVqNSuHccRc#;xBX1Na9j`;FxR)31*2<&AGk;=b6SvM;;^Guu3Bb zE(Redo;#fBu$C-lqN8;qK^g43|pm~WIWyYT?Bcs*b*qq10jh1yY(!^Eh3Xtzv(<|J>L07qj@0V(dzD; zc~v0|bQ2AZDL69<ts#Y9wo29BvkSy!^Z;;=fwj zSl&Q^y^(+eCXryCPb7fCkQP;vb^^y&%W9k8Scs5gR~ifXqK}ZzdC{dp?!U^iwu<}{ z#28K~4TW5dvi}DHnWs+OYI!+a{u2{vEaYV(NX&W5|U8i-EF-}(so+&>WV zQ{2}ZV1D%0XfR}MRuiRV5|k{RBjE7Zj1@5bP$%BCydW!GSRGobtq$_XSsN<7xKb?( z@`G)`_37~uIv^o;8RhhA<@s z8YT0k%#J}EF2c<703k$M6Po?VVhfbNgqRgy-K&bhf=Jvv%Hq$Hyo*Ay+tOOdpCpl0 zp<}2+aaHI*5((4%g2i5h6t`f}_8FIj;%0EN78xLwhD)_pZR%ZOzNsV?ScN4?&38e7 zwS=Ek52OcLhZtJ#Njhw80+^?U6tgDzNv+X+(%o`1LQB5dgts@05V58BzwCB2= z&6K6An9D&HfNmky(FzA6CKY$Ip*14tnnK%9YqH|xx)oLW z&>~JkqcuIGBRVBIh=wzE2m4@^<_^@5^42So^eF+R?%*;9jNL(jkNEb@|G#ku0sg!- zAVTE81vnkSJk!7kU(m(wK&MXystR= zf3hUM4Ldap^1~=LlSp@Y>e^^)uAiKO@h}eZ;{_1V{e$HC>brHV{Unf7!de0>|8ieZ zwMQfC97)cE{g|b9v$TG6j$=HLh&*6{=s0>Ch@%JM&~rJCL7F@Ya~$=WS!+wdr`TxJ zalElLr}sWaV+2|pjRSQ9uilga33pzMP`IH* z|Fcx1K;s4RKWb1bYgbA6lN&>DKxsyx|G)vQCg;iaZO`fcl$>ig$+>cFWVKK#FVqmk zdv4(sSOLqqG%vRnOsa4sM9ptwEhj5=SW_+qYsi&qDVSVmA-J_WXO#{{$iUW9!g&mU zG%;s*DC?0!38XH37j1<~Blq@@2Q1XNseTB;*x~ktRZxy=K*GsAFRIfzTH8zV6bel} z?nDk6d)z?_MZNF4Q0H-Zl-bBQ0W+-9__;~vaWN?_Jt=k$86g9+5>hme`$HG&=YjGO zh#Jhm40nrmQx+ctv3;y)w+JO*@Q|Q1+}g678+9l8TkAq!f4d%`#2NTA``ay?qHk$v|6OzXZxQ;v{#JeQHS2GFQb~|7(OL=QcS(EMFr9i#2MahDlkd2Fv?asTk-r&)QPH@1tV33^@Oj z!1-s-$sTH~$EH<J;aiVpn0tD;HDZeX6xoF}YTXxsU2j`CA=aUt_K0S1XZvscPu|Ez6Za9g1G6NQ$qQ@p*oMLjSH&~Lwj-wY@mKRQ zVPYM8mSI5Czc^rhQ@PBFS^6iP1x43d-3kXI=4}@>bTs9m^TuZDtiLI@xNZd>c*zJ7 zFJl{$1S)1@w}4hTLB5(3B?m3i*;LU*rZ(jdtFUvxd;YU6)`fm@B!#B#A%cU(?jd*) zmM3=-#2+N=w^ou9={lz|mjA##{HSvejGjJvdU|pg33*H$p-1x((JpI~V)BGV<}=4% zD6_{d(#;%4FTyj&uvbxsqK}9}^j6U=NOwgzJ&%j{nG-tiA{ZB3dM?<_xnLz+(EP-i ztuS`UMOf|EcoV-^}JHYy!&xx-G>@>4;)7{ACPsTAWG^Cq;qWPu_GGDI6Y_&tC$Cn3#=vm zCHR?Y1WX;k8yqll08&>_aKakG*?)VG@bUkJ{VyycYCfhVT}R6b4jsYzml0Yt>u-C~ znjau-M&QP)n`xBG8y9oNUkz+OXRRu4SWG;?8q}%i0hS?(^&Vge!s~fFKnf>vLq1&B z@!>0TK3pMu(CmNGMQbTZ`Wt~4GMmY#uo79~sbxJ#rp6cWF~k(BqD^Pc5S@us;m|@%@u()n>yFj*lGH z5Ps3KIs9nrh$hX^7v128WJkhpM>c^UvW!tLe6%T7lIy2}i=8t<*s1oofTAQ1sFJEF zAiJCtsRgko24fSXGt-YYlAEUDd@I@rZHbP+%M*i+02l69Ln5ArI_T9km$_T%S-U~WnxeGPhx#g^`13Uc?Ffz7})NfwcbA% zsZWV=wTAx*&pQ(^jeIYccp8ZB;7hdOG`JwpD=s4hZ0nw3cDCn_U#vfx-I>F;cd_Dl zZ|~y&h_`nSH64g3MdVINJc4f&rahI`jKqPdU_#N<3Ps+AaA{q@{NL`uLr4#-P5p+= z3IuJp9j_)iK;?(l2`jMPLYw6D}e)Ol(m>Mk{L zJuVrGpx8y*CGfwA_}FVI`h~C0EJeTYDcWV|7d|?ehJN8QSj*8bcyOfVe-c-qpLkbp zCHjR|pH`t?INM4`zuZgMy;whZtr47$kF5&V6!O${JC0ZKQ!o5wbq2_8qWT>))lVDx z{5LTp$~X}QIJrQ-V0Peh2~*#KXzcD(atYI<4qw9jZu$4IV90;n#liH$x0-@GZXf zpxkD~Xe{bI&$LYGDSfXhitT+#;UK~MO1Ah)a9I6~OKx}&yC5fwT)0%0k_(r`muk!- z$XRb4yAaR)-McJE3SHMWuL?+&_T*)De zn86J|Z&;>rEs%887hbTHl@u#ijA`FCbz~F8&6Q%>t>DKBwnX37Nfm7k6xFwNa3!HN z;#4FPGrd~LAq7c;7D=vF%IBBj*jGby0ErBg-l*h2K~i;Fm>OBdwn37wE(I4Kq>rl1 z+S7}aT>DhAz~*z2(tzdSMN0X8A(*u%VV~;;i!z)mFc4)|AYBiM26soK3|2}n6O1h8 zO6j1`60DTLgCDEe#+X!%jM&0jNwX=Wc^?>a+#8EFF1&SgfI>d6|%gd zEO%apxy@7j=51zVzR*~$)% z-8cv!frf8orED1V3*Qcehet*yCp@LmVjz8+Tp8|T;5$nA{?>Ut1J7_Q5Eyt0R$&Gf zOig(x-_Wz}I}Q%B?xGLtPA${zWEheI5Z59Nt29c}ArjhYH%3VLG_NL9ZT@Y?pfpoO zCZgDiph=A#LW!m4Av9%j7{T~Dq6_VY2<`U1=OFoN>L__=m~$~tt7&U zWD+>uwoNST$Q#ZayrG^7c@04X@yD16qckSqD`z9jxiFM)L0hP(v^eEKF*zB+!-Y!j zCM4s+CuH#X1Tar+7iXIrBxm9gdmBRhC_toHQXr?@5JJBw!N&N@3qhPMy$Cs%a9T

pl@LV$>k#rBF`Oha@D`)!wD!Q`E5X;xGKv z43w431mk7_)}ZVh<*h>$u4)E^IFL$mRF9}Jlhdb8P0hskiNRCC5$0+DPp4u?P2$bc z9OX%^rm7$vw~$!-9l;@Cg`Lr9%F|WeLSOyi5h^hiUgSGX1?ubxhxI;+ouMo?FsnJ>>^wiC0(JOoW=c%O_k5wP^J$)h^0KO)Y96rDi}Z6WMVDeLGVH z1&UIrsR2~=K1!$PPL%)(o~@ciYJzGp5o&4%_>a~8$7UYabat+)s=bA+ngQOEb)JUKQ=wWZWYr9= z4EGbt>RJ-CkX184>CbhRTB@*nkWa3f=B1bG>A76hDu{oh>Kf^)OI_D-QDy3zr`j@O zwO0goJLLa%9KvSJfPhOI;S(VVPYA6UV3F+#rX$@?iwQ5UErin=K-+&q$s&@$vEnI2 z)(r6U9+y65T9y^<68a=hC3$b>wpQ&P1ujr6s__j{++L^HXJRJ0(M;xg_?4|@(wGIR zmzV4+yh-mYP@R4GHypaIA&-S>T%f3g^cp~`xRzHhP$5)zJAQ%s+MCWSRF(Y2Oh~Vn zlUk@2))s-#T{9r90aCW9<0fJ`C1<_-7ZE6>={Ysp_P##Ihu_^1{XiPANNwoV%4AK?@|GwVj!f~42bt7+P*QiC2ehhL>I2d zJ5|h5bQ^s(s}LQS&|l9eLyf*F6Vr`se~Fe zD*CLKzk9aNPZ7#r{Di{#Fs)vz)&`0| zSgQe)ozAU$g_>X%uV{s~dQUA{vlc1i;?*$-ZT0-x6!fAiWyX5tTSHugyP5&{^&LAs zd-B9F={&BB@>#09K`r*uyKS^{gX$T?zfs&9^fS7MrfgP=P~2i7wAQcEssgn!Km@{M zUA+;PR6K2S*7T#8msLM${MtZ>tamh`v}L6XQa7SOO9(<~Jt&?F=LIQie-R6f^#iK5 zNo~@0!e8AaksFphCV6zkL-?y_HKv$N2uKQ8#KK!$kIKKO*6EOirTPon^P*a#Ll#o% zsMcI~FG!h&ilfj`Goaj-aVab&6l(dZ!a~i!$ z?H07^Rn-;azQiHC+2D^uE5jccyrKrtKigFxJ$XxcdJAiI-7d8EMU}8_^@>1t>?RfN zFTTQ-eV+7)A;;cL{a#fRAOa!8p3s#%j_J?`>j7VM!i4>9H~R2%ts6!o4k;fm zp}@|k*qv&n4nxSV%lELQu)}NU=_CxHzFyyh>(iD(c~nI&iduA^y z4TC6dKl(B875?jZYVd~2_9Cw2RNDTA>g>nAQKUD}M=czO=XSv!^$bc=OoRfv`XD;H zTg{e&3>C4EUo)T`<Gj2Pojpq)rJ5O2*tH; z8prUwHW7B~sWfU23QSCd(Yp0mirt5Jq%1@%G}aLrx-PQ!tDdy&ZA@Xg?=k~o8tbVP zvrpygfP}cZ=6E`@9|1|hNI=3-eV&r`s|DIlSgFG^*>0iElh9BzAWw62o}L_1zSYEE z=%*Q=^fXr#^?o@$DpW(gZgOFl(9i>FKrH`8Vf(F>DXZVJ(x`DLy zZ55z>h01!vOc{{fdaf)=JBsH;IIUlpRVwU(6n_P+RU!~d>&vJUjQDPUgzqJ_5GqDO zYt4Yt!GWo_)k^N+!n}po`sO_8UER)7E8-`_)@v#Hef6Rl+agrwc0yF6%HS#T-$&fg%waYXI$=z=PhQ1{LVLBWj>F7Zz)u4b<;rtTm<;sa}+J0&R5b zO6Bb@-a=yi0$un}teKnwTaNYFqA}+#SeWl=-TBhR=s_I1>DRmF}9VEB6#8Geo zwJi3+SzWk^pObkqxM;BuRi|&J*i){gaoLB8i!f9(NORx5r+xxmJEFRpqq&#}TXp~K zHh1LAbQj8M2DoE!#N|%vgz}9MZ=tMafQ46PR_4Ts_+DQ$FH@zHs=L<}erC4Q_>-!m zFaJiB^uvneNi{Q6R6<(KfB@!F;)J+H^z3QXN%v7=A=K3jk_VSXH(mB(A=K5IDCJ}2 z)PV|VHN$@bl@>29!e9OE9?ta)>58aO*e2jsOd#I`syYN&q zz_DEB^vQT@5&3pX`%KOCF5QCv&=W0c$2!yAa z0pTs8e&^Ah@;gI-D21ZB>@jnEyMXB_zXE7SA*W`5<1+2&b52#zj>1aazlaW8PQ0;s8f&gke8eI*dQ^78JWG0_PP^(HF3fVE2z2F&`1p3iZ2lPB_Po^=Mol2K+dw!*G|S*s2W z|3Za$?crJ+M>$_$nBm{3L^6k&oQ&}~8B?d?FLT$+|E=P4LB*L2`(h^0#wv2ax1r$<-RZtX7Q)RnKY-RoK+jMQhY%80~? zbLe4Q+=YpHCIx@1wrOMGp8oJBZJhM2nnZ=Cu}UV!LOjiYLf%XsU*nCB9~bQ?jMHm= z*7J45(g&N9@zIzQiL3BU``+NmI_l5VYQE_}F%YI{09DP#h@gJLTk`H}s-mx)k~G(iOEG3mEn2`Y&o0A`^2Vp&n?^`JdDqx^ok;kWe!q`FmVW zpuohq5-J8lN6i3(gD!*F@+1a`fe=%d`wL$!t0I4q2q*O`^!JbIlokjZ^#D5elX}giAZVaXc>H?goSAqnI3YN~cqeX0e*HNA#PZmRcm@`PoY0m(by zO5S`Pv$S65rWv5$=hDyCqnAV>l+*e6$E;saE;4Y5Sg58M;P;x#Zw_tyMS1F!2d{-Tm%5VtLG{e$@oFt%Qa6Ek6+W`NlQw;A0x zl&=m*NT?Y~S%5UPM1|r(l~9CBKPDs z^)0W161r)Ce&g7tFvq(8056<}*EaRlK?(EpUE2Danx%6toYM^d$@zlc-8mNm>YKFX zp)2RYH+?9Uwm$s7b1p>F4FAbF0{m~zg>QNzHT*-(s4GPwOw$bT4FvIK#^hA=)Y;Rg zVSQH&z(y!cWbBXa-yA=Ki7-W@>zS{FfRNBLX3#W`MQVf8u-fFV)&h&eFD^AOBKKeEB!x zuDy<`JyLx`MJ0693=&<*U)V=ZdW_}sQ;$?|pjZeSHGqmIp=(Qeq#8ywvJWm|Buvx* zw-M3b*dh?6P*8(9{BJc>M=FHV42X0nxgxDgZ%k=k9xYm&gmfBf+5f1K+DT}p8Q?U) za;ilw{&mG8B-6i8-+x{42)#4|T>83QDx{`P&d5wnHDeNjX%EVKjAhUXk5zz9v=B?r zWa+4?k|3d!WPYIT^{<;l1FR>GrX$FMWojk%zx?}7S zjc`kk8$}*oC4FgrnG)afBJPupzM`R5%#^ZB>~z)$fd8(q_psozF{UYq?il6bn|~k zGF1BsZ}iGMI#a2nDwkHG=6jT62yHY23ad94R*z84MkZQekA803kU^nKv!RrjDLIZk(L_k>G?48bB%SN}{PSu%u2r)DRaxheCkA4U&3Dwmg^w9h1Nnpu{KnX;Mp#e0dE~3fyDQQe9 zq{Nqwl`jd>84y)QBG=Pe0mhue_E&=U`N-l>UULp~yXa*!{v`&&l z0z)%hLKJ%ddovg>fC6PKOLKf|y*pQNGS|BvhuhF)Ul60Ll z;e`g!_ialhujixo{@Ow)q5-rjp_IippBUk$1+zqhDq7cqq@zn%Nw7|%a74E_rfYnE znCsaSa_BVrJgj7twi8ez`q-;lBqR_H18Vug}{+FE#^JwKIBfSwL7 z@zdE8{^v848eZ~@76|9_4|F`-^+XBHv&RK@ zRxD}b!@toVe@4NPC8>d;5k6>uZY_nolKiPvWC_m31$C^XErc2xpexL6k#x|A&=$fD z4WK6tP+@Kh=7LXT@<(=A}U?V zK|qRvibz#Kkq$OQieRUS3Mvqo4G9Ve?{m(~9s=+8mp^8AKXc|x*_qwVy?f6i)kt(` zqObFr&RGRWT5o?^`eI@6o7R%MfZmBUO+w^{F@x!5tf?8s z`{>Mhs+8a4N|%$1`s6nQ!d7y>@hce`^LC@W^m~3&O%O_4rosix%&cM{VWM}_)&gdX z1rijxK9!9#6D*K$&{JqroS7OeMI;b3Cuk_1r;C^#RO!PT2y|1}@T(ePBhjEIB96A1 zV+%fT=dJHV+qO%f z=y`NA-psemkZ{nG5-6&q>6Pw|FL@FZ z8gVp6mNUKRl@cbx`jA-AOKEKhGtdHw{(OgWlr%%EQwjBayc(S-W_r2HEFQDPr-Xa{ zsyf}Q44<7!;m#sh!acuQQ<_2FlrmW?mJrY7YKbFiSQ=we-r&bIOf-w&2CA-0VY(|I^0lre*>4~gJx>d};%rq{BvCcC8)!1-GJhc2RR z6ld`-@tfy2knworJ}~R>WJcOLBo=c_ z*YqVGbtzGq@h@+J8Es2Q{N(}9$l&Hl|Hi0PAn}*~qmh-(M0-9Z;PNrLQQ3^LYe0f5 zBcbwfvIZJbQVrbuPgXJ6qs4`US>^<*cr-;-H+?9vD(=~mDKVC3(uk_&d220El{ta+ zL~Gslvm1GBTP3t|q0uz0nwepVgi-D>j>mKm#a;g!&+6h=LML+qH$$x(zGX*ArUX#t z1ex^f4{eK6d?{0f+g;Fl%|02+H~VCoUkMZ9at)KiHddl1U!x2)%_wUp@se{*;ki7_ z5($x9YpPwkiM33G?Uh7G<^(l%=jL?HF@BU=nGz;>_Y8X_7(Xg$;E2)V@d>B2RKg?A zm~H1ao^OZZekmCeA(>uDw_dDbgJepaP|zCbRb_VrAX9RLY}%n9o5 zMG5sy$JkMWljPMPk%5sKBn&bV%8=dGP&;xsp5`S_q8}qrYJJns&O3>9jD!+0JLB9M z@mNYotYakfO-^T!cicdZb}YFP=a>^23^b?%m2GIEtZ#{PjO3wjTGPFr7jo8pReps@+FgDXLdBi^)mWt;d@OoA74f)17Avs*gP&;ga4 zKZ&i(N&3tLe<<+F&;Z9*MrJ=gHytRpsmW<;li#DE0l5&qf+-HXuYn2SJbaRlFvz7{t0Vw2 zCn%q7#7Mjom^6Aa-aO-JBB*6Fx}~9*2H`{1ClFYk~u*x ze%MqpF(%w*a6o3M{K-}(A!H9fR-C2UtxSn9-bX_|rXj6NqiD&I*vXv0OI;e(3ZH7! ze>E|8&Vb}f1Z7T;Tb*;E0RI%uhh$3pjv@w;kFoMAe zJQZ#2W%9n3l#{M>FnJ`Fa#TPHymu87h!Z?$Z7bg~ceuqIds+P4Z(}-z-s1*jyGh;J zn)+dU0H;6E>b7QNv}8#vWlqp)%)-)77ompjOyjJQDY29jXZrl2fkzBkYE>V&%k&~aJU)!4=r3FZ|WKK|BcKjM<;K=bweTNSo*l#S> zpje=-0~5{Iu$$a){Mehemw7rb-A*(Kg3$cyRH=iR79j=_Ou0E;lo@3pl3X4kOp`j8 zniSs=>r)IQo-!w>a15?j*Pys;0m+qc%F#I}VQ{+QWhI_+gtd@J$`z@8C)|l` zjXCjq^yaj`lNn>1AiGWT1#`=Y6**sdq;OXvxpN3gp33s{|)r$yP38*-A9{}ErF1KEJa&-;UsY& zWXvMTkPyf{>A^Fmm#tQUA9I3gyK1$i=+hqfSV@XV_~Q`}sqKVMx+--s)i^H;RqBb) z0>war9(&ZTCoY@>(+QNzC^E-xf^g~tX^A|KzR z&ArTM>t13Wa{~8M{)hVzn%mnHw&Nsmkdf#()uwE9JLmO>Ljoa}p@byU-}Xh~9wQ`t zk_qOJMoPqEPB8aIV`e=z&#+dzhJVZJivuFiy6W9?(&;{?d?Yi>y&6m1`|77&?^cqo zcEHJ6_*u7t(NaXhA#;L`^reRuiD$bN%PJNU4tXbC>x&Oj1V|j@f}QAkU){*ccOkK-{b8`>1V2jNLYscRKCBdRfzY|widQ+VIv0)9XzDpC|qKl(X9SvXb3Kb z{D0-G{-%Bw-baDKrbYwsk>|Yu_~$?}B{cF| zy{JJaTo)=0GWBWnKvU2bl$gkzpx{tiG{_`MG-O*);vmxiYTwfqY@b#9NgU+H^y(n9 z(gF#2{3BHwY$g{K3kh<}3A~068#$6c-WiR1u4EpeV}s3rkbk*%sZ@Q4sTs-p=-og& z9KGq+=X;c(w4tUbeLlqGi563df6NJdc28$fbEt`q5DSTfTw$7R?!qCaI*rcTljHA7 zuEay;M25((p?17vN<3svkQw5?3?VtGlo-HgN_ev2u*katXf5xfwG(V>yU>g(J&V%m z0j3Z&9As@WyDdLu8E)$4U7F4RZI75s z_+(D(y=e6Lo?&c|HGl{?X#k!F0hfDnnH+-)^q zG4hdLV*;(cd^Ie>T1YtMu{3`ao|vSF1X6Ce-cG-VMdnWH73qpdOyxr~Z?q};c(cDB zZ5o6u<*uxy{9{bnEWD2{ypDy?_j%kLIm9v^h{Z&LE60CKo5z^e(LyAmGAHO=eHt?k z|Dn|zYqHr)iK5I2G8@=Tj-i~*I+N(hpX^`O107vE!Qg%N?|T>aYm(r}QHLpNoM{&! zHA%eW1xIM#^SE;z7~LngtwUlYbAmeBaUD%5$9UY%rHq6~<^-9ITmv@u$&pnuB|vfl zO&M?6*cv1za`ZP`XDu82I4-1bq|KAS$V*O8qltbV2S(1}#zjIRb3%BE!c*4-Q`Z)g zpvd=6+hQCPIl}f`!XfXah7(OY+foUH%n4fB*tT?Ek)#~XT;d=oSRxi*{F53@LiH!6_lvZhlZeIlDCv3A z$=XSX;=I>*7PT)Z-I9>RoS+ezCgAl|cTU$**(s)Th>eRw?Si;8-2Jg%zDNdG9~bNe zrX!gj`xU1BQ}O)YC%In)?p0Dk;ugP1Wv80H{I4Jc={REXyj#nrnKsLA_2aLC1xu{r zoAh8R9##ZMXkt##oOagvf@!9rbs_sxk-QJ{yVkrhEqcK; z#!3|viDP^fKlGYmTIJ!d-EpU&L z90^*?3357ePD{EPKM-1Hk}ENbIq`E_(Wi+6v)cM3T5<8*l;cIy$#z8o74M*tFXG8X z%1emimieg8EYptmzGy=IF_OTNBJS9heB?6j;TZqcCpiga&|sT{hDhb6W*Rhw%Xg!2LFZn%u5&NXARN}hxlZbo4gMH%wbN@icDksj>HQVY3vID9a}BL zw`dZJYQg*vD%cv&o^|Goh=NYl@K9R#)$q)boQaxx*_ygh!kiJ1G~w)W^YE$2gN3GS zv^bDJ#hjp)YSwK3b0fm3&mxmEWDD2Vfi5n>?e?`rreqicxE(+Tfzo9U4EdE!cTnrs zOqEF9ht+Ufc@Op)Pn%ye^`gZ}f*EsyDm!atQEIRl_ZP8{z{b6)_hNj$FF;}%Usy@o zmzY)((>P~9xI{DN1g@S*=jyllW0?ft4m7u2*6$0ghu+Xx$3)RJ0I@ZOjR(srzWD zLe@gU9CHGT`spl&uQY|TiVul+yn>dmG?hZ|!5POmKEBcv3FCdVX+8b3(lm~ioJkz( zm=ic_Ob=G#u`;*{56zM(k&Y8+?)vo1v?#Bttkv|t^+suUtojo?;I_C8!sD3jJ-;9 z{%u@Yc^^)%S*M8re{{kkx0p(Q`AP&C0c;QNah5+ zXh9uHOe;h`Z!s}+Kkrm1r4*W$CFF1RIDx+0XsSi>K0Ib3_p+zh{=giqh$K3@37#8Em8MoAF)3$M2i6)V9{m(2(5H zXo}iw@`MH+nv4nc@5wK1Hq|5f0KN;_9`>hovD1rD;%5B&e|`bJJDs}CdOrfk& zO5!koNOiWDK^8~^=1KJa7SkuhU5=x-ntGAE54R<)+ax-*6>FW~zrleiEN&oeiZ9#jls3*zG1qIYy|h zvaKywMgEojvlaLa-Z2w~_8*29=Qt>x6kI@Ew&Pn7**`(^wwn&t;q>#N6jkPW1&Y~W z+F6w4*HB74{X$dPvIAE)DUtb7C@m^~J%I{;VCq^_`L|GNSn+ygq7O`*_4^8~*@yMLP|e~inD*wm)|AN&3aCe!)dCV@JCVydOD zp=UaGr6~VylRKTy0x?-f4xALPZw-jo+cbE$DUq&*ytHYzDQBJ9YDR^f_nDWh>7F~G)ZpZcm1*04)7hez z?_$~=#sgZN1NemMVH1XgeZb9`zaZS!7jqDg5Q6e94!8C7K8O?W6=HXz9vwzwUb$SF_8vyR8KK`t=*D3z1u@9- z!1a6R5z{VI(9hx2_X}KW{yKuEHX%<(hCP9QZnyupB%byUT$Pz3zr=qu2R<`htdpHl zVHAJyrOK4}x#?)pLR2i>|M7EE$|7w`!WX7==pAle)IzRm+W%ckA3HSHR)pIMHhzgZ zk8#m=N{7+S-b-R>@G*R}(cmjQr7=hMe#gavR{w(kJP&+n5bfwI)FwqT<)VFG;j>yf z_=fHu!@m;skDBf_H(vo-ebl^dbMMhpUz;U1V@+x5d)(mb?qgVP|6koL)BCPSe;mXA zDi15@l-_p(qHpkICAm^TJF0RVXI4)28tQZ0yd1if`xak^ZX7rLBKZIv%CcN;QuwT9 z_1c_^8}`gWktZ=-Up-;Ugou528hr*!@ahTEEKI<26~ZVm{CWX;`lK0VQTvKvbn-S{ za0)qPp0dTBrTO3CBlO9qOcx6-(UtFTc@F*7^s?Xq1->;)?EW@7`n{<^bxxaSY%BBD zp;f2Np!7|yP7ThOvesT2)#kDGTs&hMJ=UHf-=dOvxfQ3=TvnGn(`_Yt_yuiGAVf5=cbT#TH z)87_7M~Ub0#@Mc(%m{0}A=wzJ zNtE!b>12(MbZ~>S?^n~&8tNa=MH{LA21Q(!~_ zZ)UhfoBM^)_PR@3Q`GOKNrV(zI|&z(f;DK-r>o;=>hHK+3qC^eSMiYa{+^S z9T!QuZVH7l!AvvbV^!cyY3)mPMlVUp4;bc=ZjIU_0{hgANaW|FgTc78`>M59&e1ko4!%R+h!+YCikD7*g_`&tERMME%=`NDxX@fD9Ld8YQOgd{!b9*rL zMLO{ZJ`ZT%nOfGKXqsn+T6aTVaceIw#k5P;7P1#x2W2yc#t9Nzb)%9i4d6n{P97f3z%@*OcDPWoRalEp>(Z#_4z0@+-q%}d`A!RpoL?y_=C}z4rKA3wV5+$dtR?1 zjmYY`b9_xI)%IE@XA^%owy(6@S?5X!SqcIuY}!iME~aSYCU?+`b2qgwy;j$x1zjq zwg6Axij*nZtMq@&VHy$bRj{@)i91>6cK(*6B00S}*11lvbveCa7U?9uk<+VY%gHRO zLH%O<7Rw|qN4sOZ2G&AmaxYt>%+EsfLN2eE1u`)^S?@Xn6LNc{ZMMw7wsv2pTuJ&l zx0l=6>xqoa;}x+;r(gFxUVe*o`YlzY)9+LsuatEz)6cDKnR(^tg}i<%WcoF-hIi?o zyq?>andc^ePP(7+dDX3{OuAasF4l{+BVnhRn>{kaMun{5Yi2TCjPt5exBOm_NCvoK zmRccqkfwAh){Cc&`MnZhVtU~eF4Rr1QZg3sp0cGU(&~aNNmlP^C1uoK`1-$vT zz~zhX%Km;F&iljadW0V0s>ASW(EAT9kXJO4_tC&+ zwt@9%ObIU+9Vz6M2^Fghmngn8no~R;OIyf6np@hdOFQDdo?!w)uY}Q_dYfBP@4{Xu zi$?v4f7}Lau1l$fy&e{|zmDsDspO`#s)*OrqVYGwsL;Qg%TunR-e~K51I;Pw{b~1i zP*i#EdAe21Yiq$hI$GYVPqT`9&shfx(!!`<#jS&ALSQwrA~>A~N0sgzeEeTN6x4C(7kTbXt-DgHrJKEJSvhZl1=80K?7npKEn8N5_)7&`%cN52;TpRyof|-{j zt41yFHJkkb)oSDogWv(K;8Oi-G{3gj%kE2GM?KcDId!}^n=KuyW%uvU^*UaU^nIFW zGo(9pD5M_duvDOZ`mCPU(Ar3!-mv@9oj#Pkf!Fe}KE2bxD{pP2Pn9T3L#!V0sU7>e zp*O_ZNXMSH`_d<9;5EV^$_lST4I6u7!+0O(?>6mj?6pt7_9t7j*Qsx3JkcCzf}Tma zEC_ht8LOvHQ?I`@!MDm?ycU$Bnb*w%JR&yp-m&{zXiQhHJq4P36Q!=e+a~_ur#MJ-tD+tc~}U1#eP=w%+{+G4!g0KQZ^2u9TrSE>OYVUQ2qr9VU|G z{Y{nHdzbD0P|DE9>qpZPy}cG}+tsLpmpy}RX3iS)ps$xmZ+G;E;a!UC3H79w4S+AZkOTXC*X$~ zL;JFnjkCJiA5Z1-8A?o>aLV@D<)`V`0Izr?BNUut3*z&Lq}_$6&_LWHAAaCcm1Yn0 z+F7ukIt;@-I&zTrk_Ge04D*Il=wNS<^*`XLaEj{uX$#sj7!R@HJqp zdLooOZZ4Af8&w+V)uP2iy&4uAqLV{?XAx-Zjkorcp&Ny<$d`L~&GH*C8^AB70yxo^Zb*9@Ryebw*%M$IrG%AkX8i{{9q@=d& z{zz{~XaK*Hc_Q!`B~HMFeb*?jd>8`^?B{fCls7<*0-v?VD*ky-Rhm26>m4E`KBAkW zy_aovO4o48FlaBw6Y-i^RIy7qHCVPcFJ&9+jkP8AP}@mfWBOvO_pG(4jAFe$+}oVy zjl&R$*G24U-`>&`Gu~@u(N&=PU+yhHGsfexC02Xs!gz0(-Itb+x2AqGmreAlg#N<) z%G8g{Xs;TLnuz}c{$LXIm22zg6Y-!g?)#7~|>kENg)8^nFQ_*6VZh*Ky`1-&9P zXR24#0%=}tyyS=f1Y~5&;Wt>5z1lQk8Xmp3@mMYS*wy;sG_O*+TB}f8(5s!kYS(3{ z)wMt>oD%XeJ4&M&)4hJ-ypN%%vWl)v$K#V^Eu0)q*S<_HMg3-Yjji=|YB&oI$luNI z+FF~9Q!yaNlB-hh7rg!!ef45EH9Ve-o7qg<@5EEg%e3z$JZ*e5(`#xSCDVhMc+Py- zgy!_=i5+LLa~_BuvL{=2W@x?KWsaT;_kMq^&aMN#lE`ukO{G+lk!Yis?)&*fWCg@{18 zx#18;XV>>>@+;o5N2}?NQvbv8o>$SGhmJ?vuaE8`q^H+D@&ntd39IC4TbIV{Jd~e) zn&TCH?E9-ybMeH>#t59`zQ3A3*Bfck;^pBqrQP8~dU~Fh_}EuD=jY*xR|=M<2J^j_ z(|vhWiT<09Tc~78a}p?Nf!F>qpCJqJS;#{NjcMLOd@dln~Tmby4zUE=T{dXU|`^Wh=ZAh=Au6r|DOYWDg5G zvW|Zud=B)m5#^}sax5qTdJ#Oc9RCXlD*i<{-Mp7vhPu7(^|Kd*%wN*M*S(n$k{|vR zMxg*?K~{MMX!r`Rn=RG_m(wvBZ&adtD{$V#QrbK0F|X%WdUe%n;ZfNML}IAvIrG5*W=#WBj9ueDpR?)aRj3itNb@I1%G1e3Z)BEa;5vpbsQ_ zhJWN|zsO)a+q1+o>}Su1da4j9@QUUSj*$F03LZoXn5Q5rr+@_t>J|{NNI}hb0gDy5 zN|!NM%&n+d4C<+9#_K+jR;=`o0)Lbi4{s>QSzEvw1&QqhtWz*5QNUXYc61c5K|y#I z0q;0~{%7tbWTTqQ?k!-Gf+vy$Y*sM5kASTTX7v@YT|xf-0zOdCZnA)n6#VuagJ58n z5*`l>$8HAed4P6I7qHg{GCuqLqd?1-CHtU)X$u4#Rxo6#fX@`1Tp{2K1;N<$LcUTm zaHD{)75u$Tz&8r=?G|uCLFOX@PAOP^RKRHkIZq4tPJ!#%k1}O9aA#RN9KHXAO&CaL z&-q7zIzLJF1qN%`{QMBN3KF_FoE0Ux$4Vzu;0bJXt(k zR}ckRNtC&vfORGTjDl8o1f(c9dS5`Qf>93y+*U9gzlws7e+2}&<##g(xvM5!GYR-l zK_EoH0|gtx1Z04YqV4?`;R2pia6OBF%nHh66A;Sab*`2b*LnSAVe&Z>sKas7viU%U zFw#E?tcjBBXa%FJeJ%wnqs1bxf>V&Egva~}pmNEepaWQce_C=28`}!VU9!m<__E-D zt=CFjayysXYD%hC*YGk5TvN*{a80eGz&14)sG`KRwYmb=)>;Z&Q|mJLnHvHnOm1oe zAIN|;@{j!NrVI|VeUH3i-@*q&f_&9)0fLr<^bpe5H<5ny_m2WQpO)-F3O=eTV5ou$)ddV!aK4s+Q3}4S zDPXLEe;8o>O;A$GmU&je_ZB>_;On~LWSW9p7R*p^*n$@o%xWk_W-CaoFW^-Hvi_E!auA%D4GNmu zGVdyQqLo-|Qn0JFfGr9#Sg>8eRtr8<&@oYp>|zj<39+iZklkwXlr`C_pi@V&IH2H- z4gwA7;Ut}9^qP_+G~0=KGC6u3o|rob(u ze-(UGH7HK*DRJxQfdaRVGD2R@E>*XVGAodEv?LIwz)hO03fwZvuD~s$sD=FeCo{mU zqZl=D>nM)`w~k^JxOEh#z%8SA1#TG?Rp6FU2?ZYn?J6m)#I2)p3fwxXsKBkG$_jWL z;Y?Ih;FeKM1#Z>UQQ%fh{e?k)SlzN|q$Y0JG*#f1O$!BX)jXxZt(vw9+^R`b;8sm1 z1wprLx+rnWrn>^SY=YNjf1t7bX_eh3N5QwVx9(s=)*oeJ=t0+vVxcwYgFqXKMEz;dVn+Z3=8D!>i}EPD#@p#oMp z1=z_TD7|N4Q;?6s9|C<}vv{H-P| z3<_{f0qcSSBr9MsP=K2XSO*lqQ@{eC0Jjvd^d~@?4}t+!`ULsMCjplB1h}Jsl{^9N zDPRRpfcpwqwiDn9h-%qUXW34Gj0#w`6CjfUmhA)xhA3glPLMDK?$l*v@Cl#GR!77l zyAR}C=J1aKtk?+$(F$0e6Cg$b>v96*RxmvHm5{tjSalO7u?kpd6QFm36t6iTpjfotm8@xT^EanK9EWq^O48dlkmeL zIB3S;HiM1-ihWBTi2YOkQ6R{ImMG9h2}@T3v{S&Ul>mtfoXbuO(ti}t#RpPHH~%QW zs+Dl?i~?4z1n3D6v>sTY5~R19uofji9|f#E3D8dgYfSf2B`hHclaUHoJQ85E0v3-17|Y-!kMM{n0TX;6y`SVC1z05#_LCK`N+iJZ z0_6W6mWc$JswS)u2@q7kqL2VH6tEm5z)S_K0SPcm0Si9@%vQi^j{vVIV6{iS|IJat z3XcHu6tK1EBLZAdkh`^Af4?eW{X>}irhr8c0sde>JU&TJ3;5Fq(%HZLqW}vY z!v2~9RyhPnR=~=J05=85`eRK)5Km25(-7d60+uucNK?R)h5-L4U@=30I|{}@yb$1? z0v0a>xUYa^3wixL0qr2$H`Xl#$f$r73js1IV3k6E5C+LS9Gi~|2xoAGff*$r!Ur-w z+5ICwJBq>GOiy6_)f_DaVjQuL-nspw0P7Q?#=Htxl@K6S0jm%K6i~pjg8&5;u+AVr zyaJXJ1Ss+v-+$2zw0(+@Vrs(jfiNkd;77;@0+dp~dVv6C6tGkvKsg1h5eQI$!7Z-k zjoAVcd|*HStKuI9SRD`rswrS`K!6$wSP&4PmI4+41gN8c1poo+DPX-nfCdU!@DHF7 zK+v{}CH_E~s0oYv0W?#D_{{lfT0RlJr7`*0#?fd7@=UD1)~`p;NEB2W!K+0pGfZ~_(uU&&4Y(Y z3Ro}?V6p;M$^&>_0W0GHOjW>=cmP2Ktb_+J!vU;6*1rRpsV1y^2QW(k%iRIYR=^r} z0Iw)uVLO013Ru$)V4ecjvIAJ4fK}}H{=>Rq=U`0BBO$u0x z4q&qaR-psfs(@AK0JbY&5jubm0D`umEIkMEk(#jd9KbFGEHwx4i2~M`1Nc+{%gO=l zRlqWG0Q(ty#N)#vWB`YJfZ@RB???Q@0Bgk||8oT_5C`z30v3b=II4hE-~f&(U=cWg z;|f>=4&bDMOb~$s_*Q_dKNf)lIin`5{|4~A0@i;6_)!5%zXANLfVJKL&MIJmH-PgB zSk(>Sq5_t3cmh&kw&5(b z#_KPm64qLSNhSp>vIY>MfHl3?|hTutpg` zO$Dq=22fi8OOgT9RlpKt0QD8H`WQe%1uQ%U(0DO_{-3_H&Di8U?tPYqV$#wF()*|U zqX0{f!9yDbtT_hIP63OK0VFD5!7+f23?$^(nKmJ^{yH;RA&aS}m~``jRQim66kw4t zc<8Bs1;zk+D_~VIfIbRXQVgJ<0+tj57~lZ<&q87#gVcmI!~ljUVC^t~fC3f_0~oG= zrNRJ4DqxW?fYAzABn)7z0#*s*^*3G#%YwmVq5_r!19(;e3xEMUr+}ru0H!El=`Vn3 z3Rvz7V7da9`2u*s0$zVC@dfgtny{c3z)K2P&sfF-*C<||;a zE`Ws!Sf-2bKd&iaT`rg`QNS`>0Lv7x_7=c$1uVJ+utEWgZUL-Pz#3Zss}-=c7Qk8o z_WlF;ERZ+Vge9{8)+=DiEP%HautXNXy9!t$3*bEkERhB9z5-Un0@(5p?6dcuZAw`6 z3MM-gu-+BGhYDEl3Sg%K*0=)rSOIHX0qj=5>Q(@I6tKD#z&-{+S$8aN1#&=5Sk4OI zkOEe)0yv_86{`R~SCG%H-LDvI;>En+2eCNj16j<+{i6VDR`L8lsf0DE;PP7qEJ+1$ zMga>@0er831*iaiRKVI(06!~mtvJWv0yk^$6|uNz0p`E7>(b--e=u0d1t34gF8}m_ z*#GSx1z3Cv+1C`X_!L000v4YFxT%13rvN;Fpsj z9R;it1#nLROGE+OSHQAR08cFOyEZij^B*Lm64%+x432Z}kK`7MFds2c}6|lw=Kwbr`@dOa7;CM9w1r)Hd z6D$fUU`;20cm=HH#Ls_4l(3K!Krsa@;RH}Z0qZsalv2RDO#o#Suw)ZJIRz}!1W-W% zD>DI9Vi1%;W=STH%4))jOaN6Cuoe?Qbpn#D)R=`S20Cg3x&=Np>1&~;h z|9=`PVPz$lG*-Y$N&rn2u#yr$a|H{!323Q+m6KrclmZq@0%)Uv#gYKp0R-(VW3?oZ zL^WYyB!G?zSP==}X$35X1kgnRs~`b%Q@|of0M963;Uj>a3bIeK^S}2)GFeReC}43T zl8m0(e$IE_{Ls@SKA6K})76VX+~YOjE!LLjcniu)+|)3kq0K z2;fBptRDpMk^&YE0(e=$5nNdTUR}bUzsUfwND#x0}tC2uoe%%4h1Z~1Mr~&XzwuC#b6It zaTY<#0CxKTRp9w+kAE0o=^f;Qbu;2*B^&PMrA z<|_v2zal&)fUp13)8l+7vN_PlVGpN#Alaw=BN5a=_IC=L{f`XpagEt-ii2N#AP&y? zM}hZJB>RE@u0OysI&k@`ny`!xz;6mzLI>av1uUEca76)Y<^cSqz_sEU12jmqa@gXA z52RT^;~xfCDhK%~3Ro2fAXNdY;Q-uLz~VOm|0-w>@f(1<3RwIG;6DYdcmwdj0sj9d zi;#>6HE!ixQgaK)>;q|NsDBh-u^V^@SHL0QnWLFbzPQ0@kDfD5N0BLNp+Sm9X#( zKv4y(IRj8!0ZYsPlvKcCG61C&u#OBsSp}>Z15jQ8Ys3Il3@Txf7?1=7tPcZFMS(jn z)fr$NT6Gv$)bfFxs5<^pfJI=CT~7fEzW_8)P_PrkLqHlSVZ|4KCJI=A2B0|u!4J_)e43qV%|tmOjGT>*=@0Q6A6 z@+|pn&0V}Zp zj8eerD*$5@xGKgozyrqEEP5?G2 zV1*NacN9S2M4o>)Dq&d@m~2wOQYHYK6|ja0z*YsUVFIvS0SlJ^e4v13N&r4mz#1h0 zy8wa@)k#1;Q40r*q_3z7irRltHI0Q(iN774&X1uQ=Ta99Bgj{tn8z+A9X_6sGf zHUg8c6tKz&z}E^`S_I%51uQ25a6$p=hya{YzzQM&rxmbv2*7ts`T18)Kg))I{GcW* z8v^i?0u~Gb_(g%6G3OcJ!S9K{D>uaAS0Bg}`prKIus{eL{GosaLiqo`D@s@!1mG_P zEDHi~RRQaP09;qV8Xy2S6u4G+46bvts{SVysXmZq-F8RlzstYFWH%RBY76}511a#p zKMJt?2WrfKaMaeG6+Zx;RKSWK0GSoA*atwU0@n5b2w%qcU#XPEJwURm39ESkWK+N* z9srRFShoWpN&yRY0OVA_dL00{6tG?gKpq7_7U}@Wr(`1}Iso!3aKllM!G0c}LvdnJ z*atE`Mg5}yYjeOsaRsc+0Z>u_OLG8}1_)Z0tjz&ZR!vx&1E9PDmgWGcsKB+NG6VfM z8y3}kAkC`b9|g9z69=^vuqFpTf7emMq8#v0PXX(305o8*jJqD&TR>wUNF7c6qX27h zz`nTxmf-+s$pHVyL3`s_0j+%y6c26vLq9)}0sg&$_J%Fc$p>QJ**^-f?glF8s(>Xo z0J<~4V>JtI$n$?s2KO02bb~FD1nBdBU(IJZ4dnM{u!ReBSRi1K52Oi0{3Abm7z6w_ zf}c%V`;k5n`_cYUfVDH=f2;s`{%64qknw85f*Al46|hJKz_SWi7X#oq1-+q*0WgKZ z8E(aVBOvGlX~hixD8RZHun*2u!crI@vlOrj2Ec3uta$H$J~Iz~?HEcbF&^zx%*m ze=hrn0oHVYhd&j#0#_N}qlG5|m0lE!WFN?o-}H|HEaCtM9)mB~-m~_pJ`nrc{!!4+ zzr*B1F3@R~c=*o;Qs9Aq6krtxRFHvudlqm2c#;7=x`1B85&K*%_q&5GBe7;xeayBmxYu&&6OfH(}d$agf&sVjt@t`Pp&A&tK`U z((!DZlRfFv;Z zj5`5!0tQumATF!>M}Y-@NOmm+C(a3|s{r~0?4W@Hs3;9B;y0^70)r67Ifch0pf_>24?AEV^TRRQA_+`cAYl7iaT1w5yqpsi!7 z0$1sD1ru#8GZna6ULt<}l!m%$UQrWQ&0GbpngtBba^Ik-z@2@~2hz7C{*j+e4Dg99 z^c3!j{R$tjJ>Ea|4+9WXV1H{AKu&?dn+m$83fQ1v#%%%bDuB2F7ulo$q6!SQC~&RV z&fo)l|02Q)Z1SNc00>LNU>5^?%8U2>r^;#FtxjCMdlk5P52%lnb>ibNgG=lKS_bU& zb05fPeHru*1CUkV{I3=K94-ZpD_~6pSe#M-5d{Wk6hK0O!4C>tr9U&c!>x!~C>G~@ zi(tTcy~yMPHi2>iJNb>lF$U00U~t(7((*t3qd=xyl6_UdH;6O>`(y?A3J5R??!^hX zCD%WxV~wrjwwky~?Y#U;)8} zN^T7kvRDE11GvmG1v5tqcwGV11K47f0@v9!3cA_ezo{V01Szt?0X+X?wB%hiiL-6p zq`=)(wHzMC!!1Lb?$#-hvM&w5YZbW`zu!QGsv1g^4^FEM8chNucvwveC z7rrsCi2Y?B*h@H$f;Jyg3w$E4`uPC}Eigz{;BJ9N0kjs_;+6t;alNe|W~Nx&Q84vI z0skqWmxDr{fFgoz2qYKS>yrvx%R>~ndczsWNh$k=6p2vKevN=gA4q4T{G$M57PyKS z0rLFsZi;!-?q?!WfwI+kTJT(xDo|{_72h#g`{!w7k+mhYT0jxhnr{@Aq)C95V88lab$n*?a zDL`C$25l4!wxGR&Mw`TnJsYtnWY3V?%C_h3a;2Pa}@MCC>HY-O#M{AA_WL?&pwtYK!|$= zqyPc#8LSW>^Zz?b-cXaywwkpHW*n9>Zz;HIE#6k}%^|Var~onVxtjMC)UXqCs{(}R zm-)X#Nz_p(^O1szw#>&0-0c2Tft%0!6u9YpP=TAyM-;f}`~`!ctQj|-kE)5A&)+C; z^ZBF#IeYj{MS-2qf$tT#>HL!dH=WNaz;u@9uM0}te7>Z>O|(B0xcU620yojFDsa;| zS%I6*MuD5Gw*YYe*=-y^{}28yq`jIznt;2~Q2~Sr7<5(u zSpo*#6hM@KK@SBRjDX$>c6b8%D!7-*AQ%{+1nLCrWUzt*{|E>unEbDR5en{DFj~PS z+xu|}+;B`(;09o_1$_N?129ER+yDd>xB+-Ufg6BX3fus^tiTPx90hIw<|~i^!1aHT z5;p)#6u1E(1#SRVC~yPth5|PLYZ+YT`S50}Orf`YAoF2^e-vb$1|IcyeG;f}Uj})T zf;$<+VvB-o;R3cRXls3Zr~uLi>~xock1W`&;N=*x2<}w^$p$WSK*4lta##Vx4cOvy z1s~)S@Rfqsti>?}uJ zylX*i1w(6!k9rEK*z?j*fjd#bCQ96yXs*DWiB<~SnP{WHor(4e+?nX8z@3TC3f!6K z<^bluI~6_D#GQ%W3f!6KtH7O!0Seri7_7jZiGTukCPpZ*XCfFFt;C&)aSGg-n5e*= ziOCAwnV6!$or#Cj%AJW9*y1<79$v9$VwMHC{>u`X{doSX4CHenC`0g+ndbwsU*I3v zkCE^xxPtYK#D1xQ`HclER{+HY_P7!tXzRGpQpjpG>1j>YDfrET^$HHPmLl&cfb;@; zeNTaF_+|yJW!n_YZyb~|A1HB6+o`~{>=Om9WqTC3mhD&IT6Rc*YuRTE@FF(8Ug{>* zez}sLznI9F9(|bKUh=yf;)R!0dy7^e6L`S1wSc()&g6cRRE<0dH%Yf z1VRgJa!J8n+t5E0xR(F<5ZI<(W$+94EmJ@7k<8!^28f5wPK_3EO})h+DC6PUdRt9g zTkj~~w!+DO3S3j4K(KaO@6`!n@uUxANHhCKfjK=SJ4}IXC*uDpfiwiykzE0VAs9p{ zcyW|~7zH_o3&^8jinWMU@SAN`oC4R*cm{vS_b=u4ij$&Dw(*D|`aRcMLd&>%ODk~o zmQ&#Bt*F4&TbaSf>@@9Vaazp>GCnne{$T)G5nO3)1>2_zsHXr*5p2;=0W=#JG*J*^ z>u9bZ*@9LITr1l6An4cI-X{T9Z$|~L-p&eKz1lg*j>39YoaI@~(FU2PLU`S1V z|8KH?$P(w=t|7!~^6Z*y07XaNkzVQc&8~@v;Kt`+kc1k-z6q$bYE z5(Y9Qp}xTNk`H7+U-yp!W7kXeDh0Grz#0V*h+qeADk!#%K`^jE3FINzXCN1wgu_zgL$$Eg1a>KKwd}Tl|Nn8->{Tbd?G@{Q52Uk){G)(dub(M! zm42zfUGlzG009W@$#DglzZ7sv&aAYYH6UPeMopmpz~Bc3u30}Ta9+nG-Bruz5262VkV&R%$j*lrfv&3e1pU^jo+4Sv$YmiRFcZ+^C$!*=tU z-F#^`_)!*{9JQMhc5}mSKCzpFcC(H@goEjAyV++q99a+Wq}|}RMSS$9-QcHLe1zYQ z@#c!%+_jrqcJq_naG)EQyl*$jcJq;H<|C#|C{750lTmB6IHvC#X zHs|c-JGTSM{GUEH{4XFj{G5wTirw%N29AEQ8@?Cf=(OGN)vwo*aJj~T{y~E?q%_LRjaf*^ zF)0=3mkcRcL%CH8=a#3NF)6VWnlU9$I9|4VV!@J9ft_?9V@korXZMFkV5#nVlqT;H zy6X{2n=+}5-r&KD9e#4B_@OI4Sjvv7CY!n_EL_Jlp?gc&6`sH7mwgvRT7da`SpMK zNY>&$2c^K#M<^A_jOq_R%AWsggP4An9v7#DnNz~UKYxTpSMw{w>#A}Nq@ z46vdPL2L0+aC*~i%&s{0F%{05 zl8??ayZk7N$O`sXdR9CfZx4$rDHcn~gAdBM{{9GFob8m*-yWfKZvMeA`X*~i)(p1v z;_Kgr(On#8=F7lBx}Q5Go=?&pS8N+4WJ`%#T=!?`SlXlXjM4v5l*eM;{+!^%BC{A^(foQ?0R}uK6v#lJaet(qy{JRIjPFY3!I$gqyi^j zaMF;IeViQSWCc@9;iFipc-G_q;=3t~qq;7MdlGk3njf7~B82aza|_U^%PVuzH_<6sMU{JQVOn(8 z6wSmpS2~z|X5mozPGxRRT35u&30HidMO}%tJg$pxw{zoZVPmgICcfFyP49)m83Uiv z!JH{p(h#|QukVeAE#G(N=B0y$X6D5aFSxm}bZYmZSTt!H^^8d=n&A(c9+T1{H+O!j z?JzdnQ*5@16q_3_iNnEvJ`f?{3HQq z+;?pFNkVNiWKJnaXLF@wDdB8+3}D0$7}#*fvEd%uA{3E3rF33r%biCq-w0f8+uSLY zqg*cE2^?OCLOC7g5z*>rWKGFU_0}8=_Y3g|xkC4Hrxf)u|1;)rr93Ic!0$qes{Rbuu9XDPNiEFBQB6~2OlmbvtsImR z2Qs%ko7tVQe$ZvJ0&dG8$Y%FmfD)VC`x_E$cCYGse=i8lHOn$>_xGwmWzDieNBq4V z&{eanJOtHbZ^Ev>o2Dk@=T^n_Ni7f~`b@A$sM`}V7llr(Pq*rX<a5d{){A)D{Y)4PWYJdwkO#-!mncJ$U&pTcFUR6 zcy@g9OsWk1zh`WP`Myi7$o#4AQY-NGx$jbAt*=fQ+YZc_-q-L^eFuoI9p9yv9P}4Y z(d-6^>@C0R@Ab|IeKBFXGx>YpKxfUe(_#KzYPi2QB&)x7Fq_+(5NLPli6_P{p2$b+g8LD&1O&0mexB_J{R@9l{Xhf6-bk{UAI75 z30d2%ziRz6vZ>MiyfHMRK$^_=wFT0u*vc=pzKYy})ZydU7}{4LEsI_18RF7vb1Un` zr8UVWwcc+V!lx-GTjr#-akf_{;n3lk9<`qn9 z%-d51)2i||v`|_HyINLfXuAdGa(ycbX%+dDBJeykRqWnB5L2;x)1jhb_kM+Zirt$B zK@+=o5=tg^ZzU8=>|PZpmDs&(OZ~k+AXZ{ok+V=GvAaLM;qQ4+9T7GmFy*-nG`+yT zg=pLO0-1Nk#itdJOGBM*X>zHU(k-nacV%C;Wb{J*l$&QsaaEvar4_beMjBGArNZ)ZoY!)STPm}A})b44rwpVmdllAs# z_q0-B;`4ax({vD4VZ(=xv&$^k*7Qr5P8VU)IiiwI38b=k*{IEK{@gm7>=*XN2yd&Ng_ub zbJWU5npeHI#qH10fO|v;g~D|qgf8}=U2tOv$|Ug;6kXrkm{L}0&{s46zF05MIFlGA?`ie# zXRUs-^ENhM-bK>jri-2FtiGo%cE*ujZu0HWoMH0p^^qZ&Xm9t0V7207;UW>bf~4V= ziq6B$At;l?qmT?9anFg!1nc6q&S}^wM`LX06s{{zZLAG#WJatFZORyHLtEMwYeQFd zI@UItRjEDJmO(mxi4(Rn9mmP*XSZWN%!{*)h&%)rh|pCd`yZ;P04^OtnIvXg_r%$j z;TRg2M^%`ZXB$JUd<%zPmh68nDn#C%XN%~MO+Ce*XTD4q9VY*fXB!y(3|t^W_k?`V zN28zwZv{!>b1qIcF0qZ4OWZO2t&=9%Uci=|H_+=m23rnmNp89N+86l)(2gwm<8oW5 zyd%#RPOm-0e*mxDGxxt?^7rMo!R$A`m)qu~V4cqM4-~U0hYLOE=8tV~2?wG7gegc8 zE3MT_Y@ZEezkWor;kc}lZ0Yohx%@)bve|Lr^1mh9z}WBLHVl#N?TS-VRn!D`S)fc3 zr36i{dby;aJzTz4JtEYay4*GgdvU`7+XSlD7QPwU5?H`OGeKXiUt*{OKLeBhpV34M zza6qf$dQswD<2wg&zIHB|DY|FI^hle5F`i7*Bj!on-(3kDMt7%e-2UtXcTAW8Jjv2urOIcV~EU)yq3T~vTB+Po9A^6sx~ z{YbcsU&n-l;17)Zp4Ttil9G$z z`Ukp8Ax*EMb#PY$$r=p`lEg)GnQFPhuyA?eiF?DX=~rxXw5*X0w`~|IT)1uH+20|* z*)WtS{LO{|(9`gDTv{y@)W!O3%4!v9Hz`OGw?i_FK>y!IrCB|{*`AwBnhxL}0eyzb zd1-d7oGjVUM;%GAk7w_>m10k%Y;W>kLAEKB?ei3SfBDf=J396ysrFHn=NJAV9TmxNI{?W7k10qJcUgTOw||Va{c-~p?%F`L zPu^&sLzOwl|I{F_m6Kz!GRHRBG4gBQXh%Pnu*ser>jp-D;{I>=r;0e>(npyjR=wY2 z6D9AZL|EV3WZxW1h3E2ogS;ptbrcr9@~|Bvs-uVPIMa0>w#OBqoA_4XR4;wvA{5L{ zT*Ny-QBNr22NlHtTRh1UfhHc2B%W+TyICI*lqm0cXUtIRkt6n}vT0-p{DOw&7U@=u zJahf60i?yeU+uZ1;THaF&~Un(w{c7+#V1Gjf623M*yH5WFWw5rTKnCwKf*e^;D)`B zJ-6Mk=da-qh~Y^#obyu9n_dc%MCU!K|7E{` zmN(LeTK{#^9zKLBn965E1q0-^ZSCkwyd3r%O5yprkP<3$DH&S%nTZ)VDk>fJX_UN} zUjoVD^2bdX5!j6Dki@Dz%4r`-S)S)NVA*L0GPG-#7V%Z=Z=B+j{Go1FSRb4PQg=cH zz~)ZqlOEI$*x5-|(}QY(pq*s@2v<>Pgo?t4tEdFn(kb7+0S!b5wghhm7jXRPlmNLT z)89wlvMJNs8r5a5!0EOz)G>kr*ctp&Q29Y~aJdG~`!DOZwonJgJ@-Q$IHLuHIdIXP z6XuAFtOJg9B4ZC8rJ|+4s*W;A{KUE@%yA9Z^Cd}+V5YFAlN{0PX-RV68nRV+{wK*1 z7SsrI>O@8U_pu6+#F#YekkO6kiSEg$r}bImqpgP;9nWKplXp3Wh2nTh87eXmJ**kVEQqgK4AV--b=395|a>QVZKmN!OL#8sH zUkv4G<+kB@S{g(BS{+ds8}ik>3DWx1*Xb*&*#ZKVf-CrMLDbK%Twf{a>kW$Z2fkBj zrV&V#iEa5yAWtTA4Oo*2odCLILeB$FG9jOv3X;U+?^)9u6U!>C2U{IeH#04F6gsi1 zhw@IG-Yt$VY%3nNYD$Zv{E}tH|W5 zqEiD^)Gr6Y96r3i9=x2CMV9E zg`1qXqF%Yl8CHos|1*CVO7UZc2QSbW^>z9x+=2nCc*u9FX)vk&zcis2M@x2ZG}#KA za$#)1N^k}Xp3#zxu%A{@hDj|AP8{M<4bF&VV}e0L>{MN>3Q^ISP!&B)Rnes_Dzd|u z0Q8IbaMn%eqaIYVPnCJW#|)S%i6(eSeRIo)Gn1@W8l1lmqMbf}K8H1FafQiPsbBTi zoxba`6UV*xc4s7ooCaQ0%)k096zgFXzWkYrf??|wWfEMVGk3f5u|rJZujh4Pu=ZJA z7e+D<^15(j22JY1oxI#hU9=_;j%tL@zy#$%mu9DvQJ&Wbeb}z3udcpES8dek>+1BY zXeh${AVMHZ>!Yiv?oswIFCmEu2kThZnU?B7-#yy`&>1OS!c>+%NN22*stvl*Rl2fD zy-Dd_f%g)sD0#@A=`~U{g->~tyAspT-@Wc7oP~Vo??S$UR+|{hCc|-VF@baN@TGpJQVTwyB;x}SR;u-iJ0>7RxiQ}x*^SfTeDcjN9rOb6> z@yEmDwwR(2rr2rQx<-ef#ct$3f@1rZ)l?a!dV|i0Dw1E_)-~*Ltge<53e?!-4D8qw zSu6WwfzVaEita#UOR{F@TtWeT`w)`E@Q2KTR)}|EfH_GhG;itgpA=oB!mQfk~3;8-Pi2e?%U zy#u7Gh$L}g81}^R{qwc*o}I=1*4^1IhaYRrj(k@b={1f;jq>pyii4|ZLLSFI#*Dn8 zx_(SewP9(E;$Qh`{F6*hvN4dXjH`J(EHZI~E&w)GqHVnhG^~Wi7OAM}2?fDeg^cxb z+nUnAmddAwSgWSGZZ4wQgz))Lo3xz^qHv~Nzu$$v>(G8Ok5Biz5@`3=iKZ>je(|Y% z%=y>>7Y^ff2gq=aA8?JBg%+Nz5hkhK^U*@60}TIO;#FW=C3FI)RtYTtj#WbUfn1eP z6R@fxlEedxRW2yj`S7oTLt0+^H z6vanFT9ADGU00B=B8$Vep58rw*a*^mA-_z~WC4&?5@l-z5Ue7S#Fwn2Pr4TSkt_0r z)l#zwP6UgAKNUaeGKt?<51(~C3}F4c_o^#45o`^nDdg zr0MO2Db|SZT>~&Q8rAIzy|`t94_rS5fOmukli?8y62pYTYAA1D%2o)U(mgV5+aEf&f)#lyv23)Lg-r6Czpa z;If+Pa>-OtQ>}wMbrma>^cYT<#?k}e2(m;==Nbaf3AG@UJL2?#XuD6=xzY8kuX9I| z=Z1~ICic4_^2EFCTH5Ju=7c>=HVC6<))*Z`5G5*SXPe zg__*BM9DHy3yV!|+6)o0G{TcC960S$s>KLUn5Pj+ndD+%Y48XfLp&&qnL$BXrDTwxuncSlq3@vBDYgc8t3 z#{mg0(WN#6`z@jMKzmE*67by;8U;kRgx)@*qGVvUC0Qy^+7jY{%a%|Qkk}GB3hcFn z*3JW(T7tn}tLWPv)N)ysZ3Ajr%C{0YX$dU@GFn1cfrVB;W0pBdi5`kBi z5cex0c7ojNhAJEnq_UL!6R^n=asrJkp`o``lnykpB>PZBlDHKV2g9JFxNNvJce(o_ zj${9wr0cOe-8lEnSDtHjQeT)MUBGdEy=U)rH*m-j+3W!zk0sO}IARIi>p`t{Rkj8A zVKG$_&shhW-8WNd9Wj?L2a5@l_v#jh(L!+ec{22Z^HiV8^KM*v?Kn^MJPl8p2M+On z1DiV5S*De}E>Nb_3p7-9%JY>A?h&+ebc1)o!C`}eHZT7R`BBbBXP|udf;&u3%{6%Y zDFz$F3E?nMF~J*dG)m1X*>=u@DQrF>%sspx1A z`W;wfDRuQw6%_@khzn6sb0{J$SV1>X!s1UP@olIL^yKxnB_Rz_U%IVPUv{5d%zV}N z=^o`QvW64#*qBS*u$14^oDNG%G|zgWj+4C86FH_ z24s3NDVJ{_A+8VPikI8EyW^>|R%d$9H6F_J;O^{qnVxLQ?cG;c-WR*JeXvLA+MFy8 zZXO!5JQ!iNWO>l1ozC*4&^%n~Eo}8xhWRZZuq9gB1YoWuG=02^egUdll0A~IqJD)6 zl0;3cH8v$-!_ZA9#@f1v5LZhpB7UkahY}83ePu_$w0%|mcDG9BE}@sl6pEcQ+jkIn()h@|*d8 zDmCq11*O5#vzJ%_6tsvW(eG*N-k&`WrVqq%oXS4~jUS?uXP@sAK*Mk?e+EP$=8isG z2==V`rxcF8+uS#mW0RhFWGct{%q*mGY$ai?O69WIbAKwAn1k+r6(_s~t%K+tSL%j3 zTFvS7MrBZKMCh?m=W!KWG1ARzkukc4K3*Z|C z=BvyLJLu)lc2K2ucc3E7A9iqT-@tskgJb4s4!+MZ<2663JoWeKckAzSZ2mF7exGB$ z&V2elHx!Sig(6N^$13lugVSeS&2mFsWlz1IS0>tiI)hZEgS9zpkJLJGr&J4$OnE&cSZsZ_Tq+288vxRT8 zPVP8b6=eSLLyo>oFlYY3v7u{T@CV1%Bj$~Na48fj`ScdbVF;tKRspjwQ2?*pp(2M_ zMdS9X=xHGDRq~xukR(346+O$b7mTr|k~+DB2I`kwwkaoe~DZQHZ8mRX|Z z(6b!2&e8^eEvYOn0I?We3E7-5pXt_Td4);RS5~aX4Lr;EH5|uIj4Va~krY())(AtH z)4K41F@c3WmQNu~IfyRR2s5fBs;N`&vA3B|$J$An(^UPUM1Gh&hryQ3iR0q{*a z_<+GZn{qW$Yr;B?3tz!>HO{0I*fGzu&B`{XTOJuwn{d#+ByO?V2sYYYXP zSeK^3@HY0JAtDcS$AsPko?}8yKyXZGA}|{hI+>uNa-cFs85{|>{s!fLv4hp(ltaU@ z5Y%!N0P_`=ZUD?FSfZRt-Dd${ZpE?&KqhVTCTN5r*yiP4Ssf@3e|I(8FtOZ$WacX^ z+Aa;pb|fs10bnzmr3L`oK(_2>k_Ddt5i&6*x8|y-q(DWRcoiL(rJ{TwIi_Fa&Qnp) zLKWozeKDp=;*{1zmxjw>zS$y%cyVkxw(JBj3I`#~5U?!;+7y=pwJ`oijY;%d)p`wb zNX(a5o}2`EY2Ek>f1C172Nq%cw;PlATrS{azZ^#67j&G55H&s;3KXA zYG6XezzK{<63wzV3xe{tt{vH$b9k{~xPOAQ=Dv delta 1966104 zcmb?^cR&=!7r(oA!1aFI(VGPn1r%#k#9m^Jy&y;tPNajqYoZ1XxX7rnfHn5+YK#hY z6E$iqN$eV<#;*#NXiU`Kw7XkQzrWw_d*lyp=grQ0pZDIpDLXT}9RImM^6RMrNx`~^ z(NYl^k#|F`_2d}(%i zZdQC^LP}OqeuuD}(HZFPf0h%LkRG2M#<>QL_}^{h76*DW{-E$;sy|nr?9c5U83IbK z*3yE?>7#41`9UB+-7iR2l&{Xo%}LKniA&86OG!&e9LuSb>oK*t!bi15Mfqk>nxHbn zM17Fiymkn;qLwS;2ef;d`N2FtB;1oLtLetn0&ODu)Zz+L>VbmxVH$Wd3f$fi5X||< zd2kDoBbZR`_P$UqF~J8+J?NrJ@@4bAIqeWLI2TnRhA=@OE}?rZ#urrn(byN#9)LMD)Ps9h%bV*R6ap$t zK~k=?c5R>;Jfkj%{%lYkHs1t#Rwzwed2py!6Q7zGmzEkgA}l>OCp9H8iwlVN;KD7T zT&FrATv?2c%NgPU*j4^@xVH6ba+N7YaBl8c7ei6L%ElR=o|~3alpg{r`&dFaen>;E zT|GTG_i&Ju`yr-2cP~x{!e`g?hq{G=h|EQmYM{9|7$!ac|?i8E?RhF?mBb zw_*aIv7TH>oRsTRD~Jmi(SY#*+k+A6F+}9&LnYti=XE` zbGO6lGL3gC!o~HVRuP#Vbs>rms%{_Tcbm(Q`6yQ4)rH$KvMs7;h@N@5G7x6jLyq%o z5W;2D(Ge9ZhI(^xF?#9)jiZ{lwveBu*YRLHLByX2JfU|B{U-St@^$w3r*)f+;uuvb z;{moSW_obfhWZ0p@C+5#GpGq;k18l4({GXwn@_w9)g#RSCU7Xa!q#M~jVrPK_TckJ zc6);NM=D*x#Tg_QEaC4K?v1YiM5@R+}O52yLl6Vh+Rsq77@Nb_iQ&c|FobU_*qh9XDAN z?uL9@1cfD~q~;{T{>~jlEPmz=V*1Yr*5K{I+fWVKf*D4C5LY}O06iaFu5UU z``Mt{Ec6kKEWIdkYz}ItoHjXx^knWkXIPquru;0fQDd%K;wQHUCj_`!o@1)*Pj@i2 z3{#_H9%JfzOs#wK3{yujwd?2Sn0kyU{`WVSx`e5U8h>Mo$CNUfP%kmHv=^Z^Pr>Ay zY(hT7RPTznnDH-6o&D||rnY11vj>D)fT>$8#6ytUM=+JpmrzeIwRVvj-#d$`T1|AA z`W;gz95K~EBgu0HYmRd8u_XDPGzV^V>CQPl`)N8&ebe*T&R+OnrN~0j3^c zsx&JCQ{P}}{47E(!qmp)k@(&lOeNoKim5}Gx}DhqQ%@l^Wv*M3uAg9X7rr@gU~5eM ziK){TLao4*LT$y=isSw9y}g(UTbzigSBRS8 zwzn_|lRx5{9k(T8>ISAx{Yt29nCjO&1>d`jskrkNOufg{uBcQ@-Ne-N_vx6riz&~i z8JMcTRFokTQ~zLU${)S5FglQhe_=rhc8g3{z_{^)6yLrcPpNdQU=a!4%hI1-@5;sq@!MFtr0y>LI05 zFu4zt!}Cfp^#W6hw3V1TgQ@isH)0B4>hV)Tt;E#sW}EQ6|6oenkx;uawdGdSP}Dt(CjmktN*I;T!xh@M)>o9dkxhMxw_b~NSYeHSY)RZ|t z;BxO@fyy5nG%Fwi8gTwK*v>-NWrcCm1^$Jj(U(Mh#Q_i zl2eWK=JJ+!aF=p|xC?os+|b}+m68NBA2KZ%+nsB$+snqhb{Q_jZ7Vg13M@yt*5md_ z(I^Ckz>&Xjnm;#cyq-HWqb}zHbgOvjjY<^QLylkQew{KH4cWKrzE_d7zXmt}V z350TBN&phBfLv%8LfQ=D0({$Z6_cghtSK#-I7<0pz3%M@h9a;&Oc577ISM)y4OkS7 zbD7_k3tiBb8G^Y&r+IK+Pr?ACw7kHA1~h~Mhx};`fdAYIH5WLuJJSM_@L5B_U7Qul z&7AQG%sO8b2F|UlDd&pjx8piY4+H+nx_WN~eq?$!(`Hsa`{M%V|*vl?M1&z#W$DuxEks)~s+#uahB z=6A$QIpc z!MI3V+sUnAX*A5D(q&_MaL4n#up1YAnaTy{1;YUHq`*PkyDyu;;91K3ys-sV3cA|v zmtpgoa*x;7hXwvdx(T%YTHq$6!hNIy)6V)FY7#fd%Ff|>&u+){-q4HdQ_vK;0}a{8 z9YZ;QBx@ga&iO707A!c%lbA30HHxj`Q1N z5a`X9w6>7&cw0Mx|n=VSQ%)x0B>;q zi|cVS7k1?QmwG{;uHsscF`6}Npo zg5K?h<{XG)*+a+dD z@I@bYZdg9D>@u{hFTB3T9VP1h+RW^0;=U{C#(lHBHoS3@la=Oh$4bL+5BMjD;u@{2 z&8=CcMZF&F(C%{4J43jtom>U?c!>%3jQCMrwMxO|5+?M#U_=%54|i>KB$r3}Mx4uK zj~m8qUL6Yi=T2Ps>OgMVs$}RZG~Gd#r>_~vP514@Wh|6%F>7>O-&LVd!(&iP2zqpv za#L1WV8(A;%G&x;H1k0w59Z1jb>O_$4P^5hW9u_CF+K=>HExT2mjrURNgYaOCaz;C@C)gz2fG#5fJjkwr(A>fuIMaH3my*Bg~RK{^w zi7jEJwPT*4=F3E)!ko`O6?4tjoR5};`-q`@XS+7dnaf%&2T+QvXaPJhkvKF^{DvkycR}*&hJSEb z_Q5D>A$>uM)Z^0k)&v?=svDQH#ETohuMTqt3$@24w`;17o4nTu+W1YAq5cHT_>lNn zT;|bKkmmi|6Jnx?AIki~nkfMXyq_CjYeADhc!#Szkjq^^G!djv22$?r{v1$mYO$2N zcPIyJlRcMmX$Nz_fm!et%;7S>o5T%2Gzp9jhZ(QF%i-=EoWwo(ZW4(42S}kzG(ki% zGmlN+{x~{~`>lL3mwap*clYo#F1CCc_)-BSW*!?0!j&-bc_^3D z|2TDL(f14kZk#?OVe=>9T#%MtCgprikL8NaPT`79Pc7C!SxbK$1D1Vp2;TU9EC_ve zNWv{UH3n?cK9}zFIg`hL$>uVIvySsSmnRAz9>HnO=W@#PW58qYaw+F>;Q_bs+*mMN z|6IZu&yR&AuW%VZO?N|6PvnF1KR@MK{yLF+aB&j25qn$0MB?Q<@YL|!l`H?%hk49tuSPID z{@sjzrD$yd8BbO=QE#;!-@VWMcr}JOz%{tmn)!L>=xf=`|GomgQ+s0u1GyL8oagqx zbA!sj3e!%@{iO`^9B4a8I&nQ7?)u-waM~L|#R;sI8~MlU|D78v0ogn4eDdhMxElQ2 zlSi&#@oW}ORVz!Jm(v-%YsMIN-g@@Jm3hux`s=sqiUR%(7~h=}|31z_dF|e1{X6o; zzV8d=@n;z3jtJJ?HWy~ozap6Tb7P)D$v`b*^8Ou(o#o6R7-9TM1@j19=c||#=-OXH zuD&|v1+qc!&hY;Z;ye>`$^}Xs;KStpI}*S0WmY2{BLkVk|Bl3cK};6%b7*ZQ^WTve zTZid`{JJxkk&2<@1EI{p>PqHe@cxPd?eB1g$HE&j`(3Ibm4~e>Ljtv%_EuxyXGAlF z$gRc>Om*9Z45WwVyfZTdUGH>dzJ*c1FYCqp2>rp2?#KKN!T7#|m_K0K=A&Yn z7brh6k=a)rlR(Bdzq^CZvqpIGn@2G{kn6E=nhd7gwHmI%a``c1m{v&J-IJKw=z47i z6A%5zx5;OIN7~mZWJW2fgHj@9l%Q;LGd=jRjFIqNmoo>vtR{GW%ZRFFf=xINg`*b4 z=Nx6)pjz2|iitt`8_qJr(KY7+xn8_Xu8~)nzfpepEoKp_%~N-nw{Gxy;tyt-6kZcw zFn=O?=s!$1SZ?<>Y#Aa`BFuXqN%Kzfa z8f4Hzh2f2j;EfNf1Lt&%Cm$BVW{av*5eR{Y2z`(pJ0e+MWd8YP>|k^aZN;jQJuTa@ zJJGeG3;P7+-|WF&sYdXQ0ZT?PdVY34whJ-|#VuIemxY_Q$RvF%yT)0Q_9U=nsJ_cb zvfra?{wTH%Qg~N78-?osMGpHIUGI!%Z=w7nQ`l&U^X}_p9sYl0mVv_AeL92fbJ(r_ zyF9*dE?bZN-}yk?V^JI6dw-OQ|70F37XdGEs+J#6z}{7nWVaRUK87TXr7X*mWbi6> zCC$CMnterc@2;~I_;Wpbvkocy`+2sQ3Y&L}mAaAKb@$ohRKnzk>}i@D@`zPY9mYRl zXFF4gHiG~(NDIoAiDE#-GuFpB-}K<~pR-qqN?`0Oc9yeZCcb8`I5XFU=JWvPJjQzM zek{uJ1pU2JjSHKIV4&xUJ^4~E(P-j(;O8rv>ZEQ+yaZ$fh+O$lKhXgv=JP0uu$B@Y zis?yf@LWyNd}nG! z)Ol@Uj)^+a7O>~IXd_K#ofNI5riPpreeJA{iDyK0og9fX`0#V0FR6j2FNl^ntApD` zQNA;MCTyS?eB@=@sIuc{QIWGc-2X+SaM}+=*F;OGAEItLUl$W@iN0}Khog5zE2s`R zzl)YT>xZ59MTecP3->=nxm1Ux|8b@+cvz*8PP?E8` zsW`(I&jfjCu=oM(ve;0ulOtCj9?ITMJHagt#7AjzM!2{eF`B>GP^_gB6sCpv6fJP| z6Y)kmPXN*4K}s@hVS0*hOGxth0P%jJ9)Dg zNIZ+GI<`a%&xGQ~qw(u(F6g^nT$`Hp<#w?T)q3Af@qcJ?&mOTqP2S%tZb_4o`^A4! z9X>fA{(fe_)jV!^R?JIG}eD39z)r7zZGwmk+Rtm zm)lfAqRgd&CX*B{TWQ(a8kfT~_b;tW2Gw`GyGsx)u*Jj0`gA$g%jFU+8{^}$kd_q( zx=eR+rrDR5*LImnYpX^hqF5fz{AOZW9o}g@)iv%oj z>ET&?uC|4*7wf`^ar*@9a2NWhmX_dh+(|=-eEz#+mn`bGs8kng8}vwXnM8fHF3ZK0 zR^7odE^Vq~jT=yhR7k+NFI-%~nN10LY?o%TiyN_v51sB}tiF66%Fm=G_4(3fQs_LJ zN#7Q_D5*(57rXd4)BFnux%L7T>s=IJey?0T7{7j88ZTPzQrCsl(9cV04XsOG<>IV- z9?IW94cWNaX2`6qE>W~@F70%Qr-pRd=TbzY@=2M?En48_F_&jfdbBrab8lQ-e$r`| zQD!nMy#39kuan~~7G?q^PxD;)iu*3{RK0}%xXhs~<=qpPtu*)GbC=7s|6Iemww9At z^+M@7mA186o~}=5?#$Y*7BA-}5IsToiLv5^W#g3~BfPyED6^>b!2h?%-r$e6t|y4e z$J@DXai;ok`xS~;^15!W)*ksuch{@5Q~I^1>tI@g9s0R?IkDx(!%&>+%oGIj4F~4K zpCkddp|0h`-s?kMMY8|hoje>3$2#LD$d|{5r@5+GxKJ6;R&U_@X1Hd^AQ3(t62FXh zO>w4sgJOsA=O(*4H9bVk05W@nL!muf`9{-S@6yVuGt+e*jnQMXUBxtVf1T^v!kIP( zaU#IYGj4hirJ1mR_bPN9RgBLwRT%5J;0;`7(L-ktQnM+#Z?iv4Fo1n(8>Hi{|<>bX6nJ}#{9_R2(B{NfI7 z8B|}-Zf;v>fnPp#TSSx7d$?IAnC*MH?WNNh=#+KvR!iAN@&?P<85X4O|+FAG1*qO=2W*$wCwHA zZDmVl+sbyCYbz_yciTqGo?c)p`(=@>Y-F*m?4Q8qheOM4Wha-|%GOzFEBkPj+YTys z(*|4FQJZXK4O?twFK=}#qh;6av6W5QYb&e%)>iiXez)s%C^~e+&8<3ZqZWwDh0i9j zr`&v;Z5upnVsssjzkbeb35}@Pm)!zr^4qI!UplE|R~|No{<> z#_ct22hlo7BdY2wlf>E%+IvW>?clMe#M%zFdP@dS-z^$NI&Wa3+Ql)Q3glnMw{HUJyqC4Qi#Mp~D@-dO@ScuL-wwfwHG z5{;N7FZGaw(4_h^$w``gFhCM7ccN;nkj|`=LEbR1t*D&_q)(N&ll9~q36do;tSFe1 zE}7z-Ms}&bd~t@v?94>0igLbu%WO#rOZ0l2E16w=y+mUq7H1lggI<46l;lyprcaSL zGsxHk@~{@#Ix~Z?NkH}J%SX+WET$?w{9N*RbzH^Y{6aF}U#PtYb8TKqpC_4I9hHcU z6Xr{Pb|K-AP$WsOzQDMJl62A(!R^HoXHKCx)PnkJ2`eHR1}>M3sJ@1}6_UBMH`!bw zxj|(wT`h5DP0~TxBWomK)OyhdNm8|y1;1>Pz~`R=c_<&YQBsGhJ#v!-F4dv_5X5ei zIJ1W6p!S^Y68Pkg1)BE!8$Nd9B`>Ll%KefB)$s$b{th<7>PR4w-sF%3ZUbN&Zu$pwy4wenGNa0Y35aF!BjECBfC}av_w2tQE-aN}duw@Ur_7o(BDe z2a@x|-Tbacl3sMUH&#frv~1Jok~X9(<7dB?oS5#y}vc8knqMChk)Mik|ahpMXPDzb85On;w zGtv_@JbIs#{z1dz(@WBCXyv*5B7IMV8ShBrY3{p9bul0GYLxdk4v^wcMz- zj5tNh52`CWNuAQLzHBpPt7s^Dp&}LjGFmo)7MRvv7Dpzm{PP~NH#9ij4VL{%z4kC( z2Dfu?oE%J)mC@u^BW0UuvU`fGlqTO>WXqhj8kD3;O}su!){g>@8!ubm(8-DcFp#9h zVQ>Mu@2FZH{HD#aek44>fGsjTXcHy%*un3f$vkNYhrE&vb7s{BcjCx;Pyr;tyy?A+ zqak@nB_Hg}gSCUi4SM-`8k6}Z`9%fMJhP@;L;IKob>-IR8&zMv$H@o5Ji6D`yrCTK zwPEj6G?L$@0eq*eyq22en)}GDvAnvk{3;Eef?;wPwc)*C15X-`l32ngadNAx-;A&& z_a(@KX%#+8kxQL?j0^)6t0nb-%vIsZm*mRFx|5Eee!jeq)BQb?$jcVU&CVR)#q|ay z)a5rVmv^MiT~sQ!4v|+^$}?zpICPV|oVuvN7Wo_MjOM%K8tTr$-^tH789UaBj5=zo z$Ul$C`_YOVdQrZE!ukDbtH_Plg#RXQMw8F9Ru1LQM`AV9+@WNKT>;9Bm z8`Y%O^2Su|k+<@1tJjj$;T5%bxvQd&2d+~fbyLtjWQCt1)alyAtrW=y@&$4QIJsD% z0*WHJo_}PP*J8l@ItriS9Huj`siW9VE9yeHq8;@{?PiJ_PL8wh`N&p^J+#9AZml>& zYx$Q>iX+vmH=3ugjzX35Q7#USZ3T+1RD!%%k?eHc7c_rb3wXSjd4P7y z6}5nR<8mbrQ(d*d>!hbU7_dwMKVXJNk{`D!+@17W7{Dl-^l}BCw@dL4?OA8+wbk>L zL)EC~dq-{cyy>{Dp6C9kP|-SAf7whE z=}e`}$)|KIR>EKYTp39X_L`@(PHgYaS6U~w#|o9!iS46>O6%0(=pvNogF59Aj*|B)PG3_x@qPs;{K4!Ao<>xtILjY# zKz%Y%2X3YKiNV=-N;&9%L)p)Xx#;bP3J>_H7gc>=+11m)H@T^7;>?&}71I&?b4NL$ z8hX?LHy*Ll zKT*Q31pLn*?gUk3@le)AC5jF7R#bAOQdjJ+l7e3QSS>&AopPWG`+@&cp<3!flB;wo zI0r-C;U^eWkus7j^Hu#qb2s>_;Oi8)K%)>9JgbkBZuL}CS(02-Ulm2!9yC?mqjGPw zQo(T#mu=ooHB4U((=IZPLFOKFHV7W5a^_`N80)^^T*C?_|7M`d&6y6Ov}uKB@oZHv zP_ESafg6+68h+If)gfn^aaB=U{!+z&W2062Px3kE-{?Rxf#$NR{08Qfro1X^!%Vq)h;Dc$IW5{9$6|~@k^B_-*bwp6$^9cO;b&D zQb|}Bt@#DhRYA_QKBVKG*{XaO<}p8Sp6VI{ua>V=yU^9IP_+qNPcI%8(k0j&6}7XL<-lbyc8bE-vR=+nBFRL(5LBbV?nfa*Kj zI8gNU;4lBIia|Bo_^N7!lg=T6Mqg7ItEYX0-2vR#7a zo~kQSWypP}>xOvcs|Tu|s;A1|f2c+yRZ5b|=Y}w!vqjol6cqr|V(_Vqh{dhlD^%&$8AW=Kpj*(6M z_zP0?W2a*UOBk+D!!IK|1{YLnryDaCq}8Y!R?jPUb?Svkm2pP3)5988<&e92ZuL}o z=%G$Vs`T+zJ2R8SVT)Dy%13>+dKL86PrU`HvMEr##o5M;Re2MnzF0j~(rT;MBUQ{H z>dj87!fWcP2a#PT0)(9`YO#1zXShbm6DRsJA+^UT^aaC>U)}faL?ccJisC z)cxUvlYGMDN}k%OgF7Dzh6`=zB>eqx>cwg}jh!|}eHBf2hkdEmncy{JrMiD2yq<8= zJb=?lew#vb#RFbv*VZ(v1+V4ZG(S0Wvd^Xnuj!}xO=Y!9nxLtyp7WtN6*xB~+?Ai3 zqzOVQZ?R~i&>{HDjGw zt-z-B0-9EQ%Y~X#&RWAm38$ToWXRkE++41af+^mfF8sz7nsd%70;wZGdxYj!~Ce9<*c z84A*VH#BEu@LKbsX1g1_Uart&RjZvLBeY<$x2FW0y$;VYSNx?ZK!DJkGu5^P3s&uZ zsP#e($i+>I8`=elwlSh5YVASP;7%B{KRCODfcs`-g9~ULsFj0)rM`>!J>FW@RwZZr zw2z#QacecZ@KCx1DZ9E3F(NZWTL;mL8)#3Viir=`9!J-@4Yi$7FOl6uJF_|u8x288 z>!)I{{Mt)*ett`BVug5M%V6v|peg_`0k1 zlWH5`0igaCu&<|94^GEwRp8SwpWYzDPa6tydTT==OlfZ|o`+@i(^h9fhb@C>ZL|u$ zsK0gvvM6#8vFP1kV$tU@+6UE{9z_66gj&o$iPtWLwM=ScMY6WY=>Y*p7?KH~ObNd~ zRl6H`J~Kmm8ii5oTq@~ z8+A!*inTADcrgp0aS<(<@^Hy?E5lquU$*q&e_f@mF9PR^hG~I$oz|K2ifAzx{`(+* z{`opB{I(Jj#p^a|FS;;1g75}C;t%V9al6)uPiUfD5nr&ad4(_EWQP`>@z;z zqfKH-^6XyiE*VL3N3@I=Nv^q}tw{^~dP^HXlZw0A&!~iq``Xh=Qnvd`?JN;V-hHio zP7BW_d~&> z7P>MghCu3C*F7zD=UL_@f1$N*nG3vTwAaDT@Fm}(qb^d;Y$p3od~cnT`%b>#*6Od^ z(7(%)fbli^$brB2Bn^MFk8ZJy+02g{rppn->ytR$Yk#n7fT}ZSFhlpPljeY19V`67 zzPYR%ygW6xE}uVBHx8b;Ojc=m_pfyg;RZKK4qC1&qRDrqx(0Cj4&}C5t*b|q zO4ztxca|2Idr)_pN*H-qmq2r`9n}q`$u1{!vuX0qDP0Op4n1v?>vI;VgEhN%&ZbWB zMVmUeFWc0K{l&%>aMh;H57%@*QVAPx>dsMh^6%;_G}rBST>#5GB=1hPdZ0tco{%R_ z{h@n7OP_tBn@@8`SL%MJ$%Gd=bT$H&4f<2JizXkuvOzESOShcnM*po_Mw3tf(Y0r+ zc%9$rIumibOZ9-lbrI`>DaLeHJ*=;SJt`gllSKbL&D|o`pQL5KQ0uLJ{YR^ZpM}8s z3^eG`>0PASdJp|Uiagd!-xDFj7ejqPy0_kqf9$QdMn;IA9=_&}S=0e~gS8yrHc;;c z_kNM6w7Pn0plz?Ow+34O2)#AX7B;epJKq>7j@bg5>8+LgZ3}%{YI^|h+fv_>B93aM z-%6A9qV(vf3&Ok8M&BBi=HXkdu;0R2i`wf;spVZe>#Z@lu&aJBDX^!z-Wti}J@nQ% zEa|Pc#^I!XHh(=Eptm-FguynpT0`~LhE&~BWz#~6Rco--;p*pV~TzY)$!se z{d}rpcDk)5H)Yx!@=vxt9`4N}6Enu^;kRr_mGBQH=##08xXJKaiKNJdsrq5a3$WJw zX+^}%wN=FGdA5q^QfRA)*_^E+jxMy}8W!0M{(Ol|^G-``2CG-tyj#A~X0T!nGB_hc ztK-M6!}atWhGX;f`ZH8R(7 zpGd>W`lAgY@aYcaj?6Pyn`ND`hTRn6@i;?2>fg_%+H5mSH>6Ps+$_U2Dq-qZh9H{U zwaDNLzh)Q$!|1mX1N@!}h8VosunHdOMQEzsHeo;RG5krZOF}%u$C7 z=u8V@YgBINMcYNuDZ><67d0;%CQ#e9-LtV}-8bB$Y{?G|3n+yAiD5KVXHKO7P<0|$ zqt&U;MaB`dK$4sBH+Y&G0T0m|Z%|ivbvN#ya+PM|M4G$A(|CvG&hs|H_uesEy#OOa z3$zL{!WZLlZbU7kH~hK-k{i>~c#T$8w@ya*i6xx-Qx_xrkjuHr8XbSBn-PBe0Oyu> zH-1mcE*)qbK&wSO+?Yi5oiM_P&U`|-do0FqDl0nG2tOc$1-u4YIe&LJhsDBX1-heS{7A|EHQmuGH7LmkyDy;eGC0ybpR&Db;@*o|JTTflhnji4 zy*qk60I{9y?v4(gq2#ij?(1o{Ghl%GDC+8;V%_&jKv_2!4$D&9tW+`SEj2z~3`Tmt{2 z=QKv8=f}C29#O_zjcGUa&nE`c3tGC3ujyy%s*pOSI1{+q*3=igXl)w9)B~BNyn)}} z&SVh5&;7)8G4%v~olKvxH3oz8qjkeTLT9B1INQe*#27$kcas;op-$0_V``wnUZAYA zsf4MG(%(@YBRDuu*AMinv(^i&?rLfP|Gy?;gbYu+nl@Vbwx#MOGMzsH7}?#_k{M`a znb+NPi?S4Nf&Qs4vV^$Rs9||J2n5X5`SE}CFzsWR9D$q+toUHy^}ek)IMc^elbK0` zW$>!cOy?OUgD4Ia&;wOJ=!0UyeI`%$8B4g0AgaG<8MBsH4D*PuBHkL|p=r zv8F7)b0~cV{cJ-&o8eEcY+83w=5W3iU#gjp(Np`e}-OhNGWB=;urHGYkD7aLYRQ zlWVy`g;qjpSdm5N&(w&sJSRkX03u!zVs33jyds3G4kU6dzaVD*Orog{1OMGgp<7bB+nzoAzBS6gY%;>u!Om9dW*#9Q{@*#|gkz|kqcGWgS&?Vw7y@ql=>tI7 zV%;jcq@SxZ*obA1J`o644Dmz|>X6)U44> zV@C{wez_l5yio5ZPjEzw6{4k4w8>wXglKvqbm#|Y1{>P6V*NTMA8eg%Y9OEQh%r}) zv4~=vonxvku*gV6ef|N4yA7i^Fh#TbhJw;@<~i)4VPM*GU9h}d00u)lo;@H0`(YTk z-N-ORfJ4RYgQcb#d=&fa>_b4gm!SiD7i!?9uPwi4zk}LLJbPOx_$d^uaUb+i!DyTm z+%ORX_MloYw?*r5HNTUhR!wy*fzp| znuG8#cr_^1jZKazE;clfTLfaTo=E~dbFiKbL3%s0E7-PE7a#!fBp@Sf8Vmg8MeYrc z0WheH;MQG}8(6VQKZ9Km12%Wj*OM1Hq812HmqXNhrpDlOSG^F>n+VOf0Sc7yp@3l8 zGE*}Ut7l}?PYu9fV6w2spe88PP6%*OL@-ALxaVUWBaMnZ6hk8Ike!=G+QS$UX^-r8 zaHKK!1#(|Pxm5$Lid;Cz7ALy05G3G@&IrQ3(br;?!+}<0tRq(sw?`4yR}SLVSfj{e zI5@w@F!)0^9KvouUA^F*FLBX#I4BrBD$1vmW&cpGwa+r#EsrWJ@QF?}Y_6+k(Ju|HwTa%A!a zWxf1#AiS@>3-Ip?*JKt92N6FR8q13Wvas3(0=1V@wRYWs*vvdk01!lE?6Cs~8cIzHFq|}$U)GwUNfU*s-t6zg zfx7Mex*+!CU^n>#N7&y4u+OZ6dN1hFHbs;EJw*l&}DnkW#S9qZVjtinO* z!4JCS5MoLTWM*5o)o{RUf%8V|urOttsVTbxqQYh+UI9_TvaOmR`Dy_^_GhU8e+%{J z!6>u8z@HRona!Vqdv%EtONbI6mW&NQ3Q!yxRXxIR+Qxv#hOk}Mu>q#KvHyt$z1o@^ z$e#%0U~T^pX#1LK3kQcf0*yim!0$F~1>s(w+`Ahq7#CvNn;U?0cTFY$Q>|I|IKU*p z5yBi-HSkzNoP7qz2F8&g!aq?TAdugH$k)W-d7MD0Fba(8k&F+-S9E;n5=X{|ZUR(1 zW9TGA?HA`bKv22uU@0^eX=i7r1H@>k3Yv+=w759EFtuAHkS%Fs&Sp5Pu0U z93BE15{5s840Lqpwaq92-ySw?VcbE=5mQsSc|_HKg6lxqqt>1*a0Jn`?5-|M5H^j7 zd<}>@^FdD*N$x2}kXSDJP1gZz`%Ra~wiyA^zBD$Hw{-+;EdczK0xC|JLIr@0iO?1w z18iag#9e1OxP8JDBOfh5`Hz>mHpn<>3Xtata-q)xK*{G~F{rq&^8>d|noMvJ0DUx; z9X$d>Jczzg`L`#{(3i%{!sTRy8`Nudo~CJmVFixAzv+kq&=J6 zzgwueZ~xE<2VaV|%x11YlV(JdB}5Z2g7$0z6o;OzIbk?$W57LI>SNsiGOWSWNcKM? zfMw|Y#z2*6c9TC52&3JbUFFwQW%jAAu|TaB1m$;|%7Xa)gxtGJL&8v@gWqpP6KOOnZz0JfD47C&AQS2X||pXsJ4 z+S$Q|0Bx9|6WcwWbag%LcgRTC4GE_YD1+i1dpZizE*@z_U>~Z^fT%{ z_dAN@1tO2dJNBM-Rhc(BUn=qw_BvJYrlYj00%;Hbe-&(?H`QU81W+2_9wHYd*rNs8 z{N64S{>w$}HB%G_d#e*Jve=c3eXH}53qkJrLY;$J+OWv7 zbvRrPq@4uxn?onjngm=Mq)7xovw0Q6YNQC=*5CJ13Bpx(*4XYnUVu?=ViZAsplF9Jp_Q&!vsg)T1A} zBmu;U;H+b*Kn7NEkx)grj(*$J2>5=luPM+ong}oYK+m@1Mj=E+Pr(Pj*H31TCVbLgC793w*lb}06Juvo4ybGJOONP}ivS#VJ(mUGcM~0-m8kp+ z7+2tdPYLdiReg;jhS`Ib(wc#73p`~oKwvro__@OK0*7+-I`-`lP?@3i22XSK^+a!m zFd%bDxB)x`E#Z!$J6wSFOcI3B0CNxa%@ELgfH?@fd1V?W4;9?)J_l!U>O8T%=((*wy4zkRz9`m?d=7~EWS;Wpa<&#V&9mC z3M}tQEN>3ZzA@FUDjh$W*7@5MBuYwRfL7_M2eE&f^zvj!gaiQso0Wu|9tG0>F?oFq zXX!tt+EsCwRFCe0sOv>E3Qj`1F-CSKoK;QG8^EBqCY^o?oDIcU0{od8-5Bctfc~4n zhwRYNl@nl(_U&6!u6(gTW9;aK_6+K1kp(0H##i5#-Izp1waxZ2#F6WTX7Wj(@*kbh zlT`1u3wxSdD%RSW@lHu+=EsG%%ys4G?fFFL8KKatNkAK*ANrv+YoTscmwS5?FD)cq zV&E}l)?7zlA9kPr5C2d`=pRO8?!%rN0y4In&0x!c>C!5jUXqc5O)o;kverzr>4k{1 zxh78DY@|KN9s00AM9apYQVw@a8iMT-a~RpK>iOT91{0=Ft1$iOW{#96{dcAzgbB{= zY)DrWlkDZ~`&B*N7S^o6)TmJdXqt&U*)K+t&8s=~vZ!Xr<`pvw$%C`mOEMW*7UxEO zbOVdRPXd`iX1swV2>qc%weeQfV3D>=7^0ey?JMX=w0*^#1ih7JFZSd}vU_z#pb_rR zzjsvT3S_kIV0{R9978xPu?{2393je-ks2xZR$o*8S^(!zjWLAjrGSY(!k+s|Kc6)w zlN~KnvON&+%tW7T?|RsPWN?1EX@DTOhZC{tWXIW4EV-e8>>t_Eib^J1TG5Vht%Pvh zl8J8|wzT4i=;j|_j;M->x3p4{?OR%-9MMJ!(Q+x8!M^*1Qiul58NEdrfUYxrcc>dpwyuTAdUi;fdB!A<~6p{A^{g z@6b|NWyuVPyDImP!-Q>;1ZV7>W|n1up6{(6)s32bK(UMh-?)C0VM8= ziX2Q~OCe9y{Xz;;fJ!>{iODo((Y?0p+!XS7bXb7m&;_LshC?<6{B-27UwAVG?-$+{ zh{4KUcU1NfR`%nYh8BYKi%o5T=SGoxms13b!+6tBY9X73a*I7;F|-@#UEfSsER2?q zZW^W%p(4OU5OpHKys>N~f!7d!lR|I2H8Zo31G7?ufejFoF_Z7PcqQRv)bS*ug z3zaVupkg;J5umPvg+H>nM-hr`ZWN%W6LgNC7g$KRofM!rgj)t-IA&wO;bz~?yJsQW zdG`e(u%dSbidIrZ9k%l_iR_y;MFsVpMebd*phvF#j2f(HYHlRgj;b0}ta6lnV1?(n z3YwW?1VXZj5a}q#aW% Y+)K1C6G(ur%s(+Y7L8pW8-&#r7EG7*14XOIQkRFSN9? z3&SaC6bYwf`)xA+O%O`Y8s!*IcIgiD-&|r!^HF4h1)3rVsLlXyZ7qkOXaRUR1SMNr zs|4_E&afqc|?cBREOeGB&^N~Ku}l-M2#UFKiD~NTsdrQ zJsL%}wjK)vVQn7@wS7gkMSEKUh_M9X-Ur%_BRB3qY}`D%sdFr8>l$KGhy? zY(VNqH@3zT`RY{1sGDE|#!*MyM5C@VERCYBs{j#4T}L5e-&Dt_qcYpVQYh-$+S!Fs zmkKpSomiUvHiuJ;jCBE?zxfiEW!1y)c6mZp-ByC?v02)W6G6hZVX%?f`{3A4KN>(uN36t z6^rHe47y^$T1vo@f#wYP4*M;1I<^%!HCEr8*$VOpnHwp#+Hc}V;2`j1khzxlB+Lex zb;Ik(zqc14ZR5DmI~So7{?SE&ucIdlsu%!c6Pdo@ZE4T{E{fBA8XE*H?rR){tFWdZqpx7Qf`v^*VhPoYsEKWrBGQWoJ_8}~V4kJIZ-$wO9 z4b`&y2mawy!*G{-eJj_7gCt~u`g3o%WPB16C7qsVpB$&40W@loWkbbAb< z-j#t{1*5GG2F+pNkF4WRykJn6W)^NL6cIgYp?tcj5SUH|g24h9R9%ADSV*`ARONz$ z!2xzmI$6LOC*a0P!Yu)tk~5$saQ#Lgv6x8Abkq-!d>9W|=0$92I$5q+K45F4zAoCB=*|9+ZeOrDa2GtXs% zGsu!n-3)sOp>7Pm3ewlGJ4jic^! zJ2uN<4+@VVQ;g{d!*N+*1;L*}@F!-FMzKo(;Ls>a2*Y+81D+f?EGwMPz{?6h3B+JM ze-!9>o!0cnjv<#4kRNOs3tYL9+&c;D*fuN2D++&SkQIfuj;MdxQ5iQ-nhz&TZPw^( z3c_m@k@@mtc&lxAc+NyzL?`17GD$FmXF3F0D2OPq23iZi%&rm)RAO)@iLqcivv4Zj zCzDLY``T}lK?0X1*%7P!a`;1F$Vh%L21Wr4LHg!TwR?kjdKghdMr@QN1} zz7oLWI?NZqFGk)JZs|~f*$6<`0k0*%aC5*0JRSCe=*auG0sx0tTSvI~s$4kW>Nk*A!SLi<}V_W!Y;PBfPgGu*xjQ zGr}8)l)oLNZ?s9r0Y&^k11d6$1XL3N6z;hig3`s-!LLmgo`4JDmx^ov&M!3kDjL|C zg#k4%iv-kQ`)v|X{ROfUvK$}ntg^ElyRJ>dj(Uij9vFeP2!e?&DilCm)PEH~T(YRJ zP@n;JPD`0W!nu5SYiZ-91Ih;h_OjP+&pvr7mA1J)a1XvE?wS{mUsLF-I%VB-t zdKOt-4WhF0Ow8&&spcM?k?vdN?xT2dth@d`sR1Vx=1ycXVq z2S2_RfTMb37YV`Fz|tRCVxT}pANXG~^eL`%;e*&7BKZ0TI`ZVkuMp9;#GuR}OAP89hscuW2qMcP2YI6r znB1qz8sAe7LlpK4B9uVL%Ukt=VVzfv+CBpT5$%Z@amv zd~elPUt58j#r`t3^-#XBhpqzy6JYz#UcXEU&S#S%is1Xm=zwk^_$TV6pfE3;(`K4P{ELeF%F)Bg50xA2ddQP2IOa&kcC z8?7g(dDtBNU$h#3*qpAIBG3WXY4P7>a(6+dO|cvX9Q?J`XsFt}^J7fl#u0P0YzZp3 z6#gWFs5@Tm1$ufBJ?9DaocK|(M9)`8%{@&Y^&Z4cFKg}T5^TAX!xS&qwl|dv!bhl{ zc5QStlS6yJOR!V_+3S8>uw^HL-G+X;pr4NDXB_&;Lq8kQ&o}VL-VGs!Ik@l~TyPF9 zG{^qo2rLXM3snMf#ck?}V1m2-do!RsWp?I&t93eM?oz+1`LG|rs{V$o#j4_ZMygt% zCqe1tA=x1OdvhxkRJW(=x`Qc4Japjf_hxU!LsSTd`rTZ6OYQNyAR89IJx7kyJqHgz zYT(6uROkw)g@U*n<|ID$j5&c-xaC!~qPveP%E9e`A@L=&2u~l1Z;c2RnerGeprVe# z!$Ckh&?e7C#v1d`#Gnn>_Ct&_pXx*!0;r*@5uRJbA5{@*!GP#}_2cy)db$TFztG5o z|KftV6~ng51LaS=lF${dFpdBP7tMb&@gV<_xq%{4sCD#v?Fcq54-_8Nbz{@>K(xgp z0#t}oeLvU!9P-+F{5%w&dv$5$ZSFd-aX@1O4I<-vJm0y6;WfmVfI|7C6DY6nnwLxtB#UwlB`CEKY>l;b_-D*h7k z-TuV0d;3384sK^#tJNeXf%yY`*R!%Q=wZPF_}ABdBQlO*K;@m_00sOMkD#@;@JfJh zTWjybNAhjEby_xH42bCC87Z2Y$AAELOLJB|1{6&8@KmUUZ1}v>xi5l3*ydvZv)wyD z@rm$u@6-TveA_Cs1Ca^6eg2-g5t4|HQTfkGlgNc^SnAXr-r+FVru+^)J6w1d)*sv- z{M{VRz*mKAvQx%@!kylYu)diIsm+k|$`GxCzHn|340r4T%?4lLX)7 z3gGN!TO1=}{vMY8#Gywh(3d(lk0t z-U_AhPN65;A`b-UJvy;X@<4CSvzxMN=K#-v`vY|)TbuoU4Dc6u*H)Ysx&+Vi+RSPu zw;Saf>KJ=fC8F-8`-k04{-J6G9PHsPnKk^O$L30wtr$akD|p4dRmoq?W&G!rX88S1 zckuNyb2Ei`tRMtYyM%8$Rx%zm1OvySeybs_(pz3BCUEV!*~#vL=mnr&_LO8&Fcg$XA+i|6$iVG?;Nj)>FU_YForSEhAL|ab#9<+CJ8%x&Er~ckV22Q^=zZ9oKCBU`S@ZI}!6X3tt{ozkISA;`1_9Wc3 zwRv&^@uV0wX82jKe@3~3_ixO7oa^o!Tq#N!3wN|@M|vt?!rq@?XU=nUCOj~2b7njb zoteTYN`-9yo+Ht}j%1b#@xX_kYTMs<%Amf+0d3Z450QBX$mRCF*DS}|iHo3%Ou-`a5 zKVj;F-fE9V?9@Ea>rbB$aL&ymSYDL7kijSP;Tio1nTN-}<6HPCak)n$g_lqjJWxlW z9AUFJkHd2p_*u0|xkonJi;%1lzE6eTG^S0Fk5qcpVZ=Ge$byDmO%!=T$=Jv&YUEUG zq|6>a;P#Qw0A#EO2yf@51HY>Otq4j3`!ya76lp?Tu$2oOtsF(IglDahm8+T%c>3cY2`oI_DeColk0^{McLLKPkUS(jRPp=QgK>Ix7K&ZiExx-i% zaH~@bpf!5zP&^cBxc#tKe2;sA99Sd&!W4*hSId1pB;cL9M^D9T0R+%C_Kr7w1l00s z9GsDl83SMIGI@+ssKyIp*TwHMRyH2=uI1g0bsZ1l7JC{&4-b$3L)&}DM^$u>!_U2; zgk(bchTXk)Q-IJR0YWbcg4BejsPrHTu9QSY=_DdOln7+#1OcT92?_xONu;PK2#-EI zJ_-Uh#6t10VdFh>=I-vfH_P+=eG=Y(lDkt*n=>=#oN1A~lii-m63dlM@Rhw)C%(VU zKR%w;OdrZ`IP9H5e+Lrtsy+4C$&-ri7I&qv1Fo3V|wNI00e>e{K&FWNp8P23O^n0HJsd_#-otJ~{g zQSLFKDvk=(q{lXADlePsbePfRp0PJ9mty1XYQsolq7NFa2fzH+h-%7I9v&E%rp}tm zvkz-g{Oma9;BD*Jm#|MLvB>Co$>@2S0cZXac#bWwu6li{w7PGavhPoL3{ar&_q*gV z0C?nA9_&&((#Mk#j5=@dWWs^X^?_+TyIp)D8$>I>xGEh0 zb-*;qMo;IuuFO{KZ08qZ3A;ttb9 zdx|oUpJ`%G7tqj^FhTRW608>mlRrKtUF{BJ*SDv^Rjiwu1N*>s|8&O?wvQG>w)ct@ z6WimG0O9+RzB9Bu(s#r|4Ozu)O~Hrq@JFn6(MM0_#?**vi5q(O0E^2X6~1{ z-DA^jbYP$a+H|<(saaZGTkv#9z8(sr4HI8C!=&@h43mo0S?~pa?3G%c}x3l zf3v{+6#E)hS3vNLLS?)3G}eTsfNxX3V1KnnYTfBPbF|hwBc9|!O`IbRR?=(9O0y^M zKFQ8`tP6q8#hhgGgU_8d9gc?R8n?H#_hbEN6`WE0SAiL2Bka@W01)M76k1EpC>r4Q%qY63BWIMI z;!FI*83h`Bz;vGM)*|&ZkwMKSmq_rmCC(@lI@#T~|xQA5FD8DrzD^+t*i%rsFEC z{;`##S1C!j(unTgC7O)p_0byc3cG)T1ZKii+|AX47k*g1Is1uX!a?JfNWnn^)KJWk zJiQxClA$w*>~Zc0=1KR%BpFOIirdG*m8}V`HEO*X{K%l#1lE9N3!y7@`ISB%C%nZB zIZ0B%L-4v+3hYd)<7%M9^D8~=I>uDg;2CmyG$F*P#F}E`oqO7Qm?`s4B}$-x*#-7Z z=MT0w<7*OKYnYo7iOj+E#DclUX$CU4thfEJ`uq&Ou|r$}dx2&nb2)^$C6c*d!W^HF zZckCC&ye%SbXpx1_jAiG zhX22?XH3I@5zR#tMr6;LV&i)rv3E0*=4DT9JrnIk*&#k=ODS>4+9HFsMKlLkOW;Wp z0}|EEGr7{;mB6;rY~*T_!POqWT%Frg%|#lmrff7ohFqDDAy?KE8~=S6G@2>d$JKnv zm0ER%Fb)laQ57u-@h*tEs<&V^5?15&>B1M60oD*YO5*((as2GHdWix5ovHBreu;J2 z&n70t@;9#D+?pv@Z{jlT6<)m&!?cBf{J9NAWteC(ERuICZ;?27QMMhn8sCVID(UyA z9iI7f@c1$IF{)#h45(gu@4g_uZ7jHK)5hB0Q&M^NC+r`e#HJ1!y`N(S(;i z+Nhg4(VK?RmE>7+8RzTq_F+nuI&@{FUTS=iKXZZ$a8<8`!b+GJmd~M!usl5e1 zn`LiSX(pA${DW+;Q5I7oki}vviwl8%aU5bE^4OIB>nVFFJ3;HA#Za19uQC>cl)d_v z51B`Jw+dqiloU>axTgC3EWT%eE0JBN*im%f8lw9RMHfP*!08Gv+uIn%j*O)XTqe@iB`o)N35DD zaJj@RdjfOQTm<~M0T|Zk0kEmd#^>0ZsGV}i1$X6vi^VfFFNf!RT`Qg~q0oKK^FoP2 zT?PNac{X>RvydW?pxSBATavxVj`BMw+zBQ&a0mE3W>zj)LH>=U*padL)AFllH+mU}ZABNwKR2)LI5t&xe zwj-Ri&XwZL3XGl1Cegb0P?S%Z5t>9f>$QeKeCrDPlYHC?`;mZkx$y2$RA^JSfzl!d zWMvHz<~AwJNYkkN4_I=7<&d;U$0PjDC+?Nf!h1X$Ip}NwB?tw3$ST<7gwJJ$U^`xO zb>Np**}rCID1dt?-S^B`P0|$$c)V>$sLo3ZueRjjOC3h9U_8%ccTvz>Aq#Nt1ABpciHdBKd z!M+clmrJTq`|Uqiyiipy4!^LkdY}npLlMN{eQm)hrPq%#| zs^DVBHSvXu9oJ@C7dxQI_}TvI8=qj}@BnPD8hTC(JF6`IHjN;tprq3Es? zm3W&UqTOLHkd|9>5(2nJ%hAHJDJ@1j8X6%|DO`+qu^>mtoG5IMX1!M9c23)_)e-BpC^Jzg0 z)h&KOMj;o|9CQe89_~_uUwGf1pls!L-UmPV6^Akz3%uWLaCVhBkmKnBVj@ugGS~{9!^>L7HV-Cj@lB%~ zP1V~kh;s|w+0PUWuC)GW5Ou{z6zu5*0=qC%vx#NRXsSJ4>UjP~_6%EBK@|4!ZsH63 zc(*xs?cohQ+dDbN+T7rGh-a>S$?_ftcZXvN;WV2#NJ08KZhsh#PzrN;lMp^4(aeW zKD9UXba+}AJG}BBA9=x^Nk-}e0xS0S(m7(Jj^)2xu=mu*iDcU0AEMO3aJ`b9p(&_p z?}-#tHJ}Ll-jczw9|T;RV}xzKqcyM}U7aKQ(a*pg^rMhcQNq)YxQN@RU%(C%v4h|X zS{eIk;qoyJmAP`?Md)0p=+R{a9XwZpw$DY-!2~qN$PEDYT^?B;I!11i=gP=U3kn{( zim~mXnSrAt{1=fMf@3<7Ht&H}h?x63b9@mRc7hfM z4FZ#NXN@2mZ5z@8IA=~3lw*IICcdygO`Chy{?z@d{lEVDQ|>ol)2yIU!2Yz1q!^g< z-mX-C8pM}9>uOUF7aPde&gdA)QysA}JjoF|k?kb7WXF01E~gNCzcxb?i@xE98uv?c zh3%lJi{_$@66~Gn^4jyvrLfrmV$vb}&iD36^}V^W1GM_9bjUm?!5*6GEILttmGC)-U$< z%#`e%BVmOOKqjM!U-+{-7={V#O}FOCY4Qn5F^c4Ik>U}Fm?mNCQQzD4+H5W@itZAa z|6b;n0li|TB+TJV2}`udQ`nHnje{u!(a9Cqlj)%j7uX)3=Oqs}0-4$nHv&=ZBZOiX ze^v>yxSd6rY|YiI9OaJDFzRD zmB)FC{XyX3z@Yq!^5tQ5+c*`t0tjR+tz|zHxPP1{2Z&Fg4Zw+kYk)HX9355Xd^s5G z3UCb5e-s$#U~tidGBEZPenH?dvI)DbF#NHsQ1s8b4tp5sbf;rjGkCSb{pwtU$VomTMPG=aqNA0PKYyeL`+z`{2PF$b96>h!bxKM@97PJdXsMI# z@-e+qDn%dVs%CR4v0JjZ%mYStCMmUEIc>d(Zfa+#6z{zwDf3o0i@0Ujukrgd@@B+p>p&2ah)34(`t)93T3dntzLQaHa`J9tFeRR*R$<6y%juu7~rR z18y|rIhvyyKXY+(B)@q(Yz}Kd@W^So*#c?rrqLX)y$iSPkBo72V13Kyo*RE3ge*3F zV(+asS|F!%KU}yQE|5Joa)GDEcDFk^s96hSkKJN-4AC13=(NX1Q*>hbE`fk~g2JZI zbezBcDyisd@F1^%7<-n&#U8(ereJSdBvP=AfhDw;U)3Gg*k)P~yZuIxhS)K)k>=nu z9GW_~4L|$YQ-jnu7RVjCM`#(Jsd{jM?4)nQe=t=;vP3bjrCmI{ert8#0%>XQqY%7H zr0OMTR&lWK3e84S`=SB+J0KHg`d|WEn%V#vtzZ*mw1SKJRckE5RAMu?i94M0ttqfu zEhxNo2u)VF@=(<{KK?ydeHOV8c=C1vyl~-BHK-h18^2J;k!eo$4VLRbj^JIZi$J@C z0X~0$94y;W;MjbvMT)8UCVn~g)qn>V;sY)9f@uYm)4+wY4Kf!>i-^bxc30j>=&JTz zDE;f+v@ZGuJr+u`S}*jHgBkL50p1DcH||BOE3tc5vKg3ur+cCg*@K#4tIB=J?KNtY0Jtu#Ki{JczPL zcFgSnKn!4mLD?p?P$W{EkAw7($X5Bx!Mu zpu*mFO))29pT=`Di{xOG4N3}Qq%whrb#)A85qTgaPrt&Z3l%A*rWH3w3eSKW{P%Q>W=~Nd$p1u< zV&WgCh{bt0MI^GNv<8mFi}Iu@u7=AHh1X2jHs*+Vd2)`JP3z(ukzSS7aW!FI(6UI-C4-VrXe3%QMB3=4n#v_tn);E!{xQkEIstmK zI96jCV`Ti9407HEf)n44x@zY;_^;z-On=_JJz8;B6-}GE&JR2Aajpc zEa!(Fi>;xthCFR7Y!>|QpXCZop86DdfnajTT6CZ6jUSs2=qt)n%u*RB>R*lR&VxMWhY zSPth0X;~c3_brzF_1I!LoM(v=)cGx5EW7Kgv?_Mj9gF2CvKr(sEX{(&B-Cpn7Of*H zYeFAdM}G?7sI7mAFVxn*?yjv{9&?=V8v;6BDgAq#<5~#p6kxpT7{_TAvjm9oObB?Q zES9D~Gu7wIzOUX`St3uAMUq^D#k_k*l2dWi;MbpUbYU$C9z1$%^Ml#lVhJC45zdxX zEpk1=?l)Btgy-nh8>wC3*3jX43VXnsEl$cQU3l?$2LwrrVv&yLU? z1$$%T!^IA>yuhp}?H(PM`SjB(+ygkya)6-!u`nBt-5(pvp0&V`L`XEP*bA0i#L$pW z%+&u6=qYTKrK*Lym#x`8?&|V8pWDOP>y{Ee?jrckeXjcd7kgp*U9s#P3lJX_;=JMA z+6cq@A)rBC8@GK9AoNx2pR2OYw~C{m2;gt_oiseU%)2;{K==!$(eaEMX52=<@KWAAIhC zOXcCwrPCZe*eF^>M9^$^sp7jHU^G-IcbJpblAA1=0?XdRoT83gZ=Ef^#81y*&e2Py ziVhSRR7I0Sf=9Nfq9Z%s*O|?y$rz_8`Yf(-z>7=4xO}m1ZMK5u7oUc+=u72XwE++b z+Y%|jxe8D#m*G6(%^fW&I8Q&$QTnAhju3S|K!clf^&%@Hb0|f*FFI`{_vJd;Dy)R2 zqjy>Qa#rODVP<^dc3N>n3GSG=GTTv)ouXJlL5%}SCqXO3^>Ru3vMPK)$t#NxN&*~= zf>TOSrX*=-$jjw;mAQ_~>h+~^OCS6fTlz}&%yZON0-}~Fe0ND!BC{@^oDRB3|+ zRmO`Lfy>~Q5_mg$M4n?7>qqMfd#h`@ND=l{-UpQ%0f5BT;@n6SZ@k2jp=JVFaot*0 zP3ItW+%jpxO`zyeer_Va$;+e}N94!THanUskBdU`cr9G?2j5*HhFe)4Az8*Hz4T>x zrQl1F;%SIV-aZBm5yyWhaJ zmn(yjG$@0SG{8~3){(_V(_$E>8!2%-MKgRjM&|R}$HSv}ll6{!v`mahnu=%nr8N}=OX{THiRUZG8ZTX&97 zGSTHZBvR1j0Xop-`8Z$pmrrO}ba~F_%W34xeA!p_h!S!d!M>vYGhezqXJ}P)dEU#H zF3+KS>GG6-@H{6<+3U2p9FN8B7D_%LQusa5`iqc)rjbj0p=spen_hM#65C}C^c-=S z2AxJdfWQRsnnKZyywDnZp*2Qmmb)}?duh8@9Gm@_Lv^+}*0OE_fM?1^&nKOxp!!_? z8a$sDr8$&Fat+$@UaQ<-$m0}y6wle=Sjt8b=+YeWgU_A$qBMt!b~?JUELuej6EXg) z7_q>O0Dsh!rtK@k?b9KEz?r~f!ba9 zNh#666exHS@m)@LhvuQ-)uC2JBQ;|0L+HJWs1>rxQ?nrWHSLJc;2deURYZ@f*qT`N6{QP0Z3iZk5JolEP4jWGe zb8bo0qe3Ev{yn!`nubLGKyfc0g9F9@s4*|xb+vjy&E_@u&CEs>Hheu?xB?y%jkUd- zGnkTurs4u`a~t(8jKd~p~|a) z#z#y^sm}X7lVSvK{orx`7h2PMJmcrL9f=;BffklF!v)YDuo+@-Bt)AbXa$gqHbcY; zI4rT#5yO9Y$C0Z4*DB)A2!}Gh3ym|B|La}HI_3~SJcA^T9TOZC-|G*GgM5du7z)=H zrfo)((Pn8ZQqX1rVW7>@YlXB~`p~jyv-DUYZI(eR&}In%z73lNqyn$Xgf>>Yu8>ws zDy@uGOUD(`YH7SeS}hG$5Ua&RF4`GXXoNyESe6RlXs|33Uudu_<3(p3iNU^L%V~b) ztRurlXCV(9n4^96%6c!b4PIay5STxErSm@>JN?-!$saoYVkH8Ar!mo9IZ9K6y@KJJ z5)gs7`|CB5YtUB7-9?Y{%hm0*c-Lg-QuYynF6|XR_}m{tgNeJpy6wJdmsgv9PV1r3 z;=i6@w1j=^xXON`b?{)$Pb;L?aT9p;S}kF44XRf_XxlKJ{VCWso>HA>#dT%%%ay8Q zF7?5G;s&u)YbmwEO1Wh!gXW--D2@n#DHC@Qyquxsa?!hh%IIBqD9ITT_8b$}wwmZw zvke@xX^t0%$cAGGHeM7IRF~zKD}$Jzj0w{p^;0IX9keV8@MQzj0h;5(1liy*bz~>Y zWfx^UcAw(I5&wlFmtCTz5d5bG_#bGF4?JWe_&>^JBM*@6;XzoN(S9|AD_=X-hJFdE zLG8@kzrvyzEicE{-JmDl_@1aEht>uK@FjkF%*`)XNOSW;QG}YCMIyn|`Ow@vcNMm0 zHWdIo$(yFcHsRyHadZu6Q=srGT~q3^b~GQ&%~o9bTLdYdsqK=N$9FA2o3kd;f;Oih zi09U69mTI-bF{9g?TKCW_Vd@>&8*T(pk2YK;&4<=AY`9^P zg`8nE>hRR>9Thf2ycC8|LJa%Olw?fYXDT^y7ya%?LDOycsFYMiom(JHH~5ctt|yJI z9VD%`!rx(^^d~nRTa{fr=a!=`+f5~b5vd)Pc2o}V%pc+EX4;Ir@JGk^inbpR+cDr} zXo}1+DTxd|e2Ru9+9{DjTXVCdsPNEzb=ATGX{TKdbO-SXV^gNH&nN&i1umRVtZ@8R z5T|@hMq9;^w>G9S!)>y;p;H%#$h2c&B=yK|J&~$1?#{xpD2l z>fanueEiRH4>bxmfam_hzn1`g9@TCJX?V70rx%OAhB#atIL;# zyMm($QGfyss+k4yh;zst$3aU65(Y7BYsh8*hY%#};b|nrfRy)U<-1iZFIAlD8F1yp zhchr7YZWbt+x(XptqO-?qy5m~hPCzp=LwIIOiRc?{8=soYdC(Rk$hO-LnHY(zfr}R zsV^1@v{Ou`6ydn->k{wNJnRye+dWyCE`d@APIej&HYGo4qy$hBZ|UG zVKUf%HNshz;cr6QUa6i3d)eou#PM-a&YkQGiw4Sdg_FXM|BI{4{(eO*>X)*AC4c_1}1fW2iF{G*}W$J`VPf-lQAvfwb zR#wY?Xu^g4(3)cOLsPPMcej$n%W6BjsIjZ1%4@4-FI+)MMAq{~ijVbHeB-X9XVg8b z<(}MPS{_+?m9X@NWQkFhc>G?iv9euqBwiAV*-Bt|alz;%ju$B}Njmd=bmI2;Z%7>+ zErP$Y(wS3~G%4T?$Ubdwi+W611E9T%AY#0K5kiC4_>=vWN9xsa`SitjtnfBL4Tjj> zqz;TGiD^mhpodqFP{v>RXcxmuG*vh+zdXObvlnY?qEZ;w;#^dW-x?sH!b>U6l7nkg zjwovPHRObo|MK#L6YVG-?6M!G+lCADIE0N5UpRz~SYzF>f`gXS2pBlMJ65PS zzBlY)8|Q^S-V1%agzhiyajA*3*k9b^-%Xuc*<1m^)0`OhSVB{TSBZO_;KXz*XM4V^ zM&0m?=Sc~Jz`V+a{lHzRA)g;%9h`yk2K3DYkBox&!R&r%jf{dk)7&|L71Jsh0P$bN z2!M=f;ml!g(>my2A6p}b+@ot`00cuDm&z6U)KYBZ@%oW`(ZWZ=ID93sU&~eaudJXP z6~Y`~^G_OC=Xnhvl=Hu7Eor*V05ZM)x2Pk>`8sRiOZ@cs->*UE6qlvHB#O{6f0jt_ zC;{4W-?VX#V+{lVPckm|C8&$fAU3_?0yi3`{uXJ;^W1A>J!c~tvAyR02Z&)j$(`o8jpcF1s zE0`R5ll_NQLvN%q_wslJjHIdOB|-%hUT9&zv#H_gDoBF|Ao;>;&4Tv#a&}Xy{9_$x zf7*emk$lfSX982_$WY8 zx&%#Bl)oCH{7H(E_ni?xh$r=RE@90n`8YO|u8tU^c38)A8$>3vPBa_1Yr%`gMI|Zi zc=5v?Gp)xuz9~7rg^A7F{>~neQ>+czd>t?QB0S!V6T>v+iZ+u7imtT{SAOy}hXS@U zG>!MhGbLC2?yb&TEB6vjU5k5(Y<_y9d&*iF3Rv)f^Ic01#}LA4U}K>5Y~_s zkgAyG^G;UEBf$j%9Q9m$L|LOiUg{3r#r6?A;sm(d`2#OKf~5PXudb6bShI1VL)mFs z6eqfO*U7N^r!>b4M1^d;nde%$Y>XsBHb#;?NaE7!4`S+iqE(3GZv#mf&G8|DY((NJ zmyJju+k+%NE`9=QO^YG?7V9Mw-Dr*vK4c^Of#tFhK4g2~!}cfGD)n^ea5j#XMI>Vl zBvWaQ4+&%=lKJJb5eZ~_kl+pvKg!|W1>N4eptoHcd zN8rU+O$mJE!S(E+zc~1o(ar(-F41_jQ*+vyVz$Q-@+hSoN65c&np8Mm;~R58Q){xr z6!@*O=;)Hg4dP?ekTWD*;pgIZ$MKraxD(lVk}j_`IGguYFsN3^ndzY`6-MiEF%syf zMGfTA*g|1KSynqHn%5fdEaX3w#)XTo-`I~7hi?S?bG;nF{-)X95lsDkJ@3CCp6lHp z2QMLQ>0`deaq#ldVI1)KalIV8Oz3d5Em!n9pcb3K3hT!N@jtVifi}tnAVOc^GyoLr zG|P5Q4QRXp-n^U@+Kx5d0QnwU4PUBvwTvIhQfRVxsa|QyPe0{sZ!V8xsgE4vfLTKx z|0=v^EU0m{Gj=N6g&_3yAECG~@H9xIAkm=Q@IK6#62~NGO_e=EOQPqWwLyCRSu_Vd z|EwdAtWone$g}-RXf`$qKEJzAP-=Mpt2W5<{iJ2qz*}76eE-}H@_heX3I$vK^7xRJ z0YxCo@TqDYwwLCkFTR@~I1HqU&EpgS&+ZuCO2Efc{wDa~#lnyb?zsv)V&u=nqlh?! z&=mQUM9HPR&>af9Oeraw7m=ZP)jUj|0;E+-%2MMWP}p@^2~^=R_6toBTA*Ivz^`

zaGwi}w#`_$aVEwEnU zXgxTX=XHy}$y!jfs29yPO1)@CbFj%`yT`Xyy7Tlo&K9gE&BX@m#&695cNHIy9tbeR zzBAHbeCAwdQiM$jZJi(!2eP{TWN-d+Wk9k!W?M{F~iVzgPkeCL-eu#oDusZTkj=xNOoIHjQ~%tk9AcSXyc zW7W7qIawsoZ1jR%h0+UdT*%LLi8CvoWunj}R$HN5NcL%^kwM9k{b{8iO}P9(fTN`J z;rMeZdx%maGy$Fuyt3MIIsN)S*ron%4bBd{v%Ug!`1V5;HZ+GTZX%EnNZokM{YWq#RxTDJ< z{%8LLSBT$7@nCzWZj${XeG~Qzv-~`l;F6y_dSDl;B<8Y3p9F6tmmOH&7Kkb(O=N-|n83q*>?ioxZx zS2oGzv+cAj=*TE_tHIuDo8_%E93In8jzZ}d1t{Uxt0JV;qnKZq}kJ^ujh0xx2cEp~||=k_|&l?*=~Z(doY+|)rlYkEB6 zH}^Xm^WR^0{+m^Q3CQr6rsx|7kQ9Ubdxmrya}nr1k2t{blERZmRqezY(|mO994|@t z%=VI8V)H|vJNhNL#P%074)|Vh4gUKFo!zSS0bm|?EBTOff*viPQ+Mkh1YJq|jQ9wJ zJxG!`4m~4h#*a})yd-CnOqz{Dj|iTq!(NhI=SiSe1Wp8Mlkagyv^PclAT0Wbz=;VT z_Udv)2T+{oh2YJqlz5}13`wNhmWe8;X!+s`6)pcI>mmm#81|k!px)j^4jOXy0ES4u zZ;@kz7y3po^oqPRIA10-;y5-8oTgr}ns#z-QNQ-%+9|3JQ zW7mq}rR(a%vEH;0;%&QG_AlT9!yo>oK^8vV1rEzCe9&4l4zdTN;#v66L>(CdnJfqp zKaGWtJQr7vJ2n2t`_3pGq;Bpc#UjC@9C$kH1;c)ZQsR$aYWT1u;F4IBc*GhFI1*k>k;n-eq}0hVo+ zz5fFOanrcmWC784jdOXhc#ZSb&C;m3M#1`wny(Dl|Aqg;gb~zcj~>@Xz((8K1lDWH zu$2@XPGK)@mQz^nW;un;+)Q?gPou>_dyLzgX#-F(d*66Y+5*Wq&?Jj59B7ia;6Ou8 zxqUrJC`DXAeRmc9?s;bqc{PC1upYR-PU0gUjZIU3om7&a5z$S74_^GS^P8sa1mxE6 z=V|xb5UQQA!Yxu3Jne3Vzv^S2`|C+is>-vlT3wLZFaSQ5U-`NXZ~Td~!hy1pr)yQ4 z)!T@!Ab2mulSa8OPXT;ii9gzO_=E2xXU~Q&e1qb)_`)|09u)Ut<7MZI#3jSa#Gg;Z z9jtiaYoxfl4lk0tE$;ontI~RiYf|u1oRB56;1lovXethbaYPzU&}QNa2aJ z3*syUp03y}_Uqz4;Ah1~C)`YSTx?G5-7@Y(XL?=o7NEAK?f4rSU zq@QIroAX!NoWGM~gM_@Xm1@p} zKz{0~^PLQT(C1YgdiH%<25)-J`8soMHFJ}$!;WV2)IxD{4E~J&*4Y5gZ1ZoO4OtTl z0OR_F23zI2^QE|eifsP&5LhkRGpbN3j8$h-lF@^B<%Cl5_xH{+1#XWnz3v>N4%jM} znmf08EQqhX;e1z_%tzdGHf2*O)95liyH(tL*N(?cZWgY-uvM&mCi7{xoX=HYy%U*# z^EanUd5SOl(HX~{qUeO>8_BJWG;yn3E*`g4?&@CrUuOZ^N$cTi$kE>`G{}1?Qn&f= z;O^un;I~*I)-qiX?f=>NuKLfd{M)WtQ}z)>jxst+W%L=!sCmH3t+0!wY*GyW`&VaL zWrP**K0wM&Z0TU|;p?F&uA5eIy=$;>(h%41UfMEN5Rn&uh^*kcL{p`@W@FtADTjlC?@2&D> zH$T1F4M4@qZaPo>L$3`him?G&J+{Jv+ZcJ4y^JvySE`i|6JYtOn<>c{L0+lU2r`ft zg=z8fk?A&7wLpbO-K@1vJphe(-TAoqFE+0fjBFId->9zbS3i519~l&zz%El}u-z}v zcK_Db?h{V8iQ!A@zSp_cvV2NgMj(m-+KS@C?ewlqA%NKSc^H z`Y)qx|7qyNr(B!M!d|g8Dq>o~sDp$yP(pZqEv<_RXi$Yd0JLJzxw+}VApU$! ztqE^hQ(L39eud}n*K4!3lmH=1B}LSSomKw|3c?W@u4(CCLu&zt)Gmfa(vXXk_q;mBAbS7|d~M z4J)G+>P3UMi4I^Uh3O=Ob@3fwIl?FXs*8NR8urmGp-_{f{iCTupXBx197sgzwu zo5fbq!XmJvz;W}sS|4@UHW@edi*TEW>ny2~0hM`LtE5;)OUXD+-)%fTNgtw%GBSj7 zLVSszp1rF;Fz#J_Mr2S0?=KQOtpU4Po?@qHiU_R~JgFrqAMs)JwFc}w&BVaUKezd; z1obkY5sUkXA2+Q6V!fwUmk%$AtMEwdX{iw9l+cMT`j1vF-lk-sr+{YYZJJz3yUM39 zAvGyFXqHBl;w7yzX-nprk$z0n>gW+<3gQP$nc8+_1 zG$+~*V0UAl+gj6=D9}aiK_!D9Owt+zbleWRk7BhbemhC)tTz_)P#udQ1ab)BH|4XF zwZ-gynk-B>-Da(MA1xxn>IL@n;3$%4@GHq`2yYpN)v*l|`55mSF1|3{HGI1atp6&U zwVLYU?Xq*v5fo9uXAu%P#Af9isnImq zpxix2v}=FcdQk&qw?TZN>^4Z*g_vX~50B-v(Kh*2`j;y&2*x+I2bCH;1T;Uao%S?4 zK)FH9f1RWljO5)b%u}QNKzE;%>c89EFd^-e;I9@W8Dmz7TG;9oWZ+o`4A;_2jQqZHPaEU}KuLh{XyBo+$_o zf_gN?V-TpZJLKIVPLgX7m$#}?`gWdmATZ@w89!Lu?RSW?GEUVU&98OUnz3HAme5Gs zU25SJ9u1}C6i!RYDcrV0PT``AoWkAWOZ@aq;n6!}FK;h0s8ZDu2_E_36h4urc&2c5 z$__rfKG>$yXfDp-&+Q;{_#D6^_In`#IEP1bt*6$k0%mD$Z*9Cf5pE+8x4CjF-Qy@7 z%9a?|JlsoL$~MqsoV1_pRUt1}HRs#=YNOaW6M5or{ArQ`?TxeiJwbZ1ndY|n zf$qMvLoV6By@O|eq(7iU^ST4HhU(27y#D}gkbcQ4FJt-T6rqqz^S5a-4sP#SYyLuu zcn3Ed1!%Br5S1Pswi8ltU<(&tH~_)J)|pzO%{Q)LL*X3%F7R^9k;!{Ms4WXIwV#~h zBOlgk@pgm2pKd6?d3qDhGKnO`AR}*mC7U~}_l@d&%|n`9jo;~!ZqUP8qSBcsKdjYN z;QC;<7NxflsA*rXO=uxAI!!i6bhqKf{WYEEIHIca%j;@4iS8%rqR9G-FBDmS6d4(^ zK{j&8{`nDYvtLcGT$pMEUpyS*0TqsBjKt+|XA@oIcD z1!%Bt5Qptp&_Zh%y+c&RX51;huo-vWUGpCWro7um=v3i>50e^h8xiw*^Z_sMgI?eV ztvW)d^*}yk3XEKfM`=C$P4Hm2RptNs!Rg@bAJrzae+rpO9}uj+mWijz?JU$nMR*%<$|jZ?Bq#%MOa z=wo{r$FG@VwEJ1aE+Pnw1=Qr(W3~1?%T_&H2@>A}Z2qCjcmR@w@c>#%8WZpCL}Nk| zWu!6DS)da?J;ua4a(uZiN>Gh{kFtigL|00w$Cd!cFZoFb2lS(v!jw?@2+~QwQysiZ zh6IoVG$-EKDMA8GD_~DR2oD=DoX3vWs;OOfNy}oKpn`IdM#;i(0InH4O_M8QS(xcy zCUkh?VBv?=o3r^89qxmfBT{fa0@cEo$l7JW^3Qr&5VxMM2BC?U$X3%F5Pkwrnivqs zpUu`>Rf-{xmyUigj=e@pVJqyhw!#tF3emI`fR?@RGFDy{o~iV)Mdk`9C`Dr>9f-i4 zwk9IPPFpiskYeLQo`!g;sUU17>A{nJ?o$m(kw*tJl^}J_F5KFpJTFNsy5kBDp#n6f zpZXbE3(;3=@X;BdPx#eoiUw;}O|+N{Q-ynC4541t;DEv~!?ryOW>}3^K_;H@3MZ$k zB*kdVyvmtj6f@dleo(k$UX`}kon6vec!$@SqBT_N^Q2iYMU5E%A)=fqTB05!$fI3B zCG--bESVn z*~B^1wZRs3z{qjLERTIQijsv*GMuCs6jjnbGn!;rACHmt$g3W)*O&!H+H*qeb=AqQ zN{=i{5I}`Kgiz$O(rh%@Ak>|O4cmanJpx|!d{GbOw?KTM{1!<05fcsM=QYvVO0l)d z)iV8diptqdh8(hTwJ?6MEp*6v&x6IbnR16Mu#uz~j8)QNqnLNM*PgWbLE$boI>l;l z>p16t-S(F36dt=RkdOKFs*`UVu7&Hxf>7F0>j>q_ly70J=OwW9@8zF&deUb*Uct=b>1Kq{GXd%G`GBHZk5v_uMsz8 zfi~Ws>DFYS_96?~4Y)i5AR25DG({L}JoTqR5EXt=>r(K9BPgR9$v5cC%d3>PG>~h5 zYk~aQ*7!&smZ%S9^#}@Sz4<}vPTVaoHpyPBC9)J+1x+^pRSc7@%@S=Y>rLz6M%?bZ zWPgxU^M;Y&;Xq%Vmo*(J%&q$oq(A zKVH<@7mQG2Z2mct=3;9AB4baqlr$F=IG!n%k3<<``AB?;pB{6u^=>)RC5jB%e*#2; zM?b(`gvYtX(?X|cvM?GsJ}vaoZsVr=^E6*BBkd+3sLOy3mytvAZ_MLaN6`rGIV zFC&2#)r1u!kQdmeEmI;i0i81QHl+&9M%-3#nRZmrjpFn+B}5??je%I zA*Z@XLHdk<6s^U5cBV#aqMd0MDLBJIC%}WlTh?hmDiyQ12bMTCYIcRSrfASgZL!C= zZ;a-^xwyEJe-&yUDgk}>z~-4jLlankS^!qVTX1piSWVwU+I+|!c|7g}X>-_4`re?H zaP3&}c5tD>I@YVsdQwoRS#jY#L-<2mv^L7qeAyQ0>yu~^RIY4_XckaiPPww%>)q9! zd&pMs@`!GRgm($xz*BfgwM4eM9F~<7%VvLA@QrSX#Q|J}Z_|1Nya51l6a0~K01r}t zZ%cq7X8GU=Ka`Iq0opijgueujx!_~#<$zwKK);hfg9%U`w^wUoh{7P!#&h6kpAx`} z_i72OY7tRXZ(}NOYHtVluVNdb63UmornNLd{QwdIK&Je{bD2&*tvJ#(vAI%@FMU<3 z%^FY)=+D&k0asfT$@ny-xoEeRBGtqYLyv&oMTT6{%R%c&pgkm^{lAG-nOIN^638wG zaXf)I%@2KdmFaRR)0GsWPp0tfk5{G}{mZnG&{NnbTu1EUt}<*`Uekdi#$U%x01-;LQQ9brQ7{Ox=CfIna0dEEb1rrA}TTs~f4_MY=Efp@wDn1NrK8^lIMdRj&dbFbL zl`Tg!h4r*llf;I5i4B!FyYbMY+SAGiKKm%(%CuCXL>d)_8Mp@Xk)_&TMn-8AxR*e5p>l5MQ-T?d%4|_}NqIBbsEpPr=Ry{e0NXaPIrC1(OxqP~LkkW~N z`6tIehflhCHw?zFNVvWW)1Cba8$DXZ7m0;>b+*&kt{`c z+cHMdRb?*^JF4|4Irpw+Q&_$KqmpsqL2X%yuYC_z0Xp)s_q2wrv!yDPLA1oxey=>D z+h(u09wM6Wd0(reJitGCAA)p){zr8K>i|pjveV$@KFPm1tu1_Puf3&(pGR8d&fYW!-t~}y?4=XkJPyYe6?aJ++fZE<)4sjQXxSt=ysh?_zei7q@ zWWtFPk~PJ~I|qe_@Q{DQx>;%W8X?S703(_sA6KfXRbMkpSzI2$uV2u1SJc9e`%Ftw zSuW)m+i8Z;PBUl@-aJv7;DRTY(o<^iJ%d|47O?s?g{SsRiDzqRNo+1orM6W{&1&xS zO6jdGe@))74LDI;CY(ZCAvDFf66D=4wDatQ38&b|<(o~63l?Zqd6ee{?@*t8Xst=6 zf8)LcT2tY1@rh9-7r)X*tLnF}@%z4kvEX|v459&bWMBWrXs@r}mMPB+QNGj_$Q51p zwQJgNg;jl>bQ+6+P*;M53Yn=9I!;<8JHFEf1TcrS7U{^ zI%<^6LmaqLfg|zM*R3P5!OL@!7%>tDKP^bbk+=mf>l4yh$+9+SbD!u$llEJm78F$| z)2KtQ@QKr&aPWlNeOOhtCz*x{0`vzeI39BkwJx>kKAybSUW+xQ z_=WyN4iG8W^2Yv`M*HO6`TG0BISYAMKpiC$VWlRws@_Gd3qQpHlBBxTs`7|x`hEPn z|J1bexE*cb36g4h2Y#fQZdc~=e^=8Ru=x}x^85nj`Ni@)^WUrM11ryTj=^*eB>PJc4)%MBtq>q_C$D-J{inJv}pU3V{;xMFLeLvAH5rD<> z2X`cLJb&;9sRLz2XswbP5eD*(={IWfooDoPrkU`IZG?XCxt;s@$cyk?Sy6%Bhcz`- z!Rs#c>W$Qf`}wBfdJ5}c&Bn*qAopBpSRLN4duRmfWhv4D9xBLi^0OoK_7S2Nydv9WBp1pwT*VUVEgbHU?FrPadOI7=Bs(vVNg z)Z_n8Bw_nqu`I^|z=uRUBX>7B!G0D^{biqAvun+-N9*y*8XjiTSyTA7Uq|uu!wl&=ikmt0(u%jkIr(T!Xp1dqT}nCusE-1Ul}RxB0>6{v5S>2>aPo z+N;pF422FT0Rlbi3|>YcS1RY@tWg(y^^!~0Q%YT(Lt!NQkSj>4N zDL9J2Guq1ixm3h{q5>*nfANKi*uTWO>W07~_d*}x zg+4+;Cu`E))x?0>`b2-Li3e-zo7iLl!PAPUpgAu(z)S zR}tZk>Fmb3jbDDGWletek(RC4Ia(eU98c4tF+8rJK7?H>SL&-0xsdoP%@M+s_#hh> z6005{(#LGPTp6;(<;s$rr2WO#|vI@@a#r_Y)xLB!7#Hl1^#nGB=Au76=>V}iXCIK^52OND zD!1}|&Gp6=u)#dqSrhJi1#z`0SP&AVuN3Gh6K+aR+3%4y{%s5WNw$tAXSUP_RfYg& zLV`Z=lPUU4h3%wRKm*eC9bWp3HA+)e-x}pnS`*hO4~rBWk5+(^w~HIgUv8skvrlM2 z5d%@q^X#^|#?I3W41pYKtLLjf9uRJ0UG@{r#&)_%+v#sV?UdDC@1cHwfS(%$ui8Oj zv1nn!f-xd%ij7a|pf@oW^hJg~JRl=OXAh8TdM9+$7qFCrMEiiT4Bo#Ju$4@c!<$7V z@EluUU0BO1>jc`@+mtJw2kCy$r+vzUa9T%C38u<-rL!Iz>1!3^7VTuHCD=1zL-wpG zkNoCyYLI#w8Ww^o z3cT*u9sIe22YfM=5UTq|d<@rr+~JD&op}#|;a9bmdJX z8IDUO9$EujBYEjO>BX1)`Me&fsNsjC8xQ~Sd6YjVvyVWK!#Mh)Z|0bdrzkLG5YhMNTCC3Q$bK0J~9&a zs5UwzZ%TNxOkc>x(z>|)qiKJ=BHKSa!gDE)`EbE)M&}+9{_c6W+`IlEj1CkmzCVbU z4$w=Lr95|_-iYN>5>R}Lt>RlN#TP=vSE8(pYn8y``htJ3aEuGJhPuzMa=>t<+z)8u!&g$Z48UOfo~9X zM>{u+rU=^!9rD08q@7!Zh&>8&ukc=n5twE3K3Dq_Oq`ay;be*oLTi%c+ zXB`2Z4k`*ohbAWuDLZL0+EM?o*4##mfC*;f7e?#T*g=|XscBeXrkb~Ag{Rpl6^43= zHa}<6``XS5fapA)6JO{&o_oXUJYp|FW9=Vr$j(!DjK08c=UG$X&cid^`WW73lMeUQ zj0KD7JIX8eqW{tq(TjLe^Jzl+MB`;#CAkKhd6lDPFAF>jkUTzvaQke2u(+!q79D5^ zbC^nd`i^QlETeMut=TvTK&~%{(aKUp1~KlY**0E0RhO>{M*F1;mRxjQz4C@fbN5Wp zYgZctI6!mDUV*HK4ol6gF7Q&#{gMb%Zj8qG#c&IK>G~ImX1tP)I!0?#wVwOtD z#0?WeX6U`uUPt5wV0~yddN4hX`200>&=DCeKngHgaEiY>Q}0;;8`skC>u2d9YU&Yr z9&W6lg7VRkk|q3kxy+b-MEWI9(`?XMxX&)8cCc~;-I9U>-7Dgi_@OU^l40DWX-YCI zpWXMOJH&0$tMM5xg6V5j`33#GDsO@qWFkzXfvLjs}HVJGnxo?sRuw+#Jb}FN(wH)T@Wd>b@v^S>yCRt3B~lrGD>2jn{?kf!|_z^UnJ5j2~X4cjYsW>ko0@ErS2ONOvkW?#P1`-VqD*AQf)0 zMcGEZ>FXj&0#_F6ErO|NJ1^FU+)L4hy(vW-_9p4wDB6}Hg^D)hO)1)-H*rbV>%4TQ zRfQQAxy;%sU1e49Mv|97pa3L;7pZ~T;YDgIkI3cBd>G}HJ9^vvbOiUZBhuCieNoTP z@KYdf!#(RMe`VYV;ho+GM|AOWSR-9Z`NNrw(-iN_wv?Bx(EDU8BAFmT^k42VZMaan zi{O#&j33PIoo^C%=1o%-uSs_3O=*(7Z_P%N403%7rJq=e5Pv2@s44YlU?#zZQUKsv zD7|h0VE7zR#^=`jX(>b8n*S3CIyPZPi871!!PQs=Vl&V{w!4T4{hB#%O6%|xzqnSf zr!?eM*XfCBqodL=+$jj7U1C0^)aTMPx8P6L=UHnuqeXl!O)5-jvgf$uZXF|mtD|%v!w)u>{5P^x|bZ44$dZ1X^)nv>yOIb zw8xr_y$N!C4$cuv5$WLEO~=7>7J{(dg(lSBu}3}nyW|zUzIyQ}Kky1D@MnesFA)f- z0zXM9@U6^#MUznt-PW3)(;{Ba#zp}ett147y7;H4g1Y#Z_(EO$>woB?8<-JZ&DqO| z5mChY^uRqRJf?J8P^kxOu=ql-!KJ9;{=Ar>JN7>IeuPBNuhDF-`I4q*|v` zy4i6g*C6X&crZcy!QJ|EER8^yi?V+3xl?(+J$hf(mlj61#c$zK>b5*a>!72NSt=ck zVLW#)EM(3q)*oau%9WZzOO0bI%N59%1=L}sa)Hw?DO`CS7C8GuW$CZbLUMuA$*;T) z3!I{ebXVRIU*f07UFlychvrm~K{Xo!#=e$BcjaxG;&oS)b9~u;y$<`3=AyUqL8;Fa zQ!fG@aZnBkKyL*wpPH%nsDv>V#1|dXYpQRTN>Am6m4)M!B%i19TdDL^ey7=>na0iA zzktY>N2XTNRgtuXP!bF;#gugKyp-UQqBry&iW*ynE{PIbl6gdLp;YNs=5a*2!|chCh`EK%&DERmk?(=Uy(k0X{hiY8tH@%7$A1gvKx6#!tUG~f=Q3$G zccw(4-TbIXp_|o=jI@H^)EP+&v(^ zPjARJQkqb}YpH;@`x9{LVkuw*#rXR-t_Jd~lX_$&x&`5a8&c+!GL-TgRw=JA7|us2 z`<7PD(5hl8i;S^Wea~0bBP(=IKo!wF(aNNIQmah5Cw_W>JEqL*o;2tEc0&xR*?aon z3_nHhg`Z&y)q;=B*FGjEW$cQ1M>5Ck92^&%jL7f}oIQ zlpmz-=5GA}qg1Hxb4(^# z>Kl#;l<_$xvn^$aWAcCDK)-}r>KlGZ8n%q>E8)8;OQ!Tx?xyqr5?2uY5_1eMZ&GfcMl1dK zbC>n{%4lAAS+A!)c1)^qv_MDI_(vi}vH~;CLRPwdOBAFvpP)s2ehLL>w2M3XnAFJG zq6%u{3*rkk@`Yn}*T`FM`Bq0$nYx ze5t2OXWh^;58U9b@^P);t;XY8kbp1Htrd`0!5{DAS|Y{!xK@44bHhGWc*_kQb-@?t z-~(Tv8+x@udm_L_!pE$9FVG=)FU4>yzpuD~9&hZ&Tg&lA^$Fr8X1qOoxA?+qrfuQ| zRJ<1WZSjTIvBrzL`0(=4O!0*mSH3I0@W#J8;<`4xD(sP0XTc}lg0)&)_=8s^DdHLp zyzAu`v9lcy6dV?Nh;hI3M6neTH&^~GHeKMd_Z6{_hpUJygyV@TDRV>&2ZKjrh5L$b zxKr5R=(jMTcwz_-bl(u4KfhIS^BX-@VW&h}c!mdj*zoOR!fZ|Eg{>n3dD8cKG_&Vb zdwSxeryhN51uO&hhZGf#*2bS4TE@OASNn5I?KlOiL{+&0Xa9J-yI$=8P$RzkVAnp} zm5|bsRXy$@;Lb7f@|{YOp#T~J6DuCvftT;<70kRD%D?|XKcC?b_{xd{FOG5z<>PMX zS6FRAwS4Y&S*MgFwaIZlytBPNYeuuti)(aT`UoT6?i#MPJubYs7QAPJ++eQti`Dt{ zTY7_t1W}6)8nt4w%kss<_ZdD8Ft^NiNQw+D%2YDm(`A>^UA z)I@d1aUK@{7t`!22S4@MszK_u<8uGsvY+p-$VwY3%8@_ynjsXu;klZU42|DfNu~UF z&Gd#PHUHM574;mnn^;VP|Cy`fGkL!;Era-Pcl0yruZDKsraYsA^)uDZfD`D!LStW6 zToqa6LGCAK1-jH*$NBA_YBgZDC`NRgqEA?K{rYj~o_+_a_H(V@Sp!i3$16Epq({Ch zfY9!dc*0u+9j0%f>e;w7!8tliXO2sU>C|y_m}2}0-VH#-V`7ei%cJTC3_qbPkH1-u zjkMr4LK;I)2&G7K9kmi-0xTaBGbI^~TvVw>9>XW3yBhEZYq&0|FPso10zMUX!3&I@Ss@rVAoY;2fq>QYR-01ez3u}0RR!Qz~N}Wx52|hT%#-CGDCxp z;k(@~m%8Ny&;QXG%eGLA*x>Jo6xw>5jMm!#Rm2i$gHYE{c7fItW_{#zYrX&Y>S3#| zJt12in8#MnJt13t#tG>r`)LXH^b^u}507xovvg5Blz1t^wTRU@NiBIy^<6I3xrE5b+d+o%FfF!CRd;^? z!Ovx-$1+-0ZVGXp^mjpugrCiEE+TFWL2oPFAuaX2%YDfeH0jYuz>57eRFM!mnB0{jD zAVtwwP=f^#DM4vcLy=yB0s^A^W@q2sn|HbReP815pK#3XPTSep+1=TFdcA(#NmLFd|4)YX8jE_{Pw zkFPK*DOb4Pdh1G!E!rUp#+>KZx;iSdjR=M%S<6NDd>kX>2l5#^KksYZ35>R|7RXnT? zx-@n3f@DV>RsTW0iUGv%28D$f-YM{fzzvGdv7Iyv*t}Cv^#^%xBJc-tL1a;iW05wJ z@`(ZtGXxw)OHjZ$U1Qg)Gk)Mp+vslXDO!vIPBR2Vk2_0BXf>^|-D8`mlYWpNQ=dc; zpy^)d9@|%Wo6kvg)YIOjrHKAbihiwM1zrqk;$B!9r|~m&9rXnvd@#&H2y_A$)aC`% zRY6YFtwm1MtuMsRzs>>gU;&%D9U^tB1o9*G9a$=LExvzI3f|>NM5c0HjyHU9np&fA zL3dz7M}DXkj{Z64U3UcUmgb01BR276v!j!>$W6o)#j%q!j6girdrsIfI*#D^uA5P6 zwM~3(dq;Y(u(T09^K$usbcY*e%^B$qms)d^^fsiC3@I7G3<Nb5PC~2O7X*CE5V}|=c>c`yDc1V`7@Y|IA>M9{xf**|MM)cnh!Sdi&3_^+G@%y zrV_6p5R)r@_M3zR^&MYp`KFbl4p_^%R*u^0H)X8Fc#Lg1!6>a|Vr$2X+K&|MV=czB zXB%l1w3dSug4VK6K>p2I&O-%hE$0nuIWMi{3dM!i@;kMbTmKttiIVESSjJk6g0qIT z>?>m}Muk0;3Da6ElB2ayEt(QTB$ILvHJ3&|LLr(WNV!%;i%MF69L zz{geAv~|QQFXrFrNYduf_Glh2|7bcBWidZ;r=uw&Q#5yVa_Gci7;mY~{L$Bw7zNM& zC_TxeKl*wSqr$_K1JgDvqM~h3wV5I+{6e6`Hnt0VXdA`i7urU#U)z}elB)CK)3s6p zcK-;A_MDWO+Fr^G^ntM?+=d)(z10IvkDy30{ZtGU@^NhXTA zHWQ<0$mjNSG`1MU_MVObm0D3IZsr9%ww9JiN#lw#Q$Xk{APydqUK^RIR^KdFl%Y?= zzNihP?Zi0f&|g5rIH;^P`Rz}^hqn(;ie0FVgQqc1LK3isnXV5L>IwYj z!+&Loh_{8+Z#VPlCu+E~?^^?MLCwGVELaMzKttI{BW6g?_yM{PgV-H3Tc^e9h^WHZ|raY0#ru#%vZ6!tU->B?8D?zC;4p!EgkDC?S0@hh|c*d;QG#>sQe3t%+S+NZe zv~8>-KJXV{hp)Z`FCOorjG<0<5S<=Iorcjd1r1-{ZFd2#R6hIVSQ{^z(!ElBuWtQ` zAATN=EVfcsP|24Bgqq}LBJ&T1lE(!*AJc-ikb(5y=vRet3hPB6V_0MEM8`Zut+$1D zc{aA4)__t(#ifb{#?DQPE%Gu5(HwU?=6JMH)|j$IDk_DNMn!cI5UQvo$-KTr4%>ec zo$dL`9u7Ajcp)}d{#yTHY?wBHqWW+2*3V0tm}H?o#nDs=dTe$6HWJ5l1X52Jw18s(r`&R<;Urp|ht3LxZF|Usci@!%bxP|9jk9BK@DOJ?o zexkk8Tlj|N&PKl4dn3G_vPV=)#0?hscsu+S56Uo`ucXCT#Mg*VbA7c1qvOc!zLma^ zmBjo9yOshM*GIzdb>erH3Th$-!2fy9@n>N3t09ANk(4Iz-U+2Gx;pA^0ij*pV5TZ<-=t}>%CE7^ZPOO5W zu85eNwi_m=_l!LR~x^xbdSr9k}|VJQMO0Waj~1JQI>P@|J9s zd9DRM^oTc$O1CV^s~wx3gzE*u^MOj4*73bPVD4`HteiGav%LeYGP+J4b~<12{zu;A&X|fY_%s4_)nGJZGUJu7alE;ntxZ z-zpPVk5fj_8iKd^^y(4A8V(uOpmWC%End{}uEvEmtQVN5HPqOKR-_z4Yf$%Z#d9J! z$_C>w9a$G4y~qoT9HX_N7It9!F?%3^0AuKq zD)GvTIAR0s!K)#Q9ZR$)2y#5NQ6JeR9|U`zmcS@6-W!8rd~YnjOmS)2@b-Mi5;*ah zu#Klr*K_TDIL{lu&3lZ~lE)V~oP7QF-D5ObRi5JX-6l?P`r7f_CQrQ2m-nThd8hdG zJ-<-k=$bfQ0BBG3r(De_h+C-rLLs<&Q7j<1djY)QcN%B+b#4#1uub7J7C+=>w1Mpo z_b_Ff>Cn_0Aez|v{9e>Dj&k5cL9Db+ZIc`Brziq*r4_kduC$`JLrbr{iC3Q@wi5!5 z?MOhQ1URm=0Kd7?DoX@cTFti0l~xN%1V*K?(rQ8}Wo?%$Eej=FX#pi%X<3MPcl5R6 zR6tAsIXx2M&8U7m2-`}Xg+wWB`Y08+9Il0Jj#88Lc}=1RNh6~ zDu1FCuTQZb4%Da=$-b_)x?t{cgAO1f7V@FN-#B9}K zP?~qJ)Qltv%Krn2rdqsDTO$G5BVQfgVoVPew3}(oeacMfBKeAs9ku@l+IIOIO;;Z* zCIgsET22SywYNFj(fO%xkn~`oBSjg;=M_3?s>6%re(xtjan$e4r<%lrB%Iqu`*6@b zah`9>JX!_Mh=V?Z)1*lhEMg?m((@P~t%6z6lncYyg~?%7^gK};hw^;!3y1RjVjRkL z%khiho9BTB#MeVJzi_6msNIv3UIy*;|;%Y^ho?%@Ime7ZORzh4ekutMMKZ9!{uaA>y8!P9T58C8Li{O zv?z*qd`o?jR+mD=^vr4t2u{!N6xlD1W_)a$xa(R5t%v95ZFa~6fi|?n`^KW$Yloa} z@39n%>GrN2WV#&$SVU?@n5gDS&4B4PF*+|a2 zW@JE){>f2WdxJ8D6L1=2K$bxc-fN5FaVyw7hHtq;9=6opA-_9Oa|gF|h=bXLBFB#0 zC?K>W@7v~BuN|TFupV9e8W1As!C2H`+#b( z!=df7U=!b}{wFsyGL(W*18%!yw>QLmUffNBTHE=AT!_UU|1@EAB#df=r#b@jiEBaw~G*okb_G6Ud^MddRE~wQ> zYek!j2ux{?&F2@Lj+d+bl%KubliNM6pEiZIK<1vXGS{?l$sWf)s`3hdeV?O&wush8 z2J;DnZ~0?z{9SRW#DtARg?T?0uDUBONzvv}jADJ3XqvlGcQ&npb5Z|Zal5r53dXs} zY-wZ}SXwHF9hu5YJ_>olR7iRaTc*_&iNilT^@ZMkE9S1=amngcxKw*JqL%%tus58= zE()e_7Q6Vfzkn2z2qqqJtnfE^O?%ND#77->%i8-S|G0teM%M{~`2E{m|RsTiK zXnusrv;RV7v`VzB672#&XEcQ}CT6rk*u8fv z+5`&6DQ)tV?8;1Orb0DsEJcp<+H({l#+&xEfS@w~1>mytgT%Pg+G1J}{oyO1yE|gz zwO42fCWeJ)^lib54^6m7UH1zg-^!JueM0M)>%0$tAyZt@FY?=~d7`d&$+~tx?dIyL zU*wW?6-8q%S@(i1i0_QB_OkM|=>Fz0>gSIkW}ptJ_YqLzKRJ!%at1tGe*xv7L5eI-=Hrw#Nl_ z=1$35+DX3HKmzR-fY=%O$#$_IPw*B$xfN5R6tuGZ;L5!?;~%FbR}2*cGO9n zE=&N&nepMyR|uZMz768~C>jNc5!^{0qb@Xff7;|7J+Niapa-U7muMKb0*(lJ=y{Kd zU+8&{?kv~y)>WJz_}vQlsFJR<$9P9HZ~p+?x!I{YU(jw6HQ>5C`x=25Ld^V6h{h?f z1c}-OI6an*4_t)rlJD}dUDDATqirV8V}cCr#RSa2?lVm z*A~BUu-AsCBE=(5{x%E1JaDt1)b9MrU%aK(aDJj?TBH)8R$BrwSeW@uCH=$LGqK-l zeF$P1R`uE~M`_M(IZFMI&g-$;J4(mP0ZMDh0or1BnE^Ug5W@lbEN`0VoRZi>0O(k2 zMcKhsJ{%;U&}LIGhD3v2y}QC8(cz1+Y1&H^B}VXRrLnJQuTwDkgT(@ZJQ~;eEG^L= ztfh_6AFL7(^ar3S2%*~WzP|(ZjkF>Ji>LIYv%dx3i2`$FC z@W5^|Ue5p)h-=uhqM97998yt|d0KnDC69P0C|upUTV5alf*8qI2x27T3$gQWuEw^u za%RqzUjt_%23fURI-wQ2r4vfp11xw(B!Dq;sAe2 z;Ku>}wD^Ss{OLXA&gNt4J2&_n*N-%CuGU_syy7O{s{~?Dp7~|v$F*JND?E_qT%@fd zByfZ)YlMQjsVhM*;1l z6)f0;uAn+OAp2cVL052N4`1EHIU#X{fKXqMPZ_}zvf#Z?#bR4Q0)n=+Vh-?6uS4Ot66ahxI_Px^LgZ4^$Qum6pR^!O% z7G)Ov2Aq_OBO@vU;S?=vgrI;0fFVk7!iDIlFYN)o3;>Fn_ zG|Ty+wvmEyw)kE^kWu68!O{}%n++-mZ=&s^EzwQx5fC(G&>Wib6=}+U(yD06e-Kkv zm0zWsTrH|uZTX^M%V#MDwB=KVE$=aGc_+1H3(M#rskRB1XvVF61qhmPYw-)sxb?4S z#u|-)IAWr=7Co5YejQ+{BOgZZ|XoM=rm>1y_0bWmjkCVn4T8m00)+t}}{H zfBR|>-_gbSj5b7I^Z1Un-^35i9zY-lD>EyXt#BV7*UdRW8&43+JE?w1<&FE*xRZ(> zUR#`;&`W!cHpGjmkfPQR=0owtGG&_lt&de)cK-;y0}ig8J_NYrwNqLbN1SpmFX`bN znjoskQMOL}68|-Boz9Gr>bnvU7o7-kNz|u9)hyo(ei zj@EMmf}?fZuX4dR^={`wTHrpS8VvAm+b09O+h_@FT)BDL*nnXE`aMpEQiHF*2Uv@v zRWQi2?=$BtH5o8LkO$drzw~ydM44@%(eJWN}lT;r%*Q>9!1V1#g|JFlfO zim&bOOw>lvX69C3{yw?Y_X;gWtP3dCHwe~cqh_S5qxO-cl(M)nDdqEhGAU&}#SJdk zNJ{yX64sK^w&f z4s~X!QQsNQ8by64pEU{{93~AR;=9Wg{OK^Ct!__ljW;4wWyP+HYF0P#|z~g1bgI zA7Yt81E|i{{K!UU2cEXy7Lt9t2^GJ@Fq!#a#X~Uh*3bNc!Bu&|v!#K2^hoEKPzwbv z?r{}9o#$+zumL7%!BBTzKR2-=smqxU=;L_rMS7SD{_=TfS%e|ijU^DanA03$eWM-EZ&bRXtsn9zZ9YmQx}y- zeEEKS_(xr^pXXdn9O{qiD-)dK84;QvdCQrdScW}|x;7+Lk1o7_qH}}7Z)m|0y!fqS zL4_kHI(IADCX+WqeWmNOs_}`BI^F8e`}u(9ohfXmS%)M4#pUsTXuq5%7VwN2&Q!ua zlk)`J1Aff;4kJW)!Q=2O($)Rq6PD5WpW1BfnlH7>q41y4iDtOY~a! z7SvM*M22@pr9Fm^bHY2Gez=-hiHvaJoeHNt_IdlLo)(Cf?Kc@HLgBCg}>_mZ0*qX^4SWSVBg3qe3Erb`e z%TfWL3*8?N$a?`BVZ4YZgO+~f%;x)FaxP~92hC9fJ(nHzmT%kJ4$5qBc+_PUOzPjl z;DNWIl$GMYMmG3+2V^$*+Xv*`06(3R2YAi*qFNlp_o7%UEA?WWm5c{5;zQ+q+CjVg1#ltg)?d0T|8>7Oy$S&!Dmb*JfS_j zApq1KCdockA3G@R;Uov|`U!0&X8MwUYF5xlr4GG}sUI0O^cbJ}J{V0-afVHu2r%)Y zbnE%mD` z;IkGxAO26Ys_r?+e|p{NWP7N7g!})?SFJk@weB#~nlVa$jD;VvjIjSmtz7@IWi_7p zHh8QZrc#xOg{1|~AxdB~Aj-Q<)tm5kORc(7nuu2NW3^>trmRC~p8*T@D|}GVxaxfJ zBt3&qO*~bVuYTWNjYs4={~MD~()i}rojOaS+5x3T_7VVUtMySzHT94*)q!=x4{IaL zR&wIZe=s44kE<76SDC;|-*MJs51TbGOjO4Go7htiiBPdIm`&JnXZ^@~d^>go@4npG zB9xLfHVd-fvsdQ>pVggg0ilR-R~03)i1o3kcUW`RX=$B-=8S!@*0!(^`j8u<>Q~okh;?SP!$hSgB_xb`$`lUPXrT zv?U*$5!s-y%{R_Pf$V;tmXT&lBmZGgVdf9c>w)T|5}v6=$MfD>oK4tt(kwSt&sL|D z@MW=jyf(!wFx+#r9WL&~>Q8`&UA5KOh~=9#a9N|we-Y>__DnaHecKBd{!+g;d7()uIzil1oHol!T&dA zfw3;r7mW+zW4lC541gkDvi4L8pR*fwBlep$r5tcm*{>YGNjU<*RCwm}d#m#s`)W1g z5f9h0Mdg{=HWr}Y_!G(~gO9QK3RQ2X^Gzj)FFWW=;OBNavslOx=y+oj2?eWqM0QM7 zv%nB6ZEL+CexE~sUUBe&yPYkVZdQ>JCGcej%8eINk9fN0lB$m;U7$&etICg*z=GbC z(0~UBq*=08mceouc^~*I7*!8KA9?R)@ZQZVFnEU-B7%79ea=S%h8|J)(xTLcY?xU| zazFUrxF74~eqgdblyGUJS$Fg0-hg)^+}rt$1I~Bg8Tn=UYC7#@jy>Hf%?7#DG?632(Ke)s>hOi$dl|R>)eFHwr!v5?d&hOw- zJ@&xZqs|=mD`5g<*lozL+bl3-7;?<{Zoqj^{?_}_+p>#hx#a%rzj1%v%YED5oYM*S z#`ABG`C~O51OBsx`^hIDAuaYO-?7u_B@x6%;^CJBsVL$TEA2xAWW!&ZdFF@$-STs*jB_Ej&UhKmI7bQd+j4 z`cZr|)9^@zBZKuO3cH_B7CKi3Nu~#xaD(ZL5d9JLv7@}WmfnCpVHQh^%Vc?okn&8JP z4-(ET%YL8fIX$5!I6^-6Y*c*Vx>8tSvrma|Vm^yDb!_ZZtvjl4-IWqu7HVby+2`fs~gASKB6Oss1CV|?{i zXF6+WR*{_7Jywnlx8$~}dQ;$B%&dfSW8V*Gif4974;uxMJR(@nQa2wJkG?|E56nL5 zy~o4|ypIha)X{hJGdS;O78tts&OGXbV|>tV2-qJs>qyqemB;#259?yqA*>sZ`Td`7bc|FE9%X{>|B^@R%|Cd}daX0(@Ma0PrCPse3W; z5CLjP=K)lG1TYE~dju#{&N@3Q>@=Z>{QhR}`J5G5QP2XdY(Qo3gQH6{*VykC!tBA4grn7;Ii$A5UaVlq}tI z9Q9YW;I89x66wKnYv^yOuO27fV+o;-jK3xsf6atT#!ct(;c@9a)|pi#<7>)e9KQDp zMo`vyI3(k*m0{c{;FNK@bRLI}OXqQnP)Ei~B;zF}+|an`JN`T_eaCgPj^zA`<+ST_m|SXoEsk@TBXJUWlsznLb6gR$ms(rwo?3k(5F=h5aj!+G3p zR+195`mLNzG!})%7eQnE`kGMvTU8L>^-ZS!6oTU^>q%Fqjq|M0t{L zucbF+Pn)HZ+v(+TJ6m$=$6t^k=#rf0`EqW+hfB`Y9>@Lq3uCl&J?__E7^N+b|Ihvc zK3AKYV1^mS;+HI&`S`l}P-P?ERad`@Z6Z1lE`?}3Ny_uxZ}KRuyZkRfWX3$W){}{z zbawzu3A15f9}M%_=FG}*+m8#1n4~%X0iP5iD5NaZ{K=&%M-BREl(hbpKI{Xx6GRx)J$(59u8<`R>4$+p$j0hS_LJ&Zk1u#Rh~Pi6%K0QTO24|?TJ79xOXsT$8|r5|Qr_|_`wTs1^3Jb@W( ztdNwhX|11Ee&I{n=t*oBf#d1@juYj0zr%nDGS~t@Q6keThEMAro2-VdFo{%{l*Uc)%Oi>=CfRji`eddJ7;TR&XKx_pgsAG#`gp%mbI`Z{@ z5L2YjS;QRQNw3bw-5(HL7FshCcqS?_9IcsnQval6y5UK)hlP6JrMAp=dh4prJq1A_a#-(FGjJYkHT}jt3cV}I?U?`%v2Xa zC%~ONc9AfM8qd*#LbP)NDo5T4nLT>5yZ)ydatgns!L(C8CKJq+e*UDgpYk)H)WB2n zu5_S@#&<+DI34rB;%XbwB|j98iRiIiT2W1owuSurcyCD$h(TJt^}Z zK~>_0Fnf^HH&r!4KrN~|*h|j~d=kJsqBR`eJx!XSVNNecgxOLA{>NA8kS7&UtwOQdQ0#(vjkexsk> zf)S#k7qf|mjEaPDc=lJf7k=4aZ>_2~fuqf~;lyJ_%V>twhwLi&@ExBwQ18OD)24ZY zRwyAO+$9a+6>EK|s>Jb2L-Yp-3AY~-__Pz9XsPLVlVuwV@)(IV5x+1JYjV0wBvuHK zShC_T3fnSF|CDtnLYPrlXA|m;!oIC|wkJekS6F`&C!V=h_d_JF-)STGYFLs0Pbf{( zd$9?m9Y$anSB*I>L$JKl@_MI#WF#UQ0BC4LG~@4xXhvEITXCx$PLq&GG?5|EQt@j5 z|KdTtWdg8h4T~Zxa9*Mt2@DTCZR*G>^}|$5usq!^9{pu<(lvn?upo zQMkx0_huoeU!CTc-f`AtMP?P5t-AhnIbqFakR4JG)TO6+_;P2x$d5!zoVh)BfcU|2 zdR<0{a-3jG+uNR3Pn_m+K1gu0Q-mIdQOC=p_d9f*2%|u`eEf_tE!7fWprI{6D=|?R zZUbM=4>=>JaP5q#Z=?`>rW}dvXG{v1JP#Dm(-R7&r&rgV#=Q6P!*3sG8_U`d zjKZsxt=ZxXw|$e)f@h3zRZDzHx)lrKhKv3PbTG}9X(wju8RIbg#M^O3HvVIRBs!SK z#V>R)kDn>)VAejNyZt(txXF4Un@1Qo9n5SK>LFg4i{Rj39^qfV>5S&H+So$)?E}Ii z_|0rvHd|)Wkxs`C;k<$~Wt>hSX=gf}kItaeQC9P`>H1xE|G0?Hc@wad@j0ZG^f@n_ zAwEYmkv`|R`1K|adQxwZ2pn2{&PxIyeU7mVgRG=h{M#q>x3x30%<2>_pOH@Cs#!%k zh2P7w&)d#Qr*Qm?a0+!Rk$&arpbT56dgctzUhZrjN?9$F&Q$%ZS4QI^0z953n&P5? zG{tE?F;Y~gnGPpSAu)LYUPpl|i>#?H+JbGv852MZ&kA5bCfl0wY0v8`)SR=zsU?Mw zCK#J#^9^$#ejcc(6X0TXM&2eFpo2 zAi`KM<5qY`w5fc zO6x?WtQZSxMz=-s8gumn>IKkcS+{)UtaQtN5;m|O{}2ev>qq6B3^>8`A!GX9D3fR7 z`^2SZrEe}JXoYVkj2ku2N$Cdle+X*ds0ddp8kq{x2-I4DwyM|a>;1leRiOT2&jW;wOKPNVTJK6onoc9=5_~^)JKE3u`v3yQ}KIH$N zt~`J36Y>1^WqL-Kl>p!HqIxf%_GAA@UNX`d5x5}lvvWLmfh#uDQjf=_-Zeq_q42FY z^w~=NeS-M|;?E)Rr$qcYD*hZ7e@=)$r^KH#@MjorcQn33lqs)~oU!$sc=#ZJ>jR#u zTb|Ic$sWh+zpZz)-!IS^1_Hlu1^}%L8tTkcA3J9ZipRL^UHx?9>!R*e_~RWE0zw9b zD9c0fJ`=yzK`*&(Ok2X&JU1FL9VV1U@PC%;E=Y6I--E?>{CN?zrt^a4kxun%@DR-- zYw&IF>2U$TRDSJeTzt;^nRR*d_w{D1&3V9wY&PR_vs}iVyp|?Z{6aGxS1B{D&r6;w z4JqupLZ6_r9wvHzWHoH0o%uj-8F24;xJ41vv?=RHifuhyO?YWawT5bMl&V$qQQy08 z!=T-`U!Q8riS5fM;6JoS$KLVqDpy#U*2>HJhY-!{ap z@pcOvhO$6_dBzObr(rL*U65{wQLwODXy&&EU zSwt5z;ag!Y z`h{?T-TS8i(1lkqc5kM-^#Wd)DSUjJK3rk!qB$PN4+mGf!na-UMPU}$4sW1r=EcP@ zQG!i82j|x}D?Y!P-T%7c3g)wS>C@OalLUt@m6u>*{1DC?%jfRabJm{w$g9a!HTG@-AVahB@;=3&cI`7lM0+D(!?|kBA-!HeVktZG>sk-AavSFuyQ0suVXn6I%;bs6Y`WZ^rc7`H23o%Cby2 zhw%%y2>aYuVULSmMew0n$f46eeH?ZSa;?;|6LY+L8dpgy4dE(DLmquX@1)$%?>nJ) zXTyEkN15%7oSGq}c)n~OXx8+M^1Pf*cpF64dRwnVoC-r`8idj#{pG`0ttNh3R z7Z|Ib*1N$~llxEWZ9^BB7$N#qdI#xTccwIBubFTo+J}v=0I1Cijt00GX~xk3o1z&R z&~yG5j0`xd7qc%3B_ElLsrs{jMs!I9!s- zRWFp9DGvPD@A_=knJ|v3Lg_mKgF^a_q*O?s|7~`Pdfz3vjX01LqRjpNP3DnOW{vn4 zaEtgk4%4iR2dscRN=?WcQu{*e{MHpc+rp<;YWVO1^g)(a=y3^k<9Xbl`kQPK;oKBD z-w-;Vlwy|;x~8WDthxjbK#Yvg*&0%eVz2x+u|Jn$hf=W>z9Xf(BT`rv`a>fJ80e$a zguWrQFT~Ef-hf0f0v6*__O&wKE47(zaTfYrWLxYjmFMt#N@ZMJGQR`UObZuFSEe!ixSCr7(e)k%-$91&%N56vwn{d;0z=Gz$KX8&t8lmHeG<(=cioPkBY{84x zt0Da0E!d}|BiS=d!8xLz#;>f`{#|}$ou&Fx7SXwq!sk|VwaD*VErjP(>0gn3K}*yW z7HVOL4}Puv(C$=GMwIq-<)XAgn4apZYLDM#SPuV+Z>{q+Z;cM&ONJ)Z=S4xTZ+J;z zV3abEFRkKAWsef+F*FyCaVQT7>5c8>GTvs!?--xkEGBqc-iN`w$H??#UQ`=y_?7(7 zBdVfPeME$7lrol|3wE_)V+ng;lG%~-1%S@_qXes2>d4v zs#Tkh3wPaF8Kwg^fz9WPx!=v;hd0VYwVo3Is@CtNeBVg5@*Y!M_wckH@w3@&f0#|d zo4ufh{2|xn8Yuu-jctoyIH@>lYgKle%l-#$ThREBA5M35in`O6mD>P?Se{eL$aI;S ze|wo0ouUr^oiB@t$`r#vtizOUko4&4q;!(%FAaCc`*jm{{w|kdOMmTAh2PWHoyw-&}Gx^gv59tv^2212ZT4N{>8J`_HHweqcrLNqg|bn-1lDo~14?(r?f zWg(ObG9U%0tabiCwYuGpUF1FShrg8}KVH*SUon<}q?ud>4*i2H1Lvf;Trs!|#P6R@ z5zOEP`)ByZ6j#s0CxnXW03T-RTrU5>b(XSOLQRRmW9b z4P8v&5WwiGbRPC_UJ855gkvC(KO-PSSzMS~&&3r+8et%i_?oDVVi~DE7II=ck=Ga< zU%<~7={E7}8Y?3Bh5u4E^R;QNMr;d#o9=7VWprPWWhTMhydd4xggql#$DBH+elIIEu)-iqBM z{OegRH+M8~4PpUTpp|+4lC9pn%(qR5w^sLI$GE9|jj+Run!2jm%V9>m(8_9A33cGO zL`oJ=WEu<{mPij2#!ZY5gC)6dZCoYXenqYlZYQO-Y!GGKm-jA$Z{dt<<*LQ{)50FE z`_(>I%9&w?Uy)xkB7FoqOZYXTURN-&f%PKDFf=b29oi&d>J`}SctTBP(@8Pzc1$jh z){DTp_y7Q*#mBXEHCKTWCO1$@pl>7R9VEsOok%Q0^iT?sFI5yCo*DkW!d4NU#L73p zv?C)+lr$|Y%5dGSu=S)3*v4@79RYwd%~sa)k}TItz7^ek>ca30w%ez+y8enxWubV5 z5s~3&Tr(!Toaf?eYijE&@+MUaKDUpn0blY~IOB26`!YVWqpOrDS1tD1fumvkZ5YPi zgc0m6=bfP9n5#VdnfOMmI%$i&6?L_o!Rz8{b6rg}(peYzv}fZRk}+wlD}XX~5TR^z z5QP{|iQIZ8{1euia3T7K=)|}LOk2tY$+YL=KV_ZEZ)n_LwKPO!-moaMaL|kKDGJLY zh;TJpaySPRE63JwQV3&ftNP?s{5}|anihz0HC<}2Y~(ikYPsWT@>MymCKF`XQPZ7a z?bUYxL~A!=#0g)C- zF&Z{Uw{aKm_*J?6S*Cz;D2Lk6tHw}!7lv8@tNEwDvE}+x8itFMqSJl(sfIh%wtq_N zXh%!II^apUOG8|(%Nj@LKg%_a=6_1#XijiRy$x_R3K;ySe65-dCB;H<%D{3+jRwxa z=Z4Z@3@JV01M5I4eMx-0_;Z~EmLV3qhEHaeEvS0Uo0lA+S$NfVC)^3yFfam)t4J-bhL4;-xuN+X7+snT?n7y3T-AG@mkj)*(*PKYP@vz5T_poy&F>|pVaO#@E(}x7z z&TjY?7d+d!o&x4qC?p`{6h5*fqba#m7xXt9WP@m$8QdpX3V;&f0@Qg3w(|FFC(Xnc)>vAe=L#lX}R`3m} zwNI40$9TtexjR%_G^OjSt-c(kU6<=C$_KieGBxX)Y=Dy#X&h+QL?n+P2*nDsj(Jct zL9-quexX^9;>%{ZQtTG1Hb(GP7*98B&A9%s%VwwNtI*bSP=q(qBkrq}6!W+j`4e8` zPatw;B5x^r&Bf0@>FO>?8Yi|MjF7~IIe%Tw8y^e+z}mg>r+Pdka88Fm-lRVPAxVFt zEDuu=)(E**h(BG#nJ}I=4;9-3xaIJZ(D;r*+p{i3QI}umuJ_;x^___30*Re>XP{W-5^hVa$1TvcO=2z9`V9luM`Kb)_JsJpHkU9}6? zg|6bw=eS-B7Oh0eFrWMUU7h%r1EDQhlN%l#HsG$Up5)1N6DocQ^fRYdd|MIpd%Xgi z%F1ciRDSSiXjqt)ADKQIw!oDM`>Z(&Tyde6a{N4k%#IpxLuN+}GUbs{;`vK|zP7Gg zp1=HESgRt2g*L(s4^xM~ASL=0?Hgt@aLr}#F7%PG)D-lljEvRJ~_ zz{9&j4Y=?Aq!2KX>vI$9!aLjWyPMsQ{`02Xko)dU-f;ck(`WejZq}QwA}!@F@0b83 zi%h5nCWJ4`boWwI{*qZxZnHpejss;!rTX|4zO4`vpz761isColcFkn%O%fbBRAxch z{SeN}`ioymNlf5%-gV`$T;FDx3+2C=kqZ^K+_jiJK-z6s?&_ru{Y!554+N1#8r15# zeRJ3}-&&LYlDp)yNWqRZ&>RYI>-sfP0C?+g+`5KR+#v_#F5PA4hj-TR!`4}=_EOgv z$iE>4h#U$Kc`+$4kwd8mIdVQQxNbXk+FG@j`kR6LPf~!$p#a|>=`o|0n+4tU+5|T# zKotuGh{ifH2dOF$1;pJnVz7Fo1a%vC)7u^sy8L&K48TSXad!^P>-m?$7oX~{Gg6hq zsB^1{phA(c)g#v3iXZyO6`TlljZo`eL0J6Pld;wFFPX8GC92S&>NK@*LuPDEX__=y z8(?w{BS_q(^*-D&0?x(7>M75x!j;qRVajlB`^42+x|@e@;yPMGMljX_4sgL#dZuP8 ze)AJo1>G+WmoRm}O}S(7tYCu5)6e7zJcXFn(ecbO!D2$l=F>l`90#G45Nww(N{h~a zt!V?c*h;7a7q0`vSSlOS_iKfTU$~YBsqce6#ZCLyyrLKZ18pQlS$Z>}j=KIPU-N!! z9rl$kC7k0v7o7m7?CsMc__WVl6**^tiAQSLM@F3FC{v(%bbytd*XSF!^*&&8-CRu=>VL`Ar9SpDl!kbgkQj&$;hn13u@ShE@6W z3-#mq%0{hx3iQCiz!2ZDH#UV0C9IkH9_Xv@(Nf=x=$nt;;hJ7SNz{IZQu`6|sMKi! zK$Y5u$b2^()QfMaq`j6@#OBeal~C%-Rst5KzC3MONa3p8u4ET^p*@`NR z{UgUL`^WSqXkHBkfSOmZ;3P{8`bS#UxUjU&Jng6C`7Dbzt%R=Hc?nq5BvPvifB(%@ zPff>f}f zbvr^P2dWKV9;q;623$Hu?j>S|G9vc_a<&p_Gu8dfEP4AOlG-rq?u>xVU@miWQfjg- zlqIo#&3L8-69nBBvS5`LSu7x93OirP7=BQrQyQPXCpopS*G1PAMJ@eD z&SUT|&SNpZyBaF0{T45%;;O@H+%iqi>sZz3Te$ly11R^cawoC0``k@=@nu(B#k%(u zj?AWMZif=V4_$Gkun5AB7z$BM1b_~O&|C60O2{oa7LHtXtzn&LGYG0${U=%!jHw+> zdT2yd;s5Y;qQXzEyILub$am?6t1cT)=$mRBP1QI_sxgYpO(Nj^F!;9H_=XqUJ$X*X zDY)``JUN8Fe6yl)0M+P7KJ#x^eKwM?h8msatI^?xghLIDP9L1|EL%pK{kIxjV$!1; z#XQc!u8P~OD4X~g)m@h-+%laFenxF0)#%QD*XST#R0SfdlC%GnMgzXN1*@sx+D-;P zyx||}^n|ZYzcyrCZ|HQJn%tM&pw0eUo&IUkv*>hAd{PK+wa622j(IQz@}7SgKw(R& zxm}8j7gclDWJ$NFUctO}tT_4LFt^N?MVFw|=gUIe)_L%7h(vREDJM~YYE5efOaTSos+slo!XltMa82Q=Vh1OcH!XDeNG2Au_lLFjYf&%5uq%P`~ z+xQW;JB4i{6@caYA(_l-2cna9n@HsP9loNMR7Wj^ zlhF5*TXeC{c&;i*Kvs(k~y>VzDru(YVe_XK;?&=#2d8oLy@ zc1lsqfrG31Ve#(ASQ3HGo#%G&HDA|k#Kk)8(6+Wj+gIL~RWu1rFM3auR%<+)mAT0AKQh=5T z1;R4nwnmBDU5hOwO}azOQfZPO6YSpt z3jfv!$k7@Ja$=1GOr##2=8fZXQrsihF|$Z+@g9bZ(aw#UvP+}@M=lhger}Nh)DILq zQ`=pK9VP|dkzn^r8*&8`+zDzQ;My}37;f8%4BMH>JlEl_$s+>Osstpe#>jX*rBRIP zfDfOEkugq?q9dc9N&5zOO@Zt;TmaWp&5=w%oJq6q9Etj6;5N>}^D4 z91Cs5FB}VPRU8X;%UCdmP+u6xGm-{#R^NS!5yxHlPknb?h4m)1O|RV3gnBw_X63e) zATVp`j^uOF+_PAoiCvoga8-8eW26AP6$;QHKMw*5hx{U`fOh{Z-_XQk_Y2f=?H=%; z-48e08+M=3qjM@aK6J&a%u;Fh?-T5w0t)|j56IE(33Ai!?S535H%#SoQ``x>UNd(t z+e@gT&^uLW{U=BPT0az^^+=Ls)zaMdz{jVaOz( z9v2Nk?Bb;Q_H@w-O}~-&g{I#qpnTKs0V7qI{^B<7GZxdI+t%GsVenlX8tWMWNhcHP zHT|QN^!-Z@xokXbS<*f>(8P|W4=)}M%5*nlqX`_1pkIKr{3#%xu>5JHg0OsbQUG7O z5RM!0Nb!Y$@=PBHjPK}<*ZP_54a;8xX?g0h0A6~uwwt|a7NhB_ODXyf0?_t-q8yQm z_b=#Qt63-DdoU)v1^I(7{%?xyNc>HDO<>^@QnTi+YRHzd|<#~vgFf}V1(x8bFd zI=OZ~V&^%7czWZS{W%<6PvY;M>L0^ME#ZaSYH*O*_0_$RZ{A!%4YLGa4KhN3O+(!| ziB18h77${xh0dix;n4ftOB8Jxg%^y9bnynm-2>QrCRm*NwiU0G2Jz|NsX_J?P&6^G zC8Rp#J(3K6a5=Y(UmotB&j>cbc6WaG0e6LuQazm+%nL3)QiUxcEPl!0({aBSZSuVwcTw zIpLNDk@@_eAe>afpa+cnNYOuBncFuh>Kg&WelQ*!0g~gtcgHb8l8@i(HomM;2C9#C zx3bg)ts3t>?14|E_JMt%jUeY*`1ji&?uuwQl%-bzlE!F5wP0#<0|B+@C1P;gLjm2Y zK%{&<*2S_(EAXVo8F3fB<59YoruM1AmkmqOdGSUqN~7{}k=?A^A?hdMH$+$#!3ca9 zFBr5#jPirv;?>v&Rgin-Tdq%VXIVNKHyWtjdR&x~7f*0!+vf@b=%VI{U+ALdRl&)G zk;#P5UgjRjw?5=9@#ml}KkR;ytstzL)5yCf)a#%QRdN~`cheQdGk#5q<9|KkeuRBv zl0fIAd?nP=P5r!z@G>!cpzey|w@>ez!S?yq-0iK2Zp9C?d7oABx|J?G>j`%w>03xu z>092Y;@7v_Ru#00z9qP-;ad(KOsc`hO>(zN{7mpe9n4!MgGTf+_W9b|S%g4hSYz>I z_oM&^;2L}&(8Y98A_6rvp(+_vsgRxkE4WY~Z4N5FV_B6%`Td$2Rr!v)lJ8U_s`AWT zbu;#}>zDk9Uu zxOaay5iDRR$iMb!y%8gl@${$MwW2zS#;8)``Qz>&+wUp*zY(5f5T4?f@Z*&5bN?s8 zuFEMYp;Th|wov}!C+mk0TIgWX#FN^<>{@4v!%rJN?pb#Owz`~F`ERARVT6z{$?V87 zy6DUco^yA$)4uVzgHBcX_`g##?bHH2WiSMGOmKI%?-tb2SL_kL&{yoKioU{MIFtK= z`=mc_G3`b7`&y|fiIMhr&4kF1u(T>yqHA@{K4%tqT}W}oUC5ES?xj3@mK#1o77SAO zhE&!4kjvA8Ri3#Nz8+i@mKx5d_N>{PC6UG$5;=qUk@)1UYCQhiiWi5c)`%&~I^dEk zo|B+)vK4XbWq0#{_CN=Br2l%ic6B~_j=Oatkhc1W(*&nXniD5YeBf-@#l*DgY`)~z zdKDSRpqaN>XCfCy2!ja#Ewv;nm4yf(&V(8tKi|EAJ>pvnV}l97GB%iCmcr%0){y@{ z=bd}{sk4LmvJaAz*c`K1ZbQxFYZiKzn~Q>_69e54Czie;sJ{Aqu=HO*2IB!jhQtG9 zpyA&&NMjUg#sg!4BM}b_2$u0czhD^;{6aWHC5(e4M5+YkRrfLV0wirTO|HdCNo`y{ zpCj_zkn%7h4?psqyQ6waO2dwm*4{Z^Jz{WHY~idS&(YL+tX4JCl94?TuCQbQH9M&p zANx9NqugGN4?bS2Cd(jgkjXYY_calBJe&mYB8#-`F4g>LzT~F{E=OO%BXzSaOl&t4 z?%dKKoe_}mM@H<@6sgQFIvvla!)v&ZUWb8~Q1k?Mrp5e3>|&?p?r}&kgwP?)5Jb@- zJt=;nLwd4Wnc$@mf|vGw*S|I1bl=imBdp5|>^Dt_bVaYhcW#9%;%0%@6>YARD|(3+ zZ>t@~`#xB+E&J5OE|ae@i`oy(yuxaRKZ>x|`krkg?QpfUS@z_d_q2xU#%eMODjHq0 zJ3HZ9^QfPi#bauAVE_2mykV`GJG!BruZgWSfZ0Pp^@bNkM;I9**M`ZY09SXSAhDL6 zm#lC*StC*k&Fb*tyu9}CD%{$E?yg>@;b}|8oe8zNvaZ(Zz0^BHxUE5Ivk(GDA^-;> zP1ysa0P#mOOr`jjHB6mN8zbwJ4c2Fq#)uUPU|Ac(_0WLYY%wWC)R&squ!iwI$?tXRs-x5h?~Z8Z8wK9aUq6w&&8GRM<2^932(Y$dUE2T88Dm5Mvu{J`L{zDp>Dz#Mfs+5CD6AIh4 zOb%3-rkOTs>Xo!3dVL%9s=63gx}=^CAuW+&#yw7^XwqQon1!AoX>#nlYDY~TSlnqA z%l(t~8d>V)YH-IQwW($rE8N`>=M@3%G?iZpR^v7J;c?W)1`VcVjMU_w|AS_+#Qy-r zKT+am1iyHkvYrBa5!>LnqAYTJIbfE?ZJEg~_A)^ZYr6Z@mniaA0XdxCYh?0 zYC8xoMZO0?FO+M%Hd6;m#XbLNob^G&0S^ zQqgKA{N|%2l(_FqNWe z@x22gLyg0y=umH0%OM!SZF@WcwIkGzso>EQbk-ijv#D1N-4aq#w*{wq$57#5go`}6zUP(b#AD%{#>(^iZt3I(pa-xiu526>G5(!dVq)o zq|jUlDbrjSg{VE)#?5YOuq$!@lplwuIRkw~>uN@W>yGdd(XaPvm_hDf$Dl;h`e z+0FRUm1z&FO~RzJX-3-MzEz_z;>T9$>2K=`G!m}zT?5vEE=5RN{9w!o|RBxH9lihYIckug$tog;ukK2 zHieb9Gn0Sb{jiLELe{-IpCPS(hu3qTX#f_t<3< zvCNJs4U=bnYPe}xm?HoMkR21l@gzSoTuzM9q!x}LaCVoy&MsW8VJ$h>@=YB;hAA?o zCV4t9HiNq$B3-eCFZw0~eU?OTJ!eN#1?;xsI`LXr>^L#@4VM#Re}Y|1j7lGZeR#N> z7b){{UIgqoFB0s+pkyAT{UDLZV<{KGip4?uUT8_Soj(23-7w(!aAQf(|I?Ik^#x!} zq+UAdYm|E{X_Sz+RfX#X^;&1QwJ2h#qzm7Z>kTim| z6bO9xU9+2-P>;|vf30Ls76c{DVckr`vJ*Q+$WH7_3edek!KIBUz16%3*^8q{1?L=ld_cf>F3H}Pws4HNfy#3H4pMo#+RqST$v z?sj@L+k+9V{F{%xeB{Nu&Wm>)+5?P}l@q!2d z#0w(Rz7#k=hd`%0$Y3WCsEw4!K>=?M9Ma1gZB}srg&ya8u$P4e)3@1)pj$Mb-BVnYOXUiJznhz|CBF^F)e zrU_=6a%V)+A$COkHjLXFngkqz&fPI5I+~BRCFQCYBSZ#J0*4K{n!IT7vmqLk8_^PI z0B$1S$LNB2PGpjD>z4t?{tp2zVJtegC>EjlmDY zJd=3tBT3m&>jZ#$n3*=dp{hGmeF1nD7i+%NlbZ0GCGA4RuS~XyAOKUzj(Wfs!S^Nt zykqk${vW>EC!SCN4IHu6?xK!DAbcDW-cV6TfVex8yW0KqMBW3??;@pjPEyjB+W%wi zy#u4F(*I%a4K*i$gft*MGk0dvD>amaUPD6fB!uRGQUpN(3AVLFAp$unDzL7K*g(

FI}Fr4zV^PK1O&!q);S(Z`AH`{G5 zg@$$VDg}DhSH=~w&MHYbk^G!gSSPuSAEGja@aWiYwy4Ex1%}ENmZ=EChjVQbJ|)Hv zJ2yZ-@dhm@mVc-v#qzZ-TQ^o{t&H3Mfhyy1b@-f?ZeRL;z5;?q+-1N zMEvtaBax9xqF<)yZ99o6!aQR^Pd5Ufi=y%($w0wh{MUo8(zg>%7UD8Q5!#j8iv%2t zY;bAVmcs?S3L8e`-|?_5#fz?@jRjB&TRIz03KVDB=jx@Ppa@4ZBg_LqQ2>EeKn%X; z@`MzQ$SO}BZ5FTQSFi6Bn37_7vB-d(d&ixiQF#-x?1glMnPyiadi zGY5(LLVelonO)E~=#~i3aut)kx?A%~_GaAkxm$5DwScw^M17?mX8 z$>M&tTwQyL?Izkuf*gDBelqs_f<*7(eLiawsk#NaOUKpO&2$$W=@ayzNX1J$D?JdwkGLJf zIDS5I_vG|8JZxlo77v?ev-2;;pN5az9fnt?+ZW9+0Z>%NMLAb0vuR#No%opY)L`CXt2-j4)g444wE75mNxi#&{{_u#aPeiL32%T?Tyq5@)b}qPF`HDE5ACu~x*_&$Kz&0AId? z__@Z;Op6jjNO9c#Rv8Gvz~e#--euHWZQsDRt+FM{ap9wK+fSN4FAA3{+Pu2lO4}`3 zP<52fceF`%u{(+E*v7X-VMNmI=G*7Oqj1v1Ffs6q0$H`E!^3&$yk?Eb9syH>ZU!k% z{3qGY;D>iwgKfS`B+w{ygV}Obpomz*boj!47kh2Q#@nSK9{Yz=fKw zYEf!%UDYyMXHD-H&C9;Gr}1e^Y{8mMtf?xsKBAI|O|j%j*ybD&jl-eUerubtVpg{5 z8O?Lrxsq5a%s)+Myp6<$`9bao-YNCG-83m&KH3yaDuG2yI?c3p`UBodrg1P>LoCA$hf4HlbHia4 zbUfH_h$7L|Gs$+(tP5Lj>#2p%Jh|7f;dDHkwPGG0YC9g=N!E#M$RQmV&oYU z4c%Lgr1ca$#PJwQBGqBJ2uLfz?c?=%G4gb50m;R+;vAFiGN=x34}3c1_Q!0Qf-W9i zQM%v-=FwHCqUSNBI}vK|^mq;a(d_fv<4RbpiFwsqu!#z03gx9wr?w8-90RYr$9V8O zw#3L)aiX9|2ZvzALavGt&f`9kDtat0thOx=xksgjZ_$h?j3kJ4`XGK{#V{5{N&z!G z^#-Bgysb2PpUA`g_gBO(+<$)sT1Fsw*o2Ds^b4GgH7lg2(# z9OTB5*c&Q2s!~11s(!zPUbkWH*$^*a#|mmIuu3XN_xsj#zuy&qwaEsV=zi@xOZQ`) zK}mDyQ0~{Zvvj|x&H>yH$e{auOL!>v%j_)OFPjn=BoB@z*0RNY909D>?tL75I$57>|Jpc8Jdi3$cACFGHks zk(VLtl(y&)NnK<|0|XvK^Pq8_hkxZN&;t-288oDed7W&SmFOUo=vco*hv#PqqT>1k zYa%V87`TBlq8Kc)QeI$EzFJbYtSB0XrQ`>aR}M_toxBPFeb`1T;cAocy^?T~aVZES zmEZ+bWYrn{IF$PsG#T8ffOnVcAGa-li^1PNZYvCW8I;3es3a2ha`y3xC!hl!6Rk!& z-~rW)b+9)ZqOmuK$k+q-TkABa5;z(~(FCB61J8cG{wdoqc1)EOek!q`qy1LsYyuN} z2c{9g1pW(2U;-kxr(c<7D2=|XE69LdUK78t%WGW&clrI`BcjW9e#Z8VpXt`%y|!xB zRZvo+2Tr#NN2^4S5Y@+8IPR72wMFrP8ysEu$meW#vP{K-bo11%GL{!wagsPZU3j>b%8OsJ#j;ew1$#PDUhJW~lw>32D@@9(|F4us z25kbO2wSqnO0>o#x=j-GiA(SqsQe6&R@-Nb^O06{n`lMP(^PI3kQ7&u;EO_HLI?dO z?iE|Vpazfu`^~kl*b?;Dy2|OBOAw$PCqhx=Fmfd#3PUtWweTs8eqYo;zx+V_Lcjb# z`lY`qSdV(!hko2~T!ZZn_5)$AX8)&Es)u1BsWDOaf>UiGe zM|<}lUDbIPU-=f?nK_+kL@`oSo^qX%E)e6L)4LZ5cKBd=IjmUG9{`LYhVMLR>lOEh zFf?_Bua)KHTpo9N))0}wD1e~Q-qoB9elhA}LzJf`hlE_CsD|?@BXdW{?KI`ccX^}P zCY2(iZqdoL4Bm~3SG`S&!yRIH)XQIe8<*o4q(yO_b;y?Kr*P)%yq>Hs0E7D3d8vNt z^k<%egY~&=tD_gA-gXZ@fGV+`cY+3q+Sb6#PH^RMavb{wA zPpo{j`BkiZOL!7IH{B>^L~yxQ!_Q+8m+^E~;jZ|gaHtRwBgHWB3nRs_xPXhb{EuuO z`-v1~AKPkKg|D{eKEVu?>S11ew1p!V>=H)uS)X)?;8Xu;yPd64EV$^e+Hz^;Fa!Ge zk~n!KVCSc{E7?YC$!gz{*t`8m>|Pv4diQIe+4{)dO^RaghP$lA$88Hp=YCFb#LoQ+ zcm;NDKtmWCw^*dpem#|lh9}pEgK&VPR%F;ycvW{}3Shw<`NC#nACXKk9BS`d-Rnf0 z9C3lS$FpFU+6#xE9pcF+;U3a~IEjW(nqoA2yA|4`Yv}7rBKQVUa#hN08UtuWZzst8 z$~IOHjhCng9Z3c*lg~XCoeS{u;@~}~OT5H82%)0$nhh>T#9x95n$83~2#QC*gQlEv zO-}h%PP-RH=IGfbtG@p?Rs!N6geVoxF%FI+JTR~!ya9-YfzVoB20}JBKqW*sAayWK zb!wvcMbX|px%k>RpYgq|ZM2X5&Cv8$oWwaG4(92I!mTk1R0}yU3fv)nVHCI{K4268 z@YS}wZi_1)cIl&S{EEz!P~Ig0;C{=0u#K=RWf7GX4;MEKG{X3XoRrpl_mG?{KJ7G}Wo3e#9X~77p@DO|(of8evtifX^N|fV5dkzS ziQi_eJYSVCcX$XnYA)R2SuaXsH@RN?!ftYXLg3}zHi$oBx!3={w&Q+AO<3;5^6M_x zHiT{^Vwl(Y9#l!_rr0W56XbP1t};DBR=?ByK@|>}7xEL;0OtI>BCNKSV*Idk*Fo!8 z074Ft$~bR+8*C#0LJr`+y=!ObG12~M$z6rJ_!7-7b`}1q*?R|)8*V)*Va9w6ocHjKrSTpZI88KhUDL`>AL^3;9o0mw=qhLp(Ay`< z8D^VA2@7%^5f6tsoCvQLsU8z7ooU>nZyCd%Y-5L|YH0WX{hmbmx?n4*jJk2FZV&m> zZE3J`5TIhCZb_wGGJ**iF&);brL3!cWQ9O5XIdsLtK>aQ<;96R0)>1BEhKcuX6Ot)Caehw# zfF3Ca^Nb{r0Hai<_=Qm_Gb!L;el)^<#7}VgA<}*^bci4z{oQlTxI`tXxHKe5#-#x& z(<4^({uaiibFTbUi560+sFUF2ho^gX5=9HShSbCL!3usN);>yKnnZv?YOICs@GXQG zA&*)MJ>)H<;6WNJh4g(%a_8bO$pBw8cP>P(7bE1jwaD(_*A3K?}waEM%i6w=9>i<=~ni@O}aX8i%z9W0%cLgLP3sYfr8fqFEy3eC`x z<-KFX3mIxHAs7I3#Ev9sc7zKlCxwvybd&y-BtzK=a&d=ejWri(PxsQsHJpE^kehIQ zlRVRmMu$B&=>BALnt|vbUsayA^Aph-;c?(Yz5`BwVr(365FzAYUvWnB`(4c+cEH!O zLmpHV&0*&yl_FYGKIjd3UZi5soejNvP4zJGSw4BEndy`EtknX-!QaOTwkSZ$p>W7o%!~J)Y z>y|da`39ThTX_&iBaTavMjS_Sg%P#IysDes#g>wEwBZ#g(uS*30@?8L6lp^sjW(pD z(S|gkriXnI+e(;#H&FAL$RDJNX}(8&>zL-F<&^m-@JF3*J=2Dy93a~CWZL6IohT&acGB^1pVxVa%PnTFNDMm4&vz?Z*Y8{BG2|HY1qqf@|@i8bPezt zivii7Hzn=4b)t1A^at7G%8=0S#CLq_%GZGbF5xHxm>QU^<&bxa4Lxl9@TQK}47U%{ci7OT zA%sadUz(7S9!$u>{5Xccde)WANHOK|+5>_k+!O1c5w5=r;qn3FNp_iCc^C$3j2stC zoh}gSN~g|tQ>U(^GU^n~bH~%!Kdi1R#@f62(F+{81oQ$%=qr>F`U*`zy>_?H&Sf-J z&PCT2w(->pTMJ=7rV;6sYLh@DF|te|xk9ztm0?q~t9Vrz;2o|Yd8pS?t6u9+FQ2Zr zW2`+(yF#i3Oi(S#1l6Jms1{;<&{R~bepU{^+K#sm(B2g@h1^XW0c`W!N%Fmo8XPhvoItGVB|N5=%_TVcp5~iXYhp;#H0Ebb{Sz#lJcnPajUBTYO1P;GTJ{; zRrVnvfXkcr1pyO|qyb>71Z=aE&ICj3Y*<_lMT`=uM8s~qYIn|xplrj0{m3P?grIt+ zAqT5M!_Qz<_LO0ef!aj;NL4h#dHK^heHlqn9YuE-^1vd>kZ3B;qOtkziwWV3%y&c$ zcw+Qe``~CY+wv?WU|KI%ILicAT;W_Le&Gt|DkH!OXFfkL)BdKP70%IF_F1f2DInJr z8@DDDj#h~t-qr6me;I=tkn1Y!JJ~ixSWe6Fa@kfx?xsCq$(36^hCE|O0FZr#93EdK zC9&yVGMnz8*>p|syZ{s2eB4T^s?EofhIHOjBo_&PVG{mP5^i#dLrfu5c1(jD(&54#O?OP?xCqp7T%^>&N6f2}wo58@o`RENB{{$knp3RdlA$Y4LZR=mTh); ztYdG703a`TniBy)UNoC?kr0A5=OiMPx+a@-g^(#$^7I%K(tRZSq zGP7F;^>>;b^Qi+yC%woiJLXS9A=;A1iH52rNvg+~ChyYdQlS#IWSRJdEm`Koju}F4 zX7b{9az;myH^g2_8N76@eRT9pFQHjpLbD_xrU-$XUu{bca=8cbw%6H5$jhIeT{Lq@ z?g7UQ4tQDBBfPF6Cws7_0rc29`*)cO1l_st#|r}@QV0x)$a5nqz#za0c-KhR;ol?W z&R%@cdV6zDZ(+Y%;zX>YSOf5}j@jNk2&&TfJf<76W;w38G;!1RN8;z?=Av z>!z*K;Z35}EqgTo+YR;{cAwB6jakdfp0>k6WoIQDtrEpAG3jX`Zbvs>{*QB^eEW^| zGwdEkogb++Qh3Mnxw#pKk;!&{$ z*L#7>a=!h~=vZE|-!6eWKEA~cz#U&YC2$A)D}XzA)t9-!bwQ8#es$nb@5%~??}r8_y9}cdz&vX(R^=n3`z=s4?oQYEab7^ z6L;BP^>MD;XN*3)SzlYwSgoDV4ARo7@B%a*H7_Z;pk~{C~RED<)yw&Wn zgrlW5K4Z5Dl#f25(SrH9TKgEbUGd@2@+RJgAMWmLE)(x#F}IIpPm+2yvBsR3KvnQe zarWKz8`vA9O7Rk7yjCw;0ztlCcFDc_khj-PW}jI~>YupePWAUBW5>Pr@gf7!F_yfu z*3N$O%}wRF4Gu+c8{ESI@iD?viNgy*p>PLOKw~753?Zb*@Knd0X#aYO+eF*L+`B=7 z>NeO_DmS|y=j;Cri)5q*2Y*h{uXXXV2xA^E*=BDSFRI83MWY03@m~)r#%>pmnDJnF zUl(2@5@gJD^5PCT*$9gfQl?~g@?0$~*^7&zPfO)B-Qk(W3{^xlcL6Vdr&TU|n`-?I zdtuX#K0g&_2%#t$LL-291TAA->&u%nLV27qRWE~k!U&mhjgX7>(h?;o^c956zz$xe z(m8bS5`H$OWil|ri8nZn;k9d*T+efDk2P9Q!K=YvZ z@l=VVN=R2c1?R*>6b=b7{EnpbaXzUSY{SN+hHH-sdgeaZ!>Js1j7~mguV*aH>v?jt zZY)S=TAEb0t;#f&6(`}a`?viGyPX*-SLv!Jry*);Q{T&m4=0LmxB4h6PQ~^3G`Yjx zHcf6J5w=3HbY@A2;ZHtgU+k0W)l_elCO5f3ONAHvAgYgBO1t6fRN7sf@GA=(@m>HHGwob~BR1#&80F+!@b>;K zViYmU(BBBu`0uCTduZRre|0&`IqH7{zudkC9+YqF?g-|`8=5so_R%pxuLoZfkSz5? zKsEFDN~F@*v@cE0JYEFxeQ{ZSB?K@!t=)Gi&c5M9pyUA2ZoL2E)Jx^N2c+2#5XqF;zqgwGb<^zi(s#YME`O5hVD!b3hqTR!HAGME)@-s}h@8;njf*FORefylsB4q>#(%=lGbuw3J%{ee z1-ytkHaG$~U^n=ypV}L=wS4_CfGAlu!6h+c>rB~Lz<`>OZ&hn^y8*zPjpkD7s8WP*gEyTRBo!LW=i0gRAM4!+0i1E zda1)y9GV7a#LJz8&_nrk{hYa{U%40_ZU8Ho_ZidvhS$ZuVo_ z+L4Ytp7XWc&M(e6-J!NaUi(WI0rcyEp#YG%o`|SS`>@rt>rAEBn5M-WYA=$ya(EbH zb@n<{&tohcA4L2V(G zbtJJ9RPvXS&%1Tif)`>qSFgWl&*s}!I3jrY5MwNhB0OOq$OQEW&yuHF@Y2p3U2#(l zGIGC4cd&4h0al+J?MGC1Se87W`aM(Z(#&VLK_kFgsvW%HqTPi^EqXDKeAP(ePYuk9 z(g$S8jhZk)pLUJ^5>v>H8boRtPUL_VEaB@f+LyB-Bo#Iy68VXaIfXu{=qX9dlf$Da zVc?0o5>oKeXt$t)ry~o+FFYMtm?e)bYekD7UJJCg#A|s|Gd`kCTenj;A~kjskp`P} zy-M&lYYPB^uvyRPMh4&hLTZ$3*1Hu8u9|hT*{lzfTx?dzz-HY{GO$_wi0a;yC7;L? zwlzkv*GLT{^-7j}9@9uNlmw7lAplT5C%K{;e5X00y^+pdA?g2106h0xorQj-?dE-h zjqdsd(~%x<I*^*=1`tyJXw8 z%7*IZnTm)I3GTI4f|@D<`{x1*g|dL^=u%)bkhwHER+L7UiW9%krQ)*DrJ{XY%B;5* z^bld=?oi`Pe-qDYH%}gGbeCbaXyxf}9+nEP&oVn2H?rhL> zg$SdMz9L)3kTH>f)o^vTj3I*rJ=*lyih;8ZHhbYCc579V*aRIN@6NK;x|S6229s!# z>MxD)F*Xp@hR&J8qN(&Auaed%jebFJM6Y^L z{6epK@qc&~ND5vxn{RtJhwUN?pxVY7>(~cGF?6WI zD#2rgmONp`NOs~g7#YeN(%bTScgG06`x{3%?{H1>ME1R6CfsVg{!O+-CHReG;7J2y z;7P-mV1ih?d|l;7RQE|}uzX_&e=gC;)66plQV!1;w71dIqP>HcJ0S;5jQ3?6InwP8 zCK;viCxsN$-QHDV!8zF4oE+Zq3wsUA64g~mDdEk0TkK=3(2#UR)`^G&tglMpT7RR2 z4JHZbm-rC3Zw@}hwH8m2Um2eis804FTSn75h)ZyJpgIDWplKb%C0HG(4gwQURdDDQ z2bpnwL>;uaiB3RlAPykbvU{vl@%mq_NX4iO4xqpZ_U4%21kaILIO}~HOyqarTc0CV z6cVH$#38DgXFELi1Aw=CGDo5m>>>mq%9x)hdju+r?@QO_$eVwgczwDtfKeq-SDdC$ zXCl($8|B{xdF=gvh+o+I|HuhAO<9y_{Ih8Xug)^6Swt?>H+>U3ct@4s?cg7_Y%hYB zeg)IaqJP2#m#iO(+VV{~#u}EU_;BpPfH8>=Bmp}da7h5G^!>3T*Z^y(eyWr>QjGE= zt~;6MBzv0(_$KaXOsfF0+#OP!%zkJCrE!LmvY(;&SJ#D2+aLPW(b2J12cC ziujl~VaIx9bxTW(Vjpjl^UvSM7>|Xv&xdldyLqntgsUXH_M^4uWo5>wlGZBS>x(VG z0f5QYB3}QOZ6$Lk!nml4@x#e&r zdg{~jWrJUM#1+j?On|WonEJN1u2`C56K*KZRmt+=N9?3#f!la&lEtg;N@>Gp6S6S* zO4w3AZYH~yBw~OR6EL#*pV-XQQ(U&Y6xF>9fBsTpKc6gGy%i4xbvak0)oNB zPFpElQNE|acQecL<-3_5h``Dy--%SyC`)DIjJ+f|rp@r@x@|*V8ud5>|o z%J4?C79a><@6Flgn#+zT!ZM=y;pA>Cptu3wk}4R?PJ#LY&*TemF`TYnVT@)Mt)>2J zDTT-ZG2Ot1rh6l;h;Ck53OXR$S}MJpyvW#>WZ zkn$)@xyfc3$v`$DLm&oJ`DU0LAlJhI5d-carI79xlkOuV1L;Br-or$+fM`r_@Y~w%RYVK{HMI4;k z#T(bvOq%vV#D#(9K zpWa=D?3pS@4N2Nm9)3N{|NLJCU(j8KZIr|_EFr$jL{V*+UesNVN`$K%m1qK9pgWV5 zKZM;vM36hzDIx`y%D#8UgfhAB&Dxqy~=aQE5m?@>Zi6!t4Qsu}^#!N;^s|XCp zMW}n&U-0&_cXty?U_Ysg?9jRm(z*>Q)3ok!)4E@%9BJL0hst5b8`!qr1+?wQ(zXqz zZ3$0lTbh8jE$@*(g0=7A&;KxX?(|qkeXie>H~VnS=9iQ>zP#voPn9}+(zIGl&fsz!us?c0cIWU9)8>x(FZ2? zkmv&;@WT`6@ly2&{rVpAZRL$Bhw!Qj#OqFfymmZh%g`tHz$cf!tYC-2fp7%+!;oEU zPi8x<{O~In{|LnI=^pYCrcc*Ia01|mk1&a9qDf3}0Py`QPFWDB3z;uvJ$m|cCIKaH^u#Hw1|L4Z--u;|qqM9g z!GtKFscKRf(i1g=-m?1v<0*C}5mEIPx2c<3<(j(P?9uHOl_hn*upIKmXrRHfT|sT+h^*?I_4aF7V9G~91$xL@VUcu)%{1^UUJe0>=}c$`wX zsATPR0|U3;k5b1_+F{`7!HVz<{g|obeyJp3DwVV(#Bc;Hps7m9*Srl_vlARcU>3k* zK`{<&s{byQuoz+0^LQJHLN}85h9#~Ae8$tpLF(UfZ~3&q`WKDAvpGa9+%hg#3EmcH{zGs1 zI1gF?c1E{n#__YS8)a;zVnKF`uQFTUCX$OS02%!|rW))jl7TJYM^yJR*#gsgds+Y% zLwVYRq6KpGf0)K!CMZ$k&rqas7j{Y%P4O5XX_rOs6@}6G&x&7Y{AU9izqY|>^f5ag z-p9OVT+R+DuG0J8Rta9)H@3|C@is`+0i!){+?m-$+W(|tL+pRtwEtO>i}r^MwEuCE zf%f+!uKP1-|NUP3Pdfm+prM6wYjpPkBV6xLD7(OCf*x&!Hx&c36=;g56_7(&bV8x0 z6%xfSY=y)^KjBBblaHpa3O$72rCZrr`>5y)FQrT`rA$eQoVwg20;zZ?U&lKgG)Bn1 za?j4U**kafr3YbX+vSw+AC=uugNILu%;N8SV3e{tUslpoF?&_2_=O{cs8=&% zcUS(f-otFFAZMtdgr;?i*=D784f-Dq^NyL{P|k^`Bwb-PW<_o z`17Oqb5{I04?GW#o6;H5O|x@{D6fO}k`K!qx|c9NtNpz+A{h!f7N-5t3%! zkRE{8+Ruy)0R&4vZY+$NBN$7;hzL85LoirXXa<8-g(4VyJJaRvEyU>|{#+*h{3)vB ziC@|9XNCJs@OW|EQ53rsi`>_10DV#FFpj9 z#41G&N;iX7Bs$D~R<2UTFYIUQTG-FZcb*I9^S(5G38B>a(z?u{+Vy<*DZ|NbRBU-e zsiQ=z64oEtj29Cp-*Bwq^%c$zzRVDTg0lB0*Me^^0;^l=)_!ATY5JpmB<2MCiP6IBSgdEZjMUrJ)xmQ#f~^=1)Mn6M_gFS<*okc7RPf2CdKl%zBd*& z&m6b%(eETD=m-1oFRsmSvV%mBiYbngPG>{{9dQo`$$Ikg2rXED9mE${6QBPHsNi~E z*EZ(VU0A5agF-tN1)1`9)p`}o?!A`N<1O?*0Bszghi>zEQ7?Wc)= ziM(4o^qldSZ>yGN8HK#pdE<6Af{1qVcgFxWmLx3Q=oqh!;7fmk1Lq+sUC53O{#x@L zT=)RLGuzRQ-}i6hel}lG=g`U~xP%{`?su%RFZeNJ{P~l ze?3?bD`6{Iz?y-feBE=PNH7Ce@=mzh`CCqWamXo^+6SQ^`0hd7LTX>gPYL=FOwDuS zlh|2Rh94<(&ei|bS8fnA>3_ci^Skr9q5QbYUddNnFfy9k0l`5!Xs3iRp~J(K$OP8U zqSOf`8jMJY{(xPslPG8^3tg^+m)|p?Id{f9e%c|lDW|#*F2ZVvCHu01-SQ-_l;*`v zT9<2ixlw$h=9mZ<$G+7Z(^$TRKqMhxPH?jOaV^48oS-P18I&^24Lg08QP(TTF;HjY z3DKpWI8ykdtsOaRI!OhOF44yG{5FnkpVHuPfW&yQV{nAx)<(`dO8fET`}4AR>$Z-2 z*-Ao7L^Ue5d8=)CKRGWuS63LUL*<&Pyy8wxsE)4N(av$b#_k~mQMfI9ZLnhu+d|X* z2p24ct1*R}#~iotln(A_{$J+U!uFEdRx#VlntQ02Kt_m3lsD;*2Kvijl6m62yx^eW z{dC@E#3+Cx93K?Sh7cYgIi$XGLo8`5(|o>-C7iYHnGTL5jh!I%g^bjNLZpneF1k?N z%rM7Pjr~NbVmp5w?&!__AgRKXK~Rj>T-&3oPkAwn5j{IdPG_3)6%;W9f?g#;}!I+meN5W0$iC4>f%#gSRh_?x6b}ODY7m<+3}jz>SdtGlNVNX z;V4jpg+=HqkRWdPi6taFjot8T2LIIN=)gp}C)9%WCF}!|fQrAuQ58!;^SDCN9%z9z;Fd!!PkOjRR}yPYn>|w-;TS+7lbP)6+Iwaf^bJ~9WFpk8C&Gy}hQ78) zBGjDt%V-Wljdw^5pGczYaIo%ysHFpw(tB?al5_skS5d;0;dyzm_A+Hz7*X8vfpD*UjpQJ9%i8>5* zG!ljZ%lkTFTVh!F>R{<$M;8`Pq(ZwEiv()duEo->F(59%j~P!YUK*p8 z5k}Og0>h^cFnro+`nAOp*klc1j<#GC$d)%tTT-X29pqTqBGWCGrdv*gK-1lAHQiEE zqbsH9yznKDk(!srb~_0tYCDNQ^|ljkj)?x9Fx*k6A1Rh7JRcA#(1?cv8S!{iBl3$Q z9IIMn#do9?-yu?<70+6&_?D^L{$eZkjy^zjDKUMFbU$E?3KvyneCH2672o-b04U!1 zKZrfqeCNLnLWg+g?c$(UIC|FJ8X6qG*(wDk7&zd6 z-lA=V+eGwEMl>>BbW5jJJo1**u)2Sbb$qDlGX`MT*Jjk^PH?Q%f^HZ9v!*rxICc}! zLim8TUT7hAnL0Iz@Edr;2uD8cOB@3HXr2T!kmmUU3Y{9X7UbEUKRA`a5AU2xctfWh zB7ugZYlVOV#2xGkM>fY#K|f0>fg3aj?*+zYDT?+q($`l)GmDP2d;l-on?07h|48o6 zcRzaC$uIslw+$aQ!?8#IYydz1B>?JtPWYn{KmA`uJl)iYiL)HbTV%hFJobYhzV`dW zYQGPp{ThY+o@E^ds`4#0oz4czk)l!B4n9iU=ynX}Iqzkd@GcO8oV;Ue7d&MBraMh5 z-IN-ucN@sdz6W#mATnWG${&aWWmA7F<|k)b{1Hq!x^|ZPxls*0w6L>O~2`!qxTpTVDdS5kh~O0{bI|J zw4Q>l_?$*ajG~7drz7+kgXE>ESt>_vmre`BiU%id1z!pA(F+D5+}Wd9JLadr>Piqxxtx!5R<7UI(0 zs}cEeqZpxRHjz|tz!E-mSXOtkT!J=g$G3NNwF%j%O7_{J8B-WZ5NZH&dr2vaBBeZD zC$%Vz-YfFtr4aE;UJ8MB?Cml_W(e0pV44$sdH;9P7x3-t91XsXdc>XCk1P@zs~mT; z!-}6gVh~3KCGV(IugkXJiWIsmEO&x=>F*gE*q4gB^w!T!Z#_pc&|4t`z4fxe(p&Yx zpryHgt-STGK#mkLIDoeTUG&z^6+_co?SrMaItVARxi7xfb(5p8>AE&&uzzO-7U-;m z1#wnC26i7eopnDnDL89e(^M&bxae^qJ$2EylsX(-G=Z0| z>lDs&w%Y31RHBavl=1F2t+gkSB6!4x-yI?}J+5F%S{l7n)If(^CVrtqE`z25hm58U z33(Vk--Ny;U~O7eJKptm&ElQu$~D`Fr@wvqsyiH4v1%d|hE)6>kxKN)RNb=uklQ%8 zC-TK7$G5U=iiPyit%GGmeS&15k3t6e=swd&UnK>+KB~PGz7u7p4hB^1ivT=+4B(=`0$r4_P%avEiz4qavin}H-R_8oWA+o99gAR=J$j2HvrWe# za8wt<8%7#VJ#2_{&3i><>Y6txYQ#0wr^#c0h^J>u|Gd#kB9avG`ezg&>?>wjbe5=q z?wKuqp?hWzLHCUE=bks#<=pMafpZ6SdRDja9tVJV4JWM83o%L#R;eD=)h$5u!YKJy z7=REb9ZY?dO;^;V2TmR$JPr zB|nf-BlO^*a)=2Ts$3q2n0Ea9gZ_q?=%Idxm>_5v9&Rj-Wu%2v2afjRp6*GYhnNuc z2Uqc(5XE!t37fr5PY?<^b8%#*3+@!3f5Z_PH%SS}I(0D2glMdYs3LlAg1gvS zsjn)6)1N4s01R+|DCXh29K+ZoRaRam!Ut)7D-4lPTKe3fyljuHEZTn|j#yemZcl$T z4N@AtMzF+Ku~z)TSh03!;GwJ-0-YGjc0S>F&UYxo<-kKvIsiz5sG*|9T`JWhMfIC4 z+}k;HHf1M!R1uZ|c6B0V7KG<2Q%OeteLWLU-IBz#Tu3?#M)xlpFbQ zy#czh4rFo2dPq?+hpc~@F8`y-kweyZ0eJlC-{l1h@pZir9~SDVSI1%UsaN zkW|d!{vj+vJJ$wcBAmnRe%0s`O;SBhW3noZDiO+}>y8n>&~?Y~r7t)fp+2J=Z!FX2 z@!%I7FZyv<_L5^VTi|Q9G=AdmLkmZ%L=WrggDvz|m~6Ecm-TODs}*(Wv@3^6r@fVA zpwmJIepc_EVe+-@R#E`{l?Q0vhrra9+c!&sor85Ch+k=&qX>BvbYDG8Hsh>e*o-jM z`J&!oZ}U17h3I(iGJAslhS`Ewi|VumD-=CB)xj1dsTMA!QAb4$Y{3u3FKodNu?2nB zb#=2|bJ+ZCJ{)`I9xVaGASUMOphNPU`~=g+<%(^MQpS0m9k!IUNGD2Yj2zFIOs6i3zE$){n~_utm(r-ILKkeaY2p{Q*))FsZHL3B&E#7A_IDhw`RR0< z-*s$f%ZX9&uHhPzAj}9mr6=EWj4D~8(mm3&cpqu|#{v@g{dN&Nabj!%t5Gb}Za|D5 z#_o;7B{D>9Bit`}gj9p;0_Kgt2Zsxw#whqwU>tyGks^34@Ij%}0DkUyxE8u?xVT<8 zmAyv_DLMy{PJecc zL~d;aG%YT@+w;;79TVa}ZC}T^f(X^{q2o0cE~?NgcAtIJ{0(Mko-QFB6vaLg<1tC4 zh?_Mf434V2OvQZ-J!yozSYat?UM}hFr#K=zHYtwRYDW1fj-ZZBisKEZnSP2Ro+B*| z1}}+E6eY16nl}P{RIRAVTf^4)5*x(v8RRu06=#eahZ8JEKElLuyoc0+SXilV0eir; zgr;kf2l<}Q9r+>cMFr1f22mVqM)0yba)t#HN=v^0%icCZKH9uygnYDl^$6aOZWJ>j zy6`6RtIfncJbf0rjznVnOpwM1a$Nkv2y%P`PC5Mz+&`Uk?DrEx{`%6fn*BngR5Q(= zRH}!03%;kyaeZ3m5TeA7V(wNWy*+$5AM>5V@N{!hSa$Ot!NxE(>#Dl>e8CXA z`C|A5gGJ+Uo1K4r(b0h~{@#%k*GlBm;o_{atQanGIKn@!RC4!`A1f2^kJ?Q<_XmfK z{Y~Y{x$g~p{f}_)fWRP44pVDJ;+x`7A&|#0b?ya!)Ygg0!}OISCH7;;ndS$X#xstt zq05zYeLRSddr6u^e0*i3M0~7QIbxhB-~x3~ds!(I*+ikYN5aJ^0sBZbLfFSnPYG&h zUh{(NUS9N*BRQlg|1VAcU-{*K;(zf!^MB%>^s~ds2!9!7Ta5ximEV`>d%-aU=A)&g z8D^uK7Du>8T3W=xrUuxJn&5l(`j_?K_-eVezg(&9>Co<{MoP>_;*#Dx=o9#ix~~uf zBTYZ?3nNXxQ2`^3^Ebykej-h;-yQd}Nkk`{t;`|`IO&@-N+MT{QyCtCS{i-e=r)pf zydz~eTds(ciHaYV?yE*M0p+`mRL1ynGuT4lSY40*N>D!kw0vVs2Yx0fC6u4|%Mt8} zHl&)2HYGq4q79i;>=x`X+C0ynyy%z|2O|20mr^C*mSpE`tX}<};~`TEx;xmgYsfxD z5S|!KHdeC_Rf^nl!EyF|k&5H&RiMUXc(n69DHopREYZIiC1F6mQ5k0N6CW?s_0bZp zuhnRvWOf~#`d>CWz|_CPXo;rqyddZqk`bxz!YGN<2P_d`g|LM6g)^O55@LAAH?nek zQlYzUgd%G zx>D-Jh+Z7mq0>i8kci2I6iziJfb9fS^q|p1#Mri5!tr|re8-*b2e7TA63Sb2%{a!W zxCnKP$b3(amdJd2Ngb4VcOaQx@z)jz%6CY#4vpE5E24cQC?81?UBR^bqoz`KE2WmD z6f@$HWcoxpf+vPRhn7L@KY}3!wO_<93~IlO4j9y?g*#vM6Vxg?Ie%guOMrmsoEX$% zNCGawI`TcS&H=TTcMUFKD$gTRi}yns54k$raQR*(B~huDOcw8v3^j#(NigZoj*(2H|B{zJqVoMr@{#H} zld3*Oxq+9e4!H`NFN_pH+UJnAz}`x7u41Vq8%Y~uq)mE|3?yB2sC9-mM&j}fCYeao z;F`@j3W$PT?X_VXQs773O(1}*3P4Clx=@Fw3es2#Bq zENpZ6#xJvK*cu`#jzskiXEQHL-^Rh~BSWrH6wRTiMx~IU=uVM}AvhhhQCNMClhR^9 z(suIlG-q7MPL&Shk$~xYV~h;h2ULzcuzGDwfT5^y3=TzXxu{{@S;vt53bdSnUf&7( ztou{CGQv!bL^Pqi*qOo+o$nmsEDt$v6Db%*O>{n5F?WD-0Q-y70ndS3BB5P_qewAN z5OUwfPY!U#*OlLB%+pv%DG*ju)l^~dlJK-}?4Jl_>CaI6( zd}^s2=TlXNY1hG}(yl{QjEU*bw;PaSro<=6h(vUAAQQgUXR? zP6uN1i=Q^s#4WA*Qh7wPfqZESi z0XsaRA?!pGm|%QhU34U3UFk?P0UT*M>qq3V`jGh?h}JRZ9| z9#VmL&m+FxbLEiyzp>S%K6=l}GTAFvstoj=RY9A|%v19%Dhr!bs|jG^ZDn%e?PKF` zacX{ts9}B{9XO&z2}fyBOM(f)M^iE4oS61n8$nKf9UWflW6b&D0i%k2L?lJ+-Z!;- zUuBruo$+XQPGw2$eh8r59|5&HO|%1!s2$-bwX-CcFnl!C8&9>vR{c)1+_B2rQMJsm zvf(mShV1r;zc+lW#NQjKa%FcMIyOK^oiG*~FO)VOTxJm9djrSHpb9KeH^NftW=Sy7 z_h_nDH$82vC#Jy^MWUPw1U`M+7+kApcZ#WtOh@$d+hJ@8%dTYi5>2qH;QEq_RL`J} z5PZ*q<{}W)k@C1kc_xtN4N`NTK^g@4HZ7lPcJKb$}r;8T)@QKyGTSyp6cw!Xo6~z3#K~% zlIm!;V-rZ2b27UUp~c*lCUZM)go0TW?iCFan&7f(xcG(3s^Q~sS>=1Mg_u_aJ;6(9 zUSElMHPK6Hl9$pXNr|b0>2e{Lz`VMS-#^1SR^A(w6BjSVr2re^NG;Zv_Azm8AVGj$ zWtI!VGvJRG^h%@<&?}MWMih|i0QTcuBVD_WH@-yk1;n!`pQI#iba$mUD+V<;VL2v&6|G9zlOCe&NC9LUE{s$5TIw zjb_}zE)ffE++AwdMoi6NlF!edj=znUKQd+%+aUBbr+et*)#!h@yz0K9L@kMbT_p6$2Nea%;{&*ue{D{MZ5~Han9E( z#!Jj3`0#x&Z@0`jp2y#A599w_>b$Sj-#~MIV$W#@-}q5tTXrik#GYl&N;s(j8<-$U z$E+Yqo5o8JrOj6XaNvTgyXRhYjRi0=30&P=wRaL--gEa~*HNT8=o*9mb3=&Q%e=R$wo z>7318B(=gFu98kuthMUAweShhD%q|Gmjt%KCoeNan)&2qs`#DD5iZG3Be|!Hmlxg6 zuW~*_eX4H9HO>xNs6N5#*yGJ_Sp=&jUX$b+ujzd0jppXrUrK!O3q8KB*%wm0MjgW! z4^3^y*Q{~g!4e63XjKz5$q!?9!UPjEY1dk35z8d?YPz}R#008>cuBWk=X{P0BvsZI zgQorYj&-n;RX9QJxy@>q-k(jg6w)V6kb6RxlZ@Q`uJIxRcbdkmcfu#`Np4w@YoRtt zSW(eF?#^DzHj+X@0KM9z{Q${8+K_?YfOwo_AlYhPvhOU;zLo7Kg^+B+1g>?==uTS} zsX{tZJxMAc)dpXxh#U0>DTK9u0jki0Si6Z{AL3}nU$C|YNQXB%3whG{ah;=@`VBOn z-2d8rtFyRcHV{{MQOD#B57L4hx>$<-J2-P^*K99fl&B@Q!MX_<#D6`2QP~sZRUvQ^ z-(LA&B?_B`}2yV=&T-b9D+S+11Y2P0eaqJBwp^g$CPWZMu@qU;H{{4`*qoFX=f zG^G>eTpne@Z6^?n@3}l7g`fN0=*{nZF0DCxZk`B)odr;WCyJxvqD1#>AsCH2J(Q%- zrx860W6$L(T?`y0{Li{(ZT|TR!U#LQr>iTGC#}hz&aU%iW*)?>7OA*kfYygyz>nEI z)^Z3=zhxpWuh!?4%$z$z1k_P6A8ej4+A|-Qar0(yajpx0p$CRpO%`uKin!YOwa7 zye>m(Ncp0MmV_97)xFMtFq(=Q{^+aWsjbfUSqTvmH9RpbnL(thNCQ)jAepG(h8wbv z2F(KnwXLxRTR^fQ&dZmJ+8m{2rzRb18QflQ7BHeDuPJf$3MvPhVq=WK53kWgFBUhX z^Fbc`HbyncM2p^{cttefRVyv(!z}D8S2w+U5-*+OibbaDUt8Q)e{zys^6s|MfBb*Z zf6-ryA?Q3X5O<`TDpU1zT#o)eryb<&3C z?r|1IHfey!$ATh+Bb}%(*kXD z+9o=n(>6e^aN5@iBW1By18{rKkHyesff>3iWu{yfS`S^8wjR2yCBbxAnu;!a;_D8r z`OkH~0`T&$&MvKf1(|vB*q&+ZcdPX1zyCq$oBD6i6zRV{?XYjJvoJw9uZgcrM1TSN z(7)TIFp|X4d*K6Jd(2H&G0GrjU(W7tm^M*vhOLI_z#h14unOM5i~EdpREFha3g31i zE;Xn>2(@Qd7Z)p@qI?Y<9~Y5*dG1~@#th5}<3&GoZ4NSk@8lqah+(cIX$r`IONdLc zl0rjSk`AcVuJw0Bwpy!|M3xgka9zaGudmO_3N_ zUlaCd(vty9de)Cg;}19&w`f^@T-xwB5dv+fO|{tYQ=-$y(uUe*UiOxA35yhE%}Lj# zF<>}9e-H*8;6rRzSO2y%OoRIYN8WK}vp$3=nysg(6KES_$W#d*M%)qBjA>c9wXZlk z^Q!r&Dg4Q!Et=L}p%+Y*uxtfHGPLDnt1WX;JuQnTzvay0r8^xXc+NZaO>7~ld1(x} zKpHY@Dm5g}Sy~#*Z(Eewi`Ulz@J!;z$??3N%?sw+-gmCn?}Eb5W@qw_jm}^#ilcEi z{x9P`;Lo^8v*7jwkazL^i&Mi}Zry6ry4A!+Xx-gb>)tA@d$X`^wijRQbyDxr*tTBU z_GW3@y6vAhQ#Jj&sj!sEO=15c?9hVW{x1vuM_SM_X{+B?kOE(Ja2oLW24_-By19PJ zwB9Kq7Fw_EG)q4}A+2{@`euD)`d~d~n#3?V?)9SZ;H+`{*fpuy;5MlVyy|o3M%cFq z|H5gozJj0`420r(uW11m{6nWT9U^j0IGcme?ioI>(7R2Oov<4bLns%VngrC)9;nLW*?tCY?!2En*IU);mEjVt2t#$o}X#yFvIDWi!G^QlwHaSfJ@4?AU3m^qN-Y|x5Je{2)(ch}N zEo@a+^n){3*CVIPX%74=@jgpnNbWty)(yvkoZBHbUBGsUU znu7-CW7IVLa>WMmrP8O%`Av4Z7F;*-7iWSNv^mWUUL<&Z-@!d za=|k!j(Ez{=>%GCFG~;w)GYB5_+ab|>FU72$7&moc9uYT*r6LAfdvNu>^-axo*}{X zh7w886$j1;(4Wg@H0{q|#}OQeQaHU)ZCx!{F_?Y4KhJLGN@o3ucxc*6t7-d~iuam9 zAoW&~YL~(()AZ$vjgNf~-2;b=_c7P1c3UpPOZk`avd#m$)*cChIC^ht4w}7mVNM%9 z>%2Wydw}l}Ox^D? zO^mpEjij15hKvZYhKu)9HIK=}FsnuK6XC9rdN}q86InGB+*Tl~`WgM)A=BmgW6ucJ zD?XbNTBK_y>pW9+C2?q15~&ir2aK;@iUY=to#Bf9k}c^AS-N5&jzLm+RealY-8oa@ z7W5*y;`CEw!^ds1R*oShYQ$9%gpVU6 zJq;;L1R|D3=ZYHWICJs1Mccbh)B6Hi`-$ zV!<$#;Ne~U)}@FAr8B$jWDIVLi*t6pt3=Tt$EHs@f%0VBYY4mqE(O(Ydt za*(y&Mp8nAglLlBF{FDCtc}8QhO%9xaPH@>k^qHGn5O4vNtmVp6cMJ0i0$Pj?NAzh zSa3s^X%xTEWg7p7%Yc;VGKceBpHi3MaC@Z>KUd(YW#176F!p?{5b%~q4{6C?xa zLI%=(iDV#M$RKp5vZJH`)@&>n7%TnRmm~vuL58O$LMHgJsJo)vdx55icOK$O)69D_ zq_Dg^dX=nY^fhNlVy@b7=z6VCTSuSM;ow?cxJ|L8R0t4 zhFJ^aRg6Iu@|<@N$%S*?bgvZ;h5oH|Ynx)GR#U#r{M%_IlUd9M$^XJduDW<>bF`FPE5 z1>Gd4xFBG{lNSU>ay*3HSs@Q$cM%3kn}-8%+3QCeJcOMJ#}pR5ed1YmH%zs+V1 z?T*IM+>2sEi9&E1d;Y>4J0CpJmB%{G_VMyTwT*okKQhr}vznkAFPP*?)*O7|B#56b zQVo^2^V|vk{3dUcn{5ZApM9FaJ*M z!)PiVECbB`7*{S2>z@&>_XAoDDOvobsW3ykf(VWsENAXKrp=aJ=5mrry39?p%`Wpd zlCPW$jxYVHUNhT&mkC-2^zd#3{P2bt>@SZ(4)&MFNDkWfkpN7dmG%uK_Vx6ab$rYm zR~&${oGf<@(chabJIY}~S?Taj0P_FzqXTx7bwEyZ6pIR^qnsDIh>r4a!Vz^j8-UrL zQWrlRg{l(Gv71Cyn%yL(QW;T@*CQ$eY!@Y0`i(83pNJ;GenRx|=_fr17xbI@EIk-( zdv+dl6;g>qJIb!2kF4aACc)0iXi^mg93Du(Nm4*Y8WTGU@M&D&%JSi(`pV_AWnZD* zi+#nC5W|mL4jqoBVqcjjnnUZfSW(AATR*Hds}B>K>%jpy3(-4$A}mL~EB=*|lH zcxpRQ3oTN9_fW<}qGzN+kcY5}u2%)U1dUbpdzWOkk5mHhtJGfzWQ#W|#ok^LukWCB z^7RNr!g{t6Z#c3&gdj*^;yFACl?6z}{grrsL~}~Dc4w|(!6d4xodhxk@XYPROavbv zT{Z`F!fB)?e&I9{uJj2&aXOC_TL}yJFH2nS_{=47PTy{s>kigc)b`Av#e_0iC3u)t zHy;R*+&gc)3U;A#6?J)mIg{^ME!x@W8LOqr-${$L6Yo%*KoJ%CrX;%ah5T{+Zc|V_|LW7p@4&~!pws{NIh~-sx zrLr*>t2cL!0(83hjD?R6~yQ0yyCM~$?P6d zALH8=VO&3Rs0ZiB_%lmX@Lr)-@L4sYUOdkUi_HioG`(&Ow|PVhdV8dP4M+ypqqM7K zYwo_75bmR+@^4~mkE@9`M*sdy@IwDSE`FhZ9}nc;#p_(JHudkJRj#e<7a}vRS$|Rq z9;VfAT!J-g?fq#{eAXvjBKY9zT^m^FT#(xASGde*KNnF(wAOt64X$O(u;wSz{Ak{& zxfwruqbq{5_90>3{}!^o){4DkMZNW0E+OBVD(G%Cm-L)tH@nh3J%?CB_M9J^^qfk; z5PQzTxw7Yce%uz#&;8AnAJ76EipY$&JJDCy&ozDZ29k|q(Ym<- z2Fp9BG5tE!Bia_>+B_RR`Sv*BaApx&kxDj_#z@R!__85UqPEm>oG zh4(h4vx{tX6|FZjgnF7BE5Q_475H*%XFlvNdtGs1t!<<>+!Dcd$A%1(`>Ep@mG)C% z;<4VAstsZ3xH%T#M^n#Wabdk}sJ4RTr5(1V!{o;NW=4R)z&P6hDs9Z~XH*isRGfPP zL@#COv@hpZ^f0-Vd)F`;#o5_TJYYzsHxO|botlW-WUH>89wxh_v%!uAL7q3E0D=|| zMk%~o>cPa)HXVKL#rmekyNpgdz1@8|oMkyyl<(OyzGfAB29x$VkzZp8im7k#7sb>! zGNvN@?b&xPy-;jR_1^QNd0Nk{wymMnh64}Tv|tHPHYB>8rdvt$dQh!4T;d7dVi8QO zZbsm>#4jRE(&8=d0^>Z&k2p`<@CsOhEm%2vyVg`F2ViDVxLZ$$-FowPY|#KUD#9;M zk-5_rqu!8FQLB81O_Y54TYWrTuc!7IF2mukowlygpo4c5{LShRqF}Lz*2bj;OFo;f9w+@$p zf!i1XhRLXbp+sTB&BNAMgYYaP-tdw%ZLCo zgW4l#W}q|6?iKkVsU4NS$TaPDZ_#p1ru^cg@E2YR8$cJgF)b{uTVkrIHO<8dI`Ezm z5<0LqD@3a21X8`fKh+63a5U=72mkIC)7}y~kfqS;1-0u4xyo!g!g4*r2J*-(pMpoQ zCSi6Jo;Ye}VpgO2HHw->J0jMgQ0mBv@E3JtMdJEX-X|7vrMdWo?F1hi<>}Glr)|H5 z9%Q;3Jy@xgBzv%fBV-S@*CLo|6`ZR2Bpvn;Y)$PFKJZOTgzU!r$n=~Z!I1+mu_835 z|7?Ur4*YloLk|4YH`lK|xd=J1?jztzzCNh^NI5SHInd#oE9DV+;L?&2=y(GOF{zOf zH?R|<(&-3L>5Riv)B+A1z_OA}4;m6iF#<_ILQHCNZ7L%Wb0C<^2{mvv%Rnp(4VGIO zfmi|oPIKT8C^X2Xl`tyt1**ySVqEG(?RA!c_`YoL{g4reFA(UI=u1W*mOwCB(pt%X zoy*zBjuGZT@_;aVw4l358OIW8sKFjN$P~Y6YZDC-;yuXhV%1L@2y_dmj>oEQ8g6E^ za#v*ofg(9w(;3_H;U()C)XK!NfgH!Ne0Nn99~= zwARisy?lbn00(5{j9@y?%1|)zEIz>`#;i>~s(r^wSh2*4$)}vH(H-rffy%=+LI$k; zs8xy7JyIhLc~r(z2%}Ow5mrFTqXt%hjghI9COsOU$IE)uPmhN<0czZ%vd06Fh2Iw3nEIR;`s8)|D|TT30kN>;d)DMy5}^SZ`pHr1Dlp@)*&Rmhe>Ok%ueuBbif%GZ$R25Hq&% zs*RT0c#(`syMI8S`*qbAfwmC+sOkw4x#9L0_1jUt+jx=U(9;<)YO~RDBHiz)l-g?Z z(Q@xD2s!h;yYDS0;E_VCz$R_lQg_XJjj9WRr~8MT7=;eiL8K=DD@E&~`eq<*jvd zKie42>;T_~;HCE726!nX5O`@Oa!!MP%E3!9g@KnM%|n=cz#qX&Rrvqhz|>Z)w^uzR zBvRu{Z^%EuGW`QxLBMHs@P>bV{AUIJLysNW9hn$AOR;4j(&-+{Xcv`Z2FE%t-d&EAKVO^vz?e?e%8Ei)dRSrh9G^g1QN z@2uHbtZZV>(ubmB$jt-Bh}f~JfS`R9`7`II{KtQIH6Jl!BmUlFiWtMo*j z%Yw7U#2)p=VSZ{K)s62#jlpMsfHSi(J3PXV^`3EJOOkzra!Q0G+jFa*gz|6|u-5~f z87t!e_TU&1|7mjPD8F3Bs70qcH4<4V_O1~Fn9_!mK}=zay}deaj1l4E#!!UYPGjEJ z;Ggmc$CUC2Cz1yw7Jb!tW=&)a_51|Za~DxkFg8{H8Ou{Wf6wdrI!iWGsB%4LoV-?F zy!YSGK_V?XJyV=@+r!0Cr~Lt)3lsUJ?#@a*G00_4)g$tla^ZKU_fWz`W=ngFnANXV zk~rT!y)x)G*}3*P;({9>RK4U58jv`oCr>fWzEt_}22txo+_}_9f>0fuZvR_tohRRe z!~e=e*C6riPj`ltw#&39!(HY)RfI*xHPr`mvorgr3|8QE6q=1kGvY$?lyLRYJiJeq zDHb)gAFjkZTT`)EwQrs{KgE@*_vJFNDb$^bDSW8tBb6wAxjc89&A9-Pmb!MwWLAJe0Gnap34dnpaXp*!vJ;+$GPU!Ff8c&OftXAQ5H*-OpHC-hLgJ*OZO zq|kmiFrfW#{}#x*Lo;JDvR37#*43+z9XjlhhgW-Q0z3SoTN9lZ!wxuJc}IkGuuq7= zEb{Kq82p8Qny8^Q^Jyv*0}k?z&-b`rvukIh6Ktsd7&0(>xJ<+ZXt;a!1oibLO3r+2&E*wiZ20ra& z%(?gsIApXplXz?y57;Y%$7T&&6UGwujy{3wL36nEn8MrBxUmwtA#bb?8k@eK7ly{v zqiC$XGN)^nT6>r*7~j-U;1o|v7qKs^b%+S*=4^&uwTZ$L_7GA0Hb7zJ9q$k#?&xoy zt-d>!FxvF@xl-iWbB1TnOV38Iwt;Qwa7~zn!^@?m@J%ORtQ9?x87^|hRMC<%hJ(*= zb;!ZjeI5LUVf3rg!3I>DUTqv}AUDIiiXsk;gjq1k;m#fN31D!%@kVNE5jNEREnMyY zd#F8KcX9DFjj~~Jd5R;u_FG~0J~T1QCshCb4}>akYAFhb+Z$J|f2Da}tdbJryAn>D{va=VQ@nV8xhU?%(pit%U5Ywq909WF^SD^@ z-Yj45E%WQWDcu_x6oe+zyQI)(mO?qz{SB1P+?CZVB(xeIFsD+z2Z2A#i@}~H% z#1h0K@Y)uDbvixH{;T@YI5;xOOwd2!qRD?B`ugun=|8Wb?)-TBUFoxTxp?x~ zZ@xY|D@{2wPGnw69jn%OO!kuSHxCOj@ZJ6Za5LFHu;_*K#^UT`7zCV;sbbb`5sA9{ zG1kJVtFk{vgMiXPY#DEFTF*~UC9Y2baLGD#({4f^mHe0-1d_QP)JJv26yClP4D*^i zCe3|7{;f0-*XKf)V)oOBR#^JY47;kR(;uS?S^7-QoQ#}m7`cdy^yxh=h9qQ&cC+nw zRizr$iH2npxp1;+QUB0*yqwt}KvQYAmG(GAojaZ|uSDZQdx#4A zN!0Dl_I2iR=}fO~Z^df+?8>$m^qo3=yvV3&i_@ob2axl&_&RS2GiIXUytmY(zWOm< z_U1Y7u(v!f=gqnV&Rf3Do}{Rsju)qDB_xRff;kU>aJ?h(igaF}j`bdS-K?FKP`AqQ zsD1#l0KiKBfcu4f`lqi?-<3AzJTpmC442~dHNEx(*0ye*OEr;Q44wAb@p7m#La{V# zi@lSgHlHBD>%QK^9NAP{-)b)CvnNn%_6@+kB4@cHR5Td^aM82AND8U418b*)^|0TX zguCQ%HnC#wi?JeRySVr$7k| zF$G=;?u0+FGepcy1#3uRZmNGnj~=Mk{|owbL;z~M+y0sN0+=?_+U>FD>j$|qxDnNJ zFG~SKsC)mcs@*%nfz7IyuvCA6aTn+Qb@fu8n?UEx`dLn)Jv^W&PbS`_UYH;*CM2Zj zmw1jtPXdbgXDk%HogiPevw6yzvyN8Eb0Yhoy|MlrFARG}cd6AT(v1l{cp|Go+{94T ziE{ZHHc{S?U@Y_LeikrQ4*4)$Gbp1^q#x&bo`qTjj45@;1QFiBKB^{dfq6QGiZ**- z`IvLqUR}+aC=+^19=CrQ;cs3r zT%7tI&V|f{a+nBf0)PjnOYNie2~0mhkvEp580r-Kw~CPm2xciFZ69o(E@Iqe{$vd+F!6|s#%j{l+Qz6Jj%x~<|6Z% zj977PcAs#uOm#o6x8f>c*BLX~xA?6*%Zl8z>`2bg2rKjrfvV+TZi@0;{6$foJBgw^ zl0`Xg&Cs^#XfOu5)LAdvuY`I9d{J6L8@bbv6YOp#Vqdk-(noS#D8z@e6oY5M=T!`G zFMKt)NdLP1d3^?xBZGa)Bw4EkoI2PU<%C3>53@C&}(`*CfBOu1pa* zZ$W1`g%`x#dHfzwmRdH6zNn(Vz{wQv&l!B*oaCpQ4gbQ{ED&e682CX#OwbpTd57Ih#vh+s%$^Om~ z&UQ&?8c6NCRM%uVM*#rlw9=+LrxI5SA-{z@%A&dK0iU_nLJ4jI)k8@LF?1a zK?kNUfH^VLo+>ixyKAU@C(D6{pz$7@ESuzHbSH0;4>SLk!oZ^``e1GWwZtL5r3SDp zH~>ZR1hYX6ftUhdJbg0DEbjyqhc*fcP{e@8TL8W~l$aYJlOT9JuDU5x`X(o06UwB< zzZri~S;U$TtoN* ziBn`izK-~4sh`_h#Jqwk@n}56b);z!t(Tq1!)&QE4H_^wrP3z=ri(*$8|SOspFCA> z$5ZHBtqrEo00F+BcYt%hvcId}%QMosS}vFeUu)BIIR($vO8>ZQZ=oooMCMg{iav&u zsn;1fMfN(Ar^sF>5p$HEU?L1z(C{hpiGmJ4EKgj&&7C4LGQ*wfiYfGJKwrhl)WI(| zm~VvjG)!i6&RlG{3=o>bp)8;(d9ybAc!@uD48$X>l3vRBlk!Il{->n!-uw}84EfV% z-p~fZP$MX%kKivv9MeCk!16%BlC;ZdHbhk{|7EZ}#y;a1al% zK_{W!v4JO{UMX}Eir`}2$#@c~_M9TGX1AFluV%NNLYK((`?;PJvG-z%SHuz?(zvM- z4@n=-OVCbfzG2zSskr1e@Q=LABmARLknNtN&iW&q!KrC*raTM^BKFa}Q!VA-vbA>u zqwl2i7S7Zpn1-j2FLl}{@E3L3C#D8im-PSB{*_l(U7B;lo}%dQa^8L;a8igB0Iu}f3sbnItNq3IYilB3#enxB~%JqZA=wDRCwY4YL6ah{7%AM0%o>%F-k zGA;)M;i_XWr_ibcD75Ox;}k5ThQF=ytnMP6oG7U!5i|OTEal8JZSU?XuKZ!i&(qV2o+4ALU1s=ksa4fD!tiydcd- zeg*F|PU@!qNdLDM*CsyPAcEyGJ^VS``@vn8=b)~Q<>%rsM>Dn2bQuYshB3aXDk6k=y9AI%_v&(6zZRwV+!@pV93S$llSO7cpjQe zbOlpzGSQV&=#oz1j{6=|hfXJK2z@vwV{?a(_FRv2useuKzL*{9Xs$KFoN`hjPDMJ> zl>wNsiwc5hWbzh-Ba>GOj7*)pQ|Nk5Cz7_R>}q3z>repo=&fg^;dabvgJizTh5U!I4Zt6pJ7<0_AC=3yLHBko5@)Dt~`zo;jIZ#>02QZ%*^BDeddBsf0u)BCJX zbo>=MmT7GCK2undyq!6AhU{=gGm4>5!JAdu4jF5~JLt<9ciHRsk>^=9gW)^q+j$x4 zaJI~l9nMCmJw&T68v6Hw=$^+VCMoO_?P-xz~}2u~3!$aDB|$ zMFlA|sCY}kLB%U&5Z=}NKCNjdy%QHoldlWNo4QK_^ufC%fIjHGc_D~_4ubZTct+DL z7iLQ62Ys+l8Jj4(6WSs#BdF)SF;l+2{(WXCfj{VTc}esow36$s9ntzsP9RrqFkHEj zQ^=L;d|kOSpexr%SI(RzUFj_aUFnrVu0*s4{Z%g1$CU=$gLg@E<@>ylawP+O z&_DMnX!w&CB!9wHZ3?2Weyw$l1mY3jDC7(%PvVd=7C>V!Ynoi}FI+P{rWd-5*z4Iz`Tw zdnaB@t!s)_HL60=H$nni6fx0Bc&6d9lXL1mza7;(kYC-P=hR z5nd?}5fAFCxnQ4QFyI=z3t=#9<%O(Z;2C{_fj}Gd5}$H55f|U$R*k39r15XBP#_Ed zL~hW}@thP7XN-6_!zmCClY*{7bzXcVEKdK1lPDH08?ODuU#$^B!{?9#_A!(*(vjZW z(UD#$v?=ra54LpgWa=f}m~HkFgwde8=CI%*6Kr#2NZUAtOz1erFrgDCkqPbR$Z*b? z<1d^MWa19UfhO2Qct3~*Z|-Pz*QnU<{Ea)@qz=Gb7mmu99FmxO4Pd5To zutrw{P~l$A1OXLvuN3m`J#(er*>f$uaWUdGL!re8pBORaX_IdgN|Glt_)DJ5%nh)~ zH*J*Tte@4$s?m;z^ryJW@;rv67-9=PtkRNWorF@@I4EhcewuNY8-1_NmHS#BaSH8) z0R=YtBE;Dh!<#}NT)PCD&foA{R8N4S~M|=$l>ON0S#tBMdAm|1#uraS7 zFTTZhh%v|O1rJ2>6mN045oj63VLtw%ILx0{Ar4F763p$2pBU^o)iGFK%-usVIG?2$ z5(_@6Vhoyq5sk!wzY<328<_|hi0i;Tc-v(!r_cuLIx%~O<9_uSh!z0c)Su-UC|XXi z>U`B-wBY`V3Ig!SWrQE=JZnYf97l{g8*0U?_Fz4gxaNn%>gtz9SgjXvu~dC4S&AXH z;C$7p&w~D+xZJTu-_In-Gx*)0I__Iq_+zlBlMRmWIJVLqumKVs(Q9PUh%xW zg*6}7L zod(lZ{+QAj7BpXuVP0IVF)SCzxcchFS<~w4Zi98d`Eva7(ic}>N|4Cg0OOYzXFAEf z@woi-fcuHc?(3|huMYgqd~AGmK%d7I1v_$;Wg={|!=)E;0$9*Ogk7)iQVXORLF?zk zL+5#MS-O`UE0)_*>dwTHROiO7^E{DX?1=Xx>aY}b)W4__L)3HsCsDau;c(B(D*TRs z{vMYB3(Owsy!jB(@DTyuyz(Og`d7XMlzHOcCmn6P^WzQedKCg9K1 zUOjWZ{Dc5+58yVMb3=oqX=~^LNTDvPHvXb6tM&rwvUIkI4$qSTP$!Zq^D;C}?v5pkU}D|xX-!gb8_hJJv1_3z+=e}WL$ftQ@= z8ug=iwUaKk4#KNtbj$4^-uL7e5$JaRUU{WK-1 zfvt(gxSC7xC-jwsnWKC!_S)?|#r%B^hxPz^g*@0xWbSp^;n*s<=Y3Wp{=zyhm{j@k z0-Uc43}iuOCMXpFfymE}qlIcFQB22EO^u8O~ws!g#(lRlzwQCYG&VS#*|o~K7w z=5_k@w$9O_`v_NUoe5tcUw82o)7H`|*b1UbryO#$R@BW4;4giLzuRU43zZh(BlVrk-1XcTO_JcgGxiD)F|6>;)wvSLOX%GwAsR zs(3znSd0cg%IkW?%g&zlzQ6=N_?=uJA5xwG)$w80_NN@3#oDJFgS6jSS&S3Ju}Q8c zd>Q;=F`&mn$La4Dq67g_z!CI}?+HpYp7E_+ARl!2sRxgMjPGQ|igq_*5>@v?ap?2p z6fJ$BWd&(M5#n4Z-}5c?)rj*AT;o-k%!0GWh*?J+3F6xq90ZqBdiYsKu%h-_NcFGu zDvf{MF;!6}i;ZQDOl>OD->UhE3uVnezK|aH1YLqk8b|P* zIXA0)|Lr;ylVCRm^Ud9W9DZI}U3NSdsjb&fb8El6l@?0NI2s zk`rX@jAM$H;hWRtos;Is{sqc8a_jm|csR94oN8~6*H}gY)t#Vzy-?&UNtvQdIJ3le zZ#!y+RYQR^H|~eOs)_1n9qpq*eebaN)^e$cf5(|oy6UWBlcEh_>Y9O(BrXi^U8Rt1 zwAw2q2U!ILbytl-C(d9VjxZl0{)pgbsupN!Svhv^qy!|NBz8h*ke%Nky5@l|&$ z_Nw7LD1$ZZ#nQWmpF@4IhRYaVs*aNuU*!!`U#wsi*wP(iRN1F;FBz5lg)g@YjNA7n zH;C>wN}kw!#SyJB9cA6-tgP-tZ&T$mZ_CQ{Nr)25t~y$2Je4XpEE|BrAgrir%TFm3 zSc#r@w3N4~#xIf^>|+;6oah!y%Kgv!fM%F#_5pN9>FpnTPf_n#B0n3{n-wDO<%ktO z8o{jgUqa0}2s%QMpFO6j(jAEswn^*4O3EnvdqA>sC+29cHe14VGmxQ|_?DnfYGDNh z>t2J&!B(;Cn!~1TV`WIcVy52#sUNhqJ=Y!1=zMJJG<0in754-yeEqtklg1OQHndLa zypZV(2Nt2cmsQ1C5fWEA|0hSDs(!gd{QirhyLOqeH~aeJx|SAoq!yned-yU`@1PL% z!V+w!^-F8~=EzaCfBruVjDz?;y&1rz8|Z9y)NWM2f~ZfIKt(mHUcYqmpN=$DYf#`5 z5i~`$O4XMNe!4_Zgq59CL!#qknwRlL0OgCkza8x(*~n*3CSY{OO+vdU$=6aMo1<7- z1mB9kXc2sC0WE?q=1wJx(f5QmG z8whl_>+ad93ECfwY6*ZWTtHmTpkT2t#5qi>yVQzUnitj>wrH%hE|=ho$n%M?)CFVhvP_ zb&)oWWg@PVB-h0(ow!aSJ0iuKqtlbMwTw!v%ev-wP&nsEf#{CfA(oNY>|aXYj@t8# zK(zz})Jt7hAh8|&hZ~zIPb-i!WtLISlsgsp%#>rMVcpV9`CAl=f10?Cz=giSI1;n) z)l?T24>)a>u#VR)wHF8+=Pg*r8%qh+QTyASh;tzKVhz&SQt=A-}jmKx9@nQ)E^wK&Ykc8w&e?Wji1O3wSGB03i*aUDyl zB{dE46@~+;mW8P_(vK{Sk9O8lv>e}jG!g8+Oil#5TU28r*k(=mYIVdiLUzEPqhZ; zu2L%82uoHw0mD-XZn0Smu3lOa@61)Sy-Z8lWN@y#(=c(TMKw$u{pJHN1iiQnI_LWy zO3+@m=yFba%Ew0a?PWAE4dq6{Ky>=PWH(OdU5htvCiQ=O?==<;&Oq`z8gx!g2~TJBHnyg%-1p-RT} zMb6W`g2{&59(`{QN?$IYeQBADB@A%@ad`ax3|Jh}F5GR)*~>5P5^{Bqv?RY3zW0{d>lyJG7 zYrImefZA3epwh(BG-t84(3dr}mU+u%Ynf+JDU>D!Z3dU&|%Q-^hsbo=J?`pwVIYp`2M(ao`9oE#@SkW#q zrL2bWnPJUm7S*ukPt%&eERwY5cf*?C!a&yiY*+)_$r{F8TH})tC1$ zL1g`?RZ#iuyi(ZC`$JWi7s}0f_@4mR2nDgMgY#GQSfOb5T&g34nMpkZZO|VnlwHFq z@Eo9TdXENWhh15sWUMnuY@T+trYO8MB}B}+w|8ZZjzCF)oA>HL2*W#58fXWZIuJNL z>%EH!e6F#tQ10CBF7$zl)xKh7sc{enedTxQL{anUwG<`};UsqyN=&soQtO0>C3iW0 zRP_}E3aiy#VFjb*$&eLtLeoHO>FaFjHKEzk-I-sx35^hCdq#ywj|DTa(aE}G8 zkRH2b1$j(jzvhRqayP|WRFAEtEV!qv41gV4(_4k_neeZLxz4ljP;JmX&U9@kQ^E4s zAj4y0$Yb82r*uro6u`oPxUY4q9CiIxNFVlNijWUy`}(l2;ln;FmA!d> zTw(aJkGCJo-bf88ExF$b$1cyTAQV{bStj3d;t9ivuT~7Z^L?EYDj9ZE#m5Y%9bpaleQ?&gkwQrrz6LHVBs->)y@uxFI$dwtG zz}s-Gm9h;7uawxR?X17)49aY1Im4TUi1QCSF9kikQX;@=!x(c4km7eIWq@Ry`zdfQ z0gUwOmM#u+j;dsQh=CVV%Z=*KbUA9Bf7;ZK6c+fjPq5oaq! zJ-!lOUZ#XFepa9#H4J%y4Dp%KZ~3uNf(X0dw26O$V9O_OHhj;d3L}*m=o(sXUI|l& z%zMw*y#0nfdyG2!!us2+GlG4^u^C}s3uve@jtm#V@Pg|eyyl&R>>3M zHl?}aopY3+A*&>=t2UG=ZdK`^RWdf=`#Cdw8z9X+%I#bZlIi zxd&;Pp(n(`PIKqU&Md7T(}rqvHYV^^*msqT&^}-go*LIapR`h2!-`qGS-UQcE3-*Z zu9Ujcl10(ddzGAcEZd$Qa(p^$1gIxh5sIev98 z?8W0^<}7EjcARNLUi{eCi$@I0O2~^xweMMpo9MuAEHPdVM4bQ9Ci9%t6g6Tsq2X## ztE~oPd9dDUibFMiwVz2axe#U|jl`IFPF=)}Ppn(zKve6j76_56)nWRO51V2Fk3@Yn zMWRwm3|j6?7l>w{b!Me*njf3Mbdh@HTB{|Js}YB#|1NgcRn*Zy1xQ>ikI5zv#s%9l zpeSuHOpy-s8f7wZ_YWFO0|@2Ua>?@ZR{N>m8-5oTIcWOeMT( z(en!{q5RO}l`8eee`+@@o_LVhTm5Y{T|U=pt+9fij$VL}`Gqq@`;Cw;3InJ*Z=DmxiHE1Il;85HBekD=deb^qXrmhjn^U!sdbV#eO+SbU;Cs&lX#oP#X)FPEsyd2xduxS6GQOr$4aIXJbC3lc zZsp=HI^4=#<9oOT!=yNys}2)4HaN>7{0*89h*RsFcZ=eo&g!DwHfIe{_E&nA=(o}7 z(MDQY!ZsyT@^CA`)TiL(Dpm3vCb;mfw2|5jON6ZRDQje%7cc_WIe=rGD}t@ZDJ!UNKdGXe!25b(8%_7WqI0^7vDTb+s8HkSVX zRe)k{&>Ab|;H7cwHfNf8i2|*G*p!l0U;W$&w8_Yt2in6-76e+X7&x2N0ID0>K1ubW6pkOGxfnD>@OM!La}_PNcI;FWX-EFg2|%(0@miA zYC~A6RfF|?3lFriQQr~C6F?AEMExQHv(%gCLMJO?F2K0dZS}jf~i13)rOoo zI7QdRz*E=_dg{~@EoY>y)6QCQ1f6BR39$r_DB5R?K&PKTpwsMc8G&k&PP2hZN1(4k zE_`>B{%DAh3t_Wlf8vs^1@rHEb9nT2FyIt^@4nSnA`)aLOCMtcaAXH7Q z3nP#?AebfT2BRORdR~QKYMT6zfE$e2qQP@cr%1bGkI-0Fc`{qV8bpLKmI9>aXp~9E zvlEJ*cMghv6}`io!(rwwY7VqWnZZ;wn?sWLYnHo`ixjJJL-nZ^?*(F3vU`iZl&9dc z4{eQ=LQO~D36HuI{Dn_HeDlkvAEIrUGenX1^(j9bns0g0>GqS|JvghSb|R3BvcXw) zKZPTVtxTX%dScvm?NmrH3$GQAz5F?!sTx6Wz5|K7`>TSZUkS zPKV;B?SU)A9L}R{18(YTJpboiIrd+e9yWy`GKJ4Ach8gS}k5H zv*_}W@1zkvZ>*(5zR+Em!H67HoZAu{Bf`d2ucJP-Rw7E2h<5KgyH#TI50+(fgz55N zQF~TGaOi$Zn+4`8x9?aQ-WSeQe_JcUH^cSVKP(C!dbgCX+ntdKc>X#6=gMECuPN~gCgd&j&fNI*HK#wO8vjdivKw!#akA2cx|{0 zJes5q4|Jmr&r3Ht2hW?Ikfz-opit2^$L$&`Lw!+2%dbK&u^=HkrcicG`z@E6&B}8H zBJ^+gMmvkGavDTAwekt51-0^t_={Tk#B~*0xmccO8zG9$J74#joq8@fBNS}~GleD? zORWS`Vik@z1w|aKvx+-qgbDX3cZ3+&Dfu34nC znydOz*RvV!l%^y^i*LVh-le_8iqYKnjdgO(^C=_1P}^Gt0EVrx3LJOZUwJZevE;G>k)*3s`a-R)4D#& zk0ejO^}Z0O+GDI7O&;^W8#ov}O8?_v)F8sjV=4`-i=t} zEmFYnk|;*~6BZr~(!B$qwZ&Hq`q8;q+sG2E>EZWLk5p!QNWLlSliXZiZ?QF=v>dil zO`q6rMbq6HSWfvwvUUuN!o7nMsWW;Pe^F=j z?gl?29L!@!h=L&3Nk3iC@@lT%L%(IZ8(q-PR+8+3zTF_Zpeq)^)TrQvDt1BFY)$Q= z@5tmfTCFF*5_16ov+5{6;yg8LfBBJ(-SaXYUr`t2!H~)|)-NZ7!oyT+?O%WTADpsdqUrs`doS zPbRK4#Oz@N5`zSQMb(~S1WN)?O$i8#s-0uGi0>JL?|DWbzCfTm?Qx+&Htjn`wU|Q| zlR1K-YQY<=swC#>M(LaSj6lqRK>HX8jDUQLLYy7M?2azu?Irky_9Ogji)c7CVv}@g)F#lv?5}WetG7uGZtd&i$j#{|MxbY4@%o;Inygv0Y==-gNh3YP}Ht49I}bqg`N}@rAJZsloZ{O?1~?_i9lD zjtZRVK04!!4z-K02Pe4{Ama1eDU2^YzvT%K8V_l;H1uG$gqTSE-V6cI%evgGP$LGHYkg9cKMP*QYa9@hDSV4^>0EmZwJ#g_I{h?Zct}2sFka+#+b`i=93U55Fphn zn>A<#$8)9~Wfn==ani8kjevGMW!SM*+QFDh zJA4wNLJw6Fh0+CWRo@&+0pVA;@EY1>I!q+y` z5M>PYMHJ2@gOm`ZKhoN(4{nsJ7Y|dJs*ctN!!gwyYGHk_TYVf%#7<)Y%TFfGHB4L~ zP4tdD>NI9b3$>}NsEiWa$DULyS1-eh#RDfuH(*vBXc+K4hgx z$9D}KFZ$Dw;8U$Z*nm%c+v2f6AbhIEQmn3CebZ3?8L7VVpmcp%jvAt|i4B%8ZY;35 zmAPPm8NA%2Yp@0UPD_}E_=}b>4Y$w|hCRnEzp>E0Cw!rpogpufAC~ESx9ff_3mKRr zG498wSqY}xg6Av0P@%25&vIO2wL2}wa&Insi`*LP#R#;S284DkZK+x|BY z^t9U|=dt!JUh`N_FPBZt-y-L+1R*+hi`*7#hphRwn3Kt(ZLyN)lW&h?sirdwSviq& zumn}YT>M3qFgI`|-2E$j-hRNnuETz6;{N+!*7XF_fHqCnS_!7`f>Twj3D`6Z79}TB z8jBxZOwQE~S|Vhf>^17-Sw^5b0Yck4_GE1@BUp9fM^(=rqfSlke~s)ya2(>tyUhuBZJ}$GCp3L0a%u zV89!OY9*L*tFnS$(ckrp*3jZ9{T~726<(1^Wd!m+5Xk=#j9~fSk8Ym&TVLY9J|9}1ZpQW09Fl6OK-iIv6|9$Wm`M=LrKYJ?#md9QW zmvb6fAi?q;F6T6~oYPRrNwZEH?-TJ4yAt8q>YWd}I?8)AvdYT&4TtUN6nnNZy!7J3 zu1<;ye_x-Obj3XyxsHT?%8~Lgg(2l3%|nAHKGp@m{BKuP)(1u&*N=4x^p)OFB{QSth#u_PnT&*@E2Vj=!=IvbRf9^H|pv5 zq9yLM(RTFbxJswhza1--`p>$n@Fz9fzws9Y5aH(4MBjoomqqxUH9LzFkGN8_t>_7I zE3BuNx;l!CPr^fbZnjeK7tR6-CRD*Qh@UsdRlT&#;~J=F$1LtBv!|H+sH=a_A<&W@ zXn+5xYl-#}&$9?t&u8u$u8Y_u@m-a-#9yOasoGhV<6H~)f-}8udlMSQnuON%E>{DU zYmFT`?BOw^20b!*wddolbkJTj#`Q@37qKWchU)S_4Wz*VTTnwUv0KKtde*Iw^^j2V zTwNplc*ygj7?9_BvNDIPMJ|tM@|df3ZEv>X)ME7kG4bAhbw%9jctGxrj;a>C+M_(F z-XbpkTPsTE*+qV-yR#bgqy(932zk8fwcUj3AxebEpXzE^)VEfM$O(R^Qg`c3RlQ{o z!gr2b8#8KNs(jR3EOJd1#Rpvyl5Y8US4~B|<4O78;Ev+}NT>uo{3IN9r^dOpVa!|# z27C&G#=^(T-wz3?7!G+)VmM@qnUh_sD_3KrTP)0_KbzvRY5kc36gYD+fp@qMqB`x> z`@sTyVc=To+M@|p>QIEcXWd(UOToQcD5cylPE7|}a?Z93SMH@sBt$~x4ovT++=fXp zB5p;DQ)z*}GsU$!35_HD)QIQSC*>uwhBIATG?qb}o9w<_9BF(tTs-t-JOs$~2! zrsoC(#wjJJv6w&Cb%z$R&1wu(?%F1$byT2o1m*I}9rnkxI94vVo4dCfy-jYTH-J~^ zcsGsEJzBC{hwg%0&9+H&k4}t0#eqQE!BCubZT)K?Z=@72>sL<{H%)FL;u74UVICcr z6$Dd;wc|=POeWw{q$qOpu@E87RVt(k`8L?_f*eplY2mCEW%a^@khWP zS0RXI01C}F78x7GQ1x;k*Z(42uXEQE0*LxK#53X>fJoeA)4fH~$8#(xTLDHRDN=%f zu#Do=GEn-BZE`7p0;=HXx4Vv!h0>=rp;kyL)FPCj4}hwzOCYrRj{32D~0mvgJ}!CglzY-D?=1d zyIMoO*>C%jtCC~89Mse)fC7n+_NOofX;j;U3A|BFlyy{cwG{%)lhjV2M*7+b&;|=9lJdb+u8{54X$b`X4c=mRH{o;MLEiS2gBU zacG;XG7n|V2}`Vc&hXzkrV9D*7hnIqWf`QLCjY_vr`*?4^R${fyxK%hQB~)u)py7T zU#F$x)co!8;bBI8PKbEpjnvknaJTCO@GL&V}o?X5({A1-)McF|c&H2E+-Mx32&uOpT}YH!8}|GtyjSe?H^zWiUv zRJ1%lFOcU~lIOi5`1!-Gv6UOgj2>W?;ptgS74q~pUr$drJUs=}+u=$p#{wv2C2x+O zj~af4Cr#YXZEqb)H~{J5?60m!asFg_bwUIXaU<^ZA;hZx-60VI&NJ;S7k?7S#aGG2 zK3y+OT8dY>?c%~9XSk?xbbo00{6nT2`TT~j&)+kAer|^Z4bXPVN2BL_Jc9@c8&A4E z4ocr?U!8b@onqhiNY3YE|;gK-Mmm)_OIh&t7zS zs$}6*!@{Xd7qW1(uZ5Eg3&$H49yBZ*Uv442Q^olNfC?ymaO5!7e7)o-LTf%ha~sb+ z+a<2RB{2PQdy4i2QwG|moNuWYc1m1s|ihm!?b^AG?x7y9Bo` z&i))9-n#P23s8O|eW$<%nqK%NK1qWg<;x_j>$=@Bfk$()$bT1>^$DWzKdy9%HZYJC zqW*HzN0pn!8R`J|fg$76$Iw8U?4rTGwB38I+KRehmqZv?#Dtc&5Cy)D64uum5|1dyZ7e&DKCnO0+}K3hEfA#AG5X4;V-xBL2WhO}`i`tg`{g5|HO z3q{WB?P{6axd#P79<^R?&%o(Yq?oDOYKrZjxVEVmcF8C6mzWyl)C;HUX8bRge(N_( zshg!RZ4!UAc2VuDTDKM4j4=He!nC;Qopud=c!%jfzV7`{I^aDSrjPY>FVpJowhC3% z$AmgmXSW=?-VcYp!x z&fU}j_zBjGxj!VrcOYTObm5z%kgB$SapCpMT7a!jAP-HMi>Rybg9*I(XGoh>_ii~m zC6tGetQc+v*1N^GI!0K<2uG(0x(wjO;oBriP5hlHngqu-QmTs;S6p2bMaEpfQQ?+d zawl-(RoBxR>(S*-;HIx#Bef$;CvZ2QbKQB*Z9S~S@=d<7N_YO)e=ZQ$B5aLC+CJEH zd&S}|PK|=?v=?^EW3%@d0XH6z0N>-hOZ{TExR{WTqJ70O$aeQtgADajpxC$upF)7I zG;A}tmQd5Vo>O1~qA={)jk|k;6 zLAec#+qpd_SgGaZt8%yDb=Nd07yuU<%FtYDiIAbWXpaod4U9mc2?PvHWv__80cTbF z8QqG^-GRcUbWecD1hy2Jix@wO%(wT*t2yTwfkN|4AQ_(o3{4P1p~;0{Xh!()Fnl5B z+&^%?;RcgS4)|@4d^1&RFVwcNV@$0X2y_S@#Rx`;H7DU=?r)3}H3+{_!76+%l?OLM z+(R_l<;MN)g2o~jTLd6<=xX!5vUw0z#I1W}^H_-NdGi>@^Wt|o> z0@W!HsD~~FE3t>($}(8(VAI|J-RHi&0onoZrFJlb@w`(5gPuj+6>zm`&8Mhx-;DV&$MQFp?*LAUeJo4&fP= z(OH{rWtMj+5IH2mZ;8@&QSJtcx&&NxC^6T69#Pi7-8GV_Z?;~;GdYo4Q6P0BPvS4? zNS@pmxFZ2YsUwMRj|eJ)60o{wVM0EJ4Oqk z($)4$e2+**AbCJAOXA6Fgdf8_Z-^D~?w1wg=#}M=N3Tcr(c~0N#VFx=bZ08k+^ol>ew8{qp>Esod8pQvv7MRh-l{)nC2U3D_8!_0 zE5*1HG(-(i9|R8}qK9vOiRht?4^$}qtwfifLWJwFAW$K~^{6O`a6Q)fD+G6LN7>zR z8Y_df(le$n<|daLupZ0-a2*d}JxUovI-os@3Dm;hfI7tkT0-=AXTO2y@g6HcqZn;O zofS%&JJ5BL&-UXwG)|P&R_f{!;jou6hw&w;qx

zRe`HWY3}x3Ra!nhk6@u?HeHC|Luu}wkx>UgK6M`r@E3I-4GsjHo$pU~KU1;SIGEv{ zre$JzYX~xW4Y!qQimuY#R*c}Y&D;Pu_fcXau_VhqN9$sVkR3)x&>!Dex1;|F@FT*H z9-g)$zM15AIpR5R34QmP8z>P$jw2^>xPb`r4A=;WApb*&tA-Na_*LR^ASHhJzbQdb zARVx`cXG<5)Ag(En`gBHOwvEXK@)IpnO zahL0^cF#AzEz(LfMS7+ll&`ak&Zc;@l~x8pvyx>8aaIxmh(XaQS}~*2)C8zBHCcR6 zPHLWF8L0SCD&AImg%PME5X_Qv-OP_OKr=tr&1#F^y1Nt2nGP!^XFB&D^z9|TMbXqt z{(KO7$tW>ndPW`bR}Z%<8f^FOCGTf?TD>G~F8{?yI5Cgy<6HO-D~EB3t90qzFs0T) zNyc~SWp)>u}CM*hZ_KqG%2h;?{gEQZ|U&evM8d~`Ldc?n(3(wcJu zu0Jm<3aTY$^>W7s^(cXlR(e9>wYym!TBda?3DC1YP(nSs_A}Zjdv^E?p*yagWlBxi zszE;8(_->rRKa^%UMX}>Yv{dhx0j-HPb;fLzI#gtPWTkD|9$RB+G3_E**V{^b3P}a zowMGrkqWOFxAbu*YQ>C520jtUz&+ByP-Y-(0m9G~%S<#r1_`3cL?&9AsIe50^8ieM zcmf$W*D|jBb2O@}MBYqmTq19#HGoWr-EozvPeJe%CYV7$58tXCl564MLspEDrRt#o zRT*|jZXs|><;L$nB{V!o{b`9U?PJE^}Jx_;%QtMMSN4by@YZjA{{VfhwL z=`C^xy6xJ1EITQEPavfS`cs;o##sSaTLxfHi|JPRG>)ann}FR8Nq@IKWceFFJtBBB zEZ1A44{`UaRtQ|h?3{WHg5Z}3ZyD53Cgp$GE=uIg*i}uet5K(}81TnewM5~Dl{K`r zmKxXrHxo3qSR)OrIJMXcTybjQ)xwma?%P=S8E?i{9-_1GiiBl{@VKgl82HeHkm$+M z8-7hH8s@%3D`N`M41l%<{N^v+H_W|6(cWSuunUZ~d~baJlaJW|P5&rfa`;=~Z#GRz@Ie+O{kGqbd-EtVpSD5erWvOh2 za+PjV8awa7BIAdwItT!^NUO&L(>8LQ!*a_po)Kuv5eT&9n0Z)kIW}b(C`2ycp-}qa z01daz;Q(8Xz?U}4>M(w^QFiZP**WxK1Zro!0?8NztSam;(y0&#p{;i=g!ak&xY$$s zumml8d91s$Hk(N&KTJO?H{h2u0(lMyv;n`75wL_ZU95e~ouW-=>HkYMok;x(jT=s+ z$~Wn<6Rsvpz_Mq+6x@nG8|-Kh79l8PBg0DW=eTugS zJR<#X=+8{H@jBu!D@o2oe};I(ndmi(U}{w*7~Ue+FbPu@egq8hZIe-c#CgJw$XO`t zLOAM(8NHJGXsN6)%^4Gq$aQoR`dUK0RTsmc{AN+_MPPjb{>f*;Ns)yZamkg?XJIPRc_geej$jm9+qkFAoBj?soGF0MbN-G7!zpV z3T7|#f*3+O>LN9YD(L2 z1XR}ksJ!IYk>w|K+Z_$y`kqJqxSo*9`lFhBW8rp-=~jtc#!{rGTOF02wjH%Rji6;L z?r^zeoR+hwH=94SM>#$}j>4!@nvcJzQ<{G?;99%=3im$WzUX$*e5Lz7ZL_7eT#(W( z{st@6lwEM5itF;{H@JgE+_B__V$-0cMcQFYggg>F0JVc}oy!=3#w8%Y_#8neb?Vup z65Qq;mW%4}tw447sZoa&&*p$J4bTS|FB+hKJ}L+3Um1af{1`~cEyn^4&>)14=C}|# zc${@OIzw%6Ok&?OItJBfb;->H&N-Awv0^JsH7jg*B^{$FhtIj$Wm{7fq|tPMOQRv# zPmOx^gEe?;RwUYOV8><$Q?53uA=l=eL>?~95i3FIEUs^G*N@(hKH1c8Gg)sMTM(4KwcXvwYZ)MKhNbUx572&N^1unk*8fjdswuSKWEH!bd@bZSXlt}9n#%?s7h7IRzLlp_jX^rqnC-Z%F$XJ1O+V#$fH9)kaX(F;@ZN$& z_&#^{NIw>OsslH?pY^@0vGUolYbU&(Z0Am|uHJK8&Wi|>q1SOa8Lp06@jAR_c~90M zOEBGO2+N5af~BbvAI4u)i4PyA#;3DNgm-wSGkQd_N1f%I;Q3+h^rY^Q`Q@C(mU9{_ zIk9lqjH6k+SbfmlMoyJwMU-JY4LSvXY6`4+gf6CDqFomHp zAk9NBk@01_=PzXW0sf-rt$XnP8r_P^!|OM69cU82x}dvPsH zyOzJgYQg29#nU%9?WCD(5q5FZgN{IdQxp6ie?irX_&;ZE5?hbBhpWX935OD+1>vi1 zqX{JS_&f(+nVmXRTEHg|nD~$(3&p z*8xaD9utx_qcotz*9^U&s5sPQV{jDq6U}BrvUK30x$i=Gf!oPl+HToZm0ygN>x#Erb&jD zR%&@X-<~!^b(G3ReZ?31p=BwazGjN2pL1`l#I|8gUH$-Gc7+qBrO}l0lSc ze4FfFsBru?nIHcHd%0}A|0VZ+uTVKOD(!aB{bl!i+D@iZ_ETx?wSz2Si!;5qx)Xel zE7vD2LU{~7Tj>fG;LUkr^k?px@?rls`(RtQ>I|0B|Ko&14 z2c3O$G>>mqvU`{zW)h>47$DG1ocWAkNdT%TVMT~DQjC1ZJzU%Do0TMNFeL0}RFVJ$ zlJE>8kc5GsJkkNoHw6F+ah$lYH@>I#o^MVPaMloTiBU-a5JhlTP6L$FV$t8+dD6rYL#dU9;ipg6e?t@W{if zJ?}v%TA&YCBRluQD{hPK8oP|Y$r>}<8Y61 zqEcV9JLN9WCRyp&=zF%l2|ZlxP;Y661~+RHwCDtwx~HK{TjDKIzQKbJK;&O^SLQ=4 z<>u>Ls2rks3iyL&A(bDZu?OE@di8VnGF2^sy8kF?m{L-D;VbuWCFldNj-Uq%> zS$Qu&FkCu8FLX2(4C3E}w4S2>8}L**u5MZ-V`06x@GpGR8A1(#49+rjaLBIvGbZrB zID?Ldvy^&Di2B9}ddkd@3~D?L*{#`KPci!2N^MVq>u4&WR(o2`5Z<6z6(t`8g($C< zp8L+-RZ-nfOCW=ECX^;P&Zh%Ra9TYrpE)rnmI``&pLfljU4dX7cb7KY3-F)1v*X8w|{T^?1s0E^PZOY1@oC? za^IXl?kn`?z6;~+nF8Dg)2-fV;Q&OH9$uAjq_=J}3~$b0s*yLh`g(J!;mt`;`{EZI zV`Z!AP*L2v&i`ZWy#uPQ-p6rYF9ekX3If*!3dj_>3-<&pHB*A7l_{E;-rQzorQ&E? zIXUh0-7a%9q#TKw<`ze4xj;?DOvO=ZroZPr=XLLS?u&c-{Jv0s#Py74pXWShJ+C^N zA<(D11UmZFM#22T_4MI<+x7I%^@Gd#gn!cQ>@dNOLjBdBP)|vrMo^mslliK4jT*e- zsdFuO!Sm;AyyngH##OXWUa6q^;Ronnuj(7Ir>Pa=q#_0)~_^cX7acYYeonaXW{MewQm5K z#=DG4g&c8Jca~_K))i8gRzjDMW&Jxv0UhgU$fcgL!aL=|Bcx-sO|#^VTk9w^uqJX3 z^*^3$iD@0IVsyr+d=G^?15D*j^;cHNbPul*%23oV{hO#ciaJt=T7B0-1}c0&h_x!Y zVLXoiIYY?L5sFaApP7X`RdPRh1tvUznM_!g4*$frpFb51tY>Yn1sqyoWOg`003wSA z{*A@*%GSj35qIXx@GiDqeQQ-mC0f!xgUNk_CS>w&Gn0EHS33p!Uc zrJCCUv8Ui|NWs1YSoSZ@tXXs>#(GoJm#vh0LGTw7X&t)IKA3kH+#GhoaCUyl%J|G} zEyKAr&blz*;7TK1#9_iD+QhGZY~qx(33CMcc-5w*=^UA`hr~D4_panUC!{&pUP1~Q z!8NlH?3S`eyDtHLMTSUx22yvGvTRUQRg%-;%0LmtR$=6+0~*|E+O|?=fjY9KTX0dm z6l-cJmP_yxG)2v;XjZh*a7;%>< zpu?!8WJ^os3tC#gWsi~$|Bc)Rdl2kw4Sv`yw%m=7D--e*w2{_WdTV(I-(jLHv(5Q@imcZ$DV6Vn9Vg6a6FrsuQ2U zd$+O%Ltu!~{>`7XFQT-);wd=;y0O*b=W3VN5_vcHmKN43ZktoNm#yLpMkcjoWkiA~ z_rM=a#(db2$N?#L{PI#G(MT;pVH0_g*^5|ykc-L#+$~7V7$h90$Qbmsa5Bb}u~<4B zzf;Ddm2w9;s*804BhH`W4sv`~>qs_`5Coz&P5>WLrS3h~8Jqr#X#p}sj9`x|=)9~s zY*LT@K_1#pB^9`P4Hb^#X-RA}sQ_Uc-x=^hrEAm=@)WP{58m5pA+>NDt$QeM*43KG zbH7Rr)aL`*uOTe}re0X^gWO6RB~VeH^Z>z)TWOee;Zsry11N_(Z?!%a@{uZChFKR# zf!O9V?vW6XZt)s~=UO%i5O^ZES^UBi!OcI&q^d3I($iW~ zW5*RCat9vokd&%YH{NP}Wm6mig!QzB@UXb}#`62Fe<>7Fw-*iF2CfF$4a-N}LIvvf zBI%)Y>w{F+g&+8=-qw5;X9A_g@Vq|OHq1uKgHYD$L)t6)k^dH&@3;oSaq^J4Zep#|)z zPmJrJxpzKkGBeMbZ6V;?>J%~pN^>nwi^gb1&xl`WM$fE9GqQM@k#Q^QAeg_nBYFBx zYe^Jw6>h*Y2J$JH);zI|vWCqglqjb$OO<+hZLg-&DEKSAJ`YPx3FKjEDNnIa6$-R2 z4bmSA4KE|*Xj~tz=962dv}GTX3Z-Hnl)64xEgi=zt4)prRD7_nwY9#-P%%DO|JhLS z2Le7-@oNMjdJBB3evp(3?KXA2YVP=pYJ#rALJI&1-kp1OwS268Q8kw5!{SD|pB_b7 z4bmHEx>k&@)%`T$YZ|8av=HLm8WeKb*(WhCve<1;jl?gsr$&5We`}IYa{@xqoNn~D z?lJ9Uzuvry*fp~A-uV#XWe8}7TTrHCQ>AV~s*^PfgXi-%(j)o3gRGNScLklJwPY8| zYu0y@3Y?gr0x!S~A{FRCvU&bsYd4ln%9VNfpx%{LEX^ymxUzZ8f5h5WF91|xGP>}H zHCmriEImk;fKSbrv}6jTNd2VM< zrEb*Kd2NmwS@O6wkS~4$Hi++3(4|IlKuY3bYd)zE8VSmQg7JfR+?X{Cj+L3> z7iwju)JiDPiaS_r`HXdaW!-2*ga{jyiw4ORA6_!#{jkN?s%KPhlpK8YfQHZ z_@3vitu^E70O=vG4$L>3oyAz|)TrU=FNnZLy+hVY&#>v?_$dD8^VU|;MM5gn0RKnC zgtH6oUXAqTBZn6!C0Fr07Z%cn_CrG+Q(%|zg2eO%Y@#aR6)#zH*mI-+BxpRnp9m6! zBqrwO@qG02@vw{NuaC%KQn?SNF!{`1ACbbOav#iKvcg}Vk*SaXjj{s1BPZrr(Hv!M zOsZb&V+xaB%n);91A{~Mic$>zz$#Q8lS^xjJSKmVUNCSU)-Ql~Adg|??Y$b@F%!<7 zhKLTvg$+zxqMu!hZ&ui80;*!BHAg?WR=$qdyH>uA*bSDQmYBr|?POI;tjFyvgeBwa z#rEp}DLSeS;ukuq4(t4`YRAs8{#4mf70k8HV|R)EmFAB-RH+;HjLp?sdlbH7tt*q2 zOe(ZK#as#l$6-DM$cMXR+8|!`rq#mFUk$6pi@CKwn@U=$aX-ns`GDBC2;QaOflT(6 zx%ud)?JYIh`abrRxedCKMY54TXq~*6 zAOc-UDF9t%ZOo4x0tXxPuC;aaKv73sNpC_ix)PB6g~|xhA3iC@&tBiXNVeM=Ev7`E~LI)~R(ebxPg*yQ}K0+$LaTPWesIxXj3$5|a3% z#~k6hddKuU-S(r*nBq`1Vhct-Yu3{FnD?z6BP$&Ycl;4<6v3tb2?xge4v9`Bxpeg zwOIT@2etS|zYc2q=hp4s>)PROCUud=_+g8z@CDEAb}PSiq4jCDiExRLRq5&bJN8k9 zZc=7c?=si)!bR4J?4W`xBi;Q!%1HM#slc@dRN(g8eo~>L-1Vx|O`mJukMgOqZHcuP z3tI27d%1?z*UL3@B&onPG*n=$9ZxE74XyLQuVC?`lk)$Q0NjOJ4f@m);I!AcDj5P> zG-+R3TWOg*|7&Z8p0!>sd-e$?s8d?2xZ)UK7 zk`kM6Q3FI{G^%{@3ymtDmwoGJ(_{^dUa^#&w9LA#^6WRe$oe6hK+xlb?%l;7m%J<5?0m^mO z==GHi;KoX;1D;peS6Ls42E^WqA4|}J;$LPzlLDZlIx+1q`BHh8g1Ah+R6eard#1VZ^jZZo>X16);=EcLqMb_d%@z*VbASSfdR9$B2XQ zqHYw=+hXllIqYlBm;PjJ9kNvbbBBH6sj?O>I>>x=0_Bw6fKp+EM_1ytGNA$HH}P7T zl<--XAxgZmUPg&0*UKpJ_)FWc7CWrw#Jn$|lkY z>0a-L?%kE?KD@=+Jo=cBI-TIx5Qs5b;Ygkq2$^d?n7H|pa3kI?6Kf<9IvECTp8$hY zPJqEb0TJk{nD~Xhiv8qw0z9}K&H>0dfjm+?zQcNzC5ZlpWulL2Nea;OC-7MZtl5Rb z8VBdZsya7GGuBlra399cr(~q^2Odl8%(4`8;;Ve%bY=cz_^L2V@_Ke3>4$D=epyaS zxVnaqNA7^zs$yrMctm0!Hp<)*BlE{hO-n{5-ojq+*>sv}3Qr&`d`Y9^{_K69P2c`W zJ{I|s)Z$V^REWnSrC-E1V=G84(k>oa2!Z$3-IVY6C6@7K(aE>7J?6$peu;tTD5*t6 zq9P`_H9Jo#5Qo?qf%}qfEK@e5yvpiqRCa)k5O&~3$wUKEi?E>r-_^v12Bfe=QtLsW zLlfLP0Y1uNlb>W=%&ibZ2LnTIQi~X%0$++eKq?e)s1?AqI|LUU3kT>8EWQmz&OuFn zsyqk54s25nR~%~d*OM{=^=E((v86w8B7FNW@~G7o4OZqoF~tx;;xY+u2~77UFsH+R zFd}RrQxsHVhI&(#kQu5_l%j{u1UWXxsH>5SrQ%it9F;6Wa6*y1X*TuiA zZ`~-}`gT%_?r}4pa?01WzWp0I0X~c=yr8mY8z!*4T92`sJu!B zif>b%wPti@R|s~{HJrT77A5FyYs#~9@1D=wvsln3XkvIU=yVIm<2BmOEuq;Pi^5;9 zPt{nY>N0PPt-qH{&|`lon1Gi=U0a6hpKmOJd~MMhYpr^56scpA6sdz$D3SKrBt?1$ zsTCsCZ{Or+v3&m~-!j#EY?7;FK!|xt2tq@kUL`2d{I(gr*aU*xEKnoumUmAf&==j;IEfCo&03T+rAoxT;k;-#t!+T1QE?N(fu30dH?MJ{RyVsYdI0)1RC_*^I-{WIf_@0rNJ?@dzkUq6DQOQLhqA3c31R zij9$C$=b8<8mTZj3!DsJ`d;E9c9>9yKIT`0t6xcl;_6Q~S64_ia&^fcSNaxzT%9+# z0+h%VL1}R1Rf1eCsbh06QY^XJr?^6eSwFUa&)RPxRxVaft+z;pwI&t7nv;h;8P+po zUUUtuhWO8ww}ns1ONeK8k#>SdnEcD?+h9%fc=M)}N6ABy&rmu_;Q8VB@Rr)`qF+ye zANeHs4L-d}kk9j<*>7j082Qwkl7O%qQHer>p3IlpCpdrLZWpd!3OC~VMVrH8!)$}u z{|F~IW#MA$eNpP3%3iPM;bh+2FBUf1RO56mLRw} z#pO*nlKcJ^Lav?XhUhKXpQMwb`J#ztnFuo=bSnht4`d{>dRvv!(Jt9mKVGfTRv&hW zsW4RxkS0A(Ed_L$Ood5Gqy^U8DwnwzB`5kE)J_&7VHH_wk-*Nqu7Nd%Tx#VCWVqDI z6Tfh&mABRJQtQ)3w(lx0wbD0PYV*a7ZF$V4XjhAzoFS^zO~8z`)mm6h=Xdlf58}Fd$sSK!2L_e;WZy#IG$UVn8!{k z6jCwA48>d~6{r}f=vpr|ksTuyN-;i2bsd$8+2TVnV&#L}7mQ7)rAKU&8v1l>LYN-8 zO={?ihIwn40m=wIm& zv4bjgqpr@kmhckFKLO2yMc$)EQayPJg;Y-;5S6%zGJsT|dY}T;(}z?j_4pvw)tiS~ zVcfKaN6_Zo@kZ&kmik0PEBWcRaD9@YmEHn8)k<4}Picjex2O$5-*2FX&{_f0A zZqL7bGq#Eci8AfZWbY&|kag%ik);7MLG%@ueepi~ui_Wpettz<^2DpEsp7g8-YVQG ze&NNiHsY=ZUPhWPe&MB%UgCff&vaLda|=Ag87(#!aWg%siP&twJ&l24=%Mf3B7Wgu zZ!H)HyW$HbJvh0x@OVHWd|dL@+C6wqYnzk(DjJ}e_wcy(HX}LGK2<7yiC|;K)N0H# zkQ`}FasMzryp3&t!0$j#@n;WPL;s*yc*XU>&G|=dZ5iy6Di<{6=zoCq?@XL->ab=N zi{+!1H*~U~?OsgC4()BtLnsEgU(&o!#3=zAhen_b63VxUmlsx4Sn$K5UNE&R`jx23LmK( zSrl=rElATBZkF|gy0FuvmKsPyWYO}WGuJ23Y?q@+Vd=u?ZP{^(Tga=_pS;d0dADb+_sCG&-RuR@Z$XrO za07o`Fx}h(!)(RuUD73M96VoqvqT;Y&Vz&@;$ZNQ%QlgHYi_l)L>_#tBNaRM*zeY% z0*|G3k_wRJWAJG>kYhGK|D6`B&EvTvY@^s|(gty#FrZ!`6$lk70IG#=9cfEsK|7T( zA?OndwC*N*%P8ARtQl#E2%7AaWT%q~L;w{?c1KbnVCztUr*v+(`D1OF>~7LZbk}kV z$JyGjL8KVb<;u>$FYw-x=Qg~*VU%LcZAYL)d987BQ~T{YY` z;`O^qczCze2gIxx;YqG0y2?w9uM1MdKi$dIUV`>@?Ge#nFy0RC9#LQn&82JYO?h!{ zv-+4}jm;(e#BqDPO0f3cPMKhBK5a1>&TifTj(tw$pYO!&t575i&%=N^m0^vSJXKZi ziQ}lQK6j_MA(`3CwNlVTUHB|TB#d--f;D3rU#BWD6hl`Y_DuDNVFV@Dp0z#0_7gM} zi|sk=XHkGL?^C?=S=)Ygk+fLzvOPyX2ev8>B+rqGyjiw*-g#d5T#fPblWa*WbeGZ| zc#22#I=lQRpusM=e@GR;=l4myO%L29ck2Nm?)MUe+vU9(uM*tvZ8F6c??oBR2s!$h zopQIn93Y8LIMtbIJH~PdiO5*5U6Qe0qyiaxeVT1gz>r-!*WPZD$cB>Y1>8PZAMB5{ zvAg7fj~8os?{w-3(w7u ztEB_|Q`U~^tS{OnH>a1F;V<+Df4MLCcu^{y>6SVvCf1fG}iXJrLndr6=19r^?P>9?`+&hD#QrX?)o?S z2lAz}ZLKN&ykfS^21hl(bWa_yp^ynSL&#nwI0O&PvF&1{m^-q;vJcL+jb_ggnjk*S z@oKhYp6y<*0wE5qjiefnYGC+!j%xH1JLO5i&){E|CS>WmcH*;%5aQyt!>%7(QF#A) zbZWq=-Qd+lGRf86G#D9uR!B4j57kNF^`5EfI#;@U6A5CSONlc4>x^nHWq9VfxX7Y+ zGShN&{Wv7Wf!vbfFRo>B-?JrY0l|BW43i;yls#ubXbyJn*ycWft7OWSJ-D3lvW2(j z+n%f9x<;?LN9K2`NvHtT%9U;X6j4fNMNQH+e|fh={RUj-g9M2ryJSZKg zs?O#s^#={1K1iriLY-_DYG1MZ7$qnPB&Rjfcz(t zJmHNF*PegxF3S7HHc8XMc*(amD}VYcTd)RuhhoKD_h&ybR`k!6hxC< zN$3(|Pj1e-_R7uKT_Q%J^ihynWtbCiDAvO659?oJyP=7Y0}r@6ifD3HBxwwgHT)OClxATPugcZtK4>5 z(f@w6wbu0TeKLn(#6HuwskhJ1xQW?^4XwbJz7`{nhX z{-#=SP9iGt32tv%`I=2;H;nQ@uIqN57hsRkTkZGkWJhW*@wC5e?eu5&^OEKEIGN0F zA~XNBLNF<3wLL+K>r7Cb!GvjDAwOxF}_7vN#024*;Fce*8szpUZB`SIc zt#m8e;)7Dx_Wk(QdfsV!Hv5P6GS1latNZ11YxWDs%s7h>2XNBtpcZeHH8RyAHBdRG zc}gt1O5wVxiSkK}G`nTqW_KjO-d1n>i!?it_z-q1!s^;1qqhsd)at$`n850q@$*ye z3+J!t>8n{+LZRDl#C&H4&`Gs|TLpR6tSAD~tzOr5B$F81y`mc$+kN5}8ryxpps`tq zv3brFz5@n@Tj^BGK90|c$Y>!p1UmEF4XF*Ie7K<*V|m3P+aO->DC8Q4B!wBg)kEc0 z9$UwL9~+}6=4g*2RDqk|8K}}X=Qze>0!7n0BqBUlo z!?+ngac+tnfd#a=+c+#fm~c)0MLvjo^cUrnYT>aOBwKYnR1T@mzib|)FEI>7q)&vC zO*E9r0tqz~7s0CB6Q)r7j#Rk~C3=_{z_+B8a8*&Hz%6#yFm4aC_hdUrTLDqN^77f? z7bA({p`Qo%umsB7hP~q;0DY^(TZh^X@fAt(dPu7eRXVMN&oFNp?YGxm0F$M#?J6R`CVG5ls zze>M}*|@GZvv-P)7Ikzm)FO1L!7x46{t4Sns_-1JV0g+s0cF1$IiZe`YS?BNtN}wl zkC^}XRjig`;al=r{g5r9mvPQ46GI&U+1{DZL*M-?rqbz9-Dt^eMWL)jQCKuJ!M;yp z^$#dB#?fd$5FXeFk9(P@Ldh5xG3y@C`KY}S>HK1n{RPM|^Gve6ElVZ<@LVVVLOuAt zBq;^3Ia)FwmSTUztF?-C6(-|qX7dAh+{GK5NmBuv5Or} z#CGQXh7EX5`j}?Co-7sE_|O!42>+*ry}P@uFI=^y%k52Z&Et9tK=VdRcmy|r@Sr#= zAf?FJ1U@s}-p#AEFKl%rw(%ZpQ>^xfw7MMrMDxF`_TEiH1Z0%=!?G>W7F-8dYVFtE zLX4A+3CyMQjp&bF?pyH-z1+74e8zag_$s^IR|tQ`VV}ab6Bg06ZB_+ttTT>RZxSth zw?z~mu)k3RKc8WDvELL1>3GV3aPi5=L-<$bCh)-*8L+H&Lw6V8xdj-;1-a}b` zKuwgyH?V^sEA$N!2c>T~djvRCoQPHSqgU_#S}3%~cVchbilk`AdPs71p7*W-ue z=0dQ5O`XzZr4KHad2ls1|SnMt0Mr+I^(T4(gO0|+pJqrQrRBX4sl7 zTBBXf5x>x`=J2Jt_9UMRyi35Gh^KS%?B{&M)6?&?FAQBs2rzEBexr(TVTB@Ict|GN z`czfA$(ymOT65A^nP_X10*vSVZLF>mD~rQ zU}6HneeLb_n}!Ko|0Ko2pY02C5@7b$+(!hjnv?KzGqn#xTVpJt>c#Evx;>JrI9ZIv zlv^y2KrNeWf0o6N0&!(9q_HT#7;+=kiBE&rx*7g#`%)n6mpRBrM#(hi|7FPOS;sB?2qf?8;1~F#$6?^61c0>oskj_ z-Z@806HsIVtNCFMG3~ItT-4yO%(nG9ArpC@Aqw2QW1_9k56ko+3rSPt=uU6JTgO0-I~bq$ns zJUNkFC+(5)D}E>sIwG%bdQpC4i#0yRB0$h-{*r>Zoj2WTbuv;SMPFg!rIhd@vTadA z1YH?lc_HJ$?HFLV%K5PK5ugJ7Ru}OL{Z^MFmFB}D*ap2_tL&+YG9I&QTIhYEuN+no zmlr=Aoyi8MB9E)m?&D>{?Y(pEQgv>EW^Apdr&77L9#_z%yYhj~HSP#av-L9Rf}ZMm z5P|SiQ;(1oTmLh+de77fvuiCkw_2uJsl-~l%&oQ`k$V=Uqyl#bM1?1()>%?3HW%Q* z5lA$<@YOC%Ge}iAwQ7}mv?7-f0i_a06sbTQqC%w8YECK;d;qU_!rohm0W)cJBK0Vz zb_T>=qyiyA1?+}IaZIAsm((KIb{?>pK5GoAN3bIdu#-szf`tm)WOD=EOc>6=6WI@@tYYYObsG2y%CX7QJ4;M~7+T%Oah5{_}7^(caVzH&UZWGq<;KtuG3DK?tV@=>c|>%8PGJ zXze8#G3Du{rSih@p;9AX)=<(9g*v!Q3Ux54P(m#z<5PB}qy&>nlLz7MnkkubkZFvOFl!^}rUXm6;e@6S zgj+fyN6?{CnKrAObVIrRX2|t7Qh{=v32C!5jhD@_H)jDyO}2W|pIk$a`mj~Zn)P=X zX3c_Rrvww;eJ^>Td8(dxRK5sEHlu2O)Q<`szEI(dfWOP+ivSa*JN4U+$`=8*6C|*g zFj(*556L}8R>OL{N-$s61VW7u!!c53k$%!} zUNCi&hC`Z}3`Zu+nn!vmyCJ=#-5gbRqta$ABYn|$zB(!gA3JS*%-4_*JT*Tic?vxyc_J7Mp1ewsCrp|} ziX~6M$2>f#q*=oWiOASc$=Fa*E*L9(GVFeR`Z1X(>v>X%d`T=2e1>VU{dXEE#)5G6ok6Ax@HOqWo3AGp!UKUTB+CaqgVJU~L0m@P&Oa z`x+I9yju1Ws^QgahKzM zOtANHA0{aBW05)E$dA>503Gm^y$hoSI9InlF4;&r?q)-%hA+9mDfjWzOiTfSRe6T%j^T$yM$;wK6q0VxG~N+Sgi%n zdvLKWwHeQkhNr|!6m)g`t}i?;x9NT`)yh4j<1#tcLR#tBrt?9r>kCk3bbPcv_qYnB zVVmyV<#vaD@VE$_ZTcao6Ssf95K!sfS|LFLf%5|vQs5Sdfg#uOhiHr{I4gdk3eHwm zfxM}+I3_-bZ-}*}@zS?!E&1wea9rG|X*_(ANnFr=XnA6z%8OXOZk7E}R_iwaZfp&q zk^)qLo2D6utEr^iZKrDUL!qgUvBnBIQIh31siYKBEh-5rF%y%8R(h1=gIrhCZ&FD& zyp_~=tvy5Q&UY+_M`xqg+QYOS@az%p%R~vlR8KVsCe#xtaLdF%l54q7G)6u36~9nV zeSfPoRHUAo{b(=sp^5J6;pl4&!HSv~p$gnsXB?@fCQ3Hh>hK+(rZ<-Pu%;^%L>&c& zI%b<{Q5{f;>L{R<9(DMj*)>_JLmSE+o9v@tv@F;J$8$@hB3^&FML66?K}Ad!AgLl; z1P3aD6u3oVfX}t85sgt1YsD{A#9AMU$lPMjv5+_99zgJ@J#S({Z_5r3pb`(D5(y|& zU0Z@2B)lX~AHv_;YTx4{WyAN|>}OcH0AP$Rm<(iEgq+`0sT=u>{nb+JG=BKE^G$i! z0l1j@$GRqwJf_5c54)o9$Solsh+TjEW^4&X?6h-M_kz@)sB^x8Vq9&f%JV|V)^|9hB4YK$P{Jo ztp5UrB6dFj1uh8)3M0z&D#0i-sT3}dkYX8S7N3ye^D2NO-sY#4+555hlfa=dqL7uQ zCnYOQNd>af{-nW5M^b~Vv^|NeRDP>{D<5;p-rCJc#!1NuU_ed?2FVE{C47Foqpeo~ zhGk7odh@`4vtMP;5`vJ2rwksRA{DR(n5fS^DGxykNd>Yn+aC+_k%a&-T|OpjREGYV z!33Z{CI|{c9bP4Bw)_XlD^;D=jL+r^hl zEd0v^$YMo`CD;-LRz2ZfenLjGpPi7WEFXg@gxMZubx(PKax{1*3fu;dr!1-Pna0)$ z$t;aDMUf?+@?*fQPoV*$%y!-~^)|ivDO5abMnI?qL-Z+08#_g5Gfq?nkuFH!07@X7 zsI=nyF4%`x?d{k!-entH5{kHFzq>jBirQYbmuuQY9`~0$kxeEPqnw`cC#RRFoI)lg zMSLWD1kTsSHrkV?cteL{9D9<$gkc~bbVpZeK29|&bUNVaY`?ir>8T;XA<)Dyy^p{;-*sB~iq?*PtlZQX6GtidkrMuiQ{qihTYkQ% zW3ayA6rWY#%pxorRIG!Fj*cvS^(lTN)6r93c}jS~$f6Z(9T6I9T&@NKnx~1CD2d8a zPFP7X_d!;miHViq4vy)py{WN@6^n%5rkt>1DL1oXP!RzYz=~Fn+XEc8c{q7Jz|mD> zE)ycNQW{81LntRtnfo9o(8SD1kYhf3$<)}yNka+$dCJLQD)Q&yCXGRA8k010mO-jqf9!*<5GR*q7DofDDHDcoHHfc>HI6xaB^hfI;&_?Qtv4!)_uFp2jh!bl1IJ** zu4h!KCwBe0nz8E-%+Z*Ss_SsEn+m#&Sbd;#-2lO3I%a(=uWW zJxwCkbaSgzQ>)eCjxOw0bE_<`Ru8a;NCOO3?>{Yr)yGH$QUMhhtO6Antomkz2CEu? zs1&S{Zu0ix$#T!eLqtP&$SS(Zko67mOXKY=j`q0oJdzhte7~f=m(17!}%4F9o9!(JSDW~ zjB8SxIx-n4mT}Ebr)A{#BS7**uc^NSi!^#o{9W>rNGgz*%-;=OvPq5LMeD++q&R%s zf9d_Z7b{u^?r82XzAp!8kR5^s*+~l~&@qA~Eszf_UVzEg-E3ggH;wedsBbb*i%}o^ za5G4wK2j{9KI?(1g1$AUWni`Bv<$4i1PO|uZ@GdggT5kB;5HNt`hNah27UWTQxw*2 zKf)?g!V)2$2I&{w!eUzp5Kq_#Up|5s?c~=KihidQ8lhj^GalBB*i;m_$;8laM4F?@ zq2Ho(M-%>OOUIp64E>4#K$ISkddA5AkVeSGF_L`7&lqWa#$#AJA?&NaP>e1N`$FW< zZq6Gx9FMc+1fq)iDz$E=nu(|nvQORTbll4BQN=3gQ=RKdRC#A)&{wH~K&>3~Jz;_^ z;|m3&o&-J?WaA0?rkndoog|q1AS=+s#LDh2 zjt#7}sj-O_BM^7~L3C384;j5yqM{yDi0GB^! z+oP&+gUkm$8KHUzh0N%8iJYI9QnZzLoQjXLmx*8aUiMM(nhzgG28xGG_z-Npc%p%i zKQ4$n&UpL#193GJuioZ}J4|?2YOXk4!K0oV;uoGLL=P2vd$^ZfDt_UX;Ypzsh{t%v zshF2}{wH_zW-Ek^My)yuI=3&kbzM`CTb5|)+&Z>gQr z0{4<}eo)Ip!&8Vw190t@058}O+MahEoIID6`9yixKsmo{{o34qCMGI9Vn)!oQRBxx z{K#CFfIi;U9=;6VIyM>phflnBD>&dU5k9hXU6sp3@5s_s!jcZ2@5qqkXr8|#G_0uG z9gcUjP;~uy!gmaX(Qe{S4G?3#5CgY+py+y55xWH81P;^F{YMde*!b2<2rr>of?VO=SB1;UKwViICJs zu_c+sjO(tmBB@U%e>WweD(U+@w0R@O^!=0+w;cbhx*P%3I?T{M^8rVwrq4Mm)BnI< zk-5KUXg|jwP5Yj2dC1X~tsuNs9CEhe#fh3tFG3sY5OK|%v48zp@dneuuk?3psG5Sd zKmw~3`HmLsYl`{73?oDTeo;zKwU(R}Q%;ut0J;ZUA zwL0e>jGegls3V(oA_ZBljJx$#=j0m~0;$z1BB8=vxwBVJDfOAsHKD!tvA z<;kTky2@Rkoq`PUPj@c$f#>i_N(_t*Z(o!y3NXy*be3n;wc9X{ddObI$64;sTEwYD z>ZRvpBK4!H38dk0KB6B!FV~NiJnWhCc)k*fRN+l&AWbDw@9-aZin`ifA!rBB?`98g zdP9&#J??Hr>si?7Syw+wI^Dnu5BIzxIU|QZ_)3)mSD2pAVbu-w#)O&M-<#_AfJG8a zCFRa|K609)JBuczV3-htJPc2FB6;2Ea0*hX%jD^fHrzJF5v;i*7TLPqbFg(uTUWT} zo|p)M03{J%gndL3TpN-eRrq#mE9>q}M~=md4P$W?QNgnsq&F#=`Ml%a0R8R?OvMr9 zvn9`Y+0i{nSzj(fB<_B5*y>lMBB1wQ4r z<|!=r0vWIF&`t}2?EA1GTFLK3UZ^a<8E-pYtE%ku3sQDErNSe-BvDFbce6rr*=Z@Cwdy3T~(r^8Ube#`ty!{KuTUE8jrG@~PQYwT1 z&pRDK;b!?QB20Z@$Z!9bj*r`^_7Rm*^HQaZJ_V_}BK8qZ6OB2xl?n1w$|T z@q$e*;vn{EiKDwYC-XC3I~rG2hIKB=5nbmZ@hd`x#WlYSsxJ!ZfDXDS2Xw$iX@6J0 zbUj?yKhnIF-)vhjU;k%z}N z&jwvPjwX-Q&v^bx4TZ;s7liTR4US=jYi;o5?+p-sgk3TYeCl5!M(*Yx5)WxRMcn*z zaB$@rH2M+_z7RSMaK~c!EFetFokZgA=&IUM@Fh9)f+9f;6bcFq@GQp0~#lRRsYpJ?~t^mmG4$$?V=w|LhnZpqF2g zK{ouw?A~Af;uxw0)VpkC_YS}8!;tmR%Q%D7uM`G0;o3n*hL<)WjGkQ$VpFv`{MSRU z)mVp8A~cHghA5=A8+6&2H!jP0qwbM}*({56h5f!hy!418v^q5DT@)I$lp2@iw@TKR z!Eqa0zE3;ma4;7^t7hLJ{$%$!$}WnIe_&38fiuSNyhDxwJb#=sf@i)0*`*JDl3b_o zk7_b8=rS)TNK0UYD4p)H67jrQv;z#D`x&CWcEa&FdyDk_Z$!%#8ZXh7l{+5QV9?z5 zJBW52L90Z&+Mj5*{hy*Om;vcU&z*5Jt&Uk}E4byXBblwB)OiGY#4OP73{Jl_1RDLC zb0@n<`r_tA~B))*}Mo9ZQ-OPK^&Y|_|Cl!xcB>^v#u8m_x?o9>KpxeMX#4; zY!@B#G_56Hf6392S^xCqFk1ZSC**ARXXSO{wabnVs-=b`{_$UqmMn>qBGj}J}Y_DC;TbX{uhyM z|BV#CF{C(wdr5J8fU~EjAO2G&@-HQ5m0LLIPn4(sU6cd)&1+60oqv9ivs&`h_x~xg z`0uAAdVIrmvp|0~1iA|aYGm;b`%8_j|3s?r(AyF2%!Y3rdI>d#IeTk*+rKc4KWk60 zf>1N+%+rhv$~>;FX4hH^82+N#Zh!qtRNIz!ee+x`ey(;_2mffEXW&*hzd3=7fmoVmN*e=BW7X z;OFbbH}Sc{TXw0aqQ3JX%`33O^T2tL&S%(CLJJ(h4bJ&e6?l&QE>!*44`ad6O(33l ze|!>re5HHho$N=2f`|8lv$*2F>P0ZFSv1Zz?sMk8abo%iofK^$!Y0l#B`M=@D_unn9D8s3R2XByVJ-nIIQ5#dpesRUHA(59~UwB2@P`1E8 zZ75x#gk!c9a3fn~=KosNaWV2^TAF(=Q7zy;1Z3s6Pg$PDrG_sGuvEi`6`r$2aK6ek){@YKialiRl&V^wx3JIx zw|)-6kO{N*VBJ(>akVGMPh%s4e%@7?LEjI=H4W2yS}4tKY*G}tmZ1V0TG24^3$19_ zRrEqWtq7<@D;nI!S>J13DVoyO*-vBB2=(ZZCaVIEwfs{}Yw0rgTtlAU!8w){D(Gk^ za6Z4Lv$GBRkd&iOn9VnKbXwVLQjTWggFM%)tI{96(#e_0ib)T&xRqC>KiWFGe)0qRe2*Y&?#M=Jp-<}4YZ=GGgklGFwj{7 zDmBn&6&mS+Fl#Ix4d~aPtuc7eP@ge(zDYadcR?sP=#8FamLM|E(nx@l6PWlVC$MY& zP3IXPSva5*+0IyR(+R)D`4miMggjw7d3IIcHl4mTwHh_5X+0%#&o$$g9!{9g6ar~I z-FR6Ku%3HJIqJOIH8Gt<@)#%<2dY>aBa(IiIjlG^~! zWKxbMG(zHkm6RLpulI6Bvk{~mO~{9YT-or!bTFY7*OUo)CbXN=%e&Q)S4zIPX860e zdOMT#g>aJ+Qk=wO3k=kp(iKW#PIyxCwW=~EG;`-As)d};q9{1GIU&J$md&EEoX^BB zIiLNDIkg0m#f7)&cR2s1p^?1swjtN~6+5o*%c-kW6}UAuqq+fZ&a$*5Ugs|7$Lwzf zo#TC_zkqy^YvJNGdCx31E9G7m@i%a1j6!Tx?{9f?Dvnfu<2UY^K`q`hvzcr0MpHdL z=3ZxS4}v}SItQ?xq$MJ_#XxW`sZa=@77+|K*CK*jD1ryrM02CuXIV?_Z~12K6;g?p zr6zbf<7Fuy(sx~ek(H6ykHclDJbvOqXFJWfB1Ia@D^drDK{qfWG`Re{R3OC|?fbtC zi^gw&Bt7KJin$;(Le2S*QW0FRoM^Z6dPfpwu{D%(af0<;e`i%5%HfKqe}cVH$PWtQ zSzeHszJQge5)PYgIcz^E!2Pz^UUeDB60^>mT0?@H=i{yHw4W}v?af=75ybQKLC$vU zy00#L^&n@9${p+nl2TaR>&iYUStC=^n|XEdY}G{X5I9iG#;qj6J3T0LI5xz!;1yo^Vyp zvAcP?mL>Yi=X0zxfj(w>Mviz}2Y~0yJYS11X)uXt*YQndj|G6JXBzn zZb6c6a)`fsUCmi!h#wOa;1K^E%mbJ5>qk2W$9yBo>F9o6k!mdA@%-STDwa$5J~OL6 zx^y;p_FelQAjNR%Xy1XN0PPzDA?&;8$=S{@Eui^7z=6oel1O@hfj^?h{o`l* z+V+pUZVAkLOd2u(UTM`@i{VS3c3OB?=j2);F$&;WUePfT!}p|Qk`a77_YJ4PVsrp-$K!?uN4k*&@vUz-o9VCr!~b~0*__QXBYM>zqPKk@ zs{59+wGMpEKh>fMBXZ;rWXVjUtPw#VJce%hM?U`w{6{|j(*NOW(h{>miD|&q)Z&hr z9r#_7oDmT_FamZxnv+N}4BLeoy&5r|C_X|YWVVzmv z%&y#M$3J}M`_3r7txbp8T%Y26l?C2V=IV4+b_ z;nNX+DUhNg{`Q99h=;!lj(CzNr;d1-qRw!{c<#7L6^jrkp5wXWdQytUC@xKhinhMa z9VrZ9P4hCt19^2Ex?85T`5m*IL2Nmp23`AcQXpJAD-#81M3aiLW;?rU0XKy-gj3gU zLX|tV7f$`38-AQRyD6PI2-4)#1FizJirRXU5cuJSMm>7-o6@5vdLxq_U5n!t^PD~| z&)RNEhfWbnhko^jbm(5_yd8Rvn}$Qb%^T+<5Rv&tcbDXk5p?L!b-@y)A6Joa7Z=S|nC)^1;rgY9y_#GCO`?>al^TYwYcQ|CWl zGn&r~(Q5OqH?vvOjJd{>Nabb;G_Kq%E%mtB$`lm~LCQ!Ma}_PRDW9!ZBK?b^lJ}iW zH1?;W-FRvU6BmKYr0>5VIJNQT7C0|7tyLqyW4Is?F;>j%!o|^&|2g}R$%Ax~T;28o zY|+qCGra~M z*d*h2y#Su9UTYJ@w=Z;#Wb@6f-Z8Z*-gRd$_MN%aH>%aF{B{#R?L<~=gvSb-VAv;GjgED4S30A8uu}Z- zy=eje6Vh9l63;#~W18;|(;{E2Q~ogg>5m(MB0M{zF(XDmX4;kn1J1Om8qeyNk)<`{ z^Vh;vr6~CL#V2jDLWyC^iMD;wW9yuKH0IFNi1N&|5s?Bcjz?qpkPeqg&v&pE-MQY` zR%@EAI=LO8c?QyZ>3rw^oDKPmUJV+O3Ab(K370^VQ`3V#Is5(p!J!S{VH=$}WR|N0 z>gA2jw-_x|Q#J7iTBLJNo-@9!MNUoRY8i+9`XT*Y2if>5(J z>1fP#&l}QvYl~CY*xRHNt~(VaM#hIX3`(G%pd>~$FaWktAjsqy<)vlAO-1sX+nl#q zs6%zno#4Ti&TZ8v>PG<$=g#%w7tWpQ;j+FniB6qGa8&{l(U4orMR3_ANMnZ;G4dSX zS5@FPj~N%Mxp%g@#2La%pNMb5ukLbw$1W=ra;Ah=gE&({{u`X#-rNHhV;=i7FPy_K z2MY~QW{#WZb$Iw5*xHBYII%W+*?B)pG&hR#ZuHq+=i{uixlw!XMy30lL)ks%MtPn_ zIIH@QkV|9&5wq&|zc^oZPpG7wTsr;?Z$y_m$B`NJ8G#CC)M){7M#T^D_CDaujyWTw zM5on#N^EjkE&BC0ZJmITPfM8Smuti6&PHGaVB$hD1@hiCOrE(eM zr8C1L*Q?3Hr?$zm(81_-$>0QpOSZf#h(VY9p7@0>`MsKcmNOsy;jHQV&e1dS&Qa;a z@*r+M=lqdCDh}^k|kyctyBx+Y8!>=wyg~{d0u%&t|dpb zM%%hW{6gEhBM@!N=cS}2(C<>lz@pe|&H%6ZU!I@2{&p^9Llp%w`ORojAVjVY4dk;< zX55}LSXFooZeP`d1IQ)ur2GK!a|$qqAq{+Ba!n5em;63_1irX#i+X(0U5WRxw@E)d z(C2|Nl$e8mZiVm&#+%q3CH#9UQvMS+3A6}p5?C=TgS7r zq#ZiY;@fHk>!$QAW_rZXmAY&0%I|yKseOj$1pII-XW97GI_4#?0 z(K=*>0OyVt#1c-g5yW@S@6tmc9AkyW4@C%ja%tv*2E5*nR=Zaz_~;z{WFW4F^u0j% zT4$EN8{kcD{V=5paDGI#AFzWcwF9U`EOW~nGNo*+TfDzDOKP-(!mKb4)m!)Ui zs^?3Nn)FkE+~zNrPV=n1Yn@wq==TRnl6wYuNM8C-n+MtZs-x80JC#X(H-2!E_c$ZKNo%EL|kZ0xBhe?UJnVqA5Y0&?Uq8~)x7Lq6H z!HgIrxyMb%gWFkwHR42gRbWJCbxr(2XLT*e=R`P+M@MA*Nf#*Spo;E~%z#x&L@nrU z7$v6XYC;NdE{foBu^HKg!x{(Y)KhhCEzQ_jO(&(kJ#1IdrKj?N&Sk4*c&ac<@_N>t zbiwsYHqUR8(Od6QORisvMc%UZUM;xmH-V%g{BCi8E3w40ExB3XTccpYhs z9(c8ZXeX&qh@ch`y*Dl~mK`xS!FyG!y-|&Bnhdv|NlV0X$-oj+TUmy}0=0mpGmA9W zB7#dE1Op#|z0_t;CJtojq$MIqtu5u%kyI!IP+NAjO-FW{xfT(m^0>P*96T(sT@!e| z4T6(*L3~?^oQHyI8S@bDmz2>?chwfbM>3x@(O!>lP0HvL119A?5rrs`;C-z%Y#bp5 zQas&Pg$HOj{fG|{hm2OhjOph^RU)0(bD{wKuB{e#{SZNpcuBGtn0>EGAJHBaUF=O?}(9imc~=pg4G>8!s6#m(>1 zlaID$G+`8*n0rDX;VZ2dQan1#NHjBw`Z}-qz|x}(||T{ zyF!4&qz0ol3FF)PIV07b|KX$+zxg8EGT={!M%XW(rr^mPVRsaCwGbw z1xyMI0q3{P=*5N-)FuHNd0@Re3IRVs`Un9>(Iy@N7wu@55vQ@~-i?j#Jd++$vN3f` zk}XZy!#?uvdkbHZF_yu@cQn`qq*86KtOA+h{{3oFjWS)~Po|rsOhbspLaI8ke_zC> zbjgSbDN>+}-IcOBa(CsJs*#5TNBklA!xs|VUMT|3#rBF97PY++7;J2>)CyK63Je*y zp#p;aoPmTxKipsOVoU6=09#?%Fa`-ivc0mvFd!;kG$2xd2J|3nO(-(ij`3+??>@qI zx{*FOIB64)?a0BogXMX*HjIaKk;e0$*?7dT9N9hN1vb_j01V5Eu?(`Jp#_a3m2y-L zAJmth?~xJDW{@hho)@K@D{t`>23H=D;&4Wv9xO-X$Y41lDK-qZO$7}&ewCP(V(j-= zuxVrn=8n9VSirUsB0-jh&)H;fw~5pucjD8_+HaD-lcW;)JLZqS3V-|^G57;~=y51M zMmiw9 zM=Q}=u*5!Izs`8(0~smo25FDJn&%&{{y)z>v z=p7(kkbe%g3ZIl{77!gF>JU3ET0YyEp%nH zVNa7{T(S-2rGr3QLrJ;Vv9tIf%=Ku943l$1%v*MeV#_X`?fjieGX6$-hf-6>S=r00+dR70mwLk;jlktx*RgG^V)P&pV9LUAy7p0K_Cet9}C z-jo!i4F^3WbMd`leT1Qmjsh}OMv_8hD1(-`l>xX=852co90!xcFI2`Psf-YEMe97z z+G6h$MN=)iA?5N}<1_kLUhx2$;Q=(Gl2*Hl6Vo_;>k}CRiz zKABLXM(UKg6X&M5qQu7|w(;{5G7{N${s7e0T}6D<(-|?1#N9$40K#kV&}V^!jsGVE zxSN;tOom14%|o6Al>7hB4h_YX2p=d1N&u(+PXLo8fJer;)&Z{*=epL*Kl4P-+3-Kl zS5QO=`3j1tb72Dgdxa+QP#q#!DkkmzR3v_o87RanZ%k)!K>Wh@<`cyGS^2IP-*)2r z%md=h89rxwSG?fBS1*r>i=ue#dZ@Tnh1b%47DwNBp1w#NpWp%00I|P`Tl>LcCj>WF za)pDz`D3~Gg+44n5RJpgE+8L=ixVGD%*fYohVn6AbhdN+M&b2PvAl_bn@;~9ZOjdYFPcC=0 zw(*1VRojOfjsKTnH^sq1S--B zDw#_uhW|G~H9-v%paz?CO;FjoWiF>WN@XXOyRzZZ?TQtyl&Dc$sDt@`^ZgxXijLFG zj`Piqvn?INXY)Rj+42>xFSJ{t;n^Hw=*+EQ^($Rf$`%d@T+&}-;qKhKZiuw6;SJHp zgrN%8wd6DW#7S9vwsUM57!qMhcwFQ|4P@AZ#BdT*7fzkxI|Ft*35M)BuHrS z?OhH4nSyVn-2z@(-iL9KrH5rHf8xBFMZWfB>!QRI0C-P1!#rCJ#f!-^k)6M=o%Tg>&ewu1BmH4bBW|Ez4x;S^4Zx;y|o zZad6k#WAe9m3tto_^Dqc^ChQ6vYYR8om6(RE4H}0u{F25BH_z{D2*LN8tRiVENiyA z8{90j_Ab|q#!BUWA(i_He^M$3gQc?Fr2HN(mE5}B_qgC>-bbWwlVx)xfWac0L)UbS zWDjk3{TB|2Zn@Xx)|$o2VS%zyVx^_1F|mHx?7z=7tFf|y*Y&u?{6YAWvdQ8EP>cD^ zr2H3@4Lk9GYqzEoDw`@Ar5h`H#8sleT~Q6JX4MYYw=g`a9tMNC^+9Pc6R1#T1%v_y z(~BM2>FU@>$=Jrk+E~}G;nENEqiisImXY2Y1_Dm|(-{sad`!ZT9T_AxB(O7{RY8%9J$!H`5UsrlCn zU+Wk=j=_4@x^9WGG=Sr40}5FD9@q6z?@5|q5v!k;R-_%1MJ!8qkAiQ2069ZT56f~t zj+zIWG*8ZD_x#HRFMK`js@DE1p|dk#Zu3J#A#nPB1Wg=JY^kj32^bYhoKy$&o1S!` zE_j;b#CUf!yQ@vwC@qQfi<{scr6$CQ(;PAQD^7ESh9!<)p18wZ5azSR!C8h)vz!`f z%D7pmZ^ZJ5DW9!7=I+cYCb}cip{;oWvoC+*fBHWpV~fKuHVt^Q4zV|hSWbTB65keP zXY>h{e~gDW`_sABo)PHnVo!{<{st9UIeUxmZ2{3QciV${iT zB5jB?;pP_Ssjgdk7JFkxK_i!1)NHgmD2|_NEKaN9WYC$TKcS0z0Cj7hb@>$SYEsN6 zkIly#yW|K0G=irN@W7F?8?7ix({2dRX70X`KCE`X>soD#wF@NDt{JImybyiNA7jON zn3wBaud^QeaVi4h`?Axg#)5fbde{Dlgb~fEPxa}Gy&X8>8PiR1;*9|!E|@`<->f>>)^lkcZ4vP>GWcg|BI7|) z)WgLqvEgXOn~;)TKB+~Ui>YOXE}exY(|vBDOUFNx$Ic&g?ND>$g+rHH7yBw$RM=?X zj~#d^#;J`ZobnYKzQK!3o_=svt~wb$UipK01sRJZG}D^F2BGL`!g1LbD0Lua!3ZLa7X$&S9}cCpyk zTpBy|j%!nxngFU>a;v+I76wm#>qf8ak_0ii)_*c1UV)=R;IOu|>Rep(&8lB@>FoHH zQ!Uu{?=@EQa~Y7Gx}oxXgnBNXRkm}dYUhZ2r42YanbZb;6#_>a_#f!?cRiO4xz;^X za}$R69L%mr>D)-apHP>dfWd_dsJLmV|BV+Bz<*wa-QEv6y1NPC=Kbty&Srn;x>>z6 zfo)&vZmUfqBT2`)kw^*jwNBF*q=Opg1uEbG}aj5kH#ydP2ZigE!^ayssb~mdDn8<#H>|Qy#pa*g;_W1?#(-o%xbGNGUCwvvt1~bawErXhJXZCp4j#g$X&R2|*pY zrK4EcPpi|6Dau#|cwr4Ed!j5*Bn^SkQ;E+|OvuMWN=F zvv9KRoP;hcC`qHy{>tAOG&ERkS?bS^CPQ>F)=3?jl=I3nDQ6g7y7QEU30i&(03s6)k8We?kiy=)g%R zF_Z&Rj!wa-o*9e_S20DX*rPNulS(Ky9z8t%S3 zR8GRBxYtC@=lz8c{4>%bS%mha&Uc8nMCQl}KUqyNsO=^01#D}qJAy5@xvRAr37sS* zLg4h>>@brOFNL`stS-!*tKDhsJU!_`{em(RwWJ?rCLVE!%)}1-6`6_9umXk)nTflA zBFs#XrowP%I093jnVEpLrpqIknZev9V zxd;9|DJQGWaN}2bV=pcR7(Ek`0%K}laIaJ5v#OTv_F5GY14hyIX0q2_XT`KmHb8N}agZh0$rmJ)UV0EisIiv$63x}R|R26Ac{4*OHwmp67efKoElXHCwYC5Rqjhq+>W$N7$7h2WiB#}0# z-Et|W4UVh-N)ma3e-i>wf-h4EzAYpeP3H)Z{oU^+X0dg5pX$WgcL;#P9JVN#%%EC>vsC!0QieA*}p7@ay>Su67e?Wv?j zrVGkiiF83Fsl^SdGWHMM-A;q~;jKjI?`;+EhH{j<*m}d= zMZL8Zd#jf_g&j5Aaq8Mu!UG!4!P9|IK=5G(fE4&8#nJE#fMY9fjL!Eq{)Eo=Hg?A2 zZb!W1;|`GkSmSj+R%%g@nE+_2+?Ta=w_wc*+;?iv5aLnIPs##6@ii9(-O(QIIf)^l z`wq4W_^Ulw#^>&EcDARxwTQMzd*QU!5;Y~Fzl!ntaZWWxTVJBiCZ-+aB~(q1OU76r z+!6u%DN=<2``+Nr-^msv+)5-c{lenx;3?|xWWT1H^C#4F^W@+#3$=@Z`rcNo>TCC% z>`)x+O@3eOo)J>>jo-eg11|=yZpq@rn64`-JY5#}d8lbT76w?ZXU^~4GZI4p_T?rM zT{rLVZZFhKnxdMOBv#emeVIclxId>76=@iF;le|K?OE-$4@PLa$=C5xDP45>mT zCkJ;PDO*q_6PSJhaXwJVSMV-4oagZ;RPwyPP;zoITwvkeB$PaGh4l&+8kellwIHg*0T=3c7ZDFKtD?B--K%kChxn3RPIOv*l$Y$j!&AuV9ZH8+=^ zgp-Pa0Pdw^k(H(EuE@#)G|b9|;Lf)RFhN#US&GI0lkzp??vBbQLjU{9-O=i&$zo34 z#7Urbu$<6@b22ILOOM0Htn7bzV^rc#{0Wu#lTe~{Qa&)Ja9APvAYKWbBtSyo^m$Uu1jw`F+yk}#)_&8IF4QF`_c4+5!`#QX z6p{NFg}()?_T7qB4%x`hGN2F4FOd5f2*hCSgP;}5NPJ3QwKsDg(AJz_R`VzRr$6^G zFhy7y@Mg8Lmb@Tz?&DTjMROmwLovyH+$md;+{fk=Idqi!*@4U4x`sqy>SG{NCO0be z;n!)lax1qP%p1g|J;_O+L+55f6Q0RfQQ?kMw0)!)rcd~y@{v}J@$3UsXu*iYd4d0M zo$>PmhpY(AfbaDbas2a#^yEhFGS72eohgwA^ghN zuxzILJGfw`*DT0yq^C-Q!ssPAm6$?%=A7+zMG;c~S*@Saxiu@h(cOhTHoH-=i(er~ zXolio_4D1ynuAaxW0&r{lp0HXst5vOfKE6*pbip$!y(=3Dz}%_zGsV6>~&>x-EEby zE1&ks!yV?9}+zE|HZlGOrY8gXF_iShY4C@n*^QnCE!3%lBtDGlwKS3BfaH;U=)h7~Fykmv}(i0^l>3x3Aov$TNglcNk|H?DE#h8F;e8rb2P3MmneAw*3W^rNBoKD1`)+Lp5hZGTsx0tRUvp8=eZ1B^H!%cs--7gjhuVYvZylU) z#)Ao@sqj!Irb{)YpmU0ej+;5b7zb~FC%?|ltatZMTfnQRt|m+7WH2l;9$QEiABgFf z1$Vw(wjjZ?&UpD+mG`n)b`^-+hkuE6^sdw%hK8UJoi-a(A~8m z^hkUUsJ1CNTZ7@_i_@oy=jPwo~{M zYC9z(IK3sc{c<`_Z%u`l;oQ4I&B*sZ0KsP7Hg|8$MX1F=nkx(ZRMb4tMB6C30&++X zZg(%%`b+2}{ZW!3Cf`w{7AIe*;OP%#I-7DI%)v8AJ*>rM@?&ZS@oy?KMDm0B?U?*f zO4#M!fs;F_~5Hk6+?H~nynF^fciCcMF)a*9?gqqzZG)vMUFl%Evgv7uBKoEt?10jzF z!0irz+uZ=1JP;DjYIe9;!<5z!b0M885Az_&!9dZf& z7O>NcrnhoP;C^laePFSHbjVLY45mW}S~2}RFU`zMhd^6%=FvHF{--}3@{?&~z?;>` z>Lmqy1~Ok#!J{Ark^`C!=?ldq9nxR666ug_?~m&SuO-VwVp*mbOGp%^Lx7qeBHfL- zc+RiS2*zvaRy|2CI*no_PX+C-9r@h zUzx1;ESOaPO_;<0=VfXGZ)b{aaElGVL663~?Fh8orXI)?hdK@rv@)pqoR?C2cpeM| zUXWFv1)_M)<7fFdhAdBI^0;jkf6XwO6&-Nj5|-@rXFgKl$-fdKXGu5m6lSnBWvVCJ+K7j~-r1d5m=m9;1Lf&f@_2cYsH};|v z&<*T3CxtK>-yLAXJinnVX665aWY=|s6c|9JDLX}SV{Ne12}E(AgA@d;vIz$|a1d;L z`Rf)e=s?Fdr^s@^ugr4z4|IGQ_6l$z4sRSJ{Ge`MqPjgCO1EIO{h0H0IOQ~N@7ED* zZQDj=IxM7TsP#_qc0xU&N2>ZWUP@KH&s6O*U?G9GKhBcAIJq_Q97hmoKTBNPjFh^% zJ#WE_+$y~L#NYB@=iY==v-!$5ym%<*{mxl9GNS322f5?H4d=HIL^bl@Mi70;@D3J# zc_uka4pS+*Uc8iw4o;2WOpuTz(i`QZ8;`0IZVwiAsqBH{s1A?I!V5d*O5xMU9?gBA8fbGKj^ZD+iC`%`i?{FN2BOP}T^3bu~ zBntvVs0n-heqlzk)h_oG?GXuGoa@+;W#&7cAvGW;GvBcTq{#Cf2T3iu+)%Mdhj)OW ze_--NtpxHNAsF#J1SZ4t9qY2B3$22;@cc1%j`{_Bs^yeBnH@3Q@#>dZ!fSqr!>9Va zjUdEi2PyCijN`#%$1l7wy3J?#6S~c3;hH?_yB!{wD0#92j&^|CcEY`|)S|7XpYK2= zWWEmPJMunpZ_(mgOPQh0qh*1gg{GYEu%HWP$9urWe+U#lXX}6`iibQph(MS$6`p8B zYpE>-vSebDEP^QLSl`Lm3E*w8sEa#Rq75WN_!c zvIPl*6A4Ve)Hq9c2H-N@1raRtNhv>ql8p^6AoUWCh8Bv zTJl3*I72i1Tla0+HIf^V{8%Up{CqU!u!jZb+{6&jeK%6YyMFMW_#jP%;^&7}{5_mt zRQ!Wn@t3CE$P1{tuaqoFb&I^mZc>Hnt_tqFOSYiuCNTYC;*6lWU*=s<-LLQ`RQD@? zq3)`>LqEc*7HU?``Uwtt9G4^r9epSZ{K%Vf&;xY@u46ddBI3SA`%ywC>5d;-i@Eob zY+%XE6ye+p6?obsHrqVy5l>pkghzBXS*+8tLj-B~4jw?m(;gvM^nDMQ_BDY%cC> zI~{G?aPkXpLDR2zie6^9M}*&H^#;G70x!RKoxc!?FIkS@FD>C4ckl8id~<3Bf4Kr* zMe*_@b$BAPmOtT1za)PC1`mTR{)9=6b$lsC?;wI(1THu8`4i4R@A0P(TeIpFuF>rDozBh?TtUFiDYi$^t2D-C zh&ox%PEOX%OSv}6QvSr}^cr8|(~>ag zq*4jjr>T3*F&CSf7H6x6@mYCfMK4yrL+>2_0B?)q!Mx03C+pf=@6!;${0%FbvHP0q zMQnHTm{wsQKtGms=8Hs@5uvx#j#^Q=8GaJ%J%U&LESrA@3@+&TG%kwew$KY&HpC62 zRkzG?+6jBv?Bp)ju!II}9|UmlIjjtm>=2^%K_51yGAD;^jMQg0A{@?Iqi1ctLCS;T&G=!N!0k_ch?@plEQZ-LMWzAID(Tpf3H zWr<1p<65ok%V&iVwr4=ElM9pEYtNCIxPJQO%2R}^SK6@cuX%JEv|&G-N$=XW9u0le`9vAGMN);rl!+6W34ki$OpM_>#{kUT(hRQzrVIj%l5mNUg-2Ieo+1 zh@JYpH2s<=O9K(Po=($$h)Qc47y&T)@p`H@vWUfX(mQT`GQ6{z))xJX(pIvPPhmJk zZ@dV`w>(q7R_iW-GcYJ|MU^82N}rc4bLvC10l^(k-=h>Hh3wGQ{}G=LQli;4S^5!e z66wtOWG9w3>#UB4JE-}GzDL6^|5Q)WGG`xcVaTRcvMGM62fm{-M!O|s)75Ro2WYlf zYe%V2fuGQ+O)7C}4_j+HGX4P?Y%<%66d{`Bm&PvAUI=cA#6NGMIb^LJr9uUK;wF*R zMn<;Pj#+C>G`tB#^Lqz0dBrI)KNFI0&C?cC_j;-_tpkl%R927m$UmQ?E>KUY%G|dO|do_Wt-H_#`32& z>#fbV)|i@~B>VGE!(PDd&gAOrZG*s?y7o_V+Nr7Wg*Qu0Xe+|(6KnJ~ZD)CX7-U0x zGuFC`qvn75_k0Gm6^^!-H=&D;gNVNRW<8Hp6!t09wiD9Pk*PiA%(3kP&f;zxo~=Df zs`%py!5?Fbbvti_TRfbP6V=g9cC$-w)PX;-R249%TaQ+^w-ft3|K{*1 zEB6qpVEs%Kv+p5NinH%g-~wmgk4O!2@d4%H3&BMsZzQ;29~ydYQx+6Xei)}mOxlDp zF=?lt<;X6;Qa0PO-?dn4(H@$ZF0I1!QhPWrz`TUFt@xtS%I>j(6VXOl~vDeQFrZCFKMb z#d_~|4rH-cHH%S=_U6}r+M8ehA<(ME=}D||x~-)~>A}*n-g<(ilHU?u~N3q}2 z5PNKio}KoW$cLBcdBMorvppqx=ddR^-a{XxwAY>@cwyagvqRf^<*83lm#kcfw zCFA(_kG)I8MOE5#IBCH0p9o9-Yg+pEg|DDd$%qM{uijNX+FrP19}!B#$e~1h(NF?m z{q;6~jkRxo-LMm^I3nO?S$<_*dVBGinUwbCr>#zONM!>C=uc}g9pq?`My_=bMy`=s zF!JY=_N@0HJzMKY%8~rG9f(1@;14ipYCe+(>%-Kn4#JQDI(}4!LYIczpmg>SeSt=Z`g}XxEThF@L}peAEYl%mJ<}Z3n4E0pCxV z+1pUS>(=RA)NQ7K0S5}0;*bJvPnM#5xjRp}i|QC+^;^F%E=T>{wK{IglC6$JPXFs^PGOQnNf>^!|l zjZ~9h2AK#OTH&xz@arLM?Zx$wWN`%#K5uE9lV$$lyrVAq52vC;&5^`FtunTmllA=5 z*)zRREGt@X#q!>5 zlWp4ou5`faBah)9{1m}_y(t|kX7J?gqn)hiYCnT{erhF`gT zol^}_a>1P);d;Cq^;iZi!`UO#^%~m=VE@2k_!#Ubg#AF&tR4g7CPfxw?6V^#OCO3E!ei#i<*#U=)s9h!y68dc4QSZ_4f9ol0@PEB>c%ssQ>eR zN3lWsPDfTgpnER6yIHEv);^IE#X9|*(npK$Bu64otZXWZYsTt(^lO5XN$8B}gvgb5 zSg}tpQQzt)j`QdFs+uvUZ&Wk(zE6M0*1eOBm0ve3f!%R7r6v1jmL3U~CME9aBqgr& zW9#SYF3SY|=3ISz<84w<%TD||zXh8-Q}1ARNr{*;9m`9oO!G{(y0F@L`aW%r?7;%b zsf4}3nwTYesa-nZorcO=Tqux>fwY104BK9*4^ivDLiyhJ<6u{O?>oe}@a+Xf!neiQ zuT}buQI-ZGTkx+d^{Lw9gd_~m*Yz9GW0))qqy)A!eUyo@bJ;a|1S?yhZ_-|sXfQ1y z!u3~xYaXt@fWNTuJ7`2JhivI5$akO*Xj9L|>iLvPEv_fK=!A0zEW z5Vx~aAc$-0#NZ9XxYN8L?vLcx>lsHlfFb}xJ6}$X73Hy#7g*#GJ0;~R+r6D(GWj(*OS_+T2qZnX1#zhCW(TTumz^-!mX$wH&;{PL z<{WCb6EHBiOO;JQbgmS1sxkQMVas0~t7%lHct)7m7d3U_!DlvebrfP zzOCo2@k-2l+KFQm>MDJ0sb$;?G1P2r@=*R#Q*!{FKQ`uxJ)Wm4{Zq=oPy9u|HiX6A zq%$pqKhOW^w#hgKD7jwqh&T`Ih$T_2s z(}8ow0G4vIJ|r!c7tlH4cPR!wM?9|$C!_}^{`B8?Gum&cY(_`;G+E5hqAPd-TJ&!) ztoR2Z`3Pr)HMk(k!Mz|y4DJO4fE?WGKq5SXxQ*1Jk9}*7Tu0TrpcNn319&SlIfEg@ znj8_M0TLY96p0+!4N7rjlTtFW)v6rf5LW=*+##L>pqJ^>w08-GD1gJfz#;(rBIfBF z@kPuZNqgkz2g=d85F8b4f}rRd!BOHDvU|XMK+qL$^&ANIc%#dHSW<}J!0gxs2=WgH zo+@g`3oI1kH!zF3h;Lw)koHJn?=D2P zJ?*rJTe2D2d%6hP+jR*@7h@6r<;x^$dXjR;u6{Cppte}z5TV7kD7YagbQiYuxSm$` z^cH=eqTbYn?OE$7zfjBLck2Ta$yf;p8^$WmcUw7LobR^rC!FuLb;0>AkB= z$+iXnL)wnKY!QIII{2r&B{tY*I zpsbFAeFFXqoIBtp@#`l}T`F{yKNsLM8oqTOTPv$J2DE{m$_TKaArVVDh zuDc?e)n9oUw_U^8$M@-3>PKD37t@Y(k)P613C$?8@q!L5`{wt$ynveX82Bs~9Fl&6dU~a2R2S?u(D$t#BGOQ;kvVj~#kz zD{vSF!x9>_Y|+)Sg&u-yAM_Dh=!rY^nT?1Z_UtxF*}0vteQt#=w$D3%m72}g)#~Bu zpsuX=zT)IkYbzo78yhcqj=rw^5xu`^zl=(A%6-PL^hp89DPl6A$a$dO!!{4t=U*7J zS6X_MCBR z*i={ixb9KZXS=e(L0~ldD4QqefXO{gOiuk5{K2=suRD{Pih5&@{8Jy?II}>KGL(O^ zJD$`B*#Buk%&qlkuy*!>iSU;x9s}C>j`zMgeXjin+K+2B;g;Zj-^zY?kopn$o8P02 zAE*F9;A!gHx{8SM)~+I=450$wEnP)K`OjzcE21n7L_|6JS^d>0BUg@TvHxuEO^R4m zKVzh7Tm75zp&A?IQ^?RyEuWo0y8N zASnb5z7e^Q+uUD@qhG@a38^edVMHd z&U)Y#*e+{xKp$pb+n~|S?5zVZ@7+x+*0lTg`t!5~p~H8F zxIA8`6$lu*aKP&PT*h~?6GNI^t~fG&>X6>eHVuq-*c(fncG^;eG+lB^rW)F5A@#l(H01>Ix8dC`yc4V_7SuKogfLinE+jyk2^PxA*3lt z2!ofNO!-JpWB)s%k5(6&2xlFIDQYok%>Bk;aC+n}i?(a`OG1)42CrjN*Iz&{nOjaA*5S7d*QVnVN&M?4No z%YcOLIj(=89)@q8K&W$pCdW?b{cWG*i}zCPp9Mi5rk=<*U8##|VCYJPptE5q;JIFKmo1_7T^XUz$l9V*}3NFtyyh>;b57^-~&%{zS0|WQIsUN zTF9@O3W5*!_y>aJ2Uk*Z`CV(uZ&8ua+x`^oc5&qQ&j6Z+@@w^@{;Ybu8+-Rhy#p&e zO{Dj6u=KvYu=Je2>5;6okD;-=pY+DujW4BlL`d%l6$47|k6`J&C)j%1l-~2L$7<|{ zpCJ()>mozx;)oDFx&AARMLbpu2>o&_pX(mM&i|qxRy^$RSyE`(7Nu?X%+Y8<`Z`kTBx~^-C9vX=Ze0SEvU10VuK0iNyXJ zQeye+qg^mQE5nT@jZgKYDZ7)De;lCA+(EKCM)>(q$}W-Bbo*6fr4caOwc>pONj8Yl zCQ7+;CSXNlpUFubC;a0$}bSnzKoEpi_#u(3q-2oi2DUoB^*tbyL&{7!Zjd~Ri zxN%YnS`<&_XC)v%z0{9nUVie{>|<*2-vP=p-0WzjL#R z$wrp_I}2G{q_KLCNWUh$eqoAqLW=Q`y$x^aABRm9shXvWbR0(k;;cKAW+W=MAvzq& z+Bv#|eHcZ?<);qPNr*dEZ@5ZonZ~HbP5Gvl`>{Bu;k5U&pavNw%np`Oi6CAnWP3V5 zGS0~|nzI2};2nNjFs8`9gaW|4{J0)tV%eYe@Yt{$p^hEcHpppTO z+|6ON4sk#>jAfmSb2RpxlN@JDSZ%hEYNZ#0&If`SUTkWsP)BX~jsL`yevvGut?{_+ zASkYE&*--HR~xYP3T5jZp|}gpB&_0_uVdNsdoPB~zo6q48}=706mfli5zO9xQ=iXq zeQvP-Mtd~b(tj~!_ncLB&Yj&OS$=2ZF(r$g>}<5NXB%XEp+RIC#N@je4NYF@Vw5$- zIF_tC2Ao7^MST_85NbHx4{t>M}H2@R!+dGXlBEY-JkT;xXE&UmNUz$7rp7 zV~9NDP7appbQ8t1y-TqfpP!+{m{Hpp-17(81ouO>Z62pNNU14rP9VPf9^ru!+>UO+ zpKv?6g-2{h|HL;;@%Rm@9g}App&vhhH?F`~8D+5s7I*h}I5^eGNM-f+!8+NshjFVt zn*;T)PN@7$QUZ0TeAcAhkx>HQk)B3{-5}6~^1FFV<@cpksQhjoq5KiFhAUs`#$N6X zV;}lT>H`XQgkZs!&#H@!bOpXgQD}^Aj@jq_Q7r%CuUj@3=V~h1*+L^zt?~$^=X20h z>1h-fDjkywSJPrtdTMabg|rDOy=Yg9NCyRI3R+NEp179xK&7waPpI^Df1&hLk5Kx` zlD|+oBoXek@1(S#z8@qdCK)wN)i&FMO9^w3d*h8CCf8@f?w{}+H< z6UOT{)_Xc-AN1I67pioVv2#(4V6TMJ? zwvoi2&^D617oHIAHEpAIu(7JtG9j3QdsEW}H%2kXhZqN=@;N=`Tw-p*b|*z*6E@!~ zHetJv8k57Ci$qB{D=Rhn*h>ip#!Wpb1Ww;DulYvr)x(W=HbhB@W%$%-*@QTD&2XcO zeL97M`)L(kar|#0{)!L1hK3#3Aj@Y1%Z(H^?u{i5J8dd<$l815D&z>*s&5U)jEDYi zV=*I)!gL_kYJHt3ZMY+bVceax7!9vua8E{?1P=Dvchlnh`wE6>yLbsMEwFWcnPIRO zM;X=j7fHKKRmH>9{a!rwXWvgM*va8VS#TTiWnP-gM$soO?r;{u2-D=13diXpB2xUC3>d@C5dd%I77Dyvdnkmt1m_?=c|RXJuoduREM1 z^WDsA&{=xBJDjfic0#%x9;Bkdh7#E|(~WX#F|x6(q;G(Y{elg32U?DY@so@WI+~;g zl^MohdqM$0BDeKI_NaS$hT&G!EVy9=_VrqYYy%^MWeq9ppGe2PALlSH_ZqXqe5ZiN z_5X`)mk1B$a^dBK;Bw(Dz~#ab%729SH)b3E4Y^R<)1-xBEX(j2F)Z`TInCG~KI7S_ z5kxTNaxsAviREHMfmkj|NsY;D&BdapIh%WhG15MtpuqJaF$7ZIyaEgy;I8i}^Ni6D zGStm8+AAyA@p(o&b!CBY9_MjT)JqsbVdFe~>UY?KznK=}JUuwL=S{Q;ydgf2;n?3w zi}~oW-^ELCjv8Db&S#IPGL|Y&vbU;?Z2MERJ)Z#J)}kp3EZNEz3dB6Mf;aWgz3a|< zGt(te=D~nk3N804V}#vOf@6li*{eLtk-%F-{FRBj3d9t42QMp0qKrw(#o=H3X^KD& znvi{1+dQX#k2=D1q{Dqe%o=$Cra`!W5n(@#cB1CW3 zLpnz=-YS+Ftzo>aSZWMNAIgE#an_My!*K>V*jzRscg$`J)i~BV1ovJ|d-F3nb<6U` zWGa8v(>(oa=^1yuQJhFAF*V==j_`>29*zgCY%hO8E8F`QR@R}1u(FvejGIGR+4W7d zvgIp{Ls732?#=o59a1C=>~+(?4w4#^y_$JeTiOHz#flr#v{2*b zD`91ha^3^2Yy^KoD;vQM)EMm&LoNI-nMQWmEfR>7hSEA+;7EA+MK#GKc z&Fv{>uvw%AsK+!^<0)W3!BF<b9mEjMuzebd+0U@({AD@sKH!LaiYPT=wM8@*V1B~lBNgue3Ukk`2h;hln#&# zbd@^(#e1OI5Ar8e`@svVeR@wZw@le&tOz-`EN!&fxzLN)qyb~Pvt65wo1;D`30n<$4G_AU`}4!)P9}-7U~ay%J-*Gf9NVy{|7|^q(VIV^RrKz4VaMjEX%;i?Hdco;i#r={7O)>McGGY;F|qX?kwzBubhw-xaVGnX%pQ+7}WuA`}RL*tejUa8OEnS!ROLdtpLY z&91x`wh-3z5&^*i4v^};oMJ#nB}#?#_PV)Z$o8g4nUKTkVgO5hm~av&3Pu$PDiR`X_-Xh2eAMgvb$NC%#P;}!P%j7WCk zLD&_x)CJ-K_3>UJt#NNJmj7eV5_aMthzKZWl5{g7_#Z_QhzJrx_hD5FjWlL|*x0Uy z^~PBGg1|8@pxW?b2JOnYAhkCXfW$E_Sh(x|W%$fwN#~QhvXhS( ztD_7~P{7&XS1;OolOi#GjNW4WbR#t;qfHz?PuNEim}0Pmz~URxTMU*Q&<9yIC)L7W znaQeaVX(~VEe6X74v-F(T#CUzSdz$Dr}?x24x6sQFy_)Ga@ee(#W-x1^Aa33U3&+H zO*%&gd-jjRYeaVfCwu_iMZ4kvx*en(7(fs976WJ|Z)O=lk~VVyZKRN30F~M;C34uT z?=6PS^4{WY+9kd5@}4BhoTT0yIqy*Da^!^W6Bs$&*gbWS5T9IUOj18F$57}lHilz} zD#=d+C|!=BUpXB(hJNEuIEH@vi!lV^uRf+5%();dE|I?a5rCd6pvO*XpY3Q~=!YJ` zpAdQkJNY#18cA>Wmo7Zt?qsfKj9$VC_75CWhtbPa?h2q+`T>7J2c?uxjkrMNaKUzC+xHp2szxDsGuKrp z-^^8pv%LL=D}sv!HqigaU(8K|G-hTzD;*X8o>tEJK)IB%xN1*pHvgGc-L&zfw0f|o z)CSGi@zL=fOZ#fCXIPJ#%EtQ!@X~I^hINZmSg*^XqwJ*;X(2nX(&d2MecWXAN@NW( z2k*vpNvq;*aJDc<6Y0cGmU|L6za4ik`%k?QsgyG1C8IQ5_AoQqq=$*-*tqxu>N> z&_wN(0IYgWqIr+`i?WnIVF)y#Nuo_*_3s#A?2msNkCldkKBw`}*L`AiW3f+o!`X*t zXSJ;B|C%vYwSPu9V0ff!|DE0*ENAk_I5-4WzpSJs>-~$-UOO$@asE57(_6!OsNWUh zbega=47MR!TzUD7>GQ9cGJD=e-*2Fp<;D4|=uM*{;Zxq1t`?savd71@gQZ=18zdnZSRByHVdxU7$m#$d>lrZr%KXh#_FiK!iIy^3rbvQD?x z3JIy}3%sQY&mHkxF262(@!LjYuJQ8gFWOE}7m8!Jw8U?SP54Lwpqe30;O4w*Jg=(L zi^P#z_?1U)>tAgTACUjRIHRs9B9>A^SPxi=a?=I0w7Ccmf1#Gj3zsCZ?~+y+Z2qan zN@$+CvS{gb|3i1+_UmD%nW1j`d4z?XWH@8t5&JqKQ(f-08aXQ?Jj10KWbCavjZ?5^u)r?RMDjB#3qgf3R; zZQb&ECWXN1OD{1G)r6llKGWQ!UsZ;8l$uu}uCXs673)WNM=5!1&v~P#Rz}KCw)4*6 z9q={xoK1T?i7a<+%tUQAX@fv7FJV;!dKr5Gb$UcPt3b4=KJm+Gx@S zftDjsU7JQK5Gqt4)GAVeP29IAgMs8yn^3V zkW(V=DhO?n{3zD)7$-=zCLDdqX&b>Cul^&prA9h%cdWGzkU^%RYuzflr$kNPq?j)mE!o&Xgbzmv7dQ*&y?bpV zy?`<{cXrR@0UoPCw zyos9jb1w1Bu|@WUv2Xt@omGCZqO%s$7x0+tGY=b8dta8n)RUpvNd-ok%cEx*S{5nw zH;-HFO}8}X^LBz{AW{f4qA%Vkkl0Lu@Xvw1ullevi@k7pj>FT_RtyAIAIeN&JFoWU zX#Hh#h8X*p1oj~nK;T4e94YX(MA~S}AlfuRTjAf*_7B^2K$bE#B1c;qjAwCQ{NyfS z*)G8T4gD8o}#BTxY!0nH>WO+-x*GJtgaYOW4?{zrY@g?4Q+5@tj z@rXmcyDvLg;Pq;x14c3#QZLbhNDFR$(?QG4TlB8lJ^~Re5)uz7IS0r{X(1jhkeq<`!TI8+MJ|?J;_#@D@*xT2BL{>mVY44H6f+EB- zpc5G({#Q09QR=C_7l=~-=qo}*m@qCJB1+~`gt$0uuqCV!+C+%hpe13PE$`!9s%7?* zV+}=G=4=*ePvfPS&rF9ElHc1n|Fc<-+6wx?w?3l6+i5+my*jY6HQ~KfFI;5|sm%BW zv3GwK*TJLPI8$%+y?&4i-$#CHTkio{o)yd>R+*F=4i_TB?o_dw)=%Usllw8ex$r7$ zbgjPcuqxx4T>DH`b0+$3uC_(mP6CU2o|@f9 zg9kasTIa^Lg6xm`iF@*o_TwK|aIowio&!o4QwDj`n9|eZ)mrqIAOZ-&`@=+eE;B`g zhX4Ycs}B`<9IRt6_%FPdr@xj;>XGko_Fym14VHdE6Jt9;nA+b;*y-M$4U@)HIR4G62$Mvzh@rx&}k*t1Eat%JyEFUaX`A*W^Ck0qX~6y-`m&&vAQ zhPH^n4$!l}PY*m;>AAF@r&3!@N|Bxgb#425dMX-i9z>AoB~)4na|&iQp#yiKj{w_qj|2@8Z;kzaCVUvIY0vOH^&*0HV>k?lc4#S zq!|ts{BsM6jd4G`oTCdlKY0zpCrg8ZITAV^-pqneGZ{xX=X!v}(LOqZ8; zRN&r($)2GmMhAOmvS*T(K^k$iN(x(F;W4xvQjSULhHAFpN$|l2!6@pzUz-}hx2zI3j_I^@^HIZ=X<>At9U8RZBhl^&*QiwMauQk%pJOvt@dBjPys(Y*gHR;v&$3)LYN2P2atEtl=$WV8Ljd3&$QE|f zKRjjH7E+F@f&^?vtZa}76gSG2{`t?hY7hpBbx$tx7>f3iY=Kdat$vW{5y3-XjPJSI z+nTMt#`B=|9x2^k0{b%cZ0%xCnnqg((PVBWKKIu&K_pk6)_@TrA>1PpA^UHH2wc5n zKQkJo{V-&Y8caj>_`#Al^bumsgs2$;6djd!vNZ{+pbL0Qh1?q2M~jXNUPqhsyU zY|w?B`AB`*_5nPse@#tR>j#UFmHCerodwI?!lehRK6DycAv2RRj3PCui18*yj08)mD?%<@Z6P zyNYeQ&y!|fCCdw0^{GCkw!4Se*vadZ_S#liB?EC~3)^$QC&d2x!$a`&lv2g^JmJY{ zDect|`~V_W{bfWDM$F-ySZ#wOz{oBcwgb>8%NLoYy%-Yr{tMuKL*TZ-Qp%Kb!?Rn$ zvH)Vh#VLTEl|R=lHHz{J2@&URCtNQRmZyDcMTh~rx@w5{Xa(uS-ue+%MEpW#P-$Y_ zH9NS=ON*yG37G~=tNuaYb1StpLzq){!Z`!l8BKiWP6z^HhDyT^-Fee4&)9~YbN0`T zU|Ej}x5NolpO5=S!dQ zJlwD|PO0iJY51WrpLo_Y%F>w|k2(#s1fQ8ymeqmv)T&y00tXEzdzdhsY*}GuBw;dY zul5)wJ}lWwRukjtKI{UDTX@lx}dWJL&hR@Wj;879n! zbRy={p!Co3sCbQ*;zZ(n(Nm-?BH+=6Xfx1cV%^afJrfm6Z(KT8|4qjv=6uDo*3u8L ze)NiGskY^BJL42UX+bSIL0G6oJ_mHIt3BxHrfBs97^?C)Qf1vGrn z>~S?bwiQ2|uG%D!8z(IC2VoZ!A+?JR zR&2s9fXd<U>wk;E(rBvFcMHZ6_&9@gv<0vK(8w!r!Jg_E8^ibjjk2)v(qF4IQ+ zP46U@*JEK^6zS{_E{A{SaceV3cb;&uU_k@?^D|E`ODQhfvp$FYrK?G2TzLr=!7-Wv zEk!f<)?x;A1Lu@qr)qZ-U}yn%3>S0K9kRl-fIWT-cwAPIN$If*S-?Jv1(3;lvakTa zhzl>pNKN2vD>`8U&^lx&H=R_4DP88 zD8o6R;Xe0hw(Tbmu1akEd^q1-cuje3ru5$@`0XGd6v#oa`B$_kYsf|I*peJ=4nZG^ zizHUBv}oC|GdiwI{9CkS2x$>IruH>|zP+4bK-vJGd~_saqczBoega+x?naKH*@5aU;f zsLw;~^?Hd?CXNsQrFeuOtUMrjKA`)u<+o1JG+sz3b=Up!hv#FPmQEVu5rX7$F=Hgl ziUvmr^2^O51TNVqFn9D;$}g~Z^eRX8)T%-3I^ENStR7Q^%_Ot%Fz>e-L5 zLx;pG4+TWAk7oXw!|Jb9BG|<4o;dZga(+f2l{E|Z7HHFC7nBM=D4f)RYwn%OiZ-b&)D0@ZX@UXpMkFHIubuwxI1bNt@iImd0S}h8TlL_792m)@m(ANXdd!O35a{ z908s7!>#K0a&aaH44B`1#)rP#swVkTPOZ6BO}CB60K={7+A6JGqL-6_d)3|f6Yf=a zhr1?1?^S=9;9VYKubS;{>HSU{Vdco&t1gwL{#F@3OiPu8NseNJUfBy z2QIWJ5|0?_c*Hpbc3;H^^N91_B<~4r5$T7!gjbCayM(Jq1@00;1#Y}<$%(*g+}~F|UxkI2i8Db|tM4Zl{q#Mm~F5F)QIA%X-JYPXXH2yvrH?J3Sf~RS0U1x7WI@r5)FL{VG6S0@f3J=`ZtS%+TI~W#R z-jlwT^IWdCk*AyCn;hmqjn+~KSbn-$?0DvoQk(=k^8!rQn=g3Mez@aVIEwCg_9Xzg zYpWKI5{HzFNdyRYG+~@5z3Rl>~0tv!DpZPkEB8Qa!0R+lD z&ue9KaY*@UlfbJ<1rRtfkq3mJXJ>IU`6t`SL?i+`h?8nlSnd+1B4VE9&VzYEv&6joXcxA=_|hXpBj0{gY~f zIFlSdS`H9Az7Wl7i@p7{Xi^R#&}OX-Dd2H~8V$JkE+cKp6`Cg5OBPE%p++1KE+Mdx zG2G)TIdyym@ol+4lQ+JwSSagiK!d{S~jTQC{cIX-o8w zCiFm%vg1R%A853I$7#y_LINA41f)wwwFr7PT{1fR67@-!OdSKo=#ts^6S`!!F&A>l z`VIHa3gME~{WRPgrf6v#f}G7wpRAQE^^e$^#ZC0dYF|iy-aeLn^z-Z} z)^!BD|It|@la84q1PQ)Qb#IRFW+_@R>47V5uQ9^i7)~m1#f1uV4knQbzSt_gm@>{g zRP7G++#~x3sYi%cnh;l#3WNw12=O*jfe_&+u?Z0!vR$MeJ3cfZGQozAmFh;YP=V~UBozquCj<)@{8n7< zO%g{1yO1^rwc}VJ_8z1Hp+W^h9YiV+YDZQ*(>oNPuB-4))25PY1bCSVu#!|DK&U`~ zOGyO+ybJ-FdNjRJMj9d54JOzJNCkq03IzK&sX(wB{B#2M|Il71)d=vQ3GgVXK!8wz zTKbAqAi#rGI?-`d#z|!$*gs6LF{A>)LIu!iI*#e27GeM4Cl(B_2i}Gla`1rt@z>!Sxb#lE39g6c_un17K+G=a zNanKMbK#Yva>4;j#c(F^qD(G}BYja?DS?fCp`wz<+f zN~@90f&rR`Byaj#fOQ9}yg7rPGSbiV zgK0l>$PbO94*9zT0D7^9#|el0FsYCZ`In^B-yEG@+8mu;$$;sf{>K#HYZ64TM)0M< z=Hsb9ZXX{oS>cbj7%%8+K`PK6&maYyH2AJw>|$?*MjHlEX1?6lY`n0Q3sSboRsuxf z8N|N9Sc=%`YrQ4J08Nj#rvRE55-2KJyfK(W6eQ&VIx2spLk z1SqD2w?ZFyDNx%=D$oP}Cn-P=oVVm2IBm&wNX$G{czy)G@W9_Du#lC?Xn|dQAT!6WX36i<(2WPa2m*xZ?E8sW&_hj#^ z^RCtiUbH(ht(y(K60YuUGM@($IWCjD{VcoMPMpOoc(A@1zn zjNQK(ULkpd{kqxf(%zI!gdB0B>$MBX@d&8rCyxuh%$ae!w~)}6CFpyy0pVuFUP^c( zOS{8+o$Xh@$o_eUcZ~KYp#+)uU5M;=QjQ{nTcMU}v6o6SLy`U70CQ_W(l1ubeed#K zY0J6PRMy*ff%x(XEL;(~Udo1VfY-gdk_sH%eMkYvs&r-B@3Bms=9%42m!h83>p+nF zWisc3(J5rao7yC%#4z2i0~7oe*ft<$o^FRhg|S`UfhAg`Ty(f)nxP%_hsY3s$Gq32zr$y9bZN}254~W7Q`WLs z2j5AU(BI4T^-V-*rfcRWO?I70YMj zwlxY77)iL6z_Uw}TABd&`fK0BTPolwvKon$IozJ9EZ%3p=N=}Dt1x)8Mv$5NsrV;d zq%<)@8Y*Jax)1PzMI8t7^35?VO&|)s>-foryy!quOWyj~_;&0=!6{1T9B*G9Z@k*} zzA6>Jgoi8~|Bsi&>uX(xi2hjLAigv3P7v?(T>RU;yDMoldcw8ppM^Qi{cR~oyo?wNSS&qjq2-1c+#R4{ocLqK?9>0!N zQ{_TjcAoWNU?raanqCQ>_Br)Jd~IDDiawGcGU9FzMCm8uR|G|=4jqW@oq&}?Q&sMc z2vQdUQIrQFBS3dYREp284KK7Tp>b3JD$zP_gAlr=mZUr&RzhxL{CrmT=K+pokt3huH?K0gc$3_aog zB46oHUR=_#1J8UlKF=Qk07c>J^X^sE7W1sv;v2HXgo-=8%zZ-kivp^H1(GcJ&Kgj0 zE%9OP1=lk1B9k@;%hnf_SK&w2)ejVG8!s~fTh5o6;CHV&bN~zs&K)`wzil1K6aO38 z$aD+-*U%Kvgxx0ep$o`-dMz^q)uUal$ot*NrG5Jz++F|FUpNQX!neN~U!`o#Tk#f6 z4;?0lIJB(&JMqmm$gDi{ZhS1W4s#kR$06>@?_6-?bUlVRc^JNB25;O?JR9HVpAWL6 zj00ui{OVint5pXo92@5i;iFFR4f)#l;%l&uggPAh2SouL`gW3B9QxM4qWFsS>~rx? zvI(TA@LVCxz3DjDrl=utSf(@tq=p(2EXoZHsV;u^3a6v!&=59EKHK%o`w;#S0A75~ zV&~H@#xG@06S}fLgl8!8G?S(GQ>xTCVH8)40#xO}AI7J!R}=;gcysD_L797cn6aV# z>xc2f*(an)`|lvQ{6KKtotHlkU-CH*k{J%WZ!vQ%@FwzHOFLHX4*tC>xY(-<_l{M5 zBJapNONZdx*Pt7fb~+(nXClowC_=1$0MM_t4B*>7jjtLkn#hb(!XVJg+DC=^pxTFK6mf#s=`54;cCBiA(`i0 zj-Sd#sm_HONcF4Z1!eBY;o$8wQv*KgHa6tMMn;GSWn-kG^QQ z%mSB?iqq#3umX~yVf@JLSuyM}QVY%CgM%Ta?xL;O^M=bi{k{gLQT5CC2iZwi$N~EE z27-^rXb}I!gf1+vr$Jghr(#BjmE*V;WjDg7+)x+&NG* zz*p6$@zy`Y_xR`YQBQ4#kRwKLwIa5Oe(5ChFrf@%T%2JZC#5j&Kj;Vg>IB0O4lmQs zX2)H7hqH})M>8f0G2b$BxVVZrj!*tEK9_yq4tqY0F>M5UM1mgJ`^sYQM|X8BN}q%2e-4}L-k zKgMeTk^J<%_y*MpW`iA4BJ9Rsr#|%TWT!2E;`jLRY%-w>gGA&h*Wd}xC_6buo}zyV ztj4c))uT-dvy3hH#RLX9%lF0E8p&C8F)YSN!Dj%v^o|ZuBW0w%b0ud4zrh(PA)JkM z<*fIgkl;B%=u(`O8Jv}oTI38b!=1~Lm*FmuTIA`hFP=V=JW-QhdoMnQaAaKDFOwV* zyaq?4gmCnXlOtjO82E_;()yVZn6eR{PIQ!KuCElRKMme^ZjuwQimlM(r4+ zkEVKzzpR@FnObE-qP}HvW7Z~H4Yr8HqT^J7W5Opo7|gG|QU8AfP5mT(3I8C#Tvszf zCeo|)=}of5PF=gmT;avX^+!LRn-Ti&Tj~J5n_ck&TBbh#^9%UGedwx};ARw#AoC;faA`4O)gjB3fen^{DuT z@zZte&g)T)s0#|5>ruiW3;>@N^SiZt7^D|<-uFuWp?Xx;3@df4a)hf(w zw|}$KsNP-_pm3Xi!CTQJbAS0%`i?+zaB#Jfe;MzH@`eEox9WSc<;&^tSG}Cxu1V!e zJR-vUtmz$x+MOkm5Gy_Xt!y8j@#Ab<d6DTx72Y<=9QqGM z2Mi5q@j8&>Sn`>gKib0e>YJ!_OaWry7kXV3&^h^)Y@T!o*7R_JKiYhl{Ye^t7wW@{ z#+(1?&dA8O&0^@}R;t2v!3@#SsI`vX1#v^?&p1=co%02Jg0z6AMiFM`Z$Xa1*2 z9bq%3^B_K3VsZq7AFks2Srkz5oi!MH+Yq0IjX{QFPH=zgJ=~Pib$0NgFDRmS- z9c5|9=cFfZVoOLf9FJ2QGXi+<2bMN$HLZd{F##;kTb3N_(#T&yFH}@f^-uVAWFX&e zH@^_@5|F{$U$r!1rwBnP@{_(q{sQT8tc71CK0P(jrYq;-eAqRdqDvn-v! z`zt45*zk;)=w4?z4!efQDoiuM+dO>gLlC+@Ob`ks(fQP-0PC-gakphm%?AKAyTXxDx-hpZRgqEg`p&$uaCU;S2}%=HGGlyB8aHav%gD zc?WL?@EiU8bK2h;*6=N%3E5+#-K^m&$=BT9|%W`mXjS| zp+dYn8S?&dT=N_b7h`0E;){$+hBI9hz7elGRWMBr4icDN8dNv$Fz9=XiqPb zSPJnn;0fUO2AdoB;cv7={?bF{#w?MLgMK;3UBGt9yJq19{u$x=@lYiUR7mOASufkCuMt<81RLc7ZfI8f1fqrAC@tvQJ5ALlIg4m<%l_ zyuYEvdx{{c*7*lOdz+6oKc)rpcSnQHRv)A62|YtqKJ{U<)pPqhe2fp3tuxjf?T5DN z0b`_)0|+JP51NYtDrAjkkAvy!FGI#PR;1=I8);P$Itv@e4kScwrK?i{dH4kL3Dc-C zCjQdg`8r?m5^2yBEoe}Bt(Qfvn(%=cbRJ5YdQ%s#A{bC5zHvV7ktR@O)oNp)m$6C zcCEECZ#T_9Gk?wy-*bc<6yGIx@jWd$J7S3M+v(<7{cR}sNq2L$jVGtAA|FSJUS zI>1U(r;YqHb?v5;C@Sv!WQg!PKWaX0YBm5fxP^NDS-c8l-!7)YH=fyKfA!Z zN?XU1^384720|ImX+^%|z1@qv=b9kwLV3rWvR3EO^LhsR9bXoXl@7O%P==yEA_}PJ zR~Q^G6{2s;hc7a3X0MS}72z%P(@rErtfg5k;n>CNkHRj|67y@Oo1nt8HYUfhTLe2w z^SUo-{^~`V`C~wuS6ki)<29E1<#DyIrS^VJ$T>RE(l=zBn*{%DFn2{tunJkKmP zcjYf#vNmLq0^A5@l`c0Sr9zkW$ZXaP6|S z1sg=DL5U9-hyEhOW9dASUt0rfEE1A&6nJ@S5O|v^8P)vNTvO&am^e1WdIo+t1&69T zT@+B&?JfD!GsYR|-%HjY9ut|?Qiy*LTTVJqk}o2qDEZ}vK4*CRd&&?6+1fc;%eMJ;dQ9o}m^sFK3 zxQ%Acej?4A$2DV_yK16C#E8SHk6rASL1c{NpVUFg&)!JV$HAqqoA` z(`LNVA|YNaj`!Q|Gcy!F-g7#{Rq^<3<|sb|tv4OdUw#Ne@uq|vA?c6|Q9vc#NYK|^ zj~Oo)#6xz#f_OM-RT2IeZoNB@DB;1Uu2$CzW-k zv#qgqnm_r3xdnTbR6;%|p0}H1YXv)Uf1@O4$MdAsZb_jFbH&onzod{>#-G?{PIRSL z=*Sg!E}wC7Nrx}yfcdyd&o%M$FG8L#AXmu>{mQ>`eZ+t@a#87h=J=W)GROL(`*+97 zSmZ7dHR^thAd%|+?~<=y#`Auu<}{vp8d5WnPnt7XC&Elc7=YeBS7w9&6&2wrHYSkw zI%2-256R`_FPX#nQ(vTo@kviQ?LZ&wON?Ws7(M641xL(5eC;v+@;w82pQp_o*gzr( z^whK5Wq7~AS>Ie~0>hp$|IAjCW)&j8l?n@$U(7gIkhCi^zXSKb?v|Nbv*!q6)WT!F z#COW87M>cN5+##8AjQhO<`LLY$~x}fQt-)KsgF+*+EAA7yUX&R!R0z;nUYu z(_8SXC(K=V(FyZ<_6_N!LPYzeLP|x8&UyVy=I;FS3(3ittbqRw(SrExmtb$O<^(r$ zXA^vwd%X#sa~#HSDB@d(h1Wc7wy`RNFqCpjQ9!LeV1l$oZGzNT zka9O3^HK79EP=GG5ZT%kDi_&4*CUXJzHYvy!J_{Sb6Yl!AV#&#@g>cNy+||ejCrs> z4l`>4@B6g5J>Cq>~DfVTr;? zW!S1x!hJ8A_Lz-2H^nOrSsPwYxMZn6Snxz{5{C#szcxW!A8jt?N z+<+h1G9-}K`!*T24L&e8=9XLL23lR7bkW?I)t~5Q^5GMGn0(`jo+h97fq8@h-%5=(Sbpv_s&&jR%sh@;6 zzcyFlr+!YZ%x`{^T#f(r2mCYVig_m-f{wUq?!?|DRG}Ar)0ccdlJa#6K__!KuBR}S zhu^8h*Ie_UIgUjV(om{NqJa8>`jg~bUuTk>>;DMsHk}P5%_>B!_e(5rFr?p)!XuR3 zxoOVPOmiohc#)nG&*l?^D8kvkM7Ugv&?Tr}`GYyf56`L1lOShtWqJAp_9SUmA;LOn2rJJJ79J8U`{GA)OHKQbSNqxAjeSgTqP#BplGima z@=E%Td7MA;Iw$3Iju3(J`pI2h?;7%Y%TTVl$1-NJDwCDDRD`_Xd(#(w1EqS)AuiCZ zp}hAW=21NS5A)NeHk0A}WpGLYf9F@{!~)5vJG#ZohO1>VT4*TAr;1BQ$EyD8U%c(p zx6}Cpcl~mArshBm%+gT|emK2`kX}eHQ9wLvxV2*>(jOTs)Ks}e1e&+hLVN&9;CD$y@Et#782L|#_>!dW}dHrBFW@nug z_}2KU$UxrnQ!{)vO@q6t7Tr=WU=xtWM}+ij$+i%xi$_~>d<@ARIV3I?4^#ahKQ!31 zUg(54lM6rSDDRo+_;o8Y!_*T+YA%y!XWG? zrMQo?YYKkL#04C;ecH52X~|Bwft#RL-tYdrC>MCKw_n;ir4u{r4ZNszN^=izzNU_) z3%lY5ukGSdbuF%)E86e4LF+&}KE*{@_19}|m+CQ!s7GVHB!Ew?1W%u3EeNT_vwlvl z&acEOLcy*V@im>-o+FF zw9W36(t^PcSM5m@1=Q^731ZuG@sffT&QC>IuCM{5QH5AtKZQdN&vVHh?spl5yX`D&i$Y1-@o2`&9q5$!N9 zXbux4C9&9&5X;XdfGJ-h)P8 zKnuQ8yOnmI59aQl%G*z~!uu#Sv=G-&q;zG^PW~!_ZkviPFNNf|vt@R&MF;Ru2g~>R zqN)6;C*UC062b_&z5*XSto1TLkg)9U#{ik;O@(c{UMW@vKb&fUBect%mD!S&N2W^S zJln&W^BaA#|AWFjdz_RiJ;k3-qGo^}Hd_{EvFhW;GsG zttv#IjPJ4-Q(Lg>o!SZfEXTZvj2Ev_%ZFV(nbQDd!EFO~{_H-2DLS|`T zVm1ENp-27S!fDG#bca`Q+7e-)PWBfC)N8aN+_iwm!Nn6sZR2~LVq;0u3Xx-uD<&#O z^tvp?@|0=K!?2JTo)XJj-KWG@=tGQ~y@(Odoz}>?5ya1p@Lw6>&9QgVEU|1k5eCZf zkh>h05bhSD9NY4D(k&y{Dbln;#4`BdYR{FXxhdmi!rEtsGQK%B#xXl=lJK^}}@~Zibs~(`0BusTJB1 zn&i%CI8Xrh$8}&*jbDGBF#t|Lh7YjJG35Yj$0w%5urY)+;h^=AzPQSp=IK=61XM3S zCO3WfG}7%)C3eD>#NP5Ev719I_xm9+I0E-oFkZrsm z%aUwrJROc}9;nxxHJz@E3&zTLRWg>>nq-MDT@e%*x!#=!`p$%WLy(q0Z}{fu9{*mR zfEPjS@W7=ds&sUX+I-BMl&gBibotr@{8g__WWAUe$a#+C6<8TOG}_XNJxut)m}atI z#a9k$?sQMHfkPD!{6i&hP~B9|oz72B=~S2H5^`|vSR)FkDvTBMb=PyI%f}rmPG#MvXlm5sV35k zSyLdF8a_j*F!CP4Pe1H)$YW-B4mqsT+VK1la18lWUIp-8V}>038iX+9y@M#AgU|bLq}1YP z$5{U9gC%Ofvka!Q2zAKxVt1zD{Y1g^Lk80uod0z)Eqof7Ilh0HD)hm4|FVZv>hhYg z4ZJ$H?mT;zrHm1OB%Z%a;yJS|nd}lFOgw(n`y*B0cm=4iq+;AwRepAkD1(5n`%fN7aC=Xv$3ZDr& zhA%2b&E)ednJp3DxevfaLKeP|cQx9)AW*cUw|9e^ruwTDD2A%FtZOj{o9SU)ZhtwQ*zj|3Io0~YC1X- z-p0DusuO#a)ZmMf`H@vx>PKgCEw^K5c7fE2_err``~9#H2OT(-6l8Aar=E*y5blMO z+#@r2!(Tc?Xq)({)s_b!IIpwD606^y$*pTZIm&0s$0Lu3{-{IVLJ;6Xt)##qCDAuL zho2etuSXn1qlsTQG;k4iEj%maF*1LwwJh-ZM3~p<`MZEX&j%r%>ob0 zf73LX4I)6;#{k(!H#UaUVDka8xgPh3d~(zaZ@DcV!Ex7XJ%Wz0nbR>AR`1cLPn!`V zMrBW&IAX*G=^~c`ib4}q@FVjctj#BLOT&m30xi{v+Jp}A0^R!jyTM$%S;Y^Q$n~{& zdoI+yS)po1-ku95y*UO%5G`yy>LxrHH_{mwTU71rGFu>;1EO)Q6$FEFt{X@77TM{qrdk*vASD&V2gCNAS~f z@LU-TeHOdzUVl^8>*tKI^+IRvd&bz7$*~2aerSg!TC2%t@316AyeGP(<93|jz-bO2 z%BuS)fYEs_al@>CI?p*cugk(nuQ<7t?6PcU%}6OuZcRl2o!n@TGd=JqY=-_`uOS;mT46{CA86g~GXx&_D4&|2)PdC$t&Ev2 zbC0DBdfCyx|iNw#7e+UlP$ei~q*+BdzDM>IxK|n9kgm zYUXYCT7G1kR5@?h$=)Yav2T2cs{}eLw?vj5*k{Sm*iql`#&f8L5xxyybHFm2y+Xi+ zbVEG4e_7I4USBz`;OaMW7sX3`X0oI+q^B4EwSTI`-5% z<6jGYRL~0rxt(Uo86g711)(x{jUmri>ci=zna^0dMsyP0Qm+wB@SxYYd?Do;8$(Lf z`*4$Kskjb2W)`2?(VXrHjt|7;yMe>Cg`zUcG#BVQ;-pZW58|@ng$!WN=mv8UYklj;-9M6&fbWCDG3kofkNiEQ$gJc`_Z{62^x;2!))Q)+VGUiDdSlx z0e4xbX#IG@S1e6fe*z#EDzkkpRA$SC3K17BRBC%r07&_Wt0_HQu;ZfK0~9_V^cr|~ zpjr4ZqBsUKZ2{?Edl>)XHQ3fzL1=a3-FV%3iNSl~iPSD^GXY0Ot*{&5Tw;e-0y|Mg zqrNTap?FV1cOL^Y<&32ldx5~>q^qzQpCKfp%8Sp~!^+~mPSGprZ_egZ588VY?8b)y zDST4Z#O~q5M>y32+zfi^D*`=w>Z{@xdg`mQ(NlX3;y?rY{oFB|S2<@{;2y-SXTK9> zFrNR9DsZ4K^z(Ba5XD${%r7Z5`ToakIpJO~VK2SsNcU1#v~YDV);ZF>SXF1ry^K4+%>7{Oo{N>a4 z{nIz*93v6Nq6lu0^x%DG_v)c9p2P25OGsr)Ni7;wfhfQcFj5o?dAmyxQjl(j00jE! zf;qgPianC|?PIIO^XB&&&UTXS(419whV^fS(Gac-&G{$+7uZ7;xDoI?Ifu7@&61=; zGxR13!02xi3`t8{QXTK~nfQg1sj1;ai=4!RBBGUD5;UNdeI|aPm3=nHM?AFsvSpsv zc&Nzlc<2N6A0iF3&^xMNh#~Vr{}H9|$=57vSoOKkrDOFXmef_}%8z%{Cl&bd4yaJy zV{T4rG2en;HW47=>mUI<>3di#U?$QF^|_|G()w?LfTi`n_mw3A76doHvRETbqHk*b zKPUm9_46r7=E>}SLIS$wTLO%>>q{Uo;uu2;Fybg0(V8()h>Cn`j$8`$-e(Ks?*yct zFcr)-@gvPso3KTsrEm`L@fKtezWL_m^I@y!$_X`Hv@+I1SvPHF4Lr(qOC*~^dc(Q9 zU6s_1+8$o>2F%-gNhP9s?C($=^@6JPmV{pK~$ug29`=-!{D3W;I&yY2FfB>Q| zQ~er%{S7LUkje;;`mc%bL}BX%47dv z&{BicA}!EP(9$nKtIx#m|8H7EDqBAUgC^bYQO(*IE+>7YSsUrC=gU;~tD-;ZPM;(Q zFqKUT977}c6shcRyC4;nq?`DKO44n6@7BX%0H8a zFGkeoTdG*^XA4L@OhkS7snhrU)0`m?-j~fK9pY5CffT64b+IVLxege@v>(iMADf<< zZ%lJXNh_Rt;6ydEdO34=V!oW=W{L)6hBNJluI^OT8!-6cR7afS@cUR7=i?^Yholnm zT=0SCiWfZaeJrz_-uBOz(;LO*oZi?Tf&>$ey9E;YVVon`@ZG=S`EqhwgXR3ly{KA2 zM39cu84#!(E6n25|NK()T)~g%eG4Sb|VibkqX`5om)0#V@qMfeU=tU~Fyc z|4B>>>S^KUJEd0V8DZ99HiZZVO?iSUa4_I+bn8I5iY-;0%l)K<3+R5*22zb1LJJpQ z0ISbm01~u3#10Vv+)LUg+jnCxkQ!{dPc;=^hm3aRt3)$CbR(^A-U8`PM#E@Gcaqe= z8lhiWz(+K&S|a9&&Z$2cN3dZI(ec*#Z1yFoQqP>Gv_Tr$BF_<(3c>fMqTQ=U>A9y2oK1sgaX{icsI(*Sy(=FXheK?MWZO% z+Kxq%Qgm8ZUkqftevEa1YXiq??pk|(I>Oq9btLTsmwMZLA4_+8{{Q6AI3*C4FFB-? zx^ZYgdT{trtaTzAOlWeB3w*r*2_8)G4!1W)lnaEKDL;ZO$ifF{-q7rbut8i15u z4EBh2IZQAYG!%Wv203)j@r<$Rf1x~w`= zsin#V0Pk2qiF6l0V`_;&lho2j(3eOpUAfQpPg6?{2?z4O+FC2Ki;60)@=MJMWPYgy zArDtYjYR=U)KJPMaLeWr9L5{g-dZi3bmmZq+{Oj&S*9MOQ=F1jr^XU4p@3wW1`u#J z8jLJcKcGQmnV=ai2|fC=6=0Sr%qx9x)y0|~PBg4F2s9b? zh_0a4Lg@-ZNd>xsnhSkQRgnv&E4V4pxVi$iP`U!9I#aHoqbihHW`IUlK%j{$FhO50 zbxVrSMKhG5F|ASdltuSnC@p#*!GhML+8bNh{T8A{NB54>lElh{MNf5j7WqgzJHG@t}hkr`I-RLw>Z$?<(!#a=P4swT=4xN-!{J^!&y8Cook=KAFXQabGp!9YEB`Ii zYL18#Ers$K~Oi_8MRWx=VDaMxs@Y^1}NGWa>-?vEaFi~){{hUS8_Q#MGX!|1< z`LO-GMbh@IqJ^vN4__p0f4J&Q+5S>hC~Y60(e?>6v3;Nz!+?`#bN*=<;E;a}Lp75K z1PI%%Ly2k1ukM170PaqIs!KjX2^2c)auN^vh!*yzpaCuHFYya4>@Qyy z)@_(|xr>Ee7-rqZ>MVwa)VM-bfdgORX8()}6Qv7ASf{c$)j7$LHeD=pr17K{^O8-W zz>y;rza50ag2Xst>xJ6fCW}dqbO33FInvChe4ZeE%44kz(*zYfpBZAVm-StSWFI z^*2(?Tnq`GhgPOCK4n>IPPi8gxn~wjH+)12(>yd5LuFpNJMt$9{NqYQxamq6k?w0N52mUy(_~)-pZR8byUgyMUSNtN!<3TBr8pj;Z@S@ZLmO`jP z$yF~-?Pr$`p>fV`i40Q+ zvEG5A~ zDgnpfK!F>f^?gfaZ~)CPI8Xpae{Gjya8TEU7(>zmSbP&cC7k#(ha(nl5~G7WK?HjL zsp1!U|EWuTc>jS5t*&SFAv#FnpT@$Q1&jaPsUFW*WbMFK61H$2SgHyf=>0vl4^H%{ za4-GlZd@w8e*v%{gYXqgtkK$jzJG}|DPp6bgnIf#iZtoz@xx`uNGTXaAMVE~d!V$Z z5w1Q(x)q+Q?6qaqUK%@1iiH|PoDv1pIn#z{WFL|yXtj9G{(Vu3Mg~&A4YwVK+D+HX zK_nYGH)KDOMrdk3EcM~I?}Apbj-A+k(LzofynUgywSHqMzp%4gD*J|Xg+}t_QfVab zgMJGmIR{^M+S?_GQOd!AzyT1`hSH^D@AR`q)MMLVfJA%!fX9Tx*@> z60O38NgMxZt+fy9D_YZ#wWlg@Agz$|-D{su4dO$JtvTUdFyszfCiO7|Sa8iSRTCMe zF%zd`PdCDm$vkJBwQIyMK_}JGG)1^vD2_XpT3KU{kYcyb!!4jykf7Bb;X60LcW7x7 zu~^hNUt3~r$~F;rp&42U*H#-FH=dK@WBkr4Yv-WJqLDMIKtEi(O#0zs)t~ai$5o;9 z!vKxTMFOq-u>J`2C9=i~Hd_5!F2eAHvgri3S}0yxCKrmIlUiYbAs>qZ90DU@{E3i9 zJm1;8PGHm+Bf~`cbm&v=$IIN;i@%V*aY|5q8-c-(%gB^aWx3K?oDvkcv0e;VE~f-& zCZ+^JtI^+WNvk+`RL47w#+s4nm6HKbSG2-*f)2F8_Tm>>Vf*Ditnl&eZnFYf;p83G zQ7nV-gL6TODsUk6cP_xJz~!CRwJck8F4M=umdjffgYhrsfy2B|kUNMM?6yYgNx-3; zG=AA_jjmPz-O2lP7hXvX=baw2Hi{S|P*CgaL2zRJH+ZhOGe7c2Y8;<3*W8j%+GQ1Q z@u_ctts@OEm9uiW_zGJ+{^V!Y77lQDhtaQD$03stW9nH(kYdpM*Xyb8u!E!&T*z?V z`f(&ykfj~u=k{9jU0@UwuhW)d3+Ui-83@xZF=9L*AW>ieGBZm_!O84P(wCadu8LBe z%myu&li9%o)03aF;5kh{x$OlE;A-QcR}4D@;6pJe*Smdc8wh08*ryYmQl1gPI=z?8oREFVKqcYsJ4{R z*Tx8abKF{AW7`tvh+pX6`>gcp z-^cT^m#u}KQP#>+aPVL(VIBSZC{^Gjjbic@Xlx)AM$l-3)7~RCcf-zSR`*D z)p&w}uS93#85`~41#dv&V5w+e1kR_R;2*xoHVg^+`ho8sGWo84DQH~swuYbkq> zfTI&o;KqjEfK}27Kr?g#3c%mCPdK_Q-tF;ohd}v+lY1unY^{&A~KZ5yYGhqtNyHpi8&=;0gfO*gV*t(7# zRh`T5?eHoYzU{}qavR?Z1-biH$wgK%Fe~G?O`lq0wF~^@r`FVneWF{c=<5j{4B6o8 zxkc;}DOFR`zey=hO_x@wXw9V!hHULVxBk%w*Qh+jM%PR zazGId*N_11yY=Z6)N*WP5>N_)lqN^+5QknP+&&LMrlCf1((PM;cWi`{zF*C*BN~RGsbzUvU$XqL}iN^Z zY3tbMs&nb#bQTqCy{%eiZ@2=)`?pjkKE{cAsvww*o zayWbZVD}=P`v;n-QtF^JO4V`nE3Hw^-T_`Aeja2H#wYKxRAxHCiGDuw9!y3}Nhv1x zjyzmFfM3l>YscEqDsU(!faTerv3j%-q}@_jq8p^vlxJ(Ub`(w|-1`V!;-DKk^CF1V1VkeJQ33dQhvO^jn zI}6<)^>J(X4;Q;NpuHpD1~!6*{(aQw>0`Ic$T*bko2-!of;3$)vqhe&kpBUkoYtF%y!RbH!X0(q!G3WSkp zmHE(MTYY}1O0Jg z^~!5yU_(iF<2l?b&tYXTA+})}8%lc=d6yhoAb1|i6KmVjT>zCEndu4LEzH)+1sce2 z!tZrXGqdHM(5=I5yWF86821D$u48NO0_etO15Y+FetVvDh4I^wc{3Ojg&4kpkHzq< zPd(ca?IOQd4|M!P(gee|3u{IAW{xarpGAu9dOev9&UmqZ*2_TtuYp6Bb^i6ja1=AXz>eUwCG|VG1~GrHZO+zxsy0h6y6*w^a zd(H|MqveCrs`J+U(sIJRV8~4=mWj8vJgL3yfd+0z=f`DF9AoTjKFE)?w{?z45meI1 zti2*z=HlMHKdq9+vPdyb34ISHH)G>SDe7`ou{;1v!SMiWez81RvXHbuhc&<0$9l7{ zSgto86fKF zjEVE;YdHaTqrpgL-U1rL(N}0D>@(D(zfWLb#L-vp^cmZjM2(!pgKnbT)msN_qutdP zztHaLuk&Gd-`j0oZjt4+NUX#UceC|j9Yq(^?%JvX2WEe-lA+xtj7eksy{xq5EJIU}o9a$+EkT5L7x6_e9& z|K&H0?I6Wy{fE~{>wk(=6z}LZMsV)yChGBZ(*Bo;Hm>%+cb&BVy{bE9|L0Vpw10p` z`zO%S{*PorpAI-FN*P#JU%^sK|M7@01Qme;T^@GR>h(R~u0UNMhMoxJDCC4|BMs_R9 zAQJDt%pl-y;x)F;AC{CtD}kL1pV3_a=>a$7h}`A%7h){VfdG3$54ByiMh~?^{6Y`4 z1ElUHdo!Lld%)&pBkqp}Y{l$(LIq}To>2u3q!qFe_ueR59sblH+kSRVVL<1ky(1*m zp5y!QXL$BdTR5*VCoPkG>jtQQxn6p)|Bwp2)dv;o*(cKmrJl-{2@vt@6CxPPB3yw6 z=yf;9zT-#*ddRvwdk9bz6J%=6;z_0I8k*v*!87aS3(a0cnES?h=_j9pF_M0A>j+z8 zZ7@GQ!qzk54Z#rglSc`M;3wObWfi2QX>26H52vi-_^Hj%$wc0MtgQu`Oe*oLa=S^k zR(kFRAJNOB8{{W}28(9KBJ09jcx7_l#0bCQ3>fK1Z6yDGl-1LsyD^s1!$T;EAu;BVDM#&@l1-pl0l8f)*1J zBl&?bw$?7tO2}uVkl!MWl#pNdMe9W`w1SYEhIrD-*Nn6EcR`KO1U59@^+1AsARM@?5%*RZzwbdUi;R|+~TeHEWm7;Z^FIq==(h8pojjNrj zWT%M5{WD6ekTTI<12VKkBs99hYj+Mv& z9a`YbtI!)=Z7acz^}Fzq}=FC;N(kJMB~dp+tTevz*kbVf)_K zu>IjVY{EVXPX-BJmGHoMwqzIV%0NR(rGeHiRoai((LjSsefZ$0(!ViKuQbFh01rha zpwzq*!Hr8@AX!9?p8Z@i#s|deHa-Tka(rr+RV}b}*4ZH1vDi^l<7ueVfKs6vt;;@I zWGmO$cnU9)Fz3Iuw_;OismO(n=d+gD#=Af(W)`_Y2Z>G{x%doTYdS;|eHPj}^5L)c ztl`oJCU_BJiCZ6lF=>SjKk!9ZFv7JlFch$;)CLHc?xfye5kzwI3)nf`Tw?5;f(f|^ z&wyNFD0ksX8*DGWLy2$|o{?oeQ!0byoI=|ijeSet3$9!HYNgz=2KEHLB;~O0IF$WP z3Jk#Z^Seg50Jgu_Z6sq{>7)Uu71zlB|s^roEOIo>^t zUtedt%N`)ju+QL|4H!?@V9Q|llPb3!4SM^i9*e*2*q)aUu3DdPW#DbZ<#1ndA8w@x@#sWjh!TcX^Jk>G62Z8z9fLZ+Jsj+TsXaDi6rd!>2_Ol7b0*6e*Sh_S5|YQ z(sJ~EKr>FWlx8=LG5S3qbwP(A!KIoSWMizzAj^$*G6i$oXeaTyW7UKq|MpIO!USQs zQtKgp;YzK?Mz1Tias10&w*Qj{&M-gp*KXTdHjKy#7kqcd_C46f4 z$hovBEP9jT3%#Kl3?r@FV3YKQ$Iqt?W$g&K$gPBWfVbWx159X!bFc?M-AyvJ)B63i zr&u4-pBs836_#P3&+M4~CL5u^F=sdVgS3WhtSZEuoe7}$%@5K#QE)sJL8vwI)k6(x z0So#UMXiCpF6msPg2KFtl-r-R^YRtSeEwh?`k#`2;6K_92B)Ab#j!BjEt^qfGC-mFagLT^^K3B8%ur`Et|@Lk=}FW6RieT}>#PJssh*H)R| z{yfdf&z`VtU>Asp(8Zlq1rCNPTC^%vPRo#@2xcznKhQ zjXeW_(ndlFn#o)4-INdr^#6xQf%5UrZbz33E(Z#4E^%! zn|(|G7dOiZV6A9DCxFw?SN4Gc5q!ZJTQ#`!1-^fP=_V8&9TOPKZV?0`s>Ac`*Ci6q z8~wjRvpc;jcVHCD(N^{@CV{12PV@Tsqu`Y(cD?2ndBeBX7Nvp6LeLf;EHv2S$pYT+ zJ-rztL_Yrv<^^!}5)a1f9k9D>sa=}`?dobn@t$NSwv}+ zk=2;FMNDFm@Bn>uNZGv)Y#|z3MH=B$rWzSJp5a~RM1BkdP<)OSAyu>cMSo{f)q0p&Q4s!k24X)qSz6!23vd(G0% zY_r)p(y^NqjOpYZltLR``*T|nyGp>__&3160MueL7nO!NG@>wYhGqu9^5&!^>|XZP7)RZ1v$H zAKNNj@tT`F6n#T7@Yd9J-nd!-hV7a5Pg~l;Gk{Nr=`GOaX`fbpa*a-4ygDdO}Vl; zZpb23Uxwc&eMndK`7gHKn!aM2bY%+OaOo5tT^X@0r+mOV(Ut8K=+Tw!62H)u?b_x$ z+=sEiaR2)6|F_}(`|Jb}47#y0Rp4NwqJsQTna8N}C(LN?D>O2`e{UNvIG4~Rkd#AU zJP#`HE<@BvypcAr6tvHSS#B%&WgY88%nR~#7Gdy#+cTiax0 ze-uwE@!WO{;zCqEM#UZ>Soy&PZN2#2J=6oHXuFKb<^tX zVeglapEkU(hJ7NtO~BnaF~GmyE)(OI5PPIYcSWiPN5Wg=Sb}ya-F2hGcyg-R4w>S? z97~h}S2>oZs!--w07~Xq2)N9#D6)(wvB3`Masf;GM{V63IMu%Y}*#$5`ZU-yz-dQqU^tmXn&;o4|$Ju}$o~Beshc)Ge=2U0{a&xu$k_ zN9sX>9<5}#d%FPy0t4^~q(BAW<3uS2;LE{&M24j-BRy6#E!}Cv-pffd3|trQ^bu9A z+bN^UKB5JUz4M_jOtHfcXM`%!EZPBH+|u5d9U|q<@Oz)c;~9QGC%O~iH${Zuw?Ks9 zxA=kK_j@~K_MWTi1 z1ZiU=TDA>H->xz9E;U3Lh%3c1GTfcZ3Od;>8p|M%IGZU*BV@`%7tk4osw`3=#s?GL55g~!xLkKSpW#(~x-p0yyP79Tq_eL7oC znh2r^5e9op1QFf!X}fUs;8~w1iNsF?rtX4x?^sK_{6wWp z=1`1jmo^bu8xC2Uu4U&E?KL$0*Ijb%Rfvtbmo~z=m$);h3W7((xwpn{&^?@cYl>eu z_txC)d+r5w$Mw#(9`;3E=ic=dF!#Q6pM5WDA?TsE2%4w@2OAagA{t=B`4zVuX0b$t zMozM}-Ewm3Ln?4`f(kV`4JEZ|auOh7a*E%rzOUhhkKC@ijdI-J$bus4e6Dkz}SSS%q4_YKx&*r&6lv{d8@8@jh! zL?G~LGJKV|GH)?Cy$L_w)1J&Wkb2Zx)q`eqNk~XF? z*kq1{%bAZU<3Nw5hQQcjjVsdz+Ba(~<$pqU=KvYKKL2how{@|PBcA@%`mBWdAArO~3qpmLGKO*GyBXhym~UrnUXpC1ao`gsE3rt^lsr%f=! zUNX#HqUmouCf&5+*YNEW9^EuCSLcX>UqCngg+PyP`m*?iZu;_LzTGrv7rN;iS@tcS z&se;hZC}EEB^+Ts=_gg-z+bq-KW`orozR{4JbJq(|6zPaJzf-@Fp|}HT&b=I{N@2=u_(pI>0cvbgrxZ3kL-}Pr==RncOSlRTuVDAZ8B4`xJV>0Wt!a5^F5EtUL zLhKN4c;UB1=RhCu$dUG_M15z0<74(Yp-woSP$dk*mwocMJhyu97f9*p ze>~3nO|vJkyQCd*_1oWZRe6s$u57h)J+S@!I6v~cy*~Sy^bdn%oLcn&F9%k|mD1>u z8Bek%dq8N0V6^LSB(^mvz{7$~_TW+J5RZOhxi;M{H;nNssL-$Q?4E$PB%AqTQ)`)S zfJVK$8N54)$UF3h3fjdaVrJRy$P1%E<&;6qt<9Wes zd!g5;)X$d{(Xdy~vsdS*=Ge>F3L;H(ol8`Kg8_f?yn7?5gPafrnAu?YA) zJ*IGO&9`T;=iLFHaR;o!?=G-E#Ll|`>hJE6A?{^Tfgvtbs1WyiQmaB-0U|=&ji6ED zz>61I)`)t0*-dGFby%*VgMsU$Bb<_(99*kSRT4aBKg+HNm8fV}F z_jaKK0XN^g*JU+V&4k5K7rFh`DF|WDY{-z5w9yqSP0!U5d?N``au&N`FUk9qRG!%BN58 zsrgAATt+B!kEM-%<_UaqCHz&@mBX-e3--v!{nQgOa)0Ux8Mz;NLPqX{e$vL+eyzE1 zXsxo_>+RoaEO@U{XpD4~1nbBwdiAoTQZN_R+&82VOg82KDP#D*UPvFu%%p{oGEq6> zfJYau?IwO+Ys{zagG5kKmG*(5iV&mwhI=uaQa1l&`g%x&lFsq){s>Zl8u}pr&lY=2 z7eMFKMMyE8b?dK)e_^ZrRW_S+hwHUNU3)gw7V`_+?2Xt`Qt8xdZK2@C>S=*R{OEQ! z3oPGmkEyLVG-v>v{Lbn0I2Yu|+!F*LGB=yw+hLCjB2+>gaVkD6jXh65QBkjs8_aa* z`HH1yeI8w6ufqSk(;n)ALs{;-d!^;RM|x2lzU_m891H@&_DMN}5hTKa5jhx;A&3y8NeqR6bPR5k@)&>( zg@C%7qF|&m7YvoDNv*n)nrGM5P{dpWPmK5rzGFYEHOCUl++1Wm=@@7e%nQyvVE;** z!SfEDip{u-dZhwVZ60^pYN3>ctc!iwmod$G-z=6MTdj+gCuRLXcg}tacm*LWJF^s+RXMu^~T{GE-q+Y~0@cONz z9z&^@S9Tk~ZV{k6)8TN#J{chWmy~0GbbTMc)~d6eRokx=U&ThER>VetJ9~6|I6v}n z`Un>53OYcK+AlkAM=G#$sKCy9_E8GCRztQt(Qh_}~ zMe$n+-2zEDb{zawAJwr4=fb>~R`g%6`HAV8k;*L^Pb+ zL1c#E+|V!06WKP38rI$B3Q~aDa@oC^bbs`u{YiF+6yT&%_@cdq{@i{(^>uqQ_B^Qt zkCUT60|Khq(c&30ys{s^RUfoLv~Vu8uU$)T7;;b)(S`OQUh`#p2N%>BDtQ1>YB6#> z|L^o?HFlX$h4J9Iw_sEE8(J#f^}4)YUIzC7KQFGK{^kX|)~oiXz4ZQty&VfYpcGk5 zccS;Xufd)-?cFIr_|{$C>vs6o9chK~i-2uLukwpK;7fkBl~{~JCV&#&08a1cg4<1k z1}K#vc*Jdb$^n^oQ=J;&C56O<%;7if|6v0N14`6GX{orvJAh}u4S_m^h9IE{$M+Q` zdqTH+$DZf{jgQXld8SPB;z9R2hG`JUm6 zq$hmO@Pz|1qTYW%M$}Inz=)br`r$o8YgzA$_Gu;-c#x>7$k?c{Hl7@;d{7;2f^*{O zU$F+HjT*T|q!eSk2E6ba6<^O9e3g-Q$k)?8_&V*KFXC66e3^K!Dj6+Z5Gz7ICI}T{A7`|6ftNn8 zYDPEHP2l@%)eI}UMH&h(s9pC#>8}UT3A&iZy>IOCUWXvBL$?@i`@-ImpXku7h6@cy zGkW=;L&O#goe^&#kV(m4zPF%BCiqTW%3vYRNz14Q4HX}Mhx6bfpl?I^b=nKR`z>y! zp{cat*KgQkJONQh(nxay`h}bJ)-KRsDEIMpJrW2hu`DtLUxFm2b*(aZ@AM-a{CbUaq{jSRS}J&d%^UAcq%2Pxystvu ziCP%=nqgZm&RA%5`RSkS={k5%+|*NYG+<3&XyTF#=FRoPMDtv|aGXT_*CCoWk2x&! z=CPz5&LdHWeS{3H4tw}3F_G9pa}{Lh|RQ{`Al+qpP&TQnSJZ4Am^7J``9GpCJf7Y~nBN%}CY$!eNN;V8BFN2<}AEx$o|u z_P${xoOUdpjDTEywP=H&9T#yW;ukLBN)CHXnvdf{??E#0;Sp*S#aHP{?(6n6dyT+;A|tn8Y+WYryx#~ih&9|P0)Xq8?-YPq#Qjd7V0F_) zFI*-UT0zT|u-F_baG@1KDm<$=tx$BTwZR-XP%F7uZ}2X9t>uzH5~)A}P=N&6kO~h0 z(M&88wT+Tc)KD!t%#W(GH!PFyK;H*7$c0x_up>?zz&ivxo`~2W#H9~12FBR)N;;;oair9BO-jfca#s zkkbhym0KCN|?dg6>`Zz+o;g|s}*v|@eOH)N1TbFF4i37 z6yp)n2G;Ut>HxR$rC@2KNNLWvf!Qi@iU zv_jD;tqfpKwO9JslMt6?=^H$8}4C%fn_9e5%{uC8gMdvw6itFcJz4!@$}ap-5Y!EqA4i^DZPhUSw-2 zF3&Pz3oQjXw6#1W$%|bpj9$G`270-oK8bHx)q<51E)?e+i{3Oa2nhDHT<&bq%*X+n;_d#)9)m9PK1+Fpf?o1!yA9JiCclcv=X~$<`CVi|<=} z_)oTB=W6Kdk5F$qgj<*5j}ZQs18^h006A_6@gr#V$~+m%&dYPhvL(_T@mgt~obJeqSSj$*SoUo~2xD2?ychndGJXgc zGWp63$9=`JZq*f+ZxJdG{1{5z8kY8(#%hsbd_h-J6wt7fHpJNIg^_9V^n_1kY^1=g zQ;-xK=!E7^dp0dyXC|Qo?};-t*ig~~X0A+94sJe)<2IDEPXkO)k9~^oMoX0z%{=jP zu9+!rUKCLFa=yg*itdi4zLeKW%Io}6UK5D&7ylFGcY8W= zd?}xllu!Gmd^`~4pZ+JxXCHS|)l7cxaYu^&ug_%v>Yu4`r3~zDAc7@7lP}-@PyNdu zo|qQxB`Qqx8LS#1iGdGTAipv(Ezt`US0X+gXCFSWldDeA{L`D$vUHYA@WO`=s_|(D zTh1xc7D~zDA&mfGu-681%zj^Ab@@!rqEu9TsbPMGiw8X!bOCwSNX4XeEQc@&-d^4y zU3zlb0F6CQsf%s)s;w2xj{u~-tb399(t(Z=Vcyu}@~Gyg@=oNTIcX_6%OzNG6{4_O zamv)syjLNWc)=1!7SE~fs3U&0;brf%E6v^`cvMLCF)77a{k_ll`WlWnFK}F%D6-b= zlM6qSOOp?C(;f<9J1HU&k8PQo)`%UTr6R7}`I%ggP;eErfB%^b+J7L;upiF`>c^|T z{fO^C6t_{*Ap&812SN!eH56H;1`1j&fXM|3g~xaq&Sl@zQVX@`Q< zUKPMV6XE4NYn(uREiSZt1>@&laMTZ={|rJ;$t9K{K77u9C#_XbpH)Hp+&gIo>qi>m z3Z!=+MhCBwSsXHwV8?pYg0vRI{#7SLuW@wnB5pG-3vwF_LvdS_kGNoU>iQ?Jd<@AI zlrDyUWOs+VyNUd2VWAZfw zImYCDj0{#zOb{4k6lbCOVU=9*fb)M9 zRzyCGtpFKBYI`Y|0H(I#qBa1G@By4m2B!$Z!~OfPAinX#wA3&X@VSFy5i{Z*rTEn# zE(YWc#V-uV8?FwJ-d^;&W0`M6KI;v~3YI2X(<6p$RDqjl&W8^sA}`GgK1(ahPakPl zUWVm;6)ls`4sZb%gs1+eOAjgp0kEGd; zt(GCV0jiYg<%?4t3ECPSG0ib3;xU1jhU6)P5QgM0f136@+e}JDNZ#y0>Mx9KAm}k7 zA2q`fs<8v47$friqJT!^v>`_1mELkp&`++G5xD{{Cfz;-$B6vlnT~E6yG-b)u=x6F z88+P@wJL1-b#(w&{jW7LY+56lS^L99SX^FlW33M^ujX~3|yl3-Pz-I*b6sTS(##zr>RR5N{iRcm+R_2g!huY90f|-h?7XAfTi{ zZ$tb}Au(R`L2B<@8ZSOi(5iUxRVXF#;_C!RczD=<>|e_>*2vkIcCiQ-wXvc>72ff! zqILD>K^r1uRD4>Qe8Q(YWaP_tq&>+O>`42beM*@Sd%RV9E9DMvqvlx&74bz4K5hv_ zj^0RR&hIXTB_oCQgjTR~ZTd1tB8wu8aI%ib z4=`L~^L_dfLq^4>wcl3HmmwpitK@ePf`ZE+0Fxmjg;!ENVuRNKeP(^w4Mf3}SpB6~ z14%0s>&ZZ3jqooP8HygUtn@V{toVGBP*ie>kdeYmMprr7!YQUns~o9p0cnN-z32*q@&&xB1_<7O;nS5Tz|cLHhJw{&)Tp4W;jj}% zxhHBoP6V=z9xI3Z4G5y5#+&&vYW$P5!yda4ND)QW`WT`WH7d?5QorWQsPR{V9HU13 z^o0-j)qD~*R$r?I8HSB@Ndb

fE&nLP8%jQEM?|)B&AMVHR6IgUvzAsQ;ADhi-PX z)j=ZyFv17ZPU0*?%oys|d+}$sINF7gc*GsNiI4^(#=(Mhj2NF0zc6BaW^I6oao1MZ z`(WP?!MAR6e8gTSD!?4>E2_XvH0P5C5HXJb!ZC-vtB}hOao$=PBF@IY$#_`W4+q(^ z*2+k342UQrxrI9&O<{k*v7L_L5wiqZ8p(|#bTE=TUA|2UU;A@f54Mw3!N*l<@{@O) zwPXiKDUNjj<0pPetL_Eg_xWa-d`t7z_mz`xT`9!vg~j*?Krzi zs&LF*5Cte=Q8{B>UMns8^j^ncc8`FIXtBHx_#MlFp&44R55PqjgJ8j7geiCbXJ1&$ zhgE1$&h!UAA)&iBYLss1w=nI!?+?DipJ~m!@rw@u<@*EebUPp` zyZylfE1`V+NTZn0&9LAWp&Z#bVS@#I6n^VS_F@8~Ph~pR6-~rsxLCsQxBp6;&weBL za0R2vz3q()4wS_vL<*%9a#f$()=dQAux zW5ZgE$j{O!My#7IG~Vg7Bg%^~cF%&-jwDu}5Jkh*c>Ebhx)(H>p3?>x1cLAh7mG)D zfuikovVm$Ek3Q!Z=>@1b$g)8r;^boKeZ1gpePfA6b*y|0?sI&Fq7^S_m0qm9-D5$6 zYF=NoPR{G^k#@LNSnzkfuoQ5dZ`p+Qg4pU<0i254qgmAEuai^ze1cz1?LOdh){&`w zFKL5Q`%zLLdQIQEPQIk|!Skiy-qZn|aE#@A>fsX4%kV}D@9LT%dUQv6st%g*4?S8z zd-?Zoeuj6lWLon0R+!mvLa(qM)PWOvsQ85wdgyw;6Z+G<=@odn;xnNKUxn=eaiTR% z0mZ6nk0B&*(jQYaxea@rl)@{= z8vJzSHnIAQ^}K4aGbzALX7P`AW=s^~9y8D)?lCLdx6;U< zW4C?#Q&9u+4 zoQr!)7!^d0^G`|yhml_FNkqUg61f3NaEwHWUpPjhHuxPQ19_V}j+wq=BQc41MT%s%6h%+201|d zu$Y~?K@O03(19Ev$24b*_9nllIXgw93Y64x8W9>eK;F@vy=G@R#WiBM*`RD@ulurO zx46am!IRC4v1x=J#sv{YobRwjq!i>DAcK^ESv0l*>2Z z2Fg-|b$J(0QvQY#&gB{_w^5lK2J}j5>lk0@jbgHuA9T&HTGAP*vDmv^hFvL?T27(2E;fS;zbiP&ULNI@{B(*biSpMvqPkCE}jk0mUDIcQsJni1K$LrKss>oOFHmP0UUT# zg!4as?>>6}zCCkK{zet&4wfvKpz}bYDsc0jbN|$iuuclE^#1KP$-GB9{F}_r_N`Vi zQ~|k(XSdyCd3aEg^zfsjoej0&d|9;fsff0s1@-Wa6$)UoP0+8 zHnn}g`LyulM7GujuLCcU6_cxYfh*Sc*ua68`7v-EALSg^P>B4bFZAcNo!+d76;zc* z0+8zT1=X^r+_d5naSBm2?JYF(zeE!>^Sj~~n)zL6=6*l1*9eq;y>VZ@EY>;2H)I)C z*EyPnZw5rvRLiRZH~stl<`3M^)tr~8?_A5`6ml8N$MWbnXCiAs%JCg->}GPERvM{Q zFKPvdcu`wxvoLv?;`76NcFoPw)Jt!6oBGUnXLW55&yRPui>N7Z({3qCh+!}@zDXOC zcj%fvggr~DFs|ABXXX2dYfvW@tc!z&6WlVUY3!WJCX&+J2v-gM?qliogQjkVW3-Q@ z$Fk|9+A|yIQ#J<(N9Jvo)7&7@%nC>1nmFrJctsST5{k$qAkgLUJ<{uYF@T8xA5c5v z`9JkYudT7wgf)!DR6{GfV{gdc?v=ihZ71z=lbk)Z{rpOjvne}B$|2}#zzc?yPt^BH zQGKsr{|*EgK0CD+5iMAX1_b!I*{O}ZDJ46fWY-7@oS5UY^k8i}@6g=Y%?sM52n#Wl z2cyeUTh!1}(PgkG#pn_Yv+qmI@94F+@ENn4*JQB-9`hfyc&@`=xRS61Uu%>i{RkU^ za-T>|)T?dbMl)9gtEO<_S2V`A%!p=bst~`Tp;hCNE@vzS78f1K@4d3B1RB>~l?6Lw z?G?O5uDu?@a=G@RN`QktE%-P6(+{x;1QiCU$`~y3AG1Yfgt`w*kJH$^{|Y}FXp2i6 zd$o2BV;>W6^y7HR#HXYbr=X9w$QXx$i>@r^!_9w`qpgw*pj&?UV`fMMRV@Ok##SZJ?e39wfl$D~-QjM*h zPj|OUA5^<17D6x5<>T!e~v2Wx4SrT}uN6^d$<=B7J)+zEle*{JTd^ zHURUe4;rP05sUOxf>GlzP7{pbFisc0a2Tg=^E-?O@`B#ZH+;wPrYD?P>`5XZzUJ+t z3fx3thi}sN?ZU=?n$Vd{uaAYKH4=^$!pK<>G`?!Z| zi1Pq@L@+@o%S=_^=KXBNqypD_PyyE`H)o%a3boV|wPL9U z$O}E+MEt@Vw2QvQLVko)Aaba{ j!6$&}jx{(9tVf@~N{aWYjD ztn@mekbiirbDYM86I_C;@~VyHzMlDlH$0x~;&;Y7OH?EX+@_r^TF4_n@e`a^G&YH% zJObNn+E0YlVJ;~}rYG^!6P<<^H0EqFUUeq1B{pb%65I#0p;2WoaFv`|?FSr>{!v~$ z*{NMNXl)Xo^ty9`7jB_Hq6;ex`q~%j>{4`l(^`uEy;3f};Vh!DOO&QK8iZmN(o*rN z`qCGC`6Q>q3*5$vbr0T;gq6tlZU2@Pxgqw#WakSy3)`Va$Koz6JCyTSVWeDrm)k*J zMvVO|eF|Kh6|hZ3*(P>}jI$DFIIr=?r(!&fow<2UdJ;<|&9Up9{D)lln1%(2Hr?F@ zqdRxV;LrlHDZ$z|&|-%?&k@THbEirA%i=3$2QKLHgJ(JGYit6c;Vrs#G;NF}hGTvD zWcC(;Mp@pR6sxXW_SjsRI`cbZV1K*m;lOOKY!$AC6jTCDPp^Jm^*zI?~%xmfZZVH(%`f9&Av z-gUNiL!zn=iOW7ib}CDCLy9*bZb+M!t4LG4ZfSWFYPp<`fH9)n+S5^EhuqTv_Y4U8 z@dYl!S1xjXz|sjP!f--7W2U+!n##8>hL;Li{|)X5UihB#GxjWjvpHQ0;qaYu*Xa}R zSA2^|iD3cs+KI~xtvkQ;Z%ApRO1KCgxH3fDcv}E*R{Zq)&PUh>Hf9J8Ylkasg2zqP zf8ac*ui7b(n<$boQW+E+uV^Oop=Z*7DHUV6y@EQ%a{I(DjOF(2#8}R6zC3Na%$KKq z|2-oFUxH-26A`qxi<GoX1xA-pfpPIVQlUauQ7hu&IlFjnAGkGp;mPz2cGMfRi+<2TevVWi za;QM$*GPp7UB9oCqAA=Wpr3O!J&P6p(q% zy!l3Fb-wwqvsUp=z~R8o*&{hM57lSZ*5wIA4tPu1Ba9S~P7ruIgmx92p>OCWexYyZ z#usjM)+(v)D(SY1hh#YW1n7C!59vMFGekn{`KMI@AqqK}AJgZsiK^b9eyG=Im_~%{Lu(#{4%mTQPfoLQJSR zoD@)r5pTh3S@lCNi595q%isvdVJ=wo@Lu;}a4!fgRA(Z)dJDqQ{Fao^w z)0U5FyHV3{aZ2=;&X-smsRosG(PMW@TW&!rP{~k%N=_pcO39*DD7o}*xt}TkOHup& zkG5=W$hf5>6K~vmgpmR&D&Xx9_Ojp%^*cuVLj8`}%@=KS*8D#k^N{`Uj(a8%5si7e zDj-zBML)i zSNlIX2J3iW4xxw^OA5Ti0>qhNe+X#Q=1uVnwRux&vlMj=L45oaJu?5rqs}%uyF*Ao zHoOME^0l)8e5$X?H;@f4z6bDFcB>MIMR?x#kf-YNb#Son)zjtns4OBA?#~@rw>##n zTVA<7>;2iC-TaMX&Ng0bh`@e!>5Q15*gf!pySwStSUo!*;yN6y_TTZ5xCh@Emm(~{ zyT*q1(j)yc@%(qrvHqFJbTiS>FB2Jm$3&0+jfrWIQdVazDrq~&_=Iuz{%wkOfZsg_ zG1ehl^Kz=WwVK)|>O~3YQ5Md<~$1|M9GA4gdjl+KEAEvkZEvezSURH?k;1x2L+9syf>aYFipy6#IHb23fwv{nXp$b)u0(J)f9k*@AjVjke{6uHTEdMg-iM^tD{Qr zCw_6(40>X35Fb-6qc-bHU{C>%2U5TwsQ@oiUv|YAQ$aCcT?Gzw`RVc*?YtQ9rvMAS z(_X27y;q&X_=;aVp*xY?T7|x0$qp@SvRkNb?~w_Zc3~NY*Sl~x3Jxr~Vv5HUs-Cq}2 ztL+l|r1?P$n+hycpaQYUQ@^=~=iYL*)nPFD2RtwPil6!-`3crypBkXHuBt1$Drujz z65RdJo`BoB$^uW5d}>KN`i|2i4$i7SPrL{wDu~bF`|iM6{23b!f}_4KSpt`sjT!Q=!bKfiFB}D#+^9m`{WBDSL2K{c7i}* z(0$AXb$VdCP=4s^3FUd&d$2F`H#_{beKJVb_A3j*2ooyQ_czOsT2F+jT@%L9P<#!v zvIZxB#BaPn+>c(e*X@&ui6zhnGBGhA#8pL$=dXphT1KoBY|+HT`-D$SOf*Q!*ut7o zHpHciTei0Pr~3u*B{*ohtTkmP65RNDHh@T4DQ(go%)J)>cEnFneAuteL&~R$D(o(6+smf? zBxG1r*>!;(C#^-up#QL+kGlwa<1Ua2)YJEY^i<$iPa@&xc=6ZopGpXLRPJtGL9;8uWw;(%M2&@__W%&;lK?0uuZ17NgKikdIJ;Tlm(Kp2sfH`iI1Y5^9|{K0p?@TPp+o=ZK!9xoD{H%6^7Z1w>bSbGZA1|C;+s@~n`q9o2jIoS zJ7r8|-zns{qSwCWTkE3$7 z2~}X(AUtiv$ljo?Hl^SVQHhky%(!Pq^nH5Btn5@M$PVL~ajvEjhXgt5eb*EEi{o4~ zSmZ%~u&f$35@U}@OFQAb623Xf2)Ji^NSCOa)+dozv^_gW6dZo&&BTs zEfweRn(@mn2qY-9+I-#F7kaDVs_X?VEQA=eC2is%oWS6%X04jskbE~;l1Hbw z+UcMioIQL*`UAS&v)y_sWk+ncR^V2OaFV3~oIMs0aGX69xOM%(+ZLCTkV|6c7P>!3 zuj1rE4Zp#S<{iR_({lT9;Rceg-S~5F){g7M{6yRSuA^2e^``RHH zdw&ZO!;DZ_%?QPDMtEu1Q`Uq~k(bVJHHo+;DA5VwI3bPUc+|*@3w%%-#!cv>pBdOD zHmL65Al~QMjGCrW%viI!C9RS7CjGEkp$nBP0+Ol5OP ztr$|}RC_Bhg{)^6S6V1R<2KRkcD(GPuJ_re1cz{y1cwz|F6U8QT}#+@0%#*<0m4y` zF5scX=?)D(57Z4jjbg}x`Q$M1Am<25bkhpliWg5ECMkkV`+(_K3^@^dJ=<Kl*&mKrBR6Htb zMLgQ-h>A!3FrJ-qM7p1PpdN5Pm6ZE=NVuODhdpO`pGmw=UsvOZ6hVy+gg8PTz0bmK z$*-`tNGZmoXIr(nub8w|mMer!Cs-jIh0{g-+s@A~^Q5b{#uk%0;YjoqM`R3@M=Eel zyX;7Swg37fG7_C6T6iK+bSobnk#6N9g-p4X!>Ula6@W&!LZFpf(H8?QxYsjck!VJv zTPmLNDTPO*Px*~d!D(8xx6b5UJA&IwBirA#wlETeZcEKxbOgWS$?s;gSiwpiRkn@e zT;a5)_7X>BIMye#1#G>n`Cs9qk4nFAw?m7zERlfQShmnNJ}MXR&pYKmGxW0iY)W>Q4yU0*D`ikA(#GY|553$&X5Z9S5TpHmRCrva#{jJIIZ1B zmDBRWefF0}rPIm-70G<%rk7k*VXwofmt4+>F9mMuqCO+U&_zAHIO97O{*|(QjFN`F zmyr|{{Z$bE_`QrqtU9Siw-E_f_4rL0*8fVnjnblp$8DTklF@+IJ38jRydJ1H#7cFA z^QB{4^}M*oMW<6xrP5X)jN_uSBPmde&i0}d7oDI@b??g{kiXNdhojjuq!r%#@^m2i zU-(Mi`$FW$yN&dxzLNL8^d+cZ#n=HZJ;GdP`>$lKGwmyR?F-?&XHfp4k1~pCY&mI* zBU#C7Ddyv^q=$O!6Y*Yb=YNIY22{mi+QelUJ=rk=jz+L)S%#sX`%2u=7RJMuXVhWm z35aJqgMKEEHm-c7wlb6=DuDpiu_B{c1;u}H`Q`*z;2rm6*Yx5ASBpNNUjgnfk_{b1 zKqsgGEM05{Qxu;V+rSGZ!EzB);~(xn5{?m#^AnRH$w!8Y+gFIuhE6K+Yp@t}QccA# zbW%+rW#-RG@#ZK$W2i+(dKc+@FIwRFKq?mmPdLn2(s|%3@iH zg78vx`1mRh)zzQ)nrqpOo3P=e_V8cHU5Y&c1<&>4(eKxMn2FzRZlPCN@-1tsRu1*U za&~XtcZREqo(d`fr_@44QYAg9y{Cr^u)?Y7fHo%xDrV&r$E=^IdSh00JCXXE!9#Lg z6(V{I(sXFIBfN;6J)xw)tvQPg{OB(~`%d-xVT(j7Ik|{ma&nRVM)pgMc!F;oJ$b*Gu6A+IN0`44QfFLQ=Cy_iZ}Oct`FkJr1#ZSca|qA3qM{R)|MSp(Rs1YW9Uktau!L z4j$i#$Gqp^u|PaRUVulqc;t)62Jwh^2_DtNqhJ&~eix6QN5i8~JeH1uN1k|$%Nz^O z&f@XZICu;akN3yJ<74rdHUS&la+Y3w(WNKg@@EmijCB`WqXNuw~6maKaUfMcFf^_D>5vYys0OGa9l^_ ziJ$_5lTk3z_&Yo7>^M;?fs_}d4lZLS2q!c7=DK;<_<>SB5i|Qkf@vZBU z%9j!i-ABD9@h$(kHHlaJ%vIWsa58%}Fs|1nF8%3aGCeR*fYRBYh|VXha&2VqdLx4~ zWN~nX&pbYNwW}AKM=JA- z$c`#|*{-rjElD2vR;uh^ePceGL7F`%l}(j|v`6^iZ7$QJvH1P2rP zA@ECvPtww~Qat2@^_EHw#L9g58CT;VVQf`5j}Pb9j=0+1ht^8)OGn{FR|!H_Xsuj* zQ9ws!F~Nwb2Yn|ktVeU>Kf$EY15%gf@R0Eul4U*umo@d6Ye&$)?}GS{-fgO}Y(ia_ znAYE}s%Mp|a)&+<&c}b}O1ckK_2b#cT`gEYLKju_x?NRINEv!rs=A$NJi_LaRu4*7 z+(XA#SKCgx_QGvV(@wi$*mgo2HMQBUDcFDJHmYbBXsXP}W~F(b)9|jh?C8tI`TG3{ z!F*B0#D6{oJ`JxiKRN4a%GMKJPa}pMY6qL_(^53kc8 zffvh%X+g>D8>vz;ZDDkGe;0hi#FNhVUx2M&trc!D-^TKS1zK{rABx$njt6mLp;npi zxafM5^(5^kBpF?_ZanXjD?{&mT<*jzd&y<6k#?Y=9-ytgn}+fD%dTJ^dD#`urr06h z@Ic~CFISrw-Psa5&_ZvZxL+U-zupF<=O34u@!g~XY#%Nl{79=SYVmd6F?;Q>azQ56 zip)4jB@Q=+`qc|Bxa!I+k_rg;xf0zX83E#8T-EgY$9Y~}qlWzK);J zR)UYc?y9AA;LC5i>atD*0?aUh_t{&dq1K)ozeC(ALO;Fd2~78E@Ve!eE3W**q5;kf z*124uH9W3yrILi!FxJkI zfrHP@3jEOEl9l-2KS1Cd%C!*qO-tZ6Nrg?|MN;7R2!s-N0TFm^D-QB)di=`%6j| z1h&u5eNiHobf&c@0jQvCgo-7by(Emkao5#^kzy&EYe0`;fh2qLp6e8gJE;bdFjg&= zPbg|cuvk)#T^D&HxCB4jRF8zuvNzO>8mtw8@Cc~8PO5c^o_P|D6(t-#bWlwqp|!Uw z_N0`Mkh3JTmxS@(b>np}zC8A+$DHJyUTJD-)HFYO-Z;y~Q6`0WqosJGNx8RW>N8LB z6*pb6Y&HQ=^5s(b7E1Yi2cvbh&uCyvY#8;S23Np<3mj$C((_O9#8F0F_PJkbt0}eZ z9%^@r8x1NvEDQ{XzK0rQuf->-e8{1nxjY)kojA!qFJZ*8Q+~;PN6B53@DOfK)vAc%B;Ijm(O^i6qDRG# zs1zrz0x($@=h0aYwCJ8^@Kwml;jC8JC?PVwSs5*U;hUAwr|^wf$<`u5!YpoE2+A^? z1NdX*jQM_Z983Obf=pg>IxN)a&R3Q)5{)UKO#0`JtA* z?VNc1oP3599qR8Zqn}I|Rl?&>nXU zd$418`&etN z3wRNa0Zj}GH&ix;vKpiv(u_JSC2K?~JT$c^9$m#qVlI0n3I$Ew1Vq3WNUeoeT{DV& z03ykVk0@V8d{a)@BEE_OSVnw91Yz;->*BQ|KRx_%Rem?w2#HuCKd{gBP>cGmKl&l|=?HiWc8>&rfiehgBo(XC-Tq04;T4)lsQP{%e# zF&^IvY;S=baz2F|%+}cJKc)3y95AJ^19qT26ex;MNi~A`$FW8T@11It=R^A&RoMl5 zo9}5GKs+X*G{5cW9m3BhMAT$=?cjfUgO6!vJj=q)DGL<3fs;#}(u@qZYOWPA!uj4b zqb-ZG1IBs*K0MJV$EQrrD$C(l9BX5THW6Cye^%Zz<-gP9@aqA5%i%|$z4?dIDg=4w|{)jUD<1LN24Tro?yp(*ECW9 zn09R>PLXBzlp-g5!vXp9Y^c z>rr?WaDy@j`Pt|C|7e8TGX}U0g zgL_(opqpnG>eUJNR@w^4Aoqlf#XTvJ+{gDF?uYwI-Hin-g|Z>IcYZHBz)32Q`vd)q z){vZD+ygvQcT%Z3;8DVUmSkTW$=f|?v?APFi76n1+!Hd^V%c5-7bW&GnlVyrb%{tT zwh$y`TG8Dp|9;$fp3R~R3bAHbV$C2GC|3Lcqq+X!_xzawMk4!|)S_IjWhU*ERUWDM zKqHw*WgQ0qDkv49V)Y3rA?#1}Wq)d4=#_Jn55fK^i~UoiLiNh;vRD2fm8w^MQ@sKo znC?3eQYAi}VkNAB3bIeASe;@ou{wnm6RD2-N)_H8I;GKhV)8<&xbxE1;z)(3Q?xdG z@BpJJYfCCUQt7SEtKU6!r4<7G65|WvLsL7Aq z2O;fkL&0uG8Zkxc0eU{;VWS$0^Ghg}5=!zAI{U0qoAi@MEZI*)DyyIDC1HH(b4Eu- ziiy?j_URE19F&t_95pNU1GT)cz`N#E~BJP_yjAhny$ zmtS(*DY?U*Zi^pd#FbO_;ikrijWH?*0WEv(`O*(E_x!V8A{Qx<-<3?$OB%HU$Rx7Q zJ~D~yGwcV+9cNT$Wq$NB_bi?Ls4QK3m=7CoG{%8798=G}viu-TkPxv<&|YGto=Gt= z!G6%)9>>>!KmCevnx#?Jzy!f9FP;dmciND0w7`N5W(oe=M57w)unKz>vYmYhgfhTh zR5I9WH5TWihOZg1#Qd!L^xFI=#UivUvFs&b{OoJSR4=B~yPcFDQ7nBS1ZLYBHRS~_ zz&68oFr4$G*7Ye^X~1W*F^a^rIt^%5TAjw$&}}lDJ*(ECVXKAUxDH(-e&ITF&5wc7 z>JugzFZ)}0wwi1#Vh6o-Xl2Crs#4F&bJqPQTTV?fO7Op?z~bk$B0yH2e#mB@`q5f> zUdS<~v+JZCt~?8VSYVe1K{B~Y9dO=Q4>*@jkyiLKgXyS)E_pR@^t$&)&jEzG#f1U@ z)jYXhd(>PbvE%|F1nOk&1>UzzLWm`4pwE8YdY+pqow2s_S z9K3IqD>VPz1;!k`X^ZN z{Q6cUgJxxy;I1V`B^yAc*hfb2%3CWk{=*XEba?DVp)K)<6OVZDXml}%AMD({9Z{vV z+Np9;%&`$Xs`tdYpfw>s`Eo@l1lRJYqmw}{V$5^D&u+C4s}BGtc&vK z4V-!i*UMbw4L2t?3IgW%{uif3^BEr-!`Z6>Ar6wU+;ExJp@s>nRQ$p*^6Uc`Bk{)| zJ$?2Q<9vI66c+wd3i7QmAn%a>!ZKr^#@!w%|{i9t)DPy2pZq6u40Y9_?BdQ$%w z`!u=yiX!4lvJp@9e{$$EcqQ4|i+u6*rj2+(k*677w9@ETb+KqmQ`Ulv`w+xdK77xu ztq*(eY@&P^t5Y%~d{7WQ@U3xXSpKL_js6<@ny`89xLGZ~)GDL6#!iu9=&els>x=T} zgu-hbb@0J^ezj3aV}%5Pz{@x7UG^BeMM@EE;YEHb-+0CsyeD7gVC*L^o5|DxyzJ*j zYcFt{xRwL3v&GMTZd4Dd`4cPvdv>qJV!ScKt^{!gqxw(s3`Wbt760Mn!-Z||N_EWA zB?$*GAm9*2BrUOwJv&)2BDjo6Ob>L=We8tNA}AG*nC9W?$YdG6#DzcP>gi5HGeGO7?pXFW}|=0V2-UWhq(u zo}X}G;yb{;1sy$|&?sm(jLox^pAP2>b{Jj%;Z%VA3k<`nit9low4dgjPpr*$5>|vc zmcOieRVs7)Pj~9$)npSb_t~_=i@diaBYu~fI=1S z&35q)Pb382uTV3G-7Bu&{fRf*3olo^nCxeEWpxQ}xhuda03@!#ZIIRY%5G*o*3u7n z@%^wri-M!NY6(c{?`}(V>05r1o3S_kB+tu4%^w!bpFd!Hr9H#b4;r=EP(lNZU{D}+ zy~I21Fd7#D8-RQJ>r4paEq665#mjyV^Te=C*Mj+nhm1-OLVel*{^DT}asc5Bg`8p+ z^2tlmCi?P@M~uB}A!)Gqa7z0M*$eDe^p0$y_r0XlBKD}mkU^)g#BvG?rBev^GhhW$ zI7I(w74EuSrFzg;V0Y0$@P_IeLLH}PbcjbT-IsGXcwf#TAI92lP5<+f^o8&j{6b%j zCx8xoXZ#Age6}7p>a%K>)sR6OsCqeoBdB*-IRdToh;TlRw=c!}v`c~SR!_eC5N~kO zDF4rG;59LNVDDSSQ$_<;i77d%- zL4^?bUu*!v=>e34mhcBCOH2>HU6Q92{8_@Um*h+4Mdx7q0s-LKsgxFc$@j)`HlMJQ z`?6`R@#m;gF`r}5w)wugT1=Zm`K%v|%GzAM@(07gK2kJz!-1`y4D&-Y`@_q8_-~CO z`1Bu*c5EGKQTT^pT|}`4v@0&6_|jH8XHBuXI#fpgkx+rpn9~tPfH%YderIyWx^N6! z`^|_FkhvEdrw8H!zde?FSuWmJR(?2`7gRUvRhcVL;_Cf|_$B_u4PkKpeC}mF;mOA3 zBR&)r)GTI-0xM3QP{XXsS8lG^B8-%}RW78*)%=X99jk>E`5BtwYQCuWg{%3ZKg-0< zSkVOcOHQ~b_e*A7Hs<J`Z>$)yURQBGc^l~@)_&E|IYcr zcvz44nU6VWhVxG*UM|HuUNIhG^%Y@h2YxuouJ^OFgPT{39OfV`lpQ4hEbSn}R*QB3 zm1qa9)G}pxgRdRsSPyTo0lazvWDhN4aN`={4OBU0cvK3hcZ?Hv#1ss|I3K+=xAl1+`1pyqIDdHCn&6HmP4b2X>A-C$|jT7%cX)mGy zH8dYnrEdB;c@JP{o?UmXJTG+@MrDs*c-1e>N__KcmrKi0IY`lzqtXu(+1bAk@BA`p z;Te_Mi+u4tc(*;-R*4qy;xEKG&-I4z9t;2}EFjb`6FgTltLUA7u^T`Sfe{U0t@tJW zbsGT4iw2M_DyRWGDhlkrIh2&TJ0Lq7$;z98whVyJccGKsDcYkY>=M7w5_Sc&gndEg zr#_aDzoUrRM`LFRC(0B~s!}&6IiKI3DHOb8KF#|*WDa826msnIa6ifpu@_A%hO`<4y95ko zX6S$YB9ivQSu&|djENS;wxj|vLIq;%N-G4$L=Q$duGoU8q31OK63lJJCZI_X;mOGN2?cSH`T)8w@VP_=*s-A=^OOAeFTi zl|7^asXzr%`Ic4)Dr>!|{8HY0oD~uvM0>?TdyiBgTByJi0%h02nXgh;RqrhpxUYC{ z!xvq{_?6_83|5N(A?|8dWfv!q3d9W+cr0LLxEaMvS_`;!Q7aAsxV64ACaE*)NuUsU zHw*dGqymvc1?U4VI0+7}$zGtf0=cNA$jdh9UxGgzn-apGIngbcm#ti+$V0RL^)KyT z|N0kiP}%IlW)KWWIL9KqfK(u1sKAa`N-G3SQ9)@=uVM~iI|vlw-D=@IN-7X9R3P4S zv_jw&6&BvUPr(U|;3zQ9KM54#y&4D1N9{%ByTMfrok8!TVg*i^v;!wqC;jsX0z(DFiTNQVMKpEU-2;l8T1ozz(+Dg2^*H-Hg|}74UZHW&-O@ zKw#2;N`JHqv z4KjVuKy3J8qyf)sY1Xx2!0(tAcbGdgHl3n)yj5?;NrC7cZ91RfGT-t7#J=ocm}A*T zzR)qIndA%oL`O55t+zqz(+hZB^~6eE;I^)`4(U>f@V&^56f;_5M+rvcs#R-q8aqKs zQHG#Ds z-!<+uIwi)doi-E(YY0e*`p*abm)6-rf&x|lwx#;FNrh1Tob8#l^v?=;^sFY)Y&EGw zt>*>O`eu*T&pc|@B;(lna3zpKtrK!yTK}3*Lajps)H-P(wQeg2=R^CMF^rZj_DoLK z2v#wdd4ZwUyFF%(@hVk~wO^IB`ZUh%ZjSb9hrQLThdGdyC+)DSDQ`$Lq9^zVT8fQV zjwlJMul{BntNC9s#P@(>C|E&EsZc(e7q^}S3WhdocodG-8wLJ4~w8eq?p2D0aE1y;|~Qs}&{Y(7DV z{YD{B|0A-@QH+*iyQP2I?n$$kR}<{Axz z;My~0b+5*#zN=p9%Re>5tfsMSf(-T7ANKx>Yh(J83Z=iXmj1?*S{yGg2h!imhO0*S(^F1$_%^594J$&n}2gjQ!Uow*r zK|MIGqb>2jUNnQ@9#~Yt_^%&|3F>+sR)r^vM6<_86VySM>jB1Lzw4fH$QOUvpXwk{ z>Hw$-9U!$Jc(p>p<`)SW6dz!P_-@W%)YNtVJ~!5E?fwlMPt|7e&Ew1#Y!1PJ3)r^; zvAPJvb}wN2mKxZGEK{1eSykQ9X@V(v1`VNVn}Zz6#PXL-Pl?djZbBV(yF==h?I0CO z!Kd5`K0~Te!6yQ7eJQYln@g^NBpMkZ>80g+gcfQU8laJp2GYoE1>wB@tdttQq70om z@$sO_zr$rK37s0VD!(hGi4K50?u*|ttxqia?81nF15VHhdaG+Z{#s&19yKSWHtC2Y zw@3=-g*RcEq?}=FG<6az)>{(N=q)H1Mx?X=dvTk0FV>u5#%rt}!Gpcn8@LqSwl}Hp zcna-#9yJv_`HQ4d^r7~w65MzD$tzr&W;Vg>iOp9yrOZGRyOGfJ>c+W*9Cjl#z-}ZB zWH;Ih!ujgyro&4XRAJN%)5Sg|SW$&OjZe%l>v}Z~$u%?B7k}4oYp(gaR}-Ont*20r zsW*cKynE}uo>(Bizfltl4ZRwyo5wZDVt)|ym>;+<3f%bt{6PsCn#2BB`E8Km1jV_ftupnZHzae{!5X$TLgw-wPwdIk z2_Q1pRumBC67pBhHFxX(aBBo4#|H6w@0c(Dv-bJWzLxgS+HyfVfA<2j*?l2cy~s?u z4+PnK;d|y=|6GD>etwDh<^8mO{C#u&eYDU2=mWENQ8tL!354Ww(bum8U;{{H z^te_Xg2sU<<7IIZNDY{Be=U$DPa&2p?u@ITf?!kn6d=N5wL#Hd)F9e=j4h@_#NM<4 zH@ItC%PL-w=q7rvFl)2VY~Ucp*%fA7DIx_pt3DeKSLac@Qw-Zd;Hl`FSHhZ;G{P(= zFNl9AmL2nMk{KkJ-_&nZqA&cRi!JN1Oa9>JQ>a02Bm$W|f&_6Vw&{T6O+<@j>-jB!Q=b_F8R@^kM`TTPSEl??pH10AC8%#_8oO=c6V6|eHS8B1c=RB1z<|G+(Mz7-w*@ZzRqewPxw%sO+fKJgFU zv0_SP{>3^oU7O6yt~XOzj-8!11FWke z5gS4Hm824dUmA$oIybeZo4kZq)TU2{QQ?nT3BGF+tksV2%bS4YS9X$z0+BrJCRucg z8Cysh9DIN$73F!m0jZ@9#bbigOR<}F9c;*KF#SwCH7GgO(bi1XfeC{LG+=DW!PTeP$Y5TMgYE z!N=SlUV=~CXV%ufj_3zTI!e6SmT1$8W#MmmN3jRNbzyy0>R! z;tRA)INK4)H{OMJ{+AUDkN(Q6$qy$V_?g~%LgF`9(2oQ%lDK>zCN@RFZ>#P=sSnZ27V>7DcTZsvzMYLA2xgI z^>0b<=~1$taEq_q2P`GpSkfEa3gFURZgzx%N%y8p1vlXHkDB$XHcbI+c5&G>; zblKpR)FnY9b$Q?`GeLjmmfQqY^=mVf4JBC69}fz|`AcrjVX#!<(6~5XcgPGODs{_n z3*V~xR@4Qy#5&zF-iMEw@9Xn!@vYA_t;|mxGbghJgc;A2t-pOsF8SUjwdidkD#Jhw z`Od7beafBRnT^;g0)fJ;3?$4Zw=ho~H=B@d$dKLeHeY%iLJmq1qJ$yrD?$Jm%oMyu zmQIPPN+1Jv*agxU2SlZJLLZ)!+ORlx-7|wjo6NGlt)s>SV29nDp?twfvxa`_7H?iA zC6e7HXi&&M0ts1^FFu8)f9#Z5opgs=$XjxiN_gkC=*EKN-W~VzY4csZ&YyBH;Dy7> z&zO-~JU?*8tic-nX&at#eE9cfbKj8(*UCutE}S)E2z%{iAJqMmHyqovDyvKIVYlxO zNh!e}I%CH21?S9%wJv<^IkPS6O2BZoc_aYYK5nwtzc`$T zge^VG?96-=fSG(ZGi!e`yAi=NrM^Gl(U-vHKOpEZGJf$AEK2s1QZ)Pz{^V~THS1L+ z-~kQ)3~8Kq*~?P_8ua=Ejr3HwXJEk3uxH@LpM2iWFu~p=Sg?a3R|aR@KX z7b$`^Uu0FhDv)|2&PsR8!FtU*vYYRI?kK^>=_xH>7sduX#b9xFyhnr{dnZ5~l;q~7 zFes%J;pP$9%Q1I&-BKyBRbv#wfbJzz!H7Vp8n1lMOd`<`;KJ@BxNMQ7{?r|DTB9x- zKv3b_niYuu;cotIVWr|c9+%fi7q%BlTP#b5OdwmeEup*9Z&V*iwz{eZEh zTaY{U*wU()?yc9|52bX~|GFdn_Fs2k^jr_Gq}}1&i>GvAMgOu{ss2|0D=otp7fTTd znE#YWd6aZ!7pc~JckBrmtKzmdH|v8_Uep@!ypWU#-jSuWg{|82SV}9FWM?EH5F@6W zk;5fZQc3?lDj8|WV@svfWeo{FoV!a`NHN)Cq*Tn^T0>s7bV_tp0v*sAvPoMUTkA`E zSwq9WRD`OH;mKuEqS!dn2D^Q9AgLyyR7tpJR(umZGy79`W{1H{Z^gn>#Q&JTSJ@c1 z%zxQU!K$eLm)8($7?Lth`%ox3`L{lG^6ntcnl3HNP=DC0C2)9V(`b)N1qX6;nF1*t@o&SL-egJzo|RB#SWijOdgK zylSNsljy&j)PME6(zRD7XfYVTq`?=JQew0W{!68ldMuMbz;57hzIDWfO1$IbVlDNw zKrB4wVWDJ1N&}L^_fUtI@|BBMVLs#|Q=?1p_aai_v|;>kL`q{ef{@3q84`%-%O0XP ztE43Q71^eIi+ltkDQVgg{%0ig!25Pi76;;Fg@+U9fv$v; z$E5NXSjt~OFiPc%1ljHAlm^-^Ubk9G0^3a>Q2HH#Xdd;@>|8yC=EW3E{Fn*Q^aMmD zIIa_ZzAM)WSM0`$$|qeDL|AEWw>`vL4 z+1Y)z@H54hrhHzSJs2#q45L@n;k8iok8H( z>}YH@-$OFdD!|>X>Ib$~liJuSm#scd;Mgj^iuXNU7R&LxRy{2hZ9}QMZE;*E)~}WE zB?Xq%&2NXE@Hs6+@a1Wtip$;yHbp&oTIg#*UHs`juzCAsd0-Rl*z-h6l>lf*JW?LA zX7G`PmO^%#aF3yP>#^iC^_Q!7#ImY3>;fspu=^9d)Vqpa)l?p?k7;-s)~PgwWXs6F81iwtmPs6c*afL z*b}5e<_@T^ub;*4TcM!8C7ZqIjr(qYOOh|{yzpy#vV-2ZPYi%b5@p(pk>g$!n!(@h z%gRRbnm4DU@K^q4sqkpROJUks9HOv#Fzd+*yF}W?oesZ)&&}$S#C|6Qpv3>Na8+5 zODYg(pO|5Z_nrK(XW6a1j)|bmD~8MpB9b{t-yPCI&wOF1eiDDq1%KZ96597WNrNNP{`(NA?m8 zy8YvJN>M>5gjA5*DZK!3yx&aAP!BY8ljM}yomel@s&EqzG&}@wVf%EG2NWwG&%CJ( zEB)8XV{Wvp_N|QDp@#fx<@aV;w)s}xdJ}B%o&2wrt7cmgeJejO+tQ!S{in*f3zupT zjpsNqo^*b6X31ifo!wV1;QX%E{uLTC!xQP%O}GrU+uUm^_%TheyzQ>ajf`XFqjo@yzU&Xit% zY>GHh*(5|aP@xb7_SY?hr9IbNOT(^xj1vhVGEO9t3aE*eAptbe9{dgxv44&eb{Qu? z&%%$8tk?Ga0zwd7NZ^7Cxmgq{Aiw3o4>v$R^KlJnMvO$vKme#UapuEa4;6M*2vOJt zb~CAfs+xtWVzUSwO-Gz^P?qq+3oWT^87V|{-4{q*Yoxlo^47!a8z+&lqwSoTCDj#1 zNPC#hc0v_(CMt-qLn_FyLjmIOg9ipkvq(9}GZ$I%*&)&-W}o{5333F~=9PW&^)s!- ziDY=tcA-(~;wXd%b?k$gv=7qjH!rp%D9q5v%V;mlp14eSZ0HF?Tq8)J#d(vKq?+gp zC6>=$Y4P*bHMNnyDTG&7XkTD2Yh6KTdvrw(A&OlgDu}Ki6=YX<0km@w6pAv5a}nx* zM!Y(!Zx*|Tw2sFj`UMbaR3qO`39GZ@nf0ioZF!*t@l*r_U}lV`B5ov<(Vr+9#$yV= zzPu#+Qms{aOz&*^sXpYXTd<+#Zj!zgmL^4YjK!Iy2Ro1I^2TrUHf*1Ezprm ztJ}3@+X!u$W!-m@3Bln!h$RE=wRtu8c}_FRg}iB%LSP0fQm@*NgI*k3#EZ_R#MHmN z#@qgsU*3ta)pK^@#)f+4w6~iTve%sqkd$7NW^x|ek<<9_p-n22_ z_Oh)Tod)tJH(GAI!ae6O1zf3KXvCFAAg)~?Oo(YiRD5IbNje+;S$4?Q?{Xs5bB%cM zCzh^!*jE-O&wmisz(?+~82N-pEw8bzqM|lEUi!6Vv6|hOU(?^3&vHot+ICOA{yEXb z9~zCmYwT8du*y5?EFNIB@I$lGgP8QMRJ%5YH7RGj2cIbM|GXvcEch!C!lsw6u&w0qwLiXS6<+tbXE!!;ju_sAOdX##uv5Zpnq!fGdnSYXZ zkDs1|P?gJzp0EV5e6dn}QtL^|EQwkU0VpCWLfu*^h81D_;nuPE@b4zkr7Ae7AgQqcH^*3DhZsO~DFyNO2?Rp)WNY|r0 zqG;9LqO}#Q!DZYKY?RaPUaJT9>#G>92Z0W659z{Y5`nOoskbaHT^4mh6X|&7H0xMC?M=7i%}xHZfWPsE+;O?xu<(GaAB4x?}K z*5TDsJf(^+J!DC*pZbXfPTVdc)#Sa+2SwUKb$^ehmMRcb8?=`m0X0DawtlI-kMh3A zViI}s(!|cnyE3CW*SvLt$xklmI@pMh8do}scmB-s4kHNS>gFTtL&A*sfLC!?2Q++Z z+#7T{c_YuLuqN=Wzr(kLA9M;_d`42gZOV(YEIrttqyWDoK>>V6Dqu}Rbw!Ko1Vs(} zg!C2k_X$g1lOLvCCjsXH`%r#1zGZY>Z%Ze>?Mq7*>`%cP=ST(l4QYQ>Mv0A&3 zxs3_G8oBIYu8Q+8BXAz@r(kxD5~`NmSf z$_QLULDdl&AO;Kwm7`cMQA2(=;+Q~g{-Avj2_*JM)24EnqcBtsXp~!F&*lk&C>1lG z@U1kq-pXbX051Q|6aZZQ1^p{#>+6Q)p&{~^@=Ah>iw;Yr(7qcf*YYLbgFR504}EXx zr7jBPhx42cwve=hraW1cSxX1@8^J`Oeh$==icwDAiB#|fP?^=JO_Hu>?V%JxAExc+ zW*aj+IKXAoL(kt5!mA(a*MY?uLFZbsgbS~vx?FlI{K;bSZJ||l|2C}SzgB*%x_?KH z$~bL4qN)6Csd9CCD2EW$i{mB>4?A&hvM>=RafcS+rK8l+3e!-*2JWpGCVt`GieaF! zmmF=I>35Q!x~hKauj2EYR~*ad=dvIzJ9@!#6T5*3gb{7J4sesLeJSXOHiq}U@3fKc zbT!w)+9I8d3~LLGGOVp81sK+#0K?kjv_OP4D8R6Gr%{GAKb*Vn03467mVC+5$sN{6 z1sT>R8@<9>90_ZO1bqx^pBQ<_UzXwKI|PI}{8Yjs#xfTfjq%JgmLY5{set^h@!{9NtXtW$1P^2M zlAZT4BLQNF-bw&yllXz)Elt*aq!eX+Gk~lg1duf`(WQ5lHgHmsKZaSaV-z5wr1G?v z3fAZ~kwyMsz{N1BOvo;zv@-^XCdnnAx}uxuuNVX$o041;AD4VEGNP+xUC z|2o3@if_dHKGHgmwH5W<)-BS%6dm9uTf65!2$siVtj&3ZaiEb;-rp#KCx4aIH`Wg= zS9hKnV|~jV&j^N$XXa*J@rmATY260O6zEtZ9Mgf>V{i@0Rl`glQKhgfvLjtj0w{N<-HLVxiKLqdOG z81g57Az^bn>n`7ru(iE)Hk(Wog89=#9pENg8{88>t9yGQmHFg;jiVXX_aA908#2GG3QZh6PyITA{EF1S}tH4AWMz zHj@$z3r_?xnw?=XEUXeWWLS{PSjLuDnBai&Zc#SyTQjU}JUMJw#d?=;Cswfl`=(55 zR}XBA8~X$zRm56S6ZZ;s>t@{#*){>=+@o`r^-Xq`K*h8}Jr%~wdsx$a(Kq$54rNL> z5F@h`fsVVVd|Kbw)7qa!d!dI3H1}4qj&mtZO!mS zZ<=Er$$I%gAGNtM-T*{-jWIul|B_=J$V&a7VML}PcxhG(2voC}T$blqe`2FZgJ@yb zg=-cznUtV~O$^7d(7U>?$q$dN`OUosn}yZZ zUhct$RFH#>tNA|+Hg5^~IM^KGH}$pNWS%boG{#OM9AXaI`)Ua2>=OdU56)jUmmi$J zA_W);jt4TjADhdu=8&kNuN9VG`2xMJdiPr4Cm_7YK`FZ!MXrkQlJi5tH{_s6yw%O= z!&sz1(?$Vw)o=m8Py)RGuG$u63E>s|zJb<_ER7)JzPJt%a$j5rQh**>6d^sdgcP8M z_KpbPq2&?MLy5994~@}9(U#+Y9G`!xshLr_ILCy&oS}SPzb;AY*a#l^VRdUZ-kXEb zfjF2ZISBXQ08UQK3Qdgm!-CwOLpi{0c3yxuzIvFo%!ASM;zfn~2wS*D=uwYbIv5E8 z2A#GMxX(;&4T8ZoSN_Nd>kjq|!NMNdqV>oYQh+_OSL>0tNdflA8-euke!w0f>d>~! z16kazM9HE$yZ~|h@@VTYMxiL&Q$#qi>8DkM99hDFIWe*@5DPZ_FlxjYU5{r+vRK`+ z-C<6I5S*GPMS?kFbZsSmVRUU388Es|8E@U=8(nXh0IMF^qCTCPXXyYp+1gkCgXp^D z14}fYG!X)Nl}-VpE8HixWRkU9bwtYGI>EbqOhft7Un*jG#3z+`Y%W0(%bm&`Po$qG zS!)<4NcatCd8Aw{-9!p-u@nm6;FI<|(=)VGte8S6u9ylAA-c!<(UHr}_e{0E?GEPz zLx%J8NUv~Cmq?EYf*8)fjO5lD>$PUPfY5lJNqB-6hcfuIL$`+1U#hWwps>@V3>OxD ziPRPrE|3z8>OVyW2vk=^$*BINsG%<`lm!#j-Cf?4Z@$6WSUn9Y5J8=?i$Ogq%1hW& zgl&AxCRJe2c%Cc(7|-p{Ct5tW@cU+2A7Q--GDeTwC>hUlNr8wS3S2ET*V>WwCvXfN z)lmVoG(1X%bD||JoJZ?IXb%MeRSX`KDh3ZPfEG(B6l3Ylge#1t6azOIQUJ!AUeJlK z%UR8elEL)LTdXg$^`sqC$Ag+W9wY^*j_0I0>Iodx@k}6f?D@Z_LreF8DyoB0MRj-q z;<#l#WTzC0vaRxzt$xOBR*S-ZBD|t-KWf7LNDACzXnRBBXl+k>(`enGP{xqx09_sx zja}Z1b~(ob5qghnDK^l?0}+I_$9C8bgeYu>tx`0V5PZ2C)(a5F6YjPyWE3jD&527| zOGu+=CKPSd0_#MNdZ^0pi7Lgglo=(5rDW)5@m({KXWU~Q%Vv_6F^QTk0B)zl`PdTB zC(g%~5nR;geS!43M(UFheaiXRJ<)PLb{A<1=VP}=OZKKilVa3NjFR)Qw+SNh_a@~J z=VRH6tsk;u1P?T%&Bu-qD9*q@0gY za>JIvsy+o^H+`(h{iZIrzII1LBw$ zC*QWx+Ro$4CqKNRs=`E0sWvn;{jz*PHey)&)L2VHYu1L=tlq7;-*)a(2XiW)2V_&Z z^)WU~)Ybw!=vI5qdyo!wldpX|xEv(om`MYgU;aV>FxFfbBiG@R*IRcP{(>%9`m{NP zT_zRKDKEwZ2;iZy{BYyy9xBwVnLj1R@EiO%-&9Rt@S{O^IYdkj%QB?IY9TE(Rxd^h ztzrXE=%P~?6)`AZP}DP&0=;_zR;^cto-|glL(@8OOaINM09<`1% zVTm+_h6b0N;(L}C6&seFGSn~4Pq!-K7oUHZdaBC|(R2;`bG>UXoCUaLg-bvdUhhiB zzdB%<3!Q%LDL$&MxU*sHDZ}y;-(>T&BMCv6R23JmTIQ2*0_?(y?NaedeVzCxRy>N0 zZ*TV#&vfD&%pZ$i_yFjiaQ*N4Te^4RgPyY9!nhDaa{%m&6|o|PidFyooiCZ&J-N{@ zaQp2je*BH0N&McYt*oQCzDPSNdvdP(sO&3%1S|+#7hab;{trrIyEl<78jD* zB42An&i*MS`3|mp(j>{-9*D>WaWB+pm%w%5osz@hVlTZ<3?|P$QLf^Vg%u`s_$5hW zAY4bL(Rk;XKr~VT31|ph7hWv4&x1yiH;n{IW1mLjb)CkL=K|4KENKW_7hbnE`!6a- zjyH{-lE&=6q#QHgnkP+;?{@^E(FKq|4uR{!OT2#epwZu(Mqf$eXN|@goyMG`_KO{dxQ%hL*gt?ff6U^mCw?;@D^`W^Gnq>)R^S?Dy2wFr z`rBWGC^1&ebbTyC#Hakyw~3{^@_B1)`xU~JwupcBiGRKp|6C=cNf7_^6#w*vfB3e& zLsOcH-~?KLx1$fXb@GePTYIs20s}pFHt)OLX5|@2BaM}}=uq)X3?Q|WuQYQQzdZ67 zED3C{3ggLL&PVdFUDo$1{83nXr4)GI!t?F;yl7i@etA_@YEwYuY@JE-rNc;vY14(tGFeCdpeO66@~f!TF~Lydg*o-5pxpz9=@QR;_hR*d!A z1MB~T9@zSp)l@ewJf?o_Yu4_H`jbf>M}z+w3#>#=X|tuV_(4(+O~y1QW-;?^;{4 zD8j+vp|;AXUIIW31wKm%mhfx{YymiAP3H&ShPhoCsR`aw$sdXC)MjyV zQ+a5dJP8H|h{Acx{noz>)8in++AuAKcR659WitpTsKsgjq{UlNi`|qSyy&2HV$gb= zB=tCn@PK+;;;qMtx@5|Dp~pwrMp8+5Y1C=q2~_#(^-Ah^T^%rqD;CxTd+f`EuV_2$ zzZbvZ4l>wbA4hCnG>UmJG|%@e8j#3~E+(cLJ_RMF7|d=_xUXGJKbUCgbd?-~3Y1;xqdgg}HNl_i-G`Kwg++kdFzna=Y zX4yUtl-UB$sX*6Pd}P0nzu-76G8$Xl@}-kF;zd&m$GZ z*j(%yQVks_zeQyb4x};FUy_0c-cmldmZ&D6C{9r>`Jjc7*MDw(&v0vt5I%H&b~2ks z=%e0l4y3nxq~1b$fT8f3*RoT2#>?eV{DUv7@xdw)?oog2xYfaC5oS<_YrJ(hQ`6ye zO^5qWz(Va-QcZYJ^l#p7_q3*u>8K9~u%MP~zI9o=QJ5AUQh}>z--ErOcu3`U@w?na zjJ&~nev1?5Q%3X4Us;!X3@NRSJM#IbUt3qP-w8XQQf)2b7ai(utoGsH9fW`JhBcC} zI%OTgnzYniU{Ae$Y@8pGuEucH1g=HA{G&C3mnrcP9Dfadv~LvO{UaP6NF>c{+uWzW z+OnlwpNMTK_j&toRxCIyi*SWPZGE9(Cmh?E7;Dr;=g_UK)w3SKz^k3Gd5u%1% zV(24&g>u*T)=V?->FGV^Nh3;I2Rtqy#-D0|re|-Jyt?twpxg)5={y5lbt*{Hqt008 zuyF(+GsQcbF{1!tTy4yYeuR~%+1^;YOPd(g8(PXw2RD$?ZK|zWxsSha*4l|JA@G{v z<>S;^a9wdX%1-a`e--ow?CVqe078f@EoQi=iD5>|vVa7if2mbGqqO$CZ*R> zE1|Tfy|dDQ_~LUh#XtX=qb;A;$kv&?>V+>v>3dIg48Qfz2qXXOC#xCWRr=#6YYO{- zV4@6%0?BYp%AoY&;lEhhMEemzuJKcj`o3J**@MLsjVdbD>s!h--O)fwtm%#bJ&P}) zwDVG)c2t^(`MBK=e1S(kYOON0j0Y9sLPxy#g$o_=@wm{@Y_`D0d#r9T@w4w&Ud!A3 zX5HlL`4PWcA7F*LhMH~zBb znt@SI|4$PDO}E1T>&yPO7Aovs0><&P?3q461pw4)pEK5GYyoK+1Hd{0zyL7veg|U$ zhykED9-e`Kgzhib-;$;NbMoL8lP~VQ{yUxPb!*@sly3gMD03qN*=n)73%AGtp z#MUL|0Z|bnfcC`@NXQ64Y3UK*dqM~!0OE@XK=Jhm@Rt|93Zi&LfG}R%*p|YYC+K~I zA}}~$;x~%5OpsCR&UoJZ7i(&?9~oo_pe$hspa2X3o8x5&co5VjLcl6evW%Y;pcLnar0X8Ip9(L_ zy*=EP!5$#>P85`mi`D;jGYK^`zh4c7K7LPVNWUMKp!Av-JHE6z- zBialMc?N+A0ziTQFZ>~UAbW*C!KL7Id}OK3@HR-J#OJ57cSx~xtUy-zp|nbd4B_U5 z)qHnnM-D$;Z@9Ak&p4|sQ(pm!c;D$MZ;4(c%;5?Q&I*1cP>gC3mBFMnWz2^RUIug- zRD_oSDP~=-V)Cc{mB5wu6-B(-P#BEh9&~Y@NEmTjQSFn#nfl0dTR(aK&yy`|u@Rvw z>#ovHkEDd8tWn#U<=hee$Mu)O!$o2Iu}-!EKE0Ez7Vd+;+{xCCRT2$=myA*Sm@#xk z`6OTi`H9Z9?#+meB=F)*6he@P-K>~$>XhZZe_QUYG5~4cG*EYE;v!==mf;6ex-mb1-4S&yM1#bHx9W54*s>y zfd$RSPbc#aGiku)C_;s#QaIq#K1e+(UHCSutwe?Pr5fwO3L}(|Yk&mrv@JJ<4I;#Z zrj!AqMxf=>F@Cg_QE0o;bs+TFzC5?cmc;rJMuf7WW(ojRR;84sEK#~_LARW{*g{eZ zbF_2aa@w(_6biF6bzvf({Jy=^8+|Z)*b7rx$ZIUNG!Mk$2ZIU)%3Te7Q&XO2vmFlk z0La%J%5B3wB79&sy!TJtaNJKffb(bb5kJ^N`LmATg6Kg$&uKHWgM=mQke>vAcE~$Y zu(z}hxvA8)nl(<+Jr6r%_x*iBc*F;}U0FCS61~zmi64H_mg-R_NM);rBpKL&DXQ%= zH>Mf+v2xqNkV4>sXCBW@WyORa3=#!N0S2uyexkqML2F)xEs{5@vLyr&E(|$IA$)34 zPAY>R4fz?yi(vvlHQrN`u6vU7fvLqgQ&7*DW&*HmpGh`^8dFHTy15ZvXzWzjM z_b@U{L-u_pF|Qq8x4-C0lWfd-Qd`Ll(UfV7cV*sECkqZsR1lhW>hV#wmy{{|q0x|d zPVHQszxZM@hP-xf#?Cc(#)0)AL28%|`eeJEem!(j>p_3C7qI#Bdr zQ->;@AF1N{nwemPhI^Ak_`z{GDQpqp0u{S3kYc$X#iCUnzR}hy813GvY4=XT3TpRp z0ifEwO_OG>rrq#`jRA0~u=oVSZ5AHJ<`44k!@2X!V^OtV6b>Nq8YH(%s z%Rm}C=SO2O56k9XtamVe@`0fISUskx?HG|C)uyI+sqLsH)hC+T=5BIKXC{HAjb}ls zO^N2)?u0=E+9z78TVywK`)#&ehJqB>w)#|u)~t}w6vn3HiHdS!<~x*>!p=QgcaJET zd`D38GPPHVbmU%y5e$7pymgi(MaoQ(etc?1&i!mEsfF`^h_6FJ_|};@9oUVuNI3J< z6zR;gPLR$F123u>cp_@%5nmg^`5y~yCH#$rw#DjWDZKjTiWvUV+PoO{1Yrvm{>VQm z{8?Xxqq%Oq*VZ-|2j7swx2}SZ0UHQ6sP#7mfI9eEDd8GT>k&8S+{2ELS`a;}*_Q-> zUn>BE_q`>j*aJ0KWq;hj3RO04)%tab?IhUzr%P>JS!`?FjWB*jwhk~bwQB7c3o-_%a0M-{J^}%%u#BPs z;k@FmoD_cUjk9g}7u?3dj&Hml)+446>Zm$bAl1$Cqq+wlu#F5tb+FfJ%PPoj#}g({ zbN6^_Zj2__NKJE9NAj|H_0pVP{N*EgDeNKA0Gj6`1c2rV7}7i`YLMosuGYEoQFr^b zw$DR81~#~IEUzQ`lrV&P{xFc9Px{w$K0m(J7Rsls4{BDc9F`hCOxQt<|0)2~Ru5{j zy`yU!mX#BoorT&5vd~oBOr0E+Hseb&^6**>p z=+J31|Lzgn+>jFBgx93!Co?PI36)-y8XzuIruxPO%&T60EV#TXKUD^Ye8LJUe53$S zh39C(^-Pt)q0{|2oXsHBBJXy#A z6692J-ey}P-g2|;PQ%lwuw!vePBPmS24Iyx_E=7D51xgnQ6s%Y?IBn!Q9)ADjdd^C4k)+tgD=5n z%R47tEh4Rg@7h~`F`E&`Zz(&4h@7boj>np*{Q*LP^!_X~+F_dk+w`{OxC}g{_ zjf_IDmU$O@j?@a$2bAp%?GxSc-Fs7veEe&+Uk#r@H=KVtCzfyd+!@P`5z6QWNB&8X z-}<@%WGLCNK@3(hcfVn49ZWR&2pFq=CMScz507XP^{2NE-Zkcw4PENk>4#4rYTZyR9XD{kvM@ZG!LHYx~Bsp)N{ zv859(FlO`<02(vWG(kGHmDYB-Q30-;cjU)+<@DrBcI7N*6G$t;DsHS!k6NDyz>h9D zY*S$0=hF8eD_%lqqW)?F>2H-E{kd(fLl8?{b;D?8~ML*@O#XB{rZqv2c zn@t za&3oKjd{&))^>GopH1LZM}rD`h7+Jf^jY}fsl-O@yiDtFZds8Be4D>Pfuwt zJsk)TJ=VYUv#qrPcViv@1rpyQ=k#yTdQot_{N847T%<-+ zY@#w>^;YI;O_}#=%KX#Vdj|W6R0~#_?`z7upDL5jeWsIiI4@dM8p6|0 z*>deN|I?w8GE* zoYTVazYZas{gRW<1`-~G=_>t2LwUYa+|g2}9-mxZG}@;J;pR#;KhEr(SvBE7s4r@U zxB4n{>C`?Qq@&-wz0VD70jV0KZNdSG1{De-Br2kT)`Nj|SKz9>xe@kaK0M6s-pB$E zA^2C>EhRvsd$%l-w?LhvB2@J7-{Fd7hG+RM)~@ z5)$7LM)VO;Wu2KBe!1NSqiu_h0fwe_9eszUh7p}7N0l|^xBd(piAFZb4LSu?V>-%R zurY)^=$fi1@i$FCBRk5GH@u@TeBNTMA$ME8O%Lz99Iy1iT}@xwXAL zTS8bvA)oaYa*-zFJ=l?5`5LuwD0_=k3o;_9Z|DT57DcXG54moFVmJ$?aU>!)hljUm zh)3#~KsvnW#~;c&*stuBP2Bij*qyvPF~*djV9wsO^L2f z_Ps1cU}+;GeqWf>0=%Omfr{@7YDy=0%RWWNO*CE8U|7lXgC2RZyp>1mdrHgx$11!q zl@xwo7Z}%RyBI3(i_7iFMtETx0F5WN$TfT5>ulF};UnAPN>bWyi0`u4DY!9F0Bf^;zW?5Jz4u9Jt>{=PdYod1@Rn<~F3 zC0;t+oL`r1Ulno@=<}NCFcAGkI6*!B5kQYkI{WGo$02Anj#n?g;twIX_VFv2-%V|D zTQT_2;5DeumYu!S`I9cMa#pA_ofqZXA7@D_S!G(5vGs3WmAKra+3O`T?W8GlF zDcA;F&oo9gs$DwE9j~O4IAK^BHNaax5KoHiCF)sEQ`lN;KM`^d;PQw&%Q~=HLIk^g z!9QuDPWHXu1;xx!1udj`oweB82jNia9i8Rc_8o*b6!9@{5$B_b%B?&y-`=&6t9K3L z9x17?S>Z)e^}NkK9JZlW+wFO5FM(t4Z=DpAp}h7_G9T{D57&D2{@)ABdIr19r@q)3 zPew+&PI`;=yzIGK0f8Jpn>VSWk?-i1i|40W@Gna3FRE%9pZ~nA0}DyhZC-SvdQ}>x zk-mvkIGEw1cqPvH+$>gmRyKzf^idh^QI_NPI{ zHf>6IOFmisK9oOswf#!>@JBR(7jUQbgK=a4(ST4}^iAGsyIPa0Dosuv=Y3Q*n=K;M zf>qo-Iss~cBi|oxIT|_Iq+!MoCYuOl)%v> z_|XvWQDN_SE9^;4p2swWrDvD#X5Wx%!7A*ePJk*5cE!Vi(NBsJrH$;q&mO|R9A;mr zgz-tk?QQt3Aq|G7z!2HZa27;jOP>Ql7z@zTTQ(pT+JcwJ<-K ze678cx}ggnF{8X4+ek`rgu)FQ>;6f?&0TQAhDUxfe`a}`pdKJ|*m za#zzNdjb!iVh`$6-{;^FxT^_%czT4=)ypG}NXb9edU)+Mxwo-cf%M<3g{o0q2) zP$&6&@_{q$9a&GJ1`N!Dy_MHp6E35xj3>iyuuo%CNHx6EEXn%>`*nIXp%b;hES|J3 z7WW;93(eG2I59o8+M%`r_#|sFUlN&QjPrB-f(u#}7XrrfwU^8t4G(vP?fXx(?7%h= z4)9Kh^H~;JYsHrFX9VO225s z&8*0MJHvOt+Nh7h;~4yCa1XSLuyik{`bO*ElV}%R;4YcYHZ?I_dIA8k*N;P?xY`eo z2Rm-F9}6jlcKE!Dxt*Csw5WL?N?({Bz#l5oeTP<@&R)FD-kiUA9lSyEpGcpVu1OC+ z8dyW=M|ex0oz6$ST~)#}@3LR7PSyU{HXp`ax5$M(#~JypciZ1nmh-*~AZc7l8bx`R z29kHJlsE7cZrv1HOTJ~Hz1O>EIIs;p-cuV^_LaO_%Wtw~X+^Q$|Au0BG*?nI_by zQpV^EG-u^g?(SL`OfEoPk>z z9sKBW`!#Hk;6!r+L<*`=U+l4ynWI?X9DAKD2lG zE@kk>8|>>nsADYj!TcRMeyXJx-~FO$Oq}B*h1+~x-(~Qchwa5C(kBgN6EftJZv{dS zyy>jB_=Pu}_0E*9I_Ni@y~y{x* z{YpwPq(W)RC*|b|C`Uxpt>3h>v9NBSGk4x20%vG9(L^CjAO)f}936_>WzXZ&Oid!y zFThm9ldFE@avjq;{>_Gt=g-(v;Xv!IXY8fsV}dE#*KZRp=Z}NrO585RjoWc%f} z2qf+uy#xLiU0ZE04&g~J*zIhiH|jcxs@x&E^JYsWn*Qv1a zf$^KlL34C>zH~KA{_lGtcQ!xxdV@bk`LsNPC%ag8n{!TPWqr?Y<21bcvhwUd=LKdL8CmQ0~ZM@Jel|sd-)dW82eS05o?7^&u zFXGG(?ALoBVvd@z6E+f+W`*z(J99g*GExnug6aI+l<1y{gDZyuuBQ*k;?q_-y76Hj z*^^@4_ZAMs;7e!siuWKa(o?e!Y70UeL(z>CfT74##h3tMBznKQj6~JDa`&psviSO+ z>}}Z!Qb#1%uxY1(ci#_q5AhS9LXsUNDrre}$`O0ETARfWuX31KEop7rta3YhmH=?4 z31BWA>FDTz3F67e)nXUu=x)<=z0Y?awL4)`q2O!zl5)9CVgQZns`e ziZl^@=#{(kLo-WzaP#LdL;YTFonv6rRjP%SQ^1`FRQ6-`iR=Fh7)NY^EY0Y;#@>i%A zddOh(JE?{4^h+RjQhQ2wIv{G$NOZ1;j6~;1Qy7U_^aM=z_#pPY0VYNwirEl})Q^Dj zKxZ+JXy>@n)o17u8+)Jdv9w9~AVW^ikh(7m?JSS*gZWBN0YI&53l+V1rs9whPpm-j z#lP8`m`HnW({c5LhhVE5wQK-s5?xzwQj2eWL2V7LJ)WR@aiAqaV{{Hg)}%sp;o?y~ z?N%ZppEtn~8S9rrKI%_l-yks`!#DrP>f;OldkX6H&vSqjm>uMF&CQsU(rBaN+gn4M5 zS6;}iW}Usr5O>g07E-AmQkDl4H78qUD>^|fTOp`gwnBWcp|8P@F=|!|(ik=SieDHt z`(_8uR=~|LTiF-q*x;M3SX(*F{M{Cg{>(*0!tgg<2e_FC_5lI>kd^%E*(iSSQtoJW zi%x;#BJxeyauNAnQs7=hZhR8}XO8A6o7%Qy;htSUx6ZibV=uKgM*aMx`7FaUw2zJ*FW6Tf{}GWll-BeDWd z$tF1l!`wHom7|k-BAZWW<>;V(34JNnwSjTZz&wT!z;$f`aCZ=hE7!Gu63A#JKZ{>z zB|l3m@m-MUn&R-2$Tn^57{;3A=u)9oG}QraqQNGz>$2dHv9;|S&H0h9Ae;3=!4;n) z2QfpAdk~w|#*qs50IzA|C^g3mp6D3XNM}-HudvUP0B}Juh$PR=ZY;~Bt%{YwQVMVn zdCV@LION6GuWRoJQ`E6Ja>~ z;mhTvxoVC!>J29?*c@(sD#ZRHzDC0HAjx0S2was&9*=3IGG`C?J6A$^6L%G*bqz4^I67dJ<`iG!n6 znthN~68iXwV}DW}Z?;c|Y6m`+w93n1@9ALeJ#IMgVE|-qP8N6ElVV-eZ``7OONw<- zzX~MkPyZKDwQU3Yq^KSoc*(0_`pElH>%2)UJWscCo%0rXS|`PmVx4nSUVu(&lNYFy zqICUh!6lq47KlQW0l|2p4zHXXSIC8`+xTdwqtIL<*ra|sROcHPs`weF<4<-kf$ED+4?tIn74X%h z6h}WEsPi|0mf-p$wjB-q$yl<+C>1k{0*46=tMCahDr5apbU#nIscKW zjr{NQyvA$+VFH(+KFgC!P{&9Cj*p)T0P0gS;Ujr+2h6$-amJ)@MXslk_T0wd`V=mi z7E4gSlO}P5)|=GkeZPPP8kV3!^MN2)NQlzWwI!&=yl)jugmEqjRdJNok+e3?gVn$& zZ3@8Ip%)!a6ETejuEFZirMd|=(51SIU+7ZZ^L+>DZIjC<@;&_=_jvn}gFo2c(U+AI zanO&PI>1e|c4=^abZCI%H8w_XS1uKe$d^k+HKYIsN+?+0x;l@|B?Y)x1O>QQG(;#k zlP6DAQeyqE>l(~6uX7}-mV9@vJ!%1rmbVOYFl8NIILJ|K9xR%sUT7n`hDQTLciNgLMV7!wbX4>mLRDXpJMy16_Cjmc6C> zCy;75;>Yz4knXkZEnWYdAWvOCy0>)wXwnqAejWiJOMr2Wd|((qGZn44=?Y_^ zTm9jhab6&r55%JT z-lR4#&j8^Y2K$8s-HQWlu)hoXK}^S?8oItudo{h~Kp%iB9O#J!HE;}8hy(q0!285ySjh}~{cLl7--x`? z>748d|8=b2qFuDkS@U z;|K<>k3uQ()Rq*ut2S-~K==Bn`0c}!$v;mrfV>7>@A>K4#QWath|@k@Te$0XM?1yJ zm)`D(F@qqUVdV{?16(d80C$Ih_;R_lzhDlnWPtdERx+T_*Ge!Q%(&Ax9n9yiR5=-M zc9+A>rVvTRd(P$h-)_P|ri2&)2HoRm#;4xx7;AF*5^&vID3v&_&>e*#i)*DU;`0|k z0(Y~hL4)uFy$Lyu!Z(2G2sFq9&dqWZTTU944>7On*SNkiqv%0}Z6akjbzi)%YbdXt zoR^|*Ddg)1mbYcw2nvSsrwapw@?Fq@B8yujYG|SS$wiLTsEqbY_#)WLuhO3{~{QfxRr-8;w6BF=_A18<&H;K7s4Y7P_)94W9U^B!p~+G_Fy@r z7(~#v-1X2!@ZGj%;Zs*ShLfJwvg9uOiIQMiYGVddAC?CHs}c;eh>gJ#jV0}gIu zexRE%mhk2d#IB7zVx6PZMB-mV5p<47A!6GWLwDie&`$iq!J!>Lyw1_i`%~IPe%*S9 zpN;>{4URFaP*kSN?|C}FP4mCl?*HP$jvGvV+ICeG%ORm>v3p2>t@$zhgN=?zWjOz4 zqocxHAy}g0LblGM92fABvk3%><3f=8^MU0kEtwrlniiu&{p)w&>Sc{Ov(=!A zPs-DdN)zb{x4DQeMH4+OsGx~{FMgqke(%>rujTVLI~MsSx&61m9)OS%s7y`tDjnda z8RW)sK5{2~nHsV*Z>-5re#Y;@-~N3xR2Ki%fAn4<(c)I9$p+7;_g_1A89 zG*(!e&NlaYQ7(%XiEWB-hs?8%E*@3%`D1yB49S(G7FtCgeqvX^@pE8_49TgY7M(-d zOXM69?&NIHGsfg81OPF)3f@z}kW3L9Lb94xBBzke=OSDP=wT~)i_%kiTnGTi$#1n)-+zA)VTWr@H0B7}QlHx1l^>EVp=YrzEi(l_E4 z`qDShAAV+xmwo-H$t#YD>@tx9CyN(#fScZb5$cbv%UjG$7Gg}|tX&j8zaMNfqHT79 z5-xv>wO*4SCR||_>2DWGJjR53_MSF2)xNy+^*Cu+AF&=07$xdTi`<#GO#GS6#m+=VC4!VMzwV&pQ+9#0g2|q) z2yKVlPZqhT{O*>#&I${+0%zLL;~(E><>yEBN$0iS=FMlV2zo=`vGxRt9SCUr==MCj z2fpZ+Xq}yAvR}+rT!~VQJmq7MOdLdu(vdWtoABfBgBC)peC|Zp!U!VZs+AAkS&Q7l z*nIqLP57}7U~AAQ!kU+SS~fcjRx(8Lo4q6NMmC+GOM@c-G`Q)4&k`bs*348*4!8@- zEr(g>PeVFOdS`uer-@J9nfE$-h|uujF-9tBl~wlHH_zwAD{RNV;&0bvTD2?hHnx|b z*X$~-iV{qqYiO;%uCcydXPtC`hO|X?!BbXV6YF#;t8`oQ(rnd!FlSala6c5odh>DrpM~+$+h_BPC9B7W+h;ppTixe zP5F?o9UYZQe&^S)%1})(^i37zwg5{rgKhGT(>zg4%aFExwcfO)=_hzD6L*PIBjJcb--6l^HZze4^ z#C!Eg8*bH8S3%2N9K|X;FgxlIYcZoj==1v*&cU4GB54T2hpquFeEtUBBSPE{hx6)K zGdr-P`G!zfw2rQQb_})4j{{H*!>o>=wf75j8tejyB}}=!$~B1}`WZ4kV$lsnpjn(X z^$;AOgZC7_(81yS$uGVW`)hfpUmXv6`*%JMzW`5uR}n!l+bh!nZkn~Lf_L&;Kh9gm z#_Mg%eE_5F^0@7AyF6~|hq!B)T}A=B-5mwsI*ks>UHsEO9R1A0M3dCQorDH{&4;&n zm$1bIibE17032-rgXD7*AM?4Qmd&qlx`GZ4;>YrLKZETpwS=&q&TS=7Jtf#lpg3-B z<=g&t%wrTArP=3&sBQ&iiHJZkF{RrgFi~GxN=Ny@l$~~4xkFAb?-K24!SlMSOYQ1kcInZ7c#_xd z2e@FD9{n|VmGI~J) zn@Z62&bpC6(V_rN=5G`q^EaIxEq|K?>JncP1sV86AFU&3{9fabn+Wz#(k=h;iu@wT52Nc!vfB zOJ*O0LeduGYhSY;3BZdvE%!OCbx%&Dv#r7!J9X<4_(W5)4M}7gv(loT!Pn|AeB>rV=w77L@GU| zanxinjUy4u9dSj_!!&NBU>T$QDDexU{3vIDH13T!r~feDod0m(w2@E$J#P@3O_d-v zQs1Bh+~og@fS(rcT*j8_ZOeea2zVFwD=c(kz>oDq+_eA(eP^Ot<0SFEg^(bWhhNHT zqHNsyO2)~`b9Ph;QU#~f;*{cK%{qzMViTrNV|03vv3S#+` z^|_5%J)wy~zxpx^N=FHFPia}(l@a-we037CiuQTb$s;dR$9o{cl3QCovT=S2`;}G~ zJ__iEQk>}?=os{m2uvFEDL-()%T#Yx^LHtRFnE7UdDv*r(d4&u(ELP?1|V#<lq*W?vLYne0!67K`KByqsRuTWlAXN}4bUDhip}rjfr<@Z?g2U|@Q0sn%3te?FP8IIl^4De z$uIPBW_nK4F2C+>Z!Y?;5+umHr6N3BRL%Fto>+r?q{P22`?7AN*0He zNv%(II$JC3rhmnssfpCFkMl16fRv)|6=Raxq;4Ryh~r_Sd$+Du8U=Iw*3`oPHun|8|a%| zJ8IH+?UPC~UU)U6`4 z=nbDTl^(oifU_OzMQY)9gYLX|s58(73&rI!BsCMYw2*|?Kc$z;FPZ72IsB4&4FQ}F z=~JaZ3u1E#MTB@OH>Rs^*o$6ia4R5DP8SXsqyRy~!cGyrp zc7(H%eM^MF<*l!DfSYKrN5vw>J9GKLk8D?myZtn6tTPD?XOxX~7Md>zMyPY1Ae_0+xTNzT zYjgTB8({%P=E`7?bAdXFSP5wq^DQ{+@|(i?6L5oftD`IAMuoAY6x|!XOHOq9*}gKR zLV9+-s6ah?Xod9bp`<1B>^lem;|*YJn(z1<9gPzQuhxp>9kd**hui&^tQe?bsJ@aQb{)%jYL= zbaFPC$br#mq7HBq{V%?-9UPM%$F~g3f1KT+6Oa*V9K1{Ii1pR?ZuJkDH zX(VuL`haMt{JtHwcx@McIDdJb^BVIU zL4roh@jA`=%=yk66&6=T3{+gMSd>?mrlwTMC*@K}DSp=y4-u)YsshZFx>VsKL}B5g znhamC`)>ZCf>d7gOAliZ83lB7q5*j2KaR;S@nw4Lr2M9Q+}Ql&5Id0O`E#7DnbR-t z)p?U(n*$K@x-6pEIp8U-W8uNIg+7=awHoLx(Zig1iPKQ$f}Py8$TW=+wzl6tzL zX9r?-fnR1p(QW)QyX4yZzP=oUPs}ectOHppC+2r#8@yQ%Thi5sBn!TKxu4?2_riJx z>1sajUT07L^bh{rw6zC)oZS29HAZKlepD@t`fR@r;rNXkdb)$*Bj9=8r2JI&2`Sdq z_CX-Eed$+i|Btrs4ve~J8uoXA09gX0f)GMN?+|*)<&pqNuBFgB2~7wk^j;D`YG?vk zkY4N}@>rsP6nou{%3$XJ=<;%kSC*k3Lp8 zL7*)An6iL<{3{`feJnt4OiZ-;ayzmhF(IgOb~#?Sr*m^wC0ma*H@9%KC1t(8SfEC> z{Gu1tFnn>eS%g-bn^n0dMmZG<4)=k4o3DE)!xl~S?DEF>mMr(o999~;A>%g_OCkK? zOoCNPJB55mKxB zYIlIXIw1SX*YVNusK^6d&gO&gJ`CV^d<&{^Jig=2!Q~Ut2?6Mz$(G+IrMBWV8VU7g z3lp1rP)D==me9jUa!WSGiVpjZqQv$l7Mi2Y-@iFk z$`P?pi_&w86K@$TmcV1G^wc-z=Byzt6&@DA_}rz54|u?%M4h}q4Y*(Zc*aN%K#kbu z1#ODWQJZL5eiek(f*O%71Aa05(*SB*^vve#3+$;zw%pW&Vd7=93J%`Z*^&`mTD&q5 zb^{9u177-3$`Y9 z+1`ldlTtJW0OOetCz?IraSFu=(fu zF35frzi>hJD_Dcy1=+1vGyZ=(TZZR+{@jz;l^;Ku#`xIRGqPBCFFm$!fmcNrxP&O< zt7R^-p?u8ynlXYe_W{ zTNQ}d7DM2rziFK&JuOIHZ41w6oq!x2WP>Z>vO}%AC>e3i%BtP|0Q3S7c4?Ye0 zA%Vx-)V~#(%cKIyKn3LQqxrKTAr06KQj27u)@D+O^Lo3yJ${1j&>KCf@LO*r2E)S>W4?hiR2v27 z)a5TEqToKkkmoyh<(9V++wf{{_s9^xEX+w*!f~>|8;y-Xp!3h81;Y7Xj%dn4L?QbA z1*JJxGkO@Nd3~hoUqHao8_($z!1XWhBVB)Y(ZbX9&*&pvKmX%DxW%03wDu0#1%(Gk zhty?z2nmen@GSZcNyqmr`qKiLGq_C^4?_3xu%B4lAVDc-WaFCnqv+KFbI|Khf>(0i zBxF#MR|83M%C98iPOfQ29}Ev&g5dPkTD%1RA0UG_s;+vI`8p7pAN`VX-=;zlcK@eo zO&2koz}DUB-<+7KYpCZh=q=~3fE-shVdHTZCD+(HJ|D% z8Ua_+Bk@1cF6Xe3=bEgU(H8`DoE1M6zi?Lk6!ZcyzTa69Y!he2+#u^tzq8`jGTmyB z^VGZllURkveVN#j)X8LH(rrzt-2~{>N3Y zHi5WmQw3|En4o^Z1a<3|G1mnwZCsN;psP=y1@1V% zr6@&Tf4#3fX%_NMVpM6%ZxbQncl48PKa(^S&Jw?+aS!_r(wN`y1g0`u!3@ z1Vwo$fGE5Cih^!Gt)I*a0CsmL=%vd`Knj;Ghe$P&dNBa0*Ci=Nv?f?KC`*kdhC!Qw@2@An-gxi(#AWQBMlKgH z+Q5`Q{{y%d3z)bc6N_23{#q62`+UGd`^z-}G!tura36qQCClQLeRcmlQlHn_iy#>Q zYWg5Jq|f{8=R~JrO6o7y1e(5b{{&t=pG?M|TT?KEF|*M}&_}P=SNuY+*SCLQuLm82 zUhlD5*8g8?fmF`+g2QVBN4nW0q8{{h<8^^cmVaPD@C{q0@!|@=Sj|0qu%@l{iU}b-QVTyG1wpTVUJLr z*~nVKXvzCFvi6EuAShGUJ(jQ{g8fqP`;`sWk?|7fGo;{;u5Q$ZhHYBTW* zU23y|fnDktXeVBzf3mA}uirp&dzk{s(&LHNXoK}2T0u{mq6=Ii6qk(>2TDEojTrOO zY_LWy6Ds`&%49@7sX+Gx6*{3Zi_~H=0%|cC(R-lZgvxpXj|r94ip)+@fn=aU=REe4 zS|kItE;2fy@+N^oYeQei(=wmCW2mkry za*#l(_Rh`9!ReuJc|V93rdtQZ^b#bfr%fU>g{OV7p&4F!syxVRAeg<|RU!}=T*uJ@ z5nShPOl2XW5Myg|X_3v^-!OF@Bm-(Q0msk~K1I|Uw($Hvw30qZM%6*0m1k7levrzg zG_zX8O*)LIhe07m)Om!Aj;M!dTE1cRIDt^)Q#^>NxLQ!dxLW+cxOy@Cz_|KBLJA}r zt!en)HD2pi9t^G950V)bB@RZ_g>|Zg@+vvj4yMNj@gx)6vUjAFMNz}h`q`4y=205IYl!EY2g=C0r68pu>)L~4WL;B~rA8C0pv^F=vc0!; zhrw=W#4@VZmZdV;R|mq$beau#17^xxHvV~({v+r0~HpB z4kmN2PwkyS;uuZK(j5b>t>DQsf(;WO8eXy6c(7aqJTTZgjhP8JPOd)ST?Wg^6`J8L zh7Ul4!SX&e@DV@M3fFfB1pxd8^rVtCE7$}=*o#j!6OL7U{xZzEjx8YIUVJL>xr$F{ zh8q}~PX+J|=@{G=C4J8?=UIEQ9bQCYG!8YJ(k3D)!yzftvGjvva}~q%^k6xq>PBix zC5_aSN_?2x>cB1Hl=_-r0;km1#V?#vUk6n{ZYGL+LcSK%Nk7GNM_GUKJDKt_O{TaT zdbGPaNqjo0fL$cY!AbRkE^rC)PrPLY6sw7eHHu#xW1Y=@(p2Q^dV8>(U4w?`VS_Uh zROp#0jMU=H1hqIbT^}r;$MC~_{&$1r%ybqkT3*-@4`YT;%A1lmVbruyQ>LnGJ8gKc z@m6QdcY-xKHJvBCV#a^1%{+~DC9GhKcFwz9Cjx<&fwSf~f_amP)&~4#ySWFml6o%; z>L@+MfRo!0(!_m7kqs23Xf@|b4;EOf7{)Aqe3G>hn?u0G&{dAqL+rq6H?Yb=AH)o z<8R@A0ii?=2Aux`Jh!jCJg?IcRymc2YI8;hrwOT9pwdw3hyejQVhx};`EiJJ#J7j= zXXk<=2G0Bgel|op;^2YiaV(J#Mn|miss}SV4V4_TLFV4fNx;4MRNywnCp1Gx?1S$! zq9fsmLp?fx9~x}VW)r-~#Aqzaos&i~SF~w}d6Qw9J5+jM4X<1`fmdFb3|Du*g9|_} z{E(oJUU-A}g zZ@%0*GUkxLNnPI~gb2F6N#{CGsRa#Qi|?p`6_EBynudwl{Jx77^a69hSqr8JZKntI^W~wVf<9FwH^CXpp=e|S6yvQ zkN8~_pzO-|{xOt~U2PrYK^#0%W{eLcWg6XdTf&mtO;>I$O3_V2H{ezB?6uZo@WfiR zb=HnnK-IOs*J`mKMpaSyhfuNLO(oePqyuwem7$$F$ zQ||SXU#*AO&a?Fd5jqhqx^hmdhn2#)?fVUWZ;CnFbYK`ysAaRTgQOkGvOkb4hyBZv z7?tls>WN`6JN#z8pTQ4zvL8A`9Uk?8e`J_=kmxgZfq>)5RLdXcWcCFu71wJo0E_s1 zj}M~rP$Lff2!xO?Czhg=uxFUOL%ox~`>@q&S{(>(rG$$l8h3e!Odfan>GnKsT6|bE z8Fa2{F>uj=)yoCh(Sg+$ztDlz&qW93{aX1LKKPzFgxA?_<$lA+vb{?vNAK$S=F0r| zTysmlb%%8=OAhw7cj6mndbtt>vb>o%PYkWx_j$r|gFOwG;Fq^4HfFKq_s5 zH_%v5px+mo2eSvgfJ{ZXG8)}LDli&_3LTB^CbbxiLM=w4zyan-{D`0L$dxX*U9QUo zzZ-3@UGk_k)OeLwdDPl3#v#yBFWiyPDSFhpl)Xm^FmmkR-Q;ZofwxQFSYlpbVxN#= zd2)4`xg)zmO7X}qfbp>9<~Kdy(ec8O--^8Q3UhtaPr3ZwQ`W}p7t$ErFWl^c+XcG= z=1}0n*th?*w+($&G<1iW{a3=3BQ1vV!Ge)>E8%_=Wn7=MubxNjO&sAD@Oi7uJ3ZiC zj5jwm%ado7Tab1xo?Dxm0f|obvm?8a;BI@0(vp)Tk(StSA1+$)nxGf?BdtGX2>DFOc=&+N-I|x^9!nrw{J|U$UAH|NAssgwXPeAENTyY{ z3xe4hl661gT*n{yI_uz!ku4mHYx$~5Duy|v6V@ELI@D<-S6PWIXG_Ke0-q^q|uE4x^<)-vB1{P2urYZ9OkgqY`g_!%% z%;r$;A)C{+)Op4{HHaM}NDe+=&k7S3h~rN^+;_ON_3ze5gPkIP*h?Ri0=#>4ivRS7 zwTU-i1D<&Yb{wwyLVs`vR*4j?=q2I+RLpP^>?AI}VPxr_pPJ_wrPn_-zX0zVkM^)J zHR`I+Qjxm}9?f?hp@WxRMWsf$sUpDu6f!0MA$*d=kJ19VBt(Y{?0w$;{_Fs)(` z;ExwHOKRgm8N*@JMt4FI4-^5T>#}TJJ-~4}i{7NK7q}73lgrzhctC5h@}*egNh1_% zOdzpl1Q3fj5|>!qR>9W7gRbVXm=JUcRn*JY+5=oVy^6LZ_@?}O6>Vm=hqTi3#*RR| zJ`Fv3#o9KMjEY*Yl=#Nn!G9-AZj)4pCw^{j#t*kis^Y;4a*n?JRlCH| zG@9(q`_!Hs<$mHK91duU*#1j`TZ|hX!ffIgh@cY$mHgUObF4R%8Z>uFTQ~fXYvA-K zRv0!a)v5WZD?{N+qj_Fc+w-i(175=g#g3z;z>ZOa?~b;ml5SUMqWG0sHuXftAA^`N zT88aD5xCAd z$v>!WvziW%@>ZCFduf#1nZu-dDPcvp;&8VsZYo)L?g5fhH$LL6YuS?7dD2P@b68tJ zXZbn!e+85wK8s664u|;!GU}RrMd$sj+E-fMbcQcLQ5vqdZtYr8z9)Rjg{YOiV@A|60NN$pi4BM%Ri}-RNsRE5zNK- zfKtZA5{>7+T%}xTan+` zJBUr7I7HtbZJyMgO{b-zZzu3w4hYaGv<}c$@B}9~%T=Ti&fLp*e2NXe#yG8BtncRj zCO=xnwTEUkM)p4tm1_@5U2EYfLRM%2cwL)iOZ4CshaXDziWhW{z@F72sgVb~mhH5Z z?F?y#vVHJZvV9&vwg^A6aeD<@a}VO0*&hg1C0b!GTY?8PvU;(XE!C*N<9pjuSfz2= zw6t3+KQ4ee>`N$T%G9>XGxzMBxbf?3mqd=(b?V1h9MhOy!J zx3##qX-%wCb$ME8UO!tmgV_j9caQU7ef5e1Ab8CVurQ^dVDf4Op-HP@l{QX>&|h~* zn#Cp%^jeVVv=jva-QkG|jZFp7`A{SF%K$4T{xyIi*KHgo{)5uM%2GNfrJG<_`-e<` z@h(mmW9a-8VZqBisMznZaU^y&y)#apM|qF5LnrrEpl<&N^dO>VFDD1lvz9@TdJR;J z(KGz;jh;#8DfnajR-Wy1UOQLzl31Ex+LM+5oMSFZ}iZKc;^K6+IEN2Fd&FOS1G z+4PtMBonj(OdvxD59<+!3_W83Eq~N_8Hr|& zcSWLOCfYi{a{xOh+6rPu36wMv%_cP5=keJ4q*O$roy)GU{_Gus6oa1MCfR;4*r%iz z_vJ2#0vaaLhIvzM2Tb3>w;EeG>@gZrT|T6cn8;r{&1N&PUkC{~*m|)2N@G! z^SBqxN$bA~=V zz>aK-pawwxFp+}Z#Lc6?Nzd6?khp};Q>;6wfLF#G?)!_GlTEB}gz^)4PZ z_~l`303Npc=fPiJ2urBWTh{!a;2_WiH-;vq1ij$0fKtCyp9?_sgfG=V7QkyPw$=3z z9A|iZoAEp$icvxN79X-HtapBXg-eZkdTi&Ex>BVEV5hiw%poMP^ykxpNK`svN zkqQj&{y_PBqt;3jd0x3*?L)};5=#T)7XdFnJZ`!<0mFsb`IM<@{O}K8TqV+~RXN3xwvbU#Hs^eU$&W#a_u2}@gx|6nHr4x&7-AycwP{4RX zQ&53Q>O}W)qb9$#H)#Yfu9wtA{7U21?pUj^eguU(6l23kspzO60Fz4)3NLz!3_$f5 zWN!e)jgZIJ+bRUHxfGQM8jf$awPA~CsR+jAPLx|96x)Wlk7SU>olWr5J%C!h3uhsD~p^A13+~Ph61;UF+e1^h()H=GnR@Ktvraw$y(h}c|1bnFG}i!X zY*=7yxI^<^L?ExBq(aWD0vei6E|8)5RMHMZ^8%>@-&u4%e7MBc-eV4zd2P*@qBO2R zMdt9s9bM|hj}QC<1v0O_jeuhZV|>1kmWrXa4LHPgj}M|PP$Sko0--o5?gKEgK%NxO z<3}EY4TCHRMn**Znog3zdLpU7U>zzjShtZ15v&_cdCs#ohfziR>B`r=*tSNLuY~!blVrI5GxVdp zO1R*lt&1^^zkJX(GbU6ZrQ!Oo8ijl|YTmzWGuSjjTZHS}{#;oy$EdStHd$jWg?PQ0 z!4~Thj-mP@H-BoHByIS?7i`?Lev%B;HDs`K@C33HLiO5ljJuF#))PsLKhKIq~=5|8h|cuUXt{D00vIF82G?11MdZ5;FJFo1KT#k zjNru}vGZgZBz7eg=)pTq4zLRA!Ee6?9-Q_uCXm}s#sspd88igPT037erZVu9 zF%cp1XWp=l=Z*x8tiNJ*$P{@vhA<0g{Dg!)@O!7oknm#yu0z7h zv{ZzIA5THg6+t|gBK(mMAk`%BiMRHA2<;N}ow#^wFK9b3Iq4W=!&gb@7$4}lWZa0j zu)2SD24nAdQhGEAKis|!A{Yz|!9%_UXR9=?OaIg4p2*n=^bfAXEJ zfd_QTc8K(D)V{wAX9Q3Q@x1B{I2tfZlPrz9VXI`Yy}CqRmD(x_P_FWF%GwG2E8Zx$ z_+HX@_B;W{?1~TgL7s3MOcTGB1WnO?eSo$Jpw#Mw9apdC1FU$?tY+!4lSwNLc9s$p zpMoFygRL3+jFjSh2w)|rlJY#jbAGgqW;eVbjkEByG;F?7yx1jAtWNB}?wdyJQgq2# z{>x900;bUTMVoLhK+{>!l1KqlNW^mip(J7}98a}uy=!}zJx=i9YDKqGFHq2SxLt7kPunvFdyzE6 z`Ss3BdxGisH2FoCS4pjVdNm!L7GNFn{xmVQwhIxqrj{Z2F&NE^dZz-Y@?YFXnclB?!R^<2*tD>t{bXT+-*w>E81(S=K%Ulm$Q05(hTFv zUeg1pKX1AW!=@1Ziy1vaI1}Z}6ealHA+y(FSp+x8qV~6apzYJ;d|pVvaZqE5XE`ku z^LZgKh$$W)MDw9Wq<92Ek>c?I$e4~P9#fC$yzmWshN*2Jz}6Bll z&h1TM4#SE29ldHtUP>Fse%EB=9_-H`fw+nGJ^U4Eo$R!fay<4>S{e(Vp-mn$KvibA zL2+Bv56k(tr^^Zd0_a%gY2cE5Q&XE6yy~OY`+3#sc5}>a!2_N4KO;=xv_HRmmo#pU zvWs)v=vi)+@6tS|$Bc5kPH>kdES+$sT}!ta0c<;GhRor%5zSmFj@oGr`LG-9%M=uV zZX=DZJfSAsomJeT;~gOgQ2{#$oMtyU9EgX#&H^;rs<&A@p3 zQg(xIjn_7>>Vjy+Nb$~pAm}|@C#@1c_Gi+Ato%&CtKw`N2F6S|4DNzVV#L_%+tXQX zZ>akuHrj0VJF1dNy|M*tNE-|E4q5?-lf*>AA72qIi_Yh|c= ze6P*q`l*E2%9c6?yA-&Q%C~+B79Ls)5z^s@Wp#@Hj8bG1? zcqXO@N}q0Pf6QQ2W`Ryz7A?MOqTv<4A+sdu>+S8|v3dj?7YcP|!M7g6Ej9)}+=%p3 z2pypspF-$Ns?km3QIYnu0(4ooS@JCe&n^>hAw+5h)eF^vh0~FirXDQlRO|pk8H2z& z+~{I&5lR?#J%%ujfQrWuj5_@DF7^%{h-LCfd{uklEcpUL5ox7Gn;%HDRenXocTD_< zCf_k3ymB$CkX}+shyik<+o89-x?Oc6bi24EWBO>Oe83LO&_CdD7+>%lKqRqpmp6qk zpud-v7Db$ot46smURX1-0)89ptWb({{Nk5%{9s9b9sl%X`(eMYBR%mCc<+g|E$KWi z+aAhWrP|lAo20jJ*0`n%T+$T(Lv-)wSq*Ga@};=o*?N57)M1(}r;a~o@q<^oivMT`RSYE)Oov=0)AII)spN+|Gq^ z{T$alQi}&Lp%xEdemYy)xgVbMFU*#9{u)>tL_fsNYw-ANdkub|wWWd)$H(`v_ldb6 zC{P1`gOJ1}Lt*>0RG!t>K9Mz<1F&j(!-%L_W?5cJM9oC1=Y|>*+%g(!Ygx@Yky4y1 zw)VHTGE(__{q4-LsL;T=U0DxsWAD|X^72ijYC zkVhl-0rY0O^gjdbjSZGhSi>kzH&huT?}mKqVEeOd7HKEv#*OKngBHz!d|W3>d$xpB zgT$@)t%(sGOof3YUNeVJ+LS&dLK9ak+1qAOPk$T`he)nDo+$!cT?6RoScF7%?V2CQ30T1(TKccn)`Y%k=pizWe*M2J8}P zggKT^0}1-=9GPPwUCZMyq;)c#p93ds(qq_pg6iNbM;g0F3PcTe)9iDuudl( z=E|7HhtG6C1u;!f_qpZxrF2WWsZAirR&zykJeBPx+<3{Z&P#4bi8d78ftR5Ur*~lg zA}ug9*IcM~s17JLw@czN8bG0JMNo*1C69jjyuh9nO?SOed?G^5h@ehqN9uqeH^fiLADC-z5;OyEnmz&4j9(XH)xmIM!XAB8GWwAFOS3 zQo9%z}xN_DZ^a?=gfxvA&Cro`&G@gU3O%5Q6Ms>@Tlm?K|>OFJ>1Q)Ew#(D+n` zya76b#THzEhkErafd*1Up9PV?=TxU$gPL&i0AL>XXq)sXVw^U)w1UJ-n!Zmv`wRNOr7b{C4rMG*e4K>;4^PIG_F3d?P z(2B*w)9}34!PRy@?=tj*^Q*=BuMqV+DFDR1)D5 z!;2ZTz@74%DoW8pKxsO>SU+Ee7aK?;JeaXIfSB9CPQ(Q|Dker3tHk+Th%QzUOc-4} zM+$KE1xSo8D5Q=qmJx7_E^y~J-8;UD-^NAg5V5`S-ly@XX*0F2P# z6r>AW{Qnc5>Hvz>_^#O*Q9OB)WetnfR5&iWYA)bmk(sbZGe4#wYffrKa>1y{#SuUx-^SQ~MXz|;Gvk4F;Hl{1I%SZ*H zg$g+K8^!UP=bK0^;)X3f%JPjFmVxXU0))7qRJf0j3d9W+c%=AUQh{inM6^b<_|uiQ z{-jNfC=KH3u>2^{=40JsOn2QrN_?G!ui9x3GhJK2ckHw~Vz3<@)c0vb(o>!6(B(z; zBPqp&)IDLkwB2nDQJS~gzRF;xh1#fe<}!qoV&>Asx9^2jB!w0;WsIhv67GZoKe#FJ-i0N;#QPs!Nb0fi70JdWVvpzB!Uv(vUV=E zbYy9yRB#>yVEpo8i^T&T_sFxBz$&r77rZHHp-ekb^!N%Lrk(Qrfa7Tq3XW-~d0vpn z$f~85g&vIHszU2RWlXy)#1pG=-PH>FuhnsNnWdb;c2Iia90H2>C@mH005E=Fg~jXv z@5P0B2=8IZMXc>FxgbYpzglUTWn%9UlDH3{#j7I|25&7S`w$DB6K42j;6^oMqf5Yz zh@?8Kv)ttG{tF{$?8ZLpp&Rdz_So$|f}CHkw^TlnXsz1C!TUD8=7r@bEC4e=H5zXlY@v4upu864c$bHic52q{H@=ES-R3zHoU7 zqy@8RsaSWX7s_=h1@~fC9sBHFDA@%nUhFFJE_SCdBQSU#nT|n;q8|0E-2JB zKGX1~7pUoJscRRcmzrx!2A@!B1`fQ`ti%H~MpjRY*VW3w8>I#%BzXt)LNS2rW+rG?i%(u4e3!2Lx zKz?E?(F!I*xGr!_ipBp7v5Nfnr(k0GmnI-1y=RI@q<5UuVnhVBBE4=r$#c%w2eFSy zJqAW+v9*PLO)9V2>Wu?UOSgQdw#%j$3Kwc$m~r@n==J5LCd zG_cu7XvjqTIr|*$IP2c7j@jVdr1By?$S{e1`Jg3()h4B4aMaQ5f~0YgcF+y{#7a|7 zo`20A#z+On7cOpoY#-0e1fl50sLr~;)s6WZ_@z(m&#_**O744PEs}9^9;pzzh5G?l zKDQ^b0#c4!9?$^$#Lll=v`6zDpV^&kIRQfbFHu-aNCjeDBC+lx<%ks;Xsol@E2JI~ zzN`?wM=B8E%K~9Ej|&ZI%swHNh!t9)8Q2%083a(w?Jw;0`LWZMh82SW!I)n8TRF7^ z-974%a|c4^#NzaUQKW$A8_;G~XNz59zq0s+V;_F;-LF{chw85~LdWt`Ii_I&x;goO z>;qX{fq*Q|qGELcAshRZeKYH%t7JE~TP!n=t>G`6IP=R=5x@5?Y=0g-ZE5s(8di~dEkZ|VIGPk_Q5D`>4~}S2 zeTQg)K6a=0g?ffx|3^Ll_J(B;dw~)c!|9+d(8T%f@9f*yd%8;M`7NdA*NC3K^ai@L zSnf5Fa#S;vqnhuL3RE*xpqc@zP;+&^9Kl2x|GuT}|H_ip!HQ=HA))8$q(F-*5ocCU zSmM%g8}SQu48Q)5I-YnEJ}s9a5Kvq0t_w6_-s(sD`)sJLk~$u^M4IV%Qh~l;Aiw<+ z43s&f9MuO6P$xXM(gbk-S5nu#4GbTD+j_K_ta=rFXaa}HA7uaIhYlF;<>k^rIeTT3uY7%F_7 z4xR1iA=Rxto!WZ>%6$2GOAj9wHdS#nGF@82tNm%O$F6uYfXAOc55&N=CGsLJVSu-~ zXOH(!e�-etK&_kT-&O)j#d^S@{RGDWUjC-FOhi_r2p^mEZc)-j4n6i0}B+($9xD zuWE8MF4qXi^2vSE>#`<(8E6oQfwstim-;7uZix%`RX<-HuH88Ziqp^SW@4sYu%7X#1N+FSsG87t^V5D;@*x_JP31gTo(h{mQ zB5k+6f@46?;s?u>d|^pr4|+9?&`s6CsOUkN&DqtsdI-N<(NQs)Afv+%zHwcf?+Qr| zE46%Sv6|RUf*O}T8ns#!ZhcT^4|w9&makYTZDZWyn;Kz4cSmDl0qU)dQhvUQBgKQfUZrZj74&m}S0pfwd~4~+ zcZNE|sd8L?X-IXI@>^g{oT!5qxct%p3e~d@%3MQCm;)Y*3R$Yh7G z8}4YzqDdvn9lkVx>xo+`SM5Y@*kwC#-O_+au3icc;h#k~>>iZ;Nv@!S0ke?&y&INE z%t9FQ5??JD6M;h^J~Z9ukg9(e{#Pg+F->5Ax;1>wHzJFl|U&^Ic16D`L!Ii*k%HR-LNrGH|+7-4Qqe4 zv>-k}4Fw?0PeF|b5B@qr!7o>eSY6xkJUc;H@=}CaMjus*fM#BbQ20O*BD)c^A4XYj zjY(#CR}coMfAG!HZ29M}cNxZR6Y^f&)=YNWb;T{7aWE~@M()L}0>7uYg=T_0af1qA zGjRc!itunr{NHyhJy~5ZG6YKtpXHxOMMRbEs^@4J627UNdgyxoMhVxNf6&6=sIA9t zE1&l2J5*%t>h_GV{1w@WsC2;(#v~cy7sezR{B}!6!)U!e!KW2*?`{J$6Um7+tsEPC zH)Y4Pc1&Y=L_$m}4ABKH^2M9Vp2N7F;8@3IY1}fSFm0Jw={OAdBQ7l@w{_UqIs$~t z$znIqau4mm_e$8&q3OP3_kx>UYxTv!LaAoQT5&CEe>VCd$x0Kpwrf8@pWY?Z%NN=$m4e z2MEua^4r}U?b%m?sM^BDz1Z+ z@#vUwACI>%8n-$lass$}8;+rZw%~-w6+Z}bT?tgMC3T`d8aU#lZXw$1L^(0rz4+ zY55j1kYZfaEQGmbQZN7_*c0y_z-pk2&0#gBYH+Or1wIKmp33U2(B|#Mt6DYJSs|5$ zvqn1t?!~LxYD-ulgAHhgvxe5D!Z(SCD`t&IVs|conaS6+PEU&_qu*5{JP4+lhX_v4 zkq;HW(2)-XR{h>e_$bq{+Sh$ITkK%``7B3IHj{{jK76V!a8WLPsO&zxdJgchM&p(% z{FN)DzuiVE(BDFZ_P0-xTJ*P2i~e@$3VFQF56}4za-+ASwrS!Dm%E+Q+Yx8H$G7%& zbc=aVV5Hu55+Q-!_FZe2Ty~a}qPMMDRJ$zR7L*Xm7xZ-mv(p4KuA`E7^$IS{Y@NIv zHZVyYMuBVJZCQzDPv{zNx(;gT?`Xho5)gDF*TDAtZlL`Jh9M5oyeC>HNBh+3^m-9r zhyqlBN=APPni7{Je8^ksEv&?Ev`wyOgzarvB{Wq@9i(1$WdQ26SNc+)w>G^& zq#x?=!bAIH_^uHV4g6SUj1MT)9Ueon5Prl&C2!s(ic*}a9)tlYzFM3uPB{-;DW|Hz zq!9|yKadck{Rn|`RqvH@uIf!t;aoM36yRJ1kT_RSNIh3&6L39OIakVK&WS5|%Eqiz zW2Ky{sPuTs`S-5LN7-`(g>Yu!T5HNX9Vjgv;pk_u_Xs5JY@Q(nxU&fmyoDvXkq0PF zDarS$h7iM1nBM~7#GG=&l5Ax+C^q*ulYXY9;_Lu`@$Zt8>wCZ>I~7-H<3iotSSfd^ zDQ009zKmRh9u%uRUAQYAznoE#p~1uo*n>&rel?8r*4%xk_1SNhGi zL5CMD;JCqMvkum6!%GP&!Am;8OJWRSgjmCNhrEl-cEJZ<)*QR;r#Nxor< zBPC{^z)mNCwS*i_0C7_tU$b+h6kYLzF=e)%rOu6Es>5djkj5}p>j8l2fxE>r{;WzWF#d!J zJUm*PRAA@{6&QN{RxG`cA9nM9EtX#BO0mle{khB$Yb5d7%N>@OUxk3w>c7+y%M+M8 z`*m5w(g|e|dv^W@l+b-dav1AQ5aY|7+j=B!DXls(d8onqk~+5sF^ya;L#ENB7DJ}t zs{^>YNvov`NfIsS@_y)Q=|YAQROmvMk^*!gLwWpKa3K`X?Lv&c{Pa=>Jiyqkby!Rv z(UJzTR6z71kFJ(pKFjQ=d#HBKC6ir`O}ejfW1nP<54ilj<8X{f6Pv)m*MU%1P?i(0>=%V@v`skwiieKoW`T~RAF6zW9 z>0|iGhaH=IUDOj>9g|oAkpo@SI9=c(T3k|g7iF1|yq_)AxMkS0XpMAH8%YJaD5%g& zcY;=0`z|iuexU7nhdh*8+qJne@`qBua5<2`a>;WwpGTQ%!Me<)bcj zNh630M;Ng@=LzAiJ_-r(4Y!)Fl@GhTrbUO%GV!z#T!4Uf@|zbdnjm#A5{(D}(TU?l z71LUIANC%oQrw57!r%)pS(%Ap{F5gf@3RpEnQ&I&S`$iT!%C|?gb5V-PF94qB7b zHcmqqxQG_-E0d>!hj4nB`O!6LA$;cxjuEVerod0sOz&-qT*q%)vf8tTq{2Afy-CT7 z!Oemrp>X5W;= z=m%=Kd3R%4Sxa!)gjXBVs9y94H@cB-bR#7?avE?xyxEgG2);S}9{4MLij~PL=_=sbU`s{JiPE4Z#o22YCYVpR$9rxH#(gfr6 zL+j*Z_&%w?$q*{=R#w|r9d+3SQj3!z)QZUvUd{|V=ZNO5UUN9v4+IEt-&DAb^=^gB zjYgSD^wWc(!_K9IHWUkqXpODjBC8<5&U#LfkDLlD%pn z705hP;OfyyDiAGHP_)O+IQp{D1PIX%S7@h^3PcMP$a4Hg5X>whwTK&PHSW=DE2&4c zT%mn}R3KWYKyFJ(1!9B>fzk9LxO8#2-v1cq30u-0s+RvGjHlw@DWgV@EEusd|0P~@ zw^}44EyR;wbxqUO2^Zd<@4wrfU^!}CZkFxs(n2tZovfnRUcn?O&;LFD)mmJ?2 ztTCa3R}>F?|5`KFnv`NLzVQaRM?}H#;#1)ljt(r<3*2bTt9=PR(+7IUmyT4{+XuSz zw=W(0JbA$|y^(;#nO$vFQ6bg7MOOpH^!ue5F=9si^eso72rY_w zi5jS1nbxhQ2lbqznaw;3u9Syo{FVxWsRkS!zu{=bf4B<%`T}7J#m;>`ml;Z)bEHzs zb3@5d=F|5VA>ngAh`SGF@H~)F`O# zCfKDOX2i4lq*@4MirW-mMrpap-;A>UUZ>b_?F`gMxkGr$JviY>X`?u_K!{_i0N+|H z=$7Jg2IucMve+QPlDmsc{ggcYNUa`31^m`s7(|mvB}y|PkTi3pG(IDU$fB;R_LH(u zx+n`RKv{Zw$g*jua{+st@S{c9r$pIDYPBdwq$o#8C5mz=kSK2l5QU5!bx0Tpi<1$d zgfJ|{PRBhH$4_ktYRN7Vnu6VuqM#5HGz$AUyCx%z_=!wsy6JnsCLX{3k+c$7BGauv zoc_59GejOrFL)<2jws#5sZ=_piAtvhsPx?)O6Plmos(Fz5`P1tQHdN7jYus{`NR4; zoA8SjoUNFdR*B2y&;}p2Ap@WB zXu#hIai*|Yq!eS6;flBixR_CC!TSF=tMkjundMQ6EDe(^nHF#0VJmV{47eVB)sAa{B*>KfxK_HbCpNfhZjo6JLX67 z#0Y1#az6kk+&BUI**{U9#0vekE{F!(z*q_p^GUO&)iQlo!gmjHCZvnW6z)=DFrNmo zdvTR+nVBtz=S>?iX4urRb6gwm0<1U)sx}sfkjiB$;IGKnM>->8v`cI)rM;n9;3p!T z%UKlnveInv%yzgaRs4yJY%N}`yR(tefZvXC)-pBVeD_diP4O3lxfTQmI*Fz{fcNgm z8aY!)f2oRkT%I`%=V3LRsYF6mUzIQuW^tyn%B0{*D`#dD(Shy; zUgv&iPISJ2#kAEp@e9*dKxaI-1AUbT09=h1hG3YWz@YY_)QW0101r ze@b1pgfJnpHFXMgfo4Jkkrm>AOX#Z>K*mJNF^gj{RqK9h5m@usgH;=j~$ z)-g5QEHkotFegfNRn{0~zqTa>x?fw1QlEY;*A0q!QFcTPQ#T+l#xwlIuC)_1*tHp( z1B~ZBz?wJ?={=swRGKV#?NQRmnMy{pDo)ufPvy1V%&+uwrjX&R09p`UuxFc+0@1T| zh!(V7-6JWHCuCKP<8cFG8bvP`O|hd_h+o*zD?ow(qkCTy=RDtzuKc#6vK-yJ012=5 zwj-A9Av}rE9koLjXr6eJX3*DLy!*PSnX~%+WK^5RPjQdv7ks)tRjPBVCLp{1RZ^h4 z{+KBB==#{7L*Uw9M^jZ^xkGTZavuVKG=dMM5d=XAKlpTGNc$3uU`55wf24`dntMnnZEd%Q95)DPJz|UZq^~N5ZINyw zbBni|Pylwq4H`oRDL`W&8qtb(8$$*$hDSwHbQ6z>UuX=ENn;>;SKmCucXon!)W;0Y zbauv;e{0DlH&Y^tne2$V3b{v0&JU=_B*h$xC7v z6oMK zO8!@Z5Y6JJKxScjIM7O-OcOmN-{1QfhN`%s4C8Yj!%zSh2tQ~T=ScxZ21F;MKTcR6 zGHCy>%Mv<>UuX#(fb9Si#_?olp|3r_MoJaw7My^Dr-U|(V_5ESB zjBcTxk5N<w6Op}NKnis4j~AsLy^p~^yz-U^ z!T&;FM+6J-7lVam1c&Hwc<}Q?4`-m$8S7=I|5d=yUou-H(4>;-LY2=Kn&B#EXO_bPN}Cfo6%v+Q0@rk~W|N#2GeceGwpTvpMUUZu@ljK&iv?8l&v+KS=?0 zcz{*Dc+7{U#Qvt3Y?t?*iYjczr0?yqqTO;KBApI6@sEtL7* z_4WN;nfsxV*J@j3R;ZfB?U5DgsLL^zfmtDFgjpfdNM?oXfK6nDoTL?Ig{*-%?YGr` zR){zw&8hqZp`LYBO=Z9#K9BZ?k6kK&Uy1(FE`K5g=#5C15hJ*p1Kwz*kOd8KmH35* zxC->^d8R_nOJn%mp3Vn-?Qlrk{bAA>?ExJ8X0Wp!+edVSYtvo2K=a@p8@Xa_YTCNh zD_FVS+ZiJ)lJx=SPzr2$x}aRy%iA?-X_2p!0_}oMh*A%e9NO2}#dH>kg71OPwY~uV zWS@|>n5#Os)jNI|Dan2)I|gp5T<+(QG*I-Br$@4&dNMh_fz>7ud)oQKz;p&^);NWi;jt;1hX+ zXwKlmAg`Rk_=3EVqx1@+9SKpa0MG3OZBq!WRFZA2@N zEpSBg1Br3rEQ?g>UUrC5k6tbq>TGQc~5L$=9* z=h)^wAt(SVVE{XrGAo{(jv@kURFJ@KdM~6GZ;k~}o!=dA!Cd}f1d|VgM<|YU+&c_UOe1JgU@d0Bm8cS{O$Rhs(K~J3|;G6C`+mOy4FE##%W=VWNYA(A- z3cT!NqHOXhfe>FxiXu3)Sp4nLkfZxaz@o~37QayCKcmXY>k6nj z4k5hi7-!O7sl7cvuwztJ-sM8Ou=4q#+hNR28d|;{s|vq7#vIcHnn(ATnIsBAxe>e_{im<)+X#X#-P6}1FosSKq^G$-FOXm|NJJX2Hr%Bz7 z(>zI?|2f(DJljV~y>vc9w%bi0(C7&wEgWAk6^#C{fJIFo5x-E=M^Mw%{c2h`kkx&X zgI)zquFr1RfW1zLiEkB}j&BzZGnudZDeb@f?uhR(m($aoBb|O6TJf`GI|&=N+1dZa zna=$|rf;|NqF1s;i@#y#yALnPZ3g4{jagAVcagIWzdXYk!kb?UYRd0S>=MEstv8BR zY`Ydz%c#n;<~f_NupOX9HGzuY&j{rwjymB0__TVlz6Zx^?cfKG_GnXCctdrXVI4m< zDy;?IHQ(9fzdJe4L8x4#5-(f;ZoLv=N9;v~w-5#Nh;6XsZ`Yx24dBjS_Cn`+mO>iA z%$dp8cB%Pa-kF!oBxxF^pdCE^%kC-0eWis(&iY2sm>uPKQqxh5SU#bOnj8IBnwu6# zb0rPd+zj_2MV6T&ZSa%S>l zrL(g6`{o{Sw6~@c-p{F;8OALy&8ihNb!Ry~u7fs&#SzwJ!9d*74jqv@B|! zz>79J>$3@j2Q|9B;*pBn@xeB>pO%W#6p!rWC#q-G^#DKp zu(MxTnBU{c6YYT#JIr1Oj?SvXZyrew6>EZUF@=@mzi)FsQSKse$6Mc>)0$l-e4_F{ z3!wa~ew2TDhcmAX{F^?8Xf(M>-;vT<1Q6Ib|zF&b?rr~Kq<&>yL^2@@*~cHWze6Iz;hl2 zpO8QpLG|?!1yp@4r991c34hQ6?w>U4VT^W{dC0iyx6UDa`s2>KK$um#; zVLE@EmWtO7AmrT-b0mc>>-c=x&5ehOTQxI6N`E@wj5JI??c(g9vm^V3aDyuT;jdI| z?Dn;##D6(QmqEp*o4fd}Ly#Z7NjO0rN9^`8rthRw-zpuy{X^yq)<^)UnDkV+&Ngf~VF`6SRJ8Up zeUF#w^$f{(Z0XSg0?Qga_K>sYf2rtOk2v%A%|p)SY#`wUwY)$S&>`E8h}L_zoX3AX z3YKtNsVic+MoGb^+uT|NQZ6m7ztAm3EQWTkPqUf6 z-p=DkW~ZCJ*e>30N#X0lVnd?+EXVS%Y?m)io;>F7z}n8^&e7~U$}5~(aQ;UZxE80y zyUM(*OXW>og$?tdJ=!$!3e7#xrg%3$j8xzi8mQ2BvFngpyhj7Icr)h@sjavIBR<*> z+?KQre9s$@GFB-t0w;3*xl){9_;q-yM@klSf)dOHlF>Rr?GqN^1P_a^)3%I!d)KHNbK@7;iu+g#Rk0#9G_kv9nan;ZG~Gg zy&Z_-b9>}o58;^S)XIwU&#$;oLP_J%TUvmpUmy6uIn@IUPruFvN@7Q746q_Tt~_cF zPq^M~5UaEo6rpufBkuScW`Ws?oW07o3c`H)|u|X1!|!BUZH_h z$ThnZ0Pd_K7pHwaj2plENJf^+|A=9Xx4Neb0Wdo@L;S+**bHFRcQZculR0B}-+3dW z`OyPiLV2}DnYDQ6aj=(#iy(D0{;di%d^g4-KX#5~Yl)6TCepb|7r6NO2mE0t$;h3P z6)JMe^pO$#$S2MM_Nb;MFUs!OE5GqG;{j_M_B^RY=LxlVn{dZo`67iMR`a(5jPQVS zKSK`~zrI~m2*CrBP+il~z32et?Ll$iIRAnGK?nE+{K7-V{K_KG=BUq|^sly6toXq#Im^! zSowXxyc%{m2#kFJ20_(*au5g=Xr~r;xaRQ27^aw3*dr?}7nz_|7sD04? zW9_>Gqbi=qeeXg^Hb6ok0n$Sc5fWPQKKw0iyskz(&IWE0h6L7^QB4VU%=9Z`cyC0K;h1 zJ769Rqm{%j45O9a2^2>0h&$|NJ{U0De|KMp7P;tj-m0kER#soAVf0B1x^)%6tNmSm zi`pkGm?vECww-lW66CEw?ZE(W8KMT$=^NdiW;vvM+nEO*)ZUR3)e!`a6V*rFk?(p> zBn4uQsy)Kj-R#y?@{8oX&Obef%_BG%!Dky>-zEjf6$&#Wdj{+Tuiy3BD4nOi+N~5n zX0yM}oTM(;6S^vZw=UD~naBkt?6cXUN`mYO1C~oyA43X+`)C7rVkvtIHkH6}H3kH@ z8tcasOWOyt#iShlalXNDB`H9LaB^HQ{Di=fArRoirr&aTO+o-8c=`g4nAlA4bc^!( zA;FV=*kL*PVWe8x9T&3D56>;EcI^jF4zg^gbRk0voG3$-O)UjdSK1`J zD-0{Iw24s&UKOWrxI1TdraRL3iA&>Bc)xSwvRF$cfeUAj3Lw(c;@u#Q_tUIBTO*v8 zeI~I7%OZ5>Ck`G~!Jff#2pk>Dfz^3Hf8bp?0S?SxUUd}pF1i97u=%l~y+&{z@RIY| zgbU+hdF@Dhatx?q_JqnrAkJ%XlVKWxs!fL36e@C<(|AFYy(**FnXkj{ZHr3w|C$r< z+P6M?fk?v%aC~KZWv$Hn3JiX5Il58;f9A@#s{Bf%UAzDaR~ser+>iTLYAA4lHy(>Fn!L|WY-uK!#y9pm>x+?`L zokIInDR*?q1dSC@mg4$r6!Zs$iWD25@s!`jT`}RS?@F^3z7B%b(2Kww;JeZ$bfH(A z(#u%i61~8tqZX!C;C++q^;uQI5+~tH%Tx)eXu>uop)2{{N%maU$VxEj@2C(xZ3Q1y zzf%R>(|}*8YLB)xSP{e%{}|Vvbs*@_a2=zd$5RMSsl8b~ji*kvSB>~o5Yw)^X$6n{ z)85jg1$J^jOsYK|5Os#?DeOAY#FP7GqR>RccnBx@Ir}_ zeD5kq%e8K9e~Nvm1j-rm+V|uP`Eyc$3oIzWW!nK#fHPVsz!~i-u!#7!R?S0Qo$Nfp z!uiY@gYPX;fPA3<`IcCzd>{EjftN2{C>Fprp7#M~L5Def>&R{~-kCDNlQZQx?^$Qc zDMA*`lpC((cp~zBp%#sJ^N5~!A0z>In?{I72Wc<(p@Vb~ztBNCtSr_+mbSIe_4A1Q z3GM6;YOEhI1G+?S1@Ow9zW(l90_IvH@{{07W{r(i++|w!2~b;nIAQoozU;JpDw{zN zupy_xG47U*NM7(m$#}Myl!^;IVP;t5us3Ea3EX$-Bv7t9YwyoClfuID_J_H%>G-s8 zeB-b5$Y+`j7?v}7^c>Ghp5wAtfJQ}z2MCRi;U}m{BlZ(1L@f-Wiv;c^0)~a%>`mBh zQU*#)zk~d;??by9k=e^i_sWkUg;ahrfqRLh{AzsWH?ieeIzd27Waq@D7Nd!f2D6?R zeqvIII$k@w2?MVL9qf!7kJ+RU*BVCS3@30e5irclvfJ4NQii<{m|-sjf56@y`cKKJ zY%akPPNB`>iM{Pn(kI>`g=mdgTTP4H8gvQHI+bT3^ z%+8Q9RKlRSPT*b|ee3(&HO*O-uZ=Dh!L(JXrT@(_42Bg6x|g9>iK?WGDv?IuUK*bg z=oqaD#vL64)K`vS7`rE7;1dDHM#p%R6ry7oL}Lh?5@BMkUgr38HkDwYdjLz5dyL42 zL1i()!k96C6^R)uNhw+dUWI=Yn(Pw-_elpzj2T~%!aMrMF3IpGLgQn&3sq^vE|Nmj z!XUa$;9eqa7k3SUm{IzJ|C?(VtYQedmzD07pG*p={B#2M5=r?+%;-Q6?&umIO}NIq zfls7Jn`9GeFMAz~jD9hk6rx`kEi-|@y+qo4t__8NF^!a=M*uUEN7Nn$>%+GQ7J9^z z4~R#sBc;L?I+WtI&|67?SFk8VmnbBKcXA1Rufg#QA@XsALKxB-vFoG|_3%<@t5w5O zDit-#5e!hKxZ%X7M^%DPIienEq|l^CYf?a|P!9|o-3Z1Vy#uO;fg_ZL$9c=A?UUJBLW`AJTeVa< zUiTS$`{KsRRjb7;rVan$8GCSKK+Y@W`nShQ@A`N2ID0ki0G~h3{y@y*Vsb!dgAbG0 z0%ps^i9f#iX-qv~Mya1T?01qVil@LH+W0lq@Z-)hR zLtZe&ma11+Q_Ko7X$@a?vU7tn2ZVgz0h!$2OQlr!LxAXN8g%3Zzn7}vuYy?A>&@2i zeYfqkSPQcT#u7eVYT&rMKk5hC; z9*xjJ9&Op-Ms@T5eqy{GK8Qd_(IK7!RTKX%)tbQ%--J>*&?^)Qxj+4>HGEc%qn8O? z=pLbTFuq1JdJSHV7d29`@U9m;fXve>HK~%nf9&}38rz^yWX5pK8s2K4Bb%+E1tKAd zUcHk-g;Icy2}X);Q7Tj(ho?+)mfkle(F`J+NFH%y6 zI2vm#d@V7%s7sl(e4EEHiIpJ*7AeMMwZUuAz>$Fs%+qGuT`_*GLOery)c)`Z>v&4u z_*mA6NJJ0FecbT`Ye}IZ`wM71ymhHO6TZ-pxM6u|Z6XZZu*KBz>)9iO9rWd7o?CH3 zs@`+0=*ww*=150E)PoAesty1+f?uk9LnrGhZP%*#XC`UP+ zO;W5l1{QTlfOmg46OC00Z=-;sQ666@Qh3#QSV-Bne9P$0NdW9#jOQZyCbG|s++>*9o#5R1?DtkPM3&z!| zAQivVN~Nmfh2_>6#|y*Psg5Cz7sA_wId9pU``?Nj%}2gtZ(tIPhYOW!D8V_a?NzjI z`K&kXE%XNK_{?3fY1GInD6JSlt^Ea^tmQ}yT*KY=IA*C~N9`d#>ur$O(<<@7Vk8dm zmxwo~`d5vgc*mY?5{RcHN5(tCOi(-kMD+qRxWm9zs;UW1-Sqh!(Nzo>CNz}s##Vc* z393d9en;XHAC)jGh)L1|GP3D=*YfZe;bp>C-m~9kn+Y@YdOTtE2|u|K(wU!-LgB(N zadN#6DdBGjTsW|{4^8dgw|`hC)6W0mzs4=KpRAMqOGPUGz2WuWn?y4D@3mqi-?v_# zj-`@?1D98=?3K*3SKFg?P+)1aqq$yby>#Fz>&-nyk6d5O%&1xbQ5F~Wih@cC7q(Qg zquye@yy>NtRcN!~gmwxbRCqDzH$><=_I@Uz%8jWi=*ASF+?Yb)jg0ENZ(Ql7%tO>g zH>POHjVV;Q@q{}PqZ?CV;l|oWqQ%pASnHH;X^_;pf< z(fFhFMl{YRB^Zr2NSph|#BDrn73^P8m$C%o>T-mB9hy^oHk%6dIkR?zhkpR^>KKtL zTvv3%9$w?otXlZGgIic&JR@Q*S6Txn1iT`&P>siGgGK? z=A1hcqcc-tjL8ev<80IC$d7Kb-(=4dX1C2@*wD@w+hv>`xL83fQ`_eLTvdk`gBA0y$ zvkNLxc`}8fCsTm(WC|U%rc-r({3}RcHYCcTCsQ=#$rP$Qxx*ca(UU1Ldh+BA^49jf zeBEAqI=}jq9-@D>7Pn=!jRMw2|9GuD@caxBp=R1+1=KgwuIG4z%^-NVPd<$TeEZ}S zip!CuM<)mK%d;E_`kNo}u-T4k>}^7bJ!7eCKK~iZ>JJ00Mo#3FjgJ-UYa`E*EIS94 zJn}V114aR8l@~sg8`EP!9&Aj**T#f(=4DrAAtaB3Thk=@p%Bx>eMsRQ)5Q-P z97hr&A4e#}H0>l(h-O)$-84RBy zL|%qE6k^*vM+#95FV$)BkHl86q@uXBn6a8`N(mCaVH-U z^~NoQ)Kkq;Af}wZtoXUM)VZA zrSQ87vGO%re8GJv(FtMHhTX6!0VR}iwR(CUWV`49<8 zz>wPt6jg02tbk(NR#-_m!A#KDR#={2%+&wGe7UXAUyzx%6RoAaveMh0A~0`)jNWoMH5ip~59>!JinL3h={Mg5DEP00LDH{zUF4P)wmVsh_c* zP=be-aI}fi6^BS*j?*wuRc2@@?sv}btPQjT%#83MP+F!m9~{2ye2d3O=6 z5O&aY&f9NS2!jR0UzA2tU-&jbc$_Y$9|pHW5sg^Ysq`YyBm~iT+@tOeRs$xYiFO8g~%}@g>oY z7W&SOa;d-DDr$Riq6!0u!n{==QJA-~)Uu;~9;z>{+rD5GdagL3zXcGAd8>dzMc#@E zRjYjp#nnCqsMS7&Vi2gE;Hbr-K2;q_1Sx+RxR*eQF-q6IBONaEO?2WrgZ;5jWa|Ak z%58-Ak{rJ|46+=UdP7x(|v@Zy1_M0hb=u9Ft$2yltc@K0sJih2^} zUX`Vdba$6er4v)3%88!`$>_u{63N1e;l}^Kl4pNJk4ItCv!bGNUVJcI(FomKEQ-E?|3RT-- ze-drcg((`!Ko_P^bm6j_EUr&6kWRR8Jb`*gEjvyu?PK~6nmdTEF5S8*PZ*+yXdQ)> zjJ*Zn-|($Jy$^J9ar?;w5Cz1$1)Vm^ELJ8F?hEy-m4M1n&#%^VEMYwe8YZ#a6yQr@ zQK%(}<=G^YSi=Y*hWy7i6*C%+-4tjvlu0brVXDaqD3y#!EDFFRmSdB&Kr4`ESO8Xk z#`Py;G~}4aA}b!RwZ(c2^H?8K%lVD+*;@T#XrU=?h990~Bgi>5I zmnQ|jqI~uceLgQr!Wkt;#aFzRJILqIGAcz!!m#{m5dkOV~ z&E&{*e}eHZnF=q%u>{@A(4@(;1c7QYo4~zu@fSf59-{prTBR{#pP79F;MkIt z3EU_0kIm9G>X5=ax<*aD>;Vwen$UO|YBhOYXDI7N%CIdAn%)HNrO|7CM!aGO!T2|? zFc?lG=w60iC0-_FREY%y?xpc5fe!I5!MKw{2ue&|;Tsl)v9}QhJ`rGS^osqY5D!cn zL_ZQZB~ngtfnZ>Q^AA3%y`!rL9r&_SfS~0$xJl-&LbfQsz&hP2ccqo&Ieo2sWosu{s4bd5Iv!zjs-!R3*>IYIRo-lGTds;SjHqi;0E}Fl1JXqN=Rc zNGQgv))R!2FRP^u7X}Y7Tb-~)CbfiBElI5`0isDQp#dhf{4~I`vU9e`v$FHd3dpRM zHX9Z2Piid%roNfmG zS9`0J%&qdUY$hqNNHLOJE&nf4WR`0vVJ4bHdz2S=9Fy6j1a1*xB)JAiAr%9fmutfu zZsJi!vk=d)Cb?cE0#%ZWQz)os12mcBqWD6=IAv=i$wh>DlU(_PoiE9yZ-5udd`D&1 zC=`>o1j=$Lkw%s)bqmdMeXm$qkIJ5cYT!}X(*y_S^(Ro707qpnZ8J zp(;Tz1SDgEU?`D{34%w9kvyhACJ3lxOmYR1j0pnJ022hS6vza@t5#7j7b9vx08yAA z2qX#<1eQv6)Yn1nMS@_1Rpy#vWPTPvCMF01$`lC#DpMs0C=?R}6rd6W6smGu$BDL> zAfRX}K|rBu2r0TFF($ewu~_!PW;D2(kqoF=z}Ibc)#E*@!jLzJ(7|Ff1-O-tq zWOQcG0G;`XZPJ;aw2B&8jHpQgL|L3!i9%<#RI;N!4{9%*dA?QVoML3Y89=7RnTbr{ z%v7dwW(q}TrU2#46sodaJBYUE%oI&IGleQ=K6FQ7bY@D7&RmXfo8f4qgCC2emR1dY z`?Z-@;X;udEkutfkg1)p0-4+j{@mi?c(tzp`U1Q-p%q8aFu7HQ0({9W3N*`O4X#I*1HBCJFihE+<;w8AQX*b-yGjUEWk0^Wz z3tk-Ksb>HYd7`MoB4C;`FC*CoKVCa|Hl07d(D7ey3CoRW-+=$K&{1|Wvi4O7?t-~e z31r<6kK`)ws3#tSqT%5Y4`(Vo9uyCI8a%SZW0!dB5szW@;W0`)3LC)Vuz0-F2p%iN zV`*b}EEkWQba)IFkIA;C@GLDJRhq#gK|Fdjhetp0XxjoFoy6mdmhjjs9@|@qf5l@^ zYj}9Xqj4rYnv2K(#N)m;@VF@+{}Ydh_VB1A9vwQs;{ov))d?PBJ57e?=?CC(UObL> z75|FIKs!8!h)3xxc$5{73Ekl_MLaI_fJc#d41O3M!^ER`FL-2%$9H|;aa26s>I;t* z;?Xc09?itVJpdjLiAS%;g6^B_=?71beHc8l#N*}&c>GU1>W_v;6Y)4Y1|G-7 zEgrAD43F93adJ95&Wgw28Soe?9)G?H4^8x`C&l9#@whk-9!26Yp2H(oJVNHfqnvmw z5RW&+qt*g=;1})l#V`D_d54AY>w$$qlkf8!6hHB+#)}rgFZ`@*rN!_IKVqoAXC@ajKt#hK`j zvh#U5rip$yUOe!6uQ}qn8oc?Yhj>*PUwOVMP8i`yr7fG_m&o~y@f^nf>3IYCtmxp} z{sz2!nZ_r-;rNGb1)%p}3C!L*^RRD1N{Rp|7C=jzlrPOwFUD3Z6EeNz=n-R{7%*s# z=U9EdZIvTJ@6&*1zYS+Bj#@cn57tWPhYc3Fi!|0kZ>dj?AMzDdFNfW3pH0B%9&SYepd_(U`q0-w8D4k9{u3=!)C(yS3Q zj?ikVEgSHHRgMaJ2agoBHz3(pMAXq?LA>638PR(8;gaN+fFx%Wi8h62u7T#5ncr`X zBV1#)9hUZ+`EEu@9=;JK*Grm|kK%1tWt7(!jYb;;t%H!l6FoJnmKMVtMEqMkynX48 ze9byXJ66@lDVDGM$kC3c9t#h#Cn%`+C1xnoNB`HmlLo&Q{!?WB+Vu`y>lTRdU0q#U ziKjY>D)6wiw#s~Dma|5_=R-#ejb*9|h-%qmGX#L2iV+W?F%tR-XI&>rAjLYEt#LYX=zm`5~2M-_Qti?uK*=Iym zWuiSF_)lN5u^6Rps7ZR_xDEpXHpJHd+QQt`x`@d9c#~tY4)>hoe&%>opAS`puXXa& zy(#7R8jmxIFJ0BP3_oEns?L|bJ^?O#+v1pE+p;5wXMAm|%L<4kmVNDj!;aOpdhqQh z^zH0}At8K;D=}REYKQp3QW_sx;CS_JO*C(lqZ1Fi+BldOY;)8N{X}U1&70K09xedX zbv_c>r1R_unC7qFAwT`|_2-TitVodxFX_ftgO}V3^aZ$1y^$f7`|PJj?!>vjv|Y8G_;o7%*bY8xx1;|()2}?=_=TfIXnCap z+OJzgV*#NCEVq+~f891y3+1D}b=2cGQk=U&yHK*kUR@J;>L_Oke(`>1p5A>YA5quY zne|XOqH+UuH?3FpPF^^@b0W{4YAYXf44Q(Es-2g`3x+iOZ?k6N(ZWTr4Z83T_B!gA zl@%R6;t6XVJNoLl?XaVb23K(GbaduFUW2cl%KHQQBkwag?2mn)!;^qo2w@M zUVn|&Z<%a28&r+EZpKFOiN83y@Qjek_s+#$h3nNE4MJa4${0D|zjM3_8w`yPI$Z2qg(6#TKds%5r1h|hvlcgq;`Q1&+eUb1T6^Gb z*$gJ3*bIJ{JG^>w(G2<;@OkmsEQm_tvsv0)(Whd0!mQXja2Fc}nXBcJq9bX*1n0#i z`pg~j&g~^f97_Yn&o%cbeuB5v=QCfN+>kdp=2*`f?lN`hWIj@}HS3nDpu##hMBh^d zPE4EJo3&L^M4Kh^t8Zw{q5{bFwAlrBc0cvhY}S*IKoG2r_wMNr?vh75T)TMD5!X;Q zDj?S51PksqiVQ4BTwU3RUuiHjf@fcWk7vRRAcF6$85A7kX%AXN{+N&uN-0GYPt=ol ziPsC#_?m`8LwM^HXPq!WHg2)uZ|vfEU7Zc|#NE8Gd8dv# zNH__f?J`R!{4A?Zh~k+)|FYvPo%K}^IpNFrryMIUDun}?vGvvq1TE@Rmme&0{1rMv zkr=Hr^5eE8_(PxNK5u(wH{^1@`=AROuaHRdJVmvCZntWlxUIQ8Dk%FKVnGrwTs-`K zv&e0)cCht^2phHyQ$Cbd5uXYnTM&3~?ognjoX{;0D*L ze>xJ)VC|f{Iv>(0H<=}UVRh}gdPpV8L-h-op`7SB`3W;C?AFS08h>FpPC8+%`gOxE zl-p}<=7u{PVy_l%6Q|n3*ugewAsvWLZN!^Y*Gz<=@;00u_A?`lWLS#6$zJ- zX$H?I_@*OcYDqSluxZh7aY50J()w)4yLrC~5YnB;!4(wTx+e4AZj55f_dC#2(U#uV`jcQdAZiMtt*v0?^S8FMM+~5a=RGhae%Hkl?fjG#5IWyP5tjPkR$awy&oRzy_PrISpqD3wU_|n;@9oXm zRV$kFJ*|#*(S*1(E8WRTe+8CSGY?~O8uXPsmKbR*MK(cvX_B)At7a`6S>D!02U2`> z7WIwf^@f$}!&>@b{yZ#2Gh{qqEkqejrHr1|LX^?eEaT&cb5oxzEw+vAqSxd1#@I4G+v+dSG6au75NM$~; zma`4}!HS7OzBh#YYAwb3Kq=Pe>)J3a{N0Lzq5#DZwJzD|jtuOS|FWJ~1s;p*2}&u~ z6SKdxtS8C?vaz11@iqJswB6j3QewgF%`1vI%3X~W1*Sk!1eJ77BNTg6AVW&ct$Ckz z-+lM-uyk7$tuY^7*V%=oD}2%M25Jp?VM9|$Zu2!si3p`IB{DD7c`q^|7zkqYl&|^f zy^iEillEdU9@|~$NAo_lmBKstsPmmBut5sKaRSj_05AZ)_oY}jG~!`7RYvQ%U(0g| zQwTmzA22;Q$y)E}U*n+*8&sK(atvr7%44~6c8NM{Ea3oA2li?Tb4rTxHhTZBaY)hn ziGS1aTeP7jm2sn)HXhLxgZxgx9E1EW@e70euCL|W7^Wc4@xwPInmAVni0!wVIJdLo zL{Amlk141xw%^r9Z_G(9NS^J7PpGerXvcU$&e$;Cwf#gpyR3wg03SdV&n2)o2KY+X zAIxJxd%y;M!S=pAG86FU*D@0jW5rs#y=w}*dX8^|0200t0v`fv&l*}WF$$#a5#PgY z&DvN?F@iv;2mrc}CNc_vwf>g~a22YA5r9(42yh6T(v(ps56DIY7$LL~w1pKOZX64C zG53V;l}U{Vu=HEUccEic9gGOz%cAL%_wXhM9Zr^~aIn|w6Zeocz{~t(TUZ2ucX@Fr!k!@n+6qaFSUrK{25S1X9@@b3!%cKA!sM54oA?ch9W z`w}X!Zg5Bv`l+ z$ICRdU4ruPae6g&MU@Ln8kvL(gtz_&_~C`N(w=D}$~4!v@4@3?0eH_mo)kLI6B4I~ z@0E#)h`m1X2Kzql`r2O7Sg|~>i?b2vo!b@KOz6F?et2awZ!l~v8M(F+b!FrdyUcs! zbohPHT1ozrOxh0b;TZTO4#%9UJ5cb>fyZd$2#iNSUK;H?`y$HZ6u1@8;Mo`W zA!{P%Hl3@W;+OF1={^7J%p12&dG3SG5AA{Y4*Ab~dCu$3RGys#JM5DV42#JB zx`#8|#y(cM^JV`yllY0WXR5I+1Pb-E!__n|^nwjbKkRsC_iF5bKX$L)&XxYysgIQI z&rbPcU+Uvr?vI`OL6dBD!ykKGUuQ>u?8|+fgIURaruGqfukPneH(?j`bJ}A*5^QP6 zBDUsvU&2D?#Kz33wuF7KPt&_+5=$~OZpSmmmI%?~_K7d?$EpP?YO@Kx@kr20A?Qsr4HV8Z;m$ zt!dN2IqCHWi{6B)rP;QD?3uZx8#DOfiw?reBFeCj?v}jXMuygzKN|>4;|qQ5idT0m9%)C zGtyW>_*?4!{c`8{^giBkw9|bz%Gsj#2hDr2bUg-tO|~lES^%hTRT3(-(JStkJMG6; zyFO-FgbJfo+*oHX)|)`{7P}nUe*V;2R|^w1v`07YoYFhwZnW2&KApriyw9qw|4a+X z|LJLGvZhVv!Q-5EHiM{y2A=kB2A(esY}l$qNzif4~^y6#3%+w=Q__|}-gu?&8g z?YvR|sGXY-Job#M9Unf~=`hiV zE>M1fwF|&0U(u`}4o@<`r^moa<@sq5zn01P^@faJ3rYNn3>3c>z=hf3gUFqyIER}8 z=*bz*7X0ri&S9+50c8Pb3YjglS5Q!IY@I&w?gLc>ANs5_T8rc_JnO8_YAPXo)N=f~J+-s?GMAC^u?wms+Ut~Wd&UvTeWE~q{4V|X8>+X^MTtmLSRyUzPW%X-;6CMWlGAQ)0}nubq@PDE}nf#2)t5Yv4@|sjtp#J z`SF@^2js$S=5%LtY^30V-!%MA{1X2@KgZL#3}j;?5Aa#>9V23)Wz1bATma{|+Yv zRQm~LIMu!>n??$i6tn+&rJ(=5K?uA`d;Pa!Koj#>3!Jg~b?UyiMdPFUej?b3f4%Mt z&4=y_En{}y--yGY`&Oh7Kt}fs5z@Lw?h@4KxVyzKbllyA#X9cG3nA2!2+bh?H_vam z$oZ(oP6!5uA1U|!K|y`)JN~ZR_jPtf@st5KfDq4R@K}+p%3tz^vya9~e516>`@z*+ z*S?WSsJ{wjrYhEoP+1{hmJ0VG8WAjL)!H1hRB0B}gKs*YXWa-YO6>fN+=%E+3Vb}Y z&fN7jB-Mvl3o+9Tq?qUeWl@($-*G<1rVvyVFv$=wlN2Zclcaz*tc555NKFEcz3cR_ ze1eJsHW&hSk^&_FZnS1O{XD(dMS_Y_eleunCIw2$FH*|F zYLMe8{jF+L#6T%PZ<6wAwV_j4B0&{Wv{)Yg5rnLI1g?a{a@T5TjF#3y_gr?=HCA`WPtq3mUXh$3E)A{G$167hnp z!n@W&tilTx{#Ax}oUDMLB7ZoTD@?SHz!iVE>PDF82W#Phf&S_rukmzu_8Y-O_C=Dt z?K?{&E*+enBJGn<##W1kTg$NqMWz~nDOpHAmP}AlL=8SFA8L?J;JzB@HNF!&Of6Xl zYbgqVQm+?bZaHv_k-6pOo1In56+u**UJ}2dK41={lJfovtH1~qhnaGcez;K0PQnF= z4DU}09f}Hh{3-ad6of8wNI#+i-d=e~ZOL%w9yX3B4r7vBSgzjU{ErLEE_~^gu_f74 zgsaGr-h8LC3ENFDaLu-zpWNwe?!O)`{0_I7%3#xot9I?4^`&{*Td>#k`e#Am<&{dt z6#$#~>Rry6{wfUJ4a55R@A$Oc&UkjgD*jwC;(wFkwI}(4FPv2aN!#~@vz1Aj#Zrb^ z#8Uatp75o+@PlAXW26QnRpsNx+NuXd1C;0V^VDFmq+FOtuY9nW>`KjpXd~^(d3&5G zL`Nnkyy3jn9_KSAc@`ZFM53e2%eC3-{G7EVdZ5d_vSUJh_5gtjm($xGly`|xbRi~I zwUBW}iip`OuVxrxX4Z~76H0`H4i-?HCS8WvfjHl|^!%f3^XDCK9@E&fgk;urke_=H z`g+%x5CTWnb3Uxyug^co3$L`T#TJrMu&J>fF;5z{Jgm0wn;wj@P3=0yjc zjr1qKr_xRF^R16${F_70C(020VD(d&usVTf9CvqMXNgvs zry!R?5IOLR;`P6GerAHMI}3^HwGXvPVZT%2ajpQw+mAR?OvLCv35ny9S;!$}G2uTZ zG?cvUs58z4MdHw7&h9Mcj>PyrIjxNLjmxf2Jcvgk;U1;L(yqGsAOGMyrn5}K3_Ypk zA$cc4OH!a*>A^$Nl^!Cc%9XMX71Kv^4$1SfhA%~^7B$}82dUyxgfc{`x2cxy2})&8 z5qYAibU^?oZ5bgDO;*RkA@^lHp2v?`Qi6{@Ql=s=cj+(23ts%EYX0A4$3CFZW=aXdLD6>eqQ)}q z5YN8g9L0Vnve3(OD|K(k{vc4HstwS1`06n)oAA*;zFa+~6TIR1>Lq7AR_?H}6S#+Q zp*uT_?oq)n(o{YS=ik_} zSSO+wx_i6B(%svU0&LmOxMwr#MWCW(bwEcyCFov1J@6X5T{esm2tU=@@vxiDXh!fk zS}Vg*s=A&F+{9%VQwSB9Yk)pUTFQSyF#WJG*zsAnoHdBOQe?Xe{Y1B*@~~SF04OZF zMSh3hoi?28@3*DFL9cYTx?_ zOP0bCzV`_`xuH`<-aW`QSbI=NjNylaTzyzC3oqM4Ua{~)i51(chf27Hv0(&?vLEu7 zT}R5!QnF#uk;W62m#sqPyoNbw6JR&Xl=jia<-@2_OJhrjMC@UUzL!005h=hfkbAIH zP1^?0Kj(*_MD`IW#t~)d^Y!X$pzYgjoB8*Ht>4RI6EHF6%f1*~jr4>xSsf6IJ(Y;{ z_Ea2E4ib4dq6h-fbqE2DC{{oe4}Kdq=qZ{UAIrFg+KQk$+a|YZ#;z0gdB3^_>Q{=Z z%3ol2@v@AlN=})_I>f2Lv97l&zNUpL%o^9ktRxQZ^JVLK2lqx{t`;R(jUzrnj%|^2 zM7Bi|DG;4L|JcBxtu&TS!00W2k47Z;UL#_->p}?7h(Hj2(^-WP0=d~=F3#1J^&#j! z{=()I9m5p?$Z(aAf4+*VlE$7evuHQ(r7|JJVhyCl%;fOd@B8@)$Ho%*D`Q-pH2t|F zGHRes)65L*+6(-nI9L5LFDSUT$`#^W8EmnFbBypW@YV6I{*2(meXr2}S|-3A)@q6^ zhWZ!yj|r|gf9zU`uKKLNAN#{Z*FqDvh>XPB8_5b!Jt6}~E;N`39ObLJ7U(C8de*D$ zYQxSD-e~(%NBGG4u0~}}sRD0BcUNP<(wIR~I(O!W+IK)FZ|9E$dI<7S`#Kbzd{< zOZU6x2hX+Pp<6h1n>JUkq(5g!f=ZX<1$DuHrV+Mirx$p3Jr`#$5V%ELQ^O<7;x?ta zF6k=`{yWoLPPT@yK-R1Hi2AO^WmYM;*B|oJU8!uFf=kC=#rrgHJ;n&WoZ5_dZR#Vi zwsSOeHDZSekqCp3R0IRdmpc5T`pKgz6sBEi9K{pnwXH>*y_u}qs-tqTO(k25U|_B= z8(~Fb*Ll6fG3ke^n?OVgIcD}lz0@(;D@v&XlNDkVTw0+N&ur=%%m}`+f}VPeI~%$h zvigJyM}xY@aA5OabhqG{ja&_JFbHIU=F$S7B|0>fDl9;3WnkKl`2s_rQQZh1BwlhH z)#GIk_6{erTDq?4>?u+U98N|blf%hqQh;M&{LPSHexivUZ+rO|oH<-oD~Y{AaMX(N zC20qLSK!Cg06%KP(CVaS9iI(J?ch&~U1Ox|QQofcpxd=sXLATI z>>4wFkX>UYDUj2|hvAyyY-eaS+ln9H81ecNHQ7pngIy!zgEsZGABvg!e)t3S3`olU z)5DcQ`b7_^Fi6IEER~EtO90Ym6Y@7b$F?u;Jg6ilWi*cR2AALb}ZjoM<_)c%BK1juwN~D@%Dkt(VrUC)RR6>9;b#A|j z)!2Ik8=Fe77t?);EnL$Ih~gg%aqTxjago#OM;y$&U9aO%*F>EiB2v(F-x#L*h7@?a z-u?QoKgtZ|MN+Cv_e*i6yD3fQ&4v@x^_Qjtsc1SP)oVIjZ-)M){1#0o2!t^Rfn0A| z08#ilxCsqAPeL@S%W4p=!o(&tFfCkg@@ViT6BLOvz6yDmrT-go;b@qqQ&o@-5~Oes z(33Fibon=8A$i`OkVpI(^cw@iVV^tE^7Ns>u_j_1@2(yRZpDTZVlm#C(6GvDkHQ8L zRb94z85iSak9o3fQ+|S@$j3a**t3KcPRnwCDrQxabHA{2@(^4(9~fTlg?+Q|A7HrNb(kIQE0s|rlb@T7vvW&i?g20|d4 z!2*clf4j<*XB3LH!F28n!WC;n(XckHUWBzBg^Jo}y?M?nE_ki6yG?woBkUzuNIwOe zv*Jr!gJG{vygfAFAWxgtZUEb67GdmpZV^!Lo~IVmZinrMv`*DCJFewS;{Rz%|~{{DyFY8n%<465B5@+UQ%3D_t+O?aeBlFnOh+Yk2|n>I(a_ z4fB7P;aU^K>RPe!{f*=kayU;WrD{xSb3%?u?MSJwl6uC8Vuo}339O)ZOd>n9!(}`I zX*^jQn#ibF3_=OphdS9nA`Vv$$$Z^BSL-qa8@w(1v%;!8fxBw5u>>EjCaMN^t}o-R zbdw0>N-vs8>^7m&mj2`5oF*wjd_0}8kU)j&0rxQrV4*~@RRvZNY;Oe?y4qPPkP-D< zRsMYGq4%>b1m9NyRH^SrZAO`ds45&V6A6_LEQZAkRmn0BHq2i`QQ|zfB7Z4#sGZy1 za5d6@J;9s3;Yu!Zk>D76)1Au%Pw*;BTv?0|$UGx9Wr>r@M};MHK*uR7 zMYl{@pOjAW%Lz4QEx%C0h~{$ATJ?nN$K}BnjehLA6vK2{2V}r2OYaAVRHO%nd|gGH z_)O+&N3j}_?S#sB?6bZ2g~vYIpDgy+=c2b<^#dB%nPs(?m16P)uOB(@f{LZBjDtRvL!ISD-T9_b_=h7;k zf?p$e@71pKSTLdaSlUBMLE~5&zP=MJXpG}U*p>11ovH+i(IuLXUF&MeC^k57H(rp^ z|3ALIqkN=nXeA}iIO@|zLF8MVc+{u0fZ|Xx3=HbM$_#P?u20z`gaW4oJx|Gzq$ep* zBgv>!awHi|O4Ud*;#4ss$;4A~B&i60#aW-`f*g;!8CSJ|GJ(9vX@EOT1B3d@2U|IK(w6FP{}X}slzOQD8BW@u}w`-94Vr=Kr&-1(Fy0HDZlFg>~s^!VKHwgwZA^NP%jT-;Fl8O-iv%4*Z>7Un|Zm zK|hFqTy5z?Lwhwmmj5Fw5qz*ZN!tD_-Lx$!K$C#K)U@^f8CGEZv_$p@DOP^k^XFpx^igRP8-xU|oeil* ztYVzv1G%^iCvr_Q=7~h0nC8R#t7)IPq8Y)L6J`q_ir3lU>SsbzR^*haSd#h?kGT9; z2w%F>6=o_zQ)c|ETufYr<~${b+ScG1VyJC#N=})-B0_NTg0W+_fO=yGPMObuZSnSj zbA&+I_UGbkTSRP&HxV5F8E>v*#|R%3EWW#|fB!S83D?`5{0b(`LQ64OjytU!N@*D_ zpk6H@!ZpgTvPZa011q+eQL=gjiaxk@uPfXHRh_HjX&LZ36B?}S%>1nS+Ua8aDC@MT zbH%8jW1P~YD&*~ljUozAbHgD-su)mAXsG&<1Fri`P&L;be@Eh_g{~eZVsx04)6zkr zp>~FYsJR#!bHt!3=VFm`lq4;IS2L^@YT!IumyKD4{O7nk2&Lb_F>ovJ*>FPiB|w|o%eDD%hzy9oB=x+lLti5&iD}2YdEn4OHG_ATTo+vaP?%32r4p6J0mAwZApRR z0j0~5#H$%0A=R17ih?sRK*1RpsEiunyD}bvied&EVxA@iN(_|Z?N<1*%=1E#?!U;?yOtx2s}_ z{6lA5Zb-3_GT+F-9j9I5&3Ih09XrD-oQH)0#gu{0$Xv$qPtUoM`H3e>SGL_cW8^UZ zAbc^0`P-Rdf}ZWH++7DVb6*lO;;5jfQ$0`vSB_K-u#`R450g~anBP`E3(Sn3qoRM3 zfMWDN1U<|*zg=|6b%SLP3Y<8!I4dU(El7b1_ubFRaNmQJVz|$}HKD$CwwRh{pT%&m zeaL54cBhakmyyd|kcm?%Difzt7J!k8r%?1bJkvdisDxtyMZ>Wm@tSKEqfiXzO`%!D zO|^~BiYey(`4g|ZO6lw^!VT@R#IVZ}QlRXTZ`frcDOF?sN5vUtdvS&_j`)L6Gz=Ar zhOqz)!%!$12G3KUBs!sCC>k1OQp%Y6j6#tZ&sJZ*BXPzjP1>4>p?9@oCC({N#EC6s zk3yH!9n;RAF6xeSy+3X8o|P_%V`9Gc9f?nDYSP_Aj4rU)>;ioCsgRQS*Z+2P)|j2J zL_g?qPWF#3qyYT@C)WMX858S)q*ysZ_PJtu$nbO6Lu?{8;KW*W_GsBhKrT+KiCpi* zI(LA(UI>wg+gpH-JA(w@IQd+ubamT&&=Ws%xRB6+o&)rG#i{uAIeF!tP%-Rhts3dZ zL`AWqMn$5xS^)5cka-g$O=#$FnEd{nD1_eXN8G%myQM$zJ0;y+*mrj%_LOojH4&o& zbUa66KwW;QwEI)`2VsUy|C`bDzmWoH`cAeozZjpZEcc7@dS9z+jOT>8i_4N%{>2*` zM>2PHV$?X%{HPU8c-PYi&oR%j+uoctt z__K1|wv@1k8pCzt^E)yofZibymu;J%4RP7_8NpX=xbffGaJOtj?7ev{vReq;Se|>V zLrMr?hQh_#O1>Cbj4P3xICw}1q?l~|IEZ`Wq z_(O0@EK$p|0lM$W3zOSa#4j?AL4GkX7}RKvP^R21E>o(<&_hcOyDgn*TpZq&*HFnOBr8yeo!Qa zF~z)9EF54BBCpvKwFcs!6q20N&P@tHN?vi}vYC)5l5K|!ILY=6Mc z(`vZ8TamkmUiQOlRnt8%lrTLnZdU9TaX=u_*?u87%Ir=VJfm5?(oq3w>;Ve6M=2$R zFR112_5Xj-=gDmNcv`Dv2}wL-t-Ey094TCrozyH3J^-xubVydze+Mo=?~~UjYp*7DwF#)W zkg|bGXkdqjuhR$!=`^CugR(`HJ)xj%;_bFk&3+2F_*GhMu^yKzZyjl06vbP@GIWA$Y=i6;Xix;%d7E2p(X|J z+jtb>HU8$iwoPY#yq!BL|Lt^lRZTztE6@APF&O^l!@Z3oG_4$8*4*8Qgz@*tvEdLfcN_h_3!=L>!OJU! zdBo?r^s~^j20Au^&9Cot*{-Fe~N1-(*umy^_aDVw#go*(~dgk-v?cHnG8Z$vH9+sG%qQ8GZ<~HAj zzc;$U`!5~c!`beDsN10t8n$i34q8hSJe^Z?D21$LbM~{f^lI|cZME&95z=^A_4H`% zUHLmsQw2cAQ0P+P z<6P*2QG$Ufv|diD&bw^rau=Zj8#cbY92+Yr0pNP#6J2k0b2rvl4FxArueyMu+Q!`^ ze&l?h!wsK$Bh-mb_k7lZ0I)A5>?#8vASx(ZiU+&gIW{2RiEH!e{GJt-M865A{?|y;w8JgKV-uQ6jeG9nNWr2?$Ap_4TqvJ zo~GhMCS$9?1Fy6jcoAQxjrAz8rTlCN_Z)-3JS*#wV#rW*#>c2k>Wa^g@lU(E#kYE7 zv=JkOb7>F81UH;1%)g-Wn)&GuyUS>7t)HluY&G;%7iIQl6)DYm+TByz!4rD98?apj z4#MOW9q^&&yivvizPw+YhC2XzyBpcSqq)7#Qw<|jZH&DvkSSL1%px<1XaAlM%+J<& zDpvpH;=DfYMD}Yy>1Y2<`VA#L=KiOu29^%%`%oes{8@bW$^^mhUTuBE{f)h(UcJaVD4N^EbLOb<1y%BOFZr}j0hGZ ziJY6ns2YWN8{6l8`H4f_J#}{7EGC)fR-6#TH$3icSn-M~@=gUj)%l-~yQhZIB3Vz= zx#VRZdsR;}GIpBYBiy|i;UQG+8-F2?Jkh;zkci}oOXBMB$49#B#m-Rr_{t-^H58Gx z1y3kwSQ2^#Zc{A3$ipGsrM)FOWE*`p1YeQudiA2rc6G99jY|&9A+;Ap-f)RIuK|~h zoYx>TmEmhSmy79$BQC3sh({G3xh#(=^fdFS#Shf&TSM=0S>{{X13#~>BGt9nimh~A zKy?-QF3z5EZ)NKOQY@YEGh?dcSB~w1Ij;{CSoG+g`cBZHm%BdOO$vO0Uf*6^jSESQ zMU*FFRu$P+MAEM^-V=z7CX)~J3+B&{bI0iCFY~v@xf9rhfLfd@PK)297SP8(8Skz} zdW63Y{P*$h0ii^NUm^e0F_Gt%eXKEKS1hg_w&KwmX5^FQASpt~Wk(c4fxgmc&IP9C ztj9CjRY_*`t*lj>))Pfu|HC$oo$TJmx&)x8p?AC@m)r$kmSlYG{in%&B{)G;nCp%YZL9bg9#B5d-G>n{sYAvUI4jq!jRsN-k5m~zGW(De z2~Q@5N78vHsRv{Ls|I=cU4c<1t#_?R_+jJ%r;A^h3!HvM<^r*!#dCI7`la<;!FslM^bipv3m#*P4{p@*h{Bh! z;Keb%?`|M6F00lECi60qZSX_n2Klger~HR+MS0gk4^=fU)*zhci3vL{283dsZqQ8l zeGO4bD2AJ;UUcWNFNOM8O zoaj+hj=vF`m73qU*yi=Z!U7L)!yJ)i(wOUDX~N18CY$IkDcj@ui~)FM^0`C!S<@m0!@0| zJ?%dxfV`GLEgRbAUxf}?Vpw$sKU5clW~|`(Oh9Ne&IR@1D;E0ft1|sFVs(WQJmxUu zfC>pQy8G6{?kCw10!4Q(yvk>M?@l+NgUi_Y@G5owYuGW@N8hJ(#7{N63c899U_HB1F7Fwh#jOGqYN=?;@h_xe&@cS3GO<<#<0o@b$fp^^P?}^#9Abx1M zJB0-i9Yo)$;Hf1b)aalQ8vSo*`gh$sSPMducsr{bf4oYayX_^?7xbn|l*x82c2x`E zrQUZx$ak%DuL&9e8t|C7tcGk5)y3zrIn;(Dhz+%@C!+Yp>_>umL2OnnUamsFaPFvd zk6K=Pgn#}4WZ54fI!Tk}2?#Z5FQc9h6-htdx7z(Sn@i~Kv0Y~?c_zF5c&%wj{_u6~ zBu#t(1A(sW0yrrTgtWvyYl zqdl`mvCD)GdjB|flK`;eUoMgfDvEiJJN^ZwnaRl6-}VjReKxue2i3d=e%ob6Rt;7g zetD-GD$-WJM*4n(YuNXLpzq(u3vCr5dF$p628#$#nZLNn9er;MpU4MphIp7r^pS>d zFCf%sj(P1voi#LL_OsQyQm|4CmjL$+tQuxhwe?Yf6hPIoJpA`_=>|2dy-)uDdzTNIc>^7mp7C&}9%gyxb%Biu%Z_5_^Z@AC;uKxhcBFNJam#4A&Ayg{by%jDKH>Jz7?=u) z?V(Xu$@WlyiJWKTRk=O1W}kb7dG3eXLvQSd{g-J(PiXpNo^h&A^R5c$TXC$shqJ;+ zKH?8|G@n-pJ!yfG#a*tffl<#ZfLFL@{&nN5yraqRlAM3z9?jM$G(IXmtGoXGbz{%y zIv+I?!trh^!ghs#=f(pI!d;$uv*1Na+~mowo>eJm5wPN6EgQx&Lc^i;U_a-&+|S9r zmX#7F@Z?s`4e@Icf8~(7RV*lP_U5SqAeVVpayGNd1P7g5yYX`?{P$ zQgqPgo^(uXozljR&n>0T6?rpwBGDy0w!59h34lyt@MRa=HF#J^*|t38nEN_wL2&az zU`>;L1M}da>8b#-4ZXT1a=aAWc|)GNa;stvUO7m&-ynlhpBtEI({Dh7!i#|sRRlJM z3*%;Ykb=keh!j5RCwCoY0Yvc;L1P~*L!csM;k$}^9MNLdakt%{ToX$|LeAAfaXKM} zwR`~LODC)vi4}7DlkOJm4N45dmPrQG#JEg@N*+}j%-iUO%!k&89T0dkFn?dk?(HX7+p&8d{=m*{oPIRLs31{*A8i7dWXw<)QI56XS`qll5-M3~e0LTI9o` zZ^&$N2f`XVKwANj9Uvb%Ko`xH^Be5ti0}9gAhbBkjEWYOpKUB29u7cn5eGba;Xyyy5T(;6w!d;*Bo6JfJ=9rc4{Tohc zievkpm+kvjw(nB59|d5GIT@jL;$tD5Y#(2BQ;yIZYc`t9pI+F zd#^^1qvm*GkKfrLUl|VVf2GGFM>ZUQoPQL9P!X6|fIJ&yP2;z0L zZa3xV`nVNgh(f^8HL#38qiZIxlA|l3k)vzPn`Cqqcye@ID1K$~p?|xZ$AaGG(Y3Y! zm`2y*@4Dx)r3wtE*&tysGBoDy69!&$hlakc_!|S|M+(A4oCsYn02n7)-Beri{DPMC z89P9bF-GsXDM!jZs({Am(>LWvc~%w6-hb+*iY@w8XcYL6x4sbmiji`)z@{T5NWmCQ zq{tX;0Yve>hvCLV3Qao=<5JmMK4as=#Dsz2+4+4|gb50<-N_Q}NS9O!(5O6|;zQ!L z1*?BYV!YVML@Y+fFK^1xao0^cIzB|Wq2;q~Ny}%c0&4l8x1{ACSH;ruLv9hvKXt1( z%NwI3NI}aJDbn&5fH68!s2UyT5*@_6kWn->I+~zjbbR;U=x}s2kqF~CZzs{XqiA_a3CBCkNxz}b}0V%WCyvTbc; z+nloPY+-8?>f*>o_{x#(g3@2arq1&w1eerqN&6lKLm2i|0~-l8WMHF_kJuasw&#Ve zIIz7Se&N9O0%$1CHyOU;#*?^AbMtf0Oz?d^Lrrmbgd6mvO# z1(4=h4Xq+RYX}>JS!38vLW1MhHmIu@zdrk2j$c1o5soMX^*Z%$1S_)#EHaBEmi8G> zP0H%U%KV`m3&jNgAx|SllL91!0z8OVn-svZpf(q;G{gB*Eh9@FL=+n002;WGfd%&t4(O7{XurLx%8|RDlt~<2xn>^XX5! zBY5pPS<(8kKg7w0s(eVDta9uvg)PIxlK)5BbH_(nH0|?T5+Hko6mkiqkOTsug@hD3 zB%uTd3FWG^Bou`Mgn)vLE}|GI0$CK4Vi!@c#SXlvh@gVl6#=`V5`2Aav~PCyx!bwR zo&J7=&p*sDyHj>{c4v0BJWvW>dXSq=JO09HLUZ!zovisW(?n%-rN(hW;E5;N2v44J z(AtrQb+#tKN7mYOwx+TD{w(%U7Dv1+dS+VFqwBNaRhia=Si%7Y+xk#>$baP9AsrYg z65b?^f1PO^;|mp&`K^D+$$aTw)D!A|Lz9ef71embP~!z9HT8s+zojRPCwRD8Z~iyY zTiV~!6FQ-B5QC6bh0AFA0=9|~Ceji50Sre-p~?{!5E0N3(rU^P`ap#v9Q99l=m>pK zgznDz>27v6Yj=&!BZN?QbN-elI7byw-Q8j6?oL%KZSHoeJMODHVsyqaO5lP|ffFjw z+K!BHm3DyP8-=3oPAmbNd6pof?r1gCU7y}or!Ps7slZrl|34vD_OWL8;9+_srOMid zeM0d>dZZpxdtdAAzEGk4S%0JDYD>k8*`3$TgI8Y`{e`Yln<-#L`t-kKBw{|R%o!t* zCIaA@Lh!6tyR$}w(4N#q6HY%%OgQJPj1XYjlo3MeS$VW8iK2-mX~k7qsNV9dblpvW zM(5%pDe0aOdU#Vh&q3_6X>>}>#=J~6k&wZ2A6uHX43G7xYzRJ$j~i&6$EpYd%*AEN zYN{|!$@w7js;`?huPq;B-5zRM2u;@R51*W*P-5jcq$s@V{y~Kn>IsPIFre5VM8JUJ zZt)8Pin~Ei0RxJ!O07=>2q-=-v;K!YMcX1W(6~r`LP5O&#g5ApQ1swi9A^@E*;rU4 z54}%|;opw1R?4AL-v21HAA$_+T^?n%u3)GA%TLjA za61FV8T+6;GR`14GR}DPEQvEjJsD?A6%y>@rB_-DlR$UAamIF~9wW}c zZPb}WYTQPhM*x`oo_S7gqtcp?-YMfFp380c`3aA4n9b7_V%0CT+dm}sv&Rjpg+f(;GKq+Qx}eoSo0i&LQ?30p z<^vWEuhn@Os!2s;*1kN=+6z89Ovs@kmPth{Q*f$?dksZwR>e{g8>u254WFJNQ5m`E56A!%qDx z^0Tw8(|wR}UtkI80myu44+!%t($}7o3-i@5pNiL`lP@T1$8aM-06cR8h8sOD7~w`Q zQWwLGZWo9_4!j`44VXP;xRG-~h8tZdnm63&1Oc?j#3TR>ktq-YiIe2BNo^EpCKU)K zt6aXtK0dT|)eTms#+H-X;`kw3N&pbZ#q&CASfrUisex?-3B}iZ?O2#+$@xO5FDmF3%48Yet1yqJ1 zVALw>Q*0qY!JzCWXtf9d=kZyqt+N^TFJCLm^?C4D+-zO-T39kqiMujV{2Iib^sm3& zuYTmmWxd#bQVS!#eSWnrHfE#QaZ(Fq`|P3&7=I=Ohz6d(sESbV*$7t10AUgBCLui9W8CUk# z6p>B?S!F~@aAZU}@*;^yMLijjju!$<r;O8we+v}}Q2ZG94`>dLVRKGk848qHSInlL>9-MIVw=;CCC=Zv=b z)i!~!eCu*k3m?K59cO*stKrcxjFw1qrDA$oUIQ-JVvW<-OA0OzuiUZ~7B2e;6czOn zPupgF$)`352q)%W6g4rB4UrR<4fcbbM@Qn{x_p@`PGDhHk zUct{SaVD7mR0Y(FMQVJ_2avLe)|6cfFQ!HCJv*$uWbmD+@sWqEx!QO>;$aBBmCVM* z4)BP2-_?>49x_Vu0~k>fh2oZ4Pr@918?Ax92Dj8G6ddCSHtb*VK7Z6Y#aArhqy7i- zzGN%Ze+Av_8J$@hx!pQYV^xG2s&0lRRX0NwP}MCnRJU9e%f-u5qPjIcs*6^tGXl&R zeDM?31V&g$&G`Z1c+#uZUOv@SXz(Nv0M%Cy84ry3Kt(2S??2&TCeQ~(XwI!s&2_H5 z{wZrSoqbCPq2|6cH20+{pql&J(A+syEH(Eh(Oj4w#OREhv%uqI=#>_}@SXBT=K72( z9xv~xC+qygJLPRzitcCKiTunPka1A!%MOy8KK=@R_TBRK#KsjnF?j{x1lRe}wIW{k zyfu{#@Ml!u&!|i>dg(}c>wt{T94T+9L;Kd8b;OEOVoi9*_sZMoR{`pK>Ka)xR zOlB)4*BmYH7?24lFVV~7_|ftX`U;)1_si2+wLksa{OQ+7`Y<8Pe8t+HShYu4(yB?X zNUQb(7*vBIu?(kn>ghAj?3ZyY@jw zBEqEX8)A%lc*bX}DBjlBfPBio;KgzG>yWvoc*+lV{a56Q+q4!w$hf#X?l*@_*l(Sz zF(;vh%X=$NJpg$QtAZO-NaV~}P57Jx*0$O-e$N4GM>a!MkxTrkCcbxv)!4+EXY$M= zFT7>VBts!lI$W!XA4#uBV1$v_#2T!v;!_X8{?!_P>UUD=8zuE<46=5?ebh4dQ}F+4 z(-^*Ha7=SDG(7D1bBC<0eYj!&hrJEgYIYG`!sc}$oCukya9I7=+tz%xFF&jBu?>R9!92#M z+4zXV*1YYk=9Uw5`|)*bj!cu_4vd(j8Qza zvbvFtLilr^So^Y?f1-f7l3AZxBYi0d)pv##L#UbUMV^~tCGCP!|r2u$jfdD*@|9HZ> zmvtreFrSo304kqEpv1oPK`>;Sj%y!IaIiT8LX~~#qe4BCnTW)bRXEvN8W^Q*q>~7U zqY+IZ9MFhp4P`_Wibizfzv6xM4Hyx{lb+3+9k2dZ3YZ=Dp&*Q?V<`5E-V**=oQ2wF zXf%B1#pEbP)=TnS(5#})ES9WlVZrO^Dv`K}-7SQ`#LXV@3llecc*+mpyZufD{TLu+ zv*btXbLn23e&lOgBJcmRbu+s_ zFfd*5cPP)^Vk^;q59Nz*ut73rbNN_i2~!3xYH88D@-$>8yp?=2Hktm_J9w+7zF`{~ zOsc}gwy}P!C-=F{N$^nlIz#U+fz6B)z>S-q=%;D zAx0X_?xZzEQlpZW|88yNLstb;oBe8|9GKLggfXeH`|pH?CpEyHm~j$mykc#nHg5aV zx>94$E4VnKSC&*O05n(OgNeC{Lj(t>$^!y`<4@S-8;&Wp@1M1P1y2o-is*g63X|UV zD^);e$FpHFPjOxq%OxY6*E#L8l55lmr$~KF7$5ntwPTEu+BiT0oX`mqPSOec0EC6$ z%lD~`papbG&!?I=aP)CxRV?#?3gkz4Xco))S7eiJo9Tm$HnH>hZfR^FMHW%L4-df^ z-p)_s<4v|SpCU!U`L7g)hS+ZNLB{pO)PKc;2lU(VVdt%IHGbR;O?@bcAYX&;Y>IA) z?AIwuKL%YZ(k$|7&PqZX1N{{|>H-A%D-@h|{I*82;~!APGVa>ai1@`Pf_A#G&$6PC z>~z9KcDf(H*wLg=wIn@6WI)eJtD)z_C8-ZoBwD`sSG+@3&CJJqHEIlB^tv^IQ3^Pj z)KLn;6le|PjB70)sPLT2q1htSCA*+=ZAvrS_Zo|BtV|jQUsPi`_@Yz+?SuA>Wgm1@ z#j+3DH70$K*Era~GoB>^E;#TA7ug4X0HY5mRP}+C$bfx7tDz=po7<9^57e6$nEbEE zm=>VOIG8XkFpnaOKA_c*Go}S76p=A4aQnX^hsWE7_>jbrxba``jFmlQiYxma|AJ?% z>?s}!iy8La|B8&(Mv-x49|0X~SXGoirw|c1x1&sKy#KQ3i{VwTS>!WKE#dd=r{T^Gza17+SYzqRdxo#|u+! zc^En7I$8*(^R3(83RYJ)#2}{;$Zj zt!>kMkg@B~XH-&TVWjmqE1yA&6ooneN&$TaMMg_q_OEz;K7&#~^SPpl4D(OJY-E^8 zcAl${kuXDs_~N^^78>h$Vtj}(s(!Z(w>&Ro!5IGq@e5=87n<N^BG0C^EF#*iyN8ad?zIKb)V8w|C_$``GTjL_L6D%OT7AXJ1=e z^EAqF*C|J7^lJZ3nj#fn5d*$vayZ{Q-j>PF_Os10KR|K8Vu$e)SKBV_CI@P3xwciY z(kAnhg|;GX0xz6u8^TvDTo}&ZIz6E&U$DX!&Q})M{u^=-`19c_Z8>~efh}BzVS_3= z;IFce!nrox*;QW|&R68x;aP#+wj_S|4jbdsXN5%ay2?v@@JR~Y^mPye#xg#%8pEsd zZ83cH+olM!fO`its`du~q4xhD)n0wKq1vAY*`6|=r?{6zwQw6i3?I>p+HR`a+ATwD zEi|nSe{ra-7r(EVXfll-8BC2&%i_CAY&oWtV99F|QsVf95}UmNM%Xl&Db+RRRVSFm zEI__mD-sZ@HF$_-u&qdsXVMm1m)X8IJ1E+j%89AG$&n*{&EqNf=IskY?LihgTe5N z)z;g5KNSfLe6xSI>`>iuB4KJAZ+V|BnLqg|{BNe+*0KQ|WZK9=`R>H4lFabKuUmEt z2O+$+0$TLsa#fM^*5{PgU_|KUJNPZTN-N!fe`HGj|ddi0^OkOscns z=2hDZ^r&hEDqERmUPkdQhau@p3>6id4Heabrx~S% zJPw@rl)r7+<|imm)Xig5H_ububmOO|*|Hj3bn9IN4#eTQ3K? zU)f6}-5KT$w1Qx)t&=1lq6J8Dogiu9DNRio=4WUr(p^XCTKL(UKoM`#T1fnWB>ovK zK;j1o@gHa@5o|s*ou;J1(Xh=RD{aHfX9ycP z+XP_ju8WYfP1DR57|&c~d&u0V83^U^`Z(p7n&Gi$b1W?p14xGwaqijNnwH=Qf)X*E z=ocg8-s6ciwj0g8X*DF>-5@=bmLO>;LDDW-f~28@ke+U?qBW4}41?-IT7p!e1gOT! z$?8s8jHIF1LmGECgJ=wPH)~A)jW7m2tt1Ej#}R7aM?pPf;J+mJ{WpT&u)&s}R42f6 zqcCyX}7Q9Se%F+6LFZI})f3J1AH zT7ri$TmXLSDn@yo;uw%K|oT_Jwc-ake31&L1xFyGu}OV-Ro zsf=m`If{bC3ep4>d1Y)>3!Z$R-l!g$v5=hPkERXf*FR`;`_{*WWS5nlE-h(^{zY|E zgt?e9t$Jy~5Po82Y96CdbTo?u1Wi?R)!pOrc0lB$_u+wCp{w1YgA3^w&XKQBA|znqQ;EXWF_Z z>3b;EcOr40%LIMLj|^BcM3BX!!2!tL*1d!2ThR-jhoqXnuSfT5O7~Yu7h>7tJ8Zdv z>d5sITKWnLF+>I*aaU+Z^Eyflz2%xn=`9z*U*Rq1N8&Dvxpfri&@&WJt0@BF(W=;H z;dQs{2&tX2)7IFe4dhi%+q#&GDV9(IM1fJyK;8uxTO*_7ULR;SYU70L=$nN!XuHPK zApQ8q&)E8y`}t52$&SM>%n##(pM`|p)wB#V9{u>6&)OFGB8hcHee%78EZK5&^>bhBoav zxHOC(?rn-qs;AUk$_aMby7AR9t<6088C#ZjlTAwzWQs)Zi_H_?k%qAnomPk)pd@dh-1Y$6*e)clV z|Cm2|tYSh-K5nngWlkn+WRMepu{$YRPW_Jm*xoYdQWOjqvZCcVsZP-{R!RA&F?{a+ zH3$>V?SnvSSUrTneh8gsUDcBR{ZZE_o;mBPKITdF5Go{s)`_RQVH;%$A|v{hlxV}R z&`Q#;gheaAk_hz-zp_UB692^SD#AugD?ZW=i)Hhhw&qDmqL4b8#sc8!Ds(h5CB`Wn zR~T8(&T2r~yckn`Eqr*dqdaiA@i>LxeD$b+;CuzWrj{G~qvdkr07by%#_Q3<3mk>h zZ2ue6RbLY=*Bg7I<$B{4iiR`ji_vlheH8wR8T26_Bi0)}GU6Db8Y8md7&6BI1jkTQ z@e9XL)0jYGXvB%!tNDP#5G>UnL-|K+ubJBl0-lbM83_V07*{`a8OG2PUz|?le-3~* z?n{o^Mw#;n8yrKiX#`?0cIWcc_icyGC8UUB%v8)regH93{}?%Vc76*H*~EIa%DuHP zunx!}hT{n67UNk_Qz~*r9iv7-B-ArTz-sZU8^7^mThF9i@tYcaD?+6f3_eaX*AS4{ z)EveOK5fVrQ85=Pji+4KQWj|H+bIN1{Sg5{Q_qDRn!hXa`Qcw}H<;dl_V0Q;BhCCK z#Xv{)n$RNIchlbEi;vmzOrQW>RX8(8+aoF@$*AFFiY{y(KG-MFz3xMQBnE9?dr*=U zXKc+rg3I+bp+f~0oA0bSK+yip;uqS#xp^S_M<259gl(IT{nvsIDb~#C0@=s*QwhXi zTHT-ra*VL_VkJ!Lo6o@d;b1I0f*$g(2sZgaWXzKxa~Svbk20eP`@o%VxmlDUSK;@TDP zaP8`m;?W;%)67rOYAEb>gZwMB1lPt;BG<-0*;330X))4=Vh?>B!U1*ETn^!U_+$_! z#b_nz#1fm6Aq@45A^ey4mCyJ8V#`a)5x?nRN~XeKQVg>1x9~%!ZHLSkX&H{?x@Nfz z@>?Dgi7=m|v~dtOj|I^@hKhqYN85`}aqEEfQe0b=;}^hH~) zX1+k-mt`1uv~D(^rL=Jv#8`+FI1C~M1cw1AK6PZpYkHCK0dTGOg#+MP z_%!Pe)^sz?eu*wifv+`2@ePga6>(T(sNF*{1kM{&PHa`6h18B{Y#*fQA#kGO!HM5z z&KHz#g#UTZiU|lgD<;a^7zRcO8t`dGJt~~1_Pw$PKf7GN)U*p6Z;}UzY&62eqYO!6 zR{=LDJ{HMC%vk;)GESJh3KPLGE;o{dtH;#GTVEyU7|6ln(cf|q}}+c;}Z%hehJH{o^h$MD>)#xsQgT9O@#fu(m)K>Tq*-` zG^#CMU1ZOxy}p?}LSyeL@kOJ`lHL&jIuI#;zW29@y-dd~p*+=;n9ff6BE!4^DD-A8utYxGefx z#Gg;GcVdf(K2U!T`0H=J)ZdLle_i-b`y9Ws=LynfQzG{2vr>yUDlMMb;Tpy7X#<~f zI1XI-;WTF_c9QT%9Ul899iEap)Q0e#ZSCa^RUUlTq+=5;jz8bd-h+KY1VQbc7XWH~ zA4=^VMeWtTlVNYEv8Z@8X2h%$bHRVsiHMg6XpSm9WUn7nsKc0yT0Raw%_6AEa}xSR z3)hOqmRQIJ$>{LNn+LOS>q z)S#3Fj_%R&!0P-=`&hln`d0WLG@MyZ4N2W(njUXVOVi`!wAAk$940F1YHzM-ckzlG z=!|uwVZti()$tgC)E`y%fqLOgCRoJnx%R1-ZV?l-YQ8FvUHp6!%U{ zc`C14XpiO`%iblp zmqmGp2rH_*MPI`7w!75cSJQuQ!7rBCi}}G4rM};SsZVdI0){PSIF37fL_>Vu1XCTD zef6%!DGYx2+FSFMe#7-=qb)xgYU?u1^&-m}?twdC1N93`dGRiVe9R&Q%?m_2|uzS6#!-KmK4lOr9I;sS7USHt57do@!6 zzt`eu$-iBADoMuN8wv8Rj*dx|z{oN&^7!t&XW1@-QFyi8rtg48iZ=ruZ7EYCZT9As zvIG9LUT-NMLi~snES?PLPyji^UhErEAQXt-0THE`LImR38KXzA3#1mJ|Lw>9rq}XD zFiV0m6qGR?e}1IWKFr&$kKV|0uo6-aDHj`*uOtOX z848f{)uaF^M|SBTDQl1NMU(6mY!Rt}G;cO&t|SFW6AF;#CQ{(lm3FhQysHl84Q0=g znn-(>L3_E8SCqnzkW$59moJ0kZ-YX9BsG!2w+4ehNdYo|0u(+hQFV@@ z{jHZaCd`7EVfM|=yCU89f)P}Q;aYIwI`?tD_Gm}J>XssT=Hi`a*c&Gb z6!}C%u3#_zX(Z3w_rgQb_U4H&LVUxlsRCfkHj8K2=a_pa!7W^z3#plwXy%=-v9~ex zPYmThzn7QF2C6z@NtVki4u)jwg^592`|w1}Wi>^i#QRV}G9K}MUTdCJHmL#e+W_8c zmOVo6ktpWDZZ!~!Cshj3XdIcZWQ9b-RyYMXBEi0iO;KQuekn57*FmxxOVUiZb2OS>$GfsRxLBO=J92LX7e<;%A8n0uZ5PtCLi z+J|@Lwm?s>wNK|CUvGEvjn~_EguDSQ<`ui`9od_t?NNj6leA#w@?Ii(WJb(|SKZj4 zWrt}GNVp|uV0#8Xy!MW<%+~@y4dxYKFTCrEU{&Js+NYK5B9=wohw7#Aj-eWT**#_^2tm zj{s0LS!${wdlQo+mGt6G^BjEU$?F_!B*DBKn$pSyBluj$mSym#mV=sx@YM;e!)x%8;z>33OS^g3 zmV>;rwe%Wp@6OVRL}GG@9wGpA)WEgqtuSm_CCg!R^I!H~**Jm)Bj(aR=55F^8tKC< zQuVSYospRApIBuZ?Vp9*0$h1zxT6ibmGDPBF8L=tt`4lneth#Cry}`J-^4fJku|L@ zb-|9xT)=bgv!}5IL@w0kHUXg8yh&>FdPAEpML1q#&k?MKYV&ES&Fcebvu>;Xf2Lz# zn%Qyr?b&g{6jk`yKdJBsslo{2;2;X)o5#Wx&@J2S9r()l{Aj*#`z7bug%(X8fpFtm zcN?|ork7l0w3{2if0_d^XqxREUKEL>=y#wn` zSfUo;Y}GSCw?>M1_EYwpSYIW|her!|_8>@i4I9~6eB|Ty6qZF~Lu0fF z05!(W*hsxYD><}Ncyc3NoSGlYPxW*Zuqgz8JHaOgfk}13 zB|1~I+l`=ts>=u@3_T0AbCpMB1L zME|=Lf2Y=-&dw30s5JN@tjBWeyP~iZbVdH-fA2Io{!@773-*+TsPH$B3gL&Z3gc7! zRCq=<@fSmdkuTY2u}-2A%|M;^k7C+G3-G=&po!=;QH<;&4La^+PX#$)-)UdL= za8lqw3j;KG5QC5V=(=u9{Py(xneXf_OAvA3$Vj3-Ek&dru7qUuk^S~;Jua2+EOA(P z%Qx*Uvg1>MsJjQ8Zg5{?hX3K_+7dyXj^7!C9V8#JL%4(8#BfF-`Mf&PSJ6N=TVJ1-eV@!8`_>eu)LL~KAr@M11rYJbR+C-Y|tpI%t zN^Q?mu1suanJVbxVH~&kg@^Efv_t zK*oWyPysxg8+Q8)2hKo#?}^hfJmQFbDZ58;z|o`C@H0p3z1brKj)q^8Dh>axR5EV% zkXmBgXfF$FOU*5r9oRdh3@N;4@$;ltVr3^{!G(9dBnx3>V$u~V2P$4<(rBP`m# zun&+CW2fL6_(XHTF?%Bm5!Pd+?%ru+0Fjn^D?m@H0d&1!f&=IV@e2pg4Y2lt(`@wz z&{JR7->g4?_8zxC&h8S}bO5bX01xNtR~x+E9awYnbQ14!3Qlqkd2-Nv_Nd|_29X_J z(^4L&mK2I{0H@TmzJd(?R_I50${HNdyQC62po2)FA3H`05c{AP8wXK<2D-PT$w8F) zz`SnK|C}XMJR`#NN18E`nzUA0!;vIPa3sZ%5)YpK2YgfbJ9{yMT3%)2@ChOd4xii8 zJj3Us@9lkbNF}55>GXp=Jv$$`)Ehoq1a&%m?jY=N_;`{rP9FUuY@7EXvM&D7{vzv1 z0E151=Y*62K#rlZ);NYD1Vnv7fNS4gS16|j2f@Vv(aLxI95h!^(ONpDJb|Sg(}i!Y zv&Fbe1dxud5rR}vbUpYm0f#rF#?B2-8YW!^X@bXmfgTxIL@C}1(EVy;Ef?HzWZfoy z;mEqJb-j^Q3$Ce&RvIAStKQzQ;j;5ryOpP$u|L7K2?6NfyiWlD?3bUC{NO%MI*^f6cc8)U12YJ}8`2#PRt}Yca(8u|G%wdO0Y-01^1$01ePc z_fDvDvvVCc{b_Flr!sJ-h}4riMH^b22ijsr%DjkhoKb zKu5|(A`^}jOj~sp*kqNEbdNt?2UWw^dZ~-Ps|g=`79zcj-p;0Q{M^-{I)NNJ*? zV}xFW4nOm{13tICrCBZ;?u$2ok4Om(HxCm~j5hB9g~54i&CR!-x3^`}Np%>3#-7!b zHbI=*+%~vpWlk4p#t`I3esbpPlb{4nVp}Q{L65b$f#;czUB&viHu6mNF!(FZWDfy0 zaEUIKv_#>oU*s6f9#YigX<_j#a7)1Yt@+!Zx)N$fX^yTY{TZPAu5)By%KWDg#}EtY zJ}*p4dYQ8Aik;d*Kg=%!KOb;@;H>Km~X2k-{2wk_tI6CVqpa2H9V2aOlQ>Kd-J39JE z0f0EZqPZi_2U_)jqfD;?q2VhkdIkIy6TrB1`AL@#h@7YdoV4B(P#-P80haGV>Hthm zj{izbQMT9et)lH2HE!q;oXoy5 z+VY-i3w{!&eOr)PIe-DY;zJi>0_f9}oCL=_y`U{$(-rpKElussSP?<=c9zzc7bZG- z)z6j66i_jnv-CpQh?|dt()MH?Y-y;XX4K!If{(l>B0*JwCup< z5h}8aEW_(Jt2U#R15PHdB9(=;!ueL<(3S5w5XShAHL|@;8FV-TO^N4K6DpsZH$QwtB zit)8rA1dM?5N6q8iDbSlEVJAuXkx%~yZD7xcze6xR(P?kw8E)5jvWE5aQWr2!czWi zu46O1pEMb*a618bt?+)s3OB1lPdlqGlRT|>N;k(4wnuT01{i>)d$(bLhnMG1U>_0; zG{EsExNq89>Gp!-u3FX0!N(R249A+=52642Ny#(O3l@|kakaLG-+7P@3Om>#+E z<{?`Bc!NzZxAvV8j>a16BjhmVYjOO)w1)y*PIesFrEs&=aWxyJI7rJ1z|vjPUd}?z zZH_r?0>QwA{P^~AAwL@aigW!pk_wpho2x2d60u;*%u;q2sfA=#0uynre+wxPYO*_Hq|v&!#phEWCs2P>c}%RCKh_;`b;^5QWR*@nt~1-tl;X zA@d$N?ZxCTkH<#}6giH&3GQV)bG)NxVu^s#v7Ao@7rWAU^{@{S7>9A5KVDB&Lq@Z; zAC$ufpje55^VCX*gINgxNDZi2Y!a_}AE|WQ$J4_x&te6xYiqoz1knD19o7{a|d#W9p^ zS70LC{e1dVuv3ELFI*%cZsECZ$1%1)AgO(P+BC-&wvQBwcE%_>mav5_Pnfz zCp}_pmnbaHB;(ElD_%A6W@^8p4`ufGdx2o+L44`)YMywFV-gGN2w-FO!km`gQRcMZ ztFGPx$Z4(ClRM(~d{YSAn<3E?I|fN-b?C@PO~WW&acGa56F6kvj`*(2AiHr>!M zlxrIk(%DU<7~6E>+xRRUPPB+GN7qmLEbEBxmO{#A)?7zFZ4Tc#*O6qNqlm!cBvn<*QEF?m!fPKT#(#4};~9MBxRH_8YbzICnBrb8Q1m9&jQ zl}!l%+~J}-^px5eH#lz9*xN)Bzxg6wS{Fr?H&Yhe% zOb);iSIQ|<^>BSOG*0z%CU-7y%w^%7lxbo&hjo%R8%7GSoA)$HaGKIO!71&jktwVV zDORSN(kVzcXLdr<6+MvJJt7-Ul8w04F<1v?sBg*)P1g?)$KP4($Y&IarfULxqeeC!+|Ee_+uD;6;(fSyr|Z}zP0gu`+*sjb>p9jtBl$hH~7 zQo9YCX1PTXp_2-xS{H+kg_yJ8uOTL;TK6j)IZa~P_%$jgJ`6njHpdM8i%$IHZI0IL z1VK{LejZHPAEmVX&)XgC64mr*d{p~mLaf&ca4QsmD*wQc{WT>!CM13Ql~=EjkW8rA zn3u`oJ1aZG9uP^%*nmj2?rO(dn%=gv-0})ohi_U5TVBM4dvy$<8pO}TEqw$-TwwJT zzc6&}3x{`oLuU+UJvM+T$aAY4i|XH#-M8BDICGLVV03C#01yA_yBi)1^J{w88}aJ9 zz&Bo{ILPQU0897e&N4c^cCF)jb~C}isPFpDGCI8${)*^y9jSl;+iFz-gU21~9pl;K zq!yBS1el2E^hHu2(6vXn#vMJ`n*8;P;O=6sG^^>G9TCh% zNaL>EbOONPDP|rvRX}lcOy=572YjS0Jfc5;XNx0WgYQ;8U6I0;6FhVuOEabWSV{^o zbbw?|1akH^4u|z8!F>>^LSNoDf5|LAe4Tj+Z>( zNMIC-bJ(Ix={Dwru<*5J-t|GpOY9^ehD|wUH02m6Ku@^(A;%cgUztWMa+VaU7X1;d zMWJ1=MJ6x^8I1hbXcMqQUr58hTe_PL&A?vg}=g&UX>}`{ewhiWzE|J zR9W-u`kpRmlK&yKy&b5%8l;VfWE%~O)Lz6EvgZg5;0R||uF^uar-jHx`ZmzCAs)K< zzkDmpMFsoaSG;`Q=NXt*!?RSkDZ-8Tk!OJL?~1VS!M?*f!C7V@6N|?|32%W8GDlEG z2bn8=p@YoLLI>%W{lT|uLu(yN>-)ubYaMs8QX(TJ3+)5|Ld)&6(kz)+9-<08GF5N7 z3{JCrpCg(_yy&=rxfKWbh(rLE?x|VEBN7=eIl8jz2?}n$1xAs6_UucJ>)1+yA-ssT zLi9;C$J1iBW_eDF!6D6uNKN!c+p^>#uxCgCIwB}QM+E5Th=K?q9np<|UC$8_4C#ml z@TfhG%3-3ibVMh`FY!;$lL6v)y?RX=P?dzUme$>KRQ(KfLo?!zE#anKc_AsliM;I7F^}ux;4=%3v8`D-DaBb1*X3ifgE-!)*|;ue zq$BvN2OaskGh2RG#Hr{RU4M9a>-PHMY`!?!k;;~;VzNSC7>wPW+1T%9!VY>W#?eXe z!!M51<5%;JBhU0;Hl!UgI;OLS{rO?@?hnRqSAgbS^OvKCV27yz!cL|JK+EXEsFu-( z`2phi;=_*D8HK`rm3W5)vRTkaBAAh;R7bY_V`%#(;s141fi+~y5O6@3q zXLIqb)Yt&s=Rw zpjBJ5+(0o`bWOVIWHEW}G&+L|CNHV4w5xU_&R+WLKmmW(Kn z<0Y#Art3bDBQJb?e;!Vw?It34?dv7bINmjWo0OtmiW0QT&q#>}PkU*7jB^2lIv%6> zM97k+~E0sY_`A>C@)JAx4{jXfUQ*(C6{u{{ETd156hDm3bgUV9HNyTKo zb9Z`g3xRq@u4q13jp5V9|zQN>NUw_uHhd8fc zZ3MotT)+8n&B-H+Q7fs1i_zhEaxq#- z3UEC;oF8fI#B&Ak`LM>$QI-JhaCZeBH#^tzLrt8mJhu`^J-IudkcV9xYjiD~j$SU9 zVdt*m_l7%561xfj?ZzY`4z4%-Tm>iPxG1}KM!NlPk4XNC75CKgq*s;4=dE&fEG&kogL@clu49 zTr{l`XvSh$US2v1B_dA>3~|vy8RDYF4-m)0qn+Ith2j$6MGzPwa|kuT0$aJUN41aL}>m~3uouV2Spd5eH)h;mJ-5wEuF&|1)%O184a1~X^7|oEs9z&m||6 z)~N~>qm`H8<=I@mdh4kuzR=-p#3Qe?-@u}}DZ#`xUu*!rZus14nsW?mMe2&lK5*UI zMXj9$8p|V}iosQ02DojwnN&g&8@oyO;*lWYrokgvEvbbP zJZ(tuIw=t7kQ<-X$=RD7C2+<2Y2>YS7Jqt)bL5tQeE<^R8>*>5q+TkNU`RJ~DqkHE z8zxYs2hzI3FY!-LLR9>&7iUC@`qV-Ftc+3Kh`@wsm>?#NnkGaeyBi77XjQJ#V(=-e z!aiW+A|;yW|EY`hR~Ya8yA!+1I2{GX=^iANxzUEbuc}5sQ$4J^N|0s>VQHI9N_yky zoBVJ?o`PSFS5}EUjIfkx(xHSG7|Z~;Bz`Sp0*Edr66{SJ$co8#{*O&2b!AEtJsySHaK>e40(L8y@!Xi z@j~Vz9Ukz&Gh$Emacv6<6&1 ziA^CQ`59MZX&w|)8rRCf&ZBHDLBzE6$|25Nwtzr!tctX?3F^wn?@<4;b*N-56?-U`|iL7*4=q zDAvr2ywarggu@5rS}HU3^cw8T`k!+ zge|T(`~Y$MgHg_6pK2KOeu%72jJV~2-`D44{vHB z!(JZD$&*#q-!QPO`3kbC!aGBba;^nfI2)IOovTsraN=| z-NUW{@Z96-3C?!>^GVKxhHSr};D7YwFHRN@$PlSeoe91C)cKpy#4}Qz{KKo9f3q&4 zmf`X)n>OLQ?o~4(I1rquGR3!AIDD%ml+SlNXYtePXEf!*-OgIg!5d9;_F*m}jL@uR z6Lf-oBX5Gxu8)ECo$kE8p$avP=mp*=bb302A70hq=Eb%C8ZDL09NJ56UcB?Aa|OGN zUIJ=fo?mnkemIryYEj8=To`zBDDc+z_wbeDM2JHWKzo?Dw$1twV%r1}=osmP<&_Fdo%(b*azr7+vX1OA9BNexVW zK1cxQNb!j1HUY(z*8zU=KBqh)TC>Di!}gH+VsQYEJk~)x!d@nDOn!dc8`FcI5;)8T z#>-6~_6`z@eBB#k5q7&klPdy#_$Qd!--7}XiM-rfMk16SMk0QIIKF3@bC{1<7>T?9 z_;CC|dya3t13d08KR6#}34MT>F@55KC$5iNP{xr0Y*bDkY*ZeBt43w_3DT&3eS$Qq zGZctM0Y40{C_ikJA0UoDvBK$K6pD>%4*1?i9bj{bc-WrVedKA5*`xsI$MMiRoue6r zBDtBATo>MPrSmLzS3A9r`fQZy;pKNCOvIn-Q{4=#zC5*vVw$gc4j-Sl03Zda$A^Jc<-}!SzD`ad*GzOe52^u~YRCp?m&K=QKtEI9A^`q~9l{*T8LvhlI#H zPa5pKw-eXT$07%Cytfk&sdmQw&X;vPy`Q|d6S&Trhn$^sJxA7w3s?sNvR~eqUTh(* z%PSc;O0}smRLF*#8YSWvZfcbD!%dA?wW)zYlQf^&)W@8mnomvsA5o zSN0Mea52OPAijGx)Db(iu3gTyo;ZWllc$Bp@V&d7qhnQ=v0t#lFymdG^_26<#MuHs z1B`J*7~H7Eb;d^oitCJ$r-wFl)rOjjGVJ|*!T`gQp9nyOCqD=%cK&R>_diB>Qrqo0 za7V0B0hCc^ZYq$@+(Zh{nYSvyxh9psaqN!RThx`GdD$7@IkS!ha-w-x2tdLUt%X1^ zlE1(Zy*XtlTtia=@c4(hFFFsg5+VWmhi?RV><%OOOE7uuOHO;p7(kJ^t}z8N*9CtY zPlK(OiG&z5XQEaSq%AWF=~`N8_DBwf&why`e#MeFT4^9o`5Q2dR?!RcJV8zjdp>j+ymRixnOqjqYzKp z1^bo|1op;llCPBhP8{jYG_Y1fX8BHEp)zNbS-jI1E`Unpd>*&id5>ODD4kIeK|#Us z1Al!BgLtE1h4pP3y^*p5BTDH>2%|Tm0Q5%P3Z>@T!e65m!X25(xVG@RO`}us_UMg- z9<~jiO{H}`&HSd{`chY7?W}{&;URDpch9?Ua3yfP+Kj`_4m!JskjBjQ!uKF>-bSFv zP-L#Pdw7?la44W2O7&6r`1&(JP@>;=X4glV^}aKcy%7ZE&-a~ed{8jMqqJ;X5U(ke zk=TfP3!AhmouwHWdNmPxe3$#1elixr?-Gz1+gky=gYv6C3$f6z{vv*%U;U*J{VLhr zH`N~b(3uxFDY5tRdSbYLc?n*7W7`N6#4Ss_!XIxlsewNHIRd~@hxgx~ z7EqkSt|*e5yB8NbIXglsqd$1NNV@O0Ndda=ABxa@pCWMYY^QxEdL`Hq>i-qV8Sfr} zO1=130?Y8?z!$wZ=h!`N-8(>mOt`AJIQ>+w{Ir081e)gOB{#nZPJFY?dFuNHtI>&hY8| zG1Z{&H`?^=FR%z*PDI2`TWYjvDJck+CfMBHNE2)&m9e3iCb&0POSkuzX#&!VMw&po zn`i&(OfuiC2+}OUK46Ghg4b0!$r9`h#_(OK+NQn?F-wq@H8T>r1hWK$D`pAc3*V@5 zsteS(A0Uo@{ToC$6p9*Oq%@9uXRo1Qd7r`6pN5_QU#soptAB^nd+`I5eW}qFE1;gy zhOc7e3_$D3Bh|gbN6#J*#Ju_q2x4BHp+Ky(+bepWS=$W*99P z7-zb|QHyQ!R4Ota;oEf9xj$qnfcc%rd*?=@O;c5yZ~;zcL81rm0{j(17<&m9-~o}I9p*Y@(hovo z#8dGBtMEl3t|1mOVS8DEkH83^;GrAR(FQO8_)2ic0N|?u7yyuG=hVU)x=lShM-E1L ziNmQJb$GB&&_wEIywuM~>g1@kcyIEfg>LHb(&F?)ZW7&TtFns$*RU25wux zJ4BJLVS2lPByK47uLQG&Q3(#>rSP6xwPw6=ge#4e`_~-fttrj~*8Uvf3enhH|5~$E zt$EHo{&U=T{C|6sy(jRAq7YDXLvUy~*%g!G1ue8lu2_ump>VQZD zK6{=3$n}ow5eylVXam)ey-0x~!;z!nR|0>xxvP6(y!cI{5t9HIZWE&sd%1H2U%e1= zjEgqdBlxNTcH^Is)6Eg=6H;AdDr(}dYEYuWV<~CuLqZwDn_mdPJK?fZ0*VuEJm1^d zWjwO+LA+}|YcfbR1-)hHAi3lXB?Y+T{kes!52H|=a`Zvc1z#K}!;0Tqy4JF;1XmE{ z+grFgz$HVZ(Uq6zQK;XGY8 zek$2@Yseg^&JU--0_i$}h;wgb+tRMupdkKZ;UM%M`q6=WS6jP{&l;Z<36*gd1UO}Rui#nNW;NC6VXG!2CcqVRb6 z;w+bZ=0n&W1~TWw#F8yDM>A$Im=!Q8_#S45-<=cLEJ9h0s~G~S#?|Zk9mN>O+(~MC zLjXAM4{U=i19&moqIQ&T?c(aAEfaN(RLx>S4R{-=ngyapkv^lC3fjEUdJWI=@-wX6 z&~RTw;}MX(zC!2o^VzPu^v{ZAzUCOgQKEnHPojV475&j1S4QG@VzR;6(s)|&148oW z9M?of0oWn$$+qlOZNWqhncYaDCU&sueQ&g4p>;i-^4-AN-ubTmy54#)#w)=pP4D4) zTGRUu#@uB{U!X5%lm3Jg=whN?0CWOglPMjH=}YLnF}+<~W0VSv=kj_FmT8oNi_OC8 zmv$e_*PI!X$?xyux|X*)KB1}jwU|vI?4hA$1hJLO!%POYVmA#4;651crqyGfXD}DL zX<9a)+Rru8$8kVTw6A>5m-sbLXd|Kvh^vNMxR3@zstw{725cJ!`)6$MKE_m@TIjkX z;5)vXFGrv>=}b5uSLAw=Jw-HxvDp&};Aueh0!2nM zrXlcaA3tC0>YTVoKxs6yors0e%*-d6hw_^SyY{js0?!C^gb5}-=8qgkYG4GCL;yHE zQ+h|RZ~?@L@-e<<72d^e z&QKqdHg=l>BGvX8?SkFr!l81t8?X+q90#jiGK9Q5Vf^F7=@JZa;=EG)!in?Bq5dmf z^-3gk8@>{`cf9MhfOF{OIN=LRh%WrZ9kxteJ7Y~)I+Gi)arm+nK182^4L*-WX>Y;L3yXU=8L)lLMT92z*c){#VQUUYcuc-?1 zX~(Nv1?&W=h0H!zweTWb#1xmAU%1-UmHp{o^*2=&7pOs6Ca3gU0K49lPB7$@K6NOW z(gli~($h=e*Dd@Ww`)k^VgaR7`g9@}PU&5yxn5))1qzwXlc)LPWvCjE8^IUB=S+8f zZDM^?0mpBjj5skWjSVDF@$8S*r>4p^rGDl8vt1d?S+6pWo9$W}r1sSMwTH}c_4KKY zTUM$Kp)x4yQ6gilEg5m)JnLFlV~bC#3_mn&D6e{H!cFW>!Ut#V6JIrEOaRecK{dSV zwf;KSW9$)97Z-F7l*o0*1Ec`g9iPs1&0`cQCN6y|N>-@fS0dNSN!PpHVTTDW5EoQxYCES1odFV^q^?)I zSW;Js#~)tea{7=#*~+DC+I>9r7FdE-T=_H8pufch_!RH4Lrd5UH-L;>}@b74`38e8^AU=*rVQM)BG(nK0j@sHmn4m0`pyyly$j_xLcm z-~>4_Uv4T@T`qJ|GoTe?0_KrYWXo%(-|qTOGbNY8>oNJw+p!daq@+zO4PwI`O6B4> zomW-6Iz_7?-&_v)c>ZLyYdwo6RK?st<~O5ab5%pmZ_W9;ce?J>2J>+%U3ames#rup zWig7AMRFQcN+y?0t6*~RA*ovJJ(s9QmCB8VE8wr#8d)y8UR*5-GBbH&mFs-vF=CZ~ z(^>7BHLfWk`chD#$jk?N(I=jLgMD1hu;bHF4)q$gN z;?IML@F!pVnUMs4=7>KFYr&tT;?J7e@CRQ-{=5!+;S;I1>cJO2r?<8~eBqm9_cwqq zd{Any_`>IcS~i3)d|c$g^rrBM*E;tQw?g8*ns14#W$+@MIC0+s-g9!L4SeBI^Ebr~ zdfd716gx0*Z{2ONe*#z9H4%8h`1VfWRO8%mtQg@Z_T^E7Tm|Js{eYO4cvR1Fy?DQk z_Rj1RQ30h>U&iwH7Y+>L8Dno$ z=5Z|t=JDmX=0wA>)?s1%w8tLFuWhpTNDD@F*_~457jtjaEItMu?YYhN*V%7MB1_nx zQtHLu6j16s5f*slR(oe#ne@3?-4*4}r$3uQRw_1ES|8)mM>ksa*uh$0g z?42-XXA>nvH8WcAV|BIWdS<#DXfB0-m4rtaby1UH0ei=m?ci$7n5$ z?|R1Gn57Z2D-PMyD!V5O2(7oi>GE)2uXK5MYVIlf7B-)hlLr1%3S92@XpK9&vk`gH z=MqZdj<_Ch->kh4UtR}}e}A&aK8QatWoSkI)E@ihkljF^M_vS%VlUxDDehURxJo4y zcMxcd8`8p-57nX#np}ln&2@zp|L)kg6)ASll=`_MggW(rPGhx@G6O(?Ki-5D!*cND?W<6M z8QZdxwE@y+D51aT0jNJMpKBhw{Vog;s_$icU3MR#E>%@WK&Yy2rSsICN>$MZ?c2(? zQ^mmf(T0R3@_j?PHDO&9T=qr#qTTi2*#4MTVAYir;;AR>!`Q&U+>tv+i`?l(%EUhY*(W+?4BWoCp=NyEi z>zj_+E8RJ_a7Fu=W5CTU!i}t%tpY-8W(IJu7|!5M8z8NC!g2eja9+C4TD!gxP6s$y(jO_VqkrO&s3r0q;5#K};WdVLZIq2pXO^ zyjc(W130`HOGgHf620uY>AdiA-Z1{zN&B*(1I3oR9Vq(nn*X(b#A;=zCI}6GL|P36 z@Hq+hhFBS%@V0#rOHl+wWi;ZEUnF#hQ9v(McXEb|7d0PO5%y8OW3R{;eNruoCy%Qb zCjVXECpD6LQ(LfJ3Wu!a$fR~n^zIoluGA%ir#@iMj13~6pp;seW%9`P>}@Kx1T-p! zbBPz;imc2?DGt?MORt*2^Qsv`tBTw*d^1ISiGT4*AfEdCl`6d6DSK3WvPht|8z%sk zi&pp@EFeC9%D$P+AW&}?TrZ(|VBu*h8yqbb0gt5$BIQPp4=0z4L=qZQbx}}6h73_m$&ew6m*9V~ zJ8(0P{Ky{XPa$*n;6^1Nv3%}F_P&g;BGhi(*0uo{6&vsu!LQip^+bl8VBeRi^eQzd zTwhegEvg8dWyfWrObMh6%2X}06q)M7b0T61!Yfk@{0}n4L@5kD)2+_0e*()B6*48G zw-lqedyCegsvwvo_F_X6Hd2|ne@2c*EebHV}p=&Z_kvy%B73;ne32% zF?a}7bQzvZ*=4+tDMQiF#hC2FpjqDsY~q2Vi-D<$?mkU)NX1Rq*8)?oH+rPINKI)w zygxh&f`R2ym{lFq4!}~PV0+i(6T-0Odv^}TcVT2)k8>p{gtMFhex*?BWrI|U(jk8QWLNJ6Uw^1wGY6K^jE4@y{WMwv&%bK#sHY8-+iB7i7MPwL8=k~3j4$6x zpEeMCiRmg;_IwYQhJNlq*-In0# zs#QLVm&Q}C+v6CaAS|IF&sZ7SnDrreu}?hRET^9Sz(CnCwT55OgSG%-aCtr>^&)We zkedjIjd)wHXhzs^d?WB<$MLQB!j9uxkR7hTWu)Wa7k{>24bojy{?)#k-S+2kMA}~p z;3c?t-Q9N=>7FZ$fBCPyEI)PA-jkId zq1EIm<&6~ij!WDi@n%{qZ?;8i&pHIn4tEgJ?AZQ;2rVe9_FoZD(e{7w(WIDg#jb4r zHwVh*FEY#KKSq32-`sQSFMFO=euBs+I{`mOda8oUR*G|+ z2|Vf+%yCE|=}12jm>V7G3H+~H_G^B*Qxc3jpX1!mz4cl?;z32xa*lQ=2Q`L<*I6@8u-AeVsHYzpBz>bJD%IOfEVPC3f(xF*Zvt$yOMj0D37&dt)L&_7eb9He9oz%Wg|**Q1iF&Fg`KF zsHy)oh%XN@YO{X=8Tdmn5M6?SGJH~~(OMrfh)1+B>O}{qo*+~Jw~xp0>#ueT;|XPq zT3QX>wTuCw|16)e$j&i73;W)Zlp6UcU2JPKtW=WHAY8%nml6F#KdAu{%frhVqZk1T z^S3tA9TL)7y8&N@iW7%pI))i8<|LeY9mIP2kStlZLsY6&x4C~L*0W8>vbyMel`iER zSDKtNP)<>!MK|=?L{965I-n?4>LUCo=A}bWOp$;E5+P>o2qT`q@0b?GNM=?GWBgGT4tXDwBIp=@ zP@1$Ce6@-r-l;6~i`m-*ff{+<1Z4}~{Q&%091541k(NtF9@0H|2LjP2;>c4i8_W(z zp6cQYN1p20K}Vjkd`cx_Zjj-pb7f-?Oz5f}7fINf zpyIZUaJKgJscD!R`!qK{<8dUTTpt3~AbsT<0$8{uIcCAwgquw#a3OY;@NnUHf ziOZ`+!#}Yt8w|Hh?v77lD@ak)?2^)CTrXv`L8If73MbsJFB~kVEejP2@0e9%Vhh^~ zUJ@^3@we1@sbbdF<2X;e!?9wkyJFY5qgFCydgZbj8Ts* z2&6x^H2N!i^e?o9(d7T4&+D}_rZFNuX`!`-NE3;IU&}<$wIDsX$Zbt($q?lo*!j%CBD$Lcxy;W*8;F5g*0&glE(kn-WXB^=eyonlVx$2VWh*|5|`7g-4d76 zy9A)&-|x#i$i7o%B389St--1phx-n;DXa=U?zfFXlu zfQ#LCI*TXU4NiY=gmIVqMi`$_XCUK=@v|a%ja1{gh!{dp#&CX5HR{0JJiePzKO%{y zYW=c?=?TE?uB?7~V>|3SGdlCm-Ho{D$|4(%m)7MtG5o>qMv*`A{Z|I3C6vfX1(w%b zFX~|wMD(JBK|N{ls-!h0lajokr*TAc@H2hD@pnF8G}H3i(&B>uN{S0Br`?W|i7MG7t5tDs$jno!wyn;4_AwU0BU8X$ zFKrF4))(r39m&s;vto<0?Z{bg-oKwwm2hTtZmR@mRrr#A#_)($6h{DiR`zB85A1nP z^*8Ek+G+k<8Zh<&MT(4_vKadu8OyDqbYM-*-i9Jz-gShr4&)d58w0Dap0~Pi^{mwm zWREN|_>4V(Q47aO$!JVaJ;Jq0#z0~LmhPzqT+1+4+))#+4A)p2VXG=^W4zDS#40>; zvk_H1(5O&>U(FRqi8-R2i(^ zva;RkEuo0mTb9yE&}|QYe7&WBkls?Hxsj-l#2o@rUgM@d%n%DB@%-4Wp>?&Pg1r>J zxovc!t)c-=$cs(u^4w=qBgzS0pw|D9o!ZdEq-0hguwbV)gWqWD=pp;GSqdt?uuq$C zZ~C-K+~Y9LmG`3{Z+X0MFts);oqgpr>aeYf0m&A=Ub<08)~Tp#R4DJdditGhBSGWo z#XHY-R*0ZX$jwR=;uU<`oeC~?aarVM4mV=)J(jDec%BvcFDOMcRj?^z~3bALGB zm214HUp4s9JP0@aL^QA>&ls-#AgfhG*ZA^l1Ecgm41Td{b_@RSFk|MOx1(Mhc&lN% z3>@WsT%ihs51&D32Oa6r%mDy8>%Alxfi1w5;M(~MhTNCXbEL6@SKn^f`SOv*SXM)n zAyy?`6RmVaV5W%T9CCAmKq7W+d?69xsMne z9ypCFzA&tTZIDB5eajBu1RY;J(;;`g0b2<#2C_v_mu?kz^|mEiMepKSMooEJ{X(}f zFvK?9VOhm=hup|kFs@-Z@11Y-;(tsu_JwQ)S$M&2qcPh`q!PxVZ*&OfyPy6ns1!C| z>0u6WGCT>c?=>p%P2XROMq)`P+@)j6rm<|qAYjF3+wl7A0Oe_J=LhHh5P}u`J^9= z_Wac;Mz}VEqt<@2v=-u&Th_v$0#?Mqh;qAMR+!Kogn_>^68OKH%}Bnvz__!uL8Ux#`*A z9&NT!S%c-<*g3}iY!G1qbvOX-#T1t3k~-AFc$WghedqlVRw*1Ua1|QOSU*Ay^)xY1 zPrWV9dpf11jd{#?h0P_!?y02}5Nej5GzLqp$Ofx(Bb?Vys91Ov3w z`paVbcc~;#w-rWpc$kjxc~7;}0^}5JPLLy7;)j3f8Sd$~8vOeZ6KM0jZJeFBxl;97 z4ogvEq@u#1*OC{orStKH+0}Udm20i}U&VLd-4EvfhYBh@0Q7M;-nFYIy00+adb1Iyo#mOE zjRx$pq9aBfYZW92b@#WXd~rdDC%+gm!Nr=t_TBNf*WZKcZRyBM zJ1a`!-G?cHi1^q0KA`w6@jl?UB0sJ3(*htFH~5)PvYK=7ANzTZY%>xx)`l={nGK5z z#L$vt%6JNf#vTOVEfw!8WyLs1DR3{h+G9LtpEf#bY~cS{*a}|w6~yz7$OP? zh2{wL2>NQsmoLev6+2eo#vq$pd|{By?ZO}%xB>vdEoW%7SonQVvasdPb{Q+vh%NhU z^zNr4y@f{@<*EOyQAT5r6WL|sF!MU}SHOEtmk-`;WV2O@0%;Wm3hJfnUg?r+gZ=jy z&$3-A0|%4O(w}n4b-=Cg+rW{*j{9eTVEZnuv3^+P!h_H+?=yz7PyMrI>1TnG*yZ+} ze}aVrQgN5t&A`)Ua*~i)`!on7!a%AYI>^BNrw2ssz9tW+w6c!^S$>J2|jc zu|BRYdrzecJ8i{r+ud6^(pNc`BX6ymog;6pdLswdtJoW))cz+Owd5|lYdN^(;08%d z{S5XO|7cyFd+M-^i1l9bdCHLqUIPdXcWT7%G+2LM2#As@T=B)RsQfQc{LWCrau+R4U0a z)L%)xhe{>&CZ$kGxb!v|knXRWmK07>QA_z2y4geJauV1ZZVc1`AF7GsLp1^Ws3t%5 zQB8r6SpMW&##~0gQccYP169+fZyP_egM>3M+I0OTOHD7S1WQd5-Zfr>2MJT&gOJvT zDwQbdeM_n@l#=rLI6CO>SW0?_ltLw)UQoNCesd@~5*&(yUlJmm}6@~6U1b#rNT!UFrBgBu9^H_i;L zE`G%-YVmv38|a-NW7pxeSQmf1!!>x&$sc8(T)c%!7=HeM;VlIgtWnA>)+lHiYt&EE zSfhcESpMusMiC=mS)=g!XegZK`x&Dk0?+HhTN#+K4%z=fDtPk=mCkW ztys{c@c#U#p=pVg^dk5b>vSt~g_HDMFAJ#byFAc$#c2A+x%|oqM>F;b$uH_y zY_s!M-`A?LD~xgsg=GQAAn#y{eOHzCji@u>DS}Vzy|lMPzHa)<@V0@)Ag(o6%u{wC zI%Pasz#;@xb*^pr?k|m{dc8b;ZGt0-H6Ufs5bNa0#@`~(XNaNsjymzGb1yGFpF~n} z)dgcDqX6uy67r-XBjDHK6OR|rVZq0n%XbDnmmo$l@N(Fog*@MVZCuv$3BWTPFQ^(c z4-88Dt1F!!h^0fBmn`@wxS~2w&_ri%zW73CZ+>3s&K}eRI(tQzjeS9#z31;H^nYzt9|^!3CmA8h*2;vE%%;0%fY*1OlNPX z4AQ|no+ll=!+FxN>R-)OjxWDzOk`gKX8jZp3IFYie?miE&@sIUtS_Q-^=DurI#*B> zohzV%o>35;2tJi(v_H@Cj7U!D85QTDXH*q(Se{Y+VelpXl}DxypSV(&7u_Bhm9R%- zp>EPz#hm3PVcf5&K%fTZ9wMBcuqLo@BbCc?lTsB#bu|&41r%HI8c-PQ2=?6kMNE@T z|J>=i9cGGfp-Y5aC0OIyv0fdc`QDqxHhs!4*-K4TdEgxYaB3zGlN~_8FxdgrAI3%J zq)&kV#WgN~9J_Kq(cUV`bR@91ND1ZT{W1)_yqhEu z6>`JE^siC~dUr5%$GFf?c?ywFqMBFA_F4NC z7Yl+5`)YjXkOQ%vKg&95>YfW_9b-cx+^vHki&n_27t~UCVJxf$!8;q_#pNAkWBrl) z>vW(3QEXA<`$^0jAU>apqyj=~lf z+QPL;JhYl)CnIIJh!PS@sUkV9$S*coTq1;i+)j^Zvs7f10N@r9#!&WO@SaWD}a z#XnDS>*rZ?lc0n26cHG9nm4f31ioH*mmFbN^%+3(@vt9=&LU9Q83^^PYds zEd4DYBL@7>{1dEj3Z&wQ|9xO8j`)y@Bfggc25j_^KEs#Z$8C#3qho47EFX+Be za?-p5DpXu={?kYq1Nn)RQZ7W*QRqTc9|as*ZXdc3v7;omI-}$m2H4Pr0Bq<&P;B5r zWNRa(2jRy$`dEPwD^5hf(#JXr7=(}Y0Vu&2CmKrlLKn+9N~*}I5-b&AoM_r8OGndH zI?>U?mQ-^CbTny{)X^kTO2vuR15$aUlq92;)>`;>NG-vYF@@b7EpUczeI2z};%I*x(&G7~{*Df~g9uK$-016Q zt%Dh1kO&ZBkSGwL2ol-4jfP5W(6}z^K`{Dwga`M0X!Uf-r@#xwZbgUyIYx-!*B2og z1sO$zXpBF~;o1m-ZSrV&MfncCHQmulNR8DlM44lZc`EJX{ZtA$h$XlsliVayf?kp+RFw8zW`! z2)|19;cRmtW;`&pK|rb4o{xq)8fyA0W8~rfS4k;fo6=uKCG^uzj!}chReJ~RMV>hf zrk^j8LfGyLYF6m3e>q0Zgf5U&>=r+_u>CLw2M_2L{~7M+ufI4(Hu@6S_MSI}XgdF4 zgrhkN8LKP@XDsk+>O`v-(JPGgA}l}3kt+~l1EmN>1C8CMI8y2zfwL=px24VvN}V{p z>Ou&E$;wz{L`MPjQ|D`A94}}#V{9nTtlGUg?^1hC7;jqHQQMXap#6VD*JHy7CKLe{ z+k7I7lOlu&HwEWg(aNo`9@Ta7s^c6FF(*NT)0`3+hX}k@^UE45hRw>J^zn|(8tfzg zX##Y~>j(;|@O=7^V^gU9^H@1o z3z~<2H67+^)E)HFgBb?Q)oR<^lXIm8<>Ec9VivS|iHW|%lW`{ zH}=5#V))%LsBtC5s&%FWP@``|P~#xkC?XJIO#}#74*hQd2I1qL1SZ8qpvqFmFD&Un zkW9s;)AfW0r3eWm0Yqrb8$MX8j^6q~IW)B;sVGOw2c;aT56Y2bF+ab~(S(R$trY=! z6oa6*#0Z4M@?9$&8yNvhF{%RwOAHJ?o&a$~@bP*06Z?g# z@NvB**G5tZPN&J^& zuWf)qq3$?8GqG-iCfR&l*%rQIqhmkZ4{2<2^knTxIq==;@PbdlcS|KuRNAqB3m6}= z83@q=xKmL{WkpTfjKlh`(o!K&#GyA6XTLmiwm81l_@+$`u~A%*5bd8>qjjbB(Ek@) zUA8%nXzWo%E*Qe9vO}3B5yk{%jvsx>F)*QoKvawJEhT)%ns%tfW-+|ENic&W+EGBml_~nR8X&S7oWTP0kZhYweCFfS;t}a zrXrvMkugEYx=-@V=NvDvFGvC0HumW_92FrVzkfHl_csI6Z}`%W?{PfI%8yqTj3LZ0 zzM_c}oV>d2;`FniyOUX&u|esNBg5re%NhSBm4Gw;W%?`QF;Mra zN|1B?m!)~AO*1FQ%MrT$c#PP=6b|f1PWT0S9M$~LjgTw z|3q8kxqi&iOJlbPQ=s~E{ZC7bKUIPhLyO^)-f`4pRVIK!NW2l2cDBAQ!V>USl{|8m zG{IktiXuaAff*(6!;BIHLSnh=4aYl-fTaMxQ2{sz(2O@f858RHtdqI5}nk%B^O{l*0T`&q}+ zY$!<(Qb#DM&56D!RD@QRC;jDU9F-@smykJ3pof)oKKi#GVXFOvr>rLu9fPOd!(X?LpPk%=7Yj$0Cg#^5-sH z_gG5ukOZ%iZhQ{L^gc-lP|~|WlyoLI-#`ZWCS)YvGW6M3z# z9DUet0rb%$Q$4@sk^MZ8Z(Rui43I`dU7B5RWazANzA`0@0OA-EPoP2|E(Rv8GH-dw zvD&W)7#UopA)dcf+;9Od}ZZyaq|+W^!7yjsp)t9S)FKk_5p#=@@%WD%mmi7uid6jC#r>+2#outFIyu*;h4#tS~wE zcI7w_%<^X}% z5Rngx>?K9sWQk13SRxaM6nVWr*F}FjCb1vh}|A9c>za$}m>wki9 ztxXQf^<|4|LdN2nKqS|f{JGZth33{mV5PC3W|QT>+l(YwY!`()`?6jH9>8^v$tBIJ zPjIe*3JxiRip4d7@cpsQ0UG2a)|IC_hp`#{Jf!PWEvBcE1h1|q*__STGLjI$_2M90 zuL#aHkU_2q8H;NIk-C1!pY7*Doq6mveyLI6@N8J38cFdSF>7{T;~!BBbk= ztkRcA0+znuU;2-7&N;kEIj0pCN!QBpGhxnnR_-BH^V@W~)*Q0`P z{a|peGc2wN8H;NIkzA+wbKNu2Sh_7S{wKxi0c?y(Pw(46AKU7yHJaiFEzKL((uWkOVZXFKFo{ENqH0A+*WRDY9TF zNx*{o6mJzH*@vnC*=8gYmTqK~ZbTBWbbViGoG8Uqb3VlekxW>6z!ceY4Il|#U5}~m zbh9xeAwbt7rWKuXw!h-M&ACS@1SiyR4&(2{`?85SN_>LTJ4fNm5`4&Y&>Z$_M01w; z5QsFN{{A)bMIzYnkN#q%>)%^7@jXfK)}NOBNBOs;BBDY>_L4Or(94=w zP#Y$1)dP?c#XwG9O|+@w9LSf|@>9%(T0X@@H4REk$b>o~GFdtz5UHcf{yHkE=RCl2 z{FzJF9S=)ub&v$Fj{d9<*7^`h2(Z@thf7-P!$H{&6X?kVcToURq9e%Z(@}UM=P0%z zATP1jwIvzg^&2XK0^v|uL^w-X1R|9+1hR^yoi*d-9nnQ1q|{A+9HL%g6{T>zT-o^| zfEl?)cV0lfvB0F7!`kpIXKGK@|9Dt#Q2L7$f;jhZ{Ws*hpB^$*o?L^t9-dtL`C+-T z^Ajl`bk1>pbOowPtn8eJUyCQPVp3T|EQ@sOE>Eu$1^tzEha(O55;n#9x9%>>-%oKi ziY+T9$Qab`G!?!usNZR7sX_f6Eu05}ZdHEi?&I`gA-krhek*5`#)b%HO01v{Qc&Ll z!M!5PTjo@ZndT6tUA`-#xjtp8TtL6t z%Nfm=e*-rHUFikg_Ugbg%LB?x&x+wk`#Ym}lhoOf;;RXJF0jnbAZ4m{aL!<_2jtX` zO_f`oKk!em_6tKQZb-fmn2P&_Are(io>O~l1#_Hu4!n+O}|v#hfiU#Ai*#t%rwUsef{@fR(|U-M^tpT#&J zM8^FPBIALOSf1L?*`E=xWSj>uZuAF@|4GG#w$Id3;|cLD?TDM zo&eXG5{kPf+P(*Rxwnp+EA7+}sC-gFC}VJt7w%Mv+pu0Ff(hyj~7S@lx%T zBpJ1`)Y8fZ)QSz7qg>Dce0aY#{KCH5KKhGNs|NzhKW~*k=BHH~upw`;ru^W_1&EJ& z_7flV90-Z!#fI|*M!-_fX@J49Y}|~|224Q=k9FZ!43D*@$ss#zy0QQqOd}5sWlR8l zEn4iw*ljvLwbhv(%9|8L)ME8WAzY)W#gFGX<;G_{dAi(aQh{&I0TZe*UFy6BDdSu8 z(R)uvJM2pm5#a*_VU|SbYyN-{w^9ekI8I`m5Qq`B^Y~bNq$EaML82H%J;YR3SPY*^ zc+_xbZ#cUT_)^qHzB1EMu^QY*G2CggU8+W1o^Qk8!q+R(-d1a_|k_bgc6TdxPK*QP7eZkE0lJ zL-P?3LB#g=xMAGD7BWMb2{wuQW?)C5SD4|g?W^OREh{NTD#|G9 zKht@O3C?rupVB$8a{dv(iEmS-!f6Tj3dJQhReA#I;%QkI!pMaW7)wVoUj?(7pw$7C5;>3?Uerq=;*ZybFEy+SaF-e! zA6K6xNX&pgz6)>#gj|3t(%g72(t3det_uf3`Lmqe@BF4Xc^hn&|7A-s*LhFe?SvO% z%@9}8;2k){;?y;s`JNyS9^uKSYGPj=Zh_n@HfG@Njx^z^44Nu06BjA~e5?6>t#xm{ zWmi%|wqJ;WT6vbQ_|$3LySqn0#g}M>iyypGk38@$@qafu%kqf@&NJox$dJo-PxBRp z&N}P^#f9VzUkX1pL-f{d@z%~c*W2C2o)Wm(ZzJqh`06pZf|s%)FI%M$uMY11UN%Y7 zb9=7yQ_c4K4C|uR-)DGI=R5mq@J!y~1u*lk`KYRuq(7a*wK$%%3ikQnlUAz(p9pXG zsJwu8?-S0)?%et;ZOmTjtYNG2sC5f3eE7`c_)2GbbVmW8UUX%_SvNiEQF-s>J5M^l zh!~(s&5$?4cU@npj?Dn9Ne83rGN(%CC>~t)U%GfBAC(7h+ViL-&X)H?K-k3dza`H3 zj4;YkylH{r^;hDFTLCM8s%K~S=3TxU7S5kv=6qXU_b9({2m- z_K)(EH-=Z`bIzM#Jb$AzlAl`PY&?ju8>kLwJLGdD(7?T9a3t4 zO*1|EnrM!+>i?@sfo`-4Jh=!g;df}C3tWBmUuVb*6R*SAC@xG4(w^McW^mt4$@k5a zHzn&c6}Q+U;g#FB1+8|t0s7lOJ}BnW+wKc@+JE`3&&C!q0g=fC!Y{}AzP-yXec?vJJLEC4_dw|KWO-F0ic!JT`*|fuHAK}Y}^HBoTu1qQWWeWjpx5y z{Vpyfw)lc};3WrV_)>R*ZZb}HjnX^KlnpMoT6{Q9{*UvD_7sob=4{0~Y=MC1v$Ffx z_J1jJzf>l~ox5!g^yH4ZL@M+I&sT0jM!2vpz(C6T_?QlRT;=RS6h6vc*BBd{pk ztmIS1TBQuF6MjoS8ZIZ->WTmRX|+XmcwlvDjV4kNcr!U|6;QY6N!I{A#HEgFcR`e! zWbm|q#tHlR5@)HV2UcobP#UkGK4;+WFMq^(Pv;Lm=Zu3hqAQ+*QLnioB{_2>ilSJ z-erg_ikbddI`In=(i`!JqKqV)Xopc+w;Fm!xL_-6aKG5nd5Y&1zHS%J%kKl8X82>2 zx28@7qIhfS69K7`W08y;7Y8I4i+fWc6&yHT(4kT+6W?CX?Z$qmy)>pEJR7ga&f+UB z4uNxwr=3mHYKW3}Z|aNUOZ@A-H&uL>xHq+#$VK~xY62jgM(E_*4{qwoe!-ccMI5AX zd?yLV{S!jZV%&d2rDMa@kIxb_qxO|bxHRw2!ZANYFvyR`$JCFmD#}tO4)VSSoVOUE zi9>ioiHrvnRT!H3=B36`{sAjC4KOLtlyzC^uc8P}HExP8oNC;hC8rwCibjB&5wQVb z;i|J_yNWvKTpZxlu4vJwhIknyn(tfaEWZ352k9O$$iH)&&QJk;i!fiK1;m zTK(hB1O^y{43Nk=fFF-o`UeIvYio4dh^_XUR!tsOC@c zM&59Ek$cdT5MJXdtSx**sG&=CtQl-l+{x4a3(*_Gs%(HINIa#ATMdwk4GO?Elz=+5 z8sJS)1RLOQ;tLz#Z?mxh#sq7CWqH)w&fEU8I6OZ&_#NjaR&kC`%hJ~I;%%m&Ufa3{ z=O=MoyPp?qbXMgx-h)-g8j6f+Xt67!^c{0bX?`yOx@$vQ^Tcz`PWrYva%li)V91)#fY2b^s1^|j ziRINlaW-HCENVtRysSS7xJ8_LI{b<_^;D=XacJ--!Xhf*iU9a2Ao0BOydGA-j}10! zGghFg>|&DHuDG1uL@!%VibOF5^7fBB9`(7iqi!p}n016rA+hHCctdQ{0(nDhbCoPw zfu**_r4hNm0M!P!qT!7oKtzPGOA^5=K{5-hD?tVkB0fO|lt#lP1<~{7kn2H!5{9>l zI6~vFuDLR_G5eQj_IPD8UH`|bf-9;D@QmbA!UvKU_vud+@I04UhwUKw zm3p?7#`=DrdX7~!>&HJV*uq9=-K@8npzHRHvyf4MGN28BMi|f{__YiOPfn6H<+=W? zb5}^jC4~@vg?Zk1MY*Hu`2B;;^RsiY)i z()aqR0Hc8X*sFSYd>aWPY}?8g_Sx^NYR{6`^`C9!@DCPff?$%$GqJ+E( z2>G?*X@k&$XFK0I*O?7DquLPIIN$NFI6_jp)mQs5@wlR9xkVckM7l+51ptR6 z&=tOyUAvt5F5B;)&vJ`)KPKIx-6U1GMR0ky7H-yK?+~~ez}|eU6er^BWAXrJA(-(w z@FGsY|MLg;hKfbUh)}T{qd#P>I4Xsxa4AF;W9e z0Q@w7eo@1@(l2UE^84J0`g2PWsr6jBfdWLroAYbWm5xzug@rmsX>cQ~xH^A;N+ym` zztX4}bLARxAy1ArTk1dr9itLN&@q}c*K&*=B1C+WOe~GYEG3D$Hw`GEV?-zs$EYSD zfR0i8Tv-PUeyut{$7m19h>p>-0zm7)vpCkQrs;3Ym7dX?q<}K46Q%Kf#;2d7Rm}$R zMZzqpXLOXHvsE*HW)y&)QRD~VWi*TXXBGG87?D=R!7-}k=@DlR3t_g$m0^itqmm+P z-5B!kT=_zA{Y3MJh$xlavWWcnxs1QFEhd~db(ydlBqonNU1oJy_uB*xIZIF_IMm+= zz1rhwg_TQqEA=0Td!`;wY+-{g%75)3GRCdgvJTM$C;Zee}ep zcG=Srb@=-2B2TS4=3z}A{J3zmT=g7X(q&CGTj-7Y1rMI;S0gKpP<8k(=^ zTcj}B7GBuM?9HAcXi=8`lqSnwpDYI(oBas4mM^j?xGYxcI!l(dP0Xq6Z9-JY!W7SO zykZlx3wo2P`E#7F~0f8{ zi7)g={(2n!5k~wGVMs}~2JUzH$>wH{Dwtvoi(ZUJVF4WXUmS&QzFhWqWs5XB#L!`Me8vCw5D4uSAcLq;AVcyx(?RZHO#&P84fHq{M z1neAkP{fL;FfIawitrSM2+If$4nrvQM5ogjhO$Af0vm|UkM4Xd3GUTQZOl)$G8?hB zf?d=^3QuZlT6->9DX91oUE;mlb8-5FS(cw{ZJsIbM}}`%o16p-ZB^^r2G5hruXe?T zU=FT8oOkc`TL2pmL{JXoaxH~;MSu1lM81JsJD%Lptl$}czu8o?&6;Pe*Up+JpF7T9 zQZ0h_nPxCvzN6Wa@9khdqiy4kj%E|~6w$+qj^=QE>pbjo`SN!ki_-Vb^KH3+*RDI6 zWjOC-+V5s@(Z?$XUSn6~|65Mm$hUSjJF$&~lfvyVy1XU;)Z<(?Pd?$u=gD>2LtV_7 z>|;_)TMoq@4lMQ|DJC{Itd=#+@!?}o5iaA;0G#mdp*FR+o7q1mNKLsP=6T&eZ!?xBmT4TxU+HDGXU@RvUGpAmqS4$#*+YSO@NG1> zN1_i5C53^BNN*xw5LaM#m@jw8m%?_C2@VH4DpO(g;?T(>M~xk^+T9%R^URiWWB8(5 zk>QLW;$Ta)^qBd+363=6xYc6@jcMn8pgi1dDhkU9&mQsBoLA^?Hce(c{0k&-mg7eP!@q%$SiX6X*?|$Ts5LA6`vss8+m_D* z$6`bN(^=+QtjhvlT}TC>P#qRXp*pBkOQ`ho&gZlt{ODi^LK-TS7dpVp%wC|x(T4La zL(EqCp80Zmles`nZ!%S(d2+88#(f`MAg4F8RI*ePhRdfD#QFlMCxKZ6d*OxW(}o!z zQ35eeX*MsgrZig#Vq|tB!3i5fyv(W@3~-Dy7=l=6Q-*eRP!U#&pNg>S|{Y@{8(aB6O2{X@d2?IOsN|LNRhn;XQ>Z8|iG zpMDH>fh7+xqH4S*Obi>E_4Fqt8OopOIJX%iAYvNrKp0{gp3_6kRvHU`BA9KIc>+(k zMwC&h^W+<2oAb<^@)R7(w~mWWK6-p#vpg#Xr2wymhphB6nJYdE>79b71BoSbY+H#ftS8ySVHri~?CXpi8c7;)D;{{RJm@mfnN1u@K38)l&%51DillNq? zk)$+qYqB+J@GcLqtoFEPKH*~%C%!vLDRlbq?ysjPpIb*bTYI*-&409e;z)Q}j5jyv z_Xbs7zG>L>6Hmxj*4`kpDE%EL`g>pMPus)KOfl<5D@(TK!-sjfhs}BHFhL|-n}iY> z52_sCkib*9yy{f56}zIqVrWT^R|Tyt@}!{W_*C{33ksv~6Oz~@tW%nP&SEBLOV--qax!^&oen2 zPm+8r6B^c~I%5}#8FT_aIo~{?t>8~CFk6;irHX=rQXMmD@v95W2YCN^W;k5nf`lSJ z144_RFefsSTj(a8DLE>0b16(!k7e1y^~DQ?SCztRF51~xUkH+IwO97UKWXM`5l09; zp4&FJHb1n;?8r_ku%wB%B^~i(E;b`IMhYQWBAT@v14QH{M`GOtF7hWy$xFl7BnWt0JiY(*kSK@Nr- z<0)8frfPb%C;8T=%s8Ggzk3M3lrW_Qt3go7nip3|#qkL%L342=QB(;L*oqBQc@oDA zxO-|+5%{ zDJUyq!di2>raxopC}h3amF*>1lu*y{P3z4e>^YJcAXK6xvC|UjsV8O2NPN0Nbt0LS zYb)0_n&%=uROl?vYs)xSC=cIcJ{Ix?r142V8130tDwlA;n)B-uDz(u+ds2CJw(p+= zpXxu+Dg4l8GrO{Ct4We6pu@K=uvKG(U|{>QvTg-k%*$@e1Db%vH&LLa`S`77H^vr~ z+5~C`)qJey`>iI|;P_bKHq*}Plk!UEb$H9|W_MPHBnq7qZPt~@6ZysM5EDySguN)g z|0#2n)=OZH=dV6xX0ZMQgF@ejk9ykd$NG@O0QB`F`kwyir|dBEv~d#s&pSZ+Nd$vJ zKY=gZX{NCWBryPeeTm-fkABlG^CJIjXF#X?=`&_3TU9!)1`^jYh0DK>vouvrq_+#K zTr06;<*s`U`nThRYCyAUB&m{uvRT=8n}6Hbx1^v?FZ#tre9wN8X$D8{-OPnm90 ziTjI17!3Aoeco)ZvHKSL8yc|%EB`GiAuh{9S>NzbGUs`j6UX6?dE!fEAMHZ{f-Sc1 z%#9=Yn@CRH52`yWk*ENoEusO5YZ|lzYE0Rer-kcJDVI{LMwF-1U+ekB9FMtOV|@bz zB{PZUk{$n|Nd>hkdzKtDo9pFGRTKt#ZAfS$$IgF*f|HTgtp9?6owQk*7yzgPN z4Vzj@q4S5$(Tq?E>`huqChd!*vm=%q_)ka7vax<_TMqtf^HF8R)zVmHH7EB*mE28u z-cd6ncB5bgW7eC*7sjkNEtWCs6p`C8GzAo27%Cior=dc17P0u8S&qlOWgbtf5QM<2J0&0w3+)@| zYReb4bywmG-Zs~==86K!g~ynh2_OxlQ9gt(+{xBuN$9Gi>-AY`KzWV_Av-O>=79$x z3qE`3P7gu?uU#0S&6D3VM+8;M-G$^q;Ujt1Ye|(o6Hb}`)oi1dKqPHposs&eCGzl8 z$CGu!JrQTjvRe7YLf}|f0dcK%*Wsy`%-VeUC9^zRN)%D}DFo%8Tq6CL+_JNx^fgOl zP`=BD=8QX=_5zRNA%^$hM`klNpU^tf&eexs;Cg7KX9bkj+T0~F_Fk|=#@^3=Z+^p$ zlCr{(v5t;)=y`{AB-qklm4r0dZ+Q;{`b{<8CSMEUr?Qod_-m8Oem_nARQC%Mnm|>|x9}1M< z#9<6EYJm}ZZ+LC#EAy|Q=6!eT4^T$~c;k!a1(ru-f=aMfJX{LuWoGd`pxEe=`4G!j zxJ9+ggHtg-m#%kpLaGs7!R27GFl z);DsWI>Eug;A-hZmdZtpE`L56&JWji#YKv8a^>QZ_?pZ!zc)K2OcdX=@j3)Rn%@#! zx!~A*zgJ+@UmJmiFRNV86N}JPpDX4r_PYY}{nwx}>R&Yz*}nveLtE~HgTwXTm-7Ey zH5-&H^RFlqwamwz91gu@X8dS&_ABFScC{6k*6To&OY{tu^Hx8Zxq8E8;xdMKp8R+7 z*zge(hfl~GKXSGE8~*y}!725ZH3G`mUKGAi=^{~lQtB?(z?$x z(!wJuaS2a4G@=pT@?2;gefcu^zR^mRESi(GSA8icOswtTP_to~j1OO0DqlKMtXl!j zM<91iXIwZzb+MDHF(ah;@f252KR{FqS6}uDEh3ztg!;5}}cbNxu6hCcDrP*cy!+h#AFrTU|^Ha>P*E|<ihHGc~a;}_cMHEr3;Vbj%f4QjC=Dw9%>Hi#$PhA|3X;Xv!jTaMNvl*A`Ze6TLj zl6CPpP(>{fs!~f709uOmjIp`C(-;K{5#h8m(Cj8`02fatf-Q)}lN|UJiziMnb+LG| zg)ofmX`=vm+f!0z?(6!Y<#_JpFv;m_6xzW+(cYAz>CiC5#!k3J9r#G#1)n|8Bt~IS zHoTPMtM+?%YPhSLz7dpdv4@K$zp5e}*}Fm6!#%5qnd>METj6I75Du6c8eTP2K?y;a zdR!b-re*|9C7nRR3fT$NRE1Sl>TxSbC(v+(UndZ+Y~6}c5)%Au1y>J70npfM@x-JV z@I)ygCHpEkMG-^tD(?B06#Y^i{d!}Cd}e;jH)a)aw_|Vi zZD7`m0a?{vlv{yW{|v}_B*E2{#jFH1dp&O9`bDjjH#ye!Pq1!sgjBf6F^0R2IwN>& zO;=Tx5|}UXV)yQRYcE%de1^&^L%Bp(D(mZ?IZJ=QqGtC`u&6;Q-Wxe8Fjd?e33pfc zQ9*yQ6kX%am>~Y-LC{eNf0E!pe-iF^D6H)o5-BoECvvsm=OF)IZCAU50|H8&$gN86 zmJ^9nn{`wM?;J4s^A2}D2bAVl&5t-&RF=psFnbk5_LX+1n(a z&qLBru9W-yPmp%9Q`Q(NB?<^!CRtGbdI7|fh=C@70%I?&_WhY_`$LTO#Z0%(g(5ywD8 z*e~PR)6^BBv9^I2al=f@RZxyHPG^&UKK+K+gIZ!)u2t(56j%>=p z2@thY?sr&ur^wJ@NEWO?6YkO^%Bvw>zm@AM+fK?WJK16>XbVY21?^j%Gem!NmE8Sv zgruT|y8bh`1<}ucm40yR4@A5z{WONX)~E(b0M$SNC{N{fuICwrqCBv9GC-cDyym3M zp`POVU0h@T63&!Ve_K-hO;S-R-1}8!wdDs_Tdl0nSMhqxYSI8|ug03ULC+yKe?>8;t3P!p9C?Qufp3~L!0do+hlthD9OG6$^QbD49w#guj zwmz;dn?h1hm}fr!^{_ z_)x1U>i-1l32@^sErMHg%GNF|5C{7YDh{fT0?;Z(Kj7NPC{$=q9|Yy0573T@p`@FB z7`g&*i?!#(zwLO&s?czK*Gi7Q=M};{`kwz20AD{U_7vszaXk%Blb7uaT~$a?Fq^oq zh}cAhBD4v3y{%q9SF`w?qT9lO#M+(k522Xf&((oZfN~e>5K6M5!Cmyriwc<4KL7(N z;7_mzF%kG5{DP;g?UIro%K#K)ED;?D_e zNudqgO<)RlaOuN6s$iNGck$w^35mF_Qgey5u2K`?cw${8PvFjhKfZMp0U_%uBF&BN zp`d{K|C_+XzO!-v{dXV8?~+6vPYj_95y2dcLTwgf|8^cZ$W>TQ2nA;Yig{Gea=qa8 z4A($bBp5?EVUFA_$J*(?QbEO+Fsa2;@6hR^?{!^JBU8uvYwVQfS*pZ?G71#?(Iw5mt` zTvv754@K6Z#}CjKtjZq7_pNt^^A~bl=e0<_bSU&A(Z$MS_P^w6#gEn1n#0|CXC8#n zIsZ|2oE~2+mpKZiHwovn=jGJlALqLA?ktcml!9C~(!%-eJXaD6C-hewhkm!f6;?O8 zxq#9-EGro5riT>ERgZs$xel=Iq$t#UTJeK-e85$))m0G^mkes2ypgUnO>^_Tqg>6{ zI6_isYYfrW)MB~l(X^OfAD)%Ow>VsJ{M1vfNM3!6>rU^}Q|yi4e~)psU?T`0Uai%O z3RGI2lqJVf+OfT^O>6@xdC!!#RuMv_aZp+x4%>r%3poMw_~~z54cQxnveMmgqPzE{ z?zE=-g$b^acWq&Z`BxKNP1s>V*Q=|#(H8}jTG%U629KqzIagiz>?SFC&y@AEB1Dvx z@sR6$NIVa{ueef9ZB_$5ydAmHRdrrC+1n}`aI`bfRqDg8p?9sTSU!5Hs}YMObd|2! z3n@0qUpDMCb76?bKa^WUbszJPlzKAHh+Pb0LIx*j6x zDwOKdp;=!1JST}q&UB^TwbCZ?sYKcsV-a7Vz}RIL(3}s?HpGf z{$qiw0nkh*zZ$R!1Xa>^t}NZXM#dXQt&taKl!6tbXj_)Ly4oCTLV3z0 zcOoM>Iao+7tqV_C=5j|u1}j#!UVJ(Dv&&pf5{8Ix+EH~=oD|6gSM(gVDzNk!Qv(Zb zQaOrboa-e8;f2F;(%JI@fM$})_iuEy;UiYMCb73kHn2-;Rp;ayE6hbwC&huQ8)=Uk zWcwPV#n&yqA<0k&BlQbw$MXX^ouYgTx#k?f!fX&WqXSq*z{^oMwD^cvym7 zW~~g0lv@jYT9X1q8nTukjb1A!iSU&AdRI#wP~vo$q6EEX=^%lOq!C&dm*-UB`6FzV z*~tKC@fueHKOna5W4DIZ)lYyb#EkHH_!Tq4z5K=oS2EAtQn3{qKv+c`_ZI-FwlYb9^};n&BT$+oE?vg)_^ zv-M)gD*)h~7v|JquadmT)5{i5xzitv)_g1#Zgw?_S5{};qxB*w{N`p?KSlvch5Icw zw@5biz0kbG@(VRupWfE^mS27)*i$#g#=vYSmK}1kmK`Mkcx+YGof})W@W|( zWoez=4<bNG6|r_5)hR)%N32(fqUohz@Gy)(#(y)y*rqF!|+Fr5@qopY1* zvU6@mQbl*6H6ke6NtF5_s3AD1s_XE7(Xi@%D6w?p;EX zLBLjAgnPAxL`uG1UhsH`pE=~}qQOxOp|*LX+?k`UTH-V=j1?b%-) zEGeMsWhCEv(%VQL+8`tQV9}GV+B@iZ8>9!5M@ov?=J@K@q77EVTSAhtmB3LtA5Kox zDBL2rIx+bzSG>RtFMmM~yr6bNeeVX@-u4G#+D$MWl9+t$4KQH+2IuZWFL!4Hah@SK zzxw~-ZuwWW8rgmaRMK7oQQcIi;FPlVp{un`bTGnPK+eolu6Rbd6UGwbQb@ex85~Qv zc*@mVa|m=P>eO(b4c;2ZHHcOl{cD`12!O0{PyT6Fo@PtmXg!M6rS_aK{`(nM?T~E9 z#JfD>s>_Cu@=#Bs;7SqP!zMaNU{|oO9pY_2bTy7v{dt&l1v2=Q4`D}V20?*VE8>Bb zO62apQFc^)HsUcVPyR=)0!>@OZ=7}2X3Gc;VJ`Y2%EwwSALY)u>JdJ|B_9iT*K;r( z`u}MA?!c&u;9=jp1VT2D1d`AKB=k-~?OjrQA9Bc2xP?qL`6V4 zhyer%h@dDPq<29&1hJ!jGqdk*=PsAu_xnt~e{wIovoo`^)3&^Q(;1E_#|AsaYF1#3 zw?-em9(jZ9)P7?THlw|=o%{Z0@5+h!JCpw8k11e9CP z!&w{_#=V-C1g4I+N|s*$Tu?$-0iP%#tgt|x#R-%ULdZ@W)7LG_UmW~Fz^rg>0nEMc zj)E19jKNbI$PJeUZxPLqGacZq{IHQO_4F#ez=$uo4Er{ZY6?0xj0r$Dt>XeU_kQ=v z;1`6QHKPo1zydYT?z2D|&-IOwCx05;UyS#MdKz%NkkUxJ!YeROgbF%*)8^XXhT?7C zS}R!u5K0z-0ws%i@Th0c0JC_7OS_*3uMyoDPt>0S+nNYClaw>HZ&}fm zRZ@2*r%xRqBi?_eq`dp*OO;fd9=6bm(`gKvx;K<}Z>;K`4F*@OU$_^l=C`W9H1zw|>KX{qh2W~M$-S5XhNjXv$G2M4B^3nb7@Gq{`bk&VCricaPJ#*k7b5V*y>ZvDz;wF|W;7-n#$ zS{n)s7%UwR_bMxY6?VHQk*O6C87{9Gj#BBC4-VO*Nwp|>HO#)(j8`;beCoAkeR+QH zqcPn1dxQr8lG2T)NSV@&X81(uMzhSk(+zO(boBSdaQoW<(~bPSjhF?CP^}Eni^&6Y z%}OvH)1@9IPtPAY+-HAW9xHD~%ioIIYYVrgz!HoAbkkg!D#6%U!ah+v%bHPwF*Z{r z7^5@k;BZE?y@QzL50tKejL|YD+TJrJ4=OrE7?NqF2n67If7-S!n_7QGTV1Ra(%+zhSn9u+oBKxlnjoNm_4uq&1V(Q19O0y_>IlN79;ZNozW5 zMbcX9k=A-vL-k`~}2X>oicEnu9a#TnPq%2j%~s@>(&$sX10-Nj|b3q@_# z&f^!-y2$YA_D9W8KoEp#T$S-P>`mp}3Gf|^%OGHg(Z&%hOEM3F@nDFK`baAnh3H5u z@G3AKES&UOTp>BErhT!k-ba>NCbCu}m^vRZwQTW`k6Icvq^q{QoT$MXk(_%0I?~GC ztcK9_;OHD09m%-{d_4*mIypX+b4(SDMoR>`jp;x|K!V+ml!*;g_bD5grJE@GeG?0O zy8ldqeWI~M-b#RMU>O4kM%$S43dyx$jymRI&hUE0uneycIe~T}R!)$~a15$%Zz_0! zHjD)p!*G@r7>1Qb8p;FR28(FzEm$|bbN34jKSu15+-vF11FrX-H3yBE{JZuZu>FfD4)wUKQYFg1H#i^?L+AJtHfYOEL4 zjgj`&Ht3`@(ngjIW4)b+-*2icC%5VvFJ>@gG@R#8&l4sz${AWcUa&@zWPiQ8y`{Ne zv79^#`m~6(r3msqXXI1Ghz*ojju|J%NU9GpjwoI;Fps}UD=mkn*q`#j;Ee$AIxA@;y#(_)D0TLLI$4W)+aEQ=Zw$9q z{GS&q#s8VrQhpTvi50dZKk?I{qMtAwD*FlPkdhK?m6%07QEFd=HKV}Y01#5(Zp3Ox z?1>y<8->t-%ghGY8z4H0+Z-JU9T+E}bH+*NcYB6KhqB&KVTnO7_u!zE9zDT0A#pPZ zChp#Y?X`Rw(}1lUY;P_m{x31u?M-rH*krfY6mR_RF!XTP6LMo%<$&4J2md<^PN%)A z4+gK&n0G;zm`{Vk;L?n-o|H)M>3sOHbX^{pB-@R#TgPe+Fq(9%W-k_KkJ~saBGvw( zVcz(J9Oo?tPD6f;5BYCu$i1HPvZX?oSu5>1!LTmn(jqJUK9GKye8`?_nIFtWXc!73ph4xMQ)R|(r(jOD<_SD z9<66>X)ITBMz$(OwAX|_k=Nun(STzv=+V`-1|AC&@3Wt%b-2BscolDuxXlQY&fUNQ zrE^&j<--jF!rn7rtA&^PXvX8FZ7EZV$fcgqOBidf8>{mRYr*SZM(4S)_QqkXfP@$? z&x{3Ytj4H#g&56&z3j>7$Jwh3Rwc=W92f@!+l-+hC&a+CVC0bT_6a^1wD~?*qNH_W z2}#R0C;R=>;p5dW*)NNam@Gi2 ztz>_pF7*sVdO^}Hgh#m^6YDe?mGO5k{b-A5UFe~mwsxsnNXwoA!R#9iAZa0O=Tfzh zmc3NHf&XAC#D??!P^UE%W&Q#Bh;;N)+Gk6x%%4H3%zyq;|I8m?t<1mZGI;t-ZkcAU zTW&3u^34Bz&6Jh-)A{QX*v3j$!Jd-Kz31OBLPJ=Ye>GjArs9>cfPBJxAT3-)Mj-EJQGjF7ScbW+fMXv6~yWlY| zGvegx7?@Yf-;jpW#O?3>`@ZFT3{>xpR$oEV$J8JnpXGm6R{@7n7#Yq8dhUevAU(FYO) zD^UT6MrE;vlQb#}O!rK_{+`_)#;epvCn}th0kdvi@CQe+p7kkRdEvRmh{I<*Fj( z?BCyulJ^(cpBH~HqUe~)YsXYVZ8`biqAjPaKQrw!4YTlawMOOx;88=F^AW6(ac}79 zF?e8g!eu#>s1q*uq)xaj&pT{_&vVLtvBnx%bg_M8Nje0hJgRpfKZ5r+@g-&BqpX9A z?T;AdNAR`^zN1_nDO7hZL3%<$`!c7vF2`?EA_L zyo=lhUjtCDY~Z0&Iv-pQcTDNq&=RJxQs%JQ}Z!uEL^I-T?P`6VGoCNm5xs# z)f$97AbIqWu74fY%gp_CDL$c#NO%6%^g>_HDkCQ5gvcXjin`=y%k6!;1tK%yzmice z=q{?}sFfvG*kcXxobH5-FYQb&HxUbX)aCTmJIgbc2h-)O>8ve@1@E3RUX#X3cT>9e zbL95W|N6=@vM8?{b{7ltp--vY{&S@Y6z^{(=-+wG(N<4bBF0~f5thkj+R zBMvfJ+Z#HPi~ouRe4O@?+@-Sw+?V~`a`if7)K2?LB6I~nTG|Uk+)b|e&i-FNMnxxSd3l$;gY*DYl*1U3VLxg z=srqx%vVig=B;vs%Qfd5L2^{KBTPnJw*S}Hl!?z;vd6bDeX7NHAkjUB1zdF1Rfnp; zWf=C9x>)RIKrojXO%lunCYU=)FgDO7IcjfHcp2=dy-_~IW1d+dyZ&HrAILAf;n2BpG1d!&5thP}S* zcfyQp1MU)^ zaSwJPCNX*>r{}qxURQELkC6CvDtw>&c~b?5HnhFuEj~SGj2BqG-_KAZVoIM<`Qebcmy&n98V;P(JY&%B0om zD+4c}SnA2DMI2qlX4a}eWRs&E$9C4zC+(x<*@+`3NAelDB;&90T(q8l$1y9|Z%^koA!y(+>-{ zH6>b1*IlFh(CKK$NHLN%D-g{Y&Zsb_Lz+{gl;ff?M~0PlB#L>AFe%P#E}w;3KA<|a z<)pT*qO!)20TCJf9Qm3KzbUJgbu<-kGU_C)wf@qYVfACWC9RgRjEaTEr;4^s@9Bt%*@{YI7n``8d3NX;O84o15>s)ZZ`v|V8+*00ATyBkX{MWm8 zaBgm1StBRKJ8Fn4j5J9tbgiF`U9$Rf-jbT5m+Lc89-#_w8U-JVY**QlWFiqJw1_H> z)5gQ{RuxBG(UFlvAsOwliM5o`W3AWtWKa! zN}@9(OcEO9FQJZ#`3~!p%`N)^Y;G!RRUkSwNfRLnWgTqgsBOT$}Vl^)@!vTDLn)i7kHd^vGrtOw05|)<%=cd%4PkEfSJN4 z>F@N-m#oYO>*U&gj#%-4b(@40hYWG|^oQ!lua>Z`JnFbE8Zxd6L|BQ~>!xat04Xtv zz4=I}EZG&z>Shw{&FuS=AY&T|z9z*)!(J-~--VAK=WI39=7a9Z)Ut*0XbqW6(mEh% z8lT6d5g%1GVZeSZeK^fwr&c` zHT@jrL}5ms#=aI7aI*@POLqR{UccL|6%M0e8$G!_Bi}Um#93!=+o$@ zGWm`9%y0A^SZR&^Abf5mBc2&mDAK>r{Zyan%eaqx#)iMIKV*9aiFcgCb%lU22{r4*~Bc~3C=-HLdu?DspR3Aknf=^VT@ z;dF$`v#xx(PB@Xi(Cvs5n;2nIfiwP{{G9b@y`=*0r#g0s9M-fz+~;jSN=$aNL(pcZ z8>lzGO8q;lT0{Q zwQyAK_uHKkGNC3+NfXZGZ-e6pc-;*Wz#kZOlGLAAz$JB9b>e^}scz3Yc8Ox2Yxx$0 zq)hR-S~x>0B&sYBRUN}|*;8Lk=F3PdbJ7!~HH4(y2wg$>kasR<5XA% z+cL@Pr_6LN8n}PY5)Di{lk;I)MPGxy!I7-Wct9#djyW%41QvOwktC%R{!*G|@jum) zQl;dSt0J2B)f#uvHn6?r4&aL4j8u zZlycQi(p2Y2BHQQaCJ3-JnmBdYYoKJH$h!nv1SFLuFV-0CaSn$uvYTsEXSUpAwW@{ zU*k@YE8fx?>*j(QtpueKQoX5rV6Qz`u3F`emRWD-D=RhaS!zmRXT2w(P4ySrK&w0b zve3rsWR0Hdm~Rx#(Cy%uO6JJoak6oS3OTA3AE6uLyv! z-g-#Gr%3tKM~)`3#qgQi-yd3ja>_18y{w#%96d}insG=LxMlBMB=2ujuZh0TDrWC< zRFvKO8FkFhHmWayV?e8MjIHIOM1!#EcMb;j&`COn8o}oLjp|j>3=kz=%~F1Y(K8JlEVXRyFyTl5Lyzc$f( zuzxd1>d+s$LuTR4>O~VU5c=>iT zbjA7#8uLFM|Ba?k?-{h+3=GqI2JP^P-ZN;oncg!HeGr81gim|h`>&Bg+17_1b4HIx)pjH8G#`YOIb>iX8CPylP}bHx zuof-reoF}-d4MaMl?S-OFzA5t&t?@+9{K{%F-K`W*sKGJ8Ty4Xm=$0+OM2BRq4^C{ z`~ndjQT!-%Gb+k+`(Xd9vL6j2PG%nQY)jQuB;fOkf9`kG3`l|Ei63$+o;>n}iYJfy zljy)m^z@S0e9%!jAPEX5&>7!w0*<`5qLF!#>`N{mH|Q+5xdsH1S}^XaZBp z&?69PXZa&eXNcd`!XLf0SM`9H$^UZEkpJZcd6lUoC*FdQq1e)k z6~y;hGI7)_e6xG|EeE_hz`!W7q-|A^C5=_+$TDTCiYza)TJj5%hi>e6Obap9h$v+dBJKlV{@lIq=puNj?hh>Ce`-KM1QO5G3h0KF$7w%@!wPj`}mm z>dzonLH!x)>CbppL;ZQ0^=ES4{jugUK!Ezg2~dA{0rjW*-;S1om+JoX*Zl$4VuU!= zC6DkG1speTV1wg2R7anZ?gr+90e2hYp91a{Ebv$(1>BQgQoudUAgQNtumeZVSy>b} zR7Xv)D~h*pt>gnwygk6$QM}zt?0VTUw}6mwmIEx&yYwZtX{|z*LaK$QqV`Ykt$-3&{M=}Pf=WX3QlcLA!lD7 zYTmIiRce^vtH9|Zk{gi&`f_N|CvQbm~*gLs&T7yA^@?pCEHXwQMjmc zlK7IfpkTXs8%^Jg&t+n`Ge$-nPi`T8U_cmn%|je$oVd;ERm27om=Qc+71Z$hHubfu z&}^-87_CjHz;73L$gUQlPEm;g5!wpb3T+~*Ahb|HA4iBQYO5~Vuv)?mwe($t&q3c( zojs#8Q=S1xTO!9qIj7q`-DbsqCO5T2Icu9*q67#l0eBM0d@5H)J8Q=-!BQTB-_|s6 zi83JzUV0p4h-VmUm;p2|pplQVY-F^?Z_P*FD&>4lOx49|J~{;ph+k_y${MQqXa;LS zZfXt|kWWDUfutepa2cmzh_wumT=>dt6_Qr63UUVLU$?;-vR-w{+jeHd5`J1}yx7HH z$i?lDJ(@YKGZY81Rd519OXI;~m7>x#+txxS(CRVGSx)4lwfC!}A~LDGv$1(KTRvCb z*<4)rCv}C9y01tXPs*hgoUKa)qC-)G)1j!r3n*%gh;wH7utT2d?yG%Z1*{pwiR=_x zsJR40gx3k)ig&IxM3wCzSsv8mw<`(8vkH=6#8aa~WtYm%Dn>IorZTK2wqOwCQk!gN zF7@HtZMN7ZmP^(lqML&W_5 zYr9!Bop1WIqrr;HZdk|w#_=9M&q!UZ<^0(cUowm;owP=3Gpq3EdNtdj?be~EBdnT+ z=>QkvStUdp>G_q=%1n&0YM?g5hq(I>Dl0e{*Hw5Gc+vMk31#kU>>htM?;$#0Ee|$p z@~8=|NqKo|8U$WIa{Q-9(c(TtXb|ou6s{?X?a)d}gW%UVCaZh{C+v6d;wcSbu;N%l za3pY3NU9m?14g7fH*%KrDJ9ZxHF7>H>N5<1NSBmT8aogBGzQ8Q<=qoST8j>>@&7=+ zc~fT-9}GI7$kM7nHzmQ{vCW)G=A3M~_Ct3P?8Q)8H^G-qa@bfb@c2tg>)zf$Y291~ zNy;#52ea7)-~kWxYG^*0t?s@}hyUS@B=H(+g-M+`ZHLNp#_sU&L5nBck$dx;7#5B^ zDuQVMt)3i1%#`RH$0tg3j_=4L(V5f6`EKq+XKY*NDv`rDq(tYIF7OadpP&CkM|S`F zMn%~+$@!dk=qs(1w0aVNWZJ(wRJt>;J+z2nEik1p;H=og&aP&$uhhaxy(aD84!%lG z_*ilWX9rQ&9~`~_X@MtJAJAPq!s=;70yc>_I!a^g42aU00bj}ZDt#M=vU18|pj>A$ z&#_v{VxX3?7+{t5Tl46vUd%ARvXU7FsgjwiJ5(|Q5LPm?6rW7Fva_>Y?7ui}Jej$! z2a=K*dFQOXx18C<*;}k)T$07odfmEH#(MSSfO8?*B^uGu+w02OQW;j@^flB#|KHkQp5r(cAT+_=Vx3 zbm<-zkoklDk@-jLB=ax66Dq7|Pv&22r!xQZZ-o^%b}H*%3S*2nUx&i~X#Is)BeH(m zPG$Y~zEZQCJE(Vwa?QWxBL!zpy8t$b9&1F?AQ#XZ(US}4gHPlF`s~c@0y2Mb4wun= zoG%8vg6WO?+csPX5rw85Ec?$XS62@0>-<8DW_>5WGEx_KdXip%w9CjY{lWAnX)0tkfSk>P{H*9?dp6eI_O zosGp|R!)t#?^H9X3#@|t1XR#Wim1lOZRL`JW!G@$0P!b-B-Fnu)FEGMjU?2+TBu`K z1)+utj+(q%JqAR*uJyH=q_tudgcd5ad+Wk#2{+V|dwUb~4!?Aqhq$$So3hh#Zwyko zx1l@Hy`_}I{?fkTL?j0A>Wg*q&3|r`k^el^Br^6T1mUi3IFk|1+vK$?_E};QW0w2} zT@Nyym6Dg6Bp~2WUI#09o+C-NMp zz9!ER!?wGFN3QHFe~j=W?Ru;874C zY`cJW%O_(V5gmXeM8~#IIcJK}43?}YTDqPC*Ngiv@Ocw@j(f_8j|qrlm)iHH^H9ON zECpteN`Y^Dt>QC4SQ`8YJ_XAPPdgjNn)u9>_LdfqT5MSOv~#l|x-w2_yWw1imidUb zN?<oCOD{)_b1p18kQG~p`kIe-4i%}oTpj9j9t{nalXsfIB_D^XacRx)5Y_m~ z@P|%G4BUn1m+7;tu>-Izb=q37V6@eW#Y?`}lf$0J0t&(AE_o0?rSrnGu;Mj`!O>&RXVoyVR2DUVn1mGIGcM*W_sW$H~$3j~CD! zZ0L(H;pe5`Ce&dhBb^jmFCjk9{!@)X zk_0QsgVQ}rK8d?!2OyU1l(J6hE)g_TKW;oV+NXffN);E0ofoD))m zQ7=1Rw~gCv4e12dfEap)F*Iej?~vjFDW;1>m7+eyP_*0QE-!cisnX25upagCG-nNS z{%$q2@3A&SRx+}S|DVa$p6=}8LspO7NF}I&T2M4oYQckVP1&NdB`!84q1<@WF=XE^7GUs>15!{5^d9-`@U3dX}n$b@_LQ29!_ z^C=PhjaE{cE(V~R7W9ou>Ee!sl$I;sbdD2cSu@ITN`9kGIF*2V9v|t~BPI_tI#ntB zjpgYXr1JE)K;hx!Yb-!mp8ipM!hh-Oy6}ELIq96?EGy^Faz@1lVI_C{ceLb`>;Gex zGtLmn2xpliy8evmE%NL6EkPEV<18k+F!Z#;oXQHw=$u$U=8y73-`i-ebBlPE!IAGB z`;GFwV_5|mOofi|MdSzboOQwVd_NB^PkM_%puLzgzR}Aj#yfJ#J5KoGEqY#%pz^$f zun9@4u(DI2rcW{Xk?dx!`9__KUFT0}6{iFzEZ%W8G9Ud$(z)0`G-$2P550Ac=?L@} z&&B@WPva1$ao$UV&cz0zK`x!sAeYVy$fd`<=WHi>`qM2;`x7L0g z{Ce3)kln+~+TsZYOuP)?ypUQwoax*sUhswMAQ#Q;DMEQ6?oK|-3P{K9)`bm;Z67*o zo3p-^d*{J=`r8bIy7U(B65QAEE>kj$1?BYESkawPfjc9;r?6SE)X7EW$FP?FncV%c zv!?jmpY}RV8@`?l;xrzWmlr$h#QslIW!+C86mWWa%*R>69-@S84hBz#=Ull#>sY{? zi^naad!$(K8*)pr;CFnYSn&I|dBlRk%ba6#$ATTpAlr}J!_*C5jwq@NJVeu9&37!Q zE&o~zyP5r$JG+TEO+n4<1CUIsut$Y~jw`?>8nYIZ^VgT{Hd#5pS$B_GIvlmq*pdt|pSAV}PZ6z`s za{Q57n45_r+f=aFpKVd|7t; z+KE^4QS%DlEAy@JeI6p{yxTcdG-b6Y0-;6FNKX0QSsx`37IY4HkU54CB_~%H7!}zZ zTjdr5kR&m1k|YLR;O&ADiv(Z=2agYeQCYiuU}M%>A#?VqEw(*st~=3})#R}8Sm5zz zWBznCmIv;oOtj7Y-a3Mp!5WaecpC{?iw29n#~Efr8~AZKrrlEw;K(>sT9e)xtR+o) zrxUAs9zOni4{H?1x$lMkb&%)BJu0HLV_D7_{WYbME$!TQ@<8Ii8ZjtX70*u~O^W9y zz7H7B(`4}j&hfe9`ThgWm&HBCG0p96>jDq;f_Ql);{|wk#d!#hff;*&U$%G`6M$mc zLwi*??|0ZaT$JQ3!kusc`Uq?RhVNBz{FNiH`d^QMP{gn01)>n12Mryw3lJ)c<SWtYXkX4a`9Z?ugWpk@i1jpi%=7q(i-%v!ik}|A;&1l^Ly)umh@rLvP3{F+iYlA zR%V`ob%oo(r{Xw+BY$^fukv?CSOrDi zr`~$1hz!2stY+TaE9+i?>BemaLXH6rv>)-Th5f#l9D^}PcKgX$kBQb=bOJi$|R!9kv&Lr&vwlSL+{-g7*sIgBg6m_b~KGmrztircbMk`t8 z3Z!6d7zCvgE%xbj!tAs!k4{+!hJX%riqoM^@dE19Q$gc<3!l=f&SBySMjgXQ#uQtq zFBHCY+2I;Y19)3+EHEqXldks%B^i5F82An)lw@uO;ox#-7N|2WcfRXOCOJ%Efk!!L zlDuIbO_H-1B#C1^7sqxb4s#G3(Z&7V)$l*=_bz9xXqLPbW9@_Tn0Y$k;{4kC9m$$|#GB2RvrFF|GInEkJNx3`+Hn&PMMAV3Tp%R=MHPIvwbCZMBDeP^RyVtdQ1^*v@Y<_D~SDPnb6QxNKXFwPPqKycR0)Y zvL>UZsR8JwP2I2J+NM98UyJ#y1uaz0+piWXXYW^`t=(VFeqyaZ)JnjChjq8H3fi!R z3fiz;`~da^_Oe>qu!UOMu=ODS=x@lpuP`WL;i857KC2+)P(jFp{srXb0j-{d9BMi8 zd8TWiD9eBdcS)GhA>%bz1>uGY!adw@C5a}imT*HY$1SIsE~n_upa^+a3%Q+D5OSy> z^3^&qD#BoB?y zS;(~gRu;k_DGM=1$SEPNln4N@l92sKY?{0r;%X2(6-#;E@gyHT+!m(`(T_6zX#Jo< zc%yu+A9yWb-W$Eb#36pRKHt`m>4mXLsKHv5t!a5$X>oLjBsnKCAF{C+v_Ko??fzic)t%4>4scb%>NL(C`#f z(G-YKcQ_I14lkhY3@!_fkeBM=$?@yYh*;OBq7&nc`t$H1rEU+i3U7Y~Tm5mcO6t!* z-k;%l_s2^9fC%-66QTa_0_xAg3a;LQm+Jl`0TMnw*>SFS#Jh|$>Q9E%pA1%k{gHHS z#;QZswHa$zHT7r(@6l$}BOAC*x;R7IkCpBK73vVDLLK4-)S-)&K;L+&?$8|FA-X%` zckm0C3jPGYm>+6UKrp>JIKMdL&a-fhdjzq%z|*Pp zg5+ShsHZ8YRW-YmRuBwV)W^?yyR}S{=sZ%gO`>`$P2y9GJt5U=@@J zK!wf(CbC+}1fZ5O0YFZfKpyPrOd#>Fl?gCNwH^_3SRFP32rCs>f=`KZbb_mXY+Zcj zsX%GQ3Y?HDFP)Q$!$nQ_1(21j3PN+^BHnA>=Vaa~6{MtT8Ji-Y?r zUD2{nV^>dcTa!^b8h~!vElWo`HF2#MK}SGxmLZXjK6FIs=mV~!vHnn{jwl_i$tp-k zp+f6uQ&x*QYLt@Oo4dN2fSXh_5AL*z-u0*`gH$SdRHLOBa!dnP z8TnR%D=PLDf^nTa&LpLER(+a(yg7c(6vbeleu2;02lmz+5 zN=-}YYXIVDD?r!qmLYe0@Tp(17NoD+EPed~6wm8ZPx(U~v-I^Es~~-a3azidv0BpC zW2CRf7x>d6!(o<;$%8?yva63+UX?*Am7RM;c~yY0RJO`dcv>w#eH6Uv3M}OsDj73c zL+NukwXmID+)a+n@NZn5L6C+rY@Sg?!IFk1AuwrZdwe1dZGSXx4b3>B{OIs5t`~Bz zkksz#nlA=1`lMC;bb*I{foK(dXXkJ?*I+S1Q&74TfMil-7JySrj#tM0B8G2b6@o)?lFSstXcRy=vs(h3Htw4&Ehr4;~SX~iyl zdQx8K30jec&s-~dGfwCzltR1d5beXU`N{1RiO5g4W;F^>^37<&mlYYn}(_K@&Z6SGM zfGfZo{T~hlbsvZ*csklw7kDVAPcMM%0zR2kQYH^}JtopL1yc9u03_3f%XqtMu9(bV zNzq?`D_UVB=z^eUe^4ud*@t>|7Vr2&&h>*F(z~Sm)aiL9-H2j8i|jb~-1+to8BV26HSr{zcfU>OyIR7TbF2W3>7~-lII~0LJF1&On8{nrq+2XoancZhlB{4rBws{QOM_z2MP6Md-iQf(` zi`){nS?4N-Wu%3cw|xN&(gFUh93}dxO&XiI`xyBt8|V+-I8Yz)Fzz~;=Z=xHyWo%H z3`255A;A%$Jsn>h(Q^4}S6kC|T;5s@;~RY3s}J+m!nL2r*#c1bakT&hh!(x%deo1Z zXnD72WRk7g@n9KQv=DsgQ)80t_BuSMGM+6`9I(<61MJqp4pTcBRpiMDpq;tKl7!#o zxDtLhhR~}bW+%>J-{Uf~@1O?Q)&E)iPXU)C{xJ;c!2@0{)t9TDXM6?}|D59_{&@@u zt;)>iOfA%6%Uk|gmi#yQquRhxeWg+5Jp!jZBXGta*9ng6C)PO}1RF?SW?rpX#%CBH zoYj!s-wv)N;+c+7U@VV1W}QeW3VMlAF%-*^eB6vTAVxDs=Lt&?BMwe=b&sih0@RM; zVHJF$cv$5`9`SJh%dU~RGry^?xTcEM*qVpJ=DNT`Gkt3QLt)0NuD+t1#;tO`0L0R| zo=`d8@2|QZ7pbfTg+hls_&Vf#15dCh_`E;R1Ye*98zF?v@duje1)`iV4_0(e_}B?6 zd@)EBz8alS;R_(F@Rf~EkIC(CxN63B#b+MAnlMf%e9>q7cCk_lU)i{kpm#jsPXfOcSxV*$l5ls+8x&-(5y*N2ArD`-@jtCIMgHSl^81I|gl?nw~Mlgg1~ zpHNZk?gU#sPL6NXN#&zq>{aLiL=<`y!cOL^ zC&~A{#;}a33K4@Nd0QbdL5$@3d~sNz=hKra^sHc*$crxJs6N-I$o2W7qTsU+`bNR$ zfIqJ9Ij)neZ{+$w`pWh3VbHGcCLeXYqWPLU_yM@S$$!)m28abcA585&0MEyjQ+qyU zBOWi5)>Tef0G_YpDNq^me5LS-JYT6(xjkRzRQGT>d7*1eZqL_r5qQ2tY|TAi9bMp| znLaK5o=>)23TgCX)7(+=T&AmuXsgL6Cm4WkTANeK3BD9Nv5?&Qp=*Tb!D<#!AdH(`>){tSyVjhNW71NSLKz&I{k(_@ zB3hSu3=j>0=KrrEk7V`J@rkT{`sv(OPdi%_Js^eCY*xPZv}NxMQrWvat?V5jEPD?<15ayZ{V!a#Vpm})xA*ys6|#5wa%==P zv9y%Zn*83F>yc}5QIw%3d#}O@$lfbr0onVi(`fIFWt+V%rrO$`v9gaO)od%b zx}H(?9(qR7EV?=T;`zSDtSRYvgELCcE5a}8c?H1o3vB9gF1_(Bh6&4~b!osOsrocT zO{)GXK9Q=w3iDIgf$;wT!7%yvj{lF_4)kf=QafEc#Uj>SWj4CN(}4n6ASRO6zlH_k z)tZ8elke*S56QGuXH=ZLx(h<&*BU^5$YA>!G8toQ#y2qgIOAV^LRFhv&nSy3^R3Gv ze({IO(NM~wGyrEqN6@vPUi6h5#;~%ej5C%+Aqu+Jq~ck4S}VW(4i=ABVX2QrX-ewW zCi>cNb!?(7DmnHY|8`Xv1Q|w4RzQZ)3=7CG-T?u648!Ov)l%q&vR zDzm6~R+&W)_yx0w>86`{g##pVj`!j3=HtZheKB@D5TwE`i+=?pk8AEm*q>!bIag^c=>@F>~qm}`qT?ceD9)uEwb z0HeiEr|ZSDP4c9NN zqU6&jUEd3FPU}n{-YwY`J{K&vFL)7FeosMKP};u{@eVM4ygz%|^`ofCfc@CEkXJjW z*e-ldy%m6L7x%Jl0qwT>)IF+|keO#)olF={dWj$)_?)wNRH%u>mk0z?`>gbHuF8fO z#F(PtKXcyIPz+(EbiK|XIpTt=es1VJ7hDNqd~WEJi>{8jq0j$$DOm2k=&B=L3(({e zlyi0<6eO3^Lu;J}V_jHIUn9v1`_UBw-=Ja`QM#<9b#IzaOA;8Jte&r3h}Ry$XHuNW zLZlRDHsTY-nT_Wt&O`^g`R5%u`HJga?%C9)pIonsgN#E85PNljhjRMd0+>yOcZ6HA zYn5@AkxyT9^%3Va85Jc0&`mpc4x>a_xn`}qpZJBfpu{TYoJy>2pHr7Xy!fG0j%%^#$>8V!Uh;W$pfH(L(9CD{ zJ=b94ae3#StG{@HRnnX%^*oCrW6sl@2fjYj^1f?OiN**_;;~#WkkIen=b}SzHvDtn zRl|5)R{zCSSG?g*Y&s`4&r7WHudc*^#Av>iiw<2faPC)EZDXYj`^}XoR{PUg&gpFO z(ndqxf3 zU|en3Wc**aKXJjUOSnHFBmeg7JB7<0LGDIo#q)BJePBcLZ{Qm<+dmj)%4~nNSh%cN zFl^32p&Bv98?d`gW!t;4q2)9aRwZKszMKhZ zlZ+b2hlFVioyn0G6{BVB*#H=%|% zGgcrVm6zwDx^E}p>xviEAzDB)gdn+;ryaTxJp4g)2xKl38<`X5|W zD_y{dbfr95-+TiK(DO`Z&B*h-a#1(ROsU3RQc4Ak zD5Y{k0V>Ii61sX8z~RH}^nZo$mSGrA~cQmK^)Pb#$vpGc)v zT?*)@hRM5?+yQoAKdKDgYd5Fc&h>a#{lAB1L2SUv2&W@d##ME96F+DQq)gFY=>iW) zICqs(6}Y>ptJIpxRZES2gx~4|Vr1>=?&c!sN00zlwugRH$_7xhXcCYDDB_fqL6WZ0 zJnm6821&{W-^m$M&Ycno0G6&LBC+F_WL8agjo71D%#|&hF-$3S?ON`ZhG@b#q;<%A zZm)X98Ded+He>{7(WNUZK-CWGgaxG9M=$9`7uyp*TC0)6Sp&W7^7xNT%b$U7`r__G z;*V|*>F7GsPw-vU_AOf!R|1wBCKX8yY(?iDN`i-RHdE_2#Gylh$A$E<<2xJ8$l#jU!m zEbh_E%HrOKU$nS)SW~jNd6$*Ny#l{zaZ>;bh84~w8QJ7762hW@FQqviZAT@fu<{ck zCKJ1gPh?_OFXv%my&iD~xW*--qkEGuu6SukGO@ok#~z{uamE!cd=HXuOvx!K&zqF3l)U+ z0;?dj+X<}!r_Z{&)mssH42O0(#jjW{he0Zr^ZR9TIi&!?ayj8Y!4v+g?!IYL?PiP| z-P;`*8;&5{{rsslP~CmAx3~L{A)*n1?3ULbwa)cYl*(X zXo{6dX0@NlRT!1=-=;FVJA77$^QmJplbpwP(SFEb%s}kqFy6o?au{#?l!wE3*zOMS z4oHZ@Jx6@ZxFm6uQ=T$WQ%9q#qcRktk(opunxdM+Pa^V z+Xx-&eo=hOTA+0pU#l^ptK8v}OK$f#alsG9JOdcem)v0$WI<3t7W6l(Knuba^seT1 z5G#J!AP>H@{cHd=ppeZVmHoW;lbVkMgk?XquENs>d2Xn?e(X9dOxt&r*~Mkn zf}+NSt19U{b5(^yiY5PI%FX`5H(rISNKF0 z^3}E676Kh%P%ks=WbM?drD=I?AOR>DCeiUFZw`(q7=}POd6m;Z@I%nBBKjij-AzV@{_ET zY$Xi~$X0N$aNqInBi$q9do$g8%-7&rJv@g#gEi6m`vI2{x(4*4V9 z$B~}aNYAfKX<$s1-RHT>3XT)T!Fr42C5DRZ{rT(4-qYY0?fr@C>Ko8SZ-D$Pg(iW9 zVu44XxF46bNV*>wwrV$mWsg$r%gBYFk0>G^S)WqVs4H*Hch?gM3 zsw*SjbJs6E6d5Bmwsvc4$dvcoEkq55gfuoT{<)f>J1eEtgc`E#`>?*qp`p{sC32yy zazkAQQ}G7grW7SbR?3IA(Vjlc+*7xRJe-vhA2b0dWR$R15)&CI>cu$TiP8$o(|Gxe(ZiV;H3sL^S3s)sG6g;jGN(rTT&OhKNo+nK2y~AMHei$I*?vqBn zHQ+|s2!OC6Mi+bvm5(fUH;FBb&pcq<)8fI2v~`2a)i)hGMGwX$o)n7BL0H~6nL*H9 z0}Pu-*w}N@mSG4?+Aicen}U2 z=oi4(!D`D@tK9JV@*1~O%+?fCiV%Qg+AJDu>yXeVtOX7Bht^;(v<5p540^EVcm|t6 zs==OkQw=siSc82SpXSJZpSc^x&cbItUe7aDV6YRij(_H^XOusoi#<|Hrgq72`FRCd z<#X`o7c`87a2YQrf9`G?QT`v(x|$qujB`t8CtFLw@FAPsWd6Q2ro~^lgu3hO2h9vz zM7&0{ipnaz(QOz-ja$%TWr|RdIkI@1?6?Us%p$tn?_*;z0;+O-Y|N0aZ-y^7F?86G z5+KhcGjsOMv`dBUsbYp*o z^x!JC=WYedMXQ3Vix>RqJj>|7UCoNliSOKX0@9&_N}LWIRN@67Ve129EfI5)Squ7) z5vn@$6ffG{z&N0^WE~bL5rV~e&K}zi0L%1Z`ytlAo8uY#G~edwTPnpne3RDX4Y<{P zyJxL!7i&#xZC@$2)@ior+T9|zy-G)?mqZ~fP;6x#*yXNbi1NN55L@xa-7>rsZ`|bt zdZ6pyRs-FTfzv=I$jE)3Rm0Y|RYs*on(3qUB^r*JzDmXmh?XAmKDVtQ@8?f3g;8{S zDdL#_&lD?u?|#;&ca#O~{vH+oLM>u%;#N{W&lWEMhhlFUN4y=p>< z3^zRh?U3S+_CalqZSBpqw@xEc#% z8aN$SYK69D+VZR(A-x|qj5K-vp!<584TyLh{@IuXe>T9MacR5ZTM_up2&{aaDqb6x zR?jLVV2XMZ5NSr+n&yP%GQM^HW^&YFcai^o6t0%Ma@bvL5(}u{^TE#}Pid?1&u{qW z0siT+8UFOaKdraGpZ54?);9Pv5C2@<0e^1cpP@V94}E#{#@FyfpRl~O8=mMBXCZsw zi9TL)?R$8lJMbrsz)NK5BH9?dV~Z}LJBm+q-`8Bc)rhW9>V;Rr(A7CT@%jw9@1qgE z5=yU5SI5`9=4P`kfo_M7h^Q)GP|jIS{5ZUu;lQK7G`k zC6420TUjA_54i1TpF76Pft06p{|dIW8#m?FAKbNDW9YB~(4|S9uU#@7_Jrg#9b-%w zuNz4B0>uAbgL})?LrWHt%_bFZDxFIn>ni^Br~N?L?WFhH#udd=c+Ere5g~NWaKi=Awhkf5)k(j}iRoi|*11GHwg((|I(O1NT~xW_*IT$e^SHZ5 z2jtm9%=RC8c@%mg*X|w^AA zT}U7LU*{M@=R}^3k^5ioS!7Q4bRnNR&FA!X%Y?nPL**A&+_&LX z{!f1bRoKD0Y}8IoHNU(=%MB&Y2f^?cdHV68L!NrlHGI_EwD0f83#EG3m)~7=kN=Ne z6qs_&8U1gFv02`^=58Q1Gvb+JQY*?hXR+EP&iM~m)*Wf2_ihKDcsp?2y-57bTHSS} zJ|g~N1)$E!=FfN33XvaVMM>X~E_&Bva-{tPj_>8#09=juxG~GPZEQ zjAWT}TO~80xd&~~U1^N$Ti-l$N5)U@A1~Lul2b+2z2`2I-x2IAf4%3fEIKo8ydzkA z6qa(6>xeuinH}!ROnXXQS*vBLQ}(^@end=V?O`k{%DWd2)(d5YG@euM%IU3AQ{<9g z+%Epc#@ME!Dr!C{_c(yTN#Tq3Y-3?QP{0VA@S?fQgYJC zK}F=O<~OU$e^Xi)k&DX4{?|84JQihcxC^&|Iby{I#+V+E6IjXzWS#2jYHL8g{L9@_ z++s~tRJiRfkq9iRX(P3+D8?A^3bjOiEagHKzyXzIwI>%fG3>-E$|^83)#P&mRua=n_DTz^$^_4;=u(CMjV zWU27f{5pB_M@yIJK>XDz9||7Pk=5sOfi@v2-CbFva|`-k|__mt^i zQ%g*V^Wgnj$Xg<(5AJMAh=?h@JDPJKLM9FB62o&Sz)$J++W>Q?k4x5!N}b`GWR1Cy z(n9_fm3m1GVcdXZYs%4vt$8=6E=9&D^OgC^zc4ZFBJ0&m4UzATFiOa%lBpfUGnxzz zYfX7~fzdoB0P(b^@2N%aKT4*q6|b{q?JB0GnA7g5Meix_i^so59ZF~}GX0@G&`|pH z-6nsi4L}Kx8|-Ekvj+eXsG#EpM_C0>uOUYlwEIe>J+zqK~v1@7V-zI zf{;T6Adi-DMQznZ=+8_;yc7V$heBwh)E7l1U(gh@!q1BRL{>o*pkhqzzAZ!>R^ese zs30#?O6_WTxNp-awXl4*N$TUGpD%cdnPL$b$|{HeROl{@Wwk^l?!7YYy)@`lMjpdV zi`BK$Qxn3+fsoP*QNo=%7p7}d{*H(etd&H|GY8(2voG{bl;_e@t4ClHb%()+$iO&x zrb=pqa!+F^_jZG|_#rVqo>EW#d)+-oEM-hnWLm=tDDPSdo$o)WtUsicNACy#PI)vS zW_k3H0AQ3ybNV`bZTquqKJsX?xng25qj|6^D9+EUApV2Y3+d1zTnawXB3#OS zT7>&Qw7qv=RmJi+?m0IJB%6fvP!f^=NvJ8*00ENFTL@J_fy8_7x!2Ief}ql*NRcA2 z&w>yY3yOg4DvE%jJ_`yeDmIAEim33OAf4~*?74U6oZNig`vJdy!ew@LW_D(Fc6WBp zIZ-`CG{dbF#7n+^sBZ8Rxz2S#g5yVd&NmxQQX>1q;M!~CvkKdf>dj=Vys0MAvh`OM zE6dwDUuSnJx+*v(2H^%@Y2Db)`6OFSI$&75?=Kk^m;5DT5=M;8cC07hjd>#Ay+Rsr zLPG;ajCV)_&gE^T?w(*bj7EOiDqLK_lq! z|B{dFV9>Z5$kYfLq?ZgDuD?jo5M5-@XmJvL-OZoq>g=34OF(JRFqD91(126h6D(Ks zF((Ed*zic*i9ki<&~o|0ZqC^jY&FGK-qiVWr#QIEXnyzYS{Q3hSmG2PMF2R(hYJ8s z@mVk*{8L<;#y1u@o3iNy9cTEIleNt7yH3g(-r}U3;S)~E8SWtz)C_l>lvM)5;a_nF zQwC&3DHxSk&1|Y=A}!ABmj!*C**@_LXSVNTtuy-<=d29`oY&FNMHyW*DGND)2ctjIV8zr=t2AH_)K8TVgE z;t2zt@u}YlG&)V*Q&i1qf@kS$L4@vlMe;Bvo?WirE4}U*DI}?>vRx4_`u`GQ`=?wo0 z=kEwqh4WK+mGe{G5ov||KTAh#n?8? zd0mjHFl4y%arQD1Tup`N71ZyOS7j>fz6gc&F(aK$_O{}n*0-b}d@J{!lAHg8QO>FC zYtjwp!WXA-F2K!n{_7JQKcTl+-?YC$ZKem}@&gUHp|3|8)XD>`V&#!!llX(9 zougQDE9MBj+24|ON78__p#f?4A`OZ*wBoAv=_y&DT+5)<^nDiwMW-)rg-I{Ds%<%? z=5LJXBIobTLWXzw+Of_Kse1*KPS>qUU2?kmlEyi^!-trO;J6o_LjYn$a{z|S(%4YV zEY0d*_}foRZD=RmgvV7l+p@=P`0xh*M=G3s?bvK-so&&N5nmO2>;_oXG`|a znq6*oLY~|vc^~#wO+=^5*`p@nF&iRkW7W(~*3qdI{z@aAf7NTJ1VJAI-bC>W1Kz~bwXXJ!CpzZ^32{G9gp}g~BB}~;a}_iY z;_koV)xJQa?_&5plObNLQ5;B!3&OYZ{?l@~KfgURicekQ9LSy~eKF2$IxW}yM^DQ& zzZNnoXsiPYHG&4|C4M(cb8dF#rrs}p)1Yy;0LV~kuJM>J{6>N0 zZKGJ@i`Lw61#7&i&C?^`Em4OEdGPthYj+PH$4(HS@O$=$0HELB&rjUx?8sN#3Q4!H zGXaU^1@G?ubs}{Aj4X@NN$Y_}oUQn!+ng=nm9{Nzhg^3f(x|O=y5W=6Rd+bM*1THE zJR=KdKIa2xIP>F=3PDh7q4LNH+%S1y@z08pr&P;gsZP*%@V3s+U{U)61Q8Xvww6&n78uomyPe&%RRS%Q=fyN?9YIJ0Vve?iZ=dZf z(eD6jijV_>VKvo$f{cRgvkKOcx0wq^fgcGP(i9a{k<|){8cX8a_6?0?1kAxxns6+j zJ99?XRh?6vIF9h|T1FUp7F|XE9AfE{!&{{&Uok(COZkM{O^3)>d3N}g*FgIH&;to^L zK*YVmR0*5|AV!G%{^)z1mCUU;kcb8(3J>t$JeKF$Rc2-8*>1Soct%Zz=xE`QT zBjS=?GU5(COCql5A|vjT;+KafFNfrVOZ=u0cZdL3A}-z~Y*Ant){3ILT)_>csmbeB zIHTBRLOKv_-y}esQo95I=emoRt#rP^z91Mln=sIR3ZLzocWoo~DQU&&bL3t}IDc`K zv$5mo*-*Y}OG*YiMsUO=(tkNy%g*GKoJHD`{OD?DR{U$CBMrE~6{8>FYDPahB#E!R z-`U?Ho|)p@EhlaWn5}?FpeE~xpZM)x0tu6XX;0TRm(Gf>e{!E+AhwPjrh z)|JDrm%&w_tVm19_ck6@$9-w^=sf?>U*_=RD;<9Q70j3mVQiASAHwQ`>Lm~&7v!p(T&r#Bo@=2(+D{79U5+k2aC`#48q0mv2z?ScE0Vy ziG%ry(Z!*>%~Q^1Y`Pc$s$&wbc*b8JI8{N#FX4jA#$WCMLe>XHKkeMA-NWB_+L;%* zkdWsmDx4X-(Pr3>E>~b7OR2VyKepL9A_)4F9rfF?4K>lXJ>zU~v#Zdn2!H zN4MKqk>9zqQBly=xPRGGDZGDGdNMBxbA_d>v8=L$Jcz^hEYU~v-$s_jMNXRHa!;JT zrt&)huD%qW97$36o?)Y>YZv*~&pUHMF9AvgKQMfBU!qX+eaQblFJgTPPaikGRT`yW zdJibnZ-RK9|7~JCuYSQs7}_T1FKweQ01kscf$1n9 zWIBqrO5`qvQ+WuCIDD*^kIx&{iO=*o2k7lC@I4=2o5FWr7@w)+_&2XOo3o*UEJ`_$Ps?|iHMFG)Dt=w1IZ}u3Uwk5* zCyg9i!P6cqj^nR+T#>wNhqF_Zg(07_R8RB0u*3O=&L%5Kc;0TYb@xq$rxPBVKgu!V zLMVJMCc7n@NpSMtfW60Upo%TSyYM-M!(#P&E{GMm37>N`Gmbad<#hdjcR#NE?JVTG z_qe0A$^6VNXKTAyiye=EFwy5=qHnYd^Dq@=vnfpZd`FzNmVdj)IV6sY9(3C{nRkB^ z>MZEcr~L>+-}hfrZ zyN3hD!85k%3H*D-4Aw77 zNDHfLGqKDS@gpBNi+JtXtKsX8vkp7myzpBnryI!8 zVo^t&*Rl9Z!Di7vLZ0jEh`eMv->#qLCGqHx=i+$RYUfC;DV$`Tjj&l5%}+C6FEZ3r zDO24`_~3kUsA5Kj7s~VNcWTI=_}=-5)|2=Cm$L)wtq^6{e)3<==1}9k|6fpVSwelk#esJcH2-H~0(wn#X(b?6)0VcxDY$~Cuf=_SW?I*Yjpz;J8 zr%Ai`e;MbPpPkFKmHd~V!JMlpQxT(Mehg{N9-vUMsNxJ>&ENV3Mqi`L)Jyl(;hzl& ziRb0R(?WTxqt00NOf3{P{p#%Uzfss(3x#z@!8}xkVCqPds=n`kQODE2Ip1`A3$8Z# z7+lUACT!73tB*Nf6;6H6l|8_p) zXa)Zh3y%h$VEGS3SV}IK+A^e=G1qWyyHT7Je75l2o5mE%H#Vr4WzI7aKKSmxoP~~| zLLNs-CL3;*Sw2Ck4}piHdb>K|Gd;UcI>WDIYZFPBU*O__o>B@iquH{{E+{p8u!|a_ zJ7&O;#KS!JW7^}63SR!{xCs98S=eGtItwA>5gvKYna4Jg5o45i820wuW$x-WU&E_< zx!Z=U1s~zl-YQ7qgQ8t&ywRI*i!;`j9&ve^aACRpKX}RoIOhL@2%xO}x`5K%+FB4R z$6c(ge)*zvrpES@UbYSES1@wiuzo{ua3A(19okPYpo1=WfDZPE4j3Qb`nO(snd9L{ zF1f>btnSLT2&RT}+CH3paya^GI5K4zo%puT9TED9Yj|-3qaV+kRu;kUbhv)f8)^L6 zY*%}hs;L=0&eQO`2)m34{Qe*F$x3tES8=-FM>; z^LoWiwHsnEAIiXNR7N$v8rTEW_$+3F{}k&puHhA>l>_u!!HoN+_SL6>ZNHs3FgeKl zt^~?_du-!!9u@7nl@Sb{ztC04--~vgjQl_i@B&}eVN@~uR6%$~va7|qm&01=A80(k z$S7WSQ^SbTcNKzv=WzM2j5Wl8tdu{T;i}88k9Cb@zbNV)G%oAmlY{WA{27e2M{_jd zqvKpf>=fx&z0l=K3f_fp|G=BVyTrQ=vPfO|I}CJ$URUSavu+xwhv@u(=jJ4SKEYL= z|CZny#G2Vr(*vl!*xz0G8Y{G86a+BVu9}{_uD&at|B>wK#YWf>%Os)}!Yfi;`8<7! zmQkDRS`Y6H{KyNg<{_1*Vel^v7?#e+FgZ9?6a7t%uUh6FFv43<*(VAfLIzCpf@7{= zE&glPk>PLiN#4nkfQoxuP^)#m?IoI>JJj76UP+o3$IE;4?7TZdxzXue7F~7{FW^qmkd_05mZUx>grMAe#V!~XhWtGQ2S>G&j_Ly(l??fjbZC6eX;;xz8JYf) z&c~i{Wm%*R1eDZo|J#5Qd^a?4J)yB*$Urb=Vpiffg^HM2)aO>F={!<*x3qM@lfUi& z?W&{`J^2Iqz{$T2f8(FYjrg+;cXLN0|}mod9;oe)CKVY*+om-O$2z zPXl+WC?W^!QXpxU?pu=UYN)ZNi3~8-QsQ0aoeJ$LGc&pQu1?Hn?bx->TFv~(KtZ#l z)PRec?=+!A%(MRYZCyX`gKb?G+1pl9-FVEIm{?v^zgq;6#{5(uB}BeMFF$p0uKAppGEmm0=+m z*sKm&oa{~`4r#vr2)M=GV>F5)+(7>a(w|F*OGQTxO9`<|uU_ls!WIrXeOxdxg^^Ai z=kNT#r)RMoTNgaBiauz0+DBO4LS)Yau4EqF(A~oVMbcBdxbj%PV5BX$NTE?za9+wt z1(z}Z8-*h;g~nJYz$7iz4%alI?_!}VS7WmYS+wG;5IMhQkp^YO`$MD^*OFF@lm(aN+xZ&CYT(2!(~9EGv^W3blH1g70uYS9je}1jEErviKoR$?MADQQLZN z&wwwg4uga4wwqlMy!CI6mi+wWE)o2RrtTbGJ{FEu5C7(9hT3rk1a;ID%lCr_bTcUUKoZskQc0a-2Z-h1b-mcoz16?afS0IuXDj=P8ggo zH#yQ-!!R`rRAdsI%mS|2EDT*UKFCgmS1)ko@R?(-f^$Niu-o;nCM=G~qFl41fKu12 z2NDX`j0}^mS$Ko19~(gWUPYDmRlL-J-tV9*KdT?XyF50yKA$tr^@%<$jBo7-%kp$0 z3aWGpRq0()rPkR#v)ncMihWa?!0)VZ<+BNdzf$80yBfXb(A@BEXZI2I80mHuHMmi+ zsi8rPrs;0i+ad1*b3S!kXj5M3bcw4KRNOzQ;y#y(3%YC0<az5Gm2LYh4OT7?+89+f@=?4FXc~k zW$~pqDRpMlAyYfI4o>Y_)EPV5)q?N-)>Vfuopd$SnaWEiyPC1oIx5;IbruUKo#72Z zP?+IREuKEb^$;6LdVwNK;|uIjc9`s-C)ZKwQux9wEGGqg+v}_%nmQsGHZT#B zU@{#hxc3!_v1|C`J6vN^o)rM|H_?2Bee*R1_x>B7UU{ z@lPCb4NgiE*jNvkE`DJ>V0vAyz3$FT9w@N!0eN&4Oeg?5=|>~(bS?e=#f2IVI%c}i zj=NmbSr;`NjxN+u0sN!6Vz)(}7xvYu!+YEcmMnj-j)x6Ze7Nu#$KbkQJpabfL|*pk z^cHM9X+~cgTvs|x|GLs?g2-9f4>W7$P0?wZOIIPN(pB>6+FfOVV27@SW7^C)odLfMeyvQ|= zeXFR;cyXw%%(@?}%ORDX$Xnm*DrP6`SSRYrsNx8R!JGL;j4IGjvC7+(#gYaURiG84 zil6wlpR#(hmIM{OEGrzntUD_pE$Cob;er17OCc%+(M{!N)WJ?KcV$QiBdF5Bc1j0J zQn6^9V22K7g!3tPK=S3_eXdR^pNYX!58Fkwp)&BeWt~hU#{EHBy$+Xsni5v3PZ>{8 z)WJmq3DEfpEGrGm(&34nIRc6S3p4^5P%r;!mFr9P2tmf&%!BX>Hj(>$kTj&f<{F}J z59iZfb2Vo#kOoZ4Yz-%Sj-7x7*9MV>z%s85`0h3C%=kM61jRQW_ySJ(e|l1_oYuMr zI}U=uPu#6%vM=ncKBcUxgR%PKQ&-ctnymQlb*@xhjO~*ti9BWsyl8HYUXbND1FSYQ z2y4O4*;)NfS%pRf8P)cKuI!+r!c-pBA0~k;0FlSJI5aBGGI;F?S0C0i0@S2Z_OhhK zf(BWNiUyCCG{u;Z`(e#Y1rJpA(LG zO8u^Ikz_1pB+`j!-HXEqSy`fryZ)6>M0;G1ON3~+9`_W#a6RtHa1$40*~H1W9ChF9 zT4i5*3whEru667NGDzHQU8ewkw#(LD;R0OdhEr|cGp;cH(W210eBZOKrEI$5BbVYS zOfJO}7@t-!xr{9(2)NiTQV6(Kw^`(Nv&RS)E}9#dT&uT}2J8+Ecmmi(8gQ+iGrF>; z28~ALAovGK<4XM{LBy5%GiI*TKamz>`dOfR^?^xn6bLwuUxk&GU>$QKI6^MbMA34I z9u9BOhT{TRq9Y@L5H8UPk#dPX{-SGON~NGrSIUu!ArCCkzRk=4; zq3Jw)g}V!Drr>75K1>ZgC6Yg~!d<~gFCkq2wMDVfmz&uo6qm3P|VSy1vTJY&l`}P!MLgst0G5 zs*9mnSM?Ww5w0sQ*%@sojCKWKgv&}zMt~_UX6cA9Tw4GlT#x-6E>|fO1Le0w3=G#t zE~K#t0>n63{)H>W(ibo0u+H^Qf?GQQyqBZQMWEG&iXrE#JD{RSc?Z-D;auDSG2(JE zz7{~&=Yi?93j(nN98nOZZ*!jU#!WcBLs zvUgm=S)rh2ZhtV`7ASyUh|B-1l&oi3cj3kxdhCU5L6lX+C|v| z-v+@B1K*QTGVqQ3(A6VlfB@6L*MW!?2z)R-A$PfzG=WbI=CAK_UGCY$uhGcJXBAZ% zy!I+E30`{y6oVINLItlw1Q~M!O93@S8zrUDA&2e zw1d3(Ggog%d*FdltD~JqTgsy-2oDTfHF<#Bh_FRRgJH`82!t&P#jrJw$f0(b6ivk~ z3RQ7y>iA8#2W;ku?y#)fu@o z^<{g%B!yvS?+7Koip5Cqw2&vT(L?gZFZ7W7dbOu~fgO)+KCY1CGD#{h1C)Q(c*YN| zK}p>MlzRjy_mGq$)j6c}0{=Lx!pl>BblqLE61e(D*V)MHM0azSDl37@6-2C9vJ&{Z zdcuCP5_p6{@XK}i-{>>=ff4TEeDE1KsND4nR07|ssFOuI32Yp7{mdR9Jh}#}JW@|K-}pN(ca#6nyk`0EPNf zA9_g)ZyXL6^IP{SK`>=!y;>Y#-j@5`1$P9t^t>EzzYmq zE8#bsf$L@}p*T3oCu;8$GS#9D2w>tx08wXMopiR82#;&BNZ4qL_#@{bcesc)!b5Uv z2e~`4^%Uq=81$&R;OZVldiW2&kr$!7Y^%MK$>!0Et}!*(a5T&wdl!5bZxKIqsW!BV~-6Mhie}8neUQMHczQBt<*jO+-=~#~K8BM}YVgs%H7h|4Jc09%{sB zXR&A0I*YNF=pAEa5%H3B-6HtlNH=FM5rU}S?NYzn30&xR-CLzuj`zS1^2fxcvkyos z>h@i`ZVyV`+Ct^fnL`@K3HQS(Z5BUokCkPpgry}p{TpE>v?j_>9e^y8)1;RzIjvuc z<@>9k^g@eM4u{fSuuIG0&=VN(1U@;|-GsP-5*E)6lr6e}1t8oYG0xqAQK+(F3nCEu z!OD%Z(uY(Kud{WLh2YQ!)lU1M z+ARQ~b}R&^P%I(d7K|#RXn16c7A3?KihA!WRAZLm!wd?f<+XNvXbQ}#Cb2SelqT#` zz>nPDi$$s!3;GaGCdlI9U*gQ-;iGne#OnjKpCqU9o_R6&&EhLrSR*ar7aymk5P$LT zWq%(JcfKQdQEPX)tQ(F=clXyF_2SLCVetc>uEme?9FKRE_gjPNXrC2{Y>K34nhSYp zEqFyg@Vv79MX_3zFSdodrKTeg5%F@K{{kj_ytH zMw#b2x?8g%B9G85?AL%C-E|E}kkyxDdW*9fJ_6Q-XPj}h=G(fv>+&A+p*;6vpCj&y zC%RU^s|(!utboXdT1LOU!LH^GQUPuG?#}LNHkEX`ItreI^!2t0q+l~kI_sQ5_n{CD z9I+snJwSM)GS}Lb`IuCuC02gd3u5K&LU$ehN_TgoE1B|;NtoLM_WP@d97=I72`CMa z_sM}RO_0Uum`#6=biF$2dndppPy-B4UE*Btaj0ViclUJn;7?C*wd6-SjgRD>p6*d0 z$3Y6deP7e2?B7HlROugfm7Wi-(#t7Q55#l*XaXNH+0~RCCG3?ZqZ4hK{8^6i2h=1i zHP=GvCckfoyC-WRP}O`djjv-5yJ?B?83E`_6(klCdD$h3g6oOdJy4H~m-WDP;gxZs z9yrJbp%NI#I?h-7yVsTm!MK7qa){*F2(hmFSS1-4=6($Y2&CyQ|J@$}PBA?9&B627 zTt!{pYu%M7um4w&262_8-NlPa-GyvDfs3@Ftp9~xqEb)0gBJ~P4@(Lnb0s`5ZDcZ-pvn|jc_Jo*lQH#$MZbFmOH2lTmMc=?9Jg}2Kv$1Ds zDF4rJ_sXm6I6iQk2#tj$fi&i9K&R0az(0s9bWfM?mqc0Uo2sbG3xfvm$dD@ZZAF?z zLKa>HU+sc3)zqXqu{wOJ6D!1nNLZPWWOb4HymZX52%a*}e{(=ONoP4>R!Z1CCQ1UBV3Z|1CYPI}1q$wVJMv&h~FbL#q5}{S@9k;7ph}5_p*yiqc*(W7oD@);TCqeHo2J3z)6ffKV zB!Ym)m?fPQ4Kg8 z3z|2xKGAx+`e@$&Q|o3CF0exTQdXFlQ-!|+fhnqgu$^gt%JkY`Ol|5{Off-6nEDfR z_^O6Ugpp7$CRYJjCRa%>dvbMdeVJUHPY9rTW>ZO*OGz!>kBL>~CrVKC6Uq|(!~zKT z35BAcJVWGAenQbO!-u861PaQqmHzIu6T;G8(uI`%QYcFCvAwgn>|qoQrNGi(3PqQV zsvmIKK#ox#n=Gq62Eq4Z;1vaW|72PEOJbb}*zm#|QJO|VuYXAt5g#{k(G9@&aY?Qx ze&Lc_uYtYZ1J+)%_IIB9p_(gk`h0*k7yaqBtC<4$*)DtV3Rhx0!D13X)&BNSeB_$k zwSiodJ2jBCzt<83Ty=*l1XcSxgqz-n#Q0RN)eV4|oR;NuETYJh)fAZvh0 zFCm<$0S@Iw4eDKXw$|bb(UCtY?sS>2*HC#SMgY85j1*8@=0TOJmaZ8=#(S@H_&O!r zE2a}TuJZ6+S$w>wGiks$*P$U<26_UPSmi<2)>Xc)=!WVJlMhIyH$8SP>h>T6FJa!N9GS;5d?@~6DxsfU%XPoO5oQBZtVoHppFs{aTjVo${&Kn zeq=)#VZ$5B2us|IL|8Ii{Gm=vQjD;F2q7@S{waQ8g#EK&un4;`^;!?Vf4%#@ni1Cf z2wd~mZ3O*kgbh&uKig$%u117i{{-Y(RlRST;v*w$qee2q!h6tEjO#?OFvhiOWX8DO zqy=MKyGAlbLVv9H4Kk3*q(&sjZF|h!QU*DKia}1l)X;t=nIPCO zBmt*UP9t&!qMR)Fokg0!bq4e2zVux7nFK=>=rlTVh9XO&)Jg>=hmqw1ict!5p`z3# zf{feMsz!3VT16T#Ouf=bhN&H-0mIbGjYyc<3s@pdfwC-ND(+qZpoftvUbWfXm|6IU zDD@4f8P6i$*%^IB8T}#|MG{6bO4Y*2toW_stDbfDc3hKUh9^A*#4@J=j^-j|5}6|R z-WDdf4X!zyM)LlcjtAqD1rUf&6pHbwB@qO}3-0SEnhH=9ssdEu|3(2L6s3SW!$%s) zP2loIGDIzbNhzNHB0eTV)W*^>mZ&V_4;5mDVT76@q`(L@Rs6yTH8rKy2-WQc_kBS# zcUKmAMy}fdcRRT+!=Gn1#N_a&UUW}kONfFnm$y&>{NuR7kQd-Pk5wt+n99@E^H?9$ z?QA7*5x)Sw-RB;pKae8RcR_@z{0As7ut$UNRiE#E5pG{1UWMywEc_*%WFVW9Vh>~o z1z!wg--7dFAUpUf1hRh!I1Oa;iGY~C!^+_#Yo++&{Bq@ zdF4btWT(4Ca+F~pKyN&3Nb$2$<1d(BvKfDYS0A|X*VzezZmjszM11QYP5dbrf5wVG zPl!K{i9c=dP4VK-HR9FB7sRg);#XVvbF2ALs^*n~+`UL@F_Kw~Bo<@$#n^Q*c3XU_ z{BqTxHO(b=e04E$ZxG;qZGiiF@vEia*-ZRF?thD4f_r6a@n@nKB7F8ro5*AKxO-m4 zO+lLHR25+_%@O}@eC=xY+|SQg>MBIE*=)d zhY#C{hYIj%oEJrbIo7og5tq1F*BdPgnd*u^UTVHg@;UhnCf3JU^$~%AT z{)zoS1QR2TR}{>%+>umF*d%_dFvTz2$34WW_q+e0pGoDj4!GyAa|#93Mu?eT`}zC7 z5li8RK5;M9V&HQH?xifQv41k4ca;)Fn6J2v=CNP6OKKM`#rNK4?r$~LqIODV?Q14d zN)9?qP~DzQW4g-kNz~8~(XsS}-@b5v%z6@z`~T%`!hinK?PUWA6!dM@C2u$cyH4o9 z56nqw!}lL@NARq#+?Cq(eAQR(MtaZ2y!aVULkme^ZsL~AeA_9p0Jvq6Z}`{liV!xP za0S0?!Z!{whQOt7{t1{sDFN6>D1+~D3f_r4is&Wa!uqf@ z5?;&Gup-NG0EU$@1HN%MV37y%j8lHA!^`)%!+Fjn_vM_2Vd22hG}R`=XvW}& zxq{E&!aL$`767_<3$QBTSchC3qW?P9kN~Ou@12K5zTO|~*&T82?g6G1gQ7&Usr-t!l8h<0jXw04@0-;(z5CE#y$4#|X zNwxYa`+A^!;xOrVRrLCesn;sIUWfCq9mY{TES;Yi1PcFCGa|GZ9F0(Hjr;*-Jgbf8eIkt#J}_J<3im~0sir0bG&MKMFs?{bqot-slM$mQ-DTI* zC^-aucsfqdby?ja`3=S1N(3joVQE|rlIyce=^a?XU~&i zqwYSp>u#&5yJw~D_?>4)M)679JDxw1;(-@E{PXTGUe3KUBM7CdqQIX`1wLyk&Ss0!svZ9ID0KB)+48(TW#Mhex+BERVkOH3D9s zvopm=V~ogxO3W1iI#ug}Tw;X?&5&iLucjIoSWnUoPZxtT8Atkd_Fdo1xJP4Ki9l8Dy{^({6u^HvxsuCS@cWzi_*+KA^ZMDw zIQE93&gW(uuB0IBDtBh!bIZQu=Efq8eMY(r?d%z$?}ujb38N1){C5l^MzLddtX~us zzUL{ViE`UjZHy86HBGE!;0w$l{La?KEi8qg3XWQRUe?Cw$XXIOlBnNA-1jE(^KFbS ztbnu@=NJ=oXvOU?J_nlJ&sqz?^N+1nfQ*=qy~$@(PO z_Xr%x`cU?+>WTC-Ac0)&F4m(b;knAx@_9B5J*<&Wz$fnAaNER9_WWVd?xrt>G zEJ0S!XezJm+mQxASIdC9bt8$VM>(3aV$vvRLt|c%F-SOD#cHpYjUnwwb(BffOB#^s zC`ondHEbL~t;hN%HQ~4F2dm$!)kq%IV`Snr)FDfybr0f((H1s|t0GNQA!Sg@%=E>dpVIs9ytuFVf9|Fr1_6;E>l1IM% zy^Py6_6GrrTujRE0)VoaX&+n1B;O}}jN=Y=zV?o0635mt(Kl$Ik*%?aW@@Y|FOa~G z4>CHlB+`hhO3b3pdGL)Vtj5EXKzcKk63`Dd<;O#fVeyqpYBMPj!Dp8mQ!UKIB9dAI zkw}@!PmGy1i*roI@0JMMs?y3Pn&optNC3SppS)als>Ak>^iLte002M zl+l85JB#}%iz;N{0O#b@d&64><$>j579Q6ct)d73jrCe&p7mhKaYZBUWcV#$#e~dAN9sIut zwS^b48*TZRWnLQ%k*-ooG@q;`;}Ds%B;SA=j2xZ)PB`EwHjOiyvy%iW2B81mj5i-| z?69CqFP=CSK9n0WH;gwdH|}(VXNK|D2aM>&N72E+>%_z*crfQ`C^JpK1)a;n1)Pi70LlFL z`5_q=sNb`4*gPV{vi%8QAVkJj0~`iN!dC-SlUCIIw^Z8Sr0#{Z)oVOWsS9OGae)g44?7p$qba;}_Vb&K zrkaDFy&0?=niUwB$RxNm_}b?zgXU%HWuc`7x8z$48buT{Q60-Dv+a)?Wh|4>hV`Zw zKkit?v`qQnI>knNPrlVCVx34AoP#hD^dgE5hHn)`0R9lQ@HRNNvcZIeSmhe4sF32< zPGHQ?74IxM%rNfP%d_~2%*sam#~DT;a}zQ`68PNJtUHY9>_!4FKIOTN-A(`~@{L*2 zLnx-0zi~$CXww{J@HEtzFJtg-brdfEeg&Rxbb_5gvS!giiCy0fhW zief&%58Q2}Sh20l&ChVJ4KN?Nz&nrx7gIQ*V2qu7YDv!!U+Nqq$H6{TT-TO+;C(iS z!bAC8^I=i{TD9;!^FeK&a&3W;$fquK)Tz;J^gTu?`#ornM$j>JfpG)7WNVHRy#33{ zGko`C;~BnWA*?8NnciM#3}Ug_0aFuk1o1_SjGI|gTeAa*@M){+rPZKTwb*FQI@r*G zO!mFTY>JE-S)$A)HC&Ekq~7a~7Cwm7Z)vQYkj@Z+;)ZM)q;DV%fk1IfwizgHBds`n zZ{~ZJ8(leWpXOu-X0AO>O9eav& z!Fd4aICUvHPF(^pr!IedrSTbigHW)|+!lU$1LpM4+|<>^0{s9eOU&F|tKn4mIU$2n z;!{5Ge&a6oDS_MOV{1wNW1&3r9TgvDlu18!t}dwYWsrCGpYt=C!!5v8M;do8}c%J`IhKnS8O-ZgFUE@?np z9QNCynzZ2Xza_)}tyWufkhTE&a_uEl&=y(?NUC=_incHMTkX)q5X)3zHuGG$?1DFOOP&7#MS0KkVjmUroAy~p74fy`UERIsdzA3N57JL4G>6^^I zcopU$rHI?jvK_`Kww81jYo7%TXJ^K1MyeIM19k{=IuFcdPyW}=F|Qjrmd@x#r-&Qz z@SVoH>_b8cz387U<)r>6X+SSJ;`gHONei0oJ8HILwR%wx=|#W*y@)bEFVb5n?+kbm zU`a2c=wedqNv-%tn~Y|xKItaJ(cncBA6m{`O z6b*XITSgu$B66TXDH<9yZLiVL(s|GG-cmN~|LRw5c(N^BgcTap8E4*%tC;~=}8 zkU>LEZzT;moiuh1sGYDT!kL z5CV>8rX(m|oH$bj(Gq=lGxfSPy{wt6g6{#jRq-ffVKcrx#_ME}tpnsZWuX=hyXF>Nw|0xYE!osG$1ut72+KQzTdf+Bz6>Y=Ts9P8KS%QqJeOdtgs;$^Mp@Z+o&yC^;_BKJp@~b@{g!o?89?~FY126g} zq_KXewVV%MlU7vN7j$4hDus!;K(Y|Mr6cX(MgKBxwD1t87m_zI5qBy+aQZs2x?hg3 z?+-?O2a9Z@d`AQkN8L6M|2~gSX7EE@b~N>rCa4_9V97lMP-CB{m%vjW^K@rT3BH(q z{KzjxL?qyt`ue>o*M69s%6FHg#qrEvjh9(_YY)nypX87a95Bgq+fl=#_iZDOif50) zS~!Sw7J_U2`I_I15v)If3tf<7#{fyRcN-bZN_hT%;F9dwW5(P1M3eM=zXR!MganeF z%$xsVJi;auID}yrn@<3!Jiy?qW_D_5MYT#XP)bp0m14?q<7NFZQ;L!kMnCqHjkvan z|8THI( z(;?oGjP;T>T%3<+lp4uQthO{6sP&{9Bwhpjxzk4sk|`5 z>-%~*i_W!qDdWB<&veEJTurfb0>vrDa^)1Wpj)jlS_)DpR|c;Tej?VB#6PO%G4vu+ zoS`wE0j#%;HoRZ_WQ?bjl@PcsY>bhlyHnB+=}@nUiMglaJi}Ne>5caE@R9LQlHeh5 z8`bM2RVSsI%H2+9{cyu~<^lLvroW#ner8j*2eY zi*`3Psc1e3E}v`cpM)REv6p8wgt)So!mS=!AxE@3SH_if9rByA!vtM9D4O2`sj+dYhtiOtfHLro*=TO zFt?mf2ezEmdp*UL3J_pyzSxA6p7@K{L{(YEiJOKb9TY>rhZR2;zwnX5&-3I%tuq8R zewi9d>Ui0a_8z{vjpvz~<#Szp_vCm6YwS;=4=kViO#%FzmpyicHU3Zt&iL6p&%NxT zqAtqkx`wX}@fUt+8?+WlLAY050L6dcP4P8r>lvuAgnSsGS(JlCMlt!a3@$RCRMWM# zV>MS;SWVZ9AYg4)kwTc8Z_H&k5Cr6NUB0Zosw55A6B@7vZ3bz;sxD~2sxH4|F`@=- z6~RKf%T2l)NCVP^27DRI7Se!pp}|5Ii_qR7SV;FxlkR7v0qH^m(*2$^AYEv%(8VgW za|8?N{%z6?Z>tP}bfE$DkW3noE;RV*VhLIvK|qqN+e+1TCk;pv8c@_hq(P9>TJxbL zo zl*dH@T8zM!1!!9Z&ujR>KA!$57sPC!6=%PY=^-l4%m)`d6X7F!TS%uIbtAkr!|!oe)#I!b8a z3HxUOz|{ffIlh-}&cr%l{N*x8u^s8_9mbE$@O0w4N?~~kZ3n34)E6lzsDP*#;z?l| zfn#A;gLYv?)l4xk(MJK8=)2e! zx0m`k_*c9&?$Ah&OJmCjA=L9?sprK6u2itmRKcU96?OfHT?Nn9t^)IO6N}r)^qqy1 zP=O6#Rw7X-Znx(wi3s82-QGO*K9NT33Tjd~G{*CU1&S1)N-l?e^Itn>d%Ybkolzeu zdw9H^%pU%mP{QotA9kgjhp#F?t(guEhy_i`EzCE?kwKc-LjvKLJzOA&mY7z|;rEaC z9AcU6t&>I1XfHEV8KeOd@15J5*Ed~B3tF%fuW-SU2TK%sw+~DdyuDF!niYINU#9m6 z70kO|PXT6yf&-+Gd3P!f-rh`UFK=(Ak!~o>BqGf$DGkmhyloC94$dYEec?(rKr(-L zp{KP4inHkf!X9T6?T5380?-VNg@9&J0?eobH&4su2R)uY*&Bow=FWGRw%9=$&=#Ng zZSfgt!O`z0qyMf}Tg1uDAJ9izQ2J<#zX(~eL&x_Y0+zG|MaPTHx;$f|CzC~VP`)ID z(Zf2B401w;fM?+Khcbnd22DZ9V^ZD*Fikv;&2r9X=rJ(GC;??LYyz zz?5~M3rr55HN*2cJ5K1J4UU;MI7S+9I)rpILsM8sn+NJ0i3i4X40xc;3T9C#FhDC% z255yWLN{QAW6}x~86#7djxsV8l1^xb0xC=&DNL}?q@+PRSQv=VWCNIXpis1fi||J~ zPz%wb`L;i#LWh+-bz~Z{~Q`vwI0ew8(;va#k!L4QP?|ev51%EvSTts1ly8 z)gp~#gaQU=5y}89vWw95Tf_laGD1;wyruoLqr9a(NV=go2dFrQl{mJkp~OLxQ2IDE zYyi_F6pALfK-i;6CS>EFmwJw2pk+ z5(rWSq*07sYtOfHy3d8Q;Hssb4)8XG;~P9#@hU_&mgWF1Xb#E+Z&|M+l>O$=0UNbN zu~Az#Kr-*W+*8CT6t#6TA&T0f7^p1@z<>^K0OOtlzIy~bx_(Za(&X12j^D0F=%?Gt z%epk)^1^fzVTWgqM+Lxt=1>==yF1AX(>Dn|YV!@dHa|pdiandUGu_ci z-kI(oz15xR51q_A)1OE)693*#{J7s#N7i`S=|C1OL&>UJ)4B!n)-NO@S`nno_!Oh%;|ZUnWw5+2yUN_JR<#M1QoCypRU{;;m_K%3M5} zQz8I<{o<`@n+H7AA#5B$#9Pxb1=6|4kcNPB>o*t3Thm)eE6(kybYOQEVDPW$+8NTd zfk*Mbj0#41h|_9{ngk~1D8Ey1_z2~T50|uNR171LIalp$700+E44wxd^25bs3PYzfc$*Z<|N{E5Y zc5}S(zKG{NWjcG6Fse%Q4AK3=eTg*KJUUMfce{VMr7wBfvi$^K4Ht0eaC3ZdFMFyr zR;`d#p8r<`ls6&Ooq2V(rwzsCkh&kl&Jj#uB)z(`Z{w?;Bnx4Q8r6kZO`>w|Yo6H_ zqBc#MHQ(Qvn%r*Jq&fb8=UjT-(_CYnZJe|YeC``?rPP7Kt)Zd4RAhb^({E6bWdvU- z5^$&@zho5(O{wrE1(a7M6@1hlPd-KF=wGvJh+7Ph5m&y=g-@(&w$%suNnOgrfiMXi13!2kHO1z*s zBYxop&6zI2E@<`-)eS!UJ{8DGh3Lg6Xo-s_II zlQ{d(Gl^v=;_~eVLAX_>ca>jdZ?Mnv9qUATVA8!^SDDN2O&T!i4h{H0nBk-WuLqz3 zuLp7=XZq4D)7V6UfF!*p$(f`9NkRjXTud5}BsBO*;^XN@R*jg+st6X+U2oFeN*a(Z zG$7rbqygzdgP$&55Y(a`ydY=_ooieWkPh;KAiOKb3j%>HF9?1UznbznpL@Ebq>JD5 zf`ADCc_iH@-`sP8fZ>AR+RJ-44mv`EH5P_{5X$0?fPZx1o-p5xL!M-fT~nxpfxuOo zaw#CL`INe?capE+*Pa_gSaj_jL**1D9euzSUfY*K`e3H^Ts15V%?K1Pe^YqX_ntHh zHa`2;u_oeO|MCpBAR^g8W4!}dzna(&{opCLVv9Yb8nO9=I}se;0O(urqX%BCR89zD zJoXX*uJ`5qkDooAEQn&2N>v=9YpBM&Q&~u8iSrGcF95jzPUqVjc(Z&PfAx%Wuquit zo?KgBD7WA1NrSjR(O%*Qe)qIuJ_5&$_X~w2((WmgS(o3s;?+rp4PLEUWln9E=!Gt`r+jt~Nk2 zFWcy?u!!!z9xxxGPwb|gA1@ecP?-B4&oK)HG<-JcCk$`F08x_plP5hZEKqdd&ZJ*( zehGhj3M~DUKM(w`ox7j*46$^^9L0l$GDpGTU$`H_!i}+KJX{tnx)G0B*$q7^n6*=-^8*(=4O1>??I#G~fVBY|txd7f+BSfBokXF2 zYv-`tgfc3gqM^a?$#x6WT1x&|H+dQKIiVyjgY-}6;E!~Z7eO$c#6=JZE#_nTltYH@ zUBW0p+4>aW5?tQH6TA&9ozd1eb+g#oH#fxlx5gTES8k4WPVO%4oJ<;&opZZOJLi*D zv~!#8#Liv2*J@|;DO})!cBWj=&O-^|fSmyw?M$)J&NhH)X9`tzoo2!UsKF&=zq^fey+j!nt&k)`?+S|b* z0|tjG!ZEn)XmdgtFAnvD?g5*tPcW@1l-u?Bg>t(-ho7kL&Ew@8>$PW}5k|Pw91sAt z)O6rmV!glWe|G2F_fBidPEd4zTIzSA4gDOL4vP74%4fJD;PLZGQJMO$-DNKASJEGy z?8v03_Ii8|e&X>7nJlq~@=bKI*dD~m(t0Q-%bya}RS-p=3Qn|>Nwl+_Xa`EPXAq*8 zMx#Vw-8R!`KN9)DTOp0M@Y*o=c67x<@J6=-;4bi7hlcvSf!#tFqiUxKfK;syR`FS3 zYz;xd{MkwnT0C{Ik~FBv_*4%$88?$w)YB7mNH3Bh;mc=~LuSgL3tZA$dvmN@L`B_^ zTYF})_X&03d)i7~(A2xuf{n8bH*DY3#NODFlWwSzgd*ZPO^TH3*i_P7ssy;8N-SIgDk&h;g-Y~` zJzj3(E!7x7hckQ=J}bvNhz%gvVn+bjyh*ONHN}=kbEOkgjI&B7q5_|67ERMFP+CaE zLoZLi2{PvMdPoi z^sW@Y@X))msMbU8*KNHUgB^O`Z0G%qJxw%%hu%#J01_bMW$Uk~C{Z4I(^kmB#0EU1 zqc@YkcgKh*J}MFl^j}d7GCLPz|$o( z;OX+6B6$#Y6f56Gl9x=9v7`Y>LIaXaBMnFr8vG>HLAZcmA>H=HQq(@A0qH^m(j7q> z1YNjan!C^or4E?|jdT!K9EKBvs%Tvg@8WtpV5BvU!USC&g*U>i6SZ;zTONhy3AQ_U z_abl46rX_7qwu3deWF$_*sEC=6S=W)Zskp#FSBrtI1CogEg+<^ckWGef{YV9b)7(@1$2aqdDz=YXyIkn4gtVr0{l_D2aSLHH`G^e z?(2O*V_#Biape1~SgshKkp`@pJ63Gg%>6-HFf<-5CZX|kF@{Ec9?%hQLsJr)FV6=C zST9EzsQ4RGBI9pd2?%ZGF_1}g31N~_BI7UEU!MAcalsv*g^RdCw*kyrIRaHy=|W_{ zlNiC0&&qcl0;?W{;$~|Q>4%#wiUIGhsL%VAd5bLl)b4!T|J50HnKOra`&c^T?)*Tp zT>Uh zsY3o!B2Q-E^LR2--e@L$D2E4c@Ght+FJ_g(dn%_7I#`aobV?0ve`kr+_9w@ApU_zj zp@z0^*;CrSC23H$FX<^~UN6#$wlC^QW?pH}T4$bFLyjh;fW z@nmKLn4UtRHcz>mkVoZFTp*d`3pc#|G)BS7RaX9&-pSHcXlGPiprTWIoS*P|JFzDS zA@r0-iTbo{T)V;BUIa&*qr}Q>Bc*?LCA>SF0x-C|L+A$^X0r4V+7EpsyC?dH_K{ea z3pmzAd;qIA95l2Y5{5MqzG7Juafa~0W#p6q_?Ho^iFhv7`-`5?OP=JCdMV$9am&ZD z<9ZR-N$(|3aw2G}lUy{sut+>f9!>hAX7MCf&`X}=x{y|M%8rDx){7sQ?(F~{I?BJ< z+f4_G=zzf~-e6K3XQw!ZQuNv>;u(%oRA;ydLP?(C3@ucz(@XB4PxX{LXwWOxLOejQ zQLpO+fa=w^_BQY1n&X9D@FkfqN*eO-(%>ZxuaItdjCl#hAx?HLkp?xHKkOwZ^GBo= z_4Ym;<(D{0hkq4~Q*p~o(7wd?&xCYB4IcN-^G?-|_cBYE2@mx6KL`)~d@qcRV4M%{ z^bRB20Y3|nR8%TZ9wM(@6LWhn8Reb>j}!0Mt9Q5en8vbtE5Ad?gdYlipLRiY&r+2MEu7RAVz~sP8Z+ljQ32J6sZ>gDb!bE6ByMZvN>|Kju z6bn=gWg!$ptYl)s*LLQMy>^e*vD$OIY=L(W*(aK6-mHv7&v{RpUb+r!DN+qS5eZ5d z*;R75bR8S=ER2NDEsL-3fM4>;^;ys}e7l0ZNCpX-Y|l5oS&&D@`35M%{8&{Sc){|; z-a;}2v%Ky(IfU|_d9gJcH)G@dE04n`0m@?|Qd2Z(1R|yX&{w%mhBEy4H#qcS)cZ2KL^Ob>(Q^vmXS{6Hm7PX; z(Nb>$zk9jYV9|Y)$KxC3gRrZN>LZVy8}5Co4qtYkcNc3$y5XTN9Z%i1(?r3>EKFW1w@5LnP@S50R%}Zo?t6zQC4;$k)U#@n3x7H_w=QtTA7* z&KsK&B^v07^0cxmzVExX4_4g4_K2?L@deM7yZ7|E+;e5X^mWW~`8O1C^UU|Tg2*?% zd@2CAsDLBjyRS1J^gge#6BJP#_kQmqqvh|U0grp3ea+)uoxW-)xP&sy<0V?*6~mcb*1yv^P&?AU*$@Z)ChNK0ol z(?!w`%|tn)nJ56wG{3LkOyXpn!=W^OH*4BY%?dnRrS+2&DUCFo5U=X&)X#iGp)+Yg zJ9X$sCQ{FSfr*5VC@2>JBlpnzVZ{RZC9PS9KP zC+xRd5diLiHR>EOi}uS$bc!{hdJZ5g}m)YIhkyUqL4T06!Fs^!Pm$|1RkWrnyW4NZ#rUqS3b^3 z(%2J36c*zVZhn%J&mJN0AQjfv@()QBF(Hf5AK%XH!0WGita*K#C#{Z@c!g&zsy>%} zKosIga7qBM(}j4)k)Yj~obTB;lupchFZP#x?nQ#YdGB>F0^fYOK`_|g{@I`Ow^avV ze+v&aMt+{tid2{Np*qON@t4ZS@izz%!(aP6r!TWX#VxC;ALKMKi)C$^pN2io>R;qEWdr_>83*hy`pYi&RDYQ{IL`Ag z!iW`O3V^Lba=*;k>sT=W(g@*|8nIP`0o}Z80CDps>1GG?AN*9GMg8=}1LWAe zkg%z-dHw)tlsSMH)rMy}^%m@3gaa)*6l|IAAD43KYV2b|D8^^@J^_H&o7eytG~YpK zFla6lQY_6kv^2lkf+ki)v$btP6;=N}XSiLFc%ui8NQ9>cg$3oqY1ydDIq_wg+q|~e z$xANh^kMb?tAyMia_ZV7V5Oh5{Ci0HS3llg9t$9Cm5j5bTMu+q&?<499V{%sadwFK zh2!jybR1_HxuZx(OLR0bw($2$bB4wsMh*)BiL0TX&7M?0RbL(F+x?dN4$Xm(H)~&7 zI7WybCH_o_hd&d=pBKcR1LDs&;?Gy`XQuHcygI*NV-rI#tU%)BNVpt{md`X=TLdT! zA0tFzV*iJ%0Z zH2X?i3xjvdR23(ztBF6m#P&Dtq5nsuEie)Cx)^BR>Bl3Nd2)Ed;^f*6@F=feZABtq z_e5HAJ~p9F3${);44u4^?~ZZx;cZSwhGpEZpyHQk(W__N^yFnj&l4RD*$vBLQBZ^cQLvcQPU{HVj#k%bRbA&_0p5S`B1igE!}s%s%w>|P2nEqN@LTAV&%L^-->8gI9&Nic>gEfy=+%i*1O^bci*l$t|+ZS zOa^%O%rCAKRtJ9hJNbZj^{5P-dzEeC4Kn;udbXY`_m-nHGQ(=$@FQS`2-BJ=0zf@k z4NMZx8?y`kqb`m<3LS?py%^-TCvk+?~J3 zb}6|WYp-;N)+IWGHe+Xo+y^onx-PN|1G5kv1IyHGhth;XU1Fp#G4}p4>;y5NBjwS3I;xtKLp263zo&w`e zy*kjleCBEqA^2pnqn9w|A=o=}b&B07pfsLWlG2q_G1|z%sxPr0dWDQGw;m;<_^vCn zDmm{^lGAzqMR-B>i`G!{Y=nZ#`Ot6yKufJ}^K6{(#A-@q>n={7_C&?L%p?Me9&%-{ z909lH7u&$yRbxvDF_f2D0;H`=%}*;{2SG|aAAc?Q16GdsK5 z!;LHBhq}hbDf_HU53vCHrRVbD=}aOXqR)DwVBsK<5$XkM#I}U*_b#qjjr~bTm7{;P z9Q~`prgJO?UQ$>+Q>K_BGoc2pnLla$5?-r#SW5#lWi1UNlH`~-?v5_{ zfbz;WDpMZNC{s_?y?ZuoSWg5ZdI_tZex~)*(zm>~Yk|fV5nEI}-J2;J#Jvh@6(n~} zZdJbKosNyQV*be;t`=;wA|Z`pV|j&nNLCgE-S2n0T9Za$?GAuu++8A?dG=kd!R&dW zM;I!;lGN_yX+2!^7$sIMs0_5Quj?TjEz~P~$KTI2n!Oh!ogZ$chuLUR?yeJIm3XuM zu3k12*q6k^T(0))%OEkrNE<0g>23q4>Y0~mYerqtT|G2bHA}SwRXr86Wc5^3SlW!@ zvSc%=uh67w>SdMFj+$nb+m5Uwm7o_Zhv=1+)01fOSB?(U*y<>?s+}@WY;_chwR7%$ zqdglHBwp4IrA4`q-EU5J5-4qZo-En+a)~I__RR8pGB>N7wrA}C*|ZHhW;9|1LfW35 z<*!_|t2lR%OcKIV2XN*I4)~6Cwc)!Krlf=s8*xP2D*$RlOX1!xbDq+U^2m{{ChT28 zjU~cS>Fx4L^f9Sr%w)a}(IR#kj}SRfhgPTYN|rQoZ&tv_F|5L16_se9CIHev9}Kw_ zE3!C3f~kr+gJsOtQ3$JkB69Pp@S3e{vtGd+Ggv$*6ECJ6P5IX6T%+|_gZchfUG-!iF)v68e(pVIFyD2+mCoi6q_B<@ z!#bfhLpVX+FQ(^%TsVQqA2(d7`Zh~R{pVdB*e)W+-ypT^yx4TLW7`QXNJp&PJlYaM z$Ng^CZ2hpMBhlmP#$G3K0y_T1eIC~|_Ai19(qVld{YnTOUwB<>^^2B{HMy=n>{}wo zuS5TOFmIXXn$Nx_$RH)wZE+XuN??9c%jeE_ximd&h^&$>b6lNR^&u*r{aQ4qZ%Kh` zqQ;yA8KlMf4z>!77#K$zlV3o8CCNuwmuxp!|5tAT9+C*$?} z6Ee>{*Y|7zu~jU5W0e%^!)Vfq#0s~URzryGrE7z+BZ1i>?u?Vky=aboifgoEQEF-8 zU#*JuBj)S>DHLPAey{k2`TD(Z8|lF*4Z~LoYJ5`w7S0^^#qU_?dacYN*_T=9s-&?u zNEx8xoSgA51@P-#{jXbIC3l9m$RKmMa(>I2+_%Uzk$tGt$j;@c?5y% zfIz(~2mXFf=m4HYJl}{nV)#_aSi+{-X*+5h|$W6)Ji;j7V!_) zjw(zWuKbPj!|TK3{P4Px5IjGGC#8%2>1xhm2rrf_^VH;S+VFA;mN;Ba3==_tI2o)e z);iF5eVFh3Ue{T8NLZn>%I!C4>3uM-5jTeir<>Nr4A3C8jc=L zriSB#q~IEN4BvUcHIR)VI1!+v9MH4Un!kBRMI4N90L)44sPDG#&N_bVqYrf>#!5$%~An7qu z`a^c>mmMb}0>&TZXI^$az>X4Jka%nI|E3hL4}*WjB(UuvR|if1 z!BVi~Fie?$B0|vo%so>fOnp&DT=2PcDZvJ*u)coz-d=(VuezSpYVwj-VZ^UJLIr!k z_9*Ut%~i~z2rfvlb)8P+2&-OwP_H{Q)`M^aq;=tsz3H0Gx)2<$pVQxRrLs%{#iEJq zhTdg_?2;%?kOfxQc90eb?*%58W#ex!cvIZq3PFz7FP4e^?!)=|CV6Q!uoYo9ALSos zU{V?Dt98`X2~xDgSe#laIo8sFv_hO(>i@BNql>CH!pSA+N^x?@3twu(%9&~5?D9FG z8)ugX#4ns(9)QA^GrR0`0w!i;lg0;IFo_yFK}vuV%cBb5pWLlJ^gozb9y;Ml;Gd_} zugpE~xpLWArAAIHaW^J}a^tfRJo|muLH0A{5Ze`{BjgNFAE_c1=Qe=AxlIH?h`Ej6 zz)9uzBjlvADIvh=Qp1r_WJiKPk$^yvcMt@M1cYBC&MLL^aNXPW(9Z9!K&hnA!caNfK*B7y|PkEs5{H6zU8~n^AJM zaCjuoOUrGq#S6MPcy4=qi!dSxeBF;9uAqaCOD=iCdr7tyrdJvz=R*$oSImdT5+1a6 zbg;F)<==_%WjY}gZe?Bq!0cwpyIGM=0<~sG_5TxAm7nXV*LN)Smv}j0RV7|hPKh5N zCC)V)#j1+1zRMvxdFcrY7zV5w?!$i zFMdb-!oK*OQRVi<<9>8KP5WXlw!?iResa~&*af>oCTD!E0D%tqh5tc^JR!_T#QHZaVq9zd#D>N2QDO${{Q;u8xxH{ipxqdY@Gp4Tbjafr+lU!f4r#MiT^fXMn)& zESVs%I|GF1&a~V3`D-vCgbnpEtUDpXUb3?#b^t-3SU{lIQ3Qcv0YSw^{5zv7n@)(3 z+dCS&XsLT9TS@S!cB!RyGeICDAW-ci1c7P+LDfDnx#L83h!COJmn^aG5(J6`1d2UP z5GWQ9R4i=eo9t&ogknoAvHIPrQcx@)P;3N2pjbdyV%t_QT&yXAL5?MGj zPY_pMM2z95#!T;}-7UxDYw)ialZO*x9FvC#fZtHeQOvDvtkGF6Aw-9oJiDF|>ogS{ z2H{Z!ef7m-L~(^^%gt2?JPtf4$@9b7PZVw_Q*5rtSKB*rbmX-cs_ zF>xWzsO?}+D+JlIQi>wv^82YVBr)++qOnJRYm9tmJ1@x?&E5@`f(yuZ#_%^A86BMO zD69;y__6Lr^5o-38#-0z_l$Knl>cp$Y*b^PD{>imASbPfkw)5x^&P?+U=?IE^jE>X zVxQ}dhQ<^6pJ>=TcH3ALZ)#C{-LmPrQX*|?*4Q}6Y7ibw%K>?iYRe(N2dTc?#Mq{_ z;-w9ZSiYyJF`Ts{q5|r*HvEl7Mn`8Gg(OYx4h6-619fT>qZcW+bqJ!x*g&}h>unMo zmUj;Gk`_iU9jXqO+hywX$uYRxu7$CI9b$E>eL{#NeiVDBK6#AH;thfOKtvV~S_n?o zNCTIXwS-lvEK2q8f!+@qHqO;Hi<047ZHxGYbG0o{2v|2WvMVEmiLWT0@flocYtm96~&Hp>njQYDO#$xtGvm9_c`*SwTTB>JtXw(gg*t=M-zsCtSAV4At7)E zuFanmB8yX-Ip7C=0ny^qdN;d9f`j~bb|5Q$up2&rSS~iK@Mzx4BBPG^{Wrvl4Of7l z3dem8yK4TA9jb_e1KS&XcY7nBeIzVJH^9@0j~mu^4(}_d_$9ih)de>{MTPGieDIxv zu4RN0d<$1p?(T0)hWk|)*6}^q(b%c8pOxKM8u55V>`wwnrwhagUed+r;ixc9e&SGR zT#z$TXTbwm`Z()5hiYAJ;yVY9HcmKeRtqP3Vac+7Y14@z{c-cj8KG-6PrZ^@%lC43 zSaX1X}@n1(q>SM>r z?;6~P2f-Q7UdEFD`?+Uf)<$grf4jGl!Uhm+MQhD|{2bRS*31)7T1S1s265u~j&btD z^XWduYitSO6~S6Ox@y=>CLPcwy+~;Z9FW#~jgtrR7e3Prj*Q=BG}p8z`LVu6PrmaG zBTPHV(MgX}C;7(7li^ zg|521u!8}|+B1z2LE)Zw?yk3Xm6GVxdP)zIN= zVldG-JJE*^WiDm+1QF@8#>)lRa)QX3WWasck88~Z7T0yfcC4w*;%&zm>2Q28Vze=z z?IUPmpZ=sJ^<{!kQUQz4xgWJ-O$crwHBhY6k7gR|OG1RQ&snm6BnTxNuyA!z6b~C` z^kuhAP}K`0rgqM*pv8FOZdQj7p@OIh(j|=vLMZ?&D%hH=C$khgiKzn?SEl}&S(|Jw zW*LMEHT1VMj3Ef60kG(F!;Up|K=_5HEq2H7gvRDPwwO?%@P(G}^#q}W0~XCMiRqQV zcG^iy9k6~4Dx>^7p+XJMS{mLU2&DnAX#NLwtf>RS6257DK{T)DG6u2Bga~DSW6A!L zAW(M6%$_YYOLWz2d%fzwB}79!PB0CFB@sMIjn9@<+J+!dYMc6YF?;IRyaNbg!aUXO_`r}@j|MLV;5^$rl| zDrfPA`~re-!A#Ih(qqTVoW;KOW=f=Bk?D%v!h#Ot`PJ{;ZQ|MqFdf_CRT~=1_g67m z`wFHTUd{QavU@DgYBD{MSDOKcI`=6s*B&r4v`6`x8OAt9$b~Wec*&&p)oyO=!Je{; z{8r*&rEV;T1@=64TtVaLdv{zMrZO5dh`t@x2k;4r|vPm(`i*NIqu>t>8!sCU;E}I0X_6+@tY`I|j9R3xT z9@koAe5JEIA`K=28M=F-tOhqh>^^A>(w9t>C$^U=1Ui4wMB@B)()kXEYBP@tMt%z_cq?mD9?0kmB%CW=8pP?>E97 z>_;LM%TZVjt{eG-Kt(z9A1CrI>y4E*a%>E5KQ*(jquL}`7hKM4$s#7HP=q;4YhLQD z*+F+sQZ?eJ3$$9v%#pQ}h1OXNFol2nLuPNAl0b<_yRqnhm?#%GhY#vuwX7!*NGYMx zaKY}HXpgh3O~%_A8$>L{I2$lY#@PUZK!?1{AqkRApy&`F7svXYgxu=ByGFzdTF{1Ay{?j+W$HcQT`1`xf%nQg{9j6%Vj#g1o$p>I`%i({1){M2D%vc8|1acGh}JR)MC%2vW~-9*JG(@bVzqo}Rm+zIfo?1OuySMl+9a7n z{7YfcV}DRnt4t1bz#?NvTxLBD3_7qbi4LsGEEYdm#j_a0bRb3V5>nY$+W^A5RUd{l z1%;mf)M&|1uI?SjPdse&c65P{G>2pSXEtN+cFp^m>#fx_JpmwE8yP#WY;xihPHs&|Ws!pl~tJ4M$)%nzP z^La+0SeNdZ`&S8VkuKhG?F$$&#vyNPD3 z)a_Gbi`h;PFg1ZhM5Z&@@f=uu_34U@nNOk7Z_iMJk4V4a1VtN>)r?fA^>Fcap6xU0 zF{%U|X9Ebwc@7yHY-H%T^M1!&P-aNSeNOGTT%O~a%dn!_&~X%i-OSc0w*K4~_Np;n zW6@Is!7L`>8G4PW(rGma;>bd?uik7b&$>K4k+o0=;V!sbqv#woF!2SG>=Qdo4K#to zA~Tu9T3cx=sKEZ5sGw~iT`746f|#Y6p!ms1>yK zJ4jUuRwgw8TS0XpvKMq{a&Dgbu5nIhM~Gsq%a^UXe3>A`+#Jp~T|H?uWgjazI_>>n zL(fa6g_@psmZpLVtV^Q88k>Jr!m%24AVmigQaLu;0K&oe*(8O^8NB#xGIE-7jTq(_ zC4)s+3}5?!vBU;N=F|^?xxs&BzVe|lq%3ppM~0WB{2g=J$HwhWVv1Zv?E2Vf!tNq` zxcnnz94+qsZ)0#-<|~WClGv#K$~^uP!z{~O`bpIu%>1v+C7(hffZ79-p!?yj!`#zG zH&#U0ae}#E8X4$TP4mYv%zWzbo^!KWlUb(qdN~!XeP$%sbYZ<@d}j1wyNRaIl?opz z_bppWTwXszn9KTix+(ACvoZ6cn3==a>wm}C_D-|0&01`B@R)~ccCGkN=Zy30TOtNq z-B;7F2X%g>5LT18rXaFO04X*JLMoet4IrX=#s!$JQYiL0wR5aKr*4jF7Fbu&Ii#+V zbNqD`)ZcWKjhM>C{)Pf@@VGE7FnApK%6Og)B>J$>{c>cX`zeG~= z(8&^0K-Olnsf_|drL;}uW^68%CfYyc!`9Sec~*)IiUqhcCs2S>CHbxSjc<+b*bX8L zOR-g!f^8)Ta5Q8ORyZ0vo(6B{kJl2}vkHwfh7#)RS8@WwA6_=CW`KR9w?PSZnM4U4 z{ytE`F-ROhC#QgfK@5P&yl_h8WXB~yuYV&WiG52LaWCmBYSzy%5%xb75r&Dx{Z($e zErVyhSUH|dYWz0JTA~_pEVKbcT<$7fP?4`Ic0}5Irs}JPO9du2?J^R+ziRZcF{8sz z=6e{w!X1mWM*O=U;kZT$0?up^7}ks##kQ7;rs+GgF$jHwRg1( zg9Hawychc(mpt_|OL57hC_Wik;F5MtbOr3fV?QqhQx`ru#cr24`oj;8OswGh&mTsm z3hcdL4%~}A4mOJiZ;lfzCh@)kvxZM?!Y(NU7UoM@m>)@D#EYFIobHnDKhB$IW&=0{3;b+9q1C~QHP zaB+N`|LHJ?m8CxUb@vvmM-X+mu-kuOcSoN8m(ht=@3RnYZBky5sdBODOoGoU{X2?m ztT@|N%XhY-IaqTJS9*v$#wn3fz!UJvSa?-4&ql5Mu!yjr zABOW*Vdh;nOXL>8Lt$nkwvm!UdL>-g;CDn%e(D-*UVE5X&87{yTez{^7RPuMLo0Y?fq5d@Gn^qG%pqe0_Dx5cYG>^VaPK?DtpWfQ)O1UiG$aVQrx`J! z1)QUU+v0HJyPX|x>cEJ*rT%)sjqh|qh2r~K;ztuizr)6(+7(GiWq z>;$F`oR)mG?fo4gLh)Z);(sRyCH`yTn93eiWk3Pf83g3>Y!lAdClCUZ9qW;G+KM0o zvUR{7aU0!PH#=6`X%N}UOovS2;WlOg8%EG5HOrDZi6Ed4X;gVrWqCd^t&*dS4pb;T zpHK;_HMl}aN{6VI`{3nt25KL?Jw$YweQ?4h`qCu5E+nzVO@Lw_JXWyCeej*a0P$aZ zRSFIfCh_&rW&%%0F>A%P6=ZZ@JXQc?$LPyUF-PgnJ*oh5;H~$vxtZ-%P&x4K;cs;^ zhuNsf{`nz7j{E0(_&c4=ml+X`gU+VZ$cp@27xN~LXL9In@3$VNdPu3W_Rr5M2-!bB zEuc6nh0a&(pC9OMKB2MS?Zg@SFCIDN`-LEI=B>8R!@Y9*yt+5wKui-cp1swi8NWJS zx#ZdDkz42=3z>8a9hBiZmny^c1O=p}nJ+jAfK*LKWdT+VBV;m%(xta~mko-Oo~L@7 zU06TDj7yL*%#-?*3()dRkVO1DcWCbXWCdT^|5C zu)e4ctS=iNkgB6l^gC|0pHy~m^gAWPr8-_LNT8&~zaY$*)gffE#t%O3PG%G;oT#l5 zg|)7dl8$W2bN8iI^v%gIVOOnkZXlFpy4#T}z3CtbECOyT*C9|*1Rcn6?M}$)+PyiY z7u(7}C)e(TA$VK4XRh2oKYY>&pfZ^;Kb*nQkM)!XEYwXvSPhzpSq^%t^z|G37AN`>)KIBg`H)X3Su%6%G>H zfa{3>+y=a#6dyio8fCT@#VPZ5;wU2ohvuEKUG+)yN`(RUk2(9x3`t?)-@5J z0b`12uu^A#D5-K8bXZn1p_Iup3Rr)?S)2bf&dg^N8nn9|ooDTC*UnQ70@EtB@<>`G zDG$>s!tvrw<#=U#ExAe|D*XG~1SH144DIDIu5ZbAemuXTZ{9@nWsMCW7NE!P%9Bm< zE`ktIYHf6nC17lmK#%?-^t4UpQhISl0O(J2f>)6VJ=y3kqU55<13C7ElpNcZ4ItXq zqdDddn^cVO?ci#R@SQ|5x_TRR_2bIbK{0OK#X;3!j8gy(Abs-u1BkWF{T|VXu03wK z_BcUcFsp6uufSaV#{80^5h1OANv-`c4@Z1$C(q3_8`o5EVO<{wim*SG{ zxswCvWIst5g0{K!*nA#&z-YkY6*C%EH=jgoll;I`q^Zwn6w)%RPO1p2(*_XLi5uM% ziq+XS->T03$_%+*dnd6&8_J93hwQPe`#z{#tW65Q+B_PlO*tLNn`QRb*aD&zt8{L@ zY%OyM0;U7jCii-<7B{&!C^R~4EiqQ#E}e!G0ss+7f0|>8;y2sqZ zC=|W+vfpcmlpWG*FA+nux6AXIbrOimMXyl+dTmy|zYR#QRk_!MqX9n>t?0EMEU*1Q z5V*@-X}a9yt};Ckq3Ev)(^ZhcwSQMvnkf+c2}Nc@;w|9C&Fp)H&LQxf*xA%)o&V!tcT)5le$oo;59~R(%!}8n1uC5HDLYO0HXdzEHT$H3dQ=%nQleB zp^T9AHf0CE1U#CrpY%5A5N1AnVcq%UTenMq@kCKr`wu|+{sKX2*kXc948c@ zlbs0)VR@m0f=Dj_DSCmBN-x*|!V9>QNud~EgA1$x8%iYOD4AKHTAn_xpu7OHPUBF) z7+@5DMUN{86dkuRml1^+T8phxFIEVv)LRrpmKsR0)Pz))ngVb)lLD~XaX0fBDo|8A zB~!bZ6pCdilx5Jah{TJ$s^#2cUo*{v+eF%F1BI=;1eK?-DzaXIg zjDgt4@?G3!mTC@d2FwwMk4a*V87eNIN;(x+(Oc*@XtjjT;Op0W+hK!BoE+9g|FeLf zp9piTKZ(Yyo$&cnLtgqY>?|}^BC&NgfIKXGA}m7U+6Sd_sKg?Yd_M zFFKW*#B!BTG}NT>=1N0FcbB~)7fVef_0!hN!fptXv6jl%9#mKdxQw5fogJdIXxMX> zVZI=t&rqR9{>HF3^Y73<0pbR^iR`ozqFnYdm2^?M492>3kDFM+V~?9bzPfIibVEr) zU;Rl1Rh=1_n1%9{o;Xu(n>Lsk2sRW_eL>|IHg(T)7aetDqDwd!anoCN^Ev89d4l(fc;_%wSZtT zMt2@C+v%%j@+$}3t=Rnvi=|sZOUGsDz}NrrnYWWgeu`Xd74R<4n`>t zS4qazyH>y-e!(1GmKr;rLuIL-e9=q|rnZtHOSH&-U$%@oEkVcikaSd_P`O#O*CKa3! zvjTx72TZ#v7Qwf_W*TK>rzTgb&U?QOX~k}Y z1ve)nX341q(ID-q^M=`hWrQZL#WPHuIro zth+l^&Ge8F<(x&X$Vhw3JfaoyBS+0xUjJ>g7rT#0#|-x({?gm#Ubcw91JzEZ!QG_r zdqKFk>0;h2dDBIUqvl3!kB~o@JwZgE=tsHdn7NESO5mYHcbB67p+w`=m(COB9h&dj zadVHxP7)C)`WXN7q-n5Y1TH6DITb4NEvMj|*B1nZ)q0HAeGg71lwslTf$cw+rSAQ{ zc}FnyovhOAK*V8_bbvgb`p2ne!K79*s~tqI9phmink|E=llbHh&C#q`5Vd}6mTV~0 z>QFwk>i#Y1Lv0>E|B;zqw)*BkwZYYwnp5EA9AjPOwqb#~->}chs)xwsCS^sX< zc8h=S+&xqFxOdOQ9#{J}&QEyBjrd4L_BBMaw)W4-o{fLoT5Klc{&|roIPRY>62EZ& ze9>%qF$dW{7t#_dHZiV(73aTO*eeEcavvxl^GiVD)f``rwXWt65V)G->sG6T@a6C) za2tn!klQ!}&cM&tg$lfl1Ad6xIJ(^G-4o(oha~%#@o?-SR(#-z--^~1TUzyD*W7>o zh64)6+cp@SE-q=yWQT-lSkxDI{&{dJJ~MhyLB%gIsI8uU(`NzHGoy!|xmuO4J!gK* zjw=m9Z${j^0)R1Lz2Qx5koP=o_`=-8mwsXHV`s|ewl0_|!|gkK!91+7Z-Y4Fm0s(9 zC&~$xmDi#LZ}63QGp}i0U7frk?ghqEi##zr^(>q(T{k4Nnv*KvMMa*w`MT>1YjE=y zSDgwQjq9`dsRem;!YNfHUborcLY{NU+!!7|2mF*E{v^$*#7_(v)vu;1f|cWsoFk5@ z#PWo3i|*|zP>P<&s)(B>!L0%jV!Fd zA1gKcWrWhY<>s|sUELfW#dN3mc3w40boPKM6P8rm856f&0O{T|wL!j%`_LSDY0Sex z{2XVQyD$bi;teGcHQ7z4$WP1VJ};wG7%*Wg9XRezYZH2umPzWYy@6I~^)SYN~4gqQBD z&{e;T5!a>WncydL|C}SQmU-ivx&HtD-MZgDXllIv%^aTim)VAWLu@!z(VbDV+T5V3 z{0i(5SIbNF$fbMRsY5jN`hdYg5yJ3cDu%+wwopzUCwq6}7@Y>978HW{A6coF||B+(G6S8MT@bo(tWU%*@8W|e9Zg0~qI)rlLy}9xd z*E!YQzp`%#+y0vFq43%(2GimA%vfzMImoBoqhcQkuiFUm8tgiR1{^R{kGe-52|PcS z!^yDetSuoBLiCpR$OBM42?99*fd}ReEpex^fp%#-sOYq|9Ef9{U!;VFPhN*-U zHB7WL%peHV00=z)w8)NV$|D+N_SS-Ar`LA>gKZ;}D4ScdA14Tu4G6UU&pPgv%xA}1 z)&q&(dT~)|RLGiwM^oLKtA7Y}q)u0z;YXThMum}jg9ezSzc^POu3C4teHcHn!rion zV3Q}TE(#0azx-6KksadR6L30gy{u%xfCN{KaO~~ABX;BHzAiqU#RfB9QdD!~ap-U3 z-7|IeyMoKPft}kSmwq2Q@XVE!x@%pymQikB+IODJdR>IN6PJq|3^>EO zh&p*5W{{mk^BjJvino~^a^!`n(OkTi8f;>cd@MC*o_q?>2sW|g-~GF3Q~%Dy8S`XH z9ZZ}s)HNnfnOIeN+-6#ucr%qiIE0dXR!>V5TCAft@$=;Nn|wHRJFyCDC}HqiCOy7| zpupov93M^HKhN64Az0<{eScS+m!-!Y5W(_rlPZsO$K)2v=@qI!(-i@?_K|Wd0u85PJE!Q46Qrg@`i3%c;e%?#AbBuM$~UM69vPs)(_{1N5eE z@J!}yw;6wyTXo^G>Zo1vxmyB}RoCVhxJoj(;#&HiZRdVaXUX$}nif7SoG@ReIui&M zobw**KmfuoI#A*^8ljvck5J+*9DVKd^8M2Ue!P=Aju95=`KO9!^F;z&HuH ztjurwG@uxXVsu_skEpO>zFFhSF`_ zv9gh`PILES8;Mw9BmWEZt z0(;boCx;wBD>vB*6GvNjPMX$CPhP;!KRC4^YeaaJsYwgUsh~CsiC14VCen9*hI_Qm zwv+N;Y>AhqYN=|s4i#;I@<%>Wy%x{Oavxw%1~Z+zG&Rf#G-}v~CrexUN(RHMksTz| z*pas#=DwZ1Mxdg@(hl;MhrzMZGSqNmbOl~xICK^t1+nM{7x1=Mrp1-z2_NBZ&n^X# zgNAJ*+&%2nVoa$1_^^tcjdah}uPxw9M!I{mzX+=e#Xricd?L-13f?H0~iypM9^~gq%ybl5UvXhM!fP%J3>ZgT zFj(dD8?IpYi^*Hb+}_EoDUmJOyaOD_uTE`}Shl*p%^cUw(H)E`@!G9oHdvw10%v51TzYs{f;D%SNLV)0gSCsgL8(vX`xZxG!6~)C5Mlqpf)w*?k@(cI4 zUkRDUI(SQIEFYw~i!|0+7-Qu&u{~h&s=0#tYhv}SsS{cCaXdZRjN%c$^{L3;{N_di zuf7o8B07;V8~v=oUN(BKc zrh@zyVj}AlAw>o6S_(cV2vqQ{P|$;2w!{bxNSLm- z+2n3pQx(O!O`_||W6H`CZR#10G%^z%i_&ld?6r)ijj zx?Uv5xElnk{QPHmWvIGHt_UHpW&TMO!uq%l)S{<}TFcWm2%*Be?@Vq zs8+tx-R}1_mPc$+wdGzUTZNloG3&I50E9Pmpv0^bp`_`7jdpsOb#n8xM_|fGSV-3C z5jzKJz$zrw~DJ^-*uJEt;`D96&46HH1k9FQ#i+FP7<=wuD!i+H!F@VcS)j3Y}nfiMuK3 z1eK*&uSBU;uQrHE))25YJ@%*k?p|yqYsLnfh%IYWc_vO<9B5f0R9eXz z0wI0iSs53)Q6zVWOJ~FT$kU4Cw0AfRA|g>Ugl9kJp3HU-8?nWeKGB3R0rU@A>VBga z7RxpAON2+c-dA3^UYD+Sh<*`|?mn{^Z#;_Gr{t(`FSHgu|6DBX-L{z6+lFU4^%m?$ z#c1sp4H{!N8rMFq7u_4-!`~(LAQQ(aSd0Qv)z;F-p|Dou!AV{SogWUmTeCQVRHd)8 zq@2KOyu?5HM!w>{Jyun!^>H87HU1U%E=B>k?rCudl26@J=^CE<`N9);*e9Nn0YT^@^-keF(&; zSbfp?lnOow7_s_VWmha$U-ipj3FMv9jz-k<^?c2Jhwj+2gf7NHGV<@=fW;V{clynM zB?B(TN`w`-7~3y?;bLt6lJXa0P}Mw}kF4id3x^9zV~TpnC7YbR2I_2)IC(IseyX;} zx9ctUoti@c@EGEYLW>Xn1deA32sxf5a0V{^ga$l@2tV)`;{V_@lR71oWIr(h2fJPr zo0+%^-B3)7o5OM`a2^rXrF`Jf%vsJKgn3xnOH26fAya$Hvxwgju;3ME5sjN(mGb<9 z1u?}dJrVo{zv?VL?%w);KlsDfKMHSN0)J)R^Srwak2~S6=A>rIQ+)%TO0B_vDDp%U zf9|dfC;RmK@MK>GrSunQ)y)?u$e8)X^Xu}L|61tu?KtU9(ws5(5wEtLKeI2MhL4LD zV7h{$R>|{ajqk(rWzMElg0{C{px*F4yao%8C?!-+xrrl6p~*OvG0tPr)BozaBn;XYObn#;bqq{@F1DaN@Bt=Pc@t z>}Nd__38IvS6*C@83~8tOaJZOcdH?Vmc@sAL6!dwwfcN_>?^f+!KdyzP5}=zl&db+ zz?vHbgx01BHi;uBL6ZOh7x^A%9~(vUsYCQsMS;hQ>U`zi;v8cm6PiXY#k`NxuwjG%z=#7z z&N)GtCj4Yf-QL<#nV4}dm1(KNm)wh;>usb${QZ{roi>aR4;VOO)YZ8+2-8HKjsi3$ zen37Ze#-IR?(f{|9Jeinq2^#_f|C+)h}uN`tNUcO=iJJaF#gK-?xYAHwz55^#jo3V z>G$roao2+b^b)N`%=UOLyMNZ4=c&1Y_lun0P;mD1u7UdbrH@uGbq6tkP3b&yN$0Rz zZNB~GJ4R=zTD;7${g3WXHK)FeMAZ2nu0(#W?c8Ku{i-`mhmkLTfH_dp`3pb08-yUO zpE)$y8A~Nt^viy6r-Yy{{KGxY*(wD6?*F*sL(q$BEuE>s^x?v0e^*qG=l*n~9^dZv zR0|A?U?NX3ohW=*Rr-P7Xnj2F?nmw;2eVG@Gl|3c-ucSRTv^ zwt+KZ_@F=Cl^jq|o*&k&7Dv0bhM+C|(_L(rExO=1O^{+2Y<+=XtA3I3b3RX{;RL5- z!A!;k6c<-qZ?X};cnxd&Hpz8^$AP(QH@^BT?*6tli*K_b6iyWqI~-7@?T)p?ns zp_7}ef3qwwLg~LQ7b(-JwbO^_)tBQ-)y~M}BwSHk_;Mw# z-f|)?nxFjEldOYG{J0hV#ofS@%NjIwv|A37^U;wB&Xh9p+7fv^1M<#qoOU~k5|8uP z%sY~olgM#{bOdn12B~utm3ivx+)4T{B6HGm-gaj}dnht)hk{wB+T{kxT>lU65aD24 z)Y}{^j@X4$h;>A01M{5G`MwlSRp&CQKG33_YbjVX(+Yx+w=MOw4#5(5hs(J;m``7} zobUfOubYhvKZGoNAUDbR45d%|)EKBO<2NEa-EHJt*j4;}-iyxHDY-Dq0cP?1_0{W_ zW#HB4dXt?W2XhF6&R@<;w=pP#zM=G%K|O1En%KzEAm02+UVG=ClwMdQ6;IbSZ0NbSqVtO&O9tv^ zSIDmSEX6?A`<(vA3fb#kqZsTae_IjgCN(g%l_y0%ZS}f8uaLd&&y)$ewPAYvO3ax# z6IRj)hfW+W<~-Hj(-l`4%}|;H=1Ba=e`a;lz_@<7b)7b8*r9>h*rD0X#tw}_tT*wl zv|<%~CoAS}(fPL9J=yxE3cT>eL-3|*JI{V+2DJw}VDVm@Hj=k(553uFiiN_%Q}OUz z9NaMNH`y_HC1h0KvA7y)oU|@A%it?hJgw{sR3CbeO|s~$z!J>&hTte^zo7y@*JkeR z&eg$e6+{8}pv~T-5PUl}dwV!{1hc?er(q}0T{e2v$CXfWY)Tm`iz7X?c(cyX(b?RE zr4czb=f5bEXyBmZdgqX(Zyk}}$N51pJ(fP}&;IctG^o;l6_V{#T^6eFCtp}lf!~PC zZ{qwdm`%@E$tOhR*X8j$^vWSL7DneLJHuAdNEMwoa1E-NpAmuqoe&$$AQqK9JgFh* z&-UnKock=D2o|++~f0hbE!{A^pu*OXD7$?E`D2Leu48X3bu9eBecW(^K{Qsj(@MR zy7j~SiGiN!c1b}tB*<~bW&?KXr&rK!y_N6IK^{$WI#!cN1?>a%8>?iueuLU2X4IP! z7Ioqgvm+|;CRv^=z20iR`!R1LXB?Fv=9yX@9ywU{%6j9~{%NMxCbx$kwOaP^QIrRJ z&UK$BHFNY_E%(rzX%sI84z0VAIbgMadJP+9$vmQDXqYF*X#;0Ba}U(7t)iZ5>3eRtXRhX4N^JzsW$@jZo>=E13O+Kbpc!Acxl+7i ztG{RuQal!Ivntvnv}g@$s&T=(0Bq4}8MQVgxTqIj1UL^;*J?Lf|1l^o9*7Kd+Pr}Xca1w-# zykr!vvdf+cX*S$-djnQy+oq&x&q)~G$@KIxypzdU?|ysu_Li42)fQm?`cZAZb%0w@ zA2u60J5erCQoa5Cfq9AE>wb(c9cB`^)z;>I+-h^Spj?nD9H=)1O0Z0?eZM>g2UdxL zh0a_`387(Gk)yAte_H=7=>^A($LF(fbH6WpEwA?Pu+aWa@*m!+s>eFFt$ zAqj*pf~i5e)9V>zm!98iW-?#p^|+irhoH~M^=z@z2X%v1ISXyP7pFz}rssLuYEI`G z5;y2wcrxdHEt-#;?iuK;O|e-&8I$x{YgBwBt&w}oFmc^c;2BBULJR3!=Nf)$XkI-= zr39I0QQFMIUV4EQQf?Vi+S4NFdpYfi6PK$uPkpj#STs%gk%-5ww(&weZnaGizi_K< z!W!Iab6yhrM|ke>yCq_wlE6!AE`Z~kWw(`#Yq0HycYIu1V%>d!kT+{zTIdpTr;0yE z#GL&V@#hOMYJ3iVW*Tq8uGE5!O$uSNxKl4289NWbI zTBhH@Cscf~64ncL4%c8KH3ME>gliY7@XQ(w5}HHV!1B(Z!?>^z{#ZUz(&3k%b;5kl zBMu)(#w#42#R!pCIOtU%i~ECly8|4`bDu~{=kfP?dN@A}Sb1U%+01*7fGzQ>T{pj< zsbh23}a?Db#<3rXp_kAP8_M-0U%3+s3yo@+=Lny%wyjEB?f;m3Mp8P=;H_ zr5Hbd#1n^Cd(^f`vMNh3@WcT<>u`OEXIRV$;t$K=29U@wzp%y%a{<9CKAH>VP2f*p z4_QFS92N=RzPWo3OU-v{> zb9u#wSIELh&f)7n^H^7Wmi3nVsbIT!eE+drOWj8Muc9t^uxw&u~aYB;?wS2{^ zJY6)lTG=j2lo7j10Bjp`graSMH@f)T#HRXMd6CBsfCwWmRg?MW367iG zoj_Zwh1;AU@9(gIEPt2Wl3x}S&mI`%Yqid^xq{EEoCS9N?x z3VXiTGfDeemNRokgZP^72jA53%UXF;$Na1H;0tu_xrxgr#Fq1Y`h~Up+GbB%c7dqR ze#MhfqsqFVnmQ-#+4W-YhWck~AR?i+5D=4k7O}pl~lO+?t{#v;ikg6HI4RlaK z&@qs&n-_nR)ps8(G|vCS(@R)_AJpNd?5AtxH6D2fdWZ1^+dbb`7zU>Bo*lfc*a%`2 z`ge#BVBO?V#=qI?@FovOrFGEn)EpnfUu@@vQ{GeVjo^p*z?(LD5Z|%O(~b=ywxF{M z1b{Y+bSxd*LUQ#nPix;(yFGB^c^Tn?=5TB7TO!@pZ(UjU`AQ!4#A@18{M|jCZmfi8 zMZf*?@BH>6@!Qo&Lu2@us-=; z-RJ40vCf3+mc7?Ol)IPyXDIKj+mgq4!)H9d!<*FgpY?QL6NzT@+PJ^-np=4-{!n2I zUpO?c$1QnnwDj6&Vg-8b-e9kdz(T>5^+)zWGo9-5EP-cd2-hupZLRd$(Dh}TDLge? zJIr_HMNeg|!V932A56hSo7zlRy|km*%# z$%oJIMz46;g%aIf@XyF;E<8vBlLfe$lkyd;Jv8n2h6WA+9)1}`pp zbuC_81Q|4#8uo?nhH-|t?r~>BzAiF8EGEPVZ-4^6KQev-A2h#GMZW2+i_tuxV`fxw z&%D|^>PX5bD6b!z}CQ<@jT7ZC8M>13d?cQw(FKA5!1x&NAwb+UP=Ye zdc!k0I)qLm?E(3@*4J-%jN}k1*6QcYn-l6&uijU^^z2lk9b`c___`wI{S6ojKtPr6+$cv79Vv3_GG-L+} zZhe(pQwJt-)W&bEILX64q(q`zsh=dY&@AZ}2oj~A64JY|s|1dcPX#0wo$$C=*alUv z%H~QNq|LPn7K;rCaYBeSA_x=<2s|5<3F6`Iq4H`;zVCK2r6!N~-W|ygyS>$__W={t zH)8O_{Pl=hjMOrR29=~YdjL-j70-i;`@fN;{z?%Bd-40p^G~n}8=?BtVmG6vDung5*KHdy^&S&aQrV(g z>PZRs?lkXwmTXrfukL4w0*cw3G`_xtw-JvBtJd2$@S>-t#(D;G;3q&`H)3*@btTyI zUwKOP5gX-&_oE2nNPO-Teb`1!9F|?ZP1-2G`x&}H9y-d}DDV8wA`-MixgGe)FPg;b z^FaO^`AKX6!J_=R<;h=WlW(0u0ws6~3I0{5kaljAr;yn0VBy=#6aJ(Ujz^M&T=B#J zHU3nBH%XpIdKJWoD;r)X@*_2`d}828c{)yPls7hjgYbwF=nzMgY&y<=n>$qN%FqAc zsb{N`_5E|3+W?W>@@f}1%B^h!V%PR7F-ml8Hj2a_;g;IYrJlw%DDc5^+R>gc-s0Q5 zW~}Na6~&Ks&}x!+-mjjG`ut6@>D)`OBDCR3z`rTO@=f;U zGi#G>+|h9XtL`$3LYGnA%_c!_!>{6=IK(Q57Npbts?M z`(m_w7=aWJh(HR&2>gH;h4DivFak&arbXDKV+01yHn6Y$tAx_)9=m-gL7eemzx{XS zzdYS->M?x7idERF@C~wktc}kezK-}}>+{(JB1(j>9$Q>aui31)ywJ72?<4xH&?OKI zT@4<9)xEv^k;|K1n!(u+Vu2`3@k@+p#WHLM5ge4DpJN)>jh}kD2nKuODdpK+P#g$X z{K```IqMRsLB+BMrOMVPc{AAxq5~}x*Kq-r{JxWtXE*Q;(6<-kW-i-F*wD0X<(c-l zG!3FWuZp(`8G@B%7~NDAMmGgunC>cG5X~qw`z~)o9`RH6rtD2(4#qeoL*|G-=C`#m zV>gptEVtfeH`CJRVBR4P_C1k?p@-efC9A$J5iE8ydUfw{tpYz)-P@Q|;wowbW020v z3AYFy7=!Tq!e7O*m-&mRP=j<6E(hsmLL1!@p{fPUqGj zoe?a&e|f@3D&aUt3%O#Drp6~e;T`D61KId!;q+kH-tuJ6SF-cca@*@58wY198~aA6 z6pS8PDI$8p2>@o9g{$=XzOgahNfp>GVgyuf2ASDfm%eRoEv`05A! z_G~gS9b3G(7=&dDsG7ic;H5XluZ43YSxvo-SP@~t(k>{kw5tN8#c_Tv+#vJY^t;$h zA|Np(FGHWcSsIwVnHV^RJx}P+Ht_{Rm@>@=Ym080c7h*o>21eO5o$E+-SW&j9Wd*c zR^AR|oz_S$Ro_;Upaq@dg)JBXap-(A*i}WtvEQW>SV8^Tc)5)aE9ecYsL#ow>hZ8T zflrKWt8-ZITknmKEJ9$N2U#aPhLF4k>Ijb^G!(z^7(&A>cnl#rM^NJyyGX}va>$!m z`L4JT(|B$>@2XGb&1ogvx+tjMjMZCjDd9GVpKRxabWEzZGEaSd z!7w&ZslbF=R0y3$I=|Y%`yQJ_Xdy0Ss!bcu6FYm;wYzy`7_W}((@k#}L|9bJ&j_7N`y=QG-BMnN$?vm#L_fE%sDYZNVl}QJ;xl;=fBb8vVlg;jqhf_>1p*B4g79 zf~KW93V^I%AEc$=<<<)dA~G!ldCxl4Z!*!ODm9#)BVsYz)FajV1N)IcL0LxZRRN%R zCd!8yhDuul7R!Bm?4TS1iXBwCuc()Iy~YxQ>2Oqu+bTzuID*Bg%dWY)SMLm1v3luB zu-J8U+*(fmeaBYpza8Lld4{dsR_xPsP=v!VRfHWk1ti`Dn^qKnU5Sfm$F77@U{}(t zuXmS?54)1OTV-D#1OLKGkr(&#{>Ii2Vc=nFa9wG+VI{$$8`eEC{BFl1TdirzV+4(U zc(^=2JT3j8f3}6=G-a3N22g}YMQbxg6=R(VX( zAz^q-@wTmee?-nC_A9X%i<^434hs`N85|sfqYJxp2R;UK>wUL%9|OzM<~LP=@Ib@N2W)%;m8zj8=3gYEPX1kKid0Hr~#?U z-QGXgA!4)|kX}+yzw*_4Zhk;Y`@=gzY@tW<7Gu5B*>NRZZvKQ&XS};jZvONf=Y5fV zNjPwE)1KaF_dW2w;gL>WV@arUB6>DI!6N1d?1sL8&%G zQ9yxJ5dj-bAb@Zbfdr)Yj`SkEB?uyd@|&IAyEpsp^6~SFpMS_PJ3BiwJG(nOv%AlT zCRAZ5kMz}ZCcUd0)d?8Pxl>d%4nQX5u}53Q8%7gSB|cwr8>2M=@TCuKBW&{~)mIQ> ze1O<97;)iK;vgcPnKy_ zlcF`_h#mPrJBYf?7Ov0%Qiwjldt;Iw>$hg(r4!>0DGh{iZp_YPh5TbShHy`5Cb=xwL`LS~c)1}I}hh!f=z zA*u+B(c(q&(LjZ#ZN?Jv0bRc#nh4Hoz5kU6nSn|$Z3AuKH->2&n6^2d=wdQ0pM&j7i zX-T#HgReSVP3GS=uTE&-;OjL<48A_3;9$Gt!El$EKZ+ha_6D(-8D#7MVH|t#7slSR z`WX1jcTM96Jsiw$W=3!l5_G_dCN@n#34@xHRWx0=;5HLXmnsQNw@MgkDPXx22`zUy z!9vTW7-+ee?x9e$Tr1tPbJTo^FyAKy(Bhs3*djjEh-x;h&n!UKpzH@d`7tM&BYqR~S zzMh6QSFAi$NFmyO-UUfhwRUXo0>~dcM+*I>ueD*zzfNitY@yGy8uKj6Z!uR`ehWeZ zO z0ugz#io9`gACJ!(8NViv(u|da#lWngFO#ZUMoKN!?G~!rO9}(3+nI^#jw`C$Dpj|Y zkU-Vl1=Y>mIFt-GT==&r zX3m2f%lumupV^5{&xGjL0iygP6hLie0<030S)2u%tW9cTtRY0vA8*IbthI@Tod`dWcEp_dLUGF*kXP_k;rJmqpOKpM ztY%aqgllY1>Xgr_Dqm79$EIyhs?P4D!J(-}1RG^(NdT5CjlO2hPbO7S(6OuFTNBw> zvkF7X89hiv?5{>FV+$;xv;{5-;YX(W>a+M=kgG5EHGV&bluLd~^YZ%a{N9>j@J-jQ zTS3Yw*7YEqc02b<@(9hCN?Nu_T+Dyq4>_P&tgqo>nSvN~_ppl@Br`NLgR}Mtlm&QikNV$2a&XD6K17e$49G zW+RfJXE&2(ZL-P_IBgWNzEsjV)i_MBQPxugfU>3*&Ld@|xF~CSjI)|?n^ZtC4+}9V zwoS}Z!iEn>F*gQ@DH&Za#q_ZWr!6t_zR9;F6~47h(k7-%JeQgIEA;5;vq>Kt4G1zy z8AkvC`_0DDSjooD7^Q-ZdHMaEy59$h(+*}iG);4RCG(C>aLyyLrs0B#`g0AG>s#AdG8cb0`9`9j}iLcT1Lw>EP? zA00hPpZf^LP0}D{Nv?e>G;#b}q6ztG`U|9ev@!fZNp}t<>ZrqJ+)cWsC9<*UNwG#U zse?QZ%Zz9E)Gnw5cFJF8B-J8;%8Fua4IzXwGLkA96aa&_jWLB_@NuhPptE}AUQ!1Y z%Hx*v{;}TQza=$O>fw-EN$R0G(z}HjVFU=<;8?X9KRi0{JE7t3-=T)}l@O5QrweE} z5k@GSE|}24h_qtJ{v-;|YT)65E4(R8;augvFokpVyHF{dk_&1NVapySeI6=>Gv$w@ z2gd(>Z<&^r!g*o|<8OWPynmI#Ic(%5E#a-55RD|{`CcS$Ry|HyYm_B5FdGm9r95#H z{k@gAX+n^oGvKP~rQucBg};*O8tq9D)^G5=$R_k61w5OeLjj%-i2h#WY}^#VpQX@} z1ljSV5XmMTC~NE-?i+Fi3HPclwZ ztN`s3g7ytkh_p{g+JDf3ImyE{L0XGu2XZ98V?@liOawKIm#1>i7nz_Eq!g(_0j6xK zk^ z^D~bu>t;MZ<9o|UUZ5HAlwp3@B5&y)Sh$8Py4tDtt4RKlf`VjnDml zz90ua_iN0u(`K2`{!Y-=`^;yUvEg)i#)c{*kg?G=u+-AYrHoC4d_ddlGt>4?)HZK{ z=WDd`EN|K5Xr%!Rr9?nC6ig}>MrdO=jCOn==uLq*fHFumbWA7)IwqK|p-|k7Sm_$a zLd*I>Q^0f$rGPFMRtO z6hNhTzs8!wWV(j5Cd1YQBGNT^7GT_3GkhhhBoEMxexz{}1A~UW7mCr>o0Q_{!*tDS z3&rRgNlN|ppm{T4{;h=~XedXYbDs#uSKVe2;L4Mo2Nxj4^jZp=icd?k3wJn;BDFq>#>YHx!B# zFn3e%pDXj+4Xuo0paQ9f#)G*ViiU%L0&Ihz@gg}0ni5ic5awD)Y0q3Nw3lbGWx)aM zg)Pp+3JNc#+S79^7Sl-%LIl+pyI88PCMiMnRm+TYQbz58R59}h z7Yidoq4KDdIPlIsm%PTHP&{mSTTx(DpUC07PPjw`o-f_m&=w2p^N>Q+AEt1oNc~MC zr2+kYl$nsTRQ*ko`kO?E;B>rlv6zlmkpfiT^2{i23aAgAA)t)T5d5{$ILDz^Fpcwz zo$S%f$X*g;xj%tl6NjXFPZ%$hVVuw~k@JX<<@2cyt)E>B=MN}4_M!*$!0%X6-STeC zO#mS>IYoZ3j1_0_7y{re!hwg3-pTt7iimS&ErJ-BGxZ`rh{TNzT_$c?XI2LjH?$7l zEflx>0-3l`Wg&^1VT3S`E#|kX%1GakAK)TzQZMVqnZBvE(>*33jnwWeKKk0upa5?1a7k zY|^q#Vwn>8TuO`?oTUUEC06)(0#V#@TNv8*_mSN0H6hKw7tPFLN+! zm-=AFg*W;35maE5PRG0~mXDH8!$XL3KZeuUDWncE{6l68uM6lSbxLw|5*U=ZoCSmu z=5iTX@lH5$Ghr{hYsTUY-3L55eC==)( ze<#&D-BK^+a%iv-MyR|gN&?PPh@vr>Q$7VCn9Qlbe_=AGLQ1G)4&KN4c}DWg5Xl_h zyqU@QG$W3a2)ZHK#De;ppFHPZWpjG6^m(_!S<_|7ctbQld}b}VgVDumM_dyP(Qra% zmiBq_17k43#k9eI6p`EMmty61#u6mx9rSxp{C84{#GwF*XIpM{9TJBE zg*aZyiKbWq;zgDVjZ`M3NE`}~cmq;^#GybTj<3meqgVmroh0%8q!fum!L;lNjl&2W zX#?C(8?XFKqzD1BZ%eW>NGXzq0_6D{Qh;=!z)u%1@rJZ67&##>@pc2P2j!DUeUVS9 zpQ7fI3iE0rpLCEj!~ctycxTSLRh<2`I5{G!GsmF0rG^|JM3gF^!XFg(b2d6BA05CQj}pLtx_lABxEx8^W+mDcKm7DW&>^Ao9|j05~sNeU|1+ zE@4na6t9~NQLn#3B$O0Pl@*y#qO4#-$w_EgYic5g;+onyg(j3fv}0pTd*TWaMVUxS zF^Ym2rEgY0$k{~ zW=8t(3UqupY5aI3kj6L){I!xwH-RiqD&4k|y`CA_hYDGF3CK-batEATgGW;G;9YQ~#@*0`7(QIWv<#-PW+Q552v<-~x zK!0OohxRuH=qMl%lBYl%Nka%%=q6DNjO$@$i9&IAWM!5{{UZg;EKv&RF?~qtSsoKb z!>Bq1*rMulpzHVtw2gU$6sUHfK07nDE?z03>R@h|Te9XenOh>w$*4Mkh?wv@E5w#z z!U}m6=m=>ZCBch$E5$fGKnigjVs7cyN-+-akkWur+{ldkKP;obad>5=7>8E~6+RBN za5ny6a%m&qkE%&)d05PPkxoR*r`2qhzv4$}`9Bg$-14;)?2+Jf(#9V% zGklp&BCScoClF!ydsq4mpQe(o5*APxT!t=z$-sA*j7y}{N`^fBQJBBB$}&*D`D=e= zB7(6hFeRe(Kl)Kv|0B`_CPPZElF5*=ggj2^F{?6}(yOluOzC(d2x#N}n9@dr1-Z~* zsa$BV1R#@11R~OL=ec0=3tba@>Axnwp&1E;MbzH;b6pJPIt$s?!KBDi-CL`K>fRxx ze%0yYGn4OQo9;%h61p2rsG#n?_v>x}DM8(Rn;GpDHr)Yj)E%Xbx*H5k@WD<6L)}pT zj#|7EM4`A>er1(nfAqDn+l1SI5o*_kBCnG|7)Z}LwAJ#lF~@4l{!qxLnF*PDb-+OI z1ww1#knj9mUnQIX+8DkzR+_ZIS)0jUAOtM&+89O0*T(9t7O#ypAk~nyI;%6W-If+> z_;I;VtfAg%Tc~#mK)vI0V-$*dzoP10=J33P!GOwj=V~$Toum|v7n69CR}16)n3M*L z_k+v?{A{&4@ZVc4jQ2f41>Mh-)x!N;K?+cJOEV+=lchU!KY=u^eDK#w;~fEW!8G16 zJKaN>(LHa`#Wdb~Gvb`l24xu6Aa&`K}W%_5`ZQ6IUzX3wh8`-)I-6~Nx^9yo8U5$b6N_%D^tNG=i7zg zjxD|%Y*@1wo3Pa99bp0aMQ*S58q0od^2@|h>>85WYfaEm{*D9?kY8`TMkIbHIx4_Q z?!8PZq5_}}W`AfMn*wBVr^Oo4^Rdho?QB6hTyk7>jp*=-tRH0a0s@QF-WQ}@o4_); zG*b$UslCMn9R*%V0G7aurN9*3>T%5NZ6y^^V5oxv(>gYRWj<(u6nLgxV9D{PLSV;~ zH96SLZ=2aVT4ebCZ*8U>Ez?p@q}-U{iy-JIcM$?Wx%pv5ZLR2Mij87pg0C{Ef)Yop z6%tc)o5b>KvU%2uE`DN{Sn~QvO8fvMc5Z5FlUQW=29xG(JuP!v1J;r(-|GY&B_2lr zfu7FB(Zr=KTEQkod2uVoE2S8~;z~PPYA{ z^jhnL|51maqyJH3T_(O;vvmQt68(>=>x64ll~BOFA6(;#dPY9+$-?V9it0VriA{Mg zf{Kmx$gHtfL}S*r99lz9owmju4WlBViCMsM>qHhXa-GNmf?_ZWIGrF`ikZftmSXC% zTXmg#;ds}&dT`%$38{koF3gNypWs(J$WGLERwbca`T5uH2qjDcQUDC`HpX6p!AG}2 zF~H+3%nCJhwpO4R)IIl~>P0kic2uh1NX#Hr0wYmD!vr8@0G;cvrDmrI&BB`%V3IAA zfIJLbk^hS%NdbQX4)S0Jn>f1^EVCYTE*^^Izr;ha>qDjg@GjSZrp}Oexl)=r;eA+6 zAt?LT(1Q9K|2KEJ;M<9v#n-ali*pV$I$G4lb9^D1OX#p(-0J$I1>Dnph139z%cS1R zfWohK^;yqc_2B{dHwhM|guSV#-sh+QwTVe?2Kl9;kyWR{kZ z0?aHy0cMt|<-asF*QPpy=DKuqmIzi7d>b?StU(vGGR)cD`7F!R-C0Dd z%PMqtb};JOS*V=}3oR@b{2$zF7Lo;Yzo^7~8IKBL_B`n;e2KUCXG5Q1V|q9r82t!O zVB55EHsJ%%%9x09t5xvYvVm>ltPUp3FE+8*7oEqAkL$w3$x|`AVRDgUSjHUM~MhtdeJ7+)YYusLz4#(eX#H<`4q@RkF6WlSTA( zmNRyfLZrSu6Y56=buTZV(|G=rN4dw%H(htPP>U>l!+#Qv;#MLD_EqX@-3)^R{R0OMh}FS|_Vx3?Ilr@W zk<>xi&t@k3Eg`#QsV6sxr;3je66miT-XQ$7&Cq-B9Dxq}p}$sSqs^A^1Y1E4RT!L} z{hi>kS+kUUoVXGpwa^K7+bIA&wr&Ii2MNW% z-fDKQWkGwrQtX<`+1wcTkCo>f=$f0QxSb^x3OLMOBbBl1@Rkp49>*C4pq-S5w?p{L z4+S>{RE;ON=%gC(;0lt3n0f?wf@>k?0A096{1>`#i#DPQXOI__xhD{ly+Xny2=%2G zn$WZmmWjnZKyx${#=lacxjuS|{2)7r@DH+AS;>i~z(0WxvU3ReAUiKhz%P7GVi_Zy zRUFXLrx&i&XML|mXK@)9-wJk((8N)46MlK#EJZ13OFSL5;_Skwupsqs85_>J zywxWwr^;F#le~0U@=q>R)K%Bj;PJ`Q4ZTzW3gC&dK3uyGeX;9)GyLb;PsS zy;Z{4;}4vV^~6m~Tj#1{CR2Iie@q;p4de1QV$KQUBJ@$4#K-2Bz27H{RXgo0!kT^L zjL(XheB}JVF$DP0F4Zk>!Vk;PGlmZBm~XPZhXx9*r(ACkp~nNSf4@?V{d(H@vpJX6 z-W`n@wNL;N7H1y2uS2lJ-1c(!~GL{{*d^8Gf6Z_2|*(ZhVvpEwI?*|tOD zY*QOoLvtr(1NF9*=tAUnEXFao2D&ZRSRh*@L#>dssurOh4 zRZ>xD+6OFcmUB>6^;9%f8X5es>8UA)P(2mmEVR%Iq@sQKrhM-zqnX`kz5j`#;K;9R z20b!vTv|V0%3NnZO&^uYGCB+{z)oIt6=IFPcIIa09A}sg3jiwVb-R+@6-sh|Wd*jZ zwOQ)YThFk`-#GJUQER#;6v^ z2agwU#X(a6#p!ZXe!B5tn6KXg*urXu*vN&>#^w>)JSy*iU3q7T^5Vw#D#SJ{a(2z4 z%CtRf*J9Av9@;EwEZwfLokEOlQe$lkxxX~Cr4j4=Unoo0(pXwGaOj|!AZ_{jE#qUc zGJ7?}S=X#e+vb|mD?(j(ZCQ-NdTBTg^$#}9?C!3?QkOexW>rUJ+0qrx>SkHmAlFg; zXE}rp#Zr>{5@}*Au3PCWu9+{w9It+S~)mbQt?`r59nH>D6GrLr>CISXp$YFhDs zqO6rxJHg6o_M}Fb@9z!HN}7HqjaAy@Y-OIK9H6>RQFUDx>VgTrU#ioSMK$Ti)7ZwS z!Ntwvv@z7vW4oS?Nd6B>J#EbCxucnRH~+7Pp1D~JJ!mIbPjeqN2=gUvbLQ0`+BSB( zv!Pj^GJtBT4Fm$?uf=8@e>labeN(FtJ2}f)l#T1}DaL-^k!1%$kKHV$_*mLH>g{#)!HrOlI$Ip4M+tG?g4*Gy43EIss< zPCpO`$cS5~fAJ|Ea2JO&2>Taf%?~;|n41W7<|_DVMV9`R)-WX_#x*e^C+#6 zR(D8u{orN{)|;1=(Gi)UlSpTT{Ew#-eWWN{c!<8O0Yzr}Jq?}`mpj=of z;gq2y=0|U1!&Xp%P5sf^Qri+B%o7o2GaFWS4Zgg6+}S~gmihG-v!{Zv<4pxHZ{$#F@e8Svm*-5VE;bwUDW7QbsWaZlleL*^IOEv>^IJ+X?X2^R zxtc-(11owJ2P2OT5$;xMX7qNwY3`ymF<^jkvF#j;aj}iiM}1sFe0?rB>t!=9+t54e z7q+ko*Iuxs+L&;>Vp#;P^8m5><5MYvwKIIz**T$qh+XwwLi0sbKDI> z*NQa{hpLb=*F9RPfVMIx%Jsc@nd0-VffF>YKb%oP=)QG-I16j$!w~pY{<`I4_+D+!*V}yeq|P-U>K*3+4+eJa;nd z(+jZae>t}}%ESMr?beIvdAH)B9+j+(qdXz{C4vo()6Vi~TE3!mYKu7fzUHYjDZAOt z#!g4A6C0o1RU&sMQXr-QcDI_5-FG0nYpuf^NJ?3n^VJx(bLoh7jwH_Q?JiYKCoPBN zuo_EG%3oI>zSZ(=9B%-!mNMeS{MPIy5AqM(%08@$YkQ?^Tn5(pv!qfX>hZe~=8yI&IxtqQeqtM?f;B^Jqxd)>4BQGcQ~_40L1G1^ zju_+P8YGr6PtZy@7NC*88-$d;dbq2VdBa}80fMlukDn_Zq6tg>Cn2jHENX-j|G?TY z+1S$vR|PZAHe$t`J<#=pe6CQH#urR3W0nko-zmSVa|qs0{F))~+ZAv%4}pKSX<`?% zRS10GrDk)n($Wzw}6MWj!+iw;5Pnhyzh7YUmD_+*sRx^uiCngQechn=dWBS;Pq$OP| zxVxH_DI|W)P{idqSrzwS&ZJ5zByH{Bf-HLlS4Rbm{WGotn0ISRnD>u@$FO?J$%Jw? zFrR6smg$k5eNxdiMeD^%RdTg6`%qe4e@l2p>&diwE*eiAv|XHT0mqk3D^{`)`(k!t z!8z3;G&ljWtgn&lXk8H)-R+f`DcUvjgXhe8JUk^(tJ5 zb*kzrVSeGazYwapW4h8F!hO=7xu!Vac=7+}pQ^+~&{V zWWon|%~aZ^hU99O_qa{IX$nd}HdnMrq~lx6>bQh_=1Ia=^yel}BU&$>M48ezV#VDV_nJCgEDrG!(45~TdCt)v1=-&&z1 z95};6pY3h&|jc9AX>A*@|8gr$^l@;P>i5SFb#gs@oGZmtfTYkZXE$8N6nW-|qmv))M3?x>V- z+E9`Qc)xfQfXyb+zYOk!vRBvrzY{%nz57@ zTuq}Jb0`f@m8V+d;VIvgna%>5Ifb&wLr0hlZ@==ntR%xPyy%)>PNo!Le;>)3H*S-I zP3i?>?kiem1*&FqFbz~GG%!%Lg4PTyyv8yP#&w~w??4~dP|e(HL+q&U+=U@3b0;mq z39s@J*K`}0uMDvXu95m>xWUDbH(aH)xSOP3g5C{;+B3ii-~ceJAqR)K`b1lj$Y_Vs zXxu7SHMKpQAh$tN{1dBNcKHsbxS}+(=x&h8KQ*DRS#Y@_{79*FKQk4c!3qpbg=k4y zFHa>l^|Kts9o6@U`{!m2T8_R})jecXHQFQ2Q%>5&@Y1<8tRjUyLOZAmr5#j-0zpw; zc+EA*RKPgu3hWVAp&-@J%_UrZz6H=zccHtYEwkWwCF+M=VhivFWj!zxnXhxOn2B~W zz6J2L9OW9X=`;3-JpiNC_#Qz2luA4g1e%sq%K?)(iy0Ue$()I~%j#41h;6_WrScRv ztgL$&e;LSJPfJjdK1z10rARnHUQm2w0;u9$Z}^+B-PKw@12y2G9`hWfg)E+;w5|&l zVUAe-j;kT(4ZU1DZ(@t0Y4B+=@NXS^iHRV8PbtmZdjlQK54byk7(4xXd@<8bwYy$+ zuaLNW5XI7aiRsi(C}tw@vrvOe+@8`xiQ7_IJ@$%CnIdrk)@5Dy99(?7DBr($a!t58 zhr%XPawzODN^X?G8fuU~4x`G7yQL3lPw?H6{{9}}M8CdAIMHB@xLsOAo3yNPJ_jq- z_~3n4Q_b8&(Q&`DoZ)=PP!^)t<||F$K_(V$u%TvV~|qVbMOZW$XR9>qj$<*2CS$hJ9l9v0o|S zI|L}fjnx@jNd=bj?AVqN8^Mj$TBy%c^S>)teD85jQqHy?G~xFY(>P@)LCX1TC2}(e z#eUM5oUd#{>#mpIFZOKEIPTe6Dj3i>*k{+duDWJdrGU5HY`%UKgZ7WuT;V~`9h6c3=4xj3EbXlnbIomTrKE9}b#Z|!-8@dg z)&}bs2h$CfQXMx~H)&04A-TrExR5N`=i_(ZG&9Em0QqeWoml;V*q!LK1lJPWVX0uh zQx3=C=dFZ(E=eol1}h4VT?RH-l@5sayEgBKvxL2)ElK1COCgR9xdOpy?&*H9!FsY^ zZm_!3Hc^DmQiRU51Vz9NmI@AtFieP$NGqWTL#YU_XC{K&Tq(p+1OUtoqf}2UsW209pulYdW;488b#1@!_b$V%%o7j;XfxI@eVK#h zFvZ;mOYUPl!>%53m1gZ`d5ZYPZ*f)Ev@tB@XIB|>93_Ho@0$m$AqO7Cw5_h%4w&-D zR^;`AVk`2xQWv%&kWd)E4LtpCXaTx|b12azEPlJIj=mY>3T#AxCf|r?ue0>+t~UBs zz~^51c1j7^+d?TFME2nL+O&PJ4dFC+f>PlNoyXMgU#RT3eo#D#XWpblk-e*w=z{=z z{BorOsEK`uLiQlvdF4JN_91x>5wk;r#vx0IdXYoI6a7yD*MJIK;98Uv3S6C%YH~i~c2y_qNC6R1P})F?QXpti=%Pm-ca_x79b(On!$`Ui)an`9 z>P^uq*lN!c;GG%A45_+YJwPWPt@!%gbU;xavTYl~1}VWv$66 zyQ<}4TTZ%S;8TT{Ps0AEVo;N1X_K}5O+GyZyPy9krLXmAS2@j8bc>VV+(W{yrW^{` z6=sQ4PlacR=FWW4h$J2twJ@F}O5n`mE@T-0g}abphcn%UlxWc{JNx^bYj&uu$i?%n zAIx{C^tcrnPav}S$qTZ+6@gR1J=olfu8HQSgfQ8AglI3}lfz=~G1d#&`F)ol+_#Wc z#tq1KfWz}I^A5u&0g}wLAcPG81bnw6GGs%{dBydKW5!|WGgBPlGrxJ*@|mLmPx{Pv z_%HrneDWRcoJO&@d2kT@+ErJ9=udbdb)v^`fZwge1GLt~p!>AU??^ZNw;GSV0Y{ZG zC~0)0N8ND!Y&wn*ZY)Py=V0ncE7j4FE<|hMM3{27zhQ7FPK2KvmVR_i8)8Sj+7aPL zSED634Wb{dg8lB7{@f7}cy44>0lD8mdY!#A19AU$b?I?A9xP==8K z8LV?3df6jl_9<{g%svtDm!C#BN%;x5TgGt?7QMOpk?Uv8yi4(LDZ5D_)>5W|D)KD0s|7cm85#nh7ia+QF|{o}u2 z4XYT`Xj$55EvwPKy1QJ~8in9t4M;$vkR5~CdzQA>(`xU3A!M=;(iPNbB5m|dtI_{L zNIYnvXx2I?F->WRCs!0iv;;h8p@6OW-~1Q#@t}oLA1(WuG~(ly5#ti7&QXDb7IeZ5 znDb$Vk-TG^3tU5w^Iy1z9zUAd8agwldqJqx^KMS}88e*dtPq<@f zu;Ozv3cwfZ-7fPfX@abyAzDuO`>0q)^P2AO&B$ZGkbe>4OQ;sXYUFWu&~qQd6|`zl zc}0IYvtnAU?O1x;F&+u5YbXT})6(Ktd_H$UHuqHaa%Q}(v;vFm*SIB|WyGji?qh)# zaPy{WlDDdG(;wwT1=TPBLe;F|_y@Zt?c5{|^xqn0BP4tUa$xWRvEY-2%pljy&B z&r-kPI_+xo8}NE;I_1&tGO*M}t+R5l0Ub2U#BLOJo91oW06GqZin#BaPbt`P9RB8D z>NqIXClqzRVdg&$D1O@utTkph2jg1v_fhFNRI_1r)GHkqob>V8ARt|3NT37449T(oijbrFNSmH?UL1_V3UIoJECs=QQXbZi}ap^p~Nt;FI z;dKU$5*=G!-yP z1@~J;-w3H1R&n=*GtVbfi-dE`Cxldyv;?K9Od%*0;G$FtE=r|9kgI0T7Rk;URd=^E zX&IguUR)h+__U_f#d%>0K^pyI-5&*4FIvOh!t6?7jZA-F3}RC^q(< zf{67WEgD-BA4v9l_I`m zyDSR0WM`rZT(X~>kV`g25=-_)80C`()xf*55r8L`>=fSKlM}3KD|g-KM;uJo>|beb zV8Tqi*07p#iHm2}Z_8S}|4cp+;#*0nC#aERkpUj+x2I`gDhu=AXRCj178OI;X?>*$tm zE)_m0&LpO=r`_CrqJQR1pd@mwR*2&&r$BHwNQkfM1(<^i69qhg*b|!KyXQG$mz-Ji#I?VK6_)r=wsS6it@op zv8;VSOK@46OCh+d0WL0U3N9{d3Ir8_i?sr_7VCACGEVmjBG$)*kpf1^CWep<)}>kI zIZ6{HJ0&~m6fHs8xD+X1Ybkm_v5_|g5$oepq=1pP6Dn`G98H}H2`!k<_-ld3ei0Ft z!!SX%9vEjT!^%2lLT3nTIEi(r_9=kiI#h@M!gZ+5sZ7_QY%jaVhuEF^cE9Wn*UV0w zgnuaELi8Mg$fhT=f4My!AC_*gIiuY<*x&KsA_&PGt!oa=V*yYhV*x;@MO0Z><-4)DllnQ)Zm~%=j zNz0WIP6|pQdL=YAYz1)qqE|vo?G%d}oX~+C7~*!DClnM;^@yZ;MJeG_p#&GY`?eCf z&_OY$3*?dg^V6Qs&blYKN0_-!la9l!dM?)04SrNHrGPh)>$GU1qOC+U0oQQ;c@bp@4E_Xz6m zDg~UnNAmuutwd7y1gInLb6mjt4+<)$zCci4rxbAN3ncX&wh~EwL4Z0c|1Xcbmw7=! z<UWg_PW_Ce{+F#pQa__oM;E5x8QQBr#F6iebYaRUMbNOG?~LCz(1QsvaQXN_ z59Z}l(u1K$!h>mj%JN{s0Z)1`U3qgavn8Y46{GudD0N`kQe#C2rqmnm4>YqU$M>qAj&WZyC)%((>TjPB%ii0xWLiZ} z3`>9RS$Ga^ocpX}4yZrvg}$ZCc@zng)U(f!*!1EvB1zp9p6_%w)<1`?iA|0+XeA6k z%Q4`cMv3kR6FEAtw%+v&!w-%ERg7wXPOAag9{N=f1>O`kuhSAF zc$pIXO%QZI=ZX(B3W_qB4*#(}er246ORqB;l`(Ul1$FvY2u>0vjA`%qovlJ=11$0n zUV-2<6NX2b3WvC`zBJKY#jL8(g6MEXjtH-~mf>%*>J?v_{_gY%)5lD&AUsxu3Qx%M zE<^7_=`!>_6bP=+hu(LOHx)3tcH_^WYX^rxGWNTx`Jz8?uhY$elrio(X#H7@kK9pa ze_DXHG3D**NA%HW@pWu-EG_0%p}j$r^Zr>h3f_PC8un}Oqy)TQZoa0};-@O+o)xDm zzNRIp?5_yDA1q~Cr$~S(9%qNY*n4PUKSS@Kg>4HW2*)S_y?4MOhz7=K@zW#7KVb_*@py$o6nnEjVDf9>ijsM6=B5z&kOtl(xiSMz z+?a*W5tBsg8qD0&&5{(%-8Q}OIkst)yJUz8_;^iCdj$=)%b$aTLL0y+3_hmQilXx{ z3a5{6*HHYx+cjZq*ca|f<_okI=L#CR`vnY!;7a&@&8s2s&&~>okI&bP$Fv>XVmv%2R*{Fa1ZN88hF)Lj`Ok})BJw=3SzJFN&Rgq;R)W=7?8ccMXNuhC z#Y~Z#*20;--gz<8H=rdr)7K&N^p@vwUbbd>pon+V6^b|tK>!?uiU2qYDMY?%HDamz z3|woYjiY6ZOMy6JG6i#^Z~!86J(n#yM2%thJB2aVa(7L0g1wqHg#ESL4bL3Y0^W?4 ze@GnU{M;jaRwZtmyNtP! zmg0=CjuPDgoJnUAPdx%roDdYEI3a)xI3bLt1kuS-An0U`*#XNX1!G^`-T}ipomR)J z1H}`swS2MD{j5@5WF1CbP?WuFm%D~$MqVU_hsut)D5l;BTH?QMSwg=E$3Z{KQOcmD zsF(5=iL&cl4CnMWY4{qfsjw#%@#~Xw(?DRKPgT;qBq#mxvYeDb7?7u|CEv z6)>8?%YHN9JCEwVWvAV3G_xh8hqln{lCbJ#v_#Ay&3o5p2hO@*(ED5x2JsTbL7n%y zWZ5<>R~JqYucF5#VGliMEmS#f8pd6cn}!Lr9Iavup{jp)DKKJi*8pU3CQ-S88oe2LB^?3c^#pUo4L z9IE_?RQVBFf+}x*)xAegm)gEZi&5Kmh+ecOsviF2m1G}su%cG+>9>x zD={b}n(tTAg(X?WHFs?d;|hhuwP+xW0}%e=jxS|a*@{|y*5$Ull-ZC{!>+4KsOhbK z4Rl@1gkhywxF>sFozvqZQDGF#0x9K8H&cyG870} z#-zLM_ND^H;i#p%pEsu}T=C(kAX>vw0poBysG0_55LQug+%&Z1Y~DS033E9uK&qHP zP{7C)=CXHFY@8$%M68bq1O<#-E&UY@Rv!Z~ANlzy144|LJQ#XLBo79k5w~Ifrp*Ai zEm{9h>lg-y`r}{t8drFHQIDg@Wq9!LQIQz4*kxjH_jJ0lXylNviKp)RapIWRc$xpg z#Ky~)F|lFN`?J1ff4XC|5IGH2=!yHdIa1+~zii|s5ZUPDAOBrSW9HxP#pXmpmt@sL zG?(z+Ws%6}@YK!B*|Z)eGCqf5NMvX;W=!=Yo2!D#my_~BEVf=;Ha2>&r>nU)2y^FU zk-s>ll<;sglt7?9lBE=CQPR9_D;6FW{Q6v$wPQFZH)_^Bt)*X1GlUS9Uo;K0% zaVU*hyQst%vlg$}ccYvJV%F6^u9DT5HJC;xM0fUzSPMH`5nq?wb47SZduTPh^Y%Ls0DVDrWAYB{*rP<|@`xzXI&shEVA> zT8wk-uaxV1meukN%*+mAqRVJ85?xG*t_>!Ni;p5P&Jdts>`X<&*qI6hI}^h-3K&N?hHEZRhH&vw5V6-w zT@UoSf6Eo7F9ENBAK3cxia0v_Idir33^c=UsJ76OjZdjy7#!+%UGVj@lCwPUak|Pk zM88#~wQwe`$S!pBFZ1kQ!$(X+;iz4tgXCmuM9jP-4I( zW}!b1B0YnU{zj0NZjJ+piN^;Ns_2NVm-^fgL~kvjx7}hj5Vf>Rj{KeT^LHVL9_+pY z{c}^{k1G#^mS-mXn#2bP95>|y1leyAE5UK9-6R7)@6AAmV<;Yo;4n}G=EJ~@p^WkU zHvgJxM~`@~50AFzzCr9WmUS`pDrR%qyyajw;b6r|clPwWrkTAcI={WC_qZwMw;r?v z0_*Mc#G7pS2SZAk$+QF|97ZJ^B_!ls+Q(BapXCV2XXkscUVS`0OocwCp@J~G(uTUG zc>XeHP)MlFlYER_sfjt9PB+DvZgNw^Dn18~pFhQ{ZczfU3c6z?n!{Md&zuR2Rcz(I zFjlekW~f7$sjn3s!t(U@d=n~Q@kf8p9`mds5D!?KBoNv1tNdR48u;MNZeGFDmBoVAQdeaJ46b3vQtXRPt<^RR!0a*N+Tcwzh z=!uBF#ZhSF;yCFehFAPvP4wI_*HEqlfs1Ngv-GWQFp-hc?^{Lb@_Pclcal9dHFGFz)N|ez4p&ZElP@${O?KfmAX%FhAjw!e zNjTqXk(4eM(B&?dmXmcI>1n3Dz^0A#lrmooBKEwU*nj{rOssG^e8aEsXE|MO+!mhP zXi6A2{3C6I_4jTIR}&;hZw@Hqilb0Q#|w0gj+dfqbi5RZwKY?~*4At(WeOcH1rc}s z3IwZKyZ+SwTp!!VT|XsaZLJQ`>bSL{cp_zlTPqc;Y_0Swx5cji8YPCieh79emZjgj zEp}6&VBGp!qe9*~QQE=XlmbCV^zJR;h~9#~*4Dq+9b(tG{U~%tjE6$B1h@XR?ue~_ z9a@6RbB#O10cmzeI3WIkQ1y-&2vun{-23;0ruf0qUbF-W_Mik`5drbm%_L)X&@`Ee}1t9lmp0u_-D0TFXFwf((DsJ=-)4sWICo|KOw~3TC&@>eY znr4AJifM{Xe%M{RW#+gmEHei!u{Qao?uxBO8Cs0iRPrt{&uVuA=4tIUqV9@qJ~V+7 zl+pwmkODy!;x=CaqcD!UsxYZDJn7~j$`cN=_`BkUS3E62y13(1z-U;w<9w51Dy97ZdWb*f%_jrC>*RDX1Oa~o32Qxf zy0C@3>BNYTQ6rt$LXq?kw!jJUg;8PD+IQASm;26ILA0w=+D$Cle7$u5IkEFp=;F?^ zN4ijJ&mfB3DaCk;qM}wseB67E^7Hs+5XILi#dj@==o1Lh^d_{EedHhVyQ^m^bdy65Mb;lOZ;oxiai#l0CyR6Ua}`TPi%ej5$Nf=C_t# zd7uv(2w&#eZ7L1mjxz}LCglNloYiUDp*-LGBD}BE#2x3gbTOungU-d6#toN%q@HPs>7>GME0apV|ZXHc|QZ-#&H6T?Wb0;kFeCfw!!l-&vc;I~~qZLtr2;(Nqz@+Zmg zm9?w%`2VVQXwAY~yp!F8GHIs|HnR9m2{qWf}s>FZbx^wZv|)m&eRMv4SW=-MVW?ar{84(J({ zx}$DKHfO!3vT-E9>pm6}=557dPep`vI%q-t+)eJC^$>vTC(quHG>2uK=Kh~OHCf6h zBjD>c^%C;?j&JbP(TsZ*-|WI{Z^!6_3=X0DSt1&nu*vh2`G5EPy|pic;U^ChQavvk zIV~_(OcU|Z*D9mNRc2FDJvmvgMQQmQP?sGXU$83cyeKVe*X3U?%`=? zgV1Mb!@QlMES6-V-NsTumN!E$=coyUVjNLrjoK!U1pmk-*Sq&a$lOcy4V8Km{{rET++*RqWR+1S*d zZk1!rU1`r46I4;*g`_#z8tG&1;aofOT)hbW!+R{_#PFId=T1-GEPTlu*yzo|r#8sN z{@Cd$V~is0@xICb6$emrc@5gG27Zy}9@GAQr5by*%X7?FL8@^xE0ECDUT>LI51p)( zV~#M*$x`>g!qw{@ALq~MFMx&Yb+*;J-D4Nd3~ygZ=><6_0AaQ~qIiGSXP;-7K`_|C zeV*O9|Fk%Pj!S(ds=1;67O-b-xD{uv&QV$a^B#{T#myXAG_2F_w2o+I@|Z05ECZFc zV*7r9AyNIHr@K)|ZN36aozkUop%85*6#NaQDa}!gW$TodpVd9&scMw9SDsrlwsFDG zl|`8F??MA3+24^x!x{W4z~&UrmXCEl?5SilQb|>0=f`HRtk?SuLw?4y_R=m3H7w;J zIish&6u;#Lb$LWitHtJ>fWS`4WGyB$*0g4?_GKF?)z8n0Zt#X@ODGSbb~WmiG>9mC zGAN~I+!OJ+yf2O@!0sIL|Hc0+-|)oWaydvcVL3qW2GppU>~ExhMZ~Uu zvzE<_4>%sKO8eM_ecnr_j7q!AJ!bHLhOwxtepSwIqjkN>{!wx=seae%? zc~3B4*xD)Rt9sf~P&am{4Z$+9J;0%yv+Xt6zO$Yi#xYuv>-h3HPec9uZ!G3KSocLz ziYn%_8+_?IpyXS>S*ITrO}D$?X^_w2K}L0su}?2}nkkL)Nh~@DkuaOV`12`7p8J+D z04uE+9)dDBR2mgSm$~mH&**Gf>*LnGPS-qdYgw(__J+q1W|Ss;PB`!Fq?fplzPeF@ z6reSaKl)60z21HF*Nq0G6gA!DgB(rtI`^%0q~(3IXOq}77-OM9CGuO^Yb^XNXp-;u zlqPGm9nr<;MOul!DVW<|e|VIF8UN7J&KO28fgcou#}O3FjJhK#=O%K&gg*X5y`*o# zAD)q#F@cbX+YF{v?oUq(V-kU0C^VvzHi2#a(^J!q-OZR~L)0hSXEp8)iMC^wV&e-x zU)xw>LkGI=Jn^&%#(wz3Q`gvJ!{)^KO)mwVn`UuKxib8t${RQNx$3@le|x5c8D|Mi zkhhz0g#fsy`q}$zN-l3T1rxMgiiKa!R>k;(prgtG9lOy+xD;C(=B;9cJ+KCZpL%n{ zTTh`5B7pbxG;bI&5_wzvg6!V2Pi z#VdI8Wiujvx9l>M(a39Jxqr9Jk6o(beHR{l99q>o#i&T?3s=<|g0gN|sLP+5D)l>C zzIA9M`>C3DCcL=Py}I{VqdBRLD%)AzJHTj5plBG)*}Jjc_6jx^iwu(@LafGCTV3CM zwJw`mDm;>4NsdYYCsh*SbdV~}F(fV+A?$ZHt%5Vok>mFq%)HXO32UAn6-Ja;$gjkR zTHX@y9l&gC{JKq%tZ8j;0rPE(dAZ*kSKIr6@u3A4`#nh9WoP4m*0UG<2#TcJ^;#MK zF8pogs^cvgg4)J9-d~NcGN(2-Q))$?5p2KBD%JB|GnQvcqtMEbG(cP6O%XN7^A2$= zqJg*m%m+;j{-Xs^r<`)CJP_)v07LMju8m=@TRE4Z!94Wss|9?|H1x)1Gp?)5h-t8Z zWlJ%F^~=y95#Q%6z}7VNHa8yHE1kbKILrhb>1AyHjazM1-v`aS&*?_ahnA`1ytSr{ zx0Df1pg3jaWMf)*8!OmonO9nP+Zm+@Hn&VY=R>i~QR2&6db=34ZJ60O2Ga`b#T3#w zp|r8#LTfjWvGOn@6c`H8z)2_bU^Zb=sP3oEH~%ko}<;!Iy(Z zur!p5Vg&1Fe`mehd)w({rM0bT@15x|PN^*iS({vRk3W>ww!gEtp>f?_39SuqY}Pib zi?^$8{7JA;V<~Iul``}{EF0t+a{wBP+uS5d!ABLH@9wQ_6d?GhqCX$9lh*-#WDoC11>L66GD4#dQKK!ihxRE^>f*>l9K-s7hiuG+q;_!R490p5 zmb&|G_#k^@2c2c*9s5!bL?40c!e?1BnEmR#5AoUuP4fFDz382o!x&DON0FxX9#JQZ z08yghe+aLPVxzur)qjtmqrLzgy)uf9#L+AJjG+6eqgO`JL0>^$Swo?;SO2hj% z6;Pb7I<{J{0E3Ao8fIzX>*{47Mp8q#$&3kis8XrpwW_KZFlXvAJoH z^`VN8bw7(4?roui$lMM{xzxovUS6M_-&-?GTg@I1_dcty1oiO6p?9LUiNk15nhxlc z*i%i>PTNOvxE6MSFWSpq35P4-sKb?&i0+%+cfsX-su>BS3Tic_XNxL^n?Si%b8|HR zELV=jCBbH?ONJ*~QT2T%LQMDpGe>yeGTtG?KolAFUDDHh#Q_yq#%X=6V>KAYn{o+0&pD%g57sBUvNEOsC?gf7*P#lDJ9F(XKrQ~dauLMI^=G~=NKT~p3Fy;Me8YIzJkf!HkKsC z;}GYm1PdC*7La0Y8Tf>dO3bmSHhR>3kr_4ai?g^nA#MZ@qUN4xMd)Pog&nwFzMLcS zF^u>w<;og`9xKKTBa!D~@;|n6G5~z)wFWj)b8&kk{ zZics_?r01mVrr(b&-IzNi>3`=n?DDm8>mVwQ!@P@TcNb1$2@9TGd~TbftFT4keHD5`WS>B>q2m|`rES|eB@Zg`&fq@wio&M`fXC8yY{UL1}RO2~-rf+%ypFDl@!ef!X z`D`O>&Zd)UuqW>MZ+O$ESuF$-J$m=YEUw7lb}V&Q`7pL@j(5LfJ*ap2caD21=#ZMy=9DoPpm!;=u6ATTr0r4<%er|dO|D7rp<>H ziI^bUKi}K&U#Tn)TerYl$H+q%;3~^klLM%c8G@OV>kT6GoKJ+I?OEtuZL}d(VLk0; zbRqy;O4~dU+fy5+jKcP}p*sMLmFzR3vqBk}s%`JbmKIa6U5!`*4jxz~C_GMY{8;24 z8-SJa{9_$}^Za9oX(j>avbbE$<5~Jr?^q>Y0{O?rY}GRFx5f&>CUz0e+I3oLK?7$9 zCT2a&2(!Tp?BgyY^0RTvy`LC6E$V!2tH^i)Put3c?x3eVVe!Kf3bHYMiuEuq*fB8? zc;<;n1m3lmVj>VqF%kHey_6>c;Xw>gC)_(MTfdl=#!9a8x{ZQ=DOM`8jrsl(jg+yM zj$hfNiuM%-j0L~jFt_2Y%j$Ipp?JAY znAT@?lj}tq1eNh|#4|BA zOfd(r(VM(s@J)I@=JqY%VpB{$`lBvznkcYLPuiJbGk^9zG79_+Xfg$iyhITIZviIV zHrv39rHJTNW5S^t!Gqqjk7Wqb;4vuq@GO2IFr@ z7}E(cXkTVgr*SA|QNga^YRM2^_PyRdnz4*vV=i;?-y)Z}m=r)Rv$M8^)!6T?X#79c zzB{n0VtLqeZbBgE1kxiRA%zYh1p)~@3B84cBBGSU0AlEp+d_?iA|OR1i=qMwDm;Zm zK5x&{kbMKkG_eS3b?+?RucG}L&?rc9F5IC@hdq;d1 zbI%QP=ymvp*p)xP{cr5bSNvYmJj_(ySnL5=xXwal!6s%R+j!6~Rr`)e!ktV&$Nfo) z&i5xZ4?q-)nQUz?L94umMZh?RK9f-R>Ey+~0euNu3uGdZBxL%|H z9XFa4eg=*kOW^3Zg5~wPD>qHQO}hEFelw1af++MG6=nKu9ub6o19bEoMMuAR0HWBX z>qB6Vi_nAL^0ajXfG(pLX!<|DC>bl$@y%#lDA-1b(QjVF=r;=W@Y}Ax<$!*p9MEss zH)X#~__`!S(asQV=(kgb-%gPN@LL;Jkf%4bT)qkGJFoh;(5{eTv)%nl{HNT(X8sPV z613e_cd*iS7a``VAQJsYMVkJLx+B2dA*25Q9sNhq(SII*D0bo7l0h1UV&52_P}*8c zBV5sm6b+pi_+3e3i5UHWt7$z6F*?zU7@bI=9!?zbw;a%klmj~Pr0hi2`iByxl@ey$ zhww4QBd1~A$420I{^RtcmKN%YJJ^|Vjzn!0DRp~LSxamr$5`y=&@q z#7AJw=x?BNC^!i<;eHllC)oBeR3rl-HlFnrVk) zyEmW$jTKhuux6{EEC1xMW+kYmt`BRI4Tuv4s;Fh8q8T zwIt4yE|GP*1`7zs{+9UKH8?y$Sz`Bq3F7SE5_?HbxLz_%`|WS(0{<+@^cFh(&yo_Y zu4=}g@9JWAL^Z}3UnoN4K{G`7?Fng^597pMEcoSaS_GM2kilQg=i>)Qb>Z^y?nGDq z3-3J`H}I)M0<)Uf=sk0u|hxVAZ0uY4zNbD`0SQ@=opDTjl;_sgcle@j3~5p4#g2g zQB`G(HC@$)5seWMN#M0!d{N~nb zMf;qvL>C-4TyUHepbLIBTyT*Tm@YU^TyXX8U0_VUjtdu1S*8mb_?z*IE&$cg1r!}! z-~lk^&J>Ds=T?LvTAyOzxN2UKwVg(x*rZaoP3o+5`CHMO9lwxS_)r`13Xw9kJG8JP}yDfS`cu zjoJ4){{S)jeu@;E0Z{I5w!zK*-fa+P-)0*$USR^^ICY~U%?NmlNWuu<=)4h9bc_HG zKoskqVeKoSp(k` zTYTPU!@|5dT>pJQYb~&j*(Q7wr*^T1NW^H)tgnam(P9WOH>ZS#x~FutJ|aQ)bcHpi zWJ2d#=<;sRky1-wowsevn4x9;Epc^st9NzFdswGvL;sfc`yQ~k=_MGa&g1`<_)He0 zbV@AR96z#TBg9^AR;F0*WZz_47fQrfr9mJk(Pn~yjY}*P3%!MLk`Q1vshL^UAzrk&!a`}$Suem*IU}9I3PlDxl678F zAn~d8Y&G3atXiaD51auvMbtoPM2z#&tbf!CjHCl{*TfVi18GrZuw%L=xM@@YR}W{W zh5Q%JPT^Orv(sL=R=YGi#cg19h;^=3N@|Lh$0@4Kgu17w3vX+R+MBIJPgFj~Q?{_xL#-XPD$hckf^7l%I@T`Q z2cD%k`+`!OeF-TuwXZy}Pyl?knhUt#QCL1{M3Q2#zvfZKs;8v%ghCg0oZI;@X7Q2$ zGPi^4rXkEe(%M8!@Cd$`;LQy1Il)V)3%28;hL?fOl{fz!1|d4^(5iHP8cJNn?%gwdQLS8=@K>E!b5Ucx$IR%&@7iB@=PD zS37&O^)5vlPr%rM@f_|H0_FWJEJ!RG3%QzN<5aMSBhsm$hnR?}oN?C9infR_gq$!` zTTTGnT0tDcb>JzFRgANCVhes64WC^ov?h3x8y0-lgNL$+-F=_+84260Qw71sIxS)^ z60*Yvc^%~%jV#i2NTgMh9) zRrWyDl!@F}e-La;P*>`T1a*ZJ@EL^CfX$c*Gs=*9W-PiBfD*()9i5X+DL6 zP?x4~VW#fJ*8@Nl<|Qi196qKIL71F4I!_lA9nwP^Pk=FpqiE(FZXn^xJtGmr&|tj; z!0;JENN_YkIb(hrXoE2jh2l`e+%KK}w;XVdlybl<^&dD{#IsaQUAPV9Os;xpx;0kO zo*>-NWvl85m#rcN=(3lD%eE1?>9QA0m%aY?E(;bz2@r)YqoPcg?I(iJWgMNmjH08< zJOIX=k3w7J@N$k<|;$Sr)M!$Ixqu(gh!*6v1%~Hha_dKD;(rRtiJr zyJd7^csM-J9E9B$D29im5%S?7?A@q&fh?`i(N`NpnBcxm!9>Mh?GJ=p!^}W22m%eu zrr7V*RuXJe!{r_trdM5?YYnkzFL`3)Io{2IB2G7xQXZ%3E)dE$Yu+IR?m$)FBK7)E z)XS@L2{k(x{1wNQnnsxC)!J$8iuc7J!1sUax-u+?s4=?vJ@XE!O|BW zJ=4*SYxE4+$s9dD!1cq?b20ygqi6Vqqi3D&?eLeedJ3lWc@7uTNO&RQ?D#=Zb~itV zn;-l_ewxYeDAzH;uVwMY8urEtYwsv5YR#XC!e4FpuWw*&4`18*rp9<}3nB2@)~GVh zd>;Rk$lnTy>>j`k>`EWu*(+7=SyYcxpQkaM`m1(s*Ew!n`yXU=7I z{vW*VR6m6amBk&i zW``B~keIu{dew(Stl(&=f@8hp-cy_0Np87&H(5LQs%X%2)?8U^+3$`7w&Xc$fj&02DZLDA*k4{2z5RSzgn zo6<_)q$c#LufI;Y&$N_guuIK5C#e;}kYQet@{Z05ADq`-No5g@F@8~PmB%-`A?>MQm;O*AsK16=B-P+GmHz|w}kQMxUY#=-EhV`^%J}=upv4dVlYahZxU~X-$SQfBht!kreM-gyFtn3|YjyfZVRaQ9qvDEQR0$Jy*5uvPltgQjd z+-?0-{Va$DS6h4NC#ih2+o!eJ?X0jHwEG@=toPi)N)Q_C7*v0g|CDAr{P3{YZ=M!A zEG%{qNGiknq_X-B+fF^OKB2p9i$VCjZ_QB-$`-5mzR^f zgVts~6#V5UTQrM5Jt5fdajxOf%kXve>NB=*{RuBMSN)Zm&$`uY^|3WIbQ!0n_9|kN zKeo=16+p{+VHTie;ZcV@$4Q%7aIT}ql8#u9!b1W#j#$(5PrURy@>lwOC1M542&14| zxnIZ|6NK%}W7bakK`I+-amlm3A7L#ldtLDn@rm_8-LJv_uqmmq3b^N8Yqqjiw$zM& z_N>qD{nUB|qIuW}Yqs8&O2saxRfAdvr5P;mGi!V7sXv}GDT+PwnKkDYL(bByfzk26 z54qzB>(3!HIub=yEODG>`_N=|W0?JUeGDbM-JVCiN61j)pz_1!WV?Io>U{};RTsXr zS`=7EzI4jklf`^t_CV@Gwb^QwX{-E$@lkBdmm@mgPUmBp=Q0@l@G#hOo(7w37|a1Q znB3l)ZNH06KV!X1|0kusZL7UzSk2*KwU3`n3#?lEtu;~cI|TyS*v<9<`qxx6M%ov( zS?@>FdNoDEqgefO*4$f-v=d;2-7ynmb@<_7xIZ|AM%pKa;f}ftm%6@5J@(bo5mkDF zU_uRs8yuGJnIQFGY;x*RVGVfY77~9Zyv-aPsElG~euN{IcLlNR7v{iAw?V9?OWD9E zI(!5Ee9l`8e8o$*oz7cr@&K=Lki850?Yy;0A4$~#W5P*G#nL%<7y%pnme0Gb!C!Ay z5!Op%@rAZvHmLX9Tzw)D!P9UncIjEAbCeIs#S?;I`ny4C#17A&@`^r(64q>=GfZ^^ zi=D}mU{>a^Pu8FC!dPWuH{`oDppIqA6MWX^Imvu&h|AW(EJT4pKo`lyNX(%7gk#z%X_uTq=AIg%?qN+Z+W}T?$cT+fTZm}ad1RJYywbP4~y>;E1r%(I~O5?p)Z_2fQ zTF>ewe?e(XktNE6MYh@c5=xX1GiR{Am_x87Pk>lhY`cGFN83}1{yas*8Da2`C7Kd~ zEA9FQT8e|iyt|dQaFleDYHOvxNlQ1~IeWaiGo+TO?Rz1(pP=>(VS8S;wFxuLW_aCF@ftxNzEnT=r+Mt(y;Qe&AA{=Y{=8 zh^;r<@f$3iNdk_(ZckwRn5Di-A~`a5umuoV{`YxO=`1kB#inzV5)zT639(|eQ=;VQggx5Kwp({nO02cDxvi^SM!{Ss3m~$Y1N>rrQ1Cas^fjIo zij!S#VY@GgN`P6)us3t`EfklVNO6|8vZc$cxu+YOQDK||q}2d!{3Wo@TiJ$N-Uao_ zj>JW?0j+KQ^nFwSs{cMOzaAH@!w)m)vBDkN*hcH0Q!qN={V=BNT$oMLM53@{br^QB z%G>NxGGu~vNw!Xw%P#T1B!Ne-c`~zHafyc?9^#L;wYApuZ~{j0SG>eG5#oP!iLV0j z$%>xrNor{wZqyZicnI5*YP(0zqF@x(I^46a#*>oG!$mrIJB*()gD)DqP(PaVLWV`C zQy30ambSC)RwCC9b{*(0pdvj2w0Ug-dOY1WN1sM1(O>gA*aqk}3g&fCrm@71wvjTv zM{m)(Hc5UNwiEga$`ZTux|y~dy_|x1cc`pjn=@^X$oQz)1Kn&*^_M6~p2Xk8 zzu*J^lkU(^Bz%urr1-Ee?~Tycb%1j}`XR~!x|4ol zn|?o_bLHNQAj%ov91o5p!G;wihkdNEo2r*)y7bJi^vfofFB1pRi`>^JoqDl9Ws+;UtgTSdL!toPH8C_7%Yq0P5O^b5 zej5+7!5%;lmb(8!FzfWe+-R0sXe-d;i3qY-=0kFET$ETWt4h1iHbBukQcAwE1Yg5e zCfWum$?WJP7?7n*X`r!H<85`=kny(Rdaf7x00}+#v)nHFL0+Y^ol~LZ;a! z>9G_GSN$5^DOMKSNF{C=P|UAR=$&XWuJ|=%*|SWiE}j8fszWIfa?drm7f2;8?n*98 zebDxlK8=y?RMeXsRON+8xN>qeRDmBE}wtXCf8q7&IXyDd8w8j8GH8Au(AtCgC=_J)3f zstf6J5c@jba*Lb!qG30bHw!3#oDa;MYtK~la}*grew1DY#I1S=Z0(l%9>z-Xh^R3o&JgoC8zt6;rD0%ObEaImxv`*oEqQ}6m;FnM9MZHUYS z4gHGF-4ak7=A0d*>m(n$^pYyLPWdsr|o2pX!rF0 zf)slPi6h$muxWSf9{O#vomTZxl%Z+(5sgIDj-bUDQU^BMmgE(H8!0cFFI^WX{_@G zZMF4P-e4oPLb`p+lLN_f#-ijuS^m?IFM@j{g{ZGJVl~OIbes5P}4!<~?!gw|-US^wivwyEp_K-wMUFt z;>f1O*tEOF)Y7yE0tu{f7|EG<%2IT_1NpHiyB+@#=x%ID=`WBhZG4t@qTU9 zJSIGWo$Q6ji<%N&B#TJfE_^`+Q(yc*WuY&&8@`|v!WVJB1=eFl@7Uth>oIK6JGLhJ z4N8rgUaL*hy0Na9S-;!Xq82?PSl(O1>VUB>?Y3p412d4mgrOe z8%)O@z|8r3%t*HCJ)1vk`z};)_hVjo}^B zDer@T6_gAOzBIO$M!L>z@P!{pEx;8RMhlSqj4eQdU<*jzYrCRLU~B>ZFk1i)FlzSM z*6JTo72OR${UBE4xesWus|B=BPsNG>#@DnMEBHli75q_D&^^E)F_k7_{{yyhKlDRX zB#r%>R2GkY{w;w6FutG!MmKb4-DYZ7W0t)hx}k{1G%oo&`gH%TYH>)=h#UmcOb=*4$q-Tjz*TR@q^ z2i|a?uTTk8CpQ$U&yyPB#bA8~m4z$sQ#nLT6{8sL4J>Oc_68oKxZI!0qqW$IHO3A? zJ$ff@4Z!1jU{mp&t6oOA!1zLJ4=D3EidZIJrM1vt*&Hg6t%9EXda(XJr9wUT5Iv0@ zg3l=uhAZw69H(I1A&?+u`urKxhHJw5MM{7bJzq;juZoHq*^|u8(?!%uf^dUCf^eU~ zK-gV#bkQEO>h24!L3EODY!GCev~^Niv6&}rjV!I=V2L@?(hz^(U6!;skHA)w<7(+$ zy2QEi>ya;Pok?70h)T4H<3W{C{%BAjX_rP}3pV3RTmJ}2KiA?1UuJ`C>5_zyNV?cX z;tSWz@8hcCnt2ibg=^;UtF|@sCSSpx7CnK=@OGBHT+@68JOoePC{MDoZ(!-^ zO$ouZZmRC2Sdnb)x3GPER6^y4Mi0e_rQNTk5*HKY5Ib@frt?43Qe2h>I=*nMJ_&a@ z`E#T`D*(LtVa~^Z+G}x?5{SjoS#e}>l+%dC(MIv`>oGRwds|BEQVyj@nypkZSR75R zI`O^jPE}9fMAE7u+(v1xx1wNNHB5+Ss}5S5`XGSYAzk$@o&-t)TXY@{8h8sp{J}o( z8~7bHQLrX>ib>9Hq0p*X9GB8gSpw0)p%OAyiUGDXEo zzf@bL|0yaB$NDiEHj6sz8z~2KIPwgeq1toQ&Pxx?Eg}) zC9ti2_7wd(#Yg>quT8%?iLPip=x=WyYqmJ!0Q7$-tC%`=t1dxsC{ZJ{J}tCX)^X$J z$h`vKiH9sAXcudmH=(XQFREK205BtW=f5x`!>`&ha$G%ov5$;=q@I1ZK9VzVb=c-6 z_AmlAgfDm8W=0-Y&km2C=hO*g^P}^E*$W!feIk)#rsXIf;)^Fh1@YR)ys7U8u}2m! zY{axcdkQ2FN^$6aWMNsF=l^wFA{}(5oVvLhcqEB za9h#Y&WzfEQ6B zOu%Ivg54&!Cr`l92lES9%9A;D*vIj9jV(KvpUk@XPp-?VU&`@k&&R-RrVW&hnTFPb zQ~62k^|aWWI=$9JOr3VpV(joLo79qpb^{4NU3G60apl9TVm&eM0FjuEB$1eoBnYOX zSK{nlWZf`P<0-yVR3}W--t-%e)_39{_@&dFajR|oJzD;>ETUD1e&G~ZYoS4Op8s^w`?j*-65ow)G|;298Hfo3DfhBLZR{Px zO#2wgcve$!OwLeWfIxhdXK4h(Kd~5brIe zQ&FJiVC9-HB_$C1j}ip!k(+MMZ@f0vI4?i&k`T*OxT13+9qyy$Qc-AO2@yFS zu0J$Jm%!+pg8zaP@0LlV=$tDa&RLpazosvy{7mPRH4`0587;x*Ca@v+;l!rIL&gaP5Q-k6LaB%TMTMb<%Gk^<&O_ng1~FX+)95?l1gyk_oB%)Jt;J`TM-KLcIX z1g90S=((qdeY_ssoU{YX+)*6j%G|gJ+o8Fb@nle3^hx{X*k-(6^X^LWd!uBWWIQA&2@39KXSxJ|FiBva^s^`HZ&HyMD-t4x z8TwiRqp#-}rkgBGr_Mw7ilg1~5D(CeX9VeJllU4JL@#hvaQgK#|Ao^p_*L8VtI;6) zQm^UPUcF8WpmmLB&6$@c=J2X z#GlR0Swt|W5wnOH{8tp4KFppI8_s{zb;_GGYH-r<=P>(b-Nx};w#P|B-qO0aIB77= z8>G*oe97U>#T1SchDB~ojeF-_q|7=JTI`y?pfuL{yeO+~+-*Op=$rn6)EL4`q&Q32 zNr|v4d6h%3uM2Nc1+$bmML$B3%)E85g~(e6X|dUPoNXaGk8`w`cai*(Yreg<RxN!3ByNI0f#BrtZoNi9W^-P?laEO>L!t_H%_m$|dothy8+wme_O z!fbU1^agx+aWj>N5x9v%j0nUnPi1#`vAwyzhhn0k-mcA12TVg@vVF6qNVYpE3p3fi z3g~rd>8wtIC>cZ>i`(aDl|#wU{Zk9tC5Hl^|vmB*2y- zPq9rX0ah-qRV`7_7Dz}G#F{N6T#SSzQMk=1LC{xqfC;biWl?4B4)^w^+^?BQlJ>5| zMLbDHjOY4elAOSQVUnD{(q@6*yzklUpJiX+l_I;a4JG!+^m)_}W}Yl1U_T5ROYQR-tOQ!GtVxv-SrcB;!EX-or&@wJjmVlm@Lwxg z>)G~RvCH{ynlLJ1MS^4z@?`7ou)R`!zdV!Ice-Hi;>5rx}X_iAF)qS^dXd~hZ&4@2Zdy0jvc@){qSEa2*zAB}~W>58aYtd6ZL5s1cTGhIip6Xd3;XTz4 z5Z(M48Pf(vPX!_|Ur8b{Ur7)%mrG#GSG%Y>n6D%pGhazy>;vtsMZPKlHTkMv{C)OM z^fQ#7X`EAraZb@<(>Rw6<6NP|Xq;bbGY-6+SBr6sDLRNm<47XWI1!1V-bWG>zj<=ITtSCeIoLtwo|7!_uCzr?P^L4bt_YR2GKd5Dqazup{Fi zrBlIO>R?57&%Q#VK%?NjmYLjl!cki3jm!fIiw9yaz=!j47|wTbS9L_WEu+v=aAbL!r|Z**uK@!fXz|YMb)LJGQxcs04u;1(VD{TTNz8s9@Isj2M!?x`E!=VT+YN}l@;D_BdAvyy$>W?x zq(+z-=M|Vvaco8(rwjkD?0e{B$55hx*OX%AQC%xNhEgg z62#1Y5*R!9=52|~v4fXz%nn`xW1n#b-YnyLUSC1Y+}Up+jh&N!$k z@Ae95F&bw~+ggk>xmM#CV;m5P#*sv#aU_VD{Uk6N=TWK-8b`u0jU$24IKA4sjbmoN zFThefvFuO6#G>v?5>wb+R1SvSn;c?cOgjYH!*DSY5+%>6#QW%0wD`9l6@4S$|x75p(j6vGQ2#RBq)7(~WnwsrU$_wZpD6@>3;Kd00G za}@sj0_ibWDL)Xk+FEv!Nf`pVmGyWpUxX_?hb14>=IjzGI-DSWclD zu{}K<;cP+6p$*yU!}iht|IZ1pNq8cHbts#f$nw6h2eNTT?DgwY0r1kwo~7z2_Q?@@ zW4|v!6?W!ky{I4wg+;d>`k?YId+exvXx%@#x;K;Id#%Gp^$#csYu8N*?%rJWs!ut_6Bd{M3puO4 zw?6_WVDJ3F-b;&3l|nmLZJ6q-7DlsB@dOZy)cCz0m^LcX?x9yM7Jz^?jkIB!y8{nv^DN7`}FZBhv@BwL2VlY27`U z9cdL&mu>$*?d4{6^H5O(R;@UusJVh8FX3Oh(ujtP_fI57jO*j1vb;G(R$Wvb&nQ6? zO{uP`wf;!ms!cQDq-ss}s}HLajjC1eS3g$g2}LZxhgDwf)=(o1QIlA+VK*0D8qp+$ z74CW{qUv;j<6A{7PZNpu(tE5U(Z7us73$9#)TqrZFM-$uOH4Cu8_{=9WofSZLYnB0 zZZoNQBv1aaDXPEG6)#_Z%R@ev-Oe$TE&o+*U8M&(G8D^Us1kl`ivOtj{;mS?^`tu+ zIKHr42GIN$TC~=#km@Ep<0w*pO~ZMM$e8eK8vni&wAtVgIJ-E>)-i3?H0P|84n;-n zJ7uJ2rWIyR%t)V*Ilkz=qKx}e(o{RTQDIuAP7@0=+f5WY&G}tztX@oG{-KU8 z+C?Ie2Uu8GJE%J*V&mgd7a%O)<13aQK}Y-mN5xh3oYsP)ks%Ntvxe>C%qVTscH%1% zKSC||mq^YD=ZViq9A;S&j)Cey2oL@li4W7nXC!>Mp%@s8&q%C`bXcYF$kC;xUD@y` z$G1V#O^qPptBYc?G`k66`6;u9E7Mt78%Gzms$R2@+{tF4EAuX2c3bYgXYEN#7(3q( zhD^&%<}9I+qcwifBEpBr;$>`4v}1(!luR%_$|r6+<1#{3BgX-)f{@f~a}HNuhFA4o zpVL8mhZI0R+)8{`0!sP2ZQ4Q4QvS(%Prx2@PP{LJ5NmfKE;`K;)(-c z)#S~MWT)q7cWZwVRMh3Fp^MgDiW5T@D8&m0s{$?YT0>71ROqU#5MDeupWqm*wIk># zD!IL=b`~jcR~w$`D{Bp7Ka`Z~iNPhQK#x}sph766dsD|+?S6uaQi=>IR#IR}DdJM1 zSVdr9Gi{+K21)^XNy^vF9mBP!2`WliXGqyb3QQ^ML|ypXf!Z6M7$^nkB`JAP`T*@H zK}9Kt3@Kle0#nK%E~TsXvu7a+08%bMd5ODcXr%8b0MAhJ=sy<%vM{cvv;~X+Gt6nluu0*ID0Y6Ax;B{&bDJZE(~d? z2Y)5C_-WSYK4%9uF3Im!7ONp26sYm(_-uDfKQ5luA(rUF(>TLkb_jujgL>gqF1|sB zTbasn`I?8Ah^js99Db_0){iZCYj*_ucRGarSR%A0q_i1ZdDYQMn@FIbO0F`ts!>PB zaz#St86OnWORf@iGp@Y0xt0Lg0%dtf-SC^%im+ zOkLZs8UG3B#jdxs^sOrG>}a598;Hz3O<_2(J{^~owe_T+a0*=GO6ux(QLRd6`A^Mj zuDwZ0AuXq~)93C?Rd#xY%zF?r%jdP1LZ;@3vy)QE(z-ihwMxPUXUrIqUl<{Iij*eo zFP-Sg{d?a5*-NcVXJ=L|h?dwx3meWW#}}`q%58dMb{n147KUnk<)CS{<9d+R!QEtB zgGQKJM{UqbRb?a_at5Y2VJ3l>9V}fm!WBo3jm-ct zCaF{%V~)L~x1+5k3s~?uwvxq;^>!p{y@_xhgKAC(b8>2OHD*uUu`pZd!fN_BdRYn# zW@DKYv6NdRThh-l4!)xHLqA8V_OK_ThkP;$76aaSf|1Mf-2 z1N|{x$`h0DVeyYaTTCG?-#jwVv0r<|gp&ciB^SDoOPOyzrXx9Ua9rWlinq4m^enMK?N_!(Igzmoq*hhdv$U;x4Qc{!i>n|6 z!<-7?VXjd?Svox2J9N0?PYG%+GNe)!AhsklByMz8Dii_2n=lm z;f99D?oHmWp{{rFl= zYt1eb!$NnF8YtmrA1ZAj0nmn#8B!pzdXpU|w5JI(wBb6#hU-WH*sxN4Jwv43f06=s z+ErhrMyv)S`b@do*^FtBa<>x}m~vNro!DCa%y7_2Qi=}xl=41Xn}fCkIZwEhIVN1F z5qgZ)2t7stX!IsC9aA+5#lWq2P*2zNOf%MamXpwgyJzXmBq$nvt!Z@kX0h@(@2hjv zvUG6>2_979U3WofQ%y668^#!*VnE{-mR^~#W|!BznbwD>!B<|C9Cl`rBlC8Lpn9w% zmoL0f2vi+6PBz^7OuX=I#}x6E?-q8)r~a17P$OJ;;Xm*z-!mR-7|5PXnNXh%{@f8) zKF_g3S*rV&LmhAx=3JTM4edQbW)9U45GW4S-(&d;9ZMu^5Hgrm z92k4cidUmP>f%gX*@3T$ggo!)&ngx>KJ&W{^4W~B{!O$SL=!aUHDb=XoxIJt^%2ML zTNvweQ>wpZvdv2zZMENsP_$)qCl6cxDs;b;$re27cu7m<zXvJz6_BZLk!M#^() z5UV(*M`$Za5d@$}8|ovSSlp}5w%&yEqy2+e<1OPOv`w`U;$k?Jc)RhdE;9VoAB;@= zwDD@EK(?(oFNR&RI@__+#d&^g_7jdB>ak9&X2#qU?GvIRdg%!D(pNsbw5pGD`0aEN z2iYj*$j}ZF!RV(;96RJkE720!Fha4!c?>!yn;Skiz5TYCl@f`0e`1=i?=h&MsI8wCdh)|5w zy&OPoxxujI(=J<%8&>Gg_P^-Zp`9eeXu8|!j87QWdD>+i%u-c(+Z+*!pV9?--t0F@ zJ7^a8wmR4I$=p-*Qa$3WK%00 zqb&Dyfj1{lSXyYKi6-29%H5nBT}z$l!-O~XI-q|YRYzm*T(}Uxl3%-JLt2J|CfJJM zhue|dlCZ<&Vaa@~D12t7@^#18+H!(_+ctbu*f6(?lu!y9#sspHYX`@$25&%xcUL*q zE3dJ8-+*_u*|6t*EU7dD0{5kIC;Fs04_?Pmf7W9C`_jcxqKk|5*X?!faKVdfVl zGnWr+6UcVF<2divxGS{k)IUp8wRrd?wd$CzB$Kr6>TTN(s~v^6*!NlP>}tdy{BVoK z*4&i?Xlst>Dt1&ufdn(jrT7qkR=uE3p_WI8Z#N*-!9tE23iURJIOPRkssuI8ChKVMFif7_G zCbI?e2N!Bv3Egd5=LN$$lO^lGN9%hBvTg_9;KC7>aL|#=Mt@`)=VNM|FMSxN{~^aM zoW^8072MATe(Y$f?I)E)?_rQymg!tl$_7>$-FcVBK3!XrXl@60xuA#8w}bazx*5-VG9S#Eh>4 z{8-%K*#T_cHA~2Cb$cB^ovwda5;gcCHPX;g96%dsJFZ`jB?Tz3jn4RF_9Sg8A-mlG zREkl8n$nH7PL}s!LLhtYGska!Pk=C%|HJIIS~(Gm#(Uh;cpH5f4>QGrkIyw+d(kiO zcFYE!&)xS0Y`?4^YG8JKl>?~JmINic>OUQ7MV%3d+R@%n|ilMnzgeJvC zAw_&TPldo$e(;RCMA%JzD3dR3W#E|-b#f-lj&KZ6Ch>KKSQfuJwv95L|4w6<8YDJ~ z@UhfXT*P{uhOq!CVtA@#!WlSZ5#QYm6gbE+J~ze$xQ~sjy!FMZ{OgXf?B_?uhq1BW zIu2_YCU=Hg_3gWh(-tY+`I(GJHtkqymq1UXff7=lc0WM?+Zu;1icBm#=kRfiJ&0XB z2ZvAQ6MU39ySq42@fayE89^zYBw6oSiYEl16ptW)#wg~V9~~34*9j_0s4yhFOA1U0 zP>K?cc$T6BD3v4}IPZ8^`;nlcgzpRqS4e>=0ZLJVe-G2YSc(#$RFW{}7sq{CV}i;h zDABC)0xX>;5x6NJx`zh3NFC4T%Hbct%Rq+{=z#iuMB0+g!WcPM}cNT;&CJ;fmu?2^*KnF~3!N zU|WDGi%;?EB;lLfk9pt&_t0yOcWc2u>w%5j^V|D%kno|C8q9Vb8h(85F z@OZ>*&5|VrWv}vHaatgU;kk(9s*Qg-)+t(Jf`$7j(OF_oDw-7F9^=Zor5`9A)^2h( z)iOvKq!MwGL2aK!M#kA$VoT*&u9tD}Wsl=>FTH~yjrH+ zOGFmtl%=t@j-pnrrh2&V~X2D5-pgPU9`JUWoQ|^!Y;9fAK zv^VFDJ2q5x+_3?h;f@Wp8SdCn0B*WWZBSaIQ7DFC^=7S|R!NoOJ2n&ziMIup_LZP! zOuqNG#3A*Z@t(xF+VQ`lgDNy+N50lVB|6mjRMyl0HaHL#V!!_@4yg9!KnNLH8Qf@! z%EH|}C7jLZ0Izg>r#Vk+dbSy|7>sqZMKIPS1w0t5g7-Le#nL1@fbF?!bfVUbl$!yW zkWB(ICA*e@jD-Rokg&L&!af`BpEoAMt9Y&>H!KDsnniDj!p zoIcoNyid*+@jlg)_XCu--3Mq8PW z3dKm|59Vv%Q=NF*p=d}P+|W5qf?^Q*XNxW7aOm{-0h9sJ&SF*5b3DT^#|T4GfPLb~ zSmzg(ra49wHYdeq6ei}7C``?%B?=ou0guAQga<|;8owWiK;sV}#TbKqDEHyO#4`rb z`oJCgMKA6=2$d;JNpv>Xrg`!%ro0_Kcw?Unyzw*Z@Gt)wRr#Ulmg*{y*JMtUK*Etv zIn))De>QWjP_=4; zi1G4tJO9qwhXl$82o^wNn|Ap1lJL>~73=TyXBT=oA5_20VFkUN>DpI>7~NbkB|KF< zX;iIZ=(teW<=!*8w7ry{U?Mdl^g7RmIIJ-~@LSCew{bT1l*-^!ud9+kl-kpbL{roa zVnsODRMr+Si4j?KTjy|JqM9c=drG3vAU#He$FTl|rHNW1k;bi}R_BNdB$5$fMKs2% z9>o0O0>&pP&M&migdxhRNMGZ}PNzECX*r|_hiIMIlr(2wZ<5n#kUfTbV~=g;%=5;^ zLpu|_vB$M{_LHzNb>i6;hX=OWxu>YLq&?KS8L#zPKjW=l;YQ=_A6k8Wx=r=ZF|u0~ zWVfD*_B;`SnQcQ)(WPu41tEu>yOe*inha+P?QH@#`;s?%lD=eLPw&2j9~4!0LILkf zb`l=u5bNunBITSRrP!66qRh_&56`Xyn>#Sarb(G&(}Wsf)1)=Rj+_FpFOKR80ZXA~ zM;_M840s+E5*iZ6c5^-?L9ru$x~DXnnB3iYT+1Z9(B|pAgw4}wK@Vr8n%7Gl6&gwk zOrz)aB1RwGs}`dVfC6sx0fYw{eZi8<)|Qf9;^AY>MvBqu4-)Rm0#@1C*&&EDX6O-* zZmJW@f@k?RP(cRTp2|SmL(S0kv}R~~3PAJm=ZrN9l{-0Q8ynZ#*+F}msA+aQFHv3L zL#ur}Iv(D~k-our^oL4Q`od?9DFD5f)=To<4}G0Gw6BQ<=)Ert?|nfFxc9CY-n&W) zOz&MLI;)o6wRo?_@Lmn!VS2AoZ^L`By-9fT1OM=et^rQtWKRoV4o$|F_X_?<4pt23 zQ4#1os2DnrRt%j-0qDGwgPqwLg+ecus|}$_@is#-knUoxGfIM@)jtzfS6zdjV?&%b z6|IDD<91hOu$q1_ew{(#-0aJHi$=486u8ZCWG@fy4X-&K>ai z)S3cklD2}<@D~S`_8}QyT_5kv2v>S~sSo$T6Svw!l$;-2ihn>2RObU3S8!S%@wy8r z$e*;)KJdh@whh%Z5B<`s=8ks`w`gAxWW30FvX4kKPxU22reWvj0Sl%H)geq~|wKKP3|JK2n1e|M^;U zUo(_3^ZzTwzoV8&pg1H4G&VTZAJ#!g376B@RH=oy4MF7aYYitlw5@78)%mEuHi(eo zD6=0VQW$UdBXCp!X9Z&k)WE(t%h_MThA8aCW_;5}3w00W+X^Lm^<@Pc<|bDiD{+oj zH7DT(4q@uTzHD_8w9v(*z|5>=eMy9^?CU*!@EFq@-=}u6=}u>FPhpA7oV2_MTJcHC zR-aNu&saCz3fAI&&lvckqO{gC|7uwZ(JENP1nk+DKVVM{M+ca z-ZlFz_p4MIS#@SuxvYQG3ydUd^{(A5zD)pcE5jzzn&75UPw@KT%T#OmFMOE_eu*a; z2XY#Cbm@-bSU7K9Iq!aUM9qz0^{Yx-vTX}H2C_MiI=g#sv|T$}+JFTwbrx#diS=-| zZJP;j>9c&zt?#zMKKn3MJ;uK-d&)mInmxbFIZ6A#6d|_U_Vg25Zf}DR0<012$Xx#{ z?G(X+7-_{8bj?jt0Q2YBu!uJ|rnz>WVBiMS=l#SMjEhgjx#qn!OMfXojjg$xf>HUR zJCv6Zu>pU1zC>eeTJ6?2v$P=uiY>8ke=#|i&|&kW{E;rVvUg(o za@QpPAib9<&e%nnWel&wYJMs=o?h%UY|mzKjz;o%!g1heW8`aku(M1kgnN!=UtL5 z_>fMW1G4zQXmWosFq+g~jNGnL4f!w%E&m&b63f4@h7S^95HrRP z5TiC?MuzJd^#_PiTOcKOkJsT_{l276+oasxP&DA$1%ZE~*G?jy*2)TWIk z05RA-lpi8N%_y;f2JjxG=AbmZdL^`a4~gpeh>{r7VaAs;sPtZ&Aw^LDy5wG?)&mB( zU1Ik6q>Ye1pEPP$AItj_SD)Vuy@Or;Tf8FJ<-@Pqy8O@=on_vA{K*%cGqisbLtyuQ z*aWylFJFC|-8)>Z2x2Sp;ERr>TVdniCsTyz-p_&Y;W2#mn*r_<6`eJ8pc#SK>E1B0 z%u@`}o>-9s#W{(VqyV!6zLWu_c*dZkXDRN`Ln(Iapa*vAK5S8Z1{#QahyL<*XPoHP z399JU_Yd&dt&ib?v0I-oP;~1@b~rO)&Tx~^Zv7y!5%1QkhE+Hd6>Tcf+vA3Zl@vjR zVK(|f1C2F))tT%~W!^V<#3$9|SDiB@D##&2wI^j5u^Z~IF zrWc!%jLh+d2@#p2Vy;!wIIs;L+;Fe(?`E$2r}Ihe-vk#IyAFe?;hUJ+VN&4Ug}3}P z5cWygMCU8W$4SyC2_;Tf0!T~!S+?K3ANc5?} zgMh3xR~OzW}|Kc;~Xei7CXIz(9q!CGXE;hZs(VplW2!7u?`Y0 zv62FFFIri}R=)u|6_1lroZijYJ0^|P>uIPLziLX2hUX%dLIHQkQo;Zo0(VVu8(MvR z5UYH7exmkIf`LwXmGH0jVK=@Ftpa~^iWh%$_-BU0PkQqHl<+?5gEu-Hc;glz{0m!v zBP`d!#kdE3!;{@L!mjRM@A%kKxaVUA+p#byfNk)}MzjUX1WM6{)_szc7t zH78*uLT<1Ta-@K75~-^Pi?!D^q`+Kzh3lqngFFKU@r*azBw7XqJl>WO7G?*qbFk~RvC0vEA2>@;VpMS$17)8S=0q*txNO95N z6u=*7$op(qm^bn1Nqzw={W$RbgA(}U@ab__w4~wQx4NPN4h4cuNal*JM4 zL!ML{S5MJ2FI}g9>D;0*f{O#%H3VP|Xeks!EAF?zdhB$D8fW>3tG2IDN?zNop0%y= zS=;#7;!2*nlE9DyjfX_3yb)hJr)m^{9$e*Ng!!fs%mFS* z3QQ?bic%^r!qL2+JyB2!pin6rzw{rY)yXrX0HvsT!dT&?z?1@|CX*VkMvyCn-@w#3aQ>)D}mArQDO0vA@A*a_|^2 zK^2pfo4MvBCBi&LJdX>;Ny@`4?TWJ~CX$;II|t(hN`=@LSDo-)^9rJ{$GzrqQUo;> zdu2hK!1bauoSpvNnZ;IJbp~ma5gz8vTh!?mXA~nCG{Gpg@uIDcwu~qNJ17xV?_P7h zqi8z_7<<;~YZm&mX7BzP$5Iu*$x3vO>3W7@E;|hHVF1dIL7*JQQH+sXVd0@imcUZf|@+1^$>Pwl|18ab(F` z*xE~QEQ!j(eI_qF4=Y7hJ)^*5W14?HC~tI^Xr+R;v;5f~{Yx9NpVZQRYJ+?>c0g&G z7DDjcIx9geExeT8KW&untv9^f(Kp=GCqOJ*gJ70$!@sAb0arcN3zevj^G4%YyKY1! z3_e_6>dc`ybl}YeW{*|7>XfD`+T8>j2adz@#lUemDKMvx(?LC)KF%b?=J0WQk2EP7 z662X}3WZ69@mS)Ye@py92wcPSAkNhq3^l_ZVn-GVRWQzUQ##bxJky=|O(1!MEC@Zg#5K7<#>X3kI%n>nPwoJU*63^jst94U7Pr+V*D(seyBw3fge z2?abbM-m6;a{9ge*^}>$@BqFcKay1MpO=%PDAYlmBD1x{7+=fs-WqC=Z?Sn}BfW0X^!3~@+M5wwVM4%r0 z1a}VMD?)?-(98d5Te?j`!w|vqz&9u^@8T#oBu+>v{f7j_4hlwWagfvb7q8vD)VkEt zD_WD`X3Sx%#0?j*5=RPntdzs^gld=J;%UBaq!2yXiDhTFf~4{oIPNl<+(qyU$HwZ;XgB1JM87@H~Fqt}k zxEQvT5qgYyex_ZSORBSMxcBIXA4-WahcuC5^g~5=%PdWiq@o*QIA7TfRhgYi`zqS& zL=W^sh2e(^Qh;qXuk(UY>cQcn7yp=)q9gVb%|G+u2)voIS2$uuX8k0^@B4=U?a5u2TiL{V5vSe^qw~ND4(uykc4co)dw7E2SzRs}$b;Oc>!2kg+2~ zK*o{+Gz5PHRq4bEb6}|4g%ol-s2L;7bgA@a**!h789ss9egtlTsvrV`k%~YgPykkD za<9_f8iiuhL`ytCRp6GOXh=M#cj+DpioJLA2<*Liv&5ws{NVaPKA^}H3s#-6AX|ZV zEjg?@PYu+i(K9|l9MZ4!9esnT!~bLLxdWptmiPNEB#^y83P~tQNa#HYU1~y;dI?pK zl7!AtLk(9GdI=q}6crEw;VFVo&9i_3D=Grkrzk~K6bs}%_1Vzh?Cf{9^IZ=0hyD|e znc11y+1c6M+48|xa3*c}3lYnVL5K*a_u4-86E1>x1}zW9Aw_65;KEe}2u zP~Y+ZGmEo6nevDwWVkWdhYnXhh2EhLSKgsV4zC!maJ2tbx(E9yP$-^j{NFISL;l$? znNPejOrC4(LWTL0pB)91sMx0T`9Y4;A#6CI#)FN6hf8-KOb}6bI|ftc$UmD@aWmFX80*13DrbzQzQ zA+!&>KUfh9(DH7Hp{-1X(9b4}a?G+k255Y?>~T_BIoT0XFYP!l8|^T!ltdIJKIW^` zaOq=I&w$mlL1`mW@suVT>-da)K%m0K#J4$;lqVY}FG*Q>@)F+r&2hY=vHz0dQB&cK z^y|a2Bhh5H$q(v2l*}CURUF;hmlM0P+yQm0zztxDG!x-qFoe zN>rMd$2jNqY$8=6+;$>V0;&E5(mJu^~nd0i$5@Fe3TG+=Q%>Utn{!^gFH zXd~rr6zGCS=7QM6z601ByHOcfFBmsZtk12(2(gU7OGXBbz;X9LgJA?tx<^LfF`FGZ z2|I*BG-xa%8see3%3B;0G}cfQ_no^Ey{XW8_ierqD&v{IaVqm&WsXp5JtY8xm6LT+ z5E7?42q^Z+9V1IOo^UkQ*lAjfRz6M@xEb<^8|~=c#j(6(_0zi zEyEZf1dTz3pfM-_je%)a3Poe!Ihrb?Og?5~lne_$_JCuQ35v#eCcqfU;}%xp7xp^N zv6h4*8l&kb=^0H40?#k?9wo=QJ_Mo0xt^nxXTWmn+&` zj&qoTw~vxuH=SVRB9ZXc7XS}2%$b;rcZ7gBW-lpo%w9r`(DJlKXn6`ipxMLWj0MSZXir}2SdBcq`nR<#G?XSFAw2%<0hVwWQ(0!w;7){iw#Ve|TgL9mu4!qxwmILoI$6(++Ai#9s-9%Kwfp^kzM=Oo}O29ZX{VM}6+HOXP!)pCm zu{DO^}$Kq@<%Ej|{KcgP-P(GS-q5kim6~5nKsEjWoT+$N+d3 z!D0aHF-8Sfeb5*g0KXUd`J$@`fZfK(VYlfRBi<1F7VU6^+Tr-E?C`K* z2M~gBp9(=cP(b->jv__@xNhF{I`o8(sdxo@SgXGXasN~S_+1Q{%Lu?M%4~K@t95FOh=k5!RjD%lB73k3L zg{qUtiY4(}Z*(M2%^6&&)Oyj;*}@tKMkIEN)Oh0Ofo$q3s#Foj+LyE%$4K||*-O+& zHFsxG3Y)u&_=U|4zp%OE>D6dJVuuE~d}BeQJkF}wlEf|PI@~iMw3<9n3{U(=^LsyW z#0TaDI&-)$y+2|&(b4$a^;iYM&t2=obHsW%vt(+maNA&o^r>Hb@b(?c_jT12e(7sR zbDnb*_EqL85#poQ6XJu&w9f&HWbV@7DEns(qj=RtDZ|++Qch(8mgV5(>Jo7$niC2< z(+WsDms$kw5bYck7hIBPoCJMfj`At(UOx6mXASWIh3LxCqe{`EVtAivp;-x_o!O(Z zh-5L@zz-nsd%kdp2lH{9#BU$GLde88X(@whifggJH??ad^F`Mk^?1Zrs4Hld!V8}qSC4;r-4Ug2)Kkek!F@X`R<5X;qfMFqjv+#l6p1|n?_2&eoZg#{WZRdJ~@|f?6{zM zh<$2q7%#5}4LFt8`4Jw8brJG>0K@~q9rNvXid!cO>cgKV;@6^F8J8e@#VFm4Pt^i% zm~q7FKjiR^KRFs${|na6vp<>x<+k#)#WB@Mb&VpX3h<22qq}f?4}!SAFKR#!CP8nv zP#1&V9`Or<9{jr1828=Ju==U+()#&d9Lw0#q~bV0J*fab*~Jh49T96ob6YC^$`d*v zHi!s29FqFYk*FWdHARiW-yE&=_jBdCq*h_*u!L8HdUWvlr_xspK51Ni*5hM>0=Jdl z@$Uc6ez)`e78MPk9&Oo0!Wy@LKWlC)V&w#ildE+<*}7VOhK4!wldTcENzhTVofGvR zbIGhRERSn97q{YROKkOGZU|D^Rm*dEW{9(kNd#`IRG=iP83&{%9I(_bU9ziqIyO!FkZh zR)scaLupAdq0G)B6(5@?QxWfrI?FW`q#|~-wlzsol`|e}AkrW}TyAYkW&|XUqO@#d z8*EwNlU)!fdmfd&IH>GL+uHgh{GM!{&Y&%*WSq^m2X0~p-!M<6KkDUSyuhP3CYJ$f zcxnfpeu*XS>+5btU*Ltcs)v=dPG}nYl&Avs_NT=!?CnqUya;DQE1lrTw_i>_H?Rgj z{yxn0VE>fynN^)Z<}$BWb;7#<#4_0R&nSRTm*Q1_vFj(F3aib#MLIXJYl^$^Bmg-4 z3w>yad7UT-A!ZXxGpi#5OY>OgZ3h;gm7;mh zD+5EVEfjwv`_W55$Yw)#0mYsR)x@5={M5jc>>ffaR{Yvr`OCx>e zIC(a6Ho@Y8fBHDmNgd^=x z(UEfli`Wl@7=!D#1fYT|g<^{pz7y66-W14BcGhE6#{+9$rw~y!d^~Be8slYDB?f`0 z3QwaZB`K2_(=H-LOuOD5*ozU6SbW>`a--UpRJB!VmpCk0s*`@>izh~ZG@iA}5;efU zmMwl^V1r+`n#SzzVN2x4>pKhRT&6U$f%BTirV?XdFq^0VKH}X^6W(&$4}3jJ9mryUcPa-vpRg! z9hrSV$_QrSTkq*0C-C%i zXB^LcIW0MyAcb*sKt`p45uPCklnn^*MIzga(Ux}Lp zAxc>&q*QV1_<1HbMNMFMxdI3qG^j2?t~i2=s*lf>6HTE4G|q zeZ`b7Y#~_b3)$`-+C-Bt#MvMyJVFT37YCD`NuUwChl;R`hh=J$NT$EgLOH_7fq5GL7u3Bp$bec^6` z_(NX+`N|i3X3ZxYd}c*o@Dhab1z)kX1S^Wc!yHFPIBjevfn%w{(D^;INhU9_{ua7~ zJx&PG3yw@CUT~6Ng(b8jJY^Wf!LtO8+CnLGf{zK}kDNfeAentn${@1~r~-`sQ&dx< zbfZ8tfn%jFaBYaQJxeC=-*Et++%|;VB)2<3P`TLzuH@F|8{SNeW@8ER4_yFi=yw61 zO$!JER0nK|9FgR&8#BuI3Az6eC|JX$Uz>uTNHtN5 z@Wz8EI`4}d>@u%B9$4g zky&jljQ~C9e_`pY3E_lCvdR`)(zFKr+#)A^459T@o;Syn!ZWHiim?iv{F$!8AHtef z4;Nf$!cT}V`ys4hMe&$a>@TzvNyULgyhti)@RY1s^4(KOVljvunOHO#MC=w+pbWGm zzc?mq0-H_jIwT|6jIBMhfi*0-pfxd8AN=_ zXcFQV@-s+hqFhIL^CD*=>rEscjdpEeHUdE9fPzPL3o9~_iljJ^6D^gaayl+?KF($m zW{@vv$_ry%X}aAmGAQYM!|bf&_(_U{_z8G#W>`CZb9Po*B4%GPxudLM-08hKr8Hxi zv%b#OD=soUoiQ!53NP##)<)aT&#Z7ZVmk>1Cf+z|VLV8=&n^>hmsQN*gKD|j68Ekt z>$skGS_MNd6)22BTFM|?gDusb?`|9)&g-mpR*oa)AywsYf6~cLQ}z6LtycvUtG*DH z)8b{7Wow)bHTF57#?wZh*yX9KPY5FOsI!m$i=7v3cc!pk2?DGC6Rm#bX%(x#=eV;D zsg-f_69maeGzmWp*O*02o+h)1b*Cvm7Fk3M9z)z~3e?S~$xI?OIA#)68!L(U2!N2h z!P&{ua~e#4U$WI@y#s~77vIc6vV#bTI^;|tE&tCNv{xua8m7Jpnbo-g`<*wT37bdQ~cZx$i|ywVS7ThTdTw~ zc0zlGO*gx#ZkbMUyHV4FyXY-s8Q;4+#dmLTcD6K`Zg^?4KpBmwjJ82!1bC>gKH&D~ zp%rTc9;y$V&i8DB{C!rSxc*e!NGUFedj_l2_07&)vjP3yNtHnFqyXie6p9Y^#y!hA zGAGdyy_1qD@1#)Wooj!uFnT8~C%jXG2Nm`@yZfB8^q+g3RW2*Yid&#AEQgLq9q@KnMu zcnYB+cvgk)<6`iPoDtyq))~b0Yt5+W`T=g~7ht$$#p(#RY&Ao=Wt%{8X;fTSDK3ax zlBnqy$T4b~d^qe$P1JgMPVrhV;wL1c6cWA2Vdse1ss-F%MGPmd^M?$23y!AP61PB*^EO z`k5JWXg^1!p=X|^(#{8QoB+>M($F)7RNdwUh8bq}Tzk;=6LS$h!aX6|9(4@H*#ZK`sJVd`9fPR3 ziNMi0*Aer=iN(C*kYXjXB_1&CG~O{NfYuUUP&bM3`KI&414{g60Q-0^X$pJ_#Zqz%~5>4A-n!9pRe47_Rwiptzr?xXQEs zglqZ*O4l^W^SdU6qH9usa!m?F#~PJXxif1zOZ6Z0N=l}@l0ubNcK*G>=#{h_dgc6? zey@a#VtXzgonL$)%#I zb?QKJ1hi@{-iTfLs9YRv-}lDtB7ZaOi4MgojeN_M-qss zemh`x(l{@0UQ_|k3w$Vk;duf0b*u9NLtPW_DAZt{9djd`&v-d3$Wf@*UJjeZz9Y85 z(*xxSkZP#%cN~Q}z^t=@T~pD*m}WH24OE^ja`v%2>#ey>SuH|>`v8E&Byq@WdCn<_ za(2sXnZ^BTmdfH<;G7e`_F7mYy(5$q=l2`E9+r_{5&W?^jhBAEQI(ZPC}+RzoWgn# zHK6w%HqDaHe7~0n3%UFIA$Cp3Tp$a5iLP2?+-6d%$x3k9SO& zEoT%R1(k6~N#shZ4-x>ZvT^bmMDaZz5A1G|iM>Da%D}me0G%3;uPxj-$=-TK)km_1!Cl-01P}c--AUyg<=pq1hPc8 z-##0=y;j20FF8lEkbJ1Fa(lR+zYZ?=2%xgTKUhsdh0!jS093T2P&CGkmX@}b7Wt4c zf6Z^347t`x49pbg+MlL&dlF~|`q()E0C#^}mM$eS%HgCQ?p{KAk2zit)sp8w3b zot}>3=THfq!+*UTwuao?LOHQc>8sGzWmZ3 zZhk&R$T8?Wkxw>1UnW@G1_o@D*aCltAaEb>37-75b3D6B;D5CFsb4Xe{Y(ns1|A^N z#krU&bCma@cwdQlf)FJvSDqJj{f^GIk1x>>VP|Qa4>vM3&lM=&_@;B^wenlja9nZ+Q z#EJboo)7<|c07SX?s!sC46y6Pj%RZ~b-lXq*j+*Zox4$}+V}%EDlQ+njTM2^*}jjppJu%UY-~Zgav9|Hz2W zvf)bj3)@e6Jc7%Xc z*|nRUQj~Jf^F`1Q_dMZ85Dm{0DEjk@(B@*#ladE0Xbh<*{+xoPa^q8*r^KTvZh~UC z@d-ctiUmkAHa>s+lal1_XQMz#_2wD7pYY>Wl8oKYI{av?>-UY0JD?R>i?~eS4rqTO z6?Z^~5CED2DC7<(B@J+EV+WMV!5z@KgqeQ_RD;!8tZQ)mG=(I76MXMeRms@<{A!M| z_qj!J3E2D8@1G|p^t%a(n7KmS1qE91$QC)Zv_m`!X77vy5ZwBVQ4)_2+OEoR#5Sb1a{Kd5s-S=S^NfJv)D;FNym@h{dgWi(RYHvO z_bc<{{QU|+V2bqTc``+MlOVAE@Pxdt{(9Jaxt^g0z$}z9fU!#maxe>JlH2>DI z3~9=I<;IwXN}NwtPtE4b)H;=hX{cb*FbyT7iZoP@`9>P5SD=7QDj+L}08B##5n!aD zD%MA&p(f9l8PchN;wDmYbEUX|@dtN2g9wyqD3d&Y8j3=3F+>5lF2Nm73RP*Stwc%D zX&EKM!nor}p=umB@Oy}6;$Twf8Z6EdHRu-6q%>*Xfs(B$i*0OJ6N5{%#&)T z6gj{WalXtG0m;nMhtO-p67;qCzKW~F6Y1$>6-K6U{{9dB+W*KvY{vy)9$bZW62EX2 z)`=ITx&m(CrN6wOhrGf&rIo*{`B|=MC0Ry}X;d$^kDp~k20!?@Soix?ina7DW4748$l*s?xvF~y z3prWh&kLgP3GwHpH2Cwp_|q;O{$s*K|?ul8mO>bY9ll)gyh%f_CY1XD*tX+IIZ-)_1mV(;+>t!=(0YCU%%G ze%$!>tpN^8|_;>7WJ>37~aDX&ATNgVF<4)&sSze(XsRg*-^O~d9B^{wx(`El_p zzAOAm5P$adfj{`E_gDMDFZ??2Z#MXapWwPKUW&!%XP1Z<3-KAm4dOu)@h+49a*6%3 zY2p!25e@$CDvT3Ub|FSshu`_ybMM;4`E}3&fHs-O{uz zO!@CUP}c$-k?(0=xi-%|6A@WDwY}?*7Quu)I*C8~fGn?PWm{u)AZkn-fa46G$)39t z0AO7uDuy4t(^ba;Mflm3GY0VZj;_w^QNKC|`H3PId_(MfRJiS71r@(UoGKo7+jqG( zM_q{Hk)2#;g7S6VKHrorv6~~uhVWlEx>EVUU%k~!S9NxE*Vt*LK2}ORf0FRJ0MfN2 zsbpzJSJz7#J5S0*Ww`o=dap6=*h*3@zj{qV)0wVmMFd zb2DANVw5x^0eXG`e=XCs#v~)JyUT6~UkGFQ*V!$Ybs;E-&4o?Txa4?r7rpXAA|Y;} zSaFRE%6$5f`8}A#lu=sa9T~>{?BGRGmb$QF)t{x$s0m_r? z@TJ1y-md1XD$ZACzs(k8G+HuCIkolIiZRE##T|U3clr7xMB>Mg8MxyMZP+^#Z>9XjD=z|8=OV zIA}X=`Fq-tLp#>wM`C)0^4Hn)mVEMX*FRXx0>6z!RU7lN_1T?mO%+sx91OjGw-$^i z=Piij1A4h_tc#K-wb!*IFc^YD zS*1A>CrzEO#oi5!bZ+|0WGgMowS@~(^!f!d+xgp+sBrGdbVVji88W4Vy>|rcO+qo_ z<*!f0FXU2vM7u<=xw+RgQhG1oNB_4dRd$;%71-Zx5*r2<{#;SX*v|)!b1h~+DzLwB zk}7NrV6?DIwehu=X7q#0@z0HSWwEM@KvOk(;kASq#iWv)l!PzBE&JFoMeXx)dqaM9 zg6m7xK%xBF5JtvGkRlny1!Yvg%X8d=Nc|1zvs#h6f|S-{l^U@Hga*5N_Uh0s`kX~% zd@o#tD>DoD0N3sw)Ra`)nACwl+%2R6^X9nX`Roan>Z}6vf74t&tON?J{zE|uKl_xs zIlJGi57elo9v(}H{g&X`4A-M(KCti_sE?G5pbrN#)OEBhbU4pOHS2TtpVzedR3 zLYOYVT(4POY=dW28{m2C(1ou5vVLZnFck`|&ol==k?BZa3TM>#-U8PEHd=wP+hL9M z-VRK2Mf6tK1@vi=nF=mDYmp^f6cW#iSZN{Yc%vMyG*%c;MoAK{gpfk8r2(Fuwl*v_ zoD|7)y7rh^qaAuUFtWhYE9EO)9pqV{A>b^Kn9#aQ814~wTO^;Zeul6FSF>6FB>=vj zkIz=W3+-ZG*ns`pOxl=Z&wZOTq4qJ~nD1&UymF(qu(N*Ff$xsSzphHEFbADG>XFX9 z^-~U+Hu)Er3*R+aBoju}oF?D1S*-#`6Z`^4q4u<+g%MEm71>?)+oU&FYk=AG(Q_?jA=2J+WQh zGev#b>Hv}Wv|Vh_5>KvnJ*n&4oIL%Pg@b~V@T9e_zHxL^_Q~s9Ad*j6v5yLQn94dL zeqk!>2*146)iCa$aEd0dxVGc$)Yru4;5kR_Ro-!(Yj`}8$YIs*LC2sAVgl;e0wV!+ zY=KBXectjZA>m2*GuOx!*#%_PTz~#Y;H0ou1rw3Yfv;$8yq#BTfEU&%o^<>3Z;^EPt+qRY zM{aRF@c&=kaIKj;e)HKUtMIhluBN=jR#(-k*GwAn6RY)+{K7}$qWQB)ZYwX_>Z%f= zxnRM3`L`OG{ujRULK|#w$;7JF zOZA}0-|3!DY$1(#{*-%)yofUqlCKRDFdQ)H%!a-JO4W1jLg=>>b^Y^%5 z&b^-&!#SP!NS*aC1xK}BG|&QsJnBStEPpmC)XLZIb)^Lzp;(O-u-F2anZhmX5Zn1nl#!t$$Dd z>&!2$_Kvcq5D6Rw-?(4v7#~EiJ=txnoqs#zI$~{43zi>t4bfY>S08qbvU*LlAWw7hJx5*btZPjOKNF`LzfNS` zNzqaLi|jgJaDfbZilsfTJ=LCNeVmes>c9gH$o`}W;b(uuV1JgPkv(91?8~#=Q>V@u${gq!wFo8#cJFZw;m4kGy<*Lwl~B=QG6iF_ z074Nh1_ddBF=A0*3Ha7y=VxK^Y?1&WVgTRpUGLj@M}h`%>}Hku?&}LeBSsU+M)u** zJ?<_VFFEe&Zrx6>TnvOU8wCUh!Vo#b+UmjeLEI)n3M4q^+UUUpIz0I~S6BTo5WeQ= zZaqQ>19=+xgopnG&%!cSEB!?ezjutgo%QA4;b|l`p8pd(kBoJDtQUTVm+>LE4}PDQ zNRlK~FqGNS=dM+c;cK3EP1k?&@E@OdO}73*<)SmKeZkerYVm?KeRDeDO!_Y#xn?yL z5W@#)oGP+$en3Ur^NTxU!xL*rm`M-SP~wWbwGkDTk^o~=eF4G7Om>UB&19Y({z9eF zelNRz)2!VoIZkshd(+j6*&AzDijHdKNa6ThuzS3?{Iiax=sh)@6EyfB;z`roV3HS? zSNcc~uK(a$-9TV`Kpmurl#N+RUY&(a10YThyk!2m>tEL8R2~|*aHgk~bsYtlN4jnN z+G*DuGqtd8qH0m&_?M}Exc0jGhU;zXArr%h1p~GHJoc=sz`CCz1WV#1MwW%LgnWQ- zlK6A3E7}YE=X0(s>r0daR$<|rt_9Z96pR4}2zkb*=Ng$yoO>J|ac{ZI)7g5FmdHEn z9tc-(TfgmUW~P@$S{)w3*S`%DoN`)7h=D>i-*I&dD5QG_S}lddYXyJ(C9m{aQx${} zqLp2ZBWNf2#&=zPBh0o)c{icA)=9K~cdbKd{(G+fXx27V3i{uThan$RDBUlOVwL+1 zD3tDJqiErNdcQ)MJi=+|h(eR=>Aef(cX84RrQ4afquZGvM|&@bnL^b;@7K<3FQx6aMcXLE_%A8aO z4t|izZ`52IQks0lwN$fyL7A$E^r_(zpHeisM74~2*6CUiew5B?DI#8*Z*jCQsjN5G zex8g5}ZF$Yg6H$`u{0UJ-G$ z^dfXL_&DW_a#w4?P<(*S%KcqFBdI=U zcoQL(-~Od*fVn&x{$pzRmZe9&ay8Se9?DPI+)*UEp@X88%}WfMZ=-0x&9@K>X%7V0 zd;?fa*nESjsId9dKAS&FQE2mj5svyxW}5>;w7H2P+8io@HaArQZEk{~&7%M7nr=0L zG2Uh`@6pcs4b=y2ZX(3;_s#1*$6Ow5zOaZmdrQ9kJJ(8U%wpoG%H-7+OOsclXfU}$ zZ?+iU#{1#l#oeFP7;{;of;eXSC8AES6CZIHMg*oY4*@2-ahFi960}0%O#} ziS8&WUko8;LM$KolPlc}Mmty+6Fa1qM*QsZYSu!^PZ`3sn4j3;PO`cv`pX^eCj3ak z)yUF*H(j6W*6kE2RNR{5u5aB#q2(hN*|vVz-)LCL45+jzNb6Bg;Vz5f+ z!*eHTmGn>`7snUBTP*YNDPGLOTL(~b)Tpn35RKZFhJ?H0G;1EE#MTvQH0u}&zWlbM zkr@*8^r93lJ|L;h=bF{s#JZ5uW3}eeY89z!iLEcv1odP?ndD85aHpH)otxzCZ{<|R zEmTGCwpXoCUd+l~sp@WNJxG~glrV|L^4~u;C(bM%dl#muo}uNjcU3I^^}@xBr;hbB z4#EVx=;=SfBsa>PVJ?qd^d6(d`!4afxc|hem99HDkQ?Vq>H3;@fk^Sk-?0=RnBv#O zFHG^nFL`J1sz@4RlK+}htn!ojjTm=kJc5n&l8@idu%UyA{hysiV*h6+Cic683%+6S z$Di025R%vzI6J1$LQn_z{rxoWCupzT};%#U8@U$Xq96V=TM)+a|AaSXH(5wO#%}?|wsLl%; z53b4I-IE!`%WA@=fG5$Nd7If{9+u?p%!mYTOLDtHwt)_~!w^AG;B2*;4xXdE!Y9^o zJ0hMEdOjom90SamAtU?7DAkQs;loS$#_zp%)i7}}8e0(al>Xgn^0H+2!1&pM6S@xm zLVo}f>8neZ8os&|o_mB%s8+8F>QnH?@2dhrd{yA=C|1i(GPpa?E*2}4P zd_%qCeh{dM!1gtlBc4mQ~V_baww z%)PhGTrN^PtRe!;J~0MgwZDqrpHbXkVGJFHs(4|yQ6(=stXkq08P zYDe7W?#@s~Wb@o+?g>GS@fSV-kv_tm!wV}-kK-BFQ>ybDOCJd--PPRvq-L40%-GNo zKk^^6yE(tUbw(6lpP${BcYD8GI6s!^o?=-o zii>lS#l$|^VK-c>Y@ns;E0^I^BIa-icuEyG)-_?)jJ&Bcx7bUT$qk_X>F$Et=+eIW zBw3a&3oBV!IhDb`Mz^ZMH?D_CU*VW44Pp)kHgeH2JSeGo_@LJA1MCHWKXJ^b` z&?nKVPRBnjMd==}!4Oxb?p(%?9x3R<&n{{b$PLtoM7y^PBD6-Tp!ylJpD9_*Wg=E!hR4hq9@@ zJfP#8H*ETEVbj#o|J~`Xqp>(ag<-A=PwC{IV@Y0acuHM@QJ#{t{1%?ld^uk1(hl%v zI=hEOj}|)7ZX3tzc7dap0rKkdw2Wbucgk@qb&`-~Uf5jQwG0Wr` zTM`mPm2sQ^&hm_HwTw{4cfRszBu{P+`;li)x~ubhySoQiX(^7|dZ|6!pRxU<>R|Jx za#!yG1@(z2-gf&D7dqu+p7EkPMjnQJLUHFPQ*7wP1(9igd^s;$<88xpd$@b^gv1uL zc-fnS`?1#ugOon*q58|vUg85a&+`*~-LNtB+0fzaN+8iiGg0KfZJpT9glNwz!0CUK zXc~)IL7Y`csiZ_u8SqJB_6hEGTGv*b7L+#+XmbRfk=pSsydyP`#%i zU^qdb06>6%PHX}}DBggjylYLhXEV2%a;Uz@;Jt<*kT)QZ_jZC%ya7vjA8FKK2z$&- zIaEJv@Gc_=FO2j8zzavOsGgJqp;GjPb z9V)GG(5;+Fb1WRq6HdEZRx5>uFAl|VXZ#kJ;1u1Atj>rFilL&ee&2GrQ+WEcyJ55_ zBEP6scP0FS|MGKidN|>60jGgy7jddVZ@ANVVQY5*Yb**GaZijWc<^IdztG#68bF7d zVQruoF2iX_>2o98y*1We!Tpn(q;>*`N*V`^X=$?6r}taQwd1Z#HXsO>7{$fdN9(f^ z(=c(p6typ4*xRin`+a#p2>X3(ydv}~N7x!$YB_&`t=RH|qv$)wxZ5+w?{hVtF<9^? zxQb0bw(}y7+=CM<*o#_So{c^lAWME`YLlb;Jdee&cca; z$e`;WZ@!7aIhT7CoVC0$8=`Ad!UBiuhO2H-lQyg5a1AvP!!_vz#`26*1xCGRd7zJQch)pN9kEnrjTyZwtM2l^4ssFSICMdSW zQ?f0dAv~}xN^ez*7jM}X#zr4e($^LQBwQ-9@|JLnc%9RI433!%aJe095@8@*L7xRg zaJ-M@6NK;uZ3aKO#NDal8qc}f)GbN;H;y7tTFtd5mShsO3Eb&g4`Z_0RXU7#a^v<-6B$TrARXlw(0 z%$i#a0n^q5G{Q&#h(;JmSoj-3gROvd?z(IlL8=k6ND7IrkhECOwe{|{zDCeNgxEne ziNIEX+F^$$wUezt0oV#7H@J5(6LbamiP$}4r9?Lj+sSu@vTy=K24erv#K7MYdd3=m z{KT_fr;Bj>-3miV_qU`sgkZ=rfQ1$Ei?3PXmm|JYA^-}QCYdhR__@jY;-EU=h)IVRG1F zuY0Sh2wDX5V`@M!bYE7?qYk<=^@+ti)4M2>#B76L91uXplV3XBD%>)*IE;V!V7D&3 zY-}Mb9kdVj@7PCyS_mUmSArVKk>`CV8nwS#b^iH&cT@IdU?E|v2%z!V3Sw*Cp^h#1 zz60(l>=#0f7VG$syD9^ijoP z32JQIs#+OelOR3=X&kX}+a0-NidhV9i{*^cYwq;A>5Xqo#arnX?v#n@Qny**sDT2dddT>ak$sv1cvDND;q|ZZGPjPlx}D z5ILPNzz}(9MnoIEWUZXVZX;NKjD!!(2AA;w@H7T0yu1Z6@M)*uGM+YMJR4NTziuJp zrHV2z4pSK-4znqQtqh@4p+ig*Y{_+}p=;&FCA0#*G4#K{QW+O&GA4ke5!#fdJmLOU z52?8hlD6Mm1^25BzkCaSzn%2>b+;I>8muE>a`x=zB#bnXJtT%-J_bqH7{V8vy#epM zt*{B}M4+N-B?WHAhd&J+oze&E=mz&{>*VNQT_>l0k3QpGZW*->PE*(DQHw{;nq7sD zde+@AWSpp=x7^*B|MHYO94_Ljy5-)gZZl=ww7Pr`)PU5?cs6~Etl1b+2kge3kHfNW zDS`R}pEicSblg3J(IUYrX9yUnDi^G?8YZZ$B*Bm;f*L*_Qwg*eM;N|Ue&OHHW@KeA zmnySA=+hvMq=Ni;5$LSApM6S5!Ts!4#V_2?hF@|&yNV!hB1Qu%><%3DOy>Jfx|asY z;^sf^KFY2rg+((MS=@^X>JwhP=`Uq*?}AN<7#^7c@AE@CcNqJRk|5>c)r=r=?d4Fh z%w1Y--tHy$K2~|X>Jpg03t2C3X56t}KAwC3%kFV3Igly==2?%!%Xuvc0&|0a$nR6s zIh?>TyLc%lvWK=_rUreit*^RAuwiD(q52?$^>~6n)_}mg?(Emx^;tf_`qGzF0OlTp zS6|*$z}(}vV6_UlM^Z}W9zR&8a*s7c5t)13B~%dqUB1QMH-eXie_fM5{nm`A1hB9< z4f&w}G!-sXr4-VTSsL3%)Q8zYU4HtEdnJ2>K(Sxp>|h^%^eoJ+Xb~I&)b7cN^>X** zc~Txz0M9{V!h1ax*L|m zI3ZG4H>R}qd+xg|S_~imfqM;$-QaH{nJuV&9wJ==f%+qz9=m~`d8x3Gsf@938C8k@ zcHTWlPusw+MS3z>E5ZPqq~!)|l8P&r&OHAkcN=XNPmK21VwCQ*F= z+91b{svE@EQN8q&3+{fJmdjHw!6arJQ3@?Ql>qz}*2eMvm)%`W)B%p?-XI;%OUh#{ zowuqbB+#IihTmmHt7;l=%Z}r(UUAPg$qZIYgLDxRT>c{S7{W03$3y54M}1qsE9Q) z-Y#s)k~b=U_cytjR-_S{e+B8J3LL)4)9bQUe~v?guigDCa=7nnNQULWENGF#T+;FFA%xUIpgV&X`|3E@&p@JLjJNwwk z9s1^tA{o*sTwz7?PS7`QyhZ%owNd6mcC9xOQfmPqCi-g$3pLR%-6;L%DS}m#yeFiT ziXr8BzUMnghWPvkWZ)#6$^b(Q)faA*4n=Aw9f|_bp}u`7Z9<_BHO|-(P(H$sMxx>7TGH&|ZVbag; zt{Q7&=4;c_Hp%{;rVxfdY}h}1lx4ssXx4`t*JU<^mmOa0_rR6l@?YI>U20yvq>8Sno<>`CJ^5uEJKVjBrB9V%4A>Lr$B^zNpRd5sim8$yFuji>pe@ zX0!K{^sK{}fDvum@ZGaFRVw{F%yZgeN!lF73p>TuW67kXUvoWS^DTOR)6Lk#FxH>3 zdK!~KFkTK$HF%W>Pr9{+;<}8B)66VGL5%E{c=E5tW}ZIA)1DD}IfW62kJ;eBGDq$W zVcKSXsk^sJU=bUe5R96?Sk2=#(VAyFu=)E%By1@=NMW1?EVz{gmTt!Rr!m_JW&wA! zr#l~AV@4H|T=Yhf79-P1!)Vo&a5;4ZXOrw*=;I< zUFYdrP|u3<3^Gv%Q!i1rsYyLdJ4JyPh;DPoX1^O^pW5(I7^CYaWQuE8vX1aABVjow z*RcN;I^r7kTk#9mu<#4lu#Bu>#gZl^q_Mr}GJZY2s9QXu%pRQwX1 zym<0$FUoz#s3Z8Of1Ud57zNav;`Bh?6$@5lscX|{7gMh>(YbCo}n7cQnkRk z;oGk^0ixJ6VbNEgauM zp%9<(Z~qZdzg1e4wDL5-1GJ?B8h9${mgQTFv$Ns{o}DdYlfrqU#-5M#hqv(5#zoE9 zVQPRq9(gVnz6}6Y=)^BAt{bKQYl}Pzo7~hh?>3HY`r1rr*8*-GcWdTp!}b%Yc{v_i z^lO2QwpX^pkuUCy(sq}oH1{x#T_mN1E92RvBLlkL&e~NPfPW@9TK_~5{`v07Nzp$Ej;1y`K!yqYT0{-rDqG+M8|08p2|sp_Ns#KC&0Jn1FR{j38i`L|k7 zZ;O?06t>lJhjzyucks+LbrSTS0!*29y1A8q)wZZIKhxIpktJuV*diDc$A7tbIgVd! zt;~ssv&T?-PLuYuoB~(&og$9lX&<;N^XoO>`-9&!@rLp$9Xz%EvWt%7Z*=f!!+u8XI z8SGt%1GlgT41LgeI|rT>5K#%=&IuAd?7&|hyuIGpv)CMQ@R04lx_B#0!Ud;(6|ym1Fq&TG<`h=SmJA^n_gY8DR(jEDCr$09#ViO8IB@^Gso<%``*xQwHnvW`w~Su*mw0Kr9*t zuqNf77~r{!>D<&lL-k(`36W-mApx)`At?}x5&&zGARhE#?E^{iVWiev9n$S(rWmRN zQt;8f7hMky@66It;)464OqOT0@}`Ge16Sl9jH_FR5mF9up{{n8UmD~Y6(uNSZhVfA zcx@{mFxb-~5j@%)n%`7T4V_**>YLr%^C2rBYWgGdqyL`#m&P{H2NT(R!dlFK`0=5h zSJ?^z^~I@#B;&Lim1Nc z33~5s%6{-v&7N_dHrgDXT;$1yTOYp0HZsaxxAEWZ@+Jm~*$E#3xj7y#sLTvxZl}x( zkhulC-#NE}hd6@Zb7J6$nMuksWd@9PPy_U8S_Aaz06;wdVur_VB~Zg* z@uYM7cIDv0VHu&@TJEjETh4+=O@O>m2dXBdm(HLdh zqbu>qe9t(&%XWDtvm4=tZrN!&am&6ucaGmJNk1@NMy9%Hb3JKhfjOSO{A}Ciq1raH zZ=8MqSO_1?;I?zu_9<2Qh0}{_m3E!y`AB1Ph%)FZGq+1unMn}JRaS48u2M{}=qf8o z9rTjz0j{zX0K!$4l45>Wfis@zi#!e45rRZdd6@Ei8dy+I0hZ_~lqGr!Q~*7NRv{wf}nlsaZQH1-5W}DCPRMo^dQgfsGUjRLlaz z@;R%DrNnbqY;dqrdWRi++xMO!j1v!lC6mY1JFaM4DN1@%)rNZM(_u zOE<0X?9tg0A{>3(yF>c8mmu}u9pN%n#;O^jx zdQJ2zJLCubJ`Ln|new}?`0buv)XDEk3H5cx}Z#>W2 zk<#@mh&IMb7rIZT_At-b1{0sbgbzA|ZKrey8$n>u6Q|5IJI{taJvN;n(J7|vBt3G$ zP8IV~y3XyY!T&|bn?OpP+v(|VS+~xB^za3EC@CR{M)nU z+P$O|67Tg}4SSJfYV;!b5B4HF+TRu!ir2qb`#^@RDZ@;~P&9)Dw3FS4s)_9Y*1>k5 z*1>iN0L1f|2R!o_giITEvgymmJQrCvQPj7t@+X@*DX2f$wEeH|2ejZ9 zP8QYT>*qKsac`~cNIvbwqMppAgvpFk5b5@TP%+FnU46pyG@C$*h>Q~)8q!KV1N71N z$pe9S@7onf1Rswvh{Su&Y)c>>wuB8lX00AJ<7M(gd&p0O&lO|x=LIw6P`&IvnYwz@ zj4<*ifW`dDr9dp^PXLSg6Q~QOe||Jm4b{Ihn1|i3nhvvS$wiP=GkC`aA~)25%#~t| z%471UrI`})Zuc8`H#5Re9VNx zZ*L%p$i4a5Y!S|NC#n}{+~oioN$Ow+C|2&zm^WdUXu1)c4c;i@W-6cg_k`y*hvEQO>>e?2q4V~ zk+Lv-#+!ZkJo7vJ=qcC;e=i7=7{$bRPWdfp5*U8t&MInOM6jQ@pIq7g3JArO?QayJ zf3J_QHF74`{sdcmrP;CzUukBQc0uiYaZ2ndiFCcv*0>1{d-Z>)E#BEq_Jhv7uj8RdRNJjwSMb*u zKk+$av6O{rqM>Io$Nsb7J zWsay~Da;XhgO!3CVElVH`cKMWSc+Ck8VQFyu7!F#;7j_|$H=H*)*Bxvf79eK6Mpa% zYwQRSj2`pw9@$GDCJ4+Ay|PEIgLP- z%IAi9&#_&EDSF+`2c*~SB#0pC6}|KU>4Z-aI?S&;K^hodv?{9NZG%G|I^j`haN&eU zNh#%o=N~Yf@FRjouX&#^)vqeAK`)d{4KIZMsPxKjz!1|b+TH*+yh$0dy?!^u^a^Mv z-H@t@ZV1*vH>B1~U!1#joCc0r0bl)qRpgTeM^MLx; zz0&Zx1dE0ry_fVXJ5)(LG2!q2BLE;QKY|p)OyJ_ZhK-gI3>v+VGF)f2kq-QD=Y#S? z6M^<b94dD3#+w1gD68Xr~tqJH1E{m*c%o{W9n#-XXX` z5Lly&v_@ac8lj2s*@5$W<$M|VVht!?tU&-Ep5q(l1ZoVZIJb>@P`MmVVhEiKHu&xU zg{u0Wl=asK?vfd!8w+9IrXS4jMLOwD1ZL{(U{xS8T|J2;jBR+ZJySq^s}8&bKI@Yy zk63aZgtSpaXhW7qN(tk@Im_}IUgLz}vm90TkMimDyp7pWQV3OigsAw8R8f0`udMHF zMka5K<*<8@6h2cQ;wJ?}Ht-%{=LiM15T$?ykLR5ldXJmR`CAB%O`7YwRn-@Bd}Z12 z3<_N!Vv>*M7D)48k}qT*KrqQyN&LbjAN&fMXn&@! zmV)}$^~HbTi){XLko=n(H<&!_SF^cyIBTKg$RuA7!S?1*F--DBw(#y`JxCEeR@QBw zJTca3pUm=QAE?`pjS8f?JAevvfpY_?W+^I62CfMtSfL0o*A!e|l50u@4l>t7NHN!> z#qx8lyrUuog-kX5OZ-aZom+cT6QR=PR8zbF$cB=srqa^Z-lYJa6{mw%R`Ve9;{OmB@FmhR@dT zli`_i$M8%6760JmS;Bl9{ z4&DUTi@P3U}S6vlxA!e6VW)7 z5;{5A!G{|uG$3PBazJKmwh>OELG&%O5)WXD_?kOO8Q6HXkq8hu0`Y7k0SUK+lTG5Q zBdrhkg8=R| z5V83S%I0eO_A)rVnAD!#C+CZ&_sL1Eohap>)UwF}s>Ys%Ja_8CUHUTEsT0qct{`Qw zHI~qdY=nx)5d}Md_aV7;>m-Hz(^)ze~5SEi<`0Yq$KM09@Xtrziv6(7Pll}%=mu$Tm1e>5cJ<7OfcyGOaK`4 z--23=@l@w)CVT5y2|11T5eLnlqeCIg(pRL%fL|woUVDpYPxX#7X#+jWmY}+$q4pV~ z9`0#%u|smAJ>dtnsLRXkFxl@$prR^Tdp>uXcZi8vNFh%K~&qREz zihw8WnI4_Y?PYTt^2m{&F?f~_9&)*+CCuP8s3|{QlCfpc?RZ{rn_8_VZSYPeh4@_PiNC8cH}tl*#E;bf!|ko9SvnnpHOZ>_ z6Y+=mNPX#guQycF^A5=&ay&7|xkB%FJ?9V(kui@2ex_u`A$d3R@gncC+qn2xdQHNxdNr{ni!XRxo7K#pqQhb)4q zVgK@w_>jc~rvJm=wxWre@Jk+8BK{w1Paa@%^?jeu8{6DB%wT5hW02i2_U!v^%&4T2 z>@krgB->j)Z$xAZw?#s$kgdGPHiRM~iX==$_Gr;wzjM#M@7?qHyhr`&`_E_I+3e3zb;iVBqkH|Q!T+|5+i356%H(liwA2%0d*^EB(?1VyqPR?2Nb zy`8xN5nKRb%!4q`5N9Ut3hKb~7J9k~hLK2I3D*P6m~Er?K0aI%hs}~O*aXA;1bUuH(^OOhC~Yr(k6^}xSVw++$=lh z$#8cN2{pu344=FqZ`8_J>ZxR~K?D#7HTYtAzg0K`clXn|E5w@$a5+H}Z)bDzD!66G zQ-Mv@+1xk+C*~&JOy=pUWSITimHhBM-g@TvRdP}egm8vP2=V?edulM6u8)&s$8m)=kP5jF9+mT5dCjwfoggT2q@)X~Ej_k^cqhpNtK=;GzE#0_t-Y}(`^}C7 z&Omi85NrOV?DCV&C3b-;_13QPRAh;(wfCc05>}%t7LDk`Q()u=p^}hQ;#Nzm02#Cj zAtS9q6Tm7TxLayc${?PO-X^T0PDX~vR=6+NAs&0P@ zzA4+Ef;txr1y2(5nG43RW#x1-M^^!Oe6NDSLsTsMUPT>JKv2Q=Dxi>fufk0WNg{79 z8sCn!A!WiuL>QaE%UVGbu5X8hwBDqsqXkg$0#ZbIV3S zDTMOo-b~()?DCe;@|KdTqmRmDD@-~wcLy?O-u;yjYEPGaBS#J=Wc*tgoSy8tWhoN*KMD|nu7;+@G&HO|l^ zObqUL!s=!n%*G(UFl&`HVY6bq^{Ore+uC8kc1a`m=5zQ?TIM=mfiS6JRuL-0~@%bGgIdy2?^C&|CI-`j3)?2Y{Zrhe;^-!B*y1= z%>yfqO3UoTo+dEZlFhl9m0nnjEq9EVD)G_Pd_C!uK)o>W1TTLUe1i~AViTj52)_G`XQ^qPhWP03k7XrC zg@KBYTC#g8A2q{OhPPT-C^m^s{zAkdT7X+cZV2KSmi|fn!mu>_!mxDWT2Z~Ki8&1h zXk=yKxtBa;jl=x(B~QC#gs3hc@E1b72eC*DPrtW9g{R+xK~Lh8Z@N~^zHJ>~{6kQR z5i?B#KI5|YLV2-0L1fOrjOpXDYpX;AM)CqU`!~VTVL<_6*T6;jZ$1C!>MeV4EEJD* zm$V0>AT)hM5QSMd#;aW*B%gD+Y&ZVZHBSdtUkFoO2%pB6b@Qrtb-GR!zl2I=jriA* zDjl!hzTtWyKIhECrFqJCu;r+&CWFNBUFkL=u_jRLsxAko%#dfz$9(S@@-IV*PnX@q zcq`wCWQb%J=X3AOEL@lpfvT1Jq*O=%MYSkuK{lJuz2WIpf}jxa=y3v8zH(mZC(i@PX(B_~g@Q<@Y_m=| zWt(-lW|ID-fO!Hw;WZPHLe@+~UN({yf@Ej$lwUnRn`_qb*82l>czlm)3FfMGqGw3w zOB)qUarFTa^!w(58StYY$ou981RCUTFY%jwI#v8azZw2N@SAH3VX>k1AD%-Q(J0LM z*A&E>Mlb&2^@mFaxBTgWtEDe#0m2?x=AuYMk5rfA6DIh)PrXT;Z+|pPu2{rP@N|j$ zMPm_qjIyR-thcF;u4(+TF8Z2A!g{%;0r|MUf)L@OTY57Hn<{+eWK-NL>8i25z|*PM zs<2vi4%*>+>_#=774L0~_ZDtFFz8>dXrM;(^IG#K7jzRIfbSYp21d2uJO9ao_bj|N zJWbv!IWoVuy6NhI+_Vv*dW80SIAz z5*xdyN{s|FuwJfUyvV%M|6Ow<*lXw-vtGWl4u8WHN0_ZB7YWq6MhXtvxP}9txM=ZL zUGEb9L!5UWuT$R}$5s*q*kWHx8&>Q;a0Ul^1wC{4db!v!Y&~8p87!aRHI0~$ftq|& z{V1WU)pf|Bu2ZP4y5_?5eC|~L-Mp;Z`)}T^fO?5)Gd|?Qi+dZe4+(M9+BK0twe|r@ zVeAR^Nc0XdSj+~Z=BK7#4T#=CA1enr$ZKvZ{LJx|Oj}8Y2Go#-$CYTs5G>SSy}h z|2Qi2!ANL)gZ(0bp7)mbF5_Gz;Cq$5naq4kyMCAn^Un=(6)T?P3N#`^UTR1(pxDDA z1MeYJESIn5^|3~FASGZuZdCU+WbH{NqOSLrKn=_Df#I##og^3WL$1cZfDO0jE7U_J z>WL&1Q4dw9vub&(vgsrjQA4gqoy6}<^G;&R>_FA{+~uQdO6+S$7Gi(lEq?gx@nELn zu2i;_jDU-NyMj4$gIo=3Ue}ve z6u{JK*d;+$l)~53!O!gN-E86xS)09eg3wLC>DKFnS6G?D&1260WiF;eSUx;d%I?Bn@;^jmt zwmeUP1Luq%8sv?=@JeDcC-kTrlbP|hj0iW@nd``k)Ln1O6{%i2Th#8sMo*s5llJ-j z-j=bDOW+2u5M^YDe08R`@!PoU;kMD}pYm9BM~ZljcuO z3>SboR->FH+p*^yg$yrm*%EfhP!c#4)aq6T`U$sk#M-u%w<+&;hc|&YZ{_XH*4r^V z-A3KNNU>xwUmK%=P)r-6Zg6gEFEiN@2Nt;=^^vm5M>>~U<&v_>6`d`ua=~GhpBz>> zORNGk#A1}&Mgy&4PZ3smql5Q#mb{U8sjvzzNu|(Ku!@ty&}uSuno zLZgR!GmK<@r4z)sNEr@>Z^zmaK&Tmr9imu`ZIBN8sfibAZFH{A=BSeFyS(?1@Ogce{h{H~=?jjTnH%@nylFJeCMey*!nC zW220w-ylUti_z=c(-qu{vSZ7c<%6;fgY)a*X@qFQ%yL1Ew|AAgkU=r(}hiZJ`( zLEbNz@s9SmP`_SIcQk7EF)a+Ck7Ete_?<(%_r?^5(meHHZ%O{a5N~Bx(vB>{NaCFz z^4`UgNV>2@F-@SPthYtsRa>#VSmYh~c3!`s-hwXv!b32%$H7X5(Uk9e*jvlpRHIVb zE;HQQg=Ohv)HZOh(4xr(=$RwDJ)$5l@CeKR#}RPs3YzjY zk9ccDBFC2Z2?DKb=v3++ka_ z4BJTC76#aG_4%uXOO=W60ODdC>*AZia9zZvyV5vsSA*r>WcOD&7%?}=x@hWLr5)Tf zP(mlmx(M)C7b!fgi`7X1(2d+Q0EMtF(n4g@Kr>PX>!Khc>Y@!E>!LkH)Wyt+-p5!^ zf&r<*rBFmsDYB}N!gA2ia}qS){YY8tTgp!Mj*ZENRGzoXm(0s;Yg>-@d#Y_58%`jx z1KS~D6+?N#3_4gIze(;?6P;N9xS<_Lo1j+41jUe}mgVavdCT$cQz4RN<3vO-wW(D} zDgm1MFXbVjW;fsw!JbzLqe2~gZM`uJ;_`>jj4kb6rZd&Bb8f@iJG-`S0(MWvq_XWg zUyeK9bqM&uChSdJLcqM$chxn(-DZTQ1Iv`@Y*f&6_7q{dUo7vl>;fT&b!K}2TBYkW zRrFN?ETpqaJU!sOy@aiHQ#6h)OWn9i=u7L@oaSB43T-B}LR8uOPk0xx1ez+ExkCKL z6W)O~Xa|+b(#I$j97e(YW-}m~2nGsoQ!r|ap;cqPqu>-VMZ=v6rQeo26}s3d!&Q;j z$1)}oLz6z-t#GYF<_Xu}&1yHnL!^)%SqT{x55oWAzJ~`%NpSvN z=8Vnqu+&VFf#azs2)2b#T8*dhuoPg!T>}nmWSF*kvmBD=<9bFUUXy#D^=@Mw2!c@KM}XB6<|beFGBi_ol=QF7_(prs zeBOKBh#3Us7d-%Bqag$lN;!Z?IZ8{(mUwFs0yU-Q_vKxdc&oVkY9va^B}=^Z*)*Lj zrR>XVz6b*!0xr8u&x^1X@)-gRB4xx0uu%1H#j_TBTk!{%dJ8*?w_|TON}7G&l|yMt z$kE#>0q%QOZie2r%sYzhqN4bal1kb@e8*r zz%Sgcki1ub<8}p%zN=cQV(x2Jc^5>DxiA0MG4~*>w7|uDy@?W_DySg)T{<-+#jJl% zN-VaHd%N_!X!T5T~b>6qw6jBaCvDNrm@9>(&7J1-f+!p!h z(n11+(cF0&0FPnJ-T;H_)dUJr;W3OATV#~{U6PA9AOk|#&01WmJU?Wxx}t1oGk|D3 zaIx)?uu;_ z0a{q7W&4>ab=fSM+RfX8ci-*Z=O(bKMa3uXmk?l_s0H}JJQRCRk7I6=p%1igQYv6@tj4iZE}K9OXtccAjfCrJ8zRC%dR>b=ND$jZQ6hD z-X_OVHMh!pDB5n5hbsU#&IoO|aav(d5z~q{j=%_h9HD}i!gu7S&{WZXkK@;mdYe0; zEAean&GKwcB=oUQAY@B%J1UPlGC-ITbB%Y{YZR4m{qe`VE!Y~GD%g3A7d{T_7ZK39 z{m69`F<;vzYcwt6U`j=JDN{IktiDag395k7MTqy=6Jo{evYmp8*_~I$J+E^~h&N`t z4DsgQuH6WIScG^DlP~*1?I4KXE+f29*JOnEPoOO(B7bVU9BW88!drE_oH|su;~s2O z)@bVkS}`F3x51NAfE5G0Hmsqkg9);rGudQ8XR@aVXDXBDeUbGhq|uqq=YjS5(Ntl* z-rW18x04gP9UBt~IQlCvGezq#nTqZbe&n3B;@7~=lN6tDCJgV+r>TOSC%Nw|P>F!n z&h)aQi23Ap=}feYgEJKXrktTOowYj?cc1s3VjtNFNMADc^YoM6GVc94Q?(QL9Q`-j z!8OEl^cQr#3`CsO2LE0f9Qrxq60A$)i5#^cxqrK~t_?j}*Os!b1FUC%e+l{yk}Rhn zsLtda+Lgr=B$0rH27ho#{ME~_!+>N-4A`+%`)3%~Rc|XB22i-Xh6Y}f2eH(g4Jv6k zfM8aFS|jGS#W1n85zp6s>m9`U*eR-3{9ch7YQ-^nQ2xaI1^C8m-XpHZb`;>bz4}yO zkCUR|nrn{Rp_^uF2UcBB`O@#a&CJp8uc)}ANkMzXeSU|mxGxY0Kt0%emSBAi(9oI- zXfc%FK-m? zf>d!Gp6NDgvfp(<5=Qt%q!K;X5AOZhJKyC>&Q*sGO6F>pLPaFzYV}sk4J!iA8|Y43 z-5s33SO4Li=}yo{)W8VO8{DCjWuP`8m$&}HQ=bud;hU9sj|u+rtSbQ*-faSS$|*R} z;{b2R9*6=NK5AeCcQh1=?Kn~%$B_dK-z+wcq>2`G(PDp1HiagN7Hk|}Zu&affE`5C zafS#Yc+_Aa!6ycV@F>9b7+)8*jHIKl<1qRKVvLo!@>oH5NLV~u+oQakk1hoGv!3pZ zQgLvnAf4R3_DBJr!S)g^uv5Wi=Odabbg-A#D&%`15*nMByhvy()_1QB+QE}L>OgtI z_B$5*Px$*U(%;Q^)!vAkDii5|G3?}gv>TL}uv0s=m=SOhE=Y=6U<=>!ji+?5eVp%_ zVW#YqL4&A}{DmUEM_DZgYO(F6oVG)nw1W)+&uUbqIDbCg7c`sRlECH!-xsX&tqIh- z34vn4>cxDmT;@HJLW+%pa1#J(!Tp$RcU$1on&8T@*{#5jDn05 zzc2~{zvQ8fXi<<%ekj>j);zzCf1B)UDFY>P&KXAiIqbH^QyZU$HpqXD8|1~QjR}Iv zIPobhwr`ezk3O{_GG|~0Ikkbn7=;nQ*+s?Yyr3X%90E3S>rK9+$^T&Qx!fsT(Z1Uf zf`2o`t}WaxmLaCKFp>0PQSk9FS?7aJak0uO$guO7gu`i=&2a!O{S59!!##I_h;HLI1 zJ$+xY`$#e2ylAM}vupmFa|d?TjC+utS$db;)Lvqj+|)iY&Bu%wAJFCA-M-q)A{=P7 zd7Nr{Y8TJlGohXd+#7d}N#>VxL90Egwn=F6zp{5ZbJ8x}ss`Lucj4V0ZvI8OuNa#| zm_x0;C=#evCrGW13uzUeW{TrWPxu<}Gt)N~W1@*U|w^a zP2H6XEp(}kq&&51G1&RIuSzVx*ud9`uV~;~?m7W%uN(3}5U+Mqs$i`8g)7Y2JjuHi-!hd!u{IFE`!H~j>4Dl~u z?)S9!qh6ukF8YhJ0V~A&w*{}k?f3_Yp2FMlL9W(`6S|mx?vxix{kl_LEET1h$p-9l z8~%o7zWGs`<(L0kLlnH$+y|R^?U?QJW zDzgb2q)7;mPzwZEIyFQ%d*FL&fgrnd=4LigL-5x7e0Le+h1R>li{i`L`1-N=&g|JF zJBi~y`!@&-SW~{x29BxmB=MzpHqK-_380{5ZhKEI9vmVWVGJS{_t~Fv=HmTL+qf^& z*OZS+Dv%(VP2#nO7wN-(BG5?WdqpJQZkyAohvXm^i4=3@B9ZSSiEONxnZ;@nXe3f~ zx0Iv_$*s5_v!o8A&pbNc^;# zH30((GR2uG1TmqgSQC+&D#@o*&1}OK5lF;8U*Uh5WN0BE7lrt+T4pL+?*u_A0HUaX zZF(j}_dd1oQYJ-RhIQ?@FQLc~u$sOH>j2(^#YlM$txE;7>w9t~rd6<9ET8?EuS$X_ zC-1^KBRCrJ9`Dw3YOS*1KyJvK+oaOV>V7#HXczAB>V8+!RF8>}J$%pKy(FjMwm0G*|f zjKgE#E~d;T-h0iadt^AJImv~lV6b_|9-g|^>S}g`2Yy5-wa0W4Biy-Uhp-ym(jNx_(++o zM?k`d_F$AD3OrtG@N^V-ajz63JPB9HAVyRRG(>08h{4O3d=25A6@oI|1R3?R+S_|z z?jp{h1qqDoZpE_N2Bp^AJs1lRY85BYifR{7X9-sF^Z~wdk(BBTs+f--nCuUjpY7rI zUW2*v=TQkAQ-scHLeQW0Di%oy0K`q=R3?Wu6iYU3;4L&|_Q+U&NpKQ~_45lJ|87LQ^1*g+J~|TDz3(t7D}iIu^6mKR6AIa90|#M^ArBt-6VCVymt*ZhQCf25|tu} z!jYC@^>lx)C^)d9Z2pHha%VtTjo=rRN5z)ogc?+A8Jq$)ZRd{i%`w<%f*if#bLADE zlML{Rb>>fd<+9H&Bm*lDF8lmQ6zzInuKPeUF4ujoD_^)yih?h6gPQ@f#`!9;vhQox z6kcGKd|$S5RR9xh&>u55XAlkm*qQ_u-=kBV>Dx2Zyq&syo z7dCSNoa1y-l%i;=!H%LvSN_OE-@}YhayDt|!ZpI8>X!yh@=bG3(Fh^gga~AgPC@RB zDg1@W5I-Z3P7>;Jb{h%NP8i3dxJ8qxzI#o!mQX>rSoOYaELM>Wbc^@jmu|6-WQ5(q z+@lP6)aepCAwe_`J4rEgiObR@u99?giHi!;&kmOWMCcL}k#-4S8(o63jV?hGusi%L z$G6E{=7X>!Dv!XEQI&Ku>f9{zfjk*ygLmB4*N_x~kryn7rNP5ZP!g}~vz63W_H`nK zuoDG%JS9coo#s{d$q|W^2jP`{{WL}@(omf&Me6qfo|AG%!sDHK6QjW6oqdt;SQBPN zfyX=hBHqR=Uu7$R6kyk#GVD%#0_UK$in@}61(cx;h*pgXRcv@86WL? z*p7KHJjUQ)d7Ne$FE;}`xV9Lyy$y|ku2d(s>3&h6m85`N#KYIArVZR*yb#kI=r%?6OsKn6E_*vSJa;9wv zT0t99t)LBQ0`?h8SNJZu$7`a>hWN_pRGloV|9GCU($~!njy?KZ2V{)E$XmPM)s9Hq z*tjltlrYEdmy-no?`&Jt;wh0q^%C1F``>VH))O&1VGMNk=V% z+UVe5<8;_1aZYk}t>jKG;KJ#<=$}ZzW)f~7!w7KM9^DkxSxDUfV z1Fb;C;@Ns$rPe}$0-k9i6d;_aFG8(IP>XIGFG7Vvc&3RKlGEh{Z}}>-297fP&=U_b z*!hBPM9Oe_1HYOKiu%^4IxP|trM%a`5;Ij4m_B9a;JpG?g~3fWAx=>YTxX`ylrW#X-@7n( z-m7uT_yevpM=kK4SZ6L1Y_P@myvz86AKvcknHUw2H{RjvoJ501A)*7{lY7%I3#zy( zdqw=hRay8Y_olxpgsdiXi6LpFRTYSSCfBz(Y9M;We+)#Q-sx*+umT5wc6C7;mk87b zb(c;J8DQ3bq{o3?Nj_)H#C-AvgNJwf+OZ@}hlHb}P|r?0pu*9adwlP+nxvcztR9ei z)hiv4+r?+!>5b=?2l$(?c23Y%8Wi6#=tBT>7_+y8GAi*yANYo_u>=SSjyfPCxqgzN zOG7S3S?4-)uMNDrt#LqZJeRzVW-AB~;(kTp4w4Lw8*&l%Zf7pWRv{O6wTBdeA>va6 z6e*lg6fTntL1EF*yK4e_i2qkd9vtVb?chC;FZ^nJdsghA_8~-H;dlEv{6-n`_@aF2kZjM$oF5O39AWhM%U22eHu#j{3Aa1 zU1gu^WF7g|g;nHxpN85gZ>;%Nr-*VH?#m(po5jCA46gga_oBgKKY}FHZejPH|0B`8 zm!au6HL37XXfQ}h;M4@p-+yPDnxuV%Jv@Zx4(Iurnq}Z$F*7Mc3hJ3j2f&LnlTIXC zk73(6k@o~_VrH`Upq!aV>}tpf|LB=XHekk?$#6U7!Ei*_!SVPo$D?cd>j{o=ViLhI zPE2Np@XmGOo#n*)oDHv0hPVC(<|P!Z9@B#2aWImfV8y`*P0-5%+cX&XN_bgdk4~1| zvIuDy+qma~uZ7!IMlTB-CuK0AvF#(dED#BgW7~^S;Bi@iz{@eGc2c!0KxB~~u9gMN zL)s0|H}tZA`;b}|C`@4FfJhwoj^)e#uz6pJLvnop90YHu(>$nPym^TK)zMRyMbHc{ z5WszRy|4MYvbs?z!bP-pip?}dTquY}5f=(5MKF9u*$7CResE0g5}r4pjHe>s+w})iosumB~f3JD4cF#Ij$JcJh|$CbtvJmcKBQ2z!d|6 zL)5Fze21@1exU~C7qxkvD@9_0$$$FbvVn#KGkQne!_qtIk_?OsXB?K%gG`bUZh6ga zu$M$EW8QaI1`VJ?luHGjAVK&-CsGW2p_@78uv`%xOEQEPn4=V`sZdgc3!rM^iYQ>h zz%a$68${q68$`-C8jBGF0($um5;YM}Z?F#yrx{qp%ilvh}1zB}L__9O$HptVG0^x%i%{SCrC0Eo~BC?f3xz&82-WgC5fCWuZk z*r2H2FcQPJ%RH*d(}?dRos2e!5paCY9sV+ITM6wMPdQ4MkA5sYgTOm&r4D!z9+hW& zmgwK>enn$cp0Qe|NY4NeKDtXxSv#x_TyJ+2fJfGAmGD2y2x=!!DiUww3H|4`kCp!f zp@-RIu!{sYy3RS}I_F4+4ndknr2oVm(H^J$=e8r#e+nOQ_|Nake|{%Ob%#>vwbn-fzfg{fB<6LufKknBDvXWAh_8R(Ey z8R(ESK}Q}ZYN|By=-0_;aC71jIG6A1>bAjSL$<&H8Y4ht=+Op@9*bSetBw)^ISxMv zywf|>YdJ&+<*^ug+@>+o(BmGRET!0XgjZkVo5u*elTZm6ps^7`H~cE(hH{{jSIzHX z*9if1#Vbc-D|Urs;NC1P;%J zkQ~u=8Uu(BqryUn*%dq#pI+Brmh~k?upZ&E&vd|uldC65cDQyL(+JuHfR@aw0IyNs zU&icvl+37Bg|z&p9o=99-WUyOnY{ySu^LinA&}g|n&%R&iE!D1`fCC+>q9 zw|O!wyg=y!RI;*CoZ-r9bmDo9{G}OHG}yFeETI7ZC-b`+`-iy+lydTmjp5;#m`}7r z_0RD4NYsTxA-(LsKIBi_;ja`0MGrB!Ncv|e4mW{=V1x@%b<|o>d!YikIV3a_*wWPh z8f!{0qi;2W@G4v?#TtFXxgu(j3W*z;DTrsypIzRsUfO4z~DI!=jD}E|F+w@OE&D{B}{z^sl zB(s8Sd{cP2ZvHCn6kT48LptgdISv63IS#SG>T$@ujsmbu{c(4HJv(abnb7hNM}n`- z@Yl41V=SXk5C2j&g@A)j+VS|>_cJ#nhHf5u84geQOYk`rJnk3wCB+zpUp$i-V=x}q z$^Q_)RM}IQ5x$*0ky1u!O+1Dnq@yk(v(dpG zuLPJ$tPvIXH0%oDm6s$M%_EM0Hv%0XOrTzH=_PuJ;O}?)tr+w3Pw{kLN^~F~fMLic z`e>n5}fMuk7 zj`&rMFBt5vT^6LZhqUvH1Zff#D90ly3w5#%Y3Fkmp0A-)NPC4&ks<9@MFKXH`Htac zZr*>W|8e#nfy0h*$1&M4?jRX3a;(dDEa=Am^Y*J5vHboHR{4p81m~)Ja z-3jKW$K+maK#QFrMT?!GBO#f8{;QiReZ1ILYxj;nFw9V7?YZvbbM1p94|huOz{8tL%An7yZy0(#VVKj6br;{zlc z@TnW3?^Q@20wiL@2s*(%LK3N(gTX&K67KW1U5e_z|C|ol&gSa&aisM)@f5g>Q`=p9}EFfg(j19w?fiS~Me7Et=7hkj#G^?=R;jsnBPHWADcZH`p$V z*n1)c4*M!!`mDd59S?Rg`1s%jf=3LHZh~UjbN=)wC~yw=+do6G|8ajuMi}Ji1UmL! zxDXWXK&nL4@4P>WZww{)EI%8GI)xl4v;iZr1xu?#^!z zm1er4*;3Lp=I}XF{eMRir@xe>u6!kq+bW;jh(DB&#^z(tXR_`MA{iJ1v2VnO2M-Lt zzasM!Fsz7ECD+C*-hUbdzd%t~4<~*m>)}KKAC7_;FH2;vl1xOlTp@$E79)|#`e#h! zt#kY>;l>hQj=uui=R~nbp*R{wf&1-&4_QqpL%N!P7O7C%XZfC7m3*flPu2ot(mH6xa>WEK*Mf{4*4Do`=rJ zh5|y56*;~*JNBQUcy6(OfE@+)XVqTtS7+1y8H(H&{Hcs^L27F;FpaRi`FYs(da6W6 ziD9)I<2Y4XOGu+F@bc8CC4z@v^lvoHZJ*0~P@=-{ZE8%{)qR6Y~HCJ*4zvY zYT}ghX{QB|lkf>YtSM5+!U+6mpaSvGq3w+vtlO!00oZYskwf2LrA<% z6~9Dvp4H=D@6-z>zTq!zu*w=KPhaP6&%G=C9nA_S)q|Gj;FSN;kvR!G-ztAEv*Ahk zo+V`C#?lJ9@JW7nh$ofrSmj^NI_YG|eyj2MVg*j)ZL4*eRFR8w>jE3&dpQ%h$P%6Nw~3r9p2Kh6z~6*|MA4QXo&c?Z~2F@mvxplT=FuVYD4*Z-=Yoq zpKtqHx!)!ba`ZfMbBVfat4@~a@G#EXpnY)zL7mSNViVVE5RIE>1VL%Xbe1q}D*ra< z9|`v+Jot{k1v?)lGnS8^SF{-~vdLe~brdv{H?L@M-eVIqSHDDsZuw~PVDl()Q-<$+ zG`RshjNE#=zYc$9v%kGr45ESJrP^z|coLtx&0nsVw!FHbFa8U8n0eL?2nkpG0!*Nt zKBK4xS0_y3xi1&|ar_qloo2cdI{{bMdd2hBTm5&s&VeMO*Of@-Z*KJ$k{p)fYkygg zz`xn*?{9Xy1tRsN0ccW|f)seJb?fA4ZP@kdoFdH?TT zPUFMg^N(R`?99q`C~=ie)h-w8yxU*K6}Oe<$^Gf`-}g^tyLCEG-RIAM`)9L1@TW(E zfByr220IoBKWd-<7e?@NqkvU`*LkC8W!EJT{(8gWRoE3$?D~HHK=Z;Eczqque6&h} z`O_C-b9g!*Ri}7$qRj?Un_GGO0e_oF3Z4W0G@}TA^MF5{C7jYeiumJB5&Wf3N&N9A ziWTOcAA~rwcHt0_V8TcKc*8~o43kkd0+MQ(_ut}A46ZulFKwEQPKB#gLsF`d6v9?& zUX$^O{91_-F~Pw{{J)#5BjFyp6-u;al;Y6H6z7*d^-oK=wZqio{b#OD;;6Zn%{m>{?&&wto}H@kda!C3nprwIM_$E2HYDG}bjj#QS*;;}DdPlgU`mFyhcATVQN4{m3S(v{b^JZ~=@~l6BFFNNhYOV$4 zw4DI2d!F+@Zk|7dy}7ZL-~ElhtqmZkejQB!KOnx}1bQ29XB z(}a_Tr=$5mIbFvxr9vwKs?fs88@$zT*(Lc47ya}3)x(1e#}YCQMpfxZM(17iUocot zQW6xI%IoaNUxdGX&7Z>VBUxai7W}F2{e^ht>;94azVTHV-(Ss&wUs|p4cfS4*ZrTs zgO{tngEI%wkyrR0A{zcE$YWt+?=#=~TNuN6kD^wUTTyBC19)jqUi8PCQkk$|V_o+8 zO{ny%W;Om>Dt-8c8~&9*W#Lc$IyPAxb+2bcT?#h&8G2pw_-Wqb7k^9l3C+eyIb!k_ z9@>!Q>0~luI&qqJ`xR!Vwn8{wJ=AA$Gxoi+5RO-&P>bJSeS#E{4b+#v`J2HWij?0W zs#WNW%^7R+YmXFbXy!YkozW<^=nwyWWK?js6b;a02#%r`N{EE~^t6b}G^%`5u!#fb zyCSqhn$^rd{mo3)fG~!&IWssaA7A>C)yviL47@Y&YL)7&HG#n@jZIN=!o1n_jI%Ae zN78P=<#ay|h$Vm=Xx zEf1iWWyjW@FU@E531cgk-&$ZkEfK-vrtjsq>e}#t@U301fyh~3#*}9(2rlfvUm?;O z8+d9#>u%C^g@k==dO^#up>_DH0whfWhrR-C1U#{&P;e@Yf$B{XWa z1#EHtSy5{o-&om7Hh(_DM-{U&oTMu(dZ{?$=ZjeF`3qn5E$OP7SAeIE$t=dRi(3^~ zb;67u4ph$5wa=`dN4kP$r5=psOXtPM@Y8oUD$A$*b*TWqw*J9bQs;(BLjXI+6Rk8G zI|)hFBBL9BJ;`d$GNMxMLMivAl&_p<*s6H8?tnCzh9#`VHZr2NF6vhUDr*UAxG{>y zl>~ZYqSAYW(wnU49dZ>f%`;#7Hid6{rDS|`qR*7Fy4#2fcP67r#U6DTIa3=|+B(9X zAqa+T42TULvK~7N{o;#jqpsKY$7Q=2crto z#;6!9^Q+~oE9SnusFiKFL~kpEm2GT!Yv$inwjuobgT-s{uBp~Uc9w{$>)Dq&HA+1j z%ja!0i}B0~)^YZ|h7_Gu1{t7?mn_&9Jl)#G))9Wt&M=~k=Y{hnC9q8-i)u1|J*!rvu_+=n_6zl_Iq(2;t@>6y8x_>W zQ}wNm?6jRgdtRx5Rju^G+d|LH-ysh8j;{nC44q=>JDoyOCtqQWy6|S^I1cZitf|3Dfn92SJHisHnoCA2c8GYFw*$z&8#{$G!C5v zqR>a33}|k3{~Min7tVX;0XB?qqqQ+ar)q5kpKW1HGu@AoJQ>#Q*4nDcJUUs9t;I0e zc#MDC+L{oh%OSw3L1HyB7A;NR*q2u07uwcOHFh4l}XBTTv+-+Zn{WT=R z+g+{tte{SpL9^R<+iq61Xz@XFZ1Tm)a$PshZlHsSsH!U&xQ6YsLxy4oxkjJ_g1uZz!0@p)5x)``zs;u92~&Em6F ze0GS>F7eqTJ|FPs?y)+0mWkgli_dG~^M?4W7N51^vq5||iq9tT*&;sM#b>AZ>=vK* z;WKzv?3n(K4eUQ^?68rKEXe*4lE!6Y%bO{h-_Tly8p}T;gPfluX{7ShLDogj64Aaq zFFvirr@8n9#K$K-!vya`#Ak(wlD{fG_lcn1J>v7VnDXU`&v)YAZ^h?v5pWnUJ}-*T zV)5B6K0C!{k^r6{J}-#Rb7ws8JuQZ`C&j0%_>>YKw`f}n!Dm)%)v@EojvO1hx!KR~3Gfu70P*P~KF^5HeDOh>9T30JX4k|ouvw$qvT>M%M(ZeWq0z7opwZqEX=t?OA){pv zgSPtm`LcKM7DJNr^E*668}lARt;uY*u(w(b%*wVh%$aA!uHf{1f}#HW%0Aw*>9m~oKIQ?sj7EGTLngoKxi)%cEl=EIhs zeGo>ri!TdUYBhe3P8Gj!HNNk^UyXljxV7G7$2C$udZhI_J3|tHc5{B_iPsDAVWX^} z=JB(#r#?T*dc(YSR(8^mD58pPf(Rr(HKBW%V*(R~dejS;L;&7$j5Uj~b0L)zIg<Ch&nj?O6t6EN%$^TM?5ZXtRWu~!U+JOqjT+ljwK$kl$~IG!-fznD8~RPhkJm|ILi|@Kc33td*|!#ns^TU_WeQ)*kqm0 z(`Q+O%n9dY7;9zt5YQO>?=d^^H!4@C-WCQRz-FwvRoOjmEk5-BAi^kPDohgr@hvoTIU5W94~1F zs@(_#7CeP|=#xH}>-|Q!K+FE5JoG1$fgXC&Z|z`l-{{(eN*CZ!J@f}%K8lAXYY$B& zC?h=d)>uj)mXbNvNmh?wK{;xFBX{%E))~q}%fE3)KE8OGb)V6Z|1=F|)}1wobkg?U z5GTF!8{(w#n-XIAeT5z?!81P|2VqF9Znc|3l2!f+|DeAvoemArFhT`YCqO}URU`cM zCPMR(J6bfaruX#NE$cLYvJA;R_@s5+ZE4a<2bpnMRrniES~d7bGoiV9ieH!s@z^;U zPAXz1Rm8JY5v@!JaMpUtN-L^WpmwNOe8f}Mopz$4v91&WX_o+udEp#yKHKUZ)t}4C zL1;voaEp6*wzZJ$AtIn3?38}Mc9IPA=Yn%#I(M9=ibh0$NA>6J8ZwGMr)Yn^tN|li z+*@NQk64P#x3;lA2^N&&SLM&Y>I`MekxyF>xQd>K&Z~Y_Jy!g@uA$iC#-At7T<$z^ zW(ZQ(B`vPn7bFQO4~BoxgU2qk?qc-`YV=?M8nwlZE++RavRah?I|qhYfOR-7L(_sb z7$YEGa0u7*(&@5W_PJt>3_kD~tFfDw!Qlb%ICbM>g!kOa<8J>uk6ZPu^&ImMj?hw* z&dWZ263IZ1JO7-ufX$<+!s7&ZRF9jWA)|O)7431aXuwF1yET@oh~<~X)?pSTSWu1) zQV#b9ouNFgy@ts)l>QeX2^ZATb1@C1#P8Fyu5m%vKbYs|y=*;B+Dx@Qt^gnYigh0&R5-ZIAXblH6r#fl z{hU{=SMBVG#{>Ox(``S#bWN0Z3_nR*pJy}d*OKJ|609qUDChGzyzcj{D9 zj;F7%2CzXoPgY78D-(v&rGY61KFT}34!`3KtE=lV(4Oy5N-2IVt3W>9>L~O>lLg?JQlIX5CtzIlwm*FVPHYLn9 zouPz*s~qz2UTdscF`qylKfL_0WWHpLRg4|epi-zKRH!^9)T*^sDiNx_R6CG!2&FPM z{{x|3U1tq<85fm>YOjZ0Apga1O+b0zoT#zYD(`mb^pH3e%jM&>H(2dsNRT}RBy7p0AAJy9^0Z-2|GO{$C9a0nNAY_r-BSylR9e=kyS@7q=- zxU7S)fEB9~Zy&Vkx;yD~r-zySF7oXwA@V#x!$|h~Quc={_JxZP&KpW=baHa8(%W6U zrHA3dT7+BLY81w(2W_^lvAKjlQGxOKR$aJpWOand^05YK{FisFEZ0jRYd^HbYQ0D``c2G=gdc=u&Pb$mWJytbR z)tX5$fQ+MAQ5iKZNl(6&nbz;MPO}Mw1>}6J;(V;mP@FgZz-m%>mPk&5NXP>VvMYfK zst+j5pZ@^tGF!t-S)Qb_Jfma@R3A`+zq`*$AhI-Wi3AcDts&x8$Ii+P6sd=;UtI~86{n3qw$futT!wz(YQpAftQ7o`kowgRnT!lPovFFc##ja^k*-c!QGW2U(hc@C}rPINT zCgdE+XLU(J1aARqz<2DoN|T|mDo**5V&3tkb>~gR?ElBS2K@M!)+ko$O4u`Sq>aa= zQj&ElE6mT<9dtdHHizdDfh!3zs_NE0D%|(o|6$oAV#fS@*aJbVLJlr)1}jE3#W@s8JAE zWeZdNJd9Syg!ntNbaM<3o(Co$(`BS>$4Vy0(saQj?zWymQw5V_dC`kjPd9;%U{dW} z9`*N3zSiavY`R_Jq_I+Rw34O^j%t;7p%9N*y(p3QC<0f(#$B?~m;G|VKft~L+b3S)10|26B0l<2)7ICo9a zxAoxZUnCae#jjfnlXnR-R~H=#{!(2EtS<~qX=NTetIo-aP9|~6H=e55w_OGJKLl^T zijqHxPo|hZbr+vp(UNZypTnZs9u%MA0ysf@eiok};WIA0>MGF9KvdHa%?v~_1B=hV zqBF4AjB(ku3*6QjS89c*-G`A{DfdHN@TjEu@ULHrU5nlC!sMb8>lThSK3ohpa%WDjmMCK^M1F! zC}?^C(ZN7dzGFuqsohk84OKS$zpJbWU;EzmIR4<3=L@q*0x=3TiD%^xEKHpz5~>M5 zCRris*>geObpsX*OTJlV`oIMZ_?7~JMQjzpEF2(lg-+1;_>O{shi{VAs!(7adtaC0 zM%6$@8DK$~uY}}tH-X5T97qh_9~-!0uun;HddZv$e4IP*G&@C70i9aY?Hv~wZG6i2 z#RZPp%4L-fWR%qeOGOa8%3C+dDQmd-A^(EglXnT^s5_giJg@h*N0Mww%6;Zuxk8`cK zomV}OVK(`eFKv_axeeSwtY(Dr1hFK3C}Bxwv(L9Yt6ff4)|Vg_N|3t+@8h{;0&NK6 zX%V=BDP;p6nQVf+d`3}i-#W6)Sb*(j=3jl7z+pc6SGJD+ZbyY%`$)gq6m3l2oL=ndjafsAz+B zP*)+gjek#Fbh$*kN>kJ=`X37nsz?&Fy2LMRZ<|0H2d_$rmU~BLN>Mnou%s^gjJ#c#@ zG!6@EMnZ3{5ojI>jhwWIgnpwYR7A?RFh@o0e`;DndgCKDmGCk99= z*8R!Xc*4M(fsx=il3nBgHzxCQ^#h|4)up}A6;Uz{o!u8v&uuz;^Y3)lC!#zDoh1e{ zhU5%2%xy$*#8CYr3WbQa9-7nGJV=Pvie@Nv2*zGp(9l@^6e%Co(4!*gb5Z?n(vKc* z5?IK7B}&Hb_$Qqp97wio{PU*J9Y@c)zggfpmT=us>tOm)m6ar^Xz+yV{MzuG-ZpSy zIMRfu&D(^QRQwYy0&f^*`t`8K!X+p%^DB^&Go|#jBuY;bh(vW-2d0`muZvrBO7s1# z16^1T!L5=PMt-eXcaeboc9-DrHi6A9^AQE#wnN}9_Ar6Zdp^+Ayz4q&mKP}I9;V9y zyG?S+@KPNEO_HMWag~pLe%i2`sP=rvz`UCnZ+54^Q|u){NR86acuREx5p_mqFkbYm zLR|uT*=AkJIhNWkDi)iRbHlh;0yDbD*QP2odEM(A%#)hpGBzq@O2T6C}TXyjVGS0o)ncy zsql)?^MF0bh+OIVz;-`T|>4pWL>&J1)mJi%@i7rzy2w)jpr z(Pg96{Nqy3O}`Ui?9zN(pFjt*F%&X$nj}>KGHSNcP*6mVEX7lY!{ns;0|B=I56%Ag zYK>TtrWN=FQ;(0D}9wLELkQW1OD@9R3_gd<8vDp%bCpfRc;xaMj^6x~A?-{j7V`q`n zp@F$Bb3JN1E1IIaw+j^!`YUH-@q|qaYZ+40=40Ps1!lSek3_Ki{e;LfdH-)0*wmal zBG95~HssC9H@yGY!4noJGu=|(-76~=mR{$%yK)Am+|m`h!#gC;0Hau|x|^5nrnn&Z zie914Nj0hpb#`RnA%1*hz-#9FUiz@ARp$2^1Jf6Oi&eESIqW3W29IQoPRV02%ue1cHG zZa#%1P?ECa=>B@B?k&4_b$7G-54O&+iy#-hY3c}BSoyH8A3HN}w>d-=R;|)NQW)!A zj~|?Muj3DqbuT)*a)cE%FF5h3K(-n8lvYhBurm4n#r4@jogNOXz;4qQ=LVj2(=zfv zCf-}}nxlveLp;TQn-`eCNEr;M5EBHWm_S5Sf`85reC}e~DcTBw+xet{i(9k3Bvn)j z7l82+gBDlhAMijCTOl#ZCge6nA%}zIsA}SSp9xeAjfCnHnp4rdYB%;J!ANvtpNFil zv4hVHS=`Yu3;by7gJOQvrP12gBCLJ>e_?H2?uEdOWc%z&aSdkwD{f9hzF`o=fwv8Fn%!6yDUHS&`J=OH zKJ=q)7#^Kptd)PGsvkqLq;JgWROkU1fXvD_c*H1fB$q9@XwZrTbM22jwN0QE>DX6? zBv2#Jyf*^Rnfp+LTZ}z_Q@Y+OOM7^oc?+BK0}H+`!n>~wl;&qv1rir6TM)-f2N$N< z(^JjQf4un!)iCAYI*j=7)i4IT1cDt5WR;6H3@#WhA!Eo{JnLXiP4hh{V&>ezM8zRl20je0B#o6>NdmvjYHU?G|GM~GlXMs^|UqdOJ z-@s|0t7>)@UpGCciMaqu!c;KXEAYxg#(F9^;YNfHuyKMn)o_VfN-LbD#0(ufV)#Fs zq*NldkFJe_c5Upxxi;RH+6c`GgBNxM>blH}SpF83a-w448(G{Fd~t7JsmuHg#J$;s zFvn4ZS8en{?cmzofqRT#^8BuchwILlF-5zFqNIB^TF- zb?E*7KRbLhtazLqCPsDDV4cH(R}I$kCv9a%-CY(&qd{;w6%}9D^2ZKydF@Gq~!u-ls4b znV``*d&zf{oP?rmqey~gfuA^rZIo})x*q1jpKQ(3d_g37^E3ytbhp^_Gl+7TZ>rL& zeOgIMWBbH^!uE;866Wyq&mHsVs7%TT)!(S+fK*TV$-wXIlbfsO`ue!-bn@V8G>UR4;=`VWAfYOD)X{6eqsZnYX?YC}U=;$YxZrRVX=X9`Ao19bXKj@{55~ z_9mX*Y+7}5{?E=4)SM8zY6Lao0tDVy3VzGnJa~7TOOA71mxVpS;Ke{u!`Omi^31Un zVYPPTljWmE@$x&$^46CFbBzy4(Q7+$Qldul;zC7*dPFo2$4amKtj9`3hjS3fHdM0d z3WrL6;{wHa>&$7;K7Jeck!KE^R)D8{T_%4J{xuEui?CvJhby7@B=qE1o+Rj2D%?<( z;|Vc2!r`zwdZ$gR1RG0@-=RV&uPgS8u22rIi-#=jbq&6ULPl*_Sk=awq%hXT62CZ` ztazUKVkz3l7d2zy+8CL?VYa_EBvFn;JQ(2Aut(>NrOVqdGp0P{%%@j{nk36^O|Zfrf}? zs@Sj2W-9(y<=?8As+})qi&^tm(WT#FOnINuWHnjZ6C9a8r;=ed|Mli$%6^U_oE6Mj zZg&3_r*KhQrH4W#cy1x6zN%HK3?)J{IMOP`BhcTpN;h$w7h`j}#IT7V%T21%nE#*S z950gd=1oG9&&TJy%oY<$xZe1zPSDL)aCJh?D1*JB^PGb=pJIy?$L&MGk3QR4z+~@` zlDI`{E?+a8?I5YRzJ=Frq;yQa(**_ix{^;cbCZ&=Ge$gq(Jwit4*SGjRPGHDrGk%q zvI?pmDaL`|L+l%S0l6J);nkfDjCXjsQaQKVN{G-J39ws{!hvp}DfaLkrE)S2lP8qU z=~*S(+&?F>DDHHsP+@ZaI~q40GN@j?27?FGsXyqBhW#51s9UFgqelH34o*+6U$1`f zOy1U)jd~S-gPnzHhS;ox5gO2jdz3kfLQ#MV`3y7!@Te|q6emK=h~y+BgzxiJ^?7{h zoI9h6Ff+0sUtKPzQR?3bFqx0OCpr87*n9KvD2nZW*zT~V6CjX;HJKy?WJ{c$wFgl_ zMFmV)+}KoRRU^paf}$8vX2MLuBm;qB4WK9r$f8`^4Izlv>xSSiB7)1st6l{3>Qz90 zr>c9pt9yE8;QD?4c^`aycqZL-s!p9c=hUg{s`EkSk&R6*VO25wtjoB2 z#%+yNxNlXJ(5cytRikj@LyCfBMd_MCqpxY#`TPr2vIOzaib+;Y z)B{{tYE2<)L^K(K&9<;A_&{2)a!&N{7|8|1y+i;Z?_Qk?gP#peU z47L%j^58P$&@eeO{1E(EMHY;6@Go-I;bHuXd=7a8{~|lfbMY^-1P$U}B>V~CUs%9* zSAC58ik^CK!pt^USYR{@$=O%f38@xK`vl)^!z?4_L!ErR?f>HB>&X7WOeFHbb{!Gs zh6E<~7jUoupGC@ke-Zs! ze-bsfnOoJf+3+2dB46)uwjBDSVNF{&D{)XIA#LD0l)ZsRiDnTiCkh=QAC>(~Eq+ph zN2s+2e_^tJpq|5#?#UgC&?aXv!u_m1$JNWHW#jbvO?-v}M}L-_!EcBW6_Z(bj(jr{z%(FdLGn#KH@MWi7G`Pr;M;;7JTm zZPzrF>#aVg7%p$$G>Rz{=M4^C%WxDaYCaXZiMvosQ^^#fRhI@2XbS3jCZCF>I7G)T z3*O9JhellP@WteJi`5^K1Td?!Ag!ft!OaT)JpcZQxe3iu4D-! zCsjKc6hDj)wk8xOU(tIR6o0Az+(G){m7LR{CwJ}04F5e82lH@{_Qkg zjS!SB2jw^8m-i@@(fdv6XfCDNC+VZPZ&BSPvVEU=KxF$C>fjCfIJzK_7CDsrO=4-@ z7o4sst&`RSX|QRAXlb2JC#@S3=_T-`k%8bX43mwT{Xrf>nmMQ;awihWjpC!UkjVsy z#!!cF)xnvPnzD>gQpayq%IOJ|#HpCHJ&#ZB@?<>XKD6feu3B!`9~#4#G8&q$P@htc zJ5E}SMlYG`?wq6$;64+k)MQqoE#jdDXlZyh}1>8 zMKTs>>X$FKL*4r~^+ZQ^?re)zT|D;{^wu50Ujb@3K0NY)T~%In36&9f<NFVlE3a`L(S0QrP%QPeSD+}v5LM-p}{EZ^s zw=H-fyXFu5*TtoONMG5gV{l0r-Fhfkm1f{JNH+urbX#$kaXf>j%nUB)zS9nntP@An zrv^H)6%E<7(^HtTjEL6U4f}!enZnk8D&IkdKQ}b<&!lo>;1!W0e5L)BEt1J(5f)H% zM1*bs)Qgb$lm0-PXV?!IqhM7}!&kVoB;;)dCg{(z73?Ur3;3LI1;vX_7luoHP`=EL zd@%SyTXyoFs>i0bbW~N9a|qw|r|!dS00{Ai*)h0U{fF7%eN=Abvlpu!HS~09lE{0{27?e-4gRX4)r7in1p-bCRstM-volnSr2@ zPSB~p#2QGt;yjs+BY#L=VhxoN4S1UDSd!zXozFvCcL$a8;koCvN#>Gr;1w|?d<0Ic z-4tBPux6QBHmEX+niy19$W>;o?L_Sz=AgaJLCwkB6h>t-aoW7$^8_)Nb;)9a|!##`#$`p zKXV>BeoKTtAG9*guDoq*7K204GcN>tqEl0w+M`us5Khp&7%V{TrZ%-k!=^WNM<3$1 z!(Rv%qO9kGMd-gTz&``QwM1>NA;Y z6%%E3d`{{?HQMuH@K)5}&ZYv+d#n47Tl^Dmo_5&*%8h@JkQ@3|{g|FSPy6rg8s!6+5>FOW8NiL!*US`h331vRBXY#8-kB zqOHxL&h5@0P;|b;HsLz96GZ<0%%*(g*$Hg!ya#^eG{cv+Q9I!J%;6oueDw7zK@&QB zPt#wjpu_COVB?%d*g+(>DE32!={FY9Hw9GYZ;vxij0|@1k6-i8GEk`I*CSU`Hn>u< zLHULNK7hqhh9+%UP!H4@8*SPZT*0+wz(>gQ0mNXs)nmm>#RsX=241LkHmnlw|NSS5 zzu%K9IQXO{WS`lxTaA*6adXB|QX#xjToPLHTJQ_VZ$W5fhcu9)C1%{4Ar6T$<3i>P z%{YxSniqFQ2_J%PVe}U5i}Nj6v^e~YU^|9=h)HfqQCX<7CCX|v^6xtap*?Q}A3&q_ z?-+=G&0}Lsa=l)puVByH!JpYR3{fWPY>}!=D-{Z~uNj6z{w6ewA?id)&<7HP0`&Kw z1bs>)ytRO35Y0vJy&K%f?ZIQFQ!kUs)>Db<1v)hKqfTY0=f2=08HeF2I7!xZ(?`KJ z=&gN0f%~Vn#>$MZpbXCY!@&=wEwadX>b>B_+<&R3c#)Bfi-De%!d7qH#c1Td;3cT; z{b06+9IrZZRW>)sY<>a4d3Mc^`~zy8sy)fuS@(Vr91Od8tjY^+HKQ9Va|u7RTte3d zb7tx(SqgPS|NSU9ila;GnA#{amCvSR>iEsGoyb)CWdAgywt<`-&NsGebpQOhJ;dTq zgKsn3jTEay%o~4Q*anq+7PN4F>J{n5jcC(n@coM>(JtsJ;^)q(cBMra^+1&|dglO{ zXNh|uXN&7tO~@0*92onT5WG_Si#Xt5@EV4FT&9*i%%c=F@i0+V?_ok9ZEPR(GR&A& zypSk0e5J%ZZyDaWc~>h%DFLCXj33D3{eda);5NaWA`95f3v&XA-;GK5-t)m|90B|1lIrZsa@6n*29iM^TT-@{!N0Caq zD>G5kSZ=14u#y>%79R`VqbaR3#(yO;n#veY9#@T#98hk`&=})#%z?2nE`e97F^>N! zIGtfdnOZi+Z4@;z#?={mV_cGPhSPl-J3NW)P+8F@%=uqK!qi(dQT$GiM1@IdJ7VPVVAm5?!_EJsm7z*c)0TkBM@1BW z7Rh6x?g|AR6ETA^^A@!F=TLVlF6!4pQZ-qY=L2K3EYE&*-&$^6UfrkB&?3#10KJAX zYxDwdk_4w!P^-%t@c2Bu*Xgj^{5GrG>i0PUHuxRz+HK|lR?x61T_K{MkQ)x`r_o+j zMIX6mB4S#G;>VAeZHibk(cn85wWjp6Nh{msI@zAJo|Y)0)$UOxi0wPQ*p5hIi*HMz zrq-e7*^HLSLwT#*)Ojt5f>)!;+|VGjvTdk>T-TY_HWXrWTPD|9m!AHP%+M0Hv}JOw z9js7jwDz~hvf_%M zxIGwlUkY8lNk@Xd%mZCLoI+Rq3I(mJ?29e+tIoArnXb{v^z8L?v?A0q(bKBbdfL5} zUQfHUBId5q(;}L){hM%9gj%D`^*aLMdq;@cWmPbh0APG)n4Akd<4Km7=7x3q${aT}$X< z!g+pmnKD~$Z5LE{o(F zZjeM2s<^5)fA)A8fNJCIHYyHqYXy6gPOxXMsrM+7Jrhl>Ppzq+BuM{5Nq|~SwFmrW ztKI3aIh;0|$71uid_J?&CkRff!^OMgNHuLK>{FTJ$(0q!T|25#*6$OP^+T;p-_yzT ztUao7kxuuGN&0*#Rv&-$U3OU?P7!Gu zk9$xOR}VFp)n}5ps^9?aBKslcyz|aOvGX%KFYX)a##EyR?|&j6J!=m=&-|K3uV0s0 z_*ts2TKv%wvN5pTy5_RbHHNDE$@29Etc1#<+HyPQ+AWX2?oC02jf#dbr909Y-VR!kxPK(E3 z=WRY4oPj3W1nEi<=X<*(*-^g*jU{_n?%%C#G}`NLqu1V%@PzURR|Dg;M>uQk{Y(*T z8tq-4Ahact(3E)L>LH=$VD$(plpJ}%JlXc1J~||D4^U6>K6VBa zlfE@2lpi@JWM>r9DQ-Z5^GsS=YN<6~|0JI3G2iXwl$SySHJ zKUeLg$}KqtmZl?@OLuWIZVv6_%5l^3-YPlO>YyHwPhsUKG$~Y}DTozqu{(4*cU5BH zCU@v!O<}Az)OVa=iNcq@0*SYJLXeBur>}An`qLZwk()$4*Qw%ƖKG#pR#xj%%j zN~$;YYvs|9?*`AqEg27G5MC)mDPDX_sF-2bYR7U7MNP(Xex`mb;l>R8DK7O`8Y?>L zP(?a{FVwU9wEXX(IMAIrdW+^CO}{;~f&EU){t=3pu>XDn`)~apu>Z~!7}6Y0)jdU} zx>65`{^g*WsiDo9!a9|joH+jSZJb@xLce8jJXIy}kyBsn0x7Dfr=%es-F0_pjHa|s z(e6lW=u8~P-EqgE-bSB<__^=}MAo<)F)PLzHy&Oo8iyXd>($F3Cj_CDeaAf%Eg3Km zr`NafoD?HP(DB<+xs6godr|z~gBiex^07(n%Tt=ZJVEiJ)4s=~zQk8U;=KDqPqu+j z2fAathN+R|y^D)Sfh4KV4i0UdT05}w23(*1?C4|AS^YVX)tINh@&V}~YT%89@S7}z zMbm>rGn0$pCrJcKjCj$@;tcU_#|@ck3@DwLG<4zOpr=AzSZ*eCLvI39WG2Xb z&{aq`?hb7TZR3Il)KpMCFp>I9=ElMC0VMOu<_}kuvX5qKOlcKv*VvR+NaIo^-B0;? zQ>Z`7z9du2rt~~TO;mAhw%(Lh$YMRC&^n1f*!c`GrG3vV9?5>I<^LOs1Dz>-8Rwtm zb1mK$x{YPpX;ub*P{f4&?-JPm64*ZzOG-1lk8eRwY@{Q+%!?eQl($Pd5dGm5kSjC$ z3u0(eCR@=i`BzJ?tS-abX{Poop-DWoTXBW@sl9(YjsC|jSlB-k^Ym9{_KB3*CJ11T zRsats7r_0J0OIqyIOnxcRV#KSbS~Mc^e5zomr0b6Q047VX=`>F|&`f(;LJ6S{ajL+4t&%eD)LdDn-hvChC_Dgw`?K392;` ztv4Km9gW|qr#McihOfjIz6nJcZiGr^#QI5@b*c)<8B-6` z=9CDZL2GWQ%|+LJ{%Qf5{%xq4^Q3O3RZHnM09C6bA?ktJ4BP;V#~b~TIs8~DTissc z=^wzY8GHKs;1!ss?CBr=J~V-4m&nwzr(Z--6IVH>y;S3hS5(vhOJ`202kM9`isg_LYuA6k z4*GUbt&Z$C@zeus+8Iy+z4HC5Hce5TZC{wEda`Xl_`|CfhO5w5It(h!I{NCD9Q;tG z3|*xc8C4n^cu$`ApWj2x4Ckjv3F}j+2ZVJffeKE%>d_P>UW{C@uQn?GV(4f$H0q~U zTPG5cd-gFM5#vYq{26*&Q<`w|SVF-?2Ww_(%IP*VE=lb0nfQsJ==ii+CB0tJs9Lzq z)FE!l$4_m$BKcslEaxbv)C(hlAE<(q0pFhQI6iMGjr0LwXq)*E3#{@Z^7LK9gD|a1}o}m|C?^j zM9l1lT(qTQO+)JY{}sp3=(dlRqnq|@oXjoO@ghyG3)QEpQxd1;)V6;g(uy`OGx#b!UFlE+WIlVoczs?Tw?a)uwAY>jyaZSGogaTZNUrCNJeODN~K zc_v4k^5Mn{8Kd^h!y1QjhqYvC!Zr4p97ub!v6Q3QBMF5{)iVNf3_3|ZdrBGC*i$(q zfbXNGTvKTuF`y-@Maa3vd%QL$oXfRXc{uxM@wuFE0MhJsxOtmB;PVPn&Nav-QCw7$ zN39{}%XMaTR5c5hOmdPnwe1>%wq?FalC?JrYOX0aVmh3Ra1e@BHs+erFpky~*X(Z5 z5xA3+taXQ5@i@3o`mi?-y7tJ`e(gegnIfU{&kQOOkdy(I&StS%nydtk|sqBM-~ zh!>Wa(WJ7PwuR7|#|9j_15Ow4Vs)F{cE4HhIeYxH9|PCxWc@OV-4 zCG+#d4j0v|XNpp{>$aleE0*!5lx_NXG{-vMjK(->OeO)Ju<*E?7PHl3b6S0Z!{u;# z++MfM7O(^y;?_%QrnV?_x@~r!!|t>>K;UktAoyHX4;(DExg9Ql05wlomM0$bE!)Tx zx?MJ}Hvm%LVT|B{hsWyldE6GK$7O*RsJZo079N6E%xjT$y;+|3muFCTjK&1qCMpe^l8EjWA0jRT6%-AMbZN%{DMmH(0FQ&s!b5 z$1Ip3@86a@$^6PwHZGX`s`*(gJh8t^O{w{CqctOI2Abd?o7Wbwg1{^mTfojk(oK&A z6x3mMLgxfAXTlN~RlCJ*HhazR1||lN&+9TfoMtcR0cbV&4OHxbK1nKTF@r{%Z7#Fb zW%D?EZl^Qgba<@1*J| zj=%!UdtEL#+61!oI=oK1jkn7E;K74hJa(Vk=C#^f9;X}3&|?o+&0dQQd<8n*0=P3@ zv;>Be;Bm)fsTPTsE`KDyhfdK}$j9QeUAF*9`rtiKzy!lxk>P zS`$jGn`WD~v^%x9oM3Rs_UQclqSSpd!%6haXy3ws+i$VL>0rADE?s!cyxVJcc>`9T zCm`^4uh=|%$+Q+GKH#?syweY6X|vhA4iBiV(+|N594huX&En`b%U3alFpb#lf+OG! z_oLPb?GnKcfVT)(@CjLq3;YuJ z0Iwaa-|Dgp0k>ec@BsnAESM`6Jqr_Df!oZ(Ksz0Nh-=Jnd(mov`;0D&GhlWGyl8sE zvaaG@Zr&42QJR*$sQBPgzA#P0u`6nNp`tfxI--l_)|3w5EtIiYoGvq5p7b~!5D)PI zn7DZ>_Tc`2+hK=GKV;&PtS$A`AIRhY@x_)6H4&yd^*|A?txj>NHPxxJIMCh{q7(dN zinBjDKhKn|XT=VX3ZCLj4y()IgS^Y&ts!o7Io;q&1+NnaAH0+IN>OIR;4L?{=-~si zg1aY9s}piD+aVUP^Ja@+v$(-3k$Y!NUOdEvsnF_&zzduv_P8!POl3as)(#)<^aVul zxIchKr)fC5vF5r$f2uakX!OUM&1g$wO?%K%C(O1^pTpsE*kB&Omty@62o%j`-Ujn3 z32RBPTp;i;iNVoWivt*Q_#y5E0;}6^1)u9j(|auGCa%7=W*t*#_j-I5-t5E9#AX36 z5)kY@r^D>?I|P>#HLru|f70sMdMKH?@qP9hOJS;3A>IYQ!J{Wv)|8k)#$*i!6PeBC z0)qoNyS!G1&1W_9R;L_L!m_{vQG^eSlT20+MG77WK0J0agcNAVwb4Au-ULP zE^~z%P{Qic0`U<{zC45=0SJbzu7KTV2i0>ryxw@s879qs@`K6c*j2mj@V zc#A}4WPU43)2a(apQ{;df_XGmv#7c6QXX9()?}FicDoBU2Ow~=fRXt?2klmvA0Tjm zDJNhR4{w`~Cj+oN5AXsLxexBCSzLZQtll8zg7vAHhky_-2p(Em11bl#KwVxx*q7ZV zz~WU1cwwyrdhLcODj@FLu4T7)tSWatjYCHmM|%LG zHNVdfe$y{ly#ce`>J$PtFT{dU2rRAI(zI?xTd$1rrj!la$okWPEN|5GD(7wGPRhc( z&<#7RPry}y`w)DBTX4Y|#O$?$sd)nObe-nfm9k_56H7BfR;|&b(M_+mv^lldT#AXM z=@nvbtLazh_VRA4+YYOKD`*`LgCXz`v*499I2ttPD9q6fzb=8;*(-Q`E{_YY_`?2x z1=cPWpWE(oIl+bmvq#*wdf6(*R`n0B^$dkH74_=sE(8nf}o5{L608^61=CJyBn4(-3V9gBv+Xqpx7aXNoGP6S7 z3_itTcK~}HaHbwN-0pyGIKgk&TrTmjY1vMu0ODvf^xh)CoM!`v;(-_fVoQg|3}Goc zHg0J*@zC)3Fx#bW60I5c6>m!2qDPv<8o#XRZE|~k5W>QCjKBwMkP5(M_QKT@F9cjJ zh>Kwx18*};YB>)E12#!4F0ac9K_gsOal^90>~X_ID*4fIK}NU%f^+u zO~Hj`pM>cvb)#~WSa7N)+XO2wGi-5q%&^D;e{S)3V1omuWCsuH0H;H8dwXZ%oIb z;pp&uv}50L8(N;m3w^ zyZ-7PWV*fabG!cMcKy%o`o}*voZI!+d@eb+>wj+7AD<;Vx9d-z)H=88uldw)ZrA_Z zuD@ZvxO2PyDYsb9?fM&iYdE*-kIxwY|902^qS|%Y>~$TM#}@({jJAl!{A*zjnsa*PLm40)H08Dd#RPHvvUcG&+OVsn0k~Yb ziBjkNi;(LN9*ng?JM+REdZ%-^UB?xe0Wu=^7u@oYAlHjx00A%E%+;2V?xAe%h_-kd ztMZe)GkY5=(d~PWcSoilmuI8uuHnJl8)`$S*&LR#v*rI?eTsjPOD<4(!;M>dh{L;u z|ITE6OqD=uhBg+Xi+Y5E+!yL&T%CMLs$)U;7WU(g=>CH6KRAjK72g`J?6Dcs5EM&J z>KfHLij~#oqrEvz!`M?D(U1RKK7#v0+k|wTiuoPIW<{jyM1^XF*$EYPgjAs)+snie zMd3y^t4k+U%u+A1dWP${BK0xVi|>1eCqv@Uv8CY=284S{!#>V#NchFokugB{aj$Sc zj%tzgzLUyqdx_cHP7-)hj#?M)aeNHsEQ)p)zvvxa!f@l&5@hTM;JI2~j#S_EXHegD zeZ%9JtQl&39Z^p8iqYIG^$BjF63o@#Km0I9mDKm5lho=RsawrCw7eTK_qP|Iq9@vQ zqf|f^0<8j*hJ}4SsRxua;)>H1EMzwteRN}Iv~!fHBO)l|>$S|2yg*b-B@(0Ss8U4P z=9Y&);-06T?!7Kjf(mnH4d8ZCPl-65N7?4^6^W$@F7$her91H9X`0g50D7uJR+_*Q zbe7!lA}HG5b<*G3Q%QRpkfMDJxw&GQHN1*pfA56myc-386IX|#0+p;^BAIl%Gz;y0 zxUpBCR~3h2FanjtY%2+a1Vg$58a+5%fJWWbGanV54w@)TXtha~)Ff3O!b9AddO!~` zn*GCWJ1TI7CvyXG6>}vDPws-6`l?T9I@zaOiDI!vPhrY36)5%`+eyNOzDzBN$jB31 z=n>RYGV+(9ov!dWjxLSIlJY%cq;6`sL({)*pDV5%7!I=xY@1?PH9VD7h&pVHmQ$*E zZ2~EgP@bl)xJy6-E)F+y4`>}SfTpoTn&rq*W+o9pRxvzCnBMOy&Sba(<6x!N-MOCtQe2*19#PAj2 z3mERCN-ZhScP*dj$7SScRJW2nnTx8f3eV9L*G-4@(x6f7NNPYmQ29fj4vP<31=}w# zerKQmt(fIxSdOe~MsV2YZI*nm9!h?V9gj+il%c*ODyUx^o1 zhPN|WRjQmILVR{rDe5ySZ0BaEkEMyI3W=k_i*?0wo-ReRM~5%r<|Y=;9~0ipQMK!1 zk0*_VZ8BsQi=9L)o8qwH1nhW&BKFZ3bNfk3aymnK99|K*Z$0#QA2H{;@X8E!w^r`W z6g83i(+P5a9ONz~h$2}}3|U3VMUKXeCn`gDKd$BdDAl@-_wVDp%h}d;O$ZNX8OWS= zTUbhm-BSsRt5mQ5h9uw2d}%@x>u-Vpj48xa66k;-)jl27GI#iQhAGEX66gR0Nusv3 zKTai0Wup^_NDhrG$y5|06OjiPp~ZhlerT1n89p({mRybFpZ~lo^e{iG;eL0z$d> zw(!MFBcU{$v42URl;ZN0RpAG?wNx+3gh~3ok$Ot{z7`$2J=|SWdgodQtXA)jUe3Lu zEiI==SesAOn}8@%LDKID+{F74`_IdRnfFLPsLTecUYs(Zl&0k0r@*p~`4W@z=-8{s zQL0cWpy%2#AcAY2i3T$#NQ2a3TqW%;!_!fu#D%B!Diu8mkfXTz-f$m=<2vhf>p%B} zujV>YPl!Z>vO@(it{Vyf{D!u&t(^P z*5`szNB9z1s0$^+YP9s>@DJ>|&iceJD#cJe#py@FRjk-qpZGtK8ObiLe@te!lJmdsCO>dU1!I!o0tB8hb~V zBwH+qEw{WvsI z$30DP1Mci{G-|^TE?0f1s;l^~DF($3AVS4I5XtLkGMC(8Rz8;3!2gs}@Ym7?RrBSW}Pw1kyVylzBfhPF7_=OP?cj|b_N6Z9lV0Jz9K|7t zH7QU0h%CAFR4sT3oJT!SdyGa@MzH%L{+A$3=XTZj-<+;V{ck&XrTX9XBO@HkmdVtz z|LsRn6aSmvRqub>b(QpoUXdBIii1s);Vax9Vui~jl;XM9M1J6|#cj(bjfWlYU{P{f zWgsWAM|0}h$Qzu8B8I?Y6jwz(AakMz&AL8Pr75VJ6W18DfJY)tAJ%E+L;^G%(~e1$ zlBzC#u7y|Xm{`U|wleH`?U<~isL7ZtOc;||7!xY?HMQ=~QfOV{MHz{|4Gf9k541&%?BI793KT%SHe><6+6(jodj z%+p_)5dKDuK0P5QQegU_9Df97^C#=*Zb|K|6kd@rmDfb~+!|ps08SXF6Ci@rN#aMj z{mUfkYP9P0xtEKBCr2h`FgIY@1UNR8HjaE8rxkOjMZRU3TQFGy9-B&*C4=@{)=e{K z4DKeajRthn+kUB3P=jMrj0Hgn{_N+DZxzW)bBCdhq8slfjt`@<0G_Zs5+vkoNv}Aq*RVTH19{+Nxk;QeSza5nzvq6!KFNPQ?cm%} z=7^>bUsG)8OzNxZe>?-WL~7M1-rU?@>uc)S)3~+%4+e~`H_Jw*{$7^2a{ELlBX6%X0%|NyOU_r zXw#(P!8i#Pgo2U146`pmk5j^$OUh_`0won`zl3_Ajy1|&7TIYs+>uq(U=AAc=bCcV zZF%HL?l(MeRDd95fBZ##N>y!M5t*E4_)6TmBC(E16nJ(IhV`frSh|HSEG&ZYH zCG3cb=d3P9O^-#&x!&qy@;PGhoQzD^(dxZ6QqNH&2=+N{;sjk`H29vDxb(e`NAA>= z)WT%qX<->BuCGB9wNk$mgml zTDr;%D28rc*uGIyUdP=NiQGwh)D*ka5M8oG^@tCJLZxhD4^1Q+!#o%pc@$m|BPVWs z_14HE8SK+Cwd@ktQ`E%D7x&Q5X3-vre%+W=63H6AQWSLuTJ!YwT=B$nke0IQN5*$v`^?dl)`LP{^l_DKVzlwz)o$FLY)DUMov`IX4` z3_Dn+mdEfSikggJUr1PPt?fi1>lGJhB45KXBA(i0_(~bRkK@yg-eEpg7} z_5Z9_BRkng3X=Qm&t;iDBoS7Nuj~e?v5f`EefC#65_HqwBTukvA(yH)(YG4ReWy^+ z!5ko2?|eN%V-em064URdP_iNZI*qW7p&^4d<)Yj-BCjO*pmyYqNE3Ge51-y&n?6;a zs?I2waZ3EM*N|gMc~Nu(X`EjTZj#NBD)1g{ihL)U&7`4>AuCYEh&EJaLg?eapstqm&F*qR}yQdDI8 z>f4VEqarp~sJF0(f&DQP{V=9_3Vzq9E%8< z>^xI)-J7Z>+4*~9MO$`>DY>>SR7f=1Hr=Gxwh17#|4rM(%2u@l8SXVaFqBW%h0QM+ z=n&bY%WYG8ntPujCSlRu7gjmA�%w*S?STw5=^qES>e`tpm7!CzjrvSzD$ltyApn z227D1R%69}i>t*utQZ@K$wjfQwF-b^PEk^oZU?W3N)M@B`~p)Zk;%&3k0K+=oL{6@ z=5|GAsLZ8?JS)@ZI~wpt(uEr}T^LXCqT6SrVWkL+#o&a8w5*K;t&5PVysJ zuJ;saw(jmMlD6({#`Wp9?rwmN>J{)>%#*BB|I@decc}q}K~TQskp4fd>HqrV{a+{b zKMwAMw!E~khq$`1b_RnEJOp@SBepNh#(zJ^FmK>GQ|#rLWMH1ZOI22*@jDh?il)tb zwJX|r>#EkM;^EyUw6p!nEOe+olqnu7tnJRAuBEkk61HP`^Fr$xlrCoWV?I*s3-;6T zAwE-Do0Y+Qhsjdx3px}sjXQZ&8d!F7g8HsA7}d49Q9b*8!7efzpB6~_f`+Oun)=nA zV!6U%RfoWd=szA@p;V<71HbehHy}0LRR(m}b#yl51n&bE(D9WyNRcMUqVEx7 z(=UOTIy8DYV>%EJImPDNbBF6XjK zlImC{yi#-wJ#%sGIHs>edmlPn9T|b&$JLWeR2@t76IEu(8LC*Ci7KMOAyoS^PScm` zDTZ{j)iqLIl-X+FrL~JW=59=GJXIfUmB_(o)XjgCsOZPq!I9lUvwIPnDS|A7C{{4AvDd(b|;&!E7VII9! z1<`NH9MliFRj9-z_*tDtv|Z?1DMxl zpyDa2)0v9-FrL^Z!z=7`#KTi+CooK{L?_Q_^C&vvaqjA=_c)V#o}tG{;x3O&GoIA` z2B&osC$(o}Zjn5x!I>``D%w>yirIr1PhnM;%MyJ{s(~E-8jlX$S=*V+Y&*x*-NAf8 zI-h1{8?LVi&V-etr|zm9#QaFnC!O9#EA*P_?H{0^$d`Uc?VlpII}|kZ)_%Z_<>xs(xDf z(qZ^Y*&=!5dl3bvggQ(X>i^~gH>LK0FC@tGIY}Cd4?O){t@ma) zqz;`iw$$h3e!SaDgGuJol5)N;&{_5w5NWBsmz3w$2LwfqSn$k_i7dUvpKfl#88331VCzNkWNhj=o-Z;&Nsa z?v1e}jFLODp^ql6c@o&x-u+nsPxQ;WdT8x0d6(gG>*)d;_KSp`9?&TaS=RkGxvtzS zH}#*mu8^xgZTlvVY5aN$64P|;n>?nOtWapQ;zWX0954{(r#fMty-yjZNb^jBni=Tu zKNjYS)AQzk#BddT)sZyVX`89ktQNz|wKQ83v$6VCqoG~qk1O)}cmePr0v>q%8J7A4^ZB{^20XRg904dE~9*08&4AyA?A>#lX5uX*KtN@n)3kD!tfGy(n z`R#Tm+Sz((9){5Z_$h}U06PFj%MMtrfamA20l*z#0Rb4C(*xNE3C8K_swEo$cO_-J z1ijScOWCepg86ys&m#9b4^I zvkOow{T@I90{~ip2C`T^E`TJG24~BM7$A}d=ve?E1kg-6z0KijQ{ebiAw*U;7 zIe=k_a>c}$RfL_373k3MZ70UsQ7@Om)g3(qYe~ z(N7&vav-I|04W%tk4uo_(fPTibln2fBMBH1AdOuf zBsF5%@5++_oC1K|Z4m@Jz;4?DK;gH78U}c*699fnfsYqjF?Jg7vsnCQK!!8}VmAN_ zd;NY3;B`3#G%Wz2g_6~!Zru_<(PQ(k0XW!{O)ow^{}K}b3)(Ea6@a+`{})j8T)f2t zu-1N;AHcKR@<0+;umU##83802Kwtv!pBo^3tne@3ivp^X)rQt|{Hm)2L{;P$03H~; z20)bqDk}IS7r?`TngZUb#|CyNx-Z`auytu#E(V0DB7pWz(Wt{MLH_jleSWV3KsEz> zPB1hFK>k>G0F4FoR{(JY6fnDYar<2aj2h73T^0Z{0t{Ub#zD3LE*SL0>~;Apg4g15 z+9d3v0v8OD%VNbo$pf!>HyD@C!}FlLexEq<;;(ixrj#w(EeL=u`JyzKOK)DDj9bb z1_VIDy>1J@w%K?<__SL+PP@hFhklw}vdbobrG*wAG|=w1x!raz;M##-vHAgFF#y=z zZkG?u`4<2ljUv;U7XU6@UMHYjIbDFG1U1?mJO=GYH#u*utWqiIv;k1Ya-DNsc~#qxr|0vIk}KAK@NgR!wf%K*U);RS&>_Idy< z9dK;HFw`mm(@HZkKCOYJ(L}elbQ+;4IFNv= zp0a1qHGmSw0I2|*3TTZ0pK1du0Q57n;NW4T>}GIy;`FPR!gzX};6DLT&;b!8;5&jd z1i(_B4+N~%0Kj+3D3IW5K|BC$9k4lUUN0crI{~y7B1-_Wwb~sb1eIV?XR2 zC{2stDIL*^O@Kyi1{ib)xMx5w2iQit7tlOmo`8VX60k_Y+(W<5$IyuoLt(5~yWa~A z(k}p3os)M0?x-IiSiO?5NHG=oO{diYqhbc|W~%^Dr+_go_ z;FrNS0DiRW?qD7kAQtjD0lnD);{phv0Qd`Ytq011$8`E|U=%klh#OLjk41-6mqsUD zTH{JBGM6KcR9BRyYm#vl0j4$>ixb=mz>EsK6JU)2sTd$RVPx$PVTiHjGU*X8pA zraQppLUaMWwmSiC*9EH^z^4_^@j?iT$(#jl+~ITz;B7o$V1T(SxEz2O2~>c$>bGM& z_;^g1u4R-pHafZx@F!EXysy{t-WU&_LmS6NvkM`RG6T9R@Avw_z+puQ5s=ph5Z^eK zwTqxn(^?ckFYJDRsrFg{`aA%@q<}Q;azKx;vjBH5yMDk0_X~jC?SxPmJP`PNha0cy zJTT#cLQCk9l5(bO)kRieXa}6t1bzZS05?RfxOIB~L}v5xFeVvM zurM!%d9>JoK`<(qqoAuiK*qWOliKWaOH)%(x36G5$$Ma)12|ci190FW@_@CAgNIcH zV5Y(}A^}2@^<+WHmeH13fV2v0hm`G-6`1*|XdASxDq333o6C91;5@LR^w`0ZA@krtkla7el6U##fXG9-JlHF$NozZQ{aFyI2EFaQ}+>wt1WsyI0 zKw10QIepQAkCt~w@7@#b!5++A{ME*Oo!3DM*t+b=Q{BF@yKeQD`P_H88>@cmj>>07 z2g3Ed+h#_GW!%@d4LWr9&R%H$%xGp{4jiBfR~>{L#^EYV9fsog-;dzJO1KKj($H6p z__Pg4x3&oXB3K!V@h_6B7vWzdPumjwi=+fvihsdbK>~dRX@Ak-ZGr@Sb^PAwM{U@r zCCOf{WSFnJstcf-ymTc2c=_87l{9~T3WN~hNWe?y)hMLHgj_Fbyi8+yIIm?ym zDr1V!(z>WOt4MtgC&}ilzLImOPY|;pdO1m0S0p|)KN@8?syNa$ouAM&I{axgAML7- zPJ^U!)`sYGZj7#O=_X?(axaJqIAchm+LJB`)q%JHm8%@p#iACb3hjtRo!n$?g_RxE z3c5)Z+=?r|G~cflqy`W*A9|t(`fx$?DrOEUTo|q79#PBT-qRI!mny6#73LXMh#p!L zEkGk0qYh>XdblwLg5D++Zn(eE!r2lEqwcGslQpGr&wHw4Vou-*I!ewh5_GSt`|IZ{mDFND zDxrJX)p3`|ezfdLB( zi2)Prom;R-Y3v=h$fi@Ro7KynSz7l(U7#+oO zC1t8nVE3bX`HIeR9(9VGNTZZ`ph^S(A{Yz>IO%^i!dlC^AamKw@aS?Sps!MeU6NRR zTsg4bvcn`=!-49ZNQ+(Sf~;|BcW9+`tB)zA9ap9*ZK=vwzr@PpjA5;1@0J+rYt*R$ zMzoUN-gO|_wG$gGBa*Yf>)}>K7As(j(tZamR0smikPVEb7gv!-6YAHkyD^+I~#8}xwfJ|ekgfDo-~$%c?!QVJklweb_{WKx$L?mpoY=zd5%I zojMt9pfn;LFjp z;vF1fTGcPpRIA3|+bIHEcLvmnvyeZ8{?lfuXs^ry@g><%hdOwegAxJL?%T{jP0N0dSg2XxN7?O z!I)EGamKHTvg`kmB%C^(T_52txIoo!5@!!kAE>g3YiPwQsJLdX$CSFzZV8;Ov3-3H zhPy(okAzc{R=pvQ2UVLCQV+_h|D7945#n)Xu0;(U>$h>&QqRfKw2FE_l7WGKaoyySEUKuy0Dh`-{Y-8JMF46oFMy|Y zsUMetNv98QQD8ut-?hGm+iF1C79H(cKbesJ`2NM+5*hqEMMR|aFe>j}e@s(QCxdsA z$zXkt`ZpQwAXOug!9S@7M9v2%p{pSj9(qH5&jdxwV`mGNSnv&QeZ}!@JMbBv5lkN zoXOtA>+`y(@p-0N7LhYF>W}S|y1C<4oX* zJn-Ox)!*>H*Q+jp*fZ^^a%@ z>eTCDxr0}{6h zX0S{aY(S!{7F*A*pVpO~Wl3%ZKj=w*TwK4p3kw)bIv5bu3@(v#VZ&`7Jgvpez-!T) zL4{P{e=q|yXKVf1B(vSXXX;<){*H%CKie_8(1d5}FXVPnFYz>2v_pMhpjRkE+SW^5 zY9*S!M$ARqGlQJCXiWfsAsM3o-N&=fB7Bu4d`W^b>V>rgD_90$! z*9#EtB~<*-^rr!W*`PSd!ATd_S=yuWP*GhYn*k>3fq_JxiUSsqgs~V)jvZ)?n;V&I zoR}Ho$;Jk+RC}Abz5X@!8ktzOw^0-^vA021y}jA28hbNjmqbfxdh%?%Ckgg88}4Ii z?QK?^aoOJ5H`mv8VHaDI+uIAWco#~P)neiP`l7DvI%{%!%aoJEDkRVSR6nr`D_WD= z+eC##V{Z*sy}iu>q3QQ0D9Mp&Cyl(GMzITPb5TjVhF`d^@i3{APzhSkisjr7)Kj9h zUt7_h_6-f1;yN{aM(zR442g882dWyPikt?#R>rV=OeZwm(EvFKH&$%TA;j#8)^~@7A6+F=8=X?nu0px%$Cn5QT#~~ zq#mfy31t#5|-H$q4a~r}XfkP&HhJ_F1gF6RwCl zZE)qBRr1h+8aqC@ECO66{=}8)8sf;?>ioD`^ z<*-y?43lSN{vbhe`{Khc=er*KVPifT6m9r``8V!!Le4z3yJoq&-$^w}vh=DAiYh^J9gDi|MYc#~;|a_XU3;wO{(x{H*yHNNhMUGMAmX+^z9C+b0x zs9R2U-{rse%w*kHF-R$oyrCwe2O5bTCd4&E9eUNh)FIm)9)PUsqpi>DJEw7WW1p%# zbbL{R3uUf-Ivf3GQNs{0N05y1oO6}T)C8%rYV_jbhTmb5Qbn0`%Bj?o4p`D~FPM-@ zibsJ;7O4*4b#YR3cvXXxERtyaSO*yfD$VYtq(qxORWxEZB{?bhp&l40`2>Np<`WGQxxcA3NlRR^OY|1?l$gTb(4LwiIj9 zX4Ee~H~hqXMO8?Q?R)A0S!8_WL~DL&aOq2ypxJF=1G&=%#aH~=P^m9IhHEdVvWi#y z=zkk7(wCGgE;cAm*4#A5x~|SN=qencd6aWemEo_yCe_c~mq-&oqk7*-aF$o26DJ!4 zu9B*O>^R(Ts=>isM?EFOQHhS6Y8ay_jd{#f+q++GZ@7T=J-cQ|{*`JKs>bw1hta0) zVwXP}o?ubGQ$#t)u70&zTGE!8Xf_ioikHD{<*98wAh&g=AfLK*v9Sfr3iLJ`yEm&z zt%`iYEk@HbVrK4f^)We|K~4@gp_BL>MM4e^Q{8${Zfcp-tqcTBj&^0_qGK&$GtgUX zj6+je#-^bDEn-;H@gQ(2qt&RsMQpfAw5nC?e)fQXdbEyR!yTkJBBEc>I#$koLp>$x zbWlJ$vSR%cixWNlRacxjh*tmB&|OnnH&PGDUD~hfl6bsrET84Nx>S7zwtAt$&t{i# z#ne-x5na(MS+N27(z23U6HDi`jdjj9c+)HhNrUfP|*|Zx)}`0 zopPBDf8_PzD1}4C?PFu954myO)Vm6CWBXVk!+9xg@c>ekkH}onlw`i89;oV#UdV~z zZ3bA$jAS2jX|}g!<3^0<+F9_5tYQc-c(+cm)0ym2nOdG~7gN+^vVGX4U&qV>!QmA$ zeO$|!OETpezxszM_5rt(k_S;tqG|u2o)Qh%iEb>84bhgyU+DH56fBAL(-y?v=zd5n zcyZ5Isiq*-5^6kNG8hkXkpF1U*fy@kK#l5-;j*X)gy$A$T(8(-O+j4?+YMSsG2#b% z$49(B0zlbbIO(|b4S{TGnlS^$qh1ED)V1p+ePT=5t7T$&(1%gPWYFyc^@CnEP_uY7 z9#lNuCc{@)b;*vxJ80j&M-4ZZ?ir{Lw(g8GE^jVv=pP$Xz}62;9&EiY%d}3StQO}C zi~Ul-t{#{?*mAUyA}599$6I0p3fL_JlLuSN6cSCa6&|P$w(bO>>GzT-@sMDvlzN~V zxFWC9ZD8oCQIDF~xI&)*Ns@Tp;f0i6HXmf^artpdIg8cmbwMVc=DG7BMb{5CI8mkD z5BZjC9;eR($qaGAGq2YRIUc=En@{j~QS(Jxa&eZZI;IfPR9elD&d6eQ+w5jYX=%Y( z4b3E!jMP~QX%=> zZUC zUN=Z#W`@ckO&=r&giNB4HP#Kev05yJgozi`tY?bSwCy9=*oxA$ZIu#5J+L%(d7;M* zNusQfzRU$F$$Zc-?}R*ukTnXDTiLzhoU!YswJ_OSIAtOv#WI^An=oW;bK8A(k03xA zGrJR#cfqj4`vRByAZ-?;!?QYlHk;iK$>{uENKXujNBuDJIDcRlaW6OT3C5JVX-Kt( z^EIYx8jlSksiL+#8td8G3^`=WArEQcGfO%b25_=uNWbK>TObh@WM&gAUIDURI?W!R z-HqIZkS$qCMVxxONXl+yo`92zrWq?;)?UcXoJvb|dD+s)PR+}fx?>*r%JNj~nR8}$ z&g{;aozdj*|E1YYKo{4p%VIwtNKV`vo|?~SE6v>01iE-nEZL{`7xu(9%OGWjFnR`Txy(SP^Ftc(>6crSJVoWq>>Ud#j_u@Af#yA&`jcDxrWW?n{z;T`*_ z4Rw4!W``}QtKN^<*b@WMgYU;Kto|JWlW>(4?nH#Eu7#7Y;i|rHm@r&522MGJt6qlh z@8POXVV^o&6@h($aMcN1{_d&^;6y#%^~}By;wW--x*h&SE)KQFzsSk$4*1vqWA8iQ zq$;w#_g*r0K*9`}nE_EzWau0uClzFdAVCR2M`XyLtSCBw1P4ho-90rjh+x2gOK{a* zGpOs+HGw$`nAQNo>Y7&J`&ZTNd+Xl5-7TN*d++!Ce(b(C+tjU7b?VePr_MQbs)}X5 zwxqvUE?z78i{+-Y#;>;JY-=f>7P25u0sXbk%Z@NNRu2*HB`t?GrUA=}v*CoL;Bk5(4wCA6C| zsXY0}r&aAFi>fQqs*;;NhZiC=O6Ggx7b`W!iu~+xIl26cs*eqo_w~Fbcn7q3;`Sz!}OOyvpZS%9oJMo%LwVg~GY-=er*p|ze*kH@As_vBj zK_339YO(T?sVRDNxs{Gidk+0PZ@NYQ^II1DU5B8*IQ7Z#udD8^e+UJn|L~Pv@;(tN zaTM)31b~xC51>xIy1?x$E(UEaYodpe)bSYM$QLvzmeRW>QFOfT+D4vfPAI(8Cxyk5)&po~oVp=z$N zdZ5>aOO-3rYu@-{)pA8>n9bsuI^oo#$pS_gAajV=G2o?r*yzwCn%?b0w%on`YUN$wgGseaAiHT?=%k}!QIS{IBoG#;$b!+ zCQ{T_S2ECV;xXS&_yj%@kNL{IRcJLR;xj_ySk>B^CUUpF=Ez8=zUkpGON7b%v9abo;AKwZ=7CzRO~8NOID9YJ=ld|WBi3k9;IG{91xx>26B(kfE*u-rNs%B#Ld zQda0y=|a?vT+qC_o3d6YWz)N?UekK0O7bEYs##xiFL1s1faVmgGK={(Sv>5!iK@kd=J)TA|z zwiqZo(s_u3TB@H-X`ozUj_W1kp{|zS?E@n88Wr* z9{MUBgt=56(a#{q!}?{E;|uXglVf)LSdOT`su%~2z^WLR^)rj{h5gdS*b-GP#+ILw z_t~m(2zf2-QV>?E5IbvJRa&5)oe-K}l<6iE2$WIfxwNBj5cv*Hci|wi-h6R-^C`|? zT>DoJE4WlTY`1h+&bBj4o>`Ljj6N=rZC})j1-5+#^h~jBH@%1M={=;dV|@E@7VJ_d znFTr#Fm9V9Ka2b==U$<+lFXek_C1-Uv+{IUHcJIU@A@o}4@Oke4H+@G={|DWk6WtNY|gXmY?7O9mv~97t^$y zoIrnbSpEu*w0a`>nbFn1#y~lSR%JNx$Bx?`G4j(_6dBcbGMP1B;FHczH%_XaEj1*^ zCxJ0kcB(hP0IRaow`uJ3MQWDBO+H~H0_QWU#`05g+m!0ga$Zl`r|Rf)a=P^rM$USu z!VZxtLS51_SlyMdGo%+8>x*YdDI`5ZYKFX5nQQ^1o*tz@^z^6&YV(ayWpd8}q*uoc z-x}JdHi$6OThrMrxhGP6P|B;+TT?lyN-yD@R5^g39TlpYIVpAMTp;rA;iP-WzDPkn zag^tj;{N$~_ zt=}%?y&<&6dEx`Tgb_x1gA~rK{!tNXn(6Y0N_U}O0=lOT<9{!-II2PXEOOq$>Y>W7 zLMaW{$lniOC-N1sIt#-zAE@yy#R!x*bB=;HqR+m%`j$MQw&)EP8)3@op`LIiUw|?X z<}r)GFt<<`olbfpUBlKJ=KHW?!50loEjsf{tA{qFcv$O*f%v59h~%`z)pkjqrUEY} z(#YydOu$@8NW;j$>#FmGCzuBgOt+YfPCy70fp9@@P_JHMV6m5K7OB{*FSheb#p22UZEAvqI>ib&Z75{yOvh3w5a(^ zdd)-2s^=*}o96jHsLsEDA!p_fmsj5)=e@7DsPY?2XZu7i=IZ4Afuv|v^^3;(Yz_Oj zscJLYBp9I^V#{m0kdJPx?m}K!UESOW$|5(71{oxwOn!f0vgW4hB1sX@G7spm#egV7 z=a_>p4eK8}EL<`u#o8>@p$Emrnzy^-lg8U*>30veCI>IhZ%!UxzPU%u@^}+++1lzA z@Y6yj*q*v3+6I|Dgzke3DGxKti1xUM4#N=o2q}ydxy?W%6b4db|WuN z#yR|hdNF7GcLtGv)m6_>g!*QVJXb|p=#887LV+-q!*69OmY&$f6>x{Pz>302uHg?4 zZ8})T(PV&0_@p!7jxE)0TrtW(Rc7mKgmsXEBOY!l4L0){O2jj})(A4o%lgyJTN&DN7pH+pG(xK~-;}{-=DUbj5R;vMH}f?;S$$uI zh};V&s~=DvrxPi-9&CT9;1Ru4=cL4!v02t%lI2p&FDtL>P~7U>UoVzW-WN(?f2dY( z(M4_Bl9%eoBJ%5lxep>jn=I4CDy0Op_@eS|gBX#OAA}y5wS8;j*v-lbp;YhpnkKPw z`G>*e(45I0v0IhaLkuKQ5$>wQmNuh3rPdnUQqU-7CkK^S^E?5Alo>_O3wJlR zR7N{~Ixkjf=-4#Y>(a-XgtK?Eqzn*RV}{_8Gh#!Pi-l5Z2*R@K*aBUMwM|{zklqD1 z#0C25)2=D}6{&-~`jOBFL-9tvS#5nu|d~~U!X~{Wl zVoRFHZwz6<%R-BoY-x=;2M30v&XMi8Y2^j-E9i3W%@?$Nlr~uIXE)H{oEVQmK7jF> z79nL9MM{<5ZG&U|24p){#&(lYwiqmz zSSxZx&)CyN6~r1pZ|LAun~> zwodEw8#1AA+s)cPf0Bm|&1@k2Nj>M=1xG9e9bE{LV4CEnL(M!X^NOObR!*Acs5hIV zOy|+8Cg~$>lK6QvOMXr!ZLtTWyv1~WQkDkW;9Pg2(fP_Uy_j45i^%|YY#2FucdU^j zz!0{XvE`064asfJSa&66gyXyTi%Az(ENIcyZdc5s++_qQL(~Rcjl}bvx98QkTa1 zDMEd&twxkVt+cpE=Nua6q6d~_fP7sR`*S+ThLPx@s|83i+Bz7A#S>$Mn|jI=R@5bOP=!_1 z%v2+=s%9>^$jk(TFZ%CMGs_HWMjukOIHV!U1|wRcu35{+r0JTg#>Xzqmv>&2S=X#l z$-UzugRZ#;T~b{Wrwy8Q&037tY&%s_r2dGmxlx#RQP=2XIBX=t$C=6S0Ve}jIEEwQ z$u3vNzHUgq>K1F3JnQP%cMate7)&LGmJSZ`ANkWY5r7AwpX096h3^KG#{%4{QKnRF@Hur<~- zLq8S9+Dt(;qb;YjO%pQu%!O?Y&|9~~#wb-rK-$fS+ha~cMK+xKZ-@1Dhp{#{uP#mY zxg)kpGJu$r*cy$HI+0l3T-jZ*p;F#sdb6UEenv0mX60jK?A@_#icp>E=x(IjJuoKU zG}h+0Jw~?Q1EPr#Ce+qhpvGdbmikp&WMbs_yqoDEEhdlbJpZqhpS7D(ex~SHYuX?1 zNz=5+b~|D{CAnaj!J=z5%mA&b+7lO>RqYQK|M#fc+Z&|m7&<0-sEU?q)(tYEC92x~ z_=GleRl6(pMq@cJEVHWJp;G>eVFpz@30+cEdl7BWtZMrYOINjhC{lk!)!r$vfHfHs zMlw`qCc_3!hLmlW-2GVW?0WJZ3^9{Z{a)>TCx@&^PJAj>TTgy^SY|`+q#30AnHU1t zuMNv=$tmiE2|GCfQvtypoY*oMX6CF77L;CVqV%b2)FT?HvuV_~pO58BO2gs$yfWQs z^u0Q&BNF74hpL4F!S{OaAF(w`v8hQGku2)0m+AnTq@TmC4M`q*F*ZQTD-o*l4Bsg) z$A&8&y_jpN5!=9T(<1FE`auc z%vL@eO~*vvh^=ZWKRrCNjv1s<`KjRs9rHN4q&nsv+Mrp-Y{gK`=G?6msXwA)dJEHS z(lI0DAB+_EE;9v=aSCYaW$fYDPxYl%BycE}Wfvl*c7Dbsj2$YH`@e|Y&_Ftqf>~d( zr0*o$VTOI~NbHOHINzhgX558%P=hs?ae0?8>dQZ+aoI5o(jPIA{?wJuT8;Kx=~!}T zviZMb^X0thAdx!Jswr~+kMQQ^>cw2Zr;`Cc#hzA#>U>+G*UzyRm1V}-YLtKYFR@rX z0FY(*U5X8mCX?g^4POlxz9q5tKe6d@-e$dZ6~*Ecu+8q&i#dv$$?g-ee_2$2^7}|3Oxo+k^Kmb${*7R(qFnh_D4@F(@)wtof`)Osp(gCa5sEZICuqtVr?r1- z7~hm9w5yW!sYdbPN^2twYdzdJewMlQuH@myagTDAu{w_wpo@!|#77%IOmlufC8aQO zz8nYzIw{ENrg8Oh3wG5(H+jSe!Hln($90{)HS-fz>r3XarW*gt8Il zHQ~Y$hBd(&Q?@2pe$v*2gXT3s9aF+MrfMTv;=-_jk4ak?PMi^6+gRQ+BJ;xVrAqIe zBMb|}4s=Nu20|M&FAN(nUh~4RmLl~>7KX#Z#G4idl?&9tJ>F7IuIL^wk>#$XneEUK z8nj_a_z$PM{6!j*eQZJW4@^Wq^(CR3ipE=)uqB~5JA+Pc#Lj?_P8-N?%J@=!#@UYW zq>}hG$`wK>R7+p7^!aC-kTa@CR32Z-H=#v9lk^8Pbo91anx4ZJzeLVktT(P^mEY&U zqmj$>Vyf}g+e}fJKN*q^wcHsWpv0`8uz%9Y74N19Fnm2@+ue5=LDcn(Zg)4M0I5}@ zEjezBwtVYMMIY?sqiIZMefKiCarz(#fHiz8iq2_u$@1? zQBpn?T4mGr<^}Ps$~QtOo3?|i?`cB5`83j&eAqiaNB*>wl=g{VnhyPPpZF|AD$}Pc z1>Klb_KgptfN%80;v{x!LO5c9FpKP3G9&5PKfWZxzS5KZ<2y4XVk{dFzfjJj$b2V_arBsL+Kvc|UH|6#zKv+J?o4DmNN|IO`^k zKJBI*ZF~FvZU#6yL&D*R)U|fP*gzk!dj;9sVdW@k3u##vA7gn;By~-k0LqSubnUt% zmL1*gs4+Cp_W(nvR(cd|~-h>@I_xBMryPzb+$t4&UFQS^be9>c#ZE_gR4; zIrh=o0tK(-e)Jbm;CC|=RpA0&&Su6MoEe9ZUBURw0_#t`Lh+<>h2AbX9*UQ>nWPucUyP@R zj3gVU?CzADAC6C!m05ZXvaBU3>pX-OuruxoM@4LdblJSVfZuqqWF)`w;0B=q^f`na zyz+8|9OziX?>i{e+iRBIo_g)$TUW-PQEG*TMmrK+$#XN}7b#nXQZ%pHMpu-_-FW;w zULHR?Pkov&ej}vE+ zV~3|Zm6wH5`{6{H^mmdsC+;%WR^NR3IKB4IbK)1|32mn#+ma)@FE_I6^39g>;`hsn zG)iM70of)(DMhv(s_}C?rur(n9ZmI{(P}BvtT(BeAMZ^zmp$3s++9~P@8o)$($fSk zN#u&F<8R~%ou!SoH6QJ7xkqcf_d#G#b#@I58W>g?I#Vps=QzdJ?J=;lyBnqmL!ffd zNoS(29Mg$HjjgYfHpy47iQ_@BnL@G7EenNG#w{~RpX=i1m}{%#UzuLJ(~|h@=GrPJ z5>xGZK!Gg#qH!m4eYN#_P4%UjWXuimad`sfe0I*%$J{M#%wTBHt%9(dA@+@88d7+R zSqDAa0+hc)K6YvRT}eJLik^bLkR0^4C>E%EUK$wLvpimyem{i87YYVVeLu| zZhf@7(p4y>ydrlPP4@XKFUu3E^9d4^=_o!5LudTu;AS_)-<9PHM)Mmu^l^_#hrr!( zd%}f!_xe!iFSZCwO@HnE^3jHH(Rd245}@T4B8FBj#V0ULIqovJt9x?rx_Ik)@&XlF zjTg-ops{H5mM4uihl(y8%|j>RSxLjVweE3gZh4XACv7~}@XNJ-ZBo6a$a2E9nnU@i zyM@o5XLC|7o0w&jesL69>{};swlvkOOFmE}@ff zrsXGXBpZQ=me*`PL?IQB1DoSGxgoDQqZNC4f<1WMY784dDojUT*|?$DXY=_3o~SK? z=QUhDS1{;_;7ZD1*zRyf=q-@^nT?#a=rbE~$rz^7I_X)_y6n{Q8S6nY)8879y3>CT zRyW59XIhQ&4&L2W9IhfcXKTDfl5ZNr;(3-3_ZlHc>)Ye^$+crx2v2ym zK_}$y6o44Pljc+W`;ZnVs#^+Y?k5?Dd6|ir7i3LVwxZ_d6g8Q!ew~FypWvhWC&f%) z(a-3=MHYS4K-HH_R6S)DO{R#-q%)&X%N;K@pNwjEsj89GOxDNli$5p1$ez1#8Ox}z zRt&aexaWCyb`D!XuJ6CE4;gTO{3zZU0whl)vxI!b1bNqA;@hQh6bOtrcugBic6~Di zB(keqa;fjLQ<5hV>8s*n=>KXae;c!521_G{# z*Wq$RJ-z@g+Qlu!xDVGE#ihWEPYbixA{$AfgLDri>KIFU9_GWk>(bQ52|Lz!JE&)T zq-d>?o|Ptgo-&tykRoReE`2ABR&R1zX-X7a+K#6P%ItK!N^BAMn`$`IwPM;+bAH@&R^B0W?Q@&>GikxI$0i@Sp|P*Y6yJoqixKQ zTaC@Ehkr>y85sNPG{%0@I1#UzCgRi?`}5RH{2s)OIv9p^<;2xtbw_wjx}G=GK}nd zPB#)R1kR$a$a+x9Vp%Jd)PAYSm6cwJGJzbG7?t_omY<|1f6$m>6(V)W}aXX`K zk0a=Et0rvDT8urrj?2uR=c{8Y8fRe7PUFnFw;@WXk*}_0^?>vr;?J`+qUPYwF=+%F z$qA}vuc&+d;uDz6=9-iFp8 zhG-B5=qN|FFpr@N4UZ98H$m$ z>%P}SdOXedm3%l0=|`!!eViiw&bQ(|N&YSi=`S~dkSpGa@0RP0&rJG|24Num2N)JI zFXZRPnPUfgF$Lzd3qh*MfS1U;9AuouZY?3lid!}ym%ktHLSCJCePgo!iy;lj*!Sa3 z#Wr3S5E?nugEXb{wfWMjjQl+__h(_|O6Ah=hDjSv`?H?3i|`3LNj--1=7(_dqbjf( zZV3s%%*h`)-b}KK#{W(yzd#_Q9t0un53=+kcGF~T?%#88@TaMe7L-8 zd}dLG)M#6-HXvt zwo9bZa2;rvi|sOyZ|i4_e9I={qQ-g?3^V_y2^nYpw-otUr0wMA@vmjMlM1a)eR~0# zO?`t2=BfYf_fCC|m2qeGm2ubv^U8Q3a0BBSJdz@hElhW{U7@fSZ>{*e{t%v1wFezO zhu!bDxyb%{t163gRPqtFFa{@NUKk%zCwJ-u!@@Xug4u4vfyIBv3k@fz2UD8zjXW0N zIc4K*x7xX8ydfHP4(WX?o^N$oV09YdHgLjeDJb;eZun{}NoL z{PDlyzsQeI$h=Da-3&JRd#LJ{CS>$5N?%GrFsh}_4BR!rY{P9xr|Mc0RZo4POkG{J zZ8TH2)}of2`eVGSr2OeJeGX0f`)y%%)M@7W+qywA?`I~v?3T*TmlpCb~tJnMJqlWnANkL2_&TOyjdTX=HXDSDNWY_B*u`$XI$DRcC4Q!u>rU+JLY#!taB+Mc*D9JX#-PeS6y!~+GE zk$v){lt?Hw0xE1PC#DzZt5|ZMoWSPZo%%P1x3IR?S8v!6!7(Y-;d~uNZ;woCkf2Go z%oJm{PVO`E$CDJwnm-=HC&nL4w?EY|aaKe5JtKp>EkH8{c_xiP92ju9g)|_2$#qx|i46vNXGUc|xh03S+D9z)Siti9gM;?5Ey$V{ zi2^ddMPfo;m&-K)9w}V+e6C(h_iWUZuP&D}>xNzT+)YRH0*lU6MA^N$eL14%T7=C@ z`&hy9y||sN5@)oROE1@VJcT|7Si#Ymt|09C+$mXzbH4>_7VcZpGf|y=yQ@?t$6r`e zLMD|YmMhDQq$?}9K`+pGI(bR2#HW(7LH{OXAP}LHZGdke-`EoqjkO(#y~@2pMV8=! zEXu|t;7lx*Hjww7iC6Q44$Rx2rH`w05E0}mUo6pi`xZA7Lwf0${QBhv4ZWWtVl9C$ z_~zwi75y?;j~a!dinhj*?PFSg(j@SGGO*9id@^W2 zqBeuJ`*uL$Q>AdCCL3(yvY?}0Ak5^zL5YU-mGkv)W^MP0N@o$Adop5)MnDbCFUg)O z_Gw35=Y6!In>=iyK=z?cX`j|qAB;~r)yc()W{MnCfmNzc6`&c_FPUhj`rwHMcg7N3 zwr6Qg8ZvSmY8DB|q7^4H~Q8#6(;2 z@`OawdS0iK%%7a-LY}%k(U@#qk~rsgRLqy}nwZ(R>!x1Eb2~?+f=sw0F_L_7d19c@ zeb-dag=D~;iJ93y7m|&0*W}3$Pt0r@mY6&J;x1%1WF0d;Z%-6wuTvsFH!*V{z^`@6 zWJ)zJrQ7JF;LOSQt2zodsaC2iphmO=7GQQnH=#h635|sZ8E)Z9TTf9)!+Wi#ao`CS`VJhO2Zr0}s}BT&3OJ zmp92A<@>=%lkcb?{SilIh}towC4@F}Sai@Nv-8(~k}Bt_;QX>PQ7ccv05bV7yh5!52VBERHEZ@wqfY?=})zklEiO#7naZv0OaaOs&q7 z8B-di*c0;m1MX5mb_;<#eEF z2aNTB#?<~QI53xHDMq0#wcJs<#SB1&S-OMMbAPDPnx0!VCLH~O`E3)CQ+CGi2JRA@$40hoOSC4pRV3PxUe{AI z!|O1b8B=rD%a^{(F=_X!V>*_aG-hcGt4Q=SwSHy_0oB^bS%q61Qhl=L<_z=yu(@w$ za9pu0;WPDZq=0I4piPeZ`KN=MRI>1`t`2^0T&bk;wz>#U2Wn03~W zDHb{_67okp4rCfR5Hk(>qQR)&AM}Rs@Uh+Q47l;aGtEEBS&QkcX`C<_b=GStVWvz; z>8x$vZ0w0^ooRZ9kS2#4Qpj+HV}CKA(i!#+HX$dV`Cc4)^VB{Ro1=4z9uo% zQu%zScD0?usoLt%%-s5k8Gvc4f9Nb`l_*pCRSJqys*taWl#u)WYt0B@1ALuE$UW`% z_GoINO%E91l7XVrPg|F>^4I7cT;WTwW4)PZz~Wm_43P_b!y1>@@q zZh%NVC|KH+Vfupds|k!5ArcUC*tkw>Z9AW#Ds1a~F`lAq8>K5*^E z^ORGR>Bfd@=|rQA(QS^IZZrANjb@0?=Jog@cxgW3aJY~=0C&O}3b~>VcQg|8V+mj) zowF7b>D81heaPOuD=ahMN?WM3SwS(=lQE=a8gZJE0Sgn2^7JIwnINNJkX(r&{2}RX zs-lofx}~Ix}2x(p6xjC_sDrqvaRr08pJX4tK5C6c?~*iDw9=>WyjxWOm1879UFF;MB|x=rFB$kw4_#Q_c43SyK(-c8UsVOjd;? zC(V5u82Pn3_IOkY~n^$jg+$%3vcY4nmN2NQ6K4w64gBiQ>UiD2Q4AG7dsMD6SQ6fd*zM&oIj zS#hQrf`vEQP0P$(sheTH2c7gKPd=W;UGEzS`HqQ@r>=TZ7YYA9)$`|!s%PXhv+5Z! z&8T`61skF!If8?VECJ)a4s>_j)J@e|#q`syL!AFb-MM;V3s z>UQ~kuO#kMngsQ3_3iQx17z2$iN0o})J{4IFd9-*V`s$k44u$J`9kKz>l*85J*rtX zg6$$i#!6mekummEz@VV8c{oJrPZ6-*J?w)|Z1<2Ic--)M;tqL|3aoA(UM2vu&BGx< zws|Nxdwq!XW}?urV{45g+p)F$r0pYpO18aTmrta(5>IE?v3=*QM76R`peg2|tYD2^ zpc5te&fAGal2WICGw0QOqf%J_C+yhzd+#PD%F4Y0B;zu6kbjR*%69GVC0~Dl>9?-^ zOnU8)KTOQZQ2WjF+VaPVA?DhbDPN>ltamVh*ZqWYhVs^f377J-P^zL_awt)kUYiY2 z328h>)Y?lACn9-5+i5ulN7E^(X7LKN)u%?A@PDV2UduzV9%SjNRo!Gq$iTk6C^pvY zdp`in#tSy>%fe2{uDNI&QIVR8pBybq}6NAv(`b3X^JfI*JPk|>Z4)iA2?a@ zL*fBho*2$-VRcZcI)Ou0Bp>=Yacw<$W;nBnb&eV2?%%N6EMFJS>?^r75Q7CjHf*-w z`-M{$Jd4H(iisXG=$4&Q0}Z#Rr;%%C8o74xK^qNtN7(Me>Eck(7WBL9E~hW-_JzDo zm)+^|_z~pi27Jz1%z*!|aApI3m`ampF*||*zYi2J8t^+bny_%`J(TtSNS?u9wPQ+5 zFiYkzdt?e0vsJS7;yxT3?q&>qvyJw$tc!5H}P1t`+Ag0(p4OvQVI#45VG#npw(g z7)DAqsO4Ams$QVi)l}}>g;J(o0%>Y!}xITBn&&zopBeaONm$sfQgl3ru1H?% zubI|SDyLvswxv=JFKA$6#?@@;AYDtrtoNlZSFiUSkHiuoNOx(}EaiPsLD+E-$ikUU zD9{;+d@$ddPWPqJ>25w!Z}Px`nnn`If03M{>=h>Rkd2&`%G`MZxEPm!yR&1LgUuf$ zRZVdXl*N1=O~dnR(|qn&RI^Hw8%@uw-S?>^u0Ne?_vAy@)Et%McGEL!>(s^N8c4_M zYRV+F;&u%5^HH(1W2bQx_v?H-+Re5782xqP0K zEUoEJj(%Bljxq=3DVY}L6PJad72L65+~XTJJzduc*kxn8!sRtrW-uu0me@@VVZT>dn<-34X)I|m})&f-K<)_#Iy;j)fzp1KuD*9PIPT?kQ<4% zmo^Z|#}QIr{Ba8inT~rp@Ci+%jMwD38)|$_q_GT~KTlo!+sY!#)CfhrS{8Rv)z;9| z2>L)R^aK9YiP$q&P~@GL9Q*i`o%x*~bUZ8gu=lO7VtxPR`NV#`F9sb<(u?x^Wg54T!U zma=>yTu+#oslgib*%o~c%7VA|`z12rS1S)|Kfp@39*pFw-K)>~10VtR{3W1Bo!b3|InVbz$#asiepuQ@Z! z3>2O5-=nGJ7$q8zeIMyFDwk)R(UY7Kn#TJ2 z*_z??q%IUZi^lp`?Yj^SgC8oAk33)Vcs*Ps4X`Y>^H*lDBQMq1>Pdqr7{9*DlH@;V zV4|LqJK{o0dTzf_xtYaITG0Df6TMGeN4=vFoav};qNHi`)z((2F(nK;TPZD~0~}*{ zw6dXkZ-KEf21<`sN~;*C)eWenP18Ziyhn(KT<}KCJ$W^B&N+XH$0@hy#lmsQnsO$S z=Hryj(|f@97;^MDrSt$p&hj*63oB55n(~vkYFajuo~E#Na_kx65e`%4TY>Q&>0wIg zHP)l$LDOCqplqUwjkHx&n>JD2#$@!0cnSIDgH~8-xo9FS1jZ}Ur+Hi z-Xx5K;WUS# z=HgV9T?BBxx!Cep%?3$1CO|S%=H=rx{gj`CQf6o!o0*LMtEP#RC)7{l%s_fq>Ta>n zxsE%z;(KPE?CJSX4>I+QJG#k5vkd&$X;wylY>!VGKPI30cTGr=eJZrdkZu8*F=Urn zW`=A}j{k@iROLr&B$kQ z2F*}8RG+ky*#mg=2DRwS=)MApjkXR|T~g`P2kENe`5UqleSC;t@erO{+y z8)9uQ9kFPhi95fFLJBZYO9SD!1t@pia7N&jy!rZ=M1yIuUMv_)^JiNcO#im%LdA|5 zOzRkSmIl+0R-oKq+TVs;-%7fb!loHa|FHrS45q(irbpi<-2M>fg|m)WqRkY^>p^Hh zK5*Y7Bc+#Uvzo{F0;Q3)aqt{IY08+)KA+S{pK(}K6(1I0nJRu|w%MG2juShji>2NR=4Jx>u3Hdx{$OO+5sP_zxE=>>WZ$#NH& zBP;XuZ)vuH${hkYw++Hx@{FWZ2$0M+80#k^l+{8h3v*PEU;N~6>9yIrnzy9azOgs? zG*4(d-Hu2{OTD7#yFR2uQuYXKny!HgS%I<$i7-Z;M5IN3#_w#+o_EEw-Q-v17)+2C zX;;=<|2#fvT%VjjfE`lw8Q<@pV>UsaryQi2Al67S6U6e9#`cSvq^-Sd zIBn+|hLb-x<8WHy6WY*BkoiN&olRut+{`9Og-UDNT!RVH6J5dtY1^JQXf{Dw&P|V! zG^a@Y5fkJZVbZP1Fx^OoaAq+6MBC7-A+923i9T#nsx-x{s#jS3i!-EUoTWumzStRCW3cQB zD|sGcW=q2%-vX8!4o7B?_wriJ(|A-g96IR5g5l6=o~7Z?&Y}w@a}|VLTvfu+v$PyK zSiy43;rUr)c2l|EJj;u#3a#LD(?KrFLXyE2ux!?gj09Hoqc&Z5_WQQK(j}N_)mM+) z*-f53&!C3NDcP*G>U4a)Vj`CGjH>*78k)ydG?PFR=>aEK0=uU3_1O@yYlOExjMyE| zj$IDEh+0vT;pv-iCZ`)Xfelo0?p;axlU+8_Jrk;zq@n6YiI8U@&@CGw?^|t6$R%kA zE;b-Iy%Gpswj9K)&Opo!X&5g4zrt|z&DI$1O~ddB1BT7l0mF9|BJA~61`Jxz=&yCQD414??F=+xZ}R|uldObQjR-sir|5pK; z>G|6hnDsnaz=d25;8|nItY^zl+Qi*W4Gd!dkB#SZ<9I$1Ffs-34)XD6*7HAaCo?57 z?@ofOzsq7xi1P6EeA53jQbHcMlN6Bm?}Pq15Mp_2;? zKEbabB=rgYNy%jP2@YZw&1&XDO6ou26WlBCvi0P878;nq z72&{wnNt^r<}Qd77tdHYmHl(Z!i85ynmX~knXefCq0{R0I~?@4`k%22P{D0;cx|*G zHSejf_+M7R>34cq87kPFHa}}kt;8zefhs5eH?4syCU|vT#A^6#epjjqr_FBnk$JD} zX-m$FJ=Khq>?FhJwxc{1UPSuc9mW37xY5#oc;=VCBq6 zB0ypJNwXh1Dp(%W0L4DOI$8!OidBjkTVt>+KyiS>T4sWDONXVIARpx&60jET)c#U0 z)Ji=$_s-#>Vhsk%`|pUY3!G^Q>TbWMbswWNst5*;SU2i4rR~ z-Y2_KyYp4d%CMxxCF!uF*qw;v>thxs@cO^&W@>5ohq}pqt}?9r{;M*s{2qK_D?iJH z`{+5cK^~_9t5)h50hn2-{jM@wsh+D0R;qFGQ}!{nQVXm@_dp=rXVQ zx!8wKH74)>1KAFHZh&K&5D-2O6BGR} z^a6c6$>IZ~sjU2@e=~b>*Qf&!z>_$+{iCEbyjmYMbK;(Tlk`)X3#H77Ye*))MHZ*m zmfyxsOL1E5Y+_(_tx&) zKz!2VB01=N5|iX}s=I47}PP7uM)8@6Ga)#%=4U_7%Oik@7}u zAlqC|WgEyEJ`l}stACLCZ3C9As!wVUkwP-+$(lxF9{sgH6e}UKKO+S-ZR2gpuZPGP zp%|DGTYdvG>)xvk9^Q6PoO*cG zl%Qr0Zw+SJtWs7}?h=;%Q@;FmgTUx%3~*3m0Cr5{L)w`&E5FA%AhqE`)_z5b$unOe z@uawz*xw)p4Vt>0HaD@qu%a#5yK8f6a_lS8m<%|ExjVRJa|g2PJN$FcH`+fp{;feh zkIhb&ew`}%?Hkl6I+FV5OJC!k4^%u`K`x=PBQIV~#4 z(IezSa`O3_2IRYMNgMLw-P_y$zahhdg*SI4w|%BTfK$`0x(<9E?;C`&_*x%oeNq~_L1P;Qa+Nj4V_Jk%qAbJI437dwUzZ1<aPEtIlN3HG*4 z(M4@9l@!voQSIamaNV=OB_C^Cd#{uZcyZmXX-Z!Uz$T<;*^NVG<s$Ya#^8Eo%FcQN3kS<>^5b(QfA*T&@&4v8lkb{h#b2vXaZ}#15r9yw$ z77E*3E>AS*a^YHwU^p7Yt<~;OB;fSBNS7cQ-P(BfJ5q6u{sW|cLG8$#T}#)kwvi7D zYLz0dD-;Mh{kZZjWjc$0gqpmn-D=MVt(4Ll8u5h#z7SqU#x3S9Zv=OkyB#2?+vRsU+_n&rO6yWg=EIByJW*T3;YQHh z6%2YJL7xY&+dG_KQX9d*3X;2btX?BkWS<#lS9CmV)a6r4M-CY}VyZVgONNZKa}dte zb;|k0#C`j^HibDx*2S|Lhm$94YFHTYd2AtHAn0;LT@ic0?+J&)5!}rf_5{5FM{@p! zcY`nOE^t=Z=68T+U15LJ=L5Kyq~By4$3ppdUkbM59p`7{q4-W7};W zf7tE9YzKojGC#Ur6|bT|_HM}&-rBK+*?T3s&#ASOX};Psid>G6*B9`4?H+H)74n9C z(P#j-SNq*g2QIGh5eP$S9v$JR+evjwz=a!Z?9l*T%CS2^wj!t}9FTO{gpxX9lA>)Iqo{d{`?`YUv`4FUNQF5%m)_oGFN)^q zmuZUK*Q{$y<_xbrr^Hd>5M<3Aae@aT5wFMXarq%Uk+44;^aQ*C48R|BB&$5D=RlcL zJ>U+79N0N>d7XY=)ZxV(x}sia`DmDrZR5MOH%k@S=E&``8zm3poO|NH7w`|6y=}fIGRT|7u8?6L+tBAb=qsG&<(h zXA9#IcQ4q`7VtQ5_at4&_BX&n))^#;*l-t<&F6Kw-Ql3a=Jw)JRgc{s^xKm2eqMb< zD$dbqm^A6TX-v*e*%EeN-%ZVnu$tlqC?Dp_6UG(sZlBX`ciVkYpEvCC!tvbKcXxhr zxBKqN^*g(xwx}J;gu{9ISKhl)1sg=Y6f-4I1D-n#K%4Y3EJ z&@5qp&|~vs1q?&=Y_EMn%Gv7y_iB4lIBSPsbgC)}yKOqV$nWq#$Kkmhn-{myV)M}l z+4l$RSdE=-PlykK*%gHjdm!MAxZS`I(&L7u06POKvI7tH*l|Q`(xw8s7DEdJ-QGwf z2#tuDa7FNH4T-O!GJ76v^6qhX&3^>4YjzAQwmBi9I7YfAT0DlFb+q@1aegN29K;7wz z1f5YI!34EY7qc9bWE3)YRo2ze@3WE_mYT|de zBYp>H2}Xt@cG#n#02aNdol>blwH9-99U^O|ZW@uZYy0)J{?5)Q5DYk@)F^QWA_0#R z_pEuNZm$;_GkLtQZeIODH;@l`?3iSC7`LN)19p$g8Nf~HktnnYIadD`jWfg1kj>@= zXT!pY1RQ>Q5dU?AogtUo8NdZ~8xFTi&b#LBd!)|U`gN0Smw#d}&fc%nM$If6X*Xlj zxkWJUT)}`JnhWNXiy9bCSin)glP+C;yJ}bXBe>E%g5}yB#kv=yD?-2qRR(3@aQSdO zAr%}|#)1(a1T2UP-=Q2mKCFq+klO(&K#_)>NzB`mP%7EG^^;}ZI(uP`UaKyIaWo)s zcWW|pLv5kW?e~^Ayfd!S%tjk5j7TUL!J->=1^f{x=m4&=wgvGhPSEB_9(r&c7|lx! zD6Dy5=nj|DgZj`LF1Od=^+WC0sZj!p@x1laV$3>8L6g{I<;tMjR69G_qD;uPudOR6 z&M_)jDRdVDO?g<39U-h;p^y!e1GNqX831+;R|qekI6}$!BW{6`#Dv*=VGmaA0DKuQ zR6j(_4vP{#X&AR(ZmcRu7XNhdzP4xY`umf#J;4?UX;C8CwI%H{iCjc-1&8B)DqD#M zOZ5Y_ZHs~dkkkea^Efa~5dLt;>wtv}sRBN3Ed&6A*dFypU49R)lMiDZvj;*xCl)|F z)B(fEgC{|v>kE>$%GH%pg)i$|1;R$@$-$gHW9=N2b3)dL3(i?_j*-FEho}`&d)Eo+ zvcaW-2KB;9_8`m3i)A|MaU_d_tLemI$&G^fLOw^xWpiV_h}iIK2Gp!87;)l;J?cuc z<*YL_rXOBI)N4b^l`RNjbqh}Y9j$<+C zeb*+X&P&<1=CuP-_9y-gU2)91$0-~~$tU{40{5)qc>C{U&R z8nmmP89X+75OD?A&31%wya+D@f+%w0LQ)$!_;77oE^0;D`?S;0hrKX+pJbr>ZU>b# zTM;~czsKS9g`gv#nLMy$Z9y1TLAacdc-6MBdA%?g9jFAi5C=!#IZLeFup2%dS3T{TsDs zHuO3@?h+U2{6KBHqEI+shfD18As_{mgFy$PVHhS{(Fk}-6S7J53tboq^dq>3hHSu^ zbSXd-3hV~F2}~0R*`#$?&$3QZ*eqmO`4VfrQOI%-j)p+EkmVSeDr7-w_v8KCum>hl zAnf-0eSSK?h}Z42+sU#AR~M*ZM(VVA?Owb;gU}XqI~G9tPNyCIiX#*eB@NLHzr!E! zhoQfqxZtD14**5|9%m5Zrg}g17E^EwRt>ltkE!| zqKF}Sf*uHY$O*}1)-4a4B9Ie|dJr*n27o1;P7i!?j2>~20Cam2O7khH5RHU_h%tsE zPOSHSu%`W~kZ}*nVU9Vu8&l-=1cF|eLt(Gmjvyi|jS!qo_|*vgAla11bGi8##@g(*yWK$t z^afrXfrIIH2I1VHH7}lzVv$uQZ@Ky=2UbFJWbc|3uc~#B-6JAA1VkS1cvsjA&4qw=^PgK-zl%gCQ8a39=K|Fs-=8AHRiu&OQJN91Jpx7S4O6+q) z5J3zf&Vw*FmiLew4_Diw2xn;FAodQfKZ2T|LLf|o1fBp~2EWIHC>Eb#?yVuJ1UJnW zvB7bG&4$3E#|xj%2jc<33U01(nakBT`K{qCWw64~QF1z230Jaa_s3(FzZZM=89ywk}S3~>EQOiCtCK=1lkbbXG#%O#n3$?t=QA23I zpfLNONS8yKdK6>B1xy%(VF&GjNWCAyQinYfh=e^p2NtYkRlW7lFNn=yV+pUhf^)G0 zg2f*pZv^$XTm0c_{M89<;f3Q{6)h8--hh65ocgd3T8o!U0b)h`vT z(&9*te))pNgv(|_EI1en!MumR4QCc;`g|@2>@J%-WaFXzjRSVW2|(P3?wENfL;A5t z2rhPFLn-V=n9=VMVhLE(V8+1qjYJV73%DFXYyfy6UU2Xb;^eA=+g>@kcako1;jrcC znZ*-!dp~JYWDjEB3#uvNgs%px9ugM{I_)4eLWM4eVZ$jBwR=%ceKwaDaYTnV;=;C! z8+$6)EaUp3#XojoD-ipmZp0yAzd^DPVh&+~0T4t4BI?4x_1&}_{lkd)8FBvXJ-fKq z26^k&!|4!&&FetmGwin6VH{zL%#H8|rF_tawHA9s#Z|Y=uiq)#JLcq2@7-;+sW|R$p9;ZEA$m;n75?ws!>)xr5d1#Oe=U z2jQb|5_{hWiR9?h&qS>deq)wi$-uwW+1V-v7utzEq@dp&!WbZ6*m1DKwL~-<+kpP$ zvM&!K@aXbK;iP%75F;)EuLUlq&yGC^1YUtK+3kXVv-dBx;7JFJEQcq8m^jQv8xvjx z?0g<<1Y)B?i-==~H+#oXL=xx@Z}y(O>KX>?39{jW3cyN+#TT1h2y40E7{iTp`cyZ~ zjVZCgh={l`8Bqt8JH+njTa(ZUR8zqA%IA@t!Vq+3H0Rich-tVn4kv^PJ~N^m*befzaTbqjjA>2p zo>ISa);GDi7T_Ca+2_U-0-<|5S(woj)Awa37!8524eElTTm$1f)G!qbv0lL<#PKvF zA7G}iN<|{DkwbPH2oNNJLh6IiOb{?#6ajI_7eWFqdk|IzHaw{c#~NVsl9nBJ7w}j} zk>3k96uuX73ut-?;tMbeDGYQ~$b(FDsx!H@n7w;&JzLVUca4c+J{nunXcRq&C)4eA zKVstO(haM~7x4lWY>~NnDo9}ju>|bV*b&=6U?&Xk2k0VJX$xT6&B?uOZf7CziXb># z8ygM!xDl6tO$oP@CWd$re`HxLe3v(S&palQqvHc-)tyb)VirVTAHFhTyiik+B8Uit z!~u=wL>2&EvY|UE8-J|D(hO}FffX6D<8gT8r_k+6NL17g-^byES4suW)|cuHzY~wm z;CWZ9AK0OQm|-=81qw$G!667-?K-5jlFVTYaTc;=fGVT;FYheKtvLp&)HA`}R!+CqrofyW7UOj6>O1Azb&x1wBqGn1?M zh1CjqYGGZ|!m!T)dof`1AhjZb=oDfaa0d{}u_GzMo8;T?!2lLC>qf zAOPM$hjZt0QfE6ABZsSsL@0RUE@)+#%h=QkL2jUJJYH-PlH=VGPT#NGv>hS;?0tuM z$UjHd^8@ScL2rS61Jsl-przm>JMS_Fkz?LQ5UP7!1FHIp!0Eq(uuOr!FQY|9IIo^C0 zB`?QBd5p4@gH275NcalbC>KmcMGE18W*L-VM!LgZ8uCY=2q8wq@-c%5dSTrUBBYFX z7IUr#^g#+xCwBmShaDayWVk%A{t=2rwvZ2dS|Q}Eg=vBk-NWvT;2kwKktqoO3GNd% zQ|xXhV(j(+8eBT)=~U1^N8b@Hcg}46!idEdHjj!FVi|VXXn5O;d`y=E7NDJ4qFyJ> zqX>{?gPz77^)KtNIJiRy!@~uFLV!3qgYeRkg62kS8QVD6E7TVUeQ+HZu|oa^j}C}i&wYXg_JVk$$h4r!nRG8chKfmIn@Ahu-p z!FWstX3&HR&;=^MiR8}SC)McChtkaZBT&0qj33yc~O+@Q?fxs!(cM-{>J$=Wl^wPTyvSZ{+i z7)sRJgebr{fx8924JK9~h-^S{#YW1YJpes{pc_IYZdf=p6VE|?3q%U|7F#j4iLv_w zdkdB^5{tb)JKQN`g+hzCB1j}s6SH#li;0yw#iTk%|yeg-?og z4SR_;AGDqeD;(l1$d7bjBQm+K3r&yC+Hb^8M&EzfQJAeu*!3*47(xE-*cWq_*!;p` z=Jti7erz=$6_%#N+L1Tw31b@tff_8uQEqk=W`8)5?7OcjwXK$GVvLJfc82tr1uO@} zQUX?#V^9Q^*E!^=19fgv^6f3tPUrET&f`Cw$M1KUT)fkH{QBvE(|P=-^Y}BKwK$!} ze>#s}J2-GUkNJ<2aqiZ#@2RI*oX+Ft*E{COct4%T z&o2VVl}pbqVLF}1e>#ufc!c0|9>4K$!s$Hz>^b$P^Z1QN2TtelTO5H%r5T^j<3F9p ze>#t!-4Oo2oX0<0p7Q6+51gHoe$_wOvpilvYG13nsAx@4d%-||-9WqUza4uqfwX+R zZhpZeTFM_}&}$O%dfkHscFRxG-l!YYa0vZ$RkG#!yDySjvVZJq^rt_SmG8#i@@s0| zs(VjbPTqg3&L?jfO?tjoRnlPNWsU!|mYnzHaa*J7F2~Q#VRESENN2gc9oh1Bou}by zV7zt+***JTJ;}FU9d9pPOS-&M*R}hW=_pqg&4~QD=Yq(*xeKm}m%lO-MR~JuC&{dy z?0wFK@$%=$%y;S>@{~EG%ciaQ4adzvmG)%hk>ed3UVw*U*A|e#$>VJsIq2`Mi^$e$ z(zQ+br+Bt&twJAT>^Wn0V0r}Yd~g-9y<2y-{No~W*}HX}Di+`khP6#1frX2E&Yl~N z#IG*@FAVYec=z(<_)=NEWiz9e|=q!Key3e2Y_h# z)(O>KdkL~o=FN?^s-)>!654=Q9 zZoX^;x$*tF0eMf*PmJl3VDW#fDJ^?cD8V=S5YyT~ud8OyqyK;9B9DFHoW%=!;gBU> zLBQJv0UvHOqW4nbR)(MrNBeN&MFi))aDEf#=%S?M(fiwy8$POPOe#O9TO_^q@P~DZ zeAauklMm^igY?fQ^v~z?&zJPiH}uc9ewF{LrT_SV{`r{xIZXe2M*sYi{`s2z zIf_3K^&zWKl<(Q=Q7_U@=i{H3)aTEcyo9GZeqM=Zn6J38M}fsK%U>id4%RJbo1}m$ zP4Fw#7zu=m2Gm2V$*MlRhDg$jq|4#DFV8+fYySs-7OD(cPD?5ms*J)ul|M>spVTd@ zhnC5_UvE59sz|=`N!_!J#vi^!CPG@HWD5Xj*AKkR*XSQSV2aCQ+z78Moj3M%#n_7)XOj0Jma(bzR&CH6!`5uw_*+KNFDJE?-eBa_H6kyX^u{%XRU66ym})_K zDa!^WOE1QL6)X(E>MjI}9;L^cmHqxG9gYXrPc2anGGwCGJN6^>mE#W(V-T}Pbv*+hC^if z?KI_89ddJEUzJ%>ey~XVfZE+f*c^(dqPACps6B}dLyf5|JJk|vQdFjjCEaXTumrAa z4Zf>l8LD(aBzc_`jxwRoG62&w$f;_XW>OSc&2mN=#;~x@bK+l1#Lu;h#b1E~u#Ogj zPkN=)^~yiEZ(?ouVO}gkD*rgW2zmL>ghg2X_#?&DViIpkt99Z})#Fm}&wo`E|IAl) z->)+y6d=jhHY`Hi;OLkIsnNd2iVX@gl&53ph@L2(A(b$seU!CtZOi^Z>0^uz2F$Hp z0fawH3af79^IM6~KX_I5anh@=l8=*~Kn;r@CsiTW;z#iIBjTua+`DS+)H(L263?tE z_VU~r)8Qnc9m;XA{gW!38oeTLFy$KyqZE*uV(*HZmDeNiHHc^ITqR%;R&HUX~3?TEw?2r!CeH#^*Px`P$u=ZWFHAEr4rzSogu;4<-!b$ye=2h5ET3dzXDdPyQQt9 zoZ{q&k~TI1$26mA;#wnv0taB`40=6hsSgE|FcJ!=P$!^U<^sCz6%ZZ|w)V7)lchhr z5=!_avA6O-k4#1MnU9FBKb43g40+H*)I)-P#3yaGHMWsT#A0T1NLFmXjp;{aRg+aA zSsVDMuf?r2XJ9hAUz#`}LTS%IwOm$e4(j)_wDv{0oKT{v($@&Z4>k{uMangGNcxl@ zW`GfeD45ZNssc->c-esH3t*PXsFpgwl4_D6H5h35U0JFpwqNLL48R#q+91nx<07@} zV9Rt#*}%|*WI1LU<%(;W*eD0!x|;q1wo%83T`}_B#kvo^?m?Xx$JL#%2**|I#pj1w zrpo6jGEG{}>XE6D?q4iMvYm^4lNMu2(a;%YSfm;0YoMS`UWmGJbz)yR=qDy4Xn1Jm zy7)y)OXUv+)@H7Lur6?W|kP?VS3_xh3f@RTsaR|=BtT? zz;P9Xs{-4#0)8*L?{j zNtUscLEnCv6gHlM=#QTp}QD>^PXMPpraZVsZFO_g8Y;-3{7;@9aQ=p zx|%b~GD}jfaY)!OY^UdTRc>-nW*FDhui`A>dK^K`yL>ysY7XOiW;|)mw2vF$8-nng zNwwu-OTGHOVomE2xYShLk07l~-9zVD%1Cl`io6I!Wu^5Ikg2wdFBP@@$UxhMbdz!3 zut;Mm9~4Xq4FN3|T3$C%{`rL#o6;XK#?5ZR`Z9olpiYCD%M-_k8dg$=ziJsNDU(?P z*bKNRafND!M<-FD(_%|MNtw%`Vq?IIK8rahGlsdK+fvJ0CMau6P>#i0#_Lc7^SSCv zAQ@12ikT&pO27jOp1918f6LC4ibA{5wn`VtCwgp#ZVU}TWZO2*?3U+SJF#{bA)fH zKugDCcH`9=DVFzTxmG+F*mmV0LzLe{l-O0409kGxFMfrd%|wdJB%3b{XFVvVAyW!j zi3bH|Qu_u?)fOOrg`yH>a6!CKaK7^d7bp*MUn)S8frQs``^%H!y*0G#|dV<`t?3bw=nrVqVi@&Q^J)33S8W4 zkdT3P*Fx38Pc03~s2_c5=~PDkv#0a_nGMy3kMU)tatzNK5 z3tOP^AC?XB%M_U!@gzMmF=FVEaerDuI8W@gOlQM}q+%P6Ff7uBx%qyO9Bm1Sv9wXo z(gr-o8%r-%;} z9}|AGK(Vf-byT4IXM%a4C{6eNe}isRH5uh4xhs;|%fG@dQKTqD4T_QCW5}u)DLz0% z{hdfrf)auhElNOY269_lwe6e6ubV2g0W87_r7O%|pG<58F5l1bSJRqVf0Ly?s3Ee< zY?#?ipj13h+KE?#T3ECFq)`ZMup!1w5u<(^Yb8HvI*4v>9b_1rU)3%Q`?i)6sb`{_f*C{5rvWP}=enCj?gZ73;rzBd#j(rzWURkm_aEk^jk zx?oJ;{y7Fn&q>8VWM^wf<%kicWCy1^TN~@}gy@p0(X4S#_nwz_vG$gf_xN`8k!6)H zDw#JK@(t9k)>xAat93W)E6Oi?PjJgE>>dN~nGD%QirEMXBG-q2%c+x#scC9fd0CO) z&{*IytUwN`iBy)~0OO8irRi{l3~Li*k0S%KSAhd?bb*JyqP0U!er-(GP49hyw`ir0RAB0^*%zQ-q z|BPVAtD$48V~a@-I3Zr1l^SjsJxltNiGhau{RHa;Kef@o`} z3}jv)$o%P}=L1dXBzhX!sahr0x?5H{Br**PTUd1{GaNdJN*sW>El_7zXPQK%_A{-^ zl+k=o=pevI24Kyo^=Dac$jUTU#zmkx98`-y(lk);igl+BMF>DGC?{NxgcA=tNh9&#_cgg$>bAAk=VfpwJ=cnU4w2=tN#?V^En*YBHsp>* z1T>Sun%mi>)iN8bsj@sf$viwA(VEbOr(RG7P%ly|kiJnj6gEln)k#AnAxeitM8QK+Z$IPtg{BNh# z`ipXkZ&sh6UG>E*DuArb@&=Ipa-rV9ZlO+$W5;z^gbfUD=l^K8zTqeTL9uD@c%a9o zDa>c0-mXKvaVwmL0fMA3hDBQJ_*#q|{pE(qUVn-DsIW(1vMDzaun2NPqDD|Wza|;I z)4H-)=JP8{sXcaD*B6tYOEwQBKT*kdOV)*wE|3fqN*beH#848E>}$3)5v82jK6NJZ zEoTBkDCsZ1s!0VeV=pil%UmKBEsg22-+DxrGa+|odjK7ZlQd*K!Hidzs@D2`@|I-t zQ1P6IQsb!AF3W1Nd1x4rBX8#(P^~j$V|zwtvg|ogy!11|l>!!=$;eqP=GhNDs_F3qLrK*mEr_LJnK*^&V^| z)li?t!JslMV!>ek+txD027^|5Y??{bTrO&=^74Ns8oW_lu=_>;Gxf5bsY!aW z_)KCvVM@y+_Fu5(`^$;TvHKexGmKe9MGu!auUo76)sMw%K(#=ftJa#*QUvT!F&4Ed z#(?pVX?;4;C=e0$cS1lCX9vcjIHVWF0drC8C88j4Ko=fC+y~Z$puvvBQefT()@Abh z%gtj$KBediX)Rt|^r3aBB!98oJT{yaP{6E@t@q_$mz#%%D;fqL8l;O@`tlJUd)wJH8 zFoAd$EIWIuBq);(Cd&<00LSlXRrHAZvoN>3lnBw~3E|*#P zKMPPN8-94J73#zB;m!y>3bd05wyplV0b4kz$AkPTNdx3BR^Yg2bmJrDPXk9x z#jT@S!;g2u52V5GfVQ02u2s7>Z70Le=eC{{iM|QkwuO49FfUtbQ9K1+Yol?oVs4tTX<#Eu}nUq(pHC-DIf z01m4d3nKex3@`R4BoY+tIMp^Rwix7VmEXKqre?$<7GwKC-j-y<4nQmxPXYP0mWNcR zfeOgL%JI9t=3n8pR)s&QUodcR>5BC_{0aBBeVQO5<2WLD1qWb$01n@`+D#4*&3s_} z+U$njxc4_l7sqDgy&8=F5v~U3wP}u+M4ZlvJpm8OFUfc^YZ)Bm(aNbn}(pVn}{?Mnhcc-^ESQZG>QFKZ*eMJocpoq73nEBpW#kj1;g!{9m? zx+EM2RYNZZ%iU6dR4S!ad>=>^ypszL_ou`zgr_J|Vqw$pZ!dTPCM6a&3;&`vQ(}j~ zAes`3+DM7*hOpQr-7$zi9Gu3YU-*8?IP?o2u^o?o;nRl`&@X(NYa;pu4{g+aCUz3~ ziI>kOqhEN*Y6|*=2acD~uf<^5Lu*0+y<7PZlmLgD<&-ljvuXqx@$JSYWzQO?-O+e)TpG=m1phItDNOh!IgcE=n6%(^;<>TW+|vC zYbynmjkgR`S~CcU3b*x>nu6X{Y#xQHiKWT)N^fsAEV@_W<|ZSW3W1X!D6C_fSepZI zlJKg~@aE=Zo_Hu4PUZCG<^)zFh1}d+UENk*3YyEque^|26X2_xiy4?mV=fpSW{cHV zAJ=T{U}cSO&1K=XScPjC%dIwJoZi~xN%9VS@Ybg6NyXzgcO{ac(i@u`s+v&CmM6&v zQ$fO|H7|3F)4Q5n)fAFv``pzu5V&|(Q@&6HQC-RC#WjN!8Oi~eBEiVIwhhWxoYb_C z5&8v#atNdA!SG{TbhDmqQ_y1$3t$!EYnmlia_#~RT7H~Lu4r=gv1Y0<@xDkn;W`6Q zycN{IhBkj$3IjD;*{XxIZ9z3a@Xj?&ImFSvh{%>r$S&Q)rk!HPS2a7~mc3UsJ0QwQ z06+nPpXs)RMQr*$y{T=CEDa;bboM@kLzbG`JIGyDiWB#?E6E&|zqrJ)%!xiXz#ePD z!{X+)bki8W_S?_efzd5&W0e$63rx|;49fM^s3laianX*JUWvs>9-XjU9KV9F?63$6 ztFV>rfpkJAreho$7SmQAG1;M*xYbT$!jOb&8x|qP@NLR;eohbfZ(^joIu5?$ND(;r znsA^kZ1i86^nOWMS%m{cH7!wyWfr`N7$O{qy4$pMjrNj1`oBZPd#F8eN#kp34&2F0 z*zSv$b1AoQ;=mYs4`p-J(}5jKq7{D_*h_YiNMr=F2wk!V z;EtSJhP%st-%CB+O^Z~MdV-8YNmW7VS+)|OSDdXXxOOD-rP?g5is?vc;G4rk zJqO^%wAHU+A4HcMp;1Bhv=e==qCSjA`31xz$ejfByT!I95@Pxrsq#qFMcs28NTbcw<5koX% z3mqw9*b;3)61=1gF^aIC@fw=Wey;l1Pac$=ewDwW!s)jt`>`yyr7HE-=d0?x0nP4R2L23{?=999MNPqDRBI`a*oSy@MLGsQMS>Bzy+95;k@Fq?MJ zb`6;fwqjM8U8dlPB?w(<`$n0>Dv-I(I51+BZJ;uagA0Ac(LP2O-3Occg{|D$=n0X2 zHon6a!HJn87m5?*QZWk*?|^UMC`ImCgGs}C19ly&Lgs&<-=|4GC@u!Zb7~ILdo@*u ziL8R&%?@REvpJfvX*_|`Rrszy_&nWqQOP$aAl<-H=(W7{wg@@sB126fD9BFjEO;O z|CyNRGL4BZtQBM8ATQ-KCN_OOIa88nt`&FRn9XjdQk_OH6f7aGFLopO91!AgfszT2U?1O6WeXam3tg@Y%2Q$gL0Ps?GD@YP{Sg1`cB(9KP4bd z6Mz_aKBgS;=)~{e%CR++l?ohcc!Iqau(?v3Dm6GLq7FZYR{=Qo+13Ve7%2chDG;fz z-LDj?0{trj2H90(fMaO4FmQKGqCc4JOzjB99I%zrb&G}rE>vDOrTDi4wrX#sQU;EUu7(sZF`E~3Ra z8;c{Nq1o7hqcDY&(lBHNl1w!O+*oP3$Vo?uYUV0Y(3gEcHtn-$m&Ny^6zO*GhN=p9cUoh+-*IcfVf z=u3u4*P8D#2=VhT(?Iy!kYcW?sCn796Ef8By)qpZoMuA}z5`w%U8nEz>8!4>=n@Qz zw4nxspS2~(%_uTecViA2savW92EJqC5BmqFlW@r|u^AJJ)ooa$S#LSu*ahDdnSIU{ zE(Z-oee;nM2gdbKk;nj6_ zvVmR$8JrLW4Wz>&rh(A+Y`@Dnng*I&wGCEwamZK$Z;Bd7hZ^7(APfm5zGhgY3BR6~ z2Yvw}dO~3%DP0`tKlGAK*Ba~S~;3=m{sKFoFA|?6fbn}6~2^I5?q@j2< zW!<{Ik_wy1m*6#`E7wh?LmdP>P%3lX@2KZ6b?i-O1X2jXEn;HSTWi3Z3*d?M_vzxq z`a^2h{Av~_Ka%}&02X01fer^XJC+LpA4uw!py+jaV~zm3WVMmfi-Adeh=x0rcT#IA zTz%0*N1K?aaZm%&XE;9KBXsDpwKN-vNSmC`Kol4c2eGh-87F!$K!SrB!llt6nZw0{ z!7J;;JQVJ{{v*aY-OxBs?QA5i6OA*+OEyhIW52Z7!r;x3=#Ok;xN9mbKYWD>^c{j2 zudXVQ^-8#O)7%WNix~6kXDtkqzJG%8^`Q4(-+@9w(<}N+#OZaS@#T;T{1X8RXKQ3u z&H0T{X9SpO`v(u;4-PG7GZ=%%6; zj4gRGEW(x?y)yH#oJ8@c6~E5mVJn`wUbN!L>vdLaOd1;BA`FYPh;Ul>SO8|?fS!rH z95KRJv4=3BZIRp@l69e^d}Te}A~9S=yhLStalP*7_j%YQI{K}m2E{#+J&;v#`m+-e z#jWBOdGy<05kJOzRUb(Q>Op%h0ZYI?L#IYL!&Hrr3A%RlyX^R^gMM<&4D)fO61~V( z12zgfj#v9k&gxoBZk}O2!K^K!_)p8S_{m)}Ot(p5nt4$`*;!dNyl!0;@&&~#m&g#! z>9K)~{}N~Wkdqoys(nj}dTQ3KV;m4OchFJ+lE1a-2NB!QP@9<2b>QF^&UpgTU&fET=LA za>&~(H%ouR*T(2kn4`&AX_7KtK;@5H~Rh3N9!pf0~Ixj7Q_~s=2^h4DRP1Iyp-_W_# zN4Z&BBqfFGEoWcWNF|*E;MMySFmZp@Fu`$~Mvmg(}$C0 z!y+wde%AL6Wj9I;eQ~}EM~o1do`pq_6D=_HEXewA=U^NkdH)r0m`Fxfv?}5DO zZ%eYV{|(yjPJ$S(hF#2>E6e%7JP>*BBWozim8}0r@@0SmQ6JFhYE~Je<3%x>w62i& zym|9BB58R8z`=;i7*_j=IaLtz)5oI4nw&{2GBif;;x(@y(K~yA8+BtriH*!31QRR< ziYD-na&t<)d?lhxZ_J^@)Y^Q-%`_hSSzUOoO@md9VdywTjR0_epd4dup9 zS-%vM?`$+5;HzpV-T~ebl-2}hmUw)3``DG$K+u~6K|j4u-PI&rgionae`JmHQ$pTk zY8B?5%_%dSOBOZOz4|C?rpd7V@KM$>r8UuA`Zy#qB%0b<^GH%%J%fMvV z?haD??70e8T^zQ%P*%9!Fe?=~0P7xZ-u8<3GktVgc{Z9!V4@0Ol(4=s{Qw%gS-qZyeL-Oz}H^Q(;8?^`M?mA;Oj(OR@ z&UKihMTjv62_IUF*&k@1TvGZ7p?3uN`HB2@J=nlCf{OUso4Ppj-kT)O97m0capoZ8 zR-8!eLxlaEIOBZ@011d6xv>y}KtVM-TtyfS%1Ze?0ymi|vp6im%A|_`__dTJRqXJ! zlxkJ%*|Jn0wPd`a?WCfpL)xH^rJN17dml@IKZnRtJ4_3>Tp_$7FkK7SFSdnWO@V|o zlhyFL_Kh;U>xNh&&6q9=oY9)`1}41mQfm{5Or5F?DG_^I(B|;J;Hn6nfDm7Z5-Rw zzDlw3E$Yu;-qFZqjHA`JFup0xgf!>-58xk8h)i)sNJlig!``Q&K8>Tueptk!$a7Kl zp3+r{OvA`!4jG4$V?Ns354Fc7|AyrLH(}(iE{x!j8nGk$ZPuk<&ulhj=OJN73ns@} z+Q0Ib!#0~IEWc5qSKF)$B$Z*8C}Hu3efb2EhX&UA2NDx!txr7#xW{Rq41_9Gc}Tb?N2f=>#)gtq^UmrNY@V+)7g0Rj?bBsB zZL@j4(pf{%g@vg^*76IR#jp^w**7foMtpOEe)_NwM#-RIp#~cQSXj`!s}Hzx#i^}D zhYwg8A)nLqfFI#A*TX5V9`MZi{oeMT@@Eux5vW-&w@)C4i+$^Yj|fgd5&RRrHKc@( zQDJ7vTXen^Y%%q%Qm_cNq4`$te)d#w?o*Gk&^VuBg3rjD?8 zgq~tCcdqp!N~clw97(oY%$>`kq3E1z5oGN6+76OM^sUhbf*vUd`ssZuQIm8LLvH`E z_7if@`>Zp1&=vwC|fzDDd;rWK15NhtSdIt2w+eaRSr(EhxjR#SrJ$^%|1w}$pP>pXJv3c z*1p}hVhi7jji=i`&{Y&xLscpejvg|t;sA_5aBqekZMo+*InW4BWIOdJAil#Zls*8EXl;RU+hDDl|&U#}v zW5=#%$I1~S%u6*ywZRJAUDD%eQScZ66~FIl?D6$`KdYwKfZ2XVX|zn z`VISTlXIs767AW_Xn{cd9z^&^24ynSEbws&b>Np)_-ev5R!ux-Dp7s&EphMp1TA8y zI8Lrs5*UQL3xOWs~n5a`^i%n92X@GD4|^7 zw|tJRvGZ^FunrV6MDmtT*b~?QQPD?E75f-chad3?kNp(>q>uO@-gJ-nKmd^XeHwxt zlt$(&>+Ma#pU_Dg@!=juzE?h+MdC3di~|@LdkDyFQ=>dc>vrS~6F*AbV9%+5kF$_$ zj%x(qcYH7n-gkWPKR)mH1ZP13`~{`J-tl=7rx~%qS>zp`2H?>~du#cPm0-r7*4py7 z@a{=aO5Nhe;K}V({lV;q_XZXphGg9cBz$|XDj4(VUb#>e?vIJD`9y;7P4>{@{xHePu%rp}o&Z_=D56UWUR*JR==Qzy^Oh^?7LUi)bP8AyqJ170Cd ziTxH{vq*_W-NUziU;`3er!wR@pJAwbY#!(rOen~6KH=;+AAJpy zjl^bwobeg4p@wDPgvV}G5?RAwTxVy$3JDB=eqrB%?WB#)siuCp#lBQh*0CDkN`iBc zvWW-$>h1>*q*mK*ALCnbr%=%kHU*9(|4;=C`1xcBUH!2;?5`-tx%!3AJLm&IwRYM& z!Y;<_v{wz{Xvre?;5vj^1yN_wA+)hj)c^v)}++#pAkx zaX=>-`ic+7oI38Hy@aIn=i5RiF^mVG#`}Y?L-zW<6{q@Ed~^tEkZ)0-fy-mAU4gYn?HiQMTx(db8ySGr)%4l`q#uOG1oj-W z-&eM=nm{0=5iu~XEo@+69KfLQDBzfvSRGD75^kM}kx$!oGmw+0H)@dszqRwv$mGK! zJOjZ`LU(`5{+z6~dCNXVmT%KG=p5t**GBHU?hf)0HXs|<6P#=eGl4wjL(v7hc!E3h!@_~;042}Z9%+kH&)8*CAZ`+@f zqWMQ#(J8^{^f*h~zDzvYYq*J(4c0$t-HCI4A_?bOelHTV~(M}9^>Voxp z*o(@~6Qx}s;S2bN(wja)O@~4ir-__ofi%f8+eDs6{$pQcV%*PvX@6S@atg*>k^z`i zsjq!y_m`9^tV|3kX9-6fHVG*lfHjAH;c@7qH>BXJlEHlwYs+n%y13F3b!lv`QLu>F z>xFOaO=Nih#ij-u!(n5CZRZpXHp=N6Q4ER35hc{PX!~7zfr*rt{bN*XI8^V)aDC2s%P#Sp z_hT>RG-@pQ%RXF|tGdJmCCztZO43`wm0XzTcy+{MJN!&yW0$yY%up(dD7R%tCt2?3 z!b?d;5hA9p7X?HWcaXQW@MdkOOT4J`m`ZIdh+dV}P~k*_<3a=n@YQ%s3-rc?w({;H zuvtC=n@-r)_8WQyI1)?BD_r7!1LNNNh)og{D)$Av*WtSczbAE7TBC2UHh@>bW2Ylt zt4oxTsjwq&S_+5EPDO4n3^QP@6%`>8K#@!y_F?iMVN%;o_$tKF-cNq72&-60JG(@! z0tDAve-ykH>KFj3)?Z&1Tn}~B0m~xy6<5En?3g0UpA}&)8-=#i3)LLqe)7*nn2X1Y zBACksVlLbPzJp#N$4Qxu0tFcty|Z8>M<`9*P;=b7bY0N@9YL2l8%hK*t819;JGj<^UH&cG+pmeG zXxoz(7_vNJq%>-_zl9@q{^=n_h`rO|awD7B4&Q*N|X3(bLfZgdb0; z#NEAQXy1uwj^&PG)umj7))54EOXbh{FtnERX4`5aKYDZ&evldpIfi@8W3GXG;{^FW zz1?L|qT`*|?!t?XaS(3>!K$ED z3i9T0wN~r8wyWsE; zR(rKp8;|@T_)%ybxt5#!1D`$(1>v63RX7AMv%$0uLMT;=kpq`=(kcaqfuRMC@zR^% zaDij8vY8d*td(PPJ?$T0HY?~F^5!~OEt5A7ICFML<6)$g` z0YlF?hA3xvc!Cpt>hraX=E_YT3UjFb=>R8vR0(ju<;AJF;R3h`#9P8&-7KNFX)yFFKY! zVL|OPvXn6UlEY%MOjq-=BTgB{F@ryjaDx#3%+^KX7CySzL37y9yQtV0E)V z|KcmFt7kuS1jx!RRs;JcN5LUV0oMpw_uv4mRdC`HhxY#HIgfV^iH`!IK8)urr(hAA zx74`dm{3gqj3U#sKpZlfw!lXWq6!`S>no?A-E*@RW9ra~M}%P!VgZ}wd%BD12_sWt zL0&3BK>6h7V{~c_lo*rEI;p6 zn?;a0bP{L_UYOt#_0hg!9w~_V>C-0f1$B#u+zK!>NwD&fBQ4a}(IX!_(v{mB9XO2L zU;yTl8=5&!D&Mmb6vb+RFv;0P`IU#F6^-w=fFqJ~wywGm%DU1Ei(FqM9&iBGIjHRC zMDYNn!`f8us{we44?o11tyhNw(PA8*ZLo-`Bcrslo}ZkjSH}?!8>_?P zqYfKX2N$6Y=_Tt*hD91HOTDc4ER%e>Ra{s4+)FtluSoPDbOKrR}&31M=ra~JV>pk+R~c)prZ3Vx#l+U@DhuJnHmN* zUT=K*W2?B}^f?tLU8mt>Mi!hnfPp<&b@$vwNlHV&z>ZFzC4hn3^uycxRh?B7dB!$8 zuoMws(gq_sWP<>+-cmNA4+SuBYFT|DYk>1+yab#g9LDsE?*N0Buw zgaHgJx(jejSs4O8?d;s7)L}Kne6}l<8`l_4#npgl=N(CDVUF3|40CQb=UF(7H^=l| zq~`m?Sv&_|9Dzp9;V~0OYW!~HOWVBzXW6}pJpxfj#({b`EMkE=wWl+zxV(TO({Xby zhm8aE*zMxDIefb=P#Y78H+Bt+G-b{N_hzp|w*y31lO5Z|Ky4$Gw*k3jvfo)hwxA@a zI?&k;T%X{n7o;+hvp~&nG9$b}aX%y!u3dAhh&Bijx9B(`ab$dg9W5YsRC}=V$DmJ9 z&t!0?M=iPxajsLoVPI_=xg_x1c2)%KUvQ3=In1W75;jd)1%bfp>c@M{e;$F0M@_yaJVy6QktV zMlxm&z?uj4@yz?tE2feYq)&EgCkL`nN5wHO4{$ypM zq`lvy=g>)R%mG+?=oik7^SyB@;kDfUa;2T#V2fw_p*v0GT@Ds8d7qu(>?O-l6q^dX zDTj>&E>!^qvz`39MY)~6@-`%wq{fCt8Yh=Xc(@bi%rjg-6U*iRtUYjaKDKOpXAixTC`hi#kmd^$G(~8&ir0H^U-L)V~u^caL|@HWBqZ@y`9q$DH)AX@9@~oM^sX z=De*1yB>PKvRB~ zso@91BBqUrE1kdktHV}0OBaXnA2&g*zcJSY4mXu{iQy)AmoC>ZCK5*)Y@6ZyO?m}HZE*4z$JsnAipp^o!HWlxjS4%eKW=bF zO41vMOa3b*46U7rwh=gQN$U}U&s)30l-^l>sFlRgf>l&slo zFWnVlUS|0Dz0*EIJ4u+=)-#=(on1;xw+S}`eox{**~7RQNV&POOShW&F{E9et(}Ar zF%njfkN-Ywclsom7B=_wSyUC!8&a)aIG%LONCXLSi?yn64T z^HE8;{ciImfkF{wN`Z4gNxAoK^EH8I=rx|YyLIMKd$(vFrAP(c^Gkt{G+v-jKiSLE zBuX}Ui#DFC9^M3J?Q6>VBu2G4onHj zt``&r3n`!a=~uNqqC*#l5YeGI+Hi~thzn=+EP$&)R%6;b?g>QSOzh$e!{g> z?!AZTox>F8T0^M&a2*$=_hyC8jV6YBqtNLzyBSfrVrCm~{!?eBlEP6-ESmv1jxT-Y zTM#?W{}H@$b4=$1F*Vk$FH3>NjbsF#J*?KzBzOv zGY-Jo1Mhsxd|RFh~*L=qmGPS?ybQh@SER zv^&mIjA=xk5@A?`7{N1vPjv49_zaM>azw`o%b|`V`6WleYe4oO*Tu4OhaB^*zE7!O z+vey7$5uJwF}yHPwv9`_zgG?R#)tB!K8xqQ8H=P)C%rr`31C7Y8$Q%*V!MBFd#^uBOFhPmcL^UWOM1i_5z*6rY2KMs6Q( zs;@XF3*vnGk#P#`eD@x*k7sCI>Wgh%^CjgL*BguqUM*gVjLc@j*3$xcYQu>Ou$CMn%rmSqQx;g)ae}?dY0`x^w)VRz=sHFiP&! zcw$ZAsAI?+i0q5*I#a&>m4BPeQ~TuAfmFdHG=Jd|at_FT`4~k5^zAJ}~ zy}l_t3D;s}dG1JC-Q0i1>)#G2$`{Zip@)mVNi&O3uVuvtd$^7T%PVuuw?W>eGF^e1 z;oG@jT=#$Q(D6j=P)D2n+P@q{e4B)fUO}F_GoNUWK8|I4J&y63;Y1 zpYW_78>;RZqQiPYN9{>$s2oJb$4UC>Bf}s{LXnXH zl$h;mFMqNHba~ZPHPm=ipEKL_uF`TZqX%acQ4GLFVRd($3oej#Wo6>1zKK%Bp_5Ua z1F-hMpL4vvP2a{Gv)Ak3cx`MH>dDx{N5CTH;iKlc9?0@SicLLy9*2!ReB55q!$<5T zPQWil8k34wYz&LE!F?b6skINU9$k{tUI==`dynu*M3zv@a+wsB&_GWRe5laV^* zHP@$-qOvkk=0~Z_IdpRN>)I06N#$)0G54XT4mi8i)k1lfgW^MrZ-W=&UC--k3t>CY zpc@>vxqcbhVAV3LTJ#W~{EJ?z_fY4?TKxeQVXfjvx9R46So+3A=K&_)CqF*1Pt1>xdC8@#Za;5y-G|RtLX#=t z0DZAQGDut_$noloO|Do;`WmyzZUY*Q7C{0o=x=e|fZq*AMoLhHcNy8TRj7u_j~eoO z`@~h2V^n-}5ss4)S%l*NOy}qqo?}!CENbYL8}Aoo*kC_axt4AWv%5YIka~b9)ztx* zF2Y4nZo2N*%`-ah7w7B^AcRXa@c363cIkDW|LM?04ca>rMUm{z_hEMqVON`IjN0kC zRZLoo*e$|lrqd2r5p4LTaIWhWf60!}j8|%xiWpl}*QsJs4w0+yJ#uCx=^C2ON>cWV zRx(E~*KsLHjRFO+wvUCEu2%U^A2)Z>!VG%AGv*$=hecOFv?!n%&t$J$!NB9LiJ^v; z2F@LaSw-URqOywCCtO!dwuP(Z!+FGgj#3mq!+vG}1DoCk3O4R5uXZkQEtHjF2bl5T zcOim!0E(x@z|2#w|L7_T@pK2}lj|18({K)8Ku2yMxnKhKbVn(XT(_8qCJbPJt0Epk z)Cp%?-6f?Ht16D?hbd`XYh*lc@s8_^(w9TT%n#uKi21%C_nd2zuA;#FQG*`vem2*o z0RsgfH*25%F~-*p=<>CNh!*2{Yh3ir71!KQLp_5z@42=qr#Xq@vHc_iFtLEttFGyx#zo5ec>H1ypM9p6(;bde zVI%S;EMjt+e$BO2mjBYr>30qr%jpXrIo*VEA_MTadixuN7}Af&Ut{`Dd~7)WN_D}w zPjoZY+6O7MbokAAH=_a=Gx<~in0DRO8^Etq27$cEr-ISHL*>o~%_nZp(AQ8pk{09D z9yeV5BzeF=^NCx4fC7|Tu6%jyLGyWASq+1at?+SX$QGU@^Ygaa2Z;>nD9lNUjKUm% zSq1uqN8w6}*|6kjw5O3M$27vVHUvK?bOi;l;(WU_W#-m_6pXhBzjkxRT>nGnY!baxNzJB)F$S*&+j{8X^ zK-^Do=r(#=n+>Z;B5uP6uI7I58(j?7G;zz+aCK($qb6$JY(6oN@`r+ypMG4PwXs@KAQ(RCX0fN#t4-t|jG|Ac9yq`vYYihlt0(O*{aNf$P8nzw9Am#adut zvFxtOPT$%g{@HzXwFO4@8qk9$zZ_?r1p61y*52_P(CAbIeAOG78G4EyuWMXJ6c~?_ z@4_M$|8q)YkMozlqu6wu{F=i?@n5x@@-3sqONIFv)FHc(hWHz>tB?dO?jLjB=>k(~}yYCc1GaD$5_zg;|auvYW>N zI0;WFXH4NpLkfpc3en-u3t&yq&&5I0knDEgxtZ|v=WH`lXNaT@gQSW9lp_z*TY&>G zdb2=btNqp0))lf_O3G%`AzeEV?EVJ>JHwYG?^nz&CMny@F@H413{{gVXZM5aM;s=0 znG-w!xr_=@t7hNVRTP}yCxb4EaDrLYv5LlRKipsb&mmo&_!;Wl*#7UpB5eP71?X~( z?B()ficHP_FAf=}KVKaZ)5JT}rs(%04OK#pyBQWCz2QMz0=ccT4G$PMI4sVh>mH_r z(^RNot?ZZNu7}Mto)ST16{0gij0Zurvro%|51S`Er9_P05!v1435U%So)8U#AGzd? zhsDWc-NR2dZId{%tZw%2L1~Z)@2rx%hvli4y;9l8!1{glir~%q*(2n%!(`9?$`22NzERnmbv1=9ni+I~oto>DF$+Fup1oLU!1aUkh`J2G>Z9u;lQ5#8$CF35rYh#Y_rZcMv3;b@~kBnfVF>Zwlw%;NM~B&VPIa9Ze96p5nh zrLo!11<4N~7iOmb8kZtr^bdj=uf91W`-334^ilITIz&YI^409dL2`|w=7DsHhN26k z58$_6&ZPF`cKZtT^2Dp1w*-Mc{cc}f+I`(47%+hWJoYh zZz2qfG+sU|Rg`y1A5%zvGw^48Wkljv_ z8&PcP{q;F)?EN8mqW1^o5eMPVEEtoDQju`OA}s_oDnnkh`TSn?OD0+x_7l|7Xhavc z-yJ@Z0hn;KW}~QI7DZ_BBrF?53)~4@;<$iayV?PB#V!dGN6*U9dKhRv3?ATG(q+( z;~j3q#TfZ!o|q0SJ!yH?) zk0>zir|hPnN*(ujrPK+n5prBUkO2?^i9zZ&b=-9%r79}}_^ejvdhQlVZ4QcN^?tBg z=K6qIy6QMXuU_BXR%sV8@VIo*b};;a|-IoI4VzsMK~(s$K`uBc0Vi2Z%}MHbS~qtaa5ju zLL53Lp70$yjY-9e7HPaJ3oa_C!slpnquuCQ+z|VM0AjqOKm44F(DoG2Oa~vld{OP_Gr@ zPpF4sLcP`o^)M`6sMyA!B8Ca|+8WfuFri*MgL)W7>&1IbGYZ?LzzP8hO-5nE5o=4pHs?nUi@d#|~BP~(gHGcyGAU+nHg|G)p7`+55F z_F{J*`m@;*cMScRu*5xt{_OO;`$hWG_Pl!-{rSi9?&s*w!lmv(^rxkldjb7fskc_) zalHFk3XNXoem0Or1K@bkT><3xcKd@8ecaXgl7w_va%Y*lR!OZo$eH4+fzwQPcZtlDpAg zYo*2jjiGS^G+LsQH67m_;O@%WZVtw+LZTf2MLTpL&s%elFy33TaiF^jkCQOOTk_#R zcNi!6f!UBy+*s8?8lm@=yL(ca9fLGN<5##lu{K)}6<-<*>3D9iJB%;ED#j(LgWYv# zO9N7PHd+uiaHXn4G@U;?L=)-aA(}AqhiHnf@`Af3>#8Lv><<~s83u_+et{Q8OK@+3 zx8&>#?iw7+g~&EAiZaw4MyYEyl-GSr0CishM6PnzqviQSH5b~wN~3Y$Fpb8j)f$a= zhq-%l{YB4%{e_Q!B)&LYV|2-I4YPp#bga>|-hTuyu2w``xRrw=+)bDWS`n?|l7Nx! zDtyNaydC!($twspmI}GUC@V+0z2-SCO*7Bn7v0@h7p;jb%cN^gV|h`d{?3cM;93*G z!K(hC_bAP2;znuG8?#Q6o^2iPG_46$7$dz%W>*F=^eLP+x za>N8pja}Y!ccZO*H$kH+Y9iljJ3>|dCdkFciJG^*v`Jry1f5Op=8P1GiQ^5zd~FgR zZ(s?IH>l*uB#p>hlQbgRPS(b$nikFGFHLsCPinBS9Ne1)E%=f}Q|6c{T435S#oe9q zmS%PL*P)f2OVIp5?91*dx}tG$-l82ZYlK~TSsVTuO?5xdA<&WJ_EgBprm32aU&`X8 z1HUa6Zf6Sd2SznvPgF<3_~dqRrE^W=~Ahh^;zZ zM{IL4?BzHiv8mHFV*5GWU6|IQfRqed4R^YWgUT~B5A8BTBX-pcjo3Jsj@ageSlmIM znL1+Ou!M-kMXP3N#OBP@hz*+M?!}W4y#m(Hp9RTSJWHdsi`(6mYW3S$?r8cmYPLq) zlG*O=oPOvqf}8njHXj$GK=crA2OZPeHDYGYad+og8oLViIBT1`1#L^2>+VQ@_MNLW&~&@j?+pXW2zL#-pyd~ey(*#|1zDCvP`R*Q^i0IG(oAQ$N=X{Nh;RX3QX7|ke*CKS5)1f5R!&L;ky=y_*a|4#J&o#-w2ccS<2 zMDO2;9*F*Tq8ADNo#>&76Zm(c2X`o?&h6V4xqX=?ZeOk@ z+n3%WA;6jgS3ufEwrtyC@}!onB0-$Gs&ZzoJBo)rj#*Vn-j;8EtY~&wa*)GA8jlAb z=DH^+tkq7SASAgqczLgThz=T8BB_>qB;Wj;ofadtvS1DU;tcQQ~{GzjD$L-c|Ss7GYW9v$vDpbKjJtvf$orxAwGD>9?37uqglV z5#>)%l-wZ`LvqQ>6UIf~U&B`5bCk2gTjHU_wvZT1ELG~eA|9&w ziW=rX(n7qt>Ld3{k~9hP${sgrW^}UgM*)|6h7Vl)#628@e-cs(y!VNFEc}odk{x^T z$S|z_?rjg0y+(&e$Nn8nq_^;iJ}#=Z#T5eT$Bso`3112Dseev}_~2(a2QV-qcwZsv zW@vfP^`?7SsG+HX4{yTrPrHzw`SV!Y8Gtnl9^7(I4>c}YcpIw`n_=EN2O^|%#E?b< z{2fZvoUucnB07mx;VHIjC8f^@8vOz#hlb7X!duvrIVqh&QmPI=y^L>l8`Fk;*tjU_ zJ7eoBbyBpxz?1Y)6Z%*Vxcj}kE7-9RUX`v5;gmJqt!_E|qQk#(f~x-Hk5Ki7H$1`cd+vkEI7C0M`j;4h5uh&q$=y^|X0b9c z_;)KuQVI^89I$Kst2<3e;1KcSdP_j~eVFPj;o!oFy&eV)!f#1Of+`Q(wImyO_JO;e zV(0MD!9DKdygezt1xkINBf7$ytSaM+eBl^$`^_C89RM%?=5C;_wYA_v9wk1An;ZOF>_-#%Q)P{4aNg@;w7<*NOu`$A|8C z`3u-K4AEfO=#q6fZhF(M3ybdB^y|f50gD<}zklQomz3aB%&>$rm3?W?JSI-7H~`bp zhQBgZ|<9x>_Zh#e5% zK}U;WNQU{E^3i#dUT%_Ez)Y!cb7NhE7C zync)3P1}Le6+P`iRvAx&|J&|LfN$Dn2Fc%@GM{cPrl#^Wkxe|9TF%p3pz;N z(@->&!$zS<>I$OjdiYm=+Q02P(KDnOPf@}Ri!^pF(UfXHJx?`x_)+rKqv4PRZ1p@V zl~hC?pIR+v046N}>U*v$8(9&#R+B@(&49hSCy-u7VmtOfEAF`=%qkTG~`ks2QW~(QXZ zeB?EkaIIbIDD0TLG`#h=wyj&VXw|y;gh>-yPHrAGzTKp#@oihS8{axAs&!pm2L)1@K}gPon&B5k^*ncK87`GBBaD=aKwP5jGYfVtm}iGhhCr2or0h zVdzZks*j1~>7{u@kml1b>sHjnNtSgDZ4_+jW|#oVQD;OaZhA)V#Fx5zG6Lk@XUv_r z4W*zb!HieGjPX<|DZhBe+=*WlQ5FpIEDVsRoiTUfWg3c3!rjk^PTcfNkxm?HETHS- zj0LpWM?f11n{7bZ*F6`2WrC+OI2H`QFqI48;<`n_+HFlFNRQs5HWp1`m?4E)NQNJb z?B+3iFYLAttvB?_1iL4DF37(Xq04<#%D+-wg1fDgI|BO>PirvyWzSo3$+PB4JtE?6 zpX$kxE1xyj>026xPNzTl==8?llGs^OiS;@wn*VcWvH4T&mY4~(d-OVdYj6yNi`pG{ zF{!aU>a3{V=OCnrQN+Xm@69qcz|}q^rVG_V zu?qi?N_!wdj#n=)_OwQ;@DQztmlcYIkaWn429_@M?1gLX5X<;2f*=jSt5vkXj`)Bt zF+5sVmV241?K}UA?N>|i(QC~Wppl`ZoP^mnDh$8PrJ$o`3Oyt$)Coxwr(ay8#TlN7 zZ@!!8Sr%?MFVUj%wQ}S(_NF9HKjj`Gikqi||G)qSiDS(WP&Pdw1k6kJWGIhWRS@?P z{FX|SFFkFP66aWp_|?6~?|}2mJ=1j6h1pAOsy423GJD|w2GleN(a$kc;2g8*Iqw`3 z&t4iKYK&(u^pA%d83}cv|7n^roOX;PP$ZZ2&xKq*EjhVOGwWM|!3A2_1kCR2 zXaOEaIIDo2d9cQ`L-0?~)b*j@uP;Dl@F>qy9*i#TE(gL7Z7mLFzqq~(Dfs#jELe10 zSGnV12)lq_n@4*aSc_olVFChHj~3Hn1{@J z)cmSl(1py(7sQb12O(lc^9-~S-rJx0UDa=C?@x@I1AHtrhFGXJF|oYmsS!VM+$+<@ z%$YFjl}X{@Q|FAq|NcMrzB@dsqKn&m6GBLCfRI8b0YVLBdjSNZ6e$4$3etq#>@Kj< zLQ@0`k!I+Dz#vUP%?6S!2?^JRfPya~AicLJ9i@qgBJj=3y?b}=-MbrkeZTMd{?O+! z&oVP-=A7T0bLLFFqb5$AY>iMP;{Oz_RBFA_sN?>H|Gqi_W-GnfN~2z-GD@>m-fWdt zqcj+#*=jyp*9y`q^?X}65!bE}$Q1^oLN6r;S$PGufM@8&P_XEmyzsh;R(hk_pdqU1 zVj4XWGKu&GOOuz!n!O3QE=4P&Ua8f|l*gPZS{ZaIm70**OO543)M~AomjUsHvq8$< zyqX~SNI@)kZFgRkf1%}j&5PYXhW6H;ycl{EG`m3W0QZdJrcO3a(=)+)-{y6~{V>F* z<3q5L4;l9VO3T|OCPEwfZ?wEsE0C67*tDThi;(>PM#snhizu(zoZUk&^AA-U#suT$ zGxR(A1IMGoq^f;kUtW!WUCjT`#ZU*K_r7D;6a^Olxv|o}(Ee|sZA8!CA9zANQP6JD zggSk{bV8jf6H|4U#8l5egX+RJfBUAY-FK?ysHd3M4M1ZBr}CNE(@ zesUZ!m-8{r-Z}%9Z6Z4nOh}I5E%omZ?#O1P3waYF`vxXlCPN61X0Cy2xr;95jgK55 zAtmt6m|B#jdK3;d;q`s;~&F_z7|oVS>YbP=>Zjoku9T+LeB$U6XbRa>tI9q-nOAY}7q6S8qf8i@n~>bf`Z+9N)oQ@J}l`ti#F z(cmdiczO-?A#wIYo=bdK zP(Ew^efh;x#X;$kL`%pF!onm0>S5DM5g@~EUBopF%UZjxQeHoyUY zE5quWBnvG986WsP76*GabHz5tzyy;nO)QjWTKF8-Rpb|{FbVGVNJj`O! zC^c4t!lW~s)OuaI%4kz+%_@*#TO7-72=|QV=`%t8jaCtQLAkxok6M5vb$dNd_|SlAlNwYCsji5 z=HL^F7d~i{pw?ThX01tKQ0mh)TCK@oQCMwOh2EsL=*$)kTclYH`@pQ#q$^DdYr5JB zu~ivO7K>GH)#_o7S(PSsV8)CVi4D|xo6e#% zSZx}UN@LThOe%{`4<)o1EGDbbz}7dWoIUNvYI8^V?PN1Ky?*%W2*UzU$@am7p%CY2}Pn z%4P~hD+TULtyYn)GFU8TW4cYFPFI_CDl=3>s2n!E*`idjIl6gcLldAhdK+xtq*J78 z($lqOrB!9rYP8Uu=yX;s$K_qiYA03K0P#>ORp~a9#saldt5oPM>9C7U(6eX&brgy- z{PUbbs!p(mf#;oh>U!lgTGV8f5`3xuDI&pSQ7d%m8np#BqJgfQzHVyP+Muk#g zW{Wytja0$4K&#TCFqsS*wNYz^c4=1Ij5eD=mu_Us5>_K4OE<#4ga!s3phl}oH>>m} zlf`6!7MBhW_W@WH><{~@0$4O?qZXi?zD8LuXq#pLW#Fw$scWTB5mshWTA=e%8LWDR zPGf~m9CnOVoo<4V+l*=r8$Eax^mz)6QE4(m=VDV^p--?uAE<#&UZd12tvaoe-Prl3 z^;9Nwl)-w%D7G1WaFx`GOP2$f1zDJ8)1vr;qS zs6kB!HDEf6@XWkIo^P)l#XSNe$+JZc$uS7*xeFXq8%6&dB1&_ zaVz{C11>T5B$# znzbwLfce!d)=Ad%NiD}t9zD9{6w~O*)`_`xH^|6!G>&c!AAdj<=yUCZ;nm@Vje#=e zes!=T*AWdro_;vj5fkQs*Y6iLMCpyFexT|KhXM+dvcjRKZ+!>eS>dQfRRSwkI2vUl z$g=He5Q%Jiy1cftfez%Sor+XujJ7G>KJ z9@%y`{)F;c68*|Vzf|bgm5<>cHTv}`_+_P|Vd`24 zi(QKn&N<*89r|T~z}WTZS1bg_Za}~4K~U^Q^lK9Qg*r}|YrlyS+oHtb5T}JLz#9?w zTVh|+#V|J+^* z|FlGZQc&7A=+{f=7yi)n%jg&S?$g4mqsN&nEhmk%wzQZsCz&Q%C*|7l_gFilBKRYS zUC=N5;k~Xn4Sh-K74!>#QK%dGg&)=Fj(*{%4SJwo`016N=ofzJA{G6@PbBn0zwjZ~ z_t5n+d~>fiN@MUT**@qe+`q_rvhFp|-c~&f++F3k5NSin{2E-whmKzGn`S#dbf~Bn zp!Zs6;dU@{wWD4l#>mfuKuWySG`1o*d?2a?xVhSKDl$u2;k#Ug8*zmi6b-0sY<{%t8lJw%4oq$rk)B zEu_;tKt2NyO?|Iuy29*s&-!7~UJ}+=IsP?lU z6Z!=kUIx-`7fw&iLEp5)T_P^Qt$aWG0eH;0_V@sKiu7C^=;(AzVrm}ps@Knu|9$gQ zhAVRcJ~dTN9AF2^>e2~hytn~^_A{L}lO~6IBLoF_PxNml9y=O=q zq?A1(IqpTxfsH4%tpMwBETwvaSBe}fm|kSnId@j3#`tRBKL^|W5V!Nxl_*LujyA%; z7sZZeR66^`R!1nsSc!r_QYZg4R8#qNvg=A6dnsmmkjnUP(Y+nKGRdBgpL`@jp#EC8 z%3JWM<7dzfrnDt~b?u?b7%@>Z&lJc-K>iU}EpZF0qW$Kol-jGc3 zf$HtU>QEoy9d@LwJNqP51BdFYS216c3?O)kb`rTx-$52ZA_3EO$3^B4nT#cxS$U+6 zIYlO8i4K7$UpbaZ%0r17`Xp-L-x4;TOpx^`XA^z*kTmA=ktWHI!ayoE7PQ;t_=0}n zFv$90aTjpOST&Ilt*Jj1w-wHSL+|A_YWj^}uriqT!Zy(h?FfLBk#h`m{9(*r6TzF< zef(*-mdI-Gu6F{N;@?^AxC<1o>~`1~)nS;Aov7FBTN5chT2Ob7!yX?XZ`~fp38ouC zhmDCa@l=jc5jh5uefq5f-nt%uk!%Ax8sOJTJJxtHf`Bv4pOzC+RGZ+Ryc#*!d$$6< z5Y`+FZ@Io9J?SvHJ;-DrhP_@*dRYPH!9K79^u8E~`QEXDUc^&#+k?z}lDcTzf;RM& z!_xi1v4^>RH{#pAfgntoH-A*1yg>&Xs{(oB@Pm#`%nlLs$ajB9q!3cp{J~*wD4*xW zZ4y?!`mSy5=@XplwUkr6sa&s!>%ydmMrF6BuLjZD8UCc$n*rrv#{}jf!8zFVF?41d z&MfZ4JSCHJK5?hg49cdNUuB;h<*d0#* zhu+QCi;GG|`-7aYqIS8_zA!T%oBahyv14{xDZpVeq;F4$M3&q%fQ+zdI}c0dtUS7~``K?4O-)XZDd95`2!z;e$>Z zfirXR-Sn*^V8Pt{*O_0)DmHe`tq-cs%YUDFKqhCk&Fu`@js3d%%J=j8hd>HAqR=(P zq^NZwk~+?{euKy3Dp8#j+dkR($C;W(VX~lU;;8HdS6AFouAc(b<--=82Z|@5^tH$i zhj|pECR@Wof4VS#Fw>Sy&In!J8CVwOr%-B;w#*8PEi?)841fp{CwanXOGE$!qSP+c; zD6Wy10!QBSrG@G7NAZCLaaoD{H)QxiCq*bOREhV6DkLBvWj`1fpr=6H-2BGy=`J{K zrqb+D(STcmcnmP$7QsA-svY3ljPI<-H-^%OcyfNkJwTG<5%;sB(h;`^Dx2>_P9Prf zU`t9w@HK2reiO*Q-;Jt2k4n$v{O)C$e}rZ3+Wg#5I_8-4P`ePXrAAR4-c^rrLlV1w zWB$WXI_a47u&|G$zLbP<|5wGmqgBnfNxlPn5pAC^I0a#GS@>j!92A zSzwCqB>=_*TN2z-#+v0X2ECkv=f=EVdWGx3w~QbNDrS+Nm@ZCC@8ul!%D4ING4#G5 zdU2C)>_1+;xOFtYR}_6Vh+ag{oGJ+OT8TwWby+{^FM0&B?PcK|zFbkw$wz0!! zT^CjuZJK0#JC|QPNxcVGA^3s7UsZncq6yNzDYOI+I#RoXqBnNQKD*K2xKyPQj`MDV zx53t6%PNX)dpxiWrtv5kILb^%#|4{dy65r0COAk!!S0$~_zp!6IUd*qEdq%MYVC2U z2`0exYC>;GgZn!sIGPTsn@jxgTF6N)nBdVr^UqYH^N$BM!O6TRpFm6r6WjzD7hfx0 zC>A9fw&Ya^@L!qWSia?QP4Kjzm?tD^vA61GTO@ryh+0q~oITy))q*Xqv$-=vhnxtk z7xkqiS2&@+`2_z!D_}Nb{PKd!gDh2cTP4G`Int#UxO&~gSj+_Zn-GQm+ zX1_-@x}Ff5VOzuI*f2W%L|`)<$s;kGqs(NFw%`0t7(FQn-tS3C_H^ESsRBJa2;S=i z5)yCtR67(Rm3T~}>xqA4hTB4dnIXl>VphUQE|}usUYiT6(T7f8QzUMs`$oeZyfg<; zeZ=P}_Mv~b105%>sL1Hhi`#fLxI~aCt?G}-k+8LYW{#iot(R+#)JdtAekxIqRhG>Q zBdA&+WzlB8M^}8}_6+3&seY1=mh#7Kt`JV=2yd8ru$)A z4HU&bnYURsQk~$3|2PgoAtJ$}B(rN5bR9eO1pb z)5ECU<>3B=TZl z@6cfUp)E1s(5oLsvxZ??Dp#cwPX`WenQ%^}>Yf(aYOT}QR*BC%g@Uy8Tf7gwFcfT9 zq*2d3y{y1DT&}66`AOZ2lUi`*rU_d%!Py{`Kzx_pXKx?yjg8(a8}n34)4?PSW-)Y)PHQ=1Dx7(@TV94=I+IlpMwDWL_)z&D*p-saK%cTvYsLUM(-jX z_d|Gx2;t|o!zz`6+F|Q6QafyMMr?CM73Qp=noLVBVU>F2l1gS_N_YutPcGOB$nJ8s_e>xgUOj$nW3U(hs+ z4mlgx3DOML2``-GXA>U`Em#~z$DR%B1nWpiKC~1(s6Z#34Lrfu3nZek@`)eR*F;c1 zuZi|y0-5OHx$b1@tkgnZ<%AYS${k}08pqP(&jubD2l9f9fshi*KK8THDE3vDLabn= z!Iu7+dG_U7F4sIa`iZ%o6Vq#++vXJ9kEA~jq7?V|wpg!HOvx$uilM&`q7>2mVIzU0 zaDBn4NcwCLrBDeZBBdxfD-B%Ni?LiI#q#+L@TM2cphM&N!UEZ$vD!JQB2_sjo+ofK z$z)K!xFE<({&gOJrW`f5=1R3gRPs*GBq88ul06YckSY6{0+|TtM(3nJS2-tA+UGUD ziBW;f55Ikx=?B|%PH@5g+Oq{CtHIAAU~vMDkkff_R-6;r;4;X(cqTbrEY4Ke+CQ_w z$$ZP@+TeG7qJAsUkX`!=evY7iEJs7a`QvsMc@1HerwaB*QojaPk)~3L$(IX`M9?AU z13Tw#0*OdH&iSdww_-fMk>dIMc1ZC}2Vc?IaL>;Uiyjrj1+V)BDa2QU^ykG!_@Da) zmBZ+M=K~LZ|;)F!2o+yD!ki(-g!RoV(YiOG}}>C#A55`f;bV<71xi& zGHrxy{xdV&!Shg_8B+J8^4^xHNdMM_1@Uymg}^Gp@@G^lUf|=SIb8~yR;O!U2&^L4 zq$G{rD11MjPQDO$l31fE7ll;>yCxSBv1sT8sf)fX2J@B_%;&d356>=VgNdZmhaDx^ z|Lt1Udw$UGB!KyXbW|M1VdjlHSZ=~NEeP7ZcpTp5(dH(M3xj|?KtjP!7}o{?+vFvY zfIXQ5o0yUhLnVYM7KzN?*@YZcHJCBdKltIbpOad!#t~VC@v-#v3xUJY3A`v*Af`k( z`r`%ZWD!0yMM&};Z0Mhv;G2BI<(VK|^P*HM;xCHb^r}^b)uL$C#lSZBly9sxN14gC z$}2n;MZbJ8unpGZ4{Qr0@01iiV(5Ms0}q281QOCu(=9GaO)&nV$VbOOu0&uyzX|^C zMKfqP`u#VBvf=1_KZxf^Ailr5@KcKZCg~ zB*^NPJC&*dHk>SMBrcCm!6o_DN0-XT!3~07XRSGXX!9lPn22kkKH6n6wD<^Ug9g)$ zYK7hapR+I+wD2VvwZd#wT5a&3dYu+NPyye!xm33O6G{zPp2(k~X;*{t8;REPEleOq zgRf_$5E6Jlolf=yFG1GXLJe4Us<2-xxh=a@GVEi*b|9x$ZfyPXM3@dT22{5LMep3# zL*IrBf?Wl>4GH!v_;X>%@5b4RGj6r#Pt3xyvBG85CqLPwzcQurn=?tSk~T>KBo zP2BA|Hxdp>IMKcX-@sg0u5{>ntLMkU+SFdK|HncV^%;2fV_`D9G@JZWVGH`K0M)GPB<&)sROO{Bm)tVXape5Wn#ZsA_01yKNC zztVfwwtOopDT6PQ`>URQYcQh&d&wU`JWu?|!gRWK8F#Q(L@H^OpTCP*Mc26E$P@tpaNuF#C(OHKn`mT+ zn?|Jg3SauY@J;zFcKD;h6`{-uf(%ek3fD2~$P_Hj?I(pps1=~c)4~bj@)(1gPYWk9 z#ePK2XN7Nsz}mqx?W~$&GKu_2+%$s}0Q-aLWQrgXta1I~{tO(~zaSe!)0z@FKj;l8NYlL$}2-A-!zzN;^M^N@=b}gninNt+)OlPcQ z3OW-{b7f<|xDB(y;D@NosyI6`Z;_=sC{5x1nez4+XFqXyPVHly9%ctw9^1;zSm#nG+O#;Q zQcNVl{Ur|f9vJs{S=`Gc4~y3G>orn~AVTQ&)BSj-F`T~oqwn5RT_0H|e+}aN+nxmH zL5g`uN`r4j_(%uIkYXn#;=${sK~@9jLMHkrQkl^`u&AFn3yC6gBo<n<_VBH97 z?rhJzMwTD{mZvJ%Sr+?Z2yP~)N`eg8&&{1ZnGqxzVk`>P4~Ner7;7vHTeuX;V&n)cdgoFJ zftYQ(4BPmYc&5P_NinU-O7UDO8C*6xH!;a%hQx42%hZWXw45<*f_L%EcloyeW%4di zWIxm>7k+`98g6oVyARBQy3Ah%I?~QLkfz7+)co7LqX}y2v9m4x`eo@&pgxzmSu}C? zHcsBJL=SM<17w}+=wt%~1o^UOvPIvfzJCsG6n(b$cH!S}gPR=)&on$f|B<6N@cBMWA2RlPO6cI^!bUD|fBnvn)iX&45&cQ2PooFov z_hZ$bvm4Sk#r=2S!ZTAa}k(xxmEB+=S z3mL#BA)jUH>->QEfW%2Ms_zH@M|IiyVCcQG$LvN>#j*xvr&8NQfNUjXk^tf%0RdfJ zbAA9{k>ZsLn>rAy$HsxqR66FW$Y)l) z>N6M#98oY!&<}8Okkd)G;E8#c*^D5@c*I?m>POVo=h2UHtnD%=%dZ{_`VDm!G5t{6 zUTc%6%Z&i=lvDj3(Fmicw4@&fzrUA>qOkgN|0`YUWci8T$OeAjRgiQyx%ga}E;|Nqqj(02l{Q!9PYg z&jc9tu8(x?VXl#k;Dv(AM2euJY;C)93eEgRMP@%512R+DV!*@jD{)DMz|QcO=924V-s`dNO5`MG zO`1-FC&s*w%@8P5lcD3DAlNa*xsfrEyhLZNO=CupDOeg4sQ$LIrMResySg&1aNL1I zZ#zfPS@O&!$dGZ}du*z+m||9tyx@>D2V9!wG%`74hHrZ1Ad@lgIpF$q7)OiBV~ZIw z!#S7vj4Y3%B-Ojl!Bh@d{H}AWmUy8XvvQyveNdm{SoK2XkWHO#lT(|}Xyys-a1X!%LvtaP|h$KLcVC8IQ zD;g3hW;-=vA|w`}ElmP)cz3q5Kh4BkCoBN(_V}c0CP$0y?Z`amN~$3k^}cf`(}=7A zLmr>)TuRr!jz0L2La>r7R~?@Hi!t{GmzndOUnj_}UU~z()CiFBY-201c!6_0)0^Z2 z`>38oir}Nb>V?kHak5!#?M2SkA&iY61K26RDOxzlT6|H3zRfbYn&#igSKm8dXO_v7pS2vKEG^H^jz5-`4}k^YiwaaNKZ^PQ2fW*)6qF5& zUEy5jS3U_SR>EodUYYWxE1gsQ%GU>j0bJlXBUAoY;8aPeYa1H^c?l6ZbjLz=oFilCk%cI0O(k6{*$pzs3}6IVMk!suE&H6KD%zu}|C zK|#n3X$bZBI=5xce@PZ|1wP}o^N_S&h5Bl~5RU`$>#mVhGaRSQP&3!jf zYlWXdfuBqK*SmY#+0{d!PA+4=OvGY0wze};z*_XH`=p$Gw5a8L2_v77BH}UZnLIr;p zWBfphaqy4N$$|X705W!0Nx^k^V^AHY$KI44D0-6vRIJ452D3_G(OQfugHEG07}2L? z)H?XZ9JR)xHrte(5|>*FDKRwC%X--Ic| zrGSx;@qebi9|_0?S6`a-L#>2E&3iZx?j4p5Mygi{EO9&I!0??bqCoZ+&MDNPz$#tB zH-EsZ(wX|Q_XPdrRJ!eUXFdhDW&^nfk@s|zcKMA}==eL;6ezzIjaH3rNk*%$ojd82TY*Qb{e1iFIl@fv z)$aN2!2S+pZNanM&KlT*4B9ilrI3_F_q`Q(Bs(IlZp|KN9&NrAcqBXRr2s|W`bM(0 zNHD*VtPw5~HXJ>?umC9Cvzs#{UU)PsCvbsBz#hR5ai#5bCQ-~1D70WKa5L&H29PN@ z%v=Kc?sIk)7sat@ho8Gw0N?F%wq-WU5WVreQ!PV;W6dvQ%8%ang`Bz-4(>JVRWlU+cmZT|8x;e7SwE{0bDnGr&k}MDI;T@-5Wq?>{AERS zjL+*_dn8X*E^^Zre>9WSFQ4>hPXwIG3_0l>0XN!7uJClbH(U3tGXtJNA#;4o;Z`yk zD_(EV zVEl#IN%Z=kMM3@=#D#p2zY1pgg8bAn=inHc<*E4~zl5O1LH>rHr9u8G*jea+Cb_jF z%WJSmf8ayxJ<~3*z3Izh0m=v#BrBH}L;`&NyYnbbKM@2te05uo2!a^%f7Orw3;zrL z+yCV}QqFu_&&|h&K5>p`TK__r9-fc4AX0oC*7hk>V%aSA%css`G}DD30~=2hxrj9!yu7S*CvJUJ{R)xB{LZVBdt^zTU&!*;+L_DLfgu&WGf=O(o3;%c%2@GE4 zbF{4JqL@u&ooLyHSXk^PLyBE=EB0u(>pIP_Br)WZUrX3QCSyKXFrIOxiOc)e<_^o0 zUmE3FBQB5RBHUjOp1G~RVD}g2Au93d1aj+aL>1R*iusi&z^%qqjdp36$7C{MHUt*r z7C!tbu0^|aOw?^c9|elEzT@l3w6VLIs~3|XrJ#TP1&oPtsl^02bzKt~rCix}VqNXT zWwBQL6zl59yevns@sFjoBm`pkQhE69lm}mJc1pY}ErhX>&EVGW4x8JK8AB%HzP7US zYq`)1`DBiy^Lq2Gn{Ef`JQjAI1_m``Js2WDrr|2t<=xjP#@e&bTwsmk;%{-y}U9jB%%c>3`YmNK~N#F>9`4!{Q>{VcGP#Z zVvfpH76J={!xJXgjwEw22TL13qAO&wmjg_cmQk@L{n>4hqg@^cx;KO_?031c@O<#W zhAy*MLJ3^`_#P@PAFe8mTx}_)<{iQ+uztMN*foi%PbQ90n06z7lCuY!xz5ncAd(CVb-aaZG-D={u?K(! zK?XW@=rK<%qNuHv6Xk8hKFIqv0xl#&h5J+k5>Le}?11KxAN~UNZh07o=irL35 zZ;MR%mzAzYlJep%8OWp5pX-viencfcu%Z3b2E#|rtibkAxz5qdexelTbn)8pF)|qe z7=;RY4M+z}Dwhsy9yq6RpbD-^E1>p+dpg$}fyzIUDbE;OF9s?fahK3$>|*wVFr%xV zO!>J+*G#64v^>3^S937}VoV3~nC|7(TozNQnkSHYDj+W`Zw>_Yhq%o0aS+hAbA2qo zJ?psJ4n_m7l49UcD~(7I8Ut^%ca4sd&0;UMch#VoHwiMX-;+{Y-ILAT1w-D)wsD5U`KajrzQI%Tvy!U>HIC|!+?CEs_T3e2J&?@%TE@quWU~a_TO08C z-I#mQ70Igi`1usS57GQpS3ce1Uf`9TO+2*CIKoV}|7)(Q6#e48z^gZ#B_!ZNf7fC< z^`7*Cqi<4OBv6PJ&Klp7UT~~>kDJJmYd0h~cf~cUuc)4s&J5l&?43)rZ+8Q-1Go z*DXnTu_=7VLrL<7C+7)diXe=jMDQ#Y_l7gHhu-x0dm>XfgE)~lg_AJLH$e}vxY{!G zL!O#9g{qn>%em}4kg!8Yj3M3b&y5`dKp!aHD z0SZArep~mxzZHnV7MqskDxsOp1R02)?K;R5ktujK-g=H}4z-yro#R?bi3w1gOgQ{jJW^zX+$DyS z^IWe`%zmC&O9}8==oz9WAA)ES1U!pecbUjv3CwW-d0???Bojj>WB(BemMn3-A}J5s zCnoG#zWs{7a&x|bZP#W?m%1*~jFxN#uNHi_+|`+Rkxa&oYr)7|R}*o0eB|ZJT-PP0 zH(4Hc?$0Y+d6X6`U+J1JCX&p7^gPGP@;QDCkY-IHo5H8MF0OWUV5XDFnBz$t$D;B+ zju(^V1&*UoX>TAi1yo(_dTV8`3Q^)lB@!5U3C430#LHq%2AGL?m1_~&?bR7S?FQ36 zbS-2`Nk%2Jso18P-%4A{>>#D_xz zHn~0vrEl@n{1|YZpvGgsv0tTQzrm<4;>yKBpK*y0-hCZ)&ZpwFa+@gVWZoCMje>^FG$H4nV|twrz8X+tX? z0QC8j_`0ZO?z^16XTReBRnJ{dv>jCqG53#74-6pm0Lmhq9`M2OrU;Iaf#I-naCo<4 z+3Gdjl_|LM4AJy^LChD@J>#D?p3PBbf_Aw(+JUvT-81lJ;JDiEZSXlQ)FT|EhsMoM zB%V|BRTNf%JJ=^ww62c(0hLdX-rYGTfp|yJM_SoSiV^mnE6CzHgC6q$YansH!0O)< zW@%46|K98)9*HIQxi~Di_QrvYBNoJRmrE~^jpK8M=N@oZ=gyHilCiNCFE!Z?H#WXi z-wi0{5lIU_MU({EH*}kr7k(pj4i9gS9)Ld^y4#2eB#qUPYwU0Mn+D+C_yy?X*Wu!o zz3C>uiCj$*VnyE7)Q4HVaC3HJ_hXvw$W!yK=0$=UyP9UdNnK6--~Ohnk&kFV^JKU5 z&=-D3&iD*E<^D3j%iDqUyL$ z+!^%lcSFM-!oBbvTi&Y)j_TcOnMn9gfm<9X>@c|BqQf6@E3DyUwj?qb$+r~xkc-AB zqO2e$w;Zl)<8DlYaRzq;eeV*t_w8usUQa9dW)uV|kTf%jZ>9y;OuTF}K>`pjndoR!5vS@_b||Rbbrf?Bbmih>(NAtuc9|o+&4nwW_a^f^rxs7(0_Ia0X_^r z$D4&xa8Ne`#CCPpX9OCQA#qY~@o|L*u!lR}l`=cbf@S(_4ZAR?K zd#XH`+qwTP}m^RSv>!Fgj|j|6XZNAY6r$Y`M45D>`{~ehW99n=7y=n z)1Ne4(Y3gxZ06Fl^BcfW3;|nC6jx8$U`(d_AiVwRBMlhEHSv-nNWF)Y>73uCr$eXV zd~Y0$EJfs~(fAZE+Ye=c`C&Oapi$Ox6)8Lca@_@y#) zy`Y86AZymjSoYPW?wKJBOB6-d#TPL<$P^e}aBr@`Z&F3CaE}s~$6s6SnKG*dbBrXy zC&gIMa;3YMO!@qk?xxIDnexqn+bAxN`FTVZCHdK~%B>NX$NWs`GOG;}^#=(YdWME& zSA5`}ONj~a>dPx@+{2j!k^p}Pw`H$cooN>KHCzQ$i{txM8toL{T$SS#;YwJFO{-0S)R)qCoK6~*K z*bpOfpL+^I3~*j(>A*oiOWlxnk&~79?waU zd;tEw#l5ARW$U*GR@EhyH zAYz%|%opx~30kF5tx;Od29;W`(V<&PMzc2EsIq8udW+h^X7v1ETxf#HsxVp7l`6eP zZ_(J4Dx=k^)#>#ngCSj`P%FT_&<|qSKF8-Rpb}J8h1R0A84U`PMx)nj&04cntv9GF zYO7ggG_f1Ieeg4tSWdG_FzlK;HL;v#6(B2jo&x-J%^jYgGMlw3v(~ECSQQ$T+G;Xb z%{G(PW>P7QdZUq-1HPH5Rwy+ltHGkt7|lBPZ-qf=vTAH59Tbec*L3v`D#2hh8VwK% zrA?#I*wSIX-mJGNOg4B4#;Vk?X=8uz0ryg`t5(yd$>_fs1%Jl4~s zuF|4ZYW3+VrPZX=Xtidu#%eaHRVtM--DUwB)_)MsR{eS2;Lrr4E?oy%)2kE)1-zQ0 zGFvQqt3shkS6Q@Xqn?+;WK$@0W}{AH)M_>9YLm%`YS&rJdPBM~-N+s;SPkU}+NeQc z1zGwv%DO=t1X-6B89*;~br@KD(p^_=Fe;5oWh=dM)TGuEhc=ioqeWr^t5#_+>(iBH zQ@T}S(x}ZAo64Zln9b^RtJ-8^i!`gDqLp)d4!}~e?4^A<3#rVYeWY&yo9xzS;IP!* zojUg%R*q5{#HGu@P2FH9tQ_bzEsBHY6HF)#d<<@Jvw9Y*L5(_7r-AqXOd6e8t+!aT zMvGBzhA^>NgVu}>O*H9LI-60UGTT&UXgIL5thRKk8LDEsHQj1bu_=y4>!}2b#;DTi zwI+i}W7eotT9etR*1-!}us)b7NBIZYDgr8U@enslwrY=PVv6>6hi zYqY5iDri0?g~G<}s)*c#-lQ<<)dsCer&MUn3Y9@&F+)>SA}Y062cY59U^l!vFQ2NX zuqkY6lis3(*UA(&g8}NX&8D`fZ7S$ztek2ll+!Apj;&Ib+bA_{9x}1lfI{yHOR$-t zA?OTBr45>x0(OAStk9SsFGkp`R>yg=yE8u+0-c`9VzC+Z8k0_~QRwtWo!MZ}8Fe-t z>>6m4?5>a2Kxbjm*_2wdMXgn-HF|~BU^AHX3XM^(gCeP{DmEi;)pjbeoMsiE%=V+Q zycPlVr+biEYtX9|hE`hAxK!yTz22&`Le`*n(9Oq0KNk%N ztrz@eAIPvRj$;+s^RlT-L-0OQi;bon#ng#QYs-NRni$Y*S`?pHj$~?ZZ*$H_aFX(L z|92?+cPI-se*Qa@`G)}i4rTuiW&aLk*8hKovccffuAVsB@u&3T0KO9gAInYpsDn9i zVCXBJndPiMEaR4ps&@0Vi4XA7Iev{EH|Kqg9{)q~8vU8*-Efw=FvMoc$hDt^Q_F=- zK;0#hwtS5VVy1=#Uda0fk zR3_+=>KQ~W1bL~RDbxv2x0k0aH3|&u(c2T5iFnJ#Y-QWmz!xL4?Pc)6uxvZxCEMN% zUhK-Y_kyRNv+bGi;AggdAw2DtZ9f6`U$gC_;2u)89W|Y8?+4q;wxbraaYMu-_$SdM z9X}m(3jM-QfS*Rc;CrB%FWAqZpZIaYv*;Ioe&`(fh3|BpN5AlC{R`+9J|27#{lW(# zFQH#}?iBq4oCe9C;G>H zFYe!advTo*z!>k>W9NOep#`;)njOWSdCij^O8>!W9PteQ*#G_+epBYQ8X(GeKLJDz z_Au2RBJS`CHTnfv@_Ue9T!P#5s`Qw9kUu~kevp6K5KkV{@UgFY{2+f^B9Q{~@E%$v zcF9oB$`D3L@GocxYQ#TdzCycnqj7fc?#xIBDcs|VA=zbN~y+0%#;m&JA0uz2ju zP=5k&&f+N$m&bd@?CN%TV zuOKaVYT=F1o;A!jWL0>ztlJpRJZdL6JjSz!*-7Ri7OVLh;y(fOC7{N6UW)&WC@J*+ zW019CacwYZoM%6M^)Yy9yyqL{I#Ced&b>pXAV}%!j{%$ENf4KnG|zwV~v%)$LRWVxpkqau?9VCt}cF85?fh_I1dGQ>4yI*Evoeb!-{uk`381QOO0WLU>r zNu)3WWT5vd&n#x7s3r966f2P;6lObq;AucH?+|(1v7;&A%hj-&DP#sds()$2=S`V~ zWHR1mnDPYdGG@OnArPxXYfcUkBixIkN7j07Q1r)7(2JrY2{l&wQ*h_BM0I!#5Pbfj zM|c~2c+2$->2IEhjx+5b=gN- z+tPcUNRKmZf5L6ulMivovszZE*q$Jpg$5BkbiM|Z=i_3);ZHo~IQgD_CC`(^RDKEx z_y~y$VIqkXL10$zfRh8J4v~kCNfBrd<H=khhA-h;0}330SHN``b;)u#A*ULK7j zA~b#ojK+Qr4dFEXoE@HCq10_e&Yjn4==kHLudW$@E6&vr2p9)S)V_q1S! zlSF8o3xTzBVZW#uO!46fPZwr_lmfQU;iPAwxCO{oGSD3H=)fW1t`2&i^29N-NlM5d zf70h=5PsUTO-wEh9)zc~ML6Rjk4*9T7v~udII^uTqip zK~x7sU&WB%j~GOP`j35%IsAo6fe@(xvjoQs#$WSvg)d=ZS{{%31TDrR>IJaTQ4~Ww z{#W4z5S{dyaMzXO*VhvWiX_=AuYshdh+d<_a=a>%BaPri;*)!EatJ>8@=Z_waB4gv zZwn-!xA#HZorieL3!rT47j>a$z_*+1FMxZki`!K1k1Cb=<6cnOhNX4A$1?G2dp!_i zq(AQXoc=iVWumi5hm2A9ScJmHz$mQeP!N3ahKHWr6r2%56#UN4`cPQTx4oUC&SbAY z@)&69Fd`#gMD458N%f6l>8=lN;YdKs+O zNU;unfl0;_r!Ex0#`csDTrErS(}-Z#GtW#Wjv_i*Vz1uUHObn7*{gyoLM{w{W-2IsTNB1D$V+C4?7H1gGm^ z^TY8!dZ?Wm4EiJ#p~+0yYdbneAQt2;@HLnv44JGUvFHnmn#9ra2ADw*V}%+@V*?~^ zX1)dvHz}$U-qcQ7AlU;xM)AZ^HcJ>eBfW23U}?rHmo%g{dZodagVz%rNepC-NSu&H zMb9YebCEbKL5#)u$WNR#NSwOf*Dhq41vnUz&vG`!eIb4Ag1$_Hj0&H3tcK?@_-hzt zUT)EGeo^9kG8-|i~B#MsXYzg2dsaG3cmf*o`izTpqnxW4Frny72s4(fSu#BSAx9h7JQLr-Dv>pSK$)|nra zo*apo^A6JGzV|N|WkvFgAe2NQE$mV{DO42j)DI2Vr}bbK?o;l953A2EYF~lw7#i5N z2lEZT$Wdmpe=IIKRe??m1@|r&^_6u8W27YARum;wpiQA5>tRuvY%n`hAQ1(#ZD1>K z?m#sL8yrQk#4M>^s0d>`Z>WvLCP9AwSoT!`WpHozr|AJghJ$O1K7k)QBAde_`G)mH zgP3(>G9JlSfLA{(`d(6Aw6vQFgmwuL0-JN?jo6&=?M3`z@@}yL>_R-q8}(N(3o8Kr zEXue|MOmTrd7hfL>N5m2vTEvEDf(YQ^ocpDtmXb4qb?K~wIB`^1@7hH;2~q&_RbL% z0t!$N&xyVajUSRiuiBpXY>t1evn-PnyYBfO{aQI%~rNy}VhVO}7C(y$xNCUkAay{^> zv5wD?zMHiF7)=#p^kM?rsxGRS||lbbCGLCtlrvEFX<%n3I2nRDkR(Hq76 zvp#VDtnu~_R;)(h#j`<;@Zxp!=X?#kda*RMJH9nS|_*Zk?MVB=mn6XC>Cy+KjD?`h99J5e@E#O0w^7~ ztCY%cZ~bIN7k|d2L2(7;!@KAssue4kfn>6;+z%4q57}w96>N7(fs3_G(zmM z-j)9*1@4x7Gl2cFcCkH%{=Fhd$uE@;mz(kMKd2~*UhYAihfXm5JgQq7y&T7?D_Utk zg4pxAwEt>a(tywdSwN^{kday}>}od+57@npU=}&vELIgSu1Ix726_8^Ql>+XzE^bS= zgwIBb_jVeE`wvA85F%tBJb(1ESLlRb(aWQrUN7C7+9c|f4+D3~TE0_QWv}ApH1!2X z$D7-y1RXZFkNqTG%S-$}S(vNAouFRcw>U3e_C&{HkT!dR9?b1m{2ucQi7RxCsR=iU z6v5VovA7;6+q*oL&3(1_ONx0+6y;vS@o7yWe+Zncj@y|aQ-lUUhXG#PlL2};k*WbQ zjv*JsKOYiTDWFMIgIU-lkjG;;yk0z!f`>*qYQ7Iz5!AR3YE_bIUA0Q0;a#3fyrU?a zB_O0kcbA2u9ynyd@|eW(yg_gz@p*$edAvRkeA}ipnXQ*w{JsuM%_wb#e&*_^8Mr=h zC_b^e^eIJOFSOx%;hjn%5BOFk>;bE%qn4x|a4-adSeU_!2CpM-N%MQ|>6@C+2YG;s z!~nSh1605PB+TDx9W3r2Mjb%(G|mYaPZSx{gkjk2K#&|_RsJ7uJSV6gx@9G{i!9E zuv?!6-nm@7Ex=aM=U0lC1~{`m>}qiZ_%1>Op&!VNB&vuMp$)-ElEOjGHadpAd#xBg zQv5PeR_aF@^AM8taXYAFihm0&K=jHj!rO?$VX#K*bq+-h%7;&bV3y!az=>PMS@cw% znD-@92x9C@%n?#wGAM#GA>N0eIFobCF42*Zhhq8Bn zE&h$b4f|gZHWXUpE<7_>F>=+thgN=GDXks2f zRu)%)AI($LSf^z+NGqV`g8u8bn#JWMQ?d*>j`5){QU(D7;P`N>Fl$Fo;L-ny6uFY! zhzWT+*u{y%pY{#kxYbJ2mw0O4mz*c4u?c(^DfK10UqObOa;a=d8#O z>Q7~|9rL!fNuV1tffao|4`w1qnaMugv-Lp&tziNy`b8;;{p!}l1iBLwSkbkSoRTFn zUPZ^-mvtGueMxM0ROAYXCU0b~2GjNF6-ye>Oa>H0&~>P31DUC03f`#507D~6CX0(= ztzO!N3I&P|>)J63{E65PB1;-m5-Rcb#u8pm5zF}Ds2))zKQSMXmEx0=gDaP)m;y2x z-zoSAT&rBtL#F(&DkUwL?K0)BR4ExLE-$f~968qT+m?z`nW60YswF>B%yF`2pP8N~ zlQDwF+02-d4iW-Mi_7I&3}UCwxDsTi!s~-{Xq4AZ53gI=IU*{cnLdU52_rsRxq3-$ zimuBOPX)>km-Zluv6Y5JNv-rLuX^MRj_gODLkTikovG=Qp-=MeB)YpG1K!f;8d!)< zFiRM7*|xPyhSGGpAVk)g+1(?D6VzCWo_wDD;neZYjDYlzf{Y8`B8kUpr8w zuNMPS5=*WG2rJvxFM;3TTZdToPCHOo8Mm59@nPz0P%=6|R;z{>Q`45udefha;baLw zBvY^wnB~)nB}pY$DEg=v&O-z>hVx55I7=X$gzJ{)9qWU9Rzg$EyPxZR5+!xre|q`l z7l>E?P}&+el1p@;uvtkK9bY-H4?oBoT1;guawc2Uyrd6BH>n)hhaZ!Wfc-~Gn{myZ zYEd$V)>jVf%+Ct6q%)_g0;*LB8Mpk&t0K9HNTS5~axz6w2Ug#@WN-*$fdUE215ctX zVn&lGzN6w6@PoSKHF0_5jS_ql$g4cpqV_=aYq71sK21qJGoP#(E9yKV#mCttZAnjx zSw-YYxsTzR6K$vLmLIsC0B@ zmB7y6sFWnSxa5(BUQ#8n5113hb>5p06S&gkJ(E4MiZr0>%M}m>bR;~S6ChIrEZN7` zOGePlm#AmFBM1(f;BDUS%x*Fn2TfnH>YqzyQ(^*1OwyLWElxIwm98AEPJu=i3JE`d#_E z>K8`}C!h(c{OYqG#6MhM#T@Xfv#kgYBtvO3%);iwE8(;UCCex(6_E$ou;|A_-JPR` zo8%8m9#GU9xYcqtEQUyFpFAoVNl{}7+JGx|Hi4E@O}M{O|8YrMT3uCY*2z^l??(<( zB!WRS6b$;yhiT?IkOa@ql9;X!jOiLLrg+8sizg+M(fL_YC0K$OtHeistgnHr6VVCD zwXffCbRwIz;%uo9aAWSTiMYQ^Fd)&0GB5YMMs%f1H-yk3(ShAk7T+r`MDsDqn_;Do zLg?7&z;0=gl;mtg>68#U39kIW({-}D*Q>oGU{~c*@9s7AgzNene)yIBovts(GvtXq z!;8tEB+&z+MI+OzQ04%hA&rBB_Y98c(in;!&r|cRVGKcy^ne-&?lmZlCC>b&A!&VE zy|R6c*D1>prAS7Ubz)Ig6U<0-0(eE?b>eVb>6Q@svmiS0Dc@V$ILb`+S9OW4_`v! znBO>Je&+~+0ZF&R7gET<0oit3R3wq&Yhtmcbab42RuwG<$3$;~JIKb;Bsw`p zB%rEULyHVMq3Kx+tiV^J-&yV5uiKn3Y zr2E8Up}2%1=T!JInUo9PSby$q;zm3ps3v(7c8gKi6&QuDxH`n!#Pp?@z;VV!{*|Wl z93{U`Oy7er1UkikM@oXXhiNJ{@bu>e{xPQW9Dv^G&lwJE`ddH6`bvy6-jV+T$?Y{5 zbSUZhcZE;!tVhCz(J_9q_XLY$r+-}ZN?Z&w2J0Uv^EypTlATJWp-4A z?_HkMI9^1uN^W{irU;FI{5_=`!$4^Ldi(-$73@CsyQ1-a{42dy-6;?UG7RY7^z-U1IZ$6P-EZ7?>T`bt+<(!Ma09-=6N|(h3HkLMg zA79`IGXY#Ud<~5GzElNT94W1XhhevVK}*o_aOnuJbliM~z7LfpkRf%HRtFaq_fs^; zIt0T2e99%@5ZqND6%D~>W2Nf}dmyfa%fg04BFK%sWQw3K?EK@UtwNaAaijr=-jYl0 z%dn5rZ>1!7vMJNqgpN0A=o5gz0mi7o`h7)Ay-M}P}e5usP zj3krsQpa%c)uqxE;_`TX^c}LOZ+&z)So&jWZE<rlAivj(wU*m3bJN= zFc&{PwvJ4Oqdxas*$Ob>dTEZBM$+DBx%Ti@*^(Qj?=z*Mdd0moPL34c2q&2ra2IT8 zve%aIfIR3H4AGBZ-uFshVw#gR;Vr%<;MTp;8B7y01NC97Z%utZ-vs;=FdRWr;uDFo zKKQve5xf3cnj6yH+vcNROWQELiQ?RAV*iJ==KznY*xGv&Ajw@ykR(7LjZg!DAe{gS zy(NTR1%lM2R{?<#dH^FOFi1yHQ9={gySv!}h)+>OVnsj%}fVl1Hu7)BM|LgH0ba2L$a(V&+pKBSPlS}54Ul>RqzYdfw z)B)`sn>~LXw@H@$Ixh7Fl5f!T+O>Y){B``O#jQgnx63)uoxgEgJ79)juj|Zcs=q%v zo`qL}A+E5;WP=edT?vM@^J@%hA=}8r6gJad^1Vo1;J!_YF}Bc~IEz@QIz7mCMwamD zcG>2iU=4}lc+@t3i4;Tj%}6b@{4?V;apXUiv4u#M#-ub~*N*Nihzqqfv9yB8R1+Jc zgP}I30I%Ou@Vc4s5)Fmt_jZTEu`qH_{6Sk=d`SV31wSd6Y;d_©}=*34l==_Ad zw$em_NF5_0b^{`s>iul7&9OWOCBOx<6ebhF1YtmweMzaJ$Dl^K`(l1a%O;3HyRpwj zZOT5Gp2#i8Wxxun&-(kWH0gDrK6Q=i<1r$Fre7~#NlmL@t6LqL4i)XX*DWz9?nAjg zVBnMyE>Y1Obn;o0CY=!&FchezqBgFBjjeS_U<$XLIt_iclY|yDv?WS6Xeqv9@c$-q zGq#_vaTc|o>_)brUz9Isy{3QjIE$m8w%& z*N-=3TAN!n%<|W#v%fw8tA5k*K6(9h6;pitv#HdZ?QK0Jd`uPdUc!7@Po^m=HS8R8 z;2NG!b9S<=LW?`u&Pm&7-5)cJ)<+bg|n%c*9T^?G+d=6xxAH&z$(hJ)gNL9qfj;Znw8v8NcU};6|j?-uQ+a8#V_@@o9 zO|xvo752wnItRH9r1+Ic%^Ya^O1A6)dD=DYLx$Miw7d?J>2PZg8ave1$N>JWp|)9; zqCj|c{V*H8t6f)s(4Shv#0MEf)2r;QqIMo`TOwILhE!?Xqc;Ozg2|M*kI}OuZ722c zLRtAnWs$vq>gjCTb3vA$AyFEY?~GWHYWWi;lc+5JTm=P0_!LEoc7u$r_C5M zZN}7R#>|}AVAl9C4Mu0r$}X^e7lIB=x22YNMbqM_? zh2&A%ya9iWx6+I1Hj+eo7Pf$V z(Q{y%$QRx1xS4#>-I9oW(XC=z$QNBKd69h4$2TP zpE;-?5pTf`o@4u0hv?Vz8L#IJ$=!-;sH_~9b%9#+}jCw@Inuvb^11z(gmr?H$Qt@`|7n)g9GP+)7(tsWzIm z(l$t`%fUo?Y{{_ZW9hxI%9bg$MZd4I^;Oc$>9IwV)W_1Rx7s#S>W_A=w#`)rn$u$o z1AQMyPyJ;LmY*`koDv(vSWBX`KFZmrT7a-YW2uMpZR3J0t9UV0HTCGY!8T1<$CLf) z5sFG}wDp%(p`jaXdkqll7uXgluNWYPpg#(1y@PO3^kL$%u*^^-g-fxh(TURK(aW1` zbrq*bVC~OK!cfd++aPHY>Q!-RZOMjC)?HdjpptSoBm#|#Y!zX^SQN6&Q9c&wQicB# z*|OwS(KPlbfG;D3XYXAA8CFH{Z#pB;CtGZ1m3x5xo)kx>d@CCL`J%0satmY_m=SyL zA%Ln{xYgE4Qp#1+84$D6^zC@~5r*=&+hQzX9D=pr7u#*~lo~wQ--03Nr5(238e$YX zz8Hoo?zBCxv@is}z0)>84y#6n@j#i_0}+5_bO)b+i~tG1hO6(k?NEm5$!p##Vh~RS z2zB<@CYogJ+hhA&nZdEB4*))iy;A_`qLi1M5o*}WwjU*VaW#~FytoIb%2V1<9w5-F zM1cg(8TPBLUHHWxdR=urMBgdcQB5})ww3Uvd0~`N%K_ghKsbvJft$W&yD7_f@JNqP zvf<8AfE|C#-dfs)ir=uo%g0bPt?LeF#0+^wM}D(gV-2%Nh3MV!y|ga;?ftd|CT+L4 z(DsUQLoaWw?PCAUQ=xHetqmSx#BN(LH=#i31y$&YZ$;2S3z@ChI8yGCklq^Ctu z=_FWrlztA*q}4W}F*=ZjX1j%l@Elldb-$5SMSC8d7^BqYDTrEgY;|G;H8@w}11Zw> z%|Uc3tMxzO${I)m1QYW~S?JL;-`pS87@q>UOfQ~Y%R znJB)zpt?BiGpo98+Q*nZqVy5QSwDVAIS-iYaaR`y_fC!7=BRkaX8f*vvF&Zt|FEOB z@-bjC?jyCPZ;!!w%DEwpFw8t3G4ec!V(T{Q8LiwAN zto1BW%BQxDO6eG$5WiQ=l>e@d&VP#gM*?I5>i?Ooo>JKW{NiUgHbHQM*z{9?Zm@{A z=5yP-mPVW^3p|T2*d{A2crpk)ZN9+cpGGL}3)^r#A~v^pROzCvt%Bbm^4F5s90o7E zXsfS)a{OT#xbWKnOi~4YjC}8FzVDk$wq+*1Z^32TX=S0v(>%2GOIs&p9!ST6%Z!-A z6SzA>8CP&9Gt5#yxMFJ|D?2%w5X&-3vult6x>hlez>D%Zb$oSG@s?#|djh#}UM`B! zg(o{H&e%wg<18MY`hH^@5hQ=Yu$h$>18i!g?igyNU^VqP%Kgr!UrjY+mxiZE!>p?4 zaLD!QDEEf#N99i-o+Ha03CMkRXQ~nu%N6DBQ@E@3XN=Z?gW!ScoKYiCqUwnsYzKmr zXh4ycGwo4+Bc%pNCFMxbDDk$fC=hyax$(`ErUG;jCW=OEET4$Z-n2b~{@zi(tPazF z!J2^#YR=eDP$>Q$op_}e&ku{$HS}P@jB!H`z*)4R>0MTff3|%g&t}N1oo4`K+Rnpc zMQ=PHR_Be4`J-JB!z{nHHuGs~fM4DfEBfW_KE~Ok>!BAmJVL#Gx79`!KHvEl`FcvW z$BJ{X{)nBC%A|W-qm!fNZP?ILB6x9Xql-I7XrBmwMrb>0&cq^NXALLjdvU@?43*uy z;deqS7LELJ=L7AlLa9Avn7jsup7xEACxdFE@_IqGM%)$XzQrYwvG-|gTSKZqDxx~NNH zq&EphYb3ne!O{A$tGn~DM6fpD4otXXQv)eZ)VA4LKHPJ!fVM43+brW%k4ZrNYP@<@ zxkcKGb!BMB`iD4F+N$fAOlB9;ttGvqL#IA9`}YgsOU4Khm9aPu`o%#v z>+c5*B#gZGY4Y&zSIDW+7@O*ZAH=RRF{&FplfGsY9KC_r*g~nx9rd$IyVqoGE_DS4_;2Xu~h%b zOBiyy1YH*=m6T!}HCo~JI<(1i^{c4;>@ z!Z_>Ei_{&7QA1jS_H0$*#88fpTP~^@OFV5EHJT;0z{)l4UoWf zLmjtAeOgk!Cyl~~xwsN9sg0DoAeD}FzfV95URFB=g5P>st)m3h;6!}j)Ay?Pbl?V^ znvJZMfI-^#jsyvu~eUnVpxHsJ}J9rV}hI4l}xEqa6MA$_-E6p{|`e%A;>%GiR2 z;Vf!FWRReKwO@^wq~|nb77*tGWNJa9Yls#!tcK2ljM<|B(J;&JF^=f&>ZcXiudB#D zz>DDfU(qV!kA)2ntFMMg?@)BU`wpDn;ojKEG~#p(T`W9VLp#57fKV1=;VZbxq7A%6 zxci@i;Zep35fcoCR1|;eMDc(WX56OtHEe$vY~xbf2FX#0=8h(a-FRIok(P^(gL>7& zL2{i$bN5nCM5%pRO$?G-BvSuk81<_9P|(SbRNoO{IUE;4ZdLy)K&|c@$oQTh3#xScYUY+wA4wpVm z6o*S^HHMp`?617XHeP)v9Ho`}ITX!Zgj%A17u#wp{|4;BDc7$t*LccR;Zv?>sq*+b zq1m?!lEMfsGdnWj8ezz;y6a=LlB86q$$`l_bqsd{-I#hpbh>t+w)<2Kl9U*LN{7}b z%ARf$1`_GWItG>cTzx7KxWd1K>nkk+p?~~bZD0YU>AFNb>U2S^r*sG4bfPo{ow=ZP z*AX{}a6JMmLL=N`RI;~ECF$c6)6t$QJc3LioER(PM4aW1An5ufbr$;klKMQ^Gf4qsS4$-TxFto(AnNib4*nrSmdnYH`^L zvIxdmv|&kiRsV9^;lB345^~lkvZzP<+DA!pty<>6r98X5xQ0eAM}4usJvm5jUdueV zM2jfx2HUsDa+g}>o!2^k6xex{<8Ub?x>#z7>K0rpQ1%j$29W)K5nVzUACqucBj-X5 zbrrQ3ZvVxk8<#%9e#NXmxiI8(b2MqBeY>&&a7z1=`L#k(%#>R_(21SP$|(3Re?>@d zGHwk|Fo;>L@QW*dWi~*=M%l+nhtTO!_DRYSjzL!}DsfMl%IbIk3l|?gig<&Aa^l*a zp7NvZGw|b1OGex0DerPHkzyN0@$_RUsu#y#-BZ3Yr`49xx>O=9vTp`Be_xfLoV11G z=f>N=R(=H97eE>lusfT}#XF*EV;lPFDK68fK1KWu^UGY56jigZ_jt7u`7#WkkL` zxwL$dd)spxdu|{BJ&rb&_WrzpE7no z;uyRPba0=2C~(&hJ{Fwz_F{M>Ge;L!4&l$^p&3qb#-x}Y+cj15Qej8Tp(wz zZ2Rp8Lgcy(c^x8rH-~P`PhiaV(hS zXKP&)Hu&HK`w#c!Om zca_`L(*zAL{acuT zN5#c28D72Otta{umydJJpP+`@9aYpa*X+fze4(DXQ$egLKGo23)M3}{LxSY*am$!> zp>~TX$v5ohW%>7d=3e9tKMM3B@<&)*@Z;g&_I($Yoajb?j5Id_5Z;F^yK!H@FV?hGvz^@f2eOlpv7fN1`q*rjlkBNfgEdSsMEx&L7MV))! zURIJfF%mv42P8BtPYTfTB%PKUGOfi*4hY! z)`o%a6Q9Cqm^m=;r98BMK`$0+`p|w&{yxcE(=Q2B)cn8f-6i?=By&yw#*d=c^rQey z$I=ru9mq-3bdbOmVbgn#HOc_&LL@70FL$^ zs{$aVIa-jwsiO~q9AqS4{O0CfQa^O^4?Ep~LiZ^2CWRR5VJ6PvjyAcJqe`$enPD>( zv;u6Zf&=P{Dwv61Xad*I8Z$^8tznj5GWhy&?V+cDjvJ~kDr13FK-;xqy5}NBpr~4&bi5%;#Q;}0 zBF_g~b^W+H1%0EwsGtQ{wxWUpDQXG|5`aqVi*mdgXQ;b=iDO+%`7+{3lv~+xCC+%+ z80!v=f)4!DCb^ldu!^HViDC2O~F<}q%NvtDD0pR|w zQ3P+ER914A2HMCPZH;q`k)~~qcT7-b0Fq?U1~BYo(8_yHT?qK=0$ilb{Te@-q;Y<98t-%syS$C z>E)?tXMM*FIVssZPK^}N{%+vdEw{#7`tUW?hHL%f{1`effS;leI%I!02=oF#HpB}| zuf+9>H?+F0k)yPvOvN?v4eO}APDFQ7921p^Af4Llc%HzCpfimfPGu#}(k3kE{___= zDqV71iPD-lVgsSi=axxU_5?y#YU=0|2)&}IqpfmOfR9p4SoS<)7YhkLRl_W(XdmBe9rE){wgjCS@D$0(I_Fw|< zIaY23bx&Iyh?K?vgRlrd7c$UfLZbyb(Jv?rzgvvIQ^eUfA7q7wW^AH&+B<&2?++jE zfZfy(P$uPafXHPIE4mNDTsBlc?dTXKDYF2Yz-lgopQf?8F8wBccg=uNA6y@EMvr!J z+z#5>5Fh>>7*b!^4$7pgZV_2s%8D+~SUuFuaaB@m08L8=}*hj&{lwP%35iqR8w@RybZBZtF-^ul8~r3sN2cG(1pBL_K@E2e-wDOTK8{(Zea0Balv2`J!n5&~Xd7#qGa6!!I(nkxN-60}TFb|D&p#A# zozopzrKFz#u4(uDdp|A=%y{XT*6Ku$-Jxh&)QTs;l*wT%MzNm`1g7=VK>}A9_2FE{ zLrJNc0*n$XDCpbyUK9oBTHg*NaC+#w=V*)Y_w$;k`1*EqJlKSkWUNvtIE#1gx-P`S zA~}m;GnL8!*tB=o66NMN;A!!c6ipQHw74;+bWCWN<+mez&(^e;E2+B|JL05RorU`9 z;0Mjuo}#;#>v&|+aV)*m@kq%Bf~I|;)o8>r$8cpeNT+?Fl{^7RH)*-!IptNJMfyT3 zl!G9F`sY{C`W2379iYz_0;d(n9)5*IY1f(bUg;>5-ba70bab?Qz=^XN;Hj$|W0X&L zvVR6R6xGagbjJ^9Ps_v67$9n0wy*LW&6Mu}9^qB~AVup|L2w_lpd*yPm_3uC4afe) z=>YlA%Tp$-!BIUFon7M?rznl}iVZ?R4MwpHy7RoFeMAWaD?aa-p(L17N@SE`N}?p} zvhdYMCwv+)&gMI2E2*F~x~ehd1;zLbF|h$`(y`9xK?08QxlGbh5OCY zuhR9=-RB%+>X{ldeMoX*W1TUNC;S*2^BA1PWej^B>ix;49$^5PhKI?G z#qcnuu`WCqvP;9mV`|bRuqH?JH8}{F5%y;6_tk{O4LqyjZ>hMA-8 z*yZRGBwuN4K71P_qKtdlfhW{&H8vl=J>y4#VM2ZfmqNCA9SxA?ek@HfN&t~+Q351z zyHe}#!y{%T<|&;qXaAtqi}QYdd#o>K85EnzhYwn&S+!Bf&?ylzx}SE(F-NM>9`kR z+^k7Q@%Y>%Ty;L?xTbtW_+=}y)D4}hbD*no5u_3~6okQ$bH%NyDC_69$^;@+2tU|F zxoL#-=T*6e4xYxo4>>5WmO4&#IKK?ChU%uza43l4MLbt3L9(wqa zwa;eKKGlNiSbL)*tCqLI_oCpx@z}q|?y#sFLRH+i_AIWnXbZClXMC@~e{tOMGsX@P zl(8^A&u6?}wmuO2t>ar`C#63676$_*qbb(~+Nth_Hs5eeRl0$6>b-uCaE??)fK=Lv>V|H9 z@2IDPCT=LUGY8}@z;8i#ooma{CsCt_Ii=KBe{gJ&m1jA;xSlqERUDAidSD>Ipp0SY z$gZRQ9vFRZwxFrb;jAZR8atePoaJ*kb<|b29e)PN2N*VUIBx)K>TotU6&+4~Q=P*x zR=~XwWZFV zzQsBk*Vx||%O>QEHETG|qMAidO8!{NnIcIGDK68i`2d&d)!1gDUJY;N)2sFUHYHUu z?~m=p{EBS|SVOr- z9MfZsYT;+q!Q9yfi}Q4ZVQZs_Wt|@>KXWR?jj-0e!&5=)?l0%uAeBaK%R5IXAgp$*?PYW@+!-bv&~%{{XmcaL^ZFn^PF)Ts>7-{mq>A7eT<`#FFHTlkEudG^z5v+NJG|Xo^bYRknzg}MJVU0n&|{dT zuCDJqEh#}QxQJ*cz;Y=o1pT@&r~=xUjCEQ8`BbNaP~C>k*@1Wm7Fiiy`9{vt==+9P z@v8?SFKp!8s6+N?CeXIhinbjD@U3YZNZ`$f9;G-hnyAUG#?HM;H^2q=7@c`4r)6v6 zoF*v)d6w8ysl-?V*a%;n8>ycE!d+UnjNzDUHgFv}G)bAvll`-S_;T(pQGJ6j20Bt@ zWvU*PZju-owY-tC1fUWfm&deF@BV$VwWLR&*El!oR?tZ)00_9Y+V!xTZk=jMi;And zyoLg}^lz|8vhbYf<|^| z6b`tqW>7NYI`>jx6EviavoCm3hqD}GhM0=hXBJe7e;nfr(DZ>(R@A6h!Jy!`F_Y-z z{?jdDt>^IP+MwApCKOoD6V@{;OZXaeYZm?oC!p-Z#g&vBB!fAMsqLK&9xEi&yKlLu z+O7Y@i#8e>QC;dYePV)&Nv`0H0|{Ku{b;onZ4hxQ^VAX(8>-XMc{$4XF7i;+J2Wq? zG?nEnH9Y^dE>bxCL%8nV-QppsDXH#EtC!vfzxJ_pEwExFB>lOgiWGs~?c(ei^mR4- z_cw)grI{$btFwW8Jq}Il>TE5gpu(=sjuPJG-__Xy-$q@po3m%>#rPoJ+AI`5;9gd6 zf%WgY=zKS4clp=4s9JYt23}CNc6Vmt_op1)or9zxRI!J%k+cDI=;3T7EklcXI7i|e z`oHSoT!2@=hV^s~mrkRip3c!y2Naj#d>S8FUXsZ?vo#^R|Mu#l;j?XHY z_sRtoSeKx2nV6vts4x?kS+*rg|H<7nC!!^}8y{B!|IWnM80J~8nj^or8@%LhT-YKLDTH4Rq$gYOCt9{e-Y`VRFWR+5r8 zlf5uOv#hw#&EH1ngb<2Y)cc93$z)oNT6LK7REYc?Hb#7{GumL|OS-2o>J>Fogb!+qxnnL~7QhW2kB#*rLfGUi0 zdMx3sIC-isQRP4i&ZAQN4a-bwvV4MR=G5i+(P-LxJA>6P$2*6}mO6k4%3b7+N24cV z?QEn={?wKs)lqLvbk3Ia2r2WN8P#!_Oc^R^^@NOR3#VnKIIjn1V4A31?z&h@FG!ts zd0J0(rdbBSZ{vwdV&K!VEK_z$dskC{Lr8d zL0}_F6V-~xu@Q}y&2e5wD`q+?qWRA{t67f1;;8K2de+(1;)KbB3$$Yv9tuvI>pZSU zA$%xY9F*0mUSJ5he zp~T8#chMW@7Hc=1ZXH>5Vz?aE8inVb=wY$61_nYTAcwT}Zyf}LqRo^P26^cfkbDafvE$>pU^F>P=0EZ88>PW_DBwPLi zl9`hVN~1wbormN;tx@ZbPBpUh(-HpO5s$_$b1t?Fg~`{x$JWsgr7d^P)WegO0d5(nlV0qNq5Ni6o^PUC4 z462{~@||rh2Vk-WuingeE|l~LL<~Sj5;V?rOwdgTzpQhfw!95#QlI(n_0D9=2fAe9 zj^0L-H(=Y;!Bf`0-r!tk`3k~Qg?+m<-SeSG5Ll~ez#6$mqy}V`>mmN4aXJYHq|+oI zMWGW}u@%wzYC9WSf>MFWkj4WdXrh(#1Oz!k+TqM5XG6&n4%4Ua`6dw+)i3I1sREO! z(uJe1=)OLB))8tK8~4;-~c zAgb2kYq|~BO75GA_Jo}5jCKcaNC2`(HNYaXo>+;_FDa;5=PiGTH)w=R+5nkY{y8Xp z{PGs^gcA7ctd#`G&?TWrn8I5ZIik@TLxTiLV7xXWo>&sUv@-p&EMA{eh_9DV^J}t~l(CvHS*8XvDkS zhQ6i4xj7U_l5s=d(oxX*^Ugko%p3{C)Lzg@bvsv9#1A%L%oKFzEfh)JJBTO812I{d z^z9scJ{6YUn@nc6F+l~!9yHUtj}!_ zGl}8Ci8d3CiTgk&E;z{rC*-vf={22f_QKi;$I13U*`Sz<&i?pp8x<@QjT<6U(YziY znmt%F{IskYgG4HcCQ{LiE~B1=+sVIyh*sr}t|~u4ZiK4*pjE}ccWC#Q&MVb$C*$rz zJjIwbt41V>`)heDIJL%w{S*^+Xgl4#SEbw0U5`=s2xW2q&<{)>Mv~Wx)}WL_%j#La zBkcJaG(G&SHfbeY*G^|Gd=n2$0`)<&2go9g)&=itJb7SwC#9Xa#<#+GRO8tuhwFbi zFDTM5f*$aE0++%!tn9%Wc8;1BR@62GpPuFt6iyCv+}}jpUn>@kDkCifxWdr{j%#68 z)DLb)EzEaa`v6V)a{G3oDYnu8eV3F{(KjdJfTC|rMQ?UryOHcK`(>~7n~Zf8Ija@D zZaD&r6HK=zs}IDd6k}luZ$11)LQX~!Ix_qu*_cBfqLI$|8k?MOu)I&oGwCwDtF@Pv zTy9hsy%}3nOZrYjW;T2sB2ybaA0X3ru}uG&4V&5b$X#yYfaohamC|$_zVI}2?#tmk zsH;CE6z!GdMrq=P9Ih{|nS2{)m^o@h%_55|r(^TbUoFB>I*BMR)-GBt$-UFW4Q?DI z%a5Yd%6hmIvJ*NoP1MSAXM`zSzSYU{st7DCLK_8z*hM6HQJOZ)*0DtTTp)Piw~^^xL%QmdPS<1n{}}RO2OMbc%-=c0avAa<*xD3U z(iaehOg5-VPZeSB{{u`HaHkpJ(oy=yO^Q~@mWL3RNLPN4rrMeprAw9vFpIZGxpblZ zf-oR{$t$Fq9)k+`x0XfqEpZ|SE(0xURkYOrp;POkeU`>X2(+uN<4I_c8Aes5V!D-D z)LF80hg1a>=mYbpQg%m5yP{=!B%#3BMg@XVey(7p$Yb0jo(M=iSP4n#MP`FC zbx(RxRmrjpGEPVKxgZ62qo^;yGM02ux(U@S%1Ar)s<`pB+(81n`584K+wq8Zw%9hgYad|$cCz$9y zBLc*cnDB(w_T{prZx_`->Dfj8VL}`!%S5!*ah_ka>JR;jR!S0{Y$Di9v@Ibv5v^1c z#SbikCk3mw|9_AyDmz}Sj?xAd{b4rikTtmIl4S}M9M$iMAO%$Pq*a|5X`H7<4=s98 zvMdLP+Um@;VMYBc&%%-bcE_3QO)lw}3_^0az{oeDeH2YEydmORTXNFf8o>-$C)i z4vu;Z(67F3GI_N_p3p((JI4|ZOd9+doaZ-iRB39_PR_0B8We!1hgwbxHRvG_jcjt^EXNY{R1D&ce9OQ!Uj4g`#}PvIvXB->lTz z%t!6l7mc^fhZ%wcc%IdC4z3!$X*g;ofaQkB9Y8elZYYX2iACtn2HX!bW)e-`NF6=B zRf0a}@}^!-4v~^g48IWPalPlmr;_Y4!S(VzMn zJ%Bt3)_-5Ck>C0!Zz&3jmZH$~qeXqdF*)w3UttYZ30*x}MBWA>hvek&PMYoiMaYS^ ze;?OZwEcU8r~k?JcQQsq+xLqBztfIu;qS3^?PT7rop2s)S2oRc!B+IJvNVq1moUxM zpFQ6(TEos!2c0k4TUDA%&;kzha0#vz(PsTv^mS#tZxW-Wq6!^WM;dzF(|$CaFUZy; zFK2WTeL<&Afnsk@gaF0ZoPfxWbAw`_R_mPdWTTjL#8>=+^SH10w5;nH`N_^&L}I?8LT7+YeZ|9oM*IagBA87xX7!(R63Ul? z0g}{3?!eg5j<;LVAUlGaXoK@GzTZuZ3wPZtE05@G-btv;8gW=>T_<61XU$P`A_PT8 z(WY~t#!MYM;@Vq7iecN14!hve*;duiwuNKAppF4(y zemR%aNkHw|xl~JV7tpFl{<@Zk)|MVu1+`0aC0Z;nkNS*YeiRjLraV;%VVKSBFIJ|e?m7<3i z#PS=f8Z1;>c7Q2?%>L!`lr#j>H)b|>(e=SM5_U}d%9nu$jLsgxJ(y zZs{WG_PQ>b3js&7%!Efr)5bMYlQLY(Wy@z!dP4hK*i$2rfTs5_1ypx;mP`L`#Ls%! z+<~JZ$2})w$7bUBwGWpXwSIrJ%gD#LrjPV&(FS%4V zoxhR00XV^?9%1IVziB%T`Nh3=9(NV=jmm>0-{ry&k$v9?WS{M#thRgaimFJ#vH0K z(0h@48KrKb^E&Kfm^rUm&tk#KXS$iS@tte-c#ewT~!Mm~H4wjNCg zE?=_7h0M}TqiVqx*A3Yc+5@xhbGr11)BbI)R788tFLF#Jt$ST<^+HI=Tk1-atq#=Sn5$lyW+bua1oYJsS5FzAoh>}(Y9eh%*N(ZO9@KPb><0z(OWpbR&Hb z`J($eg2@-%2T_WA(TT9qpWpCLq2IB3n5?Bt%Z^=s!(C%3kx0Hy-|HN-s$aX zfY#Yu6D-w8y3gEkKfLSa?BTfc+s54(?QUK%Hi<})%~J6L#wK%cAF8gimS!SBdY)N& z>c6Bp-Qj8wgc}`S$}l*do}zu*;kpna_vuL|-oPo^ssHOK+PU{)k@YQCxr)8~RUltD zFa;c-)kA1uZB$R~0If+LJwSW;v@2g(z{#WOpSv@o=J5pbMT6w1o}p;{(}$zg`)|9> z1SzXI2wJ?zoq&Ek<4RUGfYkKH?v9&t@lE}!(aiU7UI50q_gwvyy~Y>|-gkW&h_T|V zD^al-V3Z}qv0UgK@AuG=cUbnl`BFIQicTrzV^B6rVfx)zXq>9 zJ0l60!nMVfV+Y`7Wl$pprzAKkJKzaXwNnyl7hP}3^0Ey70k|5}N0A<8j~d#thz^N# z?*q@j88kq^`M0ead$stTbDX`#T1kKmZP*Bqz#A6De&sr@*ns?~T_5EM92RSQ?@QrT zQS7DDiI}GuT;@vUvh^`+I`g_ z2_9s;aTC-qWZU0xQ>c;ABUQ^XsgZ#rRa_}%1`x*-DC&7~q^dweH8g-{15gq6H<9Sf z&#o<&y}Y(P$sV^cN+C}n-m@c0n^P)G-kV8JRdI%%3!v&_h@7gDPiPDoI*f&ZsG7qV z`Kzm_x_llh3Og}dBf&4H+(0BI0CJ*AzFL9+9t5D4U>oYi2pln#-vucUAI@zwqZB(8 z0os<*j0FjVb$z(VP*CxfWn{7$TV947*-K}1PxkU7kS-Q9x(Yap8{M2}_g}KykYO{U ztFOmqMpwC)Xmk~N>1Lda`7OcTP)wYg++_(ToTQ&$O~TXQ!VK8}jp^p7c*f>*)GywB z-!hdm*%QToq$c`y0Zqbu>TiJ@fcX@sdmyuPy5}+Cjz^NTDFWTA;ocZ&=D>0sC zXlaUPuJQ`ujd>8_^dny43A`y)wWd2e*m4x)Xi~I#7zUvI5khXC zg?8O?)d;{*BU-xaOUiT+X?-hqF+rlQmO+k$x->AT3+ZJV>l&JzN==O%`IEP0>72zD z!h+^qL}#%HXK`n7wvF3cT0X|GnX@>e$7arAN0#U;Hf04yXwVMaELem#%u`c4yQj;_ zS3qc_UF1tyD5RUagK`OE&=C=}in}0{gdt)T1m%7=cP)Icq+dsA)QU%4ySwWtLB0LS z-25<-`ayShOG#G{Rh0-md}dif7mJRLhL)l1zw@i2?|ZuE>M(^S%`#|Gs-8D9+(=SV zgd(H{=*wR2RHXq(rHLi6e3hw9jDmj2674%AwK-)g2H$8PPLb8F* zivqZmgZd4?CM?iRK+_)OH&XToLN6ZZj@Cg7?Dscj|BmvOo)#Utfv`W&0Ivl5y)&5F zFFpKswYScGza#}2+wVo3#qGD(Q1@*7+&9B!_WP?Io7wNzy+!-I*jpFu4b8J8(?wH9 z1O$8X7Kc;=g^$$rP~!S9rnS{2)b;?1R1b`FJ0&@_kGRC-??q-zX98`hq35VSj&i5T zaz-C5rKW8x^Q{3z6&;ZBECxDP+IIg-qc{jwq&T#*siC$QTA z#YVdwChoe&1b3myu+n06?^HJ7O6qzT8+ZbDrKs{m_ovFsJWCr-(iwpLAeGwD%Y8IE z62J#3ZUIty87-RZo~olO7{xXwCBT)|PX-Bq&C64$YVZSF*Zb%+{2JlFSi`U2EUMw; zyq4N}ntQq=|HZK9q2h0CJ;LkXLYXfo&j$oN5XlYn+F9q$^%WeLZv7 zucgn<)b1;GY!mzHbv#2od~Y&U+{ymw!7Ek7xspdHV;J#uzm zb0vSzkKt2ta#gY(deM}>N z>1$-FwB#h5{9#|6(w-&k7%S}=oW+&)danBgNxs3bnOpw19-C=xabHnu&)^pLXIdL! z*bFFUxuIK@EA|t0wR}IFuBx3^xK~MX5`I!+xOX^sK%G0wJ5089G)(w_I?Bv*-`KpT zpe*W>=e{GS_A}St2Lctqo2t`Kr@%G)i3(g^1JK=c0Oh3Z1b`|2 zM(v3*C%hG}rslhkNXk51L!IhYUFUA0z@)x|7Ar3e6^r3BXHxNG`oqx4B6^lq%8qUsxje*yT|b<~JGmFhfC>nzf7QB9Ca9a(ks-C_401L$F=TPV#1Xu0|Tv~%5Q z{O|(EpaFjI^aDMWZXlKRL@{{b`qPP(2>7N4rKBgwf4&+}Jj&Ei0S~`|((0IdfUXoe zJL5j)UZ6|{&~$bt@3?y)M!9y}yboJN5JSOi+%`5?LNi|$!WyLzA| zDt_JVI~S&$CWRS?j*~dc?>x{!kNduKRl{Yj<4Zj*a~)>}h_2)00L=*Ct}J6_=`8YN zWVKW?hZ!f`c9Rxpcgnq6sW?zDhw?mui$~3P%N-r0#PK}M9BvKI8mrU+sni_eQ2%$_ zNjhk%c?aHc|EjbC&{XsK6(4X)ap>R~ceMZ%^|v$bAW7*Z;&gxCeM*iSNLEf_cn50@ zQ%+a~BGO7I_pCeTG0`>;-95898D)HcCwHfV^5~596rKQt5_-;^E-N`a4=j+a1gU)b zGiRVS{VC$G6|(Ij5?LX`b2PU;cJI=aBUt5nR&l_lW|bg;^NkjK>R$2~X}q9m&z%hK zf>`4TexFUgh|(YJNk+rZ6;4t<2K-ZVKFru3wIe=xec(fuH`Ggfdndl`j86-(;jjG@NAxwKICE<#H|6VGFzg%Jy3hi zMJy!&(Z^h301_^0eh?{zzTpB&L8QqNxvuUBtPhq8_9N{5mX?D|_XT9U9EeL79upE4 zWM@A$x^&D!McsQYLk7|JTq0(W46(kbH|iCiur}^-<%(~+@EZ9<1{IXfV1fi9Ulv5VeCOV6 zGNtwKJNKz5<1JEb6CW+rw~3GbA#CDvw^%`HNvg`=ViI2LsVpvrp8srJsf#*BzUWHkaq>kc7j5K=jviI=MSGBT z@`d{=ctfCre9{=}Bwyum0oEe&MIEP$eBtIpdln7N3BoOcaxRzEcGv~au~iFFzq;#w zqm+DJGgYw9ZtVZK&#v{aco#v&19!QK9}pI3Z3=~MvH6^u!%txJ2FNJ@V| zB&DS%0c|hiS)x1*Qh9}@gm?x?{n0xio>z2uLR~5v7MLx~M;*dEnaTn^?T%=7K_5jL z%wJF7QejVg0I3Ypp7@xncuq?NsEx&wuWSbNa?9fyJg|7yDLX)FcvDZNyqU`7Nlu)- z@vwoGoF4fCM*xaL9_NTgub1;Ik{qZ`dCYzhheNoyeab12KuanTOJdJ&sE;p6?H=yI zYu;A@Nm`{wuh}i=`HG%N$_wTR#_AO<&sMy4xrhg;v_@5iXe$>1;OClnS}0Em;8GQ|FUpgnBTf_&RE|9j z0hq!qOnWNy3jZFsynV-egAGYsE(rnk8KiAU`lO2Iwk!`FLN+9gtx?H$HXT6625=3VS?ui zNiL!S?ToS#J@LSYbq~NIbsZfG$zZm9-kv#eJV2ejth%@>t7rKr_?N;6E+x@ zI4AW9&ZEO(x}9-!Esqi;|IE;}fwAQdM5jlUE@S@n>rkHz2^!Augm(`HthU#ikeW-a&s^UCelSTDCePy{NLuWN<2GQw(!~~Sv&;t*FRvr2uRpc>k zGe>(7@ahlWY>5Oa4Ac;1q<9W06A5FQI@16jIi4o~VAa~#^9-K1=b4(CQV)|0QmKcT zho{=`&HjPl)Wd8P!0~m4Bb$1V1rTRp`24W#smdz=ob)7U7{)lxW}b<<5`-|hNYiOh zAB4LYk?P^*o;i}@22^oeo~OJG5@<+X{O;*c6kF`>B)L&~D^E=w3htV`pU6U8{kp1cB7Owp1L|{p)!k2D)a9)p0^}L8K!GQCZaM(PV+2P z%79GT19>ye^QKZAr1Bofv2@P{d_1{Jdrwyjz=O@vSdZv0t4{~dXkA%C4VDDffVvpa zK0x1aeaH+zk5$0MWXOYu>1=WUVa3F|^u>A9CdooKdb_j7hU}d^AIdWr31*j5AqnbX zh7J=wOy6OFhH1>T=3$KU)Rx^m^MjNZ1@X}n3Owk%7$_wY-_^Dmo=KAO8bB8MEr&oB z(WxK|i*hT)$LWxSHrWdO$vMNuDu_^Lt$}(Fmiz~LxMDDHLa5SR) z&mn03Ku=5b+?W%!Ee$c4UjgB!+WJq6OK6c#Yf1!e<5oZwF!+gSu^_>~7LKFd%~7

PCfA~0bCk_?hNzv))A*JW6IOmxK{vZ?lKaF zdwR)QF;OVF>h;o?$ok=)Maniq@DU?C{V>F_5uUeo#R!_|4Ae~Oyo0knKg)^}kfsjQ zhI)_2V+R{Zr$Wh(oE(Pg|1hndau#GUlp$k0tpibLM7t6Q-F>WQR3P*hV?D{roj~a9 zah~xy=;>{}HPP?mJe?GIIBz*>shDeYck7ILI(W+diFT7yl}ZATL$2 znI}BYD1$-zwG*C^%2bfR0Joj=G|>T4t&WSIAH4aLr%8OX9|%p^|0xi<>$|vL4W&+nd8O^-Eai~_^cl|_9kk!C zhL6-Ys62QCT4nY041m@gYYhYNwG%xlI&kV)FT9UEYf}I&cvjK^)U(1$P)zDsyBlH> z&x)JjgL61IK|EUdFViMBQAPkfrgydvJ$(bAX){a@gg$oO(=HG?uGmvwSsDoaYB7#Y zA}5nAu6 zLqMT~1qLOQ)HD9@Q;+@$h07y#Bb6@*3nsDPGo0t|9-{`IdxpyQ88(Xu_aHWn2vh=goiWn#0ed=&j@sjjXG4(OE1PaK0{bL6$_@bqKiF9}w_ssG9czSo?HkWrNxkrm=XpsUkuB~# z;xu0O(|{pDYJuXv^|Y1~vqkw<%YJ->FzqCGy6=ic&wl4Qt*j-o3+T2NfK;NP^4e^z z+a3T;yX~(E;L=)j?t4!=3xH-L_EtZ5UQ+A;9D5hGW{r!;9q6vA<4CXq$A4%A={G(5 zV~r=9aINWhegV2WqEZ8Nd;ayY%5^UVwxI(Y?b&2dbpGsB1st5YtQ` zOC|wgxNe>aL}u$U4}Zba0Nv1p`<`h^4+A2VIFa`mkuIa?^~aGNIXDomw*F%O)iVlT zjTrr#XPh#M!}%BP0NJyQ?C{5vRkI&>Lhzhn$pk-O1ZS5_kUlIOSUV_RIzT+~hX=pu zv5}Vvn{yja<|}&AM&x|x`B4ElVrzaF*dW^cI4B+nl_`71r#e?kH@%-4rE{fT!jMT^ zaN#_ETu^_0KG5*?RolrAtBbF599nB*-8@{-^dFl|!m8FAV~ zen#*8Z`AWXkfaz?EO`SiK<90FgGo19!_HA-%Xr7iQbU5qUP=_+`Qx~^MBKkZy;mfu z9l#Z?>g2fh{kSj$$d&P1oNjwha571LMib#kl)iRdJq3tKo3;T723qh(fEGwID0}S6 z2g_7kZ!;yBq?ag4Deql?Pjr+lP>J2GzJ>`DrBv`Vk)&KE!ejxqIL@1Z zdc=HPPq_|Ki65s&S}#9?nnil&>QHD8dGQ~UhAY1U6dEcpctMoctpgXleibGHSPMFR z`(GC`=AGE zpF?R?ybI8e)x2eOm;(FJ2JF*bFQ^YtaCD=(ceyeI6pSmC899(A0ATfUjQ0mg8P78j zZk{Y<8c3irS=^?*f}V@_b{An2(7kwE^CgA|vl6_mbO=J#>awZ<=4d=tTh;KsD=AwA zqV$Xb_Y_G6*hDa~fE=hRZe_ZCF$L|3IqmOC)AJ_kXr2E*M#?qu|3`41-~Xem+TOS2 z^9-B0{|_KGb^nghqLCdLt#kjz3~TP+B=2NhWB32ZXwm)u=Hr-k{x$diB)V4L3omKr za&6D#T44;Ws?YN$qWH$%5+;PYifEeCZ$i+FCxm+WF?7DE>=@D2|Hj0{Ts;s8bw?)3 zjmkEmGNOmu=(Atr2rvGrz|pvVX3d@pbnkviuFcSy zy(dC+YVQ@sib4$;`%mrtG0tnL&w0^`^wU?QH{?W^8qV}pgn5BRoxL3;dD>X>DS*{X z!jm=39Q8pLZ=odTjup=uanG?qM5)%@TMu7#JJx)}zs-;0(@$ybp#~Bzggk;ZAV89t zSdwD*1T=Yx{vb8On;UB!HL(WJ;7}Xw`FL9;L^jaJl{jY3csocNG&?fAGn8T?d8YC- z+@9kJKnvBay@-K)#WS@*^SIvL7Rq-ZmFoOgW6>YIy?q10!`AO>q5N(DUbe5dn+_b$ zl=e}Sahy3H;d1@F89GQIGVf>20_s7>R*@h9R1Ed#PtD8!K9k&doX*A?5*|!KYJHqX zZH#U?+CRYCAXx6f(3y>Oh3Hf>nv4@|to}HijhQe?ZfcJ*&I?7m9v&gvjRMA0v+-+D zrJQNt*0&ixo|!rAf7)9~!b5-)!%c$fdrY8fG{hV<@ADn0Xz@O8Wz=h=cPxz!X%}`h z@F&fXca1Z*wDTglmf7AvoVq1^a6mdk{DG#80Y<5 zR^rBUqoCo4+-Jr;*$)Q#PiHb3P4u>wEXf?3&17tugnPlwcruvDNLH&(_Tv4m07;z6 zxM@%v9ikkb;>FtvG6lLqNBEW*c7^HQ1W6fYfE~-LdM6MY?;H>BUnv<~nBiTkOxB}k z##(s-Pyj4W>Op@->szm>q~4k7ohT{KaZt_Et(uJoRZBrCbx6;R*Ctj2!11a`8I(Q8 z+d$bQ;7HG*8zdc~2tMpSs~F%{n;!xR1{L_z7h>rfQm*kjKjt88nD{Xp&hz^*^wTbH z4RzH#Z@D1(Q$~Y1vyUJR>dZXjMQ3IkuXAR`9Mb{9W12(pz1t%?HR%yLIob;^)qCjU zU-N0`?knB~sOn1w=8;?<6SCOo?zZ#sK}lcikP5{8_=59y!}vxCEjt=yS<<5 zwaaxUnEN!}t73lqKbQO;d*2-%Me#oV*-ZqJJ$ec?1wwDvi*y7Fnh=VjAmuK1CkZvu z5eOh51PCTlhF+E40>UZ~a?P&Dsi1%;7wn3P6;R+eGrM;?+b*ELKfgW?dCr;loq6AP z-Zrzd?^gap+j7-?T54oQkxy%oEA?sr@Z#is8X->XDyorThMElN++1m3aC6M_&TV56 zbZ$q6o@%2hfb9{*A)VXoT&Z(&=gOU%l;R|!fzV-4R$S?2_Mo|hY=kS?BpAG&ml`p| z-PnaSECt~UP;cgnj3YquC<&NePA*)TRL(d?F0ag`*v`u_FE&)3 zVveGj)h%M8ibbedS;;0L+pYKOsto$WJdq)MKr$*Zg!ecB@%4gXl+eY{Kk(?h_J2#F zW9|PKG9%Xh_xKfE0;r-T?bQg4rv2}{q^$jkW2M^PV60gCVPHt2=+0x+wSO5e&<-4C z0SiOHJc{l)R$cpFl%N3U{o8;qc2*7qhwPPgK-`|nY4m`x>c+4(GJwb!+K!bPLxZtV zjX_P8Y*~W(|O*G>{ zbEzx)J_TjRx#oq#m31iQbad{SNPnd3wbr9YZoCGC6&_C?Z8w)|A3 zC5CqM=)6P8A>RA4Q z#7Z3tK_I4B#rRnGEz-#p(-lpo?pVT~79|J8&tr%N1u=-fEQ&rmN5QuZKf~wr^E+?s z$B-;ag6SaGC+Pml4=Xp)R6d8ytNsKM8>v3L<{mm*NxtGWX#Cx3zKVFjrE|)mVf}ci z!mkMv%f^vepJtY@Cp_H{!pD{t=uc_*Am)SCwsO zdNz;FtN%01_c7eUs=@_Z_l7NP86B^IyA3JvIk%v z4tVGVO4j#JWlfqs#-sBle}qKGCchc3t$6nc__ZZ#mMN3XT|!XqTlE|)Bg2fN@G4wxTMsASkn31n!j9h|@5WY*9PVSskxi74aFRB_> z>q%1MYB`Bt1m1sLs_EH4_nf5esMhk{p&N%-z}~9msX@`%lhhs3W(f+=rFhza_v1VX z;8?upA$s&A?2MW#ywH;w{&Z_MP+#L|20twai>0H|$F@m0U^BVb!hsN$E!TLO!%L?4 z3LPOKE*m5o2u%jxYw)_u+)$}ZQY9S2eA-&KK73DeUmcGPjJXVh_72z?(Q_eacY>ev zMvr?KAzqjKD>BRKDU|qximn6m*+0t%DlYU}VKm7?eV?@=qqHBnyf1u_~7I2t3D zd!YSx0-mOxiS+t>bt4XcUUm(KUBIpHlPOS3nl^{)yDwken!{f}jo`xdT|l4YmR9j) zx$yTz*Fa&wU0e8NxmEenoV(!PNoz}*vb27bN$We&iVkZ5SG3-GxT5s4Dl2+NwxZv0 zOppbt8N#u>Nf@_vM|Ab^xP3-kw4A z2b3N!ePN#vf%mlaG^ME=4x10aqe*NWw;p>|8i4ygd$(~bNri>{ zj*1INm4M#q9`do?k}$#i8OxeZo>LUe%pt>3cAAMbxvkQ64!eN8(8bf5rdWhFI72Dw zq)Rbo=shn{)SC#SD>#!=oUEwmog-+ZqElNC8?ff8_-hnPpxC5m7=(PHDpFmu=Z6^P zceFU_iqw;*h8#4SB7J|qph(#r0vUAu$>CfsJr15-OeSnZqDZJuIJ@ZI>~{-JZwh zHK`4Wjx>pC2)qM5^V$G!m}Tdcw1X{$aBE)^%G1gET-oFj*RD4)7Aa$GH6HQ;K4wnu2tv z$Wb+#BBTzlgG2S)F>(CPji$<5(>Efoxp~Xo(^c~JD^_{dd3v>^=J7dn97YKtbZefn*lx;<=ICU zPf=g>3h4lF)!QK4mY}=c^8~$iiu(EoBDm!G!?$6=awR_p^mKHQs+rQf9AzDNTPn#n zL^@z|dHR6yzryAJLT&j!i;yW>{x_o2TFvr*sJ8rc?Wt1xkDtoBa>4$OQ>{UHUbF~% zo|k(|4p~_A#vpqvbRF2}FXuu7xcqo|Z8Vs2-2Fm24qW@TXowlqLkKHM?EN}|N-jN} zHdSi+@l*ecCH`Ob%^`uKk&^?onFL;D_6 zJ=Pj7SbJ<)7f`X$w0gC*Tyv~pn#S&c7gf%p2h`J^WKDYy3o7VufyizJT!iB-skYO+~T}< z;l<(NJU{+B5)M$DhlVW9LxUCPp<#$Jy`Lhnu>k;1urc3WWo|F zj}>`-79;6q9?xtJN9FW4T*#N48k8^gjD*|Bdc~f{G=s^JdyhDg3BOj``)v$0A0;)YyQ>tl2>#A!?{%5PZSYQw*P8`^#1!Ey=6Z zys7~IZmFl67#_*Hfxu6Fj-NtKi1m7Qte>=i7)Mxk{AM@%Rhg%R(p(@QxK-c00N~0rZ5#(jm;jT7#{IT z*kn_VJkdGx#WCY@#@``p1L&sGnVRuU`yUPz=SMU|G179)1fLSHo^KGkipcKQPwi?{VHZ=Oom+;=={RrI6d zyPmb0Nu=nIex!~kS|S`qJ4hCy?1=siz!(Cmz-j(8NTbwkg14rtbsqu?MnmmL-K45bthu6*bjquDP-py$rS z)yKpL5-r`s=?BR*HmW4DMUVr~y&dFBi)Ydwi!~yM2vF9D(;V;ol^e}D&tLKMRk22V zPhew>I49GH(@-OXv&lq73ISFI<*ox&ipME*@+|4eM8YgygZab%vsXNIC|WxUpG6VX zAO*knDJREH9AW|M{>rnOqI=K6hfkfAJmKeJ4DuEAYu|YCz_;Ic3h05eq>nL$DZdI2 zAUcI;KTCQFkuZxqh0u_);l4CTwnUaNqVnH|U4isKkDf1++g!2Sz|0>!Ly~o^$4%*~ z)!whwc1*L`tOmW-Z0u~)!!og}ntT(b-pf{?%kg}S;|ArKfJ#o==HOw zXImvgAa9dLtSnrKO1*JIo`|y4cfzxVm-_vzMFx5$Uh2MJ-!Gn8#C55;|7pE5W5ZuJ zmaX@Xvi1H>yxwf(ubv?kecyA^Guw#LX2$dNPwD5ljDZEedps1K^qlmRRzPVeMfu=Q z&;1nL`Z?+0tbo!yf)W-OzR7V%W*gr@SxFAPJ>xPIyTXQ+si$zdmVV$^4|@D_IGt5;9GMoLIq_&1_e^ea4|)!V+g8EpWOh}+ z1vq2xcFVIuQ$on&i$Yz|pmcThs@+wETa2uxhJEaIQ5D?feGL6L;a8uyY zyhZ}!QntR(Y%Lzj5&AqMQL0|pX zR&_#SJV0E0o(hSTdI^#&97a_P|7t_;dChBR9{%){vnzba<|Uic2Y9o<^NHSZVrb!r z=OY>Po+NJvF|UQ|@$dz-`WoXo$lus>68PGm-O?$(w5N2VUX->rHiDKi2tO{h?;^VfZjG}pTyQUl2q zbYl+qshPJo*gg&_$Y6q0UO{jq$(|#9d~*Msf3G8#Q@n>&g3QiT@9I>=4Q_a`9^J)N zR4GpLzN9Hb^oA7;?{}9IEfKM^>(jlbY0YM$kKgd#ymB8{pW*GK*-7@{{l{j|qLsI; z7zv-0O>gDxqj`;lhr6C^kk}fU=w`M@Ywt`-j3v?1qr8@qq+-vRO14CZ4>O*5QlzD* zBqeo)Q#9^E5_1{Rr0m2l!7i+%_#*9n?Y+BWsDDISdV@g5TKW}SbMbxPOZ=LXTU14o zxm}5J*QhSolVMB4W!2iv6?x*;b5)sW3A+R)PHDZVHRwJ(Hg9V^32e+ohq+QNTFw=@ zVr43kE6z~tiY&)hD1XTUc*~^l_b7WZnkC0%&{>T( zybduA2?|K=>0Kku(}p8|Cm*W=mm$src7Cm!?;qv*i}>M~B2pn#Hx zy`R!K@Zc6+U?wjA33{6v!4S!~8)AW!aq9wkOd_SiYf2#-VFl(R zM5ec|W)0blgF`8po8`?=fXB}^_sHSdi37adDKP?mMsPkGK2AJIBH%qiDaaY zDdE@@62aNvDYy>>FRp-z;11Xs)(9aH>_p9z=7A-UOzB?XE@@>Sb9nbsnjo4g99YV4 zg<6AlPH$Jud9oSXTo9acdRK|zB_@%pW)jut)x@w~38m@&H(z8Tw+MkqHUKwa7d8>R zK^!v1`x3}~9Dd$-@EC77-IyPSx0R&%f?Tn!(DS9Xa+6S|#u7EnP!VwEWGqEo-Rp>06%G-i zk*LCc*cDL)_P`YHZi;?StO0Km*jNLO$~0g<6y*O8Z@D3?)v{xQKc%|x8%H>y3oA6i zI8ZUuJDSlf5cG~v1v(Bcmbl>FZ+D{s$^vJ1KIhd^8Vi~$yyU`JKu@w6EqQGO2qldl zFC73sKj%FNy7b#tTReb72lm{X4zQ0Dc;hKBY_2z+zBUyI)Qpi*17D4+Gv8~CfJ)|l zRcYSx<;N1imQQBKvghV|2hy5(>rz~`X77I`mdwvdycC#u9D+esx<^oTZD(fzd~K zSdKUT!C79hx3~sqOb=tl%Lwx3F(rqZGmOTI8bnf<6Wu5y-rgLXFdP$u-wB4J_d`A#Ts@vBxbvpxT{jcg4%Y8D>`?7a5 ztw~r&>YLbqX!tL6kluoO1hapaw}{FBrrlnbrnP7Ubcyx*-QM|hi-qW(pap+pN7xV6 zQ5q7fWN43fIi=|)8Vuc|+py2;)bu5ru}XFW!}fdIh~ekYtw;w4_Io>Oo*?1ppM`fq zy8+_??+7tGJ`y~2!26nJ3<-}fLcDpdj2uL109tkDLZI;}mG+F>ehD^tkj)Z5IA)NNL_Cu<+$TA{M3atdb)G97uZ= zOpj$PuX^XvnomRnpw-s~0~UsCMdZ_;ECf?ecLW4^4K#${_hJPjVF+?%j{h! zb(yw8&JB^r$%^E1$H~fFX>Vh{iTysR3Pl%+nOH#3AxYK?2qxOG3*PbWi=j6~n81&2 z))Uy6iy|2p1&|9OSy!eKZ`YK&&VQin_}?m&CL6DZ>E#dSsGxTf9V%2m(8%Jo;&TqM zfNlAqw-!bJTBv@YF+_p_wtwVZNYjhd4>X2HFz{-IUqQcEC_T`4onLO^E7}@TB;2V6 z*&?W4<8$7xG+h=E1|~Qr3)zh94t{;=#3$Yv3hx!#2OEmBv`@Mk*T<`4_m!pq*)6n$xt zx^gbymmrJ+T2^`2&{v}as7D183M^6{A^Ystj?euCfJ1Yoe%ua!fo$2?)jouk@)W< zDfp52HKHY=H|)vl-bs{(UQF;K+4=i;%1C^iZLw$0SJa?2^+;SSi&AiKoTd@kjMJLb zhmr@!Kxk0jxTu>L4L<@Iom{BZbRyC4BanLRFSotjC@}(_NBhXiewv;n0-9&lPd*c# zCapGd|VO=mY6 ztT_&?U2D-fO$NKxX3&{U?B!6!OO)|BNcUv^foZo!RM?OsiSZeJf;^JH@Ggj8;vEG- zcqZmw+-C$yv~RHDg}U%(K*@E*h}}S0*2;wR>iC!q@`onp0qua5PsUDyL;~;LfHgI5 zCj7Z9X6m!KEAtSGd0CJ*c-b=>vH09#U_TU0U{;_G-f?xP>FZRj%)r3Gb&}h5{Tn`4 z=FntfBDug%zcR>{$aE3BvoX*;7JweLe8W=AITnk_V%3`sHlxn&wApnAyI$*XxeYoS zT(A1W*G!B}wdLfPjb^JZ$8EG5O?H>nY{_w3Y)-4gY_=HSz24Zh32gS+qNP-d&E;^J zO*XB=>2??`T7%8vvgSCQF0HakG?!zGFAmRg5CrPB1#r#6E+^?gIqs+n2~sB0x! zaKh-To2ql$T{#w=UgtJijdq9AVRk}QwB*>$`W%zd#+LUig1lIDTBlL(G8j!3i&5t` zSuN<&fg{J|vKX9p1DpOrRV9^bu-WZat=W`ga#)ReqtRx~aaj#EodfE%&SC)N#&rp7 zz3xSOsFdi_g8I|f>eH&3)B*A*mgvCVCcg9(oxx~xn{`^V!RR(xTn1=IW`{v5V8yr?M&xAv7H<%$KIeNF-s5e2V z9K8#X;DcB`Z-9XO(sfC!wz#O6 zDyU{{j4j}_k7PeJDsw>Jevgfcu8>;27`hsfSzCQjWPfm@>mJ5Cicz4+t@I(jS zqyJ}N|7T%QP5S>VjC4x(WMRWWkEJ^`^pPmJ%0-0~0cG|Hp!9*`&qu#!ndt%bhb1R~ z?E`!Vl9dY@@C7XJ!ECsI1^ypN0gDRjP89c1@SmJliAzo_t2Xkl%!5dP`g>zz>I_I6 z?CVoA556+BEIk)&dB>AZ=Pd>E2m4yrd>&p~T&A72I@PPC^R|P_gMAOx{0Sz!%dAtu zFMoOyK%XJLR`gp?NLMRN1!o`$#d&C;;=H90vp5go7w2t$G^0zcmf>0$qF-j1|*-fZyRlRo^66;Gb_l&=~1XSlBtv>B!_Z+iQ? zXBDg&;ad!r4JSswJRFW*I@0F{C!SUqJrUd-<~{A`i0-5#UJ%%D_y>kvCOvuBtqrNF$$o3 zHAZqgZhN^a&$o`&{3&1;bFZ6D9PgXW+!mVApxwdcqFrfV@C4tZ^q<9G%LL!Cm^w>f z-IRCf#;9S+MBfVWPP*IC}*Nmis|E}G>NxnR$-I9oKG5e{lg$6{4gnbS7!tB<3 z-z1vpDu81CL3Wc$h8;Tvs*1)U^c4d{QgeZ%Ivh#lOjt0-ruz=j%uoT78@1Q8`{Jp= zZ2T?pGN^a zWr?pFb43QuzOuwOj#7ZnT;?+}f5_m$#bv(5VsMGxG~-r?lo@AGKb80f$JDO9G@{B- zf>eDf4NNHWwTw-M?cg2iKue~v0D&~1E%;?~Y*#vQDf-N=9(by#S_xmpLhlmytjq13 zINqK+VP#&+rE#ElZwF%&Pl%1V7O1y> z$+8%T0n!iB3EQPK5N>6%cll;A zKA{<@0>3ivPirtZ24Zk4)ANbsjns!&mh|zZsCZL~z)NqA7ZC-Z?BVAV*z!HT5{mw9 zDYoz=5kSOo09fIr30Sz#w;)l`vw)`ieQx+Mk_G#HFFv3U0P_SwV)M2&z$Z~L%b@ola2mNMSq?}e{P~bf1y90p+D#0AE7E6 znqqNY0UEy;kG&X=Ta3pn#^WuPD!;F$PnIRUA{- zA5ns-8;5>1z~td&LgeLr1egEXx6Nmww6Q+W+8Wda-4_~K@Nu;LGTs@1n#`zn@U@jfpiB9(ruOzX{7eY=82%`F&`6))(gC6Y0#R>M&~8Z8N>`ig2n0a zTU?~WgANb|1y3FEWoiZ>Fg^||joluNElZ6R^$uho^R1+3lRUu3+1�!mFi0DprZD zuXJh!M(^pZsfE-Io+W-Fl%@Na_4#YjU>QC=CQ8zc{*T#M?u)GFqY)$}fv*2cG!I z_q+%?-R{pK=I6tItGk$={n%FoY#;g<@W@%;0xF0f;ndimeeYq9O1-c8qrlJ`n zobyrI6`gZbG_0Ax8oyk`k^^d`-`SFAAl5CcxEavqq&35sBNDoC<}A$AiBtAN0u=Ox zDDVF6GhY{q@e1uo0kW94i3Th+FL?KJpH>Rk0({`i$zU$Zp?7@Yv&x~j#6ak)66hE> zJ2=^4VOJ@97IQ}eN_oM|kgtanum!*a*IzC&j;z{RxIs!bD5hQjk#> zxr{J6U(c)Ea_m!E3q>9TRGkc!ix9@Id|!htBMUXa@Rjd3+P0iaw**9!3=w(`cng4% z6+aW{1TKEYw))1WrI-N(*I4a;8MUYzGn8n>3pfBY`p)N+L!UODvNE}H=&s-UCX1jY z(t3cSTtpTUHZQIDQKZ#RhKi(>$PW9_cZR0RI3W=W!xvgpm`-E&N zXi%6+j9MOr%3(58Y@CT=GQ!afT=T7B-Y3L}LRjKELW5w)VBN1U5-N8!`OUYE`BK2* z+%YPO#{5XMq7{vSV7Mll2p+8x;bA6oOc0Z?P}CGn#e&|k{^p=`wNvX93)0IX&0i2*7AgB@WrsvTS^}}l@CTMuMBn(9uS{ieD{uKq zmbQ`AOnfp+T4e9KQ`0SGnu{J7G~}QcFcrS}bOilu{w=ib(0`8vjI!dPyXt ztzukWNF_2M6+$5iw*-?EN#q37Qn@c2e|AE0A}^i8wacVF7BLeP6GSp|nqwyX?m26? z&%Z97`URtd>?tjiK-#UsRN~EX!IBSgT6y&a5IS-Kz2scJxbS}Z`xnr`!2QYR(7<^% zxG~BTzQ%N#R}22SU)h+74)KUKei5M&!8gdGy+V$&)o|X)r;WQgI*^E@a-cIxMR%mq zOI3A01$N<81DMD|C#sk?^<`~Fbmj68~NMbM-MEOURD!OlBFm= zH22SrrR}BCtCRvt`v?jbhWHP1-4ADhVy0V{N=+}NlrufzN+r`2@l6Q1D<@>NH_Mfz zd^;>8!yJ@D zf8WOch6ozD*XDw_!ljM~`Z!-nGzh+d-Q3Rq9HluU%)@7%4|VWoFrNy|IJL)_Cw-gBp@N;F@DX6IWZ9#M1w#C`h`o!476!xeD3H!sF^_RrQdE{iA%mV}E*7g`7*G%iCYI~l^bqZG#FX~N~HOdL&Z6mqpp zyBwEGKfclWJJz84m7yGss}f4g=#pcFrGV>HJsxGog>qcHKx#gCS+@`hsklhglroV^ z$w%_xJd!k=PJmt5rQmRCxZmH8qDy#e{@&#hF*YA6ra_LyZxT%?yW3Ea8ePXCRgK8o zySi?R+S6>A^!n~A9R2)DMNjqcf1`O{pcigeK4de(SG(VVB#Yl)dj*nA+@3AF?_>u? z@b$~M%d?8avhVcrZ=;y&XfDBNNlptgcc`qPN~jJl@w|mxiZ;7?)qf4q{|}5tCoUi%5Jju`a0pm_MZk|7rsgNFpJS z2myRfq$nCN>tTTnTs)9;X5j)2up=>s}v{CE;G#lh!qLKig805do zTqmeRyPMQMga(E90^bHLTIfhr1Y*Gu|N9hEcZDE%Ve6Vqv|`!S1#O1<-73)SafNOaf001}}~FKP!Tkq!T~M z`Nh$yn&tjoR2mGI)p~V>D0Ur1v?#}}!>}vj^?)MU@%XAih24? zOctrrzi>Q7_U^w-_b0^B4OZdopD3CoM9#Ln3e;UC+Oum`aeMabXh7+n{TIkEk;ftX zWv(Kk1ZC~s`(8Kgneeh+J9IXHWTY&I2Um%F)dQJLN_bPj%Ptoh)9J}jR$rD6BEDlPhuIN zu`b>2d7qz|7g-o?qpzsM?8P$wA&Oze(@8V*HIbnNs?gIEWj_dJt;DG2E70d+6(9q`#qe6-1BVNH{C`vQO|b&~CC26z=!#TaEm1nj~i{;BcwGN2x?|Hog}F9xE3y$Emt`&l%gG+^gJUL^|6JcEc5RP>Gp@O9J))+9MW0g}Mlib0Ua*?-m}jH)H2|{j*}}&w#qmc$}BRc@DjRo&AQt^?meJ zCsnv0@sJC|Zc8Hfq`d@_LaEXRLUW^uk z|N7AX5XI=$2n&l-_tMW7Ss5GAic@zTxb?ArtO#1NsV?JrCmkJkFr0UJ(H?fwIe#7a zm2dI5Qct%+J_b(cRf5d=PyOGk9B-^U??22;CT2s&8%dLd24Y_TZtrHtCMx!^T`&5V zQ_K ziIlUPgRm>&3EBCV{bwoqG>^@@!gs~kyenkaNL}HuaRB z!5?9&`NVvF=CUNv^DF;6y8c>qTMxfXU1u%kxd1%ywf{EVVy(KVhhJWfV7&H?e>SaO zt8VEZ@rzbxEotc#11~Z9$?Cy>Kw%NS)LvZJfkATSTq%Eutt_TC-}^sgMnN9Jeixf3 zz6$aT(TdG;6gc^V-z;V)OFs~;$hhe%>%gCyz(y7DTMFPq>jb)x;A~l)Kni@iuwIZ_XhonO zxKlT<3k|=!UZ5ih&rySKi)IiwVQNb12OJ`BiD&D`i=Pw|D#wuoW;Y1fnQr1C@!}Eb zKxZXveD8Nb!@wYVzf0D;n%ENU94NDjQhOe5MQlj!(Ko{c^U{$#G4G(v8i+7b-{ zji6bR0D7bcRJbujQV(c2K}3um0!ffkej-zVODUd(Cevz9QaxG z4V)l&R^m2@1i`cNhm4i0kQKtGE0W4TB~k7Rdw`)}YYH?t`4>oN^9HGRH$dV@?_Mya zq8FIZDzJtgutD9$kKh&TF%G)`T%1}l7NMnq?A6;^fW^})p632ndtp-|D4n=OLyz8| z?(ALC@itDcxF3Ap7LJ#8A)z*iol(&N{clHl(gyVaFd;IEC;&XNK^g!I8$hY(xDi%qJ^#;~Z-`3#slKJYeuQmiSjiII6td3l3W z={G|9?@m)P6uF3`GxKBN+DD#3VExBT{U~PYJ271(Q(tpTMGiF{*9Pv7qibzcKh#*l zuhM-R!-pFAd$x6@HgabgKcVrYXBuCN*9$*{xPoXBV(`B>(|DdI1c^vl4Ba-0JeqBz z$dE}fm|+)bMn42rr-0KZR@4JokFp)u?CybUH2vg8b&L9lC+2Z(paSsPTdVuBm-_@( zQQVV=&F`#+<)Zoowo-I1l$F}K$LG>iA zA^m1}B+|xlao{>xfv+g$1c5H>a{NRqj=Lw=W7&arVsMz*v;dkxffLMG0vu;I$%6ya z=o1^!O*!Jc;2$|H+`c2aq0*r2TK@!g;gCQv&HO=3#hv;*w^GmCB3co>F%S%tF6rJ( z4v$l-x|>8xltursk=^iQ06ue;jgJ$ZX1ZJe*$|sG4u6*1kk-6t0 z5|k4dH|)aZj-&pZQGpxqBk?>oAN3cAv3XxUVUyICyEomfFIP4JknX~4$R5@l+$4?l z`@&T7JGn#euS^1?+<^f7)+Tk&)Pa}k>l}6gyYrdAV-$UUle!Z!NKnAo+<=GvZj-vt z=@!8d`5fOSY3SYu#YG&++)L)@5Y-|*EAJ z=9fEVvvj$WHs9@XR};Di+y@B~hi=T2OU#r*OcxomMsZ9ba)yOMMQ^tzd$gMr$jM!V>uiZ%i*xP91e1F zh&+@K$L?c`VblcK^8>Zm;{|~|6dl~GZYx`PvQBeDa#0+>sNIVlw;*7Rp{t;%)I#?@ zDKZM(EDYVVDE2@RirT+!R=1#6BiJGfdY4-pnw4qdL4}3cCs~+(5w_QbS0-B6-oG?( znPysV5!3+3F&vjV6RkMzwg!D)2&_|pMscE-9C~AEpsO5uUjF{am_c&ry=8$`a%fD6 zQx0A9Vqk{|8Yci1uT;!trV-FE0oXvb26I;i%0$qTlZv;(vXUky02i;{yehDXW>yj7 zLV56Sz?K29CXmaN5uJhvcM`2wgk^wT8)zqoE=7sMYjWtd>jD8eG)@EFl|!d(2wadu zV-a4GLzi!q&@GAL@5+S|EsDo&4g^va-vNy5a?-)TxNV)edKhtA1)al}W@`uy!r?{) z^;59*nWYKryuvMmC?;6|ReF$gfhU|Ck-M0Ri{mn_2z2V@z;dP&(STD%Too6BaaC~% zc>cWxy>{E%l@iT@l@nFQWrh$)piR*S+v<{oj1q-XfQlb`EG}U3$!+ zxQ0?lvAia(Fu}L{1O)_Vk=OVMCaM$&;hDfSakKUW$eOsq1YfEl@-=a*+gUdW4n)vN~E7Jc-Yq2b?x_NPZ+%`geT!Evo$Or}H zEQ@FmYydoSD6mE4T)J6#U|X_c?Fd*8VqjcxuNrvPa0Nj8Ke7sdClQy3RiOf4b-b<2 zgGjgnV2!g7aamjN!qGtcm@zNJfeC+aY!UP8i*evitHKm&Jh=W!AUo!bb#Y)z>q0FR z17;r$bf@2k8jFhlA>`sbhz9>c9Qb!Ue6ClV2jSu07~K0l`YTjU`40YX9`-ZeqhI*t z+aJ&`e4YPC^b0>czlwh0lmDO4FT5A|8T~>+4j28~J$Lx@T1b8{hdUz_3#rWp-mFE( zY{O6x&zF~^(pTp5 znL!O-U?I~<7#;*?g$5)E|BrrQm2S8VmSP)ms41K15A2H7bR|HzVng4*8OUND5Sl@L zFwh;$dn?e7>I&X?EAXrs2bE`P1_$Ne2W7ZDV0!|;{@I|jCDDMo!ldw64WKB<7g5eM z+oWgmh%p8}8p(EwsJ4ZoJvhcItEKC$GQ;@J7Tc{#Y z25u%|7=ZLInP@=52^gQq?ZpjRp9e;&xBpW80le$PPEa$*73UJsHx)v2%xN}s#s3)n9Lm*|x| zGQa&U6C?B6?>XD0+wZB{x!ovnvr&c8^0$I{)vUmiVC&R{%^^GZwL(;Ef%b}dIwdBH zS>o zzofb_6zswagU`XhH-TIlmJr0a{K7OBBkRHC$BxCriV2c8Twx17CAhnFQCqSf0!I@S z?F>BkV_-cq2+=|qSn>d&LC{esipQQvXu@u}8WuGZ0P-m+U2)~X0AnMF#+uQaXu!&5dzn)<5)!M% zU~%Ew7~$!c%faC?B(fDpgZERKnF0aZ zh?=YOg=R324Q9dDjkmBt9YcVli1j41f&jz|HWMs=HP}&Y+?NS(e%zebf~`g4Qr=(- z@NoZ%_6$ov!@>D8l$qfE=&8FA|x!Wzs2xbbm(Pp=~S?f2okGM?Hz)7 zU=@OpXDfp}MUZ&RR0$-WzHCx#OA#ofc_gC~gL3jjG@LM>%F_@m%7n8@E*z9Dq$(N= zG96q(dOerxbnyo#Fi%M5uJ=Pz2K?m@w$ls}x?~e?QJz@E9P7Lu#CgiF;!JwZ4pE*m z3r(V&r%Z=kkvxSR_eQWWMX%tIHfBKjREY9` z;M=0ysv=A?|4?Y?JHZL``5pL-yQNUCLvWHTC&+UgUIBRc-QYR;`yKdPTM?l`g0Skn z;1K%e4t$hNyb34G5C|iXC)w0Th;k^e-xoF2wAm?`2ey|kL<9CiZNQ{6!Equ$>?PuYaP!q$4!t!P>@J7yc505687zUO+wA1r z2|F)&`)m+oo`PJ9#`&CC!_$9uggVCu)gHkv6yr)GFTynQwzBg=&`tlnQ{7gsae}hW|z9H{3Ss+`&sZYy4fyu zTj2{cU57G2+gZLo)E`i6_&lK*tNkMQ3dKCKORyKT zlNYk5%s9SK0WmDpELbs>Ee-|yQ}oljh^v!!VjOH{Bf*R-!As0Yq8*tTJ`tHrH1fbb zz6!RJ0dof;g>vYQUk8mEVrWj|8%A7CCd1P{45VKO>Oj4o9qT6z6~-Y9jJulI^P6A~ zirFhbphK!Gdgm_Sh3N&eljy)+rGjX{9P9+a?}F(fK z7+A)GhUZ~>^*rF4pK|Vrl|vbJB53qua6I#um>NFV|F#QU{xR56^PAAiQPf-*w~kyR z@VM;qtHIjvLhx>}E)kgZ6fp6z0zsm%C}7FYL2-GXj)3|lh&Hg-zB<`29?hfdg<8Wd zn&%yt!ITiKSTzfQ;|5Ho2xvZ` zfAvPNBeR(R$BB0#=y4Oa6X4w7;ASv`DJP)$!4v-ujuj7%3+xM86RvqjaK>pP^H1=7 z=51m`s>biW81yDpsK^p!xG0fU?Ye8ifnvNXIY*uu4A@M#^Yo<+~uBg$50A!3yM#B|stWGhqCL+9z$JaRa( z7bAxg`#soM5M{uogRN~s&8a1TDq7M$QITYPPLQG46*25SsB~83`j0ftr~P}Rxr>M6 zAbi^g%zr*qkZN=oT=3JCIS#YlXfe8Nc7suyW6Cku;O7b92MIwiX3^p_dv#FM($Yrs zXM3dgh6Kax&#&0|J>h#p15X!rq|ZU&z^ZYKP$AUA31>9uy{xo7Q-MUvpVvXntLBO? zemKRgUPMZL2~~+IFU?-5yyEuqE6(S7yAJHPgFBt7Isk3^&}_QZUg<3$f!)XXSzB;J z6tLP3p>Y&#-YdQPBcOx}Glo$>qr>}$gNdC&CG>-PrI&sLG)H76QTms2-9I;Sm zNrW2xR-2Mcb0advx~Fd5Z_5Ps1}Ct{CAK@J&_8rl6eXR-&-Dd|SilxoLZjg~SfVKD zJP8UIero^YNJ-Pd`?ipqj@hTKsYMZ7k*0no)6_S_LiJ08`Y$wfazv`!3-yYc3YK;Y zp%jwzq~+HScL4SKgy2I9dQsg5nUO;W%RaGhIMO}z7Cm^Mx<`1CCn1|dEMV{S2x%$W zxli3AtdXFAoxMT_=qXV|yg7nFikQkoERb(CTlR73Dp?|!kO_BWLNp+6%K26Hp$9^_ z6!S9Vg76-F!5P-bfcSo)bY?5j1(SkSV0gcffnkYO=*S0vZ~KKlmc#BZ+izgrmcq__ zC}h$Q<8t``k@oG0tZ#%Yn2*(eJfSlf@^EMn^CdANPMJeOgTPxPX6y&v>&p{Z{Uf0S z8l*lHiiefoP@+lfP7d-j5(9A=2+^Q0@=;L+f=lw%-7m^OH2Wj6mOcZGgIz)fvNALD zINg><<};91Vq`u8slQ*kU5VQ-IxkVA8K)qrid_*woeHx<+6*ctOAP|`2g$8w0LKCJ z>3yoaz|-)zI525Vg$?X{u&NC+h9KVlc&HVBl0mu9P!DK?6kz~QJs-&k60zb|L-U)e zG{cfN3N)_}(R_7Cs1LZB3CZ23LN441ipgC8$(5c@N@-3c8U(cgm!Ak#FrT1__#6mt z5xyWAP&yt1Awcnw3fesurDMbW|bNBeNT~;RMfG`&tn*L-zV1|Vr)DT3- zvhlMjwxGgPui@Cu;`)v44}_Ip_i3nKJeplO`_6z}g6?m9I&_hKfXC%^zn2)9*ZqzM zq`IGR;Qx>Af2pQN^!NkPOfrw7p4a`5lYH=~;Jf3P5omUa{ zI}TYy!=;|fWfUF|Q8>>DDJ&fbDST6f!hnpz1OJM`@or@b|BzAmD@oys$3Be%9mj-h zAoc-BC38?v98!+84ocYsB1V+N{aOl$_*9bMk8t46%?vH7=1^ik=zV8v zXOJ~3G=qsfBxn=PQz)T97&Q`p6F_>m1_|t-=R%z*rhx#;oxbgx9eRvuLbPIs-rx}T zyomspNhgVCl9(MQH;F`pKn{3%F1BHzf@$wVVXq#_sOlGwNKp3bU13+mt5YLE@cjIQ z)ko&m0hbFx$LL}FFua2wDjr9_x=mF))C|crqOONT?p>K;bO@WF*cFj&D^Z;{X?{Z& z9g_O^g&Z&9{i-X+rPZ6XRtvoGZnSB&c8ASnb~>F}i^XNonswZMwOS~=U)^#@eZSg? zU$KpcBKuWzys{38M;u2M^5Ws+$b2Nz|8&06hR_wbl?^^guwx+F9geoVc5bEp|O zla!VWe(@Bh5|wj>bC!M))bQ3ScQlpzG)58SZ3P(&a3 z5qCzFV;bo^zP`f&$i0d`+sg?i>;u>X-q0@%srLyU(Z`e&_3LGx$9KxZ7K~r4e6yT; zvGNESS^8q-UdXOAnc0P?BQ);bkDxY16b`FL#G)etp{c`R|2{B#VPEF9xfvPJ z*?Yh)ffHTLs_*C#VorvMk$FxYlyTDIh$x9urW7%es@N6L&sV~=`sDfB5ot7B$WhPl z(Vt_ga+!?;x#YHT9VA$iR`CS$X%#^gca};t5DGJt8 zH!-MW$NnYn#7RuNV<#E}`GNi!g8#$S*Bc!bB|C{n1vQquqtpO)3I18SAd_n>T~Q?yG5_n zS{w$WTkm!_^=`f0Wp?Xx92T2_-@{f5h4--2kE-usZ}JN@uhOBT>d9{X2!<%xJ$_WWeR@ejuv;a9{TE5@?TBQ#Bv(;s z+0P7B&1fd^n6Qrc;1S;uYEHCbp8>(RZ*0ln&wSIpBhy6!55M&{%Tm=+K05YDy(Q3e z;xX=wj2K*&8#d#GN-)Dc03;d&w-PbQ7U9B-Fu@u?k2xmtEiOcea+c_TU4n1<Ek zdOnZL`FVwQG6mV{b}%5jl<@k)^!py?gX93B=W4cCrI{o_v@ z$rctqzl@=P&k2)-nyj#BL|y|w=RL4r6(srhMe(55p-azPBNv()dd#K{OriJ-8~s^g*-nv09R>J)`1PGl=mOlx#dIVp;%V z9T)#|cXEjfCJ)?#oO%?7Jg=Qih6|Gt24)J0r@wI64*ngog-qK>unB$)#$Vu zOh&iMWrx*h%x;IyXfnf-dIKmou1jFE&lWAEQgt>v9L}xRX$`R3?Y24%E~i81&e0hR zCcPV!_k?3^sdeZ)l^T6^J2>@iRc4yg9d&9Wpax#CrdljoSP;jib2yD|qs8X5Yu!06 zhY1pw<8T{wVBmx*%*oTSDQ3ulS#Ne*%{HSI@eK1do7HW}$uSz7df=_OHi518&cS_D ziqoJoSX^3%*=$E$4yVbgb)cJcW|P702I&sSNxkkxd#JQ(rni9f2iNJUo4LHr8r|x| zEBAxZ35U|b$!DtKQ|&nhhuPpX+6{WQ(U{|OSRn;&gVAMoSzQJz@OD3xz@C}D7P95C znNgkzFZ~&fE+ns+h!)|i|>LbY3ytPG$Et?*$kV$W|IE_}P$!<5f?H04k zVX@@EU!bh+x^sLTO<`#m zbKFL))o!zzEM~XKm7{gp?M5RTdZh%i4h_ew*TQSZdMF!fj@Dr}>Fg$x&EPbftwtS7 zWv<^$rRv>o8#G%eC#c^h6TFXXM8%?v29wQbbXYh|foAt9l~&EP4s3VTO$*Y^MOvU8 zcqJ~?Xte9?T9Y375@=cut3zwExh-b9Rcp7KT}F8KqXeqn%@U}jdWYU@%rV-WdV|qy zF*)33ms9U@J6!Oe-Gzv3#GdK4eixNuayhk7JUP%M8J%t|)@4VI!(=rY^-d=n+`F!l zN~vbzbo+8$Ds*pA=hV$vqXna%sp<*_EU9Xh;&wuT=^Z+)4O$%By4hV$r&VjRI*m@7 zPR9;Bd2mu}szGbeTXM`fZj;GmbXs(fRX1EDxNe3Vlg`4K(3TOt~Bjn zBFxODGnq{`i`D3|nT!U5*=Eu^9WIjr?nP}mCNsB4*poDic5fJrZniUt)ebLNLKPUJ zuaQA)JJl$tTMS)|*xb<4z{|_lC#6=$SH69DD^PFfx*91umjy;7gVkwvLds1xvl+_4 zk>l2y4N!a8{0DbJW3xa93YXh%a~T{)GnAOyrZqZppxbg;O?D$Yuog776t_tWmstlR z2UKR*YtM1!=!|ZwLvJx!tYH3kRf#CXL0hv&pVbCz+p7juH!JYATdM;Xw^!9p&9S=e zR;L@XVlx}H788ueHfZg3t;=L_xO6NG#1mti!%zV&5Za90t}|NnI-A4pbQ*0rFxctL z?6uV;UMj_IfDXrCap=qzx6xrYTJrR-FT;7Vwt=R<(1xz_r-53CEsADThmI z)oW3Rwi}`7tuQ`V+!nh%M+=h)C!794RV9^bf$`9pV}qD*0nCsQGfYoRdQ=_H?S_d7 zgn}N0S-b{D+eyz6S(^JurkIrN? zn=G9zR>JIHo84i64#MTcc?m4#2akf>(A{etE_5EW7bZ@l;~~4vqTPM~=^s}?vnwtt zrV64joWm$Kr0A;Zc8Q^@5vK#0opD=9Qd%{989;vg@^+~P_{ssy6LVlNga4VdHh7c6 z>iU1|y?1<7#q&SxIY1I}LmDK3^gw8VgfvL#Bp{%)pr~{RozOxN1cZPT=|vzzZx&Rf z*@Dsn0wN*=M5PD>?&X#g2nq^<@XVHT&)#!R^!I&zpXZ<7J$i(<2jR(gM zPDbq=+BkFQV6@In&^#w(W@aWaH;-xFzm(mWd6)lEc0BVg2Q?i$w8@~%VU1IWnNCP1 zLB1wU(2Yt&M|n^pE7rH8sqKZ#U%}hug)HHbz{trhXl=%=G(FQdhl9-47`M8SVLlUrVSX1nj zO_Q+^Q_+=AP8^(+nLKPTcH5{WD|tP_6H^kyM~Q(SY$|FiJOC>IHN zIZFc~|G8#K@o?{>l_TKq8@FEkZ<)r0%~--9LpO{+ra5H<$cxQup7a?!QUhf0H_# zm;5)W`)^XGnXLXdsrzqI_ur&WA9eWubW+zRaNg?KtJk@r zko@RBG_Mz2k!C{KICC?%&Ul~gl18v^^KS|A_>W-B0Bf{7c|Y8EJ-@EoQ#?twBp6z( z|1H#Q9&Yqq5(`_`|JKNT9qw0K5bqzkH~4)2f@z212hNzp5)R+ALnXt;)?=s~qylA^~W zfTZY_MUS;4i3_c;ZDyYw4e*?i%!?N+2n^>E_^m{w%=< zGtJhDUKSw>yHfe9Ip(#d5|s?n0yDo-dD~p`DA}?fyyuy>xqeAEG9om;$CN)#AeK*W z$b*;Xo8$2=`nmJX$tLfwoYEj=boE!i_h!1{37HGb>4ENQMxh$?f;z~3+Z-#^g5z(S z6HT?%d|E&s1{n44fEO2-lcZ+gvCy1qYEeF*F9S^dcfjyP=C*jsf6yXxN7KvY1Nt$* zZvPIrV6nN>lvO^GKSLTukpc{b2ZhxvFNNvk?b2TR7UcJr=YIu$3-ddf7PuD2cg)Tu zMWn)t@Xn@CXWLg}#k*k9ccoL8o2N-z;j`uDcBbtD-oE?hnh?Fhyv+2GKuue1?kaEp zitSMovhSx4G6;Pokd?QY32uW5q3tVqmEJLrmQ3HPIe-?uc@=i}9|bBY8cZwAb>xp& zX(m-tL9lqG`Go+(Vzg4_oViGX9Du1MQUtx^$`gi$LH9;Sg|A(eMQFS_OaRZRIrc-; zr(Xv^M=)&!2j>I>f!!QgXW9k-b4n(7F2Dn@$A zUUPxUbN{m5JgS`BUG%w2H<(-KbHBRLJlZrspF4B6IlZddI5Dh3HNR$Wjz_2;X!`<~ zH<|PCTpm_2g1vD*OU(?F^BJt3GX%O?&vyhW&mFwgJkDgC`#pW`-MYbhUCt0+m+oB2@a&+}fneojuBuXnLa0 z{r89Ff%@FEgLofM`!UD%_!upt4tvJO=6a?`eeP!;qovp7rq_uk>U00P69uZt-P6=g zpYir5=Aqh*HDSsw99Cb|=hn1GL)IPztUUq@`<>P}@V=_o+7)}u>rIn|GRfFjOYP)w zdab3t1b;|o?g6^_TzIoZ{WMLVdxI(a=n+nbvE;tWKIfFA`VZ$H!4BZc-WPP61}MY#LPZ@I_6h_ zO1fhO%*LLM5%RM^AXH`fCC0K)8lW5lpwYGC9p(F2SA04~u(Pk~vhQc7oCN@tU6P`g z!S_|3U7@eY_#ISsQAbtY^t|Um=eVKW0%^jZa0FqG$mC@nH1Cw;82&NeMO|0;8uvan zm#ZG6r!$1>8%=Q2VGfnE7C~m+&l?1&ViFjI+3WH~29;9@kg9DY@2qHd#L7JmYBwBr zS2!jo3lekgxIb5a_Uaj{>tzMFKlfbEq)N{{*CKnu&{m$YvAAxV92?&>HokFWLepl+ ziOm|P#KuNK+97it7h-s(D-J!WE$VBSweghSbV|UvJ(9r z?p-x^f{g3t(eTzWbF8luEH$!TlenZNaO9ZziKj}1{43^dwUgo+$Ke*ZgvN;tBS|_5 zmoO7B-8eZeF)0C;GgIT5G=`PO%{@KUtfZ(zRq70%)VyD0WI~g;#3o%}`7v{(kBS~y zFQG|OC_7>9QuF^GRc-UVxwAaxAU!jZWMmP>Fn!5l-9p_Jy+-%q9Qc0}3vhcl;mrfX-Dvr~zBAn%jxp084oVTKsBGfvM+llh?BX zGrq2P%p9)k2fn|UyTQO(tE=G6ssESPvyVLUAUy%p)u~Ns z-^FYFy~KeB66CMP1&S2s__!bT+{&+mBN4q1*|+mte7(#$meQ*o4hzGf<~+dxWoV)g zf92ga_o*OXaUD#55x%B_={LH;^Z;XCII>7IGDN%(}gS3OP1LT2Jw$-#$U`Tp|_$^&mN&sgye9y~U^~fBj%}AdZi!r^c&pqKUbDBPP;a@oa`9hz2^kZ{N z*Sct8at@|wVmF{(Xf2WA>_kp4v8U`az3Y!d(Eph^!b`}$AF!(oHTfP^6@hdt z+Dqg=4z0;NnkG!E{?>EBE3opx!8UUA;qs?d&vc*C=|J9e$?}&ZCm*JBt7zx+p-TmR zm87fSshp2afi`kGR+g|vpnj`7ej$F#CKDn>*Nk1NDHl1;CQm&LKCDb8r~w>EM8u-Q z+Sx=u{K+|+fK_gmQSzJoV?LRfDtt`s-%zaZj(t^yM_KwE)*Z(TG-j7hDFO_C%iH5& zsVSLu2+c{=>Ro8yY5B(MU6sz}YvHQUY8eQe#iLi5EIXy+(AvxLqUk#ofkl8$g4qiL z947@j3zEz_S`pe;vBaCM3O`Y1PC`KyOP0YW&FhW znAQ;$L$KoPv6dnq%LkIF>JhcSQ=WXF$j|bM$w#2mYK-=`v@z8ds64k@Rm=1G+%$TV zqRCwWK_RX6tlC}zx~>j&cpXefXdMC!>pEHLl8x|SUt(g^bTaG|{R`uu2_ zoTC{&)9nwmtlhiuWS?&)o_bpHBOeE>79!s5Va7Q(>Fk zfReYattG=lo^(`u`-wVwzt5#Ro_(2R`Yu!lVFD2;nGGO{w?Xg(35p?ODpSv)J| z?eArYs3@;Fs=W(EE%ufZgT?ImYk6ajYVShniNezya`zGqCY@Fr>tWt^11!O^=@@At zKF!2V+tYMfAkhAL>?rH6nw&L(cJE&`*`;GJX|Sb}mylc6XDji$8(ldi5AY2cVi{h^ z^h|>(KRya|vMe#C$HEU(!>Ci^cTBAUYD z>bcpL#`+@YH#0Qf5b@s3ww%*u?`c|YkaO$=OK&fMcb)s-&Rh3SRFb7%r3Kzs8%^i& z?wDwiWz!d$V(>20+F6zcrhNikZSHRcDrs)aeR;BFY&p3vYjRg1plG|IacN>n4~Uv% z=>(&?=TwHAf;YXrgc5c2^5pf}b&PqzhV|0AMT#(7x;ni?Q>3Vd)-=shUQ}rRG|MKF z-#2PsCo5(V-YP+mE@q6QT=9z>%XOH-cR$b z6akgzSY~?(jOr{+b>3#8l$dWKQdIFzovZpL^xc!W-?)s4vk4Ez&dE$B2)1kom*!cf z%A5GdQz5g{H=R6%Z^>9F&Bv$JEaI(4Gr!ThCWd_Or_=0zY5V&0-gSsvV97Tf7i6dL zyyMCfQD8Ym58QHyJ~=&oUpM)tt9Y&pRn!DxuZrTyi(hQnCCPs|5`zseWF8hQGximtk86E}sN>wl;l9G&<(5;j-12z&zCwF0$Y$)z zoV+LRSmG1e&XU9q#W0}22scLu7M~N>Kgn@ z7aG9K$Dj?Cmu1spte4;^)P!4`Z~$5*Q0d^i_&9SHblE@Ij3fB_n(WeIh~Hv4rU#GM ziZ&=upZlY&mL~e#)HZ#m&%Jt^rKwBqquVWU;I`e;&~#Owd&zd>P~;nP_coR4Grs<= zrLLEdQD=9Cl&4hX^vlKX(SE63UR~{ki{0@%QLf$b#-FG!j*fi2yps1VwIn%~f6cw{ z7~yN`g$JI{dg0zD{+F8d^@lpmIzN9;1L=fTv3e-{62ef*^49)j`Lw<~`$YNbR+(S%r+l*G*fUFAdF6@nwQZgA3q{+c zC3|AAQkwhpd!YEVe)#`X+3*S6_*K>NF4Vg{ST-FdO{Ti#HDOSL+tH?z0+lM;;S)^R zblDp=#O#+0veRc*h3vYn8_PGbyRc6@mVdDocm+V^?Tw%`_V!5A6QN-0r94sz23|^2 zSlN7WHMkXb`!AE{Nwwmdk*Yc8Oax7q`C{INki!0VA{k`C;;$ljUnq4=&4D?8}_I)K_k=43k%%EMI$8Yd=Ywc)Mbl{NBm()#oSY zCyM%z%TlEoq!Qvwf5TB+TJ;g-!ltnzMQy&6cWxguohL0Ks>``&t71%-1u9jS^C#JM zWFfn*{|8rMt3hIEw3kJQ6leLQJ5yIX5~LX`s=OF|>Ht#){c`PM}r3|Zv*VE7x1+GMB?^2Beo<4d-} zuYP=4{od`;N_mUlyDhs(OGp($A){z+Tj3=T)irCw<-3r<<>dM8ynV|gZK5@Yj7hZu zLGy};`t2C)x1;iI@As7O!A6ug`&RRci2CgY=eMHD$n(F|4msHQHtC$6%i>;slelN zs*2D{wUbY|3>pc93u7gT!=I><(8zS(^S57? zA4WXfl`mX$V$mtBPE0}pYIQ=C6xE4Hk>YGoXYU1fwm)aWE7sBf;_{qj>QmO`$eR&{ zJ9(U-f$a5?E3aB7o9>a0AZSy-9hIPJ6C8fc`poN@@Dn@TRn*hk%jEu@3V}`%-`dh} zYR>cWGZf0LFM?gaBs)ojv11FDr&usmj7X897tQ-zG*TbylE{Cq@Ft!$zmN5UAmf8? z7^kefu#FoveaaC=`VZ|9Mz>U~?vfOkHTkyy@Wq3RZf>}Hgdb*tIE0j=gC9y=hD&m^ShiSBkuuHC7AK!(6zKun8)>Zx?+?S1qQ59ei!fK*J*x+t4YyU3Eu8#x2!X3-i<0kg zO2-*W0Z%!l@?fM8Ca}f!jkLCg1;ddLygS&J_r~gsT$zyjAHjUJ86jr^63!m?@q&mf ztDBU_sF$W7_1dN2sxWiW9XF{pqaIp~)R`k9d^l!jM((%($;+ecfl@CNkhGo=wh{>s9BU1c zb}+($l?vf=M(|pTgf7|Es?t$LxS557()0G}(pmn=SS80*Mu^Eq!r|ZS)g(J3>=}oI zYkm%YY#YjTOY%u}oFhPzAu}7RQEM^5_+g4aufGo?&wY!KN#UXJXA^2Q!_(>Uzu$%M+(udH8q=oNVg@h%q zTLW;GLJ5Nb3D19#>c_d6!pJX8NAk?c_#vJ@BwW8e0tt^MTZ5&QjL>R160U!o77C4K z6}d@xG>~N5O+>h7V^Ijca8C&rMj>J98`dakKO?+Bn2vwTS`BCDG)KXFB+!Pxzz93n zBcXIEesY5m=1xSyg8s#!QVAox`UVoprdexBj~LHPz+cJm|dXd(q1w=E#gf&PII(q^mH_buvmzPVzrB;kEeJ&CjH+wUPORp0nADLl| z&Ygvl=*j-=MS5YIilxE$mN(_#FJfnDffE?v^k^hd9&;Gs1!8WfXqGU-P@>eG7h&gF z#|T@A4pWQ|7$J^`iDG=l2u+DnA6{&Ym+~25H{t)xs5#9bJgwA?yvs+#F_jDq{lBz& z!=7XJOi*R1)l0gXBvE)-qZg zI<(w;9VwOOE{pdjHytP!9C-6zmtg+f71r0}5KcJzCIhGrzGe49;K<5SFS#E7?IO|X z>+c?{44+)x;0rTz@3_g0`ER|JlHXQZd&}vZ@(NMQ4ewZ6%H24{pXg=tRn|ngFQ<%{ zhm?X<)~51EPH9HE$kxO;CJ*KgPUiG7(!PbOtuM)QI0aT9Wz8Dv%km0NsZMOunA|%- z@+MB{L)3cyx;y>lk2&QPQa{rtciPK&oRUMwwY4a+NI{*0&X{D#f@W#hyhfo5=oczKVB%fVxO_LvTN+GG;k2B0^EMui}q(xf7!wpvd zoJ$p-doF7naT0zfsW(Y#6G<&3snaBtOH#*4>Rpm5C8@n6^%F@QBB?x*I!#g!Na`1o z+C@?pl5&vLJ(7AvQcp>0A4!=`=V0<3lB|9jQ{RwOZIZe}Qi&vWmZVyfl$E49lhn5) z)r+KVk<>7fI!sa%N$MI&%_6DqNopxceL_;}N$P8o+Cfs^VJau?9?BkEsty%7>)Zl2j;3{Y6ssN$LnmH6f|HB-NIrJ}0RR zlKLZuB>R!%7Lv*$sRJZ6g{0mksktPzj-*zS)E<)BOj7$vY9~qkNmBbs>KsX(AgSvl zb%CVzlGF{7`kACkNa`6$J^H?K4*o)tZfB5aCaJ0gB=v-(Vo7Q>Ni`#>6C~Av zq%0)WgQRjvDwCw%BdM_@RY+3PN$M#{Eg-4q@GMT&8j`v~XgS+S@(fAtA*qujb&#Zf zBdPC5>Q|EbnWPSql$oS9kW?8-{YX-Olhi|!^85i)ACpuNNo^ykXp%ZcQVArrhNN1N z)Xj=HnCwK79}r?sk~&3FLrH2kNlhTBtt6F0QlFC45|a9gq}GwteUkcsq<$c&&qxYL zDxajblhh9+RYFo%Na_ocvSBJGYZXb}C&bGnC7s38dXn-cseFLaBvnLGlS%3#NzEatFG*^}2$DQRlAB0sCrN!wQujzI zkEGrwspBNIgQU)r)NPWwPEx;+R53{vkkmtxI!{uS&S8{dNySOy22Ui%Gr{+qqba<* z)jC{`Li-b7YY$`3JN%&Vn60W54w>&-Q@uj*6J~8|oP%u}_lM_3*}6!Vpze0-XHp8u z(*k@WD!Iw{GcL`hNr8mc8iLl{NtMFjsKeTXORolsx5!H!`Kh3p3*#) zv2dzA+@$jT7A*_%dsOh0bC8MO&H@?chcGoF7LE9 zm;DQMpI~!(6~Or;)~-V9RW6{LRs;!9oao)w6uC9WX(8a`uC;R+ zA9_iy2QTcg`pHdos7+MVn+t4dGBzXa1Oo}@ts!z@3GW0cuzRpIM4nl|y4ljjC9Ipt z(Xv&O1yH@ddge$8|_YS!JceaQ-At26!JD@Fn)4 zKRMQY5i2qe$NPIam^)gSm7igcAGhBcBS)WSJw6KVeQoUkw1U}Hi)aOL?p43c9SZU) zxWmQ<#h$33m0YS zD7#tWCv`H!?P!FX@UWymjQewHH5j{R-ZzBYZUl+ls6RwpomK@3i;>k!9QP*ycSSbh`ku0e zL18a96C5r&0tGTf9>8JxiZF^C zn##R&Fs~ZGbb|v^r}@D0+S7gEN{eD|c?m~dD56H5w!R?G*8$Ek0PGLls+M`e^6#xa z@>d+|OA$-qFbuM9xL1UTbJKAIID;1IGade3Ej~8WOxem&%_6GWIJ3@LYsrN=tZPoJ zv~$*UjM(8HZuM8AQv2A_u#>B_*9&0ZVOuMBe<2;%=uk)lbqPN*D_FSQ#s}Lt*!Gjl zVB6qF#cEOe*WrRSQhxbIW*stM-$k?z__aSQe~b$3^P{z%)P+!W=HNvFoGy3364|&% z;o4oa)|Y2-xETUmP6(<%vq>Hiu(`Oq2ei42{d1Zj@Dweu^vIe4J$|-^$-6l4#{#hT zFV+MS8Z%(=Jsr{x?B!i9S?kDGIMOcylJ8|}GwGrs(s?Zst!yl`^?(6atU5i9~)|0{<5vJH71qwClS-$24@_5FwI*z( z;0wk#G-z8Ajc%`kB5=Kjb1gb*hl7{lewV9SDpc1e94DOXmrJ$yWe7 z`;&{o!zG4L83T!Q0`OFTnB`vL1tH00z7XI1t`DTf;UN83MHDpnA))dXdw`V@>|dkb zQMPd$y#cKJ1M|`81?94JiKE(@d>>!%xsOW#_1MoE*St2NrpqcWI+qy`U(e3ys#VP7q()HZxv{0uUZ+(p4dF4UkwYptSwBDkq7kq8e8~5|H01?tp!7CDxl4%gxztAm#sQpjo@1eBJX>|eXUBUe%+jwat!yP8zl0FCnUkj)K%ZgA0`E^S@rNM@f1GSKp-%nN@_kf;H zeFI>ZhuurcWhJZmaQ#gv3QIS1u_eDotfrTFDk9eZ$c51++G9wpP+1L$t58 zXh&Z|bHBvh7LRKIw0TMepztL&tazM{A8c)Pw<2u*^+5o%spaDin>?@=6d9I)QEyj% zaps)?UsSd=lEW^sAwT#M8}g}w&+@c&m4hy6UF2$)*f6aswc2$XF88a#qs}jK$POZ; z(huU~b~@a&a&bMuQpM&kPvMA@j1a5Cmf3!l;7(JN!AHl6O_C0Otcp*EB{Zef#D7l> zAQ@_y=|_7_>8PQ62+Fk-*M_o1F$sL^nncHdo1d4az;r)bto;2Y=BW0Zs!Z2U(Xzzp z`iV=5;g(WtDe#@YEm$s6zw?KdRdHF^ru)vqxxRS`ZZ@%z=`?kaTU4{vld3>|fUN^y zvHozl8ZJqDUM5YGB3O5Kh!3zeRleF9fCv~eaDG)I&{kWHVP6TOOkGMzlcO&yQOEgaY4RJ2+lwrF{a4s9btlWu}vs4bN?F|K-II$b_?iOxK5m3Z5` z*2Z#H7_4lMe13pSeYj>skzd+IR`qqD7deaPFSEJJoEoLh2u`DW=--fKf2k5gMPmE( z4K9twh3DCIZDO48*=3OGt4(vVw|@|9jmL$oXy;dcFg4N^Ek)5!g+>jBn~}EB5Fb+N z1AU`x+ok3t2M;iYUt!`3x#H4ceyxdZhp$+1hWwy+En7ngA7n(X1nB+(^z+dOJzaqA zuR<#=(Hr~njlurPg6n%i0rh9v;-qcb0ya|uivbcANjMBeK{QT&!lk*R)ane1lHC$G zs!_fpD%$u&@Uj;6XToEn#aD{r3l5H>rh%^S|zP}pUCt3^ZCHa0grPVR!bON;t2 z!4?5W8`%*<pjyA>tZDUaHAiF(!2b-=59d5>p*tB=rW7DpuD1z$4H5b)C-U0o& ze9jrVny#E}?1&xiYb|Ga0%xCNv1|@Vdt78jKpm>`atX(DXfctuC`j)p2=A+oitrGP z))Sd@)hWOC(Vf6uC{8CXJh1-!^X?u#JDU$MO^-_wEIag}?c%K=e*YzYGCHCtDy8btL{2FH(H zvxQ22FuR}2;OI>WOw&y_T*SYtC-%s;45*C&G_9AdhSZXNM}>X(H7+9D7by+Iu?g97 z?NUd3+Xi4{IjWDsOQ!+0>JV{bdnFj#4@c40DVWfqCfso8P$T-xy7sdr z;x;f%mEIAmwA{5y&r$=E*)aJnLpv^@AybXueqTXbruI{6ww%^Xnn3=f;zQP@CKrd` z`aoNC>4{Lmj7;=_A8D)ghikQB2cb4Z6f!*t#lKEHkq6_Hqeh`t&jKkWO|Dw#(om)$ z*u^?=oQ@(6vf&PvA=sy%XJE9!LI*2-8i7ckmj2M!i%tv%4nsa>VQFM(ooeukEF61E zh9Tk%9edLXg;tv)zsot=Dsr@Kgsp+RN%!e`UNdm5ncJGcSY`pvaj-KY7&222I*ec~ zCUl>ZDjHQ;WK2<6`tJwaUH;A06JPy)U=+-nf=18xrcmWtV{EZFqw7A#WtQNHw_vgb ze>zH+ejXUczKs{ZeQPZGPqFk{VZ4c<1gdmWUFbdo-6x#kkcr%)aX9UJSwyIujkAFa zEkYL~1nOG*kH@LoWD#NYcy#wCY7w%H5GW5@C!iy|4o*(6Ww17{HxXIL)dH+C0-!AP z{v)s^lf^-ikIyC{A75!g-}M& ztvo+NF+PP;Z1r)`QiJlu2!&SX>&T$G45hY!GG?kRNva9krn>MFK?&NHC3DxA)6l!^ zC;&X3hF#-%EkL>v0NPKN$=oObCT1q~&JkLep)N2{Im-On6EK}Fla5d3cRw>lkbWd{ zuGY}#Trn=BJHshkaZiXc<)QoD_p@>be2nWEbdSv!v=~A2KE0)A1r^=<`>Xp^5w~Xk z;zaO=^>3j>E^0Z)H82z@8<5W4QfA64Uo1|6jdO5Y&tC#U<+-+C=}#>W_is7(`9zZ) zflJ(nj-51NnZ5v*94F2?bR#UuGB`bsc zhaQvqX_CaR!sk!g_<=Ns%TmU2s8vz9q%PvwW7VtiQMehTy@kCF<>e2*%*TmI3jJJ= zSF*WWUe_7$x|#91<)3*CVf&rB3%p`E3a_)xwseWHjuCJwY`TDwkMRbjwS_|s%UK=r zlav|$5^Wt8nw2(Zk>B8EZOKo*FYd!8x~TeNGZ&ln$1%*rrJ0W2$R?d8T67LQG22)Rw|cm#8KjU*_@ zt`Q3TeeIrdBZeomazhIX%&LHNBgBiVZ3*%q4mg0brOZl9iYwIL0=depS>{zf(lNahB<{LviSZiw`ALI~Uafq|)Y@_5abr7E! zL$u#uYc4xDgq1^tZ?t8}W*tPK4kBSZZlKBCgeEo+{I+6)RfX}}T)NT0ohW%Kr;N=t za2=Q|F!-`enqF0fP}5~q_*6d#RHWFQ2TBHUIV+*cmN>c{IzzM-7 z$f}6T71<1Tj22gAn&$n^WcR}bPNQOm(_+x4EL?#5?nWQBwH4F?w?lP@;`h*?e8dX+ zKwA(l#8kr-op;rOguc1;w#(A($`5QaaX6qd$30=LGT$4HeY0#) za6EKf6zq}vAueeApn?iR@@Ya%m+)xwHpN+oZLBvB5jMl|Hhr~{-5vYS=A=25}w!hS*;Vy@bWE>IJWnZz-lePP2#0jFRKt@s3; z+ISsOtd%Kg4F1KPFft-*7{;BQ-J#Pj!C`!gHjWoDnisM6D2k`Ry+%D~fS>U1I5bah+lvN6O_$Hv$l8>tDf*;I)0YzOqUOvVt?a)T)>$+6||CiWcQ0 z2m6MDQHz3L^Xbs>_gu2b+Ct2Sn3}juNoPk?qtB`#E>X1gJ-<3C#slx z$&Ylve>f{mm9Iq}#-!@o*y?y4kUn=&ZJ+(Nq4=U6rE0Vf?s)) zewD+$tcB}$3oQjUOAUx`8&VZob-WuatjJ{;mea*q4wVD4ugF1(uXn^1x{(KQGP9hQ zi{qkeHJY6xW5Z9?{b0rTvM`u_2xD~%4NJp&w6IpV8;~fwjN>UO3`2#~*T@LBwN}Pu za;i{1icXe5U0G#Ga5ysH zVnnDf%qk0U<0YpOjC83n`HXuH2;~o3Z`o?Y*5kG?JVr@>A{|69XN~NNcF~@?{RD;& z-#%tbL{|iU$G>cw1cjp8<-Wge3&!|+XaHD`>61H~4%|DI4a`@%GcsCk;J&gr?sq!xr@R?eG{HmR~{wSz@qwVRWR%BfR zw@~zer|m+ka{1$;3z7eC+A`zq#69VQ@*494MsDt^D_Y4y~OJbTI2&6@#2CL`Zi^RO^Y~k!FxPJJ=ZV zf>^-VpBT4+aO9QHO0*5+_B!mgI&2&TGhpCV44!PcV5=)n<=B%&Y-Nz@AWzgGW~+$Q zexN{f!tVN$t%m$5N8TeMQyEA8j0Jz9L;lDi^zUxa;1?9_uN>sE2%^dskpiIA)KE_* z+n;rqKXPshTxHwovaP0ExriBQ+*NWJr!utJs8lIx^D7wlu0Vd$Z9{pEQ2Fj96<85$ zoZN&1l3gz<+{7*wi1^$x2FT^?AyAuFVI=28MdT55?&EE>sH?q%^-+=`yqm;enBE z5I8T)4>~`vR*}Er*l4Gn*toIWwC0W-Z-$r`7Q`fl2HQYVdkK|ypj}Q$(ep+FAJ{6v zr90?LTX_j)p#*y1V9Q}(zO7!{k!C9s6b1#dK<|3o*2dPP;pK-dCW zZY*l9IBU+k9pt0P7xCB%w-@nKLx(A>{u0sF)F|Pmr`jB}<9Umzk5d~!)Q5Ac=-0pYX!SMvO${of( zx^Q4fHE-oaH7xf1-^EW9$9 zo*{g)3NKj71lU%=o-V5;5F@!J#vUpU=LHNA3gG>u6>i3G@+yG!*Md>Up_y#2DX->e zD+M&VVZE%HJq#kpg_|J%QCMXdu?AUPW{AGHJaiMx%ERwTI6ywi%fXd;MJ%|3Jro_D zyEP$WO*o#4GTA+)1BNBw+Y7G3pnW^r%^oe^;kc;sF1Q7Q!t1k$h}{qpr~IyvN6Bnv znTNfB9CC-XAnu}Zw^V-6jh)LTF_tUuBy9pBZhuPjP%|$!JSDyA*xg&>r zUVz(m+7XJqHU^e0ufc1cu7zxE2x;@Ow~$}wkP`&R{3`Zg(l{;1XhV=BAA5?t9YO3E zSWzoUXUQujhc^V@xCjquunL=eqZV zdnPo3!;1&G;HWJ@O{KHUUz}zv?P+ljjC^1$(*w5o;f}jXxEIRK=R?d6kn@FgI@5ua#*5kVBA!^K(f)R%1aYpJcGtz8 zk693*Tp%)%u{%s)7jgVS@k-NhGq4f618ET~`rq%aVqmC691x7R)#NhVRpsH<&0UR+ z_iPRRhXjmZUJ!O-jYyUnmO=aM=umro+#O6sov$qegEIAD>k+@o5WgX!2DGl_vwZ-^U7mBF_N8XJHQT7fSNzCS23~gm>7dj}lBEPkU z^A(gmkWJ`SGIFCbHXd!SSQ;%iEF*)bxHYvtjIV8vAm^lEa-~wAz{@52FhWTQ2_p=v zSBk&s;s|dbk;M^w*iyvvSO$ry)h}b+uTB~3exB>)|D{_BDakBBM9Qpj`NgUMISW#%_uJ@`!d7}S~m~zfRZ{mQm!ha z?ulT>RzUZ<6rCi@3^&#&Nd>Mb&_U`%&)Hube4I`fj;?jCFMMuo*(o73Q4J$r)YAWy4%ES$=Z#85$;wns!lo2m{s zdDuNRI1DDACc?n?toY(|VX;4y4zo7^-}O;-A%A0(2V}(KXf}{!>L%2o-#r&=(JH~7 z1dn2=d|_xD;?WZ<6wf=+o{i7X5&$a4FHG(@j@WKmT0o8fs}0TKt+fPNw4GX9Q?O#g5*u8hK#<|47+PP zhLxsbLC@y)$+)-G2&}mg810k4wy-Bl;~Cgk0Sw#X<=j^GFlm$_;0Pl?D#qz)_7KQu zgU9fF204824lG({+{UBS8M>z1UnV)irL~6GYyJtl3C2DtBHjTiB96yR#QzSaYI~unx{O8Jn3t1g1bT}zxSQEEg&QFZURIM#zwnm2zjS`$c_W-DR}&& z`!Jm5L_J_G25mh$$k5hX-nOn zvXuP&xJ?qx5L*XB3q)!7Fu#dr+6r~afYPec0Rt(n)tbh>M`EjB>N&b#AcG8Jus=P*e zjy+BWBVWQ`#;#I(gWPtt8^DV7wJPCJS=`$2jar6a%<>5}UDgy6GTGi#{(~3uyR(=; zpe&b7wogDG+R3s2S8511?hShrxz?X-RuK6oQ(2|<8F1uEv?A>T^QjK?u?`ilJ$VUY=Gz;}2^=*}L{<3gD>rzk zZOnQPwT(#)<%k9LMsj}+)<*=3ci`ALYvkQn!C3Uv!M>uxQe%PYM-9U;(jmFAKy|0I z4va>P#nk8NDOI{z@WxoYDEXs@%wqUvD5q3EpwMD?_}zy}c$jXij9+T6E1y!o^M`#) zQQ#+Z-yM6XYzOF4=WEx^kT;sky3LTkHH9 zU*(JMc0>mnOJF7%!JWL3ZLTQ1eS6UF!apSF755p9I;aiMkMle5AP+s@$uAARuTg$o zFZDV+BcU3z+c}Te0EAxiYGnXIFn<<0jm)(-BmOh_Nn^4nKT=FK)tXj-F^6iancq1J z|FW@+LXC5C#6aPanjsLGRmTKd-o#s!-&H}W5ij0DjCdAajv}q2^JI(_Pm+J;+~F=? zSMD(8$syY`uj2_T9;1I;ph5~p_6I`6EeZm3_YL-`a)rN`hClZg({Rcu8_<{3X-fSe z>2E{Czx0SSn0j>+&O+ijY^(^Y4Caxr;)OafkTJ#XFUR0^VAp%%>i$KQ9UWFK0xH-n=+bjw@1p0{(`8T*snx9j1sCc#c}Xd0=oc0 zo~uKitwqM2B^faIJ$sa#hmgB8$hi9sYki^)-mL6&VfN`jcWXhh{u!|J1GEC#W^E?oK<#Q{fX0crb{)k~_$=KDhpp$DnZ zxL8iDKWZ|y^b=XXrgzn#(V(;*jFxfej&mm$xyxMs@-erQ-zXvW&nU1kG2Q#v)n6oc zCzkHR&U}ei;3uI1zTaSoeeXu}d5b?QtBt#x>-xjMZv)*~K<NgEO z-^+|oYbsSC&5#ha3e$5@~Iqzi-K4#5Lh9Jv!vR)Ogt-eEru;(a-AF98@QCo#E) z>sE(Z!|PXPGv8MY!EwK!0XXf1bH7HPbRh@F?RZYEmro~C-{g9Uuwg8&6U{LMo>e~Z z#e+CXe#wD96M#|91Mmp9kq~wn!qJV=rX%R0n>k#e07otHiv4wKL&3y))gV3}MSRT= z{fZ$v#+&fQo}>0y66ZL9PJ5NVnVqL?hp}pWL-|78NZbJ*!?axX{99{~-T!9Zm)dZ2 z;`a78_BaylAgIkmR5Tkgke^$x9-B?4=m3*-fC`)bP_P5LsP9g@4+(P+=;0!?$}r}` zJ38DPe)13O)YT&DkyG~G@=6`dG9#F7Q0KHg8t=iP%pDbB=rIP` zR`FNsR>936IO#vELp@-O+WCyV4hd_JD&G-NeSSdZighq{9SjZiPdRI^BZog_Y8nDJ z&njw)qhuevSpf+;~X0%-)0dXD5J33=pG zW)UO9ln5X$AtJnHnPM>BZpW|k^(B{U3rBnoKmz)$6%LPM4x@Ag_Wo$E=09Yq0 zjyXXtD;F7%&g#E+}_d@*3yhaL& z0jie-!~Lgly@%CfhMTJChgVQdW8mmbbVlmJ`CACyW~03>OuT9zixDv- zh|3;PguwfP3PhuQcYnob-)ju0hX91jDU&etr2*<{2t)&^={GQtI+p>>7J#s(<1p@} z0h(?IM6Kr1n>aDq$AESVKp5AYi198B(1(UVbeOniMj$+{O=NUc0KyO~I&81iuSd)h zGdCCj)8PJ8K5mQ^4X+9OEU45T&%wP?M|;*&FlLO6Ix5}`+L&tc&HR;~gR}>B@y2BN zIk@TLz#Dv>ElRl^Wydw{REFAEM19zV_?Lv;_^~mS*vvdphuTPoO5OGyMfMncc7pOc zNJK?mv*ZCfn7%p~8fzT5&ru1AOVF6T!?2c%SQr@|B`?uoE!1Ht%~Bn*pVsB;Pe&Nw zK@pI)P-L0Cz5JC9^-C3%+B8%;Y9Me)LNO53uA!n+`iCl=+O`cBso|g}7mxgAuPS>= zaL*5$Fv6i24!jkk%w<+wQG)Yd(NH4o>R$J;t2cz~huE>|!|eNLDez-lbKH+>M{Q2W zq(a;S9MS8LpLBM)76DI}B4PGZ4Dpexcc@gl{9%v8M}#Qms{$t5t8%=o4ip@T@rS+9 zk<0`^tKSiuczSrA?v3B=FIxAAKJ?hcL|7e*p46A0GBd0HSlDP;>U)tJ2bE~xV86*Js!OtTH`AMEOm~2 z3mepfRw<5}(l3UH7d40&%ASD_yxe?(qIHLR6&*a>%-V%iJ^#f9cro%bTrjQ3e%E-( z*b6E;(j~R(WUqOQ@0OylnOa!d zi?IHwY?|KR5Vns7mJSNYZB-aIw*hyxRuK$Ng~~u zFIvnzuX;B0O|BJC=7%-uasfS5yh5>xLtMC6Q~}OkqNWMA!e>DJs*W)EQ_e3QBPRUf zhkmf7BVJEQ4y8bR<;Yr)A09;Q2u7q(3W5*w5#ljZM<<9iaC4RXE62Mm;LR#Qyp~~h zJedAz!ywpO)R50Xf2N2u?Dci518-6~GSGx)5z?NZrQ){kg&+j2T#>bt8%QCFwo*<9 zMv&q8&xSaMAydx^>~~E^eU4Dm-#L+U*ZH9%yrLXsZBS&=Fl@%vqhhxaZ1gp&>r)_tqBJ?=iqh6{;#kHCLLK zhV@a7p-|cqUzhYHKj~cLDuk*NCbjUstFnCUHY_E9rARY5RZ#Lt6$AcI?Gpclkw$PvdV1#K@*+3ft5RPCrw6R!m6B)ru!F1 zE4V*Tz2%=q<8U`V9ThIj$6NlrVc#n*POGUhG2$ue?04p?*te1@GquK3rLXXc;n)@F zus4Uo^^NcVh%@|#Crn8W;x`DcYYastTNg31H5b~w!bXL?_?M0f2-dxqV;)AkoL>ue zw+AHj#;(}CvN9l0lWXaXCU+5M497u%v8Z0iSi$r0Ny5&WxrWfQwa`=nlKVND$$1!b3O%zHSJJH{!ZVfU>!E z75 zAu=5iW{tr>!*2{34+RNLMj6N6i>je4h2ulT8e}}wZqROY9Q$q@j$;ufrm>-rIbPM+ zzY~z@{A@>isRpBK{Cj-KZ#>g9Y7S9tyKgH^$7d7x9Fclr>nETm)|2DE;)1_%t1T8X zK4=sHt$v6PgG1A*y2I|HcRZz+42$c=imOZU!%SgfMtI$>Al>eDDDw|^r%qq3#MQ_3+c=uKxqq+S>yZqoxb1^fOKM{5{-oEmX@Cu!jn zM@{)SMvzaGX5p*dSeQ7YKWuV(%4C_Z#Z*VEjJF0+j|Y7)g){IujT>3qra30y>0wIM zn8Ry`!)EeS(fUqzGz0k!Y7_C=#BH#N5wjevv~(4wp~L|axanmo_ZSw7CujtXeS z^BgNMEM~;pfpXCnyzOWq-{WX^1T<`gOgKBJrs%pB8-m-*1@FJaQ4a()r&3gsN>ODq1X|t=x&@c67y^hqopgq2cqC zdbHWg92?~~IMC|?(AUcy%ke%}BcO3cK$NXlS2|kC?{l>60$Th#jvQ%=A=<`r(GIS{ zzIXxAHep{xM!259YR6mB8AB|5sa#)0%2}OUy%E+^Hs57*vl+AaxIGV_xan!vcDqflw z3Xx|LI>Wfx^*z|8@m)I9j~S|5(TfINWweLXy}m*XE_1oj)>7I5Mx*Zb!J%v)=(~>Y z@>499tPL$6RuU~grhuY<{m@(E$1Zu#QA3XOVJ#Hq!&(SG_JeU%G5m$s4z-YjeYDLK z8p9p?0eW07y-O{%+(85>`^AR7*oM0i5cC7?k!Z(|sKGvcRtageLaGpKyV?BlQHA#e|Z{BwK2rcG#9baR8*hEW3q#?7dALH=#9tYbdg2lVz`TVj6xJhf% zPULU14snBuNXLGxIh{vT^8r8KVlv9mU3@b)Bn9&mq}O;kS9Im%1NPvH_22R$j|)XAYZC3z3DOAru&<&L zRLH%*Mj_wh5IAf)xsLCKYBk`HqcN1t!{*yFQfak0bVX!9Nj|Ppy}^sX(bTmFj9GC;0r9~B`tOSR?#R!uJ_?^ZYRsyL&Y)b_;3C9tX z_}EV|A||sunnr!5Er9B$^*cul-hxN56E)aGM|(<*4AF3pWdTZ>#-3H4X+QBhgX|7s zkOQ=kigvz$p=VkX4VSpZQpBY?`60@L1Zl7->A!KbqW^y2&4M;=$LP(%bSK2!py(>F z?3}|*+C?}}4r}4%cr2#>F~t{xEj#>`Sqf$ThXO~SgpYI+S)UP@k3WxB3*!YuE%BBO zC*K0hNrVw5DHEqOt_pj0+Pq-(IXeF37VzK=P$cK|I#Bj@V_%3H)YuKSe1dma{jQ=5 z2DXfH&7_T!CBREL1s;fQP`dN5Ss&LQdSPL4VhX9B&-_ z8G9b$Qt4t%h;;FA6>SN+2L**hY40%_i{`nh(LC=<*zLwc)Fm8|vQ5e%hp_}$yh(i& z6kMX}LPg#6g~ncdvmCy=NBCbM@Q*Nfr0_aANL#x!_JiPPoUSfa`4>dLsH!4*I_AEg z(xe(h+EAdau3|U9hfoOg*IH=$7As!f&>R;Aol>D5NbBE}DdRrybI>Ux-VgK&G`r>q zA`k2lIJ~RUDQU_nUZjQ|XR{^&5OE#H8jFf4G$X!5hLXlTVIpkX8;&43s2W=jOt{X2 zQACXNHcE65|7z?BUE4M>LHzy3?s%FX&5<8qPBAj&4M(jy=*~A0x?MFk3Z#)w_+ldg z&%Nbng8?fIPIC32`fNMR9LgfP-aK8YE1`qH4$}9?j!kSGzAg6MXzx;&`^iwS;?QdH=i^60(2fZzT zk{gyyaHk)l=9sYHTROlST0pAJA9@wlkOQi-=Jc;Fv;=A!vN^5D8wP%K*Bf%;n|gUo zj>ac8>XUaie5z|(#|zIHpz7hn)ne;>=#9*zbNtoiGl9n2~%3>D__ zY6$ZkhdC+0sFgkPd{bX&R)SB-f1?Au_q1|C6Y&VZXCp8(i4Mt=^LAZ*<=gyL>-x$%MWF9qHNnG@&_t1yr5D% ztaIbSd`C1|)D{cgMjemxdm#q-y&&;^R`HPEO1#dooZ{@f1?r3rC3}u?;2Tg{HauHt zr7p~tykkUSFh5)#_TiZY^|6jhMR~0Pv_9TIt)-%x%{lCoTx=Mvh-$80TCe6RrL}4% zS+7@utOE?xek!Ud>$ydV0lee1#KJr-J13a+wm|pLq3Jq|oGLl7>}>=34HX(K4~yCb zYRr+wxa|CU2)w|8I#)-f_H3(;hPdBA{ai&QV}7GLZ2cY!)-JzT;WdGE+rawGf_1+p zu&!IMuIN~#KT);OBSqlu+k_lMYO3c@KOVtJdq%HJEEr-MSVX0(=U5!s0^+OT$a)Pe zHSOqls7dok>6SH7z|piD+YRI^%r z*s=Ew$dw8t*=$$+oO-rpejzjcL86-b^27u*xDy8C*9s(RxduP`Wt03oreRJvPU7}g zmIwXe(q8W7iOBsQ2JU?Y7o*#fJgE$nJR>VHkcVcW=Su$qR!LZNo69eo9Di&e{#e8f z1}4G~N0m_;KO}F(N|({wWeJR6tetCm(;RVD4WYDGQE=3I2;ZU>;#kBPvg5nbR~;e*8{R1{xzn}F4jT~@XSSU&@- zw*p3c%~8q~dCcq0pd*Xg6(lijJ^V80>W_hJ(;ai_vNsG43lt7mrW?Y`-h~39NNV!1 zT=*Sx{eow_5PU%AoCfT31ALDHj-9(9yh%z<3NAwPS0Fq5L3*?!mi=ZxURNMJictW2 zrE*HzuK2~h=nt35VMo`TN-VUj)Qy5=mG+Dy%S-XuKPDFEM+!75z(4#8R=Pl0y?F=X z26~_7O{;Uh?VeMcH8D^VRaCksYF&?T2RweSo^sKwYMyQh{FU*gQ;j+?f`@MLHlAWa)l6G3;vt@Q4aX z9^3tXIn~)g3)Yu97Fn*U{o%FTH?UkPmdAAAxKIn$9UY70s*{GECMsH1aOr5Jg2OIi z@y-1-)KrORy;_SR8s$^1gjHi89E$b^RvQJ&GfJq>T3Voz{X*4w74F_-18SlIC1UDw z^tN&cMsT5nApSTD=x803oRqqQ;iPOaKsTzOCTof|Nn!4;IvuIx0emsl4WJl;AT1`mqWfvk$fLbd#s!OP`n&%)c$@2xtFV zp#RdLsdDO#$SKXL$HP=Vov|^V z*ba&N^B8!a?-}B*FvJBt-89gWy=xJ0Nequ~jomj#r&0uk_Wb-d4%X|q0dhbTABEWO_+?+Lz+7#pF zH@2X8ztBCRpW80pUiq$Ix*8{70Cg~EU

8a z4Ul#!h^Ij#?r{y;lk`PyAYXSeDTuELbOf{37W9{V(b0s4vZ=9rcYS9In~Ljck#*Pv z3&vQ9Av{8{*#?zNnlcLSLQ^tk(@Y%B+fLw*CS{jm`vEL8rNf*%71-yoLg!Q^*@F%J z#=36);p=xoOH{p+*K%f9y*qj7%&;o;@uTG|@EzHCjRVBOWx(eQgceJ?fladQij}f; z8$m7{7!82{)(sF^&f zdM2i9aEek0AF~Y6%GnoS3s=mCLs3TjlR8_25&2v=)VRi2UE%W1*%tZv$MbTEuoMHm zqmC~1yy}C}Jo8Jq^egA%!jFx!4Lw(8np*p1Q1fJq5Po<;PEj_)U@%o@Fm_>1s%?@k z?*zYar(cJo`H_LNO-I6cBO!d<8#$eDikO!D4PH27u?%VY4E{-R9{Lt4ZRDrwS!kFnCp(~;F)8%}s>(<*j2`o=}SzS+cL~PPV&BLsYV*ju7#=;+ z<^4y>`=@VpRa*=_sA&M>%IzgSdVt*@A^iDbIK#Msdx=l&6qB4ZVFq3-zbWOQ(5Ozg7~g)Fon@w=Ys=Z{qUjfNAJIzQ;WTB@R_gk@#t_j z+Z-Je2fzBkr20F%Jf{)+tUOG46iuMd)o8q{2{G>K>%+hZ3R5UP&2aE~v_{T6yV@}iTiET4hQ#_pvli8<&v`C*^ z@Jx2~Bp7Y7s~ZkSkwyta^i&?O4*uwLL&hnJjDW#1T3i7oy01un{dmi8Uhrhg{43XE z!PRTJ#N!o-$5ilGCz_fnxdE;HLxaOsodexjQ2k?YsD3y%l1FcZVQR3}YM9oW3~-@J zSeQdx4oI^<%{Rea`=5dTqmJ+Kml|MkhA3sFy`Sb9n5QN$tlR58;DOV zh(?(-!}3+F-f+&Xx8DBnmIC$ZHMSv=QG<8c2J>CDqU_R9#6@}Twwz9^QboN>FJDpm zStbmPau(-x1oQ46B1qduV)Zn!A~@Uwcrzd6)M4E$fTRUCEw?La&UcM7qz9FHns?e0> z^j*mEB@5sM3m~aHDmn%m0FGwmw7{}|+a9zuI+@u=<16yBM|1P@LMg3+_>4(7wLVDx zr?v(rKzwb%%vvIUGxb-fQc852Fn(rFPC;8E$qSdP`|?7_1INH6v?|FT&utyb_kM~l zzn)(<@j4r`WNv(hk{K#F4AMDJ=@5s}-4GW`>w$zKc?12j8KATAlvgmHp4cXMsftAdc7W-XtuEi7!BTiBT8)AcAE$kz<)@hUbI4$b|Hu^^7LAew@w ze~tcclYzKiMTBvQjty$EPyBc17>`Sq1F>a#Q#*pq?53Je_L?=@Q?HUcj)ABLKUqUsl<1G@9FAEI%??m zkLQ-*&wpzpXL>M6iGNZ%{TT54u@b~t% z3gw-rbSS`+`sW0q>q!0?ra!2vqK496k#YhaL1FGuH9H(W8c$r$i!U-eSqxCO2 z#j$OSK?R}B#U^S5$5;^E{f{ttNk52Q=L^h4(29V!EzoaR zpgkRE7++kuT`=Eq1%1vT$>e~^#1y@lEQ|dX=+7Ss0alXz?(1U+>v!@dI=l$^lh)5*$H(tJ zP6Y+aAO40AY%2q^g^uYNHDdsCw^ai<+0ooDdJ`R;#Gd*vr|8OU?E-nz+c}|ZyuoIS z&W02m9Ln*mb?x$*lT5aeet8YodC?%U?Hvpv*BdO>=qx-lD;;q`1QncCIxBTdl7I3& zOw^phfsmWT={UaSjWahwIMr-Y0l4?6f1^@U_aF>%qb*F>3BO#v*16C|uPg`FqWot_ zjyoZI`QS*b5dMxcrz=)t`;+{>j!BX`TseuXQgt5t0VH4ghfl}h8J6}$;0!;h-9?o6 zVCgOhvG#qeP3eZoHL-~!Rma3x7-ne{;7@X}ily%Z^c0veGBXU#Qeu62JUtp*E1_bN*>GC|CJMoNmi|3w)jP-g8BAu zOt@XD&ToE>jg4ASdtw&`c50>8Mfip)t@CsDKN#@-taCa4A}(YXgL&A0=G|wM3{p7tMwc66$nc~J8f(28a_^PNMRr4C zU=j5M3mIzpWl(*^d51c3p%Uuw6p`|QHKghc5Ojv%rhl3H5(IzyELLmx^NZWtA1;QO zh_9^2&e@uE;lV66IJ~WJkUn8MG|-TG(3&^=f-mp~KF{XBLPP^{zX}=YsKjS?Y8A{! zGDlI{=YApgXpo+vRV=$}K;Bj$X+$-4bjMPBW`LuV?Ki)W*EL8gS{fqn%m+EJDmetJ zLUBDUa~L6D(}^YQ%s@wRTd4S5ZSn7&S3o8a2g3(Z1=!qhdcmG>~>B@iFyN0v^JR4lFb8G*!ps*74B$kdqS{EnCZWoo`4$(+bIId zTEl>-%DWWvQGwAl9o2YT5l0zp&B0G%{dGDG^ zjtJ(i&2QF%uVjklSrkp>R*X-n48wF+N4%{gQbu_dMf_(!&S8Af{_KLbwvt0Dor7m=7s)p)>4bTopK*lj zxqW#t7hByC41-PrX}oa2s>VxwzP&R^9MQ7FXXXWjwstE ziMHMkS~Z?Aw^K0Bs*Pe<;}`dR9hX*eidsZCp2{41C4I|W>}e2tCB;`Q<0o`9vj(3? zwEuLpw7QNGw!i(NVaKFzF;bjmifk{P67PUnoeOn^np`EZv3(6q_gnVG&axRGh64Ak%*$0 z=@)aFj!A2uwl;FavMdAc6CKWDQlfd`meBIGjbWy?`$hjiN2h8#(8N)bT{X}z>F9Lo zcV<&ZdxUBHmBPv5~kd zanL5^QtEhog!3tmv23!Dg^4l?AdXnM6TMCPRWU)?`9USV;XnWa6O~=T;$~z&`M?%h zZ$3uU@i+_Ao$svR!hQgQ!$y+>r!@kpVW~y=`nc3kzP=(>He7FkGSZZMwO?#hYAVls z&smwBH?Yqr*jYy*{>LZU!a|3o)|2zjxF*?; zWl0}6e5V3tcjokTsAozA*Yy-IO=-M0KeaTk-O&-q>eQ9mQd>|MwjU7T{O~nw!oJ$k zQ3JDf^pjQ!IQJebXlpfmwcROncn6t~!f&Q|NK0C-+kWb7^jpoZY9|`Ae zI#`Pthu~Wokb1mhpuVZ2y2}H#(H8+RQZ*LJ-!;MK`Ni$xn9RN~aQEuC=W1ik@%^rj zc+BqkD~l|DkaVn7?e30dEZe}nrQ_~egX5N~UFedq;&fUNzg`GiwQu-kaMfhMD%F(} z;;2$m3iw<-9nE>0i{=T8OJZ?jT1A{!FP0ExUNvqn#IDQm{ytg}UC+CWDD0Z=@sKb~ zy&XmJw!~r1;@&|V?R3AlqiDprdjY=J4mKuCd6*91NTM?G8|`-A?l$+Nx~9S+j55T^ zdgz&^x9egJt;d%ZcO`hX5^nAXtG1+`)YEtP?(VQ^pvFPjuQ-bHGcCJTMVaM|ZS7iz(0N#zwJ8_KQi2aXJlg#IeZ+=0pXPtl;HW z95Fn-bGOnwZ76_o`hhPnOt*hwQ~1nb7}snufHx|@@_%8>leYzwxgcU z8*pb7xDCymMS1EsT}$&T$GhTikP+xFf6#$ps8!(I&2faGp;*Ti#kz&TG&Gr(&vh6D zk0PvrY?otNJEUT7KHHv(M>toTH(hRJZRV*w;!Irru-J|%qx4Vb%;9ZdK*HMNxDFgbR zIxa;nLnc7`-!X9CRBbh4u=%QmoXsaWv1DEDD}=QS+E5f+8ru%KSmQK`qv zoa(4xE5esfhM@`LM`xhSXkjB&(byS|s{HxD?#1|$Y4H28@M4BfLkboj442EyIpOY_ z4%{S(+td$ks#sd#iNCjN7$kCH+ zv%qY&z>vl0-l%7Ep#{t5ET6etu0XyhA%9UJ>D(izQ7zv8qaFqL(&U9)KQEDCQ9R(7g1kfJgIU#rHVBJdwSq}j+}eJEKj0dS5K|j@4{KEYaqs{h&W8I zG~ckPM+|Sa9D$#j7O-lG-ijyB{yiwESUI`EtE^iTq*a2U?;+&&zJa(>MQrZGiSXzWs_6R{9L4zkt39K*J8!Q7e9dMw?-CrpTf9YhN*g`K z7{F9V5Y$sgMy|>FWoS4M#yX+d!SEpn8-wk|&MoRf?Bc2_yLSn=pdY{Nhg*UuCaio5(k=rQsRr)`2Z3 z=uZp|+Z7H_t!|i3^j9of{GnlhvzT3KBxe)N?BmAwVVE!U2Xo#B=IDp$E<15NjPuY; zl|`W#gXtoTWp#$}fjd0~Os(u(^B&mU7}_Pj984Dyzgwy^SbR15Ruf%J^ze%xBUYSb zpf^>}3pIhx?keOo+C%!F2f_T<4#X83`DKydmj%`8@1Hml*(igBU1332;WQqC6KUeo zdsiY)3riUNWnhpmI_cw7X*0xb19Wy~G~n3^WvG?qD9d&X@U&rx9I-P|fXu?B{!lXn{~r{Z@!d@=O+z395CU{QxS6Sra$Y2Hcb=zTcQ z@_9v6r5~+rxnE>K}H)U94yu@CD3piUqc#2}_lR zlBO}|X3B|KX_rTud&FwA=o4lHPL_is4c^Cj1_?_EP~8NyxQTc4Ug^H?=)G#6e3tD% zaeea1?LhJP(Xt(=XzzT+z&=8D#@mr4u^k9p$ojpFBL{@%SZV+XOs5v*b}Hf#_=+L$ zjX@rPFIoit1p>?QGIdE~270sm%qZx`MnMB5f~OyWH}$WjWdAZs_91?ecAr#i*HK3_ ztKL-VL6xRb4+w{5=tdlIl;P{{<%aRrS0Lf_Lxz$m;1|Y?QoPKrCpH{7~vc)1uk;m(XTkaeI8N{^(*BdDdoUs9!(|3VR2@^5(fM# z1D@;fnN47D$FA*%74%E{mE_Lz*!EENoYgQcwQvyY9e2gP9K$mI58mejvYc}^p45@GLcNwO>2bTYdKA|h<>4x4! z>@uVo&FCu_bEY)c+h|9EO=j)zi?DnEC8es?Tw1QSi^y!VGew}Wbwa769;iP_b6WhEY|K{g+~qSkAo32vB{*F{7+36 z8;h?kSi>ZxBvSa(2v>go@D3*R5JD7eM(b?gCl=!y`u30HXSVhay6OyqZ7vf{KMH z(-8i{)CZ+kCZ!jrLpxbL3uwF!n*0po^q~gcAQca5o|>_N7K8yhf~bxat8pd6a`Yfr zq9d06c{Avl3@E_I+MLzdVhh~cIvh>4e8im9*il2OLn`2*pWu;fc$gc@x8`+*vjY~u z{W>7Ely3r@QOu2>uvo`Oz*+g6iR`Wg<+hGOO7~5m6Wgm^lFm{|em=xmhi|x*jUbSr zba7acgRkmRxd&r9FU8~P4aEI;e_&rrPCEP`W@R`~o*3f%r-2Qp{PJ^)%41zEMSs;JM|UrB*H+7{arQIl~c?@(0^VgQadTUkN9+Lm9AG-RKK@ zs07>vEO8WHH6f>IXe8vKI%)ZNNGWF#mSsRw}K*hnYlPFg8O=3JDs4GU%7-uRW$yhBB&*serS2UIB9 zhmK%O1Ge9S_qkuZ7L}dR*r-HMcTFg27=>5f9uUAItH8kCw!rW|AsnWvFhBPXj?Ij#hUO6=ezyb@L&aAkr0T6-!cM6U>{b#RC+}FX zN!({+UkR1?&Hdsx@rO@suy;*o8C>8&vX4>l(fUg9C37DX=A|aWXpi&@JKP^E`A5BK zJ1gOGEP`F5z#{Mh_voFp3bb1n+mQT~#!7#%q)x-*p`xcGEbb`vmWJ6cpF0hAX6MdV zit*lcP~0c{GWgnLz@{ZjM-dJljaK^MT?C`@&oS>(Xk5=(l7+P4H|M*0$pstvd29=( zI?m76#^WDSkGQBldc>M-r2VbN&&NY2#>~Sgk&e)xzTg2O_(fkW#4{Q|$jW?a1D{T| z0-?*hC1Tt73{BQ1pcCtB0QXXWJwX=?eC9u>$ZI`(1&7{F#Mu6DJ?NWeK)d*5Kvv*f zV`mVrvg~PSSk>hVlo_=hhNLa5V+hrZ@*B8UNnxlvdx0Q7l!f!Sc zZqXaA%Hj+Nifh69yYmXJet7-W()^wKxLN|2<2LiDz%_TghnDvaBj{s zm(XaKf)VFhpx5fuRt6*bWkSc>6Mz;{Z`0O{%0Bar%07Eyjmp}d%BXB*_S8>Qb`B`) zHEq)H*wmR$cYkE?qdd(@3w;2D-5x_V^xD}8}E8alnCe&$nJA3 zZ<)uhmg1e;I0M-}qo_X6Z4P ztpPysJ_5k*oRF0rozXmN{GbpX-FZ+DZ+;So+gv6%WfI_55}EFJVE=3DX>jPKU*XL= zK(7k7^Jv5FPH4$0cw^K)K3YtAKJnF10TYs%Si4RbUNkl!8;bukAjypV@cM&7{M_q< zit~n@VI1oFMX%!*owk7XN^#a=!wmGn3OX%_ubJv>hMR!=Nu1^vlUmr~Zq6e7-0?v{ z;Z=OC!U}`Wy9yr)gr#*yv4bK%AKMkVSmKu>R^0h1BM--_?3jUm*bjO`+gE-uzwpJR zrUz{y+x~G|&rJlxqk2zq^Pa)uUy}#z6`^XFU2AZ0Ub+_?yT43kiW)v_=e7F1oU>WQ z_M|4PTzl!xk)F_M?$CZt#B}{`7wtW-Y_OnxSG*pH!jvXk;dEzVcF_R*MFpfO7OISxri06_!0ZkC$%1^& z5AsaJ_jeD4FPpc6QX3{5>b3+w^4Z`ZUZxc!2zB4Z5{(Xey*%|Ij~fImRJcczNV8zp z$f&!!D_%yR*x)&K*Rht6`=N9Xtw!l|>o0 z2{H#`Wez}g;{xt9YXADsIDTXdCI?4Z9tys_OBzHPWO(Y8UNt@WaH$#DYh z@!;A#bup%*kJu4F{d5RynQ#{rHRl#k(x~eroKmRO$oH%`)>(;F?kFub4tC2h zOFjDTy)wL-?S5rmdK|1$to%`Pj>?L!#<~Hs7-`IwI37`-?gli@a#Nt=&!c9(EH$J$ zPnrOG(b+F_2VZDXAyhf3RND^1@ocJGB7KT)+?*}eD$`mzT)R^oR|(PF?ZHtlqqEH< zM5V44b@XTuiZ+!`n1pQupBobIkwS&pT~#^B4ax&ls{>jgMZXZNd{XTI^RuNm5sFzNtK7vruP4q$U}1;5^nCAnBGa&)%|ennwUbgnm_j%HXO;hLE3w;7N-Ps#O`^@ zC8)wVg}kX4&$X}{I}f;D*_JD^E$!r~B-oHtK6IY5Hv8Vl@3#ti%vJ={QHG^C&3p1*vQ52-SxFL(q#CRq}&Fbu^!iD?IgKyxHoy;|(OUaEhkLB-L0sKoGcxFn4 z5b>8$RTm8*e-YoB^DPVq3ueue+TU+rN=uli51_B0GPI zA$_t6Vay8#*v~2$MZUkRJGv?#J9w5nvy>m>h6*XbXDq;EN)N7a)?@*xvgU2P%X*k+ z5)vCPF>AFG3VFZl*g`yOEjpoR7I7c@NBw;r40ODKT1!EtDWTlW&f+}t(dg3rlkQ`U zV^*v4-K%}Z-&J^*4X6>b9LO#7u@J9%LW+e{S-M`ggY)$@rBRcTjI%W?Y zlZv41W(fPX0r!Ri=Mgs9wm?UkOGuaihT0gXAhd63UZ3`YOvaIrsM)CVYxS@Gx(5ueP~g}EiObtBcIGPGQN%txr% zQeAlb9^h>J(qq>MjO<#Y6=O^Bw0Fmr<SPCCT?($$G&dC&d;4irCG9PGT}tKndqz@*ym9)oHp8o<~G#KtyUh@LvlJV|;XL#r7W-bZ52+}ZgX5%hKeDeiWrs01f0A6d2PY8}`l%bgnFupS z@>a3ruM4(=Y1BCMsLiO?ukU zGE&y*ROsd)>GzjSFR|0<$q~k~%|E(JwM|O%>|wr7pqlQwx|?q8F<-a#Nv$BuaLL9W zTyWYev)VycxAr9dUrq!VZfyace97=j82FI%IbI>8v0VSq9OCW02#>094=HyR)&R(9 z0PLg!jAD!G!#ze&IJ4qiF>0W~E_4|K!~Q*_GWX@SD^Rbnr(zqDSb=ixGD82o#8-6% zN_PQ+^Dl?I76}-vNAAMMw8zzt&#yQG`Og>0RNCe%SQJ(N$>wL%t>jYd@M`qNcX(KHZKeg_!!S_8hN^=$Z_PR zGZ|A48pf~wFyjAp4&Y<{nOc;mFLf4Vg?q{p3gL5Zp+%yMX%lq_k6f`cj?Z4XGXj$k z_{q{XF#&YT(>A>Vl7n~PP{3Ae&v_L7ydX<&F;LO zH=I9lIYU{l!NI9;pp$T@2JnB->#s3mb|5LlAsPJ+uBKh)&_tl>y6n<7Jwu_04e;y)M=r7NyX`5 z{8AG~VQecRfhHJuVShP0u(1}XQGTEX@RTC=gZYvlvO{rq388Gzq>AQauLlM2=(E#< z_~=vF;cTr1d6kZg+L(pgN(k??fhUXqFKFf1i&F~mc7Gu#^t}b@TM5Oc_mF13dk<+S zF{bev&-%tU9I+z4k)QIvmF6Po`i*9IR_jOhmgaLE$K-EGTz75pR*LoZtV2iD7@?=8 zxR_5IMA}FYV3K;Hvofb4J+ucaPdd$rQbJD&;-6GQT94Ssi|ymRENSu=%UI%{W3(7y zekSSHUo_)HGYpaKmk`gJ>itK>m!0GlnLxJ4s4A!Te0pR-KIt*^KUn?mrs&1}^isD&@x7XfX#P z4y>~l_J!Ww?zPfM-|lt)d~5f5cs@=_!BHlakKjj3+-N>N`gE{=cv(vEFG%sRO3aW% zs>+^armB!jTd@yMUhcHxu$A3`F12Tk=CS!*zER0GxWu9-yiWY55tDpA|;EvG_yEgSJ5R7N~7Y@a(+tY{5x;XX+_VWO0IG?#%~sL#fu{Zo@?;3-Ffiy z^Xtdv6y?{$UE#cVVQW$Rr?a3g6Wb1=ZMD5DY9RX{rFJ56z-gfyinkC)7V`7llCX&G zsu_X&UJ+L~&OgV$tL?jz_+Ye{?_{BWA`6`y7MuVtiv4j#@YcNTi3tW{`r<8J%GVVs=X=@7hB1uW zN@^=pc`xobpmA=IFb=W~2VXw^2{pZEe&ucN>j* z7Jjre>K6Fu)2MHISxVV)&YqC{g!!3dPkCr+IW_7M{qP?M?#4a#2w#-XDeY3jd*S`8 z1J%TSvJEy6|7^5yK*+<)Q0Ap^c+ag;%2iZ#UV!%SQ^PA7c`V8%y*ZA-o2Kjg*dkw1#!478V#L_w24rZ8eH!!2(!I^ zYe@KwA|W7*D?&*7VuI$DpflI7A&p8)D}+OevMH4L^kcR>f5mGtxIJL2JtL-4#7epEBbq?qWQ%{+tqgSHc|QwwXxrpK7Zw zDL%+n&yX1^dXyU#{Tf;Hb+Yb8dB#sPwS4I9>^NIGPp*l^pY)AK5Bn36*7*CH@EDq% zui+AxMG?r=%JUkfF)Ds16Nu(onTwSo|$q!oYi_zS5 zU5#1E{?ZN*%)EN8reY~^J)hnVYlrbcj#{-`t*!5B!Wyd(bsM;v+ZyT+_5DJSbCjBZ z@*ki=e4T*W?WaTZ)**xj(4Os`pSX&%IVwV(L|2pzu@;D}G~?<0Ma4(+PZM38Dsf*+ z{KoHAOZ?97WQl9?w8pN+l^5YZEao`&ipLx;lXG+Lad#6}HywS0AM_t2dL*--;vE{h zQW8&#e+nKyaPq4I$4(qRX7qCVssEehdn(HcT83`=VHwEVH*rO>pxeA-V^`-Q`ETnC zgZP7f^NL28x%yaT5vH+-&C20(Uon zdsu)Gwt~b(Oo_iYfcr}mggO@{h`s-^d`IJ__g?hgn15H-*%*3svmGqK=@Ii1dD&!F zAgeY&Hj0cU@Lj1-z*^~KA7!dAz+*+Id9NKmud)$JYiANi@E=;Z>e^ZpvC_m};zwJ; z$xXs>{IcgGjLR>%V%bQQx@SvQWt_(@SS!>+{8FDjH4pbdwubaeREX29;M~2VL%iu1 zV!-uzB_zZi6(XsPt30L+G%0rYg-B}aN?`v}sn55CP5Du$KI^5Xo&u#wJw+`2pAqZ3 zU`~t-*qdFL?>hD%gcn+rU62(@ll2ppZA_7{;52;(J}AxWc2#itHujcoYh&-gYjt!D ztS^Zxo*sn47>$My@H((=NCJ8CNkTcX7qB z+R=)2^Q-eQqkwT$#VFLn z)sS7XU|i5Ks4d+4c|NYZK~Kl>q|3TS5k~O+J<)8QS}-2z80QzeMzHcK<+%gy#w;dX z*ODmulFUY+2E{eTs0^ynjz*0h%rf`v_OH93CO@($JCOA=kTZ89YTMfa+9TbkMyDD7 zoq7-(b*V-tTSz8KIk542=>V!x+e3FFzNGFtk5yT#fUG!zQ{;c`@2bOAS%A0>w0nSS zIXj|I^Yv*^vx64OFLg?)h#TqX;cuzr+wZwsup1Wgt2#N=LEu1Hdz5#ogS-RvI>07vMrRiBqgo~K0g``otV^wtA@W@ zu=)dKSyy~&mUX`Qi{pGwv%|X8NpRIu^Lo}jm3>98%g9$e6%d~eQxHAQRo|B6C5zxY z$DtCMTF4sFmt^cH95DDg3ns! zYR(Q?XupI;x5L)?S3RaC`~s}hy7{hT+bta;ae=EXyJ3O2szZ3`JFW(+evqNk8=)6{5r%bfiZKLJ1xm8tl{TpRPgF;&+v7>{@8xO`S6) z;zb=?9_-lxMlp}HgP;z=y;|NH9DLdp!vcnoQB;O{HXgstj8|5?v9d02o(8A5vP#=# z1B^`tNvlX4OJ9;%*&%YUV#8DDw z_JOMbJEkzdvKh?9gafa%1!u3)0?u@8uaqLN#NddK9Ie)Jua z|2jFpW%}#`i#nt$Q)5sgOgBp^y-vL5`9i5YDyb7qmZvJ z&F+JMDG7Wo#S{6@)dhA!U}bC`K1?=QP_$-+hv_a%2z^Or`GrgaGwCBZjmzUL zAhj$Y+Q7V*3PJ<(?iP?P77!W_HUARhp=m1p=`Rrjo@}9?Xwn-N(=*11XKPjZv!meN zt+LSbVV-g`?cG6@j_lo+7P@@~-_N`yXxgY7Dm~e#s}}l87J68i#(co@^(CdH&pX^( zgAtr;O`hR;H9nOfHf#+4+A~bz;_ntp&600WM@6I2ZEXu$4f>KSHtP$t8z0^Y!P$zW zoc9#vto94dx(|GWPIk?^*-e<;!2a(Std|{XfgLp5Q^FKAdei)GEW7{RU7szqkjyhA zna#t$^BZH>p@6J7oEs=(3?Es5w&_67(3R}0LXCMk*HCuKLiwFaS=O^twE;(zA%GA6 z0lM^1MS1jt>m`o`H6msO zaON_6RhyHKJL++Mz12x7xn0FNd%)eq_JNMIMG7)oV6?!=I|Q}ibeRx1*)%Mw_Z!X4 zQ!4TooKxuQs$jkggPJJ}u}Si7KoY@kU2wIvJ<~}Z3lgz> z1RC6k|94VLcD*))e$A7K_J)!Os^EGZ|S(dp(c;{1-W@k#Yw$} z48KlfO1C(FglCNv>2uTT@D8`DWLeiSBldyLev8Q-{TzuxeIMY+(L=#dH~!cz&CS0; z@x6^MfgiXD&+oR%C+;^aHu+5#@A?Rjsgdr|g^iVEMdcf*)Nz>8m5;xB3qv)=kKXdB zt>>no?1{Iw2yE@|(ElnbPV{X+RMa8L@ujz6e>LiA+33$YsMPzjU5&)mjJ^W2@=Ja8 z4*I^)D)ped7>SS2sfT%~sW?#_WWAN*q*&MUW5@FG&>VQCYgNqmb6icZKwU_rR5>5% zQ>Je^;5#2w$xxhiZC?@@Igsn_dfdIwMtby}N-)L+Wxb)29&tfguj;wL-hWYo8udN5 zs|LaZ@qfc{qoz707crERh-@eD zj%PMijDded}*m3ARGgQYGAfXjB3g_a;B`bRrG7r~`xrOv*q#Bywv3I|8LsnC?5A8%Ho;=k@=si8oO+P_*I7x6~VBC%CxrPT1fWHLit!yvL&OW zSwIo!dQ1xS(Gyo~7N-K%d5S15u1sWZRfVgK_Fsf7Ri)kZ%vAzcA_!V4!e);>dfaBT zj~>4t?hfGtq8>)^(4RI3O4~U>L0VD4-N-hUfE2w%9&jKfGqFg!n%LZNY^6fXPuScE zwq-hXrk9#pHge>*MD|zTQb}68<0|HzyzV--V}z+F{9)f>IUV4RWw%wbw)xzZVPr*# zC>gmfMY-ZF6dF2o3UpV6=V;6CHk#+TKzE!iAGZbh5HtE9J0cSSE=mHw7UV8xtF9pQ z%@4>bIs$I`0i<7q&mL|m!^Z|Q*cIwxEnxw zwG55$i$itWIex2QIhHFhA%#%COLdsVzA#kDs2{(TJng{NT84aIE5P+ap>{_IN2%n4 zIQmnL3n_0!k8CYr(B4vL-w$(_#|gM1Z>0N;3%O-Xf?XP;>wY~JI96%Hl_T7ZSYGVy z_YIQgp)bigeX}C&CakJT|8o(vib@vx@+LhM2J+#*Fp9aGvEC|RL~(aZ*24nWb*xW8 zkhV`z=@yi5mte0+Ix2+FqMkw+gVwApf0$a*U6HL;Y5y(huFl@G@LXYJ!lcJ+Q35}< zU|TeGDeRC6GP|_920LH@*>8eSNgyMlB-p>w!)8|ur|BYjt#U=ejW5lW(dU+BCo(op zR@sgN7^6M6@Oa`a9CD>+eDgtdBhD0S5{Bc}Yj+|mJ5I0bNcxhDW%)~^-C~k|ceHy1 zYpGJc7K3_Ewoo>+P)+X zpbkpI4X%nKh8t|Tg>tE+WF^PRjt9j;Mg8AcIozmJ$P96As539bD5J9m^gE$Oc!r&_ zKz}#RqkiOqt*MNGuiK=H;MJ=@B!`9Wt`y03+f%mGj9XSkkTQI{tW&VXWrS7TZES`4 z`ICXOqaUCp3 zIikY2>$r#84(c#pz7VELzn#-0%qFa`72-i7RBSsPqP0JW ztBZHNYUsuo72;|W_ZS?Ns!1{2A4Jt==vUq~iHq{X&D_nzUNztRW1E^!{?WV|@+-~V z_1NboaRj#~p?BP)6YnBocH3z0Xr$EMPvBk5x-P@<6EJ7gZM|N_LWJe{i;+P&1<>x(ghceTsv%9VBcZKvyXBeBCl2i_q+Iu?r%M;~cHHZAm zvN+W}m=$?VwnwVQPF>t1aOLRk6raIHq1QZyo+Kz+|Fcd;OQ@?7m+I#3V~ZnVB?~p_ zgLH1Iz2Zg}BxoQ@q`Dh*Vz)av2~KIZt}|&g|(P$`+`Y&3d^<+2#_2 zqGB1oc}nXI>#|iPtJ(*3zeyJbE6-6jGB<0yxv?c6nmDtsyEHqgLOkf}j@s>PEAt!Kv7H0&U(d)>~5^!Bw2YeD?HtFfl0b66FA9Jd%7c3 z-K37-KbA#9tzx0BNMDl0W#8%46k&`;vd${yKk4Y^J6I^&>XhC!B`l*Xzd6i}TLP}` zEx?mrL9Z|ofbfa(j++$B*IeD(gl~vL_-@=J=^7z>5xm~3?)Gf7h0O?+jcjNpqx&(E z(dyy*3K%N8#o)9NoPzB8TJo^h76h`5DyKIF!;x5L;j|iCS>-+A)C?94fx~h}Er=>Z z-EG(p7P^yCLUw$ToQVZa{4#9QLxF1Y+M4nk!`xL_p2<`i?CB)lceuNoc+xr{Du*Du zyDxiW;qs5KbVWzF(^xg&h*@r;J3YcZ7{@szPxR?)D~Jy*Y_arR&eQ_w1@f`wm1KDy z9OVvWFH0$HeR!GC?rwOD9gXgQczrh-rl2QbDs8UYWS;`OvSt4Oqf!>Cf-W2D9)=6n zH9==fL1!w00?#8Tx#%88n*~>sVlEgDG4~sV`T1mid%QcffaiMH&lPz$OmO!{SE{kx zC0UZ{%bLQ@opJ?Mw5Q9Z^W@=&hq+@|LUp4|-1|K`c2}~@dwX&)ubR7mfMM`&D;#4d z!4E?q0=1!(&~@JuYC0KhGGdBSiDxInVF=}2rubB1LGeLMu88ll5`p9?8(qmt@L5wa zENcl|F$_uOkEUY0nmk3(v6a)@9mMTPfK#MvJjHYd%r-Wz7EgN9jrBCs-No5B19UX6 zIKypcqgBv*Gu%@V;MG8fP4Q8RVzb=y*=jY*f6Q{fCAJ3pW*J+9MV7HE*qdb_kr5rt zmoBihtW55njo#+8lrQi1Q*f8({4aVK`uDvmXVtmx(c-)<-^_pGE9d18zZhx||D#G9 zKHoh7M=NR4;%+k`EiN#$VjU^VThphYz%2xns?#{N^w2PVjU0 zFGMh@5|3HvE*{_(zsG-MFKdX<%==%%Uw2m!D5kx*^SXN!E02Hhjb_Bqmt-tA@KahT zy!o5%I&Ab*sUnEVzlky#A(;=XFPK+~D#1tJ`yz_ZdJFbDLkf_0#8hlgz4t||A=e01 zkX~=Qcd%g=K?YCt^iO0~_r2rp$vy&Oui+ZH$o(?gW}(|WmD`3R3O&{1QxN%v#qN&m zluF)u39R{d7V;Bba_WI0g{TfTc#0e+L)Sg+$Je&3OOVa|?J{3_ntSjxSxiAZ=w0v% znx>Tgr|)728o(c{^l7j*`XGmn-kz1l^a;T7=A2f%)zgXNO=4DVk`x!6Jc*wd@50Sr z@IUetXiduKm1vk_rt#z}F5@NxOjtl3rDYGFX08o6=({##bz%X_+K|r@3&^!0pW{c% z+K|Qg=(9FtffShL$H0ly9&3Fdf^=(&j;2E%u~~Ocn z?)~uHaD3Juz?m2|c$e)ywOp0kK5>hAc9Lbq^{*Nl&Om1`RXEST)7=X3e2ug%U%C?| z)r!yglq!c13ROH%W|FwBN?gAIAZaa40|B0~2X zXN2yh&@`#vYY&DopD9G=_h9;Aw@!rHI|R3nJ>qWs)V%^BNiD z@~8a=+Z*NdNI~eg7Y*Pa9pO)Z2ut=MAQ3fFwn9`*IFHEt) zcKO;ue8dpvApCB{R(iFN-SYu~8nSE)$So7ZT+lX*6`Un&2XaeAWCdnf14!}TngI~1 zn!?{;s-lKU`_4D0l&X?eF^rYyi-;m69fw?jv!s1OR#aOXbpk$iKNW8033qeW+agL2 z4pF=|U`mKSAav@ac3)%5?co(k3+{b3b@Y-p22bM2G z*4uwi#cHo(cZy)qNtbgzR`0o|tSIDg<*OsrdGpUPps!$(M)3cg#Y!h^Yw{(f05YiMy7p(x&8$?x+WrsrXqgU%WAZA0DL~!4F?>r`Y!Dj6T&Fk(F_&5|Rg*qZ8io5>kyn zH}vSqELr25o|wlJj=hYbeMKI75k1_7rx;t5o2^^W=-D0vL$>?Y6?Z*xRWB%3KF9jA zaaZA2C0nSP(U)W#4HSQky0d#6r|WZoL~#$=O6i4%K-WyM*<*L`^cIKF}LqVyTrwEpjJ#? z<+&b_sp3-pa#vxURI>Abxoe>+HKuJ$rf97@P%E z@-ODOk)xnr9kh_9& zOJw|tz()t0{SWa7w67J9Q2Y1dQPBR4crd$5Ji_h&6OTOhec};h|4Te<_D{qkz>rAU&HkQvgxVj8M}+;b zcoeng24vtFVE;_K7P9{>9(nBR#Ur2nfOsU>H;YG*{eAJU*>{OYA^U#uNU{GT9s%~V z;t^=SCLT6>mUuAxFX9noe=Z*R?bpSlg#DIy|4Ym#(qP-iOUc{m?s||q4rDi<0m-Bf!2#{w7YC z!*74e-%iWl#KAos3fMP^N1$DthJt_jTs(s8%jCz4;*k+(UnQOe>__CoAs!KSu~!Qe zABjh>{i%F>DjwDB>%=3UJx4r3?LUi0Vf$Y3C}|gQJkWhC9>Mkp^08Gs3fMmok0ASP z@d&VAptl0{bK;rbex3&v&V7lRL;vOW{YKu?y*YIhT zNY)@3OiB*A<6CT?`xcPmpDsD^`xTK~6Uhyc{3ep$MUpL&yCTU!GME%RLy+BU%<|Z8 ziR89O?ug``NE{-;3i3SmT#-BwNo*4&<&g}g#sC?<8p9xiPT;G9Tcm*o=6&qq@hR}iKK~0nu#PyBrT8(CPgOTKH`o|k<>ym z*e>)G+@Is>&4Hwm;-AXm3L|@rNXj7@OiC%fm&6@3_R=CLlYw+FX`=YysW`CvIg-J4 zp@8Dk7xVGyfJhD^8EhBIC%#V>rxZ>V$#f)x?Lz;=_f0sI%Dz=3AByB-k?a)7ZjpQ@ zl6@liQX~g|&p>)a{Q0#=PKe|?k^Cl--$jxwlDi_w5s6bIZjsy<$wQI+DU!cM@~=o9 ziR6h$o{1z6PL#4Ukpze&3dvw=a3sNcJG%EyHtTsS#w7)-M5^ zXo}PnGN}!SPr~YFQX3F&qO7T5WKxR|pF|IkNln9i6KzAhiT)sy+J<-&Z6%W$iT5po znv3_9+Ku@p8j$%WT9WxDnw0q_+Lrky8kzYf+L(9~y-FrEHuEh*G&}QEv_JDrG(_`F zv`F(!G)?nOv{Ca-G*lS#J8 z^F}Q=)1DzrmFHU~*(}eS@gKs1X`h5W(>@97rhO8&PWvP*pYNv(7()FUSw-J}BO9rG z5*AbYBQ3X^NT3EOMF2_tO232SV=3A1dz3Hxlm z2}5nZ35!kjFWC#*ZT={XxcMfmx%no{y7?yTyZI&zz4<0gym%8%Q6|}X^G(?LCB5;Z zFuIv!^~I0!O_+c4P4olio9GbCH_WAd-r6m5Fc64#%Wfr&J9EQJt8^(8+%8fOCUOdtKIeR?*zB69@91}a(UI}9ecoh<+ zB3`7gUBn)avb3+>SEF=pl&xYG@@3Bl581vOe=S>HbAT1-`s#{}QS2q~`Nuk-0Ssi!l;j+mloH2Y(uwTM30&p-gT! z+xL7*ncS8|#YjnXz4l+hw#mgj=#5?cT$$Yd8UK^CC?^5&mwbr+6K`VFgvWpKA^J?b z-I^#|$am?biap;X_=h*AB8i%TWc)lNk3`aQ0g`tXBDwrJlA>=SdGr>Nc8ib{UW}yn z5?h`O`;AQe+4Nl`SC=8#wH(Q0j^y}zNM@}NJ?x+a#AGaK1TA2NWK?Io==eU6-mY_k+Pjg{`nlq!M#Yv?nCnYOC-M? zK(gX1BnuBA8GaZ^nIlLF9Yb;-$zU2W3Nd285kHL@)_ z72SDzsusV`^UUsM)89XzefRl1bL`CQ?Ci|!=VcE)es`V0h#||xucqw&!9DOj48WM* z0B7#ACz?0c8NaZy&#(tzV*UZFegebtAzr1Bep)H~>{uGGvJAklEMN;%23ImEx^Fq zfUEhyY}alxzPIbZHoGq1K|EkiLqL2Zz$Xj=jREQS7SrX`6tKG);MZ1w;jIB50`yA? zE|}lKIfMBaxwtyC13b}*eHa#|0+KremUrRn&+LkyKQiQW17JVn6RzGp0X}IQ;}tWi zmi=LRzz{kTu!^B$2H;zU9+`mfF@RqfdW;49%dmYs;NB#_pvi#a0Q*e{(*pUD&Conh zpEGQq37GUGVANB9{j&h4X9JGT0l4O|Z6V;9MF8Jt0m}i|u7Av2&R7i7oh5)SO93|u z0i)IcB8mV97>2zFSh5z-Y8_wy59{%>-ey1{!y`bp%u#RwmfHf;R}8y$0H*8&jNJuz zb2lJvFJRz4z+VRdcV7q4n}7*#0SrL4>nAg3SN{jo#)E(%M*vqCmLAOq);k9Hl%eHu zz-ERX9{`S>08BXvh&}}vbp~*Tp~a^hGmkh?*F1B=S$*~_nEvMh%`X8CGK~Kk;C&hJ z;T6DdR{^hH1N6QQSn~s4|KlIdEF_3s0&GCch^ zpFZGIhL`^ZjDG}}@C063FO~xAD+94C9N;3uxJW>&ihu(Q6)OSq86u(pH=_X~ssK(f)QFwTN%(N z0nocK;1t88CV0{V>x3>y#V zodftQ7tnMX;K~fZk24vb;_E*#3qSA8287K8JYrb205D`RAlD68{sQ2;rGRnE0S{LI zW)uMK6#?d8Eba<;5wMOS4%Oj$o1x1(z(t0a)&nY`zjwXL;Ije1li9BPA2tIQqqbdf zm9H4hRAToFoT!8&KfV7z$y3o41r(vov7vMb);KSEi=Na}mX?pZ~mTl#q zV;ibPl8Iji)8OTRO)J@s7AE!sYhX%#5m0{}AmL>|_sxKcuL9P+#=ftbzEACf>Ha}L z-**A+4+B;n1>AlgFzy84?n%Her#OAT(}17P0CLU&Dtr#O$gt)MK>sfR{VoDpd<}@Z z0(kK%fUW^Pz77cc4)7Dh(eD9AegOP^6Y$b4z}r6ozPJrgcK}b{<(%?*0XLcaECaUT zzXGy<2YmDgVDF!Rx%UBS57_yUIJ-QUYsr$e1r9msA@~oxFe|&p2hi9TaD<_M0H9eA z;H_XldI%sZ67Z1W`SO6+N`NOS1M(L{^Nj9gGdt_5z_z^_;8p^_zYSn>GT^UNz=z$~ z_l)VgyC+QUG{BL5fK!72SB9_$Zb`YgUq`@HB?C}-BHMq}*Aa@Dpe$Jc8BvJmUjffJ zADRWIJ)gY}o1r70h3OW+nu&J#V`3;v7D>1Op2r!UT!0p90SDIu?r#OO+RwH_91wS_ z;^7krQ}0lKUj@MQs(e}<@TfLmCf;maHSzjtO`N+7Olf7wE4GY(CgIO8 zUE`VnDkcH8bp?Eams!^ny#Zn8cx4w$~!$)RLfkvYhLd zc?q{n>$_!E!Yz{$Zkfk-%VdOG=I!0GjO&(na(BMGO1tHC*)8wMZh0Yg%loif-eTSI z?ui){$q*i+$kr9X@Rs0Df_ON?g2z4Zf#6X=JS}0tvl^I>2PO_11@Yv@ zZywdTWxVE=ftp*!SZ;ZwyXD#KmPv27Jd)k=6n4w=)h!RrCGzxg%LB?SPbRlKZrt)n zamzzwi99mgu2=IVG45&I(uKOE?{rIN=az2FEnSscIwrUDNN(wV+%hlimafJvorqhy z1Gn7rZkdaA%MI+7o6Rlvms@Trx7k=2Y??JO4*h^%|b&0IFE|CS-CETWag5Wmo zmgUwZvf8@D#SMCiwC5$#oZYh0xr%a=4LFXDZ8bSWS{J8X*9J@erRd5wNL6K8qMsJQHjPt`{Zb%(c3Q`#DF_;dRZZ@)q_;(OGkja^UoXhj>N zgPGTRbjf*At*z0{X0n|pJK7qZZ07g2c1yWOE!sJvp4ZMUhI{mBJG%|tqlhHCqVJI_ z$u7rxbS%ke6YjVW{0}h(zCrZ3tx=CQE(j~@YhOmE_D1a{+Vucm^LLmqcHA!WdB#}N ztC%js=eV1wYLZcj(i1C1(f)fCLn5ql5vLnG!yHJS_C~r{oMMjVIp>%aUNm&AQJrGn zsno;CPT_gz+Y7xYbST*L6_uJ&><5*~hdC1en_W^VJ;fN}G!Nj(>)G^fiZRt0;R`&S zeR{DMWscAhCWSk%R3Up>Qh-cD6X>uo{r!!17qy?xHS}f0Fe;d$V&WZDz7I4kZdfdl>tEW8!cwAZQ+jr^AC2f~_&B2&!b>XdJv!~!i?<>vZ$WfugtL^_vdi~- z=t57Uq4R3Icp)Z(LVFo)%xaZl_>-4rcK^?djIKs~+V5Q@pt9APg+I)zHhr*aqbuja zyef5~oXO?#g3cl=8J3?|%$m>J_^l_Sz;=HD3dF5y@RqkzcaF)_|UQ2p-l;djVY-p8v zd1=)LR$h-Et&&(G4}rY$bp3sb<~(G6QpKC{PE-kOU7|b;_E}`b;p)ySQ@SqCavP83 zb9(?oDeam!wTesl%Djlx4U18ZwtlQpOpKKeaq{E!t)h=~ErX4wtF2@FD>{>IfItdDE|uV%x<*U2k1XtW~(;G?W+7=2LWEql;OJ zVlLoiwbjsv?`yQC`OU-1(tPiq%Gx)P_-x@-H{&x>skj$ZU!$H`?Lt2O4CHrTc+uny zM)fr+s=kx_l~?KNUi6}oqtPY`X2v9zj5+Zl_(flFuU3QU1{B(`s&BNjtP6Q{Zvs~L z^nH^;)$UhmOnKoyg_S7sS@6I}!YXnu17s$U@_JT{Y~m=>A#ib(!OEaS=PKkiLQVh3 zH9MTo`C)pY2QnPmBdn@bXF^}&)x?`O`Q}Ei-y^JiQDIeI`$;PPZ~kKf^Jeb`LaanZ52Q&e%Ixt1NDE zt~>W|s`Jh3m#+Qyyl6pLRi2{W3adcJN>vNDb0vItUe|n@(gzvc&0L9jG_Q0Xy6;67 zrWkc8FQi(0181zC+y|ZWw^djl@#?2e^cpAHl^PBWe z$rO}<`F`)IDX5G=`h$i^Yf6jWg)%NIM}h`|=|4kqXrNITUv2 z*cvryMYa)WW<@;Cvd0@0xty9%-k2ISD0Xv=aHq!y72)9(MPW}Oj?7G>m6HsM0{M9q zof~NkD9W-&ArkfX%yp%hEMtr_$lz$0msQaXKW zQdh-*jHmgdjFC=ryI7c~kuk~`?o4fAEtpfGp*9Lpt;nhA>m&!%2Kh;C@)~ayPwbO5 z{hByR`U-pW!AiQWh+1`Vs_ETa5eLEOE@Fz2KnbgB*0S1}&`+~_d>g)w#&qm{&Bi6z zzj;}HVnc3Fjf*3X>$k0F%6Plz#oN;g_8zUdbO%!2;ab)WBjm8wAm5_22}Y(_-eNw<=Bn5} zsmuFrTb%0h=IJEYJU-_x*^`PcIiX{0oK>Pir|{;4LH+34IVi9jORHC=SXb?UNb7Mf zK94)X=dDhq=-+;bV*b+Fjhy8!E+;#|Wh%aG9%V(7+@>}(gTJjGV3wh{J(CKzMzmm} zk>NDA?+i1(8J=kLGfPRlmvw=;cUNjW-w|oq$Y~`qm(dkYUv{N^xo}E9S-Yk)hMP*lz+O<&axa(YbUJr~!y)AC8iP^TS#6^aGno^0<~w6m_&-ATUEdV>42m(G`}+q8!H zq!H3P4P>`|R&~6}J2rH6@VuU@MgLOt&1H<+A5JzB&C!Ywf3suVTpf-IBI@?Go@+vf zj0C-a_U0M`&1{N!C7YXMkV3f^9jQ~1=8uaDvnp6TI`H<8^BLSe(HAwV+oX~+J2#kZ zooS|ezRiD9?GDC;_suEBNN1{HV_?2EhR#nh2088c7fZx8mJ1CxZ&BSiC)s^0$U9>> zP&Yciy{^?mNiP3kvWSAF8GXt*^S5n0>{ln1q96>9sNn57wJ5o4oHg8+pm%w5OXtZH zJPq-t2gX_VjF1B-gWON;rW^gthlQAru{p{t>_XRE-uj{|i6>lLA#`ZEkrBP-2~*R_ z$$iGY(fG#zei+}_71!K+OOb%vc>B!oC(X)VI+PkOi%X}1cjBxEh}GEZDhpewH!5iKDcau{n6Lb;o>%UuJ>-!<8|e&$$EZH5Y%W zJO9mk)vH(?fbc&r0pDV&Rpu!a_Coy>y8{!K&R|{Hub3TJ=#BbyDRfxFRX zvxZwI{&H}(VZE>lnZ-MpN)_qet)Nf+dL^R|=WR`!ik#6ue*9CQb?p+xe)j23H|E&g zjF^YM2=kL``9UDb#!8oI7O8kFUJH-9>$nT+LAi_S7r&tkowyG4=j-X-JkWXb468bX z{GPW~RocwAhQwZ(&KcFqnmw<0#9_CUYa!j8XY_X_x|+?H-$2jXgpPHuU&%S#l7J7{ zW6&#Br7hTkQ(dRLOo2Y*LcTpQBbJNoF_jYL+Y>Wl-pSj#GIw(Ro6z|`8^l^IPS`x& z?=@f-Up$6dpEii3Wbb%us3jiRyculEZq8{JO0FJnk6ML&V>j4}d+G5rV9z&;53)KJ zVe9S%o4U{JToNufs7V=58NTKSUt9+4gUgQx%&OhAI=&X2f3a?;SytlmCvQEw@;aws zy|Re?4(~>L?#)vA!Hb~Qd!MjHZ-O2CmYKFhoKRr+IMW`_o7ldAOKcZ@a&z`pREYC4 zA2t%pFYGb~JKOZLzuQ5a>RRAsBG;Awm7?=rc&*9bV1!ZfKk;$)Jum#r?7!ht-CwKP z4eOMo2Oj}_`iOpd=BfBPR^3S8%goL`syhs@(fAX~hT&%85|0;-!lM$UJ!gz^n&Xba ze3*_uXFtls`wW|FAE%`0XsjGxh1}dR)}1aMEsn#Z;JD7NPSM@ax{JkQ6MMA&Kpuw@ z2W6(*F1};Lr~3!+*>^&ZU^kU+Sij^&A3Xs&^Q0q+8>#<|BJU)80!~rL^F}W!aN9SX z#9#Ro$UbMdMay+mao%*|k#zc|Fjzh|jsdOrL-O_KkIo8rUOJ;rpEjf1W12VC0z1Sj^2X!MyE~ zerGwKn$T3nc;-Bbc>Iq&27PTdHd-0fq#lLtY1GaxKk*s|2iG58^TTZe}&HgqCZJhC+7e=jmE_&$@Ll{(@6oi@cue8c2s% z8oB0eBbNFGJeE@1RmM!S)rk4EzhI8KZ?>8XRhmq)GADFBFs@Ii+iGLBIZzSv6*f=! z+f04w4C-^OaRwz78Wo*!&w_(1>VX+|ZpS9`OU4bx^-0khV`hn{*}CjsE9xma>da|P z$~nC@z`-@>(SN+=FTEWeWfhZTbR1kg-o8()KLg?|l+x28A>iwcIo{pYx z5?C_ym!&|zjD4^YI`)?)Q%hXHUNElSl=hx~BH(?N(&dBg6&$kKYMEpNRMYc>{P&+ty(4zzi_(bXBKFK_ETS*|q2 z^u;4Z{n50Bll_v}u830D{p*@mvu|yQbS&=&E)_+A8;n$%-?W*v5FlhCZxP-^0UL~T zXGZq3*@tpA7`>fIRp4#JlPi^`yiS~v4MtrjJCE7l!G6;XZ1Ov|Yg*53Nh+MTAMcGR zO(D}jr!Q{S&>8rLXs|u2m~7sAx8q9$9$p3X8=&Q>ioi7~X?-&vdqgKGe85goNI_nj z#cBV>W@Sr6R4)cTo8Y6%@{4BwDXk;S53Rwa)q>9NY#K}(Pu}*oTCXHiPz^5kt2tb% zo@wS+ve132!zZIUO|qjo_E|IElG)8=pAV~BrFrId9cvy^lDWuq&l*+}TUQgOx{2|2 z5iA+}v)O2E-T-2W;QiTqI4k#OppBT$`*2U6**9x6T1?RdIErN3R&o%Q#7NeWkqcZ?S>*V^om#k`5l6%uL0RwKTsM{M!Lv#@m%!6wp_ zSB(_2D8$^A_neo}A}Qi}*`6yL(v>Ndpj5<4c*y{$$&=f$M8gE=~he%XqLe9kr_ z(CkwrOoJql4*)ip~BfFq6^)@2u`hb>I ztQiBLCwBqe3j63KeYvWTQl?eW*;Sqe!A2h0B?XpcU?XLQ>{faB`1oP((nC{IXVMDvg>kc5L?4LT9r{ z;V&xEX#Sp(|Lq_mR1y4VeQp*C0&Z_h2e!4R#>jg};QEM0MUU`Z~*K?%Oa&9%Pk0`m8=9eO{4&vR{c9x10gFC9DQ4pqOFVy^H2Yd<+RU{U`*Csry>~LXqLmZzdEpv-mQvo^C4;{7 z4a_62n-wlWHzlN$w-(SP=;Z70Nw{I=XK8H;yOdnpzG=iI8LaDnH@O^RDf64;;>Ba3 zKg35;t}J@_9iy5#Cc?)#7`*TYQg}}{FZ5$R)fc*t>5cUBJH{~cLdCL@Kc*^s$GXrs zPZSlrYxp}|BKcFRj(1Db$WKugq2HxM(v5eG2=gsPV(E7mE~fzU{H|K2LszR!2>lh) z?H<$N1L)^7yLGH(-jhQ1dJM7?9Xe#MBZ~QqFFwT?LG=zB{hi*E{9z8H6^D(%&OAm3 z!rVUy^5^duO({L0Q#EIxG5jIeP|A4EUKN%kTp=)5r3>#FL(Jwa=0;&Kwz z)Z+IL30=AsX#dt`?C1NX2GIE-sl^Ko;uO^yPTkwk`45pq><9KxMaZFTKsIel3z%%w zzl*&9A#BICVBc=X)g4d!7k3VzjX7QHUQ1j)Y6q7$k|^{nA_zWVSPOSTe!$=S4QMa1 zSInN7l~bbRvfG2LokE+qQV(;h8};{#oB%-u}7rB1FwlE?d?Tk?%WyXtghT{+R%-Ssm0GCp{H~O{RP&! zjU;Eo`Jo5Q=jhyr_V`DO1WlU*3_&?+0(P9+Jhl}(mpk*(By|7d|lqyf<%_x!Hw@X0| zTy8dp(DgmrlxPWK!MN_O;OtnNCMC{)S8y;g&f5ciF;6dmdC~iv5p1W4>Q#mkBJS8@ zWO2D$1eb|ahEjH*1k#uE3XjUp%N;$wWGkJGkE~n|hl0C?53wrdKJq;m&IR?O?y!|eN#d7+uL?o_ho352eQC1clWfW%yFRIie^ zU|oC%<7%-@=Qd$Qui^0_gD<_BxBW6z+ga=bgGPHqGr7QletN z-wbx<7GaB8^!B6uU-j}XapydT!5Ow&m!bC#m=#6yL(;-aJeezOhtEU`yl8Ya$54{= z?AKskg!JuFLlVB!b4Rb@y+q zZA?fHHE(S3ScPpWt`DirB_qw8p%L>%Y$J0G!ushXE^&F@A#;0Y9wqSzh z%q6=^7JCRj!gGCpo*rB>nwY7G{WrFsqIO>!@lNws7hq1M*553rqLG zuBE$Ij5M=L7xRvPU`}~lhLV0opz~Y%R^uVZ0=_mR|*^5R(pU3y^ zu6O*(nw7MiKX}*IhH$(O|Ie$&P%|51sls2we?(c=jP7PD5%VSfKK|G$5^+AxOnr&^+7cE8>5$bkvdWS+&-{e zS+0O69sT31{*m^RLY$)cbNm^Rrc?TLqk&n)!af@bc6xd1Lc3MKslL$be4%H+$QtLA z+eks>52$WG@Pr>11-=G7ylyW>h=Q}p z-`f>0=BBJ%kQ7htenrKj+`?&cE5vR+GQ}s2g$GdjVy&KE+#bQh z^?fI^{O12?G;p>CFV<^#k>2~!Xy-J)))nR<6mZKJVs_>BcwqIt&T!}?0HqyDDjp=4b zB<6iAThVSNW!ykh$h%{-FfTyJUNb>Xf7&YB*0XV{FQ8C50lILlb_CLM-iBvLkAp)fo>RQJMB` z8(|Ig#iialxKyPW!yf93xe-fzwA!q1(;Ij1)UXCv!gkvX*5_5)>_J(F&KXh1Do0@} zyb9J$m6g%Oyj#S)_BBok>LB`V`JHt_bg{h3xqosO#op$p&Bc+?c4sNfUo0k)Lf4eh z)NGn!?(;6p4XK*P{)|h^Nh~-rpE5m0BeSuIx!@?wm)_?rcXZl+dLQ#xGlt5!ofV^^&d(0NjKzB~Ue(jWQYny&Gs++5Z66oG3koP|}uaiP+4lPINJ2Feg z?8~|*U!S3Glu?a(f0k+0iNtW5^-zYBx_$ zjP&1)01BP!Deuhgm+Z0V3)=jfQJeCUv#fa$30}xTD;>XNGL{aiU5 z??w}I6fEYx7h$diQ5LRDimf>+s_3~at78(6=B(IKky8FJ5}c(|mo;1#L&HT{0j;bw zq#PAIpMjN)#EjzAA&G(Dg}&$bA4YR$F%+@(%iHAhr~RHN-XF0V%oE>niN;cL&x}y} z!6I}hOT>KjogQ3;MvaPgUd=5g_d-9$x*B_JL&6?mWtlxca0gtO&VM?xEKMGpQNCpS z@BILupKj9e-=!Uup%)f-tnE({$^Dyfc;S{V=ktFV<(xINp2cdm|0E<@VHtWfb(A%5 zm(T})g2M;Y=Dv~O4EH%p+g!iHk8A5Y6LB|K?PkJVZn&|uckif3YnolyS&+eT?f%8A z1J^Z{!O?dj3pThiDeiA0#Y{#l!&oDy|L-)HAN%_kd1{;WA>MpDk46RCH?@S?^C##W%6VWv>%=^Vm3P`b&?)8J8WlhZi$_Ndc4n{F1Gu#K z*UbIWkkL8WS(9_JMm5ATTXxPgYdG_WFXbD!IUa*+Shq)CDgR9X(og%xPG2nVv#3w| zkTp|O1hwry2LH4^b&NfqCmw~Y_!H}EdBj;SzCtFj2+$sYG^88Pj`h4A5PJm8FRgl*H>{YV zSuDzbqE7F82dv)IFF&!0*#^WT3QAJ0XPz|UTw0wxBh#zfh43rK`w*<-h6|i!CwrCY z74%XWWqo8XmUr1Bk{*>&1I@M|=30=Wf`+1%{guz!@f_xON>P4UWql(qmLJ(8bGenb zO5}ATr;`0;GN!BWZ30+F-nSPX_ zbPABua_u}~mBsU{r=_bB^9)b8{y9Qze3f-$h-o{kZAC(DOIp^kj#D~WAN&eki*>jb zo;4$+bL;ckSuIca)u3DxKc`Q;72bf4D+`Xw1m%9v{RlR~G0!RMJT`73KtQOvnF zVLnM-0jir>K4Sh7l3}h4D23^!{?e~F)#Za3IP^mvni-(12`Vvp*ySmDCqN~dS0&~h ztTEOW8e{sZYSV>l)9YB>fOzy|0kSLzkZF&))cDwRe0{xbdRhB65WgvKaY1_3%u)i2 zl<6#CYLW+WuLde>_mWuBSi$UmdAb* zP=1J=U-90`a%}I?Cn3rj-H7=#3$z(&G$}%1C;60F#p{?tKTZREeGuh@s*cV?3|4cS zM#n-`FSFkh_l2zQHh(xB4^_>n;OD#Lt)djRfQ8>Kj-;3feCHW@`DuF-r?5Y=B3!!+ zos+%SOWQNZ!uDdRxXn~8-0m90e1OH{-p%4D8&krmr|iuf!k%VTxpewCTv_iaV$Nip zxvRMx$agVUn&Tte1}X5@d9|%>Q5Zi6+ToL*wdGVbGro^Fz>83}bF_@@ zEN!Rb+skylXMOb6=7;5!H3K8W2A01&O|2tUEAx89d>MjxuHRQ%+54Ck@pN>XIJ%zn za->}@VmZ%pd9~^8f6OgdK(8#dE^kLK-jR^hbIpR1o-VF=kkd1xf1RVhKrfe9UCet! zET6N-U;E7fORG@I@A*~D>wkxX3}o3o`)T4@^ST}5?@a%6z{i}(kD1@pYH-55z*2ol zhv`^FRfkmA{0jCRCv+M_{9L*3TRH9YfgLXk`(f5SqM}MQo3~hcu)^QHGvunMtgQrM zf5@VLzg^^XlH2Q|6nkmt0J<(-F%y{K%7MBV%aBdS(KQ3GG@zI4XG@(ted?^j)u1j> z`%0>UPyRBkLpA~@`TAr7=P9w~6Hkm!9G|GmR@ApNdz#tTp~h9rirSTCPcSQ}|A z=v!&_9@^PC6*>~dVMXXb zvsl4FdxP+SX7hO+M?SyT^lqm4^ZVk!^0ByPu_~lL7B6Py+hxsOVHV#mJHpCGvzmR0 z*${jfTO1Z&aYEZz(^&J+pK%t`^1YyDvTK%6Dv<{fWckJ2nR^A3SOHMP~Vf zr{b{kA&s#4qKxPoh%al3Y5BfF2R_Py@qLAZm96ob#R?JLoUm2CIIL`2*X*0jcEdLI zVpeupYjz{E-{!Y>(z4}Q(}yHsY=$llEZf{PyM@`YUpd*EZo5@u8CP!|D-J6=$8^|z z%x=U^GG_Dj%_du(H2pTy>&usMBrL0onzdFJ9jvSZYF5_iunOp4gI=(+Wv|N>XRARz zue9mF_PSg#Eemg&y~x@60R>*n%F32zA2S<SPXZUSGLx%WnJV3nIo@JcW=b_H(>G6I=CqiV*&EHu3`!nmpE z-Ac3aYVi-=x{6tOv(T)J@(sLm6tgnO*X(B2A9Ze~?{6 zwTrogCOSUR)fjQXGjLS)3cM)f!1Rd0AEG*q2%n9)%6!r_C4DisI6Mu_+{O=*N=PSaR9C*TTB(~1P~yq2KSaMqx)s)$2sW7WsU93;{O{|GFWH&)es*@7G_qsxuqeS+ee zsA}Fac6yi6o2Wrv_vp1Is(AnpAmK;IDJ}1WEj8&)RRiSm9>q6RgW>gDQvlQqDb%2KP}b3 zU>UlKh$#a$TI<9c*2&GnH}AsM3xXIJ0~(ain5^kpnBOiG#c2#`>2xAeIEaZ=)sTj_ zQcVL6>T5Y_UQ09?tyLvD*Gh%J?RqOU0f%m_)g)hbbgd8fqK%isBI)zisE&iQzn!X0 z-P)+G`29;eRh`~!gZep0f44ykJ4jX9s-`&fX{&1L@Gl~Kz9%f2*0xo(!5|+=I6Q8v z5^+E}bt$u*D)*nnR<=_yppjTR9FR_P9FRm6`n`{eDry@ZMKh9AC9gjyw7sfHZzQSa zet+oe@+>D$5<&|#$ZHRcZ?BT^6^6&B)ZfeLKzr2+wma?7RQ6Dh6jh5{$;ij%Qqk&f(=Vwi3y1X1a@aLQRi;lntL`w}7=kis+Xc75ZF;_o z%EjS97qqO~w0WqiMvJ?uzW9B)tD1yEwP6V8*IBisb=}YeZqv?g5@BF>-0Vny7_POb zJMNC#^k^9BKA;D>i`$ek9QLPspfqpOn?2MR9OkmAZBO+Se*ZXJrBm5nDB0W8sh8@5 zLs2jB`lpwgi?g3cV4`|!nlPDp7^LbVE;NJ$Iy*?k;x}4DdmPXZ;&DJ5Xov%=9{daq8;4MiK4 z%I8LgdWRgtFo_VA-vlO9c??Y*CUK$OE7L2(&}&NNbA+gOKA_6m;DBl#j{|Br1BcEd zRCOFCj8KhnSU*BaAC=4P1@+nj2UKZAS~5~%-!Ky0|7|)wQmzg4TAiXZaJSwjRBkQG z%#d8q$xum-8s=0{xm;kV*N!-#N<03i4sT^j!J_)=QbLxBgBR+s871}pwn5B zS=46d|5W4~qf{%O1AKp@%lvJWiVxru+{TRx(B+3M!4<3+t^BCxXcg)!ew}A{(ebw{ zM$nU^Rb6i}&7`fPRU7^LHOd@=uKM56Xly0@?jkS^p!5Tp9ZKgWsIsAx$6{Nygcq&p0Teu5ZPXbMm1zcK zV6mNnZWOuhR)iU=C`|*X%1KA85jsPnHw~cJ%MQ{n1go-=plD71{X8vjsbxBZ$V>wq zAri+$1qO(_2uugz!%;O$8$?>VAtmIfg@NKBTGH1G=xC0bsa-@qx-IsIsd@UEL@b&C z*EH3>rk3>1WEEnStSCqCrQVa(Gdf$M84a+@t}FY8Rvec-J!2~NbWfdbUXf@=pLmf{ zCaEmS8;{N?Gf#zMZ-8V^B%~RT_5z*urd-vHI*+RytP>J7X#gqGCDxTAh#=o7sk&$LVtiBT_WsS?0;el}2CO$=V_5Og{{RN7ds@li!Z#256(d-ex zCu>Yr9=@C?ls~P2&+MscxVN73qH9xCQ-A&q|7Xxh8o@3>8G3hee0#42T+a7Oj}6hU;iWg8JiKlr#ewxG@vmL;8~{ zKyxBP{dl({$=IhOHrR5vd57gJgNi>C$iHF)G!^r2xmFi3?|CcUVHhf zdsS{YIwxz|w2aC4zQu}GB&Y!;tD_7Jo~45Hb%+S{Val7O`e=iwPUq5@S!zVMBrg)v z45*9&Tp1l{-qWg_zB194{`L^P{InXN!;7ADAw7CpjnW2Dl75yZ&Q_y!7}1a(f0Vxc zI&^MF;t1d}&6qH4+6-<^LdR0y zMQXaYo~ouZi&QH={*9u&T0p_is&RoriD2`!Z)kyS5q;)AZqlBKs@m#JSw6JsIn|nC z2O8zWC4>kyGa%jE)d!xgY&rF=CcNk~Gl2IQn>BiRE*22vk8<#-W9VX)>?8Bzf8M1* zi&e|2e1c5f)%}+5gvsc&Ci8cDGU1p;dlsvn-ZE!CpT2dgNGi8PHS}WxLj7JqJ(j4k z0m6%fb9XwtL`@49gNQdXNGbPOqDIn2w~DSUq)0b2fDDw9%NWZq{^&A=m()f%-YF|k z=JP5kgkLg|a;cTl&n~5`=T#d@UatC}Zsi43B%T=%F{A-Zx<4fyQUT%OA!^SI@F3fx zFU5R;mL?ve_B@z2ELB?r#UMJ*y-HE$d#VxLSgyv<@Sjz<=0xndLuv9lY;miWs|X#D zC_Wd^{^e@3b{3Uq-?Fs#JIh(EP{EoLk>^*u9o&WjixZ*eTRxO^(+U^=tMb)}h|cpW z8nIHX(-Dcn^QB;i^UIf&ujWMNd1nY!-DpMBZng5$5sAWc0`*y~p7Pd99dvHB>fz77 zQRdZF`cwN|cpX+1YWUOeLe(cwyhP{OC!Bhba#Pzw=&i*pI?oI!=4JHlTD4G0Scegb z=d%@b7A3x`MR*u+sRl`CQFsPW=y*J`Ltj+msR60T03k);IgEPZd9I@qS?BMg$bdz= zh@$ggTKS?{uU$mHc|#R;aZ~$ORD`#PHm{<~Yt<^9W07lSK#mtnj>9L&I8G83)#in@ z=*n6|zy+!k620aDv~RsyT|@jto|yr$_>Gy7mos5>7C)|q>_piwsYTv;rHG7|P`dmZ zrP~pu`|SagZsx0MC>~nkB4W)?*X2w%Vq%z-Z=i4@)%~_qIl?>2#yP9hS_;S1I=gWbS_LG$GntCokq7s4V6gvKzS`{b;QGpp?<_Nx9AyGw;@XVH3YPwjT87qqjeJTL1)-|SV3D1WCa z%Wn#jl1Mvebfs@UQ>L#z9Y94Xp(P@aN^F-RbN3GUrh??`g z?p$lDw2Npsr_r^&YMG8ubekCv;W%3PKh>1>?Ncqh^~xvR*{3>&@NX1Pq3+$Mve#7H z3*sXB&42f&_x7XY#3GW-A(VE&GKg67O1gePEe#hB(Pm~qnoBvhX{27qm|sYdX1fD)!? za!9!JNfJ_|nE`gl5nQ)Ii7@lP$+YRC;`BNZclL3@i$XI4il!`HZL;yqw^w^j3!Uqa z`{P(aTy@$N8|MdkXcZKCoZJ6Lkak|`KWRqJ^a*tKDyni*Y+U(jOriST*43wJGin`* zD!ijsd+XI~+W(G93*p}ga!dzVMk#&bTGOWYR6kU^_=z0!XLOtu&W5pHaDJ zpyDFB%NMs$qfb$g(l*5`y30Fva3&KdeRl(h44lXNp!5pdKm)`}^q2E!-5KT929aCN zriP!YMS|L}a-x^*XEabqJAE9quC-BMBv< z%6}ekM7!~vN)H!Kgq0akG}HN7^UP)~tOzR?y-8_jalPEEgTyRi$^hL@rGKghNQ;gU zQe>1F5M!CiGjh<^i2W(rc|pzgG54TQgU>L*$R{Z4s`T_{YC)h-BBT8BL4JZYqP+jb z2Tgz zqIPunit1O5f1~D7SIN7X|J3YpQ?sW{!+*jS${&j2Gl_(&YPFB~l%WIfVD+HjrYh&J zpF9ZKi>hA3fL%O9M!Da4{ayvPG)lOMWgfZ1#6bj=n_bc`WyKC?lKK%4E?y$4%z$gy zLSEmg)%x8{NYPRr_w|3%kcWaeh@Ns;T6sggrlS)LWd=m|3T1td9=iBJFF`~``PZxT z&$ntj|7kqb(^)oo3+?$%y`l{wl$=IGzgL^|wTdos;Sc;=S}XUIHj6CsqaXM|fPVxr zi=dW{Lqw6sQ|3+elFpgPAu}Ln1$?1T(vg71QNjADE^5dCN@$5kdiuS__`>%$3{YnF zSCJ_H2b|AUL8Yncv>z)`{4LehmrbaW$u#$t+8HhmqL9phB=(TkZ|W8Oz9*#UBr|~A z&E$4@5bKbllFR_|bsdu5^)xA3$qXRh)@1cNs-h-EBAEf?QBD4GM^!bWWhvx(0FY*e z9vbT1K#5P3j`xJxwSMqIC?A={{1+n+CH79r{!G2Z)2H z9{0t+3#cjDAVSAqvS9=@`dfwLSt*Vpa6C4W((bF=NX+TZn3O#kll;PozA==q?yIMR z#30JX0NOhdBVRMwc#bbRTpUE>m;o7|#FsRX$p~lGMd%oySAxtq8qm>yRHT(B5j)1h z__YUW3LT!)%-14B=lF+cCT8mdMcSAF2~On%2XIVPH7SzD3?OrDvV6FsAVtx*UJPCM zQw^uykBZAhq>PWm(By~zzg$GaxPT@-w8}*Uivj;B7sO|li>MVd6qgIgh=z`wh+;7V zT!OIYCOans{d?Yw>3DsRvQ@#{a2k^;)!d(YKURL;vS0H}8u?hY^yA-XP9LtKmmjM^ z0YZtUaYUgfBS=m~w-`W^W^?T!nl%kP^=ar!&Hbwvy2M39iy4p!Z)?Fvm^atl^R)Js zJ)pr9@8xM4z`v2=7ihpTw_lXjBA8-Jd+MOJ#7_i`;~TB<@>E-WV_{k5>Q&dxF&j+OD$qsnDGf!aYdjRCZBro(|(z$Q%3o|KVcUYuwg z1B&y2c$!F|xJ2l96g@2C8LTfy1dT7XrL3}^5!ywxjMFHytfwzk_VxtENajVvm;uFK zW_s4NiDqKKlq+$I6Xc=HYJYrlfA z0*at<*prlB+0(lMugl>^f(EV0imvfNN(=A|3J`aZGRB|E26%?*xJAQQJuR7x)atvq z{lr%UjPJ~*v*DiJ^l_jkOotEwqPskZFHG8rdL{yB^sC$rSh)z$0i?eBO zkY|84h)nTT3J&%R)CLhIUQW5ep26Xgtf&w(phgBzpCC`Ss4+7pj;*EYmU zbcll&QAn_-ceqyh6T1iz@5dYy%7gBPcmj2%MSyt0bJQC}7%?^{Hw%?4{vtu#d9nD* zqOYYuEUah`r!3J$5FO?T)3qhq!vI}d$HF`jPQQk978$=R#19?^OOw_p%F<<~?wZuKJ$=}li zQTWmM3Z8O0gvbJ~C8L68iZ+N2a0*SV=$Wq57X{$CZ(Hg6MV7c5MEVzi|5SD+u&7w<>O@5ZIDwL)JefLC5&R84svF7QQJyf}jz#I0 z!EVQurj5^Ezdy=e&Ns=P?JB;R4_6*m-MB|qM!FovZ51o!}9O5iOzgIsb=?JFh zW@Jywn~sGw;Y8lARIjS1 zu0I>li9W@hD7w3%%TV*pi1lC#(fi3Ec$P{4QT&a+Oa`=r02@Hk`7mdb$vc{s!rgBKJG_I$ydo?&Nn2pFjyNV!z2ZC@;8#!!>t` zUo9Pl=>0Mv0sqn13z3DckoN&g__2Jo9lhl{jwEVb-IG{@f8(N;uGX7}v!BY#o;rbt zp1ja$Iv%G0{#PkgQA*+`a=|Nq#&Q_E z6TX5r?*3YyW+E9JE)F6V%z%96kXLQbFcAyZq{sv_fSj($V<%Jax+XzIB^W^G+u?Sx zB5xlcq^JbK{SD*X?GpZLTwNk;4##? zu4lQnA($=cVFoRK&F~ARkyJXyEBZ^^Y3S z0YZvMa6Q^vAEQh$h$=9^jx0ISe%gzJ2m_~MQ8N)=UQhVgGY7|AacCDJ#p{ho!)uKj+)?1Bp zBGJ<7?|EJKIhVxm^UWXkx$nn)-SgaM}0pigYI>9m4P}3Rl;(NM*DL5_K%I;j`rB-p`n}qjEm?DaaVtDx=PM)o`~XSbX;8X(s!w2!9l& z9%-Esiuc~;&CSl8T;1Kd;1Y$II=$305_ zgwbR0+BTv8;C{GW5fgFXi{Qn6pxByLpy{i)?)7x!uJkLc_i|EBT=sH+sUa&rgny^i zx2n+2T9!Z6t>rE~aoT&Y3s*4IOsP2P<-k1>x|%XkwQ*-9HH*96y06QuhU?_u&O~y> zQ7;E5KTLKBMK!=hy;vQ0qQp(_rru`WC2vC=%VSy>H@zI7^w12Y+x+pr9C=Iw;#-iw6VRRyDa~lgfrBiljweo)$66(3aM8-_~xQ|jV!M@Nr}&11au=W&UhnU zvl{2bU4__+x85Zb-q;#sra~O_;=6^$R+0h9bJ1Ed`8Bcn8zA0z7tn|%RzK5C@xXg~ zKHY4BTS2K+obC=-$Y&Es#5K0E7Ld!M)EKQ2%T?A%wxKi9;^R;>GFvmjt?v{m$M@y`n4b81Uvqr?>E(aJ$XBmhz z8#+2E3IFOz-Qs+=`D&gSr%z*BSh>wKiqqZiXh{nz(R5PW?IL(Fy25-O;3wWvnfTk~ z0PS^p(H@;_X=O82ZbBxW^ImM}R_Xr^00MKy;IS1RF)E2qDGB(=R9}3CCp8adv%$2p zmDS(OrTEtUWuxqd0{ExcocP@1TKwwHrunU{>ZVdgKt*_;C(X>&oW}`zSAj3Co3#Nu`r75 zWW@(KKP#qPU2%7JsFPJTClk~*$4nH(eAuBxN*Ajl_1WDaKOO@~0rB>W@3cExLqY|J zpI;6zk_2ks1^*_mFVZo0PGc^9ei2Z3KXmU_7pop^=wcNyMYli0e&ql~+e^{hBk)g| zR4bl-5m4@#reK4d_*J1~iI?Atw4|$5AmboL1^&nL$3KOpQvsa|P~&b^jE5PuD8zd2|hWTHQT2dBpg6H!YreFCXpiX;sS32m{`OC6Ti~o)|{= z#xslMUa=IvzXPd9FKb+o0P*-cgs%6p-Y`IX{Z6EW-qws@u@Eo6bBj~LII9p%OR!=y zJVp}(aq_#egc@`<<;1)1^^!cvqYM#;zWqhjzE83u&8&!P zUJi6tDhQ`ge_ z1FfzBzwq)(jU&$>t4Rnau&{nJXNMjXIS5aPrwy`d1c{mW?JY>B23g)<0phE7L3`RT z*lJI058eyPVcZRfuimr{%zIT3OL5T40XmxN#S{F5v110avqG^!FUoqYR{r9Xpbm}q zTD6OD96d@iJ@Op3ZhHh3yZ5l9u@+CiyJ%vvHKBx9i+5iRU>!IlIXPkAsKgPt z;!5Tk%0Jxd@4uYKc8;bEw`zGfj7-5A5 zi-oxR%{G2T{c%l%?+5yO z6i(h8N1^gusIZu1{|@&E(Mk9}NWB7wN(u1?%mF&nep%w~JpY&ZqN_a%hkC_c90hX# zdzwDES7mBA#;Wa~!maO4dBZ9}8^>7HJe)=ks?twmtT927D;|RzQqQs0cmu>gaCy2h z)*6#bi+Q_HHLNsE$)rNN0>7B#miBsSLo6TxNUe8=o zM4SS1fFpJK7^`T2S1@-n!GAONcRVG%VO0p>IQrURh1}<~ro@SO7jp4_?*h2eh@E%| zesYlR`|yQs^aLyd!Qv&j{Smr36?obi_->s)!SV!2p12BbK^)@%y{{vMJ4ef8B``kG~ziqqfsAW0eOa<~FT~$KMX$ z(}rol5m5;Nx!y>?{ftyDzJ9CIys1_z)0%ksElW41S}hC^U%o`qKC7*n0rBF?0cN0` znSqcN2}OfVh2qQ?&wYGW8)Gi+dpUr4OJfcnzgg*I`olb?f8xXU_n*0c%}kr(w)Z$a znr3w{Kz#Hbqqyl-tSKWtdH?#&%mMr4HCVjyuK8WCdgC?y5I?*epdXD)KNiifLQJN3 z8<^ zFV3-ILnTMt_HuxBe9? z7>tK)Vj*69Ie_9BUtuF_#XkjXd zpNALfk|{2I+tGq~cnc#yocZ?2M+@g!ZK>|_ht6oli7yAJBvvblE?DWsD8!*J2QcaU z!i0v;w~R|)+*C>v;>@=gMb5{YSOMa`mjje+_o8IEN~6aPgWnUJ6vRy2`EmfWY(tVp zCE{*JGKSK#`BoeMt9*7}MR5zP8i5?gF8z81&0m1UDOuv(mjjgVO^urlC`3CJ;9sox zg;tQU5C^{;NJm_Yh?HAN?3`OF5of;~z@(d2A|_O9kz0{C|K$KyZC+SWqqhgaZM#$? z4uCm;NqaR3qxEM8g_jiz@&C&KEON??UScwS4V#FE2~KBZumz~nV%*(0pAxKGjGIr6 zWAwMp`X5bxOYu4;!hdi0G?2YD`4L;t6>Ny(2EDA7hc-f+FOC@t;7?HA!m<4 zucnE&P#&+85KqAzpn(bhhn?{p93-~lGq^BaT5iRAY;La78~&6y`_H1(e1%mtgb^Bj zVj6|l-oU|y@XcRl%QGu*zjd7pFQUpRR=p68qtt(<)UajN{BpGWBlL84id8#QEXA)d z2k7JYOa?Wn!Q`RA5n?57hB<&$)=`Pc_|D`px5MrkV^Z+wV9nNHxRR5VJ*0&DAmb<- z44}(o)ePY{Iuev3cO`f>x^-9)F{g$rt?I#IDxQh&%%W*4t@{3JxNuoIz0zvr;W!G1 zQqU@#5S^UztE?n{g>Nj@E2Q9OdFydz zT6|+fp&&63*Th??=R5e9R)9Do<^UBZ(#8!|Yr42%WWivso!`AgC$E` z4_h|f+i0~85+YuQw^O5cao-|9oD8?2#qZ+gNq~409!WpHYeoBS{+r$bg@V0eCQgOh(xOecObQTh!W^Lc(Z)Q-W;`~POz|l^n#ygq>KV|M zy$H9Z5u0%nCKlp8m;)4VW{N-DY?U_F;zW2XMQp)kLafDoFbA+Mw=8mbK3c!U%J2UP z4-eOe?;W!46WCqX>M)1q^9{x`qc_7TUNKpBxDgFT!WZZyUa(5g>kp|7%Oh+wf1E z5b+rNuq(xF$A9@>&7WAnloXG_Z$k3T8f<_#30_Pmw_C4=Nld{9DLEHdyfEv2Is39uqQEt;WaR}U}AD!Bc<173FT*{;# z@dwO7=9afx0Zz-}8F)Hvz|>}#=I;KtdB2>cn;+tdWQ`B42oD2H`C{t*q17!&vc*Yo zNje3a4EC@2zsF?*sO(Oh(K(J{tIeLm{ZWM}1t{0@$v6|N#5pN$FHX}ZS5M|^n-mlO z!5pB&6^(WDF8mApV5b%0e}*gml3v|~FC{pRiZ_~ygGVO~l+Ps0{iS2rdzaPSe< z#IxG@Z{V8SQ0N}3dLYM9^WGHvjvsf(k|j=uIlx#tQRH5$G2Q%RdcGjZ6xYKwsPJBV z1Sde84(Fq(d#&F7d%5OI^z&Y;Zg!5N=3_W{E<9+Jq=*|s0?dUtVV_kwR7}PHFb8O< zJ}vohS}{7Y4?FEJ*E0uKuiKA&1?j(iR;3(_P~E381!NVvUm(z%*=*E)JPvcNdvtL> z?#DQRGUrk#Xdv0Pf>&f(uYUf!hI;~$5xc#y{X2>c)=ky(wQh)|FIQp zfOMf^q-4JLQ$Uvad15L>v`WU?{Gmf5Tp1I18^muu@Rmo+q+?ZS&{6BP%)QGxXZcvT zU5R)z+T#^V)5ig(SRlP~%xZ4pedz8nE7JcS&ky_q9k+UW-sSke_XDWi{5v)1gX31Q z5Js4?f+Tk`wdv&0Hw#hfajUq$7{^ilQ}~DSwG+4m2{=yEPvL#kiW62@1J2W)Q&wKO zaspE!7P;xCQ#hAIp0t_=2uQn6$tSG=FSQi&t< z!2eGk5*(YHhQpd;pID_m3^1Subng=@B185Z|Bu*oAgw!X4G-ZsteTr)x1`+uGx5ki z-74V`tJPKj?fD0ff>(TMwJ<2x;{dYa??+J9&#Y+%MW+SOiS}!|P_gG$2!;9245J*M zTV+f`-Du&Lc+E8MbG*@zI+r~SfX|HkRp{yGR%e3}o(0gQT(c_Bj4!Mv8T!`@zbr&o zu5gEw76qEFB%ZN~8T4>zpy|rCGgddxcDC9&#bdhC`%9~Qh7R<8sqNBdt%|0Svl|0V z+q2JF@&3!WlHnA8-l{~|zp~1NFu(+jG85E{CkQH26=ns}!0~n@Zq=p4?dQ%s9r((M z4G^>^kanEM7w1*aS#OwXE6|>E)-I3aF39bnQx|YZz4Nuz&J-9Jx}v>ZnNmG-%LJHO zr5~LF{^dUXv52dinxUrd^wtF{#$P7qG@ZC$&GY|}EvHhui&l>ij-%sCO~;$ll5Fen z_&DF(Ai8qVDjy)G*Yc)ZwklK2OE^;r*i6GOS))7>e^kUn_nXbDOC`Utye9iws{9?U zwm*MkH8(cn%6Z6d!rHRb?OPo6QcRk!Ll?fy)JT&I^%tVV%T}G28o6=Vip|i-ShG9F zz2($@`8yo8t9f`&>UgNp%!O5G==Zq3F~TShnNfByqnvhqiHC;&fTQup@9`p7ibY3x zvdo8G#cy~jQvHh6%wK4Gd^KpzHSy9k@;a0kJN{s`FrXc6_yHdtis503`3WBewf_-r zdhPMhXHe_?Nw_@fMhm-6|d+m${k~Y4<h@Y1#L(G#n!zgRV=M$fEh8uORc z@}(2(pMP0ZP2KlqQ0c#M^CSg2(Wt-iIf=xR-=am&aBSZB8^7>r_l1@1l}2;rh#dIT zYWvbyay-NGe9>e}vkzXOh0m;HkLv0nK^nO*U`Hxj1gb}9iV>9puJn*7&h4n1= ziup9!^^Y|ySf&4nphM&7Htr#l)+-hgq>9h`)kdy1G(2nOg zb&9ntmZt8qsPLZ^=XP)Ef7a_J-iB`cXAL#+@D=fP-^{&Uao_It|7iL>KRf27rgOhy zM`ozDB=vm7ZtcI1S5bbl^4S&X$5-r99tN0%-|5s%t1x~gXEzt*ZTp^wZtdJqi{5+H zZe@z$?jgTjj>5CrbqsiwdS|sKnfL^{nbn?e;>~GfHoK3BH=rxo+zJX(X@9$?ssH<} zn4+sh*xarY3H$X(qDmgs404pa%HzC8|!I1 zJrpr(Q&svRyWJ*OYI|cB_HT*ml>5e(0`%zLO~KS8$WAgX-QQ0;gY03Z9;g5Y+wDy~ z8}~Y`9tgG@8dPJShjRUWzc3ZZVMiHsXTQ_h)Ew?U`JB$@aEE#9BWG^f=7njjs7iam!YE}c5TzMP9M|lymk>0$WR4EU)M znwiV4Yx>dYn1^!zZ*w8KmCJ5mY_g^lv%~pdh59zn*?`=3Nt5#dEzWI^G4UwcP|S{^ z8liTZAepRgr!iTjX-R}#fR5*Ukc;+*+O>@BH)My}{Y@P2qVw2qns_`tjIe9+Rkw=) zIVmC1u1$83T{^JVa<9}ogKp)uyPKi?@g+6NXZJE)_rHLf?pg1J(W!iPc~f4Nb$^qs z%XdY7yR^xc<=e=_W#ty7k_GI#2FUVlOz#!2%NihSxKh4g{5S;uqvVYml zy~6HJku_X~>J_o8n3{EIZ7*V%`+qHDzc9N=#)aIJ7KYh{Oa;1JzYMd>n6Am%tU!@P z-N}*FSed34b*Dj=WE6d06z3e7BUzXAO?(D53U}vOmSBC;lCHj+;dT*Y%B#;g8_062 zKx2xzZOEGI{Qp>PWg_f+riyQG~>A9H*LfeA@hsl8f720y&N|=J%`U>*6?5N!9@>R>B@{;&HULguN(0c% z631@Il`Fj@cKM46t5NS#b{WqBZsBHFAVrq2E6|}*Skz)8wMA3G()MdwW#7_vg8%=x zz$yBov|S>EpfD#WW21bT;)M`imqTUFxhjdM>TsA^a|`a z1HQ!<(e@z|A3*IY+8>)Z!CA7s-_#TTw}(b9+?9YI!q_bgx&*Xj!>(w0zcTirw04-R z%64@VKSfc|cFl}~il)`kb`6s&BdbTDF?NfL!<%DrWn_)1QWY#PsaS@GHyKszCy;4X9y3fRAj18zmbvwxb8R!ryTLY_ItYx%~>HQjZ@0W%=ye1A< zvC$#_SQD2AL5H7uDDs0{QB=E@J;rmHcl3n9fplZ}otE@(ExU3EBkb>Xt7U(;qEq$k z@|08?2cHUI?$pL$y0rRP1eftYjHX&~yjf~vigSs}b#~PF^PauU=-`|Rg zHnh7M)D>27ogP%6tqtwD293msa-I387p-VyFE#bfql%5~EhavgerSwyedfW>YGRi% z*)qf?CN86kpn|XA6ejjM#E!4wA}mOUc;z)*mjuZW>r#AEyN3ZX&UGd(Lwt=^HnU$h z73erSH@9OA(s5eN?TQBJINP_d6AaRE=4)vWGL_3XhtPwTb}j=3Q`T1YG;4Y)6HI6(vhm4>dJ?$9E9&7gq5O5pb zq1r`pE0RK+k4q9==C;O=wed31lnADuqIh;>||pzi$3mcx1;@W_BaEkP;^`S zQ&Z)$a+JG|9Y-zO*%M3+sc;A9+k7aV3dP$aO#yrg6K|h0aS!!vZ+~b^vs4UB@jG0J znsvZgOqyRr?{~1zn)r0O*3TY5w>sLJjQNC^K>D}a;fa*3vpvJud`UZ#?0)p9vpv&* zQ#7%QeaFNbQS3mwFP-UXA2VRi!MD5FIsHt}|5pPaXxsZtj*o5)#yo6z-5%_g4e4R8 zGVNx^evs#b*Lq-wOFwnjjPHq4xFDJBp+^e;Xw=XA8xlY=s-(YH9J~{rVh798B`Tk3lopVQ_B%{7lV!f-JW^08eJWMe}|;5 zRaAJSJ-}rD5*tXBwjC``dq>(`GWNe44IE`xGDh0PbEDk;xLx#{LzQP9Z4v0r+{~f~8_VS%Eb_avBmo3KHH4M^T9v*8K&d|%Els?w2NxRy9oINPlitH!-vhbhR;z?gi zC&$^zAsok?k1@Nc2aS9KHz_;U;h%}M|-yL0IwxF9X&7w zw@a58{c*;0G|yDKfGH&%O*C=oV-xyuDo(i4hIBNR#{2BDFZK4K&kld7x1rPQ?*7v7 zCp2=J-8+QinAu%sW;@Ze8FulM>2@{KyS_aFDfiV+YtX3acIV6;PMLwzh17HgKXK=Y z_06#B8*&nF8EV=Gb8`H9TmJ-OC?8PlHSlop{@B4&@L#EQA53>b9Ax2DJMvyD)Wm3)ez1 z9XKJ7emr`zEPe2n-Nc}`rUX*rS0_tT*jzi_plLucPfu2(ZF6xsl!6;5_dI)ZfW+_3 zp`-KcImY(0x10qv?rq#OO1|`G*h>xeoR3{E+1lXV`8WgxX@eyf;5mpOX|N5QSb+b+ z1ejJ|qu7P^(171~-2c5zeU{*a8MMeQ9l`_y&%V~Z-CKmSUjIe-_e^Ykv}BPz*2Fha z@M3$MNBEPsP4`3QEcd=TKQN0|=y!8X&AFG@Ei<+?E<r ziZ9+M)uak5>~02Rp}8yUw~W2MGi#cH^JnIsyqAJ=pdhU^p6rGhDrrJj$nIno>LiL; zY4_w`>G7<-W@a^>qF3R;$B~sd^kg}=+U%_Gs8txbpycg=wENFb%h0>4?3Si3I1pZC z4+@a%XYdxg+8$wSXY7T_&BWU=9XaJ0fEP#p(W9oV}!!w$kMtJP~kOnf8u7*I(+WP9f`TuhfT;4yEbq?8KLj z--z`%MPzPp-FiDd^O-PmgKPB9=lH>RrQgcayBqL$Qp#Qb0;iU&c>UCTBUY54TW9FP zCalrJ8|}`)LMnb4m}P!cOKRNXP82nN7yCxAbg&71{Vpy>0<`|Jo9uco)&JfmJQ~SR zf5-o$>en~hd3{Bo$>!x?P_5a^y(KwS%1xE$)MtE%u~;awD>C3fjH5aA1827i$imrG zT_D-j-ISYMi$N;e7xajI-G$IW6(R-dYyQAs$#1COzYqb9739t%;57yH!UQx^P%A<} z3k6Q2tr@(-y{J_ZI;iM&oJ*t^?c9|2w{lWLdj)yw2?T_Soh3!)q+-JaI-vFyzAQh}}Q{Go^OZGbo%H0R>!NHr7p%27l zqk`NI1#D9A*nlkxT0IqutqRUQ7qDHy@c#ttP%sofl0rW}6yW2YKl2l^OHI0F6|hHv z*I&Rs1zS7Spn!u4SUVEU99F<`kpLev*u%}T{5cWcwZk#r~NK2Ko4`|F4_$RxBX-Sr)kkh8Xawf{vyJe+5pJfeM^Df)zM* zgfO_vz4#jHm1s5;z-I{SS%TzqO=KJe+?4k~C&@0X;G=2+iYlm7LqLRr8?^% zUO}v}n5bZqvm}D&QbHB zf=V@fQtNId&SA4pfpgd#P#}j5&g%-CHF8vebJUzr;2brdC~%IN&ld6hpR54qusNe9 z&SCSF0_U(fufREKE-7%1n#&5DqvnbN=cu`=V2#flHa{tG4x3vFoWtf91$@|GPux-9 z95r_pI0wm}3Y>%Fp#tY1u^0K=bE0#Uq^XH>l>DW@IY^!$)4}xT7R-J<+ zs{-dB2~gm3j*{$3oTDU%0vshg-dqZtgCvgv=OD?iz&S_?DR2&wFa^#*Qp~5sIZBEv zaE_8v3Y>$atODmCsi43)NGdVVTMYC)#szX+sp_V@&BvPcUqi{bu`<}&3bq+gPXR<& zc{&;@aEdfh;1p@bU@2ekvW}A?EnOhJXe}u@|Ffbhs%+!ti;yZnTLmnn3J|Y=wNn8) zC}62nfKCcnB^98H0v1LE=%#?hQ2GArbtNo+3eZyltDge&R=|p<0DTm&;weC11*~`q z&|d)yo&pR|z*?sOgBbW^f>_=Z#H%LbNWf49EMp3bWCbi*3NS(e3zY(lQoy>T0Am!e zA}PQ)1=ufg{-40)H1DZPo5f_Z3uI4CbyIHkbOsODzTg(IpXmazpY5hZh!icprGV8& z0p=<2vBW6Id?hR~3b0TCON#<5R>0Dt0816Hj3~fz1uPp1kfMNPLjhJQV69Mq)pGpF zP*@ujWUZR87AU|v1uO#!ut5RqegeF!fMq@bHY;G6Pk{Fnu)-(6HW&E3tnCT%zDv9; z?FsOK0+#j!*r|Y}JppzrU`bDay$V>&6JWmrR`3KkpupL4zQat;^S+GuR7{S#K=$Qv zH|1p|PtDrI{`jbz{;HfpDSRwPJlBC7W*y;Ije+~I$?570V{O^oL699 z7I0Akt8v2O8wJa+2)L|(6*yt>y#f~B1o&YwUw<-={u-Oy;pymkO-ydMK&IoCoAR>y zCTjRu0gG<}{HlP3HUaJ^U}a5!KNO$|IsWc3`GOlw|5HpJxIh|x#Hkyc-4?I>Q9~+& zpBYU1TkO+aAohQ`DKG14!v3iOmed6JM}d!ZG(ny#ajNu#UQwoh^s~A^+VFQ%Ue?P* z1s(+~j|q@n0ZU>61S?=kOn{sKKGOyZVS?mR6IQ0zx0AUK=5Ag{JSHe1$Fo|IB70+juxcehIRz|N z2~a@+%ToeW6d>0>)}#cftR}2U2@s=zB`E=_Dqu-Ufa(fZkrJS$0v4kLsI7oSC;{p! zVEIYD{?%8)(vtuU6*!}B!r%j*j)P^yqL~Y1I$F3XFN;p1f>sJxX%Zk-0Siq6#5n-> zzpOL~(oRiSSrVYV0@jlR=%|48BLO-qVAV)~t_oNt5}>;R)`kS=p@6j@`T1WjC9DGp zlLQ6MVEZyS!lSQQPb`vLAfq4Xro8{wm29s9s6TRz!x((Y6-+f?gj)EVGNY9^WyZZ+ zW`YZ((MfK~%NmeqV~PUSfCTUiUEr!!s3VvWPXmiDL4BB zgSBiQGD7S>ae>%>>ZZKk_)PxiN>~>W4V+QHI*0&g6|fK@z&Qo1eh6@00jnPZTvWj7 zhXCIwVD&?Q%S-tBD;?bh#Y2$q)r4gZ0e(=x(uM$66|krwz;y=Cc(7yU2)OA28SHI0 zq+?1Df0a1akloA#K1Sz9{ zMgIWGDPXlffC>s&-4CFm0#^3}sH}k1`~YGUuzDXrRR`eu$8voj)zySW`T%MwV39t6 z+6q{n51_6B*5d=HuYmRV02(S_DL#P44BqGYd1(0q_`FS-Y-3X2oNQXSKxV8Jr#|8A zpvnPULmLJePfqPzAolIul$S;LVBb*zi|zq*Rsd-|IsUpTVNpGpbXUM4dH_8Xuznsu zF9ocb2auqECG!9h6|iI;KtBa6nFo*r;4?#EwLFl4YQhqE0D~2fUt?qKqU0v5Idn5clo>;NV!U;#UTsR~%M z4q%!BR;vS;p@4o1s0Ol!RaXNtc3Rsp7V4(t*r2|;3 zfEDQgmMUNsI==obSK>?|F*w0<`Y5NAS?vOu)3t8O%gS@8V4VV%n*-ROfaT=?-c`Wz zasZnhfa8ya)0z`|?*7Zo@)e#>A#H<7cUSbXnuiL~*9oARmt6|l}3KwbqbZ3d9v0T@4Pn}HNm6V^5ZD6D`L%>cp_u$CD>xB?b1 z1Bg(-0%ick6|jIAKuHBGV8+K^X(cRP29vT1SgZ`7yaHA!1Bg<<`eXo=6tFHCK(qpu zA_J(RfJMjvsu{q?A1jZ6)KC+a90RDOfVIW|>L_59F@SmsSY-^LfdbYR18AgxwZs6L zC}0&azWy{-!unw_X|90v!vI<;VC67?)(TiT44{ny)(Zn@tAO>w0OA#}UKl_J0doCe zfiRFxYQh3x09_QYKo~$b1*{1M@VWw){{raw0vs36TLJ5R!J>}>7Wv}qPhTah>IKkW z0SkHo3{b#QUI2p>uznYSR{`sG0Sr~Zf?WW~3RtQOU<3o79Ga}v1u{xaSepxAi~{H2 z9nWABAI$@{3l&UNz^YpS(-g4E7O(#qN?2YCCNmYVoEE@r1uUEe z@RkCn7jH9I#ocP~yI3rAfplxJn{u<4G1$fSzV)U+ic6%xN;lYf6tMmkzy<}Zc?IyU0@l0&*bLw^-C)rxkoVMtMXvz1DPYknfcF)!-W9+H3M%Io zuu}mGTft(t0%xrI7#!l!ugQ<~50e8fk>~5<5O7riYf8c5x&juG0=S`o^`ii8DPYMcfS(!o zWIwQ46v(e?!s<`}cNDNL6u=(}SPKf^e+pOy3gAx#toa1+K!K;DfJX`->?HsH*h*N* z31uEDU=1gLbOo&21n`#vR%rrws(_W50RB8pGye~B%w^G0#-x<$g6-A zkpS{5U>ziYf(lp%381h7)3n76-s0r&J0Tfrjx<>#d6|mqD zKxqY#H)2p$0qYt8lvj{_rGO{}t9*u3Qo@QwC=;!KWr_f*C}_S~Ks5y{M+A!+3RsQ^ zpq2ub9s;PNfaQh&>MiHzZ!!U_Hw4l^O;}k7ppgPr76NFZfW?FWnkp!}ML=@}EG7ht zmI_!$2%xnB-y}SG0BNIym4g7?vBK?Or11RPetDmk$DSOKf#031`msyF~A6tEr+z$pbRhXZh0j(_PF%i(~0rY01N$02dUnybZu51wNLt0r^%5OW6Q?r+`Ik0In!t zks5#>6|g1^z%>P|Mg#DZ0v4hHxT%1}X8>-?fsk>>{K_W3@SaMI6O-RvAS>#woAR>c z3~IQifF)-D?kixe8GwfhSY-ylQji+w6Y`kJBW|=#cL7gaAdUX*rrhj*82rQbYmEJW zE)aV^_}w+;Np*S>hdZ-ISn1?7FKh16BTqAf6~uYg5c02(S_r51q33Rs>6;57wKFPbyh%-tHl zLo8akK)MynDWBxCHVbNqbMw8d$^y_%0ZXv}v{%3?EC3x9u=)x>X9X;|0?<_f%d7x& zR{(((x&Q5H7LQ4>~70T`x$6;l9)D`3SGfRPGVECpb+0v1UD7^{HwQ2@p(`2ARsrjK0DPx_)jR;M zC}80ZfFBjGOb5U<0H0};WjR28QWK{aw-}t`ZtXCSvwv}cbn7=ah~&S3Dj3#5W) zZpzJm&fq%RFM7i#1^nQ0TZj~R)lGR>9|QGeQ@~Of009gha}5x}V33``Q3eARibW0= zNR1(G%FALGu+Pl^|0QDn%Pta<*CkRQzngNi3o-bX8<=bC!(1Tt;cm*y+81abLIG=E z02EiiDi;7H1^Bp1mbm~attPB;0Z>)}3tIq`XMlen;B8snUVAILKzdQxO?g?x0`@Tq zSil0Hssa|S0Ps~;!lD%*H5IT>1wd^DEKvbaS3xt#QUKIfz=9M24Hd8!1wdm4`2P@} zd43{0tSJNhV~hJA^CI5c!Xf4#f>v(I%YqcBAyxtFQ2@j#U_ACS zieLeqTp+X6g;PGsXCVp{=;r2oS%U)LbpQl1*|mz z(4T?(MS)!Z2f9T1HJDQ?xZ6X`7Y9RKAlb=o%FCJ(sBeS<)|3DkrGPah0LCa_O$mT; z3VbXo0rG|t)|3F4sDRZZ046J7H3@*J3Rp-2V44C}j{umVfYl=aW-4Ii2!Po>C9D?# z@|FS?i2#_VfR!Nt<|}aKXAuKDDZsCm$BD&K7s!MycT--Lhd>1>3eJx630cJi&uSnN zF;l==7f223+?1DfAW*{w24~p*OJl#u1!BL&O}W|I80=*G^0TCZ9WF4>A3k)GUe1{=7BHp>Oi}?+!CpE4I1f=y2tgZC z(*q?DzZuVCUGM=Q*yFlzON=n*i(FWA_jhpXfp$34< z3^JZIuDC#I_|Z*yS(O3y*A%c41HexTScn1OCIdW`#L54<0N>9pkt%<6Q{Dl;N&fE& zSP%g<{7*sG8v^btfG`7FJW_D|wt!RxfxieySJ202$lpqOn|A+E;B@pq1y0Xifm3iZ z6sKp|6gWNeC@?)6TNb)DZXu^{zMM*&&gE9n$Mh{P13VUk-~I6(9$*0m?=pZy1B1dY zkU0!(1_Q%ET#xlNU26{HzZL4ngK{Qo<>aGHT1HwQS)R8w%? zv{F-n(@GuU`%f8)(@cFf`IE=i`GNGTkqcyOP27~5-HgFUY(Mas*tc|n*td35UMMy2 zRK+QPP6L3?3%}A%4UlPIla30yJrU4F0i+q&qPqeJGcf3>!0AN-gDc!EIGACJz6#)8 zhCvd8?RftpnhZ<^X(dj(LlijeCTk^dFvCSgGFZmV3=fs1F~$Wl`f+Z`3;hMQpP*n* zpx96LDX9=5;M7VPLRc!M8;PysKcGX<~~4r_F7|&wscZ zZZkX7#A#-y0;ich3Y=#4Gr&88EMAB)a7PX@z$+2lSJn}5#04_6qi)K}k_-I*=Lse4 zD@lP*6qK$k;4=m7q6M5$aJY(quM~V=O~82tb7~5>q~M|H)@261j2*qACfqgj?5YB% zXFn-$dUi{J)3aX`I6b?g!0Fjt1?ZXFfBmV%>DogEqAUOj1MZ0J0-3_cZpsVs1Q<>P4MvtK?5eQ8Uk=JR)D{PGR7iM!QTc1D{%T5!e9sQ z`)c)Np@*u4)3baEq-Q?7I8@?vt%w4rXWQv=3%UuZ>=N%A-33%pkneQ?)fLR_E1;Hw@utzb3f2r1iv|k58X};vg3|{0 znksocSxj0e=wLu=1(o`CKS!13=~ReP$5GldBX zoGI$7z?q^X1D{ z6gV?7O@T8bZz^zRWVQjk{+%hA%j6qgyHIZ6IhyYRSwjoml$*VTft>iD(7^V~T_E-; zZpvG8qGYd904)Z#Ukl(fH9(e#$$B+uK2^ZG3Y?Sc76tcah{ZMqon{Kyp&;3uk9R6) zWcs;BLCd*5DYIXR)9yhAvQu7pM=XvgfGz`f^_UA}uqWJf zX9URoHzXLCe5EGNN;t2;+3}YYINiFeppB{Hih^*{&#MZYj{l^9JHpqWTS}ac{G!0A z^$vr5yfpG(kgnc!fsFp1n_?vf9?1g*o{a)51+Ts<;IRX6{7o?AiJCMwl{{6@z<_@h z6x<<|WPuNH(=8}8aJ#Q6=)FyVzk;0a3kXyIxArLF^9C!Kwo6Px6#QzM2~_}{25u&w zf{O+eQ~+%TwkV>2l^FoS72Mx1AkqLn{-X8@DXAv#ozG>;D1e`P2IUpNb3TKL3O+w9 zAX)(&{If+>1#t%j)KGAoi{ScGTS>K3Vp2~*r;i0RRB-O7fF=sy7oVGHrXcGH0WB4L zU_h*bDAP(?0kZyCkO7snSCemyNhbxHKM{+r3gS(X*A?V63$vGk8J|g!J_`Q$Qb0ci zaGNjde}EEabq`kHtmmN$ob^0hfwP`RDR7qaSOv~b#o>LS!3vHDGXFab~;H>BM3Y^9I zt^#LmZc*SY#ccpSbNtF$#D@%O;w;6T3Y^`!M}e~x_bYIg;z0$@Qaqx-S&GLLM4j@< znmDP%S&F9>I7{(!1%IQ{DrYB>N`?ao-5Ir6BdDfL|0GGd12(;52cU!2xa)3J$XV|5OvF)`tq5T5SgS zatA*GeJahQxj_2)#7%jBxGmXF6|DSKz`qJ^+!2rkPU5*njKBFGLSA)97H{eM0{j)k zJ`xb90ICi=f58go+5$ope48d9RKb9B0r?crUkrTSf=ZzAz_k`p0J#GO;R+yjz#vkA zGaV%rI1^AtfinT+6*v=6(EvXGI};GCCe8#@Rp3lO4F%2w)K=h3Ks^P{1T<9OOh6L_ zG66XMH&fzFKuZPA1jH(ECZH{Y%e)?-^}sXI-UYHAI=U%uRCdYkq9EIInZfQZ@OdGC zz%}%Ai5Kz*3=$NSG?nyKusnxYBq^A0z#s)sK;SxtD1iO}gJcCzKVaY+sRZH&OvWgf zS4hBk1%r*nL`bJfHd?|cQ$co!*f#=BI3Gu{;n zobj$y;EZ>T0yA8ncbyVvyc-obT!-ISbAko|#z5#eILOTq03 z0ecnrDwPoOkrD_Ha2tmd%qlJ5V+B(TIIiGXIk7mU06GL*$EOO)RuJ%o0#8K&XMIW_ zNWf*jRPyDOE*%Mjd)ZDBG zXHUGUz}XZ23YGks=7dqkm_#A&922j9uxWQ#mcU$ z>k=tY-%YuXks2w04g>G%*Azg7fkATxkcnW>N&(~-7_?CU@dXC$0DPt!&|YBDK}}Yf zZgo}wYbN*$4$r&qgz_ zcpt3oCY6qJflTQeZpyp1on%iEApd_r0D{LhRZY%z6);_ae-{BW6)ZDgj)Fi_WS#=( zKyalC6hH-n!D0o_fROvIWlEf$r@R2Bud5i~<93mN;7Zmqz}MP%FO2*PFJ@v@X3rhechoZPG5I2kaj;AE6wb2fz0VXH|2%)19$6y0!URbIIQ5z00Bo8 zoD|^mo=^ha2QKr8g5QS-_)I}ZV{t|S?OxGJoOZ7&aN7Mzfz$3S2KY$<-jcp0wf^D)nV;X>loxsr+>1XHKzxD0J)aV2 zFEDwaV8cuSmV$e81Uyy%%?B>>M1j+brwW{Q|5f0$n*~Aw(s7^HY4=r^c%63r6*%n% zGWd-L``_ErZmkSLJv6qOO@Zv6;en|oHoJ~IJFj2 z;M7{2fxKIS*aO#E$_3J`GH%L!6IWgVzlr1LUlo-=k%4Q7R^Ys@s;VH1X`_Y$=S^H~ z1x_#ODR3%nsKBYC2?L+3$w_8SHe-D<4>;tmYr6pS_%#4C8VODsAn zfcgR#>7pQIKLek)yAtQf=&8WzRssV#n4t5(mGo5$r^p}%itxFVCq&3-6tNVVyF6;&WI%e~Z*_<_-PtE4O*?ea<2hAqUY(6xbyJqvZ z+3Yc!rDk*5Y#x}+d9%4=Hec{H4bA^-Hpk88C$ss=Y(6lXBW8o&8gYSZW^>AH@Cz-5 z_-PDp*r5+Lf0zw^GsUTuX7ki+PMFO@ey4`a{U(WD-*9TZ*?ep^_~91ARc5oxYz~>t z6SLu;G{NMC+3Yr(@6F~vv$<(D{9_4NJ~A8pD#6Fe&z{>~8_{(KReZ_S3k3PcK@)MfEu%b&Gj!=IU9 z!(WqO!{10@!yh_f!{0Aq!=EK#!`~KRv)616n+<=x1IVA?U_)lZpGzRcA4y=t-#%co z%xw5wb}#%-&u?`>`4uWQ{H72aez$`Szp}xG-)>;T&mXbjXHMAgGahXCUwdr$e?DyZ z#ugjCU&V%R7_i~H0&Mu=hYg>@vEkEjujPSq4ny)1ed|eW9KfAfJih{MOkWt43kTgk z|14P+EiWs*TTC0nQlo=Gk2&-nEeT2u&sQ}%A*RxZ-G+k^*NlQ7RgY&Ya4`xYcO4)z33!(c5f}&rGE! zQgNlgGZ~Y`>2EgqA~TE50d_hw8<+!KHGQLXFXBaN)p*hR*G>^$B#Y-4rzMvT7NMY= zsX>AGvQ_#3q1l|N6$8&@Oh(eUoTyu}BIyH;TXZUCYJF_}%b8ju@TOzEg&KsUMg{(; z$?3ULBlA_M@?uq7&y+>)%rUc$PhzF@EyN{Ka-jti%~z$?i^5kjS{0`o=T3NdN#Tpz z7lkVZ{**CUoT6-F^?ha>k{g4*otgOxo|Fo2WyX`(^hQP&NxO4n2VBm?@>Q$$VsYW4 z-xqy~q~zfzWwG3G@K%ZmO)V9O4}ZlnYuUvsQUG6&zvyyN zYTN$jK-`Uv9E5R@m4gZ#Byv!VgM}Ov#6cSla&gd~gK->; z<{%FTZ*x$e1Do5p%Rwnl-r|_=4u?xP{U^tsanO#FKXEL8W3O>AfrAbl4C7z~2hBP7 zh3y`4P@I!q4(f2wnS;ML<2eVjIN6PZ9TEe>*UP>BN{2Lm~n!9g0= z;K#8>9F*mt2M4`5D8xYwg2jF32lO90VDQkS(Kxc-J@{dP)E0jJe8GhJd*iRH!t~#1 zE2lqSI_H;QP~uhmN`%@LN-gQn*R1(vY2^1-d4Il&&M&|0Qc_7eS18qkb2v;2(4&Oq zK^}8ConMTszpP>?{x3xqPAws#-SZ=9V>UYya2+KVPAw%e%k%Tl$TD^wz{|9&aB5|o z32zooEhBQ5^TTOc(vb+92`d&!jmBB4cM;_96?T3>+VhrO5UufXHoq_>EVTb{J~BM1K}ZZIPb`IK|u%V8eF=*sP{jVX1Ah^H8Q>fnDB2>%&s3=J_7e)OM`g zAQ%jt(&+4|g{k2`ls(ePQ%e_h&H2Ux27F`T8qAMcmT;zGUe|(eHry<-a^aMMvtV|&_dG+IyCgI< zKPBWz^@O^GdCE*S4GK>!;g;gL(^4_{Q;P?>1uoH-;i*MS^13kJ@$np**I(R}d5pl* z;JtS+d$H6T&0cxBiT>9=HHxrUB5UV*3l;+_DG z<(A)u%9_z*E0oKPRe-LVVO=1oW?~(nq~=XM_<2%lvrF7Wj+&3dd0VmO;}StqYp+-0 z#=kO$9!$?x>{YZwQ))hrWQz?oA6Mk_@89Xd; zOj3e(_~7I*oJ(6;nF=qUBCasKRazC^mT#R_l((%~r#0m5yw+*XewguUT=lG|EsB=( zIUJRhYe|VsiwTydwq}jHgG~DGq^Gb<-RrSwGIdj8(`2f)#HLm8iRsB~ao4jsyRI*! z*NjHnN@%W`*bIoRnb`lJvSwn{HoGw&WYrAIy2p)Gg^-$I#Xfaodm)`>SVd^2No;I@ zchuZ0S;j1<6VG!LJ~+NjTCO5I#JL00!t!$0Vw=S-l8$-1Kqbxl>A}MT)5?#oFIl5v z=V9!*nkJ4(9Gcj-QbNM0q!FVM63k4;E{I)-+>jT!qsKUz6miY$v3l3iWVQ9YmR5{g zo#JfQT}zW*e0(h}jQNk((n|35xl^w2^|T01*SnrprnpRC=qquhUdh;*fk|T$1}6^~ zE<1MC^|Z=tf8csrr8;8Y{FS)&Y#;1)Z*=0gB-8P@j<3WeWy%{mJh8vj6aG_LnI8P_ zwKu1QKw>MOxv}1_KtoK}k*sd)Yly2E_N~W_r3JdNK|yZp6a>_~_YZFPDJ_3f?&+b( z^h&(_BQm{ypiFkJ*g_Y^mFw~ME@<#bGm^a{M~T_U|DZ?~05 zm!)>GM0y=g2bWB*%G<^z)64UASV_aTmrQ?+(+^6fx8ZHQQt5J3drPI)FsGa-KXXtO zpxXh33eabz(&gCryOilj{nF{xjA0wUxHWu)6{g6L^un~Nbb1A|$k+MB?R3viPa%t9 z1XMaqc4HTydtzAEnQrV5q)!a%4>1xG+q%S!je`7$VcDTFVq(8)>?njr3@fz{iXtYu z>m4`tB_u8{)y?b+RG%S%lWIlvz?S^ z_Q}@7^m4^ym3sW*a`RN?Xp`7CX(;L*nw0ER{xC6JPI^IoO=VGiO(U(H^pL*ka)>PG zn_iMTv9E8s96~?zHTx~NpJ}{CzjPVx2q(R|UwY{_ZMR`+_yLeNAM{8}>*DQ{q!66@YiuWqhy3;g01LS=kUgJN=hOWBcL(=6AOesMe8 z<=P$sAx2B%7-T+7%>R-b>-()6tNooDn+o9$V`oFL!^E~is>8%aL!(1tW4-UA>M_gb zSME17DKVK(qx}&K23LGCq=-4=4Tv3y{nEF1IXUBf(DI3# zaBj7H(j>bK?&H{VxVpwv{v(W9wtAAIR7a?F7|D$#*r|s6 zt{|Z7J4QuC6ai&%Nz}ocs|cF7L^}<%!j(;$8*xKP#;6gA#^`;SHtArt(L|AK{Y*@7 z$sY4Y-WZpNQOqP6jcat$yS!89-17apA60d$PF0;cb?VgRYgJj`#U8e>q;&hie8*-K zI;)a8x4hDk$Ay2Vl3KY`>6l7`yHENU26vd&^+;lbHlxZB$crtgaulYc5GSR(`o5hD zKbJwjt5Fdt&__`^Qk6%74SawbgOk(k!PSoK{i*tNDFdn>s&#cHJ&gT4zm|q;z&gj+ zxI@F>eI8I%V#Wwm2EQ1AX{z#={i$`1W}Kbd2OT+FveB&$TrYE49cbX!wK|fhrPrl> zs3k$q3_~sXw$*`N&Ye~VnxjF797D&igkM~spG{!!3kQUjNdg^uOrVO{I#QLNa_yCe z9C@g!2QE0!X5PFYT3s$}fL5b5mNP5{`!}i6F@_7eqSJx?;omzQBWPiF%h7zP4%K$N z=M2{V=yZhgasd||BS)mpgXVY)S?O&O=!sH+O3XS^mGO4tMaPRFq#!xc6i|?$&f(!& z;BSt2TKN!WGN@#9bk(7f62RtM6*aBVPF?eNdlR#CPK(7JS zKjx~+VkiizyTUpu)&9Z+=cg$8tc6b8z3LZ|T>BO}Q3cK{bfOtxi=2rx4ZEcOg=tt( zKQcHE1Q^Kw!uI>U0WJK-+s`>5P!&+@Q`&Xl)<>i&7AVL~q}FjSHr0M`k#j3*P<9iw zSk~mkzyH?cM1ys+$%(#8)HY`>AHhZ2oLM-?atf0(V8pajvquk31zD2uPZZ`faOM-a z{*vPYodfoIOjDId4{J|dbd1(E^dA#sPi%HRkDF@id(Lq*eX_I}W@4CjEPD(tyNLIl z=#MGyJCpNKwa&>5n#Q)a0DC-fv!4J8ctU-F>Yb1q*w_iNYdTVu7dmhXy4uE0wugP- zT#zZ6eG-}-skLmrItumm!0%34fci7_x-*}T!RqVI3AD=Y$&p-Xa<%v?Y4KWgmJ>a2 zcEdTHm&?CFW48H*Gds@&wC=?J-sTbLXP{iCv;)AkPUuhISSPf`Pe-cKVP`j;(jcgG z*DMz|FuST<+{Er`bv;aaF<)8$bJ5ZxeekY7UHT4JDlG%yqP32S^ub!5HQk>Ut;}41 zp-n-R8aHWaH`D1bdX%|R*82rPqx^{NIiWod&?TTcr?lxnX-?=bz-3No zYqUUrJV5tiL|P^=i&ME*1p=jjhU;EpOsmh+Ayb11^Mrqp*jqhm>OmcmUr{9y~ zT;Zey6QzYPW`ngZB_oW_Vc&EY&S{GNl+s;MLrQ>joao7)2kLM{s^T7FZ%B8&y@ci? zPFl;?>8XrJR3&+*>tXVQMl<bK^`U#g7Xxre%w@OoL|@}n}PP5PzmsT6B-3X--uM@^dr3E_PaY>Zw@41 zCPs>dR{A|MYZf@dS+;pR&TW+xE$Q>|@?=d2j@FDZnUkHbKMc795)T}eKEUtfS#C0ho1#rVnV3_J#=)ck3ci~3G`xrfxaFn(2qd^ zRfXsX*4i!XZ{hIWZZSIjdXqt~mmtmp;QL`+d!=-SLgQq@WSEQSeJAmhM1+OvHnksR3)nc06 z5#gxf4>7qHUjzQAgXI)Xn$zsY^It`?o7+EaTeCZ6X+Su1iC;%6k46Y&jTGp+F#_%1 zF3>-~^Po4zLhy{xt_Ns3T-j3Ek8tyiNL6OqgI;jQ1oB4HY;HU!$~L#|2QH9`LDCS- z^s+l7P4A;wQgo%92G`QW8~QF>-4nVEH~WZG_-UErHutoByyk#>4{mki^F8PY81p>| zq2=(+0-z)ei95rSm`;V3ba z-UX&nLVke)#R0V_rDX!AD4`4>6D4E|)e)Rt;N?24E8wY6?e_Y4LH6}OdHO%er=@wK z7f1Gh{yaI+i^i!}wl|f$fHJVQyPfkwG~3qS1JJN7$@Wg+@3v%ngZcBLY%ealv)SI^ z_>LUKms`Dgl^1fn z!zgB8WAZm(RRg=87>A8Nn(NI&<&a%W?g^@|HO9^l)>?AC=m>n1>qST4*IaJ`uc%L+ zSC26$2H6V5ak^iLfRW+fohZ>s0!>O5XciEXQf?VAkrG-B6r_YUjTb0BQ=rBifxem~ z(2G+Aii?~k;0YiQrE2~P%%O->CEb2G&zm@q6gyH%fIg*tJ3oY$K(dqxdOcVR`uDA{ z2(BK|L}?n=bcm#nt*$bcRg(oY&hiePfcXoha=n}5fLoMENZ$rhQ9=WY1bTFyj$qx| z56Xc204ra_)6#(&phXxhuizYSF zs6i2_O2ZPa%W+A?q1vfu76sZrY4xU}n|A#(Z&D1394*Cw$ODWe)t2%qv$4`#S6g0! z@{Vrz>aIqzG#$!>YGd{;3QZxCAkE~i202f_s7REelYt);k*b&=QE#~>ReM6uRfM68URK*G} zL)WHUGltvW=;do&L8==kO#1Sle;`_uv6~Z@-XEL0X8Gc4J8>nv}3rKD5YFR{79& zELr8lEwN#h4-Hn!DqkG!wslNi1O4am_6!pSnr}cJ*Y|;|>6y0LhxW8!wGR&n%4%OE z9!ll2Ouoe5?Q2nsh37*O$yXQ{Gsqfbt_PwH}X*o=tv2Lke!pr1wuz0i;S54U5 z?bRe=;2K|I6i$uVAXh>O*a0oI#-|}RQL>!BtIb~HOB#hG))?d+yu?6pb||SZSuA37 z<(CZdn>>4v)}a)K@IHOC#utZMw)~z!{*34K2cI7<@{ABWHCK?5{AZ01PgqfFeF@~H z{>vc$358LwgZ>+)oPVdMEC(uBLi2$GmeBrofea@EYW!TFo?i;&|Fu8~KzgFqF)(@JTxfuNPpRA6Q$)CQESI=U#(l}iGR0QObN zWk9k@=p3O!=;zsgiNry_3iKgRt5U%Z;8Z1a1ISbf^#RUQLOTUg6$J(kY)6#V;V6!> z?_cNZKxblIi!YgUeYvy=CL~mg-{}h_x9_VKQrBxOq{jYxeaVHmzPla-PF0{+B_7rW z;8i8m^&f%00wz^T+wBx+8BnKUnyT!*%VpAzHJQWgyZ8FO!PATBpFVU+x5ASoTOrk< zWT!TjqUU$+pS~1wCALY{P1=UbrC_+fDD91FZ{%rTGHrbOq*kurt4c$(>eD_vIqf;^ z!xPhY`qO>dH(<^X#t<&GF4(7AAdmPaBQ2#WCo zaHe8GRcYK*b;f6}I&=SQDPLzZvb!_*bA5I<4&}b=ZafHfW_QzM%RBt!bbh_PBVs89 zV^VXv(Y-0spDS~^@eFw|hpPHDryEBuG`Ab?HmBuwt6IHaIW**gpB zKFMv$Ss-U6bomK^?k&)fs!W}YEgxE;jI^I^=za?W#p{oEj~t4t;$3-?s4@d6S&6$f z9k^H#sY;8z<9PSW=v7u+?bfw4o#NaR3()!>zS=#SD%;988Wit`RZv4G7jH7KtRhmC zUsl`uU+cd67{vw0@aRv|AfqxF2=Rgx=(+8@1lBcxEOaVtO0HoPiIVsofLpDO}#O&RbH*?`(6=~ zH}Ld+#xj$|SpBrQw!&0{y?)Bg2J<@V-Bjm)xf$JU$Zs?GFn>qu8onagTJRF<6R6jA zgvob#PLlPMn%BKdceanaBAdigIr_arfG3iTp&73vc({`LsCwTL$3btE+WlRr7yes_( zB1dRbT53qeY`Gg5PN=O60M{W~GXQS1ZEpkMSBbVx09ey~0QzSK;Re~ryC13D*<2He z9k&^uV=SIDYmY&;@$7*(nZ?D`^+r>z*@XUrtp&;@pqDPcYmnP`xqil)ifV8w%*)JG zrF^PvT~LT?h|LEeoZO0Q2Dyg_LmUHMULx?F1Yb%MIso4*6WRp~yo4Bh;!DU2pWhNP zUJz&td~8c;x8VC%M6l}N8*12i!3Wjvh^y81U7Hw-UP%MIibpS?=PXc#P+)7FKi_O@ z7w<#wLEu-r8RHwZEg1l}w6-|__}#2+lK`Ir;M<$+8UTLSekIAkre~v4`~h|jh6I)3 zVfaLreq;B9PoSlK{(4$`ZymvX@~3YaSfrWc8!J5r@Zii|aKLTb0B~btI|6`PAKNtmd^5Dg8+0%q0AJL$4FLGD)Yb-o z@3poIqRb#aNGaI^T);#cynB*BnfU@OmIP`j5GZ=SK!XG|2MHHztp!s1|?K( zUTi1wp)8#|f0nLM*+d}K#eYh%C<_{}tq5&Jz>SFZ;WMGvBYNXr5-shpwcYh&{BUAh zT?c(0f$1k7gv#weol7LU_kc4Ok*XwY#_0+wY=~>W4sSUp^ugC+rFTJ9*oO^6;_&ZQ z{0QQ~xwLqd5jQJb)XA-WEG~-|lV>ow4(1cp{2DOr5+!c|Q0x*)1#VqLs#2?ASCX{G z-+oSNZ-F|_22;mlC6$icH-T6e|KrA@+\n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 34848\n", - " 0.203922\n", " True\n", + " 0.203922\n", " \n", " \n", " 50270\n", - " 0.204588\n", " True\n", + " 0.204588\n", " \n", " \n", " 3936\n", - " 0.213098\n", " True\n", + " 0.213098\n", " \n", " \n", " 733\n", - " 0.217686\n", " True\n", + " 0.217686\n", " \n", " \n", " 8094\n", - " 0.230118\n", " True\n", + " 0.230118\n", " \n", " \n", "\n", "" ], "text/plain": [ - " dark_score is_dark_issue\n", - "34848 0.203922 True\n", - "50270 0.204588 True\n", - "3936 0.213098 True\n", - "733 0.217686 True\n", - "8094 0.230118 True" + " is_dark_issue dark_score\n", + "34848 True 0.203922\n", + "50270 True 0.204588\n", + "3936 True 0.213098\n", + "733 True 0.217686\n", + "8094 True 0.230118" ] }, "execution_count": 26, @@ -2298,10 +2298,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.479850Z", - "iopub.status.busy": "2024-09-05T19:37:09.478927Z", - "iopub.status.idle": "2024-09-05T19:37:09.484511Z", - "shell.execute_reply": "2024-09-05T19:37:09.484078Z" + "iopub.execute_input": "2024-09-06T19:37:01.833972Z", + "iopub.status.busy": "2024-09-06T19:37:01.833571Z", + "iopub.status.idle": "2024-09-06T19:37:01.839439Z", + "shell.execute_reply": "2024-09-06T19:37:01.838936Z" }, "nbsphinx": "hidden" }, @@ -2338,10 +2338,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.487390Z", - "iopub.status.busy": "2024-09-05T19:37:09.486635Z", - "iopub.status.idle": "2024-09-05T19:37:09.658646Z", - "shell.execute_reply": "2024-09-05T19:37:09.658024Z" + "iopub.execute_input": "2024-09-06T19:37:01.841836Z", + "iopub.status.busy": "2024-09-06T19:37:01.841454Z", + "iopub.status.idle": "2024-09-06T19:37:02.045788Z", + "shell.execute_reply": "2024-09-06T19:37:02.045180Z" } }, "outputs": [ @@ -2383,10 +2383,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.660921Z", - "iopub.status.busy": "2024-09-05T19:37:09.660563Z", - "iopub.status.idle": "2024-09-05T19:37:09.668286Z", - "shell.execute_reply": "2024-09-05T19:37:09.667818Z" + "iopub.execute_input": "2024-09-06T19:37:02.048026Z", + "iopub.status.busy": "2024-09-06T19:37:02.047682Z", + "iopub.status.idle": "2024-09-06T19:37:02.055980Z", + "shell.execute_reply": "2024-09-06T19:37:02.055509Z" } }, "outputs": [ @@ -2411,47 +2411,47 @@ " \n", " \n", " \n", - " is_low_information_issue\n", " low_information_score\n", + " is_low_information_issue\n", " \n", " \n", " \n", " \n", " 53050\n", - " True\n", " 0.067975\n", + " True\n", " \n", " \n", " 40875\n", - " True\n", " 0.089929\n", + " True\n", " \n", " \n", " 9594\n", - " True\n", " 0.092601\n", + " True\n", " \n", " \n", " 34825\n", - " True\n", " 0.107744\n", + " True\n", " \n", " \n", " 37530\n", - " True\n", " 0.108516\n", + " True\n", " \n", " \n", "\n", "" ], "text/plain": [ - " is_low_information_issue low_information_score\n", - "53050 True 0.067975\n", - "40875 True 0.089929\n", - "9594 True 0.092601\n", - "34825 True 0.107744\n", - "37530 True 0.108516" + " low_information_score is_low_information_issue\n", + "53050 0.067975 True\n", + "40875 0.089929 True\n", + "9594 0.092601 True\n", + "34825 0.107744 True\n", + "37530 0.108516 True" ] }, "execution_count": 29, @@ -2472,10 +2472,10 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.670466Z", - "iopub.status.busy": "2024-09-05T19:37:09.670128Z", - "iopub.status.idle": "2024-09-05T19:37:09.865056Z", - "shell.execute_reply": "2024-09-05T19:37:09.864458Z" + "iopub.execute_input": "2024-09-06T19:37:02.058027Z", + "iopub.status.busy": "2024-09-06T19:37:02.057684Z", + "iopub.status.idle": "2024-09-06T19:37:02.256206Z", + "shell.execute_reply": "2024-09-06T19:37:02.255652Z" } }, "outputs": [ @@ -2515,10 +2515,10 @@ "execution_count": 31, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.867524Z", - "iopub.status.busy": "2024-09-05T19:37:09.867164Z", - "iopub.status.idle": "2024-09-05T19:37:09.871703Z", - "shell.execute_reply": "2024-09-05T19:37:09.871128Z" + "iopub.execute_input": "2024-09-06T19:37:02.258543Z", + "iopub.status.busy": "2024-09-06T19:37:02.258213Z", + "iopub.status.idle": "2024-09-06T19:37:02.262761Z", + "shell.execute_reply": "2024-09-06T19:37:02.262194Z" }, "nbsphinx": "hidden" }, @@ -2555,7 +2555,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "00cc2bccf49e4abe8b47884216705c03": { + "024f58b175f14cdca925ad2ec59e5f75": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2608,7 +2608,43 @@ "width": null } }, - "0240b26e2e8347049e4a5df861bb7a0d": { + "0445112b7e674aa2a14ea027dc8bc2f8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "06c85507cf49495584b002e6aaa044e8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "06fc43e80ab4403ca27ca8d667aca1b3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2623,15 +2659,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1f3aa8b95cdd4842a621c7fe6c7a29fe", + "layout": "IPY_MODEL_4e22cd2b18d5465c8bfc301a968400ec", "placeholder": "​", - "style": "IPY_MODEL_49f52b7cadd644dfbe381087cf21b374", + "style": "IPY_MODEL_0445112b7e674aa2a14ea027dc8bc2f8", "tabbable": null, "tooltip": null, - "value": "100%" + "value": "Generating test split: 100%" } }, - "02bb02a3558642f7ae049fe605dabbea": { + "076942f2bb5542e9a9c126f736c4b427": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2684,7 +2720,7 @@ "width": null } }, - "0777e52962fe4e3c8c417ed705b0e27a": { + "07c128e462924e039bd30ffd94caeafe": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2702,60 +2738,49 @@ "text_color": null } }, - "07d8ecbe4aaf4a9ea4aa1e00be62b06b": { - "model_module": "@jupyter-widgets/base", + "0a3d18201bb14d5c9e73af43adbe2cd8": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "HBoxModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_e6d9313a802d4513bc93abf9ffa9fc9b", + "IPY_MODEL_6d3f4ee5439044088f65368ef798b3b6", + "IPY_MODEL_351c45295ff8422c8718ee4bdefa510f" + ], + "layout": "IPY_MODEL_7c5730df719649e6ae1137849667983e", + "tabbable": null, + "tooltip": null + } + }, + "0a606b97ecff4d89be8f66714f909ba3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "0a7f73a4ae2a4e5ab8db8790ef824541": { + "0b9bdabf441e4113805b54ee83d92f75": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2770,15 +2795,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_42c78a87167c4c7d8ffa3cc9532ac783", + "layout": "IPY_MODEL_34e238c0c2c24406adb5d978aec7e807", "placeholder": "​", - "style": "IPY_MODEL_2df53c624a43411fa4091264b5c130fb", + "style": "IPY_MODEL_511e7568ac814ea8846c93d586063e8e", "tabbable": null, "tooltip": null, - "value": "Downloading data: 100%" + "value": " 60000/60000 [00:00<00:00, 285192.56 examples/s]" } }, - "0bf8b4b0c9ce4e819a7f21eaed682092": { + "0c2a412a844140bd80a53f2ac3fc325d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2831,7 +2856,7 @@ "width": null } }, - "0e62ee29a15e4b038ba6a7584ca16961": { + "0f5233a082d94dddbdb0503eb9250ed4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -2847,17 +2872,40 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_0f93410bb3374b62a08a4c4560575830", - "max": 60000.0, + "layout": "IPY_MODEL_024f58b175f14cdca925ad2ec59e5f75", + "max": 10000.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_32aa1b55f20340c4b80b5c1a4bcf07b9", + "style": "IPY_MODEL_c0366a87be804af7bcf6f5cd7f11bc3b", "tabbable": null, "tooltip": null, - "value": 60000.0 + "value": 10000.0 + } + }, + "0f970e1142174368bfc637a6cd8d6fd5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_881dec995ffa41c3b5cbe3a2f2955ed3", + "placeholder": "​", + "style": "IPY_MODEL_7500e8476ee64140b7338f73ff7b6e53", + "tabbable": null, + "tooltip": null, + "value": "Downloading readme: 100%" } }, - "0f93410bb3374b62a08a4c4560575830": { + "10a3911ad0ae43f599855a0ad46d4195": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2910,7 +2958,7 @@ "width": null } }, - "10186f0c08c84916988b4064fb8fbbb6": { + "11645e47817743048239554d8f897a74": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2963,23 +3011,7 @@ "width": null } }, - "1403cd0920194d9f88d2e816c0e364a5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "195f6f44461b4637898d20c3f277f04c": { + "118d13a1737e460b986120e1cd8488c6": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3032,78 +3064,49 @@ "width": null } }, - "1a190a961ec641a28b3c636af3b264dc": { + "11c48316135a461ea55c3d08dc541755": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d54af3f6955d4b968858d238a0210190", + "max": 9015.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_f2fa408e34274722bd36f3791c967fb2", + "tabbable": null, + "tooltip": null, + "value": 9015.0 } }, - "1b516e69e31f4ff4a0ecb31c1298142e": { - "model_module": "@jupyter-widgets/base", + "13063e602ee246eb9b552b3b781fa85e": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "1c26fb9f22394b9299592a1f50ca98d5": { + "1510cd85e1a74691abd66fcc8f87c34c": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3156,7 +3159,7 @@ "width": null } }, - "1e80382ec0ec4737898dcc5f400fdb22": { + "156d3569cd004246a2f548957d78f2bc": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3209,20 +3212,125 @@ "width": null } }, - "1f3aa8b95cdd4842a621c7fe6c7a29fe": { - "model_module": "@jupyter-widgets/base", + "15c77a61cbac476e99fb0331858d1d8c": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "1658cd683cbd496c9ff193ba8d7c35ea": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b8a497f4724b458c8448b91e3ce44d15", + "placeholder": "​", + "style": "IPY_MODEL_3c640d11994b4372834d50a9621d95c5", + "tabbable": null, + "tooltip": null, + "value": " 60000/60000 [00:51<00:00, 1138.50it/s]" + } + }, + "16923bdba0af47908931030b52eaedca": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_06fc43e80ab4403ca27ca8d667aca1b3", + "IPY_MODEL_0f5233a082d94dddbdb0503eb9250ed4", + "IPY_MODEL_8efceb1c08634d06817a3fa57d1a8f06" + ], + "layout": "IPY_MODEL_a9b1da96fea74c509d14483d998a7cf8", + "tabbable": null, + "tooltip": null + } + }, + "1e5e214067f448fe820c272b4d8b60b6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_929f19e8f15344c999957b2ce7569264", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_6c95b5f8fda84c369cae7cba5624ccfe", + "tabbable": null, + "tooltip": null, + "value": 40.0 + } + }, + "210dbd38b6ce4f9e9f8b810ac64d03bf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "23d399d3b46a4f8d82116059129fd43f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, @@ -3262,30 +3370,7 @@ "width": null } }, - "1fa1bf487aa146f7b63aba1b37340dad": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_82aff8f27b4c41438fb70e6ac7827816", - "placeholder": "​", - "style": "IPY_MODEL_3852b37239ad47a8bea5bf09447ccb1b", - "tabbable": null, - "tooltip": null, - "value": "Generating test split: 100%" - } - }, - "209db2922df34007b2eea98c10204bb3": { + "25c0e4e85ebb41299102ad0b3e0880b4": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3338,139 +3423,30 @@ "width": null } }, - "21aa7e557ff2445fb6f9a8d7299a17ff": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "222bd1aa4e7242f68a04db434eb3f8b5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_68f553c7ffe64681af4d9d9b609619d2", - "IPY_MODEL_5ac7e0143087455db2057a05611b903a", - "IPY_MODEL_b57eeb2e85db4e6c90b70606981a862d" - ], - "layout": "IPY_MODEL_2fe068acde9747ab80cba22c22af96d4", - "tabbable": null, - "tooltip": null - } - }, - "24f5d44a2aba41bab7b5b00ccd550704": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "27d51d7d7c394b8ca5b9c6dc1f2f28ef": { + "26b545a844a84c278f68d51645f7e371": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "2a0e717d35f142e2ba3bffe16092cee4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "2d18ac7cb0b941438d58c73413469ec9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_30efd8b2b2434f878122eddd7664ec22", - "IPY_MODEL_0e62ee29a15e4b038ba6a7584ca16961", - "IPY_MODEL_63dacf2552ad40888642091c1d2b28f2" - ], - "layout": "IPY_MODEL_58df9bc980ff41e19f86d334f4e6affd", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_ac970746b6684c3ba6bb43eee4014e2b", + "placeholder": "​", + "style": "IPY_MODEL_c77f86be94734e2ba274bf4267c5a824", "tabbable": null, - "tooltip": null - } - }, - "2df53c624a43411fa4091264b5c130fb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "tooltip": null, + "value": " 2/2 [00:00<00:00, 680.45it/s]" } }, - "2fe068acde9747ab80cba22c22af96d4": { + "294184439d7d474cbfc6043c1efa9d3d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3523,96 +3499,7 @@ "width": null } }, - "30efd8b2b2434f878122eddd7664ec22": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_02bb02a3558642f7ae049fe605dabbea", - "placeholder": "​", - "style": "IPY_MODEL_83ed1ab9ea0a4965aa59eb8257d4f46b", - "tabbable": null, - "tooltip": null, - "value": "100%" - } - }, - "32aa1b55f20340c4b80b5c1a4bcf07b9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "35a155d26b984654ab25b9e85ccccd6f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "3852b37239ad47a8bea5bf09447ccb1b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "3e22696dc8414bd180d0e07a4a0a62a7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "40c882020753475486c7353c336a7276": { + "29ace475fdbe4624840332dd0e509ed6": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3665,7 +3552,81 @@ "width": null } }, - "42c78a87167c4c7d8ffa3cc9532ac783": { + "2b755b9c572e43a396e62c74fba5329f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_11645e47817743048239554d8f897a74", + "max": 5175617.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_7c13df622dfc4f04853781143737296f", + "tabbable": null, + "tooltip": null, + "value": 5175617.0 + } + }, + "3273abc0b1474d17ad8e620a0b9cd685": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a53594c87ee944d2ab253fdeb3aeae5f", + "IPY_MODEL_e38940706f02447996928468d3f523eb", + "IPY_MODEL_e127093a41b442febda97da50e709395" + ], + "layout": "IPY_MODEL_d9bfaf958ae54bdaa41267876482d6af", + "tabbable": null, + "tooltip": null + } + }, + "328179309f4646028e9f8909eefb6c74": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_471bce1ec58f4d4da4ed7ed290449c5f", + "IPY_MODEL_a8fc249e1ca44d4084ed4e8e978d6058", + "IPY_MODEL_f03a0d23baa4409abb0c7271bd76ab8a" + ], + "layout": "IPY_MODEL_bb2fc960507949aea6439fcd3c77de5b", + "tabbable": null, + "tooltip": null + } + }, + "33d5aee8319348e485ec3980bc726f23": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3718,7 +3679,7 @@ "width": null } }, - "44a4010eb7a944249e17c4373fb6fae1": { + "34b3d7273cdd4ceca25a11fbb32359ce": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3771,71 +3732,7 @@ "width": null } }, - "490e0855ef974a42b2647cfedac70b97": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_00cc2bccf49e4abe8b47884216705c03", - "placeholder": "​", - "style": "IPY_MODEL_7030838d622a49648a433355d555396d", - "tabbable": null, - "tooltip": null, - "value": "100%" - } - }, - "496cb780de334794994864ce22ab43f9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b330cae0665c496d9f38d6b6c39c32cf", - "placeholder": "​", - "style": "IPY_MODEL_94dbf69483ae44dc86b8e989c13af0b1", - "tabbable": null, - "tooltip": null, - "value": "Map (num_proc=4): 100%" - } - }, - "49f52b7cadd644dfbe381087cf21b374": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "4b14e0caa5af4f9688d2d2d294a95764": { + "34e238c0c2c24406adb5d978aec7e807": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3888,7 +3785,48 @@ "width": null } }, - "4ed7e0e009174ad3afb25e53f562b45b": { + "351c45295ff8422c8718ee4bdefa510f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_8e65bd8055fd45d8999b608481497477", + "placeholder": "​", + "style": "IPY_MODEL_82b18a92ec124a52a6892b31409db80e", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 64.40it/s]" + } + }, + "3c640d11994b4372834d50a9621d95c5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "468f054b84de4a46abae17b5d6030a66": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -3903,16 +3841,85 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_1fa1bf487aa146f7b63aba1b37340dad", - "IPY_MODEL_95d93d3f700940b592f8552c390c914b", - "IPY_MODEL_79aa1e210ebd44dfa879c72b499b33e4" + "IPY_MODEL_49329574ba97425f8b3b12f07b8d53cf", + "IPY_MODEL_2b755b9c572e43a396e62c74fba5329f", + "IPY_MODEL_861644c40333498094e62f8ac990f5a3" ], - "layout": "IPY_MODEL_cda1df54889f4e3bb275c8c2fd8ec82a", + "layout": "IPY_MODEL_0c2a412a844140bd80a53f2ac3fc325d", "tabbable": null, "tooltip": null } }, - "4fd6ca7a7dd446879a6f2f55860227d9": { + "471bce1ec58f4d4da4ed7ed290449c5f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d9b3afcffed047abb3d7c9215eacb041", + "placeholder": "​", + "style": "IPY_MODEL_d0dfbf919e5f422689492055a00be836", + "tabbable": null, + "tooltip": null, + "value": "100%" + } + }, + "49329574ba97425f8b3b12f07b8d53cf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_77caecf6cce84ac885a2c431ec321e76", + "placeholder": "​", + "style": "IPY_MODEL_df804279770c4bbdbba569e996a72047", + "tabbable": null, + "tooltip": null, + "value": "Downloading data: 100%" + } + }, + "4a900a7bd2894dc2905c92a999845c41": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_78ec8846971b49dc8ac35c9865ab7855", + "placeholder": "​", + "style": "IPY_MODEL_a1e0fb35ccfd46ac9b640c1e3a97a83e", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 58.88it/s]" + } + }, + "4e22cd2b18d5465c8bfc301a968400ec": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3965,31 +3972,7 @@ "width": null } }, - "506f569cc4834fd5b04e9abd3570d2f0": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_dccf399c747d4d1d82bce77b5b675956", - "IPY_MODEL_e8f51e9d01d447c3b27b88d0c146d11b", - "IPY_MODEL_c701552093d1471bb9ace0f6dcd2c9bb" - ], - "layout": "IPY_MODEL_40c882020753475486c7353c336a7276", - "tabbable": null, - "tooltip": null - } - }, - "50c7134622e34fbb83b07d440594438c": { + "4e5be3b38c73499194dd5bfcb00e9476": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4042,48 +4025,7 @@ "width": null } }, - "51120e68bd384037a4668fe393f7be13": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_aff0b45e2c1f43a9bb8830f843804ede", - "placeholder": "​", - "style": "IPY_MODEL_6933130e7fa747cca85775e2390e2883", - "tabbable": null, - "tooltip": null, - "value": " 60000/60000 [00:00<00:00, 280070.61 examples/s]" - } - }, - "527d0aaee5894f2da400bf5690853965": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "53f7d5a3fe5045aea631347f5778ed5b": { + "50780f5c92b44525bf711232bc998378": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4136,7 +4078,25 @@ "width": null } }, - "5421281ef4324fc3960b976b5b1e7be1": { + "511e7568ac814ea8846c93d586063e8e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "5264eae69a4a44c5af270b7caaa7eeb4": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4189,7 +4149,7 @@ "width": null } }, - "5460c3ab53244166b5b83bce1568fb9a": { + "58bd914194a245c2b1a963606103a9bd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4204,33 +4164,39 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_5affd8364ad84dce9ccb9e64e3595daa", + "layout": "IPY_MODEL_65a24ce68aaf46d6b97c06a7d9ffc735", "placeholder": "​", - "style": "IPY_MODEL_f282b3d3edd34bd19404aa81c4bd2be9", + "style": "IPY_MODEL_ed24804748ab483289fec871eb4e7ebf", "tabbable": null, "tooltip": null, - "value": " 30.9M/30.9M [00:00<00:00, 82.2MB/s]" + "value": " 40/40 [00:00<00:00, 65.43it/s]" } }, - "56ab7eb7d7514ac4a5ca99fbec95176c": { + "593399f7ed16479cabf5d6887e2046b5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_9db52ec22ade4fc2a207b214ed54d964", + "IPY_MODEL_7774247051444f258f5cb5a4624a6d83", + "IPY_MODEL_f082a4eab5444b019ea911ae0fb7a92d" + ], + "layout": "IPY_MODEL_8a312c718675404cb5eaf36ae41d943d", + "tabbable": null, + "tooltip": null } }, - "57c3bbf911934c1b954d08e7df293a56": { + "5bc3a1038e00432097a539e27f83e00f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4283,7 +4249,7 @@ "width": null } }, - "57c3c61cde5d4837a1643acc4efaa530": { + "5cf6c3b877784057a47d544871ab0987": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -4301,86 +4267,95 @@ "text_color": null } }, - "58df9bc980ff41e19f86d334f4e6affd": { - "model_module": "@jupyter-widgets/base", + "5e5e4490daf942669f04f85596a7308d": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "HTMLModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_29ace475fdbe4624840332dd0e509ed6", + "placeholder": "​", + "style": "IPY_MODEL_f784e45cbe9248ae9c16491028d6bf8e", + "tabbable": null, + "tooltip": null, + "value": "100%" + } + }, + "606a0ff67cfd457c88c691c81de63a4c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "5ac7e0143087455db2057a05611b903a": { + "60b6605a27b343f3a046b38e2ee92eb3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_f9f45d26f74148d5aafa521c2e42894d", + "IPY_MODEL_f11e1a00f1c942a080552a095321e730", + "IPY_MODEL_b323c9ad204c424e81ad897a8a41faa8" + ], + "layout": "IPY_MODEL_f1c64d058ec34988a144f78b8ce7cbc8", + "tabbable": null, + "tooltip": null + } + }, + "612a34311c13432a923b885221f461b0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_bf7b754fe88b42c2a0ebefbef27aaa5d", - "max": 5175617.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_3e22696dc8414bd180d0e07a4a0a62a7", + "layout": "IPY_MODEL_156d3569cd004246a2f548957d78f2bc", + "placeholder": "​", + "style": "IPY_MODEL_0a606b97ecff4d89be8f66714f909ba3", "tabbable": null, "tooltip": null, - "value": 5175617.0 + "value": "Generating train split: 100%" } }, - "5affd8364ad84dce9ccb9e64e3595daa": { + "62625d830bc54505aa74a2a30ef3af9d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4433,7 +4408,25 @@ "width": null } }, - "5d7fd3a699f145eaa96b37d43b96276e": { + "63223699d1124f63b67f209182bf8e11": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "65a24ce68aaf46d6b97c06a7d9ffc735": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4486,7 +4479,7 @@ "width": null } }, - "5e3bb0ee765649eb8ed9db6a7ad199b2": { + "6739176497a24677bed9ce1d499ce111": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4539,7 +4532,30 @@ "width": null } }, - "5f93eedb157d4345bc780bd62a65204e": { + "67956635d769462da5b0f8ec7ca4575b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_34b3d7273cdd4ceca25a11fbb32359ce", + "placeholder": "​", + "style": "IPY_MODEL_07c128e462924e039bd30ffd94caeafe", + "tabbable": null, + "tooltip": null, + "value": "Map (num_proc=4): 100%" + } + }, + "69af7b2b232142ffa08b9e4439628311": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4592,78 +4608,39 @@ "width": null } }, - "60d20ce4cd714b879c7671b282199048": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_496cb780de334794994864ce22ab43f9", - "IPY_MODEL_ae929a9d89e44834b81a2fd963b2c35f", - "IPY_MODEL_d37c5155b2a140bc9d293b5579737109" - ], - "layout": "IPY_MODEL_1c26fb9f22394b9299592a1f50ca98d5", - "tabbable": null, - "tooltip": null - } - }, - "613725cc273047398f27ac74f75f9fd9": { + "6c5276f1cdeb4d6dafd955e313dfb495": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0a7f73a4ae2a4e5ab8db8790ef824541", - "IPY_MODEL_b9de52fff41e480faf1069d54e51bb01", - "IPY_MODEL_5460c3ab53244166b5b83bce1568fb9a" - ], - "layout": "IPY_MODEL_5e3bb0ee765649eb8ed9db6a7ad199b2", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "63dacf2552ad40888642091c1d2b28f2": { + "6c95b5f8fda84c369cae7cba5624ccfe": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_5421281ef4324fc3960b976b5b1e7be1", - "placeholder": "​", - "style": "IPY_MODEL_713797fcd2e443099904db1582f72e04", - "tabbable": null, - "tooltip": null, - "value": " 60000/60000 [00:51<00:00, 1093.09it/s]" + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "6492748e048c4fe69d67f2f82d4e0597": { + "6d3f4ee5439044088f65368ef798b3b6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -4679,17 +4656,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1e80382ec0ec4737898dcc5f400fdb22", + "layout": "IPY_MODEL_10a3911ad0ae43f599855a0ad46d4195", "max": 40.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_6e9d6a9e82ee4cadaf4d6aae8966e15c", + "style": "IPY_MODEL_ac4bae02a5884435aa084f8524ec36ab", "tabbable": null, "tooltip": null, "value": 40.0 } }, - "65f9a6bec4e948baa940c3046dc97c27": { + "6dd2d74eb1d04d61844ec3c03149c90b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", @@ -4705,7 +4682,33 @@ "description_width": "" } }, - "68f553c7ffe64681af4d9d9b609619d2": { + "6e84e471535f4aa89081faaaa485d6c3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_eec22da0f1c144399d3b96c5a790810e", + "max": 60000.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_747540cae7c946758cd31d80531063d5", + "tabbable": null, + "tooltip": null, + "value": 60000.0 + } + }, + "6e8d203ea1f24d86a8504e8c8f549098": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4720,33 +4723,121 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_c970b98ad16d4e058311518f87d4705f", + "layout": "IPY_MODEL_6fdd97c1ed34454aa0a60e98a62224d2", "placeholder": "​", - "style": "IPY_MODEL_d5f0f111e29b4da996f76d93a33612b5", + "style": "IPY_MODEL_9bec32080a844b95be00f98699eec0a5", "tabbable": null, "tooltip": null, - "value": "Downloading data: 100%" + "value": " 9.02k/9.02k [00:00<00:00, 1.14MB/s]" } }, - "6933130e7fa747cca85775e2390e2883": { - "model_module": "@jupyter-widgets/controls", + "6f0a00d7d264477684a40569e5e3fb89": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6f4b003f65a3475b87ea4dfb49e22177": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "6954ba9a0a8544c8ab34caf9382b3919": { + "6fdd97c1ed34454aa0a60e98a62224d2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4799,46 +4890,67 @@ "width": null } }, - "69ec4f0b4df24afeb44979768207ccb2": { + "747540cae7c946758cd31d80531063d5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "7500e8476ee64140b7338f73ff7b6e53": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_961e00b1790446eab77bd4a467f184f2", - "placeholder": "​", - "style": "IPY_MODEL_c35a2bc3029c426483bd38115de30f66", - "tabbable": null, - "tooltip": null, - "value": " 40/40 [00:00<00:00, 58.82it/s]" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "6ac7f8c8c82c405ea6e0f563824be3e4": { + "7774247051444f258f5cb5a4624a6d83": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_23d399d3b46a4f8d82116059129fd43f", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_13063e602ee246eb9b552b3b781fa85e", + "tabbable": null, + "tooltip": null, + "value": 40.0 } }, - "6bd96238c24c4e66a330bba2b167695c": { + "77caecf6cce84ac885a2c431ec321e76": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4891,54 +5003,7 @@ "width": null } }, - "6c99a5fc3f1d42269032bffe9d6a65ff": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_490e0855ef974a42b2647cfedac70b97", - "IPY_MODEL_ad9ad38f87fc4507894591d2e971b931", - "IPY_MODEL_943f54a9f4ed4ae88c0921a8b76bf464" - ], - "layout": "IPY_MODEL_72c90d5012e24845b7a5539b09d24a76", - "tabbable": null, - "tooltip": null - } - }, - "6ce5166958664174ac671372b3559fa4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6cecdf39711e44c98e32290468b92b89", - "placeholder": "​", - "style": "IPY_MODEL_aa92cf8d9af14ef481b63d80bff1ec7b", - "tabbable": null, - "tooltip": null, - "value": " 9.02k/9.02k [00:00<00:00, 1.13MB/s]" - } - }, - "6cecdf39711e44c98e32290468b92b89": { + "78ec8846971b49dc8ac35c9865ab7855": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4991,30 +5056,49 @@ "width": null } }, - "6de53660f780414f83690503c02977c3": { + "7acec2eb1b9b4c74860f49bf17a12246": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "7bcf07287e5846bcade12829a0129e5a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_74cac39f1ec9456089f019cf6afaf7b6", - "placeholder": "​", - "style": "IPY_MODEL_8e9c46198cc34d838d789c567dc8fb39", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_0f970e1142174368bfc637a6cd8d6fd5", + "IPY_MODEL_11c48316135a461ea55c3d08dc541755", + "IPY_MODEL_6e8d203ea1f24d86a8504e8c8f549098" + ], + "layout": "IPY_MODEL_6f4b003f65a3475b87ea4dfb49e22177", "tabbable": null, - "tooltip": null, - "value": "Downloading readme: 100%" + "tooltip": null } }, - "6e9d6a9e82ee4cadaf4d6aae8966e15c": { + "7c13df622dfc4f04853781143737296f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", @@ -5030,7 +5114,7 @@ "description_width": "" } }, - "6fa9185a75e4476a9f7bb3766fa59734": { + "7c5730df719649e6ae1137849667983e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5083,43 +5167,7 @@ "width": null } }, - "7030838d622a49648a433355d555396d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "713797fcd2e443099904db1582f72e04": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "72c90d5012e24845b7a5539b09d24a76": { + "7d5c3f6e3cdc47378b7a095dc828c708": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5172,7 +5220,30 @@ "width": null } }, - "73da71f202fa4d19a5b13c8abd8c3da4": { + "7e624075712f49aeb75f702d9f7850d8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_5264eae69a4a44c5af270b7caaa7eeb4", + "placeholder": "​", + "style": "IPY_MODEL_dac3e32ab9a846e79186067c2b27a96c", + "tabbable": null, + "tooltip": null, + "value": "Computing checksums: 100%" + } + }, + "82b18a92ec124a52a6892b31409db80e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -5190,7 +5261,7 @@ "text_color": null } }, - "74cac39f1ec9456089f019cf6afaf7b6": { + "85965cbbe5ef40678b86b3d3f8e4fc95": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5243,7 +5314,7 @@ "width": null } }, - "76b7a3bbd445436cbe99a45727980913": { + "85a6da0e361d4bb78dac486525795dad": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -5258,16 +5329,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_bdfc00756c4b4ea291b1b12d3c453adb", - "IPY_MODEL_beb7c925e927474da59521fcae36f1b5", - "IPY_MODEL_bbe8e85b50614b6895dfc5261cefbd3f" + "IPY_MODEL_612a34311c13432a923b885221f461b0", + "IPY_MODEL_c20bdfdc755d478c8d2c59d296af1748", + "IPY_MODEL_0b9bdabf441e4113805b54ee83d92f75" ], - "layout": "IPY_MODEL_07d8ecbe4aaf4a9ea4aa1e00be62b06b", + "layout": "IPY_MODEL_5bc3a1038e00432097a539e27f83e00f", "tabbable": null, "tooltip": null } }, - "79aa1e210ebd44dfa879c72b499b33e4": { + "861644c40333498094e62f8ac990f5a3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5282,41 +5353,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_6bd96238c24c4e66a330bba2b167695c", + "layout": "IPY_MODEL_a77a4e7f5f8140bf8475f4d847910210", "placeholder": "​", - "style": "IPY_MODEL_0777e52962fe4e3c8c417ed705b0e27a", - "tabbable": null, - "tooltip": null, - "value": " 10000/10000 [00:00<00:00, 247365.46 examples/s]" - } - }, - "79d0cd0446fb44d18bdfb6375cea394c": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_7bffdee10c6243ff866a02214b5a648a", - "max": 9015.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_65f9a6bec4e948baa940c3046dc97c27", + "style": "IPY_MODEL_5cf6c3b877784057a47d544871ab0987", "tabbable": null, "tooltip": null, - "value": 9015.0 + "value": " 5.18M/5.18M [00:00<00:00, 25.9MB/s]" } }, - "7bffdee10c6243ff866a02214b5a648a": { + "881dec995ffa41c3b5cbe3a2f2955ed3": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5369,94 +5414,25 @@ "width": null } }, - "803d8c89e37c4695af839e22e27d45ad": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_bf2c115cc0d44b6fa22a95924ce0e2c1", - "placeholder": "​", - "style": "IPY_MODEL_be908d64fea14e7a8dacc12ac0c6dd97", - "tabbable": null, - "tooltip": null, - "value": "Generating train split: 100%" - } - }, - "80768ed8be224e0ea7b3cc4f25feb960": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_c501ce55b0824b50bbbd81608041645c", - "IPY_MODEL_97dadb01cdf243fcb11e8a41b9d2c694", - "IPY_MODEL_a9318ad2f8454532a38c05af6ab2b318" - ], - "layout": "IPY_MODEL_4b14e0caa5af4f9688d2d2d294a95764", - "tabbable": null, - "tooltip": null - } - }, - "8089a6f0e258484bb6eb86bd123e100b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_6de53660f780414f83690503c02977c3", - "IPY_MODEL_79d0cd0446fb44d18bdfb6375cea394c", - "IPY_MODEL_6ce5166958664174ac671372b3559fa4" - ], - "layout": "IPY_MODEL_e8da8c5e504b47e9b752f785493250ce", - "tabbable": null, - "tooltip": null - } - }, - "81b854f5964b47979c3b45402b07d21d": { + "884d6ce901e24a3797e35af5711b0f35": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "82aff8f27b4c41438fb70e6ac7827816": { + "8a312c718675404cb5eaf36ae41d943d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5509,41 +5485,7 @@ "width": null } }, - "83ed1ab9ea0a4965aa59eb8257d4f46b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "8a031d58353a4a56b2ee095968c9120f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "8c1eafd77d904a36aa9f617ae2a33e13": { + "8cf5382c91f64f789a1af9c7918f14bb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5558,51 +5500,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_50c7134622e34fbb83b07d440594438c", + "layout": "IPY_MODEL_d5d9319b3ee0495d88f51937931cd00c", "placeholder": "​", - "style": "IPY_MODEL_527d0aaee5894f2da400bf5690853965", + "style": "IPY_MODEL_af8db4b8467844b8be9927dab8c5e3d9", "tabbable": null, "tooltip": null, - "value": " 40/40 [00:00<00:00, 61.56it/s]" - } - }, - "8e9c46198cc34d838d789c567dc8fb39": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "8ef171290e7f471a827e41fd51067134": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "value": "100%" } }, - "926a96fc307846809864b9a1f01356cf": { + "8e65bd8055fd45d8999b608481497477": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5655,7 +5561,7 @@ "width": null } }, - "943f54a9f4ed4ae88c0921a8b76bf464": { + "8efceb1c08634d06817a3fa57d1a8f06": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5670,59 +5576,68 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1b516e69e31f4ff4a0ecb31c1298142e", + "layout": "IPY_MODEL_85965cbbe5ef40678b86b3d3f8e4fc95", "placeholder": "​", - "style": "IPY_MODEL_8ef171290e7f471a827e41fd51067134", + "style": "IPY_MODEL_d86fc4609ac5440a807e454ed938d58e", "tabbable": null, "tooltip": null, - "value": " 40/40 [00:00<00:00, 61.32it/s]" + "value": " 10000/10000 [00:00<00:00, 249921.29 examples/s]" } }, - "94dbf69483ae44dc86b8e989c13af0b1": { - "model_module": "@jupyter-widgets/controls", + "92880a6894cd410ba97664fbbbbe340e": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "95d93d3f700940b592f8552c390c914b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_f9fd3a8802ff4c8799b62137434f622c", - "max": 10000.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_6ac7f8c8c82c405ea6e0f563824be3e4", - "tabbable": null, - "tooltip": null, - "value": 10000.0 + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "961e00b1790446eab77bd4a467f184f2": { + "929f19e8f15344c999957b2ce7569264": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5775,51 +5690,31 @@ "width": null } }, - "97dadb01cdf243fcb11e8a41b9d2c694": { + "958c94ac86804e8fbd31685a6f87d389": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_209db2922df34007b2eea98c10204bb3", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_24f5d44a2aba41bab7b5b00ccd550704", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_ac11acf9e07f48d1af94fcdf26f8c615", + "IPY_MODEL_a671667e5adf4b9798a98eda0ac57dc8", + "IPY_MODEL_4a900a7bd2894dc2905c92a999845c41" + ], + "layout": "IPY_MODEL_4e5be3b38c73499194dd5bfcb00e9476", "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "9ee9ae8ff5f64abd9dba00576d9248cd": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "tooltip": null } }, - "a0a0e34b0dda43afb7891d6f5af3db95": { + "97578dccf99646909cc139834ab78ea9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5872,7 +5767,25 @@ "width": null } }, - "a3cce43cc858462a882adcb42f8671a7": { + "9bec32080a844b95be00f98699eec0a5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "9db52ec22ade4fc2a207b214ed54d964": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5887,15 +5800,51 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_44a4010eb7a944249e17c4373fb6fae1", + "layout": "IPY_MODEL_62625d830bc54505aa74a2a30ef3af9d", "placeholder": "​", - "style": "IPY_MODEL_c5c385c1288d47d3b192dde525ec8305", + "style": "IPY_MODEL_afce32644b8041548c6a8fefb3255e26", "tabbable": null, "tooltip": null, "value": "100%" } }, - "a9318ad2f8454532a38c05af6ab2b318": { + "9fcb012408c9489cb4882ad5d8d37ecf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "a1e0fb35ccfd46ac9b640c1e3a97a83e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "a53594c87ee944d2ab253fdeb3aeae5f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5910,33 +5859,41 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b544909353d742da90404a2a70352fdf", + "layout": "IPY_MODEL_50780f5c92b44525bf711232bc998378", "placeholder": "​", - "style": "IPY_MODEL_b6f2ef3dc1a54297b205d90f139423c5", + "style": "IPY_MODEL_eefff7211ed94c5b90094ff9520c50b5", "tabbable": null, "tooltip": null, - "value": " 40/40 [00:00<00:00, 57.51it/s]" + "value": "Downloading data: 100%" } }, - "aa92cf8d9af14ef481b63d80bff1ec7b": { + "a671667e5adf4b9798a98eda0ac57dc8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_1510cd85e1a74691abd66fcc8f87c34c", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_15c77a61cbac476e99fb0331858d1d8c", + "tabbable": null, + "tooltip": null, + "value": 40.0 } }, - "abc24829115b46edb7572dc55403960a": { + "a77a4e7f5f8140bf8475f4d847910210": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5989,33 +5946,7 @@ "width": null } }, - "ad9ad38f87fc4507894591d2e971b931": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_0bf8b4b0c9ce4e819a7f21eaed682092", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_eda9c8fc9ec84b47b274aead1d312c12", - "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "ae860c8ab42f4e1a96dddec1fd6b7a29": { + "a88f012a925b438fbc901a161c09cf50": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6068,7 +5999,7 @@ "width": null } }, - "ae929a9d89e44834b81a2fd963b2c35f": { + "a8fc249e1ca44d4084ed4e8e978d6058": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -6084,17 +6015,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b0135714d63c4ad599890917e7581170", - "max": 60000.0, + "layout": "IPY_MODEL_076942f2bb5542e9a9c126f736c4b427", + "max": 40.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_2a0e717d35f142e2ba3bffe16092cee4", + "style": "IPY_MODEL_6c5276f1cdeb4d6dafd955e313dfb495", "tabbable": null, "tooltip": null, - "value": 60000.0 + "value": 40.0 } }, - "afb259c49ba34750a8a8814d7dc507b6": { + "a9b1da96fea74c509d14483d998a7cf8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6147,7 +6078,7 @@ "width": null } }, - "aff0b45e2c1f43a9bb8830f843804ede": { + "a9e701e6d5bf4ec2a9c900edea6104e5": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6200,7 +6131,7 @@ "width": null } }, - "b0135714d63c4ad599890917e7581170": { + "aba8cf45b54448a59ae5e30586981cc2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6253,7 +6184,7 @@ "width": null } }, - "b1d1946f6c3a4ee8bc68f10cfe33d799": { + "ac11acf9e07f48d1af94fcdf26f8c615": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -6268,15 +6199,31 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_10186f0c08c84916988b4064fb8fbbb6", + "layout": "IPY_MODEL_69af7b2b232142ffa08b9e4439628311", "placeholder": "​", - "style": "IPY_MODEL_73da71f202fa4d19a5b13c8abd8c3da4", + "style": "IPY_MODEL_9fcb012408c9489cb4882ad5d8d37ecf", "tabbable": null, "tooltip": null, "value": "100%" } }, - "b2edc3bafbc4407f8f9a8b986aa82b90": { + "ac4bae02a5884435aa084f8524ec36ab": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "ac970746b6684c3ba6bb43eee4014e2b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6329,7 +6276,43 @@ "width": null } }, - "b330cae0665c496d9f38d6b6c39c32cf": { + "af8db4b8467844b8be9927dab8c5e3d9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "afce32644b8041548c6a8fefb3255e26": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "b149b2726a33413c8e2fde403bed8e98": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6382,7 +6365,46 @@ "width": null } }, - "b544909353d742da90404a2a70352fdf": { + "b1625d60d8254709b2fbc8015a483069": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "b323c9ad204c424e81ad897a8a41faa8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_294184439d7d474cbfc6043c1efa9d3d", + "placeholder": "​", + "style": "IPY_MODEL_63223699d1124f63b67f209182bf8e11", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 62.13it/s]" + } + }, + "b8a497f4724b458c8448b91e3ce44d15": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6435,97 +6457,31 @@ "width": null } }, - "b57eeb2e85db4e6c90b70606981a862d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_926a96fc307846809864b9a1f01356cf", - "placeholder": "​", - "style": "IPY_MODEL_21aa7e557ff2445fb6f9a8d7299a17ff", - "tabbable": null, - "tooltip": null, - "value": " 5.18M/5.18M [00:00<00:00, 59.9MB/s]" - } - }, - "b6f2ef3dc1a54297b205d90f139423c5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "b754e4894e834fc19df74d003d4ab747": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_a0a0e34b0dda43afb7891d6f5af3db95", - "placeholder": "​", - "style": "IPY_MODEL_c5ae7198f4aa46179022a46d7c59764e", - "tabbable": null, - "tooltip": null, - "value": " 40/40 [00:00<00:00, 58.46it/s]" - } - }, - "b9de52fff41e480faf1069d54e51bb01": { + "b8c0903ec57a4db09eef7c66d76ad798": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_ae860c8ab42f4e1a96dddec1fd6b7a29", - "max": 30931277.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_1403cd0920194d9f88d2e816c0e364a5", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_5e5e4490daf942669f04f85596a7308d", + "IPY_MODEL_c1960242d8a3445da3b5cfd12aa829f9", + "IPY_MODEL_1658cd683cbd496c9ff193ba8d7c35ea" + ], + "layout": "IPY_MODEL_6739176497a24677bed9ce1d499ce111", "tabbable": null, - "tooltip": null, - "value": 30931277.0 + "tooltip": null } }, - "ba89e00a862d448e8dc72d837a38fe5a": { + "bb2fc960507949aea6439fcd3c77de5b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6578,48 +6534,7 @@ "width": null } }, - "badfbcc018f64af28731edbb3cf0c438": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "bbe8e85b50614b6895dfc5261cefbd3f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6954ba9a0a8544c8ab34caf9382b3919", - "placeholder": "​", - "style": "IPY_MODEL_9ee9ae8ff5f64abd9dba00576d9248cd", - "tabbable": null, - "tooltip": null, - "value": " 2/2 [00:00<00:00, 597.27it/s]" - } - }, - "bd82670a06d84e1fa6cb4197d311667d": { + "bcb6b4fdcebe40208119e7b000c67176": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6672,48 +6587,73 @@ "width": null } }, - "bdfc00756c4b4ea291b1b12d3c453adb": { + "bfcb4b6339d14370bc404a61e757edfd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_53f7d5a3fe5045aea631347f5778ed5b", - "placeholder": "​", - "style": "IPY_MODEL_57c3c61cde5d4837a1643acc4efaa530", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_67956635d769462da5b0f8ec7ca4575b", + "IPY_MODEL_6e84e471535f4aa89081faaaa485d6c3", + "IPY_MODEL_f0cb3f6ef1cd478f8be08c7d0285e829" + ], + "layout": "IPY_MODEL_cc31bc3295e7426890cf527d78a13416", "tabbable": null, - "tooltip": null, - "value": "Computing checksums: 100%" + "tooltip": null } }, - "be908d64fea14e7a8dacc12ac0c6dd97": { + "c0366a87be804af7bcf6f5cd7f11bc3b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" + } + }, + "c1960242d8a3445da3b5cfd12aa829f9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_92880a6894cd410ba97664fbbbbe340e", + "max": 60000.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_b1625d60d8254709b2fbc8015a483069", + "tabbable": null, + "tooltip": null, + "value": 60000.0 } }, - "beb7c925e927474da59521fcae36f1b5": { + "c20bdfdc755d478c8d2c59d296af1748": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -6729,17 +6669,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_d0cf2f4503034449b080c3b3081f634c", - "max": 2.0, + "layout": "IPY_MODEL_6f0a00d7d264477684a40569e5e3fb89", + "max": 60000.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_27d51d7d7c394b8ca5b9c6dc1f2f28ef", + "style": "IPY_MODEL_210dbd38b6ce4f9e9f8b810ac64d03bf", "tabbable": null, "tooltip": null, - "value": 2.0 + "value": 60000.0 } }, - "bf2c115cc0d44b6fa22a95924ce0e2c1": { + "c65df96729f9462e8df514c9d2bab3e8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6792,7 +6732,25 @@ "width": null } }, - "bf7b754fe88b42c2a0ebefbef27aaa5d": { + "c77f86be94734e2ba274bf4267c5a824": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "cc31bc3295e7426890cf527d78a13416": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6845,33 +6803,23 @@ "width": null } }, - "c0f63161d8b64e1d88fb06474e6eb468": { + "cdf6adba96a64fc5a04910695f01468c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_afb259c49ba34750a8a8814d7dc507b6", - "max": 60000.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_8a031d58353a4a56b2ee095968c9120f", - "tabbable": null, - "tooltip": null, - "value": 60000.0 + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "c31bcb9951714ea7b4d0d8e9793f409b": { + "cef86182d7ef449481f59dfea70aa34a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -6886,75 +6834,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_b1d1946f6c3a4ee8bc68f10cfe33d799", - "IPY_MODEL_6492748e048c4fe69d67f2f82d4e0597", - "IPY_MODEL_b754e4894e834fc19df74d003d4ab747" + "IPY_MODEL_8cf5382c91f64f789a1af9c7918f14bb", + "IPY_MODEL_1e5e214067f448fe820c272b4d8b60b6", + "IPY_MODEL_58bd914194a245c2b1a963606103a9bd" ], - "layout": "IPY_MODEL_df6d40c4585b4191920844c6eef8bc16", + "layout": "IPY_MODEL_25c0e4e85ebb41299102ad0b3e0880b4", "tabbable": null, "tooltip": null } }, - "c35a2bc3029c426483bd38115de30f66": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c501ce55b0824b50bbbd81608041645c": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_57c3bbf911934c1b954d08e7df293a56", - "placeholder": "​", - "style": "IPY_MODEL_e777bd11a1bc40dbb3b01b6f0a31135b", - "tabbable": null, - "tooltip": null, - "value": "100%" - } - }, - "c5ae7198f4aa46179022a46d7c59764e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c5c385c1288d47d3b192dde525ec8305": { + "d0dfbf919e5f422689492055a00be836": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -6972,46 +6861,60 @@ "text_color": null } }, - "c701552093d1471bb9ace0f6dcd2c9bb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_195f6f44461b4637898d20c3f277f04c", - "placeholder": "​", - "style": "IPY_MODEL_1a190a961ec641a28b3c636af3b264dc", - "tabbable": null, - "tooltip": null, - "value": " 40/40 [00:00<00:00, 62.73it/s]" - } - }, - "c87c43a894a24676985679a70e0b0d69": { - "model_module": "@jupyter-widgets/controls", + "d54af3f6955d4b968858d238a0210190": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "c970b98ad16d4e058311518f87d4705f": { + "d5d9319b3ee0495d88f51937931cd00c": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7064,7 +6967,25 @@ "width": null } }, - "cb746766609e4be886215339a1a76de1": { + "d86fc4609ac5440a807e454ed938d58e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "d936e9a2111644719473853bc9465d85": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -7080,17 +7001,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_5d7fd3a699f145eaa96b37d43b96276e", - "max": 40.0, + "layout": "IPY_MODEL_aba8cf45b54448a59ae5e30586981cc2", + "max": 2.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_35a155d26b984654ab25b9e85ccccd6f", + "style": "IPY_MODEL_e06e8dd00ef946db9d9676c674e9f1ff", "tabbable": null, "tooltip": null, - "value": 40.0 + "value": 2.0 } }, - "cda1df54889f4e3bb275c8c2fd8ec82a": { + "d9b3afcffed047abb3d7c9215eacb041": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7143,7 +7064,7 @@ "width": null } }, - "d0cf2f4503034449b080c3b3081f634c": { + "d9bfaf958ae54bdaa41267876482d6af": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7196,7 +7117,77 @@ "width": null } }, - "d37c5155b2a140bc9d293b5579737109": { + "da5cdaff84244e95b85f4f6729933e89": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "dac3e32ab9a846e79186067c2b27a96c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "df804279770c4bbdbba569e996a72047": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "e06e8dd00ef946db9d9676c674e9f1ff": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "e127093a41b442febda97da50e709395": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -7211,15 +7202,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_6fa9185a75e4476a9f7bb3766fa59734", + "layout": "IPY_MODEL_7d5c3f6e3cdc47378b7a095dc828c708", "placeholder": "​", - "style": "IPY_MODEL_56ab7eb7d7514ac4a5ca99fbec95176c", + "style": "IPY_MODEL_7acec2eb1b9b4c74860f49bf17a12246", "tabbable": null, "tooltip": null, - "value": " 60000/60000 [00:11<00:00, 6991.32 examples/s]" + "value": " 30.9M/30.9M [00:00<00:00, 85.2MB/s]" } }, - "d4701b3f33d74bc4be0e3b87b63572da": { + "e38940706f02447996928468d3f523eb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -7235,17 +7226,40 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_4fd6ca7a7dd446879a6f2f55860227d9", - "max": 40.0, + "layout": "IPY_MODEL_97578dccf99646909cc139834ab78ea9", + "max": 30931277.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_c87c43a894a24676985679a70e0b0d69", + "style": "IPY_MODEL_cdf6adba96a64fc5a04910695f01468c", "tabbable": null, "tooltip": null, - "value": 40.0 + "value": 30931277.0 + } + }, + "e6d9313a802d4513bc93abf9ffa9fc9b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_bcb6b4fdcebe40208119e7b000c67176", + "placeholder": "​", + "style": "IPY_MODEL_606a0ff67cfd457c88c691c81de63a4c", + "tabbable": null, + "tooltip": null, + "value": "100%" } }, - "d5f0f111e29b4da996f76d93a33612b5": { + "ed24804748ab483289fec871eb4e7ebf": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -7263,30 +7277,31 @@ "text_color": null } }, - "dccf399c747d4d1d82bce77b5b675956": { + "ee5568e238c045b59cf17074e12437c9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_bd82670a06d84e1fa6cb4197d311667d", - "placeholder": "​", - "style": "IPY_MODEL_badfbcc018f64af28731edbb3cf0c438", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_7e624075712f49aeb75f702d9f7850d8", + "IPY_MODEL_d936e9a2111644719473853bc9465d85", + "IPY_MODEL_26b545a844a84c278f68d51645f7e371" + ], + "layout": "IPY_MODEL_33d5aee8319348e485ec3980bc726f23", "tabbable": null, - "tooltip": null, - "value": "100%" + "tooltip": null } }, - "df6d40c4585b4191920844c6eef8bc16": { + "eec22da0f1c144399d3b96c5a790810e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7339,49 +7354,120 @@ "width": null } }, - "e1f7f496e0bd4db1ac83de92100a6631": { + "eefff7211ed94c5b90094ff9520c50b5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "f03a0d23baa4409abb0c7271bd76ab8a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_803d8c89e37c4695af839e22e27d45ad", - "IPY_MODEL_c0f63161d8b64e1d88fb06474e6eb468", - "IPY_MODEL_51120e68bd384037a4668fe393f7be13" - ], - "layout": "IPY_MODEL_ba89e00a862d448e8dc72d837a38fe5a", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_c65df96729f9462e8df514c9d2bab3e8", + "placeholder": "​", + "style": "IPY_MODEL_06c85507cf49495584b002e6aaa044e8", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": " 40/40 [00:00<00:00, 61.46it/s]" } }, - "e777bd11a1bc40dbb3b01b6f0a31135b": { + "f082a4eab5444b019ea911ae0fb7a92d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HTMLModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HTMLModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_a88f012a925b438fbc901a161c09cf50", + "placeholder": "​", + "style": "IPY_MODEL_f7b0cd88615641199d9599093664c3f3", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 63.47it/s]" + } + }, + "f0cb3f6ef1cd478f8be08c7d0285e829": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_118d13a1737e460b986120e1cd8488c6", + "placeholder": "​", + "style": "IPY_MODEL_884d6ce901e24a3797e35af5711b0f35", + "tabbable": null, + "tooltip": null, + "value": " 60000/60000 [00:11<00:00, 5023.35 examples/s]" + } + }, + "f11e1a00f1c942a080552a095321e730": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b149b2726a33413c8e2fde403bed8e98", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_6dd2d74eb1d04d61844ec3c03149c90b", + "tabbable": null, + "tooltip": null, + "value": 40.0 } }, - "e8da8c5e504b47e9b752f785493250ce": { + "f1c64d058ec34988a144f78b8ce7cbc8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7434,73 +7520,41 @@ "width": null } }, - "e8f51e9d01d447c3b27b88d0c146d11b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_abc24829115b46edb7572dc55403960a", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_81b854f5964b47979c3b45402b07d21d", - "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "ec9e629fd2904b8fbf99b7c637113a54": { + "f2fa408e34274722bd36f3791c967fb2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0240b26e2e8347049e4a5df861bb7a0d", - "IPY_MODEL_d4701b3f33d74bc4be0e3b87b63572da", - "IPY_MODEL_8c1eafd77d904a36aa9f617ae2a33e13" - ], - "layout": "IPY_MODEL_5f93eedb157d4345bc780bd62a65204e", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "eda9c8fc9ec84b47b274aead1d312c12": { + "f784e45cbe9248ae9c16491028d6bf8e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "f282b3d3edd34bd19404aa81c4bd2be9": { + "f7b0cd88615641199d9599093664c3f3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -7518,81 +7572,27 @@ "text_color": null } }, - "f2c0fcf1952846d5b613a055c1f1e0bc": { + "f9f45d26f74148d5aafa521c2e42894d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_a3cce43cc858462a882adcb42f8671a7", - "IPY_MODEL_cb746766609e4be886215339a1a76de1", - "IPY_MODEL_69ec4f0b4df24afeb44979768207ccb2" - ], - "layout": "IPY_MODEL_b2edc3bafbc4407f8f9a8b986aa82b90", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_a9e701e6d5bf4ec2a9c900edea6104e5", + "placeholder": "​", + "style": "IPY_MODEL_da5cdaff84244e95b85f4f6729933e89", "tabbable": null, - "tooltip": null - } - }, - "f9fd3a8802ff4c8799b62137434f622c": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "2.0.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "tooltip": null, + "value": "100%" } } }, diff --git a/master/.doctrees/nbsphinx/tutorials/datalab/tabular.ipynb b/master/.doctrees/nbsphinx/tutorials/datalab/tabular.ipynb index b3092f1d2..55a26f513 100644 --- a/master/.doctrees/nbsphinx/tutorials/datalab/tabular.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/datalab/tabular.ipynb @@ -73,10 +73,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:13.469873Z", - "iopub.status.busy": "2024-09-05T19:37:13.469691Z", - "iopub.status.idle": "2024-09-05T19:37:14.643451Z", - "shell.execute_reply": "2024-09-05T19:37:14.642938Z" + "iopub.execute_input": "2024-09-06T19:37:06.951842Z", + "iopub.status.busy": "2024-09-06T19:37:06.951670Z", + "iopub.status.idle": "2024-09-06T19:37:08.104160Z", + "shell.execute_reply": "2024-09-06T19:37:08.103605Z" }, "nbsphinx": "hidden" }, @@ -86,7 +86,7 @@ "dependencies = [\"cleanlab\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -111,10 +111,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.646200Z", - "iopub.status.busy": "2024-09-05T19:37:14.645631Z", - "iopub.status.idle": "2024-09-05T19:37:14.663967Z", - "shell.execute_reply": "2024-09-05T19:37:14.663492Z" + "iopub.execute_input": "2024-09-06T19:37:08.106594Z", + "iopub.status.busy": "2024-09-06T19:37:08.106312Z", + "iopub.status.idle": "2024-09-06T19:37:08.124373Z", + "shell.execute_reply": "2024-09-06T19:37:08.123937Z" } }, "outputs": [], @@ -154,10 +154,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.666331Z", - "iopub.status.busy": "2024-09-05T19:37:14.665911Z", - "iopub.status.idle": "2024-09-05T19:37:14.706816Z", - "shell.execute_reply": "2024-09-05T19:37:14.706224Z" + "iopub.execute_input": "2024-09-06T19:37:08.126574Z", + "iopub.status.busy": "2024-09-06T19:37:08.126159Z", + "iopub.status.idle": "2024-09-06T19:37:08.148467Z", + "shell.execute_reply": "2024-09-06T19:37:08.148011Z" } }, "outputs": [ @@ -264,10 +264,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.709267Z", - "iopub.status.busy": "2024-09-05T19:37:14.708881Z", - "iopub.status.idle": "2024-09-05T19:37:14.712569Z", - "shell.execute_reply": "2024-09-05T19:37:14.712080Z" + "iopub.execute_input": "2024-09-06T19:37:08.150542Z", + "iopub.status.busy": "2024-09-06T19:37:08.150195Z", + "iopub.status.idle": "2024-09-06T19:37:08.153510Z", + "shell.execute_reply": "2024-09-06T19:37:08.153043Z" } }, "outputs": [], @@ -288,10 +288,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.714680Z", - "iopub.status.busy": "2024-09-05T19:37:14.714329Z", - "iopub.status.idle": "2024-09-05T19:37:14.721981Z", - "shell.execute_reply": "2024-09-05T19:37:14.721544Z" + "iopub.execute_input": "2024-09-06T19:37:08.155506Z", + "iopub.status.busy": "2024-09-06T19:37:08.155162Z", + "iopub.status.idle": "2024-09-06T19:37:08.163216Z", + "shell.execute_reply": "2024-09-06T19:37:08.162658Z" } }, "outputs": [], @@ -336,10 +336,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.724136Z", - "iopub.status.busy": "2024-09-05T19:37:14.723769Z", - "iopub.status.idle": "2024-09-05T19:37:14.726297Z", - "shell.execute_reply": "2024-09-05T19:37:14.725816Z" + "iopub.execute_input": "2024-09-06T19:37:08.165384Z", + "iopub.status.busy": "2024-09-06T19:37:08.164978Z", + "iopub.status.idle": "2024-09-06T19:37:08.167532Z", + "shell.execute_reply": "2024-09-06T19:37:08.167093Z" } }, "outputs": [], @@ -362,10 +362,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.728450Z", - "iopub.status.busy": "2024-09-05T19:37:14.728116Z", - "iopub.status.idle": "2024-09-05T19:37:17.842883Z", - "shell.execute_reply": "2024-09-05T19:37:17.842351Z" + "iopub.execute_input": "2024-09-06T19:37:08.169550Z", + "iopub.status.busy": "2024-09-06T19:37:08.169205Z", + "iopub.status.idle": "2024-09-06T19:37:11.232996Z", + "shell.execute_reply": "2024-09-06T19:37:11.232340Z" } }, "outputs": [], @@ -401,10 +401,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:17.845676Z", - "iopub.status.busy": "2024-09-05T19:37:17.845310Z", - "iopub.status.idle": "2024-09-05T19:37:17.854733Z", - "shell.execute_reply": "2024-09-05T19:37:17.854165Z" + "iopub.execute_input": "2024-09-06T19:37:11.235550Z", + "iopub.status.busy": "2024-09-06T19:37:11.235362Z", + "iopub.status.idle": "2024-09-06T19:37:11.244291Z", + "shell.execute_reply": "2024-09-06T19:37:11.243862Z" } }, "outputs": [], @@ -436,10 +436,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:17.857062Z", - "iopub.status.busy": "2024-09-05T19:37:17.856748Z", - "iopub.status.idle": "2024-09-05T19:37:19.875306Z", - "shell.execute_reply": "2024-09-05T19:37:19.874590Z" + "iopub.execute_input": "2024-09-06T19:37:11.246379Z", + "iopub.status.busy": "2024-09-06T19:37:11.246205Z", + "iopub.status.idle": "2024-09-06T19:37:13.219249Z", + "shell.execute_reply": "2024-09-06T19:37:13.218645Z" } }, "outputs": [ @@ -476,10 +476,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.877872Z", - "iopub.status.busy": "2024-09-05T19:37:19.877351Z", - "iopub.status.idle": "2024-09-05T19:37:19.896585Z", - "shell.execute_reply": "2024-09-05T19:37:19.895985Z" + "iopub.execute_input": "2024-09-06T19:37:13.221677Z", + "iopub.status.busy": "2024-09-06T19:37:13.221173Z", + "iopub.status.idle": "2024-09-06T19:37:13.240218Z", + "shell.execute_reply": "2024-09-06T19:37:13.239749Z" }, "scrolled": true }, @@ -609,10 +609,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.898896Z", - "iopub.status.busy": "2024-09-05T19:37:19.898559Z", - "iopub.status.idle": "2024-09-05T19:37:19.907000Z", - "shell.execute_reply": "2024-09-05T19:37:19.906535Z" + "iopub.execute_input": "2024-09-06T19:37:13.242381Z", + "iopub.status.busy": "2024-09-06T19:37:13.242042Z", + "iopub.status.idle": "2024-09-06T19:37:13.250225Z", + "shell.execute_reply": "2024-09-06T19:37:13.249765Z" } }, "outputs": [ @@ -716,10 +716,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.909010Z", - "iopub.status.busy": "2024-09-05T19:37:19.908684Z", - "iopub.status.idle": "2024-09-05T19:37:19.917678Z", - "shell.execute_reply": "2024-09-05T19:37:19.917096Z" + "iopub.execute_input": "2024-09-06T19:37:13.252315Z", + "iopub.status.busy": "2024-09-06T19:37:13.251975Z", + "iopub.status.idle": "2024-09-06T19:37:13.260671Z", + "shell.execute_reply": "2024-09-06T19:37:13.260195Z" } }, "outputs": [ @@ -848,10 +848,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.919930Z", - "iopub.status.busy": "2024-09-05T19:37:19.919439Z", - "iopub.status.idle": "2024-09-05T19:37:19.927966Z", - "shell.execute_reply": "2024-09-05T19:37:19.927364Z" + "iopub.execute_input": "2024-09-06T19:37:13.262712Z", + "iopub.status.busy": "2024-09-06T19:37:13.262373Z", + "iopub.status.idle": "2024-09-06T19:37:13.270531Z", + "shell.execute_reply": "2024-09-06T19:37:13.269960Z" } }, "outputs": [ @@ -965,10 +965,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.930006Z", - "iopub.status.busy": "2024-09-05T19:37:19.929680Z", - "iopub.status.idle": "2024-09-05T19:37:19.938743Z", - "shell.execute_reply": "2024-09-05T19:37:19.938175Z" + "iopub.execute_input": "2024-09-06T19:37:13.272557Z", + "iopub.status.busy": "2024-09-06T19:37:13.272379Z", + "iopub.status.idle": "2024-09-06T19:37:13.281035Z", + "shell.execute_reply": "2024-09-06T19:37:13.280557Z" } }, "outputs": [ @@ -1079,10 +1079,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.940940Z", - "iopub.status.busy": "2024-09-05T19:37:19.940628Z", - "iopub.status.idle": "2024-09-05T19:37:19.948170Z", - "shell.execute_reply": "2024-09-05T19:37:19.947590Z" + "iopub.execute_input": "2024-09-06T19:37:13.283068Z", + "iopub.status.busy": "2024-09-06T19:37:13.282889Z", + "iopub.status.idle": "2024-09-06T19:37:13.290486Z", + "shell.execute_reply": "2024-09-06T19:37:13.290023Z" } }, "outputs": [ @@ -1197,10 +1197,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.950230Z", - "iopub.status.busy": "2024-09-05T19:37:19.949916Z", - "iopub.status.idle": "2024-09-05T19:37:19.957426Z", - "shell.execute_reply": "2024-09-05T19:37:19.956989Z" + "iopub.execute_input": "2024-09-06T19:37:13.292532Z", + "iopub.status.busy": "2024-09-06T19:37:13.292191Z", + "iopub.status.idle": "2024-09-06T19:37:13.299536Z", + "shell.execute_reply": "2024-09-06T19:37:13.298963Z" } }, "outputs": [ @@ -1306,10 +1306,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.959710Z", - "iopub.status.busy": "2024-09-05T19:37:19.959220Z", - "iopub.status.idle": "2024-09-05T19:37:19.967448Z", - "shell.execute_reply": "2024-09-05T19:37:19.967010Z" + "iopub.execute_input": "2024-09-06T19:37:13.301807Z", + "iopub.status.busy": "2024-09-06T19:37:13.301492Z", + "iopub.status.idle": "2024-09-06T19:37:13.309949Z", + "shell.execute_reply": "2024-09-06T19:37:13.309476Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/datalab/text.ipynb b/master/.doctrees/nbsphinx/tutorials/datalab/text.ipynb index 9e0aa3195..0357de56a 100644 --- a/master/.doctrees/nbsphinx/tutorials/datalab/text.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/datalab/text.ipynb @@ -75,10 +75,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:22.667514Z", - "iopub.status.busy": "2024-09-05T19:37:22.667337Z", - "iopub.status.idle": "2024-09-05T19:37:25.554239Z", - "shell.execute_reply": "2024-09-05T19:37:25.553659Z" + "iopub.execute_input": "2024-09-06T19:37:16.238148Z", + "iopub.status.busy": "2024-09-06T19:37:16.237968Z", + "iopub.status.idle": "2024-09-06T19:37:19.032647Z", + "shell.execute_reply": "2024-09-06T19:37:19.031997Z" }, "nbsphinx": "hidden" }, @@ -96,7 +96,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -121,10 +121,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.556973Z", - "iopub.status.busy": "2024-09-05T19:37:25.556474Z", - "iopub.status.idle": "2024-09-05T19:37:25.559630Z", - "shell.execute_reply": "2024-09-05T19:37:25.559168Z" + "iopub.execute_input": "2024-09-06T19:37:19.035274Z", + "iopub.status.busy": "2024-09-06T19:37:19.034943Z", + "iopub.status.idle": "2024-09-06T19:37:19.038478Z", + "shell.execute_reply": "2024-09-06T19:37:19.037992Z" } }, "outputs": [], @@ -145,10 +145,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.561758Z", - "iopub.status.busy": "2024-09-05T19:37:25.561422Z", - "iopub.status.idle": "2024-09-05T19:37:25.564391Z", - "shell.execute_reply": "2024-09-05T19:37:25.563936Z" + "iopub.execute_input": "2024-09-06T19:37:19.040624Z", + "iopub.status.busy": "2024-09-06T19:37:19.040295Z", + "iopub.status.idle": "2024-09-06T19:37:19.043522Z", + "shell.execute_reply": "2024-09-06T19:37:19.043021Z" }, "nbsphinx": "hidden" }, @@ -178,10 +178,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.566426Z", - "iopub.status.busy": "2024-09-05T19:37:25.566086Z", - "iopub.status.idle": "2024-09-05T19:37:25.606289Z", - "shell.execute_reply": "2024-09-05T19:37:25.605745Z" + "iopub.execute_input": "2024-09-06T19:37:19.045678Z", + "iopub.status.busy": "2024-09-06T19:37:19.045330Z", + "iopub.status.idle": "2024-09-06T19:37:19.065598Z", + "shell.execute_reply": "2024-09-06T19:37:19.065087Z" } }, "outputs": [ @@ -271,10 +271,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.608523Z", - "iopub.status.busy": "2024-09-05T19:37:25.608173Z", - "iopub.status.idle": "2024-09-05T19:37:25.611849Z", - "shell.execute_reply": "2024-09-05T19:37:25.611337Z" + "iopub.execute_input": "2024-09-06T19:37:19.067819Z", + "iopub.status.busy": "2024-09-06T19:37:19.067470Z", + "iopub.status.idle": "2024-09-06T19:37:19.071077Z", + "shell.execute_reply": "2024-09-06T19:37:19.070583Z" } }, "outputs": [ @@ -283,7 +283,7 @@ "output_type": "stream", "text": [ "This dataset has 10 classes.\n", - "Classes: {'card_payment_fee_charged', 'cancel_transfer', 'apple_pay_or_google_pay', 'card_about_to_expire', 'change_pin', 'visa_or_mastercard', 'beneficiary_not_allowed', 'getting_spare_card', 'lost_or_stolen_phone', 'supported_cards_and_currencies'}\n" + "Classes: {'card_about_to_expire', 'card_payment_fee_charged', 'supported_cards_and_currencies', 'apple_pay_or_google_pay', 'beneficiary_not_allowed', 'lost_or_stolen_phone', 'visa_or_mastercard', 'cancel_transfer', 'getting_spare_card', 'change_pin'}\n" ] } ], @@ -307,10 +307,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.613929Z", - "iopub.status.busy": "2024-09-05T19:37:25.613661Z", - "iopub.status.idle": "2024-09-05T19:37:25.616746Z", - "shell.execute_reply": "2024-09-05T19:37:25.616205Z" + "iopub.execute_input": "2024-09-06T19:37:19.073199Z", + "iopub.status.busy": "2024-09-06T19:37:19.072859Z", + "iopub.status.idle": "2024-09-06T19:37:19.075873Z", + "shell.execute_reply": "2024-09-06T19:37:19.075346Z" } }, "outputs": [ @@ -365,10 +365,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.618901Z", - "iopub.status.busy": "2024-09-05T19:37:25.618568Z", - "iopub.status.idle": "2024-09-05T19:37:29.268375Z", - "shell.execute_reply": "2024-09-05T19:37:29.267707Z" + "iopub.execute_input": "2024-09-06T19:37:19.077966Z", + "iopub.status.busy": "2024-09-06T19:37:19.077636Z", + "iopub.status.idle": "2024-09-06T19:37:23.171760Z", + "shell.execute_reply": "2024-09-06T19:37:23.171196Z" } }, "outputs": [ @@ -416,10 +416,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:29.271118Z", - "iopub.status.busy": "2024-09-05T19:37:29.270673Z", - "iopub.status.idle": "2024-09-05T19:37:30.169853Z", - "shell.execute_reply": "2024-09-05T19:37:30.169263Z" + "iopub.execute_input": "2024-09-06T19:37:23.174471Z", + "iopub.status.busy": "2024-09-06T19:37:23.174274Z", + "iopub.status.idle": "2024-09-06T19:37:24.103567Z", + "shell.execute_reply": "2024-09-06T19:37:24.102969Z" }, "scrolled": true }, @@ -451,10 +451,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:30.172922Z", - "iopub.status.busy": "2024-09-05T19:37:30.172351Z", - "iopub.status.idle": "2024-09-05T19:37:30.175456Z", - "shell.execute_reply": "2024-09-05T19:37:30.174947Z" + "iopub.execute_input": "2024-09-06T19:37:24.107438Z", + "iopub.status.busy": "2024-09-06T19:37:24.106451Z", + "iopub.status.idle": "2024-09-06T19:37:24.110626Z", + "shell.execute_reply": "2024-09-06T19:37:24.110110Z" } }, "outputs": [], @@ -474,10 +474,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:30.177920Z", - "iopub.status.busy": "2024-09-05T19:37:30.177550Z", - "iopub.status.idle": "2024-09-05T19:37:32.209250Z", - "shell.execute_reply": "2024-09-05T19:37:32.208579Z" + "iopub.execute_input": "2024-09-06T19:37:24.114244Z", + "iopub.status.busy": "2024-09-06T19:37:24.113304Z", + "iopub.status.idle": "2024-09-06T19:37:26.122882Z", + "shell.execute_reply": "2024-09-06T19:37:26.122195Z" }, "scrolled": true }, @@ -521,10 +521,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.212395Z", - "iopub.status.busy": "2024-09-05T19:37:32.211737Z", - "iopub.status.idle": "2024-09-05T19:37:32.235720Z", - "shell.execute_reply": "2024-09-05T19:37:32.235203Z" + "iopub.execute_input": "2024-09-06T19:37:26.126146Z", + "iopub.status.busy": "2024-09-06T19:37:26.125493Z", + "iopub.status.idle": "2024-09-06T19:37:26.149493Z", + "shell.execute_reply": "2024-09-06T19:37:26.148954Z" }, "scrolled": true }, @@ -654,10 +654,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.238297Z", - "iopub.status.busy": "2024-09-05T19:37:32.237890Z", - "iopub.status.idle": "2024-09-05T19:37:32.247569Z", - "shell.execute_reply": "2024-09-05T19:37:32.247122Z" + "iopub.execute_input": "2024-09-06T19:37:26.152122Z", + "iopub.status.busy": "2024-09-06T19:37:26.151750Z", + "iopub.status.idle": "2024-09-06T19:37:26.163613Z", + "shell.execute_reply": "2024-09-06T19:37:26.163031Z" }, "scrolled": true }, @@ -767,10 +767,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.249546Z", - "iopub.status.busy": "2024-09-05T19:37:32.249251Z", - "iopub.status.idle": "2024-09-05T19:37:32.253306Z", - "shell.execute_reply": "2024-09-05T19:37:32.252844Z" + "iopub.execute_input": "2024-09-06T19:37:26.165819Z", + "iopub.status.busy": "2024-09-06T19:37:26.165507Z", + "iopub.status.idle": "2024-09-06T19:37:26.169927Z", + "shell.execute_reply": "2024-09-06T19:37:26.169445Z" } }, "outputs": [ @@ -808,10 +808,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.255258Z", - "iopub.status.busy": "2024-09-05T19:37:32.255073Z", - "iopub.status.idle": "2024-09-05T19:37:32.261559Z", - "shell.execute_reply": "2024-09-05T19:37:32.261077Z" + "iopub.execute_input": "2024-09-06T19:37:26.171802Z", + "iopub.status.busy": "2024-09-06T19:37:26.171622Z", + "iopub.status.idle": "2024-09-06T19:37:26.178323Z", + "shell.execute_reply": "2024-09-06T19:37:26.177759Z" } }, "outputs": [ @@ -928,10 +928,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.263657Z", - "iopub.status.busy": "2024-09-05T19:37:32.263325Z", - "iopub.status.idle": "2024-09-05T19:37:32.269747Z", - "shell.execute_reply": "2024-09-05T19:37:32.269278Z" + "iopub.execute_input": "2024-09-06T19:37:26.180430Z", + "iopub.status.busy": "2024-09-06T19:37:26.180102Z", + "iopub.status.idle": "2024-09-06T19:37:26.186371Z", + "shell.execute_reply": "2024-09-06T19:37:26.185807Z" } }, "outputs": [ @@ -1014,10 +1014,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.271867Z", - "iopub.status.busy": "2024-09-05T19:37:32.271500Z", - "iopub.status.idle": "2024-09-05T19:37:32.277119Z", - "shell.execute_reply": "2024-09-05T19:37:32.276609Z" + "iopub.execute_input": "2024-09-06T19:37:26.188480Z", + "iopub.status.busy": "2024-09-06T19:37:26.188150Z", + "iopub.status.idle": "2024-09-06T19:37:26.194198Z", + "shell.execute_reply": "2024-09-06T19:37:26.193624Z" } }, "outputs": [ @@ -1125,10 +1125,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.279176Z", - "iopub.status.busy": "2024-09-05T19:37:32.278837Z", - "iopub.status.idle": "2024-09-05T19:37:32.287109Z", - "shell.execute_reply": "2024-09-05T19:37:32.286569Z" + "iopub.execute_input": "2024-09-06T19:37:26.196327Z", + "iopub.status.busy": "2024-09-06T19:37:26.195981Z", + "iopub.status.idle": "2024-09-06T19:37:26.204376Z", + "shell.execute_reply": "2024-09-06T19:37:26.203913Z" } }, "outputs": [ @@ -1239,10 +1239,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.289281Z", - "iopub.status.busy": "2024-09-05T19:37:32.288965Z", - "iopub.status.idle": "2024-09-05T19:37:32.294242Z", - "shell.execute_reply": "2024-09-05T19:37:32.293707Z" + "iopub.execute_input": "2024-09-06T19:37:26.206432Z", + "iopub.status.busy": "2024-09-06T19:37:26.206091Z", + "iopub.status.idle": "2024-09-06T19:37:26.211539Z", + "shell.execute_reply": "2024-09-06T19:37:26.211070Z" } }, "outputs": [ @@ -1310,10 +1310,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.296374Z", - "iopub.status.busy": "2024-09-05T19:37:32.296057Z", - "iopub.status.idle": "2024-09-05T19:37:32.301404Z", - "shell.execute_reply": "2024-09-05T19:37:32.300861Z" + "iopub.execute_input": "2024-09-06T19:37:26.213685Z", + "iopub.status.busy": "2024-09-06T19:37:26.213350Z", + "iopub.status.idle": "2024-09-06T19:37:26.218528Z", + "shell.execute_reply": "2024-09-06T19:37:26.218074Z" } }, "outputs": [ @@ -1392,10 +1392,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.303349Z", - "iopub.status.busy": "2024-09-05T19:37:32.303171Z", - "iopub.status.idle": "2024-09-05T19:37:32.306705Z", - "shell.execute_reply": "2024-09-05T19:37:32.306262Z" + "iopub.execute_input": "2024-09-06T19:37:26.220571Z", + "iopub.status.busy": "2024-09-06T19:37:26.220232Z", + "iopub.status.idle": "2024-09-06T19:37:26.223906Z", + "shell.execute_reply": "2024-09-06T19:37:26.223327Z" } }, "outputs": [ @@ -1449,10 +1449,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.308852Z", - "iopub.status.busy": "2024-09-05T19:37:32.308521Z", - "iopub.status.idle": "2024-09-05T19:37:32.313482Z", - "shell.execute_reply": "2024-09-05T19:37:32.313025Z" + "iopub.execute_input": "2024-09-06T19:37:26.226160Z", + "iopub.status.busy": "2024-09-06T19:37:26.225819Z", + "iopub.status.idle": "2024-09-06T19:37:26.231140Z", + "shell.execute_reply": "2024-09-06T19:37:26.230573Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/datalab/workflows.ipynb b/master/.doctrees/nbsphinx/tutorials/datalab/workflows.ipynb index b458579ea..0c93ce2cb 100644 --- a/master/.doctrees/nbsphinx/tutorials/datalab/workflows.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/datalab/workflows.ipynb @@ -38,10 +38,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:35.608990Z", - "iopub.status.busy": "2024-09-05T19:37:35.608804Z", - "iopub.status.idle": "2024-09-05T19:37:36.049800Z", - "shell.execute_reply": "2024-09-05T19:37:36.049289Z" + "iopub.execute_input": "2024-09-06T19:37:29.604724Z", + "iopub.status.busy": "2024-09-06T19:37:29.604545Z", + "iopub.status.idle": "2024-09-06T19:37:30.035194Z", + "shell.execute_reply": "2024-09-06T19:37:30.034674Z" } }, "outputs": [], @@ -87,10 +87,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:36.052464Z", - "iopub.status.busy": "2024-09-05T19:37:36.052028Z", - "iopub.status.idle": "2024-09-05T19:37:36.185608Z", - "shell.execute_reply": "2024-09-05T19:37:36.185012Z" + "iopub.execute_input": "2024-09-06T19:37:30.037845Z", + "iopub.status.busy": "2024-09-06T19:37:30.037406Z", + "iopub.status.idle": "2024-09-06T19:37:30.168185Z", + "shell.execute_reply": "2024-09-06T19:37:30.167636Z" } }, "outputs": [ @@ -181,10 +181,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:36.188213Z", - "iopub.status.busy": "2024-09-05T19:37:36.187785Z", - "iopub.status.idle": "2024-09-05T19:37:36.211771Z", - "shell.execute_reply": "2024-09-05T19:37:36.211203Z" + "iopub.execute_input": "2024-09-06T19:37:30.170587Z", + "iopub.status.busy": "2024-09-06T19:37:30.170087Z", + "iopub.status.idle": "2024-09-06T19:37:30.193350Z", + "shell.execute_reply": "2024-09-06T19:37:30.192776Z" } }, "outputs": [], @@ -210,10 +210,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:36.214778Z", - "iopub.status.busy": "2024-09-05T19:37:36.214297Z", - "iopub.status.idle": "2024-09-05T19:37:39.119007Z", - "shell.execute_reply": "2024-09-05T19:37:39.118344Z" + "iopub.execute_input": "2024-09-06T19:37:30.195997Z", + "iopub.status.busy": "2024-09-06T19:37:30.195790Z", + "iopub.status.idle": "2024-09-06T19:37:32.997740Z", + "shell.execute_reply": "2024-09-06T19:37:32.997128Z" } }, "outputs": [ @@ -700,10 +700,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:39.121802Z", - "iopub.status.busy": "2024-09-05T19:37:39.121239Z", - "iopub.status.idle": "2024-09-05T19:37:48.039020Z", - "shell.execute_reply": "2024-09-05T19:37:48.038375Z" + "iopub.execute_input": "2024-09-06T19:37:33.000426Z", + "iopub.status.busy": "2024-09-06T19:37:32.999838Z", + "iopub.status.idle": "2024-09-06T19:37:42.839981Z", + "shell.execute_reply": "2024-09-06T19:37:42.839475Z" } }, "outputs": [ @@ -804,10 +804,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:48.041586Z", - "iopub.status.busy": "2024-09-05T19:37:48.041203Z", - "iopub.status.idle": "2024-09-05T19:37:48.208174Z", - "shell.execute_reply": "2024-09-05T19:37:48.207546Z" + "iopub.execute_input": "2024-09-06T19:37:42.842458Z", + "iopub.status.busy": "2024-09-06T19:37:42.842052Z", + "iopub.status.idle": "2024-09-06T19:37:43.014469Z", + "shell.execute_reply": "2024-09-06T19:37:43.013871Z" } }, "outputs": [], @@ -838,10 +838,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:48.210728Z", - "iopub.status.busy": "2024-09-05T19:37:48.210421Z", - "iopub.status.idle": "2024-09-05T19:37:49.609527Z", - "shell.execute_reply": "2024-09-05T19:37:49.609004Z" + "iopub.execute_input": "2024-09-06T19:37:43.016817Z", + "iopub.status.busy": "2024-09-06T19:37:43.016641Z", + "iopub.status.idle": "2024-09-06T19:37:44.396004Z", + "shell.execute_reply": "2024-09-06T19:37:44.395431Z" } }, "outputs": [ @@ -1000,10 +1000,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:49.611837Z", - "iopub.status.busy": "2024-09-05T19:37:49.611455Z", - "iopub.status.idle": "2024-09-05T19:37:50.149593Z", - "shell.execute_reply": "2024-09-05T19:37:50.149038Z" + "iopub.execute_input": "2024-09-06T19:37:44.398298Z", + "iopub.status.busy": "2024-09-06T19:37:44.397931Z", + "iopub.status.idle": "2024-09-06T19:37:44.810929Z", + "shell.execute_reply": "2024-09-06T19:37:44.810371Z" } }, "outputs": [ @@ -1082,10 +1082,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.152292Z", - "iopub.status.busy": "2024-09-05T19:37:50.151696Z", - "iopub.status.idle": "2024-09-05T19:37:50.165608Z", - "shell.execute_reply": "2024-09-05T19:37:50.165110Z" + "iopub.execute_input": "2024-09-06T19:37:44.813440Z", + "iopub.status.busy": "2024-09-06T19:37:44.812940Z", + "iopub.status.idle": "2024-09-06T19:37:44.826271Z", + "shell.execute_reply": "2024-09-06T19:37:44.825842Z" } }, "outputs": [], @@ -1115,10 +1115,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.167994Z", - "iopub.status.busy": "2024-09-05T19:37:50.167587Z", - "iopub.status.idle": "2024-09-05T19:37:50.186934Z", - "shell.execute_reply": "2024-09-05T19:37:50.186405Z" + "iopub.execute_input": "2024-09-06T19:37:44.828390Z", + "iopub.status.busy": "2024-09-06T19:37:44.828044Z", + "iopub.status.idle": "2024-09-06T19:37:44.847179Z", + "shell.execute_reply": "2024-09-06T19:37:44.846760Z" } }, "outputs": [], @@ -1146,10 +1146,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.189317Z", - "iopub.status.busy": "2024-09-05T19:37:50.189017Z", - "iopub.status.idle": "2024-09-05T19:37:50.417357Z", - "shell.execute_reply": "2024-09-05T19:37:50.416811Z" + "iopub.execute_input": "2024-09-06T19:37:44.849314Z", + "iopub.status.busy": "2024-09-06T19:37:44.848979Z", + "iopub.status.idle": "2024-09-06T19:37:45.077019Z", + "shell.execute_reply": "2024-09-06T19:37:45.076447Z" } }, "outputs": [], @@ -1189,10 +1189,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.420095Z", - "iopub.status.busy": "2024-09-05T19:37:50.419658Z", - "iopub.status.idle": "2024-09-05T19:37:50.440418Z", - "shell.execute_reply": "2024-09-05T19:37:50.439793Z" + "iopub.execute_input": "2024-09-06T19:37:45.079688Z", + "iopub.status.busy": "2024-09-06T19:37:45.079281Z", + "iopub.status.idle": "2024-09-06T19:37:45.098946Z", + "shell.execute_reply": "2024-09-06T19:37:45.098466Z" } }, "outputs": [ @@ -1390,10 +1390,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.442606Z", - "iopub.status.busy": "2024-09-05T19:37:50.442414Z", - "iopub.status.idle": "2024-09-05T19:37:50.615431Z", - "shell.execute_reply": "2024-09-05T19:37:50.614827Z" + "iopub.execute_input": "2024-09-06T19:37:45.101100Z", + "iopub.status.busy": "2024-09-06T19:37:45.100762Z", + "iopub.status.idle": "2024-09-06T19:37:45.277489Z", + "shell.execute_reply": "2024-09-06T19:37:45.276850Z" } }, "outputs": [ @@ -1460,10 +1460,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.617758Z", - "iopub.status.busy": "2024-09-05T19:37:50.617562Z", - "iopub.status.idle": "2024-09-05T19:37:50.628108Z", - "shell.execute_reply": "2024-09-05T19:37:50.627590Z" + "iopub.execute_input": "2024-09-06T19:37:45.279928Z", + "iopub.status.busy": "2024-09-06T19:37:45.279722Z", + "iopub.status.idle": "2024-09-06T19:37:45.290798Z", + "shell.execute_reply": "2024-09-06T19:37:45.290229Z" } }, "outputs": [ @@ -1729,10 +1729,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.630389Z", - "iopub.status.busy": "2024-09-05T19:37:50.630031Z", - "iopub.status.idle": "2024-09-05T19:37:50.640010Z", - "shell.execute_reply": "2024-09-05T19:37:50.639473Z" + "iopub.execute_input": "2024-09-06T19:37:45.292867Z", + "iopub.status.busy": "2024-09-06T19:37:45.292672Z", + "iopub.status.idle": "2024-09-06T19:37:45.302178Z", + "shell.execute_reply": "2024-09-06T19:37:45.301745Z" } }, "outputs": [ @@ -1919,10 +1919,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.642181Z", - "iopub.status.busy": "2024-09-05T19:37:50.641826Z", - "iopub.status.idle": "2024-09-05T19:37:50.671287Z", - "shell.execute_reply": "2024-09-05T19:37:50.670793Z" + "iopub.execute_input": "2024-09-06T19:37:45.304034Z", + "iopub.status.busy": "2024-09-06T19:37:45.303861Z", + "iopub.status.idle": "2024-09-06T19:37:45.329485Z", + "shell.execute_reply": "2024-09-06T19:37:45.329066Z" } }, "outputs": [], @@ -1956,10 +1956,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.673864Z", - "iopub.status.busy": "2024-09-05T19:37:50.673387Z", - "iopub.status.idle": "2024-09-05T19:37:50.676503Z", - "shell.execute_reply": "2024-09-05T19:37:50.675922Z" + "iopub.execute_input": "2024-09-06T19:37:45.331450Z", + "iopub.status.busy": "2024-09-06T19:37:45.331118Z", + "iopub.status.idle": "2024-09-06T19:37:45.333941Z", + "shell.execute_reply": "2024-09-06T19:37:45.333348Z" } }, "outputs": [], @@ -1981,10 +1981,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.678746Z", - "iopub.status.busy": "2024-09-05T19:37:50.678397Z", - "iopub.status.idle": "2024-09-05T19:37:50.698912Z", - "shell.execute_reply": "2024-09-05T19:37:50.698309Z" + "iopub.execute_input": "2024-09-06T19:37:45.336081Z", + "iopub.status.busy": "2024-09-06T19:37:45.335742Z", + "iopub.status.idle": "2024-09-06T19:37:45.354797Z", + "shell.execute_reply": "2024-09-06T19:37:45.354315Z" } }, "outputs": [ @@ -2142,10 +2142,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.701349Z", - "iopub.status.busy": "2024-09-05T19:37:50.700967Z", - "iopub.status.idle": "2024-09-05T19:37:50.705309Z", - "shell.execute_reply": "2024-09-05T19:37:50.704840Z" + "iopub.execute_input": "2024-09-06T19:37:45.356897Z", + "iopub.status.busy": "2024-09-06T19:37:45.356543Z", + "iopub.status.idle": "2024-09-06T19:37:45.360935Z", + "shell.execute_reply": "2024-09-06T19:37:45.360328Z" } }, "outputs": [], @@ -2178,10 +2178,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.707600Z", - "iopub.status.busy": "2024-09-05T19:37:50.707256Z", - "iopub.status.idle": "2024-09-05T19:37:50.737701Z", - "shell.execute_reply": "2024-09-05T19:37:50.737181Z" + "iopub.execute_input": "2024-09-06T19:37:45.363152Z", + "iopub.status.busy": "2024-09-06T19:37:45.362835Z", + "iopub.status.idle": "2024-09-06T19:37:45.390311Z", + "shell.execute_reply": "2024-09-06T19:37:45.389739Z" } }, "outputs": [ @@ -2327,10 +2327,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.740155Z", - "iopub.status.busy": "2024-09-05T19:37:50.739645Z", - "iopub.status.idle": "2024-09-05T19:37:51.096104Z", - "shell.execute_reply": "2024-09-05T19:37:51.095515Z" + "iopub.execute_input": "2024-09-06T19:37:45.392321Z", + "iopub.status.busy": "2024-09-06T19:37:45.392005Z", + "iopub.status.idle": "2024-09-06T19:37:45.759141Z", + "shell.execute_reply": "2024-09-06T19:37:45.758581Z" } }, "outputs": [ @@ -2397,10 +2397,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.098341Z", - "iopub.status.busy": "2024-09-05T19:37:51.098156Z", - "iopub.status.idle": "2024-09-05T19:37:51.101609Z", - "shell.execute_reply": "2024-09-05T19:37:51.101125Z" + "iopub.execute_input": "2024-09-06T19:37:45.761452Z", + "iopub.status.busy": "2024-09-06T19:37:45.761084Z", + "iopub.status.idle": "2024-09-06T19:37:45.764398Z", + "shell.execute_reply": "2024-09-06T19:37:45.763923Z" } }, "outputs": [ @@ -2451,10 +2451,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.103763Z", - "iopub.status.busy": "2024-09-05T19:37:51.103431Z", - "iopub.status.idle": "2024-09-05T19:37:51.117191Z", - "shell.execute_reply": "2024-09-05T19:37:51.116674Z" + "iopub.execute_input": "2024-09-06T19:37:45.766685Z", + "iopub.status.busy": "2024-09-06T19:37:45.766351Z", + "iopub.status.idle": "2024-09-06T19:37:45.779490Z", + "shell.execute_reply": "2024-09-06T19:37:45.779045Z" } }, "outputs": [ @@ -2733,10 +2733,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.119477Z", - "iopub.status.busy": "2024-09-05T19:37:51.119122Z", - "iopub.status.idle": "2024-09-05T19:37:51.136499Z", - "shell.execute_reply": "2024-09-05T19:37:51.135847Z" + "iopub.execute_input": "2024-09-06T19:37:45.781428Z", + "iopub.status.busy": "2024-09-06T19:37:45.781250Z", + "iopub.status.idle": "2024-09-06T19:37:45.796041Z", + "shell.execute_reply": "2024-09-06T19:37:45.795601Z" } }, "outputs": [ @@ -3003,10 +3003,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.138657Z", - "iopub.status.busy": "2024-09-05T19:37:51.138457Z", - "iopub.status.idle": "2024-09-05T19:37:51.148925Z", - "shell.execute_reply": "2024-09-05T19:37:51.148440Z" + "iopub.execute_input": "2024-09-06T19:37:45.798043Z", + "iopub.status.busy": "2024-09-06T19:37:45.797870Z", + "iopub.status.idle": "2024-09-06T19:37:45.807740Z", + "shell.execute_reply": "2024-09-06T19:37:45.807165Z" } }, "outputs": [], @@ -3031,10 +3031,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.151091Z", - "iopub.status.busy": "2024-09-05T19:37:51.150913Z", - "iopub.status.idle": "2024-09-05T19:37:51.161080Z", - "shell.execute_reply": "2024-09-05T19:37:51.160404Z" + "iopub.execute_input": "2024-09-06T19:37:45.809952Z", + "iopub.status.busy": "2024-09-06T19:37:45.809629Z", + "iopub.status.idle": "2024-09-06T19:37:45.818832Z", + "shell.execute_reply": "2024-09-06T19:37:45.818256Z" } }, "outputs": [ @@ -3206,10 +3206,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.163142Z", - "iopub.status.busy": "2024-09-05T19:37:51.162957Z", - "iopub.status.idle": "2024-09-05T19:37:51.166908Z", - "shell.execute_reply": "2024-09-05T19:37:51.166441Z" + "iopub.execute_input": "2024-09-06T19:37:45.821154Z", + "iopub.status.busy": "2024-09-06T19:37:45.820691Z", + "iopub.status.idle": "2024-09-06T19:37:45.824900Z", + "shell.execute_reply": "2024-09-06T19:37:45.824317Z" } }, "outputs": [], @@ -3241,10 +3241,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.168894Z", - "iopub.status.busy": "2024-09-05T19:37:51.168718Z", - "iopub.status.idle": "2024-09-05T19:37:51.221568Z", - "shell.execute_reply": "2024-09-05T19:37:51.220997Z" + "iopub.execute_input": "2024-09-06T19:37:45.826963Z", + "iopub.status.busy": "2024-09-06T19:37:45.826647Z", + "iopub.status.idle": "2024-09-06T19:37:45.876648Z", + "shell.execute_reply": "2024-09-06T19:37:45.876084Z" } }, "outputs": [ @@ -3252,230 +3252,230 @@ "data": { "text/html": [ "\n", - "\n", + "
\n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", "
 AgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_scoreAgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_score
8nannannannannanNaTTrue0.000000
1nanFemaleRural6421.1600005.000000NaTFalse0.666667
9nanMaleRural4655.8200001.000000NaTFalse0.666667
14nanMaleRural6790.4600003.000000NaTFalse0.666667
13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.0000008nannannannannanNaTTrue0.000000
1nanFemaleRural6421.1600005.000000NaTFalse0.666667
9nanMaleRural4655.8200001.000000NaTFalse0.666667
14nanMaleRural6790.4600003.000000NaTFalse0.666667
13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.000000
\n" ], "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -3551,10 +3551,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.224233Z", - "iopub.status.busy": "2024-09-05T19:37:51.223659Z", - "iopub.status.idle": "2024-09-05T19:37:51.229976Z", - "shell.execute_reply": "2024-09-05T19:37:51.229459Z" + "iopub.execute_input": "2024-09-06T19:37:45.878907Z", + "iopub.status.busy": "2024-09-06T19:37:45.878480Z", + "iopub.status.idle": "2024-09-06T19:37:45.884204Z", + "shell.execute_reply": "2024-09-06T19:37:45.883634Z" } }, "outputs": [], @@ -3593,10 +3593,10 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.232017Z", - "iopub.status.busy": "2024-09-05T19:37:51.231819Z", - "iopub.status.idle": "2024-09-05T19:37:51.243359Z", - "shell.execute_reply": "2024-09-05T19:37:51.242861Z" + "iopub.execute_input": "2024-09-06T19:37:45.886291Z", + "iopub.status.busy": "2024-09-06T19:37:45.885973Z", + "iopub.status.idle": "2024-09-06T19:37:45.897008Z", + "shell.execute_reply": "2024-09-06T19:37:45.896438Z" } }, "outputs": [ @@ -3632,10 +3632,10 @@ "execution_count": 31, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.245457Z", - "iopub.status.busy": "2024-09-05T19:37:51.245279Z", - "iopub.status.idle": "2024-09-05T19:37:51.475856Z", - "shell.execute_reply": "2024-09-05T19:37:51.475287Z" + "iopub.execute_input": "2024-09-06T19:37:45.899243Z", + "iopub.status.busy": "2024-09-06T19:37:45.898904Z", + "iopub.status.idle": "2024-09-06T19:37:46.075809Z", + "shell.execute_reply": "2024-09-06T19:37:46.075226Z" } }, "outputs": [ @@ -3687,10 +3687,10 @@ "execution_count": 32, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.478345Z", - "iopub.status.busy": "2024-09-05T19:37:51.477903Z", - "iopub.status.idle": "2024-09-05T19:37:51.486021Z", - "shell.execute_reply": "2024-09-05T19:37:51.485523Z" + "iopub.execute_input": "2024-09-06T19:37:46.078430Z", + "iopub.status.busy": "2024-09-06T19:37:46.077957Z", + "iopub.status.idle": "2024-09-06T19:37:46.085812Z", + "shell.execute_reply": "2024-09-06T19:37:46.085244Z" }, "nbsphinx": "hidden" }, @@ -3756,10 +3756,10 @@ "execution_count": 33, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.488092Z", - "iopub.status.busy": "2024-09-05T19:37:51.487894Z", - "iopub.status.idle": "2024-09-05T19:37:51.860873Z", - "shell.execute_reply": "2024-09-05T19:37:51.860210Z" + "iopub.execute_input": "2024-09-06T19:37:46.087762Z", + "iopub.status.busy": "2024-09-06T19:37:46.087589Z", + "iopub.status.idle": "2024-09-06T19:37:46.522443Z", + "shell.execute_reply": "2024-09-06T19:37:46.521749Z" } }, "outputs": [ @@ -3767,25 +3767,25 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-09-05 19:37:51-- https://s.cleanlab.ai/CIFAR-10-subset.zip\r\n", - "Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.109.153, 185.199.108.153, 185.199.111.153, ...\r\n", - "Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.109.153|:443... connected.\r\n", - "HTTP request sent, awaiting response... 200 OK\r\n", - "Length: 986707 (964K) [application/zip]\r\n", - "Saving to: ‘CIFAR-10-subset.zip’\r\n", - "\r\n", - "\r", - "CIFAR-10-subset.zip 0%[ ] 0 --.-KB/s " + "--2024-09-06 19:37:46-- https://s.cleanlab.ai/CIFAR-10-subset.zip\r\n", + "Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.111.153, 185.199.110.153, 185.199.109.153, ...\r\n", + "Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.111.153|:443... connected.\r\n", + "HTTP request sent, awaiting response... " ] }, { "name": "stdout", "output_type": "stream", "text": [ + "200 OK\r\n", + "Length: 986707 (964K) [application/zip]\r\n", + "Saving to: ‘CIFAR-10-subset.zip’\r\n", + "\r\n", "\r", - "CIFAR-10-subset.zip 100%[===================>] 963.58K --.-KB/s in 0.03s \r\n", + "CIFAR-10-subset.zip 0%[ ] 0 --.-KB/s \r", + "CIFAR-10-subset.zip 100%[===================>] 963.58K --.-KB/s in 0.005s \r\n", "\r\n", - "2024-09-05 19:37:51 (32.9 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]\r\n", + "2024-09-06 19:37:46 (176 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]\r\n", "\r\n" ] } @@ -3801,10 +3801,10 @@ "execution_count": 34, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.863648Z", - "iopub.status.busy": "2024-09-05T19:37:51.863430Z", - "iopub.status.idle": "2024-09-05T19:37:53.857499Z", - "shell.execute_reply": "2024-09-05T19:37:53.856936Z" + "iopub.execute_input": "2024-09-06T19:37:46.525178Z", + "iopub.status.busy": "2024-09-06T19:37:46.524748Z", + "iopub.status.idle": "2024-09-06T19:37:48.452276Z", + "shell.execute_reply": "2024-09-06T19:37:48.451758Z" } }, "outputs": [], @@ -3850,10 +3850,10 @@ "execution_count": 35, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:53.860032Z", - "iopub.status.busy": "2024-09-05T19:37:53.859675Z", - "iopub.status.idle": "2024-09-05T19:37:54.515213Z", - "shell.execute_reply": "2024-09-05T19:37:54.514565Z" + "iopub.execute_input": "2024-09-06T19:37:48.454913Z", + "iopub.status.busy": "2024-09-06T19:37:48.454468Z", + "iopub.status.idle": "2024-09-06T19:37:49.092778Z", + "shell.execute_reply": "2024-09-06T19:37:49.092169Z" } }, "outputs": [ @@ -3868,7 +3868,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6a8633562ced4f21b9e1b849b611603d", + "model_id": "a5793cf283c046f188f735beef4577a5", "version_major": 2, "version_minor": 0 }, @@ -4008,10 +4008,10 @@ "execution_count": 36, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:54.518192Z", - "iopub.status.busy": "2024-09-05T19:37:54.517837Z", - "iopub.status.idle": "2024-09-05T19:37:54.531474Z", - "shell.execute_reply": "2024-09-05T19:37:54.530950Z" + "iopub.execute_input": "2024-09-06T19:37:49.095580Z", + "iopub.status.busy": "2024-09-06T19:37:49.095115Z", + "iopub.status.idle": "2024-09-06T19:37:49.108940Z", + "shell.execute_reply": "2024-09-06T19:37:49.108334Z" } }, "outputs": [ @@ -4130,35 +4130,35 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 0\n", - " 0.237196\n", " True\n", + " 0.237196\n", " \n", " \n", " 1\n", - " 0.197229\n", " True\n", + " 0.197229\n", " \n", " \n", " 2\n", - " 0.254188\n", " True\n", + " 0.254188\n", " \n", " \n", " 3\n", - " 0.229170\n", " True\n", + " 0.229170\n", " \n", " \n", " 4\n", - " 0.208907\n", " True\n", + " 0.208907\n", " \n", " \n", " ...\n", @@ -4167,28 +4167,28 @@ " \n", " \n", " 195\n", - " 0.793840\n", " False\n", + " 0.793840\n", " \n", " \n", " 196\n", - " 1.000000\n", " False\n", + " 1.000000\n", " \n", " \n", " 197\n", - " 0.971560\n", " False\n", + " 0.971560\n", " \n", " \n", " 198\n", - " 0.862236\n", " False\n", + " 0.862236\n", " \n", " \n", " 199\n", - " 0.973533\n", " False\n", + " 0.973533\n", " \n", " \n", "\n", @@ -4196,18 +4196,18 @@ "" ], "text/plain": [ - " dark_score is_dark_issue\n", - "0 0.237196 True\n", - "1 0.197229 True\n", - "2 0.254188 True\n", - "3 0.229170 True\n", - "4 0.208907 True\n", - ".. ... ...\n", - "195 0.793840 False\n", - "196 1.000000 False\n", - "197 0.971560 False\n", - "198 0.862236 False\n", - "199 0.973533 False\n", + " is_dark_issue dark_score\n", + "0 True 0.237196\n", + "1 True 0.197229\n", + "2 True 0.254188\n", + "3 True 0.229170\n", + "4 True 0.208907\n", + ".. ... ...\n", + "195 False 0.793840\n", + "196 False 1.000000\n", + "197 False 0.971560\n", + "198 False 0.862236\n", + "199 False 0.973533\n", "\n", "[200 rows x 2 columns]" ] @@ -4257,10 +4257,10 @@ "execution_count": 37, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:54.534111Z", - "iopub.status.busy": "2024-09-05T19:37:54.533778Z", - "iopub.status.idle": "2024-09-05T19:37:54.685884Z", - "shell.execute_reply": "2024-09-05T19:37:54.685435Z" + "iopub.execute_input": "2024-09-06T19:37:49.112413Z", + "iopub.status.busy": "2024-09-06T19:37:49.112212Z", + "iopub.status.idle": "2024-09-06T19:37:49.262201Z", + "shell.execute_reply": "2024-09-06T19:37:49.261645Z" } }, "outputs": [ @@ -4325,10 +4325,10 @@ "execution_count": 38, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:54.688065Z", - "iopub.status.busy": "2024-09-05T19:37:54.687765Z", - "iopub.status.idle": "2024-09-05T19:37:55.189906Z", - "shell.execute_reply": "2024-09-05T19:37:55.189260Z" + "iopub.execute_input": "2024-09-06T19:37:49.264493Z", + "iopub.status.busy": "2024-09-06T19:37:49.264138Z", + "iopub.status.idle": "2024-09-06T19:37:49.776468Z", + "shell.execute_reply": "2024-09-06T19:37:49.775810Z" }, "nbsphinx": "hidden" }, @@ -4344,7 +4344,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0491ab817f3e4abfae647f24171e651f", + "model_id": "e53b81d02870488ca1d70faf1534371f", "version_major": 2, "version_minor": 0 }, @@ -4473,35 +4473,35 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 0\n", - " 0.797509\n", " False\n", + " 0.797509\n", " \n", " \n", " 1\n", - " 0.663760\n", " False\n", + " 0.663760\n", " \n", " \n", " 2\n", - " 0.849826\n", " False\n", + " 0.849826\n", " \n", " \n", " 3\n", - " 0.773951\n", " False\n", + " 0.773951\n", " \n", " \n", " 4\n", - " 0.699518\n", " False\n", + " 0.699518\n", " \n", " \n", " ...\n", @@ -4510,28 +4510,28 @@ " \n", " \n", " 195\n", - " 0.793840\n", " False\n", + " 0.793840\n", " \n", " \n", " 196\n", - " 1.000000\n", " False\n", + " 1.000000\n", " \n", " \n", " 197\n", - " 0.971560\n", " False\n", + " 0.971560\n", " \n", " \n", " 198\n", - " 0.862236\n", " False\n", + " 0.862236\n", " \n", " \n", " 199\n", - " 0.973533\n", " False\n", + " 0.973533\n", " \n", " \n", "\n", @@ -4539,18 +4539,18 @@ "" ], "text/plain": [ - " dark_score is_dark_issue\n", - "0 0.797509 False\n", - "1 0.663760 False\n", - "2 0.849826 False\n", - "3 0.773951 False\n", - "4 0.699518 False\n", - ".. ... ...\n", - "195 0.793840 False\n", - "196 1.000000 False\n", - "197 0.971560 False\n", - "198 0.862236 False\n", - "199 0.973533 False\n", + " is_dark_issue dark_score\n", + "0 False 0.797509\n", + "1 False 0.663760\n", + "2 False 0.849826\n", + "3 False 0.773951\n", + "4 False 0.699518\n", + ".. ... ...\n", + "195 False 0.793840\n", + "196 False 1.000000\n", + "197 False 0.971560\n", + "198 False 0.862236\n", + "199 False 0.973533\n", "\n", "[200 rows x 2 columns]" ] @@ -4598,10 +4598,10 @@ "execution_count": 39, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:55.192457Z", - "iopub.status.busy": "2024-09-05T19:37:55.192089Z", - "iopub.status.idle": "2024-09-05T19:37:55.344435Z", - "shell.execute_reply": "2024-09-05T19:37:55.343755Z" + "iopub.execute_input": "2024-09-06T19:37:49.778901Z", + "iopub.status.busy": "2024-09-06T19:37:49.778528Z", + "iopub.status.idle": "2024-09-06T19:37:49.924980Z", + "shell.execute_reply": "2024-09-06T19:37:49.924477Z" }, "nbsphinx": "hidden" }, @@ -4653,31 +4653,83 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "0491ab817f3e4abfae647f24171e651f": { + "021a50164b8c491ebb069bd57b11ce1a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2cb88e5e7d0f4849b336950480e87a06": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_7e84cf312cfa4d80a5107dcdb0a45949", - "IPY_MODEL_7557f4205917445ca0c596993a114685", - "IPY_MODEL_dc9edc5341cb452cb27aada834ac562d" - ], - "layout": "IPY_MODEL_a1d59c28e7064efc92b1e3caf26f9346", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_5349f02a0bb24786bba46192aa1d90ff", + "placeholder": "​", + "style": "IPY_MODEL_b93c4b8b97f34f0b93a2d334e5065e1b", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": "100%" } }, - "37eeb5a0817c455a8d0efe07a3d6bd44": { + "313b234230ce4ce4850b3fa6a5e1b1ee": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4730,7 +4782,7 @@ "width": null } }, - "37f6d18ef4a24f62a2d67a08d8dae98c": { + "41bdd318b6d1453a8daca74a0776e419": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4783,39 +4835,7 @@ "width": null } }, - "3f81fed11b61470bac6f5d0b3b537a4f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "4bbbb6bbcc9648459b5d261cb8ab6826": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "550c28ddb9cf43c3b62b1a0b54f7bd12": { + "5349f02a0bb24786bba46192aa1d90ff": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4868,49 +4888,56 @@ "width": null } }, - "62793e1d0aa84395bb5ab3f9ff86c9b5": { + "5664879b48124f5cac1e0a8c43742995": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_da820a1ccd2b42d4a8c12ea0328d1169", + "max": 200.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_da8ad4a548a8409389fab7ddc0e601bc", + "tabbable": null, + "tooltip": null, + "value": 200.0 } }, - "6a8633562ced4f21b9e1b849b611603d": { + "6529bc3e5e35424f967dab0385030a5c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_db046a62f4e34aa594499d33fa68145f", - "IPY_MODEL_a6c8cc603a414e80a6ba376c29f15b21", - "IPY_MODEL_df91c80300534ab59fe080ab28475f7a" - ], - "layout": "IPY_MODEL_37f6d18ef4a24f62a2d67a08d8dae98c", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_41bdd318b6d1453a8daca74a0776e419", + "placeholder": "​", + "style": "IPY_MODEL_dfac24cbd04d4a6a9c6a2f3d7e34c87e", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": " 200/200 [00:00<00:00, 682.83it/s]" } }, - "7557f4205917445ca0c596993a114685": { + "733b0d114c6e48e6af9ced8acfb5bf3a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -4926,17 +4953,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_daa6b8f2481040acb873f24cfbfedc9e", + "layout": "IPY_MODEL_953f4c82aabd472c9e8dfebdf70939d8", "max": 200.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_3f81fed11b61470bac6f5d0b3b537a4f", + "style": "IPY_MODEL_86445ca79c764836a406520c67b4b945", "tabbable": null, "tooltip": null, "value": 200.0 } }, - "7e84cf312cfa4d80a5107dcdb0a45949": { + "7b9c39c715b849dbb886ceaeb96e5c35": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4951,33 +4978,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_550c28ddb9cf43c3b62b1a0b54f7bd12", + "layout": "IPY_MODEL_7fb3eb018b9d446294207573ca64cda2", "placeholder": "​", - "style": "IPY_MODEL_81f7fdaaa60c4cc5b1e29545f2666e55", + "style": "IPY_MODEL_ec3f09ac595d4dadbd0cf34793d57087", "tabbable": null, "tooltip": null, "value": "100%" } }, - "81f7fdaaa60c4cc5b1e29545f2666e55": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "a1d59c28e7064efc92b1e3caf26f9346": { + "7fb3eb018b9d446294207573ca64cda2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5030,7 +5039,23 @@ "width": null } }, - "a4073ffc99c94224857f26d6f4931b59": { + "86445ca79c764836a406520c67b4b945": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "953f4c82aabd472c9e8dfebdf70939d8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5083,33 +5108,30 @@ "width": null } }, - "a6c8cc603a414e80a6ba376c29f15b21": { + "9ffc7a8014b64edfad1dd643172601d1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_a4073ffc99c94224857f26d6f4931b59", - "max": 200.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_4bbbb6bbcc9648459b5d261cb8ab6826", + "layout": "IPY_MODEL_021a50164b8c491ebb069bd57b11ce1a", + "placeholder": "​", + "style": "IPY_MODEL_da74a2af2dfa4378a23a6009ae2f264c", "tabbable": null, "tooltip": null, - "value": 200.0 + "value": " 200/200 [00:00<00:00, 785.38it/s]" } }, - "ad306c43da45461c99570f45d29010bd": { + "a185cb088b4a4b50933699f586275482": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5162,7 +5184,31 @@ "width": null } }, - "ae6c7383e12f421aaeac59c5f8586ff1": { + "a5793cf283c046f188f735beef4577a5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_7b9c39c715b849dbb886ceaeb96e5c35", + "IPY_MODEL_5664879b48124f5cac1e0a8c43742995", + "IPY_MODEL_9ffc7a8014b64edfad1dd643172601d1" + ], + "layout": "IPY_MODEL_313b234230ce4ce4850b3fa6a5e1b1ee", + "tabbable": null, + "tooltip": null + } + }, + "b93c4b8b97f34f0b93a2d334e5065e1b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -5180,7 +5226,7 @@ "text_color": null } }, - "b54c1a0ec3ea4129adde7e57857e1a0e": { + "da74a2af2dfa4378a23a6009ae2f264c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -5198,7 +5244,7 @@ "text_color": null } }, - "c362069cd48048d7ac53b007e87189cb": { + "da820a1ccd2b42d4a8c12ea0328d1169": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5251,126 +5297,80 @@ "width": null } }, - "daa6b8f2481040acb873f24cfbfedc9e": { - "model_module": "@jupyter-widgets/base", + "da8ad4a548a8409389fab7ddc0e601bc": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "db046a62f4e34aa594499d33fa68145f": { + "dfac24cbd04d4a6a9c6a2f3d7e34c87e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_c362069cd48048d7ac53b007e87189cb", - "placeholder": "​", - "style": "IPY_MODEL_ae6c7383e12f421aaeac59c5f8586ff1", - "tabbable": null, - "tooltip": null, - "value": "100%" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "dc9edc5341cb452cb27aada834ac562d": { + "e53b81d02870488ca1d70faf1534371f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_ad306c43da45461c99570f45d29010bd", - "placeholder": "​", - "style": "IPY_MODEL_62793e1d0aa84395bb5ab3f9ff86c9b5", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_2cb88e5e7d0f4849b336950480e87a06", + "IPY_MODEL_733b0d114c6e48e6af9ced8acfb5bf3a", + "IPY_MODEL_6529bc3e5e35424f967dab0385030a5c" + ], + "layout": "IPY_MODEL_a185cb088b4a4b50933699f586275482", "tabbable": null, - "tooltip": null, - "value": " 200/200 [00:00<00:00, 716.02it/s]" + "tooltip": null } }, - "df91c80300534ab59fe080ab28475f7a": { + "ec3f09ac595d4dadbd0cf34793d57087": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_37eeb5a0817c455a8d0efe07a3d6bd44", - "placeholder": "​", - "style": "IPY_MODEL_b54c1a0ec3ea4129adde7e57857e1a0e", - "tabbable": null, - "tooltip": null, - "value": " 200/200 [00:00<00:00, 771.41it/s]" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } } }, diff --git a/master/.doctrees/nbsphinx/tutorials/dataset_health.ipynb b/master/.doctrees/nbsphinx/tutorials/dataset_health.ipynb index a14eec2f4..e932968f7 100644 --- a/master/.doctrees/nbsphinx/tutorials/dataset_health.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/dataset_health.ipynb @@ -70,10 +70,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:00.542736Z", - "iopub.status.busy": "2024-09-05T19:38:00.542299Z", - "iopub.status.idle": "2024-09-05T19:38:01.779270Z", - "shell.execute_reply": "2024-09-05T19:38:01.778627Z" + "iopub.execute_input": "2024-09-06T19:37:53.970574Z", + "iopub.status.busy": "2024-09-06T19:37:53.970388Z", + "iopub.status.idle": "2024-09-06T19:37:55.134808Z", + "shell.execute_reply": "2024-09-06T19:37:55.134157Z" }, "nbsphinx": "hidden" }, @@ -85,7 +85,7 @@ "dependencies = [\"cleanlab\", \"requests\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -110,10 +110,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:01.782074Z", - "iopub.status.busy": "2024-09-05T19:38:01.781768Z", - "iopub.status.idle": "2024-09-05T19:38:01.784644Z", - "shell.execute_reply": "2024-09-05T19:38:01.784156Z" + "iopub.execute_input": "2024-09-06T19:37:55.137505Z", + "iopub.status.busy": "2024-09-06T19:37:55.137230Z", + "iopub.status.idle": "2024-09-06T19:37:55.140659Z", + "shell.execute_reply": "2024-09-06T19:37:55.140221Z" }, "id": "_UvI80l42iyi" }, @@ -203,10 +203,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:01.786827Z", - "iopub.status.busy": "2024-09-05T19:38:01.786518Z", - "iopub.status.idle": "2024-09-05T19:38:01.798674Z", - "shell.execute_reply": "2024-09-05T19:38:01.798101Z" + "iopub.execute_input": "2024-09-06T19:37:55.142857Z", + "iopub.status.busy": "2024-09-06T19:37:55.142554Z", + "iopub.status.idle": "2024-09-06T19:37:55.154394Z", + "shell.execute_reply": "2024-09-06T19:37:55.153913Z" }, "nbsphinx": "hidden" }, @@ -285,10 +285,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:01.800785Z", - "iopub.status.busy": "2024-09-05T19:38:01.800454Z", - "iopub.status.idle": "2024-09-05T19:38:06.755445Z", - "shell.execute_reply": "2024-09-05T19:38:06.754955Z" + "iopub.execute_input": "2024-09-06T19:37:55.156367Z", + "iopub.status.busy": "2024-09-06T19:37:55.156193Z", + "iopub.status.idle": "2024-09-06T19:38:03.213180Z", + "shell.execute_reply": "2024-09-06T19:38:03.212490Z" }, "id": "dhTHOg8Pyv5G" }, diff --git a/master/.doctrees/nbsphinx/tutorials/faq.ipynb b/master/.doctrees/nbsphinx/tutorials/faq.ipynb index c5223bdbd..cec52a458 100644 --- a/master/.doctrees/nbsphinx/tutorials/faq.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/faq.ipynb @@ -18,10 +18,10 @@ "id": "2a4efdde", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:09.258191Z", - "iopub.status.busy": "2024-09-05T19:38:09.258029Z", - "iopub.status.idle": "2024-09-05T19:38:10.419368Z", - "shell.execute_reply": "2024-09-05T19:38:10.418813Z" + "iopub.execute_input": "2024-09-06T19:38:05.442254Z", + "iopub.status.busy": "2024-09-06T19:38:05.441754Z", + "iopub.status.idle": "2024-09-06T19:38:06.608058Z", + "shell.execute_reply": "2024-09-06T19:38:06.607439Z" }, "nbsphinx": "hidden" }, @@ -137,10 +137,10 @@ "id": "239d5ee7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:10.422097Z", - "iopub.status.busy": "2024-09-05T19:38:10.421633Z", - "iopub.status.idle": "2024-09-05T19:38:10.425143Z", - "shell.execute_reply": "2024-09-05T19:38:10.424685Z" + "iopub.execute_input": "2024-09-06T19:38:06.610846Z", + "iopub.status.busy": "2024-09-06T19:38:06.610375Z", + "iopub.status.idle": "2024-09-06T19:38:06.613802Z", + "shell.execute_reply": "2024-09-06T19:38:06.613322Z" } }, "outputs": [], @@ -176,10 +176,10 @@ "id": "28b324aa", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:10.427337Z", - "iopub.status.busy": "2024-09-05T19:38:10.427003Z", - "iopub.status.idle": "2024-09-05T19:38:13.858204Z", - "shell.execute_reply": "2024-09-05T19:38:13.857536Z" + "iopub.execute_input": "2024-09-06T19:38:06.615798Z", + "iopub.status.busy": "2024-09-06T19:38:06.615518Z", + "iopub.status.idle": "2024-09-06T19:38:09.981363Z", + "shell.execute_reply": "2024-09-06T19:38:09.980664Z" } }, "outputs": [], @@ -202,10 +202,10 @@ "id": "28b324ab", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.861501Z", - "iopub.status.busy": "2024-09-05T19:38:13.860747Z", - "iopub.status.idle": "2024-09-05T19:38:13.908095Z", - "shell.execute_reply": "2024-09-05T19:38:13.907257Z" + "iopub.execute_input": "2024-09-06T19:38:09.984620Z", + "iopub.status.busy": "2024-09-06T19:38:09.983724Z", + "iopub.status.idle": "2024-09-06T19:38:10.027299Z", + "shell.execute_reply": "2024-09-06T19:38:10.026694Z" } }, "outputs": [], @@ -228,10 +228,10 @@ "id": "90c10e18", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.911086Z", - "iopub.status.busy": "2024-09-05T19:38:13.910659Z", - "iopub.status.idle": "2024-09-05T19:38:13.954360Z", - "shell.execute_reply": "2024-09-05T19:38:13.953711Z" + "iopub.execute_input": "2024-09-06T19:38:10.030074Z", + "iopub.status.busy": "2024-09-06T19:38:10.029673Z", + "iopub.status.idle": "2024-09-06T19:38:10.069413Z", + "shell.execute_reply": "2024-09-06T19:38:10.068633Z" } }, "outputs": [], @@ -253,10 +253,10 @@ "id": "88839519", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.957448Z", - "iopub.status.busy": "2024-09-05T19:38:13.956977Z", - "iopub.status.idle": "2024-09-05T19:38:13.960154Z", - "shell.execute_reply": "2024-09-05T19:38:13.959671Z" + "iopub.execute_input": "2024-09-06T19:38:10.072131Z", + "iopub.status.busy": "2024-09-06T19:38:10.071875Z", + "iopub.status.idle": "2024-09-06T19:38:10.075127Z", + "shell.execute_reply": "2024-09-06T19:38:10.074582Z" } }, "outputs": [], @@ -278,10 +278,10 @@ "id": "558490c2", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.962224Z", - "iopub.status.busy": "2024-09-05T19:38:13.961891Z", - "iopub.status.idle": "2024-09-05T19:38:13.964636Z", - "shell.execute_reply": "2024-09-05T19:38:13.964076Z" + "iopub.execute_input": "2024-09-06T19:38:10.077352Z", + "iopub.status.busy": "2024-09-06T19:38:10.077011Z", + "iopub.status.idle": "2024-09-06T19:38:10.079576Z", + "shell.execute_reply": "2024-09-06T19:38:10.079132Z" } }, "outputs": [], @@ -363,10 +363,10 @@ "id": "41714b51", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.966749Z", - "iopub.status.busy": "2024-09-05T19:38:13.966438Z", - "iopub.status.idle": "2024-09-05T19:38:13.992059Z", - "shell.execute_reply": "2024-09-05T19:38:13.991451Z" + "iopub.execute_input": "2024-09-06T19:38:10.081910Z", + "iopub.status.busy": "2024-09-06T19:38:10.081719Z", + "iopub.status.idle": "2024-09-06T19:38:10.109741Z", + "shell.execute_reply": "2024-09-06T19:38:10.109183Z" } }, "outputs": [ @@ -380,7 +380,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5e9f1ab6ba2a4e2299cdd03dc9abc834", + "model_id": "10e11ec38b13425280381ff5281c4450", "version_major": 2, "version_minor": 0 }, @@ -394,7 +394,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c8b20d5d9286458984753646a34d3bf1", + "model_id": "7e2d5adb59434e2081db18c696100263", "version_major": 2, "version_minor": 0 }, @@ -452,10 +452,10 @@ "id": "20476c70", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.998276Z", - "iopub.status.busy": "2024-09-05T19:38:13.997819Z", - "iopub.status.idle": "2024-09-05T19:38:14.004565Z", - "shell.execute_reply": "2024-09-05T19:38:14.004112Z" + "iopub.execute_input": "2024-09-06T19:38:10.115104Z", + "iopub.status.busy": "2024-09-06T19:38:10.114762Z", + "iopub.status.idle": "2024-09-06T19:38:10.121297Z", + "shell.execute_reply": "2024-09-06T19:38:10.120726Z" }, "nbsphinx": "hidden" }, @@ -486,10 +486,10 @@ "id": "6983cdad", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.006609Z", - "iopub.status.busy": "2024-09-05T19:38:14.006302Z", - "iopub.status.idle": "2024-09-05T19:38:14.009865Z", - "shell.execute_reply": "2024-09-05T19:38:14.009315Z" + "iopub.execute_input": "2024-09-06T19:38:10.123497Z", + "iopub.status.busy": "2024-09-06T19:38:10.123043Z", + "iopub.status.idle": "2024-09-06T19:38:10.126503Z", + "shell.execute_reply": "2024-09-06T19:38:10.126056Z" }, "nbsphinx": "hidden" }, @@ -512,10 +512,10 @@ "id": "9092b8a0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.011915Z", - "iopub.status.busy": "2024-09-05T19:38:14.011613Z", - "iopub.status.idle": "2024-09-05T19:38:14.017930Z", - "shell.execute_reply": "2024-09-05T19:38:14.017490Z" + "iopub.execute_input": "2024-09-06T19:38:10.128505Z", + "iopub.status.busy": "2024-09-06T19:38:10.128204Z", + "iopub.status.idle": "2024-09-06T19:38:10.134549Z", + "shell.execute_reply": "2024-09-06T19:38:10.134003Z" } }, "outputs": [], @@ -565,10 +565,10 @@ "id": "b0a01109", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.019956Z", - "iopub.status.busy": "2024-09-05T19:38:14.019601Z", - "iopub.status.idle": "2024-09-05T19:38:14.064732Z", - "shell.execute_reply": "2024-09-05T19:38:14.063970Z" + "iopub.execute_input": "2024-09-06T19:38:10.136656Z", + "iopub.status.busy": "2024-09-06T19:38:10.136338Z", + "iopub.status.idle": "2024-09-06T19:38:10.179181Z", + "shell.execute_reply": "2024-09-06T19:38:10.178556Z" } }, "outputs": [], @@ -585,10 +585,10 @@ "id": "8b1da032", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.067600Z", - "iopub.status.busy": "2024-09-05T19:38:14.067120Z", - "iopub.status.idle": "2024-09-05T19:38:14.111610Z", - "shell.execute_reply": "2024-09-05T19:38:14.110852Z" + "iopub.execute_input": "2024-09-06T19:38:10.181945Z", + "iopub.status.busy": "2024-09-06T19:38:10.181555Z", + "iopub.status.idle": "2024-09-06T19:38:10.218200Z", + "shell.execute_reply": "2024-09-06T19:38:10.217453Z" }, "nbsphinx": "hidden" }, @@ -667,10 +667,10 @@ "id": "4c9e9030", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.114596Z", - "iopub.status.busy": "2024-09-05T19:38:14.114229Z", - "iopub.status.idle": "2024-09-05T19:38:14.248717Z", - "shell.execute_reply": "2024-09-05T19:38:14.248086Z" + "iopub.execute_input": "2024-09-06T19:38:10.220958Z", + "iopub.status.busy": "2024-09-06T19:38:10.220569Z", + "iopub.status.idle": "2024-09-06T19:38:10.349381Z", + "shell.execute_reply": "2024-09-06T19:38:10.348725Z" } }, "outputs": [ @@ -737,10 +737,10 @@ "id": "8751619e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.251515Z", - "iopub.status.busy": "2024-09-05T19:38:14.250905Z", - "iopub.status.idle": "2024-09-05T19:38:17.282534Z", - "shell.execute_reply": "2024-09-05T19:38:17.281859Z" + "iopub.execute_input": "2024-09-06T19:38:10.352202Z", + "iopub.status.busy": "2024-09-06T19:38:10.351437Z", + "iopub.status.idle": "2024-09-06T19:38:13.390257Z", + "shell.execute_reply": "2024-09-06T19:38:13.389586Z" } }, "outputs": [ @@ -826,10 +826,10 @@ "id": "623df36d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.284960Z", - "iopub.status.busy": "2024-09-05T19:38:17.284770Z", - "iopub.status.idle": "2024-09-05T19:38:17.345859Z", - "shell.execute_reply": "2024-09-05T19:38:17.345257Z" + "iopub.execute_input": "2024-09-06T19:38:13.392707Z", + "iopub.status.busy": "2024-09-06T19:38:13.392511Z", + "iopub.status.idle": "2024-09-06T19:38:13.450827Z", + "shell.execute_reply": "2024-09-06T19:38:13.450261Z" } }, "outputs": [ @@ -1285,10 +1285,10 @@ "id": "af3052ac", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.348231Z", - "iopub.status.busy": "2024-09-05T19:38:17.347702Z", - "iopub.status.idle": "2024-09-05T19:38:17.389681Z", - "shell.execute_reply": "2024-09-05T19:38:17.389132Z" + "iopub.execute_input": "2024-09-06T19:38:13.453108Z", + "iopub.status.busy": "2024-09-06T19:38:13.452688Z", + "iopub.status.idle": "2024-09-06T19:38:13.493414Z", + "shell.execute_reply": "2024-09-06T19:38:13.492941Z" } }, "outputs": [ @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "5ac521f4", + "id": "368f0547", "metadata": {}, "source": [ "### How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?" @@ -1327,7 +1327,7 @@ }, { "cell_type": "markdown", - "id": "eebcc205", + "id": "dc65d1a9", "metadata": {}, "source": [ "The instructions for specifying pre-computed data slices/clusters when detecting underperforming groups in a dataset are now covered in detail in the Datalab workflows tutorial.\n", @@ -1338,7 +1338,7 @@ }, { "cell_type": "markdown", - "id": "7a6303e8", + "id": "e31bf904", "metadata": {}, "source": [ "### How to handle near-duplicate data identified by Datalab?\n", @@ -1349,13 +1349,13 @@ { "cell_type": "code", "execution_count": 18, - "id": "cc272ead", + "id": "0365a86d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.392137Z", - "iopub.status.busy": "2024-09-05T19:38:17.391761Z", - "iopub.status.idle": "2024-09-05T19:38:17.399373Z", - "shell.execute_reply": "2024-09-05T19:38:17.398899Z" + "iopub.execute_input": "2024-09-06T19:38:13.495546Z", + "iopub.status.busy": "2024-09-06T19:38:13.495269Z", + "iopub.status.idle": "2024-09-06T19:38:13.502952Z", + "shell.execute_reply": "2024-09-06T19:38:13.502358Z" } }, "outputs": [], @@ -1457,7 +1457,7 @@ }, { "cell_type": "markdown", - "id": "02a9d389", + "id": "1c944acb", "metadata": {}, "source": [ "The functions above collect sets of near-duplicate examples. Within each\n", @@ -1472,13 +1472,13 @@ { "cell_type": "code", "execution_count": 19, - "id": "c59e687d", + "id": "c713e4cb", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.401606Z", - "iopub.status.busy": "2024-09-05T19:38:17.401261Z", - "iopub.status.idle": "2024-09-05T19:38:17.420424Z", - "shell.execute_reply": "2024-09-05T19:38:17.419931Z" + "iopub.execute_input": "2024-09-06T19:38:13.504946Z", + "iopub.status.busy": "2024-09-06T19:38:13.504608Z", + "iopub.status.idle": "2024-09-06T19:38:13.523104Z", + "shell.execute_reply": "2024-09-06T19:38:13.522534Z" } }, "outputs": [ @@ -1521,13 +1521,13 @@ { "cell_type": "code", "execution_count": 20, - "id": "01304147", + "id": "59184bfc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.422733Z", - "iopub.status.busy": "2024-09-05T19:38:17.422383Z", - "iopub.status.idle": "2024-09-05T19:38:17.425820Z", - "shell.execute_reply": "2024-09-05T19:38:17.425263Z" + "iopub.execute_input": "2024-09-06T19:38:13.525068Z", + "iopub.status.busy": "2024-09-06T19:38:13.524743Z", + "iopub.status.idle": "2024-09-06T19:38:13.528122Z", + "shell.execute_reply": "2024-09-06T19:38:13.527552Z" } }, "outputs": [ @@ -1622,7 +1622,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "1d1157c21ea1455bb4eba32221cfd80e": { + "0a20db80d8ee4c558ba192d544a0f48a": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1675,7 +1675,7 @@ "width": null } }, - "2bb52b5e34e0423ea8ebfa5fa2197991": { + "0e1e83d9b67447b1a76b3a2c668a8439": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1728,7 +1728,49 @@ "width": null } }, - "2ca77e6e6a914a409e7751bbd43cd433": { + "0ea8c549fffe4418b122c5d1daacdcf9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "10e11ec38b13425280381ff5281c4450": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_98a30ff8d08f40f5a59fa3959a1bfd7a", + "IPY_MODEL_9e361a1c4f7d49d28575030ed31684b4", + "IPY_MODEL_5d93e4fbfc844d82994983ca2900ac04" + ], + "layout": "IPY_MODEL_4c9d550f7159424fb6452da47b5cb51f", + "tabbable": null, + "tooltip": null + } + }, + "1989c2b222ef4983ba1d80fd96d80f9d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1781,33 +1823,23 @@ "width": null } }, - "2e05d5f980a44775b5be3782d3eb29a8": { + "278fa17d981b49c5a5afac9215c11437": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_519341eb823746dc9a9b5c92d467d3d1", - "max": 50.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_ae0adc12747d4f129ee5677a88c40300", - "tabbable": null, - "tooltip": null, - "value": 50.0 + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "519341eb823746dc9a9b5c92d467d3d1": { + "4c9d550f7159424fb6452da47b5cb51f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1860,7 +1892,30 @@ "width": null } }, - "58f64c5fbd2b49039759f382c08a00f5": { + "5d93e4fbfc844d82994983ca2900ac04": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_0a20db80d8ee4c558ba192d544a0f48a", + "placeholder": "​", + "style": "IPY_MODEL_85eb048e0015452a98d2585ecd3acea6", + "tabbable": null, + "tooltip": null, + "value": " 10000/? [00:00<00:00, 908211.86it/s]" + } + }, + "62148dc5598f487787910111c96b2850": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1913,25 +1968,7 @@ "width": null } }, - "5a2ddf974a63406796b88696f6a9e322": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "5d6f15bd3523470e8f8a7049768802e2": { + "663eab6313474ab4b43a56ac15375332": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1946,15 +1983,68 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_fbc3a6811fa1407b9fb04a0f39c1e560", + "layout": "IPY_MODEL_0e1e83d9b67447b1a76b3a2c668a8439", "placeholder": "​", - "style": "IPY_MODEL_5a2ddf974a63406796b88696f6a9e322", + "style": "IPY_MODEL_c8b6ee68eda04b79b9d7e8ba44708601", "tabbable": null, "tooltip": null, - "value": " 10000/? [00:00<00:00, 1587308.51it/s]" + "value": "number of examples processed for checking labels: " } }, - "5e9f1ab6ba2a4e2299cdd03dc9abc834": { + "71bf8e249c8e494a8293a1368b4cde75": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "7e2d5adb59434e2081db18c696100263": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -1969,16 +2059,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_89998dc91f404fc1ae7b7f0af753e147", - "IPY_MODEL_2e05d5f980a44775b5be3782d3eb29a8", - "IPY_MODEL_af016b9649554c3aa9157c6db78c9c93" + "IPY_MODEL_663eab6313474ab4b43a56ac15375332", + "IPY_MODEL_cb19cecdebc048139ef9e5b0697091e8", + "IPY_MODEL_b09565a1c786456187dacb880907b06f" ], - "layout": "IPY_MODEL_e518b7c1bace4a43bdf2824bb3ce3af4", + "layout": "IPY_MODEL_62148dc5598f487787910111c96b2850", "tabbable": null, "tooltip": null } }, - "7a097385a6104b0280db3ea1bd2b3b67": { + "85eb048e0015452a98d2585ecd3acea6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1996,30 +2086,7 @@ "text_color": null } }, - "80f0f3a7d63640f88804ff3d3f2dc1e3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_58f64c5fbd2b49039759f382c08a00f5", - "placeholder": "​", - "style": "IPY_MODEL_7a097385a6104b0280db3ea1bd2b3b67", - "tabbable": null, - "tooltip": null, - "value": "number of examples processed for checking labels: " - } - }, - "85c3014ae8d449b685c081ae4fa6d4f6": { + "8a29c209506d4b1f809b0eee618845ff": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2037,7 +2104,60 @@ "text_color": null } }, - "89998dc91f404fc1ae7b7f0af753e147": { + "8a7564586c364ea6ab0b8036f15d75de": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "98a30ff8d08f40f5a59fa3959a1bfd7a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2052,65 +2172,41 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_2bb52b5e34e0423ea8ebfa5fa2197991", + "layout": "IPY_MODEL_cbbdcb4211b04decb44b6be6dae0e74f", "placeholder": "​", - "style": "IPY_MODEL_85c3014ae8d449b685c081ae4fa6d4f6", + "style": "IPY_MODEL_0ea8c549fffe4418b122c5d1daacdcf9", "tabbable": null, "tooltip": null, "value": "number of examples processed for estimating thresholds: " } }, - "96c604f720804752bdd7e004c2d5b976": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "a626f902bf2b447aa9efceb999cecea2": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "ae0adc12747d4f129ee5677a88c40300": { + "9e361a1c4f7d49d28575030ed31684b4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_8a7564586c364ea6ab0b8036f15d75de", + "max": 50.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_278fa17d981b49c5a5afac9215c11437", + "tabbable": null, + "tooltip": null, + "value": 50.0 } }, - "af016b9649554c3aa9157c6db78c9c93": { + "b09565a1c786456187dacb880907b06f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2125,39 +2221,33 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1d1157c21ea1455bb4eba32221cfd80e", + "layout": "IPY_MODEL_71bf8e249c8e494a8293a1368b4cde75", "placeholder": "​", - "style": "IPY_MODEL_96c604f720804752bdd7e004c2d5b976", + "style": "IPY_MODEL_8a29c209506d4b1f809b0eee618845ff", "tabbable": null, "tooltip": null, - "value": " 10000/? [00:00<00:00, 891911.71it/s]" + "value": " 10000/? [00:00<00:00, 1197722.38it/s]" } }, - "c8b20d5d9286458984753646a34d3bf1": { + "c8b6ee68eda04b79b9d7e8ba44708601": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_80f0f3a7d63640f88804ff3d3f2dc1e3", - "IPY_MODEL_d492675a8a4b4225ab936898d59675f6", - "IPY_MODEL_5d6f15bd3523470e8f8a7049768802e2" - ], - "layout": "IPY_MODEL_2ca77e6e6a914a409e7751bbd43cd433", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "d492675a8a4b4225ab936898d59675f6": { + "cb19cecdebc048139ef9e5b0697091e8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -2173,17 +2263,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_de835bb464834a46b37dd59d97b91150", + "layout": "IPY_MODEL_1989c2b222ef4983ba1d80fd96d80f9d", "max": 50.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_a626f902bf2b447aa9efceb999cecea2", + "style": "IPY_MODEL_cd96842c5f86404599e6a57c4439dccf", "tabbable": null, "tooltip": null, "value": 50.0 } }, - "de835bb464834a46b37dd59d97b91150": { + "cbbdcb4211b04decb44b6be6dae0e74f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2236,110 +2326,20 @@ "width": null } }, - "e518b7c1bace4a43bdf2824bb3ce3af4": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "2.0.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "fbc3a6811fa1407b9fb04a0f39c1e560": { - "model_module": "@jupyter-widgets/base", + "cd96842c5f86404599e6a57c4439dccf": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } } }, diff --git a/master/.doctrees/nbsphinx/tutorials/improving_ml_performance.ipynb b/master/.doctrees/nbsphinx/tutorials/improving_ml_performance.ipynb index 355de44f6..0126898fa 100644 --- a/master/.doctrees/nbsphinx/tutorials/improving_ml_performance.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/improving_ml_performance.ipynb @@ -60,10 +60,10 @@ "id": "2d638465", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:20.938341Z", - "iopub.status.busy": "2024-09-05T19:38:20.938181Z", - "iopub.status.idle": "2024-09-05T19:38:22.134719Z", - "shell.execute_reply": "2024-09-05T19:38:22.134142Z" + "iopub.execute_input": "2024-09-06T19:38:17.966921Z", + "iopub.status.busy": "2024-09-06T19:38:17.966743Z", + "iopub.status.idle": "2024-09-06T19:38:19.153643Z", + "shell.execute_reply": "2024-09-06T19:38:19.153020Z" }, "nbsphinx": "hidden" }, @@ -73,7 +73,7 @@ "dependencies = [\"cleanlab\", \"xgboost\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -99,10 +99,10 @@ "id": "b0bbf715-47c6-44ea-b15e-89800e62ee04", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.137472Z", - "iopub.status.busy": "2024-09-05T19:38:22.137010Z", - "iopub.status.idle": "2024-09-05T19:38:22.141005Z", - "shell.execute_reply": "2024-09-05T19:38:22.140442Z" + "iopub.execute_input": "2024-09-06T19:38:19.156468Z", + "iopub.status.busy": "2024-09-06T19:38:19.155927Z", + "iopub.status.idle": "2024-09-06T19:38:19.159820Z", + "shell.execute_reply": "2024-09-06T19:38:19.159280Z" } }, "outputs": [], @@ -140,10 +140,10 @@ "id": "c58f8015-d051-411c-9e03-5659cf3ad956", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.143101Z", - "iopub.status.busy": "2024-09-05T19:38:22.142800Z", - "iopub.status.idle": "2024-09-05T19:38:22.317437Z", - "shell.execute_reply": "2024-09-05T19:38:22.316874Z" + "iopub.execute_input": "2024-09-06T19:38:19.161985Z", + "iopub.status.busy": "2024-09-06T19:38:19.161628Z", + "iopub.status.idle": "2024-09-06T19:38:19.848074Z", + "shell.execute_reply": "2024-09-06T19:38:19.847540Z" } }, "outputs": [ @@ -273,10 +273,10 @@ "id": "1b5f50e6-d125-4e61-b63e-4004f0c9099a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.319775Z", - "iopub.status.busy": "2024-09-05T19:38:22.319343Z", - "iopub.status.idle": "2024-09-05T19:38:22.325394Z", - "shell.execute_reply": "2024-09-05T19:38:22.324864Z" + "iopub.execute_input": "2024-09-06T19:38:19.850305Z", + "iopub.status.busy": "2024-09-06T19:38:19.849961Z", + "iopub.status.idle": "2024-09-06T19:38:19.855710Z", + "shell.execute_reply": "2024-09-06T19:38:19.855268Z" } }, "outputs": [], @@ -312,10 +312,10 @@ "id": "a36c21e9-1c32-4df9-bd87-fffeb8c2175f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.327562Z", - "iopub.status.busy": "2024-09-05T19:38:22.327255Z", - "iopub.status.idle": "2024-09-05T19:38:22.334139Z", - "shell.execute_reply": "2024-09-05T19:38:22.333587Z" + "iopub.execute_input": "2024-09-06T19:38:19.857664Z", + "iopub.status.busy": "2024-09-06T19:38:19.857483Z", + "iopub.status.idle": "2024-09-06T19:38:19.864510Z", + "shell.execute_reply": "2024-09-06T19:38:19.863928Z" } }, "outputs": [ @@ -418,10 +418,10 @@ "id": "5f856a3a-8aae-4836-b146-9ab68d8d1c7a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.336134Z", - "iopub.status.busy": "2024-09-05T19:38:22.335809Z", - "iopub.status.idle": "2024-09-05T19:38:22.340537Z", - "shell.execute_reply": "2024-09-05T19:38:22.339975Z" + "iopub.execute_input": "2024-09-06T19:38:19.866738Z", + "iopub.status.busy": "2024-09-06T19:38:19.866419Z", + "iopub.status.idle": "2024-09-06T19:38:19.871181Z", + "shell.execute_reply": "2024-09-06T19:38:19.870718Z" } }, "outputs": [], @@ -449,10 +449,10 @@ "id": "46275634-da56-4e58-9061-8108be2b585d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.342582Z", - "iopub.status.busy": "2024-09-05T19:38:22.342279Z", - "iopub.status.idle": "2024-09-05T19:38:22.348079Z", - "shell.execute_reply": "2024-09-05T19:38:22.347521Z" + "iopub.execute_input": "2024-09-06T19:38:19.873167Z", + "iopub.status.busy": "2024-09-06T19:38:19.872989Z", + "iopub.status.idle": "2024-09-06T19:38:19.879315Z", + "shell.execute_reply": "2024-09-06T19:38:19.878873Z" } }, "outputs": [], @@ -488,10 +488,10 @@ "id": "769c4c5e-a7ff-4e02-bee5-2b2e676aec14", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.350256Z", - "iopub.status.busy": "2024-09-05T19:38:22.349941Z", - "iopub.status.idle": "2024-09-05T19:38:22.354060Z", - "shell.execute_reply": "2024-09-05T19:38:22.353506Z" + "iopub.execute_input": "2024-09-06T19:38:19.881299Z", + "iopub.status.busy": "2024-09-06T19:38:19.881109Z", + "iopub.status.idle": "2024-09-06T19:38:19.885448Z", + "shell.execute_reply": "2024-09-06T19:38:19.884866Z" } }, "outputs": [], @@ -506,10 +506,10 @@ "id": "7ac47c3d-9e87-45b7-9064-bfa45578872e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.356038Z", - "iopub.status.busy": "2024-09-05T19:38:22.355647Z", - "iopub.status.idle": "2024-09-05T19:38:22.423064Z", - "shell.execute_reply": "2024-09-05T19:38:22.422472Z" + "iopub.execute_input": "2024-09-06T19:38:19.887541Z", + "iopub.status.busy": "2024-09-06T19:38:19.887226Z", + "iopub.status.idle": "2024-09-06T19:38:19.952333Z", + "shell.execute_reply": "2024-09-06T19:38:19.951659Z" } }, "outputs": [ @@ -609,10 +609,10 @@ "id": "6cef169e-d15b-4d18-9cb7-8ea589557e6b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.426072Z", - "iopub.status.busy": "2024-09-05T19:38:22.425579Z", - "iopub.status.idle": "2024-09-05T19:38:22.436851Z", - "shell.execute_reply": "2024-09-05T19:38:22.436355Z" + "iopub.execute_input": "2024-09-06T19:38:19.955055Z", + "iopub.status.busy": "2024-09-06T19:38:19.954571Z", + "iopub.status.idle": "2024-09-06T19:38:19.965639Z", + "shell.execute_reply": "2024-09-06T19:38:19.965092Z" } }, "outputs": [ @@ -724,10 +724,10 @@ "id": "b68e0418-86cf-431f-9107-2dd0a310ca42", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.439378Z", - "iopub.status.busy": "2024-09-05T19:38:22.438783Z", - "iopub.status.idle": "2024-09-05T19:38:22.460540Z", - "shell.execute_reply": "2024-09-05T19:38:22.459904Z" + "iopub.execute_input": "2024-09-06T19:38:19.968612Z", + "iopub.status.busy": "2024-09-06T19:38:19.968081Z", + "iopub.status.idle": "2024-09-06T19:38:19.989523Z", + "shell.execute_reply": "2024-09-06T19:38:19.988990Z" } }, "outputs": [ @@ -931,10 +931,10 @@ "id": "0e9bd131-429f-48af-b4fc-ed8b907950b9", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.463026Z", - "iopub.status.busy": "2024-09-05T19:38:22.462648Z", - "iopub.status.idle": "2024-09-05T19:38:22.466619Z", - "shell.execute_reply": "2024-09-05T19:38:22.466139Z" + "iopub.execute_input": "2024-09-06T19:38:19.992484Z", + "iopub.status.busy": "2024-09-06T19:38:19.991953Z", + "iopub.status.idle": "2024-09-06T19:38:19.996496Z", + "shell.execute_reply": "2024-09-06T19:38:19.995963Z" } }, "outputs": [ @@ -968,10 +968,10 @@ "id": "e72320ec-7792-4347-b2fb-630f2519127c", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.468979Z", - "iopub.status.busy": "2024-09-05T19:38:22.468612Z", - "iopub.status.idle": "2024-09-05T19:38:22.472717Z", - "shell.execute_reply": "2024-09-05T19:38:22.472228Z" + "iopub.execute_input": "2024-09-06T19:38:20.000004Z", + "iopub.status.busy": "2024-09-06T19:38:19.999084Z", + "iopub.status.idle": "2024-09-06T19:38:20.005225Z", + "shell.execute_reply": "2024-09-06T19:38:20.004698Z" } }, "outputs": [ @@ -1005,10 +1005,10 @@ "id": "8520ba4a-3ad6-408a-b377-3f47c32d745a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.476188Z", - "iopub.status.busy": "2024-09-05T19:38:22.475241Z", - "iopub.status.idle": "2024-09-05T19:38:22.486948Z", - "shell.execute_reply": "2024-09-05T19:38:22.486537Z" + "iopub.execute_input": "2024-09-06T19:38:20.008748Z", + "iopub.status.busy": "2024-09-06T19:38:20.007824Z", + "iopub.status.idle": "2024-09-06T19:38:20.018446Z", + "shell.execute_reply": "2024-09-06T19:38:20.018010Z" } }, "outputs": [ @@ -1205,10 +1205,10 @@ "id": "3c002665-c48b-4f04-91f7-ad112a49efc7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.489195Z", - "iopub.status.busy": "2024-09-05T19:38:22.488861Z", - "iopub.status.idle": "2024-09-05T19:38:22.493151Z", - "shell.execute_reply": "2024-09-05T19:38:22.492710Z" + "iopub.execute_input": "2024-09-06T19:38:20.020571Z", + "iopub.status.busy": "2024-09-06T19:38:20.020204Z", + "iopub.status.idle": "2024-09-06T19:38:20.024666Z", + "shell.execute_reply": "2024-09-06T19:38:20.024096Z" } }, "outputs": [], @@ -1234,10 +1234,10 @@ "id": "36319f39-f563-4f63-913f-821373180350", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.495336Z", - "iopub.status.busy": "2024-09-05T19:38:22.495008Z", - "iopub.status.idle": "2024-09-05T19:38:22.606998Z", - "shell.execute_reply": "2024-09-05T19:38:22.606408Z" + "iopub.execute_input": "2024-09-06T19:38:20.026677Z", + "iopub.status.busy": "2024-09-06T19:38:20.026505Z", + "iopub.status.idle": "2024-09-06T19:38:20.138981Z", + "shell.execute_reply": "2024-09-06T19:38:20.138473Z" } }, "outputs": [ @@ -1711,10 +1711,10 @@ "id": "044c0eb1-299a-4851-b1bf-268d5bce56c1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.609473Z", - "iopub.status.busy": "2024-09-05T19:38:22.609016Z", - "iopub.status.idle": "2024-09-05T19:38:22.617971Z", - "shell.execute_reply": "2024-09-05T19:38:22.617376Z" + "iopub.execute_input": "2024-09-06T19:38:20.141251Z", + "iopub.status.busy": "2024-09-06T19:38:20.140804Z", + "iopub.status.idle": "2024-09-06T19:38:20.147269Z", + "shell.execute_reply": "2024-09-06T19:38:20.146678Z" } }, "outputs": [], @@ -1738,10 +1738,10 @@ "id": "c43df278-abfe-40e5-9d48-2df3efea9379", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.620315Z", - "iopub.status.busy": "2024-09-05T19:38:22.620121Z", - "iopub.status.idle": "2024-09-05T19:38:24.659647Z", - "shell.execute_reply": "2024-09-05T19:38:24.659017Z" + "iopub.execute_input": "2024-09-06T19:38:20.149710Z", + "iopub.status.busy": "2024-09-06T19:38:20.149204Z", + "iopub.status.idle": "2024-09-06T19:38:22.175679Z", + "shell.execute_reply": "2024-09-06T19:38:22.175042Z" } }, "outputs": [ @@ -1953,10 +1953,10 @@ "id": "77c7f776-54b3-45b5-9207-715d6d2e90c0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.662641Z", - "iopub.status.busy": "2024-09-05T19:38:24.662119Z", - "iopub.status.idle": "2024-09-05T19:38:24.675048Z", - "shell.execute_reply": "2024-09-05T19:38:24.674550Z" + "iopub.execute_input": "2024-09-06T19:38:22.179907Z", + "iopub.status.busy": "2024-09-06T19:38:22.178817Z", + "iopub.status.idle": "2024-09-06T19:38:22.193599Z", + "shell.execute_reply": "2024-09-06T19:38:22.193081Z" } }, "outputs": [ @@ -2073,10 +2073,10 @@ "id": "7e218d04-0729-4f42-b264-51c73601ebe6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.677529Z", - "iopub.status.busy": "2024-09-05T19:38:24.677151Z", - "iopub.status.idle": "2024-09-05T19:38:24.680012Z", - "shell.execute_reply": "2024-09-05T19:38:24.679501Z" + "iopub.execute_input": "2024-09-06T19:38:22.197201Z", + "iopub.status.busy": "2024-09-06T19:38:22.196240Z", + "iopub.status.idle": "2024-09-06T19:38:22.200280Z", + "shell.execute_reply": "2024-09-06T19:38:22.199770Z" } }, "outputs": [], @@ -2090,10 +2090,10 @@ "id": "7e2bdb41-321e-4929-aa01-1f60948b9e8b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.682370Z", - "iopub.status.busy": "2024-09-05T19:38:24.681990Z", - "iopub.status.idle": "2024-09-05T19:38:24.686455Z", - "shell.execute_reply": "2024-09-05T19:38:24.685959Z" + "iopub.execute_input": "2024-09-06T19:38:22.203753Z", + "iopub.status.busy": "2024-09-06T19:38:22.202840Z", + "iopub.status.idle": "2024-09-06T19:38:22.208375Z", + "shell.execute_reply": "2024-09-06T19:38:22.207870Z" } }, "outputs": [], @@ -2117,10 +2117,10 @@ "id": "5ce2d89f-e832-448d-bfac-9941da15c895", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.688843Z", - "iopub.status.busy": "2024-09-05T19:38:24.688467Z", - "iopub.status.idle": "2024-09-05T19:38:24.725249Z", - "shell.execute_reply": "2024-09-05T19:38:24.724758Z" + "iopub.execute_input": "2024-09-06T19:38:22.211876Z", + "iopub.status.busy": "2024-09-06T19:38:22.210955Z", + "iopub.status.idle": "2024-09-06T19:38:22.243013Z", + "shell.execute_reply": "2024-09-06T19:38:22.242528Z" } }, "outputs": [ @@ -2160,10 +2160,10 @@ "id": "9f437756-112e-4531-84fc-6ceadd0c9ef5", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.727654Z", - "iopub.status.busy": "2024-09-05T19:38:24.727295Z", - "iopub.status.idle": "2024-09-05T19:38:25.269267Z", - "shell.execute_reply": "2024-09-05T19:38:25.268697Z" + "iopub.execute_input": "2024-09-06T19:38:22.246118Z", + "iopub.status.busy": "2024-09-06T19:38:22.245468Z", + "iopub.status.idle": "2024-09-06T19:38:22.754137Z", + "shell.execute_reply": "2024-09-06T19:38:22.753573Z" } }, "outputs": [], @@ -2194,10 +2194,10 @@ "id": "707625f6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.272182Z", - "iopub.status.busy": "2024-09-05T19:38:25.271755Z", - "iopub.status.idle": "2024-09-05T19:38:25.404404Z", - "shell.execute_reply": "2024-09-05T19:38:25.403688Z" + "iopub.execute_input": "2024-09-06T19:38:22.757125Z", + "iopub.status.busy": "2024-09-06T19:38:22.756730Z", + "iopub.status.idle": "2024-09-06T19:38:22.893326Z", + "shell.execute_reply": "2024-09-06T19:38:22.892578Z" } }, "outputs": [ @@ -2408,10 +2408,10 @@ "id": "25afe46c-a521-483c-b168-728c76d970dc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.408052Z", - "iopub.status.busy": "2024-09-05T19:38:25.407073Z", - "iopub.status.idle": "2024-09-05T19:38:25.415814Z", - "shell.execute_reply": "2024-09-05T19:38:25.415311Z" + "iopub.execute_input": "2024-09-06T19:38:22.896382Z", + "iopub.status.busy": "2024-09-06T19:38:22.896143Z", + "iopub.status.idle": "2024-09-06T19:38:22.903618Z", + "shell.execute_reply": "2024-09-06T19:38:22.903032Z" } }, "outputs": [ @@ -2441,10 +2441,10 @@ "id": "6efcf06f-cc40-4964-87df-5204d3b1b9d4", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.419323Z", - "iopub.status.busy": "2024-09-05T19:38:25.418402Z", - "iopub.status.idle": "2024-09-05T19:38:25.426295Z", - "shell.execute_reply": "2024-09-05T19:38:25.425789Z" + "iopub.execute_input": "2024-09-06T19:38:22.906322Z", + "iopub.status.busy": "2024-09-06T19:38:22.906102Z", + "iopub.status.idle": "2024-09-06T19:38:22.914842Z", + "shell.execute_reply": "2024-09-06T19:38:22.914319Z" } }, "outputs": [ @@ -2477,10 +2477,10 @@ "id": "7bc87d72-bbd5-4ed2-bc38-2218862ddfbd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.429748Z", - "iopub.status.busy": "2024-09-05T19:38:25.428807Z", - "iopub.status.idle": "2024-09-05T19:38:25.436120Z", - "shell.execute_reply": "2024-09-05T19:38:25.435593Z" + "iopub.execute_input": "2024-09-06T19:38:22.917418Z", + "iopub.status.busy": "2024-09-06T19:38:22.917212Z", + "iopub.status.idle": "2024-09-06T19:38:22.924586Z", + "shell.execute_reply": "2024-09-06T19:38:22.924068Z" } }, "outputs": [ @@ -2513,10 +2513,10 @@ "id": "9c70be3e-0ba2-4e3e-8c50-359d402ca1fe", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.439616Z", - "iopub.status.busy": "2024-09-05T19:38:25.438651Z", - "iopub.status.idle": "2024-09-05T19:38:25.444907Z", - "shell.execute_reply": "2024-09-05T19:38:25.444411Z" + "iopub.execute_input": "2024-09-06T19:38:22.927978Z", + "iopub.status.busy": "2024-09-06T19:38:22.927001Z", + "iopub.status.idle": "2024-09-06T19:38:22.932989Z", + "shell.execute_reply": "2024-09-06T19:38:22.932417Z" } }, "outputs": [ @@ -2542,10 +2542,10 @@ "id": "08080458-0cd7-447d-80e6-384cb8d31eaf", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.447298Z", - "iopub.status.busy": "2024-09-05T19:38:25.447124Z", - "iopub.status.idle": "2024-09-05T19:38:25.452420Z", - "shell.execute_reply": "2024-09-05T19:38:25.451830Z" + "iopub.execute_input": "2024-09-06T19:38:22.935455Z", + "iopub.status.busy": "2024-09-06T19:38:22.935286Z", + "iopub.status.idle": "2024-09-06T19:38:22.940366Z", + "shell.execute_reply": "2024-09-06T19:38:22.939926Z" } }, "outputs": [], @@ -2569,10 +2569,10 @@ "id": "009bb215-4d26-47da-a230-d0ccf4122629", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.454421Z", - "iopub.status.busy": "2024-09-05T19:38:25.454250Z", - "iopub.status.idle": "2024-09-05T19:38:25.536458Z", - "shell.execute_reply": "2024-09-05T19:38:25.535873Z" + "iopub.execute_input": "2024-09-06T19:38:22.942577Z", + "iopub.status.busy": "2024-09-06T19:38:22.942242Z", + "iopub.status.idle": "2024-09-06T19:38:23.018404Z", + "shell.execute_reply": "2024-09-06T19:38:23.017754Z" } }, "outputs": [ @@ -3052,10 +3052,10 @@ "id": "dcaeda51-9b24-4c04-889d-7e63563594fc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.538788Z", - "iopub.status.busy": "2024-09-05T19:38:25.538612Z", - "iopub.status.idle": "2024-09-05T19:38:25.547223Z", - "shell.execute_reply": "2024-09-05T19:38:25.546738Z" + "iopub.execute_input": "2024-09-06T19:38:23.021060Z", + "iopub.status.busy": "2024-09-06T19:38:23.020492Z", + "iopub.status.idle": "2024-09-06T19:38:23.034062Z", + "shell.execute_reply": "2024-09-06T19:38:23.033451Z" } }, "outputs": [ @@ -3111,10 +3111,10 @@ "id": "1d92d78d-e4a8-4322-bf38-f5a5dae3bf17", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.550442Z", - "iopub.status.busy": "2024-09-05T19:38:25.549562Z", - "iopub.status.idle": "2024-09-05T19:38:25.553319Z", - "shell.execute_reply": "2024-09-05T19:38:25.552755Z" + "iopub.execute_input": "2024-09-06T19:38:23.036553Z", + "iopub.status.busy": "2024-09-06T19:38:23.036240Z", + "iopub.status.idle": "2024-09-06T19:38:23.039008Z", + "shell.execute_reply": "2024-09-06T19:38:23.038465Z" } }, "outputs": [], @@ -3150,10 +3150,10 @@ "id": "941ab2a6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.555448Z", - "iopub.status.busy": "2024-09-05T19:38:25.555270Z", - "iopub.status.idle": "2024-09-05T19:38:25.565627Z", - "shell.execute_reply": "2024-09-05T19:38:25.565195Z" + "iopub.execute_input": "2024-09-06T19:38:23.041147Z", + "iopub.status.busy": "2024-09-06T19:38:23.040695Z", + "iopub.status.idle": "2024-09-06T19:38:23.050646Z", + "shell.execute_reply": "2024-09-06T19:38:23.050044Z" } }, "outputs": [], @@ -3261,10 +3261,10 @@ "id": "50666fb9", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.567569Z", - "iopub.status.busy": "2024-09-05T19:38:25.567400Z", - "iopub.status.idle": "2024-09-05T19:38:25.573998Z", - "shell.execute_reply": "2024-09-05T19:38:25.573414Z" + "iopub.execute_input": "2024-09-06T19:38:23.053067Z", + "iopub.status.busy": "2024-09-06T19:38:23.052637Z", + "iopub.status.idle": "2024-09-06T19:38:23.059254Z", + "shell.execute_reply": "2024-09-06T19:38:23.058781Z" }, "nbsphinx": "hidden" }, @@ -3346,10 +3346,10 @@ "id": "f5aa2883-d20d-481f-a012-fcc7ff8e3e7e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.576080Z", - "iopub.status.busy": "2024-09-05T19:38:25.575748Z", - "iopub.status.idle": "2024-09-05T19:38:25.579065Z", - "shell.execute_reply": "2024-09-05T19:38:25.578516Z" + "iopub.execute_input": "2024-09-06T19:38:23.061114Z", + "iopub.status.busy": "2024-09-06T19:38:23.060934Z", + "iopub.status.idle": "2024-09-06T19:38:23.064369Z", + "shell.execute_reply": "2024-09-06T19:38:23.063906Z" } }, "outputs": [], @@ -3373,10 +3373,10 @@ "id": "ce1c0ada-88b1-4654-b43f-3c0b59002979", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.581087Z", - "iopub.status.busy": "2024-09-05T19:38:25.580780Z", - "iopub.status.idle": "2024-09-05T19:38:29.675098Z", - "shell.execute_reply": "2024-09-05T19:38:29.674482Z" + "iopub.execute_input": "2024-09-06T19:38:23.066492Z", + "iopub.status.busy": "2024-09-06T19:38:23.066088Z", + "iopub.status.idle": "2024-09-06T19:38:27.075896Z", + "shell.execute_reply": "2024-09-06T19:38:27.075361Z" } }, "outputs": [ @@ -3419,10 +3419,10 @@ "id": "3f572acf-31c3-4874-9100-451796e35b06", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:29.678980Z", - "iopub.status.busy": "2024-09-05T19:38:29.678139Z", - "iopub.status.idle": "2024-09-05T19:38:29.682800Z", - "shell.execute_reply": "2024-09-05T19:38:29.682367Z" + "iopub.execute_input": "2024-09-06T19:38:27.079119Z", + "iopub.status.busy": "2024-09-06T19:38:27.078209Z", + "iopub.status.idle": "2024-09-06T19:38:27.082469Z", + "shell.execute_reply": "2024-09-06T19:38:27.082025Z" } }, "outputs": [ @@ -3460,10 +3460,10 @@ "id": "6a025a88", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:29.685051Z", - "iopub.status.busy": "2024-09-05T19:38:29.684864Z", - "iopub.status.idle": "2024-09-05T19:38:29.687798Z", - "shell.execute_reply": "2024-09-05T19:38:29.687349Z" + "iopub.execute_input": "2024-09-06T19:38:27.084613Z", + "iopub.status.busy": "2024-09-06T19:38:27.084277Z", + "iopub.status.idle": "2024-09-06T19:38:27.087400Z", + "shell.execute_reply": "2024-09-06T19:38:27.086984Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb b/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb index ff39a0ce9..d4d06d3f8 100644 --- a/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/indepth_overview.ipynb @@ -53,10 +53,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:33.024311Z", - "iopub.status.busy": "2024-09-05T19:38:33.024154Z", - "iopub.status.idle": "2024-09-05T19:38:34.264701Z", - "shell.execute_reply": "2024-09-05T19:38:34.264082Z" + "iopub.execute_input": "2024-09-06T19:38:29.945055Z", + "iopub.status.busy": "2024-09-06T19:38:29.944859Z", + "iopub.status.idle": "2024-09-06T19:38:31.152677Z", + "shell.execute_reply": "2024-09-06T19:38:31.152154Z" }, "nbsphinx": "hidden" }, @@ -68,7 +68,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -95,10 +95,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.267586Z", - "iopub.status.busy": "2024-09-05T19:38:34.267100Z", - "iopub.status.idle": "2024-09-05T19:38:34.450638Z", - "shell.execute_reply": "2024-09-05T19:38:34.449996Z" + "iopub.execute_input": "2024-09-06T19:38:31.155349Z", + "iopub.status.busy": "2024-09-06T19:38:31.154914Z", + "iopub.status.idle": "2024-09-06T19:38:31.333867Z", + "shell.execute_reply": "2024-09-06T19:38:31.333299Z" }, "id": "avXlHJcXjruP" }, @@ -234,10 +234,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.453452Z", - "iopub.status.busy": "2024-09-05T19:38:34.453074Z", - "iopub.status.idle": "2024-09-05T19:38:34.464955Z", - "shell.execute_reply": "2024-09-05T19:38:34.464480Z" + "iopub.execute_input": "2024-09-06T19:38:31.336296Z", + "iopub.status.busy": "2024-09-06T19:38:31.336106Z", + "iopub.status.idle": "2024-09-06T19:38:31.347492Z", + "shell.execute_reply": "2024-09-06T19:38:31.347045Z" }, "nbsphinx": "hidden" }, @@ -340,10 +340,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.467204Z", - "iopub.status.busy": "2024-09-05T19:38:34.466843Z", - "iopub.status.idle": "2024-09-05T19:38:34.705791Z", - "shell.execute_reply": "2024-09-05T19:38:34.705183Z" + "iopub.execute_input": "2024-09-06T19:38:31.349587Z", + "iopub.status.busy": "2024-09-06T19:38:31.349239Z", + "iopub.status.idle": "2024-09-06T19:38:31.559000Z", + "shell.execute_reply": "2024-09-06T19:38:31.558435Z" } }, "outputs": [ @@ -393,10 +393,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.708181Z", - "iopub.status.busy": "2024-09-05T19:38:34.707976Z", - "iopub.status.idle": "2024-09-05T19:38:34.734780Z", - "shell.execute_reply": "2024-09-05T19:38:34.734318Z" + "iopub.execute_input": "2024-09-06T19:38:31.561389Z", + "iopub.status.busy": "2024-09-06T19:38:31.561027Z", + "iopub.status.idle": "2024-09-06T19:38:31.587035Z", + "shell.execute_reply": "2024-09-06T19:38:31.586568Z" } }, "outputs": [], @@ -428,10 +428,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.736860Z", - "iopub.status.busy": "2024-09-05T19:38:34.736672Z", - "iopub.status.idle": "2024-09-05T19:38:36.884795Z", - "shell.execute_reply": "2024-09-05T19:38:36.884146Z" + "iopub.execute_input": "2024-09-06T19:38:31.589259Z", + "iopub.status.busy": "2024-09-06T19:38:31.588898Z", + "iopub.status.idle": "2024-09-06T19:38:33.659672Z", + "shell.execute_reply": "2024-09-06T19:38:33.658986Z" } }, "outputs": [ @@ -474,10 +474,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:36.887499Z", - "iopub.status.busy": "2024-09-05T19:38:36.886853Z", - "iopub.status.idle": "2024-09-05T19:38:36.905206Z", - "shell.execute_reply": "2024-09-05T19:38:36.904650Z" + "iopub.execute_input": "2024-09-06T19:38:33.662234Z", + "iopub.status.busy": "2024-09-06T19:38:33.661770Z", + "iopub.status.idle": "2024-09-06T19:38:33.679880Z", + "shell.execute_reply": "2024-09-06T19:38:33.679304Z" }, "scrolled": true }, @@ -607,10 +607,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:36.907433Z", - "iopub.status.busy": "2024-09-05T19:38:36.907012Z", - "iopub.status.idle": "2024-09-05T19:38:38.506025Z", - "shell.execute_reply": "2024-09-05T19:38:38.505370Z" + "iopub.execute_input": "2024-09-06T19:38:33.682125Z", + "iopub.status.busy": "2024-09-06T19:38:33.681797Z", + "iopub.status.idle": "2024-09-06T19:38:35.246559Z", + "shell.execute_reply": "2024-09-06T19:38:35.245952Z" }, "id": "AaHC5MRKjruT" }, @@ -729,10 +729,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.508964Z", - "iopub.status.busy": "2024-09-05T19:38:38.508264Z", - "iopub.status.idle": "2024-09-05T19:38:38.522533Z", - "shell.execute_reply": "2024-09-05T19:38:38.522045Z" + "iopub.execute_input": "2024-09-06T19:38:35.249384Z", + "iopub.status.busy": "2024-09-06T19:38:35.248692Z", + "iopub.status.idle": "2024-09-06T19:38:35.262909Z", + "shell.execute_reply": "2024-09-06T19:38:35.262437Z" }, "id": "Wy27rvyhjruU" }, @@ -781,10 +781,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.524864Z", - "iopub.status.busy": "2024-09-05T19:38:38.524513Z", - "iopub.status.idle": "2024-09-05T19:38:38.607517Z", - "shell.execute_reply": "2024-09-05T19:38:38.606813Z" + "iopub.execute_input": "2024-09-06T19:38:35.265091Z", + "iopub.status.busy": "2024-09-06T19:38:35.264657Z", + "iopub.status.idle": "2024-09-06T19:38:35.347361Z", + "shell.execute_reply": "2024-09-06T19:38:35.346752Z" }, "id": "Db8YHnyVjruU" }, @@ -891,10 +891,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.610151Z", - "iopub.status.busy": "2024-09-05T19:38:38.609680Z", - "iopub.status.idle": "2024-09-05T19:38:38.823788Z", - "shell.execute_reply": "2024-09-05T19:38:38.823190Z" + "iopub.execute_input": "2024-09-06T19:38:35.349859Z", + "iopub.status.busy": "2024-09-06T19:38:35.349553Z", + "iopub.status.idle": "2024-09-06T19:38:35.568160Z", + "shell.execute_reply": "2024-09-06T19:38:35.567596Z" }, "id": "iJqAHuS2jruV" }, @@ -931,10 +931,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.826041Z", - "iopub.status.busy": "2024-09-05T19:38:38.825845Z", - "iopub.status.idle": "2024-09-05T19:38:38.843439Z", - "shell.execute_reply": "2024-09-05T19:38:38.842891Z" + "iopub.execute_input": "2024-09-06T19:38:35.570518Z", + "iopub.status.busy": "2024-09-06T19:38:35.570156Z", + "iopub.status.idle": "2024-09-06T19:38:35.587030Z", + "shell.execute_reply": "2024-09-06T19:38:35.586565Z" }, "id": "PcPTZ_JJG3Cx" }, @@ -1400,10 +1400,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.845804Z", - "iopub.status.busy": "2024-09-05T19:38:38.845404Z", - "iopub.status.idle": "2024-09-05T19:38:38.855289Z", - "shell.execute_reply": "2024-09-05T19:38:38.854744Z" + "iopub.execute_input": "2024-09-06T19:38:35.589095Z", + "iopub.status.busy": "2024-09-06T19:38:35.588739Z", + "iopub.status.idle": "2024-09-06T19:38:35.598220Z", + "shell.execute_reply": "2024-09-06T19:38:35.597755Z" }, "id": "0lonvOYvjruV" }, @@ -1550,10 +1550,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.857352Z", - "iopub.status.busy": "2024-09-05T19:38:38.857028Z", - "iopub.status.idle": "2024-09-05T19:38:38.948792Z", - "shell.execute_reply": "2024-09-05T19:38:38.948130Z" + "iopub.execute_input": "2024-09-06T19:38:35.600262Z", + "iopub.status.busy": "2024-09-06T19:38:35.599918Z", + "iopub.status.idle": "2024-09-06T19:38:35.692538Z", + "shell.execute_reply": "2024-09-06T19:38:35.691918Z" }, "id": "MfqTCa3kjruV" }, @@ -1634,10 +1634,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.951301Z", - "iopub.status.busy": "2024-09-05T19:38:38.950892Z", - "iopub.status.idle": "2024-09-05T19:38:39.093684Z", - "shell.execute_reply": "2024-09-05T19:38:39.093010Z" + "iopub.execute_input": "2024-09-06T19:38:35.694934Z", + "iopub.status.busy": "2024-09-06T19:38:35.694629Z", + "iopub.status.idle": "2024-09-06T19:38:35.833017Z", + "shell.execute_reply": "2024-09-06T19:38:35.832312Z" }, "id": "9ZtWAYXqMAPL" }, @@ -1697,10 +1697,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.096217Z", - "iopub.status.busy": "2024-09-05T19:38:39.095689Z", - "iopub.status.idle": "2024-09-05T19:38:39.099737Z", - "shell.execute_reply": "2024-09-05T19:38:39.099183Z" + "iopub.execute_input": "2024-09-06T19:38:35.835595Z", + "iopub.status.busy": "2024-09-06T19:38:35.835206Z", + "iopub.status.idle": "2024-09-06T19:38:35.839051Z", + "shell.execute_reply": "2024-09-06T19:38:35.838497Z" }, "id": "0rXP3ZPWjruW" }, @@ -1738,10 +1738,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.101881Z", - "iopub.status.busy": "2024-09-05T19:38:39.101611Z", - "iopub.status.idle": "2024-09-05T19:38:39.105429Z", - "shell.execute_reply": "2024-09-05T19:38:39.104857Z" + "iopub.execute_input": "2024-09-06T19:38:35.841055Z", + "iopub.status.busy": "2024-09-06T19:38:35.840887Z", + "iopub.status.idle": "2024-09-06T19:38:35.844523Z", + "shell.execute_reply": "2024-09-06T19:38:35.843987Z" }, "id": "-iRPe8KXjruW" }, @@ -1796,10 +1796,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.107547Z", - "iopub.status.busy": "2024-09-05T19:38:39.107212Z", - "iopub.status.idle": "2024-09-05T19:38:39.143655Z", - "shell.execute_reply": "2024-09-05T19:38:39.143146Z" + "iopub.execute_input": "2024-09-06T19:38:35.846624Z", + "iopub.status.busy": "2024-09-06T19:38:35.846289Z", + "iopub.status.idle": "2024-09-06T19:38:35.883516Z", + "shell.execute_reply": "2024-09-06T19:38:35.883025Z" }, "id": "ZpipUliyjruW" }, @@ -1850,10 +1850,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.145813Z", - "iopub.status.busy": "2024-09-05T19:38:39.145467Z", - "iopub.status.idle": "2024-09-05T19:38:39.185783Z", - "shell.execute_reply": "2024-09-05T19:38:39.185245Z" + "iopub.execute_input": "2024-09-06T19:38:35.885707Z", + "iopub.status.busy": "2024-09-06T19:38:35.885360Z", + "iopub.status.idle": "2024-09-06T19:38:35.926415Z", + "shell.execute_reply": "2024-09-06T19:38:35.925951Z" }, "id": "SLq-3q4xjruX" }, @@ -1922,10 +1922,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.187839Z", - "iopub.status.busy": "2024-09-05T19:38:39.187520Z", - "iopub.status.idle": "2024-09-05T19:38:39.289564Z", - "shell.execute_reply": "2024-09-05T19:38:39.288933Z" + "iopub.execute_input": "2024-09-06T19:38:35.928488Z", + "iopub.status.busy": "2024-09-06T19:38:35.928146Z", + "iopub.status.idle": "2024-09-06T19:38:36.031351Z", + "shell.execute_reply": "2024-09-06T19:38:36.030698Z" }, "id": "g5LHhhuqFbXK" }, @@ -1957,10 +1957,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.292121Z", - "iopub.status.busy": "2024-09-05T19:38:39.291892Z", - "iopub.status.idle": "2024-09-05T19:38:39.400843Z", - "shell.execute_reply": "2024-09-05T19:38:39.400129Z" + "iopub.execute_input": "2024-09-06T19:38:36.034301Z", + "iopub.status.busy": "2024-09-06T19:38:36.033912Z", + "iopub.status.idle": "2024-09-06T19:38:36.132017Z", + "shell.execute_reply": "2024-09-06T19:38:36.131369Z" }, "id": "p7w8F8ezBcet" }, @@ -2017,10 +2017,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.403530Z", - "iopub.status.busy": "2024-09-05T19:38:39.403100Z", - "iopub.status.idle": "2024-09-05T19:38:39.617987Z", - "shell.execute_reply": "2024-09-05T19:38:39.617380Z" + "iopub.execute_input": "2024-09-06T19:38:36.134718Z", + "iopub.status.busy": "2024-09-06T19:38:36.134254Z", + "iopub.status.idle": "2024-09-06T19:38:36.372737Z", + "shell.execute_reply": "2024-09-06T19:38:36.372155Z" }, "id": "WETRL74tE_sU" }, @@ -2055,10 +2055,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.620312Z", - "iopub.status.busy": "2024-09-05T19:38:39.619935Z", - "iopub.status.idle": "2024-09-05T19:38:39.847199Z", - "shell.execute_reply": "2024-09-05T19:38:39.846563Z" + "iopub.execute_input": "2024-09-06T19:38:36.374987Z", + "iopub.status.busy": "2024-09-06T19:38:36.374694Z", + "iopub.status.idle": "2024-09-06T19:38:36.587886Z", + "shell.execute_reply": "2024-09-06T19:38:36.587278Z" }, "id": "kCfdx2gOLmXS" }, @@ -2220,10 +2220,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.849646Z", - "iopub.status.busy": "2024-09-05T19:38:39.849312Z", - "iopub.status.idle": "2024-09-05T19:38:39.855523Z", - "shell.execute_reply": "2024-09-05T19:38:39.855075Z" + "iopub.execute_input": "2024-09-06T19:38:36.590343Z", + "iopub.status.busy": "2024-09-06T19:38:36.589956Z", + "iopub.status.idle": "2024-09-06T19:38:36.595878Z", + "shell.execute_reply": "2024-09-06T19:38:36.595334Z" }, "id": "-uogYRWFYnuu" }, @@ -2277,10 +2277,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.857741Z", - "iopub.status.busy": "2024-09-05T19:38:39.857296Z", - "iopub.status.idle": "2024-09-05T19:38:40.076699Z", - "shell.execute_reply": "2024-09-05T19:38:40.076059Z" + "iopub.execute_input": "2024-09-06T19:38:36.598057Z", + "iopub.status.busy": "2024-09-06T19:38:36.597740Z", + "iopub.status.idle": "2024-09-06T19:38:36.811700Z", + "shell.execute_reply": "2024-09-06T19:38:36.811079Z" }, "id": "pG-ljrmcYp9Q" }, @@ -2327,10 +2327,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:40.079111Z", - "iopub.status.busy": "2024-09-05T19:38:40.078742Z", - "iopub.status.idle": "2024-09-05T19:38:41.162000Z", - "shell.execute_reply": "2024-09-05T19:38:41.161484Z" + "iopub.execute_input": "2024-09-06T19:38:36.813989Z", + "iopub.status.busy": "2024-09-06T19:38:36.813680Z", + "iopub.status.idle": "2024-09-06T19:38:37.873549Z", + "shell.execute_reply": "2024-09-06T19:38:37.872901Z" }, "id": "wL3ngCnuLEWd" }, diff --git a/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb b/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb index 872e74175..0b05cce8c 100644 --- a/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/multiannotator.ipynb @@ -88,10 +88,10 @@ "id": "a3ddc95f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:44.675764Z", - "iopub.status.busy": "2024-09-05T19:38:44.675335Z", - "iopub.status.idle": "2024-09-05T19:38:45.838314Z", - "shell.execute_reply": "2024-09-05T19:38:45.837761Z" + "iopub.execute_input": "2024-09-06T19:38:41.455901Z", + "iopub.status.busy": "2024-09-06T19:38:41.455732Z", + "iopub.status.idle": "2024-09-06T19:38:42.611358Z", + "shell.execute_reply": "2024-09-06T19:38:42.610733Z" }, "nbsphinx": "hidden" }, @@ -101,7 +101,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -135,10 +135,10 @@ "id": "c4efd119", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.840955Z", - "iopub.status.busy": "2024-09-05T19:38:45.840492Z", - "iopub.status.idle": "2024-09-05T19:38:45.843468Z", - "shell.execute_reply": "2024-09-05T19:38:45.843021Z" + "iopub.execute_input": "2024-09-06T19:38:42.614152Z", + "iopub.status.busy": "2024-09-06T19:38:42.613703Z", + "iopub.status.idle": "2024-09-06T19:38:42.617474Z", + "shell.execute_reply": "2024-09-06T19:38:42.616914Z" } }, "outputs": [], @@ -263,10 +263,10 @@ "id": "c37c0a69", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.845741Z", - "iopub.status.busy": "2024-09-05T19:38:45.845402Z", - "iopub.status.idle": "2024-09-05T19:38:45.853153Z", - "shell.execute_reply": "2024-09-05T19:38:45.852719Z" + "iopub.execute_input": "2024-09-06T19:38:42.619686Z", + "iopub.status.busy": "2024-09-06T19:38:42.619396Z", + "iopub.status.idle": "2024-09-06T19:38:42.627253Z", + "shell.execute_reply": "2024-09-06T19:38:42.626804Z" }, "nbsphinx": "hidden" }, @@ -350,10 +350,10 @@ "id": "99f69523", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.855196Z", - "iopub.status.busy": "2024-09-05T19:38:45.854862Z", - "iopub.status.idle": "2024-09-05T19:38:45.900555Z", - "shell.execute_reply": "2024-09-05T19:38:45.900040Z" + "iopub.execute_input": "2024-09-06T19:38:42.629251Z", + "iopub.status.busy": "2024-09-06T19:38:42.628912Z", + "iopub.status.idle": "2024-09-06T19:38:42.675739Z", + "shell.execute_reply": "2024-09-06T19:38:42.675250Z" } }, "outputs": [], @@ -379,10 +379,10 @@ "id": "8f241c16", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.902601Z", - "iopub.status.busy": "2024-09-05T19:38:45.902427Z", - "iopub.status.idle": "2024-09-05T19:38:45.919866Z", - "shell.execute_reply": "2024-09-05T19:38:45.919444Z" + "iopub.execute_input": "2024-09-06T19:38:42.677746Z", + "iopub.status.busy": "2024-09-06T19:38:42.677566Z", + "iopub.status.idle": "2024-09-06T19:38:42.695187Z", + "shell.execute_reply": "2024-09-06T19:38:42.694600Z" } }, "outputs": [ @@ -597,10 +597,10 @@ "id": "4f0819ba", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.922151Z", - "iopub.status.busy": "2024-09-05T19:38:45.921714Z", - "iopub.status.idle": "2024-09-05T19:38:45.925609Z", - "shell.execute_reply": "2024-09-05T19:38:45.925082Z" + "iopub.execute_input": "2024-09-06T19:38:42.697240Z", + "iopub.status.busy": "2024-09-06T19:38:42.696927Z", + "iopub.status.idle": "2024-09-06T19:38:42.700805Z", + "shell.execute_reply": "2024-09-06T19:38:42.700357Z" } }, "outputs": [ @@ -671,10 +671,10 @@ "id": "d009f347", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.927793Z", - "iopub.status.busy": "2024-09-05T19:38:45.927382Z", - "iopub.status.idle": "2024-09-05T19:38:45.943665Z", - "shell.execute_reply": "2024-09-05T19:38:45.943100Z" + "iopub.execute_input": "2024-09-06T19:38:42.703011Z", + "iopub.status.busy": "2024-09-06T19:38:42.702619Z", + "iopub.status.idle": "2024-09-06T19:38:42.719152Z", + "shell.execute_reply": "2024-09-06T19:38:42.718696Z" } }, "outputs": [], @@ -698,10 +698,10 @@ "id": "cbd1e415", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.945827Z", - "iopub.status.busy": "2024-09-05T19:38:45.945552Z", - "iopub.status.idle": "2024-09-05T19:38:45.971204Z", - "shell.execute_reply": "2024-09-05T19:38:45.970648Z" + "iopub.execute_input": "2024-09-06T19:38:42.721153Z", + "iopub.status.busy": "2024-09-06T19:38:42.720797Z", + "iopub.status.idle": "2024-09-06T19:38:42.746197Z", + "shell.execute_reply": "2024-09-06T19:38:42.745739Z" } }, "outputs": [], @@ -738,10 +738,10 @@ "id": "6ca92617", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.973422Z", - "iopub.status.busy": "2024-09-05T19:38:45.973114Z", - "iopub.status.idle": "2024-09-05T19:38:47.957844Z", - "shell.execute_reply": "2024-09-05T19:38:47.957281Z" + "iopub.execute_input": "2024-09-06T19:38:42.748111Z", + "iopub.status.busy": "2024-09-06T19:38:42.747776Z", + "iopub.status.idle": "2024-09-06T19:38:44.708904Z", + "shell.execute_reply": "2024-09-06T19:38:44.708307Z" } }, "outputs": [], @@ -771,10 +771,10 @@ "id": "bf945113", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.960323Z", - "iopub.status.busy": "2024-09-05T19:38:47.960036Z", - "iopub.status.idle": "2024-09-05T19:38:47.966782Z", - "shell.execute_reply": "2024-09-05T19:38:47.966212Z" + "iopub.execute_input": "2024-09-06T19:38:44.711480Z", + "iopub.status.busy": "2024-09-06T19:38:44.710993Z", + "iopub.status.idle": "2024-09-06T19:38:44.717750Z", + "shell.execute_reply": "2024-09-06T19:38:44.717182Z" }, "scrolled": true }, @@ -885,10 +885,10 @@ "id": "14251ee0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.969001Z", - "iopub.status.busy": "2024-09-05T19:38:47.968670Z", - "iopub.status.idle": "2024-09-05T19:38:47.982271Z", - "shell.execute_reply": "2024-09-05T19:38:47.981722Z" + "iopub.execute_input": "2024-09-06T19:38:44.719963Z", + "iopub.status.busy": "2024-09-06T19:38:44.719631Z", + "iopub.status.idle": "2024-09-06T19:38:44.732695Z", + "shell.execute_reply": "2024-09-06T19:38:44.732259Z" } }, "outputs": [ @@ -1138,10 +1138,10 @@ "id": "efe16638", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.984470Z", - "iopub.status.busy": "2024-09-05T19:38:47.984002Z", - "iopub.status.idle": "2024-09-05T19:38:47.990230Z", - "shell.execute_reply": "2024-09-05T19:38:47.989775Z" + "iopub.execute_input": "2024-09-06T19:38:44.734719Z", + "iopub.status.busy": "2024-09-06T19:38:44.734386Z", + "iopub.status.idle": "2024-09-06T19:38:44.740630Z", + "shell.execute_reply": "2024-09-06T19:38:44.740080Z" }, "scrolled": true }, @@ -1315,10 +1315,10 @@ "id": "abd0fb0b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.992351Z", - "iopub.status.busy": "2024-09-05T19:38:47.992012Z", - "iopub.status.idle": "2024-09-05T19:38:47.994554Z", - "shell.execute_reply": "2024-09-05T19:38:47.994115Z" + "iopub.execute_input": "2024-09-06T19:38:44.742715Z", + "iopub.status.busy": "2024-09-06T19:38:44.742407Z", + "iopub.status.idle": "2024-09-06T19:38:44.745203Z", + "shell.execute_reply": "2024-09-06T19:38:44.744635Z" } }, "outputs": [], @@ -1340,10 +1340,10 @@ "id": "cdf061df", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.996534Z", - "iopub.status.busy": "2024-09-05T19:38:47.996204Z", - "iopub.status.idle": "2024-09-05T19:38:47.999737Z", - "shell.execute_reply": "2024-09-05T19:38:47.999187Z" + "iopub.execute_input": "2024-09-06T19:38:44.747300Z", + "iopub.status.busy": "2024-09-06T19:38:44.746906Z", + "iopub.status.idle": "2024-09-06T19:38:44.750594Z", + "shell.execute_reply": "2024-09-06T19:38:44.750021Z" }, "scrolled": true }, @@ -1395,10 +1395,10 @@ "id": "08949890", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.001908Z", - "iopub.status.busy": "2024-09-05T19:38:48.001582Z", - "iopub.status.idle": "2024-09-05T19:38:48.003999Z", - "shell.execute_reply": "2024-09-05T19:38:48.003506Z" + "iopub.execute_input": "2024-09-06T19:38:44.752864Z", + "iopub.status.busy": "2024-09-06T19:38:44.752447Z", + "iopub.status.idle": "2024-09-06T19:38:44.755290Z", + "shell.execute_reply": "2024-09-06T19:38:44.754743Z" } }, "outputs": [], @@ -1422,10 +1422,10 @@ "id": "6948b073", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.006110Z", - "iopub.status.busy": "2024-09-05T19:38:48.005783Z", - "iopub.status.idle": "2024-09-05T19:38:48.009935Z", - "shell.execute_reply": "2024-09-05T19:38:48.009399Z" + "iopub.execute_input": "2024-09-06T19:38:44.757347Z", + "iopub.status.busy": "2024-09-06T19:38:44.757015Z", + "iopub.status.idle": "2024-09-06T19:38:44.761164Z", + "shell.execute_reply": "2024-09-06T19:38:44.760669Z" } }, "outputs": [ @@ -1480,10 +1480,10 @@ "id": "6f8e6914", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.012094Z", - "iopub.status.busy": "2024-09-05T19:38:48.011735Z", - "iopub.status.idle": "2024-09-05T19:38:48.039799Z", - "shell.execute_reply": "2024-09-05T19:38:48.039323Z" + "iopub.execute_input": "2024-09-06T19:38:44.763225Z", + "iopub.status.busy": "2024-09-06T19:38:44.762830Z", + "iopub.status.idle": "2024-09-06T19:38:44.791503Z", + "shell.execute_reply": "2024-09-06T19:38:44.790922Z" } }, "outputs": [], @@ -1526,10 +1526,10 @@ "id": "b806d2ea", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.042183Z", - "iopub.status.busy": "2024-09-05T19:38:48.041817Z", - "iopub.status.idle": "2024-09-05T19:38:48.046713Z", - "shell.execute_reply": "2024-09-05T19:38:48.046238Z" + "iopub.execute_input": "2024-09-06T19:38:44.793778Z", + "iopub.status.busy": "2024-09-06T19:38:44.793374Z", + "iopub.status.idle": "2024-09-06T19:38:44.798051Z", + "shell.execute_reply": "2024-09-06T19:38:44.797497Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb b/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb index 1509def8d..7626ff8d8 100644 --- a/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/multilabel_classification.ipynb @@ -64,10 +64,10 @@ "id": "7383d024-8273-4039-bccd-aab3020d331f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:51.101575Z", - "iopub.status.busy": "2024-09-05T19:38:51.101202Z", - "iopub.status.idle": "2024-09-05T19:38:52.356767Z", - "shell.execute_reply": "2024-09-05T19:38:52.356160Z" + "iopub.execute_input": "2024-09-06T19:38:47.803342Z", + "iopub.status.busy": "2024-09-06T19:38:47.803172Z", + "iopub.status.idle": "2024-09-06T19:38:49.010459Z", + "shell.execute_reply": "2024-09-06T19:38:49.009894Z" }, "nbsphinx": "hidden" }, @@ -79,7 +79,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -105,10 +105,10 @@ "id": "bf9101d8-b1a9-4305-b853-45aaf3d67a69", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:52.359268Z", - "iopub.status.busy": "2024-09-05T19:38:52.358948Z", - "iopub.status.idle": "2024-09-05T19:38:52.562776Z", - "shell.execute_reply": "2024-09-05T19:38:52.562204Z" + "iopub.execute_input": "2024-09-06T19:38:49.013219Z", + "iopub.status.busy": "2024-09-06T19:38:49.012725Z", + "iopub.status.idle": "2024-09-06T19:38:49.210289Z", + "shell.execute_reply": "2024-09-06T19:38:49.209783Z" } }, "outputs": [], @@ -268,10 +268,10 @@ "id": "e8ff5c2f-bd52-44aa-b307-b2b634147c68", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:52.565447Z", - "iopub.status.busy": "2024-09-05T19:38:52.565141Z", - "iopub.status.idle": "2024-09-05T19:38:52.579312Z", - "shell.execute_reply": "2024-09-05T19:38:52.578691Z" + "iopub.execute_input": "2024-09-06T19:38:49.212873Z", + "iopub.status.busy": "2024-09-06T19:38:49.212501Z", + "iopub.status.idle": "2024-09-06T19:38:49.226305Z", + "shell.execute_reply": "2024-09-06T19:38:49.225843Z" }, "nbsphinx": "hidden" }, @@ -407,10 +407,10 @@ "id": "dac65d3b-51e8-4682-b829-beab610b56d6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:52.581436Z", - "iopub.status.busy": "2024-09-05T19:38:52.581245Z", - "iopub.status.idle": "2024-09-05T19:38:55.240942Z", - "shell.execute_reply": "2024-09-05T19:38:55.240413Z" + "iopub.execute_input": "2024-09-06T19:38:49.228339Z", + "iopub.status.busy": "2024-09-06T19:38:49.227999Z", + "iopub.status.idle": "2024-09-06T19:38:51.870134Z", + "shell.execute_reply": "2024-09-06T19:38:51.869617Z" } }, "outputs": [ @@ -454,10 +454,10 @@ "id": "b5fa99a9-2583-4cd0-9d40-015f698cdb23", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:55.243248Z", - "iopub.status.busy": "2024-09-05T19:38:55.242887Z", - "iopub.status.idle": "2024-09-05T19:38:56.591285Z", - "shell.execute_reply": "2024-09-05T19:38:56.590684Z" + "iopub.execute_input": "2024-09-06T19:38:51.872305Z", + "iopub.status.busy": "2024-09-06T19:38:51.872107Z", + "iopub.status.idle": "2024-09-06T19:38:53.221496Z", + "shell.execute_reply": "2024-09-06T19:38:53.220930Z" } }, "outputs": [], @@ -499,10 +499,10 @@ "id": "ac1a60df", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:56.593787Z", - "iopub.status.busy": "2024-09-05T19:38:56.593425Z", - "iopub.status.idle": "2024-09-05T19:38:56.597557Z", - "shell.execute_reply": "2024-09-05T19:38:56.597077Z" + "iopub.execute_input": "2024-09-06T19:38:53.223970Z", + "iopub.status.busy": "2024-09-06T19:38:53.223773Z", + "iopub.status.idle": "2024-09-06T19:38:53.227537Z", + "shell.execute_reply": "2024-09-06T19:38:53.226991Z" } }, "outputs": [ @@ -544,10 +544,10 @@ "id": "d09115b6-ad44-474f-9c8a-85a459586439", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:56.599600Z", - "iopub.status.busy": "2024-09-05T19:38:56.599258Z", - "iopub.status.idle": "2024-09-05T19:38:58.742931Z", - "shell.execute_reply": "2024-09-05T19:38:58.742243Z" + "iopub.execute_input": "2024-09-06T19:38:53.229541Z", + "iopub.status.busy": "2024-09-06T19:38:53.229360Z", + "iopub.status.idle": "2024-09-06T19:38:55.301308Z", + "shell.execute_reply": "2024-09-06T19:38:55.300645Z" } }, "outputs": [ @@ -594,10 +594,10 @@ "id": "c18dd83b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:58.745759Z", - "iopub.status.busy": "2024-09-05T19:38:58.745328Z", - "iopub.status.idle": "2024-09-05T19:38:58.754011Z", - "shell.execute_reply": "2024-09-05T19:38:58.753467Z" + "iopub.execute_input": "2024-09-06T19:38:55.303915Z", + "iopub.status.busy": "2024-09-06T19:38:55.303372Z", + "iopub.status.idle": "2024-09-06T19:38:55.311571Z", + "shell.execute_reply": "2024-09-06T19:38:55.311093Z" } }, "outputs": [ @@ -633,10 +633,10 @@ "id": "fffa88f6-84d7-45fe-8214-0e22079a06d1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:58.756118Z", - "iopub.status.busy": "2024-09-05T19:38:58.755779Z", - "iopub.status.idle": "2024-09-05T19:39:01.611717Z", - "shell.execute_reply": "2024-09-05T19:39:01.611077Z" + "iopub.execute_input": "2024-09-06T19:38:55.313528Z", + "iopub.status.busy": "2024-09-06T19:38:55.313186Z", + "iopub.status.idle": "2024-09-06T19:38:58.079187Z", + "shell.execute_reply": "2024-09-06T19:38:58.078607Z" } }, "outputs": [ @@ -671,10 +671,10 @@ "id": "c1198575", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:01.613917Z", - "iopub.status.busy": "2024-09-05T19:39:01.613717Z", - "iopub.status.idle": "2024-09-05T19:39:01.617617Z", - "shell.execute_reply": "2024-09-05T19:39:01.617137Z" + "iopub.execute_input": "2024-09-06T19:38:58.081586Z", + "iopub.status.busy": "2024-09-06T19:38:58.081221Z", + "iopub.status.idle": "2024-09-06T19:38:58.084505Z", + "shell.execute_reply": "2024-09-06T19:38:58.083969Z" } }, "outputs": [ @@ -721,10 +721,10 @@ "id": "49161b19-7625-4fb7-add9-607d91a7eca1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:01.619758Z", - "iopub.status.busy": "2024-09-05T19:39:01.619426Z", - "iopub.status.idle": "2024-09-05T19:39:01.622958Z", - "shell.execute_reply": "2024-09-05T19:39:01.622500Z" + "iopub.execute_input": "2024-09-06T19:38:58.086650Z", + "iopub.status.busy": "2024-09-06T19:38:58.086312Z", + "iopub.status.idle": "2024-09-06T19:38:58.089596Z", + "shell.execute_reply": "2024-09-06T19:38:58.089116Z" } }, "outputs": [], @@ -769,10 +769,10 @@ "id": "d1a2c008", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:01.625218Z", - "iopub.status.busy": "2024-09-05T19:39:01.624881Z", - "iopub.status.idle": "2024-09-05T19:39:01.628607Z", - "shell.execute_reply": "2024-09-05T19:39:01.628173Z" + "iopub.execute_input": "2024-09-06T19:38:58.091573Z", + "iopub.status.busy": "2024-09-06T19:38:58.091252Z", + "iopub.status.idle": "2024-09-06T19:38:58.095249Z", + "shell.execute_reply": "2024-09-06T19:38:58.094671Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb b/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb index f25e1e63d..d7703f8af 100644 --- a/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/object_detection.ipynb @@ -70,10 +70,10 @@ "id": "0ba0dc70", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:04.529066Z", - "iopub.status.busy": "2024-09-05T19:39:04.528893Z", - "iopub.status.idle": "2024-09-05T19:39:05.764668Z", - "shell.execute_reply": "2024-09-05T19:39:05.764097Z" + "iopub.execute_input": "2024-09-06T19:39:00.696602Z", + "iopub.status.busy": "2024-09-06T19:39:00.696186Z", + "iopub.status.idle": "2024-09-06T19:39:01.907009Z", + "shell.execute_reply": "2024-09-06T19:39:01.906453Z" }, "nbsphinx": "hidden" }, @@ -83,7 +83,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -109,10 +109,10 @@ "id": "c90449c8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:05.767346Z", - "iopub.status.busy": "2024-09-05T19:39:05.766811Z", - "iopub.status.idle": "2024-09-05T19:39:06.974939Z", - "shell.execute_reply": "2024-09-05T19:39:06.974219Z" + "iopub.execute_input": "2024-09-06T19:39:01.909568Z", + "iopub.status.busy": "2024-09-06T19:39:01.909050Z", + "iopub.status.idle": "2024-09-06T19:39:04.631163Z", + "shell.execute_reply": "2024-09-06T19:39:04.630426Z" } }, "outputs": [], @@ -130,10 +130,10 @@ "id": "df8be4c6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:06.977709Z", - "iopub.status.busy": "2024-09-05T19:39:06.977293Z", - "iopub.status.idle": "2024-09-05T19:39:06.980536Z", - "shell.execute_reply": "2024-09-05T19:39:06.980078Z" + "iopub.execute_input": "2024-09-06T19:39:04.633881Z", + "iopub.status.busy": "2024-09-06T19:39:04.633499Z", + "iopub.status.idle": "2024-09-06T19:39:04.637616Z", + "shell.execute_reply": "2024-09-06T19:39:04.637024Z" } }, "outputs": [], @@ -169,10 +169,10 @@ "id": "2e9ffd6f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:06.982537Z", - "iopub.status.busy": "2024-09-05T19:39:06.982351Z", - "iopub.status.idle": "2024-09-05T19:39:06.989001Z", - "shell.execute_reply": "2024-09-05T19:39:06.988551Z" + "iopub.execute_input": "2024-09-06T19:39:04.639736Z", + "iopub.status.busy": "2024-09-06T19:39:04.639557Z", + "iopub.status.idle": "2024-09-06T19:39:04.646473Z", + "shell.execute_reply": "2024-09-06T19:39:04.646014Z" } }, "outputs": [], @@ -198,10 +198,10 @@ "id": "56705562", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:06.990912Z", - "iopub.status.busy": "2024-09-05T19:39:06.990730Z", - "iopub.status.idle": "2024-09-05T19:39:07.491100Z", - "shell.execute_reply": "2024-09-05T19:39:07.490495Z" + "iopub.execute_input": "2024-09-06T19:39:04.648396Z", + "iopub.status.busy": "2024-09-06T19:39:04.648219Z", + "iopub.status.idle": "2024-09-06T19:39:05.143459Z", + "shell.execute_reply": "2024-09-06T19:39:05.142840Z" }, "scrolled": true }, @@ -242,10 +242,10 @@ "id": "b08144d7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:07.494085Z", - "iopub.status.busy": "2024-09-05T19:39:07.493615Z", - "iopub.status.idle": "2024-09-05T19:39:07.499172Z", - "shell.execute_reply": "2024-09-05T19:39:07.498620Z" + "iopub.execute_input": "2024-09-06T19:39:05.146327Z", + "iopub.status.busy": "2024-09-06T19:39:05.146000Z", + "iopub.status.idle": "2024-09-06T19:39:05.151442Z", + "shell.execute_reply": "2024-09-06T19:39:05.150979Z" } }, "outputs": [ @@ -497,10 +497,10 @@ "id": "3d70bec6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:07.501404Z", - "iopub.status.busy": "2024-09-05T19:39:07.500976Z", - "iopub.status.idle": "2024-09-05T19:39:07.504945Z", - "shell.execute_reply": "2024-09-05T19:39:07.504506Z" + "iopub.execute_input": "2024-09-06T19:39:05.153485Z", + "iopub.status.busy": "2024-09-06T19:39:05.153173Z", + "iopub.status.idle": "2024-09-06T19:39:05.157137Z", + "shell.execute_reply": "2024-09-06T19:39:05.156658Z" } }, "outputs": [ @@ -557,10 +557,10 @@ "id": "4caa635d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:07.507284Z", - "iopub.status.busy": "2024-09-05T19:39:07.506712Z", - "iopub.status.idle": "2024-09-05T19:39:08.384414Z", - "shell.execute_reply": "2024-09-05T19:39:08.383806Z" + "iopub.execute_input": "2024-09-06T19:39:05.159200Z", + "iopub.status.busy": "2024-09-06T19:39:05.158859Z", + "iopub.status.idle": "2024-09-06T19:39:06.019168Z", + "shell.execute_reply": "2024-09-06T19:39:06.018545Z" } }, "outputs": [ @@ -616,10 +616,10 @@ "id": "a9b4c590", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:08.386698Z", - "iopub.status.busy": "2024-09-05T19:39:08.386502Z", - "iopub.status.idle": "2024-09-05T19:39:08.587093Z", - "shell.execute_reply": "2024-09-05T19:39:08.586454Z" + "iopub.execute_input": "2024-09-06T19:39:06.021668Z", + "iopub.status.busy": "2024-09-06T19:39:06.021221Z", + "iopub.status.idle": "2024-09-06T19:39:06.237090Z", + "shell.execute_reply": "2024-09-06T19:39:06.236553Z" } }, "outputs": [ @@ -627,14 +627,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Pruning 0 predictions out of 138 using threshold==0.0. These predictions are no longer considered as potential candidates for identifying label issues as their similarity with the given labels is no longer considered." - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" + "Pruning 0 predictions out of 138 using threshold==0.0. These predictions are no longer considered as potential candidates for identifying label issues as their similarity with the given labels is no longer considered.\n" ] }, { @@ -667,10 +660,10 @@ "id": "ffd9ebcc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:08.589453Z", - "iopub.status.busy": "2024-09-05T19:39:08.589096Z", - "iopub.status.idle": "2024-09-05T19:39:08.593402Z", - "shell.execute_reply": "2024-09-05T19:39:08.592837Z" + "iopub.execute_input": "2024-09-06T19:39:06.239343Z", + "iopub.status.busy": "2024-09-06T19:39:06.238930Z", + "iopub.status.idle": "2024-09-06T19:39:06.243194Z", + "shell.execute_reply": "2024-09-06T19:39:06.242735Z" } }, "outputs": [ @@ -707,10 +700,10 @@ "id": "4dd46d67", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:08.595644Z", - "iopub.status.busy": "2024-09-05T19:39:08.595324Z", - "iopub.status.idle": "2024-09-05T19:39:09.054015Z", - "shell.execute_reply": "2024-09-05T19:39:09.053402Z" + "iopub.execute_input": "2024-09-06T19:39:06.245282Z", + "iopub.status.busy": "2024-09-06T19:39:06.244951Z", + "iopub.status.idle": "2024-09-06T19:39:06.697627Z", + "shell.execute_reply": "2024-09-06T19:39:06.697015Z" } }, "outputs": [ @@ -769,10 +762,10 @@ "id": "ceec2394", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:09.057259Z", - "iopub.status.busy": "2024-09-05T19:39:09.056867Z", - "iopub.status.idle": "2024-09-05T19:39:09.390945Z", - "shell.execute_reply": "2024-09-05T19:39:09.390389Z" + "iopub.execute_input": "2024-09-06T19:39:06.700924Z", + "iopub.status.busy": "2024-09-06T19:39:06.700539Z", + "iopub.status.idle": "2024-09-06T19:39:07.035472Z", + "shell.execute_reply": "2024-09-06T19:39:07.034925Z" } }, "outputs": [ @@ -819,10 +812,10 @@ "id": "94f82b0d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:09.393790Z", - "iopub.status.busy": "2024-09-05T19:39:09.393435Z", - "iopub.status.idle": "2024-09-05T19:39:09.732820Z", - "shell.execute_reply": "2024-09-05T19:39:09.732244Z" + "iopub.execute_input": "2024-09-06T19:39:07.038382Z", + "iopub.status.busy": "2024-09-06T19:39:07.038001Z", + "iopub.status.idle": "2024-09-06T19:39:07.401507Z", + "shell.execute_reply": "2024-09-06T19:39:07.400918Z" } }, "outputs": [ @@ -869,10 +862,10 @@ "id": "1ea18c5d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:09.736269Z", - "iopub.status.busy": "2024-09-05T19:39:09.735858Z", - "iopub.status.idle": "2024-09-05T19:39:10.156424Z", - "shell.execute_reply": "2024-09-05T19:39:10.155802Z" + "iopub.execute_input": "2024-09-06T19:39:07.404511Z", + "iopub.status.busy": "2024-09-06T19:39:07.404090Z", + "iopub.status.idle": "2024-09-06T19:39:07.846501Z", + "shell.execute_reply": "2024-09-06T19:39:07.845952Z" } }, "outputs": [ @@ -932,10 +925,10 @@ "id": "7e770d23", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:10.161076Z", - "iopub.status.busy": "2024-09-05T19:39:10.160681Z", - "iopub.status.idle": "2024-09-05T19:39:10.609859Z", - "shell.execute_reply": "2024-09-05T19:39:10.609188Z" + "iopub.execute_input": "2024-09-06T19:39:07.851154Z", + "iopub.status.busy": "2024-09-06T19:39:07.850706Z", + "iopub.status.idle": "2024-09-06T19:39:08.296657Z", + "shell.execute_reply": "2024-09-06T19:39:08.296063Z" } }, "outputs": [ @@ -978,10 +971,10 @@ "id": "57e84a27", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:10.612839Z", - "iopub.status.busy": "2024-09-05T19:39:10.612663Z", - "iopub.status.idle": "2024-09-05T19:39:10.829289Z", - "shell.execute_reply": "2024-09-05T19:39:10.828816Z" + "iopub.execute_input": "2024-09-06T19:39:08.300087Z", + "iopub.status.busy": "2024-09-06T19:39:08.299623Z", + "iopub.status.idle": "2024-09-06T19:39:08.513354Z", + "shell.execute_reply": "2024-09-06T19:39:08.512755Z" } }, "outputs": [ @@ -1024,10 +1017,10 @@ "id": "0302818a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:10.831596Z", - "iopub.status.busy": "2024-09-05T19:39:10.831265Z", - "iopub.status.idle": "2024-09-05T19:39:11.014176Z", - "shell.execute_reply": "2024-09-05T19:39:11.013572Z" + "iopub.execute_input": "2024-09-06T19:39:08.515572Z", + "iopub.status.busy": "2024-09-06T19:39:08.515168Z", + "iopub.status.idle": "2024-09-06T19:39:08.694654Z", + "shell.execute_reply": "2024-09-06T19:39:08.694085Z" } }, "outputs": [ @@ -1074,10 +1067,10 @@ "id": "5cacec81-2adf-46a8-82c5-7ec0185d4356", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:11.016423Z", - "iopub.status.busy": "2024-09-05T19:39:11.016076Z", - "iopub.status.idle": "2024-09-05T19:39:11.018873Z", - "shell.execute_reply": "2024-09-05T19:39:11.018432Z" + "iopub.execute_input": "2024-09-06T19:39:08.697419Z", + "iopub.status.busy": "2024-09-06T19:39:08.697030Z", + "iopub.status.idle": "2024-09-06T19:39:08.699909Z", + "shell.execute_reply": "2024-09-06T19:39:08.699453Z" } }, "outputs": [], @@ -1097,10 +1090,10 @@ "id": "3335b8a3-d0b4-415a-a97d-c203088a124e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:11.020936Z", - "iopub.status.busy": "2024-09-05T19:39:11.020606Z", - "iopub.status.idle": "2024-09-05T19:39:11.923610Z", - "shell.execute_reply": "2024-09-05T19:39:11.922981Z" + "iopub.execute_input": "2024-09-06T19:39:08.701948Z", + "iopub.status.busy": "2024-09-06T19:39:08.701622Z", + "iopub.status.idle": "2024-09-06T19:39:09.635839Z", + "shell.execute_reply": "2024-09-06T19:39:09.635227Z" } }, "outputs": [ @@ -1179,10 +1172,10 @@ "id": "9d4b7677-6ebd-447d-b0a1-76e094686628", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:11.925987Z", - "iopub.status.busy": "2024-09-05T19:39:11.925773Z", - "iopub.status.idle": "2024-09-05T19:39:12.101177Z", - "shell.execute_reply": "2024-09-05T19:39:12.100675Z" + "iopub.execute_input": "2024-09-06T19:39:09.637949Z", + "iopub.status.busy": "2024-09-06T19:39:09.637773Z", + "iopub.status.idle": "2024-09-06T19:39:09.767317Z", + "shell.execute_reply": "2024-09-06T19:39:09.766833Z" } }, "outputs": [ @@ -1221,10 +1214,10 @@ "id": "59d7ee39-3785-434b-8680-9133014851cd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:12.103362Z", - "iopub.status.busy": "2024-09-05T19:39:12.103006Z", - "iopub.status.idle": "2024-09-05T19:39:12.232243Z", - "shell.execute_reply": "2024-09-05T19:39:12.231719Z" + "iopub.execute_input": "2024-09-06T19:39:09.769238Z", + "iopub.status.busy": "2024-09-06T19:39:09.769067Z", + "iopub.status.idle": "2024-09-06T19:39:09.969227Z", + "shell.execute_reply": "2024-09-06T19:39:09.968617Z" } }, "outputs": [], @@ -1273,10 +1266,10 @@ "id": "47b6a8ff-7a58-4a1f-baee-e6cfe7a85a6d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:12.234678Z", - "iopub.status.busy": "2024-09-05T19:39:12.234336Z", - "iopub.status.idle": "2024-09-05T19:39:12.941539Z", - "shell.execute_reply": "2024-09-05T19:39:12.940835Z" + "iopub.execute_input": "2024-09-06T19:39:09.971377Z", + "iopub.status.busy": "2024-09-06T19:39:09.971032Z", + "iopub.status.idle": "2024-09-06T19:39:10.691109Z", + "shell.execute_reply": "2024-09-06T19:39:10.690570Z" } }, "outputs": [ @@ -1358,10 +1351,10 @@ "id": "8ce74938", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:12.943960Z", - "iopub.status.busy": "2024-09-05T19:39:12.943615Z", - "iopub.status.idle": "2024-09-05T19:39:12.947337Z", - "shell.execute_reply": "2024-09-05T19:39:12.946788Z" + "iopub.execute_input": "2024-09-06T19:39:10.693528Z", + "iopub.status.busy": "2024-09-06T19:39:10.693149Z", + "iopub.status.idle": "2024-09-06T19:39:10.697005Z", + "shell.execute_reply": "2024-09-06T19:39:10.696512Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/outliers.ipynb b/master/.doctrees/nbsphinx/tutorials/outliers.ipynb index f57af3305..ab02f6a16 100644 --- a/master/.doctrees/nbsphinx/tutorials/outliers.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/outliers.ipynb @@ -109,10 +109,10 @@ "id": "2bbebfc8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:15.405392Z", - "iopub.status.busy": "2024-09-05T19:39:15.405034Z", - "iopub.status.idle": "2024-09-05T19:39:18.302373Z", - "shell.execute_reply": "2024-09-05T19:39:18.301795Z" + "iopub.execute_input": "2024-09-06T19:39:13.100046Z", + "iopub.status.busy": "2024-09-06T19:39:13.099622Z", + "iopub.status.idle": "2024-09-06T19:39:15.925691Z", + "shell.execute_reply": "2024-09-06T19:39:15.925058Z" }, "nbsphinx": "hidden" }, @@ -125,7 +125,7 @@ "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -159,10 +159,10 @@ "id": "4396f544", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:18.305069Z", - "iopub.status.busy": "2024-09-05T19:39:18.304571Z", - "iopub.status.idle": "2024-09-05T19:39:18.636404Z", - "shell.execute_reply": "2024-09-05T19:39:18.635775Z" + "iopub.execute_input": "2024-09-06T19:39:15.928762Z", + "iopub.status.busy": "2024-09-06T19:39:15.928196Z", + "iopub.status.idle": "2024-09-06T19:39:16.252610Z", + "shell.execute_reply": "2024-09-06T19:39:16.252054Z" } }, "outputs": [], @@ -188,10 +188,10 @@ "id": "3792f82e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:18.639073Z", - "iopub.status.busy": "2024-09-05T19:39:18.638746Z", - "iopub.status.idle": "2024-09-05T19:39:18.643058Z", - "shell.execute_reply": "2024-09-05T19:39:18.642503Z" + "iopub.execute_input": "2024-09-06T19:39:16.255233Z", + "iopub.status.busy": "2024-09-06T19:39:16.254751Z", + "iopub.status.idle": "2024-09-06T19:39:16.259089Z", + "shell.execute_reply": "2024-09-06T19:39:16.258660Z" }, "nbsphinx": "hidden" }, @@ -225,10 +225,10 @@ "id": "fd853a54", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:18.645337Z", - "iopub.status.busy": "2024-09-05T19:39:18.644989Z", - "iopub.status.idle": "2024-09-05T19:39:23.136533Z", - "shell.execute_reply": "2024-09-05T19:39:23.136022Z" + "iopub.execute_input": "2024-09-06T19:39:16.261376Z", + "iopub.status.busy": "2024-09-06T19:39:16.260945Z", + "iopub.status.idle": "2024-09-06T19:39:23.300858Z", + "shell.execute_reply": "2024-09-06T19:39:23.300244Z" } }, "outputs": [ @@ -252,7 +252,7 @@ "output_type": "stream", "text": [ "\r", - " 1%| | 917504/170498071 [00:00<00:20, 8230282.28it/s]" + " 0%| | 32768/170498071 [00:00<09:50, 288460.96it/s]" ] }, { @@ -260,7 +260,7 @@ "output_type": "stream", "text": [ "\r", - " 6%|▌ | 10518528/170498071 [00:00<00:02, 57525326.14it/s]" + " 0%| | 229376/170498071 [00:00<02:31, 1124759.70it/s]" ] }, { @@ -268,7 +268,7 @@ "output_type": "stream", "text": [ "\r", - " 12%|█▏ | 21200896/170498071 [00:00<00:01, 79443214.95it/s]" + " 1%| | 884736/170498071 [00:00<00:52, 3225591.40it/s]" ] }, { @@ -276,7 +276,7 @@ "output_type": "stream", "text": [ "\r", - " 19%|█▊ | 31883264/170498071 [00:00<00:01, 90066862.77it/s]" + " 2%|▏ | 3571712/170498071 [00:00<00:14, 11574707.14it/s]" ] }, { @@ -284,7 +284,7 @@ "output_type": "stream", "text": [ "\r", - " 25%|██▌ | 42795008/170498071 [00:00<00:01, 96847189.42it/s]" + " 6%|▌ | 9633792/170498071 [00:00<00:06, 25807611.79it/s]" ] }, { @@ -292,7 +292,7 @@ "output_type": "stream", "text": [ "\r", - " 31%|███▏ | 53608448/170498071 [00:00<00:01, 100648722.32it/s]" + " 9%|▉ | 15892480/170498071 [00:00<00:04, 35393042.76it/s]" ] }, { @@ -300,7 +300,7 @@ "output_type": "stream", "text": [ "\r", - " 38%|███▊ | 64421888/170498071 [00:00<00:01, 103069662.64it/s]" + " 13%|█▎ | 22052864/170498071 [00:00<00:03, 41375940.12it/s]" ] }, { @@ -308,7 +308,7 @@ "output_type": "stream", "text": [ "\r", - " 44%|████▍ | 75497472/170498071 [00:00<00:00, 105497848.58it/s]" + " 16%|█▋ | 27918336/170498071 [00:00<00:03, 46336247.02it/s]" ] }, { @@ -316,7 +316,7 @@ "output_type": "stream", "text": [ "\r", - " 51%|█████ | 86540288/170498071 [00:00<00:00, 106981473.95it/s]" + " 19%|█▉ | 32604160/170498071 [00:01<00:03, 45410241.06it/s]" ] }, { @@ -324,7 +324,7 @@ "output_type": "stream", "text": [ "\r", - " 57%|█████▋ | 97484800/170498071 [00:01<00:00, 107701030.20it/s]" + " 22%|██▏ | 37978112/170498071 [00:01<00:02, 46512554.13it/s]" ] }, { @@ -332,7 +332,7 @@ "output_type": "stream", "text": [ "\r", - " 64%|██████▎ | 108363776/170498071 [00:01<00:00, 107950290.42it/s]" + " 26%|██▌ | 44072960/170498071 [00:01<00:02, 50196826.35it/s]" ] }, { @@ -340,7 +340,7 @@ "output_type": "stream", "text": [ "\r", - " 70%|██████▉ | 119177216/170498071 [00:01<00:00, 106306696.89it/s]" + " 29%|██▉ | 49217536/170498071 [00:01<00:02, 50515326.91it/s]" ] }, { @@ -348,7 +348,7 @@ "output_type": "stream", "text": [ "\r", - " 76%|███████▌ | 129826816/170498071 [00:01<00:00, 105708288.67it/s]" + " 32%|███▏ | 54296576/170498071 [00:01<00:02, 49331301.44it/s]" ] }, { @@ -356,7 +356,7 @@ "output_type": "stream", "text": [ "\r", - " 82%|████████▏ | 140410880/170498071 [00:01<00:00, 105156306.35it/s]" + " 35%|███▌ | 60129280/170498071 [00:01<00:02, 51745509.08it/s]" ] }, { @@ -364,7 +364,7 @@ "output_type": "stream", "text": [ "\r", - " 89%|████████▉ | 151355392/170498071 [00:01<00:00, 106351362.25it/s]" + " 38%|███▊ | 65339392/170498071 [00:01<00:02, 51498978.62it/s]" ] }, { @@ -372,7 +372,7 @@ "output_type": "stream", "text": [ "\r", - " 95%|█████████▌| 162004992/170498071 [00:01<00:00, 105346005.50it/s]" + " 41%|████▏ | 70516736/170498071 [00:01<00:01, 50172708.54it/s]" ] }, { @@ -380,7 +380,151 @@ "output_type": "stream", "text": [ "\r", - "100%|██████████| 170498071/170498071 [00:01<00:00, 99832064.92it/s] " + " 45%|████▍ | 76251136/170498071 [00:01<00:01, 52173671.62it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 48%|████▊ | 81559552/170498071 [00:01<00:01, 52429909.15it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 51%|█████ | 86835200/170498071 [00:02<00:01, 50316420.17it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 54%|█████▍ | 92438528/170498071 [00:02<00:01, 51729464.30it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 57%|█████▋ | 97878016/170498071 [00:02<00:01, 52469802.74it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 61%|██████ | 103153664/170498071 [00:02<00:01, 51263628.20it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 64%|██████▎ | 108396544/170498071 [00:02<00:01, 51439851.19it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 67%|██████▋ | 114130944/170498071 [00:02<00:01, 53113973.23it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 70%|███████ | 119472128/170498071 [00:02<00:00, 51879482.02it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 73%|███████▎ | 124682240/170498071 [00:02<00:00, 50047274.18it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 77%|███████▋ | 130547712/170498071 [00:02<00:00, 52494107.90it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 80%|███████▉ | 135823360/170498071 [00:03<00:00, 52004524.51it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 83%|████████▎ | 141066240/170498071 [00:03<00:00, 50983301.18it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 86%|████████▌ | 146636800/170498071 [00:03<00:00, 52034590.57it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 89%|████████▉ | 151879680/170498071 [00:03<00:00, 52140968.39it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 92%|█████████▏| 157122560/170498071 [00:03<00:00, 50962142.96it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 95%|█████████▌| 162463744/170498071 [00:03<00:00, 51228143.58it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 99%|█████████▊| 168329216/170498071 [00:03<00:00, 53366850.10it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + "100%|██████████| 170498071/170498071 [00:03<00:00, 46456493.64it/s]" ] }, { @@ -498,10 +642,10 @@ "id": "9b64e0aa", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:23.138923Z", - "iopub.status.busy": "2024-09-05T19:39:23.138570Z", - "iopub.status.idle": "2024-09-05T19:39:23.143265Z", - "shell.execute_reply": "2024-09-05T19:39:23.142817Z" + "iopub.execute_input": "2024-09-06T19:39:23.303328Z", + "iopub.status.busy": "2024-09-06T19:39:23.302943Z", + "iopub.status.idle": "2024-09-06T19:39:23.307938Z", + "shell.execute_reply": "2024-09-06T19:39:23.307365Z" }, "nbsphinx": "hidden" }, @@ -552,10 +696,10 @@ "id": "a00aa3ed", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:23.145648Z", - "iopub.status.busy": "2024-09-05T19:39:23.145075Z", - "iopub.status.idle": "2024-09-05T19:39:23.692735Z", - "shell.execute_reply": "2024-09-05T19:39:23.692010Z" + "iopub.execute_input": "2024-09-06T19:39:23.310122Z", + "iopub.status.busy": "2024-09-06T19:39:23.309822Z", + "iopub.status.idle": "2024-09-06T19:39:23.850296Z", + "shell.execute_reply": "2024-09-06T19:39:23.849793Z" } }, "outputs": [ @@ -588,10 +732,10 @@ "id": "41e5cb6b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:23.695080Z", - "iopub.status.busy": "2024-09-05T19:39:23.694701Z", - "iopub.status.idle": "2024-09-05T19:39:24.214620Z", - "shell.execute_reply": "2024-09-05T19:39:24.214041Z" + "iopub.execute_input": "2024-09-06T19:39:23.852466Z", + "iopub.status.busy": "2024-09-06T19:39:23.852115Z", + "iopub.status.idle": "2024-09-06T19:39:24.358610Z", + "shell.execute_reply": "2024-09-06T19:39:24.358030Z" } }, "outputs": [ @@ -629,10 +773,10 @@ "id": "1cf25354", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:24.216960Z", - "iopub.status.busy": "2024-09-05T19:39:24.216573Z", - "iopub.status.idle": "2024-09-05T19:39:24.220264Z", - "shell.execute_reply": "2024-09-05T19:39:24.219778Z" + "iopub.execute_input": "2024-09-06T19:39:24.360839Z", + "iopub.status.busy": "2024-09-06T19:39:24.360464Z", + "iopub.status.idle": "2024-09-06T19:39:24.363781Z", + "shell.execute_reply": "2024-09-06T19:39:24.363295Z" } }, "outputs": [], @@ -655,17 +799,17 @@ "id": "85a58d41", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:24.222316Z", - "iopub.status.busy": "2024-09-05T19:39:24.221972Z", - "iopub.status.idle": "2024-09-05T19:39:36.692173Z", - "shell.execute_reply": "2024-09-05T19:39:36.691528Z" + "iopub.execute_input": "2024-09-06T19:39:24.365783Z", + "iopub.status.busy": "2024-09-06T19:39:24.365442Z", + "iopub.status.idle": "2024-09-06T19:39:36.716347Z", + "shell.execute_reply": "2024-09-06T19:39:36.715721Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7c531849220347c4bbd1314510f1888e", + "model_id": "3ceaa047f5ed4611b974d3fa414e2507", "version_major": 2, "version_minor": 0 }, @@ -724,10 +868,10 @@ "id": "feb0f519", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:36.694834Z", - "iopub.status.busy": "2024-09-05T19:39:36.694331Z", - "iopub.status.idle": "2024-09-05T19:39:38.805431Z", - "shell.execute_reply": "2024-09-05T19:39:38.804752Z" + "iopub.execute_input": "2024-09-06T19:39:36.718898Z", + "iopub.status.busy": "2024-09-06T19:39:36.718487Z", + "iopub.status.idle": "2024-09-06T19:39:38.825920Z", + "shell.execute_reply": "2024-09-06T19:39:38.825316Z" } }, "outputs": [ @@ -771,10 +915,10 @@ "id": "089d5860", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:38.808473Z", - "iopub.status.busy": "2024-09-05T19:39:38.807868Z", - "iopub.status.idle": "2024-09-05T19:39:39.068245Z", - "shell.execute_reply": "2024-09-05T19:39:39.067640Z" + "iopub.execute_input": "2024-09-06T19:39:38.828812Z", + "iopub.status.busy": "2024-09-06T19:39:38.828333Z", + "iopub.status.idle": "2024-09-06T19:39:39.084401Z", + "shell.execute_reply": "2024-09-06T19:39:39.083812Z" } }, "outputs": [ @@ -810,10 +954,10 @@ "id": "78b1951c", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:39.070920Z", - "iopub.status.busy": "2024-09-05T19:39:39.070467Z", - "iopub.status.idle": "2024-09-05T19:39:39.749637Z", - "shell.execute_reply": "2024-09-05T19:39:39.749023Z" + "iopub.execute_input": "2024-09-06T19:39:39.087122Z", + "iopub.status.busy": "2024-09-06T19:39:39.086611Z", + "iopub.status.idle": "2024-09-06T19:39:39.754107Z", + "shell.execute_reply": "2024-09-06T19:39:39.753534Z" } }, "outputs": [ @@ -863,10 +1007,10 @@ "id": "e9dff81b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:39.752728Z", - "iopub.status.busy": "2024-09-05T19:39:39.752257Z", - "iopub.status.idle": "2024-09-05T19:39:40.092896Z", - "shell.execute_reply": "2024-09-05T19:39:40.092212Z" + "iopub.execute_input": "2024-09-06T19:39:39.756937Z", + "iopub.status.busy": "2024-09-06T19:39:39.756623Z", + "iopub.status.idle": "2024-09-06T19:39:40.092242Z", + "shell.execute_reply": "2024-09-06T19:39:40.091655Z" } }, "outputs": [ @@ -914,10 +1058,10 @@ "id": "616769f8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:40.095138Z", - "iopub.status.busy": "2024-09-05T19:39:40.094925Z", - "iopub.status.idle": "2024-09-05T19:39:40.341300Z", - "shell.execute_reply": "2024-09-05T19:39:40.340684Z" + "iopub.execute_input": "2024-09-06T19:39:40.094221Z", + "iopub.status.busy": "2024-09-06T19:39:40.094058Z", + "iopub.status.idle": "2024-09-06T19:39:40.335215Z", + "shell.execute_reply": "2024-09-06T19:39:40.334660Z" } }, "outputs": [ @@ -973,10 +1117,10 @@ "id": "40fed4ef", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:40.344290Z", - "iopub.status.busy": "2024-09-05T19:39:40.343761Z", - "iopub.status.idle": "2024-09-05T19:39:40.431779Z", - "shell.execute_reply": "2024-09-05T19:39:40.431283Z" + "iopub.execute_input": "2024-09-06T19:39:40.337846Z", + "iopub.status.busy": "2024-09-06T19:39:40.337645Z", + "iopub.status.idle": "2024-09-06T19:39:40.434888Z", + "shell.execute_reply": "2024-09-06T19:39:40.434380Z" } }, "outputs": [], @@ -997,10 +1141,10 @@ "id": "89f9db72", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:40.434261Z", - "iopub.status.busy": "2024-09-05T19:39:40.433923Z", - "iopub.status.idle": "2024-09-05T19:39:50.771833Z", - "shell.execute_reply": "2024-09-05T19:39:50.771095Z" + "iopub.execute_input": "2024-09-06T19:39:40.437135Z", + "iopub.status.busy": "2024-09-06T19:39:40.436969Z", + "iopub.status.idle": "2024-09-06T19:39:50.846992Z", + "shell.execute_reply": "2024-09-06T19:39:50.846365Z" } }, "outputs": [ @@ -1037,10 +1181,10 @@ "id": "874c885a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:50.774513Z", - "iopub.status.busy": "2024-09-05T19:39:50.774240Z", - "iopub.status.idle": "2024-09-05T19:39:53.048664Z", - "shell.execute_reply": "2024-09-05T19:39:53.048057Z" + "iopub.execute_input": "2024-09-06T19:39:50.849274Z", + "iopub.status.busy": "2024-09-06T19:39:50.849079Z", + "iopub.status.idle": "2024-09-06T19:39:53.085840Z", + "shell.execute_reply": "2024-09-06T19:39:53.085209Z" } }, "outputs": [ @@ -1071,10 +1215,10 @@ "id": "e110fc4b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:53.051447Z", - "iopub.status.busy": "2024-09-05T19:39:53.051056Z", - "iopub.status.idle": "2024-09-05T19:39:53.260971Z", - "shell.execute_reply": "2024-09-05T19:39:53.260424Z" + "iopub.execute_input": "2024-09-06T19:39:53.088386Z", + "iopub.status.busy": "2024-09-06T19:39:53.087986Z", + "iopub.status.idle": "2024-09-06T19:39:53.295938Z", + "shell.execute_reply": "2024-09-06T19:39:53.295309Z" } }, "outputs": [], @@ -1088,10 +1232,10 @@ "id": "85b60cbf", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:53.263397Z", - "iopub.status.busy": "2024-09-05T19:39:53.263043Z", - "iopub.status.idle": "2024-09-05T19:39:53.266100Z", - "shell.execute_reply": "2024-09-05T19:39:53.265661Z" + "iopub.execute_input": "2024-09-06T19:39:53.298578Z", + "iopub.status.busy": "2024-09-06T19:39:53.298149Z", + "iopub.status.idle": "2024-09-06T19:39:53.301396Z", + "shell.execute_reply": "2024-09-06T19:39:53.300847Z" } }, "outputs": [], @@ -1129,10 +1273,10 @@ "id": "17f96fa6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:53.268739Z", - "iopub.status.busy": "2024-09-05T19:39:53.267783Z", - "iopub.status.idle": "2024-09-05T19:39:53.276580Z", - "shell.execute_reply": "2024-09-05T19:39:53.276119Z" + "iopub.execute_input": "2024-09-06T19:39:53.303545Z", + "iopub.status.busy": "2024-09-06T19:39:53.303235Z", + "iopub.status.idle": "2024-09-06T19:39:53.311553Z", + "shell.execute_reply": "2024-09-06T19:39:53.311013Z" }, "nbsphinx": "hidden" }, @@ -1177,7 +1321,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "1349f610634f47e3a436b32454886eaf": { + "2a68a2d432424faba9fe0b5e6944b5e9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1230,25 +1374,47 @@ "width": null } }, - "17b81af4f234437a8808eadad363b86b": { + "3ceaa047f5ed4611b974d3fa414e2507": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_c213a022f9994559b2b3155f2f77656c", + "IPY_MODEL_d04af2b6417a48e88c2bb6ac7a1a352f", + "IPY_MODEL_d330cb5a3ec245d28c20140821dff479" + ], + "layout": "IPY_MODEL_8965ea1fe0204e49bbde2ee4ed6b5dbe", + "tabbable": null, + "tooltip": null + } + }, + "653de3cf6239488fa0adf55f2a1ae049": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" } }, - "1faec7121f484abdb6d2297ca62c549d": { + "8965ea1fe0204e49bbde2ee4ed6b5dbe": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1301,7 +1467,7 @@ "width": null } }, - "26c77578263941ad9a13a20bef319656": { + "b06f361a24974d5a8b8c89476e47f817": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1354,54 +1520,7 @@ "width": null } }, - "39aa8065c5b8424498ce8391b1a41734": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_1faec7121f484abdb6d2297ca62c549d", - "placeholder": "​", - "style": "IPY_MODEL_810d42e3457741f5879220bcee73da3b", - "tabbable": null, - "tooltip": null, - "value": "model.safetensors: 100%" - } - }, - "7c531849220347c4bbd1314510f1888e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_39aa8065c5b8424498ce8391b1a41734", - "IPY_MODEL_9ebe6590bdfb470397e8cdde6f7f6b02", - "IPY_MODEL_b2a369aac2ff425a88c2e810df948da8" - ], - "layout": "IPY_MODEL_f8dbae4a023d4586b20790fd6be925eb", - "tabbable": null, - "tooltip": null - } - }, - "810d42e3457741f5879220bcee73da3b": { + "b895588a207f4f0ca89d7c4764c3d066": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1419,49 +1538,7 @@ "text_color": null } }, - "9cc64681cf4a45ae867cf79d8b667320": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "9ebe6590bdfb470397e8cdde6f7f6b02": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_26c77578263941ad9a13a20bef319656", - "max": 102469840.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_9cc64681cf4a45ae867cf79d8b667320", - "tabbable": null, - "tooltip": null, - "value": 102469840.0 - } - }, - "b2a369aac2ff425a88c2e810df948da8": { + "c213a022f9994559b2b3155f2f77656c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1476,15 +1553,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1349f610634f47e3a436b32454886eaf", + "layout": "IPY_MODEL_ccda1205dcc748f99c76cf1800b182ef", "placeholder": "​", - "style": "IPY_MODEL_17b81af4f234437a8808eadad363b86b", + "style": "IPY_MODEL_b895588a207f4f0ca89d7c4764c3d066", "tabbable": null, "tooltip": null, - "value": " 102M/102M [00:00<00:00, 257MB/s]" + "value": "model.safetensors: 100%" } }, - "f8dbae4a023d4586b20790fd6be925eb": { + "ccda1205dcc748f99c76cf1800b182ef": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1536,6 +1613,73 @@ "visibility": null, "width": null } + }, + "cd03cf3d325849b9a2597fce8db90de1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "d04af2b6417a48e88c2bb6ac7a1a352f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_2a68a2d432424faba9fe0b5e6944b5e9", + "max": 102469840.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_653de3cf6239488fa0adf55f2a1ae049", + "tabbable": null, + "tooltip": null, + "value": 102469840.0 + } + }, + "d330cb5a3ec245d28c20140821dff479": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b06f361a24974d5a8b8c89476e47f817", + "placeholder": "​", + "style": "IPY_MODEL_cd03cf3d325849b9a2597fce8db90de1", + "tabbable": null, + "tooltip": null, + "value": " 102M/102M [00:00<00:00, 304MB/s]" + } } }, "version_major": 2, diff --git a/master/.doctrees/nbsphinx/tutorials/regression.ipynb b/master/.doctrees/nbsphinx/tutorials/regression.ipynb index f384516c7..4e72a9c31 100644 --- a/master/.doctrees/nbsphinx/tutorials/regression.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/regression.ipynb @@ -102,10 +102,10 @@ "id": "2e1af7d8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:57.424289Z", - "iopub.status.busy": "2024-09-05T19:39:57.424123Z", - "iopub.status.idle": "2024-09-05T19:39:58.655592Z", - "shell.execute_reply": "2024-09-05T19:39:58.655038Z" + "iopub.execute_input": "2024-09-06T19:39:57.671183Z", + "iopub.status.busy": "2024-09-06T19:39:57.671012Z", + "iopub.status.idle": "2024-09-06T19:39:58.889426Z", + "shell.execute_reply": "2024-09-06T19:39:58.888863Z" }, "nbsphinx": "hidden" }, @@ -116,7 +116,7 @@ "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -142,10 +142,10 @@ "id": "4fb10b8f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.658099Z", - "iopub.status.busy": "2024-09-05T19:39:58.657787Z", - "iopub.status.idle": "2024-09-05T19:39:58.676619Z", - "shell.execute_reply": "2024-09-05T19:39:58.676046Z" + "iopub.execute_input": "2024-09-06T19:39:58.892009Z", + "iopub.status.busy": "2024-09-06T19:39:58.891558Z", + "iopub.status.idle": "2024-09-06T19:39:58.909420Z", + "shell.execute_reply": "2024-09-06T19:39:58.908966Z" } }, "outputs": [], @@ -164,10 +164,10 @@ "id": "284dc264", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.679179Z", - "iopub.status.busy": "2024-09-05T19:39:58.678732Z", - "iopub.status.idle": "2024-09-05T19:39:58.681876Z", - "shell.execute_reply": "2024-09-05T19:39:58.681391Z" + "iopub.execute_input": "2024-09-06T19:39:58.911380Z", + "iopub.status.busy": "2024-09-06T19:39:58.911122Z", + "iopub.status.idle": "2024-09-06T19:39:58.914071Z", + "shell.execute_reply": "2024-09-06T19:39:58.913630Z" }, "nbsphinx": "hidden" }, @@ -198,10 +198,10 @@ "id": "0f7450db", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.684044Z", - "iopub.status.busy": "2024-09-05T19:39:58.683742Z", - "iopub.status.idle": "2024-09-05T19:39:58.780574Z", - "shell.execute_reply": "2024-09-05T19:39:58.779978Z" + "iopub.execute_input": "2024-09-06T19:39:58.916066Z", + "iopub.status.busy": "2024-09-06T19:39:58.915883Z", + "iopub.status.idle": "2024-09-06T19:39:59.147435Z", + "shell.execute_reply": "2024-09-06T19:39:59.146903Z" } }, "outputs": [ @@ -374,10 +374,10 @@ "id": "55513fed", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.782788Z", - "iopub.status.busy": "2024-09-05T19:39:58.782453Z", - "iopub.status.idle": "2024-09-05T19:39:58.968491Z", - "shell.execute_reply": "2024-09-05T19:39:58.967817Z" + "iopub.execute_input": "2024-09-06T19:39:59.149566Z", + "iopub.status.busy": "2024-09-06T19:39:59.149370Z", + "iopub.status.idle": "2024-09-06T19:39:59.331007Z", + "shell.execute_reply": "2024-09-06T19:39:59.330438Z" }, "nbsphinx": "hidden" }, @@ -417,10 +417,10 @@ "id": "df5a0f59", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.970900Z", - "iopub.status.busy": "2024-09-05T19:39:58.970711Z", - "iopub.status.idle": "2024-09-05T19:39:59.181624Z", - "shell.execute_reply": "2024-09-05T19:39:59.181029Z" + "iopub.execute_input": "2024-09-06T19:39:59.333486Z", + "iopub.status.busy": "2024-09-06T19:39:59.333040Z", + "iopub.status.idle": "2024-09-06T19:39:59.576590Z", + "shell.execute_reply": "2024-09-06T19:39:59.575968Z" } }, "outputs": [ @@ -456,10 +456,10 @@ "id": "7af78a8a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.183736Z", - "iopub.status.busy": "2024-09-05T19:39:59.183554Z", - "iopub.status.idle": "2024-09-05T19:39:59.187818Z", - "shell.execute_reply": "2024-09-05T19:39:59.187379Z" + "iopub.execute_input": "2024-09-06T19:39:59.578938Z", + "iopub.status.busy": "2024-09-06T19:39:59.578553Z", + "iopub.status.idle": "2024-09-06T19:39:59.582923Z", + "shell.execute_reply": "2024-09-06T19:39:59.582473Z" } }, "outputs": [], @@ -477,10 +477,10 @@ "id": "9556c624", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.189662Z", - "iopub.status.busy": "2024-09-05T19:39:59.189487Z", - "iopub.status.idle": "2024-09-05T19:39:59.195334Z", - "shell.execute_reply": "2024-09-05T19:39:59.194907Z" + "iopub.execute_input": "2024-09-06T19:39:59.584759Z", + "iopub.status.busy": "2024-09-06T19:39:59.584580Z", + "iopub.status.idle": "2024-09-06T19:39:59.590790Z", + "shell.execute_reply": "2024-09-06T19:39:59.590351Z" } }, "outputs": [], @@ -527,10 +527,10 @@ "id": "3c2f1ccc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.197263Z", - "iopub.status.busy": "2024-09-05T19:39:59.197091Z", - "iopub.status.idle": "2024-09-05T19:39:59.199733Z", - "shell.execute_reply": "2024-09-05T19:39:59.199275Z" + "iopub.execute_input": "2024-09-06T19:39:59.592686Z", + "iopub.status.busy": "2024-09-06T19:39:59.592515Z", + "iopub.status.idle": "2024-09-06T19:39:59.595225Z", + "shell.execute_reply": "2024-09-06T19:39:59.594766Z" } }, "outputs": [], @@ -545,10 +545,10 @@ "id": "7e1b7860", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.201738Z", - "iopub.status.busy": "2024-09-05T19:39:59.201336Z", - "iopub.status.idle": "2024-09-05T19:40:08.299512Z", - "shell.execute_reply": "2024-09-05T19:40:08.298965Z" + "iopub.execute_input": "2024-09-06T19:39:59.597032Z", + "iopub.status.busy": "2024-09-06T19:39:59.596865Z", + "iopub.status.idle": "2024-09-06T19:40:08.597697Z", + "shell.execute_reply": "2024-09-06T19:40:08.597120Z" } }, "outputs": [], @@ -572,10 +572,10 @@ "id": "f407bd69", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.302415Z", - "iopub.status.busy": "2024-09-05T19:40:08.301779Z", - "iopub.status.idle": "2024-09-05T19:40:08.309417Z", - "shell.execute_reply": "2024-09-05T19:40:08.308954Z" + "iopub.execute_input": "2024-09-06T19:40:08.600635Z", + "iopub.status.busy": "2024-09-06T19:40:08.599991Z", + "iopub.status.idle": "2024-09-06T19:40:08.607726Z", + "shell.execute_reply": "2024-09-06T19:40:08.607259Z" } }, "outputs": [ @@ -678,10 +678,10 @@ "id": "f7385336", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.311541Z", - "iopub.status.busy": "2024-09-05T19:40:08.311201Z", - "iopub.status.idle": "2024-09-05T19:40:08.314649Z", - "shell.execute_reply": "2024-09-05T19:40:08.314198Z" + "iopub.execute_input": "2024-09-06T19:40:08.609816Z", + "iopub.status.busy": "2024-09-06T19:40:08.609470Z", + "iopub.status.idle": "2024-09-06T19:40:08.613036Z", + "shell.execute_reply": "2024-09-06T19:40:08.612542Z" } }, "outputs": [], @@ -696,10 +696,10 @@ "id": "59fc3091", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.316646Z", - "iopub.status.busy": "2024-09-05T19:40:08.316310Z", - "iopub.status.idle": "2024-09-05T19:40:08.319658Z", - "shell.execute_reply": "2024-09-05T19:40:08.319198Z" + "iopub.execute_input": "2024-09-06T19:40:08.615042Z", + "iopub.status.busy": "2024-09-06T19:40:08.614643Z", + "iopub.status.idle": "2024-09-06T19:40:08.618056Z", + "shell.execute_reply": "2024-09-06T19:40:08.617486Z" } }, "outputs": [ @@ -734,10 +734,10 @@ "id": "00949977", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.321765Z", - "iopub.status.busy": "2024-09-05T19:40:08.321376Z", - "iopub.status.idle": "2024-09-05T19:40:08.324503Z", - "shell.execute_reply": "2024-09-05T19:40:08.324037Z" + "iopub.execute_input": "2024-09-06T19:40:08.620104Z", + "iopub.status.busy": "2024-09-06T19:40:08.619791Z", + "iopub.status.idle": "2024-09-06T19:40:08.622907Z", + "shell.execute_reply": "2024-09-06T19:40:08.622416Z" } }, "outputs": [], @@ -756,10 +756,10 @@ "id": "b6c1ae3a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.326471Z", - "iopub.status.busy": "2024-09-05T19:40:08.326155Z", - "iopub.status.idle": "2024-09-05T19:40:08.333988Z", - "shell.execute_reply": "2024-09-05T19:40:08.333552Z" + "iopub.execute_input": "2024-09-06T19:40:08.624768Z", + "iopub.status.busy": "2024-09-06T19:40:08.624594Z", + "iopub.status.idle": "2024-09-06T19:40:08.632747Z", + "shell.execute_reply": "2024-09-06T19:40:08.632288Z" } }, "outputs": [ @@ -883,10 +883,10 @@ "id": "9131d82d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.336061Z", - "iopub.status.busy": "2024-09-05T19:40:08.335706Z", - "iopub.status.idle": "2024-09-05T19:40:08.338225Z", - "shell.execute_reply": "2024-09-05T19:40:08.337767Z" + "iopub.execute_input": "2024-09-06T19:40:08.634564Z", + "iopub.status.busy": "2024-09-06T19:40:08.634392Z", + "iopub.status.idle": "2024-09-06T19:40:08.637116Z", + "shell.execute_reply": "2024-09-06T19:40:08.636642Z" }, "nbsphinx": "hidden" }, @@ -921,10 +921,10 @@ "id": "31c704e7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.340281Z", - "iopub.status.busy": "2024-09-05T19:40:08.339935Z", - "iopub.status.idle": "2024-09-05T19:40:08.465417Z", - "shell.execute_reply": "2024-09-05T19:40:08.464849Z" + "iopub.execute_input": "2024-09-06T19:40:08.639192Z", + "iopub.status.busy": "2024-09-06T19:40:08.638877Z", + "iopub.status.idle": "2024-09-06T19:40:08.766647Z", + "shell.execute_reply": "2024-09-06T19:40:08.765685Z" } }, "outputs": [ @@ -963,10 +963,10 @@ "id": "0bcc43db", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.467579Z", - "iopub.status.busy": "2024-09-05T19:40:08.467388Z", - "iopub.status.idle": "2024-09-05T19:40:08.576982Z", - "shell.execute_reply": "2024-09-05T19:40:08.576322Z" + "iopub.execute_input": "2024-09-06T19:40:08.769173Z", + "iopub.status.busy": "2024-09-06T19:40:08.768972Z", + "iopub.status.idle": "2024-09-06T19:40:08.878186Z", + "shell.execute_reply": "2024-09-06T19:40:08.877593Z" } }, "outputs": [ @@ -1022,10 +1022,10 @@ "id": "7021bd68", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.579538Z", - "iopub.status.busy": "2024-09-05T19:40:08.579142Z", - "iopub.status.idle": "2024-09-05T19:40:09.091088Z", - "shell.execute_reply": "2024-09-05T19:40:09.090540Z" + "iopub.execute_input": "2024-09-06T19:40:08.880641Z", + "iopub.status.busy": "2024-09-06T19:40:08.880289Z", + "iopub.status.idle": "2024-09-06T19:40:09.386974Z", + "shell.execute_reply": "2024-09-06T19:40:09.386324Z" } }, "outputs": [], @@ -1041,10 +1041,10 @@ "id": "d49c990b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.093910Z", - "iopub.status.busy": "2024-09-05T19:40:09.093465Z", - "iopub.status.idle": "2024-09-05T19:40:09.190047Z", - "shell.execute_reply": "2024-09-05T19:40:09.189451Z" + "iopub.execute_input": "2024-09-06T19:40:09.389675Z", + "iopub.status.busy": "2024-09-06T19:40:09.389308Z", + "iopub.status.idle": "2024-09-06T19:40:09.485553Z", + "shell.execute_reply": "2024-09-06T19:40:09.484996Z" } }, "outputs": [ @@ -1079,10 +1079,10 @@ "id": "dbab6fb3", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.192506Z", - "iopub.status.busy": "2024-09-05T19:40:09.192090Z", - "iopub.status.idle": "2024-09-05T19:40:09.200751Z", - "shell.execute_reply": "2024-09-05T19:40:09.200261Z" + "iopub.execute_input": "2024-09-06T19:40:09.487964Z", + "iopub.status.busy": "2024-09-06T19:40:09.487496Z", + "iopub.status.idle": "2024-09-06T19:40:09.496128Z", + "shell.execute_reply": "2024-09-06T19:40:09.495570Z" } }, "outputs": [ @@ -1189,10 +1189,10 @@ "id": "5b39b8b5", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.202776Z", - "iopub.status.busy": "2024-09-05T19:40:09.202460Z", - "iopub.status.idle": "2024-09-05T19:40:09.205281Z", - "shell.execute_reply": "2024-09-05T19:40:09.204801Z" + "iopub.execute_input": "2024-09-06T19:40:09.498303Z", + "iopub.status.busy": "2024-09-06T19:40:09.497989Z", + "iopub.status.idle": "2024-09-06T19:40:09.500756Z", + "shell.execute_reply": "2024-09-06T19:40:09.500274Z" }, "nbsphinx": "hidden" }, @@ -1217,10 +1217,10 @@ "id": "df06525b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.207302Z", - "iopub.status.busy": "2024-09-05T19:40:09.206969Z", - "iopub.status.idle": "2024-09-05T19:40:14.941265Z", - "shell.execute_reply": "2024-09-05T19:40:14.940657Z" + "iopub.execute_input": "2024-09-06T19:40:09.502626Z", + "iopub.status.busy": "2024-09-06T19:40:09.502453Z", + "iopub.status.idle": "2024-09-06T19:40:15.134668Z", + "shell.execute_reply": "2024-09-06T19:40:15.134055Z" } }, "outputs": [ @@ -1264,10 +1264,10 @@ "id": "05282559", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:14.943675Z", - "iopub.status.busy": "2024-09-05T19:40:14.943446Z", - "iopub.status.idle": "2024-09-05T19:40:14.952597Z", - "shell.execute_reply": "2024-09-05T19:40:14.952017Z" + "iopub.execute_input": "2024-09-06T19:40:15.137003Z", + "iopub.status.busy": "2024-09-06T19:40:15.136794Z", + "iopub.status.idle": "2024-09-06T19:40:15.145626Z", + "shell.execute_reply": "2024-09-06T19:40:15.145149Z" } }, "outputs": [ @@ -1392,10 +1392,10 @@ "id": "95531cda", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:14.954943Z", - "iopub.status.busy": "2024-09-05T19:40:14.954611Z", - "iopub.status.idle": "2024-09-05T19:40:15.024368Z", - "shell.execute_reply": "2024-09-05T19:40:15.023700Z" + "iopub.execute_input": "2024-09-06T19:40:15.147739Z", + "iopub.status.busy": "2024-09-06T19:40:15.147560Z", + "iopub.status.idle": "2024-09-06T19:40:15.212105Z", + "shell.execute_reply": "2024-09-06T19:40:15.211592Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb b/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb index f4a359b72..3d1ba85ed 100644 --- a/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/segmentation.ipynb @@ -61,10 +61,10 @@ "id": "ae8a08e0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:18.199733Z", - "iopub.status.busy": "2024-09-05T19:40:18.199551Z", - "iopub.status.idle": "2024-09-05T19:40:19.726748Z", - "shell.execute_reply": "2024-09-05T19:40:19.726012Z" + "iopub.execute_input": "2024-09-06T19:40:18.378801Z", + "iopub.status.busy": "2024-09-06T19:40:18.378438Z", + "iopub.status.idle": "2024-09-06T19:40:21.013953Z", + "shell.execute_reply": "2024-09-06T19:40:21.013191Z" } }, "outputs": [], @@ -79,10 +79,10 @@ "id": "58fd4c55", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:19.729634Z", - "iopub.status.busy": "2024-09-05T19:40:19.729307Z", - "iopub.status.idle": "2024-09-05T19:41:12.917082Z", - "shell.execute_reply": "2024-09-05T19:41:12.916305Z" + "iopub.execute_input": "2024-09-06T19:40:21.016497Z", + "iopub.status.busy": "2024-09-06T19:40:21.016297Z", + "iopub.status.idle": "2024-09-06T19:41:26.205588Z", + "shell.execute_reply": "2024-09-06T19:41:26.204905Z" } }, "outputs": [], @@ -97,10 +97,10 @@ "id": "439b0305", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:12.919767Z", - "iopub.status.busy": "2024-09-05T19:41:12.919563Z", - "iopub.status.idle": "2024-09-05T19:41:14.110304Z", - "shell.execute_reply": "2024-09-05T19:41:14.109686Z" + "iopub.execute_input": "2024-09-06T19:41:26.208261Z", + "iopub.status.busy": "2024-09-06T19:41:26.207954Z", + "iopub.status.idle": "2024-09-06T19:41:27.363762Z", + "shell.execute_reply": "2024-09-06T19:41:27.363213Z" }, "nbsphinx": "hidden" }, @@ -111,7 +111,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -137,10 +137,10 @@ "id": "a1349304", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.112987Z", - "iopub.status.busy": "2024-09-05T19:41:14.112652Z", - "iopub.status.idle": "2024-09-05T19:41:14.116314Z", - "shell.execute_reply": "2024-09-05T19:41:14.115719Z" + "iopub.execute_input": "2024-09-06T19:41:27.366273Z", + "iopub.status.busy": "2024-09-06T19:41:27.365850Z", + "iopub.status.idle": "2024-09-06T19:41:27.369197Z", + "shell.execute_reply": "2024-09-06T19:41:27.368626Z" } }, "outputs": [], @@ -203,10 +203,10 @@ "id": "07dc5678", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.118606Z", - "iopub.status.busy": "2024-09-05T19:41:14.118193Z", - "iopub.status.idle": "2024-09-05T19:41:14.122291Z", - "shell.execute_reply": "2024-09-05T19:41:14.121859Z" + "iopub.execute_input": "2024-09-06T19:41:27.371272Z", + "iopub.status.busy": "2024-09-06T19:41:27.370943Z", + "iopub.status.idle": "2024-09-06T19:41:27.374872Z", + "shell.execute_reply": "2024-09-06T19:41:27.374336Z" } }, "outputs": [ @@ -247,10 +247,10 @@ "id": "25ebe22a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.124633Z", - "iopub.status.busy": "2024-09-05T19:41:14.124214Z", - "iopub.status.idle": "2024-09-05T19:41:14.128275Z", - "shell.execute_reply": "2024-09-05T19:41:14.127671Z" + "iopub.execute_input": "2024-09-06T19:41:27.377058Z", + "iopub.status.busy": "2024-09-06T19:41:27.376708Z", + "iopub.status.idle": "2024-09-06T19:41:27.380273Z", + "shell.execute_reply": "2024-09-06T19:41:27.379824Z" } }, "outputs": [ @@ -290,10 +290,10 @@ "id": "3faedea9", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.130477Z", - "iopub.status.busy": "2024-09-05T19:41:14.130083Z", - "iopub.status.idle": "2024-09-05T19:41:14.132962Z", - "shell.execute_reply": "2024-09-05T19:41:14.132498Z" + "iopub.execute_input": "2024-09-06T19:41:27.382286Z", + "iopub.status.busy": "2024-09-06T19:41:27.381955Z", + "iopub.status.idle": "2024-09-06T19:41:27.384835Z", + "shell.execute_reply": "2024-09-06T19:41:27.384366Z" } }, "outputs": [], @@ -333,17 +333,17 @@ "id": "2c2ad9ad", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.134947Z", - "iopub.status.busy": "2024-09-05T19:41:14.134627Z", - "iopub.status.idle": "2024-09-05T19:41:52.181715Z", - "shell.execute_reply": "2024-09-05T19:41:52.181015Z" + "iopub.execute_input": "2024-09-06T19:41:27.386838Z", + "iopub.status.busy": "2024-09-06T19:41:27.386506Z", + "iopub.status.idle": "2024-09-06T19:42:04.890778Z", + "shell.execute_reply": "2024-09-06T19:42:04.890135Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a4b3e7cfcb62474f9a340c5c39023be9", + "model_id": "00ec60662f03441f8733d768775a0ed1", "version_major": 2, "version_minor": 0 }, @@ -357,7 +357,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb3d14222f3f42b487321867e4e431ee", + "model_id": "af401850ebaa408dae00a90bb34bc54a", "version_major": 2, "version_minor": 0 }, @@ -400,10 +400,10 @@ "id": "95dc7268", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:52.184254Z", - "iopub.status.busy": "2024-09-05T19:41:52.184042Z", - "iopub.status.idle": "2024-09-05T19:41:52.858875Z", - "shell.execute_reply": "2024-09-05T19:41:52.858345Z" + "iopub.execute_input": "2024-09-06T19:42:04.893407Z", + "iopub.status.busy": "2024-09-06T19:42:04.893064Z", + "iopub.status.idle": "2024-09-06T19:42:05.569760Z", + "shell.execute_reply": "2024-09-06T19:42:05.569193Z" } }, "outputs": [ @@ -446,10 +446,10 @@ "id": "57fed473", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:52.861209Z", - "iopub.status.busy": "2024-09-05T19:41:52.860921Z", - "iopub.status.idle": "2024-09-05T19:41:55.873081Z", - "shell.execute_reply": "2024-09-05T19:41:55.872487Z" + "iopub.execute_input": "2024-09-06T19:42:05.572221Z", + "iopub.status.busy": "2024-09-06T19:42:05.571699Z", + "iopub.status.idle": "2024-09-06T19:42:08.487750Z", + "shell.execute_reply": "2024-09-06T19:42:08.487151Z" } }, "outputs": [ @@ -519,17 +519,17 @@ "id": "e4a006bd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:55.875319Z", - "iopub.status.busy": "2024-09-05T19:41:55.874961Z", - "iopub.status.idle": "2024-09-05T19:42:28.673127Z", - "shell.execute_reply": "2024-09-05T19:42:28.672574Z" + "iopub.execute_input": "2024-09-06T19:42:08.490015Z", + "iopub.status.busy": "2024-09-06T19:42:08.489812Z", + "iopub.status.idle": "2024-09-06T19:42:42.122207Z", + "shell.execute_reply": "2024-09-06T19:42:42.121639Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ece025087d704900ab9e6ddd077e3061", + "model_id": "a8ef1d6ee6da4d52bd3aa4ef30d9915f", "version_major": 2, "version_minor": 0 }, @@ -769,10 +769,10 @@ "id": "c8f4e163", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:28.675297Z", - "iopub.status.busy": "2024-09-05T19:42:28.674959Z", - "iopub.status.idle": "2024-09-05T19:42:44.105535Z", - "shell.execute_reply": "2024-09-05T19:42:44.104946Z" + "iopub.execute_input": "2024-09-06T19:42:42.124501Z", + "iopub.status.busy": "2024-09-06T19:42:42.124158Z", + "iopub.status.idle": "2024-09-06T19:42:57.234866Z", + "shell.execute_reply": "2024-09-06T19:42:57.234293Z" } }, "outputs": [], @@ -786,10 +786,10 @@ "id": "716c74f3", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:44.108179Z", - "iopub.status.busy": "2024-09-05T19:42:44.107699Z", - "iopub.status.idle": "2024-09-05T19:42:47.883916Z", - "shell.execute_reply": "2024-09-05T19:42:47.883404Z" + "iopub.execute_input": "2024-09-06T19:42:57.237390Z", + "iopub.status.busy": "2024-09-06T19:42:57.237016Z", + "iopub.status.idle": "2024-09-06T19:43:00.971913Z", + "shell.execute_reply": "2024-09-06T19:43:00.971312Z" } }, "outputs": [ @@ -858,17 +858,17 @@ "id": "db0b5179", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:47.886159Z", - "iopub.status.busy": "2024-09-05T19:42:47.885812Z", - "iopub.status.idle": "2024-09-05T19:42:49.385378Z", - "shell.execute_reply": "2024-09-05T19:42:49.384804Z" + "iopub.execute_input": "2024-09-06T19:43:00.974009Z", + "iopub.status.busy": "2024-09-06T19:43:00.973827Z", + "iopub.status.idle": "2024-09-06T19:43:02.404764Z", + "shell.execute_reply": "2024-09-06T19:43:02.404239Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2ca8a72007b34f2fbd2f2ae6f2cb7931", + "model_id": "33547ea19ce34215b8f9bbd75c870924", "version_major": 2, "version_minor": 0 }, @@ -898,10 +898,10 @@ "id": "390780a1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:49.388228Z", - "iopub.status.busy": "2024-09-05T19:42:49.387773Z", - "iopub.status.idle": "2024-09-05T19:42:49.418203Z", - "shell.execute_reply": "2024-09-05T19:42:49.417626Z" + "iopub.execute_input": "2024-09-06T19:43:02.407222Z", + "iopub.status.busy": "2024-09-06T19:43:02.406914Z", + "iopub.status.idle": "2024-09-06T19:43:02.435740Z", + "shell.execute_reply": "2024-09-06T19:43:02.435223Z" } }, "outputs": [], @@ -915,10 +915,10 @@ "id": "933d6ef0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:49.420836Z", - "iopub.status.busy": "2024-09-05T19:42:49.420472Z", - "iopub.status.idle": "2024-09-05T19:42:55.430102Z", - "shell.execute_reply": "2024-09-05T19:42:55.429512Z" + "iopub.execute_input": "2024-09-06T19:43:02.438408Z", + "iopub.status.busy": "2024-09-06T19:43:02.438030Z", + "iopub.status.idle": "2024-09-06T19:43:08.523002Z", + "shell.execute_reply": "2024-09-06T19:43:08.522439Z" } }, "outputs": [ @@ -991,10 +991,10 @@ "id": "86bac686", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:55.432343Z", - "iopub.status.busy": "2024-09-05T19:42:55.431963Z", - "iopub.status.idle": "2024-09-05T19:42:55.487961Z", - "shell.execute_reply": "2024-09-05T19:42:55.487400Z" + "iopub.execute_input": "2024-09-06T19:43:08.525189Z", + "iopub.status.busy": "2024-09-06T19:43:08.524868Z", + "iopub.status.idle": "2024-09-06T19:43:08.580916Z", + "shell.execute_reply": "2024-09-06T19:43:08.580242Z" }, "nbsphinx": "hidden" }, @@ -1038,53 +1038,31 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "0271e3b5aa734c59a2c1e77ab40c0fdf": { + "00ec60662f03441f8733d768775a0ed1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_bd1a028a18b94bbbb600a39d327b5d2d", - "placeholder": "​", - "style": "IPY_MODEL_d102c214e0294328845f42c3a4fc31af", - "tabbable": null, - "tooltip": null, - "value": " 30/30 [00:01<00:00, 20.22it/s]" - } - }, - "0543eae296d34562bf713d819bab46fa": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b9ce6baf57594214a8a7669202c8db27", - "placeholder": "​", - "style": "IPY_MODEL_8141ad12728f457e8d88d842133942f9", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_42d03e2415284486b25cf67ccd387444", + "IPY_MODEL_5050585031b24c079460a52a9a4fc488", + "IPY_MODEL_b1848abf52f742ed9f7657ba08af06f7" + ], + "layout": "IPY_MODEL_d73b0ac161c9411fb176d09cfe007d5d", "tabbable": null, - "tooltip": null, - "value": "images processed using softmin: 100%" + "tooltip": null } }, - "154ab31a8edf479db912cbff400be313": { + "0555e6f1fc524e749446c0929d265eab": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1137,117 +1115,101 @@ "width": null } }, - "19a073f2103145ff8d3edb1fc13352fd": { - "model_module": "@jupyter-widgets/controls", + "08c7a2f2c6804a7da25a3555d45832fe": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "LayoutModel", "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "LayoutModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_8e787c2b073e463881f6c5e2cc8dc67a", - "max": 30.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_df29b384d8354feea3a86fb145690034", - "tabbable": null, - "tooltip": null, - "value": 30.0 + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "1c9c63d3b81344a393e31ec0b1420510": { + "0f26c903e03a409eb8eb23a06ad068a1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "2ca8a72007b34f2fbd2f2ae6f2cb7931": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0543eae296d34562bf713d819bab46fa", - "IPY_MODEL_b1f2065c0c4643e5aecd80658d1aaa37", - "IPY_MODEL_0271e3b5aa734c59a2c1e77ab40c0fdf" - ], - "layout": "IPY_MODEL_acf13d87464e4f629212a388add13530", - "tabbable": null, - "tooltip": null + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "2ff9cc8a4b654553be47d8b435944b7f": { + "219cc478643a4ee5ac3bd50beeb53306": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b18e4f016fcf408a98576f5ec0eaa44b", - "max": 30.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_c13620cfc24b48c0ba51a5593d66841e", + "layout": "IPY_MODEL_7b66b5652e59476aab6385c55f338eaf", + "placeholder": "​", + "style": "IPY_MODEL_c70c5f7b514a4120b47fe4694b8aa561", "tabbable": null, "tooltip": null, - "value": 30.0 - } - }, - "30327c6cf5554d71a80f362c0e3c517a": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "value": " 30/30 [00:01<00:00, 21.35it/s]" } }, - "373286fca444445097e38e012eec4165": { + "23f68f6bcc9f4247ac306e707ae76a3e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1300,7 +1262,23 @@ "width": null } }, - "44a2a05278754fb8b099f76a80aa6e48": { + "26c9d71cd2b144f5a62f2e547396cf9d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "31810f3656744673bb829bd7c19b4796": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1353,48 +1331,47 @@ "width": null } }, - "44c9f78d8aa147219badd49c88116bf5": { + "33547ea19ce34215b8f9bbd75c870924": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_6901169080b04ad499942dc391b9b336", + "IPY_MODEL_90fef083c08c4c3c927458dfb8b00fe9", + "IPY_MODEL_219cc478643a4ee5ac3bd50beeb53306" + ], + "layout": "IPY_MODEL_571062df41e24ec2a51ede636c1c40ae", + "tabbable": null, + "tooltip": null } }, - "45ed018ec81f4df08d861bcb58442dd3": { + "428890bcca0c4c398b4c85e7b197ef23": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_44a2a05278754fb8b099f76a80aa6e48", - "placeholder": "​", - "style": "IPY_MODEL_c2b264c49d234675bf6ed2efbeefbaef", - "tabbable": null, - "tooltip": null, - "value": "number of examples processed for checking labels: 100%" + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "6d920735297d48d5aa5fa76eb77c5faa": { + "42d03e2415284486b25cf67ccd387444": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1409,31 +1386,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_ac3b63d4a32f44cdb880bf34eae8e38f", + "layout": "IPY_MODEL_08c7a2f2c6804a7da25a3555d45832fe", "placeholder": "​", - "style": "IPY_MODEL_fe96e6f2b3d44ed9a068d86177dba9d9", + "style": "IPY_MODEL_5428bca92792410db3731a76852725a2", "tabbable": null, "tooltip": null, - "value": " 30/30 [00:00<00:00, 817.50it/s]" - } - }, - "72b3805a9e3b46659f904bc081e85a45": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "value": "number of examples processed for estimating thresholds: 100%" } }, - "770a9991bd4f479da0fceb5900cbf417": { + "44a941086c164d5bb775c41c7d4ac57f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1486,48 +1447,7 @@ "width": null } }, - "780bdc9cdfc146f4b64fe526a99ff03b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b89d909a19a7460f81b9b346038cdfe0", - "placeholder": "​", - "style": "IPY_MODEL_b9e08204838a45a489517f7aac01fcdb", - "tabbable": null, - "tooltip": null, - "value": " 4997683/4997683 [00:32<00:00, 154657.78it/s]" - } - }, - "8141ad12728f457e8d88d842133942f9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "8e787c2b073e463881f6c5e2cc8dc67a": { + "474187191bb2423bbeaab8075807fc8d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1580,60 +1500,51 @@ "width": null } }, - "915659784e954336952dbe532ca9c568": { - "model_module": "@jupyter-widgets/base", + "5050585031b24c079460a52a9a4fc488": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "FloatProgressModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_fefad91592514c8b93cde6a9aa658432", + "max": 30.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_26c9d71cd2b144f5a62f2e547396cf9d", + "tabbable": null, + "tooltip": null, + "value": 30.0 + } + }, + "5428bca92792410db3731a76852725a2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "9d3137e0b66a43d2bd580b2b48653afc": { + "56086d38b6e24dd381b3d2d8adfc7dee": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1648,15 +1559,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_770a9991bd4f479da0fceb5900cbf417", + "layout": "IPY_MODEL_8b4141a6045142c1b9ba131103d924f0", "placeholder": "​", - "style": "IPY_MODEL_d654f626f86948388172098f7cc43d25", + "style": "IPY_MODEL_62e07c87b8f14d10ae3081dc89c264cb", "tabbable": null, "tooltip": null, - "value": "number of examples processed for estimating thresholds: 100%" + "value": " 30/30 [00:25<00:00,  1.19it/s]" } }, - "a1e731438d6d45e5966433bcf063a059": { + "571062df41e24ec2a51ede636c1c40ae": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1709,54 +1620,69 @@ "width": null } }, - "a38a937b167f4ba482c62fb6f9795bb4": { + "5aa47fe7e6cf4464bcbe167e6d3ba68a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "5e211e7a482d4ffc95757eed7f7aa9cc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", + "_view_name": "ProgressView", + "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_c8fa8dfe739640758359553a0e57be14", - "placeholder": "​", - "style": "IPY_MODEL_44c9f78d8aa147219badd49c88116bf5", + "layout": "IPY_MODEL_71cc03f01ffb487095fef61fe310cb72", + "max": 30.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_428890bcca0c4c398b4c85e7b197ef23", "tabbable": null, "tooltip": null, - "value": "100%" + "value": 30.0 } }, - "a4b3e7cfcb62474f9a340c5c39023be9": { + "62e07c87b8f14d10ae3081dc89c264cb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_9d3137e0b66a43d2bd580b2b48653afc", - "IPY_MODEL_19a073f2103145ff8d3edb1fc13352fd", - "IPY_MODEL_6d920735297d48d5aa5fa76eb77c5faa" - ], - "layout": "IPY_MODEL_f612b67a99514134b4f6b0b836455efc", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "a8e5b9a64739480e863ba68bb4d8600f": { + "6901169080b04ad499942dc391b9b336": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1771,15 +1697,33 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_fd5942b1092f42aeaedd8058d4d911de", + "layout": "IPY_MODEL_fa2dd8d15728476eac598aeb95576e3b", "placeholder": "​", - "style": "IPY_MODEL_30327c6cf5554d71a80f362c0e3c517a", + "style": "IPY_MODEL_a247c69930644302aed767d71b7ec676", "tabbable": null, "tooltip": null, - "value": " 30/30 [00:25<00:00,  1.15it/s]" + "value": "images processed using softmin: 100%" } }, - "ac3b63d4a32f44cdb880bf34eae8e38f": { + "71684d8531234f3d9d16e15f5e2a1318": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "71cc03f01ffb487095fef61fe310cb72": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1832,7 +1776,7 @@ "width": null } }, - "acf13d87464e4f629212a388add13530": { + "71d9c9ff1e934321985ce73f6d70432d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1885,7 +1829,25 @@ "width": null } }, - "b18e4f016fcf408a98576f5ec0eaa44b": { + "72aa2b7d62f44bfba1fef33687cd2d9c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "733932bb0ae3401390e27945e01e9afa": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1938,33 +1900,7 @@ "width": null } }, - "b1f2065c0c4643e5aecd80658d1aaa37": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_373286fca444445097e38e012eec4165", - "max": 30.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_1c9c63d3b81344a393e31ec0b1420510", - "tabbable": null, - "tooltip": null, - "value": 30.0 - } - }, - "b89d909a19a7460f81b9b346038cdfe0": { + "7b66b5652e59476aab6385c55f338eaf": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2017,7 +1953,7 @@ "width": null } }, - "b9ce6baf57594214a8a7669202c8db27": { + "8b4141a6045142c1b9ba131103d924f0": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2070,7 +2006,210 @@ "width": null } }, - "b9e08204838a45a489517f7aac01fcdb": { + "8c44f5cb10834552b9f054ccff28de8f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_0555e6f1fc524e749446c0929d265eab", + "max": 4997683.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_b4ff48b5ef42475cb8d931380feef05a", + "tabbable": null, + "tooltip": null, + "value": 4997683.0 + } + }, + "90fef083c08c4c3c927458dfb8b00fe9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d8f70224ecee42f48ecf14d646040c54", + "max": 30.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_e468d38bc9454ebf87117d355645f3f1", + "tabbable": null, + "tooltip": null, + "value": 30.0 + } + }, + "a247c69930644302aed767d71b7ec676": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "a8ef1d6ee6da4d52bd3aa4ef30d9915f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_e7a051930ecf4f8da5a7114fa550bc7c", + "IPY_MODEL_8c44f5cb10834552b9f054ccff28de8f", + "IPY_MODEL_abb55722ee8a4e9383f54ba9776bfb21" + ], + "layout": "IPY_MODEL_44a941086c164d5bb775c41c7d4ac57f", + "tabbable": null, + "tooltip": null + } + }, + "abb55722ee8a4e9383f54ba9776bfb21": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_23f68f6bcc9f4247ac306e707ae76a3e", + "placeholder": "​", + "style": "IPY_MODEL_0f26c903e03a409eb8eb23a06ad068a1", + "tabbable": null, + "tooltip": null, + "value": " 4997683/4997683 [00:33<00:00, 147431.29it/s]" + } + }, + "ac71e20e794944a5ad10d81bd3802d6a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_733932bb0ae3401390e27945e01e9afa", + "placeholder": "​", + "style": "IPY_MODEL_72aa2b7d62f44bfba1fef33687cd2d9c", + "tabbable": null, + "tooltip": null, + "value": "number of examples processed for checking labels: 100%" + } + }, + "af401850ebaa408dae00a90bb34bc54a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_ac71e20e794944a5ad10d81bd3802d6a", + "IPY_MODEL_5e211e7a482d4ffc95757eed7f7aa9cc", + "IPY_MODEL_56086d38b6e24dd381b3d2d8adfc7dee" + ], + "layout": "IPY_MODEL_71d9c9ff1e934321985ce73f6d70432d", + "tabbable": null, + "tooltip": null + } + }, + "b1848abf52f742ed9f7657ba08af06f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_474187191bb2423bbeaab8075807fc8d", + "placeholder": "​", + "style": "IPY_MODEL_5aa47fe7e6cf4464bcbe167e6d3ba68a", + "tabbable": null, + "tooltip": null, + "value": " 30/30 [00:00<00:00, 787.55it/s]" + } + }, + "b4ff48b5ef42475cb8d931380feef05a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "c70c5f7b514a4120b47fe4694b8aa561": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2088,7 +2227,7 @@ "text_color": null } }, - "bd1a028a18b94bbbb600a39d327b5d2d": { + "d73b0ac161c9411fb176d09cfe007d5d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2141,41 +2280,7 @@ "width": null } }, - "c13620cfc24b48c0ba51a5593d66841e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "c2b264c49d234675bf6ed2efbeefbaef": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c8fa8dfe739640758359553a0e57be14": { + "d8f70224ecee42f48ecf14d646040c54": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2228,43 +2333,7 @@ "width": null } }, - "d102c214e0294328845f42c3a4fc31af": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "d654f626f86948388172098f7cc43d25": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "df29b384d8354feea3a86fb145690034": { + "e468d38bc9454ebf87117d355645f3f1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", @@ -2280,57 +2349,30 @@ "description_width": "" } }, - "ece025087d704900ab9e6ddd077e3061": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_a38a937b167f4ba482c62fb6f9795bb4", - "IPY_MODEL_f5051711724c4bc0acdc14f8b27478fe", - "IPY_MODEL_780bdc9cdfc146f4b64fe526a99ff03b" - ], - "layout": "IPY_MODEL_154ab31a8edf479db912cbff400be313", - "tabbable": null, - "tooltip": null - } - }, - "f5051711724c4bc0acdc14f8b27478fe": { + "e7a051930ecf4f8da5a7114fa550bc7c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_a1e731438d6d45e5966433bcf063a059", - "max": 4997683.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_72b3805a9e3b46659f904bc081e85a45", + "layout": "IPY_MODEL_31810f3656744673bb829bd7c19b4796", + "placeholder": "​", + "style": "IPY_MODEL_71684d8531234f3d9d16e15f5e2a1318", "tabbable": null, "tooltip": null, - "value": 4997683.0 + "value": "100%" } }, - "f612b67a99514134b4f6b0b836455efc": { + "fa2dd8d15728476eac598aeb95576e3b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2383,31 +2425,7 @@ "width": null } }, - "fb3d14222f3f42b487321867e4e431ee": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_45ed018ec81f4df08d861bcb58442dd3", - "IPY_MODEL_2ff9cc8a4b654553be47d8b435944b7f", - "IPY_MODEL_a8e5b9a64739480e863ba68bb4d8600f" - ], - "layout": "IPY_MODEL_915659784e954336952dbe532ca9c568", - "tabbable": null, - "tooltip": null - } - }, - "fd5942b1092f42aeaedd8058d4d911de": { + "fefad91592514c8b93cde6a9aa658432": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2459,24 +2477,6 @@ "visibility": null, "width": null } - }, - "fe96e6f2b3d44ed9a068d86177dba9d9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } } }, "version_major": 2, diff --git a/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb b/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb index 49d76911a..c988c12c2 100644 --- a/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb +++ b/master/.doctrees/nbsphinx/tutorials/token_classification.ipynb @@ -75,10 +75,10 @@ "id": "ae8a08e0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:57.901570Z", - "iopub.status.busy": "2024-09-05T19:42:57.901387Z", - "iopub.status.idle": "2024-09-05T19:42:59.034492Z", - "shell.execute_reply": "2024-09-05T19:42:59.033839Z" + "iopub.execute_input": "2024-09-06T19:43:11.117353Z", + "iopub.status.busy": "2024-09-06T19:43:11.117178Z", + "iopub.status.idle": "2024-09-06T19:43:13.210573Z", + "shell.execute_reply": "2024-09-06T19:43:13.209958Z" } }, "outputs": [ @@ -86,7 +86,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-09-05 19:42:57-- https://data.deepai.org/conll2003.zip\r\n", + "--2024-09-06 19:43:11-- https://data.deepai.org/conll2003.zip\r\n", "Resolving data.deepai.org (data.deepai.org)... " ] }, @@ -94,15 +94,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "169.150.236.98, 2400:52e0:1a00::1067:1\r\n", - "Connecting to data.deepai.org (data.deepai.org)|169.150.236.98|:443... " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "connected.\r\n", + "169.150.249.167, 2400:52e0:1a01::907:1\r\n", + "Connecting to data.deepai.org (data.deepai.org)|169.150.249.167|:443... connected.\r\n", "HTTP request sent, awaiting response... " ] }, @@ -125,7 +118,7 @@ "\r", "conll2003.zip 100%[===================>] 959.94K --.-KB/s in 0.1s \r\n", "\r\n", - "2024-09-05 19:42:58 (6.36 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n", + "2024-09-06 19:43:11 (7.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n", "\r\n", "mkdir: cannot create directory ‘data’: File exists\r\n" ] @@ -145,9 +138,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-09-05 19:42:58-- https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n", - "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 3.5.17.152, 3.5.30.212, 54.231.228.65, ...\r\n", - "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|3.5.17.152|:443... connected.\r\n", + "--2024-09-06 19:43:11-- https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n", + "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 54.231.201.17, 52.217.193.233, 52.217.81.84, ...\r\n", + "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|54.231.201.17|:443... " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "connected.\r\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "HTTP request sent, awaiting response... " ] }, @@ -168,9 +174,33 @@ "output_type": "stream", "text": [ "\r", - "pred_probs.npz 100%[===================>] 16.26M --.-KB/s in 0.1s \r\n", + "pred_probs.npz 0%[ ] 142.53K 668KB/s " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "pred_probs.npz 8%[> ] 1.35M 3.16MB/s " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "pred_probs.npz 50%[=========> ] 8.28M 12.9MB/s " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "pred_probs.npz 100%[===================>] 16.26M 20.4MB/s in 0.8s \r\n", "\r\n", - "2024-09-05 19:42:58 (169 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n", + "2024-09-06 19:43:13 (20.4 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n", "\r\n" ] } @@ -187,10 +217,10 @@ "id": "439b0305", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:59.037334Z", - "iopub.status.busy": "2024-09-05T19:42:59.036934Z", - "iopub.status.idle": "2024-09-05T19:43:00.344176Z", - "shell.execute_reply": "2024-09-05T19:43:00.343566Z" + "iopub.execute_input": "2024-09-06T19:43:13.213109Z", + "iopub.status.busy": "2024-09-06T19:43:13.212725Z", + "iopub.status.idle": "2024-09-06T19:43:14.513752Z", + "shell.execute_reply": "2024-09-06T19:43:14.513226Z" }, "nbsphinx": "hidden" }, @@ -201,7 +231,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -227,10 +257,10 @@ "id": "a1349304", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:00.346737Z", - "iopub.status.busy": "2024-09-05T19:43:00.346278Z", - "iopub.status.idle": "2024-09-05T19:43:00.349652Z", - "shell.execute_reply": "2024-09-05T19:43:00.349193Z" + "iopub.execute_input": "2024-09-06T19:43:14.516436Z", + "iopub.status.busy": "2024-09-06T19:43:14.515941Z", + "iopub.status.idle": "2024-09-06T19:43:14.519305Z", + "shell.execute_reply": "2024-09-06T19:43:14.518871Z" } }, "outputs": [], @@ -280,10 +310,10 @@ "id": "ab9d59a0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:00.351675Z", - "iopub.status.busy": "2024-09-05T19:43:00.351340Z", - "iopub.status.idle": "2024-09-05T19:43:00.354237Z", - "shell.execute_reply": "2024-09-05T19:43:00.353818Z" + "iopub.execute_input": "2024-09-06T19:43:14.521508Z", + "iopub.status.busy": "2024-09-06T19:43:14.521171Z", + "iopub.status.idle": "2024-09-06T19:43:14.524052Z", + "shell.execute_reply": "2024-09-06T19:43:14.523615Z" }, "nbsphinx": "hidden" }, @@ -301,10 +331,10 @@ "id": "519cb80c", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:00.356189Z", - "iopub.status.busy": "2024-09-05T19:43:00.355844Z", - "iopub.status.idle": "2024-09-05T19:43:09.562038Z", - "shell.execute_reply": "2024-09-05T19:43:09.561398Z" + "iopub.execute_input": "2024-09-06T19:43:14.526149Z", + "iopub.status.busy": "2024-09-06T19:43:14.525818Z", + "iopub.status.idle": "2024-09-06T19:43:23.627822Z", + "shell.execute_reply": "2024-09-06T19:43:23.627249Z" } }, "outputs": [], @@ -378,10 +408,10 @@ "id": "202f1526", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.564850Z", - "iopub.status.busy": "2024-09-05T19:43:09.564291Z", - "iopub.status.idle": "2024-09-05T19:43:09.570178Z", - "shell.execute_reply": "2024-09-05T19:43:09.569596Z" + "iopub.execute_input": "2024-09-06T19:43:23.630427Z", + "iopub.status.busy": "2024-09-06T19:43:23.630129Z", + "iopub.status.idle": "2024-09-06T19:43:23.635623Z", + "shell.execute_reply": "2024-09-06T19:43:23.635160Z" }, "nbsphinx": "hidden" }, @@ -421,10 +451,10 @@ "id": "a4381f03", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.572335Z", - "iopub.status.busy": "2024-09-05T19:43:09.571988Z", - "iopub.status.idle": "2024-09-05T19:43:09.932566Z", - "shell.execute_reply": "2024-09-05T19:43:09.931972Z" + "iopub.execute_input": "2024-09-06T19:43:23.637682Z", + "iopub.status.busy": "2024-09-06T19:43:23.637404Z", + "iopub.status.idle": "2024-09-06T19:43:23.985761Z", + "shell.execute_reply": "2024-09-06T19:43:23.985192Z" } }, "outputs": [], @@ -461,10 +491,10 @@ "id": "7842e4a3", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.935037Z", - "iopub.status.busy": "2024-09-05T19:43:09.934669Z", - "iopub.status.idle": "2024-09-05T19:43:09.939240Z", - "shell.execute_reply": "2024-09-05T19:43:09.938758Z" + "iopub.execute_input": "2024-09-06T19:43:23.988095Z", + "iopub.status.busy": "2024-09-06T19:43:23.987906Z", + "iopub.status.idle": "2024-09-06T19:43:23.992118Z", + "shell.execute_reply": "2024-09-06T19:43:23.991556Z" } }, "outputs": [ @@ -536,10 +566,10 @@ "id": "2c2ad9ad", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.941448Z", - "iopub.status.busy": "2024-09-05T19:43:09.941115Z", - "iopub.status.idle": "2024-09-05T19:43:12.624115Z", - "shell.execute_reply": "2024-09-05T19:43:12.623415Z" + "iopub.execute_input": "2024-09-06T19:43:23.994018Z", + "iopub.status.busy": "2024-09-06T19:43:23.993843Z", + "iopub.status.idle": "2024-09-06T19:43:26.637725Z", + "shell.execute_reply": "2024-09-06T19:43:26.636888Z" } }, "outputs": [], @@ -561,10 +591,10 @@ "id": "95dc7268", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.627139Z", - "iopub.status.busy": "2024-09-05T19:43:12.626540Z", - "iopub.status.idle": "2024-09-05T19:43:12.630609Z", - "shell.execute_reply": "2024-09-05T19:43:12.630068Z" + "iopub.execute_input": "2024-09-06T19:43:26.641128Z", + "iopub.status.busy": "2024-09-06T19:43:26.640324Z", + "iopub.status.idle": "2024-09-06T19:43:26.644620Z", + "shell.execute_reply": "2024-09-06T19:43:26.644038Z" } }, "outputs": [ @@ -600,10 +630,10 @@ "id": "e13de188", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.632540Z", - "iopub.status.busy": "2024-09-05T19:43:12.632364Z", - "iopub.status.idle": "2024-09-05T19:43:12.637863Z", - "shell.execute_reply": "2024-09-05T19:43:12.637338Z" + "iopub.execute_input": "2024-09-06T19:43:26.646963Z", + "iopub.status.busy": "2024-09-06T19:43:26.646497Z", + "iopub.status.idle": "2024-09-06T19:43:26.651999Z", + "shell.execute_reply": "2024-09-06T19:43:26.651546Z" } }, "outputs": [ @@ -781,10 +811,10 @@ "id": "e4a006bd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.640008Z", - "iopub.status.busy": "2024-09-05T19:43:12.639588Z", - "iopub.status.idle": "2024-09-05T19:43:12.666041Z", - "shell.execute_reply": "2024-09-05T19:43:12.665536Z" + "iopub.execute_input": "2024-09-06T19:43:26.654071Z", + "iopub.status.busy": "2024-09-06T19:43:26.653731Z", + "iopub.status.idle": "2024-09-06T19:43:26.680854Z", + "shell.execute_reply": "2024-09-06T19:43:26.680272Z" } }, "outputs": [ @@ -886,10 +916,10 @@ "id": "c8f4e163", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.668048Z", - "iopub.status.busy": "2024-09-05T19:43:12.667853Z", - "iopub.status.idle": "2024-09-05T19:43:12.672253Z", - "shell.execute_reply": "2024-09-05T19:43:12.671653Z" + "iopub.execute_input": "2024-09-06T19:43:26.683063Z", + "iopub.status.busy": "2024-09-06T19:43:26.682748Z", + "iopub.status.idle": "2024-09-06T19:43:26.687165Z", + "shell.execute_reply": "2024-09-06T19:43:26.686677Z" } }, "outputs": [ @@ -963,10 +993,10 @@ "id": "db0b5179", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.674498Z", - "iopub.status.busy": "2024-09-05T19:43:12.674041Z", - "iopub.status.idle": "2024-09-05T19:43:14.136811Z", - "shell.execute_reply": "2024-09-05T19:43:14.136171Z" + "iopub.execute_input": "2024-09-06T19:43:26.689077Z", + "iopub.status.busy": "2024-09-06T19:43:26.688908Z", + "iopub.status.idle": "2024-09-06T19:43:28.095086Z", + "shell.execute_reply": "2024-09-06T19:43:28.094529Z" } }, "outputs": [ @@ -1138,10 +1168,10 @@ "id": "a18795eb", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:14.139136Z", - "iopub.status.busy": "2024-09-05T19:43:14.138650Z", - "iopub.status.idle": "2024-09-05T19:43:14.142973Z", - "shell.execute_reply": "2024-09-05T19:43:14.142382Z" + "iopub.execute_input": "2024-09-06T19:43:28.097561Z", + "iopub.status.busy": "2024-09-06T19:43:28.097109Z", + "iopub.status.idle": "2024-09-06T19:43:28.101190Z", + "shell.execute_reply": "2024-09-06T19:43:28.100749Z" }, "nbsphinx": "hidden" }, diff --git a/master/.doctrees/tutorials/clean_learning/index.doctree b/master/.doctrees/tutorials/clean_learning/index.doctree index 40ae7ff7f1828891cbb3c3e27a3dfa6ddef29d4a..41b7e3f4e1fe64f959116ca8dffca830affab0a0 100644 GIT binary patch delta 62 zcmX>tep-A(E~8;uW=>j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL=6Q^|TmXrH6B7Uc delta 62 zcmX>tep-A(E~8;anVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~=6Q^|TmXT-6K?Vwq@}yt(wv hL?$Ids%jJ_Pkgg<^4a&jgbl3v@Q|Ibs_GxP%m5TMNd*7^ delta 221 zcmaFyo%zLg<_%{!4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-L0nx00SdOxc~qF diff --git a/master/.doctrees/tutorials/clean_learning/text.doctree b/master/.doctrees/tutorials/clean_learning/text.doctree index 878a7550d9c77cbcec6e702e58570097ee9daf74..90395ba3d8e0c2e82e328ae673244704ac06a13f 100644 GIT binary patch delta 13415 zcmeHNS*%@E8P49Ph8exFEra!*ZBZIchcyqzL@-Ejz_t$(2e4VA5Vh5UMDb!Fl_&F6AFJ}UsK4Sco(m!8{eC zQzz~!FCtH^JO27(e?4cBaw2l{iaIMIP2Lz|iHk}KM!gw5f8tEdhkDvbj@6Kr? zwiUJ0R^=pQ4o*_)_~W&gO+qT}SL3(swm@|K&VL*h~-mAtn> zQX+HWz#E~HofQ{#JA37CuQ<1%jAf)+kZR&* z3^Q5MpmH$6k?554It60AvQe7$(JSh;LI)|y}#_t|L5Qz9;nPv0?kyc$Yx z6gLdG$Vvp}d{8E6;sG$Pg=!D%#Yw*S^ZGkgv2gpq(-kS!?M_14hre458*7PX0WGhR z6GjG)3m}3JKr%@uwcJ zX(owHOtSIL<)oegd`3Qa*TnIWh53FGE44A z*TzKg=^0YSGH7OnlL~2rhbq+IFl+}zsM<$24AzbJuN!SUA30zwUx7AYh|bi{#UCn~3(93^=@KI#TvtM(OcC$46vQb(>{U3hD1 z8DxvIPt~6OeRbu8$%YCV-&=?ZmbIYZCnlUxMkWf|K;3wMcc+a;GYKBF=PZHtgEv}v zp^f7LWFU1tW<(2ijhlQd&zAju_ zzr3;Bi9llxpjN0OYnc*UXA18UxieEfhMEp6z&5y~4Io7<$3*9egDV35q$k>|9;_d# z7A2-hiZUojOG~8}B1NV$7m@{)IzCx$&r^FruzMBN`P`A$k*FMl~*~Q@RxG!3YRdnS6$x z7ias)cHv>z6KKZIK{L+0A+s7dvpbWg)vNvNHx>c2rv38y^*Si6nFpI#nqD&w3C0`| zrc?J;;N*^4nKXqJjuysnrP9JIf>nbaMT8`QPe?5bi|l!(B+6yk$UFiA6-kirzxg(#>~1s;6A77iyHV!_+voAkj~5i<05rq9)1LT8t9at z4b&Lm1uCP^KM}i%@I#i%=#wI0e5&iuhBE;&OVoAKh0*A!!i<@u4WMzGrlzJ;a{{zs zp=5jYJvD9jzquX`Glo;tJQxY8((w7lLPBb3I0ewj8JsOz(6{W=EHhG&fK(+?4$zTK z@0*sqP_J)yJXS4?ANXN)Uo{jMI?>7~6s`gSxP!7u6eJDn7s7bQ@d~E2RQ~HvSG1X3 zIhY=Chpww%w@rwxb_L`FLA(gZ8@f=#Aq2`qls31p)^V^Lwx&Gw`nVE3~tb{^BTCvF^Exkbqpw#+#V;p31RGWcJIlOW@V^_4JZkW`TB z<4z10g32kn3RiL#mzBD3H5Ps0UA=^^(uvNXYlv8`>lbK1jno1Hh%f@KLR^Q@Vpe28 z4YMR;?h8s0m=MHO4nAAL1VQg(EU{iVHaroMQ{Y@em|=LDth9sH!Rti2!U5NbFDulI z?Qia=cMc0RI|d-_CqGqRv^W{~;8cg{C=}PmvnU;s7frG-?JE#a_0perVJeBR-c|^t z^G+es$Se_%6jIgPo0=xW;%I}d(|{vqVF{v1&bwTXA_rb3ve{*Y=oMqBX0I6c9IP*2 z#1OOKvEUR^Btnr4ga{%-j?*dPcIUN&={YC@X%64&DRc-L73rs@kx{`ZGTxUACgMld z`5&CrBKhaGi`#K53odb9t{4%+*`B08vd+Wo+Y<()V z3gP-hVz1z`dAk3vJ}dOdD}7bykvC8GXMF~pr~At`tq`O3qiLS*|I-JBdAdJO_vh*U zJl&ssaG$69M$OaxdAdJO_b1<9&Pqh)>He%Q3-fe;p6>sfzjHZH_s{%&$9cMc)>nmj tx<60%=jr}D-T${A7Ut>xs?Q?-MY^xYCqFZ||D4ia^B;fe(BO)}KLAi2MxOux delta 13383 zcmeHNTdZAG70uqKhWDdVN`Z3sPRm0`Y1jKVk3`I%56-1 zK*WRWAhEWPh%tl|svPlwG$woy115Z+h6MO9K~04Eqag+z`= z_grhuImR4w?6dcw6ZbxJ;(=$5q1WzEbo3`(5hV=Q(TW;Fswr)y?N*Gp4V0nzjnuG z{x=U_{)c9G{GIdN{!dk>4L9vscI;&5AJ1gY}tN; z+m^Njw=E9O+OxVlbV;>hc=i0U;S2LChyR#whCAowfAMh#_w9N7f>uNpgo`q{;00yM z2W3r`+D81wxHNp@={w7d$P1?)JpaI7j+(PP`{-%VN{S@7<0+~v@O2JSkm2i3&o{iV z=AJ_<4<7#U%SW|bMvp(tUIZc-5nfA4@x2y~p%~40YsE$V)*e38KQ1^)yzo?DXU<2L zGdDV8Z#qy#)#P!dMg8NhdUpBIt;~sVsg+P#2+xGKF%lh((Og+-`-_`z3TqCM7mh!= z^|&9Yy)sO3p$Ij^I>k+7QBsB+j5k(X)NkyRm)0KL3ZYG(18gb^m5Ei-rl6Tul8Pw& z_;JNW{o_vf{edSN>VwdNWX35H!J^g3264(!A#)6)m-bfQtc$De+F!}4w5ogc!Rnb7 znWlzE&MXmvrsx@1$RwE(?!XE?+WoD1>#~+*YEfq)d#i-OxqQw>1;r#w*cu(}KdIhZ zH7aYv4YNWRBce?P*>YTfzC24ocJ$49#psm>>fcnwz}?&<)yJDc-0t-kE7JY+k?Pn6 z&-ViRaamhL=Z-j;h>0p@ouliPAFfwC@kI66Wi1Ma3ztI*ED43;OvDAQZL(QAn&{~8 zErX}3R(VUTCyeoA@nB^@(81}1BN=3gj;=UZ{T%05Ixg?_VT(;6W`7RaJ^G`nX-r>7 z-fBj;7n(<-tkT{ECq!mhjdpLVuV2<^CuCGo3xz9o+L&m$2TX-i7NG4f`qXaI|K6s$M za=nu4)#pCEVf$5UcJ5r)u2Inl&Q&5FUi!L%TyxdBZpDT5X>&`TsXKIeeL*9@ z3rcAgsn^0Au&IyIm|(bM(U5Ncwg0Njlntl?^d?ObF=mrUV##Hms7H3)1Z8c=!CM6{u;+xT(AQx$5$^6tjEd#cD&h?)mDt7IYaz=C~Zj zM3&T;>=`Oi5smX0)aIBgB$I>$f?t8dd<>Q-O#+gR`UNM13BDRsI0}~tOSlzYMW=Pv z%5xexi^+~Q9juRBB1sO6g zqZ5G(>$L;Uyv&>gCcp$_N)OH@7FTd$mB2*I@$QBUZhDFmJDzZ9~^lj_cY zwK{LTAbbI)eC+$ISD8_X?RsOQ;W}H3eF~0B7-ys;0!Cnqz16NlLhNFQl!|ci>e6lX zfV%hCdSzQWQJ>1QyL}%Tyr;=7F%AVFJw%Ep)CFln=Fw+EWpLwWGiLmT=EM!v33w1f z2IWz>I-$uzJw#19P|u3)^>5cJM}K~{+EF#cNNH3KIYo5GHK3+{F4genY0qk^1g3OiE?x)tlWOB@uNa_k;kJydcRd~s(7=SS02}Vx2ChWpgmMV?UMRK@ z_8v+h0+{1A1$AgV#D$jxvO!OqaSIv^qR&=Ok<2mY0!F_`7=Z<$9hr8sLd@>Fkg>&( z6QDhR+TgqksU;iVR)`pO7*r2BErrg=kha`r86~Pts{r%5w4Q z(rq0Z%+0m|U+Knw=TBLg&0o0vsniZ=3WWz2TUooHSG6PEMPhtSH|NdOLFCQ}+h zq6=Et?ccAy*o#2U`vJ!U!7$bJ!>5rN!(D)x?0gh)R?k9RkV$Z7y>^Inr4fNc7kZx_E?Jz-*G3&7in2Y?7}1Kz+uf z88mnZ9u*RBCWXNqYI48?gW`7RQMn)SR*i1>S@pfDDTMA0f4!#dl7V3=bek@!FK?7j z4DGYu5)Sq194M zV9;cE$V75&vItOuc0~WyE8nHVPUgzC6mo*KyDzTK*+9j5y#QZKc@V>PrV3+oeN$Kk098eY!pd+6Hc-P&`s}Ez7V!0xFLX#R1$&rbufj z0m(24KUsJXtaos!a2O355!U*5Hn#?nn&2{+K}!^%8V@xFovA#5L^XUOBAY_+9&2o_ z5c%!i_J*s^ZCr>Dw6IwSGB>{d~fD*Hitl{l`-BNfW%m&LLBjLe03>w5cn0f|( z!@QZwVT{V!!Dz)|0{UZ6rbI$^xPG_>6G3u94j01aiI-Cd*)4znz;sV<9-Mn2TR5vJ zhH-^M8TAcKf{CS7S(=zU$$_|Oj*9-|w7nHl^G*?2sLRE0D_mCW;Rg3()!fntS^zdo z1c~Y_XaL9r0F@-#9Hdx+=gQ2qxwRx?5CFDR?{-0fI18x>gAH@S*hZLYNF5<}l)-=l zClcQ{NCjpX?d6L@4?u;|GV(H+R>N8qTVDL)F;b=U%Xfi4$_(t$uz-x|7xql7=q>&+0%wEvIQo{Ab z_F-gUN=va@{%C#rq%*f3O^kyXuo~|lJhK=(Z9rFMuv-+y&52i9iaR;T(qSc=^t3PC zRiAsISZ@}zG>tu=DNDm7TB)->QA}$Ab3f(2S5Ra9STf_M04wEYF=R?5xp;Nyx{ma- z!ilE(@z?j(_Z0o~Nk5wz`7BY*rJt#n&QTG!0T zpBecxBY(jg=$VoKZ(bhEjQp9A|85@;dq8TpH?`Tw_(uSbWzJb2)!(uem)x86NiJNPHA;zaWR diff --git a/master/.doctrees/tutorials/datalab/audio.doctree b/master/.doctrees/tutorials/datalab/audio.doctree index 91c6d7ef09099cd85c61cc57010b744138ac0c33..5cea7eca75610d2d705a62bccbc3f3a06eeef7f9 100644 GIT binary patch delta 8848 zcmeHMO{iU073O+Rz!w8)Xz$w6-CWNU7=mRk2i!Py{Iv z92Bh}5%rLP(20mvf`WKKvBa@z?a@#*@kc{ZF;F>4jbg_ujBP@`e*C^A_osuMQ4Xq=PfTQ_!| zzp=Bx=RNBiJIlL%){COax>Sw#hRFC3iESuF#o&_;X8q8`?wM|7lh8KT5{(d~5__g# zgSB4OB&r|IUg?gl&ph9Kcd?Qjh`5v-D<#X3qIKS}(-dSVejVOgzOh&}!Vb@Tp?j=v zM2*AWf4BVT$_WvpC00=-l2S%0*=sKnlM`&$mp|Bjxm#5qH7*v5ubQeYUgzQr?nyR! zRfcdL8N7C`dkJ@|A_l@`waipgU~8)<%A~YoRs+89*!tSnyPq%mMr=9UeRCADiyL*3g_|Uf(ml~Cly9oNJ$3J`F(Z@dV@FN#=qct~AAN+C@cb|M< zxaZa7eSIsdu}e=5H{VNyJ3waDrfkuT&~5@72UdQ$|+^8?givejti!h+DpW4T1B zR@eX_)6{@K+Y5`84>DUkipmveXTi~O@zxq;ob+xw`jwZuzbu-;hu8nMJl8j3%Q2fX z!wc7!N72^A)ztv9$P`f>_DKd`+2&$XUIS79o`{kw@MtXnnWM#7;jL3_aLF2m%dakH z;2pOC-=J*H!7(Z47#TP%Ov;)Hy`xzh@zWmo`bPXZHmeve{h+&ll?`6q`9Q^J%E(C? zvL*xyibVA5k6lDUeG)lKR|<$mQV}`EU_HtNvI))@Jt40btd*-=f#6C$MmCa>ht#2> zu*$7}^~dG!7kwk9o|0(A9FzFmY3m=o4K_R;$UH|6dLy4|6h?YqN}^he3S}*?j^&|( zqSfG}$)E_~OOnEmf?#Df)vmw#Pw>K}gDV3tYyhp%l>Y_G)c+tJDcQVPSJ@At%fdN1nt^g-NIay2f6K(V^ z;X(v@1z0GW$Tmu+lVf8dias~yab&7f@)f5N3HF|YOrpe+09-RXb-ugzmbx|KPQBR* zI|1yio$gdmwg|jf)W8-|D1i+0D@zmc{7kczU7K}hhf*JC2@U%z&3`P0Qpi;@Fp z3p!GiAoQM7l-kQu4VZR~qc1}U8gXYeJ2))OYWCNzUybftsp@!?Cx-X2Cc#q#xZ{*n z8vgKUJoVc*mrrzk(aFM^NC<`_lbpBN`Y0(yW)Z8IB`ta93tT4t89<~Zz(*SvRaRXq z-03W7jlgQkq!n|_#0}s3M|bM9RCnlFAsN9A7M2k9*pBX9qIuwZM_NXG?*7TBYY=TK z!46r$7sUie!7=A51))EMpLMNK8rp;n=79rSa`SZSwe~^Q%IG%8dS5YsiBw&-frJ}t z1eHehEL1J;H)lfTUNSVoLd;SKDrAk}ErOsFT;blZvnOl41ZiPhW8-kN$P`k6<-*9} zG48-|&M<2Q9zOqYcXri^I}JM5mq&*8ezH4)=}8J}P{WEl032S#aX!e-VjN{X%R%o( zyqKIFG9Z&7f07xGW^*dGGEd#P3eJOgoItrT$+8O}GFrKKR^Dr|KJon#X04dBrZqxN zF#Gpsy4@96o=jmYB*sfy6}ZAzuz{2?!qrTp@gB@pO2YoZ22#o(JS$-dv+!Uyygg&E z*&8gMy59X_oR1aEyo3*vq%jPt3INOMw1O{=Vn$jccAS!Fgq0K0j-KyMo>ufA-GQ}; zS;7cqDD8nOVTOcJWQHf!3eLI0DohMgG09{lk-QRnBTaxULT*-p{keu2Z;cwMO$4=i zbMtg=yxBh94$dmd)^~kM-&vresU5{+nBk!`h+Z@>b|LYOA LzH;QyuMhtR-81M? delta 8724 zcmeHMOQ>E~73TLpL2i9CrD?%}_dmI|)IplNA8Wrlt5`v>wjq;<)^tDCwxHb921Jn( z!9l?~Nl_0OIOw2=4~l|tz@o;n7MzsoK#3!%nPlcfTfcM9f0KI)y?ZV{^X@N;X6#|_ z+3v|+wqpO|_2r{|EV5=YDjOpxlMZZxAmt<3kgT;+9(&!Y7;9@O+F6qLxR^+$s)Wsj zjd46aCA;4*dTUvR9PqdB%mWerosf(>pJ` zaHiiW?5r%BoD)RO)+nN8n*u8@yr|>VH%tBHIrDc;MaWE+u=Yz`v6OAl*{Q5t; zA1|)7I)vT;3_?4y(5hEg#V6Y~Tn#&G%yNCJ6l zgf(LN8DXuM`v@DZ{GfZNH_-(b0Wa$lvI!xZC?}$f#bh)0W3Sr|3Owp4fkh2bO;a8s zhoXE|!43V(-N(io*Oxz8YzH(dD6IsD1W!P~QkNtphL=kkU%52#Nh|7{#_>T3V{mKv zZh!J4D5$wHPeL?XH*#uq@CMJavSf^rSOy@i_ z?{1y=-r`EDFGmrhkDtc(;OqEODR~=Tt*j2=3r%6bDylS5xsk!>WpZTT!W+7=}N8w7Y*6uRfDYAv?#y1v0>%BP)F&#}Vx0;~3vr-dyyp zus{47gzMO#rSg=lC91NM~5wC^PLI((hVsp8*a0qk6jIzf_r&Oux2fc#mxqMyV}cm;e? zOdMH2KG0upW6&k6lV}ByQ9Sy(Rj=FNYNd1sTq`2&v=tT(4BisX zLP+7QM5l}Z24Qq5Y;>zLeo$h=y?v2-%VtDBj-QC;HD&d{6VCsTqQUcX`_>9TNsye*# zpXGhy>R;WLx|M>90)v7SGsu#?7v!Wf+Hqxg#CbMX&?x1!LW6{ZUG_nXEV3`91b7=Y zo_=fcUdKmOVj4}^inx}pzjpm92|pDSB$Qz#giHzo?4iPvNhmX(e6@QHRF8@}f(CiO z25AFfPAG`01Jl`=>TjIyez8~yn0b&(^udsV8Iw{8Q(Ude6&>t>0v{jM%q&qGVP_X% zxsO;S zbQCnLc|7{MG%9u*Vy(39Kx|vY49GZ8OO06HTr9q*TCGBdjUWGT20dNr5DF_-v#IbH z$Q+wWHUXOr2kp&agymqJ^B|oBgn17aVlD8P$O~9&&jfhWn#&9(yYwckAfE$RHMKTjvfbQ4SUm#XK zx$NMF!9d`A8>dw+L3J_H>!qa`bEbY2?bw(z!2bLBZU^feHpq#Tzzwhg5w>-TZ7P~X zMIHzkOuW`G-1t7g3KE4>r3D4*qC|=7)oTS`2#re?*#~F`VRsHzVjol0LO_PA4}cc0 zf3y49v_~Evc+R91cgn;KcVFlpJS)Xnc?f0+Yh*GY@oBw4F@p#h8L~(z>6Au%3N|nW z@`mML^aGYx+X$lc23Dd(Zz>&ZV6E;P#Y}4+kG^iyEZ;_0BcnVctX}M{HjfPR2DUkH zYz`c)o66cHZVnuq1IOmTu{m(y+_pJzy#G~YbKuw$5p1INLCF*nWu|IY^wH(vYjiC^FKKj^2vb^rhX diff --git a/master/.doctrees/tutorials/datalab/datalab_advanced.doctree b/master/.doctrees/tutorials/datalab/datalab_advanced.doctree index 744e87f25b431b3c01a44ef7b49096177bf55524..9474aa59a2236da09d07252074f8e2be27efa68a 100644 GIT binary patch delta 1979 zcmeHIJ!@4#6y)v`#OFf=F)1u^304}+ew^Jsrx67$1T~h5NZ50C7Xp?Nu!*3JA3xw? z<8Me4Zl#5#g^4zTugW7}p^c=ph?@u!vAAjM(k`=mX3os8+iRokwbAOvF_o7du20Fsz7F*<6?(GoiXqZO)R|Ays*z+vQYi$IkR)PxUls?;#E34Yu3UIi^>g^~Maa5;`dB=yQ%KNc z^4^#REFfuV(8mVAGeyGvdQ`~|I*HzC3n6GCq+pqyg4hK7N6!o(8>7MV>T#b{vvc+A_1kwBZ!TQDc4M(Gw|}F1*5+pK&$X-H#MA+_ ijm5ck_+32fFT!CX4;y*d$Ui^H|8Au3mQD^{9RCH7_CXo| delta 1973 zcmeHGJ!@4#6y)v;h|i#cF)0Ld304}+ew_VkL_rHdjisUz_MF{C8=HubMnM}te!#`X z-|#HLt+cSTFwsWvH6{csOd}~R;`+3RjW>;5nk|-dn3*#(Tg&5H%j1L9{o?k0BNp#2 zEzW5o_acgVZj^vT2+k zr>I$4s~&Yuwa3=0`LA_!7P1hAvLc9x=o2OmQYrEo2%2;2>_~ffo81_zy-ooIppBRz z8-bpPxDI3?I;8x2_SAd!yqeCEgW{P7sRC$@MM4CdctlWI>E_iYn`qvxvdMOPg}tr1 zd8~b4S9ZZ*$mW^{A6fsnAd;93ddtgolW|5EAyNn?D5NHQVMqVSqVin^NSWxta^oH9 z1X=Nb+7hT=vZk6dKiI)`(CfXZ>Kv`gBmuS8zzYob=uEI2yrtlHTNYkd^}iXo*nI!Y zc-@UYWcO+e%7aQVdB-6ZJYlIoY1EN4iLlcq@G^1Z)|cG+J@{z)8AxIx@%Ch?bUIwj(c@f`oGuFws#Koo*noJMa@pS diff --git a/master/.doctrees/tutorials/datalab/datalab_quickstart.doctree b/master/.doctrees/tutorials/datalab/datalab_quickstart.doctree index d1a662cf0408cda197b4f34007b4db989cf3b5dd..6ee346b21035f7700356dd7aa8a9aefdb59747c9 100644 GIT binary patch delta 234 zcmZ4Tg=5JVjty5h4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE z4a}0vlT6Lc4O5$0x!PH|7`L->F)=DASQsT+8m5?;8k-oHo0ys=TACUenkE?=nIu^n t8zosF)=DAB%7z2B^jkA8YY<;n;4i`TBaH#nwzCrm>3x( try3@uY**7_YGP6%q^w3^y0sS5(&_oSOudB7l+k1Q%}!XExf#=2W&qx2L&5+6 diff --git a/master/.doctrees/tutorials/datalab/image.doctree b/master/.doctrees/tutorials/datalab/image.doctree index c3ae1a00e01d8a7d57eaca1df11a6b44a12c1e19..272a5859e8964c45133e4d3126d7fa74c60aad86 100644 GIT binary patch delta 28590 zcmeHPZLFnLb@rV1%nXctjWB>9_Z%jO!oZ#V{UJ6m4g8>r0@_psI_^(JD2(D~6e${Q zt+a|)^R~vcjESa^w82n4)>@S|f`v2&Ft!J%gt#v>5z{#I`;N;sre>lxoUY*}8-|Y4=A31YEJ0DXLE_-RL7TyR& zN!CPp?WNW<-Tv=~f9mXs_8}9^j7}0Gd~h*QW|(z^GMl7ZyWz5T)d!t=`R?1VHsix4 zoN4ZSAf5^>BGoRMq!@9;+YptJ-Rr7@%Ip08;b9Y@OeV4{K4L3EIqwq1`lBM8IHmBq zcaLjh%G=KQ4ZO`rr=lZ?D;kCO+C&$GQIbh*WpuGyTy;=+-El8_(P0y+EaN_UM_d-# z5@R{VvbL1krEy=CuZ zL&n$M@h#a%tJiLP@Qn6%o-^3-q5FPw^JBJl$9@0WKiYfLYo~ql6LT+a5A7Q4Sv%pOlh)4t);U|A@4fx|-}=~a zqKH?DNXNA2f@kgsVkLJ?+?&BhX&QuZon zF_XB;pz=EV!x!(^CRQzDYu7v^hnBA0@n7%W`ryp9zj*ZUwc8(jVB?FuN6wude(ByH z|J{P`er=6>|M0crfBNx_F|(QWtR4T*%O3ae_PZYXalRtMpAQ?YH(ote?Ly>iz8 zA}7_H$eq-lwQFFosV(2L_AiedloOmi-`jrasKGP4U!E7e8=hpu1?{e52ITAeQhHq;?|uPJne#Dr)7Tw*A_wgRr*WORpMC)2oI* zzpDNIKMYT3Zy7+5FS~PiT>GFHuC|}QbGW;`?H$A8+jH(79@Ad`_TjVJqwZRN_JQ*3 zoVN^5YX9->;j#U=x88+ke{=uf+3onA^=EgNXJ1gm!`fHhGkk78?v$_M*)Ja*oZ9~9 zTZcQQSAKPP`QT|-!t~aAhKGjZE3Z2c-5ahtaOHK^y(vv5-Tz+~u6;w=$%PT7b?+S< zdlXq^ghSzXO2Rbho*h}932DquZnchNnDzv;W)IhPSo{&mE3d%8oCe-~QzXo|64va_{ivPwNWS20t3N z@A>-hz*Bt-dR+!S{MsE?eE7AyZu-ik|Mzss;`HD*hIgLU{`N11DjZe|yHS@a?6)TK{-``S{7% z$LF+P{uN9}r}9_)vZ(z3?{rg4_laTqz{6O>>ke;DI(et$M3UJ_um2#cL;;g%(>$jg zZ)RJ>`pNp};$*pWE5|@v)OA5zO(dtdxjeEc`WTBICvpMhUfK zdWbaFj3$|7Cx}U0FfBAI(V)s)TNr>#27~+h;l}euoR&A6;^b&}Z(+3_JeQ7XG zxMz5Vj%NI>QO?K`1q73&K%ir08^N9y&e?CIHf6t&gMZ&_Zx7n$%)R2GU*C7#6??k7 zQdxLHAc7Lkt(G1E16O7dwTHQ&HDy7)b42y zq~yYjUwPo7m!5yYix1R9cJpXeIl4VpoYmfZdUO1wvNc_f<+S#tq1iUJh{>TLAzO=p z6BiHy<<`L62cwYO^cK=wJDP-;;kSEdl~W=Ii73}n0_Dwwg4GCfYB){^;RFFSlL-?D z$SjBjkTE9mEE!MJOYUucG^ownUT|Ua@^NL__QxlVNc+PJo1-U^XhSk$Am$;WO!}-T zWt@2^qv6{0BD#Vw8d}CEMA?cUy(PqooULReNYd`Vso>~l%^N$(B?d!0k`<74=b7X= zBDQy6Mr3=(&mkut{77@_U|d;5C$qIR&^I-&m}rD^kj%tG3_@f5UONI-Cm3deCbR8~ zwF@bLWuV@A0d~MBl7;mdOcjM@wwL_w6Ic>3VwzYE`-G!nIr-?Uj!u$P9@}+GQd`2z zk}O_(fu57E_|IX&Qz4lR17BUG9J_lBvVB5F=39|^&M?2l#c>QR@ z20<^Og^a}c-$hzGMc=uQj^5RRD#+JT~!nkCQy+$yk^5RdF}Jk0h(dmOAR zK(zN<)m%D;?O!-IHbmO1uWpVSYaLt)S%m6dMr%Y1XJNO!qv|7Zq>sTVX<}z?ib=Jn9Rm=PZ{W5Z=&Swmwyf$4Bh?Iptgwi z;CCB3sjQ*1ksSt}K5-f(M$#E`7P!v9ZkcgOFmANCE7M&cfSj(BZF9hg)<%%Rdq9PR zFq%5>ALa=*_0hqKf&d86qnvYL5q%5XR5lJ)3)akau0X%3>LPl5l#3TJ+f@gMZ+&O; zynRfr+Bt{*EBBya`!IkBbw=Nejc25Rk!%F*Jmkr?Zksf#L`^E?c3Z zw-Mf`3Q7ymwY1%T>1g-NCyiiTl663wvQ|wktT{9nuq2d>W|L1^o4kF=A2lzo&3)cG z8~Qvpb4Mjp0vM&NL%IQY=Q2#chl)A}H1l)j1&mVQ37Hmearr7ivH>Pa2j-au?1w3g z>=y?U4fzDPOAXBvI2~9TWMNnY{|Y}Yu6u8liA5)@pynnlG&KyG_G|^yll`;ZK z=9Kq>CuD@+e3bt-ox81E~Wz0Yk3w$jE{tHZ- z3|B=Ky9`R1BS1R94}86|Ag6%t7K$ZfV8@EcmLBSH5w>G37i;ml8r53vw^P z(!+YfIQXEM%83|%eQ;5NDdnvOY!*;KNCOd6nqpJL`W^$eO6^3! zNF(2b_<`aFb0v2Nutng4#1ZwRL{VQHj2AA#hhAVS3+OIpfBTxxHA_XYT2r6&;0>{Tj>LLNOc;7t2jym$4hd=fUqST zk9sHcl!b}Z_U3a9b!WBYw4dFy87eod841`-zXG(E?EetS%pw9b*h!INa!D#a2@n!-J1U~JLz-LtEZLhemxwty*secYn`uh6jG_jY!CVngBuo%o`2gpu7fsk@_}LIu z;t(bg9snl6foo9+x*YZMu32T;bv3KZTg3C#$m&}x+FNtr_pT&|XHjl2Ho!S7l+P2D>^uPwt4hY~J$*|i(AZ;BvxKDT|rQm`>Li^hV z)hPu*Bn2E7N+Vy66gix6iINNjE81e%jP)GD6BURcDOidOaYnHK^0sjB9Q=l;z|4S6 zoS|E7_JVE~PpXq+JNwR31pj7kCKr%Ujar!yqW~k}U_vO(-g5@(B&6y7qIW9+r8r3_ zW|>IHQv$q6&V`2okCIc*4z8efMJXY>kQlwyDplx z7ufed+MEu^GLZrb5Kv>8Ft!LV7&uo@tiqVk$F5*l1&%d=^i51SP|@%b;aI~X2JB`o zXULXG@P)y_O&6a7&PgJmZX!xLWI{z!56~-%r|cuu+Kd}IcXIog!$!~Af$T3|<+AA9 zi7SB@`;5RjA!t^RjsPVnPKbl!KxgrIr52~X?PEQ^33yw4KU)}+ifnFC&)Si7@V4ha zn&ZcdH`S3&ox*J&Q_x`yZnHytO?iO74CW5z+$WTBfo$$Aj*1ag4+54l65K9DFaVbu zn1^2v7QEmFx=nz0iNZO>y;{M5azsk}upn08@o>_s=A%DtzCEZ--hS@|ql?D1xi=v0 z46&|n4wW7dKNUf9VxjQd~Q*%WVf98RNm0h(!k25D!QUWJN0=U4TS@6*aV{$;s)o9qI(4!!R;V1wh!K08E z*=ZD2dJxmJWai<0&L{aM4g>{4A(T`{q){y@`kXZho-N{$5=qVLUv2sx2P?A|GSH5} zWFqziCkeELRms3#Z&N`L#lV+M2VVg-wt{Q*DENj|07e^&Vq{~Oi{M)$T)Qq)uvOu} z?NREG1x-X}pddwB3h`FVuvI1~y3RyY7SJo(c<};43BPHtYsj%8NrFp(MhJ_80}YET zCd#-={#ABR4qc;(WREXGj-Zl)^$OtuMP)%jHRMz~U0V?jZh+H1cDNm2EJ{MuS;SXD zhAC{)m%!jwX6#kXRc4%1wIlXI)r^@_HMk(CdO#I)01srXI*qmZO5f4gK>`>gSmB`Q`x1*4a$lc*T&Z1;6V1RAc z<&t2JY;qPhrf4!UDs02At}LP7Q)LCSik&X62k6_gkFN?nr;)~SiVQGvI)zw(vkf;T zbLBv~A^?Z8-DNOOSy)NmRYy#F?5kYa7AB=4yN?S47oXd@7dozNYA&sZv;Z$>9|?Ah zG87oZ;(s|9({0$G(2d}(9S|fQxw5Yp+U?vDEAxK2hbt?2gDb#?>@_J(glj!&1;1L;y(UPD<=M#br1Y>ZU=6IKJW!{dn z7+0q4Q+p*21VyQ2Ni<7Y7Kk{_0^M-%$QvNfKVOD5LCiV5DfD)8P7y2?(?ofkFAsWaK*izDGhI-$*GWjgAP@8uS3_Il$tAflaAF_`i z1|lkwP-11_A)|~BwHw01fkJUoM~?yHE8QIPa9Fvmtt`x9VO5*quyT5NrhX@kE4!MD z0WDAuvS~6%N~EE2!^neqh8P$LGBz{tU9f~G3_JzuEOIQ_SOoqZ30lfSn1J`Q2@)wd za=-*ga^#PIGH8WC{uTvb5lKO^NeL?}5bGgeW%A9C2!|3ngE%lHl*2)EfyqeOqJ0Y? zEVQt=)wox{Kf2-IMcaDjHuZhD=NY~xr zElOBBwsj1gRCd-C8_aSKsKP`ttI!W%q$w$7RB&Iw(j(c##d_{x>}hfI6lyt`gue;; z6kd@*i8B%k@K;+Dgsx}$0t_1Rcq{^mk=%-|)H~-0e+tzWHupn&4yHDFmwH%PJa>D` z6(hQLKJkFYUL^mKx8VnTdFhl@U zQ6Uj~*qBI|6Obzeyb~BJr7VimGhvdG(0X8aw0%Q zY@?Alj>rU|Q`wduvq-(#CO8jzwfor&V-?x7n@3kpZi8=`RJPTz!KZ!XhHW=jI}B!| z%d){?+28=%`S_-aKJHsKH~_XcdP6o~Z`t6mY;agMI6Of&%9gCdvcX~5;P50(7Rv^Q zWrM@A!C~3puxxO6TvN{G*l^k4u(h>f+2F8jaCp+rlg-MrY;bt8#)@Tw!?MBQiT~8% ze3GHkg|a1eUTMAAl9pdKI6O&rMM?858yuDm4o}d4vL&mxY;aiAUD21eEE^n_4Gxt* zfV*sPST;B;8yv`lEE^p9wvdg4`?A4d+2F8jaG-KCtFmlxSkzsyY;fp`v$|fsWrM@A z!C~3pfWL%PDVd+EuUi6Z%Gjcf zI;Er!A8Dai*_D_GCVfOxl@L9K`T&Vyq>Y(kwGUdPHrAxJ1&g#&zOZWWC#*bb&GQ?P?5{XP2VTAW8dZT z++c=BjTGgYVFpZdA~d%qG3|mDNy}tYZQHLazLdYtU)n!v#2CX=oD)$q!ICnLh}sJ- zqUXtY*?wK|rTldlzY1R$Y0^np6^XC$J=6um>u4Dk>XhQN{kq~y`Rlg4{?$i~M67ir zkq}F@a5Z z&uq_4+pq0gyY!B4%1U#-bo1lqH*Yzkx8e66{)N?#+0y+F|5Nv9`*AyWz18iBdtW{h zi}^!`zW<8mTffs^-yDB@@6x6E>zDr6_by*L`x}2a^~KFyn|s@qPJZ&VrAxkf@tWt` z?|Jl_AL@?+r#^UVCB<5!(_Yl1HqmO!lOWbN`_Ag!GAz8bl-GLA-<@#GNCj)1Oo1m_ z3&xZsocWZZt(8+UrEcp=FXgYZ-+j%7b#jp?vb6U}+1GmM{(rw^?Sl)J{`5y1m+pD| zv6VmAe(dz_>7_$Yd~wE~{mc@1bmP)V|M8KPcP1lkTRQ2<*B|llo(G@&qy8`k8x?~A zF@2E(>Lz4X2<59!J5|mIcq+CY%g!%P%R#3rBElto| zP%f0k*|y(Rd=?f9nNIKHX>)Sl*TU+!;dPI$JrzPa|x{gZEhw!hfi`{n-D=E|@3 zU)sF=>HdYyaS!50{b2XwV)GYY?Vs4ZXY%8P&F~@o_{hqS8@__C``|;}%V#wAJ=Z_A z`M0L{}t7_Cd^|k&T?bLT3-u9jCzVF=iliGN`34!T_ zZv6MwRXdu!hx+=bb@u1vXwm%UU-oys*jMM^3*G$gtlHnRS-k)H4cEQ@`pxhA(&YII zHR6Na=l<8M_=PT~`S7Od)bX!n}2wwzpc5m*Wb|G`%HhKd0fD;EYq2h?!U8}eNhHKtNHVX`Wwgp_+0;%esjyl>Xb7^qZ{_!v}^a?wC~2Z zxVP@!x3_Z*nDm>fYU;AubbL*yR(EM>9PU%IT#l}JPv1b1z{XuhRP@UXdxxPAe-A`osS0Cyl zoUE_(i!u6A?|Z}MQyVJ(q94HKiA(vVD|#<^N$VY&n>SXcy_h$1{P9iIM@}4R@Q*rz zKL^DGPsu3d2xDM&(kWrw_%2fI9gM(Ez`cD8K%v5T=d2(Byjj)3YEb9~ubnu)_44Yy zy`i=>2{jQyB`*Z9qOX$&{+A&-Zbj4k(qPN@YiCz~-7AjXJa}&Px?y4P=F)dnUl{lwpXWPEblHjY0%#B4?RhDdR2k#!k)%hr&WKwRH(( zH9=OvuGfa(gs~IaFRvy$ME@oI5wt3=| z0crLwFd>o$C&^f0!&fp2%abzHdzYGnIz-;o~rf_ii%Ey zL)tRle@pf5-oe62@ol&rS6ubRU01&Dvddqyt8h`n>bKSGeG}WR+tJ+rgX-kr%teKm z5BKcmb)i}}a?vOfjPnqTM5NBDx~?NAS*^TwY;v$eDsb0oVi|6+sBJQ)X3^eFNO(s7FQUScbBvy;P1Ln?S6NG@(dFc)JAyTQ} zVeF@0J@|aDIArHEN+WhoWB&uy`sN4MR_9&F7TJ`k$;fg3F={21un-r;Lw>A%rF=@dK{}EHB?iLiwN13x#>8EV++t!p??sgg_N~tL~3X% zic$|{&vh}e3v`9i>*k?7)iuMy=xv~DZn&X3ZUIpj;)}uIsT#VNG@MdNO)|O`nlv|G zRc#&Ld3SZ~V4;?YB#OwvEYwS9tx8(emOIWBWz7?}4^F!MRfEmrSAM#>qc=23!aOxJ zNrmu2U4p-_O5D63Sb_SFWSVbG9gs^i9wpF6mtw;*+l z9xfASBqBsu;x&|0Wpm;|u?9!K9KQ=Q>6TWU1ic&KyA647dsp?c3#DDOQ>MsLBuEbg z$oX1mxHb~JW4MycC99gN4y~Ns>~z5xXZK;myuz8Sw!_k;UH!J7y>oSrdAFTgoiv)g zrdmuHBEVrnxC4G7TnJ%3!3J;-E22qpF$O%`HyAQqOIqt%1IR%}4o-R-V3!o1WhRbs zB|h9+@Db9oMJB^CY$dKYd^DpeI0VK-^X1-}k>=m@hO-9^&1-+RdQEB2CZFqhY=Sb8 zJi#0tPZ_>Q7ag)PT<9dVhI5sEg32UT5ER8}%Nkm)c2o)OpzFp2x5G(?%0|G*fe?+` z4k#26`>Dr2tmZ*T?rNVc?{f$hg+V*hD~;KOiob2D^GCpe!aEE12G}Js7U6)f$?_cD zENvmkzQIC-_#6?@WkO)|IdnJzZwE)hgbA$$9bt7o8kn4iNDWu245DWWl3^?0c5B`l zH7pf4voMElQFitm>Z$nm{X456l~yk@z5A^zXp;bw#NZ?1bP~=+ICTf@n|S0aJW-Pa z8|sX`5G-rB7r_-i0M{a>w%j)Htw`Xr(S~k65VObg4 zoYTV1g*NF2=3%|VMU^;mXABjvvLMMcFIsSfQ;7N;S5G*p;5#F+(kc@G)<|c3LnIV% z5CQ48GSJ%^nnt=s$l@T{T3ubk>O3@?L=u&H}<*2n1&X z#}B9JFe@ekGD9qk0d5h(abCpK3X$G{25AHbSQ`Zf1;wpvt0y$b5OAYlY~+BeumT5K zXA%7)JP*uyIw%yzrS1J37RJrNn>N3AZ$*bdm;^~zOqnM50_(joz`h2V6l8ho@%>K$ ziw%*VfJWDggY6 zlgrxy=fW&vx2n=C&ia$;oaTfd4qn#0_kn852DmV?sA%)b?^GwB=^eHg`D(;i92lHI z9W(>BhIyIPT>Z1vNt2*n$YXb`r8Bw0vDK@MsBlHi>bDD<$CpiRG;?8KD^t-fmlAN8 z838GSd)2_&3fUSB_LCF?plYL?0+dX+jlr-Wh(s)j1nECGVc{c>9Vc%Y-Ux2gf_Eg1 zT)rS4*FPC48NwuiaSA_;Itzn`=DLTgt44*v+t__k^UTB5F+&50l5(Mh7opAkB_OGo zzrZkUXhXjUB-H}75jPSMMB}>(z6Dz#$+c`+g9=cOjhJ{f(p7;18FhUfLSjD&ra3Ank3V4`!;4lyV3U|;Q z%!p_Ww8`*hilBfvAxI{ur65Si!c(}3GtoAO66APe4jVO!R&rScDl2f@eEIy^Shp~H z*k=DD6&n@?or-iPe5X2pgXT&u3e_6jDAbOEV+#Y-3p4hfL3qO|L24te*D`-C)p|@b zJ+SmyhqT7#N*8ps%@ua8RaIJqSz6a&n;ZE|8&I%OE1)M=OKXkIg)dP{L#ZYmGQ)*} zbEO(7b?9aA`-qCU7=wcBun?z>ZovUyT4!tcGdMC3elQ2@s8!s<@;bUTA$o;cO}yjUF57a${`I5Vz^BV?hwotWEFlJ{8r*jt*JW&Z~ykeb%Qf!7FRXER9nV~gzp3I zn|WfZt!(!Fm1*_crCmcD9Bpfs&aJkL3JYsVek*paUx*0ZhDC^$0p)fO+5rcGL>U!H zkWM-QYN*;;C>!x2D$HD+1qkIpJ*-j?&DvA$q|Om!ERa4EQF4ZYpa_*yX^=w$tN}s9 zPNbU7D(UROS@ZWVAG~&J=ZY7hfKtQM9+Lx7wF)SGgtlkaj1-G$Y>b{cdQ zk>4Q;g2FFP5kSD6Ou!$tcYEr>wo1j2W+hQ2m^Eb2XnX*ALv98Lj@Q5r6FZze31I3r z%TSm=>tslC`nv~5pGn{f;nhf8LzV?%$LY`-1xPOO+BdhpaaoZV1`u71gb4@~pe2PO z3m1Vb5X{VKg|B?7+H%CAAiF_~wkYrf=n2q~Q0!R~;BQb#K-=-%zn6`0<{Yf-)>Ih3 z71v4AilCp}H#mETP*Vi3P7uoo2sK!#pdh!57;s*cnxa56tU@ov!oR7cgD)J~YU3(h z+tqJp$#T}-O(5yX!`Vwyhoj>V`5;_b544CPPNWemq;^K5i?uQgF0oaDhY?aCl3*z2 z!#ziG1~39*JoLtzQ}C7sZ!PB>95POz8_*sT_7)Nzl5V&@4DuF)P(GD&7!}5D?eNM` zVeD4bz34o#92yBh5w8yc<+9-Rpv{=BF@gce5gACAco=HvO*z8{(CrXFk=hiTBjr^~ zD4vkrvIsbJb0=XD;xEv3Oi=2aU>=DI4PykO%<`+Am}6lAT?%4Un7~B8*mK!n(~x>( z=-|;J2SEgHfOQ7XDOfBdOTi`t(ZqzZR3rjH5ru}7$#fLR9Z95okkMP~U^;?m5zZyl z4`4%>AH?tgw1dxj$Q}t8vd#WowSEA=J$n)zKSU~X<|HOgrZvc8why)~=9oBTlA1w{ zttFwrUnq!^kY4g}c!EeRAh)-K;;L;K*32%8?c}5`GR{7<)dp6$yle6jh26_&bvZH? zRyJjkBh+`QfJ}_8K^_#S1FGB^gm@$e8Ptg7{4UsIfOm#@IVLhmG00TIda+!1Ze=^> z*RjN$1ptdmIcx|IO%VzSM+Oc23Q88DPn)mrf@5j;92~D46-UpRz{5sK6GuACTN$t@ z7$dSL6dV`odroYo?g}pmo4^t^0zCv9@FtL5Ly=B_LX6ormtJ!?IRSBlFkm=z20+ON zN+qqiLsT>hsZAtaI?1NHyR%21+}+uu>&e}1EfPQtCMDoJ5GN7nk;H@UCcxD}Xt|lt zc!|>@Kr2z=kP@~T;Kt`NUO18LW00slrOQin#%KckZmKoT7}-M(pkot)YEF8BHBQu; zTR#ByyD)qFOdIK_F#IIrGHr`;Iy|DpgU5(o1BsP!*dkaxx(|@{QW6!Y6R%UK-R>Mn zr_~hBYYlHKUD?%kTiCk8T1{b9Q|b62q92ebN^wzafs;ebixKcVP=e)qKM5pEBq;f? zK?oIsdO#Q?b#n+nB!T+XZ9tcex4MROPaysyS;Z4%4*=2pA$Yf->=@1#3Ta_j-q~Ma z*!Hqc*+`;*g3O@!QlR3`<=hxk;3fMLpzSBXPXkt31O zRlz_bhI9`uMY1X-A(jBif-L8n7=@gCTh`NF*5T~2CsIve*iNc>^JRmh5r~i`A{J^i zoEfYN#sYIeHkNSII@F!(??5-E%_2Z+piT-@=j5C$j4M&_F2=(V7U(QTEjtS85qpqm zf!!e>0``JzLcO9L-|FqQ`CV z!O%NIKx8+N$48b8X->^47LSe>5Kh6{%Qyv5yBGozjnXivjRIa9@Em!&0Mmj`QX1LN z&d?_}c=jynPUk4i;y#3$rh};#>A-{>E&{MXfnTQdXbt1ghjl{0=(KJ46-$ubM-3Y4 z%^WjWk3y_VI0hwPy(kAd4BD_b zEKOipxY^JEp`N`%^J#lTc@|g^LuNLo%%F;)(FGL}D4uZ02u{1vQZvr9K^6{8tu`?v zUgfOoyZY_Y)*Uv;*=w6Zs6$!noW_8r1*sJ22^=S6I-msfU@@&GXpT#VL#vrWWr|Q> z8R#)Y?UX^r4$<+`*H?F|}1%5N=Oa)%Tm2v20MOB{x6LZTvu`qa-M;sLfpG1(>0JBj6VP+WyMi>D_5XiAY z2w~KSG@wFbl#^>2j7bBNvBWJ49f(*sKub z^bPV>Z8<_=0&F7M%$`7d(GH6?=j@m!h`?Yq95ytm0JM!HSuXd%{Q_2or?bmiexY-% z11B9SEgjYxYnpvu*YLyK{x)mdR&1}dtiyWEhya!g3b@6QHAM2z5kN=?EeiD)NYPJr zUhTKE|eQCGFB(-g++;-8s4<`gak!i0;UD78j) zC#u%~O&|*88c!OLZJ#)kTwHA-jX@9tRU|eyNoSIUzIM%G#}|$;KM2I&z=(iIo)QBu zDG&=G0HL;&A^$pAP+xF>jPuRg>1GO$xRCU6;?iQDV}|GjEibH%iPKC7$jQZRqQ`+l$h@CS)Cu8H%c7Y zq%m)l=sM{OJqm46k9{#_;JyisDg%V$jjzOZ}qMv0Y*w0Wb%yisD_C^2u8 zc%CMWd85QiC-1ybVxj}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL=1GiGxdC^z6CwZr delta 62 zcmZ23wOndLBBNnOnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~=1GiGxdCtU6Mg^y diff --git a/master/.doctrees/tutorials/datalab/tabular.doctree b/master/.doctrees/tutorials/datalab/tabular.doctree index b35d79e612e87359ba82e4f92d26245e9c43db88..a7ea38c93a9ebff680a08b1296cd675929f8faf5 100644 GIT binary patch delta 223 zcmbQWjeXWO_6_?u4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE z4a}0vlT6Lc4O5%nb8dgn$@u4hLQ1M>TC%Z0vYDm1sY$AtWm2lKNuo(=T4Ji9nYp2b j!FKM`j1!p%E8BCH(S(tpvgHEj894~5+HP>2@f9-wF2_Xj delta 223 zcmbQWjeXWO_6_?u4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-2@f9-w4;@6# diff --git a/master/.doctrees/tutorials/datalab/text.doctree b/master/.doctrees/tutorials/datalab/text.doctree index 39cbd042ce43cc5e12652772047da4514a6ce28d..30340024b6d9cb40150a90ba170cde6bc6fd572d 100644 GIT binary patch delta 658 zcmex8i}Uv^&J8;_4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE z4a}0vlT6Lc4O2J2nNyC zx8K322xd+0e<=+S3M^%moP0Z7e)6PriOHtvB9mP+CHNpNi2*r9J*Ia0MKvaw$yON& zR5ej-dO;;4=j7d)9blhM-k;4nIVoFu`odL=a+7lAioEOJefHY%%`i#JuFx zocNNW#Ju9P)S}7%vZauNOFP?|Vndq!a<=>BFnV8(^b delta 610 zcmex8i}Uv^&J8;_4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-hz7AjN+5~Q?w>K zr6^3k1e83H;!V6_kF+b3&C?|(KS>vvT$(OF`QZz3esvuM_2i7iy!6zV_=3#5$tTif zCQnJ16;4krDap)BkBKiXNGt-%B_|e5UX!jcIUrq$DW-P%MKvaw$yON&R5VX)dO;;4 z=j7d)9UvbGgB_NbmzYVxIQ>B)LIK<#@O zMJ7+oR-UYrZAGCG&Hg#t{c{+-F3KAx8kicJCnXu08=0CI8yi}t8W|dyB$*qgnHd_V iC2!wh%QT6JpsGvnXR%r=D{i6|53Td0O0fMSVY855@_U-fRk!`kB zt3*^Q+0wl4eKWt`@B8MPV|U*>JmtN^Q-*#qcCNp9o8PT<^BUE5smhtbZP)V{_ifFz z3}%~5C)hWzZX32{7{se_6HaGMXQHda@dkF3%)Dzx?4B912>eIkzhrnu4E=O!pJA%h zZ0$(&;8rKG4OhjlUfr5)BYA9U9vjVLV|i>^rmZj0L-GIzwk*d)kDA9Xu;uvCJbr;K z$B!lb#$_lLyEdR|B@i!;Y(UF%Vq<3V4rv>CY&m`b#T>uDmg5&t%<_ZS1jZc4fOnQ- zq9?HB_-RRfIevjH$4}4W7ufo89F07Vfi1_+%;Oi>a{R13et|9Y>l>Y#B$%5yQc}j8 zAxSWCay3>#lA{Be><8N z&c#S8S`s!_w4!BU^H3{V9yUK{MXST+(l)dqY(CY7ZV8)->(QdH+04<+VRJ$i>Is_< zR!N8LHkun+htkcBbENf9x_JhgvGi&o8djl6qOTe$;xz|VWWE{dNxiAeG!i!IzTQRC zL(n}gS`#+wYb2`~p2R<1gX+_x5b?-TR4%G9x;pIjzBd|3F^JKE(7M-`1H9m)+R*y3 zkLHKXqeS99{#A+FqGl>oMPyx)G6jW8H=*fcrFOAnC9nuy9N2^^!!d_8p{6udRrEKc zdVeK+->_MdI!h&~Dke#_GfAp#3tBu%b&KqFZi}2IWUK6UT9YAoVXF*5yPm0qiXbP= z258x|4NVQlzM!M|8M2Pu2eQCtG++-IlEsd%Nfs5RWYK1#`Dw{aT<}10vjrfxZb#RI zAm>c9AOnP~O@dfR4PRFzB;Lk^6g8NTvG_+qvKXpGbJIf|Tn8haz5&plY?oR1ZMz&} z{Ep0oXsLvN|7b$Ky+an&ZFQ2w<8^X?Gj)>0$quwAtyCAswt&*Xx#+r3#qqha*MxbQ zLD5q|X`hE?hpva`$t3OBDH*)7Q!==$OODmjB^ey)lJm5!9xV(9o7XLq(cg_0q$wIH zT)Y6n^G>%+#-4_3r=W-fr`?MIrW^~~K8{7|z5Ki!NP!l3-@8*(@7 zZ$V2#>xmYL_RKv}dE3phTiv~AaYig@YQ?yGm8|kt@0Gw0t&+eeSIH5M-Y0>_+%JJg zR!iW)`z3J88rf~m16jZ<1^mex30$>S0`FTZfnQuJM|k3Z1pfO034H7p3H-=|GQRce zWVdPG%mNPA$aCw^tT1NN)=S{_^%D5ldO5;_522gI(p%BBIS1&Bqqe+o6fYO4i&yUP zFwfCA-zhfVAvWs_8y;aleS$4sE=EuH#mhxl*u~3*DT`IQd6roFC~C@h{O+UZ_&E6%&lCKI(F*ac z0kk^HI^peTr6_+4^<{KD{1{TxkHe=PL-#F->2YG!QlpmXqW@iFf0>YKqQN&E#MG*Z zWmOY`a}3xL@iS75*q zHDcbc)WJ;miD~)<)ojo68GQA}HE{`2?kwmv{1j4V zZ4xUwl=6dB@Uaf2d?Vg!3eV8;oy{Kf0c=*GT z2`Ss6POyEn7;NLuMnl`dq;2DON@k~A-by~!ZGjJdMz$+$;^h0$aGJfDDF-5c` zl!+pKzNA4+>Qb&uzML$s?^3P^UT*4wm-T-wnJjw2B(5jXsp99-Ezu6PqaA3BIJqTS zHayg>?2r84$PplCh8S@oV~6Xym4(rXn>$-w-m$fHb7yCl7mp{~11Dc96NgSk#>8;7 zN)2M^G59{@RHO`^iDjs&6;nr_RgJ+siBb8iTExIH7CeuI{@Apz5gQnJ`%9v}F^WV* zzjDby>C0DKimPF^nGDBZe8Edl#lWja%D`$FMAMU2bD-ski2!Nps!D;v06$eWCi$Lf z6!7j);^MNeE0Zo}1uvFu?%Wu}e`8hxPP{bff0BT4G6B`q18$dSdz9HeA=io{ov_2ymM?{DP^zwGU=zM;13jYsmkRpH z>&lanO51X%<-m#wKh&{Y+cr(z@wjJOx~DlblmzZSh*TC}AkJJ8`qR#NKgR=AP0+Qf2GXEaPp?+=AAX2x6RzU zw<L#E zL-D507}SvgGZ0FP>YQO+Q?a8PHnS}jPCux=1CdHfZ48ym935im>D;#*&o#LNKQyy_ z%2T;b6<;Crp!g~afD4>VE!5t)O3ExBs~p?5$_!JtZ4N(bvp^hiE$sVAF$q)&M_-uF zwq-!Q`PjB7S6xb(r-3F&c|dTq@?f&64iuZGd4`L92E}Jns#_XnCiYB&WB4{cx$>kY zt5$$PYO(_4XEO+Dj}hB-DXb&9OPEHv>2k;bpebl+-=v?)w zYj_kAYk0YGAa9oKP!L2l2Fs(R8!opog=tSQ*TRJ~C8rRDu=WZu7_GfoL^suHlV%hj zhl{XdW7D)5XSN2D4uWg>8XN@;SnK6#sZrY`E>=wg0&hByPy_qihr2YaH^fin0E+Ma zNME6RW!IBYV7g{|7YZI!pNRZeDX%ObOSD{2juzZ|hGAwEx4z=m_pf%};?|dSYA9}f b#jUTn^?lY+C3`db;)ktzQK!424F delta 13399 zcmeHNdvI078J`>W1WCpR%DaRduuz3?vwO~-J?BIM1QMPCi97^Bl0C2TDmNsMK!sf5 zqbgz%!?@EKD{-bX)q*ulr@dAyVmlrGs3=bVDC3L;Yi-pk$V~ret)tz0?%uuk9B(&>*}_NEkv!r#J=UZ zj%zv)2T&uv?^0yj0kyQC-b=XM_1%eGU9LZ{W7w3tCRg1%xhlqgD)`T^)Z{Ag%!DNI zsR`S=61}k9O>Bd8>h-JI3uUN?Oe-SOi^y;hnUOC`CVEj3;80eenCR7t=!LR~o?b*R zltuJ#TCX~fG26W!#FdadJGLGyi^Rst_glDa7Li5tLKh=?p)8^ox>%scV-pG^ilN^H ziizG(7SS`({33dxETTt>=!LRmMA0mw7|J4gRuR2W7SXed=!G(&m&}$X3Trb$B_oWO zL}B4XHA7)kvshkGL1MOv&Oo0{4Nrfu)SzOy$q1wH(d@8}ji4n{d;@LHD0Xrqm@R5C z)(#el;qrE{R16<$2g}6p!*;Mr3>SBR^Iya7BL)I2YSWu!8)n1 z-2sh4I+Po3m?@=?<%Z|^uqwA(u%?w@3`@p=!p^#&CVytAH#1Y4FGM)2zRm-a1n6E5 ztQNz$_0p@!zQjLW59a2qAa-~$7|Y@iTrXC=?`H$a1|gUyr27JC;DrD*2&kJgF%IW4Y}4cH-5da>g>(u*2PdeLElIXTLhUGh2QR-1#|wjE3rAQvn! zFAoH*NrTux6Vo*biMJskNew1sEIvv|FNPXGW6sngYq_O!H*vHlI%O7K?vysJ*^!?R zBa;xWpH0Z)J7iPcK1(|B=qzdA{4D9jnJ%y($CR)WTR79fMsR~*ak^2i8aX>ZC?pe< z&e>qPP(3A@>Ir3Y8;lD67*Ne_yITy_gE}X~1 z^G=UU#@?nvrLc)Zr9Hi1rZ9S}7c}Hs3R^c+s@g3B9p5coyKlF2t#Lk>pId5WT4->- z#P8T6xn0#P>-NGP8Iq&TG9;IpWk_I4eoQTP0;R)0pL3gj2QY-&ue3-vp1wmyh%Nwg zg~F`866S*i68v;d+P6@GpIIouuU?c7ZfC$x?c?Ah`Xu;Mi{!rjP#i%>`P#d4$%%q>Puk1T>2UpC-WyF?@arm?egvECEdgW_W0_VEd(a zgG;4%A1uu=@0aoDyBRd)@`l)lJ{ZRa`?(3 zk$t+`p*GP?6oBn+*nH{qF+jo6wFUgMZV3EF;dpXo(|e zMFa>j^*oqU0c}RlgFn^i-Bnc@)bLDb&xAR1>J7RUw^_%Vpo#4~2PR$)q<119tJ#FN z!L?tGQ|sHHInC*jx50a*IW@39`~{3=LtBRpXZ!yQZo0g{cSqp<^R&IlF1`gOmF8)& zj(5S>%LkX*`!}$4oJy!gblo7D>w7rRkYoGEv9RqBgb36|eO=oMfPtQUA^n`dCc)**^ z{*ika&z{yRbQZ@I<5^;-avftkxskeo(P@(t*l*HL`!9_{mwxPKSnJ+%}OximVRZ7S)j#fb8m!G+#Z+)D2xQN@Ilc?C>3m%C7vbGNv43 zRsHH>{9+j14Y?ZL5Ek)<_RCepH>KJAS5+L351e^LzhDJ3xk`p^WaFpDAa#ZV7ny+QiD`rP0x}%6hiF zrm{+Pb)rFHyB_DK%`2ZQIlJfD#K~BgjzV`ag-4^nkrNwGyhd zln0zrgQ}ap?-&$X$aJw`P|JgU;6sz@9&tR3MRptmyNE*H)qNgw&8D8`o4#T4Wcq1& z=w6OatrytHwV)26!RhcUbDKO*j%H!g2u$|jNo7d*|RSx)1ist z7;WBJ-+lX(ef#RvDY_XD4_SVIsfGihQOzSJC+t}s^=-=)3`<^n!unf*D-XnyrIIy; z!!B-J*S>5;bIZ-`rK+`1yF}#Zl-uiA?B~ju+7i6jn;$7tr-l*mC~pue;H`%shLpDy zZ%7ThffM+iYx^PsdSD?gK#1S;un8UNlECnwqdSIfQY=c4ci_R;B!f3G)}XvOf2^J%RIfj|6Y$x`eNuz_mxD>c3*X^0bR}VJjZqeth>5HG>6w8FVDbq zJfvl))N&$bz-dzgUF^DsgM7_4cpGVi5Z_4qH##-=ta2sve!I?~*LVvm=ofuQNR zJj0alLD&upTU4r10zB-ylGw4c3jeG3w90CgdO9R7);$h|`BrD!h6w}A_dOdT=y-w* z(fB3DM;@fq!n$oZyk8wXu!F!NuI)%Nd}l~!)8qRQ=KCf#G}qBgNFr7DaT8`b_DzK rTd(}qEBf9ozxDFZ3+1<7`K?!e>wV4%*4dN(!#>P3}~2v qVM=1ML5e||$@XtQSSB(NR<`^%iwPrPWxxNh>}Mye>=p~_eI@`WPf1t+ delta 236 zcmdnlFS4^=WWyd#!;CUB!{WTkVtv!(WMfNn6AQyci!^hSREw14q-66X1CulZBeT@h zq>9{ diff --git a/master/.doctrees/tutorials/faq.doctree b/master/.doctrees/tutorials/faq.doctree index 7e9a36519eaa545003c9d4c400f0af3e348ef805..ab819507409f3c147511090a42be52a756225504 100644 GIT binary patch delta 3838 zcmeHJzl&Z~5aoL)xDZhhgN3-yMGzrmXYQSQ?@X_SU`SGmgm8aC#7GwmusXDq_u+6IwFP zFj&Uc^aeALgR38Z@m@FRHr)92kug+LTr9~6S*ivYOG3_GG&vY=m%r);!HuWhzjtfC zcWd$a4yxFueZIXacv0p$KCl$u7FsVitog zBa#jKvGDb9Wid*%9-|^`p^y~AE;z7Ii$%|rXc;@*-5pNO&%85yzvvh8=ext1^-c-X z<2wUPXRi-yV@|2$L+rUb}ea>`O1dda*aEN27bK+qiIQ8b2CNj$K^Z zmglGSUxtTA6qam~F{ZXXB9!04(2DrIi>uw1S>E9yDGwNA$ub1m!QZt_f@F7ud*$Yd>~~MWAMpFlfCE2 zTJaHNoP4dGYl%Q9NRkq&&bodG>;dPc3fH~2H70L$n+A$WcZrS8$BfPfXYGW)4^PjZ zd^qeZRAZg&%lXZnynFL|Welouu15DBR}zXU8XM7iPNWSEZWRfukg@@B;0q;e43eNK zHe@E(+CGvoX@qyWB!g1v^kpb9C)Q{PN>bZb;d&?Y^xe$?b$$MK%D+YE5G4d-PFr44 zp*Kiebh(J`HV%P3FoQ)E delta 3818 zcmeHJJ&0XZ5N0nCT!@H>sbsw_f(Riy=bSk|(`z9ZVoH%E%$y(8LWGrIiV%o)5kW$D zD5Nr`iwY@jqYKf>Dq?A8BR1(%h&b=uo+9W`Vb?h zlo1@jK`negT-z9J1z&ul1dJG?7cbStWQ(g}iPNHXc7K03H9h~)@Z(0mk-skuXZtNY zb9>mCox3?~j#k85@zr4kw61ch(%3h)h9c1sv)vP0*?~b;H4#Zd@)=a%ij9L34U^7b ze`8EUqik zR5s|n2v%Wdtu?uo1a(y+3OQ(V(Lw@U4lAX^3V_)bFBA`{a03&B0+RQb9W%`lLXns< zWpYa@UE~Fo9_E}1%=UjBUcp3$j5!m{yC3fC?QUPbe0toj-Xw|H2l#q+0b>vsOYu}FijHgg{oCOKbziWd5m;$f)KaQhZMljrWv;ohJ($yh z`wEf`(Q{%HwAQnb3wkf~rTTXZi`rH9J-!1Evjg|_S~zl_Pc2~fO^S9)pf}S~bIGc+ z7@+x8RU-pMmplgpC}0y5QNNn`vra;smi~hV&2cP2ZyvOibj4e9#Wkx}sU9wE7kRO? zJ? zf-dXNt*X?^l|%1!R66da-l86_?#=FB?{#@Cym$YvAl9pmUH1}coq~_Z-*pQ9_Y30xrQoC~_~%pq0Gr@M0RR91 diff --git a/master/.doctrees/tutorials/improving_ml_performance.doctree b/master/.doctrees/tutorials/improving_ml_performance.doctree index 55ef04d65890c7ece4b698283829ce27673d2dde..abaf10fb61f61c4bb159f94d173ddfc367acfade 100644 GIT binary patch delta 84 zcmca{N9@KOu?-hE4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE j4a}0vlT6Lc4O5#Lx!M`I7=f4xh?#+yWjiAmYxoiX(6|_9 delta 84 zcmca{N9@KOu?-hE4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-j}X<4GaQBsPrQKE@?Vp2+Ks!3v6lBtEIxk-|RiJ756nz?~l Rl6jJ;xw&EL<|fA1TmY2(6W;&; delta 62 zcmaDW@m69(AfsVMnVDg6US+YqX>zi$rMZcPVWLHvxk;);N^(-Nd6I!int_p7YHD(# Rp`~S7qJ>e~<|fA1TmX$a6gvO_ diff --git a/master/.doctrees/tutorials/multiannotator.doctree b/master/.doctrees/tutorials/multiannotator.doctree index 0d88a84b5c0641cfdfdc485ec1e671d8270ad0c6..8e296d6cf4cbfbc752eb1cb97950418ce1f475e8 100644 GIT binary patch delta 72 zcmeyif#cf-jtzS_4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE c4a}0vlT6Lc4O5%na<;$aWZeFilc|#r0KtbCwg3PC delta 72 zcmeyif#cf-jtzS_4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-wYbryy;zS9Ph?}1V*vnoj!O{$ diff --git a/master/.doctrees/tutorials/object_detection.doctree b/master/.doctrees/tutorials/object_detection.doctree index c55def560895fcad63f886b6be9304fb6c7fa386..94f991fc893dfcd43b6c78e96c66e2708304e7af 100644 GIT binary patch delta 72 zcmbPwoMY;7jtvJm4bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE c4a}0vlT6Lc4O5#xa<+fuWZeFdlWB=00GdP?SO5S3 delta 72 zcmbPwoMY;7jtvJm4KvEj42$zBi}g*DlZ`FSO)Lx(Ez-3nwm6hAjTdlBFQK)pbTLZacl5*ttK z_&;lH?t3@y|9jKaY~$NT(Kzj=PaaloJooPpFHD7zLknAUyD=2Cu+F76}1LBnIpH`3n_Sr+$YJnL9LSo83~#w+O))c}ra7E_Ck(?$rLiGxa*z*}vC@~9+w9zeBaV6gG*vBPK0tPf=b#CV#u>|mQOQRgoPiMO;lu*x;GM8M zdWIsf>=;l4&1gsoRmqt#|AHtOjb?rAKewo)h6oY z&zq#XsNz*-LC%)Pr^$n=IJ6WvO5{-@j}p1}pZxDcs^;)x^7&Zhf7-;740Qbl5(bv6 delta 2295 zcmeHIOGs5g7-mEaH?}Bj6L`2qP+W8#|IGYTf)EA@iV;B>h|QA(G2&_v`2br)X$0NH zp$HS(E$G&bt3y8k?+tTh8jo{rJ(n#`Wj^{oaGIFtF!f^;3A&ooO!xLol3E0osFe zfe8kZ(Zmoj))!ySmx5M1mll>Xk$7O78)cXUf!wr zmn`R%KJuvaoB5YM^07mCt))h;gaKxQu}oM_T}*-*B~@d6icBRvS2|IF-(EvOOkXi#v67^t?}X>c}g;2tVOD%mkxmg81xZ^VXnxGX#v|N6kBgdDUtllETLH`k3v*e z{(6?2=wJd&Qj97A33L?2F;Px%kbtP7ZG4|1H=8r2UD2-ui3X%MS0~=rZFf zBh~!ZHPW7y>Bs>^N{x$b&*|-82V<++E-QUr62Pe@s3fDt%2GkdvOa EKd>E(b^rhX diff --git a/master/.doctrees/tutorials/pred_probs_cross_val.doctree b/master/.doctrees/tutorials/pred_probs_cross_val.doctree index 316ec0efd484d36bed5a93339c849b7f684c0fe9..cb12241c5e19f80c8b303c5a5fb3032dde977ff4 100644 GIT binary patch delta 64 zcmZ3qfN{|R#tl}ChH05OX=SEmiTXxKDaJ;LCgzDrDXFO@iD^lu7MA8FNfst%h6ZWo U24+d-Nv7uJhN+vg8MpfZ0I#4FJpcdz delta 64 zcmZ3qfN{|R#tl}Ch8bmMhQ)c6#rmen$;OuECKiT?7HQ@tsTL{8Ny+9(1}13+MrNt0 U$%%%RmT8F=MroU~8MpfZ0H@v*nE(I) diff --git a/master/.doctrees/tutorials/regression.doctree b/master/.doctrees/tutorials/regression.doctree index 2264cca5bb53cd1b36dff746a610d14eaff2cf62..b0b64f5a51cf50e6e6fb7f1a93d74d8e8fbe512d 100644 GIT binary patch delta 220 zcmX@|fbGZwwhdc24bw7n(#lNB67`LeQjCofP0SOMQc_b*64R1QEiBDVk}OQj3=PuE z4a}0vlT6Lc4O5$+a&CXh$;dff9>_^eGfgr~Nlh}bOfQ1$@&^Xb;#K=6wA}Ptl$Rat#EYZ@^FxkRr hJMTiqW+sBF)-Pr>WhAJIc`4&Ac7m$ztYOSx1^~``LU#ZF diff --git a/master/.doctrees/tutorials/segmentation.doctree b/master/.doctrees/tutorials/segmentation.doctree index b6d91c694813654ac33ff84357ab9c1e7f41e022..9d1d72787b18fc2da81cd86519be4d1a89f5d920 100644 GIT binary patch delta 7653 zcmeHKO^jq!6;5d@GXkP8)1yqkS8rND6FSrP+nBL;uvCn<`alp5w{_3M|=`-2jWwRPb2O`+=V!SIEmOqoI-pC z@ma*(h|{yZ<694WWhz8TMi?WjP|Q@FRVrKKtkpr3JU;fu)~iF~5RF%!+&Ve?*CSi+ z9vebsK~9SjLtx=@C_)4;VpJTH<}g0~#?}v-r)GHKo9Bk$N~LT{F*$J7^H$=ir7DrV zCta5hYn|GEy<_9nnV$|yX|^ShPerjL9bNS?W~-C4!b@H}v3Y9##NY08|2Q+$QbWeO zc&Uk#i(aK%OzBIe_&Aj8gPj+q)F4=$=O2!EeHV3JL z(pqQMPRUx9MQD~Trr@PTr%2?etfGKv(bD1@a=h|dcWU<5H~L>p29{Z3}@e-G&7G^pX7)uDz39At` zxxA=nsxeHq7F%!y%mxD*3mJUODhA`m_pfy)W^ewf`_*KKKC=w~!1KeR^9kx$OK_pJfy9ki# zVk3E5s#FWy4Z298Vgoywxz^;h)wYyus|~@YGy=tUErHj{yZ~M+@w^n@E9I4pxKL~( zLCT8)Y_TqaiVt;$0eoR&urdT0ZN|!Ajx`2US(U<)#yZJ9t-x*?5~xIqf~R=qphE^u z9bs`gA+uSG^n0fNPOcXs{RS^l5u`jAvZV@Ak zuvoWPy~KDu)Gi$5Q+HCgcK5_YZ3i&C124`8=B z{&llIz2jG4X9#!fD_<@Vk*_7B^Ns%FOxu-K1-uZh_jbO|H4KO^stM%RF(`@jV^md7`|Fc z6?(q`M!CPyv zek3gmYGqy&)J%MUx?9EveSh~u>fYyHzF&wh39<9kD-xteAXP4aY%ElDv@kK&td6kpf(XByh)}edz4uV05CC&l0(Z_w z_z#om(Rt%yf}45wC-~P-^yj8F8WXkAkoF#hKy?}grqJlIawRP0^1X|g%c;ffRCqt) zz$68BPerploM8ys9Ks{$CMCAcFtA&S2E=2=ZYd>dg>EeH*i8P%=Q3 zR)6O%omH#yQ(F>7=E_hRm^m3V75E(mASMQtFUPHIpjPE4VAr~@!$4|`sXu(W)xI0B zYZbQ-yKy)5cKrUe?(wDtTQ+0u{np+OrgO1O8lH3Q{cdJ#S2(Zbz?QgcS+KSDyP5G^ zd%sn&*)mCsahtBa-_ibS?fq_UI@jKB?fur?Z|(io-tWJ7^}}xN|LOf^@P5C)_1`_p=;pPfo7dj`%Sn0VH7l>ac*7*PY!x}GA!-uI;E{#WT*C19uXf+qYaM#)$=%bl|313= z{)xV_&XSZ;Raa6>-f1Phb%hFPS<3vvpEgg;aN|3d`jU!JMtGN-vnyRXtRaLRrsuH`P#~Yic<~RQNp!?VPJzt!6NwILc zkk#JHYLh7{B~;qF*?T+Fmv;JGRbcHYdu^ze5_R;pvLs^>mZsU{*WGU>y$lieR3(MR zN45H_OJ-S<)Y_<;hxcCY?w$2N>OP$G4aafVdt~}p)A8{Blb!FK6ETD!Ia4JUauhWc zHh8qel_a8gxqA^&SUkK{wt5@L&tpX<1KK(z(pj0|tv9=~vv;4G{%*1tvXW%Aj?Xlit}uyYCT z2Gn{LQ_K4@rl#{nOqX8hz9x|Ci$=Wg%Hh@L_OD+*==ZCYimgN4j3lXvQ5qKPwIyT9 znBe}q-7`CFkfUy=h8rJrcg}8}n_i#1-Y8z$hyO>u|Mca@zW1GnAHCe_+Rf9AB*y*c z4u=1{-JR(h0j7ED-hW|{3zoiMph{a)CE;W6#@T905+z0=9%~I4StT&+6td-$;Amtt zCg^OfCs{@ms#*i!i_wUFHwI&nT=q=b1l;B7Itp8!mndvGUZRjFswj-YKmpF!vj8{d*<;~lRM_`0PtbH#*(ua#%Ibw%3PMA>}jEuOEy(w3}pw36cr^x z*>p0}Edlk;Ke|6m`sj<{5G^^4*&~X#nxpm1n5kBXx{PG6;duDrmw{Fr>8&MrAHWgEB%gb}Z8Lcp4mj@h0wG16-?4n-FR>=;rBG z=2n2)YlJq)-*y+4c#E<)FqHP$W<0tH)*=_2s<0Xz9L7#{n5w9H3`H|pq^$-)oG{CZ zH<8SUw`v56EkP#eYJ411PLir;<;eM3hBek}c^>}s!1Rf}<#;&%)#*3-39XZ+lOz3 z>3t8Y2Y&F%LqdFAh=XTeol7=p$QpOi`87P^e~~pNN68E6!a+jHRnUOo0tqq(-PVZf z6!_!G>y1ioLaf!no2Oez1t9z3lefFmeJi*%3e?cqkdz5@hnEon3fUJS6?P1g){J?O zC?-^qW)H~#Z4@+;1fGNxRY0K_AqmZ?gf&Sd0bnzdbm|p4`*%Hb}={XSN1)@UAGf0n3 zR(XsjON57DvFijv6+NUssiY&-gwEa|bfKKYG==nZnvw}oCCp-nP(%_nuV}F0dHDMk z&|uT=3Xf-pe?Bw4=TKZ!Y7KcY)p;T@YOva2EeJ{~3_y?ZD7De6ans(V){zJCd3?cY z+yqmrQ#Vhy(zoJ5Y!Al=w?N)-n5J&{$%ozJ+cj{z25#5DxLpGmzl3hr!0j4%>khhI1Gj77YR6ryfitXu Hf4$>>g)*{< diff --git a/master/.doctrees/tutorials/token_classification.doctree b/master/.doctrees/tutorials/token_classification.doctree index 13761a5b53fa659ee6ca1b2f685497bc2d3f5331..d1c6aa6d57b8ffb32ce9a20583276d8d30c43393 100644 GIT binary patch delta 1540 zcmeBt!gcxy7fS={RK|@gM>q}BGIP?(Ov@7WjgnG~jS@}F6O&R>Q%w@nl1wcu%}tUl zOw0@o(##FalFXA#&CLx{H~-}PZ7Ofa%D`Y#P?T!NrK@XXU}U0eV5w_hreJ7kWnye) zXgGOeKq+`oo0~oczGob+UkSjJBzXo{_Pko{@o}o*~d+QzJbiLvuYtOJkt0F`RE< zsApj^d7^U!FN%7gP2Q93TpEGe^-O%7^otdMATv+FK+mF>iwn~u#tIrBm6Hn-%=Njr zZ1h1so|3^HJ0(LfV&nzEm;>+8JHSb*D(Ac5z$G#tXnksu0Idy+1Fxn kT{QcM^7Q7ygvj}vQx`EaGJwG3Q~w=XMHsh=Fn!$!0LF=hjsO4v delta 1334 zcmX^8gsbxj7fS={RECW#M>q{L%FGOl^D2w=O_P(2EzM0V3==KV%uP})Qj(LB&65mF z(hQ8uQd5%?4J|Fx5-p6|}++BFE0Oz))c9G-8dJ8=?M_ zW52Kubx*95lm})Qs$`XiL_`L~*~EJCyigvj5#s1&t~dpnSB88%Kd!0r WjOLtE6PXzqK%g~@acdaU*Np(sKwMq` diff --git a/master/_sources/cleanlab/datalab/guide/issue_type_description.rst b/master/_sources/cleanlab/datalab/guide/issue_type_description.rst index c3eaabfa7..2e72a08fd 100644 --- a/master/_sources/cleanlab/datalab/guide/issue_type_description.rst +++ b/master/_sources/cleanlab/datalab/guide/issue_type_description.rst @@ -806,6 +806,14 @@ To customize optional parameters for specific image issue types, you can provide For more information, view the cleanvision `docs `_. +Spurious Correlations Issue Parameters +-------------------------------------- + +.. code-block:: python + + spurious_correlations_kwargs = { + "threshold": 0.3, # Non-negative floating value between 0 and 1, lower value implies fewer image properties may have a low enough label uncorrelatedness score to be marked as issue and vice versa. + } Cleanlab Studio (Easy Mode) --------------------------- diff --git a/master/_sources/tutorials/clean_learning/tabular.ipynb b/master/_sources/tutorials/clean_learning/tabular.ipynb index 900359041..dfa986166 100644 --- a/master/_sources/tutorials/clean_learning/tabular.ipynb +++ b/master/_sources/tutorials/clean_learning/tabular.ipynb @@ -120,7 +120,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/clean_learning/text.ipynb b/master/_sources/tutorials/clean_learning/text.ipynb index ea752b492..96aa2015a 100644 --- a/master/_sources/tutorials/clean_learning/text.ipynb +++ b/master/_sources/tutorials/clean_learning/text.ipynb @@ -129,7 +129,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/datalab/audio.ipynb b/master/_sources/tutorials/datalab/audio.ipynb index 9280c802f..fb9f7a38a 100644 --- a/master/_sources/tutorials/datalab/audio.ipynb +++ b/master/_sources/tutorials/datalab/audio.ipynb @@ -91,7 +91,7 @@ "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\" \n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/datalab/datalab_advanced.ipynb b/master/_sources/tutorials/datalab/datalab_advanced.ipynb index 89e2c0500..1f4d94f78 100644 --- a/master/_sources/tutorials/datalab/datalab_advanced.ipynb +++ b/master/_sources/tutorials/datalab/datalab_advanced.ipynb @@ -87,7 +87,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"] # TODO: make sure this list is updated\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/datalab/datalab_quickstart.ipynb b/master/_sources/tutorials/datalab/datalab_quickstart.ipynb index 18b6d59ef..e9f1461fe 100644 --- a/master/_sources/tutorials/datalab/datalab_quickstart.ipynb +++ b/master/_sources/tutorials/datalab/datalab_quickstart.ipynb @@ -85,7 +85,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"] # TODO: make sure this list is updated\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/datalab/tabular.ipynb b/master/_sources/tutorials/datalab/tabular.ipynb index c60b5df9e..5dcb0dd9f 100644 --- a/master/_sources/tutorials/datalab/tabular.ipynb +++ b/master/_sources/tutorials/datalab/tabular.ipynb @@ -80,7 +80,7 @@ "dependencies = [\"cleanlab\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/datalab/text.ipynb b/master/_sources/tutorials/datalab/text.ipynb index 4a3a1d3e9..5fca24e96 100644 --- a/master/_sources/tutorials/datalab/text.ipynb +++ b/master/_sources/tutorials/datalab/text.ipynb @@ -90,7 +90,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/dataset_health.ipynb b/master/_sources/tutorials/dataset_health.ipynb index 334b6ea56..ca90c3c59 100644 --- a/master/_sources/tutorials/dataset_health.ipynb +++ b/master/_sources/tutorials/dataset_health.ipynb @@ -79,7 +79,7 @@ "dependencies = [\"cleanlab\", \"requests\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/improving_ml_performance.ipynb b/master/_sources/tutorials/improving_ml_performance.ipynb index 09d436c41..d104da0e9 100644 --- a/master/_sources/tutorials/improving_ml_performance.ipynb +++ b/master/_sources/tutorials/improving_ml_performance.ipynb @@ -67,7 +67,7 @@ "dependencies = [\"cleanlab\", \"xgboost\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/indepth_overview.ipynb b/master/_sources/tutorials/indepth_overview.ipynb index 73e38aba1..ec9b0c142 100644 --- a/master/_sources/tutorials/indepth_overview.ipynb +++ b/master/_sources/tutorials/indepth_overview.ipynb @@ -62,7 +62,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/multiannotator.ipynb b/master/_sources/tutorials/multiannotator.ipynb index 372648258..a0ba8e763 100644 --- a/master/_sources/tutorials/multiannotator.ipynb +++ b/master/_sources/tutorials/multiannotator.ipynb @@ -95,7 +95,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/multilabel_classification.ipynb b/master/_sources/tutorials/multilabel_classification.ipynb index 6976a084b..8b7654606 100644 --- a/master/_sources/tutorials/multilabel_classification.ipynb +++ b/master/_sources/tutorials/multilabel_classification.ipynb @@ -73,7 +73,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/object_detection.ipynb b/master/_sources/tutorials/object_detection.ipynb index e993e4885..155a9b7d0 100644 --- a/master/_sources/tutorials/object_detection.ipynb +++ b/master/_sources/tutorials/object_detection.ipynb @@ -77,7 +77,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/outliers.ipynb b/master/_sources/tutorials/outliers.ipynb index 3c1170dec..40dabd38c 100644 --- a/master/_sources/tutorials/outliers.ipynb +++ b/master/_sources/tutorials/outliers.ipynb @@ -119,7 +119,7 @@ "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/regression.ipynb b/master/_sources/tutorials/regression.ipynb index 960094e91..b36b8a466 100644 --- a/master/_sources/tutorials/regression.ipynb +++ b/master/_sources/tutorials/regression.ipynb @@ -110,7 +110,7 @@ "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/segmentation.ipynb b/master/_sources/tutorials/segmentation.ipynb index c18da4750..eb6cafaa0 100644 --- a/master/_sources/tutorials/segmentation.ipynb +++ b/master/_sources/tutorials/segmentation.ipynb @@ -91,7 +91,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/_sources/tutorials/token_classification.ipynb b/master/_sources/tutorials/token_classification.ipynb index 4a41dbe71..d3bb49df4 100644 --- a/master/_sources/tutorials/token_classification.ipynb +++ b/master/_sources/tutorials/token_classification.ipynb @@ -95,7 +95,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", diff --git a/master/cleanlab/datalab/guide/index.html b/master/cleanlab/datalab/guide/index.html index cfc73541d..82ade157c 100644 --- a/master/cleanlab/datalab/guide/index.html +++ b/master/cleanlab/datalab/guide/index.html @@ -670,6 +670,7 @@

Types of issuesNull Issue Parameters
  • Data Valuation Issue Parameters
  • Image Issue Parameters
  • +
  • Spurious Correlations Issue Parameters
  • Cleanlab Studio (Easy Mode)
  • diff --git a/master/cleanlab/datalab/guide/issue_type_description.html b/master/cleanlab/datalab/guide/issue_type_description.html index cee862e61..0911e92be 100644 --- a/master/cleanlab/datalab/guide/issue_type_description.html +++ b/master/cleanlab/datalab/guide/issue_type_description.html @@ -1493,6 +1493,14 @@

    Image Issue ParametersFor more information, view the cleanvision docs.

    +
    +

    Spurious Correlations Issue Parameters#

    +
    spurious_correlations_kwargs = {
    +    "threshold": 0.3, # Non-negative floating value between 0 and 1, lower value implies fewer image properties may have a low enough label uncorrelatedness score to be marked as issue and vice versa.
    +}
    +
    +
    +

    Cleanlab Studio (Easy Mode)#

    Cleanlab Studio is a fully automated platform that can detect the same data issues as this package, as well as many more types of issues, all without you having to do any Machine Learning (or even write any code). Beyond being 100x faster to use and producing more useful results, Cleanlab Studio also provides an intelligent data correction interface for you to quickly fix the issues detected in your dataset (a single data scientist can fix millions of data points thanks to AI suggestions).

    @@ -1644,6 +1652,7 @@

    Cleanlab Studio (Easy Mode)Null Issue Parameters
  • Data Valuation Issue Parameters
  • Image Issue Parameters
  • +
  • Spurious Correlations Issue Parameters
  • Cleanlab Studio (Easy Mode)
  • diff --git a/master/objects.inv b/master/objects.inv index 1c70703111e3d82b85beb346b7cdd2c7245f8457..b35e54d50e5e8bb53872f44e9547a096451714d8 100644 GIT binary patch delta 30230 zcmV)_K!3lIv;wlU0I>iETb}0b{a1cYh1s!Eff{+6a`(s;CGvVw`1Flq=w-CmoY5PudLix~e<4guPqC z8<^W|Kk+UJ3$#WBymPHAy2tkB!$t71{xk}Ai%PncjXo8GR_cI#f5vz0GkeSjt;RuB zHdKjNjQ-uw)~Vs^uhkY=MlQXc-g{0rq>{M$`*;=a$e-WSkx1?2@Gvi}FZCx~)cx)M zHTelAKWWH?@rE5$nA|HpuCxxeFo=DuvF+Gr_LSPe60Z&$Jcwc183I%)nqf2`*OJ=}@%>PB)&F0dn+FF$+&vn z5ss)x#N$QBS}q+O=YctF31N8c9hb=xA5oDAN_mod7^l~7e`&`Ut)e_5HQ*~;+jbwP zN>h3N1u&uD3>b$g7{&XK<|u;UTa#?09nh^Bm&?rN-|=f{oQOTJ$MG?_8awv!fx7SZ zN%Kf0)jWrb_f+yC^+4`ErqIN7NHT9ILLCeD1)}0mGfry$TdIP^lyhIoVce&21LPd8 z9KSfyR^owNe+=Dyd><#|SFL-rW^wqia-QYSQ5f~&#i9C&ddyfzBojVO(Idm7=paOO-(}&YaK`L*RkTTM>@K~d%x0@*pyEtKA1(%=z z4`1jQN$Hz?Au5tbYBnW-|7fF638nWzDA2evK;t@be=}po?-d`XcV?vW?Z}2Uj$M;H zO76-+*hCeRFN?hJV&PjV|D4L#Blln-=^o*Uk`nngwFNTd^J08)i~So8AO<`>42C=M z*h}w=c=AF+d((SxR@|=Kfl)~}>U(S71mKJSC^vAC-iMKXo4BaGRvVWx`mx_vEAN`1 z*v$8sf4tZ{LqqQvqTkX-*d2NV?%?*?)GrBuPE&8_eHiJzsW;l|HuZf*KlXcU>VgUC zO})$H#pZdMdTWSLQy*e?;SrSsefoB@OB+;(oY~-Y0(rTIpv&OS&IGqfWKV{6AhbDL zn7XafGNJBsZsL0o&2D&ArgUqP*Q(koty5p+e_W2u_F8iV3v{aQ0Gl(*{q(O?Yo$)M zrF3hO|2nMQ=gPSpo9(|2>vzEeY)Y0-E&-Tjm(|3oWWf1)wQh>NW^3P4onH6u!A+D_ zP1$a8G1X5IsNHZ9=rZ`U+R0vhYnPaA$v2QTzcWpC*?aP+;%0hNk+b+#e-oNJXDaPE ze^Zv>)m^$9sO_Dkuupn|)4xMZwmv)ZjN%SwRT1;}3Ln5p*up!0+tj@6$*e7TZ$}4e zLzeAlzP2-WyD@DuGqe}e?fLdj(b$ErD8a9z4iMAW#4VhLp0{pafs49 z+jbz<0#Tf6uj6Hz7mqsA`kIAK>G=mme~6J{>`XtRn#b^&YpJg8z+DOQ>NSH`vK_ij z?e%O^NxmFcpxXp%Y+1GPQv+to=+_JCA)%EQKAyk3xcT()AAu>Osuw1EPbrL%4-BCc z`cmz^+`=C2`a320PwKDqfm&82MCuB5I!Vhgk&oFYe4~RnS!Fq?aE!`WNmVT2f7DW- z&*Is7lLLA#JfV0JPlesLhpf-nIq{dtK{|b5TE1i#ncB9ZjugFi&pX}kyAMX`_dEk~ z+I6nxI~$!;htrcDD|~D|iLcB%GtyKun0q$wn~IOz2d)JkmEYSX7mdv0{Dsg})2sC3 zDxP|FR&EM}H+i}`;xalrfBWY1f90p>)2|=TZ+^YLJPZ6o99wBM7fT;;If+{O6nb?7Dw`u8eEbYL$2Zt8HrN(-%!Sb^=~4DE77Se_itfBm((dUv`UpkO9%d$E#xT!nG`f6c^O3pvWh zagT~cj+62+O3}T>bsz^Qm_1d!BUlv`d=)ldx$|pJu5qfhej3;!^V^7EN#FXTp%Usf zrs0A|j+;*ovb-IG4D^9_t(#Y^&2qcbvW~#LE|R(4d~KM*)f9XTrC^^0^j8Q*xj#L* z$4~_J$v%HYV3gw1lY0zBe{ht2kn_IhSo$36)SXA48zk(s#2%0TZ8LPf3&9{Sr!V_x ziUS{KDPZ@`KZ*|DLB7qO=gqQgnu3p^6yTSr`6?zkaKl6K@-X8zdZ)f9-<&oGmS~o~;P} zNIL&$sDyH5Yq{v9Ld{3}v}e~M1BK|dRTuR~qr9hzuw(GBgUqK#cbla?wIv@#L0Bh0 zeU^hs_ET5zQIvvp{?lhEm?S`T1s_Ez9A{_bz7sl{&c`+j>ecP~X;4kMM^prsiBSLL zpq~jf5q>-+f{(Nyf3OGtA4lhJpAPlue4~7*w&bHI2%EH<&mz#wyJ^Tg3b!9^)%Q~C zkEz1DNxu0k0^{tPk#y5S(aeA~%uf7m3~rM7(!RYz!Y&4$j>0Tvq2ln@|btSI4kR#|itP{C@9Bh!nRgrcS&bCe2di1zKvQ}B- zG58)Ioy)N^e@`E}lXj4X_2Oo;1gx681H0TR;p)ZNx~bMFNe6cD5msl1HTgIyv7;oa z7iXKNPt|4GxL-GSY4U#6q@S&nFw6q6Hvo;(QH-6Yq0*@*83%xss~6*-|FzFKwTf%v z(^mMGoC+k{wczbqKfK z3J?0&L}(7ZD^bb4$V2$Lt3kAji+GDl<8>>CE+5v+o8&_jz)=i#P6oL{4Q{qMPM3bv zPi#($I-E}}Q<=^ktDnDAly@)}A)hkE}GlfrjF%jT~q5aFd&zr(}%Nwx$4C~Q^H%o1jKmLx0l ze^e#srwK~-w+Xg#1>`L3ANx$CpuMgNS9x}Eab}cp9F%Yv*Ez@~I`yMj&QMLB~cIDVZb+GoCDYsrVf673qi93*oZE{O)eXE&6ni6y%e;!d~byrUh zTSeXEcij5cIFF+)at?3fWV=g~b%IvWU7l|9+q}r{BfL$DjQm?7Jb%xipptWmMy}S( zM=?%&cbdU!XP~OoVw)c2W|=SYmp-a`odE{;kAsX?t+O8Z75R@@u1m%}x2s%af4JQE z%`mq$DQb3)+Gn&JIn*eZH6>|wciLyL9J$jdcQqwxc6T1WojYjX2Wi*V87f!)GssO% z2s)52Z8K6%9cqw^QjvBT*Wx4aD0bn<`8!Al87D_xG|M$jikjV{Rv9KozSPYvjR=|D ze@9Un-PFTFRY6A?BuBn9&mAd=e>3nd{9)@8DnoC&pI2p?*j)c#3!te6{=o=dxkPIo z{;z%7K{P>Ii);3;QT|~>#=%_ZARXb_pJsUpRe^`|^a`!xDlMaOQy{#_(-l4vf1jPd zee?P9Q}pTAkLNePUSFQw1b)OG()X4rBIiyw$rUNeJDi)XQ%BC-Y?4D#f0TDPHy=@7 z?W~VJY~O5~YI5&a{hX7UxI_EcG6m(y(fYY44VedaIX)&&V|NZdUdy;6rxc$~nrzh=~4%HK- zT54)}=iZ(qlRNih>L|C+mYJV@7V;j^LsD*{HHyosFr8dTE%c$Cdyz*|0=ojOk|iYk zjaY=k^zA%3*NJr=qmV<+Jt@#SYY{knMf8iL5%X)!k#?mrb zx-kVf#~Ta>L(7abb_8bd-aV{qot2MP#(FW{hx*#bvX&F=Ih#E_)crKE}fNR+^F57Iego z$IUX!j0I)90Aqz>e_3>zD?N-0oFHAtkxOc z!Mtx=BYiUkYPsTc=u*{RfN}%( zt&}hRCW{r%QkvhwplQE?b-1E5TF`QU^$iqjmJda8k?BRUhb!l+>*({<+4;v0=O5o* ze|&#&^)5QSfBby&>HK4KaTXjB{2QnV{Om+i{IuM^xnBGF^QX%T;_}+{mv8>#{PHF^ z2q?;N#Uul7kRI4s6{lq?) zE2@n49zI<&Gy@**E~uBS=XFJcYQgK@H9$JEUnrz0qkoUw$7w>y(ac_HU~QN^c?TX@ zUZyd|a1eG^PX&EwNRv4<8UPpQq;R(JbI0KX7)aw?$kEyuKCjK($M@_t>f_}y=5yJceSFVW{XSkIU_MXH-N*NgHS6OCg!u7Vd+x*F9v=&L zwTE&(C|%E^z&)db=IraGw(9rx<6`FY-F!X1f81u>K7UlooQ|8R-5kaDVtq@0od4Cc@AUG`&CSKzi_y{9%JxJ|{I04P*c7KJJ9QD&e=^{Z zpOKOy;xuSgl`rD#t}cma@yI3pQN?LenmKt~q8|Bx6|!6s`AtRLA=dpigud=jkwDs; zwAW>_j*DoSWg~5JfPpsA=A#lo>r|2Eq@`Ixp)WFhMU*8g(m66G^I^*A)m5NChSf_bhKL62^U5$7h zVu#jM>-F#*FxJL#=^C`|OrtFrS35Y+nb zWfqsNLF>*m*hau2IZxIJ0D9zZZDe&Fm%}@sTo@{%81T3?c^4P)7L{I0w#CrqaBD2C z7G7uTT?}mwcgAkwbnVGTe=1s)(49qzw^%w+jHMHou{0TaR;)QkuvyWQX?+v}9(N|Q zI_@hTt)*+wx-$(frd&mSvo2i>Z4TGQdQM98K=fH$+v~UXb}_U$TpQaAzkcl%U`&|Y zS?%3kO-p^)SfJa4UWB)Zmv=Bdh&FkC=gHmyFmqNPe(*V=>7y9%e|RvNPYh=%`3{yb zr$;C33N))D8ayj*9}cNt*?P`iL4s(>@7*o4)fPFb0~sD%)SD|ryBwFZcxf2ejTjHU z@|t+)qZsgbFxhu*NdjcX=D~KcR?XCP$RKS6xb(~)RZ<`v-4>+LdGkdFM4!c-y?B;< zGB(I3V_*4XyopJ*f7zmKUijKD)Pc}taA>LT%$;V^&PTqkj8+JjNj7#y#MaDD9Sm&_ zhsNffEG+Xtjm)Jj5!&v`M{gE!@jAo~tt;ZhS9N5vl_?z?HGEsW6T3QB$tw^$wC-`| zYy6|4RSDf$^wryH)K|sTsIM+pqy9uiPU9a>Mz!*_sMQQie^!4pP#d_&|Eodt4@k(B zH_$>+@bpQEyhQPGLt3r!S&Wv09mZ%rt6>b4drK6rey_-MnvfOHokWFd6x`L!5Xgwj zmFch}tny`UBV3u%m09b&pcjfjtcjN!1a-IYVxt_%jLntxu&FzV)8tPSrG;nvhp6vcXFSGe^SOXVAeEN=lf0<->hn8ht%;qq9Z|p?_Ys@*H zYv{&NSp`3k&xZAJFLGuti*$$dZbuJyqGtAHR&9^Kmx30q1kLP6ei;P2*y5nR>}lds z*o;1950IS`(%CFGsyT)(6MHXH z{7M;Ypp?6GifbVIN-0SnzPf0S&be7|QEZmbqk8mOF17oN%ng;`8FRXK2Cbh_GY8Ql_hIX8L~of@ye!7b zVgbs8$%FOYOIf3YJ(TV?ho7pgXDb^RT?Y3SXL+Q07ng;>HHs#^dvp22RG!VPQ8ekj zf0;|u0P#FVb1Wk+_YS~FZ6cW4yVfBvPZ<5-@!NCAUe5XY#}Vs2#go-{54sOHt<4e-$?r<4V!;hT4;%T377bT0C{({uG-pALw1g zZ|#N2Yx$=cy?H|Qx_)~nj9lJ7%Hzv)olE_#t)IB!e~QhU57aNAvvl7u z?KfE}*r1v(?Xvi?Tm5+hYs*I;I~Zs3X1(Sk2=+dheiA{2)t5hz-_@_y7^J%P)n)N! zx7LFS_SR25uQ1K%%M;4aE?7HZ>=A}h9&e_rKh9up{OD5+6I{L=p!bA>wGSpAbeLxJ z=?Tq?xtzFT`kF39Zl8|Py0XuSe_N*R?o;CR=@P9+Bb>No>In%YUSBRzeOkiW6C)2z zjIsE#JDF+blxWYK5`Qx%gJ&wN9iaATg(9~v$7nnUVC|6cX8|U-d^te-$qQ>Ys62q7 z#Ov23v!>aUp2<*S_Un~7+l$I$8cMu=U848sgd?v^K189)?#nkbd&SrvfBrpT{$Pi- zSG1n*&=ca{Tk}nF)gJj!OMQ-nonKxUi{M?DU z0Ph|$doUHbrr`CSN#o8GvPr4}adUHuWiysCbei>%)XR-Q&Fb?bcLxu?COe_a2XYX@E$gtr%=>$B1RM8ag{A$_pXo@AY*B`QX`D^5T=CHA+J zyDd5Xooee5U!YZ# zp+BPA#q-JW$B`MO$ z)$R8e>?Z~71{nAH0D382rtor9kC65#^>?H4p44Bd3vOA)5W1azRVFD`(Oje9jFP@+kr!L~fZQq~9epwLJLH>s7rWfAWm=5 zqKMThSBHbwe=G4jH5_Tdc8K5;y#QD06 zmIXXRtvF?}ci1qrwFDooqN$n%+zMKv?JmO0c=+jbcV3dC+Aw?Z4a{H5UN6XMum6@e z3hqFLe-DSXwB#09Jw9)4*pYECS){N*wcO+@JdZo}P%Zi0 zx`#$ktT(4$c=X9BK+%^~Zy1yblV9uSXeoV*fAreRAh&3Q_!{NmlOpU%&s^Q%uEuRr`Fa4pcYN9j5bF6SKQTTCl%&yEomnzwOr ze>-@dz>9~ju0Otib9wQ=Ht7ItH6yI&pyK_T}N#jozr7C=a+AzwiyL3gt+w< z`ntO8g27?x(VwZ74fZ4KaGIevAgvR?CfA^Nt*tSp*sWkVF z)Ywex%5UQvXbqU%dPQ`+&p@Gzqs`&Ve`xPB`S;B?8Z-GmlV9uSn927o(woT-a(i}6 zoe)EFdZq=nWB2SE+KWS!Fn6cAXYqt49%Q<8Ev!6ly#~=Wf(EU+iQ_9JBDtZ38UVU$ zB6_=DM4tW$RLYw0q$PxnS!Gcz%c%LT z-cnBNHB{FLv;!ILomCWwW33X>e>$@z!cm;Tp2=0RoE{J@{WXQ|M$GJ9iyo446QQp$ zAzD?t6b`MT2%{3iUeq+6PEh*wtAc)W0r@N&`ps;fW@u(?&b?3|aCF;+@G|k;0S?1j z^1F7>3aw)@l1F!5{c(2w_RZ(ZPto54J#yF9u8CVKxHqxP!MR>-?qiuSe`(l17`g4E zn3}Bvq1K|es4SADR`|qO*u0qjt%xvIYMg3?mdOf5b(>({nrLQ>Wyt5;1*lr4dPu^}JHSWYHq^lpY_Rp#rpCpY|h@$T2??Bf0T)y>8ARdo9K)Aif8fgzte z7ZmveznZ|S^&hXlM5ouEf3H5N8{TJ8wRyS+v#9RM!WF72MlrubOIa1p!mga6e=8!4 z6%nWEOvX$!(#FuFS2cCIj2N+zjq1V&izlzjG*R2GUz5@T=N~3SN=l*rwT{Ghx2&Dr9QR|vu{7q zXJZfHqzxTcK0eM3OVKnWw|9m;0) zP8Zpn)xbl81N1PTf30gwAoWIT_(3H`pma1EfWO8hNy?M{L|QG%R{WWeRb0lqTwy7^ z!POM2MQvivGEH{;lAIzgr{ma3L-qtJ(itm%AE%Woy}7Ju5+iN%Et!m9Sh6XjxG3UB zd!_e9DpQ)7pmZIojsZirpN`WRDUXZjp6;BmSGyH8NnxTYe>|(Qg(aL_6|J9JtJ@Q& zL}jEl^hadQU9Vb}YkSrAMJiL8m_X*xOB9t4d7Heo?^~ooHE0bDfm=S*?j=#NK#-IuqrgDmt!95|PT3CMN6(2$uL2s#@1x zPMR_zTARb%wBKRY;MSy$NM%ZM6FiiPdTF>R1^h=v-&k~MLszCcsfiT@+UEClm85$t z$8P6Ww`54J9=VZ4dBvV8z^I@{W??D2%*)t8BsC^mf1kyPb-3EPHw%Pn(3%*6w{cNM z^&>zqR;}ToWNTZ7C(PJ=4 zVWKL1WD)XB5vf^;ee~Ctr$%O?d6nT!wO*&lM=U-n+mfI{7(jt_*9*fDt` zwnN4aJJ4@NBt2nYs0ysfhveR&BF57iGBS3Q75*F%)Yc33%L)61{`aAPCGmp(pb9u3 z@9*&6FHGKhDo>Hlf$Asgq;#!5m8n7N!VJje?_x3w#?Gw~MC-G-u#LZ9>D;hdt|q-h zf0O8@tJs%eT)GjL3nQ_=I*Ik`Bz9USakbsX#iM(}xLi$oJCiW_qhdD}I<)7e6{H|HmJ(@h1sA4AGgvrcG=%M3fncSm@P!t(m1{^y{r(@%YaD5in_C+YeXuC*}S3_GA z3tn^6yVp@FJ%6cd_b7xZqaTZ17r7diwFGl#Y~$ba0wmw(C5pz9fV!s3Bx}--f19;8 zSeVw`2|?raPIwHnIsNiI?{KHaq)}cvObzthQ=q+qk&&O&ppZzb)lHk#4v#rjiMYK8vEoql4P0 z6+`6gEHU1MiE_(PUykk<-h@kwM8Lb%>I{O%GLxqD8z) z^JTQizm5+Z!z!60nKHVxe;;PfX`bJq)f_&MquDUK^aXy1cXN25k7LH>!g9^n$=vkm zNJ)>+h4Fl1#NOHUW3~iBo5O{vyF5>YszU>$WIOyMtGUI)NT!TR_V*(yDTcnWYGS9x zB%agN8SrWrcG2)&PIwGrq=ag!1spAfl}zgI&QO+6r*zon@RZ ztCU{xQ_my##pl?QYsL_*xE(r0ct3H5$}$LN&g#w=bWZ?#9$Ij@;;mn{o>2sMCCIJU za9+Rz(FxIbmG&hIc;-oP5V%;`svUjsEqQ zIXp+A(j29C_SfHDSLOBkOy10fNQ^ZcIX|GOW%t0qD4CVEqgyTvbnb7RP#`wf-=*%# zdXMS6H(eWjnPK!nhT(S@CUTd9smlGiI{k*`rOSLbo-UWnf4`;NqrXloLtjcK5n!@{ zOX#Bqcv1yIAe5CwzI%+;u&kQa-g%NW_<`u zrU+zO^*h~>eX~2>L*)Y5G!01VBd%ODwwUt?1**Jd3 zfSrMRR}84pyD|;O_hkOJiwEDVv$IYRug~Jl#*wU%rFq>Pk_xpmqev}>j9LNb_OYM3 z*~c*Ce{*TF$F2tJcQx2~R|67hJ@H?n}bdzRC|>D+3oPu zUy}XkvT3K#B&rw)*XEcoZ=@W?GAc4-rbG?<9i!VV%1XtvaWZQ8Zu9}Ut=mNc-CgKI zYUoPWBUi9)bl3Ty)q-Hv_&E#)QxJU)H6jhW7F_LzYs@oOikB;P%Fi$cxr@+))m?B z%9u~+&uT}=Clry3GSO}#9vkM7#bu)i6E)c+P8-+G3ebYrr9+hCIeS-(#dkVf%H}II z?~%A~!en*vDz$hz9vo#GhzqBnCdy4ee@>iK(gM+#)4fBK;z?J&7>X}7nB04yjrAy* zXBYI*jJR~1pwzg>k1l-{lt5Ym8<29z|&*Fjxde+BKh zEummb*s*0;v1wLKPvsfkd)!}27Ewi_Q{jUsiQg?2E~|o~gzMyMSbv$Kdz4OjU0uSf zli;krte6wOCgJSYphGQjJ&N&T2sb|uD$!D$lfMFZ(LfZiiL(`{-|P}1R1|rEL-JKf z-%AXOd{N;tWLHav4@tQR;U(I~e^B;lmjG%f_2o(MD-{qh*-St{z6z*-fC=D_^aLOv zpaO#Wxvti}WVvxarPMIDZ2`(79(1r+k0OSEB z4_fk$rWr1wO*Zv?P@O*EbArjfYZ{9v_>U@C-jSb+!QMzD`OoIhfBAl!f80W4%x?K# zD7t^K->XTfXeak;{y-)qoB+X}@Xj|qr}TgQJLzoxcJj9XqQ+oXAY#SePM!~AK4C#a z7#Fv+<%t0OgnuLd3ndkjk_w-b56@K<))nit z&hXLO#L+U=_w+kehi2#@WKxttMV2e{5b(c8K-l}>D_x*I+eh}f1uQGr{1>N~1!T=- z>O-N;1U>Bzx|@hU)f_5dPde-TVZ)%U#GoL3<;r+brEzhR>>jg)f1)Ba5BEnWbwkIo zo3f~uWmTZn_n#OojSOgWzM^B?B_HF|^m_9AB&-Jv*mIB&$>9o-PzsJBBnTTQ4l*xB zWeOuwO%R9#%G$p;3DZ1Y(cX@Xs!K%rJ2Hlb`)`S>X-?!_4$33ZFZ@V-&3_EYj{$p0 zTv6kfCm}{DT(uSVe{ypy;9(s%yCNves}iDb9B+4|ui=~15LImvFOoDV4NHheQiVx?Md$*c3y8_I`>W~3OhR8vz3~nh=wSDW{3Z3Y zsy7>GXG2=8f1BU&tkqi_%+_$Uv7}=UP=wM8)D=`02ecuX;<(0W=&%Mf?G5TG29Qx@ zg-GXz#zqxsPrb`a_B>W6C!lRDQQ*v}0%TBQ0>=imO4j{10y{|xH9x-cG72Wod=f88e72dVA2S|#~-U)?38z4RHo z(}Xzgf<-@2EwbPZP&6q@ihstKC!oc?TI?`sLru23yrBKnR$WE0vmTWw^x2)h99lG^ zgI;huWkB6&Pt7_cn$~^u-ULH7sgPm6WN|MfM`(XRh9%Ol&~me&&6_o7=;2UILY3rC z(k;@0e^OWRC5wPXgd2+RAL9rwSx_wS1p*)MJD{tq`2xx}WiaWv)=3$rL?DUQ9M6{| z<`cZP_IRWNB~k(=#l>Vu=9(WY=0Fn5e^8nF{Gd7Yk?FmvdlW7-gmEcj)u>qvq5U4` z)-a;!t-=dYHtns#Gf_70t=#l){NE^E-N)Gyf34Jd**z}S;j(XE2XFY-!9!l$t<(Gg zgS)}lvRz3~*XGHxK#*^R+N{-oN!5IEIwXz#K&yK?)wK<1%D;Xc*58MX3!qw37qn|H zX8PA|4&NwYcq^4UeNV%W@cC;}V@W~Ll}z61LQFal60aDU`L-|qVn}?4GI;(v5GYy8 ze-0R>v2ib6!(g>c){oFYvz!dT>$pnGX2Au!u#uqLOrUg4eepVI8G@FfS>3_L7QZAG z$M-@j;anlRFwTj+1mmWIan{4=TKke%OUT>yS$Bk-+}PGv&|GOGPG(|cx z39njw!De#pELY1VbqFuS*jkyFar-Y+rPuMi5W-KUV^l1Id3=d_&DFvdF0b1(1L3D$ zGaS>mU7FVmGX%a~pb=CVl>dqkV`MyIF&f?Gb4TJkVVe)cN2@yTnGQ}ihm;kke}As( zPR}rLJ~#;>%n5Dk(4LuOrZ*ICg-@3xB*k~h4!$BGH*t2Hr1+Vsy#(u28w)me4Mb`I zFa^LAP^O?}(((YANY2o2_I*K6Z8}dfi}loh?)ir=VbxtsJ>6>OM0FXCB!Q>A!I!hn zlrZ?RR^1WRQ@gg=*Y%^99iFt5f6Odtwu|K+;{|vZfLk@1INQQjf^w;WLT0j*oMkvE zIW@2~w~6L;?QN$oA@5lEbb|Pwb*yx&CGA+-t(Kr+v-&ljL7Z|$JGZe_;4otZ^cxUM zvRIDj#nveHwvDQLP`t5+|w_No5tBadY;>sjtphh(ev}f)xjCIVSZBq-B8n#R= zHBK%aPU%WUYZ7Yg;sS}|e=^;ge@FhCu1H9kV;tTSpRAO+LqU5Y{KJ6ozYho}0Rd+b zhkm;MpRojemMII#7_F5^XN%Z$#Q=q9yFhe4uhXOm;;9Qn5-yzTB=6bMI+GK$a;6;g z(?CvNZ8#C^{%Iha&jtN7kjEb$Q$#ISad8*YFLYEo6S&~-fc-rQeEPuLVw9y{TQ21S$k$?s zrdWrJf-^xG%Xmywg+E82ufuhhk$+S~y-(;qatte*cPM=f(O24i@xwMMTW};Q{iY!m zXak@P7;R9~veq)Re`RLe7>w>wL3?)ag_-Jo8Lgu1m-+z-HMPiinHQz5BAkmtv%i(V zNMA$eZ~f}6+tz-Y7DiPA5}4&>y^62Y2C2qnzH2K90W%v(ewz|SwIu{?B_mp|CdQnp zV+>tFF@-8W9Iz+&Nt5fDI;^k{CE-;9S2~i=Cmx(Li5p-4f4~3d=~cBwMY8<7V%`2Fd)H44*Eb|r2IyhbM_khy{EnPtArj2m1 zSEzrez~646f3EJb34nN9fOJF|?}(OdM-b|^4?PQyMFf9M?17)j0Pu3~o1W_;F=`)V|E zr?PG-*d)!Zbt<0T=-C)0O{|6VfP;Ek&A1=Y8vPob^@hF{&1~FjU~LCIK@mukB~8tF zN=JrOk*v#S8tM=s7Z+zzA^f+xuF>BD_S=MNnuBqpjs8gN?8MQ&GBb?9&8A|tfw(27 zqw)I$e=kv*#u>^hENoDoYC1hs7(H)MhUoPiaflx?GSrmGQnhdEY6a5XwbE`HX?4SX z4ts9c@1)H)zt;_4QDI>=zPHMyuW&OSi)&_r!p&GLE|6I&tTTKlX#5WlH>NTWnCNWp zSeY~R9a#HKCFQcO$On=8dArg%lv?R4@SPKr(JnNS zFN1eO^LvRtd}|N811Q-p2wk>BS|j+rhG!!}>(Tqg2_L}u{Xz|ycF)sV(HqPv3>~kn z74_i8gOblw=)M*8ILBiVN~UQ=QDx26zBr51N1R}NwLcOm_2#`dwG^T!`Myd2*54~C ze^wteZg(xxUL#+?^L3_?{=Vk*apTi2%r%4g(7=4?z`SS=9=D9N(_)N4!x(&+3f(2P z-;=`4i+Te}6Xxn$_ghC$6V`(M%}=yPYa&=B4PS?3@<}Eyp_s?IkJC!O1YU>dOq7_J z`i+Tt@j75X24bd({ivcRnaw@TcWl4he=|~%DqO;qcN?Rw7=&Fn!cGNY)T3mY*Zv&v zpPRu#U)%cxS8NYbzeiIGO-Hr=ZAy68nudI@+Z>K>RjmUD76?~q>B=OK_>oH-vIEM6 z(Fe9%7U*p*H&lq2AD}gfeyyk#yxyBIv(1K_mymyIWYk^te@jR@ z)!*t2C{!g<@k#ew+7<0ZM~qOO%?}2JxI+cxr1(vkq#qIPE-?1r2QHMB>2F=3fHeuto@Aw?$sJJK|>JM&4RRV?i zohMBeck##?fKiY`1m4sF&su@BHC!|+y*K>+lqO-jcw|lELOGcE(Yf1ye^hY$k8a!^ zFPA7~SuS?2o?fxe>ndD}!qWw-HeaA?&6^g2IyF2MAU<>;>U;tYS|(N!>^^tiCPbz- z-=JhKnWHQ>VzN zMt!Z+gbrk86c&mGtVq@!e*jY3>tv0Y0R!?N0mF4q)*W5R^eEsIDr%#zJ7O}wLSIkA zbCFg2pn^+R@dk!Ri>C4x#14#$okjzMLj$62^GQ}OG}QzS2Z{1z^->%7rPn-CvU;Vh z(JLQ8O0xPvTah2!l*!N9z(1QN`kO!#@2VonD@?|#qChEahqT6be@=qv4yjF~c~gr& z?TPOk2ElD9)(nBj01c~i7DTB^ZN+sv;T|H3Ao~57$U1U%wO$BwW5~7C6Bw4q!Srxh zyTw4>6>8e`L4azrJq)VdbRh2@1A$q{31NDot=)kjZ=QWWz{Bku6sP58dZ|{RrR%g5 z0j~a7)ta;~y3maWf9*zyDcC3MkzRxnaz?IF%bM5?($u;>vpQI-Lq>S=Uf?wGQ$~; zhB>I2Y5il&K=58YYwW$ol=9Z7Fmdi1+-c-tf2Wa$btA8*&xResI{st4 z^8o_d+@^LHi60X7H#w5aoP#La)1j{ z0C?#JI?;>$e{J#*SP%hCt>&lZn1Fx_n6jJRHZYhLHd5_`J zRk$aEro?IW&%(|#DLT%uLhU@lB6S`Fi(0_)hG)W{%_E6!NZ=oD z5nXGoG8kXdM|R@_EdqYcFTVizDZ9OaWdQSx6472wtm4lMD+%?7N0lTsh`O^2831Ge zkaR#{Rfb<$%&#+k%C4kfNlpS8aL7(OeWqQ#l5EWvyy?VdS&G%5IpElA58lM&mo&b; zMJo;ef7*aF9-~62^<0Qp`I?iK&CX;ZB&dZ<_<&yv+D(%RGl}o{CIixMZcrx7DZnD> zyn@vL4G&qVAf0cp!CmklhX_On)?M`=0)Pk_2Nl<|Xeh!Z|9s z7ztf(iTDLCYChwFFSG=MCm18NKgolRaLE|Wf7?K}4UE)1BleLHgDcS6h0Rvh*jyd% zzgj%j6KOU3bOfK(g855z+_EksE9jOHmPcwvxqT0txa4DGoV9JU&cfDl#k4(NR0RPc zA3tN^nN@z#R}+Yg=?fJ(!>|Mr%3gBi2~kCzRfSQ#IWZ)MWe>!z0!BQd`!=nklcw3g ze>T1b8bYpL!Zt2QzKR#jbvnT}B8TZEjFj=S4# z_s?FYB|k>nG~&YrtoMx169>8I8Fl_E-9fEzP5y@+XSftmG5#!h=uHgWr%2 zusaJM*Kz295F_1(-Ub1@i>LJEo@edc)4VX7$ClJ_ng^HIjDxnKnkC>Y?F3e{68s=m0^taK z9hcG6C}F5bV|avHG7DY_w`TVLe<0QZJ-i>pY9L%ZTStO4L0hv1oOLf%JK>KX2mB$H z2-Pu8VQ+M~*~0#4qG~;LGI!071Fq47{&B!dV*Q|=>Pcy)ZJG}IsoQXJ9+se$i`Mc} zx3vrk|Eb$Vavr~+m2tcHx!uJEC<|25)I+B%mV97?rz&9qmNjY0uRN?Iz*FzNe18RO zTG}RmGSZ><<5fNKbG!e|mtH@&tI^;%2GOfPHAK)t&;h@fHxVH^@7ODs!@toBR$%Ts zvNLDgW&cL+Q>jJ#8@)A!f6`Dy?`leD!t5AH-LKK>#LEqttt?^;IeRpI$LP3Cr@pk& zyT=mx76UqSnND;fDb#MV)NPOb*_%4e#RfucEAs$} zOMQZ5SnunmXdR3SE}YF?fjkmd%an29X!ZoCsheq@AX&izA&CX=5bLRG_J3c@-1TKb zC`||?D_Cv};CI%GHNSV%Co{rbxry?7RKU%J6Z7XjHGANgc=1cKsfPHF_Ag5^?iR^1 zctclov|jR*EA=G4C1vnk_<(4Bue)u!vk1A)$;=8W5Jm{LUAEaJq9s1jvhK+nQ`FNQ zDiahuAewc&@9e+sEP+x%P=8N}AlMUn+9a^3AWKh`52RrBt}x9Xpy4rl_@0V69B879 zj$fJl{vE7TKKD77Z{=>*bv3E7e^F6lR`e9cGLB4X};Hokt*0@v%5@giI@Fl1KPt9H-@|D>8c}X z>=2*Sdm_W1PF{p0@c-%LrSt+u%@VqjVSQ1?BJ2UMv(-z|Z@?Cfnw`wwUj$^hBka;^ zAb(Nv#lv@`>nQ(%X@8eT*K9WNj`$Zt|3^B~Eh=vL;cHSP|L2Pr7{%*6-iEgYLK*o? zi;4XEh*F{y`9s%39y9=<0ToJnS`Zp=q0sG;{+kL7xX|EVxyXQu{8w73{*{UQR|PLx z?pc&O#^bKV0W+XaY_~Pj`=8t3DvT4pi^lAUcDa!xo@<%|g?|*|x$q6$)uZr!`%F<` z|FSyRT(_+siR(rizvoFtW)}%2Dl96hH?fYjZg3ak&$qx|L`0E%ZGT^<$!-TF51loB zt>@9thtaWrfnE(un^HGWqOgGo3q{5Zq+tA^8u*LBw!hb~0fSX2vjaz@zd4UVe>*_b zS@#N0@w4!!*MIENMly3Kzazz;-F-)ft`u^kWI|hkS*rwc;_0KFtG;wWKC6NVe8Eq= zCQ`nD@&$}9;Cw;Nr(rfc^4xn^kni*$Gi6d%k2@qh`etS|VDugq9K&dWfakCKPYm+C zCBPO?w)Pb{9h+ag7B1(kV}H7k4vzsA`J%$*-t5EB_J0@5_U__+AFDqRX?^g5`JlU^ zPgnBcAwtH!Hz(2Y#Y>qlc*qt}bE9_Y3ARqs+%PGv<;W{E6Fzw<^NBKM#HU<)SAK9d@=>^*@q<)c@x<(Ij3cmLB{Y3cD=_Sve*ym~Fa=T!-^@zAT+^6Ota zQrO+Mt$!4Q2KB>ho_M4?`0JH=8s4$@Vj@d^!@bj3$?)hJ3q)@H}>AUGHkUq0X{zt59 zWbOcR=mb(S`!#eNQQ_K|3XKzgd>s&}Y_1Je4S%H4nJazuGYshzuaz2bsnWT+jzfPs zc^*Ec5<{MQBiSv{9Sl*a`Md3 z!5x*}I#x-TB|i^plz^fHB1$Lld@4qr-?2#byMUt5qf!KgSLW{mK+!9J7vWPDi$DqN z9e-zm;SNUny86&P3)v%IeQ-CfboF@aK#xvBq7lsw%lER)aAN$ismpXj1^LVtLM+E0 zunSi^$OMr-I%h90ZBe<&S6Di3K7B@4DA{oc&^cN>hRrJciG_Qes?qUoEja+mbPb6~ zmX7F8pV8G*cKCuz4qC~2&V3m^g>afwnSYpY!BcT;8x4FJ!mD1*v`Q}sqXMjXhS{8s%aT+2v9{(9G?5u^z+{oXeuZ0AykiK_DUpNz9Hj_Ro z*1lvm`GT47a#>3&6-t$kvn(%T^40h{Ymb&{dR`}Q;H4x|x)n>azp1H$|Ky&cr~Dzy zNKf?DZuGSa< zVA#ElB6YjubrdKDzIk!aYBg{K|tX7~yJQ^2MxLzgXf zJzBNoc>dvUT@|z?asR_P4Sy{Uyp{3uF9Y$*Nln;EJmL7;NtcW+Lj0nm+plU8*-<&+ zY+R3wu2uXpsXvJ#cKi@=TN8W1VVx!1k#0Ma4IvY+Hp{HMaEaRr6B=SKIIWYEjj(>3 zl|1}R6=!jOcNJG5LX@(xdr&|P_O{b`bL5z|0@lv@3$LO%)79$3&z(##Ad7;n`vNKDD7 zsX5;@nJ{{Sh>m^&wT`JTEuK=Hu<)hIqpB}8A61>QC*H9W>hy?6PU=#ej_$;pu;EQt z+(!^chaKSu&>4Q%dw;`WN>}l|>;-zvq2v?XT+;NkeyaVu_S`-E4KI|9Cx0i5I7zY9I9@JA2EU(8!1cHcwiQo$z zzvy^MmTxn({Zc0CQj&_((a&-(-h|2?H|6Dv-$~FH@hfVkg0em8CKdzKervg=)b)j& z18qdEfLiRe%6}g+`jXw)FelYnE$HgXR|>momc8xf19m!zx8x?y6lM(=W)oe>?eP*+ z4QS7^VC+{8*6!&uw}Gd-Sj)H^mCLhQ4Jnw?ZfVrCr@glCj(7vNJ1XnVJe_-x8ng9` zJJSMb4Qu!U%Gd6@thWet?pkX26wHPjd6?aovx@yj5rLmfP}fND8FO(}}TrKr@y` zt}xr+*tRS!#jXd0(C=YW4Xw@1_Z_wPL}6mYt*Pip%b!u;uP5_;x6Q^{dK3KPr@SBo zKfAm9J%76`>M02Ww$Fya#nF~M(W0>g*3nQLSBE7DBPpyCO)hu!v}G6egyJnb%VZrF z&;K@+iRtRfF6-&YIqk_|7x#qX%{`n%mR#xS*&hO7;9aA*gp)aFyFe>wZEc3G=C1G7 z84YSWhV(~96QKUU36+V<2wEAC!dGWvITz}h z=yU4RRl5ztaK5G6%$f_X03W7r&;l6f{=fRREHDp>h3iodR@qtbi;^8`orAt1igFFQi9u87q0t0~a0ytt za!@Cy1kyV|$)w}&^!K3udq->Grp(d!Qh%Up*VV)WiZI%JY>1?xe;;cyd84SzWRhkw zB{Qle3IAwvhlL7iw?FnZBr+}sWxNnxXd1iwaZfYxIpy|8p0oidX=bHe;Z<2r?pq?h zzHE&tzS-Og<9Q@-MvWF4Lpi+H;s$MF(pZ<| zkCtBQwS8!Z+5J6j=g;g*?0a$2Y=7A3=G}#9rLsXU*v`{YVK3Ou(f!nYOEaOeO}>6# zXD_*WiPrV~91oj>w3e8?$FQXjj?}C2aCsU(&8DpWsg_ty9Z>23-eIh%gO<8JQa53c zba@=}wib#ElU?J!S<=Pux*>;RL!MX%w`%}< zi*UlL{+XSpozPJ?ZN0CZRmxhTk#M6#zB6o&W6-b-UdEykE2LdGrSI=; zdRjuop6tknO_O%$v<>z5HGi=-G|{a)Y<<)Tm~=m+R>L;zJS*#zCmb^+V+Va0QW#Ai z@?vG^0eu{5e!~{DY-A4CvWdetuqoQUznxu1Jie)Y*y3Mxr0;KVml5x8b04v8o0F+9 z3vj3}`TZ8Gg4Yf+sLSuwN z3L0t^;s0OWweHq!B!B7udY$tML?62b^9ZKTrTr`I~ zRy4oz8UxG%`)eO$A0zf8&RD;yid1Fz_A{FvS&NEa~Z zAS#Ilnv3pGlqLwFs3@fdpv}lZh4n3by9X*EPbVvsiUY5&m&^QeJ-xZ=*>H%g=lJmJ zSFgkiBmp8Qx__@;<@gYpQCvNIUFR!C1MItm;eRJ`wwzyM@_0YqABGyPXng|z(*?9z zHMlXK60ks)WspNMFqMll*@2+a;kAB8G){aBuon-(ylJB3aiGF*9_%W2ogi-&hhs!s zN-er9XKG@QC2U&}UrC~ehXlRkcRc=Fcv?t31Q#i^ioHV{79N&fTk)_<_8 z_ve^}=C?BqJ+Ssk?p#V!^mFnUfU?c|c#f-}WJ*8R_E$gZVCV?tU)_Iv-+%|+PTfP% zS4Y=7c6o=fYw>(cruy=O_9)Gi(~`KEjf$#d13*cBNNUmSnjEH!@aQ$ZO{^kbY9Ql>0zjuU+_Rb*{X6GW z5yI~QrbG%NmOM@!9`K67h#!2HOQjtk{vdc35`Q0_Pv<#gH0s?A4*;|aNQr$z3S93{ z*#j^x1FnCH@^=V@mBJ~?c|)#J$XWUVm#ax_g^bwVxNd%ha9l$wRxTITfDG8 zTv1Gnfv*X)+sBhcGZ#d@He$@=mZ+y4vP4Cvb6O>px3T1f&is)n#)Jf}Tm~dNAC#x| z_kWX6_aP{Q?1bgndt0*^1~e<%In1*&6Dix_E5xf?nBGWM=}JMD^uv(44#sUxS`YQ` zn~U`iR-Y(5@xI+O)C+Ko7CBu+%kaEBFZ!<_x|s+Eae_o_VR2Q)#}3PFJsE%hu9y$$ zAn`E)>i$1s@^QB&=5YmwQb&6nXz1bIOMgsD3tq2gU65S4V+INhZN8E{H80#Lg7Gb= zwc1{^RTI}eYU?Aa?gc!C*`PUTz~6w2Q|Is2syAE)T)%t!QWi%R{hp zYs$)=g8ZbuD0{x%POmytWPD}n(4lW>P^{+AT1+WNb&{jOE$1}6v^JkAqOLhi@_*)H zv{s+Gysf^eiaD61KAF-nJp;!9-Ix<(KdRnwGH#2YlRm|X^r7*oH>XkT0XmHeeHs;S z{3Z`O#>$GDEhAcgU*WfYgF`+{zoq*W%Lmpcm43LoDT?!}GYiTTYGS)#kwe2)59=4p zYH<)J$l-4mx+*k4aS+6T#kVE1>VHKg%l0DYTW>*Z_Z^K)n7znJ*IO4)i1uFO%wnaqxmb}j zlv!%e+@k4JX%8|D)Pnd8-mdl_Ex@)?L)#ewhCxZ?C;$TS>a&iC@ z(sej^w1+Wh&)nCm?F*&{Sbw&@k3_ES?K&vMD}T!sQ`WwDad6h z7iG%wbGKtc`G;S0=vI*2s2VFig83MX0flk#wx4Lwnuh-L{=K=md;fj}-RZZ&?bwUx zN+v5^A733~MB9sKOD1Wa_Cf)=dl9`UEJjr76b;X}`+0kJw~n`$qJQHBB+gof!lHUcByOJ)2TyV}rHajWQQMypj zhSeazfzKHWLDpRNN!{{!<&lvUDvklrW9RISj=+Q552VN^9DjVE9GL+d6wkwa){;C= z6wd?06A#CSdPf-Htk9+)J?eLEc+~IQ@MsIQE@+E+l%mf)O3~*YkG|PHPS|W8Cv3Kl zBb%*ryuw_cbMWn{uNIu#@O-s~T{Y#yxY& zwFWyEBlxEEm<95*9ILW#jll*)V@==f zFJ%LiLP4P1C8z_i-(KCxUef7IbC?^8@*kWHBeLhGcK5f&Ck;1?OVUSbdiG~DE`!Tli(RR`BmRuGWJTi7Xn!&0zcL6(oL1FDJDW|=yza** zs&B7H&*esb^RI9OOlsK@d045=*X4~luJ}H06u24WCZzzn6K&%kO$gEhwRxXp2=M|D z8LzG2Q~~fb>hZG%`q7=NyF3OL2SM2jR{_Fj46c2Kp+Dn zQVV}6APvj0R$?0Sv;bR_B_D6>jm6L#>clz3D}Nw@JX?MQ3E-?7-~{}60*uyno?+Z* zn>uiV(LWk1m{`n5)0Irra3710noq>ap`Ot_3Ywfo+a!%KjHq}VkmpLyo%(JRW<)Ai zKP36FI*#EtxTC^Tek@+$^@b#9;has+&x<)hXwc$>XHmX}y&=FjFf`6gba3B;@>9)% zOn)JC=47YEHx>&MJzV9c5*bJ6h{b)7k+jj7=w>Jn@dJ2m_t zav`aF0G()NcSzFrIp0+EYC)^`M4kfVDUaxvZF=S-1Uw`>$H$N#B zgs|IgXlQsI2Jx{E#B6^wfktm-cz?&&wqqLcQa~UWNIW@TE+f5N{4BTAk^^x~95< zFox@GZ(TeLL);=x48ONjmi+go9`3gfV~D~wE0bH_)WZVLP^w%>mH#DQOn=X>Ac#so zLVC)|-D+VEZjHFr(CsOxoqrL>#K1f<`GN|@l)^gskr9gPm`4qvGQEFGEqy5}xpK(S zJX@V_3~X-{G)L{WR#o9v6^4FQqbK$KVk&zPt^syNn3^mA(H1}&Zz9Y_eZpLy0ar*+ zw3D?g?I@9KLCOx0+s`9JVSjuV6GrY+UD-XIbO(+s?2dde*;&Ao#XM2GXQ1q@oAewyiN$P3rQdl|@%& z;{ET-RbH3%y!dO@Lsdy&9My0LmI&rFVtBp2T`J$>V=5IBM2#YOUVmlOf=M~65=04C zBw=3YcN(7H@Suu`5T9#-a-7(ZM+3fy6AmsGDV*Y~jAl)W<6HRfG5&IMnimP|uw3`Z z>Fy`1hoZy3c`S!((ypl$twr3_Us<9RpeHZWEPm9&NAInj&`ieGFPxx zH@;1dSG$;=V`kVS9)Dbz=<^>fw0m^B)!ph@8)2L)aO&t-!GblIjrF9H6)$^VO_r;= zJeNzb{CBc0E=yQvidi2SI!L8V$soPNJusO<+7=ljrEKwo?s7ck%Uz00TN(E;!HOJsecuX5o-7c@M(}7=IIb& z2KR(dV@RhgS4#j`9KfAwD%Br;r!(Em2Q?V#F~iL~y^VZnHH0HqC8qpGGGF64JAAQYV>UIpw&E!@@xB9JGs zp|a|u!|xWt^?$UwP9qB?i75PPl2pF3lLpvzjC8O@yQZSdx*?MCozX7PCfja&4H9ax z)8_im80A%6pk3-RfwV5GOb_bs2=Vx8&@4tI?dK7qmN!#1IRguKMCvPz4Bv}#UVle640^@q8~kmmB^+zgjx)Lx zeFVPan{4EEU$v7BRIop%^CHL(5VI!J`DJmoo_4Xa%PKDRvj77(;v=O+p&FLj<-Liq zv|OLo3HBG z0ngjnK?zo<9#C5TrR&6A(0FP7nX;E-i zlrW8E$eOnhdE`QF53Tx7XRU~46tCB^opn_TZ+~?0S}otNy-s8Gi|x&EI_v53x+iO> z!rHa`WtjMp;B8$PDI4y&M&Wpeg^Tjq;=OBO5bc#<$)wJxHjBkHViArN=H-?CuxPg| ztL>|4v|X`gBpt`o&)fE47~_FE$YCL$+%7&15{WUy*Bx zyWj6-ne~I%fDmHJ)S&P?Fv`5XDy#fVDm#F{){gq#9+24&egndyDeZ~^BEb-OkVYtJ z7&w0aBQ=xz5A%N~ktWxvL{v0`GBv>}aEqr$D6viKD)RF3+3suMUlWxR5;+T9GGrWl3IzI4JVnj!Q_p z{0FXo=yZeLR%z~n)@EeLup>B;*?$j{&t}v0HTkvl0U9`vwFK8XFch-p$V>1`X^d;- z;HHY=K(`?-&x*Sh05P#+FSO~t!n6C*+}^|Qb$L;LneXoI?hK42KsQ?cn8a6De1+jF zEWU#H3gmmRjpV=n@;^J751iY}cilzC^`LKk(&KoK2Sc+x%w6&w53<)_3V+o{kwjSZ zLqg?m^!v>BiAo&TwpUd8@Sa3I@fO}RUI#Fv2Ha{}+)ilMnK_P$eb*>{A-J~Z<)~=) zUIaUa0dTZe#E^%hMk?$&4Fvj0@i2822c!CPneXyxzF7if`wStoYlvTA;A9A9xRzw? z1g_=ML=Uv<-d)&aEYf%4sefPr5bL{!NE;FWGr*z%CIc))yJ++t7C=$TpKjR{t5Z}6 zqh7&)7*RFwZi5sX({2?zsd+%tsSh+Po7K1!k+NV=QBV78W1hwLC7glbyr(@O?EI}F zoO9JjtUE~Jtwby@T#@9VM5SRJBwcyoNFx}C0#d6Uv~rXsluR1@)_;VCXsBGibw-Uw zB{aETmy5+t8g?&>`C4J~;#p?jM)G}g_ZC=)Ltr6}Dd`Hc;3m9w1l+d;6zkkfJMlbnk5Dk&vR<^_P)9C3VKaH4V`JKSE`^(Kj9$L@8va?T~ zujZS@QXa#44Jtd9Ez~wUfbD<(`~E9tZ0D*}jJum{2egHWd9BbrQeI$ma&5LSC*+)= z(qP{^yR$%odqDvoC?;mdbpqrK6Tp8oFu(`Bgwyph*Gam+f`93_Np~x@?m-#1EiJ(K zs=kYcv_#d(?K&Nez;Eh*pZjng*y(IaJZW06NpGRJ|84HWQDLW}VOZ1u zI8@VX-iYw%*ajO?0ow4RK|^;%w&4?iu_@?DD7V=fpl~WsAZo^)oq~QOzZ`0?7L0{l zp=SeoU-J=$k37j4J~p@p@_9Z;JZe=W@6#4YEPvPtFWHlzWKS+83yK}d3gw`)fS~Zs zp8~X5<$AN~94X=5?KzQe40}?_In`NX;DA8>aHkr%u3?R!)j46*%ZICF0r>;Z;p4N3 zCVk0aIsj=c=?F!KEJFG7RyNtiW=V2kE;Fn##G65pp~PxvigJ7yp0~4+VyrO<0Xq>u z6MuVY)6c2CaOyt~5X}rWK+f0zxdIjFQWINX1@4)5g5L=s8$lb8rHx;YW~-i(%gZ7B z%piTwbT%s~uttt3bY@7oQHoiUAyKlSC~S%^qRdbZ7i+9N6J&Fo0$&#mjVZi{kj_3q zB5Bv)yiE@2Z4yY!hO%RW{7S_v{hEg>3V&7c1rs` zUb!ftzZS(po-n#`&OmI?-w&I)CtzEU40J*jM*kxQLNR#B5*`ke&}t$k=hCJmwtsbN z0|kCv7y=(ENV5skSR>+>oXbGDz4dAL297M+@WnaD;Y3VG{>)WKt^&ClsQ+>)9H%U^zyQp_2^1u zg59FBr&uFM!-s0DFv&z{Cc1OBkkmAnw7@$T-j{A_=ZH4KN(^B0$>W;2X@3B|!2<$y za*xhn5ri!QttOrb0z?p61nj@yVS=tBtghOsmBC{OS@%>&TK&B1MGe6T=t&<9mioo| z{2oO?6kjGW4#*ceVzx^eKa@6Q4V8^b92W)UuC7*_`3x3AIjiSI)69YCd00qdDLI8@N?ge$>pmIR zAum{IaJ+s-kKNpLsEzr(82+e}7l`U;mOn*!|P) zpGc{f>rDQ&{PXM7WAhcYg&$*1QKl>&h(F2y@SFk5*VpoouT>LzNRsJv-qp=!U9L72 zZ5wkOFgSXh`|iHT?mF}M36mH57I~Oe&Xsp%l7FiT`MxKQbK_lQB;M#Zk4Uz8>qyKS zH;z*fq4%1&dp4>56U>7B1mKnni@Jt5ATNPc{j zzwyM!8|r;W{I^PcAd(Z2tPvk)nb5isgJpGu`>9uXnvZS5$U=(fo2i^tH4k-VT`pmI zlMzzi)_aCEmFVwg1!x*2`n))SRZ0Qrp=2IvzE&icYmU?T2Q^1fssS{7m+j5sjd)?kF#VB@*xx_t8X}F5y@L+v(!zw0!*tqE3Uh?o(9(*%)ZQ z-rq9_?$`H|TDR{;oN^JsNz-^Z$8&7&aQ%tFpeSxPMIti*LBWVf(2?WkR2h@E0lR_DcBp1TUL37E*8 zK3?jcZQ|G_X~hmX{^!SSe3ib=7@3{{AWuB}b${YG-&@RuL*LaVDmWjt@z0vriygDI ziN4r9O`8Cz2~BQ7q^5;d@?Bu-rt9fQ@@c@S;s*1qSck%6WY6vuB+DR|7jA~*=5pL5 zCt1kDD#M3>la-hk9|}fi(GFMx{PK<^UCyo~3|)a0grR$!#6Amvo<)MHa&x+qy_lmO;0alzYK6S(O#?!L6&8gp#ml#<^s4A~a z^(>gIsUsm^FkMsQL)um7V{+8zIO@Bbe1H5EM}U$F?{XSZiFcUVYP`eWR^%N~s{B5h zQW4u>r^nbL>dH+Bi3ld5I0qPH78rl;)y#t9A94-{4~l9dRWiH|ms%V6=O~pZ|7Q0= zE{Fd&yAQQl&pz?=^aOjgss-?(+x>cl9!Bq&myo=~YAyeHsO^!q_sA33g8@G&R+upL_G((^SJRuD0%w#D)bG`W3o zC-uhF?H7I9efyjTb$Ig5XL@PK&>; z(7c>gL$kG)4BwAD!n_5}^B%nuhJ?rzp#J!6Q5p!fT3YCX_a7Ya21i0=0PRLXvIEk^1v#-=u4v@- zsvXcGF*yC~A8!mRx|2OYRuoaJ-RZ({Ik{Dt?qW}joF-;J9IFG3#A~yvtcz{0#{U4K z7;2eypzk>8zqzZgubA8ur`lA-Jylzxoy z%&aK8F#8}l@;z>dgJ|4Mz`!8~*F_J{xSL+Q_levB0ZMzG!nm3~iT&u3$*fd92_MT! z=7XJPB`HWbR9a~Y60NvSL~EE$1g4qgqaeaih)#c_)d^DzMFQm~Eq|=CSmKusLuV}Y zOSieRf*W>p241c5#Rg)uMg$v>EbIi>rxlTo7+t{$H@2bf zgd5aQerz=C#GS>)!+%cSTy#3Hgr!L*1jC7s095CJ%=1oMb{g=u(cTb!%8MJv`xqzT zJz`FUvfewH?ZHdmT-eA{1H~d0OS~7GmK)r9s0Y-I1cEWxwi3Qqyig?tcVwbhao1)Yy*uZr@xc zAjC(J;NydwQL9q;*mzpOFMU$4H|O<6DrjHXXjr)Lxuc+M&ZWtsCTHrj3*)whc{QQk z1^~5nJF2xa54yGW#fwaduuc=hi^v`kl{0d$(k_;{dKrL07eQC;;Am!96K*vMKG#mu znNg#H%7u*)9e>j3In@_bvE@|X&eA>nr};I+5RBrSJd`6c0DuqZOc@FwlAG?Bj}%%q zhcGz7JYg0p$_GK2x}DL(L|R?f$MHIk>j@E&LfXVwdVsqx#s%Oh7n*AEoM){L<>Q0S zC3v*8NEda08x9v0w`Ygt2wJ@dz{50=Y9st?9NR6CXn)&HqhbD0BkD-@($I-IEQxpG zPRDWzqn3o3G;mD@!FRQrO2V9@MwKmawg^<+s1!Xh;jy|w949<>L#{zyx$yz`11mP$ z9?LxuRLl*cRxk@sDy?!DDYBM`_N^uKXbYsxmoqIf=B+Y~XxC^F&$er{NNU?P;)&gR z+p*)R-G9R}%Y);_QATEtGNMy=bl*4mNREz@8PkbCJv;Ie?dVI_f*Dt|$l zA1FbNt?bAl?808G7}Z1m)W9fhaQp2seLq!vAh(iT)hnUILEHta5==T5_+zycERI2c zL2-WiSPdPe3&|SvnRFlu^AWl)&`8sHm_0)hRDa4GW|-4A^FaPTS8|r-v$Ep!S^y@e z;H%NIET1xBW5Eaj=KaOIytx6UaH~>%*U#Xl`xLWu$j(&2!I&>k$%tKxG74Kp1I>++ z2?C~pUnHY>uVfS~<4?ay*Wee4JG}S4It7<1v_2|wKPmd^0I2gnx7hM@2IzLHT`bjH zXMZN>4zeXWKFV=FFRzRFoq@O^oUDXM*np4eX^F0ta+VTRgT6!XU3Q%7X}ScKw3S@) z*G29q?|o$>8bZ@JjZr7Qp^M0FPF(BMP#|iE)*wf!@6Ovds0EoIGMb!i9$W_#JMH90 zBGs!K)A?xcACdL~!d2hOgGpmFuWq4=djl&MKyWH7FU*<<2Bm7Z-&%g^ zEZ4-|pLodLyB(IxKDbJj7bYVMvp?OsLHlll>@Jc6ASI%&iF9eTQ;ss*Z`BsqBY&Tv z%O-&~OqZskRYD$RJnRO@c?T|~bQLyTn$43lMQPN+C;7WXjwD)H<=5h3HJ>$7iw^L< zL$}wm5=60?HS`^G{64~wL;{bbWrgUFA*ct2GEVFDO3%T5Z&B1#27Y7MH+?V|vya%c&n`YtMqdw*x?$bu~> ztL3l1{IhnkAaUt~f5Aq(DAJ^6N-l(>U`luk4wT+mJYCs5o|zM6P;G8N52>W&q!TQP z`f4@9Yq|ID!JU6%ha2DDdH)`*_b|HPJ)}LDoZZQ%+Jez@t8xMnlsE#!!BZQFqe2rr hVGsj{z%f}6VTtiBwV?sZx(tz;vem%s{{XW|2|o$VQa%6x delta 30197 zcmXVXb8sil@AuWV-K%Zez1p^I^IaQP+qP}nwr#t8?(_XUf9%d=HpA>&$3M-SM|F8jl` zFX*_*O${WoVdl{&p<1sD0yCLb_9W(cw6Yr;lvjEP`*ZV#!M+YMx_LCT`;Uf(bL`br zXymTZmj&uIdXjS_hK~?L)gsVG)Xl2d^C+BVbReMIngzKI^Q$9|R&-!RsDhR+N*kQF zi#)@2k>u|9<&J7Qj=!gbw{bmu-9T4U?_93E^kZY+>K;Ybcm6NT0qRCSe_N=#wgsNG zf!~L^(MH|OC1n!`hAtkPyTE|Rxb$_09D{cD&xt|#x*ctMmEYQz%lxN@`V5q3E6UMQ zhCRR*Nc8Dst#f6B)$Hjk3oebj(Ef=q!$V~M(1cAbnriP)j2!tg;1_8|w|)E?k9*&b zp9ac??|q2XuF$BUw|ILW3+Y1lAMaqdXH}ll1c#?iVqAr|uo2ssCT%XRX%MGXl?p!TaI-Rtso`aPp4kR!A*aIU+R@ch|5SN`RrJXp*au0Zno3caEbN@{r>AdiZ zzsB40L0st9bHYP;rkRVMEy`e#lqcPZ1Fdogrh}Z?oW6PaRf8aHnC&00e6pi8nlAvU zsr_4nBc6$z0*3RUNZ}{6r}RKk@i`QSUo~??nI2DOy`BnaCG+rm%ft?4+-}(Ij;ArT zf?${0#Rw%y0m|D{zfB6Q_Ugox?AVnsT^;(nq3HyH@VjRjM&+8?hZu(&&4mhm908$AO-QZ z`Y+4fP`y|{^0vD~T?oWqYz_)uRcv%7k48N;s@trBb!j(@9(5ieA=`{1Jw<@nTJA^4 zO_{5vGCky9S;gD49}M$eN_LGaHs>EvzLzhni(n{=8J;O)ky8&WPs@k}#e9R;{lrud zTaQ!p!bdlf+>AjSx~kKquH=m0_IMw3@%zlCPG^$n}aWe>093A(r3#g zH7ZRinkC)iZMYd%O~=sar^8vwlJn*fN_ zM4B9JV1^00ig1-NzlSHwEmW_mxPdJ3<>@v-HdQmqUf2smEd>v%9KqG8VUK<#nfGnt_TAXLk7wZh(YA&Le0EAT-t5 z$Mq0v2yeQa==cte&o7}i*zL2q%wr=#L+gG!27WPwW@Etb0=2waZ+TP#KAAXI zgRv+qL{0C_18{SAI6L46RuWU8mwwJx#3Uxb6ry}ATK8%T=G}a9lf2Ja)H?%ds+0^{ zM7wm3Pc|STXpnmqgK(%HcU0WNOsb17SMM(?637{9cp`&%1ZcYp-H~KNci16lA9H} zmYFiVSZ{x!5&#giVR)!|TBPW((?;H4@+yke&PG&to-QjlQ6cT_om~b^oL#@4r%op1 z=1TPVvv)o{0X`n+ub~{x^OkhUeEW{bO^=kHt>eQS9GOkl&O#D6dm}1r;(V{KSk5ta zwFcI;wAZOH1uF9emqs+0?UJZlc_Rh%S*l7qzr@vLUsod`yr`0hag>|yvYzPzKu{&b zWoqVQE8HKiojC>iq_>|9Nncu_4_-6EThJX7qYv=W0Fk)lM@EVHUeOl<@bU~^<(}fT zROQzo&)1*p309ewRXLMQqn~U<>hmq%=A}WN(H5<{cRR-kfi!j_gdjeEO#Wex?`o}SRN%L# z&64QX9K}r;(IqC&CE>%_+?HvXoXwcH0^;(RT+Wex{MRCyH)@f7*3Y8`G#QkV?3DF{e^VCd8CWt^Te3zIO^0Mz|WbSRFMA(N5 zutPymPWwgy-A{IP+yKe)V2jNZ+kYjl_0+ZaZd8728*j%K*~{@^O0v}`&%&$^*MI`R z3Cu9=ZnV4kTMOf+W8H)zeD#F?2->ByE!}!oKs=?{W`mu~*bQ?BPn+OU56gXD*VL|b zzoQ49wUZ_)_|*|E@s!1DezcxyFh-C8(3^xiRrY;I-#{`_3H*RAb4&fmxh((5mI*0O zC5?g*#a&LJLmuSAwMxZSO>oms*(eF~m#^<&DTd9KX0oy$ye&TpJxe$6?h*xOP)w)Il0IDFn z>7{FtZ1r?#wk>y&ocG7`4q93>kl~Awyrc*}A6h#;Q*udTyIz^nN$=ESJu{;wg>4YH zgcCS$Ml~w2D0M!U7zWZmIv?UV1zb7FR_&+1KB@>6h%Eg20n$DuY&x6`?==5(Ka112b%57K#X-P%;+s;ZKw%l#884&QIvkj_@XjUO9Lo zw>TaN@k)IR=kwU3>*J{U;rBE$J`03%EXnXjhH(31M-(}AmL@<{CD_*hBB6Y&vcJor zS?=mh$79}RmJ`Hs)6d#$l9Hj0>b9)f$iq!xHtepPJ?DMTmU$(}+EmlH z#;@v3j%mxj`uX6fS!cAHUZya_u>L(PMvmMe#x^x1`)FpYh(1ThN4Q9NvtyN*e&g3G*?+heByyQ_-)I zt)rcZWr7PqiaYEA?-(xoWuDBejN(R!pk)TK#kERuQ9^PhaNRV0(&kblu`MgH?!W0p z^A%9=z3cboXCpgR$N%JH_RrquS`(G22oM)$J&C0F^GmPhJW)EF&+>ScKBnVUYSB#c zmizFB1{s_2T7VtP~DB2-K^6GrIDEf8ysub^Tt`ZD$Xe- z8=q|S_aBgU2}Hy{$&fQU%oL@E+WB!6tPcuN3)@+ywd+`=R86bJ;%yqok)K7e<+^5m zK;H+12Pzkp5Wb?{M#&fP4l`F&7+7@dzRZ(0G7;%p1%PKPT5)*RaT6Jd^sTICEE@4^ zmT{f`5utV`@ar#v>rE~p<4HfTj!Gy2@P|?xQHe^S*oXPbg?PhFuaG2R!LZ&Y}3d&;aPq*?avkKtvM^Qu8_*^ z9#5ChMXTgQ>Hj6Q;Ml<(vlF`=@9s}jpZBMOx2c+y6f<^zg1XShE|ZASwgnkS(TIEa z6Vr>uI4Aau!@sCUc+*qji)!2#1qgr*_Ko87%?}m+lR~oVS-xgzK@Z19Uph(QV}G5P z*s+DxtU!cSppBBsOs^FRw<4-rzics+IGWg@5os*9f46UiM-MMtNf1Tc5&lFrBdWqF z*0NZ)L=70PN$z3l zb+VmJl1^{i)3k6V@lhoFBvO`~uDRXTLOyml&HL}7(KebKo8<&|ia-8M%rKAMucwkG z$54dvF+b5goJ;Jj7N{_Wg6bir1yvBFS42=jy~2pG&2!d9Cdi|*Q;aRzvb!@Yk z?VZ+$V2$%{2h?jfrgt?yrZiX!#58Z-wkT+?8d2gMRvl$^_(N@+I9yWpDIUG1NOfne>V$t`i=c%J-9Yag#siXuORsbSQ(|g8MOIPy@ zvoJPDI-+eOJJ-|bc}Iulo*>TT;89hohaI81?9Ni2vDOUu)yqHHKCZZ5=P3lO$i81E zCIpY4^@GilM_v4$;7}`ELSF2PEaPvRLf^s1owEu>v>Tid8Ur5_2$X&ZaS zUG9y)opZf=ySRSe4ZMxCtPt$zX?I1+((~_lbNyiIWP*i)0)D_Pf%&=TQ2A+J?5bC~ zzdz6J16n&>zm76~IC?sv-~-;_P`Q4p=$wTfs?b^o1J;mw`~#ZT=ImShmo|6xgYV%` z_t~+1r%*k7xCK)(@Q_2PI$+LCEluo>plG^}yeW~`WB?s&bT-`(4y-n7}w2zDA&dSX)`Q)iT%{%sgd zy}tte_U&BG{$OYw8R^%#%F9HMTzR0dpE=Ft{O~NRdhhybP381q*NdfZ(P)_=NMb5E zFg*vn96eh;eGU*EKdwY|^=#^2eFLm-+v2^c^aQYPJ=?v`Z3^?4dd=5mGQ3$*KdY10L!ckDifeelatN zE|9RD7YAiM`e6DyrCRuMwi(srTiU3f)jSJJOsRK_OJkVp1n_jp-R14%O!sisb01kRsCLag+ckJESL?%HpS#iu36Q)1-*_Dk->y zx%9y0)o?45{Cy_7a!IQ^Aks8l`;&pIpDWY&Rth@HrBcXgVUa9<8Y!)ZWHJ`v95XrQ zo$Bc6f<`gR!3OIziRXXv&(RG~7c8B6{F`is{wl}W_>yV5&tsK{!zof)nfsrJuwf(x)8ew!AKhR(>*?KC+?NCX8qkFCu1kZ7l9 z(Mr4xV4KIxvz_EpDe$>OTohb=e8Xyof&NE6?v$T{^Hf@GHY? z12uYHV3;UmZmM1_Y72@4Z0M(Kc^G@N`$u@v2>CMEJ0A6Jza}%6LJ7QO&ENlNh%bGN zGN2*Z9cVHMIGcm&0G>Jz1D}c52oK@8vdO-6R@wE)W8N@pKG5M>ldr zql*phN<17`(@BQ^e`21qwBmoI)p^wFRH`t$;4%Ht0;1!65Klsd6mJ2uaNhQw1DZ2) zFr&{V&544$A6r%9!?H6}v}rca!02X!bs==d0^n+%b32u!H9o}EP#2)}o5V+FA=R-y zC_(%?ZC+g)Im`r)Jh797R8Vur{al8q_W%4H!EvX8m-f#qBVuqnsyBnx(<=ASgYZ>e zn{U`ZrT_fshVJv!jQynIzh5V!C;lAuuKO>4;tlCZP`y9iEq|6_^x1pq;I zJc4VKN9FNRB%)X7-2AIr;f-E!q#w$dK4Xa~e6)=`RIx+NltpF?=1i`ThYjY&$_&c1 z?`Xnx3HdM5HXzlColTax=ud-*5Uuu)zy-HxJ69>hnT(uFc&*Q6_gUUhL@oB#zJJpw ziK+4Zaf&Km&40PrN+qY zza-S>gy~%XxoD`!uk}ekpBgmgW@M<9gG+jpb=B)RvtpJ8D>^cv_M5O>7>kDGJ1P-& zjxC_YnBN4jT-7HX}3FCWy9vcWulKWR<3MrKxNX-xlQtQwuVG#OZ(sXSaKvU+ftpLu=^P3!H4xwNW!jA4~DOlBKTrh@FH<-G?);vjnXygA(}T z%;+Hn-f6C{@Ou=elIB<=$hy3o=IHcnYt5`U!|>a@v{u4z40XuQ0ix})JgDT-HO-|_ zdEFwSx=9fiK#+=H({hM8XjK+YOkTX34YD`<5!S0@D@M}1a3apts4(dZ-V z>ec<24DR*2UKE!p3=oPsruIrKFV@Dv#ZvmZhBWZYwuej%?4$D~Znm|*8IsJLtWae< z?T+VJ1bAZSa3{hh09_yqiW%Wrt1`cx!+g{=#7L$icR!)}i`)V`%tO3=HyNZpgP#uQ zFB!k{>xW!fj70w)XiD8)6uxa49bnqgQHC#?H-kzOO#Pjy!Z{uM>wCceyCK$O@Ms(8 zHRf77Ms>_aaX*cR@t5Vu^)mZEG^3d4;W7j_)T-FnnfGj53Rp(_XhxUQY2_a}o`CSg zxYP17xYzu)5VOmc@2cL}h9XXRiM@Yi(m7ECSY41;zvdV|9D_VbonGoNcw%jVrqDxR z@*wJ8K{lNLqqcQ%iX9B|dBsNUY_bm>PeGi=!mW1bKc4wR(b>VvbGKUBeeNwouJ($&iBuL++r_x2yWL3?$9Dq!`9XFZEag!9b|M4E6E2tHev|j9L|~N z4MgDarmoxmmf6z>#3A#Y-1FxO$Zp+>KKX;%xo)x3so#oTqatw|9Y)7f$yEGq`EjKbax>ngzR)4=d<(#&>Iss22qE+8k4{veOX{979E{#e zqYa}AxVE^VSm`-l_fG-eyAnMGyjwT&$1!Ml{2{PzB-bFf2#<)njzF1}4gaD&vXzPf zl&pJ#zCkmQQNkugQo-It4h>zgeM{1Zk?9?3G)7Mly`2j^L4iv7!Zo~IVVI+toW`EA zwGnKBvs&axCsO655BKX#M2f3M!X+k2DC8=r)Q#`T-ceC|82m*jOG|eINJKb0x_o?r zeMks)01bEX`RPWaPq%dq6 zU)tM!lKhl~6W6T8BjOkWXeUuf)_W=PK#3g`Y^8>v>knsEZxN2iEQ@x7i74wIE)fir zJ`-tsnTL)^yKkQ}{jwOl*<_6M&AKf$xGnHHFr{;>xX&)A_1UN~sVVm%F39*}Wtd)m zdS+n#um6E;rlC7*qFX9%tjPBqA99F+XDrbsAu;9*gl6I_x9^VzC<`dGw_hY>Y3|E| zo+j~dGvLO{Sg`}H#_K>ppk+7rfN%mtF=-oQ6XZIn9PY>+oYDok-(lTQI&{+&m;lYl zQ_H4Z;<3Tn(DsE^n3tOZwFD%acSPPY;rnuJWu+XJvQ6rGgFLL%ufWu=U-TSB2XO!0 z8!)i(m|RPlP_Rh_G)LXB}uX5~Q?paIu?r&b4|j>oBmmcexl)+7OiO12AQ>};c- zs&baEFUUb1%E07{Ur#KTNf~cp)3%AK#?EBmxEkY1qf=VT)3U!o&m6??DogpcT<0O7 zUQC@~;QKg2%Ribd;eea;AFjM}YD(@9bv-kUUhOdchdKZuW^S^PR^c z37Tq~fjhk@{1@1mJ3@^#9lYG6BkJ3}`U!1PdA*8!9lXNxArd!jC7*(&QnIH}M;oO!V*W6{ZM%ZIukWLr zRV6aTHa@d$``g7uy)PEzh;v;pZGAwvxz#n}i+hYtSHP&I24mAI7G3PArn-n(*%sRG zH(tRtK}=h8k??Mqk#usa>{^2-FB~GxRtJVUR;xzPIXYLc!gl{vGW?INc^~A<(0tcg$0n=vhVG0IpU&b475PFjobJ`$AP;W*W zFyMcb1J=S7rTsU?w6X`YE5fLs_?mr^tfY^G=Zvk_+&a zK!}$a8rZ&iMNs3kb+|pMS*@945)GgPLPQE6lh=X7+_91$TDU24Y9$?}xrl8n034A~ou8 zE=vuNnbqU-@OH2C_#zOy+0{1AJYa9DLBSe7~K)o^A9;Po}{{zk6%QZY{q? zF6igZo=z&{&O=@_lx?!F`v5fM9rgCXA2c=xyQ9tVU98o>&deX z-VOH_oNnH=STjp$6tbIdfgxJO4bPKha^Pyp0=peVL?-$EKOUj=8eI#bY-X&tv%9}| zC(SOfQT}wzVf)I5BLOJzqQQ4-7$xHG3;E+zBkR!sWX5PIcXVp%(02B$LzW5|sSVNz zcs(Q~VH0N@uJeC+{Ue-*$9G07jwJ2qtkMVnYk5kY^yw2&K`NWMUnvzlI zgq9oi&R&%qIE#%R5Ve%HY0`(wtT* zl8@GPpZ*g-M)sHU5n1#|c$>`b>I1z@9!^tOcsCiL$xA|+2C=XVG3^xgA;>1+>}fcH z8;YDYWlWizwMoc`zAzr_AOp|DxHw%+<6b;ClWGU0OxnUwNC=zHg4Lr=_5lJL+rXG0 zYpm!TF=HJVP$R>^T0krxH!b2(8WD35FH*=<6#fsA29Wv&moGP^Bos%5Egv(mU%92S zwz8HHE2hnFf+7^<>tfqV0{tk=v7_s(&nA`0S{jP_H^2Glke=aB)NQ;i(PG6{h}#+~ z=+>1$Gfn>iTbRX1Nx0q0=@8p%R-ZL|{=z912!RIJ=7*4C4M zw|O3lp{u~S2cjFVYW*HfC##!XoMiusrvh#~?JYLv+i4Kd~ zeMMk^TzPg&?a5h9pdL)a&m?{~(?A9V5L`ia3{=55_^l>o!x<3&r?olbtQHg6qpEu6FxeXrzsqQA*L zK5JZq*O!ueWsA>2CFC$46sFeDstEA#v{}`Fa4Mpr0}uleSLy7qtG{&v@Q)ct5^}2; z<-k_=zuVkO!|obGqN4Cjg89Wko1Ox`9Q%FqetanOB|3BYOM&4>Ke#_%U=m)k$CV15 za^J_eD0M32Oe|;H89*H0I#MSC>YS`V=iX`PtPkkbx!5a{DIWT0d>7CvCw3>P z=)XRrmAilEFe`1jeXxJ@%cN>+oqD6TVg)dmxtKCPYx~z3fDK<$*M2bWo9eYfEu;p2 zdBjtwuEi_-_G*Zk#^E$VNu|p>jP6tT_x=EM^w2t~AJ7-D%-9-qzYEM*#gfgCmZyfZ z8!$B>d!D*$kiAe4p^A#70FB7bpRIBbY3B?z`5=umtkWqTF3qA31*~j7Ub`ep&gh-5 z^FkYppN<%=h*pP~(DrR&ZM?p8{u+Dn2+yx0$*n$P8cTmXFuj69FLrSgnsx62px_T! z%l3HBaBr3|S|p~xD}nI7pqkg{8y}LhzA^3C8npOIrRr-(zg#Coa4Yos!{)@GP_R+R zPROtzwQ{~})`HUoy*}!|)8q64-}7<6S~qyuOCq@CdwVv7HFS8w@oDlzP~G|)v4v8V z?klG^YZYaEr6Rjl|HIm6_iO$D*8+o(hIxgMud47;MQRRKpSu-HYox}e{-)ih%j~W^ zY9giExvw_ePS)ZOZiV)4WjoQRv2mkyee5YSM^^WM27r`z${)F4a$1?yqB?n7k$g*z+s^Laq9%BueRu z>;2G;y~zr6(jh_7ALB4#e7~qsJE=CgLLA$uGUI^!nSArR(_A*op;^eL5f)YkIEGs8 zGtVB%Jst!8;3>KH-VY*YmNZQH!^e6DWBL0(c=;su3&JY-=14X3-dMEvH3tL3wUWnw zilgYRLeremPu$E|LlF)E=4_L6KK=yzTe!NX2dQ;!wc55L-OwxO~}+j5zC^|1YE4ebwLTPVHRq3GJx?iVRlW~hBSP>vU@nHaYMkHDG?9gln( zK12AttiQ|$E~kk zU3>}b4Zo3%;KZj9%q`b=85kr@i>^+SVL-Azw8&Azrk>o&I_kHLxNc-t#Pm!tef}D} z;)R579_g1m0;*+u@;uI%cA`rrNFVGdUruWl#%ELJB>g6v^F((1TQ8+0j5_X0G#8YT!%X7?uQgQ}^+HoGD z4jIPJDi(@`e39w2m_=4~bedXBzvWX5)+0LA;|O&Pl5GE2h5Jzgr>TC)x{*k*XC@>R z?Ls@ltN`3AXsWN`>bpDMT!qdPo~7`9#o0hdW^>Co_{BZbaOCaCj-o@ij=1;x?u8OK zJ7dOqK=)`bGohW~rr9HlN`TMFHR&%TkA^BBqZ-Mog;dZ@Z(#A&bJR?nP2bKZlof?I z6j3{wpT~GpJrHS#pFv-^URSmm}!53&q*#piH8;KV{8?(lKJF-|o(c$fP<=yzF zGPO5)Mvh}PJBWj&wR>RK9t!*mQ(gv7#f|OjZ$TRqbTzh^9Y%e#-EA}w%g1Wzfji!` zpR4^o_KV9(l);Mzjs^!3D`N{?_RvD1t4RvQiQfgPy=^|1CAQCuuy5Mwmvt3=?>ca< z+khoM5ly*H3~P*`RHyOVt}!RM?qr{Y{>9^5C8#BQ6M!o>&r^yqf4lWMB}+IJcz+Wo z*(45SXkApqWGbb?fbYnuYh=CRopolEW;c$HfbE5AoPZm~`(Nz#`KM8|N}MehzS5`J zmEn3cz`$~ z3WrVHD5Oh4I^~n}+~g`t=Pdmo60XvM3*n-q164M*LB5OVa|hEg%6r2)(mj;uVZL-@ zM%YM*hq1#NMZbs)Tlm6oQv-10uFDzXk^A&En$cYrd`kVBWbj0JF2x?#8}_nZ@hN_hlCE0H?KufY1wHlgV2uRF2kWW4 zlyd9fvFI^TyFzbD5(R22WAV@S(-QB<5X!9?~14Mett*~oL^LxUI zwnFaV&y0z@>!g0`5C!X*3mIh1hN4zVswqah46oQ2#f_LcNSQLNSPM`fV?@S#6{*(8zS8;s zLP3!W+>&=b$jnfF>HWxZW%Oiy()yJ$uA+sh-?b#145Z4b&ms;F(b~K<@@|L8T}EG2rew_KRFz5QVDh$;;Lfyeq?iKjC$hzl3mKf z@`Ox7HIa`yg60MNyg@>I=6jXID4ltZ^RWe*fM)v{qBI54a7ufZH)j@<>j=Ci+m~Yv zg~Gd1uvC$Tl_a0w`;DL2tTGk^Lb7n33e zS+a+P6$c@kj~0|MLjLuc-Gx0CI2CtBb6*_i~;z&o>gJ!TP6(He{-k&zrgCeqyGSPl>|kv2wz_}ZX43k+}` zG$0C$8O=q)au%WbcwCZD-*ZI<4}>hN^6;jN>|g2>IrPm=lrnS@T9g$Y4FeV7VXG2$ z6qWMj*kfb}Cvajq4$ou2feJmaV$Fc;Cx-(?u2FRShaCmBp{mw6Hli!ht}d52u@4TK ztqulhQbWqkt)9w2?Ru!;W-NKulR_$~vq}htXFukClatTMH*E%)2noUD)3^Z35&Re$ zen#h?rpG87AnPNw|2hRWWV-scY-dcET~V~_1Oew-^&tXC@K&8qfv>OqRlPWNxmkR@V4E|CU#$AiAz}b05ze zyEF!6t|f)a;Z*($YcaLAPOvK8RHf|yINI(ZyTWICSgJEGkneRJElW_4naAR#vKGz zCL(@6hw&K7ysieFTY6nS;fjvl9MGhqrf^v)P73YgT0$R+K6RRlu_=os@3yYg03TlL zveU`l_g99>c$Hpb6J`u)UGJ|!I15eVCXM-nDIB&Z2Wo;m>05$xWMl54iuV|iKGI$Y z(I;SpqhAUg6~^1YcjN>9l*+2x?_LH=+Oyh4F@zH7Pd@9&18Mjh=uH(b{+U2{qMw8V zBUXIdF+?Qi-@$tVG<9?QwNhOLSrLo{=`zD09z>TcJc5uZmmg z#3?Uo_Ai_t_6W5Xhh`D#CSBLqNSD^jjTJy2&bQ0$UktYk7C`T=Ekm=l8uDV3M?DSV zp;jK7)svngYfdJ-gc1MjdA6*J4M_TZjb7-}i@^bKY4Rf2)p}&wcT>gyyCmkeWRdL7 z!Y#4)clx5bqP#O{LQ6Yhf^5(rwU}x5Rb&q)@=hLXb`LzL9Mn^Aj428g_U>8fF^ZUkR`()(wtGyN?atDQO?DswNmg z?yDEve5*5R^GcROa%N6Rys$;=kZnM`ps>ZRnNyi7nWg13H;h1k1-f2snl|^ulA{D( zKMZ5D>aoe@H;l@e3lDwJZNeEQ+Jrv7UcRnVQ*H3X1>2OsYuO6y$fHfl@l!vne+`B? zs0#Q|&;9@=){J_TSj*dH+^g*BG05Fq`LtJYV8YaIlcBSmiuMI&=}ZJ!AxMCePzG0{ z8ClvH+>qAZ0x6WlolbpV&7V=3OgwT*UsFr^KCY$VfM^|%IL%+uKn!4sl%;8nJOX6# z%#Rs9dWgyy(+QJ?yiYk^-+NN(E*MI3E$f^LIw8aoyOegfN0rQ^u-%m^ZX!>M)i%#A zU#BLa;Nq~@!YzR_lgCE9b-Hr8kylbAqX;Dhlr$;6&@tPx!{1?Tu4 z>@-O0ULQ(?pM^!tQy5j{I?$XNg{i(+iZ7B>u-$O!cH;H4fs&eJdnJIy=hVoWytA$+ zO9upEJSjuH*^3921RmhV35sGBr|Di%mXJXNE9Llk!;9{P z+ORNRZo+q3jIZzW{o{mICJC%k1vrqaG;UZUyaw})Mc|?kS|zFI1gTJ^_V~Hs&}fLy>>3JgW~oTGnfyf>iDF9t?)0_>Q0tk)x2 zp=obZ?6uo1zzA2&OyQ3}JL(!8Il2dz`&%HU$=OP>RNJrnCd_=w<=+Ln((=Ph_$VrS zGf1Zw_FE>01ZWC3DDAPh1LMbdk_5t!Nv?XIwbA3~xZ#pL7JtCjf0=`b;Vd>*Ho@AY zVX=c3cqz|j<9P!NiaqtjDkwgRdz-8O_cyg;V6E^TrV%E}?wq z4?T?5fVn`mtAx@XdiVjPO}pr}A!H9HCfTYRu>2Xg zpj)_-f6K02Uy8N$5{w`fb+R(~|6XwH^nsL_>}-aEv|;G=Ws(|cEsgQOzVnHMM8j^^ zXdJ5e4{Q)^+cauFK%0^_P4*y6c!M>-%VK=;?m7!fVaT^z5NlteofA;qwrG`BbXWru z;$slvDGUR+^G!C8f?dQ5S=molDKhZFPQVX&^%2~y_jhZ!S?ScO{CXlSP>tPsLkBM9 zNhhz%3oy*x9%td3vhXkema_<3y1Y|}hdOf9jW<(N$cEtI9;_}*D1q)C?hbd?k%{S%BvA&#(BY3-w>3O2c0*TP;$zik26pqxwuaY;Sw1g z8cI`!{Hdz8dTjCgV#`ZE*55QQ;78`>c4(}bgf+5nC{wo~v>iJ$|K#hFN-TB=xrc_q zNh|@R%OaqO&1fb5_T&}E-5-g9Wi_c+zS?Nl^lx;lYRnMR+^WqP$i{i*ws@GjaT!ok zR!@z-sd7A{-i#XAPfyFWXGV{NF;0fQfF*#&{s9?`E`tRnJ(l)?SoT$tXuG7o z7d-Ucu6BkmQhkT+G*4l=sh6gOm|fTx?O+3VxVfNp7ZB+-!bBfV>~76|>gFTttPfoO zl5B<%N}-KghU~7{TML`@eDrnbhp_kUkryuBdT3OA1aE*A9xP_E|EAyp*?R(_{>$B#)-9M@eRG|toeuk3N6keU|z8s+PD!mq~qr&<{D zm!C?QI>|lYZP33&DHlSg*dJ{Tmr?`34OXISl>{-LDAJCb_#r+|OlxOXp85LFHUbxK z<`#t(6s`an$lFcDzjrR!LJzc5E_(gJ`c*XBnV?8~50OJJ{T%mLBF5P%p|FLFn6?Dp z-`U#0JToTX(1?y9%w_WRs4c;2UdSe`8-AaV9_CoRI|4&Ucg<;<3cui6B#6i+IGTL;_y5 ziBsdYUU(KY;(ICVK`ES=JfDMz((Pb>?RzVI5A6RpG8B>o417-{5{7hm>cRC<4-x&@ zn|d2m32oporX+9RdiaYZR_X9H7Fy-uO?{oOp9#=5zYB0$MkYulH2}$xSrsK}l@IOE zEBUw1edSXar|M zH?ZB#6o-G4%?@^y|G9@wxGSfSm)!VWb(fVu*e+~|VzIrrF9-12=MELL*NR{jCS(#A zIL`!AC|A^S*ph7x9VH6$yKapT zXvvN@+A$)akM1axnr&|7MmU;bwu5kM{{cQ^(UzuLj%I$wMJwu8!LQmxb`?qId?46? zWC;BX#ocD%(gF~X>ms*96Ri(SUvCk+Ow;$mGu8tXO%Tf125c^D_Mr!M-)FO9U1t0m zX)$n8mU-b4p^-IhAQ6KF zQqQy%Oj^bEs$neZWTleM`~Y{u_E@zzG}s!wIBPHntp&vVVBUE9`8{*k?R=Ib#!c?m z_as^mU~TrL?m?*gjA@9#BOv$HK2IciGXa#4g~wKXn=q$kfUz$13+8-;$yO3SSNqoB%SyUEt!&;+H9s3s$OK7vk@AbiBemt2`~}JjHFJR%f*9v0O?A&98>q2kD3y z=1O_)*xE4s0P0qpvZnz(hQABfHObhBWk5;Ti;8^-I%Na4T1WC)tI3<&-72nCP)!Bf zk!8oIL=QsZWT~Cwd9t-OJzZ1PpZVyuoqK5v=75Jk`8de0BU&OWnia6aDUWemuL6;N zdJhxyzkJ7S?ewvFc?v`t)le#4nFl0=zV;MICE)U}FNMH=Vf`Y(lUGmLOF@6Qh{~y_ zrc{ql5CF%mUy#kQP^%%)dH}QIs?$g|WHpE9VA}{}XM7`#wzHd)9Oz*qj23T?ueqDD0Qs_v#+=d(6N|gmQwe{litG&nhq=tV;Fg1jpJQ z<8$OUFj9bv8gJMy!T|7qc5Nz?$d9+54v5!dmmO^rNdmLlP^STIfd&dhC;k<`f@ZpIMXs zw<2Ck<-{m-yGhVdT)Kko&Hx$R8zz>S%|>NIt&29J%?yT$pup(JjJmsNlHTJID3Q^- zkmxi6jek&minfQ4vVxh4fwG+}?3lqCNL_^=QtWBB%*AP;1zT-&jep4BiFbDA))ppRz*$mj4a103? zEjbn1X|n)kwgpe#U9ZGVTGuOlTs+i*HmU3@6GapA;&UN#^{>_dhkp}rCPbpuY9*-I z&%dfp$K@~wOB47{zd*aFW$|KsJ7D~U)c-xR{ssMaN#VhD^Tt<0ip5y$99#6OJ+feGkyyP?7kd69nu;X?Y<#Ct25ae>Yf5ZjXlW_3QOJ0j$ z$Tskt`~%pAf3^EFKzjnin!o+<74XsYxcd_nLoc^V#ZskYH4ilWdF-}207%TYae|=0 zbLlA&W=+$H@9iIj1$MIpf2sF1#Vv2_#ahgK`YNC`6X0acoa?L`G(~m>m*ucKyWFSr zX*<#2eqo`XJgy^k$vo~OWjn~NDm8`TkmB}Vss!Z^OA_D^(i<^hVU@(Bn#aW7OP&l+ z>#s`t;ty*QK)8XZ!-m9|0W8N6{`=`u31qefQALTcFF51ur_5;q@;xb3*%}qAx zd~Mz8fX0E7Se|AnBmWg_cgrMKsS&85{$BumHG|6V)O#;q0h^Y#$)AjL=>2$qRge7K z?tk;8*U#;0G&qhy^eRvd5ws9=!0+WvM2OBi_R8h(Z}fr{nEQ_G%o%stztQ_tY7zfN zZ%yH!G!)Uhni85YJ4RCXYxFwtazkb-ix@-B9*y5II&RacFKzVhv4lQ`-84}5!Svd5 z5FFHk_pdjd@O1Mt%(;Z0X&vr=R&Y9e*4YGR9;OkcnOB=w7G_)@ddPG^`Lu)lsYZra zHe|8v+yQZO?SN3aW!_z;6P-v3wVNz;+hc$BrcQIQfl%AZJV4@7pCB35`?@Jw2cv=u zXR}uzkHpn7Wn4I#JppR!W|}8RRW*zT4`>#7o zpi~glQz8iVgq}7DEGo!<(o^LFDVV)0O!Eh5c+4KYr(zBVnkb{=S0=xI2P>7&ea_`u zxtn!eO{(nQNuykDAP{M@XJA)77>xFlQWsK{!pj!mJqNfP2B17alS}*efb+CpQD@ZS z$X>rTU@Cin$9NysfPJb``BOexd$9&Af&6y7r12Ncywg6k-W9`tcj?fhV87_u@~gUB zNJZDAkk6;xbiG@e@AYA%3ijCSE|Xj0Wq;X#_OQf_;Vyc*>PQ+p#3%Kh$nd9=7a!<7y?{}(gsx;*UzD*3djRZg^^)`(utlS0C-e6g0U7QHyYw2!UzB|D@Ez$o%D-UR z<h0>lDga%wFbi1Vgra}WQH27C8GN2;=l~$^MW#ax-!HbrA7UhodxNC914CoWv zZO!!l=Qg+s`F?*t2ZX}84n&vwrVo3Ud!)!Rf23h^y;j0;~UF=p+JrstEi3QU=>N>W9~Srccin)Efq9+{um; z{{=4l%Xt!?jzlb@$tCGH>&Mr$PSYtVlxsoyZaNF3&uo(a5$hV6JAfQIft1XC4IM{R zxOS#Ol>$r3PH8bgr)B(4S78hfnFa`0RDKuILK* zCNAP785b0peXdH6hYyY`MUs6^a|ib_>{#WPy&0$Szx$>k-n}zbk9P6 z_Q+Qs+>I+;J>ELdqmz(mM6<*4y=*g_7=LW)GTl%?KC^`o%kc;7!qpBkL8On)*~?2? zRBrMWmX4cGpV1Xcb{qn9juww$vkHG=;a;a|bi7+j4nQ(pLt>JpBl^>4boG=SzTlFB zRm`DnH-Y&hBWc zJG>LxP*1XI+YNDI440^H3WPU#x-u`D)`~aQR=l;gLMYmo0aq;OC`P9+0adJ?+eO+Q73w&OzX`vs(lQZ$wp)xm zi#Jh^0(+~Aweso@14;X&V-lEq>qZVFPTlgU?#j=*3wFa zQl;Z8%gdO2HNMW;qotaj*U1}rDT$PB#nS9=YO3Hrxu@tUf5C;`bQq%|DVEEd` zzr()B$M8Pqxke}Np2*zr5-z{@tj^05`iMQp2pWv~cpi+aHAVm!c5kCd-7a|@1&V=h zUfeUAUaUzJer~nCwWQb7Ot&hn<4kS2tK1Sf>y?Vq+5PCAuU+k zJj=#jwv7d?_B7S;0g?StOZE>Z0cYSrEE{iYhCP!ft%E8Q7tRbiRS?(ESg75sGPKg! zyn&N719WppJ!K;Xgjvl%-H>b9SdUiWX$QL*e!~A0u<6RsWs6;pRxLT6fB0Kh1#L;( z|8P!2%L8v^{QS#6{Blx%6Lu0$IR19hC8LWFzv$@ptC~c1R8BY>*CV5A6~9dCPojt& zKSbQt#9nY%X9;(t+sE>m+3(tlwrO4?k1IS=`@U#Z`z9 zrEKgT6i|b`?R4H8Ii{_EwX^=htLzr93C$*7v7-$hMyrYY|He&!nSA1I4`%AgJKAr+ z2q?J{a>`~B?eQxufcd*7yG4)s(7}lZ7W9%dGlL1nTXhT)Q!;95&UZ~FjGiE(qn|*n zW9mzbr&K2_e5vxN>PyW>Rj2HUckF~ZJtC5mx)i6QJMkuLc+(a45ya79NB9ABh9CCc zaG26nyf1r!9&;#v`2;tYG(D}KYX7c1cMpHV3uWWU-wC76tZ}IecnLBIfgmAhB?N*5 z_O{x7_IAomO@PzMmBJba1p5;g3QoAv0i*AR=HQ_(I1oI-Zi{+YD{Ll!>~O zq~dh+v)qd}p|ZzKdHLdZ67)s&E$#Q?S6TCOQ|eIe&S8<8uZ7JIGohm5{t zH#W>kbyf?1y1Md}!mgTSZ@c+`olfE{xrsA{Sp$aIL|1ZqyaZJP+VdbGA>8u@~l=v3Z}GM8a3@{ukE`d-oWjS%6cj5G3 zd)QP%Yjg8`M=d^4m>6+uDmv2gXB7DB$$Z~!v$2-m1poLcFUY{p?k<1NZi{+K!hr3w zVQ_JOv}I4UXe@zsG!)0xVM)SB3hP9Z%UwNf*@Zo!c+1W*S;ximzfEOgy1KHy3*C;OGWDeRc&$`PEgPM*Z{gKfGs6TK* zW#Te|Rz@?P)-vkreD=bft}9+iTmkV!1dCIDE?n?R;sRBGR}#}(UQ?6#KI#UsJ;2!L z_gF$(!uI29pycfj91c;A8W)tOk%g}NsCoceUtZo@E~Z|OF( z=7KB02XE4Ctj(bZCH;TXmD(P(00z4Muf8n{%!6W~dthq@(W17}M$00{IJ%G1v27xM zQhGYju&YG?@S3eE->_BXf#+6u-2oZ!yi&5-dr)aeHGWqM_(JV|6xNI=(tU%ZZJ;CA z`P^i+pJCVyYGSWdb{71iWQSVkpl^txT!U_6&=h)TG{GTU0+y~E)X6D<^bSxm>G(VS zJ?Q`5(OS4Eb2Ppb=-PEP@qi+Xb{`vmB5CN~$C^yuC@M3Vq?t^~jA}{3KbqWOp@Q1& zk9`e^jLSh8FN7DG#_oRH(@cC$x&4tRZ2(G|S!q{zRo0XHmWZz}TVslEHn+lf9tqr0 z$#OL9s`AiU@}8$&wXgkl4v0~$>3&R=Q^I{;ylNl!RgwCteWXl0`o*lJ`#Hsb11Y2S z{BXjzH$B9UZPY5FLF6iw&s1)pZyEu(HUs$KgwJY$vneytGUzIV(q5@_6|U{0>pkKz zZIIXYU%mAm+m6mM)a@(pG1$fEmR`gIOsH&=uiw|%ORip`b$vg_!zLlE zC1&q2Z0Um|^{PBvp2knJDXV{~C6-eMlsbTS7;EaFrLK?EO&BCy9>=_`g(Aab*SK$% zbTPbc$f4MfC)UBO8vi<9vJI{|JJrQr(;y14mu=Op8JAQ44BaA}@Tz}*X6I=qbkt2- z?`vn3vX*Eh+$fRn3|r-I!!m^X9rE2^3oP?Hlxc0_lX47?DxZM7zqR7&C-k*^Caqq> z3OO8O25p#stQoP_V$2yf(8Jg>VuH;WG;D*Hv1r5!X%|lE`+J+7mQb-LJMv-Eq#ZhK zL;ZbCtPM?c>keBVbpj@T-4ChNunjxU$~xr<$4trCK_7+`M$?D9SQ&aiABURXumvp} znZvbg;_wY@ini}>XO|I=Z)zX5_*Wh2`y1S4#QWRaN37fCWGc)89O_GczXhw{wZjbR z@_RM8K*r;%pd||^SyNuBwY07QvXNTff}1gE^^dZ#|6jXg$m}ou@Fy z)!&Iir%pN^!(mH7-TB|H83OO!IyqG>;%b%TqZ;g8b~&KY-hG#XhFV4FKEpey$zD8l ztYMy#CBm_e|G&I{Yu&BeNYelL6hu6Wv4FHPv1KO{?2O@&d=VnqPUOhgU&lu}l*HA! zXbyR-Xny522ABo**FMNTN}go9E`4P;+2o-e2a6!^5!qc;-Rw(sb=6m&ZMccmkf?jd zr}ie1h33WWQNKKtL7PU;CFEGuI={rl4zj0=nh3`f)I*| zQfdI&j2u*0-@>Q#;p zkr~C+!`F3xzG5`MzDpSXcOqxY`86hw_v8IxsNss%C-6UAK&w@Q8}lgv3uIXaIV1y9 zxj2&@2r3<3>vu%s#K!=8@es_LCQ2R$Dh%hru5#B2@>X#;M#QDmqRVooCI(r;wiWS} zBzkywz{&3AsT$5%O%b^m=ef_Zm@VQ(QG=ZnZ;zyZnxs)hFQ(NM-Z?JIs!m;^(0R%@ zyaQ0^`j1kj!^#9{m1tWc;M~SJrsS#w86+Ge&e~cp1Urs zpVE7OmZVAT;xUtN%EypASFMR%kpc0=@yE?lNvS7m(cu-w*@@%QhF`H&709}}SN|05 zDIL=@a2(K$IYIWL>K!NJwg@`uQ=CX28lQS|8pR%<)2Ps=QSrua@~~s9thm`SqV@L` ze(N_lh(shB-i;; z9tPmtxGc)ctFzTcj;o~mEN8Xb+eIi;q$$1^Oj8(|f@tpT=DJ+|eUvxIsO*R;hx~VP zQ2p#>$mzKGQ-yUJdP%{{)MM~g4wCtybbQmYnGdv1?U{=eNkf^X_RKwh3Q%Tylze(o z)|jSZy8c+Zmo=02Ak#oCh~MDtY7f!^Y%4XiogrWtWMza)E!n<9rb#m@c&8;ft5P(R zf>&C$d>c9R)~pvnnalNRb5m`j5|y((M~Z2QVRBhl59Z7=!lAeZAVg zV0wUM>-$LL>fWy7B4Nva6A5O8Ce-Ocb)QFMpO%>l;3tuST$XZCrYt{qJ0_HW_(g|q z1<8%7vEn0`kHHvF7#DB*i3Y7{=uhw8o144$??=#`ek2UO>XWSp2`o^a0#|?3u}j>3zl?PFFE| z4Y$=w)#;5aYc*DlI!F;nNpE1^qEK_61KQoA(Jz%AC0r^!O1M;dWM3*-U0tv{3%O@Z zmm5s7G@Z@Xd?URWwhuhAZ^5#m^>8!}3ccgZ1)`7b%N|WOcq{mu=KwovPWwwOmL`rM-weeUt-o9*L-&GvD^X8Sm@**eE7%=I}3-=6wv z!O0EJS8K?{zQw-#II{2BCoalFs#RWBx0Hki=d4i8!%$NvZfw*XlOdBdJRKgy*1O)A;Pu9sLU;@WGB6^w@RtJ8upDb8rZG^i#*MbA12-7`qp^aC#e6hf z$wUqJvG}O@M64X@8Qr6x$!WAr(ip>tipK$YuH@XQ??z!pq;mB`k{_$%7=D90Dm>-K z;uT(RNP-s5+4TIpm=lBsElzkARr zO;xWJw2DvUDL|g`*p8t{(gq-i=(%Z$)ayu<4fbAe{bsHe)}+nC~UJbx%EvwEbt7a%9T|4U-HHD{0f4o^dqFFtlX`C7WUxQh+7Ta zo`Tx>7jaAs%p;R8s9;Pftdk!Zp}3BD)DSAu`?u86m!gs@haAnb)%nK2_C`T-)NX54 z6>e2w=vOs*Qr|D8vKQeRU}uD>$pR2<0i^LJ!fezh%=H;?g#<-AS;Sp_ zJVF%4cQIk)KGl`2^!*xt#L9n~MP_D@eh6FFeP)r9+G8E20&lo7{LGy1HL-lz1C`w( zM8$oUH9o)X3>%_n{c8wAP3l4_dXR0~8dKGzE^k^{bX6wa|Gr%1by?4gzh*sD zl?2974ToTfU``{3*X!G*@;yGLQZYf)D3a$@MlG0>vnoN9a77Y-=7oNz;Ry~8s+b7z zxfUqLi4A!);EOon;9`-&DZa{R)}%PTg%2O&FE^)ok-!eib&s6xezJNfI{cf*a=0e# znp)9X#7+H`C0YS`@-ofhM=gBx-r7kX9+=MRAUUz_oRcVX1#5NV+vIq)i|ILLhE3wZ zg^51@(L%dNw_DwRt)8_J#<>Egj*b;9ScBPEPdZugviH?wxvI-^xdh99C+p&}gmtEv z^^u{2RLYbL(o5U}lPRQakug%r7C%T1RhdOleLSP$7NTnVi0ahf=bR&>j(HNnIe*m8b$zh&<4iRQ>Pxv&3bjotI1c1c> z+^MEg{o!{y)6INPgP|TX+|1M4$d^__IC52D%6}yDHJ-D>2b@oXBr#8i2s3!V`80+M zxZriv5MhFZNTT4Y775Yc4;%$-<$1x9p#F{!kFN&JVnot@9wBOZGgXr_uy9AT&dyrawD#UaSR>T!gcE^x^K^>y+_4`; zxKuaOM#_&)UV%!)G4R6hy(s5(WW%6We7?cordq;(u_o;}qf608;5)v_MsD|2JJ~=5 z`*S)kg8Tq6Ycic*7H8{e7c0B0;$lAwFmNM2Qd$(MVX0l-n;1*W^=X~J&o1ukc>K7X zQ)A4|cR+yIs{2d_OrbPOMBI=^qegiNyDI+Fck2mw^`+yMeyqz7CV1-Kl3Xt%C z7ovnrIU;8PBifBghdM(>oSEcYq7q8Xw{o3m^R=?PP-W;d1o-VI@vW6 z;ht+0j(1qND6cKvyA}q~UI~^=>Wpf$SWF`p;aFi_Ug-~ucFVHbzM4kc6>CP)aXkIJ zZ6Ag)9=L-X7V^pM;?p3}c>CNk4U%rFZAXo^Q5+~29>Gq*ct@>V_1I8EbpeThCJ=w|a_D&N61>T-0|;#GsPF9onf>55AS{~Ft|%Z943P(Egp!7Vd7fS>$QLzL(pd%^HqG`;sZBvy+ z`~Xukl_jSsJ6DcF=q9|nU8>N5aXhaTd2&~ldD~PW^z6aY#{_8LQ zvy=J2xxIYXU1VGj`qn2sj`w&lG~2`6CExKNdkv;geH2NAML#4|{zkul&wQV##BptV zMWqk#N#ql6;Z5Up05fX9t+vJOgm#^omQArbMTIcx6%2?GRRixfNU<^P zR_p+F; z6*e!PW%g|(-#2$}frU5(7UGzat}qL3!fQvseOo}Ton!6%*cOnRr*%AzLvxab_QBjX z0KNx`utEgK_&1%n5Wa(xibR)JYAy<*vl(hZ6f}2G@FizD7$Uj_+8&gBDV}2VOuF>T z9BcHFp9awo`E6x?J1jqqo<8!^h)I^;30%9s+$`jw_53S4`{em*zF92gF|601vSZmo zZL=W(#vd&KW8V_Pw(^3naJ~6!3v! zVs>07K;AF`{6_-=e9%icT`zN;r28wFj+=D1V(T81aof^=0*tTfyJ$#`man-s6nq_+ z*JDCLSRF3gxel<)AnbSn9E`~lK??QVuZpV&V;#;Y6_YAI5N`Eg$EAm644yyzA(#JW7X^TS0Sq>Xva&F_DyH-Lib(^>1Z(K? zG}f7Q)7b31uDixY{{@p|VXqn7TuvAWSg0_Y8H>qtzU)G(?pO$(19k*1MB*7GIF!l+ zu15US3!Fbt?4Tm8VEHpGr&ZApnpYLW4Xg?|a%%8Hv+jdC+t$QC2sY=0iOV0Rd`C-E zo!qW})6oe0rvCT259fiM&ZfkZrUjey7K;1d<~|%1b~+k{HT{o6HNEDI2#=0!upt$o z4L=$*bXQ~>J^>h;f}VtOo2>x~rve3{X585+=tuI)p$2QgSjZK6Hn8_KA7S{&lbqpW zgKHq4=YzzfRz>nYZGpssjqs8^2}<_lVzQur*paMI4mt}63h(?WK$}&rH>=K(65idO z6ZyulC#9TIoizpy2;>iUs*&p&)(Bdi6Gpv!xLOvFKkytrKAULLmmH=8kk*opP;|&5 zls|7}lU;0IM6Or9Kz2G()UbfvyuX9=PuCb`8$kNY0;3;|G71x2!E|3Hi-6LC+FS;5O~^I)th_Y)0D4Q7q&MqZ{W8 z#0LHSu$g-Twgt&RCsbkdKVl#hgO@Df;XnzkCSr0fZAxNWw>D7V*M%YQp@KAjn=p+v zB7Vua43yhjpLTEH$f6BjoO2vb#DwI}T!rK+kgI|EFPFk`s_W7z4Oy z`Fb$xkw9F{fVB3{R`A)8rl0znGwVP%7@99hj>8^u7}>qN1ocMl*ocP)=R@iO&fv?r zeeV-E8Re9L{oU1!Xo&3${Pfs=bT1nNh$Ilu4UV?-tvMMnrzr-JgcJ!2fJVY1In!n* zGA^*^K4LG#294b73UbI(DM_pkrI9!FrPI|^zL`%iFN;}^u0$r-Eh>A8HG(vJsKyGD zOoV2lJ7)_?O>;>LymR4w>85s$Xd|q|05+dIu9=$#;2S(3P$&233>HCu*dows;)x(Y z1ffO1{tF%^=sLpcs;ycXJcf{UPj#f#&%0jK5S)OX^wD6cU#!pXQ4~b+WfJ3ne4!&| zyOi-mX;aov*{H;EQBdycYPFfqU@?@ldR{cm9GIR5_5|%an>Or-Ff3_EnAf91pYAB% z7;ItM+n2;=i4OZngiV2eWIePC@Epa=AGw^8Q&^_Nm0Ys!lW|S{+>v^~5`5%kg?0J! zlYu5RXeuNTqAiP87-THuf-)7%SXhh&F&2vP%dKTs&F3C-(fB#_wR7La+GyIBl+ELB z=)wHs`r%%{9Vo&tdrG7#s;2On7t?vlHAD7ymH+iG`Geg*?f!{>lzO?&U+x2llud-6Cp-c?58jehfpWSh5+#Jq9iNTs#yB+0ojRR(Ra zVXB8NFHQ{TK;iX&LAJNS@Vc*2xEfvsxcFGTFP>e5tRWZAK0xxQpWi`Ac87oimFx}! zsa%0wLpxotxYd@f=r&>D5dX=a7*d~lDq=>$m%2`$OP*>LF5~ep9A@yy&XIN8-{%%%) zrct8LixXI-6p$WD=Aq_mMRK|3IGuk`^Yw$iSYyf$M{ET2NDZ#1aFCNj53rHe#osq2 zpe8o(hk6@-_6~_UTBnJ+P}GG({V-7sEw5ACs@0m2GiVx9GTIbvfsx{20$Y*|db>7h z-1%Z;c<&KCowA+jS+BI`G`-4jU0)Ql(n~C}?Mi8pb#gTv+WhR)33iQ9GdBc8QH0xt zSw`JK0?0t<3erF_P2PTAo-WPcga z2>R-d@-kQ=0Y7mcO{D1(jwP_2E}l-y*N-6TG-&HSRTYqpf%fbDJ%iwWeLtyn`)Tt`B73tQ8U+BJsQDHdgQUd-jWs{osTiQMVqrS91#j%|`w?2zMs ze%!`a>FbP<=@|g>#KT`Fj`O|6TsZVyZK8sI^HCfBtcktYF|Q~#403tlW;kvx$4zpQg*>b>d`KDW6<9$Sy2nZEvjFH>Bq+{1QidW;qxg<3>r@osv3<=o``)mB zNf^ZPzUNY&BxRmTfi}Bm3VC}D|z_OluF(Z9;!B>Ga z*;W23L^boQ_E057`TuUF_{^p1H6$xE!(@}Gy=9%*}zJdr&Z5cOTEsIsNEU*_|o{$quI2~%&c zrgeTby}2pi3hDyVur7-AWs$2iiCX%72N!{E@%n=KT80KNB1D>o5Oun)K^0 z|Amc`&xx#jkm(c+{Rg5-(m+dpAJ7?T1%Y&)ynFyvUONnfF&7Ta%ULxvTYJgy{m3KC zTi`tJ(K}&Ch)ezf8Wf~EGH8JK=W1^-BW1W$Sn|{wC5>|tLc;2k1m#DGVMk}+)hb_X zAVyoh&N-$~N%tf*1oec;$@9!g0678VAZQN{hML?-8rv-F&UaSSw^EzWJ%2U1mC4rC z%2^;}avZSdD-nb(f?yGZ=iFvQumQ=!PJn${k=ek~iHo!iEuFqj>&#jSvs~xa!a0Ok zPN9tRL$bnWCa#WXEBUS(Jd!Uy5E zSLVErXMqEYrFe=lHwn$VGRJ-t+@_L0#VDMF=7&7edkiRR%_RGK!?@d#?WJYu@5uMk zZj0^2M08ergL&8vp>AISCV;I+LDl1foB^Ox_}I`?!7qJ(Qm;4X^+xJCU)jJ?xQ4i+ zpl!~j$)YA_>a+_(poMugQPKuro^|_twKETTi1meDObJ#_6T=H`9ueR&az)WDmbt|k z0Ou9~D(&FdOgtZ&UmlKIJ56Usjf&3}KG%0hqvup#e8QFkayv`+9G&JO5Ca2>bMgR# z=qwHHlrwdI=7ykXx~@G^z|$NJ;Kap*S*U;+#5d~p>kboX^#UKqfjh1zL_`W{6JzNC z?!FiofTvt&s>RcXwfbg{kKdNy9M&RT)R$~H@>1M19F`+!Kpud!(gb~t@UtOdw*+-< zw=#zLN9~a#nI1!j)37Ao;WZr=DGUG-X3~HN8H9v?)oyhNbB@|4wt%c6d~%~w^n_Q( z>IS@*lc^8_e4f+Tb@p)+-|jtWo_$Bs@y@gL?1#q?&sxoF~2itF$6i45L6m)*E}uJOHs~$ zQle^rYzPU<4jDa7m%x&?l1u)&$Q|XquWUp^Xd0(6>cls6r`OGiYn>VjL=AxtRWj*X^iI8EmUzY zGvxvZ{(0qvSrfsaRPFX#%TJxvv5;M}vU5NI)kn!u>Qi9N=| zKq}p5HZj4(-u2*2VlL(iB~YV8tv6PO!#I7C8z?}jA;56v58!~J8L*$kRvjNH+(Qi{ zC3%|`B5z?J1Eo>~laoh@gX(5~^Ttj%KJwai7;2Y+7EEiG?6W(mPR-!zMJi0!1%YU) z20j_4o4>odld9ni0;mNLB@j^bsQ{C#LDji^ z6hKuDEkRV@MP+gCEFD>}1!cAT^_PFvF03Lheef^XXctAA)J(}mLljJF32(uH(mRW% zE1SnNa~$@o%?;=wm6V)xf<;kZt!8*F_x?S2#!u|X-TOQ5-=p;&Mi;z?3<8t0JNZ;w yFnVrPj!(Z5M}RnZY9n!!m%k?r!pRWMBnu)eG2W#%G(cH5Qd71XnEfAt{b?(V-+tQw diff --git a/master/searchindex.js b/master/searchindex.js index 9de1d3563..3b057ca24 100644 --- a/master/searchindex.js +++ b/master/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["cleanlab/benchmarking/index", "cleanlab/benchmarking/noise_generation", "cleanlab/classification", "cleanlab/count", "cleanlab/data_valuation", "cleanlab/datalab/datalab", "cleanlab/datalab/guide/_templates/issue_types_tip", "cleanlab/datalab/guide/custom_issue_manager", "cleanlab/datalab/guide/generating_cluster_ids", "cleanlab/datalab/guide/index", "cleanlab/datalab/guide/issue_type_description", "cleanlab/datalab/guide/table", "cleanlab/datalab/index", "cleanlab/datalab/internal/adapter/imagelab", "cleanlab/datalab/internal/adapter/index", "cleanlab/datalab/internal/data", "cleanlab/datalab/internal/data_issues", "cleanlab/datalab/internal/factory", "cleanlab/datalab/internal/index", "cleanlab/datalab/internal/issue_finder", "cleanlab/datalab/internal/issue_manager/_notices/not_registered", "cleanlab/datalab/internal/issue_manager/data_valuation", "cleanlab/datalab/internal/issue_manager/duplicate", "cleanlab/datalab/internal/issue_manager/imbalance", "cleanlab/datalab/internal/issue_manager/index", "cleanlab/datalab/internal/issue_manager/issue_manager", "cleanlab/datalab/internal/issue_manager/label", "cleanlab/datalab/internal/issue_manager/multilabel/index", "cleanlab/datalab/internal/issue_manager/multilabel/label", "cleanlab/datalab/internal/issue_manager/noniid", "cleanlab/datalab/internal/issue_manager/null", "cleanlab/datalab/internal/issue_manager/outlier", "cleanlab/datalab/internal/issue_manager/regression/index", "cleanlab/datalab/internal/issue_manager/regression/label", "cleanlab/datalab/internal/issue_manager/underperforming_group", "cleanlab/datalab/internal/model_outputs", "cleanlab/datalab/internal/report", "cleanlab/datalab/internal/task", "cleanlab/datalab/optional_dependencies", "cleanlab/dataset", "cleanlab/experimental/cifar_cnn", "cleanlab/experimental/coteaching", "cleanlab/experimental/index", "cleanlab/experimental/label_issues_batched", "cleanlab/experimental/mnist_pytorch", "cleanlab/experimental/span_classification", "cleanlab/filter", "cleanlab/internal/index", "cleanlab/internal/label_quality_utils", "cleanlab/internal/latent_algebra", "cleanlab/internal/multiannotator_utils", "cleanlab/internal/multilabel_scorer", "cleanlab/internal/multilabel_utils", "cleanlab/internal/neighbor/index", "cleanlab/internal/neighbor/knn_graph", "cleanlab/internal/neighbor/metric", "cleanlab/internal/neighbor/search", "cleanlab/internal/outlier", "cleanlab/internal/token_classification_utils", "cleanlab/internal/util", "cleanlab/internal/validation", "cleanlab/models/index", "cleanlab/models/keras", "cleanlab/multiannotator", "cleanlab/multilabel_classification/dataset", "cleanlab/multilabel_classification/filter", "cleanlab/multilabel_classification/index", "cleanlab/multilabel_classification/rank", "cleanlab/object_detection/filter", "cleanlab/object_detection/index", "cleanlab/object_detection/rank", "cleanlab/object_detection/summary", "cleanlab/outlier", "cleanlab/rank", "cleanlab/regression/index", "cleanlab/regression/learn", "cleanlab/regression/rank", "cleanlab/segmentation/filter", "cleanlab/segmentation/index", "cleanlab/segmentation/rank", "cleanlab/segmentation/summary", "cleanlab/token_classification/filter", "cleanlab/token_classification/index", "cleanlab/token_classification/rank", "cleanlab/token_classification/summary", "index", "migrating/migrate_v2", "tutorials/clean_learning/index", "tutorials/clean_learning/tabular", "tutorials/clean_learning/text", "tutorials/datalab/audio", "tutorials/datalab/datalab_advanced", "tutorials/datalab/datalab_quickstart", "tutorials/datalab/image", "tutorials/datalab/index", "tutorials/datalab/tabular", "tutorials/datalab/text", "tutorials/datalab/workflows", "tutorials/dataset_health", "tutorials/faq", "tutorials/improving_ml_performance", "tutorials/indepth_overview", "tutorials/index", "tutorials/multiannotator", "tutorials/multilabel_classification", "tutorials/object_detection", "tutorials/outliers", "tutorials/pred_probs_cross_val", "tutorials/regression", "tutorials/segmentation", "tutorials/token_classification"], "filenames": ["cleanlab/benchmarking/index.rst", "cleanlab/benchmarking/noise_generation.rst", "cleanlab/classification.rst", "cleanlab/count.rst", "cleanlab/data_valuation.rst", "cleanlab/datalab/datalab.rst", "cleanlab/datalab/guide/_templates/issue_types_tip.rst", "cleanlab/datalab/guide/custom_issue_manager.rst", "cleanlab/datalab/guide/generating_cluster_ids.rst", "cleanlab/datalab/guide/index.rst", "cleanlab/datalab/guide/issue_type_description.rst", "cleanlab/datalab/guide/table.rst", "cleanlab/datalab/index.rst", "cleanlab/datalab/internal/adapter/imagelab.rst", "cleanlab/datalab/internal/adapter/index.rst", "cleanlab/datalab/internal/data.rst", "cleanlab/datalab/internal/data_issues.rst", "cleanlab/datalab/internal/factory.rst", "cleanlab/datalab/internal/index.rst", "cleanlab/datalab/internal/issue_finder.rst", "cleanlab/datalab/internal/issue_manager/_notices/not_registered.rst", "cleanlab/datalab/internal/issue_manager/data_valuation.rst", "cleanlab/datalab/internal/issue_manager/duplicate.rst", "cleanlab/datalab/internal/issue_manager/imbalance.rst", "cleanlab/datalab/internal/issue_manager/index.rst", "cleanlab/datalab/internal/issue_manager/issue_manager.rst", "cleanlab/datalab/internal/issue_manager/label.rst", "cleanlab/datalab/internal/issue_manager/multilabel/index.rst", "cleanlab/datalab/internal/issue_manager/multilabel/label.rst", "cleanlab/datalab/internal/issue_manager/noniid.rst", "cleanlab/datalab/internal/issue_manager/null.rst", "cleanlab/datalab/internal/issue_manager/outlier.rst", "cleanlab/datalab/internal/issue_manager/regression/index.rst", "cleanlab/datalab/internal/issue_manager/regression/label.rst", "cleanlab/datalab/internal/issue_manager/underperforming_group.rst", "cleanlab/datalab/internal/model_outputs.rst", "cleanlab/datalab/internal/report.rst", "cleanlab/datalab/internal/task.rst", "cleanlab/datalab/optional_dependencies.rst", "cleanlab/dataset.rst", "cleanlab/experimental/cifar_cnn.rst", "cleanlab/experimental/coteaching.rst", "cleanlab/experimental/index.rst", "cleanlab/experimental/label_issues_batched.rst", "cleanlab/experimental/mnist_pytorch.rst", "cleanlab/experimental/span_classification.rst", "cleanlab/filter.rst", "cleanlab/internal/index.rst", "cleanlab/internal/label_quality_utils.rst", "cleanlab/internal/latent_algebra.rst", "cleanlab/internal/multiannotator_utils.rst", "cleanlab/internal/multilabel_scorer.rst", "cleanlab/internal/multilabel_utils.rst", "cleanlab/internal/neighbor/index.rst", "cleanlab/internal/neighbor/knn_graph.rst", "cleanlab/internal/neighbor/metric.rst", "cleanlab/internal/neighbor/search.rst", "cleanlab/internal/outlier.rst", "cleanlab/internal/token_classification_utils.rst", "cleanlab/internal/util.rst", "cleanlab/internal/validation.rst", "cleanlab/models/index.rst", "cleanlab/models/keras.rst", "cleanlab/multiannotator.rst", "cleanlab/multilabel_classification/dataset.rst", "cleanlab/multilabel_classification/filter.rst", "cleanlab/multilabel_classification/index.rst", "cleanlab/multilabel_classification/rank.rst", "cleanlab/object_detection/filter.rst", "cleanlab/object_detection/index.rst", "cleanlab/object_detection/rank.rst", "cleanlab/object_detection/summary.rst", "cleanlab/outlier.rst", "cleanlab/rank.rst", "cleanlab/regression/index.rst", "cleanlab/regression/learn.rst", "cleanlab/regression/rank.rst", "cleanlab/segmentation/filter.rst", "cleanlab/segmentation/index.rst", "cleanlab/segmentation/rank.rst", "cleanlab/segmentation/summary.rst", "cleanlab/token_classification/filter.rst", "cleanlab/token_classification/index.rst", "cleanlab/token_classification/rank.rst", "cleanlab/token_classification/summary.rst", "index.rst", "migrating/migrate_v2.rst", "tutorials/clean_learning/index.rst", "tutorials/clean_learning/tabular.ipynb", "tutorials/clean_learning/text.ipynb", "tutorials/datalab/audio.ipynb", "tutorials/datalab/datalab_advanced.ipynb", "tutorials/datalab/datalab_quickstart.ipynb", "tutorials/datalab/image.ipynb", "tutorials/datalab/index.rst", "tutorials/datalab/tabular.ipynb", "tutorials/datalab/text.ipynb", "tutorials/datalab/workflows.ipynb", "tutorials/dataset_health.ipynb", "tutorials/faq.ipynb", "tutorials/improving_ml_performance.ipynb", "tutorials/indepth_overview.ipynb", "tutorials/index.rst", "tutorials/multiannotator.ipynb", "tutorials/multilabel_classification.ipynb", "tutorials/object_detection.ipynb", "tutorials/outliers.ipynb", "tutorials/pred_probs_cross_val.rst", "tutorials/regression.ipynb", "tutorials/segmentation.ipynb", "tutorials/token_classification.ipynb"], "titles": ["benchmarking", "noise_generation", "classification", "count", "data_valuation", "datalab", "<no title>", "Creating Your Own Issues Manager", "Generating Cluster IDs", "Datalab guides", "Datalab Issue Types", "<no title>", "datalab", "imagelab", "adapter", "data", "data_issues", "factory", "internal", "issue_finder", "<no title>", "data_valuation", "duplicate", "imbalance", "issue_manager", "issue_manager", "label", "multilabel", "label", "noniid", "null", "outlier", "regression", "label", "underperforming_group", "model_outputs", "report", "task", "<no title>", "dataset", "cifar_cnn", "coteaching", "experimental", "label_issues_batched", "mnist_pytorch", "span_classification", "filter", "internal", "label_quality_utils", "latent_algebra", "multiannotator_utils", "multilabel_scorer", "multilabel_utils", "neighbor", "knn_graph", "metric", "search", "outlier", "token_classification_utils", "util", "validation", "models", "keras", "multiannotator", "dataset", "filter", "multilabel_classification", "rank", "filter", "object_detection", "rank", "summary", "outlier", "rank", "regression", "regression.learn", "regression.rank", "filter", "segmentation", "rank", "summary", "filter", "token_classification", "rank", "summary", "cleanlab open-source documentation", "How to migrate to versions >= 2.0.0 from pre 1.0.1", "CleanLearning Tutorials", "Classification with Structured/Tabular Data and Noisy Labels", "Text Classification with Noisy Labels", "Detecting Issues in an Audio Dataset with Datalab", "Datalab: Advanced workflows to audit your data", "Datalab: A unified audit to detect all kinds of issues in data and labels", "Detecting Issues in an Image Dataset with Datalab", "Datalab Tutorials", "Detecting Issues in Tabular Data\u00a0(Numeric/Categorical columns) with Datalab", "Detecting Issues in a Text Dataset with Datalab", "Miscellaneous workflows with Datalab", "Understanding Dataset-level Labeling Issues", "FAQ", "Improving ML Performance via Data Curation with Train vs Test Splits", "The Workflows of Data-centric AI for Classification with Noisy Labels", "Tutorials", "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators", "Find Label Errors in Multi-Label Classification Datasets", "Finding Label Errors in Object Detection Datasets", "Detect Outliers with Cleanlab and PyTorch Image Models (timm)", "Computing Out-of-Sample Predicted Probabilities with Cross-Validation", "Find Noisy Labels in Regression Datasets", "Find Label Errors in Semantic Segmentation Datasets", "Find Label Errors in Token Classification (Text) Datasets"], "terms": {"noise_gener": [0, 86, 91, 92, 101, 103, 104], "noise_matrix_is_valid": [0, 1], "generate_noisy_label": [0, 1, 91, 92, 101, 103, 104], "generate_noise_matrix_from_trac": [0, 1, 91, 92, 101, 103, 104], "generate_n_rand_probabilities_that_sum_to_m": [0, 1], "randomly_distribute_n_balls_into_k_bin": [0, 1], "helper": [1, 19, 43, 48, 50, 51, 52, 53, 57, 58, 59, 70, 93, 97, 98, 110], "method": [1, 2, 3, 4, 5, 7, 10, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "ar": [1, 2, 3, 4, 5, 7, 10, 13, 14, 15, 16, 17, 18, 19, 21, 23, 24, 25, 26, 27, 29, 32, 33, 35, 37, 39, 40, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 110], "us": [1, 2, 3, 4, 5, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 85, 86, 91, 98, 107], "benchmark": [1, 40, 85, 86, 91, 92, 101, 103, 104], "cleanlab": [1, 2, 3, 4, 5, 7, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 86, 91, 92, 97, 98, 100, 102, 107], "": [1, 2, 3, 4, 10, 21, 35, 39, 40, 44, 48, 51, 54, 56, 57, 59, 63, 64, 68, 70, 71, 72, 73, 75, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "core": [1, 43, 46, 77, 79], "algorithm": [1, 2, 8, 10, 34, 41, 45, 56, 57, 59, 63, 72, 81, 83, 85, 88, 89, 92, 95, 96, 97, 98, 99, 101, 103, 104, 106, 108, 110], "These": [1, 2, 3, 4, 5, 8, 10, 24, 40, 42, 44, 45, 46, 47, 54, 61, 63, 64, 67, 71, 72, 76, 80, 81, 83, 84, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "introduc": [1, 10, 90, 97, 99, 100, 101], "synthet": [1, 103, 104, 109], "nois": [1, 2, 3, 39, 46, 49, 59, 64, 91, 92, 97, 98, 103, 108], "label": [1, 2, 3, 4, 5, 7, 8, 9, 11, 13, 15, 17, 18, 19, 23, 24, 25, 27, 32, 34, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 59, 60, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 91, 97, 100, 102, 106, 107], "classif": [1, 3, 4, 5, 7, 10, 11, 13, 15, 17, 19, 35, 37, 39, 43, 45, 46, 49, 51, 52, 59, 63, 64, 65, 66, 67, 72, 73, 81, 82, 83, 84, 85, 86, 87, 90, 91, 92, 97, 100, 102, 103, 106, 107, 108, 109], "dataset": [1, 2, 3, 4, 5, 7, 9, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 28, 29, 30, 31, 33, 34, 42, 43, 44, 45, 46, 49, 51, 55, 59, 62, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 88, 91, 95, 100, 102, 103, 107], "specif": [1, 3, 5, 9, 13, 17, 18, 19, 30, 36, 37, 42, 54, 55, 56, 61, 65, 68, 71, 80, 84, 93, 95, 96, 97, 100, 101, 105, 110], "thi": [1, 2, 3, 4, 5, 6, 7, 9, 10, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 103, 104, 105, 106, 107, 108, 109, 110], "modul": [1, 3, 13, 14, 16, 17, 18, 19, 24, 27, 32, 35, 36, 37, 39, 40, 41, 42, 43, 44, 46, 51, 53, 54, 56, 57, 59, 61, 63, 68, 71, 72, 73, 85, 93, 99, 104], "provid": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 13, 17, 19, 21, 26, 33, 37, 39, 40, 41, 43, 44, 46, 49, 53, 54, 56, 57, 59, 62, 63, 64, 65, 70, 71, 72, 73, 75, 77, 79, 80, 83, 84, 85, 88, 89, 90, 91, 92, 93, 96, 97, 99, 100, 101, 103, 106, 107, 108, 109, 110], "gener": [1, 2, 3, 7, 10, 21, 26, 28, 36, 39, 51, 54, 56, 59, 60, 72, 73, 75, 80, 89, 90, 91, 92, 93, 96, 98, 99, 100, 101, 103, 104, 106, 107, 109, 110], "valid": [1, 2, 3, 5, 10, 15, 35, 37, 39, 46, 47, 49, 50, 51, 54, 56, 57, 59, 63, 65, 68, 71, 73, 75, 76, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 108, 109, 110], "matric": [1, 3, 49, 99], "which": [1, 2, 3, 5, 7, 10, 13, 15, 16, 17, 19, 21, 25, 29, 35, 36, 37, 39, 40, 44, 45, 46, 49, 51, 55, 56, 58, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 76, 79, 80, 81, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 110], "learn": [1, 2, 3, 4, 5, 9, 10, 17, 19, 25, 33, 36, 41, 42, 43, 44, 46, 48, 50, 55, 56, 59, 61, 63, 65, 72, 74, 76, 79, 83, 85, 88, 89, 90, 91, 93, 95, 96, 97, 98, 100, 103, 104, 108], "i": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 103, 104, 105, 106, 108, 109, 110], "possibl": [1, 2, 3, 7, 10, 39, 40, 44, 46, 48, 49, 51, 65, 66, 67, 68, 70, 71, 72, 73, 75, 81, 83, 84, 92, 97, 99, 100, 101, 103, 104, 105, 108, 109, 110], "noisi": [1, 2, 3, 10, 34, 39, 41, 44, 46, 49, 59, 64, 65, 67, 73, 75, 76, 77, 79, 80, 86, 91, 92, 95, 96, 97, 99, 102, 103], "given": [1, 2, 3, 5, 10, 17, 33, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 58, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 76, 80, 81, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "matrix": [1, 2, 3, 5, 10, 13, 19, 21, 34, 39, 46, 48, 49, 52, 54, 59, 60, 65, 68, 70, 71, 72, 73, 95, 97, 105, 106], "trace": [1, 91, 92, 101, 103, 104], "valu": [1, 2, 3, 4, 5, 10, 13, 15, 16, 19, 21, 25, 29, 30, 35, 37, 39, 40, 41, 43, 44, 46, 48, 49, 51, 54, 55, 56, 57, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 84, 89, 90, 92, 93, 95, 96, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "more": [1, 2, 3, 4, 5, 7, 9, 10, 13, 16, 17, 19, 21, 29, 39, 40, 43, 44, 45, 48, 51, 54, 55, 56, 57, 59, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 79, 80, 81, 83, 85, 90, 91, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 109, 110], "function": [1, 2, 3, 4, 5, 7, 10, 13, 16, 17, 19, 26, 29, 33, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 92, 97, 98, 99, 100, 101, 103, 104, 105, 109, 110], "noise_matrix": [1, 2, 3, 10, 49, 59, 91, 92, 101, 103, 104], "py": [1, 3, 36, 40, 41, 46, 49, 51, 91, 92, 101, 103, 104], "verbos": [1, 2, 5, 7, 13, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 43, 46, 63, 64, 65, 70, 72, 73, 75, 77, 79, 80, 84, 91, 97, 101, 103], "fals": [1, 2, 3, 5, 7, 10, 13, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 50, 58, 59, 60, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 81, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 105, 106, 108, 109], "sourc": [1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "prior": [1, 2, 3, 39, 46, 49, 51], "repres": [1, 2, 3, 7, 10, 13, 15, 19, 21, 29, 35, 37, 39, 43, 46, 49, 52, 54, 55, 57, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 110], "p": [1, 2, 3, 5, 10, 39, 46, 48, 49, 57, 59, 63, 71, 72, 73, 77, 95, 96, 97, 100, 101, 103, 110], "true_label": [1, 2, 3, 39, 49, 59, 101, 103], "k": [1, 2, 3, 4, 5, 8, 10, 13, 15, 19, 21, 22, 26, 29, 31, 34, 39, 43, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 63, 64, 65, 66, 67, 68, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 88, 90, 91, 92, 97, 99, 100, 101, 103, 104, 105, 106, 109, 110], "check": [1, 2, 5, 6, 9, 10, 13, 15, 19, 30, 37, 40, 43, 44, 50, 60, 62, 68, 71, 75, 88, 89, 90, 91, 92, 93, 99, 101, 103, 104, 108], "learnabl": 1, "mean": [1, 2, 7, 8, 10, 13, 15, 16, 25, 29, 41, 44, 49, 51, 57, 70, 75, 89, 92, 96, 97, 99, 101, 103, 104, 105, 106, 108], "achiev": [1, 2, 40, 41, 44, 75, 99, 100, 103, 110], "better": [1, 5, 10, 46, 55, 63, 65, 73, 75, 76, 85, 89, 90, 92, 95, 96, 97, 99, 101, 104, 105, 106, 107, 110], "than": [1, 2, 3, 4, 7, 9, 10, 29, 31, 34, 39, 46, 55, 59, 62, 63, 68, 70, 72, 73, 75, 79, 83, 88, 90, 93, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "random": [1, 2, 3, 7, 10, 21, 34, 43, 51, 54, 63, 73, 75, 88, 90, 91, 92, 93, 95, 97, 99, 100, 101, 103, 104, 106], "perform": [1, 2, 4, 7, 10, 29, 31, 34, 40, 44, 51, 53, 54, 55, 71, 75, 85, 88, 89, 91, 99, 101, 102, 103, 104, 107, 108], "averag": [1, 3, 5, 10, 25, 31, 39, 40, 44, 51, 57, 63, 64, 71, 72, 73, 99, 103, 106], "amount": [1, 3, 93], "paramet": [1, 2, 3, 4, 5, 9, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 92, 93, 96, 97, 100], "np": [1, 2, 3, 4, 5, 7, 13, 19, 21, 34, 39, 41, 43, 45, 46, 48, 49, 51, 52, 54, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "ndarrai": [1, 2, 3, 4, 5, 13, 19, 26, 28, 29, 33, 34, 35, 39, 41, 43, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 83, 97, 110], "an": [1, 2, 3, 4, 5, 7, 9, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 54, 56, 57, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84, 85, 88, 89, 91, 92, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "arrai": [1, 2, 3, 4, 5, 7, 10, 13, 15, 19, 21, 29, 35, 39, 41, 43, 44, 45, 46, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 91, 92, 96, 97, 99, 101, 103, 104, 105, 106, 108, 109, 110], "shape": [1, 2, 3, 4, 5, 13, 19, 21, 39, 41, 43, 45, 46, 48, 49, 50, 51, 54, 55, 57, 58, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 90, 97, 98, 99, 101, 104, 105, 106, 109, 110], "condit": [1, 2, 3, 10, 49, 55, 58, 59, 73, 93, 101, 110], "probabl": [1, 2, 3, 5, 8, 10, 13, 19, 26, 28, 31, 34, 35, 39, 43, 44, 45, 46, 48, 49, 51, 52, 58, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 85, 86, 98, 99, 101, 102, 104, 105, 106, 109, 110], "k_": [1, 2, 3, 49, 59], "k_y": [1, 2, 3, 49, 59], "contain": [1, 2, 3, 5, 10, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 46, 48, 49, 53, 54, 58, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 79, 80, 81, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109], "fraction": [1, 2, 3, 10, 23, 41, 49, 59, 63, 75, 95, 99, 100], "exampl": [1, 2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 51, 52, 54, 57, 58, 59, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 100, 103, 104, 105, 107, 108, 109, 110], "everi": [1, 2, 3, 4, 5, 10, 13, 19, 40, 44, 46, 49, 58, 59, 65, 73, 75, 76, 88, 90, 91, 92, 93, 95, 96, 99, 103, 105, 107, 109, 110], "class": [1, 2, 3, 4, 5, 7, 9, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 56, 58, 59, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 103, 104, 105, 106, 107, 108, 110], "other": [1, 2, 3, 5, 10, 13, 19, 25, 30, 39, 40, 42, 43, 44, 46, 49, 52, 54, 59, 60, 61, 63, 64, 67, 71, 72, 73, 75, 80, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 106, 109, 110], "assum": [1, 2, 3, 15, 46, 49, 54, 58, 59, 73, 77, 80, 97, 99, 100, 104, 106, 108, 109, 110], "column": [1, 2, 3, 5, 10, 11, 13, 15, 16, 33, 39, 43, 46, 49, 51, 52, 55, 58, 59, 63, 64, 65, 67, 68, 71, 72, 73, 75, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 108, 109, 110], "sum": [1, 2, 3, 29, 34, 35, 39, 49, 51, 59, 64, 65, 67, 70, 75, 91, 92, 93, 99, 101, 103, 104, 109, 110], "1": [1, 2, 3, 4, 5, 7, 10, 11, 13, 15, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 57, 58, 59, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 98, 99, 107], "each": [1, 2, 3, 4, 5, 7, 8, 9, 13, 15, 16, 17, 19, 23, 25, 26, 28, 29, 34, 35, 36, 39, 40, 41, 43, 44, 45, 46, 48, 49, 51, 52, 54, 56, 57, 59, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "true": [1, 2, 3, 5, 7, 10, 13, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 46, 49, 51, 54, 58, 59, 60, 62, 63, 64, 65, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 108, 109, 110], "return": [1, 2, 3, 4, 5, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 89, 90, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "type": [1, 2, 3, 4, 5, 6, 7, 12, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 42, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 99, 100, 104, 105, 108, 109, 110], "bool": [1, 2, 3, 5, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 51, 54, 58, 59, 63, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84], "is_valid": 1, "whether": [1, 3, 5, 10, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 40, 43, 44, 46, 54, 59, 63, 64, 65, 67, 68, 84, 89, 90, 92, 93, 95, 96, 97, 98, 99, 100, 101, 108, 110], "from": [1, 2, 3, 4, 5, 7, 8, 9, 10, 12, 13, 15, 16, 17, 19, 21, 25, 26, 30, 33, 34, 35, 36, 38, 39, 40, 41, 43, 44, 45, 46, 49, 51, 52, 54, 55, 57, 58, 59, 63, 65, 67, 70, 71, 72, 73, 75, 76, 81, 83, 84, 85, 90, 93, 95, 96, 97, 98, 99, 103, 104, 105, 106, 107, 109, 110], "perfect": [1, 2, 39, 75, 101, 105], "exactli": [1, 3, 10, 39, 40, 44, 46, 66, 72, 91, 92, 93, 95, 96, 100, 101], "yield": [1, 40, 44, 100], "between": [1, 5, 9, 13, 14, 18, 19, 24, 25, 27, 29, 32, 35, 39, 40, 41, 42, 43, 44, 46, 47, 48, 50, 54, 55, 56, 57, 61, 63, 64, 67, 70, 72, 73, 75, 76, 79, 83, 84, 86, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "below": [1, 3, 4, 5, 10, 39, 40, 43, 44, 46, 48, 51, 57, 63, 64, 65, 70, 71, 79, 83, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "we": [1, 2, 3, 5, 7, 10, 13, 16, 25, 40, 43, 44, 46, 51, 59, 60, 62, 63, 70, 71, 73, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "loop": [1, 3, 49, 59, 93, 105], "implement": [1, 2, 3, 4, 9, 17, 25, 40, 41, 43, 44, 49, 53, 55, 56, 59, 72, 75, 85, 88, 90, 91, 95, 100, 106, 107], "what": [1, 5, 9, 10, 13, 19, 36, 39, 41, 43, 46, 63, 64, 68, 70, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 103, 104, 105, 106, 108, 109, 110], "doe": [1, 2, 3, 7, 10, 43, 44, 46, 51, 54, 57, 60, 70, 71, 75, 77, 79, 83, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 104, 108, 109], "do": [1, 2, 5, 9, 10, 39, 43, 44, 59, 60, 72, 73, 77, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 103, 104, 105, 106, 108, 109, 110], "fast": 1, "explain": [1, 10, 97], "python": [1, 2, 44, 62, 75, 91, 92, 98, 106], "pseudocod": [1, 107], "happen": [1, 10, 46, 65, 96, 103, 109], "n": [1, 2, 3, 5, 7, 39, 40, 43, 44, 46, 48, 49, 50, 51, 54, 55, 57, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 83, 88, 89, 90, 93, 96, 97, 98, 99, 103, 104, 105, 108, 109, 110], "without": [1, 2, 5, 9, 10, 15, 17, 23, 40, 44, 56, 67, 75, 85, 89, 90, 96, 97, 99, 100, 101, 105, 106], "ani": [1, 2, 3, 5, 7, 9, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 43, 44, 46, 48, 50, 57, 58, 59, 62, 63, 65, 67, 68, 70, 71, 73, 75, 77, 79, 80, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 107, 108, 109], "distinct": [1, 10, 21, 59, 110], "natur": [1, 10, 103, 106], "number": [1, 2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 46, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 83, 84, 86, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 109, 110], "0": [1, 2, 3, 4, 5, 7, 10, 15, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 57, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "count_joint": 1, "len": [1, 2, 3, 7, 39, 43, 49, 58, 59, 60, 72, 73, 75, 88, 89, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 110], "y": [1, 2, 3, 5, 8, 21, 33, 34, 44, 49, 51, 59, 60, 62, 71, 75, 76, 89, 90, 91, 92, 95, 97, 99, 101, 103, 104, 106, 108], "round": [1, 43, 46, 59, 75, 97, 99, 100, 108], "astyp": [1, 100, 103], "int": [1, 2, 3, 4, 5, 7, 13, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 40, 41, 43, 44, 46, 51, 52, 54, 55, 56, 57, 58, 59, 60, 64, 65, 67, 71, 72, 73, 75, 77, 79, 80, 81, 84, 90, 91, 93, 97, 100, 105, 106], "rang": [1, 3, 5, 7, 15, 49, 51, 57, 59, 71, 75, 76, 93, 97, 98, 99, 101, 103, 104, 105, 106, 108, 109, 110], "idx_flip": 1, "where": [1, 2, 3, 5, 7, 10, 13, 15, 16, 19, 25, 39, 43, 46, 49, 50, 51, 52, 54, 55, 57, 58, 59, 60, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 89, 90, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "pragma": 1, "cover": [1, 3, 86, 97, 98, 99], "choic": [1, 8, 46, 55, 57, 93, 99, 104, 106], "replac": [1, 58, 62, 73, 88, 89, 91, 92, 93, 96, 97, 98, 99, 103, 106], "max_trace_prob": 1, "min_trace_prob": 1, "1e": [1, 3, 54, 73, 90, 91, 92], "05": [1, 10, 29, 33, 58, 71, 75, 81, 83, 95, 97, 98, 99, 100, 101, 105, 110], "max_noise_r": 1, "99999": 1, "min_noise_r": 1, "valid_noise_matrix": [1, 91, 92, 101, 103, 104], "none": [1, 2, 3, 4, 5, 7, 10, 11, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 56, 57, 58, 59, 60, 62, 63, 64, 65, 66, 67, 70, 71, 72, 73, 75, 77, 79, 80, 83, 84, 91, 92, 93, 97, 99, 100, 101, 103, 104, 109], "frac_zero_noise_r": 1, "seed": [1, 2, 3, 10, 29, 42, 44, 51, 75, 88, 90, 91, 92, 95, 97, 98, 100, 101, 103, 104], "max_it": [1, 89, 90, 96, 106], "10000": [1, 43, 98, 99], "x": [1, 2, 3, 5, 10, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 40, 41, 44, 46, 48, 49, 51, 54, 56, 58, 59, 60, 62, 63, 65, 71, 72, 73, 75, 77, 88, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 106, 108], "diagon": [1, 3, 5, 46, 49, 59], "equal": [1, 3, 10, 15, 54, 65, 70, 80, 107], "creat": [1, 2, 9, 13, 19, 21, 40, 43, 44, 46, 59, 75, 85, 89, 90, 93, 95, 96, 97, 99, 100, 109, 110], "impli": [1, 10, 39, 64, 71], "float": [1, 2, 10, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 41, 42, 43, 44, 46, 48, 50, 51, 57, 58, 59, 63, 64, 65, 67, 70, 71, 75, 79, 83, 90, 91, 92, 100, 101, 103, 104], "entri": [1, 3, 5, 10, 39, 40, 44, 46, 48, 52, 54, 57, 59, 63, 64, 65, 68, 88, 89, 95, 96, 101, 104, 105, 108], "maximum": [1, 10, 13, 72, 80, 84, 97, 109], "minimum": [1, 8, 10, 13, 23, 46, 48, 65, 70, 83, 97], "noise_r": 1, "non": [1, 2, 3, 5, 7, 9, 13, 19, 29, 40, 44, 46, 54, 70, 75, 91, 99, 100, 101, 103, 105, 106], "default": [1, 2, 3, 4, 5, 7, 10, 11, 13, 17, 19, 31, 33, 36, 39, 40, 41, 43, 44, 46, 48, 49, 51, 53, 54, 55, 56, 57, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 91, 93, 97, 99, 108, 109], "If": [1, 2, 3, 4, 5, 10, 13, 15, 16, 19, 29, 31, 37, 39, 40, 43, 44, 46, 48, 49, 51, 54, 55, 58, 59, 62, 63, 64, 65, 68, 70, 71, 72, 75, 76, 77, 79, 80, 83, 84, 85, 86, 88, 89, 90, 91, 93, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "have": [1, 2, 3, 4, 5, 7, 9, 10, 13, 19, 24, 27, 29, 32, 39, 40, 42, 43, 44, 46, 49, 51, 54, 59, 62, 63, 64, 65, 68, 70, 71, 72, 73, 75, 76, 80, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "all": [1, 2, 3, 5, 7, 8, 9, 10, 13, 16, 17, 19, 25, 36, 39, 40, 43, 44, 45, 46, 49, 51, 52, 54, 58, 59, 62, 63, 64, 65, 66, 67, 70, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 86, 88, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "necessari": [1, 2, 3, 4, 7, 10, 15, 58, 91, 97], "In": [1, 2, 3, 5, 10, 39, 40, 43, 44, 54, 62, 63, 64, 66, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 106, 107, 108, 109, 110], "particular": [1, 5, 6, 10, 13, 16, 17, 19, 22, 23, 25, 29, 30, 31, 34, 40, 44, 59, 63, 67, 71, 75, 80, 84, 85, 88, 89, 90, 92, 96, 99, 103, 104, 106, 108], "satisfi": [1, 3, 39], "requir": [1, 2, 5, 7, 8, 9, 10, 11, 12, 15, 33, 38, 40, 41, 42, 43, 44, 46, 49, 54, 56, 59, 61, 62, 65, 72, 73, 75, 77, 85, 86, 90, 97, 98, 99, 100, 101, 107], "argument": [1, 2, 3, 5, 10, 11, 13, 19, 26, 30, 33, 34, 35, 40, 43, 44, 45, 46, 51, 54, 56, 60, 62, 63, 64, 65, 67, 70, 71, 72, 73, 75, 79, 80, 81, 83, 89, 92, 93, 96, 97, 98, 99, 104, 105, 108, 110], "when": [1, 2, 3, 4, 5, 10, 15, 17, 26, 29, 40, 44, 46, 49, 51, 54, 56, 57, 59, 62, 65, 67, 68, 70, 72, 73, 75, 76, 88, 89, 91, 92, 93, 95, 96, 97, 98, 100, 103, 107, 108, 109, 110], "The": [1, 2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 59, 62, 63, 64, 65, 68, 70, 71, 72, 73, 75, 77, 80, 81, 83, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 102, 103, 104, 105, 106, 107, 108, 109, 110], "rate": [1, 2, 3, 10, 41, 59, 90, 110], "set": [1, 2, 3, 5, 9, 10, 13, 15, 16, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 40, 43, 44, 46, 50, 51, 53, 54, 55, 57, 59, 62, 63, 65, 68, 70, 71, 72, 73, 75, 77, 79, 80, 88, 89, 91, 92, 95, 96, 97, 99, 100, 103, 104, 106, 107, 108, 109, 110], "note": [1, 2, 3, 7, 8, 10, 11, 15, 30, 34, 37, 40, 43, 44, 45, 46, 51, 54, 59, 62, 63, 68, 70, 71, 72, 73, 75, 76, 80, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "you": [1, 2, 3, 5, 7, 9, 10, 13, 17, 19, 39, 40, 42, 43, 44, 46, 51, 56, 61, 62, 63, 65, 68, 70, 71, 72, 73, 75, 76, 77, 80, 81, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 103, 104, 105, 106, 107, 108, 109, 110], "high": [1, 2, 10, 19, 43, 46, 54, 55, 59, 70, 73, 75, 88, 89, 91, 92, 93, 97, 98, 100, 101, 105, 108, 109, 110], "mai": [1, 2, 3, 4, 5, 10, 13, 16, 24, 25, 27, 32, 35, 39, 40, 42, 43, 44, 46, 49, 51, 54, 59, 63, 64, 68, 70, 71, 72, 73, 75, 77, 80, 84, 86, 89, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "imposs": [1, 10, 101], "also": [1, 2, 3, 5, 7, 9, 10, 25, 37, 39, 40, 43, 44, 46, 51, 58, 62, 63, 72, 75, 80, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "low": [1, 10, 13, 59, 63, 85, 91, 92, 96, 97, 101, 105, 109], "zero": [1, 3, 5, 40, 44, 48, 54, 59, 60, 91, 93, 104, 105, 106], "forc": [1, 2, 3, 5, 44, 91, 110], "instead": [1, 2, 3, 10, 13, 16, 19, 36, 39, 40, 43, 44, 46, 49, 59, 62, 63, 65, 67, 71, 72, 73, 75, 76, 79, 81, 83, 86, 88, 89, 90, 93, 95, 97, 99, 100, 101, 104, 105, 106, 108, 109, 110], "onli": [1, 2, 3, 4, 5, 7, 10, 11, 13, 19, 26, 29, 33, 39, 40, 43, 44, 45, 46, 48, 49, 54, 55, 57, 58, 59, 60, 62, 63, 72, 73, 75, 77, 79, 83, 84, 85, 89, 90, 91, 92, 93, 96, 97, 100, 103, 104, 105, 106, 107, 108, 109, 110], "guarante": [1, 3, 5, 14, 18, 24, 27, 32, 40, 42, 44, 47, 49, 61, 86], "produc": [1, 2, 5, 9, 10, 13, 19, 51, 63, 73, 75, 77, 79, 85, 88, 89, 90, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 109, 110], "higher": [1, 5, 10, 39, 46, 48, 49, 51, 57, 62, 63, 64, 75, 92, 96, 97, 99, 105], "opposit": [1, 110], "occur": [1, 3, 10, 39, 58, 70, 91, 92, 93, 99, 100, 106], "small": [1, 3, 10, 39, 43, 51, 54, 57, 59, 64, 71, 89, 93, 96, 98, 100, 104, 106], "numpi": [1, 3, 4, 5, 7, 10, 15, 21, 34, 35, 43, 44, 45, 51, 54, 57, 58, 60, 62, 67, 70, 75, 76, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "max": [1, 46, 72, 73, 92, 93, 97, 100, 106], "tri": [1, 40, 44, 107], "befor": [1, 2, 3, 40, 44, 57, 59, 72, 75, 80, 88, 89, 96, 97, 99, 100, 101, 103, 106, 108], "option": [1, 2, 3, 4, 5, 7, 8, 9, 13, 15, 16, 19, 26, 31, 33, 39, 40, 43, 44, 46, 49, 51, 54, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 83, 84, 85, 88, 90, 91, 92, 93, 95, 99, 101, 104, 108, 109], "left": [1, 2, 46, 48, 57, 59, 65, 68, 71, 91, 92, 104, 105, 106, 109], "stochast": 1, "exceed": 1, "m": [1, 5, 40, 44, 50, 51, 54, 55, 63, 68, 70, 71, 72, 91, 92, 98, 103, 104, 105, 110], "max_prob": 1, "min_prob": 1, "dirichlet": 1, "ones": [1, 40, 44, 62, 99, 101, 109], "length": [1, 5, 15, 29, 30, 39, 41, 46, 59, 65, 68, 72, 73, 75, 77, 80, 84, 88, 90, 97, 100, 104, 106, 109, 110], "must": [1, 2, 3, 4, 5, 7, 13, 19, 39, 40, 41, 42, 44, 46, 49, 51, 52, 57, 59, 61, 62, 63, 64, 65, 72, 73, 75, 77, 79, 80, 81, 83, 84, 90, 97, 100, 103, 107, 109, 110], "max_balls_per_bin": 1, "min_balls_per_bin": 1, "uniformli": 1, "integ": [1, 2, 3, 10, 15, 39, 43, 46, 52, 59, 60, 63, 65, 71, 77, 79, 80, 81, 83, 84, 88, 89, 90, 99, 100, 103, 104, 105, 109, 110], "ball": [1, 98], "bin": [1, 3, 65, 91, 92, 106], "ensur": [1, 2, 10, 40, 44, 54, 56, 57, 59, 60, 62, 70, 73, 75, 88, 89, 90, 91, 92, 93, 96, 97, 99, 100, 101, 106, 107, 108], "most": [1, 3, 5, 7, 10, 13, 19, 39, 43, 46, 51, 62, 63, 64, 65, 68, 70, 71, 72, 73, 76, 79, 83, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109], "least": [1, 4, 10, 21, 34, 39, 43, 63, 64, 70, 73, 83, 93, 99, 100, 103, 106, 109], "int_arrai": [1, 59], "can": [2, 3, 4, 5, 7, 8, 9, 13, 16, 17, 19, 36, 37, 39, 40, 41, 42, 43, 44, 46, 50, 51, 52, 54, 55, 56, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 80, 81, 84, 85, 86, 88, 89, 90, 91, 93, 95, 96, 97, 100, 104, 105, 106, 107, 108, 109, 110], "model": [2, 3, 4, 5, 9, 10, 11, 13, 19, 21, 33, 35, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 50, 56, 58, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 86, 91, 92, 97, 98, 102, 107, 109, 110], "For": [2, 3, 5, 7, 9, 10, 12, 13, 19, 25, 38, 39, 40, 43, 44, 46, 49, 51, 54, 57, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 81, 83, 84, 85, 88, 89, 90, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 109, 110], "regular": [2, 3, 43, 62], "multi": [2, 3, 4, 10, 35, 39, 40, 43, 44, 46, 50, 51, 52, 59, 60, 64, 65, 66, 67, 72, 73, 85, 97, 99, 100, 101, 102], "task": [2, 5, 7, 10, 11, 12, 13, 15, 17, 18, 19, 28, 33, 36, 39, 43, 49, 51, 52, 57, 59, 63, 65, 73, 75, 85, 89, 90, 96, 97, 98, 99, 100, 101, 104, 106, 108, 109, 110], "cleanlearn": [2, 3, 10, 26, 33, 40, 59, 62, 74, 75, 76, 85, 86, 88, 89, 100, 108], "wrap": [2, 40, 44, 53, 62, 72, 75, 85, 88, 89, 91, 92, 95, 96, 101, 108], "instanc": [2, 3, 5, 6, 7, 10, 13, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 44, 51, 62, 71, 72, 75, 80, 88, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 105], "sklearn": [2, 3, 4, 5, 8, 10, 21, 34, 39, 44, 51, 55, 56, 59, 62, 72, 75, 76, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 106, 107, 108], "classifi": [2, 3, 44, 51, 59, 63, 66, 72, 73, 85, 86, 88, 89, 90, 95, 96, 99, 103, 104, 106, 107, 109, 110], "adher": [2, 44, 75], "estim": [2, 3, 4, 5, 9, 13, 16, 25, 39, 43, 44, 46, 49, 59, 63, 64, 65, 70, 72, 75, 77, 79, 83, 85, 86, 90, 91, 92, 93, 95, 96, 97, 99, 100, 102, 105, 106, 107, 108, 109, 110], "api": [2, 3, 17, 62, 68, 71, 72, 75, 86, 97, 99, 108], "defin": [2, 3, 5, 7, 10, 17, 25, 39, 40, 41, 43, 44, 46, 73, 75, 77, 85, 91, 92, 95, 98, 99, 100, 103, 106, 110], "four": [2, 10, 98, 101, 110], "clf": [2, 3, 5, 51, 75, 85, 88, 95, 97, 99, 100, 101, 104], "fit": [2, 3, 5, 8, 10, 21, 42, 44, 54, 56, 61, 62, 72, 74, 75, 85, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 106, 107, 108, 110], "sample_weight": [2, 44, 75, 101], "predict_proba": [2, 5, 39, 42, 44, 51, 61, 62, 88, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 106], "predict": [2, 3, 4, 5, 8, 9, 10, 11, 13, 19, 25, 26, 28, 31, 33, 34, 35, 37, 39, 42, 43, 44, 45, 46, 48, 49, 51, 52, 58, 59, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 89, 98, 99, 101, 102, 106, 108, 109, 110], "score": [2, 3, 4, 5, 7, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 43, 45, 46, 48, 51, 57, 63, 64, 65, 67, 68, 70, 71, 72, 73, 74, 75, 76, 79, 81, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 106, 108], "data": [2, 3, 4, 5, 7, 8, 9, 12, 13, 16, 17, 18, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 39, 41, 42, 43, 44, 45, 46, 51, 52, 54, 55, 56, 59, 61, 62, 63, 64, 65, 66, 70, 72, 73, 74, 75, 80, 81, 82, 83, 84, 86, 93, 94, 102], "e": [2, 3, 5, 10, 15, 25, 35, 39, 40, 43, 44, 46, 49, 51, 52, 54, 59, 60, 63, 64, 65, 66, 68, 71, 72, 73, 75, 77, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108], "featur": [2, 3, 4, 5, 8, 10, 11, 13, 19, 21, 22, 26, 29, 30, 31, 33, 34, 51, 54, 55, 56, 59, 72, 75, 85, 88, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 108], "element": [2, 3, 5, 39, 45, 46, 48, 59, 63, 65, 73, 80, 81, 83, 89, 90, 96, 97, 99, 110], "first": [2, 5, 10, 20, 29, 30, 39, 43, 51, 54, 59, 63, 64, 68, 71, 73, 75, 85, 88, 89, 90, 91, 93, 95, 97, 99, 100, 103, 104, 105, 106, 108, 109, 110], "index": [2, 10, 29, 39, 46, 53, 54, 56, 58, 59, 60, 64, 73, 75, 80, 83, 84, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "should": [2, 3, 5, 7, 10, 17, 25, 29, 34, 35, 39, 40, 43, 44, 46, 48, 49, 51, 54, 56, 57, 58, 59, 62, 63, 64, 67, 68, 70, 71, 72, 73, 75, 76, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "correspond": [2, 3, 5, 10, 13, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 37, 39, 40, 43, 44, 45, 46, 48, 49, 51, 54, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "differ": [2, 5, 7, 10, 13, 14, 16, 18, 24, 27, 29, 30, 32, 39, 40, 42, 43, 44, 46, 47, 51, 54, 57, 59, 60, 61, 63, 68, 70, 72, 75, 88, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 106, 107, 108], "sampl": [2, 3, 5, 8, 10, 13, 19, 23, 34, 46, 48, 51, 54, 55, 56, 65, 68, 71, 73, 75, 76, 85, 86, 89, 97, 98, 99, 101, 102, 104, 105, 108, 109, 110], "size": [2, 10, 34, 40, 43, 44, 46, 51, 54, 55, 65, 70, 71, 75, 77, 79, 89, 93, 95, 99, 101, 103, 104, 105, 107, 109], "here": [2, 5, 7, 10, 17, 43, 46, 49, 62, 63, 64, 65, 67, 68, 71, 72, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "re": [2, 5, 40, 44, 56, 58, 63, 75, 85, 88, 89, 90, 91, 95, 96, 97, 99, 100, 108, 109, 110], "weight": [2, 10, 40, 41, 44, 51, 54, 63, 70, 73, 75, 89, 90, 91, 92, 96], "loss": [2, 41, 62, 73, 75, 93, 100], "while": [2, 3, 10, 40, 43, 44, 50, 51, 59, 75, 85, 93, 97, 99, 100, 101, 103, 104, 108], "train": [2, 3, 4, 5, 9, 10, 13, 19, 21, 35, 40, 41, 42, 44, 51, 59, 62, 63, 68, 71, 72, 75, 76, 86, 91, 92, 93, 95, 96, 98, 101, 102, 103, 104, 105, 107, 109, 110], "support": [2, 3, 4, 5, 13, 15, 17, 36, 37, 43, 45, 51, 59, 60, 62, 72, 73, 83, 85, 86, 90, 91, 92, 93, 97, 99], "your": [2, 3, 5, 9, 10, 13, 19, 39, 40, 42, 43, 44, 46, 51, 56, 59, 61, 62, 63, 64, 65, 67, 72, 73, 75, 76, 77, 79, 80, 86, 88, 89, 90, 93, 95, 98, 100, 103, 104, 105, 106, 107, 108, 109, 110], "recommend": [2, 5, 7, 10, 13, 16, 19, 43, 46, 63, 91, 92, 93, 97, 99, 100, 107, 108], "furthermor": 2, "correctli": [2, 3, 10, 39, 40, 44, 46, 49, 54, 60, 64, 65, 70, 71, 75, 77, 89, 96, 97, 99, 104, 105, 108, 109], "clonabl": [2, 75], "via": [2, 5, 7, 10, 11, 13, 16, 19, 21, 25, 39, 41, 43, 44, 51, 55, 59, 63, 68, 71, 72, 73, 75, 76, 79, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 102, 104, 105, 106, 107, 108, 109, 110], "base": [2, 3, 4, 5, 7, 10, 13, 15, 16, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 40, 43, 44, 45, 46, 49, 50, 51, 54, 55, 57, 58, 59, 60, 62, 63, 64, 65, 67, 70, 72, 73, 75, 76, 79, 81, 83, 85, 88, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "clone": [2, 75, 104], "intern": [2, 3, 7, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 43, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 67, 71, 75, 81, 86, 91, 97, 99, 101, 103, 104, 105, 106, 108, 110], "multipl": [2, 3, 5, 10, 13, 15, 16, 37, 39, 46, 57, 58, 63, 64, 65, 67, 70, 71, 75, 85, 91, 92, 93, 95, 99, 102, 104, 105, 108], "g": [2, 3, 5, 10, 15, 25, 35, 39, 40, 44, 46, 52, 54, 59, 65, 66, 68, 71, 72, 73, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108], "manual": [2, 75, 85, 88, 89, 90, 97, 99, 106, 107, 108, 110], "pytorch": [2, 40, 41, 44, 75, 85, 90, 93, 99, 102, 104, 109], "call": [2, 3, 5, 6, 10, 16, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 51, 59, 62, 72, 75, 89, 90, 91, 92, 96, 99, 101, 104, 106, 107, 108, 109, 110], "__init__": [2, 41, 75, 93], "independ": [2, 3, 10, 64, 75, 96, 97, 100, 107, 108, 110], "compat": [2, 40, 43, 44, 56, 62, 75, 76, 79, 83, 85, 88, 89, 97, 99, 107, 108], "neural": [2, 41, 62, 72, 75, 90, 93, 99, 104, 106, 108], "network": [2, 40, 41, 44, 62, 72, 75, 89, 90, 93, 96, 99, 104, 106, 108], "typic": [2, 10, 40, 44, 56, 72, 75, 88, 89, 90, 92, 93, 95, 96, 100, 106, 107], "initi": [2, 3, 10, 16, 21, 40, 44, 54, 63, 75, 88, 96, 99, 100], "insid": [2, 44, 75, 99, 101], "There": [2, 3, 7, 54, 85, 101, 103], "two": [2, 3, 10, 21, 29, 39, 40, 43, 44, 52, 54, 55, 56, 59, 68, 70, 71, 86, 89, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 108, 109, 110], "new": [2, 7, 9, 10, 17, 25, 40, 43, 44, 50, 54, 58, 59, 63, 75, 89, 90, 91, 96, 98, 99, 100, 106, 107, 110], "notion": 2, "confid": [2, 3, 10, 25, 39, 43, 46, 49, 51, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 79, 83, 85, 88, 93, 100, 101, 103, 104, 105, 107, 109, 110], "packag": [2, 5, 7, 9, 10, 12, 13, 14, 18, 38, 42, 46, 47, 59, 61, 62, 68, 71, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "prune": [2, 3, 46, 65, 75, 86, 100, 105], "everyth": [2, 71, 101], "els": [2, 71, 91, 93, 97, 98, 99, 100, 103, 104, 105], "mathemat": [2, 3, 10, 49, 104], "keep": [2, 16, 17, 59, 85, 91, 97, 98, 99, 100, 109], "belong": [2, 3, 10, 39, 46, 48, 49, 54, 64, 65, 66, 67, 72, 73, 77, 81, 83, 84, 92, 93, 100, 101, 104, 106, 109, 110], "2": [2, 3, 4, 5, 7, 10, 11, 13, 15, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 41, 43, 44, 46, 48, 49, 50, 51, 52, 54, 56, 57, 58, 59, 62, 64, 65, 67, 68, 71, 72, 73, 75, 76, 80, 81, 83, 84, 98, 99, 107], "error": [2, 3, 5, 10, 40, 44, 45, 46, 48, 49, 59, 64, 65, 67, 68, 70, 71, 73, 75, 77, 79, 80, 83, 86, 88, 90, 91, 92, 95, 96, 97, 98, 100, 102], "erron": [2, 3, 39, 46, 49, 59, 64, 65, 73, 75, 76, 77, 106, 108], "import": [2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 17, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 43, 45, 51, 54, 57, 58, 63, 67, 70, 75, 76, 81, 83, 84, 85, 88, 89, 95, 96, 97, 99, 100, 104, 105, 106, 108, 109, 110], "linear_model": [2, 5, 39, 59, 75, 85, 89, 90, 91, 92, 96, 97, 99, 101, 103, 106], "logisticregress": [2, 3, 5, 39, 59, 85, 89, 90, 91, 92, 96, 97, 99, 101, 103, 106], "logreg": 2, "cl": [2, 17, 33, 75, 85, 88, 89, 99, 101, 108], "pass": [2, 3, 5, 8, 10, 11, 13, 15, 16, 17, 19, 26, 33, 36, 40, 43, 44, 46, 50, 51, 54, 56, 59, 62, 63, 65, 71, 72, 73, 75, 80, 81, 85, 89, 90, 91, 92, 96, 97, 98, 99, 101, 103, 105, 106, 108], "x_train": [2, 88, 91, 92, 101, 103, 104, 108], "labels_maybe_with_error": 2, "had": [2, 3, 75, 105], "issu": [2, 3, 4, 5, 6, 8, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 39, 40, 42, 43, 44, 45, 46, 54, 61, 64, 65, 66, 67, 68, 69, 70, 71, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 89, 94, 102, 103, 106, 107, 108], "pred": [2, 46, 59, 88, 89, 100, 107, 108], "x_test": [2, 88, 91, 92, 101, 104, 108], "might": [2, 5, 10, 54, 63, 75, 80, 88, 89, 91, 92, 93, 97, 99, 105], "case": [2, 3, 10, 13, 16, 39, 51, 54, 63, 75, 88, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 106, 108, 110], "standard": [2, 3, 5, 33, 39, 46, 62, 64, 65, 67, 73, 75, 85, 88, 91, 92, 95, 98, 100, 101, 105], "adapt": [2, 12, 13, 18, 40, 42, 59, 61, 75, 106], "skorch": [2, 75, 85, 99], "kera": [2, 61, 68, 71, 75, 85, 99, 105], "scikera": [2, 62, 75, 99], "open": [2, 43, 88, 89, 92, 95, 96, 98, 101, 104, 105, 106, 108, 110], "doesn": [2, 10, 75, 85], "t": [2, 3, 4, 7, 10, 20, 30, 31, 40, 41, 43, 44, 45, 46, 51, 57, 58, 67, 72, 73, 75, 81, 83, 84, 85, 91, 92, 93, 96, 97, 98, 100, 101, 104, 105, 108, 110], "alreadi": [2, 5, 10, 13, 19, 40, 43, 44, 49, 54, 62, 63, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 105, 106, 108], "exist": [2, 5, 10, 15, 21, 40, 43, 44, 56, 58, 62, 68, 70, 72, 75, 85, 86, 88, 89, 91, 92, 96, 103, 110], "made": [2, 5, 13, 19, 40, 44, 55, 75, 88, 89, 93, 96, 97, 99, 100, 103, 105, 107, 108], "easi": [2, 12, 49, 75, 91, 92, 98, 99, 101, 104], "inherit": [2, 7, 41, 75], "baseestim": [2, 44, 75], "yourmodel": [2, 75], "def": [2, 7, 17, 40, 44, 62, 75, 89, 90, 91, 92, 93, 97, 98, 99, 100, 101, 103, 104, 106, 108, 110], "self": [2, 3, 5, 7, 10, 13, 15, 16, 17, 19, 34, 40, 41, 43, 44, 46, 51, 72, 73, 75, 88, 91, 93, 97, 98, 100, 104, 109, 110], "refer": [2, 10, 13, 19, 40, 44, 45, 64, 65, 67, 68, 70, 71, 72, 75, 79, 80, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 107, 108], "origin": [2, 5, 10, 44, 45, 46, 58, 59, 62, 64, 65, 68, 71, 72, 75, 76, 79, 81, 83, 88, 89, 91, 93, 95, 96, 97, 99, 101, 105, 106, 108, 110], "total": [2, 3, 4, 39, 43, 59, 64, 84, 93, 99, 109], "state": [2, 3, 5, 40, 41, 44, 50, 75, 101, 104, 105, 110], "art": [2, 41, 101, 104], "northcutt": [2, 3, 39, 72, 73], "et": [2, 3, 39, 41, 72, 73], "al": [2, 3, 39, 41, 72, 73], "2021": [2, 3, 39, 72, 73], "weak": [2, 71], "supervis": [2, 10, 91, 92, 99, 103], "find": [2, 5, 9, 10, 13, 16, 17, 19, 22, 23, 25, 26, 28, 29, 30, 31, 34, 35, 39, 40, 42, 43, 44, 45, 46, 50, 56, 58, 59, 61, 68, 71, 72, 73, 75, 77, 81, 83, 85, 86, 91, 98, 100, 102, 107], "uncertainti": [2, 10, 48, 72, 75, 99, 106, 108], "It": [2, 3, 5, 7, 10, 15, 16, 19, 25, 30, 33, 35, 36, 37, 40, 44, 46, 49, 51, 54, 55, 57, 63, 70, 71, 75, 85, 91, 92, 93, 97, 99, 101, 104, 107], "work": [2, 3, 7, 10, 15, 33, 39, 40, 43, 44, 46, 49, 58, 59, 60, 62, 63, 73, 75, 85, 86, 89, 91, 92, 97, 98, 100, 106, 108], "includ": [2, 3, 5, 7, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 40, 42, 43, 44, 54, 58, 59, 61, 63, 64, 67, 68, 72, 73, 75, 79, 80, 81, 83, 85, 86, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 105, 106, 110], "deep": [2, 42, 44, 61, 62, 75, 96], "see": [2, 3, 5, 7, 10, 13, 16, 17, 36, 39, 40, 43, 44, 45, 46, 51, 56, 59, 62, 64, 65, 67, 68, 71, 72, 73, 75, 81, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 108, 109, 110], "subfield": 2, "theori": [2, 101], "machin": [2, 4, 5, 9, 10, 17, 19, 36, 42, 57, 61, 75, 88, 89, 91, 92, 97, 98, 100, 103], "across": [2, 3, 5, 7, 10, 13, 16, 25, 39, 43, 51, 64, 71, 72, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 107, 108], "varieti": [2, 88, 89, 99], "like": [2, 3, 5, 6, 7, 10, 17, 35, 39, 40, 43, 44, 46, 49, 59, 62, 63, 64, 67, 68, 70, 73, 75, 76, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "pu": [2, 59], "input": [2, 3, 5, 9, 13, 19, 29, 39, 40, 43, 44, 49, 51, 54, 55, 58, 59, 60, 62, 71, 75, 85, 86, 89, 92, 93, 96, 98, 99, 100, 101, 103, 104, 105, 108, 109, 110], "discret": [2, 37, 46, 49, 59, 72, 73, 77, 79, 80], "vector": [2, 3, 4, 5, 10, 13, 19, 46, 49, 51, 52, 54, 59, 72, 73, 85, 89, 90, 91, 92, 93, 95, 96, 100, 101, 104, 105, 106, 109, 110], "would": [2, 3, 5, 10, 40, 43, 44, 46, 55, 59, 65, 75, 85, 89, 91, 93, 99, 100, 101, 106, 108, 110], "obtain": [2, 5, 8, 10, 13, 19, 46, 63, 65, 68, 71, 73, 76, 90, 92, 96, 99, 103, 105, 107, 109, 110], "been": [2, 4, 39, 46, 49, 54, 58, 59, 63, 64, 68, 70, 72, 73, 75, 90, 91, 95, 97, 99, 100, 101, 103, 104, 105, 106, 109, 110], "dure": [2, 10, 19, 54, 56, 72, 75, 88, 89, 90, 95, 96, 97, 99, 101, 104, 107, 108, 110], "denot": [2, 3, 49, 51, 59, 65, 72, 73, 83], "tild": 2, "paper": [2, 4, 10, 63, 72, 81, 83, 98, 101, 103, 106, 108, 110], "cv_n_fold": [2, 3, 75, 89], "5": [2, 3, 4, 5, 8, 10, 13, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 44, 46, 48, 50, 51, 59, 63, 64, 67, 68, 71, 75, 76, 83, 89, 91, 96, 98, 99, 104, 105, 106, 107, 109, 110], "converge_latent_estim": [2, 3], "pulearn": [2, 59], "find_label_issues_kwarg": [2, 10, 75, 86, 99, 101], "label_quality_scores_kwarg": [2, 10], "low_memori": [2, 65, 81, 99], "clean": [2, 70, 73, 75, 76, 85, 88, 89, 91, 92, 98, 108], "even": [2, 3, 7, 9, 10, 39, 43, 48, 49, 59, 75, 90, 97, 99, 100, 101, 103, 104, 105], "messi": [2, 75, 101], "ridden": [2, 75], "autom": [2, 9, 10, 75, 85, 88, 89, 92, 95, 96, 98, 99, 100, 101, 104, 106, 108], "robust": [2, 49, 54, 75, 92, 97, 99, 100], "prone": [2, 75], "out": [2, 3, 5, 10, 13, 19, 31, 40, 44, 46, 51, 54, 62, 65, 66, 68, 71, 72, 73, 75, 76, 84, 85, 86, 89, 97, 98, 99, 101, 102, 104, 105, 106, 108, 109, 110], "current": [2, 3, 5, 7, 10, 11, 13, 16, 17, 25, 40, 44, 45, 46, 51, 63, 70, 75, 91, 92, 99, 100, 103, 105], "intend": [2, 13, 14, 16, 17, 18, 19, 35, 36, 37, 47, 54, 63, 79, 83, 90, 91, 92, 96, 101], "A": [2, 3, 4, 5, 7, 10, 13, 15, 16, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 39, 40, 41, 44, 46, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 62, 63, 64, 67, 70, 71, 72, 73, 75, 77, 79, 80, 84, 86, 88, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 110], "follow": [2, 3, 10, 17, 33, 37, 39, 40, 43, 44, 51, 53, 57, 63, 64, 68, 70, 71, 72, 75, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "tutori": [2, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 101, 103, 104, 105, 106, 108, 109, 110], "repo": 2, "wrapper": [2, 13, 62, 88, 89, 90, 108], "around": [2, 13, 70, 91, 92, 100, 105, 106, 110], "fasttext": 2, "store": [2, 4, 5, 10, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 43, 44, 72, 75, 88, 89, 95, 96, 97, 98, 99, 109, 110], "along": [2, 51, 65, 83, 91, 92, 93, 97, 99, 106], "dimens": [2, 59, 77, 80, 93, 99, 106, 109], "select": [2, 9, 10, 29, 53, 63, 73, 93, 100, 103, 106], "split": [2, 3, 5, 10, 15, 43, 51, 58, 59, 75, 88, 90, 91, 92, 93, 95, 96, 97, 98, 101, 102, 104, 107, 110], "cross": [2, 3, 10, 39, 46, 49, 50, 51, 65, 68, 71, 73, 75, 76, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 108, 109, 110], "fold": [2, 3, 39, 46, 49, 75, 88, 90, 95, 98, 99, 105, 109], "By": [2, 39, 64, 65, 75, 91, 97, 109], "need": [2, 3, 10, 11, 39, 40, 43, 44, 46, 54, 56, 64, 65, 67, 72, 75, 85, 89, 90, 91, 92, 96, 97, 99, 100, 101, 103, 104, 105, 109], "holdout": [2, 3, 75], "comput": [2, 3, 4, 5, 7, 8, 10, 13, 22, 23, 25, 26, 29, 30, 31, 34, 39, 40, 41, 43, 44, 46, 48, 49, 50, 51, 54, 55, 56, 59, 63, 64, 65, 67, 70, 71, 72, 73, 75, 76, 77, 79, 85, 86, 89, 91, 92, 98, 101, 102, 105, 106, 108, 109], "them": [2, 3, 5, 7, 9, 10, 12, 15, 30, 35, 38, 40, 42, 43, 44, 46, 56, 61, 63, 72, 75, 86, 88, 89, 91, 92, 93, 95, 96, 97, 99, 103, 104, 106, 108, 109, 110], "numer": [2, 3, 4, 5, 10, 13, 16, 25, 33, 37, 51, 54, 55, 70, 72, 75, 80, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 100, 101, 103, 104, 106, 108], "consist": [2, 3, 10, 40, 44, 53, 59, 63, 97, 109, 110], "latent": [2, 3, 49], "thei": [2, 3, 5, 14, 18, 24, 27, 29, 32, 40, 41, 42, 44, 46, 47, 54, 57, 59, 62, 65, 70, 73, 75, 76, 79, 83, 85, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 106, 108, 110], "relat": [2, 3, 10, 16, 22, 23, 29, 30, 31, 34, 49, 59, 64, 75, 92, 96, 97], "close": [2, 3, 10, 43, 49, 72, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 105], "form": [2, 3, 10, 40, 41, 44, 49, 58, 59, 73, 75, 99], "equival": [2, 3, 40, 44, 49, 72, 106, 108], "iter": [2, 3, 39, 40, 44, 46, 59, 64, 65, 75, 99, 103, 109], "enforc": [2, 40, 44, 59], "perfectli": [2, 39, 64, 101], "certain": [2, 3, 5, 10, 40, 44, 62, 71, 75, 91, 92, 97, 98, 105, 106], "dict": [2, 3, 5, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 43, 44, 46, 50, 51, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 83, 91, 92, 93, 99, 100, 110], "keyword": [2, 3, 5, 10, 11, 13, 19, 26, 30, 33, 40, 43, 44, 46, 48, 51, 54, 56, 58, 62, 63, 65, 71, 72, 73, 75, 80, 81, 83, 91], "filter": [2, 3, 10, 43, 45, 58, 64, 66, 67, 69, 71, 78, 79, 80, 82, 83, 84, 85, 86, 88, 89, 90, 93, 96, 98, 99, 100, 104, 105, 108, 109, 110], "find_label_issu": [2, 3, 10, 33, 42, 43, 45, 46, 64, 65, 66, 67, 68, 69, 70, 71, 74, 75, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 88, 89, 99, 104, 105, 108, 109, 110], "particularli": [2, 85, 100, 103, 106], "filter_bi": [2, 3, 43, 46, 65, 86, 99], "frac_nois": [2, 46, 65, 81, 99], "min_examples_per_class": [2, 46, 65, 99, 101], "impact": [2, 4, 10, 91, 92, 93, 97], "ml": [2, 4, 5, 9, 10, 18, 75, 85, 88, 89, 91, 92, 93, 95, 96, 97, 98, 102, 103, 104, 106, 107, 108], "accuraci": [2, 10, 41, 73, 88, 89, 90, 93, 99, 100, 101, 103, 106, 108, 109], "n_job": [2, 43, 46, 65, 77, 79, 81, 99, 100, 106, 109], "disabl": [2, 40, 44, 46, 106], "process": [2, 3, 7, 13, 16, 19, 35, 40, 43, 44, 46, 54, 58, 63, 65, 71, 77, 79, 81, 89, 90, 91, 97, 99, 100, 103, 107], "caus": [2, 46, 51, 91, 92, 97, 99], "rank": [2, 3, 10, 39, 43, 45, 46, 51, 64, 65, 66, 68, 69, 71, 72, 74, 78, 80, 81, 82, 84, 85, 86, 88, 89, 91, 92, 98, 99, 104, 105, 106, 109, 110], "get_label_quality_scor": [2, 42, 43, 45, 46, 47, 51, 63, 65, 66, 67, 68, 69, 70, 73, 74, 76, 78, 79, 81, 82, 83, 86, 99, 101, 104, 105, 109, 110], "adjust_pred_prob": [2, 10, 67, 72, 73, 101], "control": [2, 5, 9, 10, 13, 19, 43, 46, 63, 71, 72, 75, 81, 83, 91, 92, 97, 98, 99], "how": [2, 3, 5, 10, 13, 15, 16, 17, 19, 25, 39, 40, 41, 43, 44, 49, 59, 63, 64, 67, 68, 70, 72, 73, 75, 79, 83, 85, 88, 89, 91, 92, 93, 95, 96, 97, 98, 100, 105, 106, 107, 108, 109], "much": [2, 10, 39, 43, 46, 75, 97, 99, 103], "output": [2, 3, 5, 10, 13, 19, 35, 40, 41, 44, 49, 59, 62, 63, 64, 68, 70, 71, 72, 75, 79, 80, 83, 84, 85, 86, 89, 90, 91, 93, 96, 97, 98, 99, 100, 105, 106, 107, 108], "print": [2, 5, 7, 13, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 59, 63, 64, 65, 70, 72, 73, 75, 77, 79, 80, 84, 86, 88, 89, 90, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "suppress": [2, 43, 63, 70, 72, 73, 75, 77, 79, 80, 109, 110], "statement": [2, 43, 63, 70, 72, 73, 75, 77, 79, 80], "big": [2, 43, 65, 71, 75, 101], "limit": [2, 5, 13, 19, 43, 54, 65, 85, 97, 105, 109, 110], "memori": [2, 40, 43, 44, 65, 71, 77, 79, 91, 109], "experiment": [2, 40, 41, 43, 44, 45, 65, 86, 88, 89, 92, 95, 96, 98, 99, 101, 104, 106, 108], "label_issues_batch": [2, 42, 65, 99], "find_label_issues_batch": [2, 42, 43, 65, 99], "pred_prob": [2, 3, 5, 8, 10, 11, 13, 19, 26, 28, 29, 31, 34, 35, 39, 43, 45, 46, 48, 49, 50, 51, 52, 59, 60, 63, 64, 65, 67, 68, 71, 72, 73, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108], "threshold": [2, 3, 4, 7, 10, 13, 21, 22, 23, 25, 31, 33, 34, 43, 57, 70, 71, 72, 73, 79, 83, 91, 97, 105, 106, 109, 110], "inverse_noise_matrix": [2, 3, 10, 49, 59, 86, 101], "label_issu": [2, 43, 46, 65, 68, 75, 77, 86, 88, 89, 90, 93, 96, 99, 100, 101, 104, 108], "clf_kwarg": [2, 3, 10, 75], "clf_final_kwarg": [2, 75], "validation_func": [2, 3, 10], "correct": [2, 5, 9, 10, 39, 43, 46, 48, 54, 63, 64, 65, 67, 68, 70, 71, 73, 75, 76, 79, 83, 85, 88, 89, 90, 92, 93, 95, 96, 98, 101, 103, 104, 105, 106, 107, 108], "result": [2, 3, 9, 10, 13, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 43, 44, 46, 48, 57, 59, 65, 67, 68, 71, 73, 75, 76, 77, 79, 83, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 104, 108, 109, 110], "identifi": [2, 3, 5, 7, 9, 10, 13, 15, 19, 30, 36, 39, 43, 45, 46, 54, 65, 68, 71, 73, 75, 76, 77, 80, 81, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 101, 104, 106, 108, 109, 110], "final": [2, 10, 75, 88, 95, 97, 100, 105, 107, 108], "remain": [2, 75, 86, 88, 89, 93, 97, 100, 104, 108, 110], "datasetlik": [2, 59, 75], "beyond": [2, 5, 7, 9, 10, 12, 38, 85, 88, 89, 100, 108, 109], "pd": [2, 3, 5, 7, 13, 16, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 50, 62, 63, 64, 75, 83, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 108, 110], "datafram": [2, 3, 5, 7, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 43, 50, 59, 60, 62, 63, 64, 75, 80, 84, 86, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 108, 109, 110], "scipi": [2, 4, 5, 13, 16, 55, 59, 72, 97], "spars": [2, 4, 5, 10, 13, 16, 19, 21, 34, 54, 59, 60, 95, 97], "csr_matrix": [2, 4, 5, 13, 16, 19, 21, 34, 54, 97], "torch": [2, 40, 41, 44, 89, 90, 93, 96, 98, 106], "util": [2, 5, 10, 13, 19, 36, 40, 41, 44, 47, 54, 62, 63, 68, 71, 75, 85, 86, 90, 91, 92, 93, 99, 101, 106], "tensorflow": [2, 59, 62, 85, 90, 99], "object": [2, 5, 10, 13, 15, 16, 19, 35, 36, 40, 41, 43, 44, 51, 54, 56, 59, 60, 62, 65, 68, 69, 70, 71, 72, 75, 83, 85, 89, 90, 92, 93, 95, 97, 99, 100, 101, 102, 104, 108], "list": [2, 3, 5, 10, 15, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 41, 43, 44, 45, 46, 52, 54, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 79, 80, 81, 83, 84, 86, 89, 90, 91, 92, 93, 98, 99, 100, 101, 104, 105, 108, 110], "index_list": 2, "subset": [2, 3, 5, 13, 19, 39, 43, 46, 59, 73, 80, 84, 88, 89, 90, 93, 95, 96, 97, 99, 104, 105, 106, 107, 108, 110], "wa": [2, 3, 15, 17, 43, 57, 59, 63, 64, 70, 72, 84, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 104, 105, 107, 109, 110], "abl": [2, 3, 10, 75, 90, 99, 100, 101, 103, 104], "format": [2, 3, 5, 10, 15, 35, 40, 43, 44, 46, 49, 50, 51, 52, 54, 59, 60, 62, 63, 64, 65, 68, 71, 72, 73, 75, 77, 79, 80, 83, 84, 88, 91, 92, 93, 95, 97, 98, 100, 103, 108, 109, 110], "make": [2, 3, 5, 21, 40, 43, 44, 51, 62, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 101, 103, 104, 105, 106, 108], "sure": [2, 5, 43, 46, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 103, 104, 105, 106, 108], "shuffl": [2, 10, 59, 90, 93, 96, 97, 104, 106], "ha": [2, 3, 5, 6, 10, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 45, 49, 51, 54, 58, 59, 63, 68, 70, 75, 81, 83, 84, 85, 88, 89, 90, 91, 92, 95, 96, 97, 100, 101, 103, 104, 105, 106, 107, 108, 110], "batch": [2, 43, 59, 62, 63, 77, 79, 93, 99, 106], "order": [2, 5, 10, 37, 39, 40, 44, 45, 46, 49, 50, 51, 57, 59, 63, 64, 65, 68, 71, 72, 73, 77, 80, 81, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 108, 109, 110], "destroi": [2, 59], "oper": [2, 40, 43, 44, 54, 59, 62, 73, 85, 88, 89, 96, 99, 106], "eg": [2, 5, 10, 59, 68, 71, 91, 92, 99, 100], "repeat": [2, 59, 63, 103, 106], "appli": [2, 10, 37, 40, 42, 44, 46, 51, 52, 54, 58, 59, 67, 72, 81, 85, 88, 89, 90, 91, 92, 93, 95, 97, 99, 100, 103, 104, 106, 107, 108, 109], "array_lik": [2, 3, 39, 46, 59, 65, 72, 76], "some": [2, 3, 5, 10, 17, 25, 39, 40, 42, 44, 46, 49, 54, 58, 59, 61, 63, 64, 65, 67, 68, 71, 72, 73, 75, 77, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "seri": [2, 3, 43, 59, 60, 75, 83, 99, 100], "row": [2, 3, 5, 10, 13, 16, 30, 35, 39, 43, 46, 48, 49, 54, 55, 59, 63, 64, 65, 67, 72, 73, 75, 80, 81, 83, 84, 88, 90, 93, 95, 96, 97, 98, 99, 100, 103, 104, 106, 110], "rather": [2, 3, 5, 10, 29, 39, 59, 62, 63, 70, 79, 83, 89, 98, 100, 103, 107, 108, 109, 110], "leav": [2, 46], "per": [2, 3, 5, 7, 10, 13, 16, 39, 43, 46, 51, 58, 63, 64, 65, 67, 70, 71, 73, 76, 77, 79, 83, 92, 99, 105, 110], "determin": [2, 3, 10, 15, 19, 25, 29, 33, 39, 43, 46, 51, 54, 59, 63, 65, 68, 70, 73, 79, 83, 91, 97, 99, 100, 103, 105, 106, 108], "cutoff": [2, 3, 55, 106], "consid": [2, 3, 4, 5, 10, 13, 16, 19, 26, 29, 31, 34, 39, 40, 44, 46, 54, 56, 59, 63, 70, 72, 73, 76, 79, 83, 88, 89, 90, 93, 95, 96, 97, 99, 100, 101, 105, 106, 107, 108, 109], "section": [2, 3, 7, 10, 86, 93, 95, 97, 99, 100, 105], "3": [2, 3, 4, 5, 7, 10, 11, 37, 39, 40, 44, 46, 49, 50, 51, 52, 55, 57, 58, 59, 62, 65, 72, 73, 75, 76, 81, 83, 98, 99, 107], "equat": [2, 3, 49], "advanc": [2, 3, 5, 9, 10, 13, 19, 70, 72, 83, 86, 92, 94, 97, 99, 100, 101], "user": [2, 3, 5, 9, 10, 13, 17, 19, 30, 35, 36, 37, 40, 44, 46, 54, 62, 70, 72, 73, 75, 79, 83, 100, 101], "specifi": [2, 3, 4, 5, 8, 10, 13, 16, 17, 19, 21, 34, 36, 40, 43, 44, 46, 51, 54, 56, 58, 62, 63, 64, 65, 68, 70, 72, 73, 75, 76, 84, 86, 89, 90, 92, 93, 96, 97, 100, 103, 105, 108], "automat": [2, 3, 5, 29, 39, 85, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "greater": [2, 3, 4, 5, 7, 9, 10, 31, 43, 55, 59, 70, 92, 98, 99, 110], "count": [2, 25, 29, 39, 43, 46, 49, 59, 64, 65, 71, 86, 93, 97, 99, 105], "observ": [2, 3, 49, 56, 90, 91, 92, 103, 106, 108], "mislabel": [2, 10, 39, 43, 45, 46, 49, 63, 64, 65, 68, 70, 73, 79, 81, 83, 84, 85, 88, 89, 90, 93, 95, 96, 99, 100, 101, 105, 108], "one": [2, 3, 5, 7, 10, 29, 39, 40, 43, 44, 45, 46, 51, 57, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 103, 106, 107, 108, 110], "get_label_issu": [2, 42, 43, 74, 75, 88, 89, 101, 108], "either": [2, 3, 4, 7, 10, 40, 43, 44, 46, 55, 63, 65, 70, 72, 73, 77, 79, 92, 97, 99, 104, 105], "boolean": [2, 7, 10, 25, 43, 46, 56, 58, 63, 65, 68, 73, 75, 77, 79, 80, 85, 89, 90, 92, 93, 96, 99, 105, 108, 109], "label_issues_mask": [2, 46, 73, 75, 86], "indic": [2, 3, 4, 5, 7, 10, 13, 16, 25, 39, 43, 44, 45, 46, 48, 51, 54, 56, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 79, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "its": [2, 5, 7, 9, 10, 13, 19, 40, 43, 44, 46, 54, 56, 57, 58, 65, 68, 71, 72, 73, 75, 77, 81, 83, 85, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 109, 110], "return_indices_ranked_bi": [2, 43, 46, 65, 81, 86, 88, 89, 99, 101], "significantli": [2, 10, 93, 97, 101, 103, 107], "reduc": [2, 43, 46, 59, 90, 99], "time": [2, 10, 40, 43, 44, 59, 63, 84, 86, 91, 93, 99, 100, 105, 109, 110], "take": [2, 5, 10, 39, 40, 44, 50, 51, 54, 56, 59, 62, 73, 88, 93, 95, 103, 104, 105, 110], "run": [2, 5, 6, 7, 9, 10, 11, 12, 13, 17, 19, 29, 30, 35, 38, 40, 43, 44, 56, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 110], "skip": [2, 10, 40, 44, 75, 90, 97, 99, 100, 104, 110], "slow": [2, 3], "step": [2, 7, 29, 51, 71, 93, 97, 100, 101, 103, 107], "caution": [2, 5, 99, 100], "previous": [2, 5, 13, 16, 59, 72, 75, 86, 88, 90, 91, 95, 96, 100, 103, 107], "assign": [2, 7, 10, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 40, 44, 50, 51, 59, 75, 88, 91, 93, 95, 97, 99, 108, 109, 110], "individu": [2, 4, 7, 10, 13, 16, 29, 40, 44, 45, 63, 67, 70, 73, 75, 81, 83, 86, 88, 92, 95, 97, 98, 99, 103, 104, 105, 110], "still": [2, 43, 44, 59, 72, 88, 93, 99, 106], "extra": [2, 40, 44, 59, 62, 63, 64, 75, 93, 96, 99, 100, 103, 106], "receiv": [2, 10, 40, 44, 45, 64, 67, 68, 75, 77, 81, 92, 105], "overwritten": [2, 75], "callabl": [2, 3, 4, 10, 29, 40, 44, 51, 54, 55, 56, 58, 62, 67, 99], "x_val": 2, "y_val": 2, "map": [2, 3, 15, 43, 44, 47, 50, 58, 59, 71, 73, 75, 80, 90, 91, 92, 93, 97, 99, 101, 104, 110], "appropri": [2, 10, 19, 37, 55, 65, 73, 91, 95, 100, 104, 105], "earli": [2, 93], "stop": [2, 93], "x_valid": 2, "y_valid": 2, "could": [2, 7, 10, 25, 39, 59, 72, 88, 91, 93, 95, 97, 100, 104, 108, 110], "f": [2, 7, 88, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108], "ignor": [2, 40, 44, 58, 62, 75, 80, 84, 90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "allow": [2, 13, 39, 40, 43, 44, 48, 56, 59, 63, 71, 72, 75, 77, 79, 89, 90, 93, 97, 99, 107, 109], "access": [2, 10, 16, 40, 44, 75, 92, 93, 98, 104], "hyperparamet": [2, 67, 72, 93], "purpos": [2, 54, 91, 92, 97, 99, 104, 108], "want": [2, 5, 10, 39, 43, 54, 60, 63, 65, 75, 89, 91, 93, 96, 98, 100, 103, 105, 106, 107, 109, 110], "explicitli": [2, 8, 10, 44, 54, 75], "yourself": [2, 5, 43, 92, 97], "altern": [2, 7, 10, 51, 56, 59, 62, 63, 73, 86, 89, 90, 93, 95, 96, 98, 99, 100, 101, 103, 104, 106, 108], "same": [2, 3, 5, 7, 9, 10, 13, 15, 17, 19, 29, 33, 40, 43, 44, 46, 54, 59, 62, 63, 65, 72, 73, 75, 79, 80, 83, 84, 85, 88, 89, 91, 92, 93, 95, 96, 97, 99, 100, 104, 105, 106, 107, 108, 109], "effect": [2, 10, 30, 40, 44, 63, 72, 75, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 106, 108], "offer": [2, 5, 9, 10, 89, 90, 91, 92, 96, 99, 100, 101, 104], "after": [2, 3, 5, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 59, 63, 75, 89, 91, 93, 96, 97, 99, 100, 101, 103, 105, 106, 107, 108, 109], "attribut": [2, 5, 7, 10, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 40, 43, 44, 51, 56, 72, 75, 88, 91, 97], "label_issues_df": [2, 75, 93], "similar": [2, 10, 39, 40, 44, 56, 59, 63, 67, 68, 70, 72, 75, 79, 83, 91, 92, 93, 95, 96, 97, 99, 100, 101, 105, 106, 109], "document": [2, 3, 5, 13, 17, 19, 39, 40, 43, 44, 45, 46, 51, 58, 62, 64, 65, 67, 70, 71, 72, 75, 79, 80, 81, 83, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 110], "descript": [2, 5, 7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36, 39, 45, 59, 68, 75, 91, 92], "were": [2, 3, 5, 10, 39, 44, 54, 64, 70, 83, 88, 90, 95, 99, 101, 103, 105, 107, 109], "present": [2, 3, 5, 10, 13, 15, 16, 23, 39, 59, 72, 80, 85, 93, 97, 99, 100, 106], "actual": [2, 3, 5, 10, 39, 54, 63, 64, 73, 92, 99, 101, 107, 110], "num_class": [2, 39, 43, 59, 62, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 104, 106], "uniqu": [2, 34, 59, 80, 91, 97, 99, 100, 104, 106], "given_label": [2, 5, 11, 28, 33, 39, 49, 75, 80, 84, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 108, 109, 110], "normal": [2, 3, 21, 29, 34, 46, 48, 51, 57, 58, 59, 73, 97, 99, 101, 106], "trick": [2, 99], "distribut": [2, 3, 5, 10, 29, 31, 39, 44, 46, 50, 57, 63, 71, 72, 73, 85, 91, 92, 93, 95, 96, 97, 100, 105, 106], "account": [2, 39, 63, 67, 72, 73, 89, 96, 99, 101, 103, 104, 106, 108], "word": [2, 3, 58, 83, 84, 99], "remov": [2, 10, 34, 39, 40, 44, 46, 75, 85, 88, 89, 93, 96, 97, 98, 99, 100, 104, 106, 108], "so": [2, 3, 5, 6, 7, 10, 17, 29, 37, 39, 40, 43, 44, 46, 54, 59, 63, 64, 70, 73, 75, 79, 83, 90, 91, 92, 93, 96, 97, 100, 101, 104, 106, 109], "proportion": [2, 10, 46], "just": [2, 3, 5, 10, 13, 16, 35, 39, 41, 43, 59, 62, 73, 75, 77, 85, 86, 88, 89, 90, 92, 93, 95, 96, 97, 99, 101, 104, 105, 106, 107, 108, 109], "procedur": 2, "get": [2, 3, 5, 8, 10, 11, 16, 34, 40, 41, 44, 46, 51, 57, 58, 59, 63, 65, 67, 72, 73, 75, 76, 77, 85, 88, 89, 90, 93, 96, 97, 98, 99, 100, 101, 106, 107, 108], "detect": [2, 5, 7, 9, 13, 16, 17, 19, 21, 25, 31, 45, 54, 57, 66, 68, 69, 70, 71, 72, 73, 74, 75, 78, 82, 85, 88, 89, 91, 94, 98, 100, 102, 104, 108, 109, 110], "arg": [2, 15, 25, 30, 34, 40, 41, 44, 51, 59, 73, 75, 100], "kwarg": [2, 7, 10, 13, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 43, 44, 45, 51, 54, 62, 71, 75, 77, 79, 80, 81, 99], "test": [2, 5, 10, 29, 44, 51, 54, 62, 75, 85, 88, 89, 91, 92, 93, 95, 96, 102, 107, 108, 110], "expect": [2, 3, 10, 40, 44, 46, 51, 54, 63, 72, 73, 75, 88, 89, 99, 100, 101, 103, 104, 105, 108, 110], "class_predict": 2, "evalu": [2, 10, 40, 41, 42, 43, 44, 71, 75, 88, 89, 90, 91, 92, 93, 99, 101, 103, 107, 108, 109], "simpli": [2, 10, 39, 73, 85, 89, 91, 92, 95, 96, 99, 101, 104, 108, 109, 110], "quantifi": [2, 4, 5, 7, 10, 13, 16, 46, 67, 72, 75, 85, 92, 93, 95, 96, 97, 100, 101, 105], "save_spac": [2, 10, 74, 75], "potenti": [2, 10, 39, 46, 58, 65, 68, 71, 73, 75, 77, 79, 84, 86, 88, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 109, 110], "cach": [2, 89, 96], "panda": [2, 5, 7, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 59, 60, 62, 63, 64, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 103, 108, 109], "unlik": [2, 10, 46, 48, 51, 62, 64, 65, 67, 83, 91, 100, 103, 104, 106, 108], "both": [2, 5, 10, 13, 19, 29, 39, 40, 44, 46, 54, 59, 63, 65, 73, 77, 79, 84, 85, 91, 93, 99, 100, 101, 103, 110], "mask": [2, 43, 46, 58, 59, 65, 68, 73, 75, 77, 79, 80, 85, 98, 99, 103, 105, 109, 110], "prefer": [2, 73, 81, 104], "plan": 2, "subsequ": [2, 3, 40, 44, 56, 89, 96, 99, 101, 105], "invok": [2, 40, 44, 101, 107], "scratch": [2, 54, 75], "To": [2, 5, 7, 9, 10, 12, 13, 16, 19, 29, 38, 40, 43, 44, 45, 46, 62, 63, 65, 67, 71, 72, 73, 75, 76, 77, 79, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "share": [2, 10, 73, 75], "mostli": [2, 59, 70, 75, 100, 104, 108], "longer": [2, 37, 50, 51, 58, 75, 86, 89, 96, 99, 100, 105], "info": [2, 5, 7, 10, 13, 16, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 64, 75, 83, 92, 97, 98, 110], "about": [2, 3, 5, 7, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 41, 43, 48, 63, 64, 67, 71, 75, 80, 83, 90, 91, 93, 95, 96, 97, 98, 99, 100, 101, 103, 106], "docstr": [2, 39, 40, 44, 59, 75, 98, 101], "unless": [2, 40, 44, 54, 75, 99], "our": [2, 3, 10, 62, 63, 73, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "is_label_issu": [2, 11, 33, 75, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 104, 108], "entir": [2, 10, 29, 43, 46, 49, 64, 65, 70, 73, 75, 77, 79, 80, 85, 91, 92, 97, 99, 100, 105, 106, 107, 109, 110], "accur": [2, 3, 5, 9, 10, 13, 19, 39, 43, 46, 55, 63, 64, 65, 68, 71, 73, 75, 76, 77, 79, 80, 86, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 106, 108], "label_qu": [2, 63, 75, 89, 101, 103, 108], "measur": [2, 5, 39, 63, 64, 75, 85, 88, 97, 98, 99, 100, 101, 103, 104, 108, 109, 110], "qualiti": [2, 3, 5, 7, 9, 10, 13, 16, 33, 34, 39, 43, 45, 46, 48, 51, 63, 64, 65, 67, 68, 70, 73, 75, 76, 79, 81, 83, 85, 86, 90, 91, 93, 99, 100, 102], "lower": [2, 4, 5, 7, 10, 13, 16, 31, 43, 51, 57, 63, 64, 67, 70, 71, 73, 75, 76, 79, 83, 89, 90, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 108, 109, 110], "eas": 2, "comparison": [2, 40, 44, 71, 100, 101, 103], "against": [2, 40, 44, 91, 95, 97, 99, 100, 103, 104], "predicted_label": [2, 5, 11, 28, 33, 75, 80, 84, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 108, 109], "ad": [2, 40, 44, 92, 103, 108], "precis": [2, 55, 57, 65, 68, 71, 97, 98, 99, 101, 109, 110], "definit": [2, 7, 37, 51, 75, 88, 95], "accessor": [2, 75], "describ": [2, 10, 21, 63, 72, 73, 75, 81, 83, 101, 103, 104, 105, 107, 110], "precomput": [2, 4, 5, 49, 54, 75, 98], "clear": [2, 40, 44, 56, 75, 89, 96, 97, 108], "save": [2, 5, 13, 19, 40, 43, 44, 71, 75, 97, 99, 105, 109, 110], "space": [2, 5, 10, 72, 75, 93, 95, 97, 98], "place": [2, 40, 44, 54, 59, 75, 88, 103], "larg": [2, 9, 10, 43, 54, 75, 93, 99, 105, 106, 109, 110], "deploi": [2, 9, 10, 75, 93, 99, 100], "care": [2, 10, 40, 44, 54, 75, 96, 97, 99, 101], "avail": [2, 4, 5, 7, 10, 15, 17, 36, 44, 56, 75, 99, 100, 101, 103, 105, 108], "cannot": [2, 5, 15, 17, 59, 100, 107, 110], "anymor": 2, "classmethod": [2, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 37, 44, 51, 75], "__init_subclass__": [2, 42, 44, 74, 75], "set_": [2, 44, 75], "_request": [2, 44, 75], "pep": [2, 44, 75], "487": [2, 44, 75], "look": [2, 5, 7, 10, 19, 40, 44, 59, 75, 80, 88, 91, 92, 95, 96, 99, 100, 101, 103, 104, 105, 106, 109, 110], "inform": [2, 5, 7, 10, 13, 16, 19, 36, 40, 44, 56, 59, 63, 64, 68, 71, 75, 80, 83, 84, 85, 90, 91, 95, 96, 97, 98, 100, 101, 103, 106, 109, 110], "__metadata_request__": [2, 44, 75], "infer": [2, 44, 59, 75, 80, 84, 88, 89, 93, 103, 104], "signatur": [2, 40, 44, 75], "accept": [2, 40, 44, 56, 57, 73, 75, 91, 92, 99], "metadata": [2, 10, 44, 75, 93, 110], "through": [2, 5, 7, 44, 75, 89, 90, 92, 96, 97, 98, 99, 100, 103, 105, 106], "develop": [2, 9, 44, 56, 75, 99, 101, 110], "request": [2, 44, 75, 88, 89, 92, 96, 97, 98, 104, 110], "those": [2, 3, 4, 10, 43, 44, 46, 53, 62, 63, 65, 71, 75, 79, 83, 84, 85, 90, 93, 97, 99, 100, 105, 109], "http": [2, 4, 5, 7, 9, 10, 12, 21, 38, 40, 41, 43, 44, 48, 56, 59, 68, 71, 72, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "www": [2, 44, 75, 106], "org": [2, 4, 21, 40, 41, 44, 56, 59, 72, 75, 99, 100, 101, 110], "dev": [2, 44, 75], "0487": [2, 44, 75], "get_metadata_rout": [2, 42, 44, 74, 75], "rout": [2, 44, 75], "pleas": [2, 40, 44, 62, 75, 85, 89, 90, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 106, 108, 110], "guid": [2, 7, 10, 44, 75, 86, 90, 91, 92, 93, 94, 95, 96, 97, 100, 101], "mechan": [2, 40, 44, 75], "metadatarequest": [2, 44, 75], "encapsul": [2, 19, 44, 70, 75], "get_param": [2, 42, 44, 61, 62, 74, 75], "subobject": [2, 44, 75], "param": [2, 10, 40, 44, 62, 72, 75, 99], "name": [2, 5, 6, 7, 10, 11, 13, 15, 16, 35, 37, 39, 40, 44, 50, 51, 55, 59, 62, 63, 64, 71, 75, 80, 84, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 108, 109, 110], "set_fit_request": [2, 42, 44, 74, 75], "str": [2, 3, 4, 5, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 49, 51, 54, 55, 56, 57, 58, 59, 62, 63, 64, 68, 70, 71, 73, 75, 80, 84, 90, 91, 97, 99, 103, 104, 105, 110], "unchang": [2, 40, 44, 75, 97, 110], "relev": [2, 10, 19, 29, 44, 75, 93, 95, 97], "enable_metadata_rout": [2, 44, 75], "set_config": [2, 44, 75], "meta": [2, 44, 75], "rais": [2, 4, 5, 13, 15, 16, 37, 40, 44, 48, 51, 54, 57, 75, 99], "alia": [2, 40, 44, 75], "metadata_rout": [2, 44, 75], "retain": [2, 44, 59, 75], "chang": [2, 35, 37, 40, 43, 44, 48, 75, 83, 88, 89, 90, 91, 96, 99, 100, 105, 106, 110], "version": [2, 4, 5, 7, 9, 10, 12, 14, 18, 24, 27, 32, 38, 40, 42, 44, 47, 48, 59, 61, 62, 73, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 108, 110], "sub": [2, 44, 70, 75], "pipelin": [2, 44, 75, 108], "otherwis": [2, 4, 7, 10, 37, 39, 40, 43, 44, 46, 52, 55, 57, 58, 59, 65, 75, 77, 79, 80, 84, 85, 89, 96, 99, 100], "updat": [2, 13, 16, 40, 43, 44, 54, 62, 75, 86, 91, 93, 100], "set_param": [2, 42, 44, 61, 62, 74, 75], "simpl": [2, 40, 44, 46, 63, 73, 75, 88, 89, 91, 92, 93, 95, 96, 100, 103, 106, 108], "well": [2, 3, 9, 10, 40, 44, 48, 49, 63, 65, 71, 73, 75, 80, 83, 84, 86, 91, 92, 93, 95, 96, 99, 100, 101, 103, 105, 106], "nest": [2, 40, 44, 45, 60, 75, 81, 83, 84, 110], "latter": [2, 40, 44, 75, 106], "compon": [2, 44, 75], "__": [2, 44, 75], "set_score_request": [2, 74, 75], "structur": [3, 72, 95, 97, 99, 100], "unobserv": 3, "less": [3, 4, 5, 10, 34, 43, 51, 63, 72, 73, 77, 79, 83, 93, 95, 97, 98, 99, 100, 101, 105, 110], "channel": [3, 90, 101], "character": 3, "flip": 3, "nm": 3, "invers": [3, 10, 39, 49, 59, 64, 89, 92, 98], "inv": 3, "confident_joint": [3, 25, 39, 46, 59, 64, 65, 86, 99, 101], "un": 3, "under": [3, 10, 40, 44, 64, 71, 72, 92, 97, 100, 106], "joint": [3, 39, 46, 49, 59, 64, 65, 98], "num_label_issu": [3, 43, 46, 65, 80, 84, 86], "estimation_method": [3, 43], "off_diagon": 3, "multi_label": [3, 39, 46, 59, 60, 65, 104], "don": [3, 10, 85, 92, 93, 96, 101, 105, 108], "statis": 3, "compute_confident_joint": [3, 39, 46, 59, 65, 101], "off": [3, 46, 59, 70, 93, 101, 105, 106], "j": [3, 5, 39, 40, 44, 45, 46, 65, 68, 71, 72, 81, 83, 84, 91, 92, 101, 109, 110], "confident_learn": [3, 46, 65, 101], "off_diagonal_calibr": 3, "calibr": [3, 4, 46, 59, 63, 103], "cj": [3, 49, 59], "axi": [3, 34, 49, 51, 57, 77, 80, 90, 91, 92, 93, 97, 99, 100, 101, 103, 104, 106, 108, 109], "bincount": [3, 91, 92, 101, 103, 104], "alwai": [3, 10, 40, 44, 59, 88, 89, 90, 101, 108], "estimate_issu": 3, "over": [3, 5, 10, 40, 43, 44, 70, 71, 77, 79, 88, 92, 93, 95, 97, 98, 99, 100, 101, 106, 108], "As": [3, 7, 85, 91, 92, 96, 100, 101, 108, 110], "add": [3, 5, 7, 13, 15, 16, 40, 44, 62, 71, 89, 90, 91, 92, 93, 96, 97, 99, 100, 101, 104], "approach": [3, 39, 43, 46, 62, 88, 95, 97, 100, 101, 104, 106, 108], "custom": [3, 7, 10, 12, 33, 40, 43, 44, 51, 58, 73, 89, 92, 96, 97, 101, 108], "know": [3, 10, 91, 92, 93, 96, 99, 101, 103, 108], "cut": [3, 70, 85, 88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "off_diagonal_custom": 3, "tl": 3, "dr": 3, "sometim": [3, 35, 105, 106, 110], "underestim": 3, "few": [3, 9, 10, 71, 85, 97, 99, 103, 104, 105, 106, 110], "4": [3, 4, 5, 10, 11, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 50, 51, 58, 67, 68, 70, 71, 73, 76, 83, 98, 99, 104, 109, 110], "detail": [3, 4, 5, 10, 13, 17, 19, 36, 39, 40, 44, 45, 51, 56, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 79, 80, 81, 85, 86, 90, 97, 99, 100, 104, 106, 110], "num_issu": [3, 7, 43, 90, 91, 92, 93, 95, 96, 97, 100, 101], "calibrate_confident_joint": 3, "up": [3, 7, 10, 20, 29, 30, 33, 46, 51, 53, 62, 63, 89, 98, 99, 105, 108, 110], "p_": [3, 39, 46], "pair": [3, 5, 10, 39, 46, 101], "v": [3, 10, 43, 64, 65, 67, 73, 91, 92, 102, 104, 105, 106, 107], "rest": [3, 5, 7, 9, 10, 12, 38, 64, 65, 67, 75, 88, 89, 91, 92, 93, 95, 96, 99, 100, 101, 103, 108], "fashion": [3, 5, 77, 88], "2x2": 3, "incorrectli": [3, 39, 64, 65, 68, 95, 100, 110], "calibrated_cj": 3, "c": [3, 10, 57, 58, 65, 73, 85, 88, 90, 91, 92, 95, 96, 97, 99, 100, 101, 104, 105, 106, 107, 108], "whose": [3, 4, 5, 10, 31, 40, 44, 49, 54, 58, 63, 67, 70, 76, 79, 83, 84, 90, 91, 92, 93, 95, 96, 99, 100, 101, 104, 105, 106, 109, 110], "truli": [3, 106, 109], "estimate_joint": [3, 39, 101], "joint_estim": 3, "confident_joint_distribut": 3, "recal": [3, 65, 71, 101, 105, 107, 109, 110], "return_indices_of_off_diagon": 3, "frequenc": [3, 29, 63, 64, 71, 80, 105, 106], "done": [3, 10, 62, 75, 91, 99, 101, 104, 106, 107], "overfit": [3, 10, 68, 71, 88, 90, 91, 92, 93, 95, 96, 107], "classifict": 3, "singl": [3, 5, 9, 10, 15, 29, 39, 40, 44, 45, 51, 52, 59, 63, 64, 70, 71, 72, 73, 83, 88, 90, 91, 97, 99, 101, 104, 105], "baselin": [3, 40, 46, 89, 106, 108], "proxi": 3, "union": [3, 5, 15, 29, 51, 54, 55, 56, 59, 60, 65, 71, 75, 83, 99], "tupl": [3, 34, 40, 44, 45, 49, 50, 52, 54, 58, 59, 63, 65, 71, 79, 81, 83, 84, 90, 110], "confident_joint_count": 3, "indices_off_diagon": 3, "simplif": 3, "effici": [3, 4, 5, 10, 43, 49, 54, 55, 63, 72, 77, 79, 85, 89, 93, 97, 99, 100, 109], "practic": [3, 88, 89, 92, 93, 100, 101, 106, 108], "complet": [3, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 105, 108], "gist": 3, "cj_ish": 3, "guess": [3, 49, 101, 103], "8": [3, 5, 7, 8, 50, 51, 52, 58, 67, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 103, 104, 105, 106, 108, 109, 110], "parallel": [3, 46, 71, 81, 98], "again": [3, 62, 88, 99, 106], "simplifi": [3, 17, 99], "understand": [3, 9, 10, 39, 64, 71, 92, 97, 101, 102, 108, 109, 110], "100": [3, 4, 40, 44, 54, 55, 57, 72, 73, 88, 89, 91, 92, 93, 95, 97, 98, 99, 100, 101, 104, 105, 106, 110], "optim": [3, 40, 41, 44, 62, 88, 89, 92, 93, 95, 96, 97, 98, 101, 103, 104, 106, 108], "speed": [3, 46, 89, 98, 99, 108], "dtype": [3, 26, 28, 29, 34, 40, 44, 58, 59, 67, 83, 90, 97, 100, 105], "enumer": [3, 40, 44, 90, 91, 92, 93, 97, 110], "s_label": 3, "confident_bin": 3, "6": [3, 5, 10, 44, 51, 59, 83, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 103, 104, 105, 106, 108, 109, 110], "num_confident_bin": 3, "argmax": [3, 46, 73, 77, 80, 90, 97, 99, 101, 105, 106, 109], "elif": 3, "estimate_lat": 3, "py_method": [3, 49], "cnt": [3, 49], "1d": [3, 5, 13, 15, 19, 35, 43, 46, 51, 52, 54, 59, 60, 67, 76, 88, 90, 97], "eqn": [3, 49], "margin": [3, 46, 49, 51, 73], "marginal_p": [3, 49], "shorthand": [3, 13, 16], "proport": [3, 10, 39, 64, 101, 107], "poorli": [3, 49, 88, 97], "inv_noise_matrix": 3, "estimate_py_and_noise_matrices_from_prob": [3, 101], "variabl": [3, 7, 17, 30, 59, 75, 76, 90, 91, 95, 101, 104, 108], "exact": [3, 10, 49, 54, 88, 91, 92, 93, 95, 97, 100], "within": [3, 4, 5, 10, 14, 18, 35, 40, 41, 44, 45, 47, 65, 70, 79, 81, 83, 91, 92, 93, 99, 105, 109], "percent": 3, "often": [3, 39, 49, 64, 99, 101, 107, 109], "estimate_confident_joint_and_cv_pred_proba": 3, "mani": [3, 9, 10, 59, 60, 71, 88, 89, 90, 91, 93, 95, 96, 99, 100, 104, 105, 106, 108], "wai": [3, 5, 10, 54, 62, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 105, 107], "pro": 3, "con": 3, "pred_proba": [3, 107], "combin": [3, 39, 91, 93, 97, 98, 99, 100, 101, 107, 108], "becaus": [3, 10, 49, 55, 59, 70, 96, 97, 99, 100, 101, 103, 105, 107], "littl": [3, 43, 98, 105, 110], "uniform": [3, 73, 98, 99, 101], "20": [3, 7, 45, 84, 90, 93, 96, 97, 98, 99, 100, 101, 105, 108, 109, 110], "Such": [3, 93, 106], "bound": [3, 26, 28, 40, 44, 58, 67, 68, 70, 71, 105], "reason": [3, 10, 25, 40, 44, 55, 72], "comment": [3, 58, 97, 110], "end": [3, 5, 40, 44, 56, 71], "file": [3, 5, 15, 42, 43, 61, 71, 88, 90, 91, 95, 96, 98, 99, 105, 106, 109, 110], "estimate_py_noise_matrices_and_cv_pred_proba": [3, 101], "handl": [3, 5, 7, 10, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 43, 44, 54, 55, 56, 86, 88, 89, 91, 92, 93, 95, 96, 97, 98, 100, 101, 104, 106, 108, 109, 110], "five": [3, 68, 71, 101, 105], "estimate_cv_predicted_prob": [3, 101], "estimate_noise_matric": 3, "get_confident_threshold": [3, 42, 43], "amongst": [3, 10, 100, 105], "confident_threshold": [3, 10, 25, 26, 43, 72], "point": [4, 5, 7, 9, 10, 21, 29, 40, 44, 54, 56, 85, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103], "valuat": [4, 9, 21], "help": [4, 39, 40, 44, 71, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 106, 108, 109, 110], "u": [4, 88, 89, 90, 91, 93, 95, 97, 99, 101, 103, 104, 107, 108, 109, 110], "assess": [4, 10, 97, 100, 105], "contribut": [4, 10, 21, 97, 105], "data_shapley_knn": 4, "knn_graph": [4, 5, 10, 11, 13, 19, 21, 22, 29, 31, 34, 47, 53, 95, 97], "metric": [4, 5, 10, 21, 22, 24, 29, 31, 34, 47, 53, 54, 56, 57, 59, 62, 71, 72, 88, 89, 90, 93, 95, 96, 97, 100, 101, 108], "10": [4, 10, 21, 22, 26, 29, 31, 34, 40, 41, 54, 71, 72, 73, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "shaplei": [4, 10, 21], "nearest": [4, 5, 10, 13, 19, 26, 29, 31, 53, 54, 55, 56, 57, 72, 92, 96, 97, 106], "neighbor": [4, 5, 10, 13, 19, 21, 26, 29, 31, 47, 54, 55, 56, 57, 72, 91, 92, 93, 95, 96, 97, 99, 106], "knn": [4, 10, 13, 16, 21, 29, 31, 34, 53, 54, 55, 56, 57, 72, 95, 106], "graph": [4, 5, 10, 13, 16, 19, 21, 29, 34, 53, 54], "calcul": [4, 10, 21, 29, 43, 51, 53, 54, 57, 63, 67, 68, 70, 71, 72, 75, 79, 93, 98, 100], "directli": [4, 5, 10, 13, 17, 19, 36, 37, 43, 56, 62, 63, 89, 92, 96, 97, 99, 100, 104, 105, 108], "lowest": [4, 10, 63, 71, 92, 93, 95, 97, 99, 100, 103, 104, 105, 109], "fall": [4, 10, 70, 79, 83, 101, 106], "flag": [4, 10, 25, 29, 46, 51, 64, 65, 68, 75, 85, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 105, 106, 108, 109], "approxim": [4, 10, 21, 43, 56, 72, 97, 103], "top": [4, 5, 10, 39, 43, 45, 46, 59, 65, 68, 71, 73, 80, 84, 85, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 104, 105, 106, 108, 110], "found": [4, 5, 7, 10, 13, 16, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 59, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 104, 106, 108, 110], "arxiv": [4, 21, 101], "ab": [4, 21, 101, 105], "1908": 4, "08619": 4, "1911": [4, 21], "07128": [4, 21], "embed": [4, 5, 10, 13, 19, 72, 85, 89, 90, 91, 92, 95, 96, 97, 100, 101, 104, 108], "represent": [4, 5, 10, 13, 19, 37, 40, 44, 52, 54, 65, 85, 89, 90, 91, 92, 93, 96, 99, 100, 101, 106], "suppli": [4, 104, 105, 108], "2d": [4, 5, 13, 19, 35, 43, 51, 52, 54, 58, 59, 63, 88, 90, 97, 104], "num_exampl": [4, 5, 13, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 64, 90, 91, 92, 93, 95, 96, 100, 101], "num_featur": [4, 5, 13, 19, 40, 44, 62], "distanc": [4, 5, 10, 13, 19, 21, 29, 31, 34, 53, 54, 55, 56, 57, 70, 72, 95, 97, 106], "construct": [4, 5, 7, 10, 13, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 44, 51, 53, 54, 56, 62, 97, 100], "nearestneighbor": [4, 5, 10, 21, 54, 56, 72, 95, 106], "cosin": [4, 10, 54, 55, 57, 72, 97, 106], "dim": [4, 72, 93, 109], "euclidean": [4, 5, 10, 54, 55, 57, 70, 72, 95], "dimension": [4, 29, 55, 59, 90, 101, 106], "scikit": [4, 44, 55, 56, 59, 72, 85, 88, 89, 90, 91, 92, 95, 96, 97, 99, 108], "fewer": [4, 10, 46, 59, 72, 97, 105], "stabl": [4, 14, 18, 24, 27, 32, 42, 47, 56, 59, 61, 72, 86, 90, 91, 92, 93, 95, 96, 100, 101], "exce": [4, 54, 93, 97], "transform": [4, 10, 35, 51, 54, 57, 59, 72, 73, 88, 89, 92, 93, 96, 97, 100, 106, 110], "rel": [4, 10, 39, 54, 63, 64, 72, 91, 92, 93, 95, 96, 100, 101, 106], "adjust": [4, 41, 46, 54, 67, 72, 73, 85, 97, 100, 101], "closer": [4, 10, 70, 97, 105], "highli": [4, 92, 93], "influenti": 4, "posit": [4, 5, 10, 40, 44, 57, 59, 71, 97, 98, 106], "convers": 4, "neg": [4, 10, 70, 71, 91, 92, 97, 98], "valueerror": [4, 5, 13, 15, 16, 37, 48, 51, 54, 57, 99], "neither": [4, 5, 10, 17, 55, 105], "nor": [4, 5, 10, 17], "larger": [4, 21, 55, 75, 77, 79, 93, 96, 98, 99], "55": [4, 58, 97, 98, 105, 108], "525": 4, "unifi": 5, "audit": [5, 9, 13, 15, 16, 19, 90, 93, 94, 95, 96, 97, 99, 100, 101, 104, 105, 108], "kind": [5, 6, 7, 10, 97, 98], "addit": [5, 7, 9, 12, 13, 16, 36, 38, 40, 44, 51, 54, 56, 60, 63, 71, 80, 81, 88, 89, 90, 91, 95, 96, 97, 100, 101, 103, 106, 107], "depend": [5, 7, 9, 12, 13, 15, 16, 38, 42, 46, 48, 59, 61, 65, 72, 75, 76, 85, 97, 107], "instal": [5, 7, 9, 12, 38, 40, 42, 43, 44, 46, 61, 62, 77, 79, 97], "pip": [5, 7, 9, 12, 38, 62, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "development": [5, 7, 9, 12, 38], "git": [5, 7, 9, 12, 38, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108], "github": [5, 7, 9, 12, 38, 40, 41, 59, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 108], "com": [5, 7, 9, 12, 38, 40, 41, 43, 48, 59, 72, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "egg": [5, 7, 9, 12, 38, 85, 98], "label_nam": [5, 7, 8, 10, 11, 15, 21, 34, 85, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 105, 108], "image_kei": [5, 10, 13, 93, 97], "interfac": [5, 9, 10, 56, 85, 88, 89, 92, 95, 96, 98, 99, 100, 101, 104, 106, 108], "librari": [5, 10, 44, 56, 68, 71, 72, 85, 89, 91, 96, 97, 98, 99], "goal": [5, 108], "track": [5, 7, 16, 17, 85, 91, 98, 99, 101], "intermedi": [5, 9, 92], "statist": [5, 10, 13, 16, 25, 29, 39, 63, 64, 71, 92, 95, 96, 97, 100, 101], "convert": [5, 10, 15, 37, 40, 44, 52, 57, 60, 63, 70, 79, 83, 86, 89, 90, 93, 96, 97, 98, 99, 100, 103, 104, 105], "hug": [5, 10, 15, 93], "face": [5, 10, 15, 19, 93, 98, 104], "kei": [5, 7, 10, 13, 15, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 44, 51, 63, 64, 70, 72, 91, 92, 93, 96, 99, 101, 103, 105], "string": [5, 10, 13, 15, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 44, 55, 59, 63, 64, 76, 80, 83, 84, 89, 95, 96, 97, 99, 103, 104, 110], "dictionari": [5, 7, 10, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 44, 50, 59, 63, 64, 67, 68, 70, 71, 91, 92, 95, 96, 101, 103, 104, 105], "path": [5, 15, 40, 43, 44, 71, 90, 91, 97, 99, 105], "local": [5, 7, 10, 15, 40, 41, 44, 90, 91, 92, 93, 98, 99, 100, 101, 103, 104, 106, 108, 110], "text": [5, 7, 10, 15, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 45, 51, 72, 81, 83, 84, 85, 87, 91, 92, 94, 98, 99, 100, 101, 102, 103, 106], "txt": [5, 15, 110], "csv": [5, 15, 88, 89, 95, 96, 100, 108], "json": [5, 15], "hub": [5, 15], "multiclass": [5, 15, 18, 51, 59, 63, 104], "regress": [5, 7, 10, 11, 13, 15, 17, 19, 24, 33, 35, 37, 89, 91, 92, 96, 102, 103, 106], "multilabel": [5, 10, 11, 15, 17, 18, 24, 28, 35, 37, 52, 104], "imag": [5, 9, 13, 39, 44, 68, 70, 71, 72, 77, 79, 80, 85, 91, 92, 94, 98, 99, 100, 102, 103, 104, 105, 107, 109], "field": [5, 10, 40, 44], "themselv": [5, 88, 89, 97, 108], "pil": [5, 93], "cleanvis": [5, 10, 13, 97], "level": [5, 10, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 54, 58, 81, 83, 92, 93, 99, 102, 104, 109], "load_dataset": [5, 15, 93], "glue": 5, "sst2": 5, "properti": [5, 9, 13, 15, 16, 37, 40, 44, 97], "has_label": [5, 15], "class_nam": [5, 15, 23, 39, 45, 64, 71, 80, 84, 85, 98, 101, 105, 109, 110], "empti": [5, 15, 49, 63, 92, 97, 99, 104], "find_issu": [5, 6, 7, 8, 10, 11, 13, 17, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36, 85, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 108], "issue_typ": [5, 6, 7, 8, 10, 11, 13, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 108], "sort": [5, 13, 19, 43, 46, 51, 63, 65, 68, 70, 71, 73, 79, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 104, 105, 108, 109, 110], "common": [5, 10, 13, 16, 19, 85, 92, 94, 97, 98, 99, 100, 101, 104, 105, 109], "real": [5, 13, 19, 85, 91, 92, 97, 99, 100, 101, 103, 108, 109], "world": [5, 13, 19, 85, 91, 92, 97, 99, 100, 101, 103, 108, 109], "interact": [5, 13, 19, 96, 99], "thereof": [5, 13, 19], "insight": [5, 13, 19, 71, 103], "best": [5, 9, 10, 13, 19, 50, 63, 73, 88, 89, 91, 92, 93, 95, 97, 99, 100, 103, 104, 106, 107, 108, 110], "properli": [5, 10, 43, 50, 54, 59, 60, 77, 90, 91, 92, 93, 95, 96, 99, 100, 101, 104, 106, 108, 109], "respect": [5, 40, 44, 68, 71, 90, 91, 92, 93, 95, 96, 100, 101, 104, 105], "lexicograph": [5, 50, 59, 90, 91, 92, 93, 95, 96, 100, 101, 104], "squar": [5, 59, 75, 98, 108], "csr": [5, 54, 97], "evenli": 5, "omit": [5, 70, 71, 93, 97, 105], "itself": [5, 35, 40, 44, 54, 97, 105], "three": [5, 10, 39, 63, 64, 75, 80, 88, 90, 91, 92, 95, 98, 101, 103, 107, 108, 109, 110], "indptr": [5, 97], "wise": 5, "start": [5, 7, 10, 37, 40, 41, 44, 51, 85, 104, 110], "th": [5, 10, 45, 50, 58, 59, 63, 65, 68, 70, 71, 72, 81, 83, 84, 96, 104, 105, 110], "ascend": [5, 39, 64, 93, 101], "segment": [5, 77, 79, 80, 102], "reflect": [5, 10, 54, 88, 89, 95, 96, 100, 103, 105, 106, 108], "maintain": [5, 62], "kneighbors_graph": [5, 21, 56, 95], "illustr": [5, 97], "todens": 5, "second": [5, 51, 59, 71, 73, 91, 95, 99, 101, 110], "duplic": [5, 9, 24, 25, 40, 44, 54, 85, 91, 97, 100, 101, 108], "explicit": 5, "precend": 5, "collect": [5, 10, 13, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 63, 97, 99, 103, 110], "unspecifi": [5, 13, 19, 46, 65], "interest": [5, 13, 19, 25, 80, 84, 88, 89, 96, 97, 100, 101, 108, 109, 110], "constructor": [5, 10, 11, 13, 19, 26, 33, 54, 56], "issuemanag": [5, 9, 13, 16, 17, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 36], "respons": [5, 13, 19, 25, 56, 75, 76, 97, 98, 108, 110], "random_st": [5, 88, 90, 91, 92, 93, 97, 100, 101, 104, 106], "lab": [5, 6, 8, 10, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 43, 85, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 108], "comprehens": [5, 85, 93, 97, 100, 104, 108], "nbr": 5, "n_neighbor": [5, 10, 21, 54, 56, 72, 97], "mode": [5, 12, 21, 40, 43, 44, 95, 106], "4x4": 5, "float64": [5, 29, 40, 44, 83], "compress": [5, 10, 54, 59, 77, 79, 97], "toarrai": [5, 54, 97], "NOT": [5, 43, 96], "23606798": 5, "41421356": [5, 54], "configur": [5, 19, 51, 92], "suppos": [5, 10, 68, 88, 89, 106, 108], "who": [5, 70, 88, 95, 97, 101, 110], "manag": [5, 8, 9, 10, 13, 16, 17, 18, 19, 20, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 62, 91, 99], "clean_learning_kwarg": [5, 10, 11, 26, 33, 99, 108], "labelissuemanag": [5, 10, 17, 24, 26], "prune_method": [5, 86], "prune_by_noise_r": [5, 46, 65, 101], "report": [5, 7, 10, 12, 13, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 64, 84, 85, 90, 91, 92, 95, 96, 97, 99, 100, 101, 104, 108, 110], "include_descript": [5, 13, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36], "show_summary_scor": [5, 13, 36, 97, 100], "show_all_issu": [5, 13, 36, 97, 100], "summari": [5, 7, 13, 16, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 45, 61, 62, 64, 69, 78, 79, 81, 82, 83, 86, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 105, 108, 109, 110], "show": [5, 7, 29, 40, 44, 50, 59, 71, 80, 84, 88, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 106, 108, 109, 110], "suffer": [5, 10, 13, 16, 25, 65, 73, 84, 97, 110], "onc": [5, 10, 25, 39, 40, 44, 88, 91, 99, 100, 101, 104, 105], "familiar": [5, 97], "overal": [5, 7, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 45, 51, 63, 64, 67, 70, 71, 75, 79, 80, 81, 83, 85, 86, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 105, 110], "sever": [5, 7, 10, 13, 15, 16, 25, 40, 43, 44, 46, 67, 70, 72, 73, 79, 83, 85, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 105, 106, 110], "compar": [5, 63, 72, 83, 91, 92, 95, 97, 100, 101, 105], "issue_summari": [5, 7, 10, 13, 16, 97], "With": [5, 9, 10, 43, 89, 96, 99, 101, 103, 108, 109, 110], "usag": [5, 43, 62], "usual": [5, 15, 35, 36, 93, 103, 108], "ti": [5, 63], "exhibit": [5, 7, 10, 13, 16, 80, 90, 91, 92, 93, 95, 96, 100, 101, 105], "ie": [5, 75], "likelihood": [5, 10, 43, 45, 46, 65, 70, 72, 73, 77, 81, 97], "wherea": [5, 10, 59, 65, 88, 89, 97, 107], "outlier": [5, 9, 11, 17, 24, 25, 34, 47, 54, 73, 85, 91, 92, 97, 100, 101, 102, 108], "fundament": [5, 10], "incompar": 5, "quantiti": [5, 101, 108], "global": [5, 7, 10, 25, 40, 44, 98], "non_iid": [5, 10, 11, 17, 29, 92, 93, 95, 96, 97, 100, 101], "hypothesi": [5, 97], "iid": [5, 7, 9, 29, 85, 95, 100, 101], "never": [5, 90, 100, 101, 104, 106, 107], "someth": [5, 7, 10, 40, 44, 73, 105], "123": [5, 91, 92], "456": [5, 88, 89, 90], "nearest_neighbor": 5, "7": [5, 10, 51, 52, 62, 81, 83, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 103, 104, 105, 106, 108, 109, 110], "9": [5, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 45, 51, 52, 67, 81, 83, 88, 89, 90, 91, 92, 95, 96, 97, 98, 101, 103, 104, 105, 106, 108, 109, 110], "distance_to_nearest_neighbor": [5, 11, 91, 92, 93, 95, 96, 100, 101], "789": 5, "get_issu": [5, 10, 13, 16, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 108], "issue_nam": [5, 6, 7, 10, 13, 16, 17, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 90, 91, 92, 93, 95, 96, 97, 100, 101], "focu": [5, 10, 13, 16, 96, 97, 100, 109, 110], "full": [5, 10, 13, 16, 43, 62, 71, 93, 100, 110], "summar": [5, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 64, 80, 84, 85, 109], "specific_issu": [5, 13, 16], "lie": [5, 10, 72, 73, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101], "get_issue_summari": [5, 10, 13, 16, 92, 97], "get_info": [5, 10, 13, 16, 92, 96, 97, 98], "yet": [5, 20, 30, 62, 98, 100, 103], "list_possible_issue_typ": [5, 17, 18], "regist": [5, 7, 17, 18, 20, 30, 40, 44, 91], "rtype": [5, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44], "registri": [5, 17, 18], "list_default_issue_typ": [5, 17, 18], "folder": [5, 90, 91, 93], "load": [5, 15, 43, 71, 93, 98, 99, 100, 101, 105, 106, 109, 110], "futur": [5, 10, 25, 40, 44, 63, 85, 91, 96], "overwrit": [5, 91], "separ": [5, 39, 51, 67, 91, 92, 93, 97, 99, 100, 105, 107], "static": 5, "rememb": [5, 96, 99, 100, 101], "part": [5, 10, 40, 44, 46, 68, 70, 71, 90, 91, 97, 98, 100, 109, 110], "ident": [5, 10, 25, 59, 96, 97], "datalab": [6, 8, 11, 13, 15, 16, 17, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 85, 88, 89, 98, 100, 103, 108], "walk": [7, 100], "alongsid": [7, 13, 40, 44, 91, 99], "pre": [7, 8, 10, 40, 44, 85, 91, 92, 108], "runtim": [7, 40, 43, 44, 75, 77, 79, 90, 93, 99, 100], "issue_manager_factori": [7, 17, 91], "myissuemanag": [7, 17], "myissuemanagerforregress": 7, "decor": [7, 17], "ll": [7, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 110], "thing": [7, 44, 89, 97, 101, 108], "next": [7, 63, 85, 88, 89, 90, 95, 96, 97, 99, 103, 105, 108, 110], "dummi": 7, "randint": [7, 34, 51, 91, 92, 97], "mark": [7, 10, 86, 105, 106, 108], "regard": [7, 92, 100, 101], "rand": [7, 51, 54, 91, 92, 97], "is_": [7, 10, 91], "_issu": [7, 10, 91], "issue_score_kei": [7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 91], "whole": [7, 10, 29, 40, 44, 92, 97], "make_summari": [7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 91], "popul": [7, 96, 100], "verbosity_level": [7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], "std": [7, 105], "raw_scor": 7, "bit": 7, "involv": [7, 43, 80, 84, 97, 99, 104], "intermediate_arg": 7, "min": [7, 51, 70, 83, 91, 99, 106], "sin_filt": 7, "sin": 7, "arang": [7, 97], "kernel": [7, 97], "affect": [7, 10, 40, 44, 55, 77, 83, 96, 97, 99], "easili": [7, 10, 49, 86, 88, 89, 90, 92, 95, 96, 100, 101, 103, 104, 106, 107, 108, 109], "hard": [7, 44, 85, 98, 106], "sai": [7, 10, 40, 44, 97, 104, 109], "anoth": [7, 10, 25, 39, 43, 55, 58, 70, 73, 89, 95, 96, 97, 99, 101, 103, 106], "try": [7, 9, 10, 43, 46, 62, 63, 77, 79, 85, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 106, 107, 108, 109], "won": [7, 40, 44, 91, 92, 99, 104], "issue_manag": [7, 10, 12, 13, 16, 18, 21, 22, 23, 26, 28, 29, 30, 31, 33, 34, 91], "instanti": [7, 19, 43, 62, 72, 89, 90, 92, 95], "477762": 7, "286455": 7, "term": [7, 10, 49, 59, 71, 90, 91, 92, 93, 95, 96, 100, 101], "4778": 7, "is_basic_issu": 7, "basic_scor": 7, "13": [7, 22, 31, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 105, 106, 108, 109, 110], "003042": 7, "058117": 7, "11": [7, 10, 62, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "121908": 7, "15": [7, 57, 62, 75, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "169312": 7, "17": [7, 89, 90, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "229044": 7, "2865": 7, "is_intermediate_issu": 7, "intermediate_scor": 7, "000000": [7, 91, 92, 97, 98, 100, 101], "007059": 7, "009967": 7, "010995": 7, "087332": 7, "016296": 7, "03947": 7, "019459": 7, "794251": 7, "underperform": [8, 9, 34, 85, 100], "group": [8, 9, 29, 34, 85, 98, 100, 105, 110], "dbscan": [8, 10, 34], "hdbscan": 8, "etc": [8, 10, 25, 35, 40, 44, 49, 62, 63, 81, 85, 91, 92, 95, 96, 97, 99, 100, 101, 104, 108], "sensit": [8, 10, 57, 97, 100], "ep": [8, 34, 71], "radiu": 8, "min_sampl": [8, 34], "kmean": [8, 97], "your_data": 8, "get_pred_prob": 8, "n_cluster": [8, 34, 97], "cluster_id": [8, 10, 11, 34, 97], "labels_": 8, "underperforming_group": [8, 10, 11, 17, 24, 92, 93, 95, 96, 97, 100, 101], "search": [9, 10, 23, 29, 30, 47, 53, 54, 55, 58, 75, 97, 99, 100, 107], "nondefault": 9, "Near": [9, 99], "imbal": [9, 24, 67, 72, 73, 92], "spuriou": [9, 13, 93], "correl": [9, 13, 93], "null": [9, 11, 17, 24, 92, 93, 96, 100, 101], "togeth": [9, 10, 49, 89, 91, 92, 93, 95, 96, 100, 101, 108, 110], "built": [9, 51, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "own": [9, 40, 42, 44, 56, 61, 67, 68, 71, 77, 81, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 103, 104, 108, 109, 110], "prerequisit": 9, "basic": [9, 44, 62, 97, 100, 106], "fulli": [9, 10, 40, 44, 62, 99], "platform": [9, 10, 85, 88, 89, 92, 93, 95, 96, 98, 99, 101, 104, 106, 107, 108], "write": [9, 10], "code": [9, 10, 40, 44, 49, 59, 62, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 103, 104, 105, 106, 108, 109, 110], "being": [9, 10, 13, 16, 39, 40, 44, 46, 51, 58, 59, 73, 88, 95, 99, 100, 101, 108, 109], "100x": [9, 10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "faster": [9, 10, 43, 72, 75, 77, 79, 85, 88, 89, 92, 95, 96, 98, 99, 101, 104, 106, 108], "intellig": [9, 10, 100], "quickli": [9, 10, 41, 88, 90, 93, 95, 96, 99, 100, 104, 106, 107, 109, 110], "fix": [9, 10, 63, 88, 89, 92, 95, 96, 97, 98, 100, 101, 104, 106, 107, 108], "scientist": [9, 10], "million": [9, 10, 110], "thank": [9, 10], "ai": [9, 10, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 102, 103, 104, 106, 108, 110], "suggest": [9, 10, 39, 63, 64, 70, 89, 93, 96, 97, 99, 108], "power": [9, 10, 93, 98, 101, 110], "automl": [9, 10, 85, 88, 89, 92, 95, 96, 98, 99, 101, 104, 106, 107, 108], "system": [9, 10, 90, 93, 109], "foundat": [9, 10, 85, 88, 89, 92, 95, 96, 97, 98, 101, 104, 106, 107, 108], "improv": [9, 10, 63, 88, 89, 92, 93, 98, 99, 101, 102, 108, 109], "click": [9, 10, 90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "tune": [9, 10, 89, 90, 96, 98, 100, 106], "serv": [9, 10, 16, 19, 103], "auto": [9, 10, 88, 89, 92, 98, 99, 100, 108], "free": [9, 10, 85, 88, 89, 90, 92, 93, 95, 96, 98, 99, 100, 101, 104, 106, 107, 108], "page": [10, 92, 99, 100, 101], "variou": [10, 16, 33, 42, 60, 61, 85, 88, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105], "why": [10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "matter": [10, 39, 64], "didn": [10, 97, 100], "plu": [10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "ye": [10, 11], "near_dupl": [10, 11, 17, 22, 91, 92, 93, 95, 96, 97, 99, 100, 101], "class_imbal": [10, 11, 17, 23, 92, 93, 95, 96, 97, 100, 101], "data_valu": [10, 11, 17, 24, 97], "No": [10, 11, 88, 89, 96, 97, 99], "reinterpret": [10, 11], "your_regression_model": [10, 11], "_score": 10, "badli": [10, 70, 88, 89, 110], "issue_scor": 10, "atyp": [10, 72, 91, 92, 93, 95, 96, 100, 101, 106], "datapoint": [10, 34, 46, 51, 59, 73, 76, 85, 88, 89, 90, 91, 92, 95, 96, 99, 100, 107, 108], "is_issu": [10, 25], "primarili": 10, "former": [10, 40, 44], "investig": [10, 90, 97], "expertis": [10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "interpret": [10, 98, 99, 101, 104, 108], "annot": [10, 39, 50, 63, 64, 65, 67, 68, 70, 71, 80, 83, 84, 85, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 102, 105, 109], "dissimilar": [10, 95, 96], "preced": 10, "incorrect": [10, 70, 73, 76, 88, 90, 91, 92, 93, 95, 96, 97, 100, 101, 105, 108], "due": [10, 43, 46, 73, 77, 79, 90, 91, 92, 93, 95, 96, 97, 100, 101, 108], "appear": [10, 39, 50, 64, 65, 68, 76, 92, 93, 95, 96, 97, 100, 108, 109], "now": [10, 13, 43, 86, 88, 89, 90, 92, 97, 99, 100, 103, 105, 106, 108, 110], "token": [10, 45, 58, 79, 80, 81, 82, 83, 84, 99, 101, 102], "hamper": [10, 93, 98], "analyt": [10, 85, 97, 99, 103], "lead": [10, 70, 73, 93, 97, 100, 105], "draw": [10, 91, 92], "conclus": [10, 96], "let": [10, 40, 44, 72, 73, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 108, 109, 110], "sort_valu": [10, 90, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 108], "head": [10, 88, 89, 90, 92, 93, 95, 96, 97, 98, 100, 101, 103, 108], "97": [10, 88, 98, 99, 100, 101, 105, 108, 110], "064045": 10, "58": [10, 88, 92, 97, 98, 101, 105, 110], "680894": 10, "41": [10, 97, 98, 100, 105, 108], "746043": 10, "794894": 10, "98": [10, 98, 99, 100, 108, 110], "802911": 10, "give": [10, 51, 73, 101, 103, 109], "li": [10, 72], "especi": [10, 88, 89, 93, 97, 99, 108], "veri": [10, 39, 64, 68, 70, 89, 91, 92, 93, 95, 96, 99, 100, 101, 103, 106, 108], "rare": [10, 46, 71, 91, 92, 93, 95, 96, 99, 100, 101], "anomal": [10, 73, 91, 92, 93, 95, 96, 100, 101], "articl": [10, 43, 99], "blog": 10, "unexpect": [10, 40, 44, 96], "consequ": 10, "inspect": [10, 89, 90, 92, 93, 100, 101, 105, 108], "011562": 10, "62": [10, 97, 100, 101, 105, 108], "019657": 10, "22": [10, 90, 91, 93, 97, 98, 100, 101, 104, 105, 110], "035243": 10, "040907": 10, "42": [10, 51, 96, 97, 98, 105, 110], "056865": 10, "smaller": [10, 72, 104, 105], "extrem": [10, 13, 91, 92, 93, 95, 96, 97, 99, 100, 101], "record": [10, 40, 44, 90, 95, 108], "abbrevi": 10, "misspel": 10, "typo": [10, 84], "resolut": 10, "video": [10, 98], "audio": [10, 91, 92, 94, 99], "minor": [10, 58], "variat": 10, "translat": [10, 100], "d": [10, 57, 88, 95, 96, 97, 99, 100, 101, 104, 108, 110], "constant": [10, 34, 75], "median": [10, 33, 57], "question": [10, 25, 85, 101], "nearli": [10, 25, 92, 93, 95, 96], "awar": [10, 86, 101], "presenc": [10, 54, 56, 101], "36": [10, 97, 98, 100, 110], "066009": 10, "80": [10, 41, 88, 95, 100, 104, 108], "003906": 10, "093245": 10, "005599": 10, "27": [10, 95, 97, 98, 100, 101, 105, 110], "156720": 10, "009751": 10, "72": [10, 97, 98, 100, 101, 104, 108], "signific": [10, 88, 89, 92, 95, 96, 98, 100, 101, 104, 106, 108], "violat": [10, 85, 95, 96, 97, 100, 101], "assumpt": [10, 95, 96, 97, 100, 101], "changepoint": [10, 95, 96, 100, 101], "shift": [10, 54, 56, 95, 96, 100, 101], "drift": [10, 92, 95, 97, 100, 101], "autocorrel": [10, 95, 96, 100, 101], "almost": [10, 95, 96, 100, 101], "adjac": [10, 54, 95, 96, 100, 101], "tend": [10, 39, 49, 95, 96, 100, 101, 109, 110], "sequenti": [10, 40, 44, 62, 93], "pai": [10, 96, 97], "attent": [10, 97], "realli": [10, 89, 96, 100, 103, 109], "mere": 10, "highlight": [10, 80, 84, 91, 92, 95, 97, 109], "necessarili": [10, 63, 71, 96, 100, 101], "wrong": [10, 63, 68, 70, 86, 89, 91, 92, 96, 99, 100, 101, 105], "gap": 10, "b": [10, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 58, 59, 83, 88, 95, 96, 97, 98, 99, 100, 101, 107, 110], "x1": [10, 68, 71, 105], "x2": [10, 68, 71, 105], "10th": 10, "100th": 10, "90": [10, 83, 88, 95, 100, 101, 107, 108], "similarli": [10, 40, 44, 91, 93, 95, 99, 100, 105], "associ": [10, 15, 19, 35, 37, 40, 44, 71, 103], "blogpost": 10, "proper": [10, 59, 63, 68, 71, 88, 93, 96, 99, 103, 105], "scenario": [10, 54, 56, 73, 91, 92], "underli": [10, 45, 56, 72, 81, 83, 110], "stem": [10, 72, 106], "evolv": 10, "influenc": 10, "act": [10, 70, 91], "accordingli": [10, 35, 54], "emploi": [10, 104, 106], "partit": [10, 107], "ahead": 10, "good": [10, 40, 44, 57, 62, 64, 70, 73, 77, 79, 80, 85, 93, 97, 100], "problem": [10, 35, 43, 51, 80, 85, 91, 92, 93, 96, 97, 99], "deploy": [10, 88, 89, 101, 108], "overlook": [10, 70, 105], "fact": 10, "thu": [10, 39, 44, 64, 88, 90, 95, 96, 100, 101, 107, 110], "diagnos": [10, 92, 99], "24": [10, 90, 97, 98, 100, 101, 103, 105, 108], "681458": 10, "37": [10, 91, 97, 98, 100], "804582": 10, "64": [10, 44, 88, 93, 95, 97, 101, 105], "810646": 10, "815691": 10, "78": [10, 88, 95, 98, 100, 101, 105, 108], "834293": 10, "Be": [10, 44], "cautiou": 10, "behavior": [10, 19, 39, 40, 44, 71, 99], "rarest": [10, 92, 100], "q": [10, 97, 105], "subpar": 10, "special": [10, 54, 58], "techniqu": [10, 105], "smote": 10, "asymmetr": [10, 39], "28": [10, 93, 96, 97, 98, 100, 101, 103, 110], "75": [10, 51, 91, 92, 97, 98, 100, 103, 104, 105, 108, 110], "33": [10, 40, 44, 97, 98, 100, 105], "68": [10, 88, 98, 100, 101, 105], "excess": [10, 93], "dark": [10, 97, 109], "bright": [10, 110], "blurri": [10, 93, 97], "lack": [10, 62, 97, 100], "unusu": [10, 105, 106], "discuss": [10, 99], "earlier": [10, 89, 110], "unintend": [10, 95, 96, 97], "relationship": [10, 39], "irrelev": 10, "exploit": 10, "fail": [10, 15], "unseen": 10, "hold": [10, 15], "aris": 10, "captur": [10, 39, 90, 105, 106, 109], "environment": 10, "preprocess": [10, 88, 89, 92, 95, 97, 106, 108], "systemat": [10, 80, 84, 103], "photograph": 10, "uncorrelated": [10, 97], "strongli": [10, 96, 97], "minu": [10, 73], "sole": [10, 75, 88, 91, 100, 103, 106], "review": [10, 88, 89, 92, 95, 96, 98, 99, 100, 101, 105, 108, 109, 110], "latch": 10, "onto": 10, "troublesom": 10, "spurious_correl": [10, 97], "correlations_df": [10, 97], "blurry_scor": [10, 97], "559": [10, 100], "dark_scor": [10, 93, 97], "808": 10, "light_scor": [10, 97], "723": [10, 95, 100], "odd_size_scor": [10, 97], "957": 10, "odd_aspect_ratio_scor": [10, 97], "835": 10, "grayscale_scor": [10, 97], "003": 10, "spurious": 10, "low_information_scor": [10, 93, 97], "688": [10, 100, 108], "categor": [10, 72, 87, 88, 91, 92, 94, 99, 100, 108], "characterist": [10, 39, 97], "grayscal": [10, 93, 97], "cluster": [10, 21, 34, 100], "slice": [10, 100], "poor": [10, 97, 100], "subpopul": [10, 100], "faq": [10, 85, 92, 93, 95, 96, 102], "get_self_confidence_for_each_label": [10, 51, 73], "r": [10, 43, 75, 91, 92, 97, 108, 109], "tabular": [10, 85, 87, 91, 92, 94, 97, 99, 100, 103], "encod": [10, 52, 71, 77, 80, 88, 89, 95, 96, 99, 100, 108, 109], "71": [10, 97, 98, 100, 101, 105, 108], "70": [10, 83, 95, 97, 100], "69": [10, 100, 101, 108], "subgroup": [10, 97], "wors": [10, 97, 103], "ratio": [10, 97], "miss": [10, 30, 40, 44, 59, 68, 70, 99, 100, 105, 108], "pattern": [10, 97], "isn": [10, 20, 30], "scalabl": 10, "sacrific": 10, "One": [10, 59, 72, 99], "quantif": 10, "39": [10, 89, 90, 91, 93, 96, 97, 98, 99, 100, 105, 108, 109, 110], "32": [10, 90, 91, 97, 98, 100, 103, 105], "valuabl": [10, 21, 97], "exert": [10, 92], "possible_issue_typ": 10, "label_kwarg": 10, "outlier_kwarg": 10, "near_duplicate_kwarg": 10, "non_iid_kwarg": 10, "class_imbalance_kwarg": 10, "underperforming_group_kwarg": 10, "null_kwarg": 10, "data_valuation_kwarg": 10, "health_summary_paramet": [10, 24, 26, 33], "health_summari": [10, 26, 39, 85, 98], "health_summary_kwarg": 10, "tandem": [10, 98], "view": [10, 40, 44, 45, 46, 79, 81, 83, 85, 88, 89, 90, 91, 92, 95, 96, 98, 100, 101, 103, 104, 105, 106, 107, 108, 110], "ood_kwarg": 10, "outofdistribut": [10, 31, 72, 106], "outsid": [10, 99, 104], "outlierissuemanag": [10, 17, 24, 31], "nearduplicateissuemanag": [10, 17, 22, 24], "noniidissuemanag": [10, 17, 24, 29], "num_permut": [10, 29], "permut": [10, 29], "significance_threshold": [10, 29], "signic": 10, "noniid": [10, 24], "classimbalanceissuemanag": [10, 17, 23, 24], "underperforminggroupissuemanag": [10, 17, 24, 34], "determinin": 10, "neighbour": 10, "min_cluster_sampl": [10, 34], "filter_cluster_id": [10, 24, 34], "clustering_kwarg": [10, 34], "nullissuemanag": [10, 17, 24, 30], "datavaluationissuemanag": [10, 17, 21, 24], "codeblock": 10, "demonstr": [10, 43, 54, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109], "howev": [10, 40, 44, 54, 59, 88, 89, 90, 93, 95, 96, 97, 100, 103, 107, 109], "mandatori": 10, "image_issue_types_kwarg": 10, "vice": [10, 64], "versa": [10, 64], "light": [10, 93, 97, 98, 105, 109], "29": [10, 93, 97, 98, 100, 103, 104, 105, 109, 110], "low_inform": [10, 93, 97], "odd_aspect_ratio": [10, 93, 97], "35": [10, 91, 97, 98, 100, 103, 104, 105], "odd_siz": [10, 93, 97], "doc": [10, 40, 44, 72, 85, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 106, 108, 110], "label_scor": [11, 26, 28, 33, 90, 91, 92, 93, 95, 96, 97, 100, 101, 104, 108], "is_outlier_issu": [11, 91, 92, 93, 95, 96, 97, 100, 101], "outlier_scor": [11, 31, 91, 92, 93, 95, 96, 97, 100, 101, 106], "is_near_duplicate_issu": [11, 91, 92, 93, 95, 96, 97, 99, 100, 101], "near_duplicate_scor": [11, 22, 91, 92, 93, 95, 96, 97, 99, 100, 101], "near_duplicate_set": [11, 22, 24, 91, 92, 93, 95, 96, 99, 100, 101], "is_non_iid_issu": [11, 92, 95, 96, 97, 100, 101], "non_iid_scor": [11, 29, 92, 95, 96, 97, 100, 101], "is_class_imbalance_issu": [11, 92, 97, 100], "class_imbalance_scor": [11, 23, 92, 97, 100], "is_underperforming_group_issu": [11, 92, 97, 100], "underperforming_group_scor": [11, 34, 92, 97, 100], "is_null_issu": [11, 92, 97, 100], "null_scor": [11, 30, 92, 97, 100], "is_data_valuation_issu": [11, 97], "data_valuation_scor": [11, 21, 97], "studio": [12, 85, 88, 89, 92, 93, 95, 96, 98, 99, 100, 101, 104, 106, 107, 108], "data_issu": [12, 13, 18, 19, 36], "issue_find": [12, 18], "factori": [12, 18, 19], "model_output": [12, 18], "incorpor": [13, 86, 101], "vision": [13, 93], "create_imagelab": [13, 14], "huggingfac": [13, 90, 91, 92, 93, 99], "imagelabdataissuesadapt": [13, 14], "strategi": [13, 16, 51, 97, 99], "dataissu": [13, 16, 18, 19, 36], "_infostrategi": [13, 16], "basi": [13, 16], "filter_based_on_max_preval": 13, "max_num": 13, "collect_issues_from_imagelab": [13, 16], "collect_issues_from_issue_manag": [13, 16], "collect_statist": [13, 16], "reus": [13, 16, 25], "avoid": [13, 16, 40, 43, 44, 46, 54, 59, 65, 68, 71, 75, 77, 79, 91, 92, 99, 100], "recomput": [13, 16, 89], "weighted_knn_graph": [13, 16], "issue_manager_that_computes_knn_graph": [13, 16], "set_health_scor": [13, 16], "health": [13, 16, 26, 39, 64, 85], "correlationvisu": [13, 14], "visual": [13, 68, 69, 71, 88, 91, 92, 93, 108, 110], "title_info": 13, "ncol": [13, 93, 106], "cell_siz": 13, "correlationreport": [13, 14], "anyth": [13, 101], "imagelabreporteradapt": [13, 14], "get_report": [13, 36], "report_str": [13, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36], "imagelabissuefinderadapt": [13, 14], "issuefind": [13, 18, 19, 36], "get_available_issue_typ": [13, 19], "handle_spurious_correl": [13, 14], "imagelab_issu": 13, "_": [13, 22, 23, 25, 26, 28, 29, 30, 33, 34, 51, 58, 59, 88, 90, 91, 93, 97, 98, 101, 104], "imagelab": [14, 16, 18], "except": [15, 40, 44, 62, 73, 91, 92, 93, 100, 103], "dataformaterror": [15, 18], "add_not": 15, "with_traceback": 15, "tb": 15, "__traceback__": 15, "datasetdicterror": [15, 18], "datasetdict": 15, "datasetloaderror": [15, 18], "dataset_typ": 15, "sublist": 15, "map_to_int": 15, "abc": [15, 25, 35], "is_avail": [15, 93], "central": [16, 110], "repositori": 16, "get_data_statist": [16, 18], "concret": 17, "subclass": [17, 40, 44, 72, 91], "regressionlabelissuemanag": [17, 24, 32, 33], "multilabelissuemanag": [17, 24, 27, 28], "from_str": [17, 37, 47, 51], "my_issu": 17, "logic": [17, 37, 43, 46, 77, 79, 100], "modeloutput": [18, 35], "multiclasspredprob": [18, 35], "regressionpredict": [18, 35], "multilabelpredprob": [18, 35], "instati": 19, "public": [19, 97, 100, 101, 105, 109, 110], "creation": [19, 44, 97], "execut": [19, 40, 44, 91, 99, 105], "coordin": [19, 68, 70, 71, 105, 110], "At": [19, 71, 99], "direct": [20, 30, 40, 44, 56, 62], "vstack": [21, 59, 93, 98, 99, 101, 103, 104], "25": [21, 29, 40, 51, 57, 92, 93, 97, 98, 100, 101, 103, 104, 105, 110], "classvar": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34], "short": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 58, 59], "item": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 59, 91, 92, 93, 99, 101, 103, 104], "some_info_kei": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34], "additional_info_kei": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34], "default_threshold": [21, 24, 31], "collect_info": [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], "info_to_omit": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "compos": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 40, 44, 89, 96, 106], "is_x_issu": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "x_score": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "val_a": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "val_b1": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "val_b2": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "occurr": [22, 23, 25, 29, 30, 31, 34, 58], "median_nn_dist": 22, "bleed": [24, 27, 32, 42], "edg": [24, 27, 32, 42, 70, 85, 88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108, 110], "sharp": [24, 27, 32, 42], "get_health_summari": [24, 26], "ood": [24, 31, 72, 73, 106], "simplified_kolmogorov_smirnov_test": [24, 29], "outlier_cluster_label": [24, 34], "no_underperforming_cluster_id": [24, 34], "perform_clust": [24, 34], "get_underperforming_clust": [24, 34], "find_issues_with_predict": [24, 32, 33], "find_issues_with_featur": [24, 32, 33], "believ": [25, 109], "priori": [25, 101], "abstract": [25, 35], "applic": [26, 63, 97, 99, 101, 103, 110], "typevar": [26, 28, 40, 44, 58, 67, 70, 71], "scalartyp": [26, 28], "covari": [26, 28, 75, 108], "summary_dict": 26, "neighbor_histogram": 29, "non_neighbor_histogram": 29, "kolmogorov": 29, "smirnov": 29, "largest": [29, 43, 51, 54, 73, 77, 79, 105, 109], "empir": [29, 50, 63], "cumul": 29, "ecdf": 29, "histogram": [29, 95, 97, 108], "absolut": [29, 33], "trial": 29, "null_track": 30, "extend": [30, 52, 62, 93, 97, 100, 105, 106, 110], "superclass": 30, "arbitrari": [30, 39, 79, 83, 91, 106, 108], "prompt": 30, "address": [30, 89, 91, 92, 96, 99], "enabl": [30, 44, 56, 100], "scaling_factor": [31, 57], "37037": 31, "q3_avg_dist": 31, "iqr_avg_dist": 31, "median_outlier_scor": 31, "issue_threshold": 31, "multipli": [33, 57], "deleg": 33, "confus": [34, 35, 39, 40, 44, 46, 59, 71, 89, 110], "50": [34, 44, 97, 99, 100, 101, 103, 105, 106, 108], "keepdim": [34, 99], "signifi": 34, "absenc": 34, "int64": [34, 90, 100, 103], "npt": 34, "int_": 34, "id": [34, 63, 91, 93, 97, 99, 103], "unique_cluster_id": 34, "exclud": [34, 36, 45, 80, 84, 91, 110], "worst": [34, 51, 103], "performed_clust": 34, "worst_cluster_id": 34, "convent": [35, 37], "subject": [35, 37, 100], "meant": [35, 37], "Not": [35, 56], "mainli": [35, 106, 110], "content": [35, 72, 90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "fetch": [35, 43, 90, 92, 97, 99], "datset": 36, "enum": [37, 51], "qualnam": [37, 51], "boundari": [37, 51, 91, 92], "continu": [37, 62, 88, 89, 93, 96, 99, 103, 105, 108, 110], "binari": [37, 51, 59, 65, 67, 101, 110], "simultan": [37, 108], "task_str": 37, "is_classif": 37, "__contains__": [37, 47, 51], "member": [37, 40, 44, 51, 91], "typeerror": [37, 51], "12": [37, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "__getitem__": [37, 47, 51], "match": [37, 39, 40, 44, 46, 51, 63, 64, 73, 91, 92, 93, 98, 105, 107, 109], "__iter__": [37, 47, 51], "__len__": [37, 47, 51], "alias": [37, 51], "is_regress": 37, "is_multilabel": 37, "overview": [39, 54, 88, 89, 90, 92, 93, 95, 96, 103, 105, 106, 108, 110], "modifi": [39, 40, 43, 44, 54, 56, 59, 99, 100, 101], "rank_classes_by_label_qu": [39, 92], "merg": [39, 54, 58, 85, 98, 99, 100, 110], "find_overlapping_class": [39, 99, 101], "problemat": [39, 64, 80, 84, 90, 105, 110], "unnorm": [39, 64, 101], "abov": [39, 40, 43, 44, 56, 59, 63, 70, 71, 73, 79, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "model_select": [39, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 106, 108], "cross_val_predict": [39, 44, 88, 89, 90, 91, 92, 95, 96, 97, 100, 101, 103, 107, 108], "get_data_labels_from_dataset": 39, "yourfavoritemodel": [39, 101], "cv": [39, 51, 88, 90, 91, 92, 95, 97, 100, 101, 103], "df": [39, 59, 84, 90, 97, 99], "overall_label_qu": [39, 64], "col": 39, "prob": [39, 58, 101, 107], "divid": [39, 64, 73], "label_nois": [39, 64], "human": [39, 98, 109, 110], "clearli": [39, 73, 93, 105, 109], "num": [39, 64, 98, 101], "overlap": [39, 85, 97, 98, 99, 101], "ontolog": 39, "publish": [39, 110], "therefor": [39, 73, 97, 100], "vehicl": [39, 98], "truck": [39, 97, 98, 106, 109], "intuit": [39, 64], "car": [39, 98, 105, 109], "frequent": [39, 63, 97, 99, 100, 108], "l": [39, 40, 44, 68, 70, 71], "class1": 39, "class2": 39, "dog": [39, 59, 64, 66, 80, 98, 99, 106, 107, 110], "cat": [39, 59, 64, 66, 98, 99, 106, 107], "co": [39, 40, 41], "noisy_label": [39, 91, 92, 104], "overlapping_class": 39, "descend": [39, 40, 44, 51, 64, 71], "overall_label_health_scor": [39, 64, 101], "half": [39, 40, 42, 44, 64, 98, 110], "health_scor": [39, 64], "classes_by_label_qu": [39, 92], "cnn": [40, 42, 44, 93], "cifar": [40, 41, 97, 98, 106], "teach": [40, 41], "bhanml": 40, "blob": [40, 97], "master": [40, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108], "call_bn": [40, 42], "bn": 40, "input_channel": 40, "n_output": 40, "dropout_r": 40, "top_bn": 40, "architectur": [40, 44], "shown": [40, 71, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 106, 107, 109, 110], "forward": [40, 41, 42, 44, 93, 103], "overridden": [40, 44], "although": [40, 44, 72, 88, 95, 100], "recip": [40, 44], "afterward": [40, 44], "sinc": [40, 44, 48, 60, 64, 71, 79, 83, 99, 100, 103, 104, 105, 107, 110], "hook": [40, 44, 98], "silent": [40, 43, 44], "t_destin": [40, 42, 44], "__call__": [40, 42, 44, 47, 51], "add_modul": [40, 42, 44], "child": [40, 44], "fn": [40, 44, 71], "recurs": [40, 44, 51], "submodul": [40, 44, 53], "children": [40, 42, 44, 110], "nn": [40, 41, 44, 54, 93], "init": [40, 44, 101], "no_grad": [40, 44, 93, 106], "init_weight": [40, 44], "linear": [40, 44, 89, 93, 96], "fill_": [40, 44], "net": [40, 44, 90, 93, 98], "in_featur": [40, 44], "out_featur": [40, 44], "bia": [40, 44, 93], "tensor": [40, 41, 44, 90, 93, 106], "requires_grad": [40, 44], "bfloat16": [40, 42, 44], "cast": [40, 44, 90], "buffer": [40, 42, 44], "datatyp": [40, 44], "xdoctest": [40, 44], "undefin": [40, 44], "var": [40, 44], "buf": [40, 44], "20l": [40, 44], "1l": [40, 44], "5l": [40, 44], "call_super_init": [40, 42, 44], "immedi": [40, 44, 106], "compil": [40, 42, 44, 62], "cpu": [40, 42, 44, 46, 90, 93], "move": [40, 44, 51, 86, 98], "cuda": [40, 42, 44, 90, 93], "devic": [40, 44, 90, 93, 100], "gpu": [40, 44, 89, 90, 96], "live": [40, 44], "copi": [40, 44, 75, 88, 90, 91, 92, 95, 97, 99, 100, 104, 107, 108], "doubl": [40, 42, 44], "dump_patch": [40, 42, 44], "eval": [40, 42, 44, 93, 104, 106], "dropout": [40, 44], "batchnorm": [40, 44], "grad": [40, 44], "extra_repr": [40, 42, 44], "line": [40, 44, 85, 91, 97, 98, 103, 106, 110], "get_buff": [40, 42, 44], "target": [40, 41, 44, 75, 76, 97, 106, 108], "throw": [40, 44], "get_submodul": [40, 42, 44], "explan": [40, 44], "qualifi": [40, 44], "referenc": [40, 44], "attributeerror": [40, 44], "invalid": [40, 44, 96], "resolv": [40, 44, 97, 110], "get_extra_st": [40, 42, 44], "state_dict": [40, 42, 44], "set_extra_st": [40, 42, 44], "build": [40, 44, 54, 93, 97, 109], "picklabl": [40, 44], "serial": [40, 44], "backward": [40, 44, 93], "break": [40, 44, 93, 105], "pickl": [40, 44, 105], "get_paramet": [40, 42, 44], "net_b": [40, 44], "net_c": [40, 44], "conv": [40, 44], "conv2d": [40, 44, 93], "16": [40, 44, 51, 54, 62, 79, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 109, 110], "kernel_s": [40, 44], "stride": [40, 44], "200": [40, 44, 73, 97, 98, 105, 110], "diagram": [40, 44, 107], "degre": [40, 44], "queri": [40, 44, 54, 56, 92, 93, 97, 99, 100, 104], "named_modul": [40, 42, 44], "o": [40, 44, 57, 58, 90, 91, 92, 98, 99, 100, 101, 104, 105, 110], "transit": [40, 44], "ipu": [40, 42, 44], "load_state_dict": [40, 42, 44], "strict": [40, 44, 51], "persist": [40, 44], "strictli": [40, 44], "inplac": [40, 44, 97, 103], "preserv": [40, 44, 59], "namedtupl": [40, 44], "missing_kei": [40, 44], "unexpected_kei": [40, 44], "runtimeerror": [40, 44], "idx": [40, 44, 59, 60, 71, 91, 93, 97, 99, 100, 101, 103, 105, 106], "named_buff": [40, 42, 44], "prefix": [40, 44, 90, 110], "remove_dupl": [40, 44], "prepend": [40, 44], "running_var": [40, 44], "named_children": [40, 42, 44], "conv4": [40, 44], "conv5": [40, 44], "memo": [40, 44], "named_paramet": [40, 42, 44], "register_backward_hook": [40, 42, 44], "deprec": [40, 44, 48], "favor": [40, 44], "register_full_backward_hook": [40, 42, 44], "removablehandl": [40, 44], "register_buff": [40, 42, 44], "running_mean": [40, 44], "register_forward_hook": [40, 42, 44], "with_kwarg": [40, 44], "always_cal": [40, 44], "possibli": [40, 44, 88, 95], "fire": [40, 44, 98], "register_module_forward_hook": [40, 44], "regardless": [40, 44, 91, 92], "register_forward_pre_hook": [40, 42, 44], "And": [40, 44], "forward_pr": [40, 44], "register_module_forward_pre_hook": [40, 44], "gradient": [40, 44, 93, 95, 108], "grad_input": [40, 44], "grad_output": [40, 44], "technic": [40, 44], "caller": [40, 44], "register_module_full_backward_hook": [40, 44], "register_full_backward_pre_hook": [40, 42, 44], "backward_pr": [40, 44], "register_module_full_backward_pre_hook": [40, 44], "register_load_state_dict_post_hook": [40, 42, 44], "post": [40, 44, 54], "incompatible_kei": [40, 44], "modif": [40, 44, 54], "thrown": [40, 44], "register_modul": [40, 42, 44], "register_paramet": [40, 42, 44], "register_state_dict_pre_hook": [40, 42, 44], "keep_var": [40, 44], "requires_grad_": [40, 42, 44], "autograd": [40, 44], "freez": [40, 44, 89, 90, 96], "finetun": [40, 44], "gan": [40, 44], "share_memori": [40, 42, 44], "share_memory_": [40, 44], "destin": [40, 44], "shallow": [40, 44], "releas": [40, 44, 62, 86, 99], "design": [40, 44, 54], "ordereddict": [40, 44], "detach": [40, 44, 93], "non_block": [40, 44], "memory_format": [40, 44], "channels_last": [40, 44], "Its": [40, 44, 51, 64, 70], "complex": [40, 44, 100], "integr": [40, 44, 56, 85, 99], "asynchron": [40, 44], "host": [40, 44], "pin": [40, 44, 89, 96, 98], "desir": [40, 44, 54, 58, 71], "4d": [40, 44], "ignore_w": [40, 44], "determinist": [40, 44, 90], "1913": [40, 44], "3420": [40, 44], "5113": [40, 44], "2325": [40, 44], "env": [40, 44], "torch_doctest_cuda1": [40, 44], "gpu1": [40, 44], "1914": [40, 44], "5112": [40, 44], "2324": [40, 44], "float16": [40, 44], "cdoubl": [40, 44], "3741": [40, 44], "2382": [40, 44], "5593": [40, 44], "4443": [40, 44], "complex128": [40, 44], "6122": [40, 44], "1150": [40, 44], "to_empti": [40, 42, 44], "storag": [40, 44], "dst_type": [40, 44], "xpu": [40, 42, 44], "zero_grad": [40, 42, 44, 93], "set_to_non": [40, 44], "reset": [40, 44], "context": [40, 44, 105], "noisili": [41, 101], "han": 41, "2018": 41, "cifar_cnn": [41, 42], "loss_coteach": [41, 42], "y_1": 41, "y_2": 41, "forget_r": 41, "class_weight": 41, "logit": [41, 62, 93], "decim": [41, 59], "forget": [41, 51, 110], "rate_schedul": 41, "epoch": [41, 42, 44, 93, 99], "initialize_lr_schedul": [41, 42], "lr": [41, 42, 44], "001": [41, 73, 97, 99], "250": [41, 91, 92, 101, 105], "epoch_decay_start": 41, "schedul": 41, "beta": 41, "adam": 41, "adjust_learning_r": [41, 42], "alpha_plan": 41, "beta1_plan": 41, "forget_rate_schedul": [41, 42], "num_gradu": 41, "expon": 41, "tell": [41, 89, 93, 96, 101], "train_load": [41, 44], "model1": [41, 101], "optimizer1": 41, "model2": [41, 101], "optimizer2": 41, "dataload": [41, 93, 106], "parser": 41, "parse_arg": 41, "num_iter_per_epoch": 41, "print_freq": 41, "topk": 41, "top1": 41, "top5": 41, "test_load": 41, "offici": [42, 61, 97, 110], "wish": [42, 61, 100, 106, 109, 110], "adj_confident_thresholds_shar": [42, 43], "labels_shar": [42, 43], "pred_probs_shar": [42, 43], "labelinspector": [42, 43, 99], "get_num_issu": [42, 43], "get_quality_scor": [42, 43], "update_confident_threshold": [42, 43], "score_label_qu": [42, 43], "split_arr": [42, 43], "span_classif": 42, "display_issu": [42, 45, 78, 79, 80, 81, 82, 83, 84, 109, 110], "mnist_pytorch": 42, "get_mnist_dataset": [42, 44], "get_sklearn_digits_dataset": [42, 44], "simplenet": [42, 44], "batch_siz": [42, 43, 44, 77, 79, 93, 99, 106, 109], "log_interv": [42, 44], "momentum": [42, 44], "no_cuda": [42, 44], "test_batch_s": [42, 44, 93], "loader": [42, 44, 93], "set_predict_proba_request": [42, 44], "set_predict_request": [42, 44], "coteach": [42, 86], "mini": [43, 77, 79, 99], "low_self_confid": [43, 46, 65], "self_confid": [43, 46, 47, 51, 65, 67, 73, 81, 83, 88, 89, 99, 101], "conveni": [43, 56, 88, 89, 90, 96, 100], "script": 43, "labels_fil": [43, 99], "pred_probs_fil": [43, 99], "quality_score_kwarg": 43, "num_issue_kwarg": 43, "return_mask": 43, "variant": [43, 63, 109], "read": [43, 48, 92, 99, 101, 106, 110], "zarr": [43, 99], "memmap": [43, 109], "pythonspe": 43, "mmap": [43, 99], "hdf5": 43, "further": [43, 45, 64, 65, 67, 70, 71, 79, 80, 90, 97, 99, 100], "yourfil": 43, "npy": [43, 98, 99, 109], "mmap_mod": [43, 109], "tip": [43, 46, 62, 99], "save_arrai": 43, "your_arrai": 43, "disk": [43, 98, 99], "npz": [43, 110], "maxim": [43, 63, 77, 79, 100, 109], "multiprocess": [43, 46, 65, 77, 79, 93, 99], "linux": [43, 77, 79], "physic": [43, 46, 77, 79, 105], "psutil": [43, 46, 77, 79], "labels_arrai": [43, 60], "predprob": 43, "pred_probs_arrai": 43, "back": [43, 54, 71, 91, 99, 100, 105, 106], "store_result": 43, "becom": [43, 97, 106], "verifi": [43, 56, 99, 100, 103, 106], "long": [43, 63, 72, 100, 103], "enough": [43, 59, 97, 99], "chunk": [43, 107], "ram": [43, 98], "end_index": 43, "labels_batch": 43, "pred_probs_batch": 43, "batch_result": 43, "indices_of_examples_with_issu": [43, 99], "shortcut": 43, "encount": [43, 46, 77], "1000": [43, 90, 96, 99, 106], "aggreg": [43, 47, 51, 63, 67, 70, 73, 83, 99, 101, 103], "seen": [43, 99, 100, 106, 110], "far": [43, 63, 100], "label_quality_scor": [43, 67, 70, 73, 76, 101, 105], "method1": 43, "method2": 43, "normalized_margin": [43, 46, 47, 51, 65, 67, 73, 81, 83], "low_normalized_margin": [43, 46, 65], "issue_indic": [43, 70, 93], "update_num_issu": 43, "arr": [43, 99], "chunksiz": 43, "convnet": 44, "bespok": [44, 62], "download": [44, 90, 97, 99, 106], "mnist": [44, 85, 90, 98], "handwritten": 44, "digit": [44, 90, 98], "last": [44, 51, 68, 71, 91, 92, 99, 100, 103, 105, 110], "sklearn_digits_test_s": 44, "01": [44, 73, 75, 90, 97, 101, 104, 105, 106], "templat": 44, "flexibli": 44, "among": [44, 63, 101], "test_set": 44, "overrid": 44, "train_idx": [44, 59, 106], "train_label": [44, 89, 100, 106], "span": [45, 100], "sentenc": [45, 58, 81, 83, 84, 89, 96], "token_classif": [45, 58, 81, 83, 84, 99], "encourag": [46, 65, 73, 76], "multilabel_classif": [46, 64, 65, 67, 73, 99, 104], "pred_probs_by_class": 46, "prune_count_matrix_col": 46, "rank_by_kwarg": [46, 65, 73, 101], "num_to_remove_per_class": [46, 65], "bad": [46, 54, 65, 70, 73, 96, 99], "seem": [46, 101, 104], "aren": 46, "confidence_weighted_entropi": [46, 47, 51, 65, 67, 73, 81, 83], "label_issues_idx": [46, 73, 100], "entropi": [46, 48, 50, 51, 72, 73], "prune_by_class": [46, 65, 101], "predicted_neq_given": [46, 65, 101], "prune_counts_matrix": 46, "smallest": [46, 73], "unus": 46, "number_of_mislabeled_examples_in_class_k": 46, "delet": [46, 85, 89, 99], "too": [46, 51, 54, 72, 93, 99, 100, 105], "thread": [46, 65], "window": [46, 98], "shorter": [46, 68], "find_predicted_neq_given": 46, "find_label_issues_using_argmax_confusion_matrix": 46, "remove_noise_from_class": [47, 59], "clip_noise_r": [47, 59], "clip_valu": [47, 59], "value_count": [47, 59, 99], "value_counts_fill_missing_class": [47, 59], "get_missing_class": [47, 59], "round_preserving_sum": [47, 59], "round_preserving_row_tot": [47, 59], "estimate_pu_f1": [47, 59], "confusion_matrix": [47, 59], "print_square_matrix": [47, 59], "print_noise_matrix": [47, 59, 101], "print_inverse_noise_matrix": [47, 59], "print_joint_matrix": [47, 59, 101], "compress_int_arrai": [47, 59], "train_val_split": [47, 59], "subset_x_i": [47, 59], "subset_label": [47, 59], "subset_data": [47, 59], "extract_indices_tf": [47, 59], "unshuffle_tensorflow_dataset": [47, 59], "is_torch_dataset": [47, 59], "is_tensorflow_dataset": [47, 59], "csr_vstack": [47, 59], "append_extra_datapoint": [47, 59], "get_num_class": [47, 59], "num_unique_class": [47, 59], "get_unique_class": [47, 59], "format_label": [47, 59], "smart_display_datafram": [47, 59], "force_two_dimens": [47, 59], "latent_algebra": [47, 86], "compute_ps_py_inv_noise_matrix": [47, 49], "compute_py_inv_noise_matrix": [47, 49], "compute_inv_noise_matrix": [47, 49], "compute_noise_matrix_from_invers": [47, 49], "compute_pi": [47, 49], "compute_pyx": [47, 49], "label_quality_util": 47, "get_normalized_entropi": [47, 48], "multilabel_util": [47, 104], "stack_compl": [47, 52], "get_onehot_num_class": [47, 52], "int2onehot": [47, 52, 104], "onehot2int": [47, 52, 104], "multilabel_scor": [47, 67], "classlabelscor": [47, 51], "exponential_moving_averag": [47, 51, 67], "softmin": [47, 51, 67, 70, 79, 83], "possible_method": [47, 51], "multilabelscor": [47, 51], "get_class_label_quality_scor": [47, 51], "multilabel_pi": [47, 51], "get_cross_validated_multilabel_pred_prob": [47, 51], "default_k": [47, 53, 54], "features_to_knn": [47, 53, 54], "construct_knn_graph_from_index": [47, 53, 54, 56], "create_knn_graph_and_index": [47, 53, 54], "correct_knn_graph": [47, 53, 54, 97], "correct_knn_distances_and_indices_with_exact_duplicate_sets_inplac": [47, 53, 54], "correct_knn_distances_and_indic": [47, 53, 54], "high_dimension_cutoff": [47, 53, 55], "row_count_cutoff": [47, 53, 55], "decide_euclidean_metr": [47, 53, 55], "decide_default_metr": [47, 53, 55], "construct_knn": [47, 53, 56], "transform_distances_to_scor": [47, 57], "correct_precision_error": [47, 57], "token_classification_util": [47, 110], "get_sent": [47, 58, 110], "filter_sent": [47, 58, 110], "process_token": [47, 58], "merge_prob": [47, 58], "color_sent": [47, 58], "assert_valid_input": [47, 60], "assert_valid_class_label": [47, 60], "assert_nonempty_input": [47, 60], "assert_indexing_work": [47, 60], "labels_to_arrai": [47, 60], "labels_to_list_multilabel": [47, 60], "min_allowed_prob": 48, "wikipedia": 48, "activ": [48, 50, 62, 63, 85, 103], "towardsdatasci": 48, "cheatsheet": 48, "ec57bc067c0b": 48, "clip": [48, 59, 90, 97], "behav": 48, "unnecessari": [48, 99], "slightli": [48, 88, 89], "interv": [48, 51, 106], "herein": 49, "inexact": 49, "cours": [49, 100], "propag": 49, "throughout": [49, 59, 75, 84, 90, 103, 109, 110], "increas": [49, 57, 70, 72, 73, 90, 91, 97, 99, 103, 104, 110], "dot": [49, 83, 99], "true_labels_class_count": 49, "pyx": 49, "multiannot": 50, "assert_valid_inputs_multiannot": 50, "labels_multiannot": [50, 63], "ensembl": [50, 51, 63, 73, 88, 95, 99, 104, 106, 108], "allow_single_label": 50, "annotator_id": 50, "assert_valid_pred_prob": 50, "pred_probs_unlabel": [50, 63], "format_multiannotator_label": [50, 63, 103], "formatted_label": [50, 59], "old": [50, 59, 86, 98], "check_consensus_label_class": 50, "consensus_label": [50, 63, 103], "consensus_method": [50, 63], "consensu": [50, 63, 85, 102, 110], "establish": [50, 62, 89, 108], "compute_soft_cross_entropi": 50, "soft": [50, 98], "find_best_temp_scal": 50, "coarse_search_rang": [50, 75, 99], "fine_search_s": [50, 75, 99], "temperatur": [50, 51, 70, 79, 83], "scale": [50, 57, 88, 97, 98, 99, 106, 109], "factor": [50, 51, 57, 77, 79], "minim": [50, 70, 106], "temp_scale_pred_prob": 50, "temp": 50, "sharpen": [50, 98], "smoothen": 50, "get_normalized_margin_for_each_label": [51, 73], "get_confidence_weighted_entropy_for_each_label": [51, 73], "scorer": 51, "alpha": [51, 67, 70, 91, 92, 97, 101, 104, 108], "exponenti": 51, "ema": 51, "s_1": 51, "s_k": 51, "ema_k": 51, "accord": [51, 65, 95, 96, 101, 110], "formula": [51, 57], "_t": 51, "cdot": 51, "s_t": 51, "qquad": 51, "leq": 51, "_1": 51, "recent": [51, 110], "success": 51, "previou": [51, 54, 93, 95, 99, 105], "discount": 51, "s_ema": 51, "175": [51, 93, 100, 101, 105], "underflow": 51, "nan": [51, 63, 88, 95, 97, 100, 103, 108], "aggregated_scor": 51, "base_scor": [51, 100], "base_scorer_kwarg": 51, "aggregator_kwarg": [51, 67], "n_sampl": [51, 97], "n_label": 51, "class_label_quality_scor": 51, "452": 51, "new_scor": 51, "575": [51, 100], "get_label_quality_scores_per_class": [51, 66, 67], "ml_scorer": 51, "binar": [51, 52], "reformat": [51, 90], "wider": 51, "splitter": 51, "kfold": [51, 93], "onevsrestclassifi": [51, 104], "randomforestclassifi": [51, 101, 104], "n_split": [51, 93, 104], "pred_prob_slic": 52, "onehot": 52, "hot": [52, 65, 71, 77, 80, 88, 95, 98, 99, 108, 109], "onehot_matrix": 52, "pairwis": [53, 55, 72], "reli": [54, 72, 89, 90, 91, 92, 96, 105, 106, 108], "sklearn_knn_kwarg": 54, "correction_featur": 54, "discourag": 54, "flexibl": [54, 99], "manner": [54, 67, 88, 89, 97, 103, 108], "701": 54, "900": [54, 88, 95, 108], "436": [54, 100], "000": [54, 89, 93, 96, 97, 98, 110], "idea": [54, 73, 100, 105], "dens": [54, 62, 97], "33140006": 54, "76210367": 54, "correct_exact_dupl": 54, "mutual": [54, 64, 104], "vari": [54, 70, 92], "exact_duplicate_set": 54, "main": [54, 63], "front": [54, 98], "consider": 54, "capabl": [54, 85, 100], "come": [54, 59, 91, 92, 99, 109], "misidentif": 54, "corrected_dist": 54, "corrected_indic": 54, "sqrt": 54, "distant": 54, "suitabl": [55, 63, 88, 95, 97, 100], "slower": 55, "decid": [55, 63, 89, 96, 98, 103, 108, 110], "predefin": 55, "met": [55, 110], "euclidean_dist": [55, 72], "spatial": [55, 72], "decis": [55, 88, 91, 92, 100], "That": [55, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "cosine_dist": 55, "knn_kwarg": 56, "html": [56, 59, 68, 71, 72, 90, 91, 92, 93, 95, 96, 99, 100, 101], "kneighbor": 56, "metric_param": 56, "n_features_in_": 56, "effective_metric_params_": 56, "effective_metric_": 56, "n_samples_fit_": 56, "__sklearn_is_fitted__": 56, "conduct": 56, "is_fit": 56, "trail": 56, "underscor": 56, "avg_dist": 57, "exp": [57, 72, 73, 91], "dt": 57, "right": [57, 68, 71, 89, 96, 104, 105, 106], "strength": [57, 71, 97], "pronounc": 57, "differenti": 57, "ly": 57, "rule": [57, 58, 85, 98], "thumb": 57, "ood_features_scor": [57, 72, 106], "88988177": 57, "80519832": 57, "toler": 57, "minkowski": 57, "noth": 57, "epsilon": 57, "sensibl": 57, "fixed_scor": 57, "readabl": 58, "lambda": [58, 90, 91, 99, 100, 103], "long_sent": 58, "headlin": 58, "charact": [58, 59], "s1": 58, "s2": 58, "processed_token": 58, "alecnlcb": 58, "entiti": [58, 85, 99, 110], "mapped_ent": 58, "unique_ident": 58, "loc": [58, 91, 92, 93, 95, 97, 110], "nbitbas": [58, 67], "probs_merg": 58, "0125": [58, 83], "0375": 58, "075": 58, "025": 58, "color": [58, 80, 91, 92, 95, 97, 101, 104, 106, 108, 109], "red": [58, 71, 91, 92, 97, 98, 101, 104, 105, 106, 109], "colored_sent": 58, "termcolor": 58, "31msentenc": 58, "0m": 58, "ancillari": 59, "class_without_nois": 59, "any_other_class": 59, "choos": [59, 73, 88, 95, 99, 101, 108], "tradition": 59, "new_sum": 59, "fill": 59, "major": [59, 63, 86, 93, 106], "versu": [59, 101], "obviou": 59, "cgdeboer": 59, "iteround": 59, "reach": 59, "prob_s_eq_1": 59, "claesen": 59, "f1": [59, 71, 96, 101], "BE": 59, "left_nam": 59, "top_nam": 59, "titl": [59, 91, 92, 97, 101, 104, 106], "short_titl": 59, "round_plac": 59, "pretti": [59, 101], "joint_matrix": 59, "num_possible_valu": 59, "holdout_idx": 59, "extract": [59, 72, 89, 90, 95, 96, 100, 103, 106, 109], "allow_shuffl": 59, "turn": [59, 85, 105], "shuffledataset": 59, "histori": 59, "pre_x": 59, "buffer_s": 59, "csr_matric": 59, "append": [59, 90, 93, 98, 99, 100, 101, 103, 104, 105, 106, 110], "bottom": [59, 68, 71, 97, 105], "to_data": 59, "from_data": 59, "taken": 59, "label_matrix": 59, "canon": 59, "displai": [59, 71, 80, 84, 89, 90, 95, 96, 97, 101, 110], "jupyt": [59, 90, 91, 92, 93, 98, 99, 100, 101, 103, 104, 106, 108, 110], "notebook": [59, 63, 90, 92, 98, 99, 100, 101, 103, 104, 105, 107, 109, 110], "consol": 59, "allow_missing_class": 60, "allow_one_class": 60, "length_x": 60, "labellik": 60, "labels_list": [60, 65], "keraswrappermodel": [61, 62, 85], "keraswrappersequenti": [61, 62], "tf": [62, 90], "legaci": 62, "newer": 62, "interim": 62, "advis": [62, 104], "stabil": [62, 72], "until": 62, "accommod": 62, "keraswrapp": 62, "huggingface_keras_imdb": 62, "unit": [62, 110], "model_kwarg": [62, 75], "compile_kwarg": 62, "sparsecategoricalcrossentropi": 62, "layer": [62, 89, 90, 96, 106], "my_keras_model": 62, "from_logit": 62, "declar": 62, "apply_softmax": 62, "analysi": 63, "analyz": [63, 85, 97, 101, 103, 104], "get_label_quality_multiannot": [63, 103], "vote": 63, "crowdsourc": [63, 85, 103], "dawid": [63, 103], "skene": [63, 103], "analog": [63, 98, 103], "chosen": [63, 73, 99, 103], "crowdlab": [63, 103], "unlabel": [63, 93, 103, 106, 109], "get_active_learning_scor": [63, 103], "activelab": [63, 103], "priorit": [63, 70, 105, 109, 110], "showcas": 63, "best_qual": 63, "quality_method": 63, "calibrate_prob": 63, "return_detailed_qu": 63, "return_annotator_stat": 63, "return_weight": 63, "label_quality_score_kwarg": 63, "did": [63, 64, 88, 89, 90, 95, 101, 103, 108], "majority_vot": 63, "broken": [63, 71, 98, 108], "highest": [63, 71, 91, 93, 100, 107], "0th": 63, "consensus_quality_scor": [63, 103], "annotator_agr": [63, 103], "reman": 63, "1st": 63, "2nd": [63, 77], "3rd": 63, "consensus_label_suffix": 63, "consensus_quality_score_suffix": 63, "suffix": 63, "emsembl": 63, "weigh": [63, 98], "agreement": [63, 103], "agre": 63, "prevent": [63, 99], "overconfid": [63, 107], "detailed_label_qu": [63, 103], "annotator_stat": [63, 103], "model_weight": 63, "annotator_weight": 63, "warn": 63, "labels_info": 63, "num_annot": [63, 103], "deriv": [63, 103], "quality_annotator_1": 63, "quality_annotator_2": 63, "quality_annotator_m": 63, "annotator_qu": [63, 103], "num_examples_label": [63, 103], "agreement_with_consensu": [63, 103], "worst_class": [63, 103], "trustworthi": [63, 103, 108], "get_label_quality_multiannotator_ensembl": 63, "weigtht": 63, "budget": 63, "retrain": [63, 89, 108], "active_learning_scor": 63, "active_learning_scores_unlabel": 63, "get_active_learning_scores_ensembl": 63, "henc": [63, 90, 91, 100, 103], "get_majority_vote_label": [63, 103], "event": 63, "lastli": [63, 95], "convert_long_to_wide_dataset": 63, "labels_multiannotator_long": 63, "wide": [63, 88, 89, 90], "labels_multiannotator_wid": 63, "common_multilabel_issu": [64, 66], "exclus": [64, 104], "rank_classes_by_multilabel_qu": [64, 66], "overall_multilabel_health_scor": [64, 66], "multilabel_health_summari": [64, 66], "classes_by_multilabel_qu": 64, "inner": [65, 79, 97], "find_multilabel_issues_per_class": [65, 66], "per_class_label_issu": 65, "label_issues_list": 65, "pred_probs_list": [65, 73, 93, 101], "anim": [66, 106], "rat": 66, "predat": 66, "pet": 66, "reptil": 66, "box": [68, 70, 71, 98, 105], "object_detect": [68, 70, 71, 105], "return_indices_ranked_by_scor": [68, 105], "overlapping_label_check": [68, 70], "suboptim": [68, 70], "locat": [68, 70, 97, 105, 109, 110], "bbox": [68, 71, 105], "image_nam": [68, 71], "y1": [68, 71, 105], "y2": [68, 71, 105], "later": [68, 71, 72, 89, 100, 110], "corner": [68, 71, 105], "xyxi": [68, 71, 105], "io": [68, 71, 90, 97, 98], "keras_cv": [68, 71], "bounding_box": [68, 71, 105], "detectron": [68, 71, 105], "detectron2": [68, 71, 105], "readthedoc": [68, 71], "en": [68, 71], "latest": [68, 71], "draw_box": [68, 71], "mmdetect": [68, 71, 105], "swap": [68, 70, 80, 84], "penal": [68, 70], "concern": [68, 70, 85, 92], "issues_from_scor": [69, 70, 78, 79, 80, 82, 83, 84, 105, 109, 110], "compute_overlooked_box_scor": [69, 70], "compute_badloc_box_scor": [69, 70], "compute_swap_box_scor": [69, 70], "pool_box_scores_per_imag": [69, 70], "object_counts_per_imag": [69, 71, 105], "bounding_box_size_distribut": [69, 71, 105], "class_label_distribut": [69, 71, 105], "get_sorted_bbox_count_idx": [69, 71], "plot_class_size_distribut": [69, 71], "plot_class_distribut": [69, 71], "get_average_per_class_confusion_matrix": [69, 71], "calculate_per_class_metr": [69, 71], "aggregation_weight": 70, "imperfect": [70, 99, 100], "chose": [70, 103, 105], "imperfectli": [70, 105], "dirti": [70, 73, 76, 108], "subtyp": 70, "badloc": 70, "nonneg": 70, "high_probability_threshold": 70, "auxiliary_input": [70, 71], "iou": [70, 71], "heavili": 70, "auxiliarytypesdict": 70, "pred_label": [70, 89], "pred_label_prob": 70, "pred_bbox": 70, "lab_label": 70, "lab_bbox": 70, "similarity_matrix": 70, "min_possible_similar": 70, "scores_overlook": 70, "low_probability_threshold": 70, "scores_badloc": 70, "accident": [70, 89, 95, 96, 99], "scores_swap": 70, "box_scor": 70, "image_scor": [70, 79, 109], "discov": [71, 92, 97, 110], "abnorm": [71, 93, 105], "auxiliari": [71, 106, 109], "_get_valid_inputs_for_compute_scor": 71, "object_count": 71, "down": 71, "bbox_siz": 71, "class_distribut": 71, "plot": [71, 91, 92, 97, 101, 104, 106, 108, 109], "sorted_idx": [71, 106], "class_to_show": 71, "hidden": [71, 106], "max_class_to_show": 71, "plt": [71, 80, 91, 92, 93, 97, 101, 104, 106, 108], "matplotlib": [71, 80, 91, 92, 93, 97, 101, 104, 105, 106, 108], "pyplot": [71, 80, 91, 92, 93, 97, 101, 104, 106, 108], "prediction_threshold": 71, "overlai": [71, 105], "figsiz": [71, 91, 92, 93, 97, 101, 104, 106], "save_path": [71, 105], "blue": [71, 98, 101, 105], "overlaid": 71, "side": [71, 98, 105], "figur": [71, 97, 101, 104, 106, 108], "extens": [71, 101, 103], "png": [71, 105], "pdf": [71, 72], "svg": 71, "num_proc": [71, 93], "intersect": [71, 99], "tp": 71, "fp": 71, "ground": [71, 98, 101, 103, 108], "truth": [71, 101, 103, 108], "bias": [71, 97], "avg_metr": 71, "distionari": 71, "95": [71, 81, 83, 95, 98, 100, 101, 108], "per_class_metr": 71, "Of": 72, "find_top_issu": [72, 73, 106], "behind": [72, 101], "dist_metr": 72, "subtract": [72, 73], "renorm": [72, 73, 99], "least_confid": 72, "sum_": 72, "log": [72, 73, 86], "softmax": [72, 79, 83, 93], "literatur": 72, "gen": 72, "liu": 72, "lochman": 72, "zach": 72, "openaccess": 72, "thecvf": 72, "cvpr2023": 72, "liu_gen_pushing_the_limits_of_softmax": 72, "based_out": 72, "distribution_detection_cvpr_2023_pap": 72, "fit_scor": [72, 106], "ood_predictions_scor": 72, "pretrain": [72, 89, 90, 96, 100, 106], "adjust_confident_threshold": 72, "probabilist": [72, 88, 90, 91, 92, 95, 96, 106, 107], "order_label_issu": [73, 86], "whichev": [73, 107], "argsort": [73, 89, 93, 96, 101, 105, 106, 108], "max_": 73, "get_label_quality_ensemble_scor": [73, 99, 101], "weight_ensemble_members_bi": 73, "custom_weight": 73, "log_loss_search_t_valu": 73, "0001": [73, 98], "scheme": 73, "log_loss_search": 73, "log_loss": [73, 96], "1e0": 73, "1e1": 73, "1e2": 73, "2e2": 73, "quality_scor": [73, 106], "forth": 73, "top_issue_indic": 73, "rank_bi": [73, 86], "weird": [73, 84], "prob_label": 73, "max_prob_not_label": 73, "AND": [73, 96], "get_epistemic_uncertainti": [74, 75], "get_aleatoric_uncertainti": [74, 75], "corrupt": [75, 108], "linearregress": [75, 99, 108], "y_with_nois": 75, "n_boot": [75, 99], "include_aleatoric_uncertainti": [75, 99], "bootstrap": [75, 99, 108], "resampl": [75, 90, 99], "epistem": [75, 99, 106, 108], "aleator": [75, 99, 108], "model_final_kwarg": 75, "coars": 75, "thorough": [75, 99], "fine": [75, 89, 90, 96, 106], "grain": 75, "grid": [75, 100], "varianc": [75, 101], "epistemic_uncertainti": 75, "residu": [75, 76, 99], "deviat": [75, 105, 108], "aleatoric_uncertainti": 75, "outr": 76, "contin": 76, "raw": [76, 85, 86, 92, 93, 98, 99, 100, 103, 105, 106, 108], "aka": [76, 90, 101, 105, 108, 110], "00323821": 76, "33692597": 76, "00191686": 76, "semant": [77, 79, 80, 102], "pixel": [77, 79, 80, 93, 106, 109], "h": [77, 79, 80, 109], "height": [77, 79, 80, 109], "w": [77, 79, 80, 109], "width": [77, 79, 80, 109], "labels_one_hot": [77, 80, 109], "stream": [77, 106, 110], "downsampl": [77, 79, 109], "shrink": [77, 79], "divis": [77, 79, 91], "common_label_issu": [78, 80, 82, 84, 109, 110], "filter_by_class": [78, 80, 109], "segmant": [79, 80], "num_pixel_issu": [79, 109], "product": [79, 93, 97, 99, 100], "pixel_scor": [79, 109], "enter": 80, "legend": [80, 91, 92, 97, 104, 105, 108, 109], "colormap": 80, "background": [80, 97], "person": [80, 99, 105, 109, 110], "ambigu": [80, 84, 89, 90, 96, 98, 101, 110], "misunderstood": [80, 84], "issues_df": [80, 93], "class_index": 80, "issues_subset": [80, 84], "filter_by_token": [82, 84, 110], "token_score_method": 83, "sentence_score_method": 83, "sentence_score_kwarg": 83, "compris": [83, 84], "token_scor": [83, 110], "converg": 83, "toward": [83, 97], "_softmin_sentence_scor": 83, "sentence_scor": [83, 110], "token_info": 83, "02": [83, 91, 92, 97, 101, 105], "03": [83, 95, 97, 98, 100, 101, 105, 110], "04": [83, 95, 97, 105], "08": [83, 97, 101, 105, 108, 110], "commonli": [84, 86, 91, 92, 104, 110], "But": [84, 96, 100, 101, 108, 110], "restrict": [84, 99], "reliabl": [85, 88, 90, 97, 99, 100, 103, 109], "thousand": 85, "imagenet": [85, 98], "popular": [85, 103, 105], "centric": [85, 93, 102], "minut": [85, 88, 89, 90, 95, 96, 98, 103, 104, 105, 108, 109, 110], "conda": 85, "feature_embed": [85, 106], "your_dataset": [85, 90, 91, 92, 93, 95, 96, 99], "column_name_of_label": [85, 90, 91, 92, 93, 95, 96], "tool": [85, 98, 101, 103], "catch": [85, 100], "dive": [85, 96, 97, 100], "plagu": [85, 92], "untrain": 85, "\u30c4": 85, "label_issues_info": [85, 92], "sklearn_compatible_model": 85, "framework": [85, 104, 105], "complianc": 85, "tag": [85, 104, 110], "sequenc": 85, "recognit": [85, 90, 99, 110], "train_data": [85, 88, 89, 106, 108], "gotten": 85, "test_data": [85, 88, 89, 101, 104, 106, 108], "deal": [85, 92, 97, 100], "feel": [85, 90, 92, 99], "ask": [85, 99], "slack": [85, 99], "project": [85, 100, 108], "welcom": 85, "commun": [85, 99], "guidelin": [85, 105], "piec": 85, "smart": [85, 88, 89, 92, 93, 95, 96, 98, 99, 101, 104, 106, 108], "edit": [85, 99, 100], "unreli": [85, 88, 90, 95, 96, 97, 100], "link": [85, 90, 98, 105], "older": 86, "outlin": 86, "substitut": [86, 100], "v2": [86, 88, 95], "get_noise_indic": 86, "psx": 86, "sorted_index_method": 86, "order_label_error": 86, "label_errors_bool": 86, "latent_estim": 86, "num_label_error": 86, "learningwithnoisylabel": 86, "neatli": 86, "organ": [86, 88, 95, 97, 98, 110], "reorgan": 86, "baseline_method": 86, "research": [86, 101], "polyplex": 86, "terminologi": 86, "label_error": 86, "quickstart": [88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 103, 104, 105, 106, 108, 109, 110], "sql": [88, 95], "databas": [88, 95], "excel": [88, 95], "parquet": [88, 95], "student": [88, 95, 100, 108, 110], "grade": [88, 95, 100, 108], "exam": [88, 95, 100, 108], "letter": [88, 95, 110], "hundr": [88, 95], "mistak": [88, 89, 93, 95, 96, 100], "extratreesclassifi": 88, "extratre": 88, "Then": [88, 89, 93, 99], "ranked_label_issu": [88, 89], "branch": [88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108], "standardscal": [88, 95, 100, 106], "labelencod": [88, 89, 100], "train_test_split": [88, 89, 91, 92, 106], "accuracy_scor": [88, 89, 90, 96, 100, 101], "grades_data": [88, 95], "read_csv": [88, 89, 95, 96, 97, 100, 108], "demo": [88, 92, 95, 104], "stud_id": [88, 95, 100], "exam_1": [88, 95, 100, 108], "exam_2": [88, 95, 100, 108], "exam_3": [88, 95, 100, 108], "letter_grad": [88, 95], "f48f73": [88, 95], "53": [88, 91, 92, 95, 97, 98, 100, 104, 105], "00": [88, 91, 92, 95, 97, 98, 100, 106], "77": [88, 91, 92, 95, 100, 105], "0bd4e7": [88, 95], "81": [88, 95, 96, 100, 105, 108, 110], "great": [88, 95, 98, 100], "particip": [88, 95, 100], "cb9d7a": [88, 95], "61": [88, 95, 97, 101, 105, 108], "94": [88, 95, 98, 100, 101, 105, 108], "9acca4": [88, 95], "48": [88, 95, 97, 98, 101, 105], "x_raw": [88, 95], "labels_raw": 88, "interg": [88, 89], "categorical_featur": [88, 108], "x_encod": [88, 95], "get_dummi": [88, 95, 108], "drop_first": [88, 95], "numeric_featur": [88, 95], "scaler": [88, 95, 106], "x_process": [88, 95], "fit_transform": [88, 95, 97, 100], "bring": [88, 89, 93, 95, 96, 103, 108], "byod": [88, 89, 93, 95, 96, 103, 108], "tress": 88, "held": [88, 90, 95, 96, 98, 105, 106, 107], "straightforward": [88, 90, 95], "benefit": [88, 90, 107, 109], "num_crossval_fold": [88, 90, 95, 100, 103], "tabl": [88, 95, 98, 103], "212": [88, 100, 101, 110], "iloc": [88, 89, 90, 95, 96, 100, 108], "92": [88, 91, 100, 101, 105], "93": [88, 98, 100, 105, 108], "827": 88, "99": [88, 97, 98, 100, 101], "86": [88, 92, 93, 95, 100, 101, 105, 108], "74": [88, 97, 100, 105, 108], "637": [88, 95], "79": [88, 98, 100, 105], "65": [88, 91, 97, 100, 105, 110], "cheat": [88, 100], "0pt": [88, 100], "120": [88, 91, 92, 100], "233": 88, "83": [88, 100, 101, 105, 108, 110], "76": [88, 100, 101, 104, 105, 108], "suspici": [88, 95], "carefulli": [88, 93, 95, 96, 100], "examin": [88, 91, 92, 95, 97, 100, 105], "labels_train": 88, "labels_test": 88, "test_siz": [88, 89, 91, 92], "acc_og": [88, 89], "783068783068783": 88, "robustli": [88, 89, 108], "14": [88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "acc_cl": [88, 89], "8095238095238095": 88, "blindli": [88, 89, 90, 99, 100, 108], "trust": [88, 89, 90, 99, 100, 101, 103, 107, 108], "effort": [88, 89, 100, 108], "cumbersom": [88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "intent": [89, 96], "servic": [89, 96, 99], "onlin": [89, 96], "bank": [89, 96, 98], "banking77": [89, 96], "oo": [89, 96], "categori": [89, 93, 96, 97, 100], "shortlist": [89, 96, 108], "scope": [89, 96], "logist": [89, 91, 92, 96, 103, 106], "probabilit": [89, 90], "drop": [89, 95, 97, 99, 100, 103, 108], "sentence_transform": [89, 96], "sentencetransform": [89, 96], "payment": [89, 96], "cancel_transf": [89, 96], "transfer": [89, 96], "fund": [89, 96], "cancel": [89, 96], "transact": [89, 96], "my": [89, 96], "revert": [89, 96], "morn": [89, 96], "realis": [89, 96], "yesterdai": [89, 96], "rent": [89, 96], "tomorrow": [89, 96], "raw_text": [89, 96], "raw_label": 89, "raw_train_text": 89, "raw_test_text": 89, "raw_train_label": 89, "raw_test_label": 89, "beneficiary_not_allow": [89, 96], "change_pin": [89, 96], "card_payment_fee_charg": [89, 96], "apple_pay_or_google_pai": [89, 96], "getting_spare_card": [89, 96], "lost_or_stolen_phon": [89, 96], "card_about_to_expir": [89, 96], "visa_or_mastercard": [89, 96], "supported_cards_and_curr": [89, 96], "card": [89, 96, 98], "utter": [89, 96], "encond": 89, "test_label": [89, 100, 101, 104, 106], "suit": [89, 96, 97, 98, 99], "electra": [89, 96], "discrimin": [89, 96], "googl": [89, 96], "train_text": 89, "test_text": 89, "home": [89, 96, 98], "runner": [89, 96], "google_electra": [89, 96], "pool": [89, 96, 99, 106], "leverag": [89, 90, 96, 99, 101, 103], "computation": [89, 90, 96], "intens": [89, 90, 96], "400": [89, 96, 100], "858371": 89, "547274": 89, "826228": 89, "966008": 89, "792449": 89, "identified_issu": [89, 108], "lowest_quality_label": [89, 90, 96, 101, 108], "to_numpi": [89, 96, 97, 100, 108], "44": [89, 97, 98, 104, 105], "646": 89, "390": 89, "628": 89, "121": [89, 101], "702": 89, "863": 89, "135": 89, "337": [89, 100, 105], "735": 89, "print_as_df": 89, "inverse_transform": 89, "charg": [89, 96], "cash": [89, 96], "holidai": [89, 96], "sent": [89, 96, 97, 110], "mine": [89, 96], "expir": [89, 96], "fight": 89, "hors": [89, 98, 106], "duck": [89, 98], "me": [89, 96, 97], "whoever": [89, 96], "consum": [89, 108], "18": [89, 90, 96, 97, 98, 99, 100, 101, 105, 106, 108, 109], "baseline_model": [89, 108], "87": [89, 92, 93, 100, 105, 108], "acceler": [89, 108], "19": [89, 90, 93, 96, 97, 98, 99, 100, 101, 105, 106, 108, 109, 110], "89": [89, 91, 95, 100, 105, 108], "spoken": 90, "500": [90, 97, 100, 106, 110], "english": [90, 98], "pronunci": 90, "wav": 90, "voxceleb": 90, "speech": [90, 110], "your_pred_prob": [90, 91, 92, 95, 96], "tensorflow_io": 90, "huggingface_hub": 90, "reproduc": [90, 95, 97, 100, 101, 103], "command": 90, "wget": [90, 97, 105, 109, 110], "navig": 90, "browser": 90, "jakobovski": 90, "archiv": [90, 110], "v1": 90, "tar": [90, 106], "gz": [90, 106], "mkdir": [90, 110], "spoken_digit": 90, "xf": 90, "6_nicolas_32": 90, "data_path": 90, "listdir": 90, "nondeterminist": 90, "file_nam": 90, "endswith": 90, "file_path": 90, "join": [90, 93, 97, 99, 100], "7_george_26": 90, "0_nicolas_24": 90, "0_nicolas_6": 90, "listen": 90, "display_exampl": 90, "expand": [90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "pulldown": [90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "colab": [90, 91, 92, 93, 98, 99, 100, 101, 103, 104, 106, 108, 110], "tfio": 90, "pathlib": 90, "ipython": [90, 97], "load_wav_16k_mono": 90, "filenam": 90, "khz": 90, "file_cont": 90, "read_fil": 90, "sample_r": 90, "decode_wav": 90, "desired_channel": 90, "squeez": 90, "rate_in": 90, "rate_out": 90, "16000": 90, "wav_file_nam": 90, "audio_r": 90, "wav_file_exampl": 90, "plai": [90, 98, 99], "button": 90, "wav_file_name_exampl": 90, "7_jackson_43": 90, "hear": 90, "extractor": 90, "encoderclassifi": 90, "spkrec": 90, "xvect": 90, "feature_extractor": 90, "from_hparam": 90, "run_opt": 90, "uncom": [90, 97], "ffmpeg": 90, "backend": 90, "wav_audio_file_path": 90, "torchaudio": 90, "extract_audio_embed": 90, "emb": [90, 93], "signal": 90, "encode_batch": 90, "embeddings_list": [90, 93], "embeddings_arrai": 90, "512": [90, 93], "196311": 90, "319459": 90, "478975": 90, "2890875": 90, "8170238": 90, "89265": 90, "898056": 90, "256195": 90, "559641": 90, "559721": 90, "62067": 90, "285245": 90, "21": [90, 91, 97, 98, 100, 101, 105, 108, 110], "709627": 90, "5033693": 90, "913803": 90, "819831": 90, "1831515": 90, "208763": 90, "084257": 90, "3210397": 90, "005453": 90, "216152": 90, "478235": 90, "6821785": 90, "053807": 90, "242471": 90, "091424": 90, "78334856": 90, "03954": 90, "23": [90, 93, 97, 98, 100, 101, 105, 108], "569176": 90, "761097": 90, "1258295": 90, "753237": 90, "3508866": 90, "598274": 90, "23712": 90, "2500": 90, "tol": 90, "decreas": [90, 99], "cv_accuraci": 90, "9708": 90, "issue_type_descript": [90, 91, 92, 93, 95, 96, 100, 101], "lt": [90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 106], "gt": [90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 110], "9976": 90, "986": 90, "002161": 90, "176": [90, 98, 101, 104], "002483": 90, "2318": 90, "004411": 90, "1005": 90, "004857": 90, "1871": 90, "007494": 90, "040587": 90, "999207": 90, "999377": 90, "975220": 90, "999367": 90, "identified_label_issu": [90, 96], "516": [90, 100], "1946": 90, "469": 90, "2132": 90, "worth": [90, 101], "6_yweweler_25": 90, "7_nicolas_43": 90, "6_theo_27": 90, "6_yweweler_36": 90, "6_yweweler_14": 90, "6_yweweler_35": 90, "6_nicolas_8": 90, "sound": 90, "quit": [90, 106], "underneath": 91, "hood": [91, 97, 99], "alert": 91, "introduct": 91, "mayb": [91, 92, 96], "your_feature_matrix": [91, 92], "toi": [91, 92, 93, 97, 98, 101, 103, 107], "inf": [91, 92], "mid": [91, 92], "bins_map": [91, 92], "create_data": [91, 92], "y_bin": [91, 92], "y_i": [91, 92], "y_bin_idx": [91, 92], "y_train": [91, 92, 101, 108], "y_test": [91, 92, 101, 108], "y_train_idx": [91, 92], "y_test_idx": [91, 92], "slide": [91, 92, 98], "frame": [91, 92], "x_out": [91, 92], "tini": [91, 92], "concaten": [91, 92, 107], "y_out": [91, 92], "y_out_bin": [91, 92], "y_out_bin_idx": [91, 92], "exact_duplicate_idx": [91, 92], "x_duplic": [91, 92], "y_duplic": [91, 92], "y_duplicate_idx": [91, 92], "noisy_labels_idx": [91, 92, 104], "scatter": [91, 92, 97, 101, 104, 108], "black": [91, 92, 98, 108], "cyan": [91, 92], "plot_data": [91, 92, 97, 101, 104, 108], "fig": [91, 92, 93, 98, 106, 108], "ax": [91, 92, 93, 97, 106, 108], "subplot": [91, 92, 93, 106], "set_titl": [91, 92, 93, 106], "set_xlabel": [91, 92], "x_1": [91, 92], "fontsiz": [91, 92, 93, 97, 101, 104], "set_ylabel": [91, 92], "x_2": [91, 92], "set_xlim": [91, 92], "set_ylim": [91, 92], "linestyl": [91, 92, 97], "circl": [91, 92, 101, 104], "misclassifi": [91, 92], "zip": [91, 92, 93, 97, 105, 110], "label_err": [91, 92], "180": [91, 92, 97, 105], "marker": [91, 92], "facecolor": [91, 92, 97], "edgecolor": [91, 92, 97], "linewidth": [91, 92, 97, 106], "dup": [91, 92], "first_legend": [91, 92], "align": [91, 92], "title_fontproperti": [91, 92], "semibold": [91, 92], "second_legend": [91, 92], "45": [91, 92, 97, 98, 100, 101, 105], "gca": [91, 92], "add_artist": [91, 92], "tight_layout": [91, 92, 97], "ideal": [91, 92], "remaind": 91, "modal": [91, 92, 99, 100, 103], "132": [91, 92, 100, 101, 105], "9318": 91, "006940": 91, "007830": 91, "40": [91, 92, 96, 97, 98, 100], "014828": 91, "107": [91, 92, 101, 104], "021241": 91, "026407": 91, "notic": [91, 101, 103, 105], "3558": [91, 92], "126": [91, 92, 101, 105], "006636": [91, 92], "130": [91, 92], "012571": [91, 92], "129": [91, 92], "127": [91, 92, 100], "014909": [91, 92], "128": [91, 92, 93], "017443": [91, 92], "6160": [91, 92], "131": [91, 92, 100, 109], "000000e": [91, 92, 100], "000002": [91, 92], "463180e": [91, 92], "07": [91, 92, 93, 95, 97, 101, 105, 108], "51": [91, 92, 95, 97, 98, 101, 105], "161148": [91, 92], "859087e": [91, 92], "30": [91, 92, 93, 97, 98, 99, 100, 104, 109, 110], "3453": 91, "029542": 91, "031182": 91, "057961": 91, "058244": 91, "54": [91, 97, 98, 101, 105, 110], "039122": 91, "044598": 91, "105": [91, 105], "105196": 91, "133654": 91, "43": [91, 97, 98, 100, 101, 105], "168033": 91, "125": 91, "101107": 91, "183382": 91, "109": [91, 97, 98, 100, 105], "209259": 91, "211042": 91, "221316": 91, "average_ood_scor": 91, "34530442089193386": 91, "52": [91, 97, 98, 100, 105], "169820": 91, "087324e": 91, "259024": 91, "583757e": 91, "91": [91, 100, 105], "346458": 91, "341292e": 91, "specfi": 91, "new_lab": 91, "scoring_funct": 91, "div": 91, "rem": 91, "inv_scal": 91, "49": [91, 97, 98, 101, 105], "superstitionissuemanag": 91, "unlucki": 91, "superstit": 91, "to_seri": 91, "issues_mask": 91, "summary_scor": 91, "9242": 91, "is_superstition_issu": 91, "superstition_scor": 91, "26": [91, 93, 97, 98, 100, 101, 103, 105], "047581": 91, "090635": 91, "129591": 91, "164840": 91, "lurk": [92, 93, 100, 101], "thoroughli": 92, "8561": 92, "001908": 92, "003564": 92, "007331": 92, "008963": 92, "009664": 92, "0227": 92, "022727": 92, "conceptu": 92, "856061": 92, "355772": 92, "616034": 92, "821750": 92, "926818": 92, "betweeen": 92, "859131": 92, "417707": 92, "664083": 92, "970324": 92, "816953": 92, "375317": 92, "641516": 92, "890575": 92, "910232": 92, "531021": 92, "460593": 92, "601188": 92, "826147": 92, "752808": 92, "321635": 92, "562539": 92, "948362": 92, "890169": 92, "090243": 92, "472909": 92, "746763": 92, "878267": 92, "examples_w_issu": [92, 99], "013445": 92, "025184": 92, "026376": 92, "inde": [92, 96], "miscellan": [92, 94, 110], "428571": 92, "111111": 92, "571429": 92, "407407": 92, "592593": 92, "337838": 92, "092593": 92, "662162": 92, "333333": [92, 98], "952381": 92, "666667": [92, 97], "portion": 92, "huge": [92, 101], "worri": [92, 96, 100], "critic": [92, 107], "60": [93, 97, 101, 108], "torchvis": [93, 97, 106], "tensordataset": 93, "stratifiedkfold": [93, 104], "tqdm": 93, "autonotebook": 93, "math": [93, 100], "fashion_mnist": 93, "num_row": 93, "60000": 93, "transformed_dataset": 93, "with_format": 93, "255": [93, 98], "cpu_count": 93, "torch_dataset": 93, "quick": [93, 104, 106], "super": 93, "relu": 93, "batchnorm2d": 93, "maxpool2d": 93, "lazylinear": 93, "flatten": 93, "get_test_accuraci": 93, "testload": [93, 106], "energi": 93, "trainload": [93, 106], "n_epoch": 93, "patienc": 93, "criterion": 93, "crossentropyloss": 93, "adamw": 93, "best_test_accuraci": 93, "start_epoch": 93, "running_loss": 93, "best_epoch": 93, "end_epoch": 93, "3f": [93, 108], "acc": [93, 101], "time_taken": 93, "compute_embed": 93, "compute_pred_prob": 93, "train_batch_s": 93, "num_work": 93, "worker": [93, 110], "train_id_list": 93, "test_id_list": 93, "train_id": 93, "test_id": 93, "embeddings_model": 93, "ntrain": 93, "trainset": 93, "testset": 93, "pin_memori": 93, "fold_embed": 93, "fold_pred_prob": 93, "finish": 93, "482": 93, "720": 93, "999": [93, 96], "329": [93, 95, 100, 105], "88": [93, 98, 100, 101, 104, 105, 108], "195": [93, 97, 100], "733": 93, "493": 93, "060": 93, "330": [93, 100, 105], "505": 93, "772": 93, "476": [93, 100], "340": [93, 100], "210": 93, "328": [93, 105], "310": 93, "693": 93, "reorder": 93, "hstack": [93, 99, 101, 103], "max_preval": [93, 97], "7714": 93, "3772": 93, "3585": 93, "166": 93, "3651": 93, "27080": 93, "873833e": 93, "40378": 93, "915575e": 93, "25316": 93, "390277e": 93, "06": [93, 100, 101, 105, 110], "2090": 93, "751164e": 93, "14999": 93, "881301e": 93, "9569": 93, "11262": 93, "000003": 93, "coat": [93, 98], "shirt": [93, 98], "19228": 93, "000010": 93, "dress": 93, "32657": 93, "000013": 93, "bag": [93, 98, 106, 107], "21282": 93, "000016": [93, 100], "53564": 93, "000018": [93, 100], "pullov": 93, "6321": 93, "30968": 93, "001267": 93, "30659": 93, "000022": [93, 110], "47824": 93, "001454": 93, "3370": 93, "000026": 93, "54565": 93, "001854": 93, "9762": 93, "258": 93, "47139": 93, "000033": 93, "166980": 93, "986195": 93, "997205": 93, "sandal": [93, 98], "948781": 93, "999358": 93, "54078": 93, "17371": 93, "000025": 93, "plot_label_issue_exampl": 93, "nrow": [93, 106], "ceil": [93, 100], "axes_list": 93, "label_issue_indic": 93, "gl": 93, "sl": 93, "fontdict": 93, "imshow": [93, 106], "cmap": [93, 97, 108], "grai": 93, "subplots_adjust": 93, "hspace": 93, "outsiz": 93, "outlier_issu": [93, 96], "outlier_issues_df": 93, "depict": [93, 104, 105, 106, 107, 109], "plot_outlier_issues_exampl": 93, "n_comparison_imag": 93, "sample_from_class": 93, "number_of_sampl": 93, "non_outlier_indic": 93, "isnul": [93, 97], "non_outlier_indices_excluding_curr": 93, "sampled_indic": 93, "label_scores_of_sampl": 93, "top_score_indic": 93, "top_label_indic": 93, "sampled_imag": 93, "get_image_given_label_and_sampl": 93, "image_from_dataset": 93, "corresponding_label": 93, "comparison_imag": 93, "images_to_plot": 93, "idlist": 93, "iterrow": 93, "near_duplicate_issu": [93, 99], "closest": 93, "counterpart": 93, "near_duplicate_issues_df": 93, "plot_near_duplicate_issue_exampl": 93, "seen_id_pair": 93, "get_image_and_given_label_and_predicted_label": 93, "duplicate_imag": 93, "nd_set": 93, "challeng": 93, "dark_issu": 93, "reveal": [93, 105, 109], "dark_issues_df": 93, "is_dark_issu": [93, 97], "34848": 93, "203922": 93, "50270": 93, "204588": 93, "3936": 93, "213098": 93, "217686": 93, "8094": 93, "230118": 93, "plot_image_issue_exampl": 93, "difficult": 93, "disproportion": [93, 97], "lowinfo_issu": 93, "lowinfo_issues_df": 93, "is_low_information_issu": 93, "53050": 93, "067975": 93, "40875": 93, "089929": 93, "9594": 93, "092601": 93, "34825": 93, "107744": 93, "37530": 93, "108516": 93, "lot": 93, "workflow": [94, 99, 100, 102, 108], "histgradientboostingclassifi": 95, "cat_featur": 95, "boost": [95, 99, 103, 108], "xgboost": [95, 99, 100, 108], "think": [95, 96, 99, 104, 109, 110], "nonzero": 95, "358": 95, "941": 95, "294": [95, 105], "46": [95, 97, 98, 100, 101, 105], "7109": 95, "000005": [95, 96], "886": 95, "000059": 95, "709": [95, 100], "000104": 95, "000169": 95, "689": 95, "000181": 95, "3590": 95, "051882e": 95, "683133e": 95, "536582e": 95, "406589e": 95, "324246e": 95, "6165": 95, "582": [95, 100], "185": [95, 97, 98, 105], "187": [95, 98, 100], "898": 95, "0000": [95, 96, 98, 100, 101], "865": 95, "515002": 95, "837": 95, "556480": 95, "622": 95, "593068": 95, "593207": 95, "920": 95, "618041": 95, "4386345844794593e": 95, "issue_result": 95, "000842": 95, "555944": 95, "004374": 95, "sorted_issu": 95, "73": [95, 97, 98, 100, 104, 105, 108], "deserv": 95, "outlier_result": 95, "sorted_outli": 95, "56": [95, 97, 98, 108], "96": [95, 97, 98, 100, 101, 104, 105, 108], "style": [95, 97, 109], "font": 95, "18px": 95, "ff00ff": 95, "bac": 95, "duplicate_result": 95, "lowest_scoring_dupl": 95, "idxmin": [95, 99], "indices_to_displai": 95, "tolist": [95, 99, 100, 104], "perhap": [95, 101, 103], "second_lowest_scoring_dupl": 95, "next_indices_to_displai": 95, "wari": [95, 96, 99], "your_featur": 96, "text_embed": 96, "data_dict": [96, 101, 103], "85": [96, 100, 105], "38": [96, 97, 98, 105], "9710": 96, "981": 96, "974": 96, "000146": 96, "982": [96, 98], "000224": 96, "971": 96, "000507": 96, "980": [96, 98], "000960": 96, "3584": 96, "994": 96, "009642": 96, "013067": 96, "013841": 96, "433": 96, "014722": 96, "989": 96, "018224": 96, "6070": 96, "160": [96, 108], "095724": 96, "148": 96, "006237": 96, "546": [96, 100], "099341": 96, "514": 96, "006485": 96, "481": 96, "123418": 96, "008165": 96, "313": [96, 100, 105], "564102": 96, "572258": 96, "574915": 96, "31": [96, 97, 98, 100, 101, 103, 105], "575507": 96, "575874": 96, "792090": 96, "257611": 96, "698710": 96, "182121": 96, "771619": 96, "data_with_suggested_label": 96, "suggested_label": 96, "withdraw": 96, "monei": 96, "lowest_quality_outli": 96, "OR": 96, "636c65616e6c616220697320617765736f6d6521": 96, "phone": [96, 98], "gone": 96, "samp": 96, "br": 96, "press": [96, 110], "nonsens": 96, "sens": 96, "detriment": 96, "duplicate_issu": 96, "fee": 96, "go": [96, 97, 98, 101], "p_valu": 96, "benign": 96, "curat": [96, 102], "bigger": 97, "make_classif": 97, "5000": [97, 106], "n_featur": 97, "n_inform": 97, "n_redund": 97, "n_repeat": 97, "n_class": 97, "n_clusters_per_class": 97, "flip_i": 97, "class_sep": 97, "faiss": 97, "x_faiss": 97, "float32": [97, 105], "normalize_l2": 97, "index_factori": 97, "hnsw32": 97, "flat": [97, 98], "metric_inner_product": 97, "a_min": 97, "a_max": 97, "create_knn_graph": 97, "assert": 97, "indices_1d": 97, "ravel": 97, "distances_1d": 97, "sort_graph_by_row_valu": 97, "warn_when_not_sort": 97, "50000": 97, "523": [97, 100], "991400": 97, "356958": 97, "362": 97, "619565": 97, "108": [97, 105], "500000": 97, "651838": 97, "999827": 97, "031217": 97, "933716": 97, "627345": 97, "998540": 97, "530909": 97, "296974": 97, "646765": 97, "942721": 97, "332824": 97, "803246": 97, "625202": 97, "999816": 97, "474031": 97, "706253": 97, "655108": 97, "997703": 97, "131466": 97, "912389": 97, "639200": 97, "4995": 97, "998646": 97, "504755": 97, "746777": 97, "680033": 97, "4996": 97, "894230": 97, "340986": 97, "816472": 97, "640711": 97, "4997": 97, "999100": 97, "428545": 97, "592421": 97, "658949": 97, "4998": 97, "986792": 97, "273710": 97, "618033": 97, "4999": 97, "986776": 97, "273524": 97, "618084": 97, "instabl": 97, "proxim": 97, "analys": 97, "comfort": 97, "explor": [97, 105, 106], "third": 97, "parti": [97, 110], "newsgroup": 97, "alt": [97, 98], "atheism": [97, 98], "sci": [97, 98], "fetch_20newsgroup": 97, "newsgroups_train": 97, "header": 97, "footer": 97, "quot": 97, "df_text": 97, "target_nam": 97, "enlighten": 97, "omnipot": 97, "19apr199320262420": 97, "kelvin": 97, "jpl": 97, "nasa": 97, "gov": 97, "baa": 97, "nhenri": 97, "he": 97, "nno": 97, "ge": 97, "nlucki": 97, "babi": [97, 98], "tfidfvector": 97, "feature_extract": 97, "x_vector": 97, "data_valuation_issu": 97, "147": [97, 101, 105], "500047": 97, "500093": 97, "499953": 97, "1068": 97, "1069": 97, "1070": 97, "1071": 97, "1072": 97, "1073": 97, "concentr": 97, "seaborn": 97, "sn": 97, "distinguish": [97, 100], "strip": 97, "stripplot": 97, "hue": [97, 108], "dodg": 97, "jitter": 97, "axvlin": [97, 106], "xlabel": 97, "ourselv": 97, "make_blob": 97, "center": [97, 98], "cluster_std": 97, "n_noisy_label": 97, "meaning": [97, 99, 100, 106], "silhouette_scor": 97, "gridsearchcv": 97, "silhouett": 97, "cluster_label": 97, "fit_predict": 97, "param_grid": [97, 100], "grid_search": 97, "best_kmean": 97, "best_estimator_": 97, "underperforming_group_issu": 97, "328308": 97, "tab10": 97, "domain": 97, "knowledg": [97, 101], "dataset_tsv": 97, "ag": [97, 108], "gender": 97, "educ": 97, "experi": 97, "highsalari": 97, "indiana": 97, "phd": 97, "male": 97, "bachelor": 97, "femal": 97, "kansa": 97, "school": [97, 98], "ohio": 97, "57": [97, 98, 100, 101, 110], "california": 97, "59": [97, 98, 105], "34": [97, 98, 101, 103, 105, 110], "63": [97, 100, 101, 105, 108], "47": [97, 98, 105], "stringio": 97, "sep": [97, 110], "easier": [97, 101], "simplic": [97, 104], "ordinalencod": 97, "columns_to_encod": 97, "encoded_df": 97, "salari": 97, "573681": 97, "underpin": 97, "caught": 97, "whenev": 97, "generate_data_depend": 97, "num_sampl": 97, "a1": 97, "a2": 97, "a3": 97, "375": 97, "975": 97, "non_iid_issu": 97, "796474": 97, "842432": 97, "922562": 97, "820759": 97, "873136": 97, "887373": 97, "825101": 97, "855875": 97, "751795": 97, "835796": 97, "ylabel": [97, 106], "coolwarm": 97, "colorbar": [97, 108], "strong": 97, "evid": [97, 100], "inter": 97, "mitig": 97, "risk": [97, 100], "deeper": 97, "tsv": 97, "tab": 97, "pars": 97, "annual_spend": 97, "number_of_transact": 97, "last_purchase_d": 97, "rural": 97, "4099": 97, "2024": [97, 110], "6421": 97, "nat": 97, "suburban": 97, "5436": 97, "4046": 97, "66": [97, 98, 100], "3467": 97, "67": [97, 98, 100, 105, 108], "4757": 97, "4199": 97, "4991": 97, "4655": 97, "82": [97, 98, 100, 101, 105, 108], "5584": 97, "urban": 97, "3102": 97, "6637": 97, "9167": 97, "6790": 97, "5327": 97, "parse_d": 97, "lose": 97, "intact": 97, "encode_categorical_column": 97, "placehold": 97, "dropna": [97, 103], "category_to_numb": 97, "_encod": 97, "gender_encod": 97, "location_encod": 97, "focus": [97, 100, 101, 103, 104, 108], "null_issu": 97, "833333": 97, "sorted_indic": [97, 105], "sorted_df": 97, "nice": 97, "styler": 97, "combined_df": 97, "concat": [97, 100, 108], "highlight_null_valu": 97, "val": [97, 101], "yellow": [97, 98], "highlight_datalab_column": 97, "lightblu": 97, "highlight_is_null_issu": 97, "orang": [97, 98], "styled_df": 97, "nbsp": [97, 99, 100, 101], "160000": 97, "820000": 97, "460000": 97, "470000": 97, "960000": 97, "620000": 97, "550000": 97, "660000": 97, "670000": [97, 98], "370000": 97, "530000": 97, "710000": 97, "020000": 97, "320000": 97, "990000": 97, "rarer": 97, "fairer": 97, "randomli": [97, 100, 101], "class_imbalance_issu": 97, "countplot": 97, "xtick": 97, "rotat": 97, "ytick": 97, "filtered_df": 97, "xy": 97, "va": 97, "textual": 97, "get_ytick": 97, "nbar": 97, "nimbal": 97, "get_legend_handles_label": 97, "title_fonts": 97, "aspect": 97, "anomali": [97, 105], "enhanc": [97, 101, 103, 105], "artifici": 97, "directori": [97, 110], "subdirectori": 97, "nc": [97, 105, 109, 110], "unzip": [97, 105, 110], "09": [97, 100, 104, 105, 108, 110], "199": [97, 100, 105], "153": [97, 100, 105], "111": [97, 103, 108], "connect": [97, 110], "443": [97, 110], "await": [97, 110], "ok": [97, 107, 110], "986707": 97, "964k": 97, "963": 97, "58k": 97, "kb": [97, 110], "mb": [97, 110], "imagefold": 97, "load_image_dataset": 97, "data_dir": 97, "root": [97, 106], "image_dataset": 97, "img": [97, 106, 108], "from_dict": [97, 99], "darkened_imag": 97, "job": 97, "015": 97, "label_uncorrelatedness_scor": 97, "image_issu": 97, "nimag": 97, "237196": 97, "197229": 97, "254188": 97, "229170": 97, "208907": 97, "793840": 97, "196": [97, 100, 101, 105], "197": [97, 101, 105], "971560": 97, "198": [97, 101, 105], "862236": 97, "973533": 97, "stronger": 97, "frog": [97, 98, 106], "darken": 97, "concept": 97, "notabl": 97, "preval": 97, "warrant": 97, "programmat": 97, "plot_scores_label": 97, "issues_copi": 97, "boxplot": 97, "refin": 98, "instruct": [98, 99, 100], "studi": [98, 105], "mnist_test_set": 98, "imagenet_val_set": 98, "tench": 98, "goldfish": 98, "white": [98, 110], "shark": 98, "tiger": 98, "hammerhead": 98, "electr": 98, "rai": 98, "stingrai": 98, "cock": 98, "hen": 98, "ostrich": 98, "brambl": 98, "goldfinch": 98, "hous": 98, "finch": 98, "junco": 98, "indigo": 98, "bunt": 98, "american": [98, 110], "robin": 98, "bulbul": 98, "jai": 98, "magpi": 98, "chickade": 98, "dipper": 98, "kite": 98, "bald": 98, "eagl": 98, "vultur": 98, "grei": 98, "owl": 98, "salamand": 98, "smooth": 98, "newt": 98, "spot": [98, 99, 105], "axolotl": 98, "bullfrog": 98, "tree": 98, "tail": 98, "loggerhead": 98, "sea": 98, "turtl": 98, "leatherback": 98, "mud": 98, "terrapin": 98, "band": 98, "gecko": 98, "green": [98, 110], "iguana": 98, "carolina": 98, "anol": 98, "desert": 98, "grassland": 98, "whiptail": 98, "lizard": 98, "agama": 98, "frill": 98, "neck": 98, "allig": 98, "gila": 98, "monster": 98, "european": 98, "chameleon": 98, "komodo": 98, "dragon": 98, "nile": 98, "crocodil": 98, "triceratop": 98, "worm": 98, "snake": 98, "ring": 98, "eastern": 98, "hog": 98, "nose": 98, "kingsnak": 98, "garter": 98, "water": 98, "vine": 98, "night": 98, "boa": 98, "constrictor": 98, "african": 98, "rock": 98, "indian": 98, "cobra": 98, "mamba": 98, "saharan": 98, "horn": 98, "viper": 98, "diamondback": 98, "rattlesnak": 98, "sidewind": 98, "trilobit": 98, "harvestman": 98, "scorpion": 98, "garden": 98, "spider": 98, "barn": 98, "southern": 98, "widow": 98, "tarantula": 98, "wolf": 98, "tick": 98, "centiped": 98, "grous": 98, "ptarmigan": 98, "ruf": 98, "prairi": 98, "peacock": 98, "quail": 98, "partridg": 98, "parrot": 98, "macaw": 98, "sulphur": 98, "crest": 98, "cockatoo": 98, "lorikeet": 98, "coucal": 98, "bee": 98, "eater": 98, "hornbil": 98, "hummingbird": 98, "jacamar": 98, "toucan": 98, "breast": 98, "mergans": 98, "goos": 98, "swan": 98, "tusker": 98, "echidna": 98, "platypu": 98, "wallabi": 98, "koala": 98, "wombat": 98, "jellyfish": 98, "anemon": 98, "brain": 98, "coral": 98, "flatworm": 98, "nematod": 98, "conch": 98, "snail": 98, "slug": 98, "chiton": 98, "chamber": 98, "nautilu": 98, "dung": 98, "crab": 98, "fiddler": 98, "king": 98, "lobster": 98, "spini": 98, "crayfish": 98, "hermit": 98, "isopod": 98, "stork": 98, "spoonbil": 98, "flamingo": 98, "heron": 98, "egret": 98, "bittern": 98, "crane": 98, "bird": [98, 106], "limpkin": 98, "gallinul": 98, "coot": 98, "bustard": 98, "ruddi": 98, "turnston": 98, "dunlin": 98, "redshank": 98, "dowitch": 98, "oystercatch": 98, "pelican": 98, "penguin": 98, "albatross": 98, "whale": 98, "killer": 98, "dugong": 98, "lion": 98, "chihuahua": 98, "japanes": 98, "chin": 98, "maltes": 98, "pekinges": 98, "shih": 98, "tzu": 98, "charl": 98, "spaniel": 98, "papillon": 98, "terrier": 98, "rhodesian": 98, "ridgeback": 98, "afghan": [98, 110], "hound": 98, "basset": 98, "beagl": 98, "bloodhound": 98, "bluetick": 98, "coonhound": 98, "tan": 98, "walker": 98, "foxhound": 98, "redbon": 98, "borzoi": 98, "irish": 98, "wolfhound": 98, "italian": 98, "greyhound": 98, "whippet": 98, "ibizan": 98, "norwegian": 98, "elkhound": 98, "otterhound": 98, "saluki": 98, "scottish": 98, "deerhound": 98, "weimaran": 98, "staffordshir": 98, "bull": 98, "bedlington": 98, "border": 98, "kerri": 98, "norfolk": 98, "norwich": 98, "yorkshir": 98, "wire": 98, "fox": 98, "lakeland": 98, "sealyham": 98, "airedal": 98, "cairn": 98, "australian": 98, "dandi": 98, "dinmont": 98, "boston": 98, "miniatur": 98, "schnauzer": 98, "giant": 98, "tibetan": 98, "silki": 98, "wheaten": 98, "west": 98, "highland": 98, "lhasa": 98, "apso": 98, "retriev": 98, "curli": 98, "golden": 98, "labrador": 98, "chesapeak": 98, "bai": 98, "german": [98, 110], "shorthair": 98, "pointer": 98, "vizsla": 98, "setter": 98, "gordon": 98, "brittani": 98, "clumber": 98, "springer": 98, "welsh": 98, "cocker": 98, "sussex": 98, "kuvasz": 98, "schipperk": 98, "groenendael": 98, "malinoi": 98, "briard": 98, "kelpi": 98, "komondor": 98, "sheepdog": 98, "shetland": 98, "colli": 98, "bouvier": 98, "de": 98, "flandr": 98, "rottweil": 98, "shepherd": 98, "dobermann": 98, "pinscher": 98, "swiss": [98, 110], "mountain": 98, "bernes": 98, "appenzel": 98, "sennenhund": 98, "entlebuch": 98, "boxer": 98, "bullmastiff": 98, "mastiff": 98, "french": 98, "bulldog": 98, "dane": 98, "st": 98, "bernard": 98, "huski": 98, "alaskan": 98, "malamut": 98, "siberian": 98, "dalmatian": 98, "affenpinsch": 98, "basenji": 98, "pug": 98, "leonberg": 98, "newfoundland": 98, "pyrenean": 98, "samoi": 98, "pomeranian": 98, "chow": 98, "keeshond": 98, "griffon": 98, "bruxelloi": 98, "pembrok": 98, "corgi": 98, "cardigan": 98, "poodl": 98, "mexican": 98, "hairless": 98, "tundra": 98, "coyot": 98, "dingo": 98, "dhole": 98, "wild": 98, "hyena": 98, "kit": 98, "arctic": 98, "tabbi": 98, "persian": 98, "siames": 98, "egyptian": 98, "mau": 98, "cougar": 98, "lynx": 98, "leopard": 98, "snow": 98, "jaguar": 98, "cheetah": 98, "brown": [98, 109], "bear": 98, "polar": 98, "sloth": 98, "mongoos": 98, "meerkat": 98, "beetl": 98, "ladybug": 98, "longhorn": 98, "leaf": 98, "rhinocero": 98, "weevil": 98, "fly": 98, "ant": 98, "grasshopp": 98, "cricket": 98, "stick": 98, "insect": 98, "cockroach": 98, "manti": 98, "cicada": 98, "leafhopp": 98, "lacew": 98, "dragonfli": 98, "damselfli": 98, "admir": 98, "ringlet": 98, "monarch": 98, "butterfli": 98, "gossam": 98, "wing": 98, "starfish": 98, "urchin": 98, "cucumb": 98, "cottontail": 98, "rabbit": 98, "hare": 98, "angora": 98, "hamster": 98, "porcupin": 98, "squirrel": 98, "marmot": 98, "beaver": 98, "guinea": 98, "pig": 98, "sorrel": 98, "zebra": 98, "boar": 98, "warthog": 98, "hippopotamu": 98, "ox": 98, "buffalo": 98, "bison": 98, "bighorn": 98, "sheep": 98, "alpin": 98, "ibex": 98, "hartebeest": 98, "impala": 98, "gazel": 98, "dromedari": 98, "llama": 98, "weasel": 98, "mink": 98, "polecat": 98, "foot": 98, "ferret": 98, "otter": 98, "skunk": 98, "badger": 98, "armadillo": 98, "toed": 98, "orangutan": 98, "gorilla": 98, "chimpanze": 98, "gibbon": 98, "siamang": 98, "guenon": 98, "pata": 98, "monkei": 98, "baboon": 98, "macaqu": 98, "langur": 98, "colobu": 98, "probosci": 98, "marmoset": 98, "capuchin": 98, "howler": 98, "titi": 98, "geoffroi": 98, "lemur": 98, "indri": 98, "asian": 98, "eleph": 98, "bush": 98, "snoek": 98, "eel": 98, "coho": 98, "salmon": 98, "beauti": 98, "clownfish": 98, "sturgeon": 98, "garfish": 98, "lionfish": 98, "pufferfish": 98, "abacu": 98, "abaya": 98, "academ": 98, "gown": 98, "accordion": 98, "acoust": 98, "guitar": 98, "aircraft": 98, "carrier": 98, "airlin": 98, "airship": 98, "altar": 98, "ambul": 98, "amphibi": 98, "clock": [98, 110], "apiari": 98, "apron": 98, "wast": 98, "assault": 98, "rifl": 98, "backpack": 98, "bakeri": 98, "balanc": 98, "beam": 98, "balloon": 98, "ballpoint": 98, "pen": 98, "aid": 98, "banjo": 98, "balust": 98, "barbel": 98, "barber": 98, "chair": [98, 105], "barbershop": 98, "baromet": 98, "barrel": 98, "wheelbarrow": 98, "basebal": 98, "basketbal": 98, "bassinet": 98, "bassoon": 98, "swim": 98, "cap": 98, "bath": 98, "towel": 98, "bathtub": 98, "station": 98, "wagon": 98, "lighthous": 98, "beaker": 98, "militari": 98, "beer": 98, "bottl": 98, "glass": 98, "bell": 98, "cot": 98, "bib": 98, "bicycl": [98, 109], "bikini": 98, "binder": 98, "binocular": 98, "birdhous": 98, "boathous": 98, "bobsleigh": 98, "bolo": 98, "tie": 98, "poke": 98, "bonnet": 98, "bookcas": 98, "bookstor": 98, "bow": 98, "brass": 98, "bra": 98, "breakwat": 98, "breastplat": 98, "broom": 98, "bucket": 98, "buckl": 98, "bulletproof": 98, "vest": 98, "butcher": 98, "shop": 98, "taxicab": 98, "cauldron": 98, "candl": 98, "cannon": 98, "cano": 98, "mirror": [98, 105], "carousel": 98, "carton": 98, "wheel": 98, "teller": 98, "cassett": 98, "player": 98, "castl": 98, "catamaran": 98, "cd": 98, "cello": 98, "mobil": [98, 110], "chain": 98, "fenc": [98, 109], "mail": 98, "chainsaw": 98, "chest": 98, "chiffoni": 98, "chime": 98, "china": 98, "cabinet": 98, "christma": 98, "stock": 98, "church": 98, "movi": 98, "theater": 98, "cleaver": 98, "cliff": 98, "dwell": 98, "cloak": 98, "clog": 98, "cocktail": 98, "shaker": 98, "coffe": 98, "mug": 98, "coffeemak": 98, "coil": 98, "lock": 98, "keyboard": 98, "confectioneri": 98, "ship": [98, 106], "corkscrew": 98, "cornet": 98, "cowboi": 98, "boot": 98, "hat": 98, "cradl": 98, "crash": 98, "helmet": 98, "crate": 98, "infant": 98, "bed": 98, "crock": 98, "pot": 98, "croquet": 98, "crutch": 98, "cuirass": 98, "dam": 98, "desk": 98, "desktop": 98, "rotari": 98, "dial": 98, "telephon": 98, "diaper": 98, "watch": 98, "dine": 98, "dishcloth": 98, "dishwash": 98, "disc": 98, "brake": 98, "dock": 98, "sled": 98, "dome": 98, "doormat": 98, "drill": 98, "rig": 98, "drum": 98, "drumstick": 98, "dumbbel": 98, "dutch": 98, "oven": 98, "fan": 98, "locomot": 98, "entertain": 98, "envelop": 98, "espresso": 98, "powder": 98, "feather": 98, "fireboat": 98, "engin": [98, 109], "screen": 98, "sheet": 98, "flagpol": 98, "flute": 98, "footbal": 98, "forklift": 98, "fountain": 98, "poster": 98, "freight": 98, "fry": 98, "pan": 98, "fur": 98, "garbag": 98, "ga": 98, "pump": 98, "goblet": 98, "kart": 98, "golf": 98, "cart": 98, "gondola": 98, "gong": 98, "grand": 98, "piano": 98, "greenhous": 98, "grill": 98, "groceri": 98, "guillotin": 98, "barrett": 98, "hair": 98, "sprai": 98, "hammer": 98, "dryer": 98, "hand": [98, 101], "handkerchief": 98, "drive": 98, "harmonica": 98, "harp": 98, "harvest": 98, "hatchet": 98, "holster": 98, "honeycomb": 98, "hoop": 98, "skirt": 98, "horizont": 98, "bar": 98, "drawn": 98, "hourglass": 98, "ipod": 98, "cloth": 98, "iron": 98, "jack": 98, "lantern": 98, "jean": 98, "jeep": 98, "jigsaw": 98, "puzzl": 98, "pull": 98, "rickshaw": 98, "joystick": 98, "kimono": 98, "knee": 98, "pad": 98, "knot": 98, "ladl": 98, "lampshad": 98, "laptop": 98, "lawn": 98, "mower": 98, "knife": 98, "lifeboat": 98, "lighter": 98, "limousin": 98, "ocean": 98, "liner": 98, "lipstick": 98, "slip": 98, "shoe": 98, "lotion": 98, "speaker": 98, "loup": 98, "sawmil": 98, "magnet": 98, "compass": 98, "mailbox": 98, "tight": 98, "tank": 98, "manhol": 98, "maraca": 98, "marimba": 98, "maypol": 98, "maze": 98, "cup": [98, 105], "medicin": 98, "megalith": 98, "microphon": 98, "microwav": 98, "milk": 98, "minibu": 98, "miniskirt": 98, "minivan": 98, "missil": 98, "mitten": [98, 99], "mix": 98, "bowl": 98, "modem": 98, "monasteri": 98, "monitor": 98, "mope": 98, "mortar": 98, "mosqu": 98, "mosquito": 98, "scooter": 98, "bike": 98, "tent": 98, "mous": [98, 99], "mousetrap": 98, "van": 98, "muzzl": 98, "nail": 98, "brace": 98, "necklac": 98, "nippl": 98, "obelisk": 98, "obo": 98, "ocarina": 98, "odomet": 98, "oil": 98, "oscilloscop": 98, "overskirt": 98, "bullock": 98, "oxygen": 98, "packet": 98, "paddl": 98, "padlock": 98, "paintbrush": 98, "pajama": 98, "palac": [98, 110], "parachut": 98, "park": 98, "bench": 98, "meter": 98, "passeng": 98, "patio": 98, "payphon": 98, "pedest": 98, "pencil": 98, "perfum": 98, "petri": 98, "dish": 98, "photocopi": 98, "plectrum": 98, "pickelhaub": 98, "picket": 98, "pickup": 98, "pier": 98, "piggi": 98, "pill": 98, "pillow": 98, "ping": 98, "pong": 98, "pinwheel": 98, "pirat": 98, "pitcher": 98, "plane": 98, "planetarium": 98, "plastic": 98, "plate": 98, "rack": 98, "plow": 98, "plunger": 98, "polaroid": 98, "camera": 98, "pole": [98, 109], "polic": 98, "poncho": 98, "billiard": 98, "soda": 98, "potter": 98, "prayer": 98, "rug": 98, "printer": 98, "prison": 98, "projectil": 98, "projector": 98, "hockei": 98, "puck": 98, "punch": 98, "purs": 98, "quill": 98, "quilt": 98, "race": 98, "racket": 98, "radiat": 98, "radio": 98, "telescop": 98, "rain": 98, "recreat": 98, "reel": 98, "reflex": 98, "refriger": 98, "remot": 98, "restaur": 98, "revolv": 98, "rotisseri": 98, "eras": 98, "rugbi": 98, "ruler": 98, "safe": 98, "safeti": 98, "salt": 98, "sarong": 98, "saxophon": 98, "scabbard": 98, "bu": [98, 109], "schooner": 98, "scoreboard": 98, "crt": 98, "screw": 98, "screwdriv": 98, "seat": 98, "belt": 98, "sew": 98, "shield": 98, "shoji": 98, "basket": 98, "shovel": 98, "shower": 98, "curtain": 98, "ski": 98, "sleep": 98, "door": 98, "slot": 98, "snorkel": 98, "snowmobil": 98, "snowplow": 98, "soap": 98, "dispens": 98, "soccer": [98, 110], "sock": [98, 99], "solar": 98, "thermal": 98, "collector": 98, "sombrero": 98, "soup": 98, "heater": 98, "shuttl": 98, "spatula": 98, "motorboat": 98, "web": 98, "spindl": 98, "sport": [98, 110], "spotlight": 98, "stage": 98, "steam": 98, "arch": 98, "bridg": 98, "steel": 98, "stethoscop": 98, "scarf": 98, "stone": 98, "wall": [98, 109], "stopwatch": 98, "stove": 98, "strainer": 98, "tram": 98, "stretcher": 98, "couch": 98, "stupa": 98, "submarin": 98, "sundial": 98, "sunglass": 98, "sunscreen": 98, "suspens": 98, "mop": 98, "sweatshirt": 98, "swimsuit": 98, "swing": 98, "switch": 98, "syring": 98, "lamp": 98, "tape": 98, "teapot": 98, "teddi": 98, "televis": [98, 110], "tenni": 98, "thatch": 98, "roof": 98, "thimbl": 98, "thresh": 98, "throne": 98, "tile": 98, "toaster": 98, "tobacco": 98, "toilet": 98, "totem": 98, "tow": 98, "tractor": 98, "semi": 98, "trailer": 98, "trai": 98, "trench": 98, "tricycl": 98, "trimaran": 98, "tripod": 98, "triumphal": 98, "trolleybu": 98, "trombon": 98, "tub": 98, "turnstil": 98, "typewrit": 98, "umbrella": 98, "unicycl": 98, "upright": 98, "vacuum": 98, "cleaner": [98, 100], "vase": 98, "vault": 98, "velvet": 98, "vend": 98, "vestment": 98, "viaduct": 98, "violin": 98, "volleybal": 98, "waffl": 98, "wallet": 98, "wardrob": 98, "sink": 98, "wash": 98, "jug": 98, "tower": 98, "whiskei": 98, "whistl": 98, "wig": 98, "shade": [98, 109], "windsor": 98, "wine": 98, "wok": 98, "wooden": 98, "spoon": 98, "wool": 98, "rail": 98, "shipwreck": 98, "yawl": 98, "yurt": 98, "websit": 98, "comic": 98, "book": 98, "crossword": 98, "traffic": [98, 105, 109], "sign": [98, 109, 110], "dust": 98, "jacket": [98, 105], "menu": 98, "guacamol": 98, "consomm": 98, "trifl": 98, "ic": 98, "cream": 98, "pop": 98, "baguett": 98, "bagel": 98, "pretzel": 98, "cheeseburg": 98, "mash": 98, "potato": 98, "cabbag": 98, "broccoli": 98, "cauliflow": 98, "zucchini": 98, "spaghetti": 98, "squash": 98, "acorn": 98, "butternut": 98, "artichok": 98, "pepper": [98, 99], "cardoon": 98, "mushroom": 98, "granni": 98, "smith": 98, "strawberri": 98, "lemon": 98, "pineappl": 98, "banana": 98, "jackfruit": 98, "custard": 98, "appl": 98, "pomegran": 98, "hai": 98, "carbonara": 98, "chocol": 98, "syrup": 98, "dough": 98, "meatloaf": 98, "pizza": 98, "pie": 98, "burrito": 98, "eggnog": 98, "alp": 98, "bubbl": 98, "reef": 98, "geyser": 98, "lakeshor": 98, "promontori": 98, "shoal": 98, "seashor": 98, "vallei": 98, "volcano": 98, "bridegroom": 98, "scuba": 98, "diver": 98, "rapese": 98, "daisi": 98, "ladi": 98, "slipper": 98, "corn": 98, "rose": 98, "hip": 98, "chestnut": 98, "fungu": 98, "agar": 98, "gyromitra": 98, "stinkhorn": 98, "earth": 98, "star": 98, "wood": 98, "bolet": 98, "ear": 98, "cifar10_test_set": 98, "airplan": [98, 106], "automobil": [98, 106], "deer": [98, 106], "cifar100_test_set": 98, "aquarium_fish": 98, "boi": 98, "camel": 98, "caterpillar": 98, "cattl": [98, 110], "cloud": 98, "dinosaur": 98, "dolphin": 98, "flatfish": 98, "forest": 98, "girl": 98, "kangaroo": 98, "lawn_mow": 98, "man": 98, "maple_tre": 98, "motorcycl": [98, 109], "oak_tre": 98, "orchid": 98, "palm_tre": 98, "pear": 98, "pickup_truck": 98, "pine_tre": 98, "plain": 98, "poppi": 98, "possum": 98, "raccoon": 98, "road": [98, 109], "rocket": 98, "seal": 98, "shrew": 98, "skyscrap": 98, "streetcar": 98, "sunflow": 98, "sweet_pepp": 98, "trout": 98, "tulip": 98, "willow_tre": 98, "woman": [98, 105], "caltech256": 98, "ak47": 98, "bat": 98, "glove": 98, "birdbath": 98, "blimp": 98, "bonsai": 98, "boom": 98, "breadmak": 98, "buddha": 98, "bulldoz": 98, "cactu": 98, "cake": 98, "tire": 98, "cartman": 98, "cereal": 98, "chandeli": 98, "chess": 98, "board": 98, "chimp": 98, "chopstick": 98, "coffin": 98, "coin": 98, "comet": 98, "cormor": 98, "globe": 98, "diamond": 98, "dice": 98, "doorknob": 98, "drink": 98, "straw": 98, "dumb": 98, "eiffel": 98, "elk": 98, "ewer": 98, "eyeglass": 98, "fern": 98, "fighter": 98, "jet": [98, 108], "extinguish": 98, "hydrant": 98, "firework": 98, "flashlight": 98, "floppi": 98, "fri": 98, "frisbe": 98, "galaxi": 98, "giraff": 98, "goat": 98, "gate": 98, "grape": 98, "pick": [98, 99], "hamburg": 98, "hammock": 98, "harpsichord": 98, "hawksbil": 98, "helicopt": 98, "hibiscu": 98, "homer": 98, "simpson": 98, "horsesho": 98, "air": 98, "skeleton": 98, "ibi": 98, "cone": 98, "iri": 98, "jesu": 98, "christ": 98, "joi": 98, "kayak": 98, "ketch": 98, "ladder": 98, "lath": 98, "licens": 98, "lightbulb": 98, "lightn": 98, "mandolin": 98, "mar": 98, "mattress": 98, "megaphon": 98, "menorah": 98, "microscop": 98, "minaret": 98, "minotaur": 98, "motorbik": 98, "mussel": 98, "neckti": 98, "octopu": 98, "palm": 98, "pilot": 98, "paperclip": 98, "shredder": 98, "pci": 98, "peopl": [98, 105], "pez": 98, "picnic": 98, "pram": 98, "prai": 98, "pyramid": 98, "rainbow": 98, "roulett": 98, "saddl": 98, "saturn": 98, "segwai": 98, "propel": 98, "sextant": 98, "music": 98, "skateboard": 98, "smokestack": 98, "sneaker": 98, "boat": 98, "stain": 98, "steer": 98, "stirrup": 98, "superman": 98, "sushi": 98, "armi": [98, 110], "sword": 98, "tambourin": 98, "teepe": 98, "court": 98, "theodolit": 98, "tomato": 98, "tombston": 98, "tour": 98, "pisa": 98, "treadmil": 98, "fork": 98, "tweezer": 98, "unicorn": 98, "vcr": 98, "waterfal": 98, "watermelon": 98, "weld": 98, "windmil": 98, "xylophon": 98, "yarmulk": 98, "yo": 98, "toad": 98, "twenty_news_test_set": 98, "comp": 98, "graphic": [98, 109], "misc": [98, 110], "sy": 98, "ibm": 98, "pc": 98, "hardwar": 98, "mac": 98, "forsal": 98, "rec": 98, "crypt": 98, "electron": 98, "med": 98, "soc": 98, "religion": 98, "christian": [98, 110], "talk": [98, 110], "polit": 98, "gun": 98, "mideast": 98, "amazon": 98, "neutral": 98, "imdb_test_set": 98, "all_class": 98, "20news_test_set": 98, "_load_classes_predprobs_label": 98, "dataset_nam": 98, "labelerror": 98, "url_bas": 98, "5392f6c71473055060be3044becdde1cbc18284d": 98, "url_label": 98, "original_test_label": 98, "_original_label": 98, "url_prob": 98, "cross_validated_predicted_prob": 98, "_pyx": 98, "num_part": 98, "datatset": 98, "bytesio": 98, "allow_pickl": 98, "pred_probs_part": 98, "url": 98, "_of_": 98, "nload": 98, "imdb": 98, "ve": [98, 99, 100, 101, 103, 105], "capit": 98, "29780": 98, "256": [98, 99, 100, 105], "780": 98, "medic": [98, 110], "doctor": 98, "254": [98, 105], "359223": 98, "640777": 98, "184": [98, 101], "258427": 98, "341176": 98, "263158": 98, "658824": 98, "337349": 98, "246575": 98, "662651": 98, "248": 98, "330000": 98, "355769": 98, "251": [98, 105], "167": [98, 101, 105], "252": [98, 100], "112": [98, 100], "253": [98, 105], "022989": 98, "049505": 98, "190": [98, 101, 105], "002216": 98, "000974": 98, "000873": 98, "000739": 98, "32635": 98, "32636": 98, "32637": 98, "32638": 98, "32639": 98, "32640": 98, "051": 98, "002242": 98, "997758": 98, "002088": 98, "001045": 98, "997912": 98, "002053": 98, "997947": 98, "001980": 98, "000991": 98, "998020": 98, "001946": 98, "002915": 98, "998054": 98, "001938": 98, "002904": 98, "998062": 98, "001020": 98, "998980": 98, "001018": 98, "002035": 98, "998982": 98, "999009": 98, "0003": 98, "0002": 98, "071": 98, "067269": 98, "929": 98, "046": 98, "058243": 98, "954": 98, "035": 98, "032096": 98, "965": 98, "031": 98, "012232": 98, "969": 98, "022": 98, "025896": 98, "978": 98, "020": [98, 101], "013092": 98, "018": 98, "013065": 98, "016": 98, "030542": 98, "984": 98, "013": 98, "020833": 98, "987": 98, "012": 98, "010020": 98, "988": 98, "0073": 98, "0020": 98, "0016": 98, "0015": 98, "0014": 98, "0013": 98, "0012": 98, "0010": 98, "0008": 98, "0007": 98, "0006": 98, "0005": 98, "0004": 98, "244": [98, 105], "452381": 98, "459770": 98, "523364": 98, "460784": 98, "446602": 98, "103774": 98, "030612": 98, "110092": 98, "049020": 98, "0034": 98, "0032": 98, "0026": 98, "0025": 98, "4945": 98, "4946": 98, "4947": 98, "4948": 98, "4949": 98, "4950": 98, "846": 98, "7532": 98, "532": 98, "034483": 98, "009646": 98, "965517": 98, "030457": 98, "020513": 98, "969543": 98, "028061": 98, "035443": 98, "971939": 98, "025316": 98, "005168": 98, "974684": 98, "049751": 98, "979487": 98, "019920": 98, "042802": 98, "980080": 98, "017677": 98, "005115": 98, "982323": 98, "012987": 98, "005236": 98, "987013": 98, "012723": 98, "025126": 98, "987277": 98, "010989": 98, "008264": 98, "989011": 98, "010283": 98, "027778": 98, "989717": 98, "009677": 98, "990323": 98, "007614": 98, "010127": 98, "992386": 98, "005051": 98, "994949": 98, "005025": 98, "994975": 98, "005013": 98, "994987": 98, "001859": 98, "001328": 98, "000929": 98, "000664": 98, "186": [98, 101], "188": [98, 101, 104], "189": [98, 101], "snippet": 99, "nlp": [99, 110], "mind": [99, 101], "alphanumer": 99, "facilit": 99, "seamless": 99, "classlabel": 99, "guidanc": 99, "labels_str": 99, "datalab_str": 99, "labels_int": 99, "remap": 99, "datalab_int": 99, "my_dict": 99, "pet_nam": 99, "rover": 99, "rocki": 99, "speci": 99, "datalab_dataset": 99, "number_of_class": 99, "total_number_of_data_point": 99, "feed": 99, "alphabet": 99, "labels_proper_format": 99, "your_classifi": 99, "issues_datafram": 99, "class_predicted_for_flagged_exampl": 99, "class_predicted_for_all_exampl": 99, "grant": 99, "On": [99, 100, 101, 105], "merged_dataset": 99, "label_column_nam": 99, "datataset": 99, "fair": [99, 101], "game": 99, "speedup": [99, 106], "tempfil": 99, "mkdtemp": 99, "sped": 99, "anywai": 99, "pred_probs_merg": 99, "merge_rare_class": 99, "count_threshold": 99, "class_mapping_orig2new": 99, "heath_summari": 99, "num_examples_per_class": 99, "rare_class": 99, "num_classes_merg": 99, "other_class": 99, "labels_merg": 99, "new_c": 99, "merged_prob": 99, "new_class": 99, "original_class": 99, "num_check": 99, "ones_array_ref": 99, "isclos": 99, "though": [99, 101, 110], "successfulli": 99, "virtuou": [99, 103], "cycl": [99, 103], "jointli": 99, "junk": 99, "clutter": 99, "unknown": 99, "caltech": 99, "combined_boolean_mask": 99, "mask1": 99, "mask2": 99, "gradientboostingclassifi": [99, 101], "true_error": [99, 101, 104], "101": [99, 100, 105], "102": [99, 104, 105], "104": [99, 101, 105], "model_to_find_error": 99, "model_to_return": 99, "cl0": 99, "randomizedsearchcv": 99, "expens": 99, "param_distribut": 99, "learning_r": [99, 100, 101], "max_depth": [99, 100, 101], "magnitud": 99, "coeffici": [99, 108], "optin": 99, "environ": [99, 100, 101], "rerun": [99, 100, 101], "cell": [99, 100, 101], "unabl": [99, 100, 101], "render": [99, 100, 101], "nbviewer": [99, 100, 101], "cleanlearninginot": [99, 101], "fittedcleanlearn": [99, 101], "linearregressionlinearregress": 99, "unexpectedli": 99, "emphas": 99, "crucial": 99, "merge_duplicate_set": 99, "merge_kei": 99, "construct_group_kei": 99, "merged_set": 99, "consolidate_set": 99, "issubset": 99, "frozenset": [99, 100], "sets_list": 99, "mutabl": 99, "new_set": 99, "current_set": 99, "intersecting_set": 99, "lowest_score_strategi": 99, "sub_df": 99, "filter_near_dupl": 99, "strategy_fn": 99, "strategy_kwarg": 99, "duplicate_row": 99, "group_kei": 99, "to_keep_indic": 99, "groupbi": 99, "explod": 99, "to_remov": 99, "isin": [99, 106], "kept": 99, "ids_to_remove_seri": 99, "assist": 99, "streamlin": [99, 100], "ux": 99, "agpl": 99, "compani": 99, "commerci": 99, "alter": [99, 100], "email": 99, "team": 99, "anywher": 99, "profession": 99, "expert": 99, "recogn": 100, "vital": 100, "leakag": 100, "comparion": 100, "leak": 100, "blueprint": 100, "divers": 100, "parameter": 100, "tldr": 100, "answer": [100, 101], "subtl": 100, "faith": 100, "danger": 100, "inevit": [100, 106], "xgbclassifi": 100, "123456": 100, "df_train": 100, "s3": [100, 105, 109, 110], "amazonaw": [100, 105, 109, 110], "clos_train_data": 100, "df_test": 100, "clos_test_data": 100, "noisy_letter_grad": 100, "018bff": 100, "076d92": 100, "c80059": 100, "e38f8a": 100, "d57e1a": 100, "grade_l": 100, "notes_l": 100, "train_featur": 100, "train_features_v2": 100, "train_labels_v2": 100, "test_featur": 100, "preprocessed_train_data": 100, "preprocessed_test_data": 100, "haven": 100, "features_df": 100, "heterogenou": 100, "full_df": 100, "reset_index": [100, 103], "749": 100, "583745": 100, "291382": 100, "5837": 100, "748": 100, "604": 100, "510": 100, "227": [100, 104, 105], "719": 100, "690": 100, "444": 100, "547": 100, "647": 100, "2914": 100, "611": 100, "687869": 100, "610": 100, "687883": 100, "612": 100, "688146": 100, "609": 100, "688189": 100, "613": 100, "688713": 100, "2913818469137725": 100, "came": [100, 110], "full_duplicate_result": 100, "train_idx_cutoff": 100, "nd_set_has_index_over_training_cutoff": 100, "exact_dupl": 100, "627": 100, "678": 100, "615": 100, "292": 100, "620": 100, "420": 100, "704": 100, "431": 100, "459": 100, "672": 100, "564": 100, "696": 100, "605": 100, "exact_duplicates_indic": 100, "indices_of_duplicates_to_drop": 100, "4a3f75": 100, "d030b5": 100, "ddd0ba": 100, "8e6d24": 100, "464aab": 100, "ee3387": 100, "61e807": 100, "71d7b9": 100, "83e31f": 100, "edeb53": 100, "cd52b5": 100, "84": [100, 105, 108], "454e51": 100, "042686": 100, "12a73f": 100, "tree_method": 100, "hist": [100, 106], "enable_categor": 100, "booster": 100, "callback": 100, "colsample_bylevel": 100, "colsample_bynod": 100, "colsample_bytre": 100, "early_stopping_round": 100, "eval_metr": 100, "feature_typ": 100, "gamma": 100, "grow_polici": 100, "importance_typ": 100, "interaction_constraint": 100, "max_bin": 100, "max_cat_threshold": 100, "max_cat_to_onehot": 100, "max_delta_step": 100, "max_leav": 100, "min_child_weight": 100, "monotone_constraint": 100, "multi_strategi": 100, "n_estim": [100, 101], "num_parallel_tre": 100, "x27": [100, 101], "softprob": 100, "xgbclassifierifittedxgbclassifi": 100, "test_pred_prob": [100, 106], "test_lab": 100, "test_features_arrai": 100, "134": 100, "798507": 100, "370259": 100, "625352": 100, "524042": 100, "097015": 100, "7985": 100, "000537": 100, "000903": 100, "001743": 100, "106": 100, "001853": 100, "002121": 100, "3703": 100, "752463e": 100, "784418e": 100, "477741e": 100, "134230e": 100, "153555e": 100, "6254": 100, "143272": 100, "146501": 100, "161431": 100, "5240": 100, "765240": 100, "771221": 100, "801589": 100, "801652": 100, "810735": 100, "5240417899434826": 100, "0970": 100, "na": [100, 103], "test_label_issue_result": 100, "test_label_issues_ord": 100, "2bd759": 100, "34ccdd": 100, "bb3bab": 100, "103": [100, 101, 105], "bf1b14": 100, "4787de": 100, "865cbd": 100, "32d53f": 100, "5b2f76": 100, "28f8b4": 100, "df814d": 100, "f17261": 100, "1db3ff": 100, "ded944": 100, "124": [100, 105], "343dd3": 100, "homework": [100, 108], "8d904d": 100, "e4f0d5": 100, "d6d208": 100, "76c083": 100, "695f96": 100, "745c23": 100, "13b36e": 100, "5ba892": 100, "9f0216": 100, "003628": 100, "004006": 100, "004031": 100, "007930": 100, "013226": 100, "015255": 100, "017692": 100, "019767": 100, "036197": 100, "054746": 100, "055110": 100, "062675": 100, "112695": 100, "121059": 100, "171280": 100, "181689": 100, "208001": 100, "275028": 100, "346032": 100, "396350": 100, "401493": 100, "474349": 100, "mislead": 100, "breviti": 100, "indices_to_drop_from_test_data": 100, "df_test_clean": 100, "acc_origin": 100, "tediou": 100, "train_features_arrai": 100, "train_lab": 100, "318": [100, 108], "601": 100, "740433": 100, "344154": 100, "588290": 100, "437267": 100, "146423": 100, "977223": 100, "7404": 100, "162": 100, "000072": 100, "348": 100, "000161": 100, "232": [100, 105], "000256": 100, "205": [100, 105], "000458": 100, "000738": 100, "3442": 100, "588": 100, "358961e": 100, "336": [100, 105], "490911e": 100, "269": 100, "122475e": 100, "321": [100, 105], "374139e": 100, "311": 100, "358617e": 100, "5883": 100, "600": 100, "592": 100, "593": 100, "594": 100, "595": 100, "596": 100, "597": 100, "598": 100, "599": 100, "221": 100, "222": [100, 101], "315": 100, "332": [100, 105], "791060e": 100, "243": [100, 105], "540": 100, "379106e": 100, "396": 100, "397": 100, "398": 100, "399": 100, "4373": 100, "165": [100, 104], "550374": 100, "627357": 100, "627496": 100, "627502": 100, "627919": 100, "43726734378061227": 100, "1464": 100, "506": 100, "393": 100, "508": 100, "9772": 100, "402": 100, "401": 100, "aggress": 100, "faithfulli": 100, "label_issue_result": 100, "566": 100, "568": 100, "571": 100, "572": 100, "574": 100, "576": 100, "578": 100, "585": 100, "587": 100, "590": 100, "near_duplicates_idx": 100, "117": [100, 101, 108], "122": [100, 101, 105], "146": 100, "155": [100, 101, 105], "156": [100, 101], "173": [100, 105], "224": [100, 105], "272": 100, "277": [100, 105], "279": [100, 105], "288": 100, "300": [100, 103, 110], "342": 100, "352": 100, "363": 100, "365": 100, "366": 100, "384": 100, "388": 100, "394": 100, "404": 100, "474": 100, "480": 100, "494": 100, "515": 100, "536": 100, "537": 100, "539": 100, "542": 100, "outliers_idx": 100, "143": [100, 104, 105], "159": [100, 104, 105], "163": [100, 101], "193": [100, 101], "194": [100, 101], "208": 100, "240": [100, 105], "241": 100, "242": [100, 105], "247": [100, 105], "287": [100, 105], "295": [100, 105], "299": [100, 105], "307": [100, 105], "350": 100, "361": 100, "378": 100, "379": 100, "392": 100, "419": 100, "432": 100, "479": 100, "484": 100, "485": 100, "489": 100, "492": 100, "504": 100, "511": 100, "522": 100, "535": 100, "543": 100, "567": 100, "579": 100, "591": 100, "idx_to_drop": 100, "276": [100, 105], "df_train_cur": 100, "clean_clf": 100, "clean_pr": 100, "acc_clean": 100, "inaccur": 100, "hybrid": 100, "quantit": 100, "hyper": 100, "default_edit_param": 100, "drop_label_issu": 100, "drop_outli": 100, "drop_near_dupl": 100, "candid": [100, 105], "edit_data": 100, "percentag": [100, 101], "num_label_issues_to_drop": 100, "num_outliers_to_drop": 100, "dedupl": 100, "unique_clust": 100, "unique_clusters_list": 100, "near_duplicates_idx_to_drop": 100, "n_drop": 100, "label_issues_idx_to_drop": 100, "outliers_idx_to_drop": 100, "train_features_clean": 100, "train_labels_clean": 100, "itertool": 100, "finer": 100, "param_combin": 100, "best_scor": 100, "best_param": 100, "train_features_preprocess": 100, "train_labels_preprocess": 100, "depth": 101, "survei": [101, 110], "scienc": 101, "multivariate_norm": [101, 103, 104], "make_data": [101, 103], "cov": [101, 103, 104], "avg_trac": [101, 104], "py_tru": 101, "noise_matrix_tru": 101, "noise_marix": 101, "s_test": 101, "noisy_test_label": 101, "purpl": 101, "namespac": 101, "exec": 101, "markerfacecolor": [101, 104], "markeredgecolor": [101, 104, 108], "markers": [101, 104, 108], "markeredgewidth": [101, 104, 108], "realist": 101, "7560": 101, "637318e": 101, "896262e": 101, "548391e": 101, "923417e": 101, "375075e": 101, "3454": 101, "014051": 101, "020451": 101, "249": [101, 105], "042594": 101, "043859": 101, "045954": 101, "6120": 101, "023714": 101, "007136": 101, "119": [101, 105], "107266": 101, "033738": 101, "238": [101, 105], "119505": 101, "236": [101, 105, 110], "037843": 101, "614915": 101, "624422": 101, "625965": 101, "626079": 101, "118": 101, "627675": 101, "695223": 101, "323529": 101, "523015": 101, "013720": 101, "675727": 101, "646521": 101, "magic": 101, "liter": 101, "identif": 101, "logisticregressionlogisticregress": 101, "ever": 101, "092": 101, "040": 101, "024": 101, "004": 101, "surpris": 101, "1705": 101, "01936": 101, "ton": 101, "yourfavoritemodel1": 101, "merged_label": 101, "merged_test_label": 101, "newli": [101, 103], "yourfavoritemodel2": 101, "yourfavoritemodel3": 101, "cl3": 101, "takeawai": 101, "my_test_pred_prob": 101, "my_test_pr": 101, "issues_test": 101, "corrected_test_label": 101, "pretend": 101, "cl_test_pr": 101, "fairli": 101, "label_acc": 101, "offset": 101, "nquestion": 101, "overestim": 101, "experienc": 101, "prioiri": 101, "known": 101, "versatil": 101, "label_issues_indic": 101, "213": [101, 105], "218": [101, 105], "152": [101, 110], "170": 101, "214": 101, "164": [101, 104], "191": [101, 105], "206": [101, 105], "115": [101, 105], "201": [101, 105], "174": 101, "150": [101, 103, 105, 110], "169": [101, 110], "151": [101, 105], "168": 101, "precision_scor": 101, "recall_scor": 101, "f1_score": 101, "true_label_issu": 101, "filter_by_list": 101, "718750": [101, 103], "807018": 101, "912": 101, "733333": 101, "800000": 101, "721311": 101, "792793": 101, "908": 101, "676923": 101, "765217": 101, "892": 101, "567901": 101, "702290": 101, "844": 101, "gaug": 101, "label_issues_count": 101, "172": [101, 104], "157": 101, "easiest": 101, "modular": 101, "penalti": 101, "l2": 101, "model3": 101, "cv_pred_probs_1": 101, "cv_pred_probs_2": 101, "cv_pred_probs_3": 101, "label_quality_scores_best": 101, "cv_pred_probs_ensembl": 101, "label_quality_scores_bett": 101, "superior": [101, 107], "timm": 102, "glad": 103, "multiannotator_label": 103, "noisier": 103, "local_data": [103, 104], "true_labels_train": [103, 104], "noise_matrix_bett": 103, "noise_matrix_wors": 103, "transpos": [103, 106], "zfill": 103, "row_na_check": 103, "notna": 103, "a0001": 103, "a0002": 103, "a0003": 103, "a0004": 103, "a0005": 103, "a0006": 103, "a0007": 103, "a0008": 103, "a0009": 103, "a0010": 103, "a0041": 103, "a0042": 103, "a0043": 103, "a0044": 103, "a0045": 103, "a0046": 103, "a0047": 103, "a0048": 103, "a0049": 103, "a0050": 103, "60856743": 103, "41693214": 103, "40908785": 103, "87147629": 103, "64941785": 103, "10774851": 103, "0524466": 103, "71853246": 103, "37169848": 103, "66031048": 103, "multiannotator_util": 103, "crude": 103, "straight": 103, "majority_vote_label": 103, "736118": 103, "757751": 103, "782232": 103, "715565": 103, "824256": 103, "quality_annotator_a0001": 103, "quality_annotator_a0002": 103, "quality_annotator_a0003": 103, "quality_annotator_a0004": 103, "quality_annotator_a0005": 103, "quality_annotator_a0006": 103, "quality_annotator_a0007": 103, "quality_annotator_a0008": 103, "quality_annotator_a0009": 103, "quality_annotator_a0010": 103, "quality_annotator_a0041": 103, "quality_annotator_a0042": 103, "quality_annotator_a0043": 103, "quality_annotator_a0044": 103, "quality_annotator_a0045": 103, "quality_annotator_a0046": 103, "quality_annotator_a0047": 103, "quality_annotator_a0048": 103, "quality_annotator_a0049": 103, "quality_annotator_a0050": 103, "070564": 103, "216078": 103, "119188": 103, "alongisd": 103, "244981": 103, "208333": 103, "295979": 103, "294118": 103, "324197": 103, "310345": 103, "355316": 103, "346154": 103, "439732": 103, "480000": 103, "a0031": 103, "523205": 103, "580645": 103, "a0034": 103, "535313": 103, "607143": 103, "a0021": 103, "606999": 103, "a0015": 103, "609526": 103, "678571": 103, "a0011": 103, "621103": 103, "692308": 103, "improved_consensus_label": 103, "majority_vote_accuraci": 103, "cleanlab_label_accuraci": 103, "8581081081081081": 103, "9797297297297297": 103, "besid": 103, "sorted_consensus_quality_scor": 103, "worst_qual": 103, "better_qu": 103, "worst_quality_accuraci": 103, "better_quality_accuraci": 103, "9893238434163701": 103, "improved_pred_prob": 103, "treat": [103, 104, 108, 110], "analzi": 103, "copyright": 104, "advertis": 104, "violenc": 104, "nsfw": 104, "celeba": 104, "make_multilabel_data": 104, "boxes_coordin": 104, "box_multilabel": 104, "make_multi": 104, "bx1": 104, "by1": 104, "bx2": 104, "by2": 104, "label_list": 104, "ur": 104, "upper": 104, "inidx": 104, "logical_and": 104, "inv_d": 104, "labels_idx": 104, "true_labels_test": 104, "dict_unique_label": 104, "get_color_arrai": 104, "dcolor": 104, "aa4400": 104, "55227f": 104, "55a100": 104, "00ff00": 104, "007f7f": 104, "386b55": 104, "0000ff": 104, "y_onehot": 104, "single_class_label": 104, "stratifi": [104, 107], "kf": 104, "train_index": 104, "test_index": 104, "clf_cv": 104, "x_train_cv": 104, "x_test_cv": 104, "y_train_cv": 104, "y_test_cv": 104, "y_pred_cv": 104, "saw": 104, "num_to_displai": 104, "275": 104, "267": 104, "225": 104, "171": 104, "234": 104, "262": [104, 105], "263": [104, 105], "266": [104, 105], "139": 104, "216": [104, 105], "265": 104, "despit": [104, 110], "suspect": 104, "888": 104, "8224": 104, "9632": 104, "968": 104, "6512": 104, "0444": 104, "774": 104, "labels_binary_format": 104, "labels_list_format": 104, "surround": 105, "scene": 105, "coco": 105, "everydai": 105, "has_label_issu": 105, "objectdetectionbenchmark": 105, "tutorial_obj": 105, "pkl": 105, "example_imag": 105, "_separate_label": 105, "_separate_predict": 105, "begin": 105, "image_path": 105, "rb": 105, "image_to_visu": 105, "seg_map": 105, "334": 105, "bboxes_ignor": 105, "290": 105, "286": 105, "285": 105, "231": [105, 110], "293": 105, "235": 105, "289": 105, "282": 105, "281": 105, "271": 105, "280": 105, "326": 105, "333": 105, "261": 105, "319": 105, "257": 105, "283": 105, "303": 105, "316": 105, "323": 105, "327": 105, "226": 105, "228": [105, 110], "219": 105, "239": 105, "209": 105, "202": 105, "230": 105, "215": 105, "220": 105, "229": 105, "217": 105, "237": 105, "207": 105, "204": 105, "223": 105, "149": 105, "140": 105, "246": 105, "268": 105, "273": 105, "284": 105, "110": 105, "136": 105, "145": 105, "297": 105, "317": 105, "192": 105, "324": 105, "203": 105, "320": 105, "314": 105, "291": 105, "000000481413": 105, "jpg": 105, "42398": 105, "44503": 105, "29968": 105, "21005": 105, "9978472": 105, "forgot": 105, "drew": 105, "label_issue_idx": 105, "num_examples_to_show": 105, "138": 105, "97489622": 105, "70610878": 105, "98764951": 105, "88899237": 105, "99085805": 105, "issue_idx": 105, "95569726e": 105, "03354841e": 105, "57510169e": 105, "58447666e": 105, "39755858e": 105, "issue_to_visu": 105, "000000009483": 105, "95569726168054e": 105, "addition": [105, 109], "visibl": 105, "missmatch": 105, "likelei": 105, "agnost": 105, "vaidat": 105, "inconsist": 105, "000000395701": 105, "033548411774308e": 105, "armchair": 105, "tv": 105, "000000154004": 105, "38300759625496356": 105, "foreground": 105, "000000448410": 105, "0008575101690203273": 105, "crowd": 105, "alon": 105, "resembl": [105, 106], "000000499768": 105, "9748962231208227": 105, "000000521141": 105, "8889923658893665": 105, "000000143931": 105, "9876495074395956": 105, "bonu": 105, "uncov": 105, "irregular": 105, "object_detection_util": 105, "calculate_bounding_box_area": 105, "num_imgs_to_show": 105, "lab_object_count": 105, "pred_object_count": 105, "000000430073": 105, "000000183709": 105, "000000189475": 105, "label_norm": 105, "pred_norm": 105, "area": [105, 109], "lab_area": 105, "pred_area": 105, "lab_area_mean": 105, "lab_area_std": 105, "max_deviation_valu": 105, "max_deviation_class": 105, "deviation_valu": 105, "deviation_class": 105, "mean_area": 105, "std_area": 105, "class_area": 105, "deviations_awai": 105, "max_deviation_index": 105, "num_imgs_to_show_per_class": 105, "class_num": 105, "000000422886": 105, "000000341828": 105, "000000461009": 105, "train_feature_embed": 106, "ood_train_feature_scor": 106, "test_feature_embed": 106, "ood_test_feature_scor": 106, "ood_train_predictions_scor": 106, "train_pred_prob": 106, "ood_test_predictions_scor": 106, "pylab": 106, "rcparam": 106, "baggingclassifi": 106, "therebi": 106, "rescal": 106, "transform_norm": 106, "totensor": 106, "animal_class": 106, "non_animal_class": 106, "animal_idx": 106, "test_idx": 106, "toronto": 106, "edu": 106, "kriz": 106, "170498071": 106, "99832064": 106, "92it": 106, "plot_imag": 106, "visualize_outli": 106, "txt_class": 106, "npimg": 106, "show_label": 106, "data_subset": 106, "resnet50": 106, "corpu": 106, "2048": 106, "embed_imag": 106, "create_model": 106, "strang": 106, "odd": 106, "train_ood_features_scor": 106, "top_train_ood_features_idx": 106, "fun": 106, "negat": 106, "homogen": 106, "bottom_train_ood_features_idx": 106, "test_ood_features_scor": 106, "top_ood_features_idx": 106, "trade": 106, "5th": 106, "percentil": 106, "fifth_percentil": 106, "plt_rang": 106, "train_outlier_scor": 106, "test_outlier_scor": 106, "ood_features_indic": 106, "revisit": 106, "return_invers": 106, "train_feature_embeddings_sc": 106, "test_feature_embeddings_sc": 106, "train_pred_label": 106, "9702": 106, "train_ood_predictions_scor": 106, "test_ood_predictions_scor": 106, "lost": 106, "unsuit": 107, "convention": 107, "aforement": 107, "hypothet": 107, "contrast": 107, "tradit": 107, "disjoint": 107, "out_of_sample_pred_probs_for_a": 107, "out_of_sample_pred_probs_for_b": 107, "out_of_sample_pred_probs_for_c": 107, "out_of_sample_pred_prob": 107, "unsur": 107, "price": 108, "incom": 108, "sensor": 108, "histgradientboostingregressor": 108, "r2_score": 108, "student_grades_r": 108, "final_scor": 108, "true_final_scor": 108, "3d": 108, "mpl_toolkit": 108, "mplot3d": 108, "axes3d": 108, "errors_idx": 108, "add_subplot": 108, "z": 108, "errors_mask": 108, "feature_column": 108, "predicted_column": 108, "x_train_raw": 108, "x_test_raw": 108, "randomforestregressor": 108, "385101": 108, "499503": 108, "698255": 108, "776647": 108, "109373": 108, "170547": 108, "481096": 108, "984759": 108, "645270": 108, "795928": 108, "141": 108, "659": 108, "367": 108, "305": 108, "560": 108, "657": 108, "view_datapoint": 108, "preds_og": 108, "r2_og": 108, "838": 108, "found_label_issu": 108, "preds_cl": 108, "r2_cl": 108, "926": 108, "favorit": 108, "968627e": 108, "228799": 108, "646674e": 108, "402962": 108, "323818e": 108, "952758": 108, "422144e": 108, "456908": 108, "465815e": 108, "753968": 108, "791186e": 108, "110719": 108, "485156e": 108, "670640": 108, "225300e": 108, "749976": 108, "499679e": 108, "947007": 108, "067882e": 108, "648396": 108, "synthia": 109, "imagesegment": 109, "given_mask": 109, "predicted_mask": 109, "set_printopt": [109, 110], "sky": 109, "sidewalk": 109, "veget": 109, "terrain": 109, "rider": 109, "pred_probs_filepath": 109, "1088": 109, "1920": 109, "label_filepath": 109, "synthia_class": 109, "maunal": 109, "100000": 109, "244800": 109, "leftmost": 109, "middl": [109, 110], "infact": 109, "rightmost": 109, "discrep": 109, "3263230": 109, "783381": 109, "275110": 109, "255917": 109, "78225": 109, "55990": 109, "54315": 109, "33591": 109, "24645": 109, "21054": 109, "15045": 109, "14171": 109, "13832": 109, "13498": 109, "11490": 109, "9164": 109, "8769": 109, "6999": 109, "6031": 109, "5011": 109, "mistakenli": 109, "class_issu": 109, "aim": [109, 110], "domin": 109, "bunch": 110, "conll": 110, "2003": 110, "love": 110, "n_i": 110, "optional_list_of_ordered_class_nam": 110, "deepai": 110, "conll2003": 110, "rm": 110, "tokenclassif": 110, "2400": 110, "52e0": 110, "1a00": 110, "1067": 110, "982975": 110, "960k": 110, "959": 110, "94k": 110, "inflat": 110, "17045998": 110, "16m": 110, "octet": 110, "26m": 110, "bert": 110, "read_npz": 110, "filepath": 110, "corrsespond": 110, "iob2": 110, "given_ent": 110, "entity_map": 110, "readfil": 110, "startswith": 110, "docstart": 110, "isalpha": 110, "isupp": 110, "indices_to_preview": 110, "nsentenc": 110, "eu": 110, "reject": 110, "boycott": 110, "british": 110, "lamb": 110, "00030412": 110, "00023826": 110, "99936208": 110, "00007009": 110, "00002545": 110, "99998795": 110, "00000401": 110, "00000218": 110, "00000455": 110, "00000131": 110, "00000749": 110, "99996115": 110, "00001371": 110, "0000087": 110, "00000895": 110, "99998936": 110, "00000382": 110, "00000178": 110, "00000366": 110, "00000137": 110, "99999101": 110, "00000266": 110, "00000174": 110, "0000035": 110, "00000109": 110, "99998768": 110, "00000482": 110, "00000202": 110, "00000438": 110, "0000011": 110, "00000465": 110, "99996392": 110, "00001105": 110, "0000116": 110, "00000878": 110, "99998671": 110, "00000364": 110, "00000213": 110, "00000472": 110, "00000281": 110, "99999073": 110, "00000211": 110, "00000159": 110, "00000442": 110, "00000115": 110, "peter": 110, "blackburn": 110, "00000358": 110, "00000529": 110, "99995623": 110, "0000129": 110, "0000024": 110, "00001812": 110, "99994141": 110, "00001645": 110, "00002162": 110, "brussel": 110, "1996": 110, "00001172": 110, "00000821": 110, "00004661": 110, "0000618": 110, "99987167": 110, "99999061": 110, "00000201": 110, "00000195": 110, "00000408": 110, "00000135": 110, "2254": 110, "2907": 110, "19392": 110, "9962": 110, "8904": 110, "19303": 110, "12918": 110, "9256": 110, "11855": 110, "18392": 110, "20426": 110, "19402": 110, "14744": 110, "19371": 110, "4645": 110, "10331": 110, "9430": 110, "6143": 110, "18367": 110, "12914": 110, "todai": 110, "weather": 110, "march": 110, "scalfaro": 110, "northern": 110, "himself": 110, "said": 110, "germani": 110, "nastja": 110, "rysich": 110, "north": 110, "spla": 110, "fought": 110, "khartoum": 110, "govern": 110, "south": 110, "1983": 110, "autonomi": 110, "animist": 110, "region": 110, "moslem": 110, "arabis": 110, "mayor": 110, "antonio": 110, "gonzalez": 110, "garcia": 110, "revolutionari": 110, "wednesdai": 110, "troop": 110, "raid": 110, "farm": 110, "stole": 110, "rape": 110, "women": 110, "spring": 110, "chg": 110, "hrw": 110, "12pct": 110, "princ": 110, "photo": 110, "moment": 110, "spokeswoman": 110, "rainier": 110, "told": 110, "reuter": 110, "danila": 110, "carib": 110, "w224": 110, "equip": 110, "radiomet": 110, "earn": 110, "19996": 110, "london": 110, "denom": 110, "sale": 110, "uk": 110, "jp": 110, "fr": 110, "maccabi": 110, "hapoel": 110, "haifa": 110, "tel": 110, "aviv": 110, "hospit": 110, "rever": 110, "roman": 110, "cathol": 110, "nun": 110, "admit": 110, "calcutta": 110, "week": 110, "ago": 110, "fever": 110, "vomit": 110, "allianc": 110, "embattl": 110, "kabul": 110, "salang": 110, "highwai": 110, "mondai": 110, "tuesdai": 110, "suprem": 110, "council": 110, "led": 110, "jumbish": 110, "milli": 110, "movement": 110, "warlord": 110, "abdul": 110, "rashid": 110, "dostum": 110, "dollar": 110, "exchang": 110, "3570": 110, "12049": 110, "born": 110, "1937": 110, "provinc": 110, "anhui": 110, "dai": 110, "shanghai": 110, "citi": 110, "prolif": 110, "author": 110, "teacher": 110, "chines": 110, "16764": 110, "1990": 110, "historian": 110, "alan": 110, "john": 110, "percival": 110, "taylor": 110, "di": 110, "20446": 110, "pace": 110, "bowler": 110, "ian": 110, "harvei": 110, "claim": 110, "victoria": 110, "15514": 110, "cotti": 110, "osc": 110, "foreign": 110, "minist": 110, "7525": 110, "sultan": 110, "specter": 110, "crown": 110, "abdullah": 110, "defenc": 110, "aviat": 110, "jeddah": 110, "saudi": 110, "agenc": 110, "2288": 110, "hi": 110, "customari": 110, "outfit": 110, "champion": 110, "damp": 110, "scalp": 110, "canada": 110, "reign": 110, "olymp": 110, "donovan": 110, "bailei": 110, "1992": 110, "linford": 110, "christi": 110, "britain": 110, "1984": 110, "1988": 110, "carl": 110, "lewi": 110, "ambigi": 110, "punctuat": 110, "chicago": 110, "digest": 110, "philadelphia": 110, "usda": 110, "york": 110, "token_issu": 110, "471": 110, "kean": 110, "year": 110, "contract": 110, "manchest": 110, "19072": 110, "societi": 110, "bite": 110, "deliv": 110, "19910": 110, "father": 110, "clarenc": 110, "woolmer": 110, "renam": 110, "uttar": 110, "pradesh": 110, "india": 110, "ranji": 110, "trophi": 110, "nation": 110, "championship": 110, "captain": 110, "1949": 110, "15658": 110, "19879": 110, "iii": 110, "brian": 110, "shimer": 110, "randi": 110, "jone": 110, "19104": 110}, "objects": {"cleanlab": [[0, 0, 0, "-", "benchmarking"], [2, 0, 0, "-", "classification"], [3, 0, 0, "-", "count"], [4, 0, 0, "-", "data_valuation"], [12, 0, 0, "-", "datalab"], [39, 0, 0, "-", "dataset"], [42, 0, 0, "-", "experimental"], [46, 0, 0, "-", "filter"], [47, 0, 0, "-", "internal"], [61, 0, 0, "-", "models"], [63, 0, 0, "-", "multiannotator"], [66, 0, 0, "-", "multilabel_classification"], [69, 0, 0, "-", "object_detection"], [72, 0, 0, "-", "outlier"], [73, 0, 0, "-", "rank"], [74, 0, 0, "-", "regression"], [78, 0, 0, "-", "segmentation"], [82, 0, 0, "-", "token_classification"]], "cleanlab.benchmarking": [[1, 0, 0, "-", "noise_generation"]], "cleanlab.benchmarking.noise_generation": [[1, 1, 1, "", "generate_n_rand_probabilities_that_sum_to_m"], [1, 1, 1, "", "generate_noise_matrix_from_trace"], [1, 1, 1, "", "generate_noisy_labels"], [1, 1, 1, "", "noise_matrix_is_valid"], [1, 1, 1, "", "randomly_distribute_N_balls_into_K_bins"]], "cleanlab.classification": [[2, 2, 1, "", "CleanLearning"]], "cleanlab.classification.CleanLearning": [[2, 3, 1, "", "__init_subclass__"], [2, 3, 1, "", "find_label_issues"], [2, 3, 1, "", "fit"], [2, 3, 1, "", "get_label_issues"], [2, 3, 1, "", "get_metadata_routing"], [2, 3, 1, "", "get_params"], [2, 3, 1, "", "predict"], [2, 3, 1, "", "predict_proba"], [2, 3, 1, "", "save_space"], [2, 3, 1, "", "score"], [2, 3, 1, "", "set_fit_request"], [2, 3, 1, "", "set_params"], [2, 3, 1, "", "set_score_request"]], "cleanlab.count": [[3, 1, 1, "", "calibrate_confident_joint"], [3, 1, 1, "", "compute_confident_joint"], [3, 1, 1, "", "estimate_confident_joint_and_cv_pred_proba"], [3, 1, 1, "", "estimate_cv_predicted_probabilities"], [3, 1, 1, "", "estimate_joint"], [3, 1, 1, "", "estimate_latent"], [3, 1, 1, "", "estimate_noise_matrices"], [3, 1, 1, "", "estimate_py_and_noise_matrices_from_probabilities"], [3, 1, 1, "", "estimate_py_noise_matrices_and_cv_pred_proba"], [3, 1, 1, "", "get_confident_thresholds"], [3, 1, 1, "", "num_label_issues"]], "cleanlab.data_valuation": [[4, 1, 1, "", "data_shapley_knn"]], "cleanlab.datalab": [[5, 0, 0, "-", "datalab"], [18, 0, 0, "-", "internal"]], "cleanlab.datalab.datalab": [[5, 2, 1, "", "Datalab"]], "cleanlab.datalab.datalab.Datalab": [[5, 4, 1, "", "class_names"], [5, 3, 1, "", "find_issues"], [5, 3, 1, "", "get_info"], [5, 3, 1, "", "get_issue_summary"], [5, 3, 1, "", "get_issues"], [5, 4, 1, "", "has_labels"], [5, 4, 1, "", "info"], [5, 4, 1, "", "issue_summary"], [5, 4, 1, "", "issues"], [5, 4, 1, "", "labels"], [5, 3, 1, "", "list_default_issue_types"], [5, 3, 1, "", "list_possible_issue_types"], [5, 3, 1, "", "load"], [5, 3, 1, "", "report"], [5, 3, 1, "", "save"]], "cleanlab.datalab.internal.adapter": [[13, 0, 0, "-", "imagelab"]], "cleanlab.datalab.internal.adapter.imagelab": [[13, 2, 1, "", "CorrelationReporter"], [13, 2, 1, "", "CorrelationVisualizer"], [13, 2, 1, "", "ImagelabDataIssuesAdapter"], [13, 2, 1, "", "ImagelabIssueFinderAdapter"], [13, 2, 1, "", "ImagelabReporterAdapter"], [13, 1, 1, "", "create_imagelab"], [13, 1, 1, "", "handle_spurious_correlations"]], "cleanlab.datalab.internal.adapter.imagelab.CorrelationReporter": [[13, 3, 1, "", "report"]], "cleanlab.datalab.internal.adapter.imagelab.CorrelationVisualizer": [[13, 3, 1, "", "visualize"]], "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter": [[13, 3, 1, "", "collect_issues_from_imagelab"], [13, 3, 1, "", "collect_issues_from_issue_manager"], [13, 3, 1, "", "collect_statistics"], [13, 3, 1, "", "filter_based_on_max_prevalence"], [13, 3, 1, "", "get_info"], [13, 3, 1, "", "get_issue_summary"], [13, 3, 1, "", "get_issues"], [13, 3, 1, "", "set_health_score"], [13, 4, 1, "", "statistics"]], "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter": [[13, 3, 1, "", "find_issues"], [13, 3, 1, "", "get_available_issue_types"]], "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter": [[13, 3, 1, "", "get_report"], [13, 3, 1, "", "report"]], "cleanlab.datalab.internal": [[15, 0, 0, "-", "data"], [16, 0, 0, "-", "data_issues"], [19, 0, 0, "-", "issue_finder"], [17, 0, 0, "-", "issue_manager_factory"], [35, 0, 0, "-", "model_outputs"], [36, 0, 0, "-", "report"], [37, 0, 0, "-", "task"]], "cleanlab.datalab.internal.data": [[15, 2, 1, "", "Data"], [15, 5, 1, "", "DataFormatError"], [15, 5, 1, "", "DatasetDictError"], [15, 5, 1, "", "DatasetLoadError"], [15, 2, 1, "", "Label"], [15, 2, 1, "", "MultiClass"], [15, 2, 1, "", "MultiLabel"]], "cleanlab.datalab.internal.data.Data": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "has_labels"]], "cleanlab.datalab.internal.data.DataFormatError": [[15, 3, 1, "", "add_note"], [15, 6, 1, "", "args"], [15, 3, 1, "", "with_traceback"]], "cleanlab.datalab.internal.data.DatasetDictError": [[15, 3, 1, "", "add_note"], [15, 6, 1, "", "args"], [15, 3, 1, "", "with_traceback"]], "cleanlab.datalab.internal.data.DatasetLoadError": [[15, 3, 1, "", "add_note"], [15, 6, 1, "", "args"], [15, 3, 1, "", "with_traceback"]], "cleanlab.datalab.internal.data.Label": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "is_available"]], "cleanlab.datalab.internal.data.MultiClass": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "is_available"]], "cleanlab.datalab.internal.data.MultiLabel": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "is_available"]], "cleanlab.datalab.internal.data_issues": [[16, 2, 1, "", "DataIssues"], [16, 1, 1, "", "get_data_statistics"]], "cleanlab.datalab.internal.data_issues.DataIssues": [[16, 3, 1, "", "collect_issues_from_imagelab"], [16, 3, 1, "", "collect_issues_from_issue_manager"], [16, 3, 1, "", "collect_statistics"], [16, 3, 1, "", "get_info"], [16, 3, 1, "", "get_issue_summary"], [16, 3, 1, "", "get_issues"], [16, 6, 1, "", "info"], [16, 6, 1, "", "issue_summary"], [16, 6, 1, "", "issues"], [16, 3, 1, "", "set_health_score"], [16, 4, 1, "", "statistics"]], "cleanlab.datalab.internal.issue_finder": [[19, 2, 1, "", "IssueFinder"]], "cleanlab.datalab.internal.issue_finder.IssueFinder": [[19, 3, 1, "", "find_issues"], [19, 3, 1, "", "get_available_issue_types"]], "cleanlab.datalab.internal.issue_manager": [[21, 0, 0, "-", "data_valuation"], [22, 0, 0, "-", "duplicate"], [23, 0, 0, "-", "imbalance"], [25, 0, 0, "-", "issue_manager"], [26, 0, 0, "-", "label"], [29, 0, 0, "-", "noniid"], [30, 0, 0, "-", "null"], [31, 0, 0, "-", "outlier"], [34, 0, 0, "-", "underperforming_group"]], "cleanlab.datalab.internal.issue_manager.data_valuation": [[21, 2, 1, "", "DataValuationIssueManager"]], "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager": [[21, 6, 1, "", "DEFAULT_THRESHOLD"], [21, 3, 1, "", "collect_info"], [21, 6, 1, "", "description"], [21, 3, 1, "", "find_issues"], [21, 6, 1, "", "info"], [21, 6, 1, "", "issue_name"], [21, 6, 1, "", "issue_score_key"], [21, 6, 1, "", "issues"], [21, 3, 1, "", "make_summary"], [21, 3, 1, "", "report"], [21, 6, 1, "", "summary"], [21, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.duplicate": [[22, 2, 1, "", "NearDuplicateIssueManager"]], "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager": [[22, 3, 1, "", "collect_info"], [22, 6, 1, "", "description"], [22, 3, 1, "", "find_issues"], [22, 6, 1, "", "info"], [22, 6, 1, "", "issue_name"], [22, 6, 1, "", "issue_score_key"], [22, 6, 1, "", "issues"], [22, 3, 1, "", "make_summary"], [22, 6, 1, "", "near_duplicate_sets"], [22, 3, 1, "", "report"], [22, 6, 1, "", "summary"], [22, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.imbalance": [[23, 2, 1, "", "ClassImbalanceIssueManager"]], "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager": [[23, 3, 1, "", "collect_info"], [23, 6, 1, "", "description"], [23, 3, 1, "", "find_issues"], [23, 6, 1, "", "info"], [23, 6, 1, "", "issue_name"], [23, 6, 1, "", "issue_score_key"], [23, 6, 1, "", "issues"], [23, 3, 1, "", "make_summary"], [23, 3, 1, "", "report"], [23, 6, 1, "", "summary"], [23, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.issue_manager": [[25, 2, 1, "", "IssueManager"]], "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager": [[25, 3, 1, "", "collect_info"], [25, 6, 1, "", "description"], [25, 3, 1, "", "find_issues"], [25, 6, 1, "", "info"], [25, 6, 1, "", "issue_name"], [25, 6, 1, "", "issue_score_key"], [25, 6, 1, "", "issues"], [25, 3, 1, "", "make_summary"], [25, 3, 1, "", "report"], [25, 6, 1, "", "summary"], [25, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.label": [[26, 2, 1, "", "LabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager": [[26, 3, 1, "", "collect_info"], [26, 6, 1, "", "description"], [26, 3, 1, "", "find_issues"], [26, 3, 1, "", "get_health_summary"], [26, 6, 1, "", "health_summary_parameters"], [26, 6, 1, "", "info"], [26, 6, 1, "", "issue_name"], [26, 6, 1, "", "issue_score_key"], [26, 6, 1, "", "issues"], [26, 3, 1, "", "make_summary"], [26, 3, 1, "", "report"], [26, 6, 1, "", "summary"], [26, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.multilabel": [[28, 0, 0, "-", "label"]], "cleanlab.datalab.internal.issue_manager.multilabel.label": [[28, 2, 1, "", "MultilabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager": [[28, 3, 1, "", "collect_info"], [28, 6, 1, "", "description"], [28, 3, 1, "", "find_issues"], [28, 6, 1, "", "info"], [28, 6, 1, "", "issue_name"], [28, 6, 1, "", "issue_score_key"], [28, 6, 1, "", "issues"], [28, 3, 1, "", "make_summary"], [28, 3, 1, "", "report"], [28, 6, 1, "", "summary"], [28, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.noniid": [[29, 2, 1, "", "NonIIDIssueManager"], [29, 1, 1, "", "simplified_kolmogorov_smirnov_test"]], "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager": [[29, 3, 1, "", "collect_info"], [29, 6, 1, "", "description"], [29, 3, 1, "", "find_issues"], [29, 6, 1, "", "info"], [29, 6, 1, "", "issue_name"], [29, 6, 1, "", "issue_score_key"], [29, 6, 1, "", "issues"], [29, 3, 1, "", "make_summary"], [29, 3, 1, "", "report"], [29, 6, 1, "", "summary"], [29, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.null": [[30, 2, 1, "", "NullIssueManager"]], "cleanlab.datalab.internal.issue_manager.null.NullIssueManager": [[30, 3, 1, "", "collect_info"], [30, 6, 1, "", "description"], [30, 3, 1, "", "find_issues"], [30, 6, 1, "", "info"], [30, 6, 1, "", "issue_name"], [30, 6, 1, "", "issue_score_key"], [30, 6, 1, "", "issues"], [30, 3, 1, "", "make_summary"], [30, 3, 1, "", "report"], [30, 6, 1, "", "summary"], [30, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.outlier": [[31, 2, 1, "", "OutlierIssueManager"]], "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager": [[31, 6, 1, "", "DEFAULT_THRESHOLDS"], [31, 3, 1, "", "collect_info"], [31, 6, 1, "", "description"], [31, 3, 1, "", "find_issues"], [31, 6, 1, "", "info"], [31, 6, 1, "", "issue_name"], [31, 6, 1, "", "issue_score_key"], [31, 6, 1, "", "issues"], [31, 3, 1, "", "make_summary"], [31, 6, 1, "", "metric"], [31, 6, 1, "", "ood"], [31, 3, 1, "", "report"], [31, 6, 1, "", "summary"], [31, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.regression": [[33, 0, 0, "-", "label"]], "cleanlab.datalab.internal.issue_manager.regression.label": [[33, 2, 1, "", "RegressionLabelIssueManager"], [33, 1, 1, "", "find_issues_with_features"], [33, 1, 1, "", "find_issues_with_predictions"]], "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager": [[33, 3, 1, "", "collect_info"], [33, 6, 1, "", "description"], [33, 3, 1, "", "find_issues"], [33, 6, 1, "", "info"], [33, 6, 1, "", "issue_name"], [33, 6, 1, "", "issue_score_key"], [33, 6, 1, "", "issues"], [33, 3, 1, "", "make_summary"], [33, 3, 1, "", "report"], [33, 6, 1, "", "summary"], [33, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.underperforming_group": [[34, 2, 1, "", "UnderperformingGroupIssueManager"]], "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager": [[34, 6, 1, "", "NO_UNDERPERFORMING_CLUSTER_ID"], [34, 6, 1, "", "OUTLIER_CLUSTER_LABELS"], [34, 3, 1, "", "collect_info"], [34, 6, 1, "", "description"], [34, 3, 1, "", "filter_cluster_ids"], [34, 3, 1, "", "find_issues"], [34, 3, 1, "", "get_underperforming_clusters"], [34, 6, 1, "", "info"], [34, 6, 1, "", "issue_name"], [34, 6, 1, "", "issue_score_key"], [34, 6, 1, "", "issues"], [34, 3, 1, "", "make_summary"], [34, 3, 1, "", "perform_clustering"], [34, 3, 1, "", "report"], [34, 6, 1, "", "summary"], [34, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager_factory": [[17, 7, 1, "", "REGISTRY"], [17, 1, 1, "", "list_default_issue_types"], [17, 1, 1, "", "list_possible_issue_types"], [17, 1, 1, "", "register"]], "cleanlab.datalab.internal.model_outputs": [[35, 2, 1, "", "ModelOutput"], [35, 2, 1, "", "MultiClassPredProbs"], [35, 2, 1, "", "MultiLabelPredProbs"], [35, 2, 1, "", "RegressionPredictions"]], "cleanlab.datalab.internal.model_outputs.ModelOutput": [[35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs": [[35, 6, 1, "", "argument"], [35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs": [[35, 6, 1, "", "argument"], [35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.model_outputs.RegressionPredictions": [[35, 6, 1, "", "argument"], [35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.report": [[36, 2, 1, "", "Reporter"]], "cleanlab.datalab.internal.report.Reporter": [[36, 3, 1, "", "get_report"], [36, 3, 1, "", "report"]], "cleanlab.datalab.internal.task": [[37, 2, 1, "", "Task"]], "cleanlab.datalab.internal.task.Task": [[37, 6, 1, "", "CLASSIFICATION"], [37, 6, 1, "", "MULTILABEL"], [37, 6, 1, "", "REGRESSION"], [37, 3, 1, "", "__contains__"], [37, 3, 1, "", "__getitem__"], [37, 3, 1, "", "__iter__"], [37, 3, 1, "", "__len__"], [37, 3, 1, "", "from_str"], [37, 4, 1, "", "is_classification"], [37, 4, 1, "", "is_multilabel"], [37, 4, 1, "", "is_regression"]], "cleanlab.dataset": [[39, 1, 1, "", "find_overlapping_classes"], [39, 1, 1, "", "health_summary"], [39, 1, 1, "", "overall_label_health_score"], [39, 1, 1, "", "rank_classes_by_label_quality"]], "cleanlab.experimental": [[40, 0, 0, "-", "cifar_cnn"], [41, 0, 0, "-", "coteaching"], [43, 0, 0, "-", "label_issues_batched"], [44, 0, 0, "-", "mnist_pytorch"], [45, 0, 0, "-", "span_classification"]], "cleanlab.experimental.cifar_cnn": [[40, 2, 1, "", "CNN"], [40, 1, 1, "", "call_bn"]], "cleanlab.experimental.cifar_cnn.CNN": [[40, 6, 1, "", "T_destination"], [40, 3, 1, "", "__call__"], [40, 3, 1, "", "add_module"], [40, 3, 1, "", "apply"], [40, 3, 1, "", "bfloat16"], [40, 3, 1, "", "buffers"], [40, 6, 1, "", "call_super_init"], [40, 3, 1, "", "children"], [40, 3, 1, "", "compile"], [40, 3, 1, "", "cpu"], [40, 3, 1, "", "cuda"], [40, 3, 1, "", "double"], [40, 6, 1, "", "dump_patches"], [40, 3, 1, "", "eval"], [40, 3, 1, "", "extra_repr"], [40, 3, 1, "", "float"], [40, 3, 1, "id0", "forward"], [40, 3, 1, "", "get_buffer"], [40, 3, 1, "", "get_extra_state"], [40, 3, 1, "", "get_parameter"], [40, 3, 1, "", "get_submodule"], [40, 3, 1, "", "half"], [40, 3, 1, "", "ipu"], [40, 3, 1, "", "load_state_dict"], [40, 3, 1, "", "modules"], [40, 3, 1, "", "named_buffers"], [40, 3, 1, "", "named_children"], [40, 3, 1, "", "named_modules"], [40, 3, 1, "", "named_parameters"], [40, 3, 1, "", "parameters"], [40, 3, 1, "", "register_backward_hook"], [40, 3, 1, "", "register_buffer"], [40, 3, 1, "", "register_forward_hook"], [40, 3, 1, "", "register_forward_pre_hook"], [40, 3, 1, "", "register_full_backward_hook"], [40, 3, 1, "", "register_full_backward_pre_hook"], [40, 3, 1, "", "register_load_state_dict_post_hook"], [40, 3, 1, "", "register_module"], [40, 3, 1, "", "register_parameter"], [40, 3, 1, "", "register_state_dict_pre_hook"], [40, 3, 1, "", "requires_grad_"], [40, 3, 1, "", "set_extra_state"], [40, 3, 1, "", "share_memory"], [40, 3, 1, "", "state_dict"], [40, 3, 1, "", "to"], [40, 3, 1, "", "to_empty"], [40, 3, 1, "", "train"], [40, 6, 1, "", "training"], [40, 3, 1, "", "type"], [40, 3, 1, "", "xpu"], [40, 3, 1, "", "zero_grad"]], "cleanlab.experimental.coteaching": [[41, 1, 1, "", "adjust_learning_rate"], [41, 1, 1, "", "evaluate"], [41, 1, 1, "", "forget_rate_scheduler"], [41, 1, 1, "", "initialize_lr_scheduler"], [41, 1, 1, "", "loss_coteaching"], [41, 1, 1, "", "train"]], "cleanlab.experimental.label_issues_batched": [[43, 2, 1, "", "LabelInspector"], [43, 7, 1, "", "adj_confident_thresholds_shared"], [43, 1, 1, "", "find_label_issues_batched"], [43, 7, 1, "", "labels_shared"], [43, 7, 1, "", "pred_probs_shared"], [43, 1, 1, "", "split_arr"]], "cleanlab.experimental.label_issues_batched.LabelInspector": [[43, 3, 1, "", "get_confident_thresholds"], [43, 3, 1, "", "get_label_issues"], [43, 3, 1, "", "get_num_issues"], [43, 3, 1, "", "get_quality_scores"], [43, 3, 1, "", "score_label_quality"], [43, 3, 1, "", "update_confident_thresholds"]], "cleanlab.experimental.mnist_pytorch": [[44, 2, 1, "", "CNN"], [44, 2, 1, "", "SimpleNet"], [44, 1, 1, "", "get_mnist_dataset"], [44, 1, 1, "", "get_sklearn_digits_dataset"]], "cleanlab.experimental.mnist_pytorch.CNN": [[44, 3, 1, "", "__init_subclass__"], [44, 6, 1, "", "batch_size"], [44, 6, 1, "", "dataset"], [44, 6, 1, "", "epochs"], [44, 3, 1, "id0", "fit"], [44, 3, 1, "", "get_metadata_routing"], [44, 3, 1, "", "get_params"], [44, 6, 1, "", "loader"], [44, 6, 1, "", "log_interval"], [44, 6, 1, "", "lr"], [44, 6, 1, "", "momentum"], [44, 6, 1, "", "no_cuda"], [44, 3, 1, "id1", "predict"], [44, 3, 1, "id4", "predict_proba"], [44, 6, 1, "", "seed"], [44, 3, 1, "", "set_fit_request"], [44, 3, 1, "", "set_params"], [44, 3, 1, "", "set_predict_proba_request"], [44, 3, 1, "", "set_predict_request"], [44, 6, 1, "", "test_batch_size"]], "cleanlab.experimental.mnist_pytorch.SimpleNet": [[44, 6, 1, "", "T_destination"], [44, 3, 1, "", "__call__"], [44, 3, 1, "", "add_module"], [44, 3, 1, "", "apply"], [44, 3, 1, "", "bfloat16"], [44, 3, 1, "", "buffers"], [44, 6, 1, "", "call_super_init"], [44, 3, 1, "", "children"], [44, 3, 1, "", "compile"], [44, 3, 1, "", "cpu"], [44, 3, 1, "", "cuda"], [44, 3, 1, "", "double"], [44, 6, 1, "", "dump_patches"], [44, 3, 1, "", "eval"], [44, 3, 1, "", "extra_repr"], [44, 3, 1, "", "float"], [44, 3, 1, "", "forward"], [44, 3, 1, "", "get_buffer"], [44, 3, 1, "", "get_extra_state"], [44, 3, 1, "", "get_parameter"], [44, 3, 1, "", "get_submodule"], [44, 3, 1, "", "half"], [44, 3, 1, "", "ipu"], [44, 3, 1, "", "load_state_dict"], [44, 3, 1, "", "modules"], [44, 3, 1, "", "named_buffers"], [44, 3, 1, "", "named_children"], [44, 3, 1, "", "named_modules"], [44, 3, 1, "", "named_parameters"], [44, 3, 1, "", "parameters"], [44, 3, 1, "", "register_backward_hook"], [44, 3, 1, "", "register_buffer"], [44, 3, 1, "", "register_forward_hook"], [44, 3, 1, "", "register_forward_pre_hook"], [44, 3, 1, "", "register_full_backward_hook"], [44, 3, 1, "", "register_full_backward_pre_hook"], [44, 3, 1, "", "register_load_state_dict_post_hook"], [44, 3, 1, "", "register_module"], [44, 3, 1, "", "register_parameter"], [44, 3, 1, "", "register_state_dict_pre_hook"], [44, 3, 1, "", "requires_grad_"], [44, 3, 1, "", "set_extra_state"], [44, 3, 1, "", "share_memory"], [44, 3, 1, "", "state_dict"], [44, 3, 1, "", "to"], [44, 3, 1, "", "to_empty"], [44, 3, 1, "", "train"], [44, 6, 1, "", "training"], [44, 3, 1, "", "type"], [44, 3, 1, "", "xpu"], [44, 3, 1, "", "zero_grad"]], "cleanlab.experimental.span_classification": [[45, 1, 1, "", "display_issues"], [45, 1, 1, "", "find_label_issues"], [45, 1, 1, "", "get_label_quality_scores"]], "cleanlab.filter": [[46, 1, 1, "", "find_label_issues"], [46, 1, 1, "", "find_label_issues_using_argmax_confusion_matrix"], [46, 1, 1, "", "find_predicted_neq_given"], [46, 7, 1, "", "pred_probs_by_class"], [46, 7, 1, "", "prune_count_matrix_cols"]], "cleanlab.internal": [[48, 0, 0, "-", "label_quality_utils"], [49, 0, 0, "-", "latent_algebra"], [50, 0, 0, "-", "multiannotator_utils"], [51, 0, 0, "-", "multilabel_scorer"], [52, 0, 0, "-", "multilabel_utils"], [53, 0, 0, "-", "neighbor"], [57, 0, 0, "-", "outlier"], [58, 0, 0, "-", "token_classification_utils"], [59, 0, 0, "-", "util"], [60, 0, 0, "-", "validation"]], "cleanlab.internal.label_quality_utils": [[48, 1, 1, "", "get_normalized_entropy"]], "cleanlab.internal.latent_algebra": [[49, 1, 1, "", "compute_inv_noise_matrix"], [49, 1, 1, "", "compute_noise_matrix_from_inverse"], [49, 1, 1, "", "compute_ps_py_inv_noise_matrix"], [49, 1, 1, "", "compute_py"], [49, 1, 1, "", "compute_py_inv_noise_matrix"], [49, 1, 1, "", "compute_pyx"]], "cleanlab.internal.multiannotator_utils": [[50, 1, 1, "", "assert_valid_inputs_multiannotator"], [50, 1, 1, "", "assert_valid_pred_probs"], [50, 1, 1, "", "check_consensus_label_classes"], [50, 1, 1, "", "compute_soft_cross_entropy"], [50, 1, 1, "", "find_best_temp_scaler"], [50, 1, 1, "", "format_multiannotator_labels"], [50, 1, 1, "", "temp_scale_pred_probs"]], "cleanlab.internal.multilabel_scorer": [[51, 2, 1, "", "Aggregator"], [51, 2, 1, "", "ClassLabelScorer"], [51, 2, 1, "", "MultilabelScorer"], [51, 1, 1, "", "exponential_moving_average"], [51, 1, 1, "", "get_cross_validated_multilabel_pred_probs"], [51, 1, 1, "", "get_label_quality_scores"], [51, 1, 1, "", "multilabel_py"], [51, 1, 1, "", "softmin"]], "cleanlab.internal.multilabel_scorer.Aggregator": [[51, 3, 1, "", "__call__"], [51, 6, 1, "", "possible_methods"]], "cleanlab.internal.multilabel_scorer.ClassLabelScorer": [[51, 6, 1, "", "CONFIDENCE_WEIGHTED_ENTROPY"], [51, 6, 1, "", "NORMALIZED_MARGIN"], [51, 6, 1, "", "SELF_CONFIDENCE"], [51, 3, 1, "", "__call__"], [51, 3, 1, "", "__contains__"], [51, 3, 1, "", "__getitem__"], [51, 3, 1, "", "__iter__"], [51, 3, 1, "", "__len__"], [51, 3, 1, "", "from_str"]], "cleanlab.internal.multilabel_scorer.MultilabelScorer": [[51, 3, 1, "", "__call__"], [51, 3, 1, "", "aggregate"], [51, 3, 1, "", "get_class_label_quality_scores"]], "cleanlab.internal.multilabel_utils": [[52, 1, 1, "", "get_onehot_num_classes"], [52, 1, 1, "", "int2onehot"], [52, 1, 1, "", "onehot2int"], [52, 1, 1, "", "stack_complement"]], "cleanlab.internal.neighbor": [[54, 0, 0, "-", "knn_graph"], [55, 0, 0, "-", "metric"], [56, 0, 0, "-", "search"]], "cleanlab.internal.neighbor.knn_graph": [[54, 7, 1, "", "DEFAULT_K"], [54, 1, 1, "", "construct_knn_graph_from_index"], [54, 1, 1, "", "correct_knn_distances_and_indices"], [54, 1, 1, "", "correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace"], [54, 1, 1, "", "correct_knn_graph"], [54, 1, 1, "", "create_knn_graph_and_index"], [54, 1, 1, "", "features_to_knn"]], "cleanlab.internal.neighbor.metric": [[55, 7, 1, "", "HIGH_DIMENSION_CUTOFF"], [55, 7, 1, "", "ROW_COUNT_CUTOFF"], [55, 1, 1, "", "decide_default_metric"], [55, 1, 1, "", "decide_euclidean_metric"]], "cleanlab.internal.neighbor.search": [[56, 1, 1, "", "construct_knn"]], "cleanlab.internal.outlier": [[57, 1, 1, "", "correct_precision_errors"], [57, 1, 1, "", "transform_distances_to_scores"]], "cleanlab.internal.token_classification_utils": [[58, 1, 1, "", "color_sentence"], [58, 1, 1, "", "filter_sentence"], [58, 1, 1, "", "get_sentence"], [58, 1, 1, "", "mapping"], [58, 1, 1, "", "merge_probs"], [58, 1, 1, "", "process_token"]], "cleanlab.internal.util": [[59, 1, 1, "", "append_extra_datapoint"], [59, 1, 1, "", "clip_noise_rates"], [59, 1, 1, "", "clip_values"], [59, 1, 1, "", "compress_int_array"], [59, 1, 1, "", "confusion_matrix"], [59, 1, 1, "", "csr_vstack"], [59, 1, 1, "", "estimate_pu_f1"], [59, 1, 1, "", "extract_indices_tf"], [59, 1, 1, "", "force_two_dimensions"], [59, 1, 1, "", "format_labels"], [59, 1, 1, "", "get_missing_classes"], [59, 1, 1, "", "get_num_classes"], [59, 1, 1, "", "get_unique_classes"], [59, 1, 1, "", "is_tensorflow_dataset"], [59, 1, 1, "", "is_torch_dataset"], [59, 1, 1, "", "num_unique_classes"], [59, 1, 1, "", "print_inverse_noise_matrix"], [59, 1, 1, "", "print_joint_matrix"], [59, 1, 1, "", "print_noise_matrix"], [59, 1, 1, "", "print_square_matrix"], [59, 1, 1, "", "remove_noise_from_class"], [59, 1, 1, "", "round_preserving_row_totals"], [59, 1, 1, "", "round_preserving_sum"], [59, 1, 1, "", "smart_display_dataframe"], [59, 1, 1, "", "subset_X_y"], [59, 1, 1, "", "subset_data"], [59, 1, 1, "", "subset_labels"], [59, 1, 1, "", "train_val_split"], [59, 1, 1, "", "unshuffle_tensorflow_dataset"], [59, 1, 1, "", "value_counts"], [59, 1, 1, "", "value_counts_fill_missing_classes"]], "cleanlab.internal.validation": [[60, 1, 1, "", "assert_indexing_works"], [60, 1, 1, "", "assert_nonempty_input"], [60, 1, 1, "", "assert_valid_class_labels"], [60, 1, 1, "", "assert_valid_inputs"], [60, 1, 1, "", "labels_to_array"], [60, 1, 1, "", "labels_to_list_multilabel"]], "cleanlab.models": [[62, 0, 0, "-", "keras"]], "cleanlab.models.keras": [[62, 2, 1, "", "KerasWrapperModel"], [62, 2, 1, "", "KerasWrapperSequential"]], "cleanlab.models.keras.KerasWrapperModel": [[62, 3, 1, "", "fit"], [62, 3, 1, "", "get_params"], [62, 3, 1, "", "predict"], [62, 3, 1, "", "predict_proba"], [62, 3, 1, "", "set_params"], [62, 3, 1, "", "summary"]], "cleanlab.models.keras.KerasWrapperSequential": [[62, 3, 1, "", "fit"], [62, 3, 1, "", "get_params"], [62, 3, 1, "", "predict"], [62, 3, 1, "", "predict_proba"], [62, 3, 1, "", "set_params"], [62, 3, 1, "", "summary"]], "cleanlab.multiannotator": [[63, 1, 1, "", "convert_long_to_wide_dataset"], [63, 1, 1, "", "get_active_learning_scores"], [63, 1, 1, "", "get_active_learning_scores_ensemble"], [63, 1, 1, "", "get_label_quality_multiannotator"], [63, 1, 1, "", "get_label_quality_multiannotator_ensemble"], [63, 1, 1, "", "get_majority_vote_label"]], "cleanlab.multilabel_classification": [[64, 0, 0, "-", "dataset"], [65, 0, 0, "-", "filter"], [67, 0, 0, "-", "rank"]], "cleanlab.multilabel_classification.dataset": [[64, 1, 1, "", "common_multilabel_issues"], [64, 1, 1, "", "multilabel_health_summary"], [64, 1, 1, "", "overall_multilabel_health_score"], [64, 1, 1, "", "rank_classes_by_multilabel_quality"]], "cleanlab.multilabel_classification.filter": [[65, 1, 1, "", "find_label_issues"], [65, 1, 1, "", "find_multilabel_issues_per_class"]], "cleanlab.multilabel_classification.rank": [[67, 1, 1, "", "get_label_quality_scores"], [67, 1, 1, "", "get_label_quality_scores_per_class"]], "cleanlab.object_detection": [[68, 0, 0, "-", "filter"], [70, 0, 0, "-", "rank"], [71, 0, 0, "-", "summary"]], "cleanlab.object_detection.filter": [[68, 1, 1, "", "find_label_issues"]], "cleanlab.object_detection.rank": [[70, 1, 1, "", "compute_badloc_box_scores"], [70, 1, 1, "", "compute_overlooked_box_scores"], [70, 1, 1, "", "compute_swap_box_scores"], [70, 1, 1, "", "get_label_quality_scores"], [70, 1, 1, "", "issues_from_scores"], [70, 1, 1, "", "pool_box_scores_per_image"]], "cleanlab.object_detection.summary": [[71, 1, 1, "", "bounding_box_size_distribution"], [71, 1, 1, "", "calculate_per_class_metrics"], [71, 1, 1, "", "class_label_distribution"], [71, 1, 1, "", "get_average_per_class_confusion_matrix"], [71, 1, 1, "", "get_sorted_bbox_count_idxs"], [71, 1, 1, "", "object_counts_per_image"], [71, 1, 1, "", "plot_class_distribution"], [71, 1, 1, "", "plot_class_size_distributions"], [71, 1, 1, "", "visualize"]], "cleanlab.outlier": [[72, 2, 1, "", "OutOfDistribution"]], "cleanlab.outlier.OutOfDistribution": [[72, 3, 1, "", "fit"], [72, 3, 1, "", "fit_score"], [72, 3, 1, "", "score"]], "cleanlab.rank": [[73, 1, 1, "", "find_top_issues"], [73, 1, 1, "", "get_confidence_weighted_entropy_for_each_label"], [73, 1, 1, "", "get_label_quality_ensemble_scores"], [73, 1, 1, "", "get_label_quality_scores"], [73, 1, 1, "", "get_normalized_margin_for_each_label"], [73, 1, 1, "", "get_self_confidence_for_each_label"], [73, 1, 1, "", "order_label_issues"]], "cleanlab.regression": [[75, 0, 0, "-", "learn"], [76, 0, 0, "-", "rank"]], "cleanlab.regression.learn": [[75, 2, 1, "", "CleanLearning"]], "cleanlab.regression.learn.CleanLearning": [[75, 3, 1, "", "__init_subclass__"], [75, 3, 1, "", "find_label_issues"], [75, 3, 1, "", "fit"], [75, 3, 1, "", "get_aleatoric_uncertainty"], [75, 3, 1, "", "get_epistemic_uncertainty"], [75, 3, 1, "", "get_label_issues"], [75, 3, 1, "", "get_metadata_routing"], [75, 3, 1, "", "get_params"], [75, 3, 1, "", "predict"], [75, 3, 1, "", "save_space"], [75, 3, 1, "", "score"], [75, 3, 1, "", "set_fit_request"], [75, 3, 1, "", "set_params"], [75, 3, 1, "", "set_score_request"]], "cleanlab.regression.rank": [[76, 1, 1, "", "get_label_quality_scores"]], "cleanlab.segmentation": [[77, 0, 0, "-", "filter"], [79, 0, 0, "-", "rank"], [80, 0, 0, "-", "summary"]], "cleanlab.segmentation.filter": [[77, 1, 1, "", "find_label_issues"]], "cleanlab.segmentation.rank": [[79, 1, 1, "", "get_label_quality_scores"], [79, 1, 1, "", "issues_from_scores"]], "cleanlab.segmentation.summary": [[80, 1, 1, "", "common_label_issues"], [80, 1, 1, "", "display_issues"], [80, 1, 1, "", "filter_by_class"]], "cleanlab.token_classification": [[81, 0, 0, "-", "filter"], [83, 0, 0, "-", "rank"], [84, 0, 0, "-", "summary"]], "cleanlab.token_classification.filter": [[81, 1, 1, "", "find_label_issues"]], "cleanlab.token_classification.rank": [[83, 1, 1, "", "get_label_quality_scores"], [83, 1, 1, "", "issues_from_scores"]], "cleanlab.token_classification.summary": [[84, 1, 1, "", "common_label_issues"], [84, 1, 1, "", "display_issues"], [84, 1, 1, "", "filter_by_token"]]}, "objtypes": {"0": "py:module", "1": "py:function", "2": "py:class", "3": "py:method", "4": "py:property", "5": "py:exception", "6": "py:attribute", "7": "py:data"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "function", "Python function"], "2": ["py", "class", "Python class"], "3": ["py", "method", "Python method"], "4": ["py", "property", "Python property"], "5": ["py", "exception", "Python exception"], "6": ["py", "attribute", "Python attribute"], "7": ["py", "data", "Python data"]}, "titleterms": {"benchmark": 0, "noise_gener": 1, "classif": [2, 88, 89, 93, 95, 96, 99, 101, 104, 110], "count": [3, 101], "data_valu": [4, 21], "datalab": [5, 7, 9, 10, 12, 90, 91, 92, 93, 94, 95, 96, 97, 99, 101, 104], "creat": [7, 91, 92, 101, 103], "your": [7, 85, 91, 92, 96, 97, 99, 101], "own": 7, "issu": [7, 9, 10, 24, 33, 85, 88, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 109, 110], "manag": [7, 24], "prerequisit": 7, "implement": 7, "issuemanag": [7, 91], "basic": 7, "check": [7, 85, 97, 100], "intermedi": 7, "advanc": [7, 91], "us": [7, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "gener": [8, 97], "cluster": [8, 97, 99], "id": 8, "guid": [9, 12], "type": [9, 10, 101], "custom": [9, 91], "cleanlab": [9, 10, 85, 88, 89, 90, 93, 95, 96, 99, 101, 103, 104, 105, 106, 108, 109, 110], "studio": [9, 10], "easi": [9, 10, 85, 93], "mode": [9, 10, 85, 93], "can": [10, 92, 98, 99, 101, 103], "detect": [10, 90, 92, 93, 95, 96, 97, 99, 101, 105, 106], "estim": [10, 101, 103, 104], "each": 10, "input": 10, "label": [10, 26, 28, 33, 85, 88, 89, 90, 92, 93, 95, 96, 98, 99, 101, 103, 104, 105, 108, 109, 110], "is_label_issu": 10, "label_scor": 10, "given_label": 10, "predicted_label": 10, "outlier": [10, 31, 57, 72, 93, 95, 96, 104, 106], "is_outlier_issu": 10, "outlier_scor": 10, "Near": [10, 92, 93, 95, 96], "duplic": [10, 22, 92, 93, 95, 96, 99, 104], "is_near_duplicate_issu": 10, "near_duplicate_scor": 10, "near_duplicate_set": 10, "distance_to_nearest_neighbor": 10, "non": [10, 96, 97], "iid": [10, 96, 97], "is_non_iid_issu": 10, "non_iid_scor": 10, "class": [10, 86, 97, 101, 109], "imbal": [10, 23, 97], "is_class_imbalance_issu": 10, "class_imbalance_scor": 10, "imag": [10, 93, 97, 106], "specif": [10, 24, 109], "spuriou": [10, 97], "correl": [10, 97], "between": 10, "properti": 10, "score": [10, 97, 101, 103, 104, 105, 109, 110], "underperform": [10, 97, 99], "group": [10, 97, 99], "is_underperforming_group_issu": 10, "underperforming_group_scor": 10, "null": [10, 30, 97], "is_null_issu": 10, "null_scor": 10, "data": [10, 15, 85, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "valuat": [10, 97], "is_data_valuation_issu": 10, "data_valuation_scor": 10, "option": [10, 97], "paramet": [10, 101], "get": [12, 91, 92, 103, 104, 105, 109, 110], "start": [12, 98], "api": 12, "refer": 12, "imagelab": 13, "adapt": 14, "data_issu": 16, "factori": 17, "intern": [18, 47], "issue_find": 19, "issue_manag": [24, 25], "regist": 24, "ml": [24, 99, 100, 101], "task": [24, 37], "multilabel": 27, "noniid": 29, "regress": [32, 74, 75, 76, 99, 108], "prioriti": 33, "order": 33, "find": [33, 88, 89, 90, 92, 93, 95, 96, 97, 99, 101, 103, 104, 105, 106, 108, 109, 110], "underperforming_group": 34, "model_output": 35, "report": [36, 93], "dataset": [39, 64, 85, 89, 90, 92, 93, 96, 97, 98, 99, 101, 104, 105, 106, 108, 109, 110], "cifar_cnn": 40, "coteach": 41, "experiment": 42, "label_issues_batch": 43, "mnist_pytorch": 44, "span_classif": 45, "filter": [46, 65, 68, 77, 81, 101], "label_quality_util": 48, "latent_algebra": 49, "multiannotator_util": 50, "multilabel_scor": 51, "multilabel_util": 52, "neighbor": 53, "knn_graph": 54, "metric": 55, "search": [56, 91], "token_classification_util": 58, "util": 59, "valid": [60, 93, 107], "model": [61, 85, 88, 89, 90, 93, 95, 96, 99, 100, 101, 103, 104, 105, 106, 108], "kera": 62, "multiannot": [63, 103], "multilabel_classif": 66, "rank": [67, 70, 73, 76, 79, 83, 101], "object_detect": 69, "summari": [71, 80, 84], "learn": [75, 92, 99, 101], "segment": [78, 109], "token_classif": [82, 110], "open": [85, 99], "sourc": [85, 99], "document": 85, "quickstart": 85, "1": [85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 108, 109, 110], "instal": [85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "2": [85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 108, 109, 110], "all": [85, 92, 101], "sort": [85, 97], "3": [85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 108, 109, 110], "handl": [85, 99], "error": [85, 89, 93, 99, 101, 103, 104, 105, 108, 109, 110], "train": [85, 88, 89, 90, 97, 99, 100, 106, 108], "robust": [85, 88, 89, 101, 108], "noisi": [85, 88, 89, 100, 101, 108], "4": [85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 105, 106, 108], "curat": [85, 100], "fix": [85, 99], "level": [85, 98, 101, 110], "5": [85, 88, 90, 92, 93, 95, 97, 100, 101, 103, 108], "improv": [85, 100, 103], "via": [85, 100, 101, 103], "mani": [85, 101], "other": [85, 103, 105, 108], "techniqu": [85, 100], "contribut": 85, "how": [86, 99, 101, 103, 104, 110], "migrat": 86, "version": 86, "0": 86, "from": [86, 88, 89, 91, 92, 100, 101, 108], "pre": [86, 90, 97, 99, 106], "function": [86, 91], "name": 86, "chang": 86, "modul": [86, 101], "new": 86, "remov": 86, "common": [86, 110], "argument": [86, 91], "variabl": 86, "cleanlearn": [87, 99, 101], "tutori": [87, 94, 98, 100, 102], "structur": 88, "tabular": [88, 95], "requir": [88, 89, 91, 92, 93, 95, 96, 103, 104, 105, 106, 108, 109, 110], "depend": [88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "load": [88, 89, 90, 91, 92, 95, 96, 97, 108], "process": [88, 95, 106, 108], "select": [88, 95], "comput": [88, 90, 93, 95, 96, 97, 99, 100, 103, 107], "out": [88, 90, 91, 92, 93, 95, 96, 100, 103, 107], "sampl": [88, 90, 91, 92, 93, 95, 96, 100, 103, 107], "predict": [88, 90, 91, 92, 93, 95, 96, 97, 100, 103, 104, 105, 107], "probabl": [88, 90, 91, 92, 93, 95, 96, 97, 100, 103, 107], "more": [88, 89, 92, 101, 108], "spend": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "too": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "much": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "time": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "qualiti": [88, 89, 92, 95, 96, 98, 101, 103, 104, 105, 106, 107, 108, 109, 110], "text": [89, 96, 97, 110], "format": [89, 96, 99, 104, 105], "defin": [89, 93, 96, 97, 108], "potenti": [89, 103, 108], "an": [90, 93, 99], "audio": 90, "import": [90, 91, 92, 93, 98, 101, 103], "them": [90, 98, 100, 101], "speechbrain": 90, "featur": [90, 93, 106], "fit": 90, "linear": 90, "workflow": [91, 97, 101], "audit": [91, 92], "classifi": [91, 92, 97], "instanti": 91, "object": [91, 105], "increment": 91, "specifi": [91, 99], "nondefault": 91, "save": 91, "ad": 91, "A": 92, "unifi": 92, "kind": [92, 105], "skip": [92, 98, 101, 103], "detail": [92, 98, 101, 103], "about": 92, "addit": 92, "inform": [92, 93], "fetch": [93, 98], "normal": 93, "fashion": 93, "mnist": 93, "prepar": [93, 97], "k": [93, 95, 107], "fold": [93, 107], "cross": [93, 107], "embed": [93, 106], "7": [93, 100, 101], "view": 93, "most": [93, 110], "like": 93, "exampl": [93, 99, 101, 106], "sever": 93, "set": [93, 101], "dark": 93, "top": [93, 109], "low": 93, "numer": 95, "categor": [95, 97], "column": 95, "construct": 95, "nearest": 95, "neighbour": 95, "graph": [95, 97], "drift": [96, 104], "miscellan": 97, "acceler": 97, "knn": 97, "obtain": 97, "identifi": [97, 99, 100, 105], "explan": 97, "vector": 97, "perform": [97, 100], "visual": [97, 101, 105, 106, 109], "synthet": 97, "result": 97, "predefin": 97, "slice": [97, 99], "i": [97, 99, 101, 107], "catch": 97, "valu": 97, "encod": 97, "initi": [97, 103], "6": [97, 100, 101], "run": [97, 99], "analysi": [97, 105], "interpret": 97, "understand": 98, "evalu": [98, 100], "health": [98, 101], "8": [98, 100, 101], "popular": 98, "faq": 99, "what": [99, 101, 107], "do": [99, 101], "infer": 99, "correct": [99, 100], "ha": 99, "flag": 99, "should": 99, "v": [99, 100], "test": [99, 100, 101, 106], "big": 99, "limit": 99, "memori": 99, "why": [99, 100], "isn": 99, "t": 99, "work": [99, 101, 103, 110], "me": 99, "differ": [99, 105], "clean": [99, 100, 101], "final": 99, "hyperparamet": [99, 100], "tune": 99, "onli": 99, "one": [99, 101, 104, 109], "doe": [99, 103, 110], "take": 99, "so": 99, "long": 99, "when": [99, 101], "licens": 99, "under": 99, "answer": 99, "question": 99, "split": 100, "did": 100, "you": [100, 101], "make": 100, "thi": [100, 101], "preprocess": 100, "fundament": 100, "problem": 100, "setup": 100, "origin": 100, "baselin": 100, "manual": 100, "address": 100, "algorithm": 100, "better": [100, 103], "strategi": 100, "optim": 100, "9": 100, "conclus": 100, "The": 101, "centric": 101, "ai": 101, "machin": 101, "find_label_issu": 101, "line": 101, "code": 101, "twenti": 101, "lowest": 101, "see": 101, "now": 101, "let": 101, "": 101, "happen": 101, "we": 101, "merg": 101, "seafoam": 101, "green": 101, "yellow": 101, "re": 101, "One": 101, "rule": 101, "overal": [101, 109], "accur": 101, "directli": 101, "fulli": 101, "character": 101, "nois": 101, "matrix": [101, 104], "joint": 101, "prior": 101, "true": 101, "distribut": 101, "flip": 101, "rate": 101, "ani": 101, "again": 101, "support": 101, "lot": 101, "method": 101, "filter_bi": 101, "automat": 101, "everi": 101, "uniqu": 101, "num_label_issu": 101, "threshold": 101, "found": 101, "Not": 101, "sure": 101, "ensembl": 101, "multipl": [101, 103], "predictor": 101, "consensu": 103, "annot": 103, "major": 103, "vote": 103, "statist": 103, "compar": 103, "inspect": 103, "retrain": 103, "further": 103, "multi": 104, "beyond": 104, "mislabel": [104, 109, 110], "given": 104, "hot": 104, "binari": 104, "without": 104, "applic": 104, "real": 104, "download": [105, 109, 110], "objectlab": 105, "exploratori": 105, "pytorch": 106, "timm": 106, "cifar10": 106, "some": 106, "pred_prob": [106, 109, 110], "wai": 108, "semant": 109, "which": 109, "ar": 109, "commonli": 109, "focus": 109, "token": 110, "word": 110, "sentenc": 110, "contain": 110, "particular": 110}, "envversion": {"sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "nbsphinx": 4, "sphinx.ext.viewcode": 1, "sphinx.ext.todo": 2, "sphinx": 58}, "alltitles": {"benchmarking": [[0, "module-cleanlab.benchmarking"]], "noise_generation": [[1, "module-cleanlab.benchmarking.noise_generation"]], "classification": [[2, "module-cleanlab.classification"]], "count": [[3, "module-cleanlab.count"]], "data_valuation": [[4, "module-cleanlab.data_valuation"], [21, "data-valuation"]], "datalab": [[5, "module-cleanlab.datalab.datalab"], [12, "module-cleanlab.datalab"]], "Creating Your Own Issues Manager": [[7, "creating-your-own-issues-manager"]], "Prerequisites": [[7, "prerequisites"]], "Implementing IssueManagers": [[7, "implementing-issuemanagers"]], "Basic Issue Check": [[7, "basic-issue-check"]], "Intermediate Issue Check": [[7, "intermediate-issue-check"]], "Advanced Issue Check": [[7, "advanced-issue-check"]], "Use with Datalab": [[7, "use-with-datalab"]], "Generating Cluster IDs": [[8, "generating-cluster-ids"]], "Datalab guides": [[9, "datalab-guides"]], "Types of issues": [[9, "types-of-issues"]], "Customizing issue types": [[9, "customizing-issue-types"]], "Cleanlab Studio (Easy Mode)": [[9, "cleanlab-studio-easy-mode"], [10, "cleanlab-studio-easy-mode"]], "Datalab Issue Types": [[10, "datalab-issue-types"]], "Types of issues Datalab can detect": [[10, "types-of-issues-datalab-can-detect"]], "Estimates for Each Issue Type": [[10, "estimates-for-each-issue-type"]], "Inputs to Datalab": [[10, "inputs-to-datalab"]], "Label Issue": [[10, "label-issue"]], "is_label_issue": [[10, "is-label-issue"]], "label_score": [[10, "label-score"]], "given_label": [[10, "given-label"], [10, "id6"]], "predicted_label": [[10, "predicted-label"]], "Outlier Issue": [[10, "outlier-issue"]], "is_outlier_issue": [[10, "is-outlier-issue"]], "outlier_score": [[10, "outlier-score"]], "(Near) Duplicate Issue": [[10, "near-duplicate-issue"]], "is_near_duplicate_issue": [[10, "is-near-duplicate-issue"]], "near_duplicate_score": [[10, "near-duplicate-score"]], "near_duplicate_sets": [[10, "near-duplicate-sets"]], "distance_to_nearest_neighbor": [[10, "distance-to-nearest-neighbor"]], "Non-IID Issue": [[10, "non-iid-issue"]], "is_non_iid_issue": [[10, "is-non-iid-issue"]], "non_iid_score": [[10, "non-iid-score"]], "Class Imbalance Issue": [[10, "class-imbalance-issue"]], "is_class_imbalance_issue": [[10, "is-class-imbalance-issue"]], "class_imbalance_score": [[10, "class-imbalance-score"]], "Image-specific Issues": [[10, "image-specific-issues"]], "Spurious Correlations between image-specific properties and labels": [[10, "spurious-correlations-between-image-specific-properties-and-labels"]], "property": [[10, "property"]], "score": [[10, "score"]], "Underperforming Group Issue": [[10, "underperforming-group-issue"]], "is_underperforming_group_issue": [[10, "is-underperforming-group-issue"]], "underperforming_group_score": [[10, "underperforming-group-score"]], "Null Issue": [[10, "null-issue"]], "is_null_issue": [[10, "is-null-issue"]], "null_score": [[10, "null-score"]], "Data Valuation Issue": [[10, "data-valuation-issue"]], "is_data_valuation_issue": [[10, "is-data-valuation-issue"]], "data_valuation_score": [[10, "data-valuation-score"]], "Optional Issue Parameters": [[10, "optional-issue-parameters"]], "Label Issue Parameters": [[10, "label-issue-parameters"]], "Outlier Issue Parameters": [[10, "outlier-issue-parameters"]], "Duplicate Issue Parameters": [[10, "duplicate-issue-parameters"]], "Non-IID Issue Parameters": [[10, "non-iid-issue-parameters"]], "Imbalance Issue Parameters": [[10, "imbalance-issue-parameters"]], "Underperforming Group Issue Parameters": [[10, "underperforming-group-issue-parameters"]], "Null Issue Parameters": [[10, "null-issue-parameters"]], "Data Valuation Issue Parameters": [[10, "data-valuation-issue-parameters"]], "Image Issue Parameters": [[10, "image-issue-parameters"]], "Getting Started": [[12, "getting-started"]], "Guides": [[12, "guides"]], "API Reference": [[12, "api-reference"]], "imagelab": [[13, "module-cleanlab.datalab.internal.adapter.imagelab"]], "adapter": [[14, "adapter"]], "data": [[15, "module-cleanlab.datalab.internal.data"]], "data_issues": [[16, "module-cleanlab.datalab.internal.data_issues"]], "factory": [[17, "module-cleanlab.datalab.internal.issue_manager_factory"]], "internal": [[18, "internal"], [47, "internal"]], "issue_finder": [[19, "issue-finder"]], "duplicate": [[22, "module-cleanlab.datalab.internal.issue_manager.duplicate"]], "imbalance": [[23, "module-cleanlab.datalab.internal.issue_manager.imbalance"]], "issue_manager": [[24, "issue-manager"], [25, "module-cleanlab.datalab.internal.issue_manager.issue_manager"]], "Registered issue managers": [[24, "registered-issue-managers"]], "ML task-specific issue managers": [[24, "ml-task-specific-issue-managers"]], "label": [[26, "module-cleanlab.datalab.internal.issue_manager.label"], [28, "module-cleanlab.datalab.internal.issue_manager.multilabel.label"], [33, "module-cleanlab.datalab.internal.issue_manager.regression.label"]], "multilabel": [[27, "multilabel"]], "noniid": [[29, "module-cleanlab.datalab.internal.issue_manager.noniid"]], "null": [[30, "null"]], "outlier": [[31, "module-cleanlab.datalab.internal.issue_manager.outlier"], [57, "module-cleanlab.internal.outlier"], [72, "module-cleanlab.outlier"]], "regression": [[32, "regression"], [74, "regression"]], "Priority Order for finding issues:": [[33, null]], "underperforming_group": [[34, "underperforming-group"]], "model_outputs": [[35, "module-cleanlab.datalab.internal.model_outputs"]], "report": [[36, "report"]], "task": [[37, "task"]], "dataset": [[39, "module-cleanlab.dataset"], [64, "module-cleanlab.multilabel_classification.dataset"]], "cifar_cnn": [[40, "module-cleanlab.experimental.cifar_cnn"]], "coteaching": [[41, "module-cleanlab.experimental.coteaching"]], "experimental": [[42, "experimental"]], "label_issues_batched": [[43, "module-cleanlab.experimental.label_issues_batched"]], "mnist_pytorch": [[44, "module-cleanlab.experimental.mnist_pytorch"]], "span_classification": [[45, "module-cleanlab.experimental.span_classification"]], "filter": [[46, "module-cleanlab.filter"], [65, "module-cleanlab.multilabel_classification.filter"], [68, "filter"], [77, "filter"], [81, "module-cleanlab.token_classification.filter"]], "label_quality_utils": [[48, "module-cleanlab.internal.label_quality_utils"]], "latent_algebra": [[49, "module-cleanlab.internal.latent_algebra"]], "multiannotator_utils": [[50, "module-cleanlab.internal.multiannotator_utils"]], "multilabel_scorer": [[51, "module-cleanlab.internal.multilabel_scorer"]], "multilabel_utils": [[52, "module-cleanlab.internal.multilabel_utils"]], "neighbor": [[53, "neighbor"]], "knn_graph": [[54, "module-cleanlab.internal.neighbor.knn_graph"]], "metric": [[55, "module-cleanlab.internal.neighbor.metric"]], "search": [[56, "module-cleanlab.internal.neighbor.search"]], "token_classification_utils": [[58, "module-cleanlab.internal.token_classification_utils"]], "util": [[59, "module-cleanlab.internal.util"]], "validation": [[60, "module-cleanlab.internal.validation"]], "models": [[61, "models"]], "keras": [[62, "module-cleanlab.models.keras"]], "multiannotator": [[63, "module-cleanlab.multiannotator"]], "multilabel_classification": [[66, "multilabel-classification"]], "rank": [[67, "module-cleanlab.multilabel_classification.rank"], [70, "module-cleanlab.object_detection.rank"], [73, "module-cleanlab.rank"], [79, "module-cleanlab.segmentation.rank"], [83, "module-cleanlab.token_classification.rank"]], "object_detection": [[69, "object-detection"]], "summary": [[71, "summary"], [80, "module-cleanlab.segmentation.summary"], [84, "module-cleanlab.token_classification.summary"]], "regression.learn": [[75, "module-cleanlab.regression.learn"]], "regression.rank": [[76, "module-cleanlab.regression.rank"]], "segmentation": [[78, "segmentation"]], "token_classification": [[82, "token-classification"]], "cleanlab open-source documentation": [[85, "cleanlab-open-source-documentation"]], "Quickstart": [[85, "quickstart"]], "1. Install cleanlab": [[85, "install-cleanlab"]], "2. Check your data for all sorts of issues": [[85, "check-your-data-for-all-sorts-of-issues"]], "3. Handle label errors and train robust models with noisy labels": [[85, "handle-label-errors-and-train-robust-models-with-noisy-labels"]], "4. Dataset curation: fix dataset-level issues": [[85, "dataset-curation-fix-dataset-level-issues"]], "5. Improve your data via many other techniques": [[85, "improve-your-data-via-many-other-techniques"]], "Contributing": [[85, "contributing"]], "Easy Mode": [[85, "easy-mode"], [93, "Easy-Mode"]], "How to migrate to versions >= 2.0.0 from pre 1.0.1": [[86, "how-to-migrate-to-versions-2-0-0-from-pre-1-0-1"]], "Function and class name changes": [[86, "function-and-class-name-changes"]], "Module name changes": [[86, "module-name-changes"]], "New modules": [[86, "new-modules"]], "Removed modules": [[86, "removed-modules"]], "Common argument and variable name changes": [[86, "common-argument-and-variable-name-changes"]], "CleanLearning Tutorials": [[87, "cleanlearning-tutorials"]], "Classification with Structured/Tabular Data and Noisy Labels": [[88, "Classification-with-Structured/Tabular-Data-and-Noisy-Labels"]], "1. Install required dependencies": [[88, "1.-Install-required-dependencies"], [89, "1.-Install-required-dependencies"], [95, "1.-Install-required-dependencies"], [96, "1.-Install-required-dependencies"], [108, "1.-Install-required-dependencies"]], "2. Load and process the data": [[88, "2.-Load-and-process-the-data"], [95, "2.-Load-and-process-the-data"], [108, "2.-Load-and-process-the-data"]], "3. Select a classification model and compute out-of-sample predicted probabilities": [[88, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"], [95, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find label issues": [[88, "4.-Use-cleanlab-to-find-label-issues"]], "5. Train a more robust model from noisy labels": [[88, "5.-Train-a-more-robust-model-from-noisy-labels"]], "Spending too much time on data quality?": [[88, "Spending-too-much-time-on-data-quality?"], [89, "Spending-too-much-time-on-data-quality?"], [92, "Spending-too-much-time-on-data-quality?"], [95, "Spending-too-much-time-on-data-quality?"], [96, "Spending-too-much-time-on-data-quality?"], [98, "Spending-too-much-time-on-data-quality?"], [101, "Spending-too-much-time-on-data-quality?"], [104, "Spending-too-much-time-on-data-quality?"], [106, "Spending-too-much-time-on-data-quality?"], [107, "spending-too-much-time-on-data-quality"], [108, "Spending-too-much-time-on-data-quality?"]], "Text Classification with Noisy Labels": [[89, "Text-Classification-with-Noisy-Labels"]], "2. Load and format the text dataset": [[89, "2.-Load-and-format-the-text-dataset"], [96, "2.-Load-and-format-the-text-dataset"]], "3. Define a classification model and use cleanlab to find potential label errors": [[89, "3.-Define-a-classification-model-and-use-cleanlab-to-find-potential-label-errors"]], "4. Train a more robust model from noisy labels": [[89, "4.-Train-a-more-robust-model-from-noisy-labels"], [108, "4.-Train-a-more-robust-model-from-noisy-labels"]], "Detecting Issues in an Audio Dataset with Datalab": [[90, "Detecting-Issues-in-an-Audio-Dataset-with-Datalab"]], "1. Install dependencies and import them": [[90, "1.-Install-dependencies-and-import-them"]], "2. Load the data": [[90, "2.-Load-the-data"]], "3. Use pre-trained SpeechBrain model to featurize audio": [[90, "3.-Use-pre-trained-SpeechBrain-model-to-featurize-audio"]], "4. Fit linear model and compute out-of-sample predicted probabilities": [[90, "4.-Fit-linear-model-and-compute-out-of-sample-predicted-probabilities"]], "5. Use cleanlab to find label issues": [[90, "5.-Use-cleanlab-to-find-label-issues"], [95, "5.-Use-cleanlab-to-find-label-issues"]], "Datalab: Advanced workflows to audit your data": [[91, "Datalab:-Advanced-workflows-to-audit-your-data"]], "Install and import required dependencies": [[91, "Install-and-import-required-dependencies"]], "Create and load the data": [[91, "Create-and-load-the-data"]], "Get out-of-sample predicted probabilities from a classifier": [[91, "Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "Instantiate Datalab object": [[91, "Instantiate-Datalab-object"]], "Functionality 1: Incremental issue search": [[91, "Functionality-1:-Incremental-issue-search"]], "Functionality 2: Specifying nondefault arguments": [[91, "Functionality-2:-Specifying-nondefault-arguments"]], "Functionality 3: Save and load Datalab objects": [[91, "Functionality-3:-Save-and-load-Datalab-objects"]], "Functionality 4: Adding a custom IssueManager": [[91, "Functionality-4:-Adding-a-custom-IssueManager"]], "Datalab: A unified audit to detect all kinds of issues in data and labels": [[92, "Datalab:-A-unified-audit-to-detect-all-kinds-of-issues-in-data-and-labels"]], "1. Install and import required dependencies": [[92, "1.-Install-and-import-required-dependencies"], [93, "1.-Install-and-import-required-dependencies"], [103, "1.-Install-and-import-required-dependencies"]], "2. Create and load the data (can skip these details)": [[92, "2.-Create-and-load-the-data-(can-skip-these-details)"]], "3. Get out-of-sample predicted probabilities from a classifier": [[92, "3.-Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "4. Use Datalab to find issues in the dataset": [[92, "4.-Use-Datalab-to-find-issues-in-the-dataset"]], "5. Learn more about the issues in your dataset": [[92, "5.-Learn-more-about-the-issues-in-your-dataset"]], "Get additional information": [[92, "Get-additional-information"]], "Near duplicate issues": [[92, "Near-duplicate-issues"], [93, "Near-duplicate-issues"]], "Detecting Issues in an Image Dataset with Datalab": [[93, "Detecting-Issues-in-an-Image-Dataset-with-Datalab"]], "2. Fetch and normalize the Fashion-MNIST dataset": [[93, "2.-Fetch-and-normalize-the-Fashion-MNIST-dataset"]], "3. Define a classification model": [[93, "3.-Define-a-classification-model"]], "4. Prepare the dataset for K-fold cross-validation": [[93, "4.-Prepare-the-dataset-for-K-fold-cross-validation"]], "5. Compute out-of-sample predicted probabilities and feature embeddings": [[93, "5.-Compute-out-of-sample-predicted-probabilities-and-feature-embeddings"]], "7. Use cleanlab to find issues": [[93, "7.-Use-cleanlab-to-find-issues"]], "View report": [[93, "View-report"]], "Label issues": [[93, "Label-issues"], [95, "Label-issues"], [96, "Label-issues"]], "View most likely examples with label errors": [[93, "View-most-likely-examples-with-label-errors"]], "Outlier issues": [[93, "Outlier-issues"], [95, "Outlier-issues"], [96, "Outlier-issues"]], "View most severe outliers": [[93, "View-most-severe-outliers"]], "View sets of near duplicate images": [[93, "View-sets-of-near-duplicate-images"]], "Dark images": [[93, "Dark-images"]], "View top examples of dark images": [[93, "View-top-examples-of-dark-images"]], "Low information images": [[93, "Low-information-images"]], "Datalab Tutorials": [[94, "datalab-tutorials"]], "Detecting Issues in Tabular Data\u00a0(Numeric/Categorical columns) with Datalab": [[95, "Detecting-Issues-in-Tabular-Data\u00a0(Numeric/Categorical-columns)-with-Datalab"]], "4. Construct K nearest neighbours graph": [[95, "4.-Construct-K-nearest-neighbours-graph"]], "Near-duplicate issues": [[95, "Near-duplicate-issues"], [96, "Near-duplicate-issues"]], "Detecting Issues in a Text Dataset with Datalab": [[96, "Detecting-Issues-in-a-Text-Dataset-with-Datalab"]], "3. Define a classification model and compute out-of-sample predicted probabilities": [[96, "3.-Define-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find issues in your dataset": [[96, "4.-Use-cleanlab-to-find-issues-in-your-dataset"]], "Non-IID issues (data drift)": [[96, "Non-IID-issues-(data-drift)"]], "Miscellaneous workflows with Datalab": [[97, "Miscellaneous-workflows-with-Datalab"]], "Accelerate Issue Checks with Pre-computed kNN Graphs": [[97, "Accelerate-Issue-Checks-with-Pre-computed-kNN-Graphs"]], "1. Load and Prepare Your Dataset": [[97, "1.-Load-and-Prepare-Your-Dataset"]], "2. Compute kNN Graph": [[97, "2.-Compute-kNN-Graph"]], "3. Train a Classifier and Obtain Predicted Probabilities": [[97, "3.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"]], "4. Identify Data Issues Using Datalab": [[97, "4.-Identify-Data-Issues-Using-Datalab"]], "Explanation:": [[97, "Explanation:"]], "Data Valuation": [[97, "Data-Valuation"]], "1. Load and Prepare the Dataset": [[97, "1.-Load-and-Prepare-the-Dataset"], [97, "id2"], [97, "id5"]], "2. Vectorize the Text Data": [[97, "2.-Vectorize-the-Text-Data"]], "3. Perform Data Valuation with Datalab": [[97, "3.-Perform-Data-Valuation-with-Datalab"]], "4. (Optional) Visualize Data Valuation Scores": [[97, "4.-(Optional)-Visualize-Data-Valuation-Scores"]], "Find Underperforming Groups in a Dataset": [[97, "Find-Underperforming-Groups-in-a-Dataset"]], "1. Generate a Synthetic Dataset": [[97, "1.-Generate-a-Synthetic-Dataset"]], "2. Train a Classifier and Obtain Predicted Probabilities": [[97, "2.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"], [97, "id3"]], "3. (Optional) Cluster the Data": [[97, "3.-(Optional)-Cluster-the-Data"]], "4. Identify Underperforming Groups with Datalab": [[97, "4.-Identify-Underperforming-Groups-with-Datalab"], [97, "id4"]], "5. (Optional) Visualize the Results": [[97, "5.-(Optional)-Visualize-the-Results"]], "Predefining Data Slices for Detecting Underperforming Groups": [[97, "Predefining-Data-Slices-for-Detecting-Underperforming-Groups"]], "3. Define a Data Slice": [[97, "3.-Define-a-Data-Slice"]], "Detect if your dataset is non-IID": [[97, "Detect-if-your-dataset-is-non-IID"]], "2. Detect Non-IID Issues Using Datalab": [[97, "2.-Detect-Non-IID-Issues-Using-Datalab"]], "3. (Optional) Visualize the Results": [[97, "3.-(Optional)-Visualize-the-Results"]], "Catch Null Values in a Dataset": [[97, "Catch-Null-Values-in-a-Dataset"]], "1. Load the Dataset": [[97, "1.-Load-the-Dataset"], [97, "id8"]], "2: Encode Categorical Values": [[97, "2:-Encode-Categorical-Values"]], "3. Initialize Datalab": [[97, "3.-Initialize-Datalab"]], "4. Detect Null Values": [[97, "4.-Detect-Null-Values"]], "5. Sort the Dataset by Null Issues": [[97, "5.-Sort-the-Dataset-by-Null-Issues"]], "6. (Optional) Visualize the Results": [[97, "6.-(Optional)-Visualize-the-Results"]], "Detect class imbalance in your dataset": [[97, "Detect-class-imbalance-in-your-dataset"]], "1. Prepare data": [[97, "1.-Prepare-data"]], "2. Detect class imbalance with Datalab": [[97, "2.-Detect-class-imbalance-with-Datalab"]], "3. (Optional) Visualize class imbalance issues": [[97, "3.-(Optional)-Visualize-class-imbalance-issues"]], "Identify Spurious Correlations in Image Datasets": [[97, "Identify-Spurious-Correlations-in-Image-Datasets"]], "2. Run Datalab Analysis": [[97, "2.-Run-Datalab-Analysis"]], "3. Interpret the Results": [[97, "3.-Interpret-the-Results"]], "Understanding Dataset-level Labeling Issues": [[98, "Understanding-Dataset-level-Labeling-Issues"]], "Install dependencies and import them": [[98, "Install-dependencies-and-import-them"], [101, "Install-dependencies-and-import-them"]], "Fetch the data (can skip these details)": [[98, "Fetch-the-data-(can-skip-these-details)"]], "Start of tutorial: Evaluate the health of 8 popular datasets": [[98, "Start-of-tutorial:-Evaluate-the-health-of-8-popular-datasets"]], "FAQ": [[99, "FAQ"]], "What data can cleanlab detect issues in?": [[99, "What-data-can-cleanlab-detect-issues-in?"]], "How do I format classification labels for cleanlab?": [[99, "How-do-I-format-classification-labels-for-cleanlab?"]], "How do I infer the correct labels for examples cleanlab has flagged?": [[99, "How-do-I-infer-the-correct-labels-for-examples-cleanlab-has-flagged?"]], "How should I handle label errors in train vs. test data?": [[99, "How-should-I-handle-label-errors-in-train-vs.-test-data?"]], "How can I find label issues in big datasets with limited memory?": [[99, "How-can-I-find-label-issues-in-big-datasets-with-limited-memory?"]], "Why isn\u2019t CleanLearning working for me?": [[99, "Why-isn\u2019t-CleanLearning-working-for-me?"]], "How can I use different models for data cleaning vs. final training in CleanLearning?": [[99, "How-can-I-use-different-models-for-data-cleaning-vs.-final-training-in-CleanLearning?"]], "How do I hyperparameter tune only the final model trained (and not the one finding label issues) in CleanLearning?": [[99, "How-do-I-hyperparameter-tune-only-the-final-model-trained-(and-not-the-one-finding-label-issues)-in-CleanLearning?"]], "Why does regression.learn.CleanLearning take so long?": [[99, "Why-does-regression.learn.CleanLearning-take-so-long?"]], "How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?": [[99, "How-do-I-specify-pre-computed-data-slices/clusters-when-detecting-the-Underperforming-Group-Issue?"]], "How to handle near-duplicate data identified by Datalab?": [[99, "How-to-handle-near-duplicate-data-identified-by-Datalab?"]], "What ML models should I run cleanlab with? How do I fix the issues cleanlab has identified?": [[99, "What-ML-models-should-I-run-cleanlab-with?-How-do-I-fix-the-issues-cleanlab-has-identified?"]], "What license is cleanlab open-sourced under?": [[99, "What-license-is-cleanlab-open-sourced-under?"]], "Can\u2019t find an answer to your question?": [[99, "Can't-find-an-answer-to-your-question?"]], "Improving ML Performance via Data Curation with Train vs Test Splits": [[100, "Improving-ML-Performance-via-Data-Curation-with-Train-vs-Test-Splits"]], "Why did you make this tutorial?": [[100, "Why-did-you-make-this-tutorial?"]], "1. Install dependencies": [[100, "1.-Install-dependencies"]], "2. Preprocess the data": [[100, "2.-Preprocess-the-data"]], "3. Check for fundamental problems in the train/test setup": [[100, "3.-Check-for-fundamental-problems-in-the-train/test-setup"]], "4. Train model with original (noisy) training data": [[100, "4.-Train-model-with-original-(noisy)-training-data"]], "Compute out-of-sample predicted probabilities for the test data from this baseline model": [[100, "Compute-out-of-sample-predicted-probabilities-for-the-test-data-from-this-baseline-model"]], "5. Check for issues in test data and manually address them": [[100, "5.-Check-for-issues-in-test-data-and-manually-address-them"]], "Use clean test data to evaluate the performance of model trained on noisy training data": [[100, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-noisy-training-data"]], "6. Check for issues in training data and algorithmically correct them": [[100, "6.-Check-for-issues-in-training-data-and-algorithmically-correct-them"]], "7. Train model on cleaned training data": [[100, "7.-Train-model-on-cleaned-training-data"]], "Use clean test data to evaluate the performance of model trained on cleaned training data": [[100, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-cleaned-training-data"]], "8. Identifying better training data curation strategies via hyperparameter optimization techniques": [[100, "8.-Identifying-better-training-data-curation-strategies-via-hyperparameter-optimization-techniques"]], "9. Conclusion": [[100, "9.-Conclusion"]], "The Workflows of Data-centric AI for Classification with Noisy Labels": [[101, "The-Workflows-of-Data-centric-AI-for-Classification-with-Noisy-Labels"]], "Create the data (can skip these details)": [[101, "Create-the-data-(can-skip-these-details)"]], "Workflow 1: Use Datalab to detect many types of issues": [[101, "Workflow-1:-Use-Datalab-to-detect-many-types-of-issues"]], "Workflow 2: Use CleanLearning for more robust Machine Learning": [[101, "Workflow-2:-Use-CleanLearning-for-more-robust-Machine-Learning"]], "Clean Learning = Machine Learning with cleaned data": [[101, "Clean-Learning-=-Machine-Learning-with-cleaned-data"]], "Workflow 3: Use CleanLearning to find_label_issues in one line of code": [[101, "Workflow-3:-Use-CleanLearning-to-find_label_issues-in-one-line-of-code"]], "Visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[101, "Visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 4: Use cleanlab to find dataset-level and class-level issues": [[101, "Workflow-4:-Use-cleanlab-to-find-dataset-level-and-class-level-issues"]], "Now, let\u2019s see what happens if we merge classes \u201cseafoam green\u201d and \u201cyellow\u201d": [[101, "Now,-let's-see-what-happens-if-we-merge-classes-%22seafoam-green%22-and-%22yellow%22"]], "Workflow 5: Clean your test set too if you\u2019re doing ML with noisy labels!": [[101, "Workflow-5:-Clean-your-test-set-too-if-you're-doing-ML-with-noisy-labels!"]], "Workflow 6: One score to rule them all \u2013 use cleanlab\u2019s overall dataset health score": [[101, "Workflow-6:-One-score-to-rule-them-all----use-cleanlab's-overall-dataset-health-score"]], "How accurate is this dataset health score?": [[101, "How-accurate-is-this-dataset-health-score?"]], "Workflow(s) 7: Use count, rank, filter modules directly": [[101, "Workflow(s)-7:-Use-count,-rank,-filter-modules-directly"]], "Workflow 7.1 (count): Fully characterize label noise (noise matrix, joint, prior of true labels, \u2026)": [[101, "Workflow-7.1-(count):-Fully-characterize-label-noise-(noise-matrix,-joint,-prior-of-true-labels,-...)"]], "Use cleanlab to estimate and visualize the joint distribution of label noise and noise matrix of label flipping rates:": [[101, "Use-cleanlab-to-estimate-and-visualize-the-joint-distribution-of-label-noise-and-noise-matrix-of-label-flipping-rates:"]], "Workflow 7.2 (filter): Find label issues for any dataset and any model in one line of code": [[101, "Workflow-7.2-(filter):-Find-label-issues-for-any-dataset-and-any-model-in-one-line-of-code"]], "Again, we can visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[101, "Again,-we-can-visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 7.2 supports lots of methods to find_label_issues() via the filter_by parameter.": [[101, "Workflow-7.2-supports-lots-of-methods-to-find_label_issues()-via-the-filter_by-parameter."]], "Workflow 7.3 (rank): Automatically rank every example by a unique label quality score. Find errors using cleanlab.count.num_label_issues as a threshold.": [[101, "Workflow-7.3-(rank):-Automatically-rank-every-example-by-a-unique-label-quality-score.-Find-errors-using-cleanlab.count.num_label_issues-as-a-threshold."]], "Again, we can visualize the label issues found to see if Cleanlab works.": [[101, "Again,-we-can-visualize-the-label-issues-found-to-see-if-Cleanlab-works."]], "Not sure when to use Workflow 7.2 or 7.3 to find label issues?": [[101, "Not-sure-when-to-use-Workflow-7.2-or-7.3-to-find-label-issues?"]], "Workflow 8: Ensembling label quality scores from multiple predictors": [[101, "Workflow-8:-Ensembling-label-quality-scores-from-multiple-predictors"]], "Tutorials": [[102, "tutorials"]], "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators": [[103, "Estimate-Consensus-and-Annotator-Quality-for-Data-Labeled-by-Multiple-Annotators"]], "2. Create the data (can skip these details)": [[103, "2.-Create-the-data-(can-skip-these-details)"]], "3. Get initial consensus labels via majority vote and compute out-of-sample predicted probabilities": [[103, "3.-Get-initial-consensus-labels-via-majority-vote-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to get better consensus labels and other statistics": [[103, "4.-Use-cleanlab-to-get-better-consensus-labels-and-other-statistics"]], "Comparing improved consensus labels": [[103, "Comparing-improved-consensus-labels"]], "Inspecting consensus quality scores to find potential consensus label errors": [[103, "Inspecting-consensus-quality-scores-to-find-potential-consensus-label-errors"]], "5. Retrain model using improved consensus labels": [[103, "5.-Retrain-model-using-improved-consensus-labels"]], "Further improvements": [[103, "Further-improvements"]], "How does cleanlab.multiannotator work?": [[103, "How-does-cleanlab.multiannotator-work?"]], "Find Label Errors in Multi-Label Classification Datasets": [[104, "Find-Label-Errors-in-Multi-Label-Classification-Datasets"]], "1. Install required dependencies and get dataset": [[104, "1.-Install-required-dependencies-and-get-dataset"]], "2. Format data, labels, and model predictions": [[104, "2.-Format-data,-labels,-and-model-predictions"], [105, "2.-Format-data,-labels,-and-model-predictions"]], "3. Use cleanlab to find label issues": [[104, "3.-Use-cleanlab-to-find-label-issues"], [105, "3.-Use-cleanlab-to-find-label-issues"], [109, "3.-Use-cleanlab-to-find-label-issues"], [110, "3.-Use-cleanlab-to-find-label-issues"]], "Label quality scores": [[104, "Label-quality-scores"]], "Data issues beyond mislabeling (outliers, duplicates, drift, \u2026)": [[104, "Data-issues-beyond-mislabeling-(outliers,-duplicates,-drift,-...)"]], "How to format labels given as a one-hot (multi-hot) binary matrix?": [[104, "How-to-format-labels-given-as-a-one-hot-(multi-hot)-binary-matrix?"]], "Estimate label issues without Datalab": [[104, "Estimate-label-issues-without-Datalab"]], "Application to Real Data": [[104, "Application-to-Real-Data"]], "Finding Label Errors in Object Detection Datasets": [[105, "Finding-Label-Errors-in-Object-Detection-Datasets"]], "1. Install required dependencies and download data": [[105, "1.-Install-required-dependencies-and-download-data"], [109, "1.-Install-required-dependencies-and-download-data"], [110, "1.-Install-required-dependencies-and-download-data"]], "Get label quality scores": [[105, "Get-label-quality-scores"], [109, "Get-label-quality-scores"]], "4. Use ObjectLab to visualize label issues": [[105, "4.-Use-ObjectLab-to-visualize-label-issues"]], "Different kinds of label issues identified by ObjectLab": [[105, "Different-kinds-of-label-issues-identified-by-ObjectLab"]], "Other uses of visualize": [[105, "Other-uses-of-visualize"]], "Exploratory data analysis": [[105, "Exploratory-data-analysis"]], "Detect Outliers with Cleanlab and PyTorch Image Models (timm)": [[106, "Detect-Outliers-with-Cleanlab-and-PyTorch-Image-Models-(timm)"]], "1. Install the required dependencies": [[106, "1.-Install-the-required-dependencies"]], "2. Pre-process the Cifar10 dataset": [[106, "2.-Pre-process-the-Cifar10-dataset"]], "Visualize some of the training and test examples": [[106, "Visualize-some-of-the-training-and-test-examples"]], "3. Use cleanlab and feature embeddings to find outliers in the data": [[106, "3.-Use-cleanlab-and-feature-embeddings-to-find-outliers-in-the-data"]], "4. Use cleanlab and pred_probs to find outliers in the data": [[106, "4.-Use-cleanlab-and-pred_probs-to-find-outliers-in-the-data"]], "Computing Out-of-Sample Predicted Probabilities with Cross-Validation": [[107, "computing-out-of-sample-predicted-probabilities-with-cross-validation"]], "Out-of-sample predicted probabilities?": [[107, "out-of-sample-predicted-probabilities"]], "What is K-fold cross-validation?": [[107, "what-is-k-fold-cross-validation"]], "Find Noisy Labels in Regression Datasets": [[108, "Find-Noisy-Labels-in-Regression-Datasets"]], "3. Define a regression model and use cleanlab to find potential label errors": [[108, "3.-Define-a-regression-model-and-use-cleanlab-to-find-potential-label-errors"]], "5. Other ways to find noisy labels in regression datasets": [[108, "5.-Other-ways-to-find-noisy-labels-in-regression-datasets"]], "Find Label Errors in Semantic Segmentation Datasets": [[109, "Find-Label-Errors-in-Semantic-Segmentation-Datasets"]], "2. Get data, labels, and pred_probs": [[109, "2.-Get-data,-labels,-and-pred_probs"], [110, "2.-Get-data,-labels,-and-pred_probs"]], "Visualize top label issues": [[109, "Visualize-top-label-issues"]], "Classes which are commonly mislabeled overall": [[109, "Classes-which-are-commonly-mislabeled-overall"]], "Focusing on one specific class": [[109, "Focusing-on-one-specific-class"]], "Find Label Errors in Token Classification (Text) Datasets": [[110, "Find-Label-Errors-in-Token-Classification-(Text)-Datasets"]], "Most common word-level token mislabels": [[110, "Most-common-word-level-token-mislabels"]], "Find sentences containing a particular mislabeled word": [[110, "Find-sentences-containing-a-particular-mislabeled-word"]], "Sentence label quality score": [[110, "Sentence-label-quality-score"]], "How does cleanlab.token_classification work?": [[110, "How-does-cleanlab.token_classification-work?"]]}, "indexentries": {"cleanlab.benchmarking": [[0, "module-cleanlab.benchmarking"]], "module": [[0, "module-cleanlab.benchmarking"], [1, "module-cleanlab.benchmarking.noise_generation"], [2, "module-cleanlab.classification"], [3, "module-cleanlab.count"], [4, "module-cleanlab.data_valuation"], [5, "module-cleanlab.datalab.datalab"], [12, "module-cleanlab.datalab"], [13, "module-cleanlab.datalab.internal.adapter.imagelab"], [15, "module-cleanlab.datalab.internal.data"], [16, "module-cleanlab.datalab.internal.data_issues"], [17, "module-cleanlab.datalab.internal.issue_manager_factory"], [18, "module-cleanlab.datalab.internal"], [19, "module-cleanlab.datalab.internal.issue_finder"], [21, "module-cleanlab.datalab.internal.issue_manager.data_valuation"], [22, "module-cleanlab.datalab.internal.issue_manager.duplicate"], [23, "module-cleanlab.datalab.internal.issue_manager.imbalance"], [25, "module-cleanlab.datalab.internal.issue_manager.issue_manager"], [26, "module-cleanlab.datalab.internal.issue_manager.label"], [28, "module-cleanlab.datalab.internal.issue_manager.multilabel.label"], [29, "module-cleanlab.datalab.internal.issue_manager.noniid"], [30, "module-cleanlab.datalab.internal.issue_manager.null"], [31, "module-cleanlab.datalab.internal.issue_manager.outlier"], [33, "module-cleanlab.datalab.internal.issue_manager.regression.label"], [34, "module-cleanlab.datalab.internal.issue_manager.underperforming_group"], [35, "module-cleanlab.datalab.internal.model_outputs"], [36, "module-cleanlab.datalab.internal.report"], [37, "module-cleanlab.datalab.internal.task"], [39, "module-cleanlab.dataset"], [40, "module-cleanlab.experimental.cifar_cnn"], [41, "module-cleanlab.experimental.coteaching"], [42, "module-cleanlab.experimental"], [43, "module-cleanlab.experimental.label_issues_batched"], [44, "module-cleanlab.experimental.mnist_pytorch"], [45, "module-cleanlab.experimental.span_classification"], [46, "module-cleanlab.filter"], [47, "module-cleanlab.internal"], [48, "module-cleanlab.internal.label_quality_utils"], [49, "module-cleanlab.internal.latent_algebra"], [50, "module-cleanlab.internal.multiannotator_utils"], [51, "module-cleanlab.internal.multilabel_scorer"], [52, "module-cleanlab.internal.multilabel_utils"], [53, "module-cleanlab.internal.neighbor"], [54, "module-cleanlab.internal.neighbor.knn_graph"], [55, "module-cleanlab.internal.neighbor.metric"], [56, "module-cleanlab.internal.neighbor.search"], [57, "module-cleanlab.internal.outlier"], [58, "module-cleanlab.internal.token_classification_utils"], [59, "module-cleanlab.internal.util"], [60, "module-cleanlab.internal.validation"], [61, "module-cleanlab.models"], [62, "module-cleanlab.models.keras"], [63, "module-cleanlab.multiannotator"], [64, "module-cleanlab.multilabel_classification.dataset"], [65, "module-cleanlab.multilabel_classification.filter"], [66, "module-cleanlab.multilabel_classification"], [67, "module-cleanlab.multilabel_classification.rank"], [68, "module-cleanlab.object_detection.filter"], [69, "module-cleanlab.object_detection"], [70, "module-cleanlab.object_detection.rank"], [71, "module-cleanlab.object_detection.summary"], [72, "module-cleanlab.outlier"], [73, "module-cleanlab.rank"], [74, "module-cleanlab.regression"], [75, "module-cleanlab.regression.learn"], [76, "module-cleanlab.regression.rank"], [77, "module-cleanlab.segmentation.filter"], [78, "module-cleanlab.segmentation"], [79, "module-cleanlab.segmentation.rank"], [80, "module-cleanlab.segmentation.summary"], [81, "module-cleanlab.token_classification.filter"], [82, "module-cleanlab.token_classification"], [83, "module-cleanlab.token_classification.rank"], [84, "module-cleanlab.token_classification.summary"]], "cleanlab.benchmarking.noise_generation": [[1, "module-cleanlab.benchmarking.noise_generation"]], "generate_n_rand_probabilities_that_sum_to_m() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.generate_n_rand_probabilities_that_sum_to_m"]], "generate_noise_matrix_from_trace() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.generate_noise_matrix_from_trace"]], "generate_noisy_labels() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.generate_noisy_labels"]], "noise_matrix_is_valid() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.noise_matrix_is_valid"]], "randomly_distribute_n_balls_into_k_bins() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.randomly_distribute_N_balls_into_K_bins"]], "cleanlearning (class in cleanlab.classification)": [[2, "cleanlab.classification.CleanLearning"]], "__init_subclass__() (cleanlab.classification.cleanlearning class method)": [[2, "cleanlab.classification.CleanLearning.__init_subclass__"]], "cleanlab.classification": [[2, "module-cleanlab.classification"]], "find_label_issues() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.find_label_issues"]], "fit() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.fit"]], "get_label_issues() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.get_label_issues"]], "get_metadata_routing() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.get_metadata_routing"]], "get_params() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.get_params"]], "predict() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.predict"]], "predict_proba() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.predict_proba"]], "save_space() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.save_space"]], "score() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.score"]], "set_fit_request() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.set_fit_request"]], "set_params() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.set_params"]], "set_score_request() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.set_score_request"]], "calibrate_confident_joint() (in module cleanlab.count)": [[3, "cleanlab.count.calibrate_confident_joint"]], "cleanlab.count": [[3, "module-cleanlab.count"]], "compute_confident_joint() (in module cleanlab.count)": [[3, "cleanlab.count.compute_confident_joint"]], "estimate_confident_joint_and_cv_pred_proba() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_confident_joint_and_cv_pred_proba"]], "estimate_cv_predicted_probabilities() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_cv_predicted_probabilities"]], "estimate_joint() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_joint"]], "estimate_latent() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_latent"]], "estimate_noise_matrices() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_noise_matrices"]], "estimate_py_and_noise_matrices_from_probabilities() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_py_and_noise_matrices_from_probabilities"]], "estimate_py_noise_matrices_and_cv_pred_proba() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_py_noise_matrices_and_cv_pred_proba"]], "get_confident_thresholds() (in module cleanlab.count)": [[3, "cleanlab.count.get_confident_thresholds"]], "num_label_issues() (in module cleanlab.count)": [[3, "cleanlab.count.num_label_issues"]], "cleanlab.data_valuation": [[4, "module-cleanlab.data_valuation"]], "data_shapley_knn() (in module cleanlab.data_valuation)": [[4, "cleanlab.data_valuation.data_shapley_knn"]], "datalab (class in cleanlab.datalab.datalab)": [[5, "cleanlab.datalab.datalab.Datalab"]], "class_names (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.class_names"]], "cleanlab.datalab.datalab": [[5, "module-cleanlab.datalab.datalab"]], "find_issues() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.find_issues"]], "get_info() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.get_info"]], "get_issue_summary() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.get_issue_summary"]], "get_issues() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.get_issues"]], "has_labels (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.has_labels"]], "info (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.info"]], "issue_summary (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.issue_summary"]], "issues (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.issues"]], "labels (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.labels"]], "list_default_issue_types() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.list_default_issue_types"]], "list_possible_issue_types() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.list_possible_issue_types"]], "load() (cleanlab.datalab.datalab.datalab static method)": [[5, "cleanlab.datalab.datalab.Datalab.load"]], "report() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.report"]], "save() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.save"]], "cleanlab.datalab": [[12, "module-cleanlab.datalab"]], "correlationreporter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationReporter"]], "correlationvisualizer (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationVisualizer"]], "imagelabdataissuesadapter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter"]], "imagelabissuefinderadapter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter"]], "imagelabreporteradapter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter"]], "cleanlab.datalab.internal.adapter.imagelab": [[13, "module-cleanlab.datalab.internal.adapter.imagelab"]], "collect_issues_from_imagelab() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.collect_issues_from_imagelab"]], "collect_issues_from_issue_manager() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.collect_issues_from_issue_manager"]], "collect_statistics() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.collect_statistics"]], "create_imagelab() (in module cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.create_imagelab"]], "filter_based_on_max_prevalence() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.filter_based_on_max_prevalence"]], "find_issues() (cleanlab.datalab.internal.adapter.imagelab.imagelabissuefinderadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter.find_issues"]], "get_available_issue_types() (cleanlab.datalab.internal.adapter.imagelab.imagelabissuefinderadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter.get_available_issue_types"]], "get_info() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.get_info"]], "get_issue_summary() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.get_issue_summary"]], "get_issues() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.get_issues"]], "get_report() (cleanlab.datalab.internal.adapter.imagelab.imagelabreporteradapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter.get_report"]], "handle_spurious_correlations() (in module cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.handle_spurious_correlations"]], "report() (cleanlab.datalab.internal.adapter.imagelab.correlationreporter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationReporter.report"]], "report() (cleanlab.datalab.internal.adapter.imagelab.imagelabreporteradapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter.report"]], "set_health_score() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.set_health_score"]], "statistics (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter property)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.statistics"]], "visualize() (cleanlab.datalab.internal.adapter.imagelab.correlationvisualizer method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationVisualizer.visualize"]], "data (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.Data"]], "dataformaterror": [[15, "cleanlab.datalab.internal.data.DataFormatError"]], "datasetdicterror": [[15, "cleanlab.datalab.internal.data.DatasetDictError"]], "datasetloaderror": [[15, "cleanlab.datalab.internal.data.DatasetLoadError"]], "label (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.Label"]], "multiclass (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.MultiClass"]], "multilabel (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.MultiLabel"]], "add_note() (cleanlab.datalab.internal.data.dataformaterror method)": [[15, "cleanlab.datalab.internal.data.DataFormatError.add_note"]], "add_note() (cleanlab.datalab.internal.data.datasetdicterror method)": [[15, "cleanlab.datalab.internal.data.DatasetDictError.add_note"]], "add_note() (cleanlab.datalab.internal.data.datasetloaderror method)": [[15, "cleanlab.datalab.internal.data.DatasetLoadError.add_note"]], "args (cleanlab.datalab.internal.data.dataformaterror attribute)": [[15, "cleanlab.datalab.internal.data.DataFormatError.args"]], "args (cleanlab.datalab.internal.data.datasetdicterror attribute)": [[15, "cleanlab.datalab.internal.data.DatasetDictError.args"]], "args (cleanlab.datalab.internal.data.datasetloaderror attribute)": [[15, "cleanlab.datalab.internal.data.DatasetLoadError.args"]], "class_names (cleanlab.datalab.internal.data.data property)": [[15, "cleanlab.datalab.internal.data.Data.class_names"]], "class_names (cleanlab.datalab.internal.data.label property)": [[15, "cleanlab.datalab.internal.data.Label.class_names"]], "class_names (cleanlab.datalab.internal.data.multiclass property)": [[15, "cleanlab.datalab.internal.data.MultiClass.class_names"]], "class_names (cleanlab.datalab.internal.data.multilabel property)": [[15, "cleanlab.datalab.internal.data.MultiLabel.class_names"]], "cleanlab.datalab.internal.data": [[15, "module-cleanlab.datalab.internal.data"]], "has_labels (cleanlab.datalab.internal.data.data property)": [[15, "cleanlab.datalab.internal.data.Data.has_labels"]], "is_available (cleanlab.datalab.internal.data.label property)": [[15, "cleanlab.datalab.internal.data.Label.is_available"]], "is_available (cleanlab.datalab.internal.data.multiclass property)": [[15, "cleanlab.datalab.internal.data.MultiClass.is_available"]], "is_available (cleanlab.datalab.internal.data.multilabel property)": [[15, "cleanlab.datalab.internal.data.MultiLabel.is_available"]], "with_traceback() (cleanlab.datalab.internal.data.dataformaterror method)": [[15, "cleanlab.datalab.internal.data.DataFormatError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetdicterror method)": [[15, "cleanlab.datalab.internal.data.DatasetDictError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetloaderror method)": [[15, "cleanlab.datalab.internal.data.DatasetLoadError.with_traceback"]], "dataissues (class in cleanlab.datalab.internal.data_issues)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues"]], "cleanlab.datalab.internal.data_issues": [[16, "module-cleanlab.datalab.internal.data_issues"]], "collect_issues_from_imagelab() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.collect_issues_from_imagelab"]], "collect_issues_from_issue_manager() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.collect_issues_from_issue_manager"]], "collect_statistics() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.collect_statistics"]], "get_data_statistics() (in module cleanlab.datalab.internal.data_issues)": [[16, "cleanlab.datalab.internal.data_issues.get_data_statistics"]], "get_info() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.get_info"]], "get_issue_summary() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.get_issue_summary"]], "get_issues() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.get_issues"]], "info (cleanlab.datalab.internal.data_issues.dataissues attribute)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.info"]], "issue_summary (cleanlab.datalab.internal.data_issues.dataissues attribute)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.issue_summary"]], "issues (cleanlab.datalab.internal.data_issues.dataissues attribute)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.issues"]], "set_health_score() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.set_health_score"]], "statistics (cleanlab.datalab.internal.data_issues.dataissues property)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.statistics"]], "registry (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.REGISTRY"]], "cleanlab.datalab.internal.issue_manager_factory": [[17, "module-cleanlab.datalab.internal.issue_manager_factory"]], "list_default_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.list_default_issue_types"]], "list_possible_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.list_possible_issue_types"]], "register() (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.register"]], "cleanlab.datalab.internal": [[18, "module-cleanlab.datalab.internal"]], "issuefinder (class in cleanlab.datalab.internal.issue_finder)": [[19, "cleanlab.datalab.internal.issue_finder.IssueFinder"]], "cleanlab.datalab.internal.issue_finder": [[19, "module-cleanlab.datalab.internal.issue_finder"]], "find_issues() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[19, "cleanlab.datalab.internal.issue_finder.IssueFinder.find_issues"]], "get_available_issue_types() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[19, "cleanlab.datalab.internal.issue_finder.IssueFinder.get_available_issue_types"]], "default_threshold (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.DEFAULT_THRESHOLD"]], "datavaluationissuemanager (class in cleanlab.datalab.internal.issue_manager.data_valuation)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager"]], "cleanlab.datalab.internal.issue_manager.data_valuation": [[21, "module-cleanlab.datalab.internal.issue_manager.data_valuation"]], "collect_info() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.verbosity_levels"]], "nearduplicateissuemanager (class in cleanlab.datalab.internal.issue_manager.duplicate)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager"]], "cleanlab.datalab.internal.issue_manager.duplicate": [[22, "module-cleanlab.datalab.internal.issue_manager.duplicate"]], "collect_info() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.make_summary"]], "near_duplicate_sets (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.near_duplicate_sets"]], "report() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.verbosity_levels"]], "classimbalanceissuemanager (class in cleanlab.datalab.internal.issue_manager.imbalance)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager"]], "cleanlab.datalab.internal.issue_manager.imbalance": [[23, "module-cleanlab.datalab.internal.issue_manager.imbalance"]], "collect_info() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager class method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager class method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.verbosity_levels"]], "issuemanager (class in cleanlab.datalab.internal.issue_manager.issue_manager)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager"]], "cleanlab.datalab.internal.issue_manager.issue_manager": [[25, "module-cleanlab.datalab.internal.issue_manager.issue_manager"]], "collect_info() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager class method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager class method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.verbosity_levels"]], "labelissuemanager (class in cleanlab.datalab.internal.issue_manager.label)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.label": [[26, "module-cleanlab.datalab.internal.issue_manager.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.find_issues"]], "get_health_summary() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.get_health_summary"]], "health_summary_parameters (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.health_summary_parameters"]], "info (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager class method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager class method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.verbosity_levels"]], "multilabelissuemanager (class in cleanlab.datalab.internal.issue_manager.multilabel.label)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.multilabel.label": [[28, "module-cleanlab.datalab.internal.issue_manager.multilabel.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager class method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager class method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.verbosity_levels"]], "noniidissuemanager (class in cleanlab.datalab.internal.issue_manager.noniid)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager"]], "cleanlab.datalab.internal.issue_manager.noniid": [[29, "module-cleanlab.datalab.internal.issue_manager.noniid"]], "collect_info() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager class method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager class method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.report"]], "simplified_kolmogorov_smirnov_test() (in module cleanlab.datalab.internal.issue_manager.noniid)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.simplified_kolmogorov_smirnov_test"]], "summary (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.verbosity_levels"]], "nullissuemanager (class in cleanlab.datalab.internal.issue_manager.null)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager"]], "cleanlab.datalab.internal.issue_manager.null": [[30, "module-cleanlab.datalab.internal.issue_manager.null"]], "collect_info() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager class method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager class method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.verbosity_levels"]], "default_thresholds (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.DEFAULT_THRESHOLDS"]], "outlierissuemanager (class in cleanlab.datalab.internal.issue_manager.outlier)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager"]], "cleanlab.datalab.internal.issue_manager.outlier": [[31, "module-cleanlab.datalab.internal.issue_manager.outlier"]], "collect_info() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager class method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.make_summary"]], "metric (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.metric"]], "ood (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.ood"]], "report() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager class method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.verbosity_levels"]], "regressionlabelissuemanager (class in cleanlab.datalab.internal.issue_manager.regression.label)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.regression.label": [[33, "module-cleanlab.datalab.internal.issue_manager.regression.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.find_issues"]], "find_issues_with_features() (in module cleanlab.datalab.internal.issue_manager.regression.label)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.find_issues_with_features"]], "find_issues_with_predictions() (in module cleanlab.datalab.internal.issue_manager.regression.label)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.find_issues_with_predictions"]], "info (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager class method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager class method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.verbosity_levels"]], "no_underperforming_cluster_id (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.NO_UNDERPERFORMING_CLUSTER_ID"]], "outlier_cluster_labels (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.OUTLIER_CLUSTER_LABELS"]], "underperforminggroupissuemanager (class in cleanlab.datalab.internal.issue_manager.underperforming_group)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager"]], "cleanlab.datalab.internal.issue_manager.underperforming_group": [[34, "module-cleanlab.datalab.internal.issue_manager.underperforming_group"]], "collect_info() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.description"]], "filter_cluster_ids() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.filter_cluster_ids"]], "find_issues() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.find_issues"]], "get_underperforming_clusters() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.get_underperforming_clusters"]], "info (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager class method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.make_summary"]], "perform_clustering() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.perform_clustering"]], "report() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager class method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.verbosity_levels"]], "modeloutput (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput"]], "multiclasspredprobs (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs"]], "multilabelpredprobs (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs"]], "regressionpredictions (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions"]], "argument (cleanlab.datalab.internal.model_outputs.multiclasspredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.argument"]], "argument (cleanlab.datalab.internal.model_outputs.multilabelpredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.argument"]], "argument (cleanlab.datalab.internal.model_outputs.regressionpredictions attribute)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.argument"]], "cleanlab.datalab.internal.model_outputs": [[35, "module-cleanlab.datalab.internal.model_outputs"]], "collect() (cleanlab.datalab.internal.model_outputs.modeloutput method)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput.collect"]], "collect() (cleanlab.datalab.internal.model_outputs.multiclasspredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.collect"]], "collect() (cleanlab.datalab.internal.model_outputs.multilabelpredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.collect"]], "collect() (cleanlab.datalab.internal.model_outputs.regressionpredictions method)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.collect"]], "data (cleanlab.datalab.internal.model_outputs.modeloutput attribute)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput.data"]], "data (cleanlab.datalab.internal.model_outputs.multiclasspredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.data"]], "data (cleanlab.datalab.internal.model_outputs.multilabelpredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.data"]], "data (cleanlab.datalab.internal.model_outputs.regressionpredictions attribute)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.data"]], "validate() (cleanlab.datalab.internal.model_outputs.modeloutput method)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput.validate"]], "validate() (cleanlab.datalab.internal.model_outputs.multiclasspredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.validate"]], "validate() (cleanlab.datalab.internal.model_outputs.multilabelpredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.validate"]], "validate() (cleanlab.datalab.internal.model_outputs.regressionpredictions method)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.validate"]], "reporter (class in cleanlab.datalab.internal.report)": [[36, "cleanlab.datalab.internal.report.Reporter"]], "cleanlab.datalab.internal.report": [[36, "module-cleanlab.datalab.internal.report"]], "get_report() (cleanlab.datalab.internal.report.reporter method)": [[36, "cleanlab.datalab.internal.report.Reporter.get_report"]], "report() (cleanlab.datalab.internal.report.reporter method)": [[36, "cleanlab.datalab.internal.report.Reporter.report"]], "classification (cleanlab.datalab.internal.task.task attribute)": [[37, "cleanlab.datalab.internal.task.Task.CLASSIFICATION"]], "multilabel (cleanlab.datalab.internal.task.task attribute)": [[37, "cleanlab.datalab.internal.task.Task.MULTILABEL"]], "regression (cleanlab.datalab.internal.task.task attribute)": [[37, "cleanlab.datalab.internal.task.Task.REGRESSION"]], "task (class in cleanlab.datalab.internal.task)": [[37, "cleanlab.datalab.internal.task.Task"]], "__contains__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__contains__"]], "__getitem__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__getitem__"]], "__iter__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__iter__"]], "__len__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__len__"]], "cleanlab.datalab.internal.task": [[37, "module-cleanlab.datalab.internal.task"]], "from_str() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.from_str"]], "is_classification (cleanlab.datalab.internal.task.task property)": [[37, "cleanlab.datalab.internal.task.Task.is_classification"]], "is_multilabel (cleanlab.datalab.internal.task.task property)": [[37, "cleanlab.datalab.internal.task.Task.is_multilabel"]], "is_regression (cleanlab.datalab.internal.task.task property)": [[37, "cleanlab.datalab.internal.task.Task.is_regression"]], "cleanlab.dataset": [[39, "module-cleanlab.dataset"]], "find_overlapping_classes() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.find_overlapping_classes"]], "health_summary() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.health_summary"]], "overall_label_health_score() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.overall_label_health_score"]], "rank_classes_by_label_quality() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.rank_classes_by_label_quality"]], "cnn (class in cleanlab.experimental.cifar_cnn)": [[40, "cleanlab.experimental.cifar_cnn.CNN"]], "t_destination (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.T_destination"]], "__call__() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.__call__"]], "add_module() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.add_module"]], "apply() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.apply"]], "bfloat16() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.bfloat16"]], "buffers() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.buffers"]], "call_bn() (in module cleanlab.experimental.cifar_cnn)": [[40, "cleanlab.experimental.cifar_cnn.call_bn"]], "call_super_init (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.call_super_init"]], "children() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.children"]], "cleanlab.experimental.cifar_cnn": [[40, "module-cleanlab.experimental.cifar_cnn"]], "compile() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.compile"]], "cpu() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.cpu"]], "cuda() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.cuda"]], "double() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.double"]], "dump_patches (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.dump_patches"]], "eval() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.eval"]], "extra_repr() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.extra_repr"]], "float() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.float"]], "forward() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.forward"], [40, "id0"]], "get_buffer() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_buffer"]], "get_extra_state() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_extra_state"]], "get_parameter() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_parameter"]], "get_submodule() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_submodule"]], "half() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.half"]], "ipu() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.ipu"]], "load_state_dict() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.load_state_dict"]], "modules() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.modules"]], "named_buffers() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_buffers"]], "named_children() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_children"]], "named_modules() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_modules"]], "named_parameters() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_parameters"]], "parameters() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.parameters"]], "register_backward_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_backward_hook"]], "register_buffer() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_buffer"]], "register_forward_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_forward_hook"]], "register_forward_pre_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_forward_pre_hook"]], "register_full_backward_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_full_backward_hook"]], "register_full_backward_pre_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_full_backward_pre_hook"]], "register_load_state_dict_post_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_load_state_dict_post_hook"]], "register_module() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_module"]], "register_parameter() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_parameter"]], "register_state_dict_pre_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_state_dict_pre_hook"]], "requires_grad_() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.requires_grad_"]], "set_extra_state() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.set_extra_state"]], "share_memory() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.share_memory"]], "state_dict() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.state_dict"]], "to() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.to"]], "to_empty() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.to_empty"]], "train() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.train"]], "training (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.training"]], "type() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.type"]], "xpu() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.xpu"]], "zero_grad() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.zero_grad"]], "adjust_learning_rate() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.adjust_learning_rate"]], "cleanlab.experimental.coteaching": [[41, "module-cleanlab.experimental.coteaching"]], "evaluate() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.evaluate"]], "forget_rate_scheduler() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.forget_rate_scheduler"]], "initialize_lr_scheduler() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.initialize_lr_scheduler"]], "loss_coteaching() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.loss_coteaching"]], "train() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.train"]], "cleanlab.experimental": [[42, "module-cleanlab.experimental"]], "labelinspector (class in cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector"]], "adj_confident_thresholds_shared (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.adj_confident_thresholds_shared"]], "cleanlab.experimental.label_issues_batched": [[43, "module-cleanlab.experimental.label_issues_batched"]], "find_label_issues_batched() (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.find_label_issues_batched"]], "get_confident_thresholds() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_confident_thresholds"]], "get_label_issues() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_label_issues"]], "get_num_issues() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_num_issues"]], "get_quality_scores() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_quality_scores"]], "labels_shared (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.labels_shared"]], "pred_probs_shared (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.pred_probs_shared"]], "score_label_quality() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.score_label_quality"]], "split_arr() (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.split_arr"]], "update_confident_thresholds() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.update_confident_thresholds"]], "cnn (class in cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.CNN"]], "simplenet (class in cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet"]], "t_destination (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.T_destination"]], "__call__() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.__call__"]], "__init_subclass__() (cleanlab.experimental.mnist_pytorch.cnn class method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.__init_subclass__"]], "add_module() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.add_module"]], "apply() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.apply"]], "batch_size (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.batch_size"]], "bfloat16() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.bfloat16"]], "buffers() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.buffers"]], "call_super_init (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.call_super_init"]], "children() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.children"]], "cleanlab.experimental.mnist_pytorch": [[44, "module-cleanlab.experimental.mnist_pytorch"]], "compile() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.compile"]], "cpu() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.cpu"]], "cuda() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.cuda"]], "dataset (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.dataset"]], "double() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.double"]], "dump_patches (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.dump_patches"]], "epochs (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.epochs"]], "eval() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.eval"]], "extra_repr() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.extra_repr"]], "fit() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.fit"], [44, "id0"]], "float() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.float"]], "forward() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.forward"]], "get_buffer() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_buffer"]], "get_extra_state() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_extra_state"]], "get_metadata_routing() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.get_metadata_routing"]], "get_mnist_dataset() (in module cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.get_mnist_dataset"]], "get_parameter() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_parameter"]], "get_params() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.get_params"]], "get_sklearn_digits_dataset() (in module cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.get_sklearn_digits_dataset"]], "get_submodule() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_submodule"]], "half() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.half"]], "ipu() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.ipu"]], "load_state_dict() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.load_state_dict"]], "loader (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.loader"]], "log_interval (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.log_interval"]], "lr (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.lr"]], "modules() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.modules"]], "momentum (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.momentum"]], "named_buffers() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_buffers"]], "named_children() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_children"]], "named_modules() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_modules"]], "named_parameters() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_parameters"]], "no_cuda (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.no_cuda"]], "parameters() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.parameters"]], "predict() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.predict"], [44, "id1"]], "predict_proba() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.predict_proba"], [44, "id4"]], "register_backward_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_backward_hook"]], "register_buffer() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_buffer"]], "register_forward_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_forward_hook"]], "register_forward_pre_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_forward_pre_hook"]], "register_full_backward_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_full_backward_hook"]], "register_full_backward_pre_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_full_backward_pre_hook"]], "register_load_state_dict_post_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_load_state_dict_post_hook"]], "register_module() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_module"]], "register_parameter() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_parameter"]], "register_state_dict_pre_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_state_dict_pre_hook"]], "requires_grad_() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.requires_grad_"]], "seed (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.seed"]], "set_extra_state() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.set_extra_state"]], "set_fit_request() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_fit_request"]], "set_params() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_params"]], "set_predict_proba_request() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_predict_proba_request"]], "set_predict_request() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_predict_request"]], "share_memory() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.share_memory"]], "state_dict() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.state_dict"]], "test_batch_size (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.test_batch_size"]], "to() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.to"]], "to_empty() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.to_empty"]], "train() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.train"]], "training (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.training"]], "type() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.type"]], "xpu() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.xpu"]], "zero_grad() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.zero_grad"]], "cleanlab.experimental.span_classification": [[45, "module-cleanlab.experimental.span_classification"]], "display_issues() (in module cleanlab.experimental.span_classification)": [[45, "cleanlab.experimental.span_classification.display_issues"]], "find_label_issues() (in module cleanlab.experimental.span_classification)": [[45, "cleanlab.experimental.span_classification.find_label_issues"]], "get_label_quality_scores() (in module cleanlab.experimental.span_classification)": [[45, "cleanlab.experimental.span_classification.get_label_quality_scores"]], "cleanlab.filter": [[46, "module-cleanlab.filter"]], "find_label_issues() (in module cleanlab.filter)": [[46, "cleanlab.filter.find_label_issues"]], "find_label_issues_using_argmax_confusion_matrix() (in module cleanlab.filter)": [[46, "cleanlab.filter.find_label_issues_using_argmax_confusion_matrix"]], "find_predicted_neq_given() (in module cleanlab.filter)": [[46, "cleanlab.filter.find_predicted_neq_given"]], "pred_probs_by_class (in module cleanlab.filter)": [[46, "cleanlab.filter.pred_probs_by_class"]], "prune_count_matrix_cols (in module cleanlab.filter)": [[46, "cleanlab.filter.prune_count_matrix_cols"]], "cleanlab.internal": [[47, "module-cleanlab.internal"]], "cleanlab.internal.label_quality_utils": [[48, "module-cleanlab.internal.label_quality_utils"]], "get_normalized_entropy() (in module cleanlab.internal.label_quality_utils)": [[48, "cleanlab.internal.label_quality_utils.get_normalized_entropy"]], "cleanlab.internal.latent_algebra": [[49, "module-cleanlab.internal.latent_algebra"]], "compute_inv_noise_matrix() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_inv_noise_matrix"]], "compute_noise_matrix_from_inverse() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_noise_matrix_from_inverse"]], "compute_ps_py_inv_noise_matrix() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_ps_py_inv_noise_matrix"]], "compute_py() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_py"]], "compute_py_inv_noise_matrix() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_py_inv_noise_matrix"]], "compute_pyx() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_pyx"]], "assert_valid_inputs_multiannotator() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.assert_valid_inputs_multiannotator"]], "assert_valid_pred_probs() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.assert_valid_pred_probs"]], "check_consensus_label_classes() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.check_consensus_label_classes"]], "cleanlab.internal.multiannotator_utils": [[50, "module-cleanlab.internal.multiannotator_utils"]], "compute_soft_cross_entropy() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.compute_soft_cross_entropy"]], "find_best_temp_scaler() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.find_best_temp_scaler"]], "format_multiannotator_labels() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.format_multiannotator_labels"]], "temp_scale_pred_probs() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.temp_scale_pred_probs"]], "aggregator (class in cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.Aggregator"]], "confidence_weighted_entropy (cleanlab.internal.multilabel_scorer.classlabelscorer attribute)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.CONFIDENCE_WEIGHTED_ENTROPY"]], "classlabelscorer (class in cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer"]], "multilabelscorer (class in cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer"]], "normalized_margin (cleanlab.internal.multilabel_scorer.classlabelscorer attribute)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.NORMALIZED_MARGIN"]], "self_confidence (cleanlab.internal.multilabel_scorer.classlabelscorer attribute)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.SELF_CONFIDENCE"]], "__call__() (cleanlab.internal.multilabel_scorer.aggregator method)": [[51, "cleanlab.internal.multilabel_scorer.Aggregator.__call__"]], "__call__() (cleanlab.internal.multilabel_scorer.classlabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__call__"]], "__call__() (cleanlab.internal.multilabel_scorer.multilabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer.__call__"]], "__contains__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__contains__"]], "__getitem__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__getitem__"]], "__iter__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__iter__"]], "__len__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__len__"]], "aggregate() (cleanlab.internal.multilabel_scorer.multilabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer.aggregate"]], "cleanlab.internal.multilabel_scorer": [[51, "module-cleanlab.internal.multilabel_scorer"]], "exponential_moving_average() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.exponential_moving_average"]], "from_str() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.from_str"]], "get_class_label_quality_scores() (cleanlab.internal.multilabel_scorer.multilabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer.get_class_label_quality_scores"]], "get_cross_validated_multilabel_pred_probs() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.get_cross_validated_multilabel_pred_probs"]], "get_label_quality_scores() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.get_label_quality_scores"]], "multilabel_py() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.multilabel_py"]], "possible_methods (cleanlab.internal.multilabel_scorer.aggregator attribute)": [[51, "cleanlab.internal.multilabel_scorer.Aggregator.possible_methods"]], "softmin() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.softmin"]], "cleanlab.internal.multilabel_utils": [[52, "module-cleanlab.internal.multilabel_utils"]], "get_onehot_num_classes() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.get_onehot_num_classes"]], "int2onehot() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.int2onehot"]], "onehot2int() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.onehot2int"]], "stack_complement() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.stack_complement"]], "cleanlab.internal.neighbor": [[53, "module-cleanlab.internal.neighbor"]], "default_k (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.DEFAULT_K"]], "cleanlab.internal.neighbor.knn_graph": [[54, "module-cleanlab.internal.neighbor.knn_graph"]], "construct_knn_graph_from_index() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.construct_knn_graph_from_index"]], "correct_knn_distances_and_indices() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.correct_knn_distances_and_indices"]], "correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace"]], "correct_knn_graph() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.correct_knn_graph"]], "create_knn_graph_and_index() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.create_knn_graph_and_index"]], "features_to_knn() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.features_to_knn"]], "high_dimension_cutoff (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.HIGH_DIMENSION_CUTOFF"]], "row_count_cutoff (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.ROW_COUNT_CUTOFF"]], "cleanlab.internal.neighbor.metric": [[55, "module-cleanlab.internal.neighbor.metric"]], "decide_default_metric() (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.decide_default_metric"]], "decide_euclidean_metric() (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.decide_euclidean_metric"]], "cleanlab.internal.neighbor.search": [[56, "module-cleanlab.internal.neighbor.search"]], "construct_knn() (in module cleanlab.internal.neighbor.search)": [[56, "cleanlab.internal.neighbor.search.construct_knn"]], "cleanlab.internal.outlier": [[57, "module-cleanlab.internal.outlier"]], "correct_precision_errors() (in module cleanlab.internal.outlier)": [[57, "cleanlab.internal.outlier.correct_precision_errors"]], "transform_distances_to_scores() (in module cleanlab.internal.outlier)": [[57, "cleanlab.internal.outlier.transform_distances_to_scores"]], "cleanlab.internal.token_classification_utils": [[58, "module-cleanlab.internal.token_classification_utils"]], "color_sentence() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.color_sentence"]], "filter_sentence() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.filter_sentence"]], "get_sentence() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.get_sentence"]], "mapping() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.mapping"]], "merge_probs() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.merge_probs"]], "process_token() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.process_token"]], "append_extra_datapoint() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.append_extra_datapoint"]], "cleanlab.internal.util": [[59, "module-cleanlab.internal.util"]], "clip_noise_rates() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.clip_noise_rates"]], "clip_values() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.clip_values"]], "compress_int_array() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.compress_int_array"]], "confusion_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.confusion_matrix"]], "csr_vstack() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.csr_vstack"]], "estimate_pu_f1() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.estimate_pu_f1"]], "extract_indices_tf() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.extract_indices_tf"]], "force_two_dimensions() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.force_two_dimensions"]], "format_labels() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.format_labels"]], "get_missing_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.get_missing_classes"]], "get_num_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.get_num_classes"]], "get_unique_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.get_unique_classes"]], "is_tensorflow_dataset() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.is_tensorflow_dataset"]], "is_torch_dataset() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.is_torch_dataset"]], "num_unique_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.num_unique_classes"]], "print_inverse_noise_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_inverse_noise_matrix"]], "print_joint_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_joint_matrix"]], "print_noise_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_noise_matrix"]], "print_square_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_square_matrix"]], "remove_noise_from_class() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.remove_noise_from_class"]], "round_preserving_row_totals() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.round_preserving_row_totals"]], "round_preserving_sum() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.round_preserving_sum"]], "smart_display_dataframe() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.smart_display_dataframe"]], "subset_x_y() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.subset_X_y"]], "subset_data() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.subset_data"]], "subset_labels() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.subset_labels"]], "train_val_split() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.train_val_split"]], "unshuffle_tensorflow_dataset() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.unshuffle_tensorflow_dataset"]], "value_counts() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.value_counts"]], "value_counts_fill_missing_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.value_counts_fill_missing_classes"]], "assert_indexing_works() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_indexing_works"]], "assert_nonempty_input() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_nonempty_input"]], "assert_valid_class_labels() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_valid_class_labels"]], "assert_valid_inputs() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_valid_inputs"]], "cleanlab.internal.validation": [[60, "module-cleanlab.internal.validation"]], "labels_to_array() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.labels_to_array"]], "labels_to_list_multilabel() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.labels_to_list_multilabel"]], "cleanlab.models": [[61, "module-cleanlab.models"]], "keraswrappermodel (class in cleanlab.models.keras)": [[62, "cleanlab.models.keras.KerasWrapperModel"]], "keraswrappersequential (class in cleanlab.models.keras)": [[62, "cleanlab.models.keras.KerasWrapperSequential"]], "cleanlab.models.keras": [[62, "module-cleanlab.models.keras"]], "fit() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.fit"]], "fit() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.fit"]], "get_params() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.get_params"]], "get_params() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.get_params"]], "predict() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.predict"]], "predict() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.predict"]], "predict_proba() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.predict_proba"]], "predict_proba() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.predict_proba"]], "set_params() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.set_params"]], "set_params() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.set_params"]], "summary() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.summary"]], "summary() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.summary"]], "cleanlab.multiannotator": [[63, "module-cleanlab.multiannotator"]], "convert_long_to_wide_dataset() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.convert_long_to_wide_dataset"]], "get_active_learning_scores() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_active_learning_scores"]], "get_active_learning_scores_ensemble() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_active_learning_scores_ensemble"]], "get_label_quality_multiannotator() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_label_quality_multiannotator"]], "get_label_quality_multiannotator_ensemble() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_label_quality_multiannotator_ensemble"]], "get_majority_vote_label() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_majority_vote_label"]], "cleanlab.multilabel_classification.dataset": [[64, "module-cleanlab.multilabel_classification.dataset"]], "common_multilabel_issues() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.common_multilabel_issues"]], "multilabel_health_summary() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.multilabel_health_summary"]], "overall_multilabel_health_score() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.overall_multilabel_health_score"]], "rank_classes_by_multilabel_quality() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.rank_classes_by_multilabel_quality"]], "cleanlab.multilabel_classification.filter": [[65, "module-cleanlab.multilabel_classification.filter"]], "find_label_issues() (in module cleanlab.multilabel_classification.filter)": [[65, "cleanlab.multilabel_classification.filter.find_label_issues"]], "find_multilabel_issues_per_class() (in module cleanlab.multilabel_classification.filter)": [[65, "cleanlab.multilabel_classification.filter.find_multilabel_issues_per_class"]], "cleanlab.multilabel_classification": [[66, "module-cleanlab.multilabel_classification"]], "cleanlab.multilabel_classification.rank": [[67, "module-cleanlab.multilabel_classification.rank"]], "get_label_quality_scores() (in module cleanlab.multilabel_classification.rank)": [[67, "cleanlab.multilabel_classification.rank.get_label_quality_scores"]], "get_label_quality_scores_per_class() (in module cleanlab.multilabel_classification.rank)": [[67, "cleanlab.multilabel_classification.rank.get_label_quality_scores_per_class"]], "cleanlab.object_detection.filter": [[68, "module-cleanlab.object_detection.filter"]], "find_label_issues() (in module cleanlab.object_detection.filter)": [[68, "cleanlab.object_detection.filter.find_label_issues"]], "cleanlab.object_detection": [[69, "module-cleanlab.object_detection"]], "cleanlab.object_detection.rank": [[70, "module-cleanlab.object_detection.rank"]], "compute_badloc_box_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.compute_badloc_box_scores"]], "compute_overlooked_box_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.compute_overlooked_box_scores"]], "compute_swap_box_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.compute_swap_box_scores"]], "get_label_quality_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.issues_from_scores"]], "pool_box_scores_per_image() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.pool_box_scores_per_image"]], "bounding_box_size_distribution() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.bounding_box_size_distribution"]], "calculate_per_class_metrics() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.calculate_per_class_metrics"]], "class_label_distribution() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.class_label_distribution"]], "cleanlab.object_detection.summary": [[71, "module-cleanlab.object_detection.summary"]], "get_average_per_class_confusion_matrix() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.get_average_per_class_confusion_matrix"]], "get_sorted_bbox_count_idxs() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.get_sorted_bbox_count_idxs"]], "object_counts_per_image() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.object_counts_per_image"]], "plot_class_distribution() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.plot_class_distribution"]], "plot_class_size_distributions() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.plot_class_size_distributions"]], "visualize() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.visualize"]], "outofdistribution (class in cleanlab.outlier)": [[72, "cleanlab.outlier.OutOfDistribution"]], "cleanlab.outlier": [[72, "module-cleanlab.outlier"]], "fit() (cleanlab.outlier.outofdistribution method)": [[72, "cleanlab.outlier.OutOfDistribution.fit"]], "fit_score() (cleanlab.outlier.outofdistribution method)": [[72, "cleanlab.outlier.OutOfDistribution.fit_score"]], "score() (cleanlab.outlier.outofdistribution method)": [[72, "cleanlab.outlier.OutOfDistribution.score"]], "cleanlab.rank": [[73, "module-cleanlab.rank"]], "find_top_issues() (in module cleanlab.rank)": [[73, "cleanlab.rank.find_top_issues"]], "get_confidence_weighted_entropy_for_each_label() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_confidence_weighted_entropy_for_each_label"]], "get_label_quality_ensemble_scores() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_label_quality_ensemble_scores"]], "get_label_quality_scores() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_label_quality_scores"]], "get_normalized_margin_for_each_label() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_normalized_margin_for_each_label"]], "get_self_confidence_for_each_label() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_self_confidence_for_each_label"]], "order_label_issues() (in module cleanlab.rank)": [[73, "cleanlab.rank.order_label_issues"]], "cleanlab.regression": [[74, "module-cleanlab.regression"]], "cleanlearning (class in cleanlab.regression.learn)": [[75, "cleanlab.regression.learn.CleanLearning"]], "__init_subclass__() (cleanlab.regression.learn.cleanlearning class method)": [[75, "cleanlab.regression.learn.CleanLearning.__init_subclass__"]], "cleanlab.regression.learn": [[75, "module-cleanlab.regression.learn"]], "find_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.find_label_issues"]], "fit() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.fit"]], "get_aleatoric_uncertainty() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_aleatoric_uncertainty"]], "get_epistemic_uncertainty() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_epistemic_uncertainty"]], "get_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_label_issues"]], "get_metadata_routing() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_metadata_routing"]], "get_params() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_params"]], "predict() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.predict"]], "save_space() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.save_space"]], "score() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.score"]], "set_fit_request() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.set_fit_request"]], "set_params() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.set_params"]], "set_score_request() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.set_score_request"]], "cleanlab.regression.rank": [[76, "module-cleanlab.regression.rank"]], "get_label_quality_scores() (in module cleanlab.regression.rank)": [[76, "cleanlab.regression.rank.get_label_quality_scores"]], "cleanlab.segmentation.filter": [[77, "module-cleanlab.segmentation.filter"]], "find_label_issues() (in module cleanlab.segmentation.filter)": [[77, "cleanlab.segmentation.filter.find_label_issues"]], "cleanlab.segmentation": [[78, "module-cleanlab.segmentation"]], "cleanlab.segmentation.rank": [[79, "module-cleanlab.segmentation.rank"]], "get_label_quality_scores() (in module cleanlab.segmentation.rank)": [[79, "cleanlab.segmentation.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.segmentation.rank)": [[79, "cleanlab.segmentation.rank.issues_from_scores"]], "cleanlab.segmentation.summary": [[80, "module-cleanlab.segmentation.summary"]], "common_label_issues() (in module cleanlab.segmentation.summary)": [[80, "cleanlab.segmentation.summary.common_label_issues"]], "display_issues() (in module cleanlab.segmentation.summary)": [[80, "cleanlab.segmentation.summary.display_issues"]], "filter_by_class() (in module cleanlab.segmentation.summary)": [[80, "cleanlab.segmentation.summary.filter_by_class"]], "cleanlab.token_classification.filter": [[81, "module-cleanlab.token_classification.filter"]], "find_label_issues() (in module cleanlab.token_classification.filter)": [[81, "cleanlab.token_classification.filter.find_label_issues"]], "cleanlab.token_classification": [[82, "module-cleanlab.token_classification"]], "cleanlab.token_classification.rank": [[83, "module-cleanlab.token_classification.rank"]], "get_label_quality_scores() (in module cleanlab.token_classification.rank)": [[83, "cleanlab.token_classification.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.token_classification.rank)": [[83, "cleanlab.token_classification.rank.issues_from_scores"]], "cleanlab.token_classification.summary": [[84, "module-cleanlab.token_classification.summary"]], "common_label_issues() (in module cleanlab.token_classification.summary)": [[84, "cleanlab.token_classification.summary.common_label_issues"]], "display_issues() (in module cleanlab.token_classification.summary)": [[84, "cleanlab.token_classification.summary.display_issues"]], "filter_by_token() (in module cleanlab.token_classification.summary)": [[84, "cleanlab.token_classification.summary.filter_by_token"]]}}) \ No newline at end of file +Search.setIndex({"docnames": ["cleanlab/benchmarking/index", "cleanlab/benchmarking/noise_generation", "cleanlab/classification", "cleanlab/count", "cleanlab/data_valuation", "cleanlab/datalab/datalab", "cleanlab/datalab/guide/_templates/issue_types_tip", "cleanlab/datalab/guide/custom_issue_manager", "cleanlab/datalab/guide/generating_cluster_ids", "cleanlab/datalab/guide/index", "cleanlab/datalab/guide/issue_type_description", "cleanlab/datalab/guide/table", "cleanlab/datalab/index", "cleanlab/datalab/internal/adapter/imagelab", "cleanlab/datalab/internal/adapter/index", "cleanlab/datalab/internal/data", "cleanlab/datalab/internal/data_issues", "cleanlab/datalab/internal/factory", "cleanlab/datalab/internal/index", "cleanlab/datalab/internal/issue_finder", "cleanlab/datalab/internal/issue_manager/_notices/not_registered", "cleanlab/datalab/internal/issue_manager/data_valuation", "cleanlab/datalab/internal/issue_manager/duplicate", "cleanlab/datalab/internal/issue_manager/imbalance", "cleanlab/datalab/internal/issue_manager/index", "cleanlab/datalab/internal/issue_manager/issue_manager", "cleanlab/datalab/internal/issue_manager/label", "cleanlab/datalab/internal/issue_manager/multilabel/index", "cleanlab/datalab/internal/issue_manager/multilabel/label", "cleanlab/datalab/internal/issue_manager/noniid", "cleanlab/datalab/internal/issue_manager/null", "cleanlab/datalab/internal/issue_manager/outlier", "cleanlab/datalab/internal/issue_manager/regression/index", "cleanlab/datalab/internal/issue_manager/regression/label", "cleanlab/datalab/internal/issue_manager/underperforming_group", "cleanlab/datalab/internal/model_outputs", "cleanlab/datalab/internal/report", "cleanlab/datalab/internal/task", "cleanlab/datalab/optional_dependencies", "cleanlab/dataset", "cleanlab/experimental/cifar_cnn", "cleanlab/experimental/coteaching", "cleanlab/experimental/index", "cleanlab/experimental/label_issues_batched", "cleanlab/experimental/mnist_pytorch", "cleanlab/experimental/span_classification", "cleanlab/filter", "cleanlab/internal/index", "cleanlab/internal/label_quality_utils", "cleanlab/internal/latent_algebra", "cleanlab/internal/multiannotator_utils", "cleanlab/internal/multilabel_scorer", "cleanlab/internal/multilabel_utils", "cleanlab/internal/neighbor/index", "cleanlab/internal/neighbor/knn_graph", "cleanlab/internal/neighbor/metric", "cleanlab/internal/neighbor/search", "cleanlab/internal/outlier", "cleanlab/internal/token_classification_utils", "cleanlab/internal/util", "cleanlab/internal/validation", "cleanlab/models/index", "cleanlab/models/keras", "cleanlab/multiannotator", "cleanlab/multilabel_classification/dataset", "cleanlab/multilabel_classification/filter", "cleanlab/multilabel_classification/index", "cleanlab/multilabel_classification/rank", "cleanlab/object_detection/filter", "cleanlab/object_detection/index", "cleanlab/object_detection/rank", "cleanlab/object_detection/summary", "cleanlab/outlier", "cleanlab/rank", "cleanlab/regression/index", "cleanlab/regression/learn", "cleanlab/regression/rank", "cleanlab/segmentation/filter", "cleanlab/segmentation/index", "cleanlab/segmentation/rank", "cleanlab/segmentation/summary", "cleanlab/token_classification/filter", "cleanlab/token_classification/index", "cleanlab/token_classification/rank", "cleanlab/token_classification/summary", "index", "migrating/migrate_v2", "tutorials/clean_learning/index", "tutorials/clean_learning/tabular", "tutorials/clean_learning/text", "tutorials/datalab/audio", "tutorials/datalab/datalab_advanced", "tutorials/datalab/datalab_quickstart", "tutorials/datalab/image", "tutorials/datalab/index", "tutorials/datalab/tabular", "tutorials/datalab/text", "tutorials/datalab/workflows", "tutorials/dataset_health", "tutorials/faq", "tutorials/improving_ml_performance", "tutorials/indepth_overview", "tutorials/index", "tutorials/multiannotator", "tutorials/multilabel_classification", "tutorials/object_detection", "tutorials/outliers", "tutorials/pred_probs_cross_val", "tutorials/regression", "tutorials/segmentation", "tutorials/token_classification"], "filenames": ["cleanlab/benchmarking/index.rst", "cleanlab/benchmarking/noise_generation.rst", "cleanlab/classification.rst", "cleanlab/count.rst", "cleanlab/data_valuation.rst", "cleanlab/datalab/datalab.rst", "cleanlab/datalab/guide/_templates/issue_types_tip.rst", "cleanlab/datalab/guide/custom_issue_manager.rst", "cleanlab/datalab/guide/generating_cluster_ids.rst", "cleanlab/datalab/guide/index.rst", "cleanlab/datalab/guide/issue_type_description.rst", "cleanlab/datalab/guide/table.rst", "cleanlab/datalab/index.rst", "cleanlab/datalab/internal/adapter/imagelab.rst", "cleanlab/datalab/internal/adapter/index.rst", "cleanlab/datalab/internal/data.rst", "cleanlab/datalab/internal/data_issues.rst", "cleanlab/datalab/internal/factory.rst", "cleanlab/datalab/internal/index.rst", "cleanlab/datalab/internal/issue_finder.rst", "cleanlab/datalab/internal/issue_manager/_notices/not_registered.rst", "cleanlab/datalab/internal/issue_manager/data_valuation.rst", "cleanlab/datalab/internal/issue_manager/duplicate.rst", "cleanlab/datalab/internal/issue_manager/imbalance.rst", "cleanlab/datalab/internal/issue_manager/index.rst", "cleanlab/datalab/internal/issue_manager/issue_manager.rst", "cleanlab/datalab/internal/issue_manager/label.rst", "cleanlab/datalab/internal/issue_manager/multilabel/index.rst", "cleanlab/datalab/internal/issue_manager/multilabel/label.rst", "cleanlab/datalab/internal/issue_manager/noniid.rst", "cleanlab/datalab/internal/issue_manager/null.rst", "cleanlab/datalab/internal/issue_manager/outlier.rst", "cleanlab/datalab/internal/issue_manager/regression/index.rst", "cleanlab/datalab/internal/issue_manager/regression/label.rst", "cleanlab/datalab/internal/issue_manager/underperforming_group.rst", "cleanlab/datalab/internal/model_outputs.rst", "cleanlab/datalab/internal/report.rst", "cleanlab/datalab/internal/task.rst", "cleanlab/datalab/optional_dependencies.rst", "cleanlab/dataset.rst", "cleanlab/experimental/cifar_cnn.rst", "cleanlab/experimental/coteaching.rst", "cleanlab/experimental/index.rst", "cleanlab/experimental/label_issues_batched.rst", "cleanlab/experimental/mnist_pytorch.rst", "cleanlab/experimental/span_classification.rst", "cleanlab/filter.rst", "cleanlab/internal/index.rst", "cleanlab/internal/label_quality_utils.rst", "cleanlab/internal/latent_algebra.rst", "cleanlab/internal/multiannotator_utils.rst", "cleanlab/internal/multilabel_scorer.rst", "cleanlab/internal/multilabel_utils.rst", "cleanlab/internal/neighbor/index.rst", "cleanlab/internal/neighbor/knn_graph.rst", "cleanlab/internal/neighbor/metric.rst", "cleanlab/internal/neighbor/search.rst", "cleanlab/internal/outlier.rst", "cleanlab/internal/token_classification_utils.rst", "cleanlab/internal/util.rst", "cleanlab/internal/validation.rst", "cleanlab/models/index.rst", "cleanlab/models/keras.rst", "cleanlab/multiannotator.rst", "cleanlab/multilabel_classification/dataset.rst", "cleanlab/multilabel_classification/filter.rst", "cleanlab/multilabel_classification/index.rst", "cleanlab/multilabel_classification/rank.rst", "cleanlab/object_detection/filter.rst", "cleanlab/object_detection/index.rst", "cleanlab/object_detection/rank.rst", "cleanlab/object_detection/summary.rst", "cleanlab/outlier.rst", "cleanlab/rank.rst", "cleanlab/regression/index.rst", "cleanlab/regression/learn.rst", "cleanlab/regression/rank.rst", "cleanlab/segmentation/filter.rst", "cleanlab/segmentation/index.rst", "cleanlab/segmentation/rank.rst", "cleanlab/segmentation/summary.rst", "cleanlab/token_classification/filter.rst", "cleanlab/token_classification/index.rst", "cleanlab/token_classification/rank.rst", "cleanlab/token_classification/summary.rst", "index.rst", "migrating/migrate_v2.rst", "tutorials/clean_learning/index.rst", "tutorials/clean_learning/tabular.ipynb", "tutorials/clean_learning/text.ipynb", "tutorials/datalab/audio.ipynb", "tutorials/datalab/datalab_advanced.ipynb", "tutorials/datalab/datalab_quickstart.ipynb", "tutorials/datalab/image.ipynb", "tutorials/datalab/index.rst", "tutorials/datalab/tabular.ipynb", "tutorials/datalab/text.ipynb", "tutorials/datalab/workflows.ipynb", "tutorials/dataset_health.ipynb", "tutorials/faq.ipynb", "tutorials/improving_ml_performance.ipynb", "tutorials/indepth_overview.ipynb", "tutorials/index.rst", "tutorials/multiannotator.ipynb", "tutorials/multilabel_classification.ipynb", "tutorials/object_detection.ipynb", "tutorials/outliers.ipynb", "tutorials/pred_probs_cross_val.rst", "tutorials/regression.ipynb", "tutorials/segmentation.ipynb", "tutorials/token_classification.ipynb"], "titles": ["benchmarking", "noise_generation", "classification", "count", "data_valuation", "datalab", "<no title>", "Creating Your Own Issues Manager", "Generating Cluster IDs", "Datalab guides", "Datalab Issue Types", "<no title>", "datalab", "imagelab", "adapter", "data", "data_issues", "factory", "internal", "issue_finder", "<no title>", "data_valuation", "duplicate", "imbalance", "issue_manager", "issue_manager", "label", "multilabel", "label", "noniid", "null", "outlier", "regression", "label", "underperforming_group", "model_outputs", "report", "task", "<no title>", "dataset", "cifar_cnn", "coteaching", "experimental", "label_issues_batched", "mnist_pytorch", "span_classification", "filter", "internal", "label_quality_utils", "latent_algebra", "multiannotator_utils", "multilabel_scorer", "multilabel_utils", "neighbor", "knn_graph", "metric", "search", "outlier", "token_classification_utils", "util", "validation", "models", "keras", "multiannotator", "dataset", "filter", "multilabel_classification", "rank", "filter", "object_detection", "rank", "summary", "outlier", "rank", "regression", "regression.learn", "regression.rank", "filter", "segmentation", "rank", "summary", "filter", "token_classification", "rank", "summary", "cleanlab open-source documentation", "How to migrate to versions >= 2.0.0 from pre 1.0.1", "CleanLearning Tutorials", "Classification with Structured/Tabular Data and Noisy Labels", "Text Classification with Noisy Labels", "Detecting Issues in an Audio Dataset with Datalab", "Datalab: Advanced workflows to audit your data", "Datalab: A unified audit to detect all kinds of issues in data and labels", "Detecting Issues in an Image Dataset with Datalab", "Datalab Tutorials", "Detecting Issues in Tabular Data\u00a0(Numeric/Categorical columns) with Datalab", "Detecting Issues in a Text Dataset with Datalab", "Miscellaneous workflows with Datalab", "Understanding Dataset-level Labeling Issues", "FAQ", "Improving ML Performance via Data Curation with Train vs Test Splits", "The Workflows of Data-centric AI for Classification with Noisy Labels", "Tutorials", "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators", "Find Label Errors in Multi-Label Classification Datasets", "Finding Label Errors in Object Detection Datasets", "Detect Outliers with Cleanlab and PyTorch Image Models (timm)", "Computing Out-of-Sample Predicted Probabilities with Cross-Validation", "Find Noisy Labels in Regression Datasets", "Find Label Errors in Semantic Segmentation Datasets", "Find Label Errors in Token Classification (Text) Datasets"], "terms": {"noise_gener": [0, 86, 91, 92, 101, 103, 104], "noise_matrix_is_valid": [0, 1], "generate_noisy_label": [0, 1, 91, 92, 101, 103, 104], "generate_noise_matrix_from_trac": [0, 1, 91, 92, 101, 103, 104], "generate_n_rand_probabilities_that_sum_to_m": [0, 1], "randomly_distribute_n_balls_into_k_bin": [0, 1], "helper": [1, 19, 43, 48, 50, 51, 52, 53, 57, 58, 59, 70, 93, 97, 98, 110], "method": [1, 2, 3, 4, 5, 7, 10, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 56, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "ar": [1, 2, 3, 4, 5, 7, 10, 13, 14, 15, 16, 17, 18, 19, 21, 23, 24, 25, 26, 27, 29, 32, 33, 35, 37, 39, 40, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 110], "us": [1, 2, 3, 4, 5, 8, 9, 10, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 85, 86, 91, 98, 107], "benchmark": [1, 40, 85, 86, 91, 92, 101, 103, 104], "cleanlab": [1, 2, 3, 4, 5, 7, 12, 13, 14, 15, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 86, 91, 92, 97, 98, 100, 102, 107], "": [1, 2, 3, 4, 10, 21, 35, 39, 40, 44, 48, 51, 54, 56, 57, 59, 63, 64, 68, 70, 71, 72, 73, 75, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "core": [1, 43, 46, 77, 79], "algorithm": [1, 2, 8, 10, 34, 41, 45, 56, 57, 59, 63, 72, 81, 83, 85, 88, 89, 92, 95, 96, 97, 98, 99, 101, 103, 104, 106, 108, 110], "These": [1, 2, 3, 4, 5, 8, 10, 24, 40, 42, 44, 45, 46, 47, 54, 61, 63, 64, 67, 71, 72, 76, 80, 81, 83, 84, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "introduc": [1, 10, 90, 97, 99, 100, 101], "synthet": [1, 103, 104, 109], "nois": [1, 2, 3, 39, 46, 49, 59, 64, 91, 92, 97, 98, 103, 108], "label": [1, 2, 3, 4, 5, 7, 8, 9, 11, 13, 15, 17, 18, 19, 23, 24, 25, 27, 32, 34, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 59, 60, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 91, 97, 100, 102, 106, 107], "classif": [1, 3, 4, 5, 7, 10, 11, 13, 15, 17, 19, 35, 37, 39, 43, 45, 46, 49, 51, 52, 59, 63, 64, 65, 66, 67, 72, 73, 81, 82, 83, 84, 85, 86, 87, 90, 91, 92, 97, 100, 102, 103, 106, 107, 108, 109], "dataset": [1, 2, 3, 4, 5, 7, 9, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 28, 29, 30, 31, 33, 34, 42, 43, 44, 45, 46, 49, 51, 55, 59, 62, 63, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 88, 91, 95, 100, 102, 103, 107], "specif": [1, 3, 5, 9, 13, 17, 18, 19, 30, 36, 37, 42, 54, 55, 56, 61, 65, 68, 71, 80, 84, 93, 95, 96, 97, 100, 101, 105, 110], "thi": [1, 2, 3, 4, 5, 6, 7, 9, 10, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 103, 104, 105, 106, 107, 108, 109, 110], "modul": [1, 3, 13, 14, 16, 17, 18, 19, 24, 27, 32, 35, 36, 37, 39, 40, 41, 42, 43, 44, 46, 51, 53, 54, 56, 57, 59, 61, 63, 68, 71, 72, 73, 85, 93, 99, 104], "provid": [1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 13, 17, 19, 21, 26, 33, 37, 39, 40, 41, 43, 44, 46, 49, 53, 54, 56, 57, 59, 62, 63, 64, 65, 70, 71, 72, 73, 75, 77, 79, 80, 83, 84, 85, 88, 89, 90, 91, 92, 93, 96, 97, 99, 100, 101, 103, 106, 107, 108, 109, 110], "gener": [1, 2, 3, 7, 10, 21, 26, 28, 36, 39, 51, 54, 56, 59, 60, 72, 73, 75, 80, 89, 90, 91, 92, 93, 96, 98, 99, 100, 101, 103, 104, 106, 107, 109, 110], "valid": [1, 2, 3, 5, 10, 15, 35, 37, 39, 46, 47, 49, 50, 51, 54, 56, 57, 59, 63, 65, 68, 71, 73, 75, 76, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 108, 109, 110], "matric": [1, 3, 49, 99], "which": [1, 2, 3, 5, 7, 10, 13, 15, 16, 17, 19, 21, 25, 29, 35, 36, 37, 39, 40, 44, 45, 46, 49, 51, 55, 56, 58, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 76, 79, 80, 81, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 110], "learn": [1, 2, 3, 4, 5, 9, 10, 17, 19, 25, 33, 36, 41, 42, 43, 44, 46, 48, 50, 55, 56, 59, 61, 63, 65, 72, 74, 76, 79, 83, 85, 88, 89, 90, 91, 93, 95, 96, 97, 98, 100, 103, 104, 108], "i": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 103, 104, 105, 106, 108, 109, 110], "possibl": [1, 2, 3, 7, 10, 39, 40, 44, 46, 48, 49, 51, 65, 66, 67, 68, 70, 71, 72, 73, 75, 81, 83, 84, 92, 97, 99, 100, 101, 103, 104, 105, 108, 109, 110], "noisi": [1, 2, 3, 10, 34, 39, 41, 44, 46, 49, 59, 64, 65, 67, 73, 75, 76, 77, 79, 80, 86, 91, 92, 95, 96, 97, 99, 102, 103], "given": [1, 2, 3, 5, 10, 17, 33, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 58, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 76, 80, 81, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "matrix": [1, 2, 3, 5, 10, 13, 19, 21, 34, 39, 46, 48, 49, 52, 54, 59, 60, 65, 68, 70, 71, 72, 73, 95, 97, 105, 106], "trace": [1, 91, 92, 101, 103, 104], "valu": [1, 2, 3, 4, 5, 10, 13, 15, 16, 19, 21, 25, 29, 30, 35, 37, 39, 40, 41, 43, 44, 46, 48, 49, 51, 54, 55, 56, 57, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 84, 89, 90, 92, 93, 95, 96, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "more": [1, 2, 3, 4, 5, 7, 9, 10, 13, 16, 17, 19, 21, 29, 39, 40, 43, 44, 45, 48, 51, 54, 55, 56, 57, 59, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 79, 80, 81, 83, 85, 90, 91, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 109, 110], "function": [1, 2, 3, 4, 5, 7, 10, 13, 16, 17, 19, 26, 29, 33, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 92, 97, 98, 99, 100, 101, 103, 104, 105, 109, 110], "noise_matrix": [1, 2, 3, 10, 49, 59, 91, 92, 101, 103, 104], "py": [1, 3, 36, 40, 41, 46, 49, 51, 91, 92, 101, 103, 104], "verbos": [1, 2, 5, 7, 13, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 43, 46, 63, 64, 65, 70, 72, 73, 75, 77, 79, 80, 84, 91, 97, 101, 103], "fals": [1, 2, 3, 5, 7, 10, 13, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 50, 58, 59, 60, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 81, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 105, 106, 108, 109], "sourc": [1, 2, 3, 4, 5, 7, 9, 10, 12, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "prior": [1, 2, 3, 39, 46, 49, 51], "repres": [1, 2, 3, 7, 10, 13, 15, 19, 21, 29, 35, 37, 39, 43, 46, 49, 52, 54, 55, 57, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 110], "p": [1, 2, 3, 5, 10, 39, 46, 48, 49, 57, 59, 63, 71, 72, 73, 77, 95, 96, 97, 100, 101, 103, 110], "true_label": [1, 2, 3, 39, 49, 59, 101, 103], "k": [1, 2, 3, 4, 5, 8, 10, 13, 15, 19, 21, 22, 26, 29, 31, 34, 39, 43, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 63, 64, 65, 66, 67, 68, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 88, 90, 91, 92, 97, 99, 100, 101, 103, 104, 105, 106, 109, 110], "check": [1, 2, 5, 6, 9, 10, 13, 15, 19, 30, 37, 40, 43, 44, 50, 60, 62, 68, 71, 75, 88, 89, 90, 91, 92, 93, 99, 101, 103, 104, 108], "learnabl": 1, "mean": [1, 2, 7, 8, 10, 13, 15, 16, 25, 29, 41, 44, 49, 51, 57, 70, 75, 89, 92, 96, 97, 99, 101, 103, 104, 105, 106, 108], "achiev": [1, 2, 40, 41, 44, 75, 99, 100, 103, 110], "better": [1, 5, 10, 46, 55, 63, 65, 73, 75, 76, 85, 89, 90, 92, 95, 96, 97, 99, 101, 104, 105, 106, 107, 110], "than": [1, 2, 3, 4, 7, 9, 10, 29, 31, 34, 39, 46, 55, 59, 62, 63, 68, 70, 72, 73, 75, 79, 83, 88, 90, 93, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "random": [1, 2, 3, 7, 10, 21, 34, 43, 51, 54, 63, 73, 75, 88, 90, 91, 92, 93, 95, 97, 99, 100, 101, 103, 104, 106], "perform": [1, 2, 4, 7, 10, 29, 31, 34, 40, 44, 51, 53, 54, 55, 71, 75, 85, 88, 89, 91, 99, 101, 102, 103, 104, 107, 108], "averag": [1, 3, 5, 10, 25, 31, 39, 40, 44, 51, 57, 63, 64, 71, 72, 73, 99, 103, 106], "amount": [1, 3, 93], "paramet": [1, 2, 3, 4, 5, 9, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 92, 93, 96, 97, 100], "np": [1, 2, 3, 4, 5, 7, 13, 19, 21, 34, 39, 41, 43, 45, 46, 48, 49, 51, 52, 54, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "ndarrai": [1, 2, 3, 4, 5, 13, 19, 26, 28, 29, 33, 34, 35, 39, 41, 43, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 83, 97, 110], "an": [1, 2, 3, 4, 5, 7, 9, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 54, 56, 57, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84, 85, 88, 89, 91, 92, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "arrai": [1, 2, 3, 4, 5, 7, 10, 13, 15, 19, 21, 29, 35, 39, 41, 43, 44, 45, 46, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 91, 92, 96, 97, 99, 101, 103, 104, 105, 106, 108, 109, 110], "shape": [1, 2, 3, 4, 5, 13, 19, 21, 39, 41, 43, 45, 46, 48, 49, 50, 51, 54, 55, 57, 58, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 90, 97, 98, 99, 101, 104, 105, 106, 109, 110], "condit": [1, 2, 3, 10, 49, 55, 58, 59, 73, 93, 101, 110], "probabl": [1, 2, 3, 5, 8, 10, 13, 19, 26, 28, 31, 34, 35, 39, 43, 44, 45, 46, 48, 49, 51, 52, 58, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 85, 86, 98, 99, 101, 102, 104, 105, 106, 109, 110], "k_": [1, 2, 3, 49, 59], "k_y": [1, 2, 3, 49, 59], "contain": [1, 2, 3, 5, 10, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 46, 48, 49, 53, 54, 58, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 79, 80, 81, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109], "fraction": [1, 2, 3, 10, 23, 41, 49, 59, 63, 75, 95, 99, 100], "exampl": [1, 2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 51, 52, 54, 57, 58, 59, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 100, 103, 104, 105, 107, 108, 109, 110], "everi": [1, 2, 3, 4, 5, 10, 13, 19, 40, 44, 46, 49, 58, 59, 65, 73, 75, 76, 88, 90, 91, 92, 93, 95, 96, 99, 103, 105, 107, 109, 110], "class": [1, 2, 3, 4, 5, 7, 9, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 56, 58, 59, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 103, 104, 105, 106, 107, 108, 110], "other": [1, 2, 3, 5, 10, 13, 19, 25, 30, 39, 40, 42, 43, 44, 46, 49, 52, 54, 59, 60, 61, 63, 64, 67, 71, 72, 73, 75, 80, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 106, 109, 110], "assum": [1, 2, 3, 15, 46, 49, 54, 58, 59, 73, 77, 80, 97, 99, 100, 104, 106, 108, 109, 110], "column": [1, 2, 3, 5, 10, 11, 13, 15, 16, 33, 39, 43, 46, 49, 51, 52, 55, 58, 59, 63, 64, 65, 67, 68, 71, 72, 73, 75, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 108, 109, 110], "sum": [1, 2, 3, 29, 34, 35, 39, 49, 51, 59, 64, 65, 67, 70, 75, 91, 92, 93, 99, 101, 103, 104, 109, 110], "1": [1, 2, 3, 4, 5, 7, 10, 11, 13, 15, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 57, 58, 59, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 98, 99, 107], "each": [1, 2, 3, 4, 5, 7, 8, 9, 13, 15, 16, 17, 19, 23, 25, 26, 28, 29, 34, 35, 36, 39, 40, 41, 43, 44, 45, 46, 48, 49, 51, 52, 54, 56, 57, 59, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "true": [1, 2, 3, 5, 7, 10, 13, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 46, 49, 51, 54, 58, 59, 60, 62, 63, 64, 65, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 108, 109, 110], "return": [1, 2, 3, 4, 5, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 89, 90, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "type": [1, 2, 3, 4, 5, 6, 7, 12, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 42, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 61, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 99, 100, 104, 105, 108, 109, 110], "bool": [1, 2, 3, 5, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 51, 54, 58, 59, 63, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 84], "is_valid": 1, "whether": [1, 3, 5, 10, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 40, 43, 44, 46, 54, 59, 63, 64, 65, 67, 68, 84, 89, 90, 92, 93, 95, 96, 97, 98, 99, 100, 101, 108, 110], "from": [1, 2, 3, 4, 5, 7, 8, 9, 10, 12, 13, 15, 16, 17, 19, 21, 25, 26, 30, 33, 34, 35, 36, 38, 39, 40, 41, 43, 44, 45, 46, 49, 51, 52, 54, 55, 57, 58, 59, 63, 65, 67, 70, 71, 72, 73, 75, 76, 81, 83, 84, 85, 90, 93, 95, 96, 97, 98, 99, 103, 104, 105, 106, 107, 109, 110], "perfect": [1, 2, 39, 75, 101, 105], "exactli": [1, 3, 10, 39, 40, 44, 46, 66, 72, 91, 92, 93, 95, 96, 100, 101], "yield": [1, 40, 44, 100], "between": [1, 5, 9, 13, 14, 18, 19, 24, 25, 27, 29, 32, 35, 39, 40, 41, 42, 43, 44, 46, 47, 48, 50, 54, 55, 56, 57, 61, 63, 64, 67, 70, 72, 73, 75, 76, 79, 83, 84, 86, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "below": [1, 3, 4, 5, 10, 39, 40, 43, 44, 46, 48, 51, 57, 63, 64, 65, 70, 71, 79, 83, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "we": [1, 2, 3, 5, 7, 10, 13, 16, 25, 40, 43, 44, 46, 51, 59, 60, 62, 63, 70, 71, 73, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "loop": [1, 3, 49, 59, 93, 105], "implement": [1, 2, 3, 4, 9, 17, 25, 40, 41, 43, 44, 49, 53, 55, 56, 59, 72, 75, 85, 88, 90, 91, 95, 100, 106, 107], "what": [1, 5, 9, 10, 13, 19, 36, 39, 41, 43, 46, 63, 64, 68, 70, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 103, 104, 105, 106, 108, 109, 110], "doe": [1, 2, 3, 7, 10, 43, 44, 46, 51, 54, 57, 60, 70, 71, 75, 77, 79, 83, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 104, 108, 109], "do": [1, 2, 5, 9, 10, 39, 43, 44, 59, 60, 72, 73, 77, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 103, 104, 105, 106, 108, 109, 110], "fast": 1, "explain": [1, 10, 97], "python": [1, 2, 44, 62, 75, 91, 92, 98, 106], "pseudocod": [1, 107], "happen": [1, 10, 46, 65, 96, 103, 109], "n": [1, 2, 3, 5, 7, 39, 40, 43, 44, 46, 48, 49, 50, 51, 54, 55, 57, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 83, 88, 89, 90, 93, 96, 97, 98, 99, 103, 104, 105, 108, 109, 110], "without": [1, 2, 5, 9, 10, 15, 17, 23, 40, 44, 56, 67, 75, 85, 89, 90, 96, 97, 99, 100, 101, 105, 106], "ani": [1, 2, 3, 5, 7, 9, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 43, 44, 46, 48, 50, 57, 58, 59, 62, 63, 65, 67, 68, 70, 71, 73, 75, 77, 79, 80, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 107, 108, 109], "distinct": [1, 10, 21, 59, 110], "natur": [1, 10, 103, 106], "number": [1, 2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 46, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 83, 84, 86, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 109, 110], "0": [1, 2, 3, 4, 5, 7, 10, 15, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 57, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "count_joint": 1, "len": [1, 2, 3, 7, 39, 43, 49, 58, 59, 60, 72, 73, 75, 88, 89, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 110], "y": [1, 2, 3, 5, 8, 21, 33, 34, 44, 49, 51, 59, 60, 62, 71, 75, 76, 89, 90, 91, 92, 95, 97, 99, 101, 103, 104, 106, 108], "round": [1, 43, 46, 59, 75, 97, 99, 100, 108], "astyp": [1, 100, 103], "int": [1, 2, 3, 4, 5, 7, 13, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 40, 41, 43, 44, 46, 51, 52, 54, 55, 56, 57, 58, 59, 60, 64, 65, 67, 71, 72, 73, 75, 77, 79, 80, 81, 84, 90, 91, 93, 97, 100, 105, 106], "rang": [1, 3, 5, 7, 15, 49, 51, 57, 59, 71, 75, 76, 93, 97, 98, 99, 101, 103, 104, 105, 106, 108, 109, 110], "idx_flip": 1, "where": [1, 2, 3, 5, 7, 10, 13, 15, 16, 19, 25, 39, 43, 46, 49, 50, 51, 52, 54, 55, 57, 58, 59, 60, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 89, 90, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "pragma": 1, "cover": [1, 3, 86, 97, 98, 99], "choic": [1, 8, 46, 55, 57, 93, 99, 104, 106], "replac": [1, 58, 62, 73, 88, 89, 91, 92, 93, 96, 97, 98, 99, 103, 106], "max_trace_prob": 1, "min_trace_prob": 1, "1e": [1, 3, 54, 73, 90, 91, 92], "05": [1, 10, 29, 33, 58, 71, 75, 81, 83, 95, 98, 99, 100, 101, 105], "max_noise_r": 1, "99999": 1, "min_noise_r": 1, "valid_noise_matrix": [1, 91, 92, 101, 103, 104], "none": [1, 2, 3, 4, 5, 7, 10, 11, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 41, 43, 44, 45, 46, 48, 49, 50, 51, 52, 54, 56, 57, 58, 59, 60, 62, 63, 64, 65, 66, 67, 70, 71, 72, 73, 75, 77, 79, 80, 83, 84, 91, 92, 93, 97, 99, 100, 101, 103, 104, 109], "frac_zero_noise_r": 1, "seed": [1, 2, 3, 10, 29, 42, 44, 51, 75, 88, 90, 91, 92, 95, 97, 98, 100, 101, 103, 104], "max_it": [1, 89, 90, 96, 106], "10000": [1, 43, 98, 99], "x": [1, 2, 3, 5, 10, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 40, 41, 44, 46, 48, 49, 51, 54, 56, 58, 59, 60, 62, 63, 65, 71, 72, 73, 75, 77, 88, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 106, 108], "diagon": [1, 3, 5, 46, 49, 59], "equal": [1, 3, 10, 15, 54, 65, 70, 80, 107], "creat": [1, 2, 9, 13, 19, 21, 40, 43, 44, 46, 59, 75, 85, 89, 90, 93, 95, 96, 97, 99, 100, 109, 110], "impli": [1, 10, 39, 64, 71], "float": [1, 2, 10, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 41, 42, 43, 44, 46, 48, 50, 51, 57, 58, 59, 63, 64, 65, 67, 70, 71, 75, 79, 83, 90, 91, 92, 100, 101, 103, 104], "entri": [1, 3, 5, 10, 39, 40, 44, 46, 48, 52, 54, 57, 59, 63, 64, 65, 68, 88, 89, 95, 96, 101, 104, 105, 108], "maximum": [1, 10, 13, 72, 80, 84, 97, 109], "minimum": [1, 8, 10, 13, 23, 46, 48, 65, 70, 83, 97], "noise_r": 1, "non": [1, 2, 3, 5, 7, 9, 13, 19, 29, 40, 44, 46, 54, 70, 75, 91, 99, 100, 101, 103, 105, 106], "default": [1, 2, 3, 4, 5, 7, 10, 11, 13, 17, 19, 31, 33, 36, 39, 40, 41, 43, 44, 46, 48, 49, 51, 53, 54, 55, 56, 57, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 91, 93, 97, 99, 108, 109], "If": [1, 2, 3, 4, 5, 10, 13, 15, 16, 19, 29, 31, 37, 39, 40, 43, 44, 46, 48, 49, 51, 54, 55, 58, 59, 62, 63, 64, 65, 68, 70, 71, 72, 75, 76, 77, 79, 80, 83, 84, 85, 86, 88, 89, 90, 91, 93, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "have": [1, 2, 3, 4, 5, 7, 9, 10, 13, 19, 24, 27, 29, 32, 39, 40, 42, 43, 44, 46, 49, 51, 54, 59, 62, 63, 64, 65, 68, 70, 71, 72, 73, 75, 76, 80, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "all": [1, 2, 3, 5, 7, 8, 9, 10, 13, 16, 17, 19, 25, 36, 39, 40, 43, 44, 45, 46, 49, 51, 52, 54, 58, 59, 62, 63, 64, 65, 66, 67, 70, 71, 72, 73, 75, 77, 79, 80, 81, 83, 84, 86, 88, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "necessari": [1, 2, 3, 4, 7, 10, 15, 58, 91, 97], "In": [1, 2, 3, 5, 10, 39, 40, 43, 44, 54, 62, 63, 64, 66, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 106, 107, 108, 109, 110], "particular": [1, 5, 6, 10, 13, 16, 17, 19, 22, 23, 25, 29, 30, 31, 34, 40, 44, 59, 63, 67, 71, 75, 80, 84, 85, 88, 89, 90, 92, 96, 99, 103, 104, 106, 108], "satisfi": [1, 3, 39], "requir": [1, 2, 5, 7, 8, 9, 10, 11, 12, 15, 33, 38, 40, 41, 42, 43, 44, 46, 49, 54, 56, 59, 61, 62, 65, 72, 73, 75, 77, 85, 86, 90, 97, 98, 99, 100, 101, 107], "argument": [1, 2, 3, 5, 10, 11, 13, 19, 26, 30, 33, 34, 35, 40, 43, 44, 45, 46, 51, 54, 56, 60, 62, 63, 64, 65, 67, 70, 71, 72, 73, 75, 79, 80, 81, 83, 89, 92, 93, 96, 97, 98, 99, 104, 105, 108, 110], "when": [1, 2, 3, 4, 5, 10, 15, 17, 26, 29, 40, 44, 46, 49, 51, 54, 56, 57, 59, 62, 65, 67, 68, 70, 72, 73, 75, 76, 88, 89, 91, 92, 93, 95, 96, 97, 98, 100, 103, 107, 108, 109, 110], "The": [1, 2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 39, 40, 43, 44, 45, 46, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 59, 62, 63, 64, 65, 68, 70, 71, 72, 73, 75, 77, 80, 81, 83, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 102, 103, 104, 105, 106, 107, 108, 109, 110], "rate": [1, 2, 3, 10, 41, 59, 90, 110], "set": [1, 2, 3, 5, 9, 10, 13, 15, 16, 19, 20, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 40, 43, 44, 46, 50, 51, 53, 54, 55, 57, 59, 62, 63, 65, 68, 70, 71, 72, 73, 75, 77, 79, 80, 88, 89, 91, 92, 95, 96, 97, 99, 100, 103, 104, 106, 107, 108, 109, 110], "note": [1, 2, 3, 7, 8, 10, 11, 15, 30, 34, 37, 40, 43, 44, 45, 46, 51, 54, 59, 62, 63, 68, 70, 71, 72, 73, 75, 76, 80, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "you": [1, 2, 3, 5, 7, 9, 10, 13, 17, 19, 39, 40, 42, 43, 44, 46, 51, 56, 61, 62, 63, 65, 68, 70, 71, 72, 73, 75, 76, 77, 80, 81, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 103, 104, 105, 106, 107, 108, 109, 110], "high": [1, 2, 10, 19, 43, 46, 54, 55, 59, 70, 73, 75, 88, 89, 91, 92, 93, 97, 98, 100, 101, 105, 108, 109, 110], "mai": [1, 2, 3, 4, 5, 10, 13, 16, 24, 25, 27, 32, 35, 39, 40, 42, 43, 44, 46, 49, 51, 54, 59, 63, 64, 68, 70, 71, 72, 73, 75, 77, 80, 84, 86, 89, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "imposs": [1, 10, 101], "also": [1, 2, 3, 5, 7, 9, 10, 25, 37, 39, 40, 43, 44, 46, 51, 58, 62, 63, 72, 75, 80, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "low": [1, 10, 13, 59, 63, 85, 91, 92, 96, 97, 101, 105, 109], "zero": [1, 3, 5, 40, 44, 48, 54, 59, 60, 91, 93, 104, 105, 106], "forc": [1, 2, 3, 5, 44, 91, 110], "instead": [1, 2, 3, 10, 13, 16, 19, 36, 39, 40, 43, 44, 46, 49, 59, 62, 63, 65, 67, 71, 72, 73, 75, 76, 79, 81, 83, 86, 88, 89, 90, 93, 95, 97, 99, 100, 101, 104, 105, 106, 108, 109, 110], "onli": [1, 2, 3, 4, 5, 7, 10, 11, 13, 19, 26, 29, 33, 39, 40, 43, 44, 45, 46, 48, 49, 54, 55, 57, 58, 59, 60, 62, 63, 72, 73, 75, 77, 79, 83, 84, 85, 89, 90, 91, 92, 93, 96, 97, 100, 103, 104, 105, 106, 107, 108, 109, 110], "guarante": [1, 3, 5, 14, 18, 24, 27, 32, 40, 42, 44, 47, 49, 61, 86], "produc": [1, 2, 5, 9, 10, 13, 19, 51, 63, 73, 75, 77, 79, 85, 88, 89, 90, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 109, 110], "higher": [1, 5, 10, 39, 46, 48, 49, 51, 57, 62, 63, 64, 75, 92, 96, 97, 99, 105], "opposit": [1, 110], "occur": [1, 3, 10, 39, 58, 70, 91, 92, 93, 99, 100, 106], "small": [1, 3, 10, 39, 43, 51, 54, 57, 59, 64, 71, 89, 93, 96, 98, 100, 104, 106], "numpi": [1, 3, 4, 5, 7, 10, 15, 21, 34, 35, 43, 44, 45, 51, 54, 57, 58, 60, 62, 67, 70, 75, 76, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "max": [1, 46, 72, 73, 92, 93, 97, 100, 106], "tri": [1, 40, 44, 107], "befor": [1, 2, 3, 40, 44, 57, 59, 72, 75, 80, 88, 89, 96, 97, 99, 100, 101, 103, 106, 108], "option": [1, 2, 3, 4, 5, 7, 8, 9, 13, 15, 16, 19, 26, 31, 33, 39, 40, 43, 44, 46, 49, 51, 54, 56, 57, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 80, 83, 84, 85, 88, 90, 91, 92, 93, 95, 99, 101, 104, 108, 109], "left": [1, 2, 46, 48, 57, 59, 65, 68, 71, 91, 92, 104, 105, 106, 109], "stochast": 1, "exceed": 1, "m": [1, 5, 40, 44, 50, 51, 54, 55, 63, 68, 70, 71, 72, 91, 92, 98, 103, 104, 105, 110], "max_prob": 1, "min_prob": 1, "dirichlet": 1, "ones": [1, 40, 44, 62, 99, 101, 109], "length": [1, 5, 15, 29, 30, 39, 41, 46, 59, 65, 68, 72, 73, 75, 77, 80, 84, 88, 90, 97, 100, 104, 106, 109, 110], "must": [1, 2, 3, 4, 5, 7, 13, 19, 39, 40, 41, 42, 44, 46, 49, 51, 52, 57, 59, 61, 62, 63, 64, 65, 72, 73, 75, 77, 79, 80, 81, 83, 84, 90, 97, 100, 103, 107, 109, 110], "max_balls_per_bin": 1, "min_balls_per_bin": 1, "uniformli": 1, "integ": [1, 2, 3, 10, 15, 39, 43, 46, 52, 59, 60, 63, 65, 71, 77, 79, 80, 81, 83, 84, 88, 89, 90, 99, 100, 103, 104, 105, 109, 110], "ball": [1, 98], "bin": [1, 3, 65, 91, 92, 106], "ensur": [1, 2, 10, 40, 44, 54, 56, 57, 59, 60, 62, 70, 73, 75, 88, 89, 90, 91, 92, 93, 96, 97, 99, 100, 101, 106, 107, 108], "most": [1, 3, 5, 7, 10, 13, 19, 39, 43, 46, 51, 62, 63, 64, 65, 68, 70, 71, 72, 73, 76, 79, 83, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109], "least": [1, 4, 10, 21, 34, 39, 43, 63, 64, 70, 73, 83, 93, 99, 100, 103, 106, 109], "int_arrai": [1, 59], "can": [2, 3, 4, 5, 7, 8, 9, 13, 16, 17, 19, 36, 37, 39, 40, 41, 42, 43, 44, 46, 50, 51, 52, 54, 55, 56, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 75, 76, 77, 80, 81, 84, 85, 86, 88, 89, 90, 91, 93, 95, 96, 97, 100, 104, 105, 106, 107, 108, 109, 110], "model": [2, 3, 4, 5, 9, 10, 11, 13, 19, 21, 33, 35, 39, 40, 41, 42, 43, 44, 45, 46, 48, 49, 50, 56, 58, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 86, 91, 92, 97, 98, 102, 107, 109, 110], "For": [2, 3, 5, 7, 9, 10, 12, 13, 19, 25, 38, 39, 40, 43, 44, 46, 49, 51, 54, 57, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 79, 81, 83, 84, 85, 88, 89, 90, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 109, 110], "regular": [2, 3, 43, 62], "multi": [2, 3, 4, 10, 35, 39, 40, 43, 44, 46, 50, 51, 52, 59, 60, 64, 65, 66, 67, 72, 73, 85, 97, 99, 100, 101, 102], "task": [2, 5, 7, 10, 11, 12, 13, 15, 17, 18, 19, 28, 33, 36, 39, 43, 49, 51, 52, 57, 59, 63, 65, 73, 75, 85, 89, 90, 96, 97, 98, 99, 100, 101, 104, 106, 108, 109, 110], "cleanlearn": [2, 3, 10, 26, 33, 40, 59, 62, 74, 75, 76, 85, 86, 88, 89, 100, 108], "wrap": [2, 40, 44, 53, 62, 72, 75, 85, 88, 89, 91, 92, 95, 96, 101, 108], "instanc": [2, 3, 5, 6, 7, 10, 13, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 44, 51, 62, 71, 72, 75, 80, 88, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 105], "sklearn": [2, 3, 4, 5, 8, 10, 21, 34, 39, 44, 51, 55, 56, 59, 62, 72, 75, 76, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 106, 107, 108], "classifi": [2, 3, 44, 51, 59, 63, 66, 72, 73, 85, 86, 88, 89, 90, 95, 96, 99, 103, 104, 106, 107, 109, 110], "adher": [2, 44, 75], "estim": [2, 3, 4, 5, 9, 13, 16, 25, 39, 43, 44, 46, 49, 59, 63, 64, 65, 70, 72, 75, 77, 79, 83, 85, 86, 90, 91, 92, 93, 95, 96, 97, 99, 100, 102, 105, 106, 107, 108, 109, 110], "api": [2, 3, 17, 62, 68, 71, 72, 75, 86, 97, 99, 108], "defin": [2, 3, 5, 7, 10, 17, 25, 39, 40, 41, 43, 44, 46, 73, 75, 77, 85, 91, 92, 95, 98, 99, 100, 103, 106, 110], "four": [2, 10, 98, 101, 110], "clf": [2, 3, 5, 51, 75, 85, 88, 95, 97, 99, 100, 101, 104], "fit": [2, 3, 5, 8, 10, 21, 42, 44, 54, 56, 61, 62, 72, 74, 75, 85, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 106, 107, 108, 110], "sample_weight": [2, 44, 75, 101], "predict_proba": [2, 5, 39, 42, 44, 51, 61, 62, 88, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 106], "predict": [2, 3, 4, 5, 8, 9, 10, 11, 13, 19, 25, 26, 28, 31, 33, 34, 35, 37, 39, 42, 43, 44, 45, 46, 48, 49, 51, 52, 58, 59, 61, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 79, 80, 81, 83, 84, 85, 86, 89, 98, 99, 101, 102, 106, 108, 109, 110], "score": [2, 3, 4, 5, 7, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 43, 45, 46, 48, 51, 57, 63, 64, 65, 67, 68, 70, 71, 72, 73, 74, 75, 76, 79, 81, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 106, 108], "data": [2, 3, 4, 5, 7, 8, 9, 12, 13, 16, 17, 18, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 39, 41, 42, 43, 44, 45, 46, 51, 52, 54, 55, 56, 59, 61, 62, 63, 64, 65, 66, 70, 72, 73, 74, 75, 80, 81, 82, 83, 84, 86, 93, 94, 102], "e": [2, 3, 5, 10, 15, 25, 35, 39, 40, 43, 44, 46, 49, 51, 52, 54, 59, 60, 63, 64, 65, 66, 68, 71, 72, 73, 75, 77, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108], "featur": [2, 3, 4, 5, 8, 10, 11, 13, 19, 21, 22, 26, 29, 30, 31, 33, 34, 51, 54, 55, 56, 59, 72, 75, 85, 88, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 108], "element": [2, 3, 5, 39, 45, 46, 48, 59, 63, 65, 73, 80, 81, 83, 89, 90, 96, 97, 99, 110], "first": [2, 5, 10, 20, 29, 30, 39, 43, 51, 54, 59, 63, 64, 68, 71, 73, 75, 85, 88, 89, 90, 91, 93, 95, 97, 99, 100, 103, 104, 105, 106, 108, 109, 110], "index": [2, 10, 29, 39, 46, 53, 54, 56, 58, 59, 60, 64, 73, 75, 80, 83, 84, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "should": [2, 3, 5, 7, 10, 17, 25, 29, 34, 35, 39, 40, 43, 44, 46, 48, 49, 51, 54, 56, 57, 58, 59, 62, 63, 64, 67, 68, 70, 71, 72, 73, 75, 76, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "correspond": [2, 3, 5, 10, 13, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 37, 39, 40, 43, 44, 45, 46, 48, 49, 51, 54, 58, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 77, 80, 81, 83, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "differ": [2, 5, 7, 10, 13, 14, 16, 18, 24, 27, 29, 30, 32, 39, 40, 42, 43, 44, 46, 47, 51, 54, 57, 59, 60, 61, 63, 68, 70, 72, 75, 88, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 106, 107, 108], "sampl": [2, 3, 5, 8, 10, 13, 19, 23, 34, 46, 48, 51, 54, 55, 56, 65, 68, 71, 73, 75, 76, 85, 86, 89, 97, 98, 99, 101, 102, 104, 105, 108, 109, 110], "size": [2, 10, 34, 40, 43, 44, 46, 51, 54, 55, 65, 70, 71, 75, 77, 79, 89, 93, 95, 99, 101, 103, 104, 105, 107, 109], "here": [2, 5, 7, 10, 17, 43, 46, 49, 62, 63, 64, 65, 67, 68, 71, 72, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "re": [2, 5, 40, 44, 56, 58, 63, 75, 85, 88, 89, 90, 91, 95, 96, 97, 99, 100, 108, 109, 110], "weight": [2, 10, 40, 41, 44, 51, 54, 63, 70, 73, 75, 89, 90, 91, 92, 96], "loss": [2, 41, 62, 73, 75, 93, 100], "while": [2, 3, 10, 40, 43, 44, 50, 51, 59, 75, 85, 93, 97, 99, 100, 101, 103, 104, 108], "train": [2, 3, 4, 5, 9, 10, 13, 19, 21, 35, 40, 41, 42, 44, 51, 59, 62, 63, 68, 71, 72, 75, 76, 86, 91, 92, 93, 95, 96, 98, 101, 102, 103, 104, 105, 107, 109, 110], "support": [2, 3, 4, 5, 13, 15, 17, 36, 37, 43, 45, 51, 59, 60, 62, 72, 73, 83, 85, 86, 90, 91, 92, 93, 97, 99], "your": [2, 3, 5, 9, 10, 13, 19, 39, 40, 42, 43, 44, 46, 51, 56, 59, 61, 62, 63, 64, 65, 67, 72, 73, 75, 76, 77, 79, 80, 86, 88, 89, 90, 93, 95, 98, 100, 103, 104, 105, 106, 107, 108, 109, 110], "recommend": [2, 5, 7, 10, 13, 16, 19, 43, 46, 63, 91, 92, 93, 97, 99, 100, 107, 108], "furthermor": 2, "correctli": [2, 3, 10, 39, 40, 44, 46, 49, 54, 60, 64, 65, 70, 71, 75, 77, 89, 96, 97, 99, 104, 105, 108, 109], "clonabl": [2, 75], "via": [2, 5, 7, 10, 11, 13, 16, 19, 21, 25, 39, 41, 43, 44, 51, 55, 59, 63, 68, 71, 72, 73, 75, 76, 79, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 102, 104, 105, 106, 107, 108, 109, 110], "base": [2, 3, 4, 5, 7, 10, 13, 15, 16, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 40, 43, 44, 45, 46, 49, 50, 51, 54, 55, 57, 58, 59, 60, 62, 63, 64, 65, 67, 70, 72, 73, 75, 76, 79, 81, 83, 85, 88, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "clone": [2, 75, 104], "intern": [2, 3, 7, 10, 11, 12, 13, 14, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 43, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 60, 67, 71, 75, 81, 86, 91, 97, 99, 101, 103, 104, 105, 106, 108, 110], "multipl": [2, 3, 5, 10, 13, 15, 16, 37, 39, 46, 57, 58, 63, 64, 65, 67, 70, 71, 75, 85, 91, 92, 93, 95, 99, 102, 104, 105, 108], "g": [2, 3, 5, 10, 15, 25, 35, 39, 40, 44, 46, 52, 54, 59, 65, 66, 68, 71, 72, 73, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108], "manual": [2, 75, 85, 88, 89, 90, 97, 99, 106, 107, 108, 110], "pytorch": [2, 40, 41, 44, 75, 85, 90, 93, 99, 102, 104, 109], "call": [2, 3, 5, 6, 10, 16, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 51, 59, 62, 72, 75, 89, 90, 91, 92, 96, 99, 101, 104, 106, 107, 108, 109, 110], "__init__": [2, 41, 75, 93], "independ": [2, 3, 10, 64, 75, 96, 97, 100, 107, 108, 110], "compat": [2, 40, 43, 44, 56, 62, 75, 76, 79, 83, 85, 88, 89, 97, 99, 107, 108], "neural": [2, 41, 62, 72, 75, 90, 93, 99, 104, 106, 108], "network": [2, 40, 41, 44, 62, 72, 75, 89, 90, 93, 96, 99, 104, 106, 108], "typic": [2, 10, 40, 44, 56, 72, 75, 88, 89, 90, 92, 93, 95, 96, 100, 106, 107], "initi": [2, 3, 10, 16, 21, 40, 44, 54, 63, 75, 88, 96, 99, 100], "insid": [2, 44, 75, 99, 101], "There": [2, 3, 7, 54, 85, 101, 103], "two": [2, 3, 10, 21, 29, 39, 40, 43, 44, 52, 54, 55, 56, 59, 68, 70, 71, 86, 89, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 108, 109, 110], "new": [2, 7, 9, 10, 17, 25, 40, 43, 44, 50, 54, 58, 59, 63, 75, 89, 90, 91, 96, 98, 99, 100, 106, 107, 110], "notion": 2, "confid": [2, 3, 10, 25, 39, 43, 46, 49, 51, 59, 63, 64, 65, 68, 70, 71, 72, 73, 75, 79, 83, 85, 88, 93, 100, 101, 103, 104, 105, 107, 109, 110], "packag": [2, 5, 7, 9, 10, 12, 13, 14, 18, 38, 42, 46, 47, 59, 61, 62, 68, 71, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "prune": [2, 3, 46, 65, 75, 86, 100, 105], "everyth": [2, 71, 101], "els": [2, 71, 91, 93, 97, 98, 99, 100, 103, 104, 105], "mathemat": [2, 3, 10, 49, 104], "keep": [2, 16, 17, 59, 85, 91, 97, 98, 99, 100, 109], "belong": [2, 3, 10, 39, 46, 48, 49, 54, 64, 65, 66, 67, 72, 73, 77, 81, 83, 84, 92, 93, 100, 101, 104, 106, 109, 110], "2": [2, 3, 4, 5, 7, 10, 11, 13, 15, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 41, 43, 44, 46, 48, 49, 50, 51, 52, 54, 56, 57, 58, 59, 62, 64, 65, 67, 68, 71, 72, 73, 75, 76, 80, 81, 83, 84, 98, 99, 107], "error": [2, 3, 5, 10, 40, 44, 45, 46, 48, 49, 59, 64, 65, 67, 68, 70, 71, 73, 75, 77, 79, 80, 83, 86, 88, 90, 91, 92, 95, 96, 97, 98, 100, 102], "erron": [2, 3, 39, 46, 49, 59, 64, 65, 73, 75, 76, 77, 106, 108], "import": [2, 3, 4, 5, 7, 8, 10, 13, 15, 16, 17, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 43, 45, 51, 54, 57, 58, 63, 67, 70, 75, 76, 81, 83, 84, 85, 88, 89, 95, 96, 97, 99, 100, 104, 105, 106, 108, 109, 110], "linear_model": [2, 5, 39, 59, 75, 85, 89, 90, 91, 92, 96, 97, 99, 101, 103, 106], "logisticregress": [2, 3, 5, 39, 59, 85, 89, 90, 91, 92, 96, 97, 99, 101, 103, 106], "logreg": 2, "cl": [2, 17, 33, 75, 85, 88, 89, 99, 101, 108], "pass": [2, 3, 5, 8, 10, 11, 13, 15, 16, 17, 19, 26, 33, 36, 40, 43, 44, 46, 50, 51, 54, 56, 59, 62, 63, 65, 71, 72, 73, 75, 80, 81, 85, 89, 90, 91, 92, 96, 97, 98, 99, 101, 103, 105, 106, 108], "x_train": [2, 88, 91, 92, 101, 103, 104, 108], "labels_maybe_with_error": 2, "had": [2, 3, 75, 105], "issu": [2, 3, 4, 5, 6, 8, 11, 12, 13, 16, 17, 18, 19, 20, 21, 22, 23, 25, 26, 27, 28, 29, 30, 31, 32, 34, 35, 36, 39, 40, 42, 43, 44, 45, 46, 54, 61, 64, 65, 66, 67, 68, 69, 70, 71, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 86, 89, 94, 102, 103, 106, 107, 108], "pred": [2, 46, 59, 88, 89, 100, 107, 108], "x_test": [2, 88, 91, 92, 101, 104, 108], "might": [2, 5, 10, 54, 63, 75, 80, 88, 89, 91, 92, 93, 97, 99, 105], "case": [2, 3, 10, 13, 16, 39, 51, 54, 63, 75, 88, 89, 90, 91, 92, 93, 95, 97, 98, 99, 100, 101, 106, 108, 110], "standard": [2, 3, 5, 33, 39, 46, 62, 64, 65, 67, 73, 75, 85, 88, 91, 92, 95, 98, 100, 101, 105], "adapt": [2, 12, 13, 18, 40, 42, 59, 61, 75, 106], "skorch": [2, 75, 85, 99], "kera": [2, 61, 68, 71, 75, 85, 99, 105], "scikera": [2, 62, 75, 99], "open": [2, 43, 88, 89, 92, 95, 96, 98, 101, 104, 105, 106, 108, 110], "doesn": [2, 10, 75, 85], "t": [2, 3, 4, 7, 10, 20, 30, 31, 40, 41, 43, 44, 45, 46, 51, 57, 58, 67, 72, 73, 75, 81, 83, 84, 85, 91, 92, 93, 96, 97, 98, 100, 101, 104, 105, 108, 110], "alreadi": [2, 5, 10, 13, 19, 40, 43, 44, 49, 54, 62, 63, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 105, 106, 108], "exist": [2, 5, 10, 15, 21, 40, 43, 44, 56, 58, 62, 68, 70, 72, 75, 85, 86, 88, 89, 91, 92, 96, 103, 110], "made": [2, 5, 13, 19, 40, 44, 55, 75, 88, 89, 93, 96, 97, 99, 100, 103, 105, 107, 108], "easi": [2, 12, 49, 75, 91, 92, 98, 99, 101, 104], "inherit": [2, 7, 41, 75], "baseestim": [2, 44, 75], "yourmodel": [2, 75], "def": [2, 7, 17, 40, 44, 62, 75, 89, 90, 91, 92, 93, 97, 98, 99, 100, 101, 103, 104, 106, 108, 110], "self": [2, 3, 5, 7, 10, 13, 15, 16, 17, 19, 34, 40, 41, 43, 44, 46, 51, 72, 73, 75, 88, 91, 93, 97, 98, 100, 104, 109, 110], "refer": [2, 10, 13, 19, 40, 44, 45, 64, 65, 67, 68, 70, 71, 72, 75, 79, 80, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 107, 108], "origin": [2, 5, 10, 44, 45, 46, 58, 59, 62, 64, 65, 68, 71, 72, 75, 76, 79, 81, 83, 88, 89, 91, 93, 95, 96, 97, 99, 101, 105, 106, 108, 110], "total": [2, 3, 4, 39, 43, 59, 64, 84, 93, 99, 109], "state": [2, 3, 5, 40, 41, 44, 50, 75, 101, 104, 105, 110], "art": [2, 41, 101, 104], "northcutt": [2, 3, 39, 72, 73], "et": [2, 3, 39, 41, 72, 73], "al": [2, 3, 39, 41, 72, 73], "2021": [2, 3, 39, 72, 73], "weak": [2, 71], "supervis": [2, 10, 91, 92, 99, 103], "find": [2, 5, 9, 10, 13, 16, 17, 19, 22, 23, 25, 26, 28, 29, 30, 31, 34, 35, 39, 40, 42, 43, 44, 45, 46, 50, 56, 58, 59, 61, 68, 71, 72, 73, 75, 77, 81, 83, 85, 86, 91, 98, 100, 102, 107], "uncertainti": [2, 10, 48, 72, 75, 99, 106, 108], "It": [2, 3, 5, 7, 10, 15, 16, 19, 25, 30, 33, 35, 36, 37, 40, 44, 46, 49, 51, 54, 55, 57, 63, 70, 71, 75, 85, 91, 92, 93, 97, 99, 101, 104, 107], "work": [2, 3, 7, 10, 15, 33, 39, 40, 43, 44, 46, 49, 58, 59, 60, 62, 63, 73, 75, 85, 86, 89, 91, 92, 97, 98, 100, 106, 108], "includ": [2, 3, 5, 7, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 40, 42, 43, 44, 54, 58, 59, 61, 63, 64, 67, 68, 72, 73, 75, 79, 80, 81, 83, 85, 86, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 105, 106, 110], "deep": [2, 42, 44, 61, 62, 75, 96], "see": [2, 3, 5, 7, 10, 13, 16, 17, 36, 39, 40, 43, 44, 45, 46, 51, 56, 59, 62, 64, 65, 67, 68, 71, 72, 73, 75, 81, 83, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 108, 109, 110], "subfield": 2, "theori": [2, 101], "machin": [2, 4, 5, 9, 10, 17, 19, 36, 42, 57, 61, 75, 88, 89, 91, 92, 97, 98, 100, 103], "across": [2, 3, 5, 7, 10, 13, 16, 25, 39, 43, 51, 64, 71, 72, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 107, 108], "varieti": [2, 88, 89, 99], "like": [2, 3, 5, 6, 7, 10, 17, 35, 39, 40, 43, 44, 46, 49, 59, 62, 63, 64, 67, 68, 70, 73, 75, 76, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "pu": [2, 59], "input": [2, 3, 5, 9, 13, 19, 29, 39, 40, 43, 44, 49, 51, 54, 55, 58, 59, 60, 62, 71, 75, 85, 86, 89, 92, 93, 96, 98, 99, 100, 101, 103, 104, 105, 108, 109, 110], "discret": [2, 37, 46, 49, 59, 72, 73, 77, 79, 80], "vector": [2, 3, 4, 5, 10, 13, 19, 46, 49, 51, 52, 54, 59, 72, 73, 85, 89, 90, 91, 92, 93, 95, 96, 100, 101, 104, 105, 106, 109, 110], "would": [2, 3, 5, 10, 40, 43, 44, 46, 55, 59, 65, 75, 85, 89, 91, 93, 99, 100, 101, 106, 108, 110], "obtain": [2, 5, 8, 10, 13, 19, 46, 63, 65, 68, 71, 73, 76, 90, 92, 96, 99, 103, 105, 107, 109, 110], "been": [2, 4, 39, 46, 49, 54, 58, 59, 63, 64, 68, 70, 72, 73, 75, 90, 91, 95, 97, 99, 100, 101, 103, 104, 105, 106, 109, 110], "dure": [2, 10, 19, 54, 56, 72, 75, 88, 89, 90, 95, 96, 97, 99, 101, 104, 107, 108, 110], "denot": [2, 3, 49, 51, 59, 65, 72, 73, 83], "tild": 2, "paper": [2, 4, 10, 63, 72, 81, 83, 98, 101, 103, 106, 108, 110], "cv_n_fold": [2, 3, 75, 89], "5": [2, 3, 4, 5, 8, 10, 13, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 44, 46, 48, 50, 51, 59, 63, 64, 67, 68, 71, 75, 76, 83, 89, 91, 96, 98, 99, 104, 105, 106, 107, 109, 110], "converge_latent_estim": [2, 3], "pulearn": [2, 59], "find_label_issues_kwarg": [2, 10, 75, 86, 99, 101], "label_quality_scores_kwarg": [2, 10], "low_memori": [2, 65, 81, 99], "clean": [2, 70, 73, 75, 76, 85, 88, 89, 91, 92, 98, 108], "even": [2, 3, 7, 9, 10, 39, 43, 48, 49, 59, 75, 90, 97, 99, 100, 101, 103, 104, 105], "messi": [2, 75, 101], "ridden": [2, 75], "autom": [2, 9, 10, 75, 85, 88, 89, 92, 95, 96, 98, 99, 100, 101, 104, 106, 108], "robust": [2, 49, 54, 75, 92, 97, 99, 100], "prone": [2, 75], "out": [2, 3, 5, 10, 13, 19, 31, 40, 44, 46, 51, 54, 62, 65, 66, 68, 71, 72, 73, 75, 76, 84, 85, 86, 89, 97, 98, 99, 101, 102, 104, 105, 106, 108, 109, 110], "current": [2, 3, 5, 7, 10, 11, 13, 16, 17, 25, 40, 44, 45, 46, 51, 63, 70, 75, 91, 92, 99, 100, 103, 105], "intend": [2, 13, 14, 16, 17, 18, 19, 35, 36, 37, 47, 54, 63, 79, 83, 90, 91, 92, 96, 101], "A": [2, 3, 4, 5, 7, 10, 13, 15, 16, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 39, 40, 41, 44, 46, 49, 50, 51, 52, 54, 55, 56, 57, 58, 59, 62, 63, 64, 67, 70, 71, 72, 73, 75, 77, 79, 80, 84, 86, 88, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 107, 110], "follow": [2, 3, 10, 17, 33, 37, 39, 40, 43, 44, 51, 53, 57, 63, 64, 68, 70, 71, 72, 75, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "tutori": [2, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 101, 103, 104, 105, 106, 108, 109, 110], "repo": 2, "wrapper": [2, 13, 62, 88, 89, 90, 108], "around": [2, 13, 70, 91, 92, 100, 105, 106, 110], "fasttext": 2, "store": [2, 4, 5, 10, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 43, 44, 72, 75, 88, 89, 95, 96, 97, 98, 99, 109, 110], "along": [2, 51, 65, 83, 91, 92, 93, 97, 99, 106], "dimens": [2, 59, 77, 80, 93, 99, 106, 109], "select": [2, 9, 10, 29, 53, 63, 73, 93, 100, 103, 106], "split": [2, 3, 5, 10, 15, 43, 51, 58, 59, 75, 88, 90, 91, 92, 93, 95, 96, 97, 98, 101, 102, 104, 107, 110], "cross": [2, 3, 10, 39, 46, 49, 50, 51, 65, 68, 71, 73, 75, 76, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 102, 104, 105, 108, 109, 110], "fold": [2, 3, 39, 46, 49, 75, 88, 90, 95, 98, 99, 105, 109], "By": [2, 39, 64, 65, 75, 91, 97, 109], "need": [2, 3, 10, 11, 39, 40, 43, 44, 46, 54, 56, 64, 65, 67, 72, 75, 85, 89, 90, 91, 92, 96, 97, 99, 100, 101, 103, 104, 105, 109], "holdout": [2, 3, 75], "comput": [2, 3, 4, 5, 7, 8, 10, 13, 22, 23, 25, 26, 29, 30, 31, 34, 39, 40, 41, 43, 44, 46, 48, 49, 50, 51, 54, 55, 56, 59, 63, 64, 65, 67, 70, 71, 72, 73, 75, 76, 77, 79, 85, 86, 89, 91, 92, 98, 101, 102, 105, 106, 108, 109], "them": [2, 3, 5, 7, 9, 10, 12, 15, 30, 35, 38, 40, 42, 43, 44, 46, 56, 61, 63, 72, 75, 86, 88, 89, 91, 92, 93, 95, 96, 97, 99, 103, 104, 106, 108, 109, 110], "numer": [2, 3, 4, 5, 10, 13, 16, 25, 33, 37, 51, 54, 55, 70, 72, 75, 80, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 96, 97, 100, 101, 103, 104, 106, 108], "consist": [2, 3, 10, 40, 44, 53, 59, 63, 97, 109, 110], "latent": [2, 3, 49], "thei": [2, 3, 5, 14, 18, 24, 27, 29, 32, 40, 41, 42, 44, 46, 47, 54, 57, 59, 62, 65, 70, 73, 75, 76, 79, 83, 85, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 106, 108, 110], "relat": [2, 3, 10, 16, 22, 23, 29, 30, 31, 34, 49, 59, 64, 75, 92, 96, 97], "close": [2, 3, 10, 43, 49, 72, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 105], "form": [2, 3, 10, 40, 41, 44, 49, 58, 59, 73, 75, 99], "equival": [2, 3, 40, 44, 49, 72, 106, 108], "iter": [2, 3, 39, 40, 44, 46, 59, 64, 65, 75, 99, 103, 109], "enforc": [2, 40, 44, 59], "perfectli": [2, 39, 64, 101], "certain": [2, 3, 5, 10, 40, 44, 62, 71, 75, 91, 92, 97, 98, 105, 106], "dict": [2, 3, 5, 10, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 43, 44, 46, 50, 51, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 83, 91, 92, 93, 99, 100, 110], "keyword": [2, 3, 5, 10, 11, 13, 19, 26, 30, 33, 40, 43, 44, 46, 48, 51, 54, 56, 58, 62, 63, 65, 71, 72, 73, 75, 80, 81, 83, 91], "filter": [2, 3, 10, 43, 45, 58, 64, 66, 67, 69, 71, 78, 79, 80, 82, 83, 84, 85, 86, 88, 89, 90, 93, 96, 98, 99, 100, 104, 105, 108, 109, 110], "find_label_issu": [2, 3, 10, 33, 42, 43, 45, 46, 64, 65, 66, 67, 68, 69, 70, 71, 74, 75, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 88, 89, 99, 104, 105, 108, 109, 110], "particularli": [2, 85, 100, 103, 106], "filter_bi": [2, 3, 43, 46, 65, 86, 99], "frac_nois": [2, 46, 65, 81, 99], "min_examples_per_class": [2, 46, 65, 99, 101], "impact": [2, 4, 10, 91, 92, 93, 97], "ml": [2, 4, 5, 9, 10, 18, 75, 85, 88, 89, 91, 92, 93, 95, 96, 97, 98, 102, 103, 104, 106, 107, 108], "accuraci": [2, 10, 41, 73, 88, 89, 90, 93, 99, 100, 101, 103, 106, 108, 109], "n_job": [2, 43, 46, 65, 77, 79, 81, 99, 100, 106, 109], "disabl": [2, 40, 44, 46, 106], "process": [2, 3, 7, 13, 16, 19, 35, 40, 43, 44, 46, 54, 58, 63, 65, 71, 77, 79, 81, 89, 90, 91, 97, 99, 100, 103, 107], "caus": [2, 46, 51, 91, 92, 97, 99], "rank": [2, 3, 10, 39, 43, 45, 46, 51, 64, 65, 66, 68, 69, 71, 72, 74, 78, 80, 81, 82, 84, 85, 86, 88, 89, 91, 92, 98, 99, 104, 105, 106, 109, 110], "get_label_quality_scor": [2, 42, 43, 45, 46, 47, 51, 63, 65, 66, 67, 68, 69, 70, 73, 74, 76, 78, 79, 81, 82, 83, 86, 99, 101, 104, 105, 109, 110], "adjust_pred_prob": [2, 10, 67, 72, 73, 101], "control": [2, 5, 9, 10, 13, 19, 43, 46, 63, 71, 72, 75, 81, 83, 91, 92, 97, 98, 99], "how": [2, 3, 5, 10, 13, 15, 16, 17, 19, 25, 39, 40, 41, 43, 44, 49, 59, 63, 64, 67, 68, 70, 72, 73, 75, 79, 83, 85, 88, 89, 91, 92, 93, 95, 96, 97, 98, 100, 105, 106, 107, 108, 109], "much": [2, 10, 39, 43, 46, 75, 97, 99, 103], "output": [2, 3, 5, 10, 13, 19, 35, 40, 41, 44, 49, 59, 62, 63, 64, 68, 70, 71, 72, 75, 79, 80, 83, 84, 85, 86, 89, 90, 91, 93, 96, 97, 98, 99, 100, 105, 106, 107, 108], "print": [2, 5, 7, 13, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 59, 63, 64, 65, 70, 72, 73, 75, 77, 79, 80, 84, 86, 88, 89, 90, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "suppress": [2, 43, 63, 70, 72, 73, 75, 77, 79, 80, 109, 110], "statement": [2, 43, 63, 70, 72, 73, 75, 77, 79, 80], "big": [2, 43, 65, 71, 75, 101], "limit": [2, 5, 13, 19, 43, 54, 65, 85, 97, 105, 109, 110], "memori": [2, 40, 43, 44, 65, 71, 77, 79, 91, 109], "experiment": [2, 40, 41, 43, 44, 45, 65, 86, 88, 89, 92, 95, 96, 98, 99, 101, 104, 106, 108], "label_issues_batch": [2, 42, 65, 99], "find_label_issues_batch": [2, 42, 43, 65, 99], "pred_prob": [2, 3, 5, 8, 10, 11, 13, 19, 26, 28, 29, 31, 34, 35, 39, 43, 45, 46, 48, 49, 50, 51, 52, 59, 60, 63, 64, 65, 67, 68, 71, 72, 73, 77, 79, 80, 81, 83, 84, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108], "threshold": [2, 3, 4, 7, 10, 13, 21, 22, 23, 25, 31, 33, 34, 43, 57, 70, 71, 72, 73, 79, 83, 91, 97, 105, 106, 109, 110], "inverse_noise_matrix": [2, 3, 10, 49, 59, 86, 101], "label_issu": [2, 43, 46, 65, 68, 75, 77, 86, 88, 89, 90, 93, 96, 99, 100, 101, 104, 108], "clf_kwarg": [2, 3, 10, 75], "clf_final_kwarg": [2, 75], "validation_func": [2, 3, 10], "correct": [2, 5, 9, 10, 39, 43, 46, 48, 54, 63, 64, 65, 67, 68, 70, 71, 73, 75, 76, 79, 83, 85, 88, 89, 90, 92, 93, 95, 96, 98, 101, 103, 104, 105, 106, 107, 108], "result": [2, 3, 9, 10, 13, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 43, 44, 46, 48, 57, 59, 65, 67, 68, 71, 73, 75, 76, 77, 79, 83, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 104, 108, 109, 110], "identifi": [2, 3, 5, 7, 9, 10, 13, 15, 19, 30, 36, 39, 43, 45, 46, 54, 65, 68, 71, 73, 75, 76, 77, 80, 81, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 101, 104, 106, 108, 109, 110], "final": [2, 10, 75, 88, 95, 97, 100, 105, 107, 108], "remain": [2, 75, 86, 88, 89, 93, 97, 100, 104, 108, 110], "datasetlik": [2, 59, 75], "beyond": [2, 5, 7, 9, 10, 12, 38, 85, 88, 89, 100, 108, 109], "pd": [2, 3, 5, 7, 13, 16, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 50, 62, 63, 64, 75, 83, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 108, 110], "datafram": [2, 3, 5, 7, 13, 15, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 43, 50, 59, 60, 62, 63, 64, 75, 80, 84, 86, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 108, 109, 110], "scipi": [2, 4, 5, 13, 16, 55, 59, 72, 97], "spars": [2, 4, 5, 10, 13, 16, 19, 21, 34, 54, 59, 60, 95, 97], "csr_matrix": [2, 4, 5, 13, 16, 19, 21, 34, 54, 97], "torch": [2, 40, 41, 44, 89, 90, 93, 96, 98, 106], "util": [2, 5, 10, 13, 19, 36, 40, 41, 44, 47, 54, 62, 63, 68, 71, 75, 85, 86, 90, 91, 92, 93, 99, 101, 106], "tensorflow": [2, 59, 62, 85, 90, 99], "object": [2, 5, 10, 13, 15, 16, 19, 35, 36, 40, 41, 43, 44, 51, 54, 56, 59, 60, 62, 65, 68, 69, 70, 71, 72, 75, 83, 85, 89, 90, 92, 93, 95, 97, 99, 100, 101, 102, 104, 108], "list": [2, 3, 5, 10, 15, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 41, 43, 44, 45, 46, 52, 54, 58, 59, 60, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 79, 80, 81, 83, 84, 86, 89, 90, 91, 92, 93, 98, 99, 100, 101, 104, 105, 108, 110], "index_list": 2, "subset": [2, 3, 5, 13, 19, 39, 43, 46, 59, 73, 80, 84, 88, 89, 90, 93, 95, 96, 97, 99, 104, 105, 106, 107, 108, 110], "wa": [2, 3, 15, 17, 43, 57, 59, 63, 64, 70, 72, 84, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 104, 105, 107, 109, 110], "abl": [2, 3, 10, 75, 90, 99, 100, 101, 103, 104], "format": [2, 3, 5, 10, 15, 35, 40, 43, 44, 46, 49, 50, 51, 52, 54, 59, 60, 62, 63, 64, 65, 68, 71, 72, 73, 75, 77, 79, 80, 83, 84, 88, 91, 92, 93, 95, 97, 98, 100, 103, 108, 109, 110], "make": [2, 3, 5, 21, 40, 43, 44, 51, 62, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 101, 103, 104, 105, 106, 108], "sure": [2, 5, 43, 46, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 103, 104, 105, 106, 108], "shuffl": [2, 10, 59, 90, 93, 96, 97, 104, 106], "ha": [2, 3, 5, 6, 10, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 45, 49, 51, 54, 58, 59, 63, 68, 70, 75, 81, 83, 84, 85, 88, 89, 90, 91, 92, 95, 96, 97, 100, 101, 103, 104, 105, 106, 107, 108, 110], "batch": [2, 43, 59, 62, 63, 77, 79, 93, 99, 106], "order": [2, 5, 10, 37, 39, 40, 44, 45, 46, 49, 50, 51, 57, 59, 63, 64, 65, 68, 71, 72, 73, 77, 80, 81, 83, 84, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 108, 109, 110], "destroi": [2, 59], "oper": [2, 40, 43, 44, 54, 59, 62, 73, 85, 88, 89, 96, 99, 106], "eg": [2, 5, 10, 59, 68, 71, 91, 92, 99, 100], "repeat": [2, 59, 63, 103, 106], "appli": [2, 10, 37, 40, 42, 44, 46, 51, 52, 54, 58, 59, 67, 72, 81, 85, 88, 89, 90, 91, 92, 93, 95, 97, 99, 100, 103, 104, 106, 107, 108, 109], "array_lik": [2, 3, 39, 46, 59, 65, 72, 76], "some": [2, 3, 5, 10, 17, 25, 39, 40, 42, 44, 46, 49, 54, 58, 59, 61, 63, 64, 65, 67, 68, 71, 72, 73, 75, 77, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "seri": [2, 3, 43, 59, 60, 75, 83, 99, 100], "row": [2, 3, 5, 10, 13, 16, 30, 35, 39, 43, 46, 48, 49, 54, 55, 59, 63, 64, 65, 67, 72, 73, 75, 80, 81, 83, 84, 88, 90, 93, 95, 96, 97, 98, 99, 100, 103, 104, 106, 110], "rather": [2, 3, 5, 10, 29, 39, 59, 62, 63, 70, 79, 83, 89, 98, 100, 103, 107, 108, 109, 110], "leav": [2, 46], "per": [2, 3, 5, 7, 10, 13, 16, 39, 43, 46, 51, 58, 63, 64, 65, 67, 70, 71, 73, 76, 77, 79, 83, 92, 99, 105, 110], "determin": [2, 3, 10, 15, 19, 25, 29, 33, 39, 43, 46, 51, 54, 59, 63, 65, 68, 70, 73, 79, 83, 91, 97, 99, 100, 103, 105, 106, 108], "cutoff": [2, 3, 55, 106], "consid": [2, 3, 4, 5, 10, 13, 16, 19, 26, 29, 31, 34, 39, 40, 44, 46, 54, 56, 59, 63, 70, 72, 73, 76, 79, 83, 88, 89, 90, 93, 95, 96, 97, 99, 100, 101, 105, 106, 107, 108, 109], "section": [2, 3, 7, 10, 86, 93, 95, 97, 99, 100, 105], "3": [2, 3, 4, 5, 7, 10, 11, 37, 39, 40, 44, 46, 49, 50, 51, 52, 55, 57, 58, 59, 62, 65, 72, 73, 75, 76, 81, 83, 98, 99, 107], "equat": [2, 3, 49], "advanc": [2, 3, 5, 9, 10, 13, 19, 70, 72, 83, 86, 92, 94, 97, 99, 100, 101], "user": [2, 3, 5, 9, 10, 13, 17, 19, 30, 35, 36, 37, 40, 44, 46, 54, 62, 70, 72, 73, 75, 79, 83, 100, 101], "specifi": [2, 3, 4, 5, 8, 10, 13, 16, 17, 19, 21, 34, 36, 40, 43, 44, 46, 51, 54, 56, 58, 62, 63, 64, 65, 68, 70, 72, 73, 75, 76, 84, 86, 89, 90, 92, 93, 96, 97, 100, 103, 105, 108], "automat": [2, 3, 5, 29, 39, 85, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "greater": [2, 3, 4, 5, 7, 9, 10, 31, 43, 55, 59, 70, 92, 98, 99, 110], "count": [2, 25, 29, 39, 43, 46, 49, 59, 64, 65, 71, 86, 93, 97, 99, 105], "observ": [2, 3, 49, 56, 90, 91, 92, 103, 106, 108], "mislabel": [2, 10, 39, 43, 45, 46, 49, 63, 64, 65, 68, 70, 73, 79, 81, 83, 84, 85, 88, 89, 90, 93, 95, 96, 99, 100, 101, 105, 108], "one": [2, 3, 5, 7, 10, 29, 39, 40, 43, 44, 45, 46, 51, 57, 59, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 77, 79, 80, 81, 83, 84, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 103, 106, 107, 108, 110], "get_label_issu": [2, 42, 43, 74, 75, 88, 89, 101, 108], "either": [2, 3, 4, 7, 10, 40, 43, 44, 46, 55, 63, 65, 70, 72, 73, 77, 79, 92, 97, 99, 104, 105], "boolean": [2, 7, 10, 25, 43, 46, 56, 58, 63, 65, 68, 73, 75, 77, 79, 80, 85, 89, 90, 92, 93, 96, 99, 105, 108, 109], "label_issues_mask": [2, 46, 73, 75, 86], "indic": [2, 3, 4, 5, 7, 10, 13, 16, 25, 39, 43, 44, 45, 46, 48, 51, 54, 56, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 73, 75, 76, 79, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "its": [2, 5, 7, 9, 10, 13, 19, 40, 43, 44, 46, 54, 56, 57, 58, 65, 68, 71, 72, 73, 75, 77, 81, 83, 85, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 107, 108, 109, 110], "return_indices_ranked_bi": [2, 43, 46, 65, 81, 86, 88, 89, 99, 101], "significantli": [2, 10, 93, 97, 101, 103, 107], "reduc": [2, 43, 46, 59, 90, 99], "time": [2, 10, 40, 43, 44, 59, 63, 84, 86, 91, 93, 99, 100, 105, 109, 110], "take": [2, 5, 10, 39, 40, 44, 50, 51, 54, 56, 59, 62, 73, 88, 93, 95, 103, 104, 105, 110], "run": [2, 5, 6, 7, 9, 10, 11, 12, 13, 17, 19, 29, 30, 35, 38, 40, 43, 44, 56, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 110], "skip": [2, 10, 40, 44, 75, 90, 97, 99, 100, 104, 110], "slow": [2, 3], "step": [2, 7, 29, 51, 71, 93, 97, 100, 101, 103, 107], "caution": [2, 5, 99, 100], "previous": [2, 5, 13, 16, 59, 72, 75, 86, 88, 90, 91, 95, 96, 100, 103, 107], "assign": [2, 7, 10, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 40, 44, 50, 51, 59, 75, 88, 91, 93, 95, 97, 99, 108, 109, 110], "individu": [2, 4, 7, 10, 13, 16, 29, 40, 44, 45, 63, 67, 70, 73, 75, 81, 83, 86, 88, 92, 95, 97, 98, 99, 103, 104, 105, 110], "still": [2, 43, 44, 59, 72, 88, 93, 99, 106], "extra": [2, 40, 44, 59, 62, 63, 64, 75, 93, 96, 99, 100, 103, 106], "receiv": [2, 10, 40, 44, 45, 64, 67, 68, 75, 77, 81, 92, 105], "overwritten": [2, 75], "callabl": [2, 3, 4, 10, 29, 40, 44, 51, 54, 55, 56, 58, 62, 67, 99], "x_val": 2, "y_val": 2, "map": [2, 3, 15, 43, 44, 47, 50, 58, 59, 71, 73, 75, 80, 90, 91, 92, 93, 97, 99, 101, 104, 110], "appropri": [2, 10, 19, 37, 55, 65, 73, 91, 95, 100, 104, 105], "earli": [2, 93], "stop": [2, 93], "x_valid": 2, "y_valid": 2, "could": [2, 7, 10, 25, 39, 59, 72, 88, 91, 93, 95, 97, 100, 104, 108, 110], "f": [2, 7, 88, 89, 90, 91, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108], "ignor": [2, 40, 44, 58, 62, 75, 80, 84, 90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "allow": [2, 13, 39, 40, 43, 44, 48, 56, 59, 63, 71, 72, 75, 77, 79, 89, 90, 93, 97, 99, 107, 109], "access": [2, 10, 16, 40, 44, 75, 92, 93, 98, 104], "hyperparamet": [2, 67, 72, 93], "purpos": [2, 54, 91, 92, 97, 99, 104, 108], "want": [2, 5, 10, 39, 43, 54, 60, 63, 65, 75, 89, 91, 93, 96, 98, 100, 103, 105, 106, 107, 109, 110], "explicitli": [2, 8, 10, 44, 54, 75], "yourself": [2, 5, 43, 92, 97], "altern": [2, 7, 10, 51, 56, 59, 62, 63, 73, 86, 89, 90, 93, 95, 96, 98, 99, 100, 101, 103, 104, 106, 108], "same": [2, 3, 5, 7, 9, 10, 13, 15, 17, 19, 29, 33, 40, 43, 44, 46, 54, 59, 62, 63, 65, 72, 73, 75, 79, 80, 83, 84, 85, 88, 89, 91, 92, 93, 95, 96, 97, 99, 100, 104, 105, 106, 107, 108, 109], "effect": [2, 10, 30, 40, 44, 63, 72, 75, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 106, 108], "offer": [2, 5, 9, 10, 89, 90, 91, 92, 96, 99, 100, 101, 104], "after": [2, 3, 5, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 59, 63, 75, 89, 91, 93, 96, 97, 99, 100, 101, 103, 105, 106, 107, 108, 109], "attribut": [2, 5, 7, 10, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 40, 43, 44, 51, 56, 72, 75, 88, 91, 97], "label_issues_df": [2, 75, 93], "similar": [2, 10, 39, 40, 44, 56, 59, 63, 67, 68, 70, 72, 75, 79, 83, 91, 92, 93, 95, 96, 97, 99, 100, 101, 105, 106, 109], "document": [2, 3, 5, 13, 17, 19, 39, 40, 43, 44, 45, 46, 51, 58, 62, 64, 65, 67, 70, 71, 72, 75, 79, 80, 81, 83, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 110], "descript": [2, 5, 7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36, 39, 45, 59, 68, 75, 91, 92], "were": [2, 3, 5, 10, 39, 44, 54, 64, 70, 83, 88, 90, 95, 99, 101, 103, 105, 107, 109], "present": [2, 3, 5, 10, 13, 15, 16, 23, 39, 59, 72, 80, 85, 93, 97, 99, 100, 106], "actual": [2, 3, 5, 10, 39, 54, 63, 64, 73, 92, 99, 101, 107, 110], "num_class": [2, 39, 43, 59, 62, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 104, 106], "uniqu": [2, 34, 59, 80, 91, 97, 99, 100, 104, 106], "given_label": [2, 5, 11, 28, 33, 39, 49, 75, 80, 84, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 108, 109, 110], "normal": [2, 3, 21, 29, 34, 46, 48, 51, 57, 58, 59, 73, 97, 99, 101, 106], "trick": [2, 99], "distribut": [2, 3, 5, 10, 29, 31, 39, 44, 46, 50, 57, 63, 71, 72, 73, 85, 91, 92, 93, 95, 96, 97, 100, 105, 106], "account": [2, 39, 63, 67, 72, 73, 89, 96, 99, 101, 103, 104, 106, 108], "word": [2, 3, 58, 83, 84, 99], "remov": [2, 10, 34, 39, 40, 44, 46, 75, 85, 88, 89, 93, 96, 97, 98, 99, 100, 104, 106, 108], "so": [2, 3, 5, 6, 7, 10, 17, 29, 37, 39, 40, 43, 44, 46, 54, 59, 63, 64, 70, 73, 75, 79, 83, 90, 91, 92, 93, 96, 97, 100, 101, 104, 106, 109], "proportion": [2, 10, 46], "just": [2, 3, 5, 10, 13, 16, 35, 39, 41, 43, 59, 62, 73, 75, 77, 85, 86, 88, 89, 90, 92, 93, 95, 96, 97, 99, 101, 104, 105, 106, 107, 108, 109], "procedur": 2, "get": [2, 3, 5, 8, 10, 11, 16, 34, 40, 41, 44, 46, 51, 57, 58, 59, 63, 65, 67, 72, 73, 75, 76, 77, 85, 88, 89, 90, 93, 96, 97, 98, 99, 100, 101, 106, 107, 108], "detect": [2, 5, 7, 9, 13, 16, 17, 19, 21, 25, 31, 45, 54, 57, 66, 68, 69, 70, 71, 72, 73, 74, 75, 78, 82, 85, 88, 89, 91, 94, 98, 100, 102, 104, 108, 109, 110], "arg": [2, 15, 25, 30, 34, 40, 41, 44, 51, 59, 73, 75, 100], "kwarg": [2, 7, 10, 13, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 43, 44, 45, 51, 54, 62, 71, 75, 77, 79, 80, 81, 99], "test": [2, 5, 10, 29, 44, 51, 54, 62, 75, 85, 88, 89, 91, 92, 93, 95, 96, 102, 107, 108, 110], "expect": [2, 3, 10, 40, 44, 46, 51, 54, 63, 72, 73, 75, 88, 89, 99, 100, 101, 103, 104, 105, 108, 110], "class_predict": 2, "evalu": [2, 10, 40, 41, 42, 43, 44, 71, 75, 88, 89, 90, 91, 92, 93, 99, 101, 103, 107, 108, 109], "simpli": [2, 10, 39, 73, 85, 89, 91, 92, 95, 96, 99, 101, 104, 108, 109, 110], "quantifi": [2, 4, 5, 7, 10, 13, 16, 46, 67, 72, 75, 85, 92, 93, 95, 96, 97, 100, 101, 105], "save_spac": [2, 10, 74, 75], "potenti": [2, 10, 39, 46, 58, 65, 68, 71, 73, 75, 77, 79, 84, 86, 88, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 109, 110], "cach": [2, 89, 96], "panda": [2, 5, 7, 15, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 59, 60, 62, 63, 64, 86, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 103, 108, 109], "unlik": [2, 10, 46, 48, 51, 62, 64, 65, 67, 83, 91, 100, 103, 104, 106, 108], "both": [2, 5, 10, 13, 19, 29, 39, 40, 44, 46, 54, 59, 63, 65, 73, 77, 79, 84, 85, 91, 93, 99, 100, 101, 103, 110], "mask": [2, 43, 46, 58, 59, 65, 68, 73, 75, 77, 79, 80, 85, 98, 99, 103, 105, 109, 110], "prefer": [2, 73, 81, 104], "plan": 2, "subsequ": [2, 3, 40, 44, 56, 89, 96, 99, 101, 105], "invok": [2, 40, 44, 101, 107], "scratch": [2, 54, 75], "To": [2, 5, 7, 9, 10, 12, 13, 16, 19, 29, 38, 40, 43, 44, 45, 46, 62, 63, 65, 67, 71, 72, 73, 75, 76, 77, 79, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 107, 108, 109, 110], "share": [2, 10, 73, 75], "mostli": [2, 59, 70, 75, 100, 104, 108], "longer": [2, 37, 50, 51, 58, 75, 86, 89, 96, 99, 100, 105], "info": [2, 5, 7, 10, 13, 16, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 64, 75, 83, 92, 97, 98, 110], "about": [2, 3, 5, 7, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 41, 43, 48, 63, 64, 67, 71, 75, 80, 83, 90, 91, 93, 95, 96, 97, 98, 99, 100, 101, 103, 106], "docstr": [2, 39, 40, 44, 59, 75, 98, 101], "unless": [2, 40, 44, 54, 75, 99], "our": [2, 3, 10, 62, 63, 73, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "is_label_issu": [2, 11, 33, 75, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 104, 108], "entir": [2, 10, 29, 43, 46, 49, 64, 65, 70, 73, 75, 77, 79, 80, 85, 91, 92, 97, 99, 100, 105, 106, 107, 109, 110], "accur": [2, 3, 5, 9, 10, 13, 19, 39, 43, 46, 55, 63, 64, 65, 68, 71, 73, 75, 76, 77, 79, 80, 86, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 103, 104, 106, 108], "label_qu": [2, 63, 75, 89, 101, 103, 108], "measur": [2, 5, 39, 63, 64, 75, 85, 88, 97, 98, 99, 100, 101, 103, 104, 108, 109, 110], "qualiti": [2, 3, 5, 7, 9, 10, 13, 16, 33, 34, 39, 43, 45, 46, 48, 51, 63, 64, 65, 67, 68, 70, 73, 75, 76, 79, 81, 83, 85, 86, 90, 91, 93, 99, 100, 102], "lower": [2, 4, 5, 7, 10, 13, 16, 31, 43, 51, 57, 63, 64, 67, 70, 71, 73, 75, 76, 79, 83, 89, 90, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 108, 109, 110], "eas": 2, "comparison": [2, 40, 44, 71, 100, 101, 103], "against": [2, 40, 44, 91, 95, 97, 99, 100, 103, 104], "predicted_label": [2, 5, 11, 28, 33, 75, 80, 84, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 108, 109], "ad": [2, 40, 44, 92, 103, 108], "precis": [2, 55, 57, 65, 68, 71, 97, 98, 99, 101, 109, 110], "definit": [2, 7, 37, 51, 75, 88, 95], "accessor": [2, 75], "describ": [2, 10, 21, 63, 72, 73, 75, 81, 83, 101, 103, 104, 105, 107, 110], "precomput": [2, 4, 5, 49, 54, 75, 98], "clear": [2, 40, 44, 56, 75, 89, 96, 97, 108], "save": [2, 5, 13, 19, 40, 43, 44, 71, 75, 97, 99, 105, 109, 110], "space": [2, 5, 10, 72, 75, 93, 95, 97, 98], "place": [2, 40, 44, 54, 59, 75, 88, 103], "larg": [2, 9, 10, 43, 54, 75, 93, 99, 105, 106, 109, 110], "deploi": [2, 9, 10, 75, 93, 99, 100], "care": [2, 10, 40, 44, 54, 75, 96, 97, 99, 101], "avail": [2, 4, 5, 7, 10, 15, 17, 36, 44, 56, 75, 99, 100, 101, 103, 105, 108], "cannot": [2, 5, 15, 17, 59, 100, 107, 110], "anymor": 2, "classmethod": [2, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 37, 44, 51, 75], "__init_subclass__": [2, 42, 44, 74, 75], "set_": [2, 44, 75], "_request": [2, 44, 75], "pep": [2, 44, 75], "487": [2, 44, 75], "look": [2, 5, 7, 10, 19, 40, 44, 59, 75, 80, 88, 91, 92, 95, 96, 99, 100, 101, 103, 104, 105, 106, 109, 110], "inform": [2, 5, 7, 10, 13, 16, 19, 36, 40, 44, 56, 59, 63, 64, 68, 71, 75, 80, 83, 84, 85, 90, 91, 95, 96, 97, 98, 100, 101, 103, 106, 109, 110], "__metadata_request__": [2, 44, 75], "infer": [2, 44, 59, 75, 80, 84, 88, 89, 93, 103, 104], "signatur": [2, 40, 44, 75], "accept": [2, 40, 44, 56, 57, 73, 75, 91, 92, 99], "metadata": [2, 10, 44, 75, 93, 110], "through": [2, 5, 7, 44, 75, 89, 90, 92, 96, 97, 98, 99, 100, 103, 105, 106], "develop": [2, 9, 44, 56, 75, 99, 101, 110], "request": [2, 44, 75, 88, 89, 92, 96, 97, 98, 104, 110], "those": [2, 3, 4, 10, 43, 44, 46, 53, 62, 63, 65, 71, 75, 79, 83, 84, 85, 90, 93, 97, 99, 100, 105, 109], "http": [2, 4, 5, 7, 9, 10, 12, 21, 38, 40, 41, 43, 44, 48, 56, 59, 68, 71, 72, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "www": [2, 44, 75, 106], "org": [2, 4, 21, 40, 41, 44, 56, 59, 72, 75, 99, 100, 101, 110], "dev": [2, 44, 75], "0487": [2, 44, 75], "get_metadata_rout": [2, 42, 44, 74, 75], "rout": [2, 44, 75], "pleas": [2, 40, 44, 62, 75, 85, 89, 90, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 106, 108, 110], "guid": [2, 7, 10, 44, 75, 86, 90, 91, 92, 93, 94, 95, 96, 97, 100, 101], "mechan": [2, 40, 44, 75], "metadatarequest": [2, 44, 75], "encapsul": [2, 19, 44, 70, 75], "get_param": [2, 42, 44, 61, 62, 74, 75], "subobject": [2, 44, 75], "param": [2, 10, 40, 44, 62, 72, 75, 99], "name": [2, 5, 6, 7, 10, 11, 13, 15, 16, 35, 37, 39, 40, 44, 50, 51, 55, 59, 62, 63, 64, 71, 75, 80, 84, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 108, 109, 110], "set_fit_request": [2, 42, 44, 74, 75], "str": [2, 3, 4, 5, 13, 15, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 43, 44, 46, 49, 51, 54, 55, 56, 57, 58, 59, 62, 63, 64, 68, 70, 71, 73, 75, 80, 84, 90, 91, 97, 99, 103, 104, 105, 110], "unchang": [2, 40, 44, 75, 97, 110], "relev": [2, 10, 19, 29, 44, 75, 93, 95, 97], "enable_metadata_rout": [2, 44, 75], "set_config": [2, 44, 75], "meta": [2, 44, 75], "rais": [2, 4, 5, 13, 15, 16, 37, 40, 44, 48, 51, 54, 57, 75, 99], "alia": [2, 40, 44, 75], "metadata_rout": [2, 44, 75], "retain": [2, 44, 59, 75], "chang": [2, 35, 37, 40, 43, 44, 48, 75, 83, 88, 89, 90, 91, 96, 99, 100, 105, 106, 110], "version": [2, 4, 5, 7, 9, 10, 12, 14, 18, 24, 27, 32, 38, 40, 42, 44, 47, 48, 59, 61, 62, 73, 75, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 108, 110], "sub": [2, 44, 70, 75], "pipelin": [2, 44, 75, 108], "otherwis": [2, 4, 7, 10, 37, 39, 40, 43, 44, 46, 52, 55, 57, 58, 59, 65, 75, 77, 79, 80, 84, 85, 89, 96, 99, 100], "updat": [2, 13, 16, 40, 43, 44, 54, 62, 75, 86, 91, 93, 100], "set_param": [2, 42, 44, 61, 62, 74, 75], "simpl": [2, 40, 44, 46, 63, 73, 75, 88, 89, 91, 92, 93, 95, 96, 100, 103, 106, 108], "well": [2, 3, 9, 10, 40, 44, 48, 49, 63, 65, 71, 73, 75, 80, 83, 84, 86, 91, 92, 93, 95, 96, 99, 100, 101, 103, 105, 106], "nest": [2, 40, 44, 45, 60, 75, 81, 83, 84, 110], "latter": [2, 40, 44, 75, 106], "compon": [2, 44, 75], "__": [2, 44, 75], "set_score_request": [2, 74, 75], "structur": [3, 72, 95, 97, 99, 100], "unobserv": 3, "less": [3, 4, 5, 10, 34, 43, 51, 63, 72, 73, 77, 79, 83, 93, 95, 97, 98, 99, 100, 101, 105, 110], "channel": [3, 90, 101], "character": 3, "flip": 3, "nm": 3, "invers": [3, 10, 39, 49, 59, 64, 89, 92, 98], "inv": 3, "confident_joint": [3, 25, 39, 46, 59, 64, 65, 86, 99, 101], "un": 3, "under": [3, 10, 40, 44, 64, 71, 72, 92, 97, 100, 106], "joint": [3, 39, 46, 49, 59, 64, 65, 98], "num_label_issu": [3, 43, 46, 65, 80, 84, 86], "estimation_method": [3, 43], "off_diagon": 3, "multi_label": [3, 39, 46, 59, 60, 65, 104], "don": [3, 10, 85, 92, 93, 96, 101, 105, 108], "statis": 3, "compute_confident_joint": [3, 39, 46, 59, 65, 101], "off": [3, 46, 59, 70, 93, 101, 105, 106], "j": [3, 5, 39, 40, 44, 45, 46, 65, 68, 71, 72, 81, 83, 84, 91, 92, 101, 109, 110], "confident_learn": [3, 46, 65, 101], "off_diagonal_calibr": 3, "calibr": [3, 4, 46, 59, 63, 103], "cj": [3, 49, 59], "axi": [3, 34, 49, 51, 57, 77, 80, 90, 91, 92, 93, 97, 99, 100, 101, 103, 104, 106, 108, 109], "bincount": [3, 91, 92, 101, 103, 104], "alwai": [3, 10, 40, 44, 59, 88, 89, 90, 101, 108], "estimate_issu": 3, "over": [3, 5, 10, 40, 43, 44, 70, 71, 77, 79, 88, 92, 93, 95, 97, 98, 99, 100, 101, 106, 108], "As": [3, 7, 85, 91, 92, 96, 100, 101, 108, 110], "add": [3, 5, 7, 13, 15, 16, 40, 44, 62, 71, 89, 90, 91, 92, 93, 96, 97, 99, 100, 101, 104], "approach": [3, 39, 43, 46, 62, 88, 95, 97, 100, 101, 104, 106, 108], "custom": [3, 7, 10, 12, 33, 40, 43, 44, 51, 58, 73, 89, 92, 96, 97, 101, 108], "know": [3, 10, 91, 92, 93, 96, 99, 101, 103, 108], "cut": [3, 70, 85, 88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "off_diagonal_custom": 3, "tl": 3, "dr": 3, "sometim": [3, 35, 105, 106, 110], "underestim": 3, "few": [3, 9, 10, 71, 85, 97, 99, 103, 104, 105, 106, 110], "4": [3, 4, 5, 10, 11, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 50, 51, 58, 67, 68, 70, 71, 73, 76, 83, 98, 99, 104, 109, 110], "detail": [3, 4, 5, 10, 13, 17, 19, 36, 39, 40, 44, 45, 51, 56, 59, 62, 63, 64, 65, 67, 68, 70, 71, 72, 79, 80, 81, 85, 86, 90, 97, 99, 100, 104, 106, 110], "num_issu": [3, 7, 43, 90, 91, 92, 93, 95, 96, 97, 100, 101], "calibrate_confident_joint": 3, "up": [3, 7, 10, 20, 29, 30, 33, 46, 51, 53, 62, 63, 89, 98, 99, 105, 108, 110], "p_": [3, 39, 46], "pair": [3, 5, 10, 39, 46, 101], "v": [3, 10, 43, 64, 65, 67, 73, 91, 92, 102, 104, 105, 106, 107], "rest": [3, 5, 7, 9, 10, 12, 38, 64, 65, 67, 75, 88, 89, 91, 92, 93, 95, 96, 99, 100, 101, 103, 108], "fashion": [3, 5, 77, 88], "2x2": 3, "incorrectli": [3, 39, 64, 65, 68, 95, 100, 110], "calibrated_cj": 3, "c": [3, 10, 57, 58, 65, 73, 85, 88, 90, 91, 92, 95, 96, 97, 99, 100, 101, 104, 105, 106, 107, 108], "whose": [3, 4, 5, 10, 31, 40, 44, 49, 54, 58, 63, 67, 70, 76, 79, 83, 84, 90, 91, 92, 93, 95, 96, 99, 100, 101, 104, 105, 106, 109, 110], "truli": [3, 106, 109], "estimate_joint": [3, 39, 101], "joint_estim": 3, "confident_joint_distribut": 3, "recal": [3, 65, 71, 101, 105, 107, 109, 110], "return_indices_of_off_diagon": 3, "frequenc": [3, 29, 63, 64, 71, 80, 105, 106], "done": [3, 10, 62, 75, 91, 99, 101, 104, 106, 107], "overfit": [3, 10, 68, 71, 88, 90, 91, 92, 93, 95, 96, 107], "classifict": 3, "singl": [3, 5, 9, 10, 15, 29, 39, 40, 44, 45, 51, 52, 59, 63, 64, 70, 71, 72, 73, 83, 88, 90, 91, 97, 99, 101, 104, 105], "baselin": [3, 40, 46, 89, 106, 108], "proxi": 3, "union": [3, 5, 15, 29, 51, 54, 55, 56, 59, 60, 65, 71, 75, 83, 99], "tupl": [3, 34, 40, 44, 45, 49, 50, 52, 54, 58, 59, 63, 65, 71, 79, 81, 83, 84, 90, 110], "confident_joint_count": 3, "indices_off_diagon": 3, "simplif": 3, "effici": [3, 4, 5, 10, 43, 49, 54, 55, 63, 72, 77, 79, 85, 89, 93, 97, 99, 100, 109], "practic": [3, 88, 89, 92, 93, 100, 101, 106, 108], "complet": [3, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 105, 108], "gist": 3, "cj_ish": 3, "guess": [3, 49, 101, 103], "8": [3, 5, 7, 8, 50, 51, 52, 58, 67, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 103, 104, 105, 106, 108, 109, 110], "parallel": [3, 46, 71, 81, 98], "again": [3, 62, 88, 99, 106], "simplifi": [3, 17, 99], "understand": [3, 9, 10, 39, 64, 71, 92, 97, 101, 102, 108, 109, 110], "100": [3, 4, 40, 44, 54, 55, 57, 72, 73, 88, 89, 91, 92, 93, 95, 97, 98, 99, 100, 101, 104, 105, 106, 110], "optim": [3, 40, 41, 44, 62, 88, 89, 92, 93, 95, 96, 97, 98, 101, 103, 104, 106, 108], "speed": [3, 46, 89, 98, 99, 108], "dtype": [3, 26, 28, 29, 34, 40, 44, 58, 59, 67, 83, 90, 97, 100, 105], "enumer": [3, 40, 44, 90, 91, 92, 93, 97, 110], "s_label": 3, "confident_bin": 3, "6": [3, 5, 10, 44, 51, 59, 83, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 103, 104, 105, 106, 108, 109, 110], "num_confident_bin": 3, "argmax": [3, 46, 73, 77, 80, 90, 97, 99, 101, 105, 106, 109], "elif": 3, "estimate_lat": 3, "py_method": [3, 49], "cnt": [3, 49], "1d": [3, 5, 13, 15, 19, 35, 43, 46, 51, 52, 54, 59, 60, 67, 76, 88, 90, 97], "eqn": [3, 49], "margin": [3, 46, 49, 51, 73], "marginal_p": [3, 49], "shorthand": [3, 13, 16], "proport": [3, 10, 39, 64, 101, 107], "poorli": [3, 49, 88, 97], "inv_noise_matrix": 3, "estimate_py_and_noise_matrices_from_prob": [3, 101], "variabl": [3, 7, 17, 30, 59, 75, 76, 90, 91, 95, 101, 104, 108], "exact": [3, 10, 49, 54, 88, 91, 92, 93, 95, 97, 100], "within": [3, 4, 5, 10, 14, 18, 35, 40, 41, 44, 45, 47, 65, 70, 79, 81, 83, 91, 92, 93, 99, 105, 109], "percent": 3, "often": [3, 39, 49, 64, 99, 101, 107, 109], "estimate_confident_joint_and_cv_pred_proba": 3, "mani": [3, 9, 10, 59, 60, 71, 88, 89, 90, 91, 93, 95, 96, 99, 100, 104, 105, 106, 108], "wai": [3, 5, 10, 54, 62, 85, 86, 88, 89, 90, 91, 92, 95, 96, 97, 99, 100, 101, 103, 104, 105, 107], "pro": 3, "con": 3, "pred_proba": [3, 107], "combin": [3, 39, 91, 93, 97, 98, 99, 100, 101, 107, 108], "becaus": [3, 10, 49, 55, 59, 70, 96, 97, 99, 100, 101, 103, 105, 107], "littl": [3, 43, 98, 105, 110], "uniform": [3, 73, 98, 99, 101], "20": [3, 7, 45, 84, 90, 93, 96, 97, 98, 99, 100, 101, 105, 108, 109, 110], "Such": [3, 93, 106], "bound": [3, 26, 28, 40, 44, 58, 67, 68, 70, 71, 105], "reason": [3, 10, 25, 40, 44, 55, 72], "comment": [3, 58, 97, 110], "end": [3, 5, 40, 44, 56, 71], "file": [3, 5, 15, 42, 43, 61, 71, 88, 90, 91, 95, 96, 98, 99, 105, 106, 109, 110], "estimate_py_noise_matrices_and_cv_pred_proba": [3, 101], "handl": [3, 5, 7, 10, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 43, 44, 54, 55, 56, 86, 88, 89, 91, 92, 93, 95, 96, 97, 98, 100, 101, 104, 106, 108, 109, 110], "five": [3, 68, 71, 101, 105], "estimate_cv_predicted_prob": [3, 101], "estimate_noise_matric": 3, "get_confident_threshold": [3, 42, 43], "amongst": [3, 10, 100, 105], "confident_threshold": [3, 10, 25, 26, 43, 72], "point": [4, 5, 7, 9, 10, 21, 29, 40, 44, 54, 56, 85, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103], "valuat": [4, 9, 21], "help": [4, 39, 40, 44, 71, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 106, 108, 109, 110], "u": [4, 88, 89, 90, 91, 93, 95, 97, 99, 101, 103, 104, 107, 108, 109, 110], "assess": [4, 10, 97, 100, 105], "contribut": [4, 10, 21, 97, 105], "data_shapley_knn": 4, "knn_graph": [4, 5, 10, 11, 13, 19, 21, 22, 29, 31, 34, 47, 53, 95, 97], "metric": [4, 5, 10, 21, 22, 24, 29, 31, 34, 47, 53, 54, 56, 57, 59, 62, 71, 72, 88, 89, 90, 93, 95, 96, 97, 100, 101, 108], "10": [4, 10, 21, 22, 26, 29, 31, 34, 40, 41, 54, 71, 72, 73, 84, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "shaplei": [4, 10, 21], "nearest": [4, 5, 10, 13, 19, 26, 29, 31, 53, 54, 55, 56, 57, 72, 92, 96, 97, 106], "neighbor": [4, 5, 10, 13, 19, 21, 26, 29, 31, 47, 54, 55, 56, 57, 72, 91, 92, 93, 95, 96, 97, 99, 106], "knn": [4, 10, 13, 16, 21, 29, 31, 34, 53, 54, 55, 56, 57, 72, 95, 106], "graph": [4, 5, 10, 13, 16, 19, 21, 29, 34, 53, 54], "calcul": [4, 10, 21, 29, 43, 51, 53, 54, 57, 63, 67, 68, 70, 71, 72, 75, 79, 93, 98, 100], "directli": [4, 5, 10, 13, 17, 19, 36, 37, 43, 56, 62, 63, 89, 92, 96, 97, 99, 100, 104, 105, 108], "lowest": [4, 10, 63, 71, 92, 93, 95, 97, 99, 100, 103, 104, 105, 109], "fall": [4, 10, 70, 79, 83, 101, 106], "flag": [4, 10, 25, 29, 46, 51, 64, 65, 68, 75, 85, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 105, 106, 108, 109], "approxim": [4, 10, 21, 43, 56, 72, 97, 103], "top": [4, 5, 10, 39, 43, 45, 46, 59, 65, 68, 71, 73, 80, 84, 85, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 104, 105, 106, 108, 110], "found": [4, 5, 7, 10, 13, 16, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 59, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 104, 106, 108, 110], "arxiv": [4, 21, 101], "ab": [4, 21, 101, 105], "1908": 4, "08619": 4, "1911": [4, 21], "07128": [4, 21], "embed": [4, 5, 10, 13, 19, 72, 85, 89, 90, 91, 92, 95, 96, 97, 100, 101, 104, 108], "represent": [4, 5, 10, 13, 19, 37, 40, 44, 52, 54, 65, 85, 89, 90, 91, 92, 93, 96, 99, 100, 101, 106], "suppli": [4, 104, 105, 108], "2d": [4, 5, 13, 19, 35, 43, 51, 52, 54, 58, 59, 63, 88, 90, 97, 104], "num_exampl": [4, 5, 13, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36, 39, 64, 90, 91, 92, 93, 95, 96, 100, 101], "num_featur": [4, 5, 13, 19, 40, 44, 62], "distanc": [4, 5, 10, 13, 19, 21, 29, 31, 34, 53, 54, 55, 56, 57, 70, 72, 95, 97, 106], "construct": [4, 5, 7, 10, 13, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 40, 44, 51, 53, 54, 56, 62, 97, 100], "nearestneighbor": [4, 5, 10, 21, 54, 56, 72, 95, 106], "cosin": [4, 10, 54, 55, 57, 72, 97, 106], "dim": [4, 72, 93, 109], "euclidean": [4, 5, 10, 54, 55, 57, 70, 72, 95], "dimension": [4, 29, 55, 59, 90, 101, 106], "scikit": [4, 44, 55, 56, 59, 72, 85, 88, 89, 90, 91, 92, 95, 96, 97, 99, 108], "fewer": [4, 10, 46, 59, 72, 97, 105], "stabl": [4, 14, 18, 24, 27, 32, 42, 47, 56, 59, 61, 72, 86, 90, 91, 92, 93, 95, 96, 100, 101], "exce": [4, 54, 93, 97], "transform": [4, 10, 35, 51, 54, 57, 59, 72, 73, 88, 89, 92, 93, 96, 97, 100, 106, 110], "rel": [4, 10, 39, 54, 63, 64, 72, 91, 92, 93, 95, 96, 100, 101, 106], "adjust": [4, 41, 46, 54, 67, 72, 73, 85, 97, 100, 101], "closer": [4, 10, 70, 97, 105], "highli": [4, 92, 93], "influenti": 4, "posit": [4, 5, 10, 40, 44, 57, 59, 71, 97, 98, 106], "convers": 4, "neg": [4, 10, 70, 71, 91, 92, 97, 98], "valueerror": [4, 5, 13, 15, 16, 37, 48, 51, 54, 57, 99], "neither": [4, 5, 10, 17, 55, 105], "nor": [4, 5, 10, 17], "larger": [4, 21, 55, 75, 77, 79, 93, 96, 98, 99], "55": [4, 58, 97, 98, 105, 108], "525": 4, "unifi": 5, "audit": [5, 9, 13, 15, 16, 19, 90, 93, 94, 95, 96, 97, 99, 100, 101, 104, 105, 108], "kind": [5, 6, 7, 10, 97, 98], "addit": [5, 7, 9, 12, 13, 16, 36, 38, 40, 44, 51, 54, 56, 60, 63, 71, 80, 81, 88, 89, 90, 91, 95, 96, 97, 100, 101, 103, 106, 107], "depend": [5, 7, 9, 12, 13, 15, 16, 38, 42, 46, 48, 59, 61, 65, 72, 75, 76, 85, 97, 107], "instal": [5, 7, 9, 12, 38, 40, 42, 43, 44, 46, 61, 62, 77, 79, 97], "pip": [5, 7, 9, 12, 38, 62, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "development": [5, 7, 9, 12, 38], "git": [5, 7, 9, 12, 38, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108], "github": [5, 7, 9, 12, 38, 40, 41, 59, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 100, 101, 103, 104, 105, 106, 108], "com": [5, 7, 9, 12, 38, 40, 41, 43, 48, 59, 72, 85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "egg": [5, 7, 9, 12, 38, 85, 98], "label_nam": [5, 7, 8, 10, 11, 15, 21, 34, 85, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 105, 108], "image_kei": [5, 10, 13, 93, 97], "interfac": [5, 9, 10, 56, 85, 88, 89, 92, 95, 96, 98, 99, 100, 101, 104, 106, 108], "librari": [5, 10, 44, 56, 68, 71, 72, 85, 89, 91, 96, 97, 98, 99], "goal": [5, 108], "track": [5, 7, 16, 17, 85, 91, 98, 99, 101], "intermedi": [5, 9, 92], "statist": [5, 10, 13, 16, 25, 29, 39, 63, 64, 71, 92, 95, 96, 97, 100, 101], "convert": [5, 10, 15, 37, 40, 44, 52, 57, 60, 63, 70, 79, 83, 86, 89, 90, 93, 96, 97, 98, 99, 100, 103, 104, 105], "hug": [5, 10, 15, 93], "face": [5, 10, 15, 19, 93, 98, 104], "kei": [5, 7, 10, 13, 15, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 44, 51, 63, 64, 70, 72, 91, 92, 93, 96, 99, 101, 103, 105], "string": [5, 10, 13, 15, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 37, 39, 40, 44, 55, 59, 63, 64, 76, 80, 83, 84, 89, 95, 96, 97, 99, 103, 104, 110], "dictionari": [5, 7, 10, 13, 15, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 40, 44, 50, 59, 63, 64, 67, 68, 70, 71, 91, 92, 95, 96, 101, 103, 104, 105], "path": [5, 15, 40, 43, 44, 71, 90, 91, 97, 99, 105], "local": [5, 7, 10, 15, 40, 41, 44, 90, 91, 92, 93, 98, 99, 100, 101, 103, 104, 106, 108, 110], "text": [5, 7, 10, 15, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 45, 51, 72, 81, 83, 84, 85, 87, 91, 92, 94, 98, 99, 100, 101, 102, 103, 106], "txt": [5, 15, 110], "csv": [5, 15, 88, 89, 95, 96, 100, 108], "json": [5, 15], "hub": [5, 15], "multiclass": [5, 15, 18, 51, 59, 63, 104], "regress": [5, 7, 10, 11, 13, 15, 17, 19, 24, 33, 35, 37, 89, 91, 92, 96, 102, 103, 106], "multilabel": [5, 10, 11, 15, 17, 18, 24, 28, 35, 37, 52, 104], "imag": [5, 9, 13, 39, 44, 68, 70, 71, 72, 77, 79, 80, 85, 91, 92, 94, 98, 99, 100, 102, 103, 104, 105, 107, 109], "field": [5, 10, 40, 44], "themselv": [5, 88, 89, 97, 108], "pil": [5, 93], "cleanvis": [5, 10, 13, 97], "level": [5, 10, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36, 39, 54, 58, 81, 83, 92, 93, 99, 102, 104, 109], "load_dataset": [5, 15, 93], "glue": 5, "sst2": 5, "properti": [5, 9, 13, 15, 16, 37, 40, 44, 97], "has_label": [5, 15], "class_nam": [5, 15, 23, 39, 45, 64, 71, 80, 84, 85, 98, 101, 105, 109, 110], "empti": [5, 15, 49, 63, 92, 97, 99, 104], "find_issu": [5, 6, 7, 8, 10, 11, 13, 17, 19, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 36, 85, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 108], "issue_typ": [5, 6, 7, 8, 10, 11, 13, 16, 17, 19, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 108], "sort": [5, 13, 19, 43, 46, 51, 63, 65, 68, 70, 71, 73, 79, 81, 83, 88, 89, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 104, 105, 108, 109, 110], "common": [5, 10, 13, 16, 19, 85, 92, 94, 97, 98, 99, 100, 101, 104, 105, 109], "real": [5, 13, 19, 85, 91, 92, 97, 99, 100, 101, 103, 108, 109], "world": [5, 13, 19, 85, 91, 92, 97, 99, 100, 101, 103, 108, 109], "interact": [5, 13, 19, 96, 99], "thereof": [5, 13, 19], "insight": [5, 13, 19, 71, 103], "best": [5, 9, 10, 13, 19, 50, 63, 73, 88, 89, 91, 92, 93, 95, 97, 99, 100, 103, 104, 106, 107, 108, 110], "properli": [5, 10, 43, 50, 54, 59, 60, 77, 90, 91, 92, 93, 95, 96, 99, 100, 101, 104, 106, 108, 109], "respect": [5, 40, 44, 68, 71, 90, 91, 92, 93, 95, 96, 100, 101, 104, 105], "lexicograph": [5, 50, 59, 90, 91, 92, 93, 95, 96, 100, 101, 104], "squar": [5, 59, 75, 98, 108], "csr": [5, 54, 97], "evenli": 5, "omit": [5, 70, 71, 93, 97, 105], "itself": [5, 35, 40, 44, 54, 97, 105], "three": [5, 10, 39, 63, 64, 75, 80, 88, 90, 91, 92, 95, 98, 101, 103, 107, 108, 109, 110], "indptr": [5, 97], "wise": 5, "start": [5, 7, 10, 37, 40, 41, 44, 51, 85, 104, 110], "th": [5, 10, 45, 50, 58, 59, 63, 65, 68, 70, 71, 72, 81, 83, 84, 96, 104, 105, 110], "ascend": [5, 39, 64, 93, 101], "segment": [5, 77, 79, 80, 102], "reflect": [5, 10, 54, 88, 89, 95, 96, 100, 103, 105, 106, 108], "maintain": [5, 62], "kneighbors_graph": [5, 21, 56, 95], "illustr": [5, 97], "todens": 5, "second": [5, 51, 59, 71, 73, 91, 95, 99, 101, 110], "duplic": [5, 9, 24, 25, 40, 44, 54, 85, 91, 97, 100, 101, 108], "explicit": 5, "precend": 5, "collect": [5, 10, 13, 16, 19, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 35, 63, 97, 99, 103, 110], "unspecifi": [5, 13, 19, 46, 65], "interest": [5, 13, 19, 25, 80, 84, 88, 89, 96, 97, 100, 101, 108, 109, 110], "constructor": [5, 10, 11, 13, 19, 26, 33, 54, 56], "issuemanag": [5, 9, 13, 16, 17, 19, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 36], "respons": [5, 13, 19, 25, 56, 75, 76, 97, 98, 108, 110], "random_st": [5, 88, 90, 91, 92, 93, 97, 100, 101, 104, 106], "lab": [5, 6, 8, 10, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 43, 85, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 108], "comprehens": [5, 85, 93, 97, 100, 104, 108], "nbr": 5, "n_neighbor": [5, 10, 21, 54, 56, 72, 97], "mode": [5, 12, 21, 40, 43, 44, 95, 106], "4x4": 5, "float64": [5, 29, 40, 44, 83], "compress": [5, 10, 54, 59, 77, 79, 97], "toarrai": [5, 54, 97], "NOT": [5, 43, 96], "23606798": 5, "41421356": [5, 54], "configur": [5, 19, 51, 92], "suppos": [5, 10, 68, 88, 89, 106, 108], "who": [5, 70, 88, 95, 97, 101, 110], "manag": [5, 8, 9, 10, 13, 16, 17, 18, 19, 20, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 62, 91, 99], "clean_learning_kwarg": [5, 10, 11, 26, 33, 99, 108], "labelissuemanag": [5, 10, 17, 24, 26], "prune_method": [5, 86], "prune_by_noise_r": [5, 46, 65, 101], "report": [5, 7, 10, 12, 13, 18, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 64, 84, 85, 90, 91, 92, 95, 96, 97, 99, 100, 101, 104, 108, 110], "include_descript": [5, 13, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 36], "show_summary_scor": [5, 13, 36, 97, 100], "show_all_issu": [5, 13, 36, 97, 100], "summari": [5, 7, 13, 16, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 39, 45, 61, 62, 64, 69, 78, 79, 81, 82, 83, 86, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 105, 108, 109, 110], "show": [5, 7, 29, 40, 44, 50, 59, 71, 80, 84, 88, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 106, 108, 109, 110], "suffer": [5, 10, 13, 16, 25, 65, 73, 84, 97, 110], "onc": [5, 10, 25, 39, 40, 44, 88, 91, 99, 100, 101, 104, 105], "familiar": [5, 97], "overal": [5, 7, 10, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 45, 51, 63, 64, 67, 70, 71, 75, 79, 80, 81, 83, 85, 86, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 103, 105, 110], "sever": [5, 7, 10, 13, 15, 16, 25, 40, 43, 44, 46, 67, 70, 72, 73, 79, 83, 85, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 105, 106, 110], "compar": [5, 63, 72, 83, 91, 92, 95, 97, 100, 101, 105], "issue_summari": [5, 7, 10, 13, 16, 97], "With": [5, 9, 10, 43, 89, 96, 99, 101, 103, 108, 109, 110], "usag": [5, 43, 62], "usual": [5, 15, 35, 36, 93, 103, 108], "ti": [5, 63], "exhibit": [5, 7, 10, 13, 16, 80, 90, 91, 92, 93, 95, 96, 100, 101, 105], "ie": [5, 75], "likelihood": [5, 10, 43, 45, 46, 65, 70, 72, 73, 77, 81, 97], "wherea": [5, 10, 59, 65, 88, 89, 97, 107], "outlier": [5, 9, 11, 17, 24, 25, 34, 47, 54, 73, 85, 91, 92, 97, 100, 101, 102, 108], "fundament": [5, 10], "incompar": 5, "quantiti": [5, 101, 108], "global": [5, 7, 10, 25, 40, 44, 98], "non_iid": [5, 10, 11, 17, 29, 92, 93, 95, 96, 97, 100, 101], "hypothesi": [5, 97], "iid": [5, 7, 9, 29, 85, 95, 100, 101], "never": [5, 90, 100, 101, 104, 106, 107], "someth": [5, 7, 10, 40, 44, 73, 105], "123": [5, 91, 92], "456": [5, 88, 89, 90], "nearest_neighbor": 5, "7": [5, 10, 51, 52, 62, 81, 83, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 103, 104, 105, 106, 108, 109, 110], "9": [5, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 45, 51, 52, 67, 81, 83, 88, 89, 90, 91, 92, 95, 96, 97, 98, 101, 103, 104, 105, 106, 108, 109, 110], "distance_to_nearest_neighbor": [5, 11, 91, 92, 93, 95, 96, 100, 101], "789": 5, "get_issu": [5, 10, 13, 16, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 104, 108], "issue_nam": [5, 6, 7, 10, 13, 16, 17, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 90, 91, 92, 93, 95, 96, 97, 100, 101], "focu": [5, 10, 13, 16, 96, 97, 100, 109, 110], "full": [5, 10, 13, 16, 43, 62, 71, 93, 100, 110], "summar": [5, 13, 16, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 39, 64, 80, 84, 85, 109], "specific_issu": [5, 13, 16], "lie": [5, 10, 72, 73, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101], "get_issue_summari": [5, 10, 13, 16, 92, 97], "get_info": [5, 10, 13, 16, 92, 96, 97, 98], "yet": [5, 20, 30, 62, 98, 100, 103], "list_possible_issue_typ": [5, 17, 18], "regist": [5, 7, 17, 18, 20, 30, 40, 44, 91], "rtype": [5, 17, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44], "registri": [5, 17, 18], "list_default_issue_typ": [5, 17, 18], "folder": [5, 90, 91, 93], "load": [5, 15, 43, 71, 93, 98, 99, 100, 101, 105, 106, 109, 110], "futur": [5, 10, 25, 40, 44, 63, 85, 91, 96], "overwrit": [5, 91], "separ": [5, 39, 51, 67, 91, 92, 93, 97, 99, 100, 105, 107], "static": 5, "rememb": [5, 96, 99, 100, 101], "part": [5, 10, 40, 44, 46, 68, 70, 71, 90, 91, 97, 98, 100, 109, 110], "ident": [5, 10, 25, 59, 96, 97], "datalab": [6, 8, 11, 13, 15, 16, 17, 19, 20, 21, 22, 23, 24, 25, 26, 28, 29, 30, 31, 33, 34, 35, 36, 37, 38, 85, 88, 89, 98, 100, 103, 108], "walk": [7, 100], "alongsid": [7, 13, 40, 44, 91, 99], "pre": [7, 8, 10, 40, 44, 85, 91, 92, 108], "runtim": [7, 40, 43, 44, 75, 77, 79, 90, 93, 99, 100], "issue_manager_factori": [7, 17, 91], "myissuemanag": [7, 17], "myissuemanagerforregress": 7, "decor": [7, 17], "ll": [7, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 107, 108, 110], "thing": [7, 44, 89, 97, 101, 108], "next": [7, 63, 85, 88, 89, 90, 95, 96, 97, 99, 103, 105, 108, 110], "dummi": 7, "randint": [7, 34, 51, 91, 92, 97], "mark": [7, 10, 86, 105, 106, 108], "regard": [7, 92, 100, 101], "rand": [7, 51, 54, 91, 92, 97], "is_": [7, 10, 91], "_issu": [7, 10, 91], "issue_score_kei": [7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 91], "whole": [7, 10, 29, 40, 44, 92, 97], "make_summari": [7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 91], "popul": [7, 96, 100], "verbosity_level": [7, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], "std": [7, 105], "raw_scor": 7, "bit": 7, "involv": [7, 43, 80, 84, 97, 99, 104], "intermediate_arg": 7, "min": [7, 51, 70, 83, 91, 99, 106], "sin_filt": 7, "sin": 7, "arang": [7, 97], "kernel": [7, 97], "affect": [7, 10, 40, 44, 55, 77, 83, 96, 97, 99], "easili": [7, 10, 49, 86, 88, 89, 90, 92, 95, 96, 100, 101, 103, 104, 106, 107, 108, 109], "hard": [7, 44, 85, 98, 106], "sai": [7, 10, 40, 44, 97, 104, 109], "anoth": [7, 10, 25, 39, 43, 55, 58, 70, 73, 89, 95, 96, 97, 99, 101, 103, 106], "try": [7, 9, 10, 43, 46, 62, 63, 77, 79, 85, 88, 89, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 106, 107, 108, 109], "won": [7, 40, 44, 91, 92, 99, 104], "issue_manag": [7, 10, 12, 13, 16, 18, 21, 22, 23, 26, 28, 29, 30, 31, 33, 34, 91], "instanti": [7, 19, 43, 62, 72, 89, 90, 92, 95], "477762": 7, "286455": 7, "term": [7, 10, 49, 59, 71, 90, 91, 92, 93, 95, 96, 100, 101], "4778": 7, "is_basic_issu": 7, "basic_scor": 7, "13": [7, 22, 31, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 105, 106, 108, 109, 110], "003042": 7, "058117": 7, "11": [7, 10, 62, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "121908": 7, "15": [7, 57, 62, 75, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "169312": 7, "17": [7, 89, 90, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "229044": 7, "2865": 7, "is_intermediate_issu": 7, "intermediate_scor": 7, "000000": [7, 91, 92, 97, 98, 100, 101], "007059": 7, "009967": 7, "010995": 7, "087332": 7, "016296": 7, "03947": 7, "019459": 7, "794251": 7, "underperform": [8, 9, 34, 85, 100], "group": [8, 9, 29, 34, 85, 98, 100, 105, 110], "dbscan": [8, 10, 34], "hdbscan": 8, "etc": [8, 10, 25, 35, 40, 44, 49, 62, 63, 81, 85, 91, 92, 95, 96, 97, 99, 100, 101, 104, 108], "sensit": [8, 10, 57, 97, 100], "ep": [8, 34, 71], "radiu": 8, "min_sampl": [8, 34], "kmean": [8, 97], "your_data": 8, "get_pred_prob": 8, "n_cluster": [8, 34, 97], "cluster_id": [8, 10, 11, 34, 97], "labels_": 8, "underperforming_group": [8, 10, 11, 17, 24, 92, 93, 95, 96, 97, 100, 101], "search": [9, 10, 23, 29, 30, 47, 53, 54, 55, 58, 75, 97, 99, 100, 107], "nondefault": 9, "Near": [9, 99], "imbal": [9, 24, 67, 72, 73, 92], "spuriou": [9, 13, 93], "correl": [9, 13, 93], "null": [9, 11, 17, 24, 92, 93, 96, 100, 101], "togeth": [9, 10, 49, 89, 91, 92, 93, 95, 96, 100, 101, 108, 110], "built": [9, 51, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "own": [9, 40, 42, 44, 56, 61, 67, 68, 71, 77, 81, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 103, 104, 108, 109, 110], "prerequisit": 9, "basic": [9, 44, 62, 97, 100, 106], "fulli": [9, 10, 40, 44, 62, 99], "platform": [9, 10, 85, 88, 89, 92, 93, 95, 96, 98, 99, 101, 104, 106, 107, 108], "write": [9, 10], "code": [9, 10, 40, 44, 49, 59, 62, 85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 98, 99, 103, 104, 105, 106, 108, 109, 110], "being": [9, 10, 13, 16, 39, 40, 44, 46, 51, 58, 59, 73, 88, 95, 99, 100, 101, 108, 109], "100x": [9, 10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "faster": [9, 10, 43, 72, 75, 77, 79, 85, 88, 89, 92, 95, 96, 98, 99, 101, 104, 106, 108], "intellig": [9, 10, 100], "quickli": [9, 10, 41, 88, 90, 93, 95, 96, 99, 100, 104, 106, 107, 109, 110], "fix": [9, 10, 63, 88, 89, 92, 95, 96, 97, 98, 100, 101, 104, 106, 107, 108], "scientist": [9, 10], "million": [9, 10, 110], "thank": [9, 10], "ai": [9, 10, 85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 102, 103, 104, 106, 108, 110], "suggest": [9, 10, 39, 63, 64, 70, 89, 93, 96, 97, 99, 108], "power": [9, 10, 93, 98, 101, 110], "automl": [9, 10, 85, 88, 89, 92, 95, 96, 98, 99, 101, 104, 106, 107, 108], "system": [9, 10, 90, 93, 109], "foundat": [9, 10, 85, 88, 89, 92, 95, 96, 97, 98, 101, 104, 106, 107, 108], "improv": [9, 10, 63, 88, 89, 92, 93, 98, 99, 101, 102, 108, 109], "click": [9, 10, 90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "tune": [9, 10, 89, 90, 96, 98, 100, 106], "serv": [9, 10, 16, 19, 103], "auto": [9, 10, 88, 89, 92, 98, 99, 100, 108], "free": [9, 10, 85, 88, 89, 90, 92, 93, 95, 96, 98, 99, 100, 101, 104, 106, 107, 108], "page": [10, 92, 99, 100, 101], "variou": [10, 16, 33, 42, 60, 61, 85, 88, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105], "why": [10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "matter": [10, 39, 64], "didn": [10, 97, 100], "plu": [10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "ye": [10, 11], "near_dupl": [10, 11, 17, 22, 91, 92, 93, 95, 96, 97, 99, 100, 101], "class_imbal": [10, 11, 17, 23, 92, 93, 95, 96, 97, 100, 101], "data_valu": [10, 11, 17, 24, 97], "No": [10, 11, 88, 89, 96, 97, 99], "reinterpret": [10, 11], "your_regression_model": [10, 11], "_score": 10, "badli": [10, 70, 88, 89, 110], "issue_scor": 10, "atyp": [10, 72, 91, 92, 93, 95, 96, 100, 101, 106], "datapoint": [10, 34, 46, 51, 59, 73, 76, 85, 88, 89, 90, 91, 92, 95, 96, 99, 100, 107, 108], "is_issu": [10, 25], "primarili": 10, "former": [10, 40, 44], "investig": [10, 90, 97], "expertis": [10, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "interpret": [10, 98, 99, 101, 104, 108], "annot": [10, 39, 50, 63, 64, 65, 67, 68, 70, 71, 80, 83, 84, 85, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 102, 105, 109], "dissimilar": [10, 95, 96], "preced": 10, "incorrect": [10, 70, 73, 76, 88, 90, 91, 92, 93, 95, 96, 97, 100, 101, 105, 108], "due": [10, 43, 46, 73, 77, 79, 90, 91, 92, 93, 95, 96, 97, 100, 101, 108], "appear": [10, 39, 50, 64, 65, 68, 76, 92, 93, 95, 96, 97, 100, 108, 109], "now": [10, 13, 43, 86, 88, 89, 90, 92, 97, 99, 100, 103, 105, 106, 108, 110], "token": [10, 45, 58, 79, 80, 81, 82, 83, 84, 99, 101, 102], "hamper": [10, 93, 98], "analyt": [10, 85, 97, 99, 103], "lead": [10, 70, 73, 93, 97, 100, 105], "draw": [10, 91, 92], "conclus": [10, 96], "let": [10, 40, 44, 72, 73, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 103, 104, 105, 106, 108, 109, 110], "sort_valu": [10, 90, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 108], "head": [10, 88, 89, 90, 92, 93, 95, 96, 97, 98, 100, 101, 103, 108], "97": [10, 88, 98, 99, 100, 101, 105, 108, 110], "064045": 10, "58": [10, 88, 92, 97, 98, 101, 105], "680894": 10, "41": [10, 97, 98, 100, 105, 108], "746043": 10, "794894": 10, "98": [10, 98, 99, 100, 108], "802911": 10, "give": [10, 51, 73, 101, 103, 109], "li": [10, 72], "especi": [10, 88, 89, 93, 97, 99, 108], "veri": [10, 39, 64, 68, 70, 89, 91, 92, 93, 95, 96, 99, 100, 101, 103, 106, 108], "rare": [10, 46, 71, 91, 92, 93, 95, 96, 99, 100, 101], "anomal": [10, 73, 91, 92, 93, 95, 96, 100, 101], "articl": [10, 43, 99], "blog": 10, "unexpect": [10, 40, 44, 96], "consequ": 10, "inspect": [10, 89, 90, 92, 93, 100, 101, 105, 108], "011562": 10, "62": [10, 97, 100, 101, 105, 108], "019657": 10, "22": [10, 90, 91, 93, 97, 98, 100, 101, 104, 105, 110], "035243": 10, "040907": 10, "42": [10, 51, 96, 97, 98, 105, 110], "056865": 10, "smaller": [10, 72, 104, 105], "extrem": [10, 13, 91, 92, 93, 95, 96, 97, 99, 100, 101], "record": [10, 40, 44, 90, 95, 108], "abbrevi": 10, "misspel": 10, "typo": [10, 84], "resolut": 10, "video": [10, 98], "audio": [10, 91, 92, 94, 99], "minor": [10, 58], "variat": 10, "translat": [10, 100], "d": [10, 57, 88, 95, 96, 97, 99, 100, 101, 104, 108, 110], "constant": [10, 34, 75], "median": [10, 33, 57], "question": [10, 25, 85, 101], "nearli": [10, 25, 92, 93, 95, 96], "awar": [10, 86, 101], "presenc": [10, 54, 56, 101], "36": [10, 97, 98, 100, 110], "066009": 10, "80": [10, 41, 88, 95, 100, 104, 108], "003906": 10, "093245": 10, "005599": 10, "27": [10, 95, 97, 98, 100, 101, 105, 110], "156720": 10, "009751": 10, "72": [10, 97, 98, 100, 101, 104, 108], "signific": [10, 88, 89, 92, 95, 96, 98, 100, 101, 104, 106, 108], "violat": [10, 85, 95, 96, 97, 100, 101], "assumpt": [10, 95, 96, 97, 100, 101], "changepoint": [10, 95, 96, 100, 101], "shift": [10, 54, 56, 95, 96, 100, 101], "drift": [10, 92, 95, 97, 100, 101], "autocorrel": [10, 95, 96, 100, 101], "almost": [10, 95, 96, 100, 101], "adjac": [10, 54, 95, 96, 100, 101], "tend": [10, 39, 49, 95, 96, 100, 101, 109, 110], "sequenti": [10, 40, 44, 62, 93], "pai": [10, 96, 97], "attent": [10, 97], "realli": [10, 89, 96, 100, 103, 109], "mere": 10, "highlight": [10, 80, 84, 91, 92, 95, 97, 109], "necessarili": [10, 63, 71, 96, 100, 101], "wrong": [10, 63, 68, 70, 86, 89, 91, 92, 96, 99, 100, 101, 105], "gap": 10, "b": [10, 21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 39, 58, 59, 83, 88, 95, 96, 97, 98, 99, 100, 101, 107, 110], "x1": [10, 68, 71, 105], "x2": [10, 68, 71, 105], "10th": 10, "100th": 10, "90": [10, 83, 88, 95, 100, 101, 107, 108], "similarli": [10, 40, 44, 91, 93, 95, 99, 100, 105], "associ": [10, 15, 19, 35, 37, 40, 44, 71, 103], "blogpost": 10, "proper": [10, 59, 63, 68, 71, 88, 93, 96, 99, 103, 105], "scenario": [10, 54, 56, 73, 91, 92], "underli": [10, 45, 56, 72, 81, 83, 110], "stem": [10, 72, 106], "evolv": 10, "influenc": 10, "act": [10, 70, 91], "accordingli": [10, 35, 54], "emploi": [10, 104, 106], "partit": [10, 107], "ahead": 10, "good": [10, 40, 44, 57, 62, 64, 70, 73, 77, 79, 80, 85, 93, 97, 100], "problem": [10, 35, 43, 51, 80, 85, 91, 92, 93, 96, 97, 99], "deploy": [10, 88, 89, 101, 108], "overlook": [10, 70, 105], "fact": 10, "thu": [10, 39, 44, 64, 88, 90, 95, 96, 100, 101, 107, 110], "diagnos": [10, 92, 99], "24": [10, 90, 97, 98, 100, 101, 103, 105, 108], "681458": 10, "37": [10, 91, 97, 98, 100], "804582": 10, "64": [10, 44, 88, 93, 95, 97, 101, 105], "810646": 10, "815691": 10, "78": [10, 88, 95, 98, 100, 101, 105, 108], "834293": 10, "Be": [10, 44], "cautiou": 10, "behavior": [10, 19, 39, 40, 44, 71, 99], "rarest": [10, 92, 100], "q": [10, 97, 105], "subpar": 10, "special": [10, 54, 58], "techniqu": [10, 105], "smote": 10, "asymmetr": [10, 39], "28": [10, 93, 96, 97, 98, 100, 101, 103, 110], "75": [10, 51, 91, 92, 97, 98, 100, 103, 104, 105, 108, 110], "33": [10, 40, 44, 97, 98, 100, 105], "68": [10, 88, 98, 100, 101, 105], "excess": [10, 93], "dark": [10, 97, 109], "bright": [10, 110], "blurri": [10, 93, 97], "lack": [10, 62, 97, 100], "unusu": [10, 105, 106], "discuss": [10, 99], "earlier": [10, 89, 110], "unintend": [10, 95, 96, 97], "relationship": [10, 39], "irrelev": 10, "exploit": 10, "fail": [10, 15], "unseen": 10, "hold": [10, 15], "aris": 10, "captur": [10, 39, 90, 105, 106, 109], "environment": 10, "preprocess": [10, 88, 89, 92, 95, 97, 106, 108], "systemat": [10, 80, 84, 103], "photograph": 10, "uncorrelated": [10, 97], "strongli": [10, 96, 97], "minu": [10, 73], "sole": [10, 75, 88, 91, 100, 103, 106], "review": [10, 88, 89, 92, 95, 96, 98, 99, 100, 101, 105, 108, 109, 110], "latch": 10, "onto": 10, "troublesom": 10, "spurious_correl": [10, 97], "correlations_df": [10, 97], "blurry_scor": [10, 97], "559": [10, 100], "dark_scor": [10, 93, 97], "808": 10, "light_scor": [10, 97], "723": [10, 95, 100], "odd_size_scor": [10, 97], "957": 10, "odd_aspect_ratio_scor": [10, 97], "835": 10, "grayscale_scor": [10, 97], "003": 10, "spurious": 10, "low_information_scor": [10, 93, 97], "688": [10, 100, 108], "categor": [10, 72, 87, 88, 91, 92, 94, 99, 100, 108], "characterist": [10, 39, 97], "grayscal": [10, 93, 97], "cluster": [10, 21, 34, 100], "slice": [10, 100], "poor": [10, 97, 100], "subpopul": [10, 100], "faq": [10, 85, 92, 93, 95, 96, 102], "get_self_confidence_for_each_label": [10, 51, 73], "r": [10, 43, 75, 91, 92, 97, 108, 109], "tabular": [10, 85, 87, 91, 92, 94, 97, 99, 100, 103], "encod": [10, 52, 71, 77, 80, 88, 89, 95, 96, 99, 100, 108, 109], "71": [10, 97, 98, 100, 101, 105, 108], "70": [10, 83, 95, 97, 100], "69": [10, 100, 101, 108], "subgroup": [10, 97], "wors": [10, 97, 103], "ratio": [10, 97], "miss": [10, 30, 40, 44, 59, 68, 70, 99, 100, 105, 108], "pattern": [10, 97], "isn": [10, 20, 30], "scalabl": 10, "sacrific": 10, "One": [10, 59, 72, 99], "quantif": 10, "39": [10, 89, 90, 91, 93, 96, 97, 98, 99, 100, 105, 108, 109, 110], "32": [10, 90, 91, 97, 98, 100, 103, 105], "valuabl": [10, 21, 97], "exert": [10, 92], "possible_issue_typ": 10, "label_kwarg": 10, "outlier_kwarg": 10, "near_duplicate_kwarg": 10, "non_iid_kwarg": 10, "class_imbalance_kwarg": 10, "underperforming_group_kwarg": 10, "null_kwarg": 10, "data_valuation_kwarg": 10, "health_summary_paramet": [10, 24, 26, 33], "health_summari": [10, 26, 39, 85, 98], "health_summary_kwarg": 10, "tandem": [10, 98], "view": [10, 40, 44, 45, 46, 79, 81, 83, 85, 88, 89, 90, 91, 92, 95, 96, 98, 100, 101, 103, 104, 105, 106, 107, 108, 110], "ood_kwarg": 10, "outofdistribut": [10, 31, 72, 106], "outsid": [10, 99, 104], "outlierissuemanag": [10, 17, 24, 31], "nearduplicateissuemanag": [10, 17, 22, 24], "noniidissuemanag": [10, 17, 24, 29], "num_permut": [10, 29], "permut": [10, 29], "significance_threshold": [10, 29], "signic": 10, "noniid": [10, 24], "classimbalanceissuemanag": [10, 17, 23, 24], "underperforminggroupissuemanag": [10, 17, 24, 34], "determinin": 10, "neighbour": 10, "min_cluster_sampl": [10, 34], "filter_cluster_id": [10, 24, 34], "clustering_kwarg": [10, 34], "nullissuemanag": [10, 17, 24, 30], "datavaluationissuemanag": [10, 17, 21, 24], "codeblock": 10, "demonstr": [10, 43, 54, 91, 92, 93, 96, 97, 98, 99, 100, 101, 103, 104, 105, 107, 108, 109], "howev": [10, 40, 44, 54, 59, 88, 89, 90, 93, 95, 96, 97, 100, 103, 107, 109], "mandatori": 10, "image_issue_types_kwarg": 10, "vice": [10, 64], "versa": [10, 64], "light": [10, 93, 97, 98, 105, 109], "29": [10, 93, 97, 98, 100, 103, 104, 105, 109, 110], "low_inform": [10, 93, 97], "odd_aspect_ratio": [10, 93, 97], "35": [10, 91, 97, 98, 100, 103, 104, 105], "odd_siz": [10, 93, 97], "doc": [10, 40, 44, 72, 85, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 106, 108, 110], "spurious_correlations_kwarg": 10, "enough": [10, 43, 59, 97, 99], "label_scor": [11, 26, 28, 33, 90, 91, 92, 93, 95, 96, 97, 100, 101, 104, 108], "is_outlier_issu": [11, 91, 92, 93, 95, 96, 97, 100, 101], "outlier_scor": [11, 31, 91, 92, 93, 95, 96, 97, 100, 101, 106], "is_near_duplicate_issu": [11, 91, 92, 93, 95, 96, 97, 99, 100, 101], "near_duplicate_scor": [11, 22, 91, 92, 93, 95, 96, 97, 99, 100, 101], "near_duplicate_set": [11, 22, 24, 91, 92, 93, 95, 96, 99, 100, 101], "is_non_iid_issu": [11, 92, 95, 96, 97, 100, 101], "non_iid_scor": [11, 29, 92, 95, 96, 97, 100, 101], "is_class_imbalance_issu": [11, 92, 97, 100], "class_imbalance_scor": [11, 23, 92, 97, 100], "is_underperforming_group_issu": [11, 92, 97, 100], "underperforming_group_scor": [11, 34, 92, 97, 100], "is_null_issu": [11, 92, 97, 100], "null_scor": [11, 30, 92, 97, 100], "is_data_valuation_issu": [11, 97], "data_valuation_scor": [11, 21, 97], "studio": [12, 85, 88, 89, 92, 93, 95, 96, 98, 99, 100, 101, 104, 106, 107, 108], "data_issu": [12, 13, 18, 19, 36], "issue_find": [12, 18], "factori": [12, 18, 19], "model_output": [12, 18], "incorpor": [13, 86, 101], "vision": [13, 93], "create_imagelab": [13, 14], "huggingfac": [13, 90, 91, 92, 93, 99], "imagelabdataissuesadapt": [13, 14], "strategi": [13, 16, 51, 97, 99], "dataissu": [13, 16, 18, 19, 36], "_infostrategi": [13, 16], "basi": [13, 16], "filter_based_on_max_preval": 13, "max_num": 13, "collect_issues_from_imagelab": [13, 16], "collect_issues_from_issue_manag": [13, 16], "collect_statist": [13, 16], "reus": [13, 16, 25], "avoid": [13, 16, 40, 43, 44, 46, 54, 59, 65, 68, 71, 75, 77, 79, 91, 92, 99, 100], "recomput": [13, 16, 89], "weighted_knn_graph": [13, 16], "issue_manager_that_computes_knn_graph": [13, 16], "set_health_scor": [13, 16], "health": [13, 16, 26, 39, 64, 85], "correlationvisu": [13, 14], "visual": [13, 68, 69, 71, 88, 91, 92, 93, 108, 110], "title_info": 13, "ncol": [13, 93, 106], "cell_siz": 13, "correlationreport": [13, 14], "anyth": [13, 101], "imagelabreporteradapt": [13, 14], "get_report": [13, 36], "report_str": [13, 21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 36], "imagelabissuefinderadapt": [13, 14], "issuefind": [13, 18, 19, 36], "get_available_issue_typ": [13, 19], "handle_spurious_correl": [13, 14], "imagelab_issu": 13, "_": [13, 22, 23, 25, 26, 28, 29, 30, 33, 34, 51, 58, 59, 88, 90, 91, 93, 97, 98, 101, 104], "imagelab": [14, 16, 18], "except": [15, 40, 44, 62, 73, 91, 92, 93, 100, 103], "dataformaterror": [15, 18], "add_not": 15, "with_traceback": 15, "tb": 15, "__traceback__": 15, "datasetdicterror": [15, 18], "datasetdict": 15, "datasetloaderror": [15, 18], "dataset_typ": 15, "sublist": 15, "map_to_int": 15, "abc": [15, 25, 35], "is_avail": [15, 93], "central": [16, 110], "repositori": 16, "get_data_statist": [16, 18], "concret": 17, "subclass": [17, 40, 44, 72, 91], "regressionlabelissuemanag": [17, 24, 32, 33], "multilabelissuemanag": [17, 24, 27, 28], "from_str": [17, 37, 47, 51], "my_issu": 17, "logic": [17, 37, 43, 46, 77, 79, 100], "modeloutput": [18, 35], "multiclasspredprob": [18, 35], "regressionpredict": [18, 35], "multilabelpredprob": [18, 35], "instati": 19, "public": [19, 97, 100, 101, 105, 109, 110], "creation": [19, 44, 97], "execut": [19, 40, 44, 91, 99, 105], "coordin": [19, 68, 70, 71, 105, 110], "At": [19, 71, 99], "direct": [20, 30, 40, 44, 56, 62], "vstack": [21, 59, 93, 98, 99, 101, 103, 104], "25": [21, 29, 40, 51, 57, 92, 93, 97, 98, 100, 101, 103, 104, 105, 110], "classvar": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34], "short": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 58, 59], "item": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34, 40, 44, 59, 91, 92, 93, 99, 101, 103, 104], "some_info_kei": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34], "additional_info_kei": [21, 22, 23, 25, 26, 28, 29, 30, 31, 33, 34], "default_threshold": [21, 24, 31], "collect_info": [21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], "info_to_omit": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "compos": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34, 40, 44, 89, 96, 106], "is_x_issu": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "x_score": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "val_a": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "val_b1": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "val_b2": [21, 22, 23, 25, 26, 28, 29, 31, 33, 34], "occurr": [22, 23, 25, 29, 30, 31, 34, 58], "median_nn_dist": 22, "bleed": [24, 27, 32, 42], "edg": [24, 27, 32, 42, 70, 85, 88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108, 110], "sharp": [24, 27, 32, 42], "get_health_summari": [24, 26], "ood": [24, 31, 72, 73, 106], "simplified_kolmogorov_smirnov_test": [24, 29], "outlier_cluster_label": [24, 34], "no_underperforming_cluster_id": [24, 34], "perform_clust": [24, 34], "get_underperforming_clust": [24, 34], "find_issues_with_predict": [24, 32, 33], "find_issues_with_featur": [24, 32, 33], "believ": [25, 109], "priori": [25, 101], "abstract": [25, 35], "applic": [26, 63, 97, 99, 101, 103, 110], "typevar": [26, 28, 40, 44, 58, 67, 70, 71], "scalartyp": [26, 28], "covari": [26, 28, 75, 108], "summary_dict": 26, "neighbor_histogram": 29, "non_neighbor_histogram": 29, "kolmogorov": 29, "smirnov": 29, "largest": [29, 43, 51, 54, 73, 77, 79, 105, 109], "empir": [29, 50, 63], "cumul": 29, "ecdf": 29, "histogram": [29, 95, 97, 108], "absolut": [29, 33], "trial": 29, "null_track": 30, "extend": [30, 52, 62, 93, 97, 100, 105, 106, 110], "superclass": 30, "arbitrari": [30, 39, 79, 83, 91, 106, 108], "prompt": 30, "address": [30, 89, 91, 92, 96, 99], "enabl": [30, 44, 56, 100], "scaling_factor": [31, 57], "37037": 31, "q3_avg_dist": 31, "iqr_avg_dist": 31, "median_outlier_scor": 31, "issue_threshold": 31, "multipli": [33, 57], "deleg": 33, "confus": [34, 35, 39, 40, 44, 46, 59, 71, 89, 110], "50": [34, 44, 97, 99, 100, 101, 103, 105, 106, 108], "keepdim": [34, 99], "signifi": 34, "absenc": 34, "int64": [34, 90, 100, 103], "npt": 34, "int_": 34, "id": [34, 63, 91, 93, 97, 99, 103], "unique_cluster_id": 34, "exclud": [34, 36, 45, 80, 84, 91, 110], "worst": [34, 51, 103], "performed_clust": 34, "worst_cluster_id": 34, "convent": [35, 37], "subject": [35, 37, 100], "meant": [35, 37], "Not": [35, 56], "mainli": [35, 106, 110], "content": [35, 72, 90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "fetch": [35, 43, 90, 92, 97, 99], "datset": 36, "enum": [37, 51], "qualnam": [37, 51], "boundari": [37, 51, 91, 92], "continu": [37, 62, 88, 89, 93, 96, 99, 103, 105, 108, 110], "binari": [37, 51, 59, 65, 67, 101, 110], "simultan": [37, 108], "task_str": 37, "is_classif": 37, "__contains__": [37, 47, 51], "member": [37, 40, 44, 51, 91], "typeerror": [37, 51], "12": [37, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 108, 109, 110], "__getitem__": [37, 47, 51], "match": [37, 39, 40, 44, 46, 51, 63, 64, 73, 91, 92, 93, 98, 105, 107, 109], "__iter__": [37, 47, 51], "__len__": [37, 47, 51], "alias": [37, 51], "is_regress": 37, "is_multilabel": 37, "overview": [39, 54, 88, 89, 90, 92, 93, 95, 96, 103, 105, 106, 108, 110], "modifi": [39, 40, 43, 44, 54, 56, 59, 99, 100, 101], "rank_classes_by_label_qu": [39, 92], "merg": [39, 54, 58, 85, 98, 99, 100, 110], "find_overlapping_class": [39, 99, 101], "problemat": [39, 64, 80, 84, 90, 105, 110], "unnorm": [39, 64, 101], "abov": [39, 40, 43, 44, 56, 59, 63, 70, 71, 73, 79, 83, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 107, 108, 109, 110], "model_select": [39, 51, 88, 89, 90, 91, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 106, 108], "cross_val_predict": [39, 44, 88, 89, 90, 91, 92, 95, 96, 97, 100, 101, 103, 107, 108], "get_data_labels_from_dataset": 39, "yourfavoritemodel": [39, 101], "cv": [39, 51, 88, 90, 91, 92, 95, 97, 100, 101, 103], "df": [39, 59, 84, 90, 97, 99], "overall_label_qu": [39, 64], "col": 39, "prob": [39, 58, 101, 107], "divid": [39, 64, 73], "label_nois": [39, 64], "human": [39, 98, 109, 110], "clearli": [39, 73, 93, 105, 109], "num": [39, 64, 98, 101], "overlap": [39, 85, 97, 98, 99, 101], "ontolog": 39, "publish": [39, 110], "therefor": [39, 73, 97, 100], "vehicl": [39, 98], "truck": [39, 97, 98, 106, 109], "intuit": [39, 64], "car": [39, 98, 105, 109], "frequent": [39, 63, 97, 99, 100, 108], "l": [39, 40, 44, 68, 70, 71], "class1": 39, "class2": 39, "dog": [39, 59, 64, 66, 80, 98, 99, 106, 107, 110], "cat": [39, 59, 64, 66, 98, 99, 106, 107], "co": [39, 40, 41], "noisy_label": [39, 91, 92, 104], "overlapping_class": 39, "descend": [39, 40, 44, 51, 64, 71], "overall_label_health_scor": [39, 64, 101], "half": [39, 40, 42, 44, 64, 98, 110], "health_scor": [39, 64], "classes_by_label_qu": [39, 92], "cnn": [40, 42, 44, 93], "cifar": [40, 41, 97, 98, 106], "teach": [40, 41], "bhanml": 40, "blob": [40, 97], "master": [40, 88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 104, 105, 106, 108], "call_bn": [40, 42], "bn": 40, "input_channel": 40, "n_output": 40, "dropout_r": 40, "top_bn": 40, "architectur": [40, 44], "shown": [40, 71, 90, 91, 92, 93, 95, 96, 99, 100, 101, 103, 106, 107, 109, 110], "forward": [40, 41, 42, 44, 93, 103], "overridden": [40, 44], "although": [40, 44, 72, 88, 95, 100], "recip": [40, 44], "afterward": [40, 44], "sinc": [40, 44, 48, 60, 64, 71, 79, 83, 99, 100, 103, 104, 105, 107, 110], "hook": [40, 44, 98], "silent": [40, 43, 44], "t_destin": [40, 42, 44], "__call__": [40, 42, 44, 47, 51], "add_modul": [40, 42, 44], "child": [40, 44], "fn": [40, 44, 71], "recurs": [40, 44, 51], "submodul": [40, 44, 53], "children": [40, 42, 44, 110], "nn": [40, 41, 44, 54, 93], "init": [40, 44, 101], "no_grad": [40, 44, 93, 106], "init_weight": [40, 44], "linear": [40, 44, 89, 93, 96], "fill_": [40, 44], "net": [40, 44, 90, 93, 98], "in_featur": [40, 44], "out_featur": [40, 44], "bia": [40, 44, 93], "tensor": [40, 41, 44, 90, 93, 106], "requires_grad": [40, 44], "bfloat16": [40, 42, 44], "cast": [40, 44, 90], "buffer": [40, 42, 44], "datatyp": [40, 44], "xdoctest": [40, 44], "undefin": [40, 44], "var": [40, 44], "buf": [40, 44], "20l": [40, 44], "1l": [40, 44], "5l": [40, 44], "call_super_init": [40, 42, 44], "immedi": [40, 44, 106], "compil": [40, 42, 44, 62], "cpu": [40, 42, 44, 46, 90, 93], "move": [40, 44, 51, 86, 98], "cuda": [40, 42, 44, 90, 93], "devic": [40, 44, 90, 93, 100], "gpu": [40, 44, 89, 90, 96], "live": [40, 44], "copi": [40, 44, 75, 88, 90, 91, 92, 95, 97, 99, 100, 104, 107, 108], "doubl": [40, 42, 44], "dump_patch": [40, 42, 44], "eval": [40, 42, 44, 93, 104, 106], "dropout": [40, 44], "batchnorm": [40, 44], "grad": [40, 44], "extra_repr": [40, 42, 44], "line": [40, 44, 85, 91, 97, 98, 103, 106, 110], "get_buff": [40, 42, 44], "target": [40, 41, 44, 75, 76, 97, 106, 108], "throw": [40, 44], "get_submodul": [40, 42, 44], "explan": [40, 44], "qualifi": [40, 44], "referenc": [40, 44], "attributeerror": [40, 44], "invalid": [40, 44, 96], "resolv": [40, 44, 97, 110], "get_extra_st": [40, 42, 44], "state_dict": [40, 42, 44], "set_extra_st": [40, 42, 44], "build": [40, 44, 54, 93, 97, 109], "picklabl": [40, 44], "serial": [40, 44], "backward": [40, 44, 93], "break": [40, 44, 93, 105], "pickl": [40, 44, 105], "get_paramet": [40, 42, 44], "net_b": [40, 44], "net_c": [40, 44], "conv": [40, 44], "conv2d": [40, 44, 93], "16": [40, 44, 51, 54, 62, 79, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 105, 106, 109, 110], "kernel_s": [40, 44], "stride": [40, 44], "200": [40, 44, 73, 97, 98, 105, 110], "diagram": [40, 44, 107], "degre": [40, 44], "queri": [40, 44, 54, 56, 92, 93, 97, 99, 100, 104], "named_modul": [40, 42, 44], "o": [40, 44, 57, 58, 90, 91, 92, 98, 99, 100, 101, 104, 105, 110], "transit": [40, 44], "ipu": [40, 42, 44], "load_state_dict": [40, 42, 44], "strict": [40, 44, 51], "persist": [40, 44], "strictli": [40, 44], "inplac": [40, 44, 97, 103], "preserv": [40, 44, 59], "namedtupl": [40, 44], "missing_kei": [40, 44], "unexpected_kei": [40, 44], "runtimeerror": [40, 44], "idx": [40, 44, 59, 60, 71, 91, 93, 97, 99, 100, 101, 103, 105, 106], "named_buff": [40, 42, 44], "prefix": [40, 44, 90, 110], "remove_dupl": [40, 44], "prepend": [40, 44], "running_var": [40, 44], "named_children": [40, 42, 44], "conv4": [40, 44], "conv5": [40, 44], "memo": [40, 44], "named_paramet": [40, 42, 44], "register_backward_hook": [40, 42, 44], "deprec": [40, 44, 48], "favor": [40, 44], "register_full_backward_hook": [40, 42, 44], "removablehandl": [40, 44], "register_buff": [40, 42, 44], "running_mean": [40, 44], "register_forward_hook": [40, 42, 44], "with_kwarg": [40, 44], "always_cal": [40, 44], "possibli": [40, 44, 88, 95], "fire": [40, 44, 98], "register_module_forward_hook": [40, 44], "regardless": [40, 44, 91, 92], "register_forward_pre_hook": [40, 42, 44], "And": [40, 44], "forward_pr": [40, 44], "register_module_forward_pre_hook": [40, 44], "gradient": [40, 44, 93, 95, 108], "grad_input": [40, 44], "grad_output": [40, 44], "technic": [40, 44], "caller": [40, 44], "register_module_full_backward_hook": [40, 44], "register_full_backward_pre_hook": [40, 42, 44], "backward_pr": [40, 44], "register_module_full_backward_pre_hook": [40, 44], "register_load_state_dict_post_hook": [40, 42, 44], "post": [40, 44, 54], "incompatible_kei": [40, 44], "modif": [40, 44, 54], "thrown": [40, 44], "register_modul": [40, 42, 44], "register_paramet": [40, 42, 44], "register_state_dict_pre_hook": [40, 42, 44], "keep_var": [40, 44], "requires_grad_": [40, 42, 44], "autograd": [40, 44], "freez": [40, 44, 89, 90, 96], "finetun": [40, 44], "gan": [40, 44], "share_memori": [40, 42, 44], "share_memory_": [40, 44], "destin": [40, 44], "shallow": [40, 44], "releas": [40, 44, 62, 86, 99], "design": [40, 44, 54], "ordereddict": [40, 44], "detach": [40, 44, 93], "non_block": [40, 44], "memory_format": [40, 44], "channels_last": [40, 44], "Its": [40, 44, 51, 64, 70], "complex": [40, 44, 100], "integr": [40, 44, 56, 85, 99], "asynchron": [40, 44], "host": [40, 44], "pin": [40, 44, 89, 96, 98], "desir": [40, 44, 54, 58, 71], "4d": [40, 44], "ignore_w": [40, 44], "determinist": [40, 44, 90], "1913": [40, 44], "3420": [40, 44], "5113": [40, 44], "2325": [40, 44], "env": [40, 44], "torch_doctest_cuda1": [40, 44], "gpu1": [40, 44], "1914": [40, 44], "5112": [40, 44], "2324": [40, 44], "float16": [40, 44], "cdoubl": [40, 44], "3741": [40, 44], "2382": [40, 44], "5593": [40, 44], "4443": [40, 44], "complex128": [40, 44], "6122": [40, 44], "1150": [40, 44], "to_empti": [40, 42, 44], "storag": [40, 44], "dst_type": [40, 44], "xpu": [40, 42, 44], "zero_grad": [40, 42, 44, 93], "set_to_non": [40, 44], "reset": [40, 44], "context": [40, 44, 105], "noisili": [41, 101], "han": 41, "2018": 41, "cifar_cnn": [41, 42], "loss_coteach": [41, 42], "y_1": 41, "y_2": 41, "forget_r": 41, "class_weight": 41, "logit": [41, 62, 93], "decim": [41, 59], "forget": [41, 51, 110], "rate_schedul": 41, "epoch": [41, 42, 44, 93, 99], "initialize_lr_schedul": [41, 42], "lr": [41, 42, 44], "001": [41, 73, 97, 99], "250": [41, 91, 92, 101, 105], "epoch_decay_start": 41, "schedul": 41, "beta": 41, "adam": 41, "adjust_learning_r": [41, 42], "alpha_plan": 41, "beta1_plan": 41, "forget_rate_schedul": [41, 42], "num_gradu": 41, "expon": 41, "tell": [41, 89, 93, 96, 101], "train_load": [41, 44], "model1": [41, 101], "optimizer1": 41, "model2": [41, 101], "optimizer2": 41, "dataload": [41, 93, 106], "parser": 41, "parse_arg": 41, "num_iter_per_epoch": 41, "print_freq": 41, "topk": 41, "top1": 41, "top5": 41, "test_load": 41, "offici": [42, 61, 97, 110], "wish": [42, 61, 100, 106, 109, 110], "adj_confident_thresholds_shar": [42, 43], "labels_shar": [42, 43], "pred_probs_shar": [42, 43], "labelinspector": [42, 43, 99], "get_num_issu": [42, 43], "get_quality_scor": [42, 43], "update_confident_threshold": [42, 43], "score_label_qu": [42, 43], "split_arr": [42, 43], "span_classif": 42, "display_issu": [42, 45, 78, 79, 80, 81, 82, 83, 84, 109, 110], "mnist_pytorch": 42, "get_mnist_dataset": [42, 44], "get_sklearn_digits_dataset": [42, 44], "simplenet": [42, 44], "batch_siz": [42, 43, 44, 77, 79, 93, 99, 106, 109], "log_interv": [42, 44], "momentum": [42, 44], "no_cuda": [42, 44], "test_batch_s": [42, 44, 93], "loader": [42, 44, 93], "set_predict_proba_request": [42, 44], "set_predict_request": [42, 44], "coteach": [42, 86], "mini": [43, 77, 79, 99], "low_self_confid": [43, 46, 65], "self_confid": [43, 46, 47, 51, 65, 67, 73, 81, 83, 88, 89, 99, 101], "conveni": [43, 56, 88, 89, 90, 96, 100], "script": 43, "labels_fil": [43, 99], "pred_probs_fil": [43, 99], "quality_score_kwarg": 43, "num_issue_kwarg": 43, "return_mask": 43, "variant": [43, 63, 109], "read": [43, 48, 92, 99, 101, 106, 110], "zarr": [43, 99], "memmap": [43, 109], "pythonspe": 43, "mmap": [43, 99], "hdf5": 43, "further": [43, 45, 64, 65, 67, 70, 71, 79, 80, 90, 97, 99, 100], "yourfil": 43, "npy": [43, 98, 99, 109], "mmap_mod": [43, 109], "tip": [43, 46, 62, 99], "save_arrai": 43, "your_arrai": 43, "disk": [43, 98, 99], "npz": [43, 110], "maxim": [43, 63, 77, 79, 100, 109], "multiprocess": [43, 46, 65, 77, 79, 93, 99], "linux": [43, 77, 79], "physic": [43, 46, 77, 79, 105], "psutil": [43, 46, 77, 79], "labels_arrai": [43, 60], "predprob": 43, "pred_probs_arrai": 43, "back": [43, 54, 71, 91, 99, 100, 105, 106], "store_result": 43, "becom": [43, 97, 106], "verifi": [43, 56, 99, 100, 103, 106], "long": [43, 63, 72, 100, 103], "chunk": [43, 107], "ram": [43, 98], "end_index": 43, "labels_batch": 43, "pred_probs_batch": 43, "batch_result": 43, "indices_of_examples_with_issu": [43, 99], "shortcut": 43, "encount": [43, 46, 77], "1000": [43, 90, 96, 99, 106], "aggreg": [43, 47, 51, 63, 67, 70, 73, 83, 99, 101, 103], "seen": [43, 99, 100, 106, 110], "far": [43, 63, 100], "label_quality_scor": [43, 67, 70, 73, 76, 101, 105], "method1": 43, "method2": 43, "normalized_margin": [43, 46, 47, 51, 65, 67, 73, 81, 83], "low_normalized_margin": [43, 46, 65], "issue_indic": [43, 70, 93], "update_num_issu": 43, "arr": [43, 99], "chunksiz": 43, "convnet": 44, "bespok": [44, 62], "download": [44, 90, 97, 99, 106], "mnist": [44, 85, 90, 98], "handwritten": 44, "digit": [44, 90, 98], "last": [44, 51, 68, 71, 91, 92, 99, 100, 103, 105, 110], "sklearn_digits_test_s": 44, "01": [44, 73, 75, 90, 97, 101, 104, 105], "templat": 44, "flexibli": 44, "among": [44, 63, 101], "test_set": 44, "overrid": 44, "train_idx": [44, 59, 106], "train_label": [44, 89, 100, 106], "span": [45, 100], "sentenc": [45, 58, 81, 83, 84, 89, 96], "token_classif": [45, 58, 81, 83, 84, 99], "encourag": [46, 65, 73, 76], "multilabel_classif": [46, 64, 65, 67, 73, 99, 104], "pred_probs_by_class": 46, "prune_count_matrix_col": 46, "rank_by_kwarg": [46, 65, 73, 101], "num_to_remove_per_class": [46, 65], "bad": [46, 54, 65, 70, 73, 96, 99], "seem": [46, 101, 104], "aren": 46, "confidence_weighted_entropi": [46, 47, 51, 65, 67, 73, 81, 83], "label_issues_idx": [46, 73, 100], "entropi": [46, 48, 50, 51, 72, 73], "prune_by_class": [46, 65, 101], "predicted_neq_given": [46, 65, 101], "prune_counts_matrix": 46, "smallest": [46, 73], "unus": 46, "number_of_mislabeled_examples_in_class_k": 46, "delet": [46, 85, 89, 99], "too": [46, 51, 54, 72, 93, 99, 100, 105], "thread": [46, 65], "window": [46, 98], "shorter": [46, 68], "find_predicted_neq_given": 46, "find_label_issues_using_argmax_confusion_matrix": 46, "remove_noise_from_class": [47, 59], "clip_noise_r": [47, 59], "clip_valu": [47, 59], "value_count": [47, 59, 99], "value_counts_fill_missing_class": [47, 59], "get_missing_class": [47, 59], "round_preserving_sum": [47, 59], "round_preserving_row_tot": [47, 59], "estimate_pu_f1": [47, 59], "confusion_matrix": [47, 59], "print_square_matrix": [47, 59], "print_noise_matrix": [47, 59, 101], "print_inverse_noise_matrix": [47, 59], "print_joint_matrix": [47, 59, 101], "compress_int_arrai": [47, 59], "train_val_split": [47, 59], "subset_x_i": [47, 59], "subset_label": [47, 59], "subset_data": [47, 59], "extract_indices_tf": [47, 59], "unshuffle_tensorflow_dataset": [47, 59], "is_torch_dataset": [47, 59], "is_tensorflow_dataset": [47, 59], "csr_vstack": [47, 59], "append_extra_datapoint": [47, 59], "get_num_class": [47, 59], "num_unique_class": [47, 59], "get_unique_class": [47, 59], "format_label": [47, 59], "smart_display_datafram": [47, 59], "force_two_dimens": [47, 59], "latent_algebra": [47, 86], "compute_ps_py_inv_noise_matrix": [47, 49], "compute_py_inv_noise_matrix": [47, 49], "compute_inv_noise_matrix": [47, 49], "compute_noise_matrix_from_invers": [47, 49], "compute_pi": [47, 49], "compute_pyx": [47, 49], "label_quality_util": 47, "get_normalized_entropi": [47, 48], "multilabel_util": [47, 104], "stack_compl": [47, 52], "get_onehot_num_class": [47, 52], "int2onehot": [47, 52, 104], "onehot2int": [47, 52, 104], "multilabel_scor": [47, 67], "classlabelscor": [47, 51], "exponential_moving_averag": [47, 51, 67], "softmin": [47, 51, 67, 70, 79, 83], "possible_method": [47, 51], "multilabelscor": [47, 51], "get_class_label_quality_scor": [47, 51], "multilabel_pi": [47, 51], "get_cross_validated_multilabel_pred_prob": [47, 51], "default_k": [47, 53, 54], "features_to_knn": [47, 53, 54], "construct_knn_graph_from_index": [47, 53, 54, 56], "create_knn_graph_and_index": [47, 53, 54], "correct_knn_graph": [47, 53, 54, 97], "correct_knn_distances_and_indices_with_exact_duplicate_sets_inplac": [47, 53, 54], "correct_knn_distances_and_indic": [47, 53, 54], "high_dimension_cutoff": [47, 53, 55], "row_count_cutoff": [47, 53, 55], "decide_euclidean_metr": [47, 53, 55], "decide_default_metr": [47, 53, 55], "construct_knn": [47, 53, 56], "transform_distances_to_scor": [47, 57], "correct_precision_error": [47, 57], "token_classification_util": [47, 110], "get_sent": [47, 58, 110], "filter_sent": [47, 58, 110], "process_token": [47, 58], "merge_prob": [47, 58], "color_sent": [47, 58], "assert_valid_input": [47, 60], "assert_valid_class_label": [47, 60], "assert_nonempty_input": [47, 60], "assert_indexing_work": [47, 60], "labels_to_arrai": [47, 60], "labels_to_list_multilabel": [47, 60], "min_allowed_prob": 48, "wikipedia": 48, "activ": [48, 50, 62, 63, 85, 103], "towardsdatasci": 48, "cheatsheet": 48, "ec57bc067c0b": 48, "clip": [48, 59, 90, 97], "behav": 48, "unnecessari": [48, 99], "slightli": [48, 88, 89], "interv": [48, 51, 106], "herein": 49, "inexact": 49, "cours": [49, 100], "propag": 49, "throughout": [49, 59, 75, 84, 90, 103, 109, 110], "increas": [49, 57, 70, 72, 73, 90, 91, 97, 99, 103, 104, 110], "dot": [49, 83, 99], "true_labels_class_count": 49, "pyx": 49, "multiannot": 50, "assert_valid_inputs_multiannot": 50, "labels_multiannot": [50, 63], "ensembl": [50, 51, 63, 73, 88, 95, 99, 104, 106, 108], "allow_single_label": 50, "annotator_id": 50, "assert_valid_pred_prob": 50, "pred_probs_unlabel": [50, 63], "format_multiannotator_label": [50, 63, 103], "formatted_label": [50, 59], "old": [50, 59, 86, 98], "check_consensus_label_class": 50, "consensus_label": [50, 63, 103], "consensus_method": [50, 63], "consensu": [50, 63, 85, 102, 110], "establish": [50, 62, 89, 108], "compute_soft_cross_entropi": 50, "soft": [50, 98], "find_best_temp_scal": 50, "coarse_search_rang": [50, 75, 99], "fine_search_s": [50, 75, 99], "temperatur": [50, 51, 70, 79, 83], "scale": [50, 57, 88, 97, 98, 99, 106, 109], "factor": [50, 51, 57, 77, 79], "minim": [50, 70, 106], "temp_scale_pred_prob": 50, "temp": 50, "sharpen": [50, 98], "smoothen": 50, "get_normalized_margin_for_each_label": [51, 73], "get_confidence_weighted_entropy_for_each_label": [51, 73], "scorer": 51, "alpha": [51, 67, 70, 91, 92, 97, 101, 104, 108], "exponenti": 51, "ema": 51, "s_1": 51, "s_k": 51, "ema_k": 51, "accord": [51, 65, 95, 96, 101, 110], "formula": [51, 57], "_t": 51, "cdot": 51, "s_t": 51, "qquad": 51, "leq": 51, "_1": 51, "recent": [51, 110], "success": 51, "previou": [51, 54, 93, 95, 99, 105], "discount": 51, "s_ema": 51, "175": [51, 93, 100, 101, 105], "underflow": 51, "nan": [51, 63, 88, 95, 97, 100, 103, 108], "aggregated_scor": 51, "base_scor": [51, 100], "base_scorer_kwarg": 51, "aggregator_kwarg": [51, 67], "n_sampl": [51, 97], "n_label": 51, "class_label_quality_scor": 51, "452": 51, "new_scor": 51, "575": [51, 100], "get_label_quality_scores_per_class": [51, 66, 67], "ml_scorer": 51, "binar": [51, 52], "reformat": [51, 90], "wider": 51, "splitter": 51, "kfold": [51, 93], "onevsrestclassifi": [51, 104], "randomforestclassifi": [51, 101, 104], "n_split": [51, 93, 104], "pred_prob_slic": 52, "onehot": 52, "hot": [52, 65, 71, 77, 80, 88, 95, 98, 99, 108, 109], "onehot_matrix": 52, "pairwis": [53, 55, 72], "reli": [54, 72, 89, 90, 91, 92, 96, 105, 106, 108], "sklearn_knn_kwarg": 54, "correction_featur": 54, "discourag": 54, "flexibl": [54, 99], "manner": [54, 67, 88, 89, 97, 103, 108], "701": 54, "900": [54, 88, 95, 108], "436": [54, 100], "000": [54, 89, 93, 96, 97, 98, 110], "idea": [54, 73, 100, 105], "dens": [54, 62, 97], "33140006": 54, "76210367": 54, "correct_exact_dupl": 54, "mutual": [54, 64, 104], "vari": [54, 70, 92], "exact_duplicate_set": 54, "main": [54, 63], "front": [54, 98], "consider": 54, "capabl": [54, 85, 100], "come": [54, 59, 91, 92, 99, 109], "misidentif": 54, "corrected_dist": 54, "corrected_indic": 54, "sqrt": 54, "distant": 54, "suitabl": [55, 63, 88, 95, 97, 100], "slower": 55, "decid": [55, 63, 89, 96, 98, 103, 108, 110], "predefin": 55, "met": [55, 110], "euclidean_dist": [55, 72], "spatial": [55, 72], "decis": [55, 88, 91, 92, 100], "That": [55, 88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "cosine_dist": 55, "knn_kwarg": 56, "html": [56, 59, 68, 71, 72, 90, 91, 92, 93, 95, 96, 99, 100, 101], "kneighbor": 56, "metric_param": 56, "n_features_in_": 56, "effective_metric_params_": 56, "effective_metric_": 56, "n_samples_fit_": 56, "__sklearn_is_fitted__": 56, "conduct": 56, "is_fit": 56, "trail": 56, "underscor": 56, "avg_dist": 57, "exp": [57, 72, 73, 91], "dt": 57, "right": [57, 68, 71, 89, 96, 104, 105, 106], "strength": [57, 71, 97], "pronounc": 57, "differenti": 57, "ly": 57, "rule": [57, 58, 85, 98], "thumb": 57, "ood_features_scor": [57, 72, 106], "88988177": 57, "80519832": 57, "toler": 57, "minkowski": 57, "noth": 57, "epsilon": 57, "sensibl": 57, "fixed_scor": 57, "readabl": 58, "lambda": [58, 90, 91, 99, 100, 103], "long_sent": 58, "headlin": 58, "charact": [58, 59], "s1": 58, "s2": 58, "processed_token": 58, "alecnlcb": 58, "entiti": [58, 85, 99, 110], "mapped_ent": 58, "unique_ident": 58, "loc": [58, 91, 92, 93, 95, 97, 110], "nbitbas": [58, 67], "probs_merg": 58, "0125": [58, 83], "0375": 58, "075": 58, "025": 58, "color": [58, 80, 91, 92, 95, 97, 101, 104, 106, 108, 109], "red": [58, 71, 91, 92, 97, 98, 101, 104, 105, 106, 109], "colored_sent": 58, "termcolor": 58, "31msentenc": 58, "0m": 58, "ancillari": 59, "class_without_nois": 59, "any_other_class": 59, "choos": [59, 73, 88, 95, 99, 101, 108], "tradition": 59, "new_sum": 59, "fill": 59, "major": [59, 63, 86, 93, 106], "versu": [59, 101], "obviou": 59, "cgdeboer": 59, "iteround": 59, "reach": 59, "prob_s_eq_1": 59, "claesen": 59, "f1": [59, 71, 96, 101], "BE": 59, "left_nam": 59, "top_nam": 59, "titl": [59, 91, 92, 97, 101, 104, 106], "short_titl": 59, "round_plac": 59, "pretti": [59, 101], "joint_matrix": 59, "num_possible_valu": 59, "holdout_idx": 59, "extract": [59, 72, 89, 90, 95, 96, 100, 103, 106, 109], "allow_shuffl": 59, "turn": [59, 85, 105], "shuffledataset": 59, "histori": 59, "pre_x": 59, "buffer_s": 59, "csr_matric": 59, "append": [59, 90, 93, 98, 99, 100, 101, 103, 104, 105, 106, 110], "bottom": [59, 68, 71, 97, 105], "to_data": 59, "from_data": 59, "taken": 59, "label_matrix": 59, "canon": 59, "displai": [59, 71, 80, 84, 89, 90, 95, 96, 97, 101, 110], "jupyt": [59, 90, 91, 92, 93, 98, 99, 100, 101, 103, 104, 106, 108, 110], "notebook": [59, 63, 90, 92, 98, 99, 100, 101, 103, 104, 105, 107, 109, 110], "consol": 59, "allow_missing_class": 60, "allow_one_class": 60, "length_x": 60, "labellik": 60, "labels_list": [60, 65], "keraswrappermodel": [61, 62, 85], "keraswrappersequenti": [61, 62], "tf": [62, 90], "legaci": 62, "newer": 62, "interim": 62, "advis": [62, 104], "stabil": [62, 72], "until": 62, "accommod": 62, "keraswrapp": 62, "huggingface_keras_imdb": 62, "unit": [62, 110], "model_kwarg": [62, 75], "compile_kwarg": 62, "sparsecategoricalcrossentropi": 62, "layer": [62, 89, 90, 96, 106], "my_keras_model": 62, "from_logit": 62, "declar": 62, "apply_softmax": 62, "analysi": 63, "analyz": [63, 85, 97, 101, 103, 104], "get_label_quality_multiannot": [63, 103], "vote": 63, "crowdsourc": [63, 85, 103], "dawid": [63, 103], "skene": [63, 103], "analog": [63, 98, 103], "chosen": [63, 73, 99, 103], "crowdlab": [63, 103], "unlabel": [63, 93, 103, 106, 109], "get_active_learning_scor": [63, 103], "activelab": [63, 103], "priorit": [63, 70, 105, 109, 110], "showcas": 63, "best_qual": 63, "quality_method": 63, "calibrate_prob": 63, "return_detailed_qu": 63, "return_annotator_stat": 63, "return_weight": 63, "label_quality_score_kwarg": 63, "did": [63, 64, 88, 89, 90, 95, 101, 103, 108], "majority_vot": 63, "broken": [63, 71, 98, 108], "highest": [63, 71, 91, 93, 100, 107], "0th": 63, "consensus_quality_scor": [63, 103], "annotator_agr": [63, 103], "reman": 63, "1st": 63, "2nd": [63, 77], "3rd": 63, "consensus_label_suffix": 63, "consensus_quality_score_suffix": 63, "suffix": 63, "emsembl": 63, "weigh": [63, 98], "agreement": [63, 103], "agre": 63, "prevent": [63, 99], "overconfid": [63, 107], "detailed_label_qu": [63, 103], "annotator_stat": [63, 103], "model_weight": 63, "annotator_weight": 63, "warn": 63, "labels_info": 63, "num_annot": [63, 103], "deriv": [63, 103], "quality_annotator_1": 63, "quality_annotator_2": 63, "quality_annotator_m": 63, "annotator_qu": [63, 103], "num_examples_label": [63, 103], "agreement_with_consensu": [63, 103], "worst_class": [63, 103], "trustworthi": [63, 103, 108], "get_label_quality_multiannotator_ensembl": 63, "weigtht": 63, "budget": 63, "retrain": [63, 89, 108], "active_learning_scor": 63, "active_learning_scores_unlabel": 63, "get_active_learning_scores_ensembl": 63, "henc": [63, 90, 91, 100, 103], "get_majority_vote_label": [63, 103], "event": 63, "lastli": [63, 95], "convert_long_to_wide_dataset": 63, "labels_multiannotator_long": 63, "wide": [63, 88, 89, 90], "labels_multiannotator_wid": 63, "common_multilabel_issu": [64, 66], "exclus": [64, 104], "rank_classes_by_multilabel_qu": [64, 66], "overall_multilabel_health_scor": [64, 66], "multilabel_health_summari": [64, 66], "classes_by_multilabel_qu": 64, "inner": [65, 79, 97], "find_multilabel_issues_per_class": [65, 66], "per_class_label_issu": 65, "label_issues_list": 65, "pred_probs_list": [65, 73, 93, 101], "anim": [66, 106], "rat": 66, "predat": 66, "pet": 66, "reptil": 66, "box": [68, 70, 71, 98, 105], "object_detect": [68, 70, 71, 105], "return_indices_ranked_by_scor": [68, 105], "overlapping_label_check": [68, 70], "suboptim": [68, 70], "locat": [68, 70, 97, 105, 109, 110], "bbox": [68, 71, 105], "image_nam": [68, 71], "y1": [68, 71, 105], "y2": [68, 71, 105], "later": [68, 71, 72, 89, 100, 110], "corner": [68, 71, 105], "xyxi": [68, 71, 105], "io": [68, 71, 90, 97, 98], "keras_cv": [68, 71], "bounding_box": [68, 71, 105], "detectron": [68, 71, 105], "detectron2": [68, 71, 105], "readthedoc": [68, 71], "en": [68, 71], "latest": [68, 71], "draw_box": [68, 71], "mmdetect": [68, 71, 105], "swap": [68, 70, 80, 84], "penal": [68, 70], "concern": [68, 70, 85, 92], "issues_from_scor": [69, 70, 78, 79, 80, 82, 83, 84, 105, 109, 110], "compute_overlooked_box_scor": [69, 70], "compute_badloc_box_scor": [69, 70], "compute_swap_box_scor": [69, 70], "pool_box_scores_per_imag": [69, 70], "object_counts_per_imag": [69, 71, 105], "bounding_box_size_distribut": [69, 71, 105], "class_label_distribut": [69, 71, 105], "get_sorted_bbox_count_idx": [69, 71], "plot_class_size_distribut": [69, 71], "plot_class_distribut": [69, 71], "get_average_per_class_confusion_matrix": [69, 71], "calculate_per_class_metr": [69, 71], "aggregation_weight": 70, "imperfect": [70, 99, 100], "chose": [70, 103, 105], "imperfectli": [70, 105], "dirti": [70, 73, 76, 108], "subtyp": 70, "badloc": 70, "nonneg": 70, "high_probability_threshold": 70, "auxiliary_input": [70, 71], "iou": [70, 71], "heavili": 70, "auxiliarytypesdict": 70, "pred_label": [70, 89], "pred_label_prob": 70, "pred_bbox": 70, "lab_label": 70, "lab_bbox": 70, "similarity_matrix": 70, "min_possible_similar": 70, "scores_overlook": 70, "low_probability_threshold": 70, "scores_badloc": 70, "accident": [70, 89, 95, 96, 99], "scores_swap": 70, "box_scor": 70, "image_scor": [70, 79, 109], "discov": [71, 92, 97, 110], "abnorm": [71, 93, 105], "auxiliari": [71, 106, 109], "_get_valid_inputs_for_compute_scor": 71, "object_count": 71, "down": 71, "bbox_siz": 71, "class_distribut": 71, "plot": [71, 91, 92, 97, 101, 104, 106, 108, 109], "sorted_idx": [71, 106], "class_to_show": 71, "hidden": [71, 106], "max_class_to_show": 71, "plt": [71, 80, 91, 92, 93, 97, 101, 104, 106, 108], "matplotlib": [71, 80, 91, 92, 93, 97, 101, 104, 105, 106, 108], "pyplot": [71, 80, 91, 92, 93, 97, 101, 104, 106, 108], "prediction_threshold": 71, "overlai": [71, 105], "figsiz": [71, 91, 92, 93, 97, 101, 104, 106], "save_path": [71, 105], "blue": [71, 98, 101, 105], "overlaid": 71, "side": [71, 98, 105], "figur": [71, 97, 101, 104, 106, 108], "extens": [71, 101, 103], "png": [71, 105], "pdf": [71, 72], "svg": 71, "num_proc": [71, 93], "intersect": [71, 99], "tp": 71, "fp": 71, "ground": [71, 98, 101, 103, 108], "truth": [71, 101, 103, 108], "bias": [71, 97], "avg_metr": 71, "distionari": 71, "95": [71, 81, 83, 95, 98, 100, 101, 108], "per_class_metr": 71, "Of": 72, "find_top_issu": [72, 73, 106], "behind": [72, 101], "dist_metr": 72, "subtract": [72, 73], "renorm": [72, 73, 99], "least_confid": 72, "sum_": 72, "log": [72, 73, 86], "softmax": [72, 79, 83, 93], "literatur": 72, "gen": 72, "liu": 72, "lochman": 72, "zach": 72, "openaccess": 72, "thecvf": 72, "cvpr2023": 72, "liu_gen_pushing_the_limits_of_softmax": 72, "based_out": 72, "distribution_detection_cvpr_2023_pap": 72, "fit_scor": [72, 106], "ood_predictions_scor": 72, "pretrain": [72, 89, 90, 96, 100, 106], "adjust_confident_threshold": 72, "probabilist": [72, 88, 90, 91, 92, 95, 96, 106, 107], "order_label_issu": [73, 86], "whichev": [73, 107], "argsort": [73, 89, 93, 96, 101, 105, 106, 108], "max_": 73, "get_label_quality_ensemble_scor": [73, 99, 101], "weight_ensemble_members_bi": 73, "custom_weight": 73, "log_loss_search_t_valu": 73, "0001": [73, 98], "scheme": 73, "log_loss_search": 73, "log_loss": [73, 96], "1e0": 73, "1e1": 73, "1e2": 73, "2e2": 73, "quality_scor": [73, 106], "forth": 73, "top_issue_indic": 73, "rank_bi": [73, 86], "weird": [73, 84], "prob_label": 73, "max_prob_not_label": 73, "AND": [73, 96], "get_epistemic_uncertainti": [74, 75], "get_aleatoric_uncertainti": [74, 75], "corrupt": [75, 108], "linearregress": [75, 99, 108], "y_with_nois": 75, "n_boot": [75, 99], "include_aleatoric_uncertainti": [75, 99], "bootstrap": [75, 99, 108], "resampl": [75, 90, 99], "epistem": [75, 99, 106, 108], "aleator": [75, 99, 108], "model_final_kwarg": 75, "coars": 75, "thorough": [75, 99], "fine": [75, 89, 90, 96, 106], "grain": 75, "grid": [75, 100], "varianc": [75, 101], "epistemic_uncertainti": 75, "residu": [75, 76, 99], "deviat": [75, 105, 108], "aleatoric_uncertainti": 75, "outr": 76, "contin": 76, "raw": [76, 85, 86, 92, 93, 98, 99, 100, 103, 105, 106, 108], "aka": [76, 90, 101, 105, 108, 110], "00323821": 76, "33692597": 76, "00191686": 76, "semant": [77, 79, 80, 102], "pixel": [77, 79, 80, 93, 106, 109], "h": [77, 79, 80, 109], "height": [77, 79, 80, 109], "w": [77, 79, 80, 109], "width": [77, 79, 80, 109], "labels_one_hot": [77, 80, 109], "stream": [77, 106, 110], "downsampl": [77, 79, 109], "shrink": [77, 79], "divis": [77, 79, 91], "common_label_issu": [78, 80, 82, 84, 109, 110], "filter_by_class": [78, 80, 109], "segmant": [79, 80], "num_pixel_issu": [79, 109], "product": [79, 93, 97, 99, 100], "pixel_scor": [79, 109], "enter": 80, "legend": [80, 91, 92, 97, 104, 105, 108, 109], "colormap": 80, "background": [80, 97], "person": [80, 99, 105, 109, 110], "ambigu": [80, 84, 89, 90, 96, 98, 101, 110], "misunderstood": [80, 84], "issues_df": [80, 93], "class_index": 80, "issues_subset": [80, 84], "filter_by_token": [82, 84, 110], "token_score_method": 83, "sentence_score_method": 83, "sentence_score_kwarg": 83, "compris": [83, 84], "token_scor": [83, 110], "converg": 83, "toward": [83, 97], "_softmin_sentence_scor": 83, "sentence_scor": [83, 110], "token_info": 83, "02": [83, 91, 92, 97, 101, 105], "03": [83, 95, 97, 98, 100, 101, 105, 106, 110], "04": [83, 95, 97, 105], "08": [83, 97, 101, 105, 108, 110], "commonli": [84, 86, 91, 92, 104, 110], "But": [84, 96, 100, 101, 108, 110], "restrict": [84, 99], "reliabl": [85, 88, 90, 97, 99, 100, 103, 109], "thousand": 85, "imagenet": [85, 98], "popular": [85, 103, 105], "centric": [85, 93, 102], "minut": [85, 88, 89, 90, 95, 96, 98, 103, 104, 105, 108, 109, 110], "conda": 85, "feature_embed": [85, 106], "your_dataset": [85, 90, 91, 92, 93, 95, 96, 99], "column_name_of_label": [85, 90, 91, 92, 93, 95, 96], "tool": [85, 98, 101, 103], "catch": [85, 100], "dive": [85, 96, 97, 100], "plagu": [85, 92], "untrain": 85, "\u30c4": 85, "label_issues_info": [85, 92], "sklearn_compatible_model": 85, "framework": [85, 104, 105], "complianc": 85, "tag": [85, 104, 110], "sequenc": 85, "recognit": [85, 90, 99, 110], "train_data": [85, 88, 89, 106, 108], "gotten": 85, "test_data": [85, 88, 89, 101, 104, 106, 108], "deal": [85, 92, 97, 100], "feel": [85, 90, 92, 99], "ask": [85, 99], "slack": [85, 99], "project": [85, 100, 108], "welcom": 85, "commun": [85, 99], "guidelin": [85, 105], "piec": 85, "smart": [85, 88, 89, 92, 93, 95, 96, 98, 99, 101, 104, 106, 108], "edit": [85, 99, 100], "unreli": [85, 88, 90, 95, 96, 97, 100], "link": [85, 90, 98, 105], "older": 86, "outlin": 86, "substitut": [86, 100], "v2": [86, 88, 95], "get_noise_indic": 86, "psx": 86, "sorted_index_method": 86, "order_label_error": 86, "label_errors_bool": 86, "latent_estim": 86, "num_label_error": 86, "learningwithnoisylabel": 86, "neatli": 86, "organ": [86, 88, 95, 97, 98, 110], "reorgan": 86, "baseline_method": 86, "research": [86, 101], "polyplex": 86, "terminologi": 86, "label_error": 86, "quickstart": [88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 103, 104, 105, 106, 108, 109, 110], "sql": [88, 95], "databas": [88, 95], "excel": [88, 95], "parquet": [88, 95], "student": [88, 95, 100, 108, 110], "grade": [88, 95, 100, 108], "exam": [88, 95, 100, 108], "letter": [88, 95, 110], "hundr": [88, 95], "mistak": [88, 89, 93, 95, 96, 100], "extratreesclassifi": 88, "extratre": 88, "Then": [88, 89, 93, 99], "ranked_label_issu": [88, 89], "branch": [88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108], "standardscal": [88, 95, 100, 106], "labelencod": [88, 89, 100], "train_test_split": [88, 89, 91, 92, 106], "accuracy_scor": [88, 89, 90, 96, 100, 101], "grades_data": [88, 95], "read_csv": [88, 89, 95, 96, 97, 100, 108], "demo": [88, 92, 95, 104], "stud_id": [88, 95, 100], "exam_1": [88, 95, 100, 108], "exam_2": [88, 95, 100, 108], "exam_3": [88, 95, 100, 108], "letter_grad": [88, 95], "f48f73": [88, 95], "53": [88, 91, 92, 95, 97, 98, 100, 104, 105], "00": [88, 91, 92, 95, 97, 98, 100, 106], "77": [88, 91, 92, 95, 100, 105], "0bd4e7": [88, 95], "81": [88, 95, 96, 100, 105, 108, 110], "great": [88, 95, 98, 100], "particip": [88, 95, 100], "cb9d7a": [88, 95], "61": [88, 95, 97, 101, 105, 108], "94": [88, 95, 98, 100, 101, 105, 108], "9acca4": [88, 95], "48": [88, 95, 97, 98, 101, 105], "x_raw": [88, 95], "labels_raw": 88, "interg": [88, 89], "categorical_featur": [88, 108], "x_encod": [88, 95], "get_dummi": [88, 95, 108], "drop_first": [88, 95], "numeric_featur": [88, 95], "scaler": [88, 95, 106], "x_process": [88, 95], "fit_transform": [88, 95, 97, 100], "bring": [88, 89, 93, 95, 96, 103, 108], "byod": [88, 89, 93, 95, 96, 103, 108], "tress": 88, "held": [88, 90, 95, 96, 98, 105, 106, 107], "straightforward": [88, 90, 95], "benefit": [88, 90, 107, 109], "num_crossval_fold": [88, 90, 95, 100, 103], "tabl": [88, 95, 98, 103], "212": [88, 100, 101], "iloc": [88, 89, 90, 95, 96, 100, 108], "92": [88, 91, 100, 101, 105], "93": [88, 98, 100, 105, 108], "827": 88, "99": [88, 97, 98, 100, 101], "86": [88, 92, 93, 95, 100, 101, 105, 108], "74": [88, 97, 100, 105, 108], "637": [88, 95], "79": [88, 98, 100, 105], "65": [88, 91, 97, 100, 105], "cheat": [88, 100], "0pt": [88, 100], "120": [88, 91, 92, 100], "233": [88, 110], "83": [88, 100, 101, 105, 108, 110], "76": [88, 100, 101, 104, 105, 108], "suspici": [88, 95], "carefulli": [88, 93, 95, 96, 100], "examin": [88, 91, 92, 95, 97, 100, 105], "labels_train": 88, "labels_test": 88, "test_siz": [88, 89, 91, 92], "acc_og": [88, 89], "783068783068783": 88, "robustli": [88, 89, 108], "14": [88, 89, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "acc_cl": [88, 89], "8095238095238095": 88, "blindli": [88, 89, 90, 99, 100, 108], "trust": [88, 89, 90, 99, 100, 101, 103, 107, 108], "effort": [88, 89, 100, 108], "cumbersom": [88, 89, 92, 95, 96, 98, 101, 104, 106, 108], "intent": [89, 96], "servic": [89, 96, 99], "onlin": [89, 96], "bank": [89, 96, 98], "banking77": [89, 96], "oo": [89, 96], "categori": [89, 93, 96, 97, 100], "shortlist": [89, 96, 108], "scope": [89, 96], "logist": [89, 91, 92, 96, 103, 106], "probabilit": [89, 90], "drop": [89, 95, 97, 99, 100, 103, 108], "sentence_transform": [89, 96], "sentencetransform": [89, 96], "payment": [89, 96], "cancel_transf": [89, 96], "transfer": [89, 96], "fund": [89, 96], "cancel": [89, 96], "transact": [89, 96], "my": [89, 96], "revert": [89, 96], "morn": [89, 96], "realis": [89, 96], "yesterdai": [89, 96], "rent": [89, 96], "tomorrow": [89, 96], "raw_text": [89, 96], "raw_label": 89, "raw_train_text": 89, "raw_test_text": 89, "raw_train_label": 89, "raw_test_label": 89, "change_pin": [89, 96], "visa_or_mastercard": [89, 96], "getting_spare_card": [89, 96], "supported_cards_and_curr": [89, 96], "lost_or_stolen_phon": [89, 96], "beneficiary_not_allow": [89, 96], "apple_pay_or_google_pai": [89, 96], "card_about_to_expir": [89, 96], "card_payment_fee_charg": [89, 96], "card": [89, 96, 98], "utter": [89, 96], "encond": 89, "test_label": [89, 100, 101, 104, 106], "suit": [89, 96, 97, 98, 99], "electra": [89, 96], "discrimin": [89, 96], "googl": [89, 96], "train_text": 89, "test_text": 89, "home": [89, 96, 98], "runner": [89, 96], "google_electra": [89, 96], "pool": [89, 96, 99, 106], "leverag": [89, 90, 96, 99, 101, 103], "computation": [89, 90, 96], "intens": [89, 90, 96], "400": [89, 96, 100], "858371": 89, "547274": 89, "826228": 89, "966008": 89, "792449": 89, "identified_issu": [89, 108], "lowest_quality_label": [89, 90, 96, 101, 108], "to_numpi": [89, 96, 97, 100, 108], "44": [89, 97, 98, 104, 105], "646": 89, "390": 89, "628": 89, "121": [89, 101], "702": 89, "863": 89, "135": 89, "337": [89, 100, 105], "735": 89, "print_as_df": 89, "inverse_transform": 89, "charg": [89, 96], "cash": [89, 96], "holidai": [89, 96], "sent": [89, 96, 97, 110], "mine": [89, 96], "expir": [89, 96], "fight": 89, "hors": [89, 98, 106], "duck": [89, 98], "me": [89, 96, 97], "whoever": [89, 96], "consum": [89, 108], "18": [89, 90, 96, 97, 98, 99, 100, 101, 105, 106, 108, 109], "baseline_model": [89, 108], "87": [89, 92, 93, 100, 105, 108], "acceler": [89, 108], "19": [89, 90, 93, 96, 97, 98, 99, 100, 101, 105, 106, 108, 109, 110], "89": [89, 91, 95, 100, 105, 108], "spoken": 90, "500": [90, 97, 100, 106, 110], "english": [90, 98], "pronunci": 90, "wav": 90, "voxceleb": 90, "speech": [90, 110], "your_pred_prob": [90, 91, 92, 95, 96], "tensorflow_io": 90, "huggingface_hub": 90, "reproduc": [90, 95, 97, 100, 101, 103], "command": 90, "wget": [90, 97, 105, 109, 110], "navig": 90, "browser": 90, "jakobovski": 90, "archiv": [90, 110], "v1": 90, "tar": [90, 106], "gz": [90, 106], "mkdir": [90, 110], "spoken_digit": 90, "xf": 90, "6_nicolas_32": 90, "data_path": 90, "listdir": 90, "nondeterminist": 90, "file_nam": 90, "endswith": 90, "file_path": 90, "join": [90, 93, 97, 99, 100], "7_george_26": 90, "0_nicolas_24": 90, "0_nicolas_6": 90, "listen": 90, "display_exampl": 90, "expand": [90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "pulldown": [90, 91, 92, 93, 98, 100, 101, 103, 104, 106, 108, 110], "colab": [90, 91, 92, 93, 98, 99, 100, 101, 103, 104, 106, 108, 110], "tfio": 90, "pathlib": 90, "ipython": [90, 97], "load_wav_16k_mono": 90, "filenam": 90, "khz": 90, "file_cont": 90, "read_fil": 90, "sample_r": 90, "decode_wav": 90, "desired_channel": 90, "squeez": 90, "rate_in": 90, "rate_out": 90, "16000": 90, "wav_file_nam": 90, "audio_r": 90, "wav_file_exampl": 90, "plai": [90, 98, 99], "button": 90, "wav_file_name_exampl": 90, "7_jackson_43": 90, "hear": 90, "extractor": 90, "encoderclassifi": 90, "spkrec": 90, "xvect": 90, "feature_extractor": 90, "from_hparam": 90, "run_opt": 90, "uncom": [90, 97], "ffmpeg": 90, "backend": 90, "wav_audio_file_path": 90, "torchaudio": 90, "extract_audio_embed": 90, "emb": [90, 93], "signal": 90, "encode_batch": 90, "embeddings_list": [90, 93], "embeddings_arrai": 90, "512": [90, 93], "196311": 90, "319459": 90, "478975": 90, "2890875": 90, "8170238": 90, "89265": 90, "898056": 90, "256195": 90, "559641": 90, "559721": 90, "62067": 90, "285245": 90, "21": [90, 91, 97, 98, 100, 101, 105, 108, 110], "709627": 90, "5033693": 90, "913803": 90, "819831": 90, "1831515": 90, "208763": 90, "084257": 90, "3210397": 90, "005453": 90, "216152": 90, "478235": 90, "6821785": 90, "053807": 90, "242471": 90, "091424": 90, "78334856": 90, "03954": 90, "23": [90, 93, 97, 98, 100, 101, 105, 108], "569176": 90, "761097": 90, "1258295": 90, "753237": 90, "3508866": 90, "598274": 90, "23712": 90, "2500": 90, "tol": 90, "decreas": [90, 99], "cv_accuraci": 90, "9708": 90, "issue_type_descript": [90, 91, 92, 93, 95, 96, 100, 101], "lt": [90, 91, 92, 93, 95, 96, 97, 98, 100, 101, 103, 106], "gt": [90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 110], "9976": 90, "986": 90, "002161": 90, "176": [90, 97, 98, 101, 104], "002483": 90, "2318": 90, "004411": 90, "1005": 90, "004857": 90, "1871": 90, "007494": 90, "040587": 90, "999207": 90, "999377": 90, "975220": 90, "999367": 90, "identified_label_issu": [90, 96], "516": [90, 100], "1946": 90, "469": 90, "2132": 90, "worth": [90, 101], "6_yweweler_25": 90, "7_nicolas_43": 90, "6_theo_27": 90, "6_yweweler_36": 90, "6_yweweler_14": 90, "6_yweweler_35": 90, "6_nicolas_8": 90, "sound": 90, "quit": [90, 106], "underneath": 91, "hood": [91, 97, 99], "alert": 91, "introduct": 91, "mayb": [91, 92, 96], "your_feature_matrix": [91, 92], "toi": [91, 92, 93, 97, 98, 101, 103, 107], "inf": [91, 92], "mid": [91, 92], "bins_map": [91, 92], "create_data": [91, 92], "y_bin": [91, 92], "y_i": [91, 92], "y_bin_idx": [91, 92], "y_train": [91, 92, 101, 108], "y_test": [91, 92, 101, 108], "y_train_idx": [91, 92], "y_test_idx": [91, 92], "slide": [91, 92, 98], "frame": [91, 92], "x_out": [91, 92], "tini": [91, 92], "concaten": [91, 92, 107], "y_out": [91, 92], "y_out_bin": [91, 92], "y_out_bin_idx": [91, 92], "exact_duplicate_idx": [91, 92], "x_duplic": [91, 92], "y_duplic": [91, 92], "y_duplicate_idx": [91, 92], "noisy_labels_idx": [91, 92, 104], "scatter": [91, 92, 97, 101, 104, 108], "black": [91, 92, 98, 108], "cyan": [91, 92], "plot_data": [91, 92, 97, 101, 104, 108], "fig": [91, 92, 93, 98, 106, 108], "ax": [91, 92, 93, 97, 106, 108], "subplot": [91, 92, 93, 106], "set_titl": [91, 92, 93, 106], "set_xlabel": [91, 92], "x_1": [91, 92], "fontsiz": [91, 92, 93, 97, 101, 104], "set_ylabel": [91, 92], "x_2": [91, 92], "set_xlim": [91, 92], "set_ylim": [91, 92], "linestyl": [91, 92, 97], "circl": [91, 92, 101, 104], "misclassifi": [91, 92], "zip": [91, 92, 93, 97, 105, 110], "label_err": [91, 92], "180": [91, 92, 97, 105], "marker": [91, 92], "facecolor": [91, 92, 97], "edgecolor": [91, 92, 97], "linewidth": [91, 92, 97, 106], "dup": [91, 92], "first_legend": [91, 92], "align": [91, 92], "title_fontproperti": [91, 92], "semibold": [91, 92], "second_legend": [91, 92], "45": [91, 92, 97, 98, 100, 101, 105], "gca": [91, 92], "add_artist": [91, 92], "tight_layout": [91, 92, 97], "ideal": [91, 92], "remaind": 91, "modal": [91, 92, 99, 100, 103], "132": [91, 92, 100, 101, 105], "9318": 91, "006940": 91, "007830": 91, "40": [91, 92, 96, 97, 98, 100], "014828": 91, "107": [91, 92, 101, 104], "021241": 91, "026407": 91, "notic": [91, 101, 103, 105], "3558": [91, 92], "126": [91, 92, 101, 105], "006636": [91, 92], "130": [91, 92], "012571": [91, 92], "129": [91, 92], "127": [91, 92, 100], "014909": [91, 92], "128": [91, 92, 93], "017443": [91, 92], "6160": [91, 92], "131": [91, 92, 100, 109], "000000e": [91, 92, 100], "000002": [91, 92], "463180e": [91, 92], "07": [91, 92, 93, 95, 97, 101, 105, 108], "51": [91, 92, 95, 97, 98, 101, 105], "161148": [91, 92], "859087e": [91, 92], "30": [91, 92, 93, 97, 98, 99, 100, 104, 109, 110], "3453": 91, "029542": 91, "031182": 91, "057961": 91, "058244": 91, "54": [91, 97, 98, 101, 105, 110], "039122": 91, "044598": 91, "105": [91, 105], "105196": 91, "133654": 91, "43": [91, 97, 98, 100, 101, 105, 110], "168033": 91, "125": 91, "101107": 91, "183382": 91, "109": [91, 97, 98, 100, 105], "209259": 91, "211042": 91, "221316": 91, "average_ood_scor": 91, "34530442089193386": 91, "52": [91, 97, 98, 100, 105, 110], "169820": 91, "087324e": 91, "259024": 91, "583757e": 91, "91": [91, 100, 105], "346458": 91, "341292e": 91, "specfi": 91, "new_lab": 91, "scoring_funct": 91, "div": 91, "rem": 91, "inv_scal": 91, "49": [91, 97, 98, 101, 105], "superstitionissuemanag": 91, "unlucki": 91, "superstit": 91, "to_seri": 91, "issues_mask": 91, "summary_scor": 91, "9242": 91, "is_superstition_issu": 91, "superstition_scor": 91, "26": [91, 93, 97, 98, 100, 101, 103, 105], "047581": 91, "090635": 91, "129591": 91, "164840": 91, "lurk": [92, 93, 100, 101], "thoroughli": 92, "8561": 92, "001908": 92, "003564": 92, "007331": 92, "008963": 92, "009664": 92, "0227": 92, "022727": 92, "conceptu": 92, "856061": 92, "355772": 92, "616034": 92, "821750": 92, "926818": 92, "betweeen": 92, "859131": 92, "417707": 92, "664083": 92, "970324": 92, "816953": 92, "375317": 92, "641516": 92, "890575": 92, "910232": 92, "531021": 92, "460593": 92, "601188": 92, "826147": 92, "752808": 92, "321635": 92, "562539": 92, "948362": 92, "890169": 92, "090243": 92, "472909": 92, "746763": 92, "878267": 92, "examples_w_issu": [92, 99], "013445": 92, "025184": 92, "026376": 92, "inde": [92, 96], "miscellan": [92, 94, 110], "428571": 92, "111111": 92, "571429": 92, "407407": 92, "592593": 92, "337838": 92, "092593": 92, "662162": 92, "333333": [92, 98], "952381": 92, "666667": [92, 97], "portion": 92, "huge": [92, 101], "worri": [92, 96, 100], "critic": [92, 107], "60": [93, 97, 101, 108], "torchvis": [93, 97, 106], "tensordataset": 93, "stratifiedkfold": [93, 104], "tqdm": 93, "autonotebook": 93, "math": [93, 100], "fashion_mnist": 93, "num_row": 93, "60000": 93, "transformed_dataset": 93, "with_format": 93, "255": [93, 98], "cpu_count": 93, "torch_dataset": 93, "quick": [93, 104, 106], "super": 93, "relu": 93, "batchnorm2d": 93, "maxpool2d": 93, "lazylinear": 93, "flatten": 93, "get_test_accuraci": 93, "testload": [93, 106], "energi": 93, "trainload": [93, 106], "n_epoch": 93, "patienc": 93, "criterion": 93, "crossentropyloss": 93, "adamw": 93, "best_test_accuraci": 93, "start_epoch": 93, "running_loss": 93, "best_epoch": 93, "end_epoch": 93, "3f": [93, 108], "acc": [93, 101], "time_taken": 93, "compute_embed": 93, "compute_pred_prob": 93, "train_batch_s": 93, "num_work": 93, "worker": [93, 110], "train_id_list": 93, "test_id_list": 93, "train_id": 93, "test_id": 93, "embeddings_model": 93, "ntrain": 93, "trainset": 93, "testset": 93, "pin_memori": 93, "fold_embed": 93, "fold_pred_prob": 93, "finish": 93, "482": 93, "720": 93, "923": 93, "329": [93, 95, 100, 105], "88": [93, 98, 100, 101, 104, 105, 108], "195": [93, 97, 100], "597": [93, 100], "493": 93, "060": 93, "922": 93, "330": [93, 100, 105], "505": 93, "912": [93, 101], "476": [93, 100], "340": [93, 100], "879": 93, "328": [93, 105], "310": 93, "556": 93, "reorder": 93, "hstack": [93, 99, 101, 103], "max_preval": [93, 97], "7714": 93, "3772": 93, "3585": 93, "166": 93, "3651": 93, "27080": 93, "873833e": 93, "40378": 93, "915575e": 93, "25316": 93, "390277e": 93, "06": [93, 97, 100, 101, 105, 110], "2090": 93, "751164e": 93, "14999": 93, "881301e": 93, "9569": 93, "11262": 93, "000003": 93, "coat": [93, 98], "shirt": [93, 98], "19228": 93, "000010": 93, "dress": 93, "32657": 93, "000013": 93, "bag": [93, 98, 106, 107], "21282": 93, "000016": [93, 100], "53564": 93, "000018": [93, 100], "pullov": 93, "6321": 93, "30968": 93, "001267": 93, "30659": 93, "000022": [93, 110], "47824": 93, "001454": 93, "3370": 93, "000026": 93, "54565": 93, "001854": 93, "9762": 93, "258": 93, "47139": 93, "000033": 93, "166980": 93, "986195": 93, "997205": 93, "sandal": [93, 98], "948781": 93, "999358": 93, "54078": 93, "17371": 93, "000025": 93, "plot_label_issue_exampl": 93, "nrow": [93, 106], "ceil": [93, 100], "axes_list": 93, "label_issue_indic": 93, "gl": 93, "sl": 93, "fontdict": 93, "imshow": [93, 106], "cmap": [93, 97, 108], "grai": 93, "subplots_adjust": 93, "hspace": 93, "outsiz": 93, "outlier_issu": [93, 96], "outlier_issues_df": 93, "depict": [93, 104, 105, 106, 107, 109], "plot_outlier_issues_exampl": 93, "n_comparison_imag": 93, "sample_from_class": 93, "number_of_sampl": 93, "non_outlier_indic": 93, "isnul": [93, 97], "non_outlier_indices_excluding_curr": 93, "sampled_indic": 93, "label_scores_of_sampl": 93, "top_score_indic": 93, "top_label_indic": 93, "sampled_imag": 93, "get_image_given_label_and_sampl": 93, "image_from_dataset": 93, "corresponding_label": 93, "comparison_imag": 93, "images_to_plot": 93, "idlist": 93, "iterrow": 93, "near_duplicate_issu": [93, 99], "closest": 93, "counterpart": 93, "near_duplicate_issues_df": 93, "plot_near_duplicate_issue_exampl": 93, "seen_id_pair": 93, "get_image_and_given_label_and_predicted_label": 93, "duplicate_imag": 93, "nd_set": 93, "challeng": 93, "dark_issu": 93, "reveal": [93, 105, 109], "dark_issues_df": 93, "is_dark_issu": [93, 97], "34848": 93, "203922": 93, "50270": 93, "204588": 93, "3936": 93, "213098": 93, "733": 93, "217686": 93, "8094": 93, "230118": 93, "plot_image_issue_exampl": 93, "difficult": 93, "disproportion": [93, 97], "lowinfo_issu": 93, "lowinfo_issues_df": 93, "is_low_information_issu": 93, "53050": 93, "067975": 93, "40875": 93, "089929": 93, "9594": 93, "092601": 93, "34825": 93, "107744": 93, "37530": 93, "108516": 93, "lot": 93, "workflow": [94, 99, 100, 102, 108], "histgradientboostingclassifi": 95, "cat_featur": 95, "boost": [95, 99, 103, 108], "xgboost": [95, 99, 100, 108], "think": [95, 96, 99, 104, 109, 110], "nonzero": 95, "358": 95, "941": 95, "294": [95, 105], "46": [95, 97, 98, 100, 101, 105], "7109": 95, "000005": [95, 96], "886": 95, "000059": 95, "709": [95, 100], "000104": 95, "000169": 95, "689": 95, "000181": 95, "3590": 95, "051882e": 95, "683133e": 95, "536582e": 95, "406589e": 95, "324246e": 95, "6165": 95, "582": [95, 100], "185": [95, 97, 98, 105], "187": [95, 98, 100], "898": 95, "0000": [95, 96, 98, 100, 101], "865": 95, "515002": 95, "837": 95, "556480": 95, "622": 95, "593068": 95, "593207": 95, "920": 95, "618041": 95, "4386345844794593e": 95, "issue_result": 95, "000842": 95, "555944": 95, "004374": 95, "sorted_issu": 95, "73": [95, 97, 98, 100, 104, 105, 108], "deserv": 95, "outlier_result": 95, "sorted_outli": 95, "56": [95, 97, 98, 108], "96": [95, 97, 98, 100, 101, 104, 105, 108], "style": [95, 97, 109], "font": 95, "18px": 95, "ff00ff": 95, "bac": 95, "duplicate_result": 95, "lowest_scoring_dupl": 95, "idxmin": [95, 99], "indices_to_displai": 95, "tolist": [95, 99, 100, 104], "perhap": [95, 101, 103], "second_lowest_scoring_dupl": 95, "next_indices_to_displai": 95, "wari": [95, 96, 99], "your_featur": 96, "text_embed": 96, "data_dict": [96, 101, 103], "85": [96, 100, 105], "38": [96, 97, 98, 105], "9710": 96, "981": 96, "974": 96, "000146": 96, "982": [96, 98], "000224": 96, "971": 96, "000507": 96, "980": [96, 98], "000960": 96, "3584": 96, "994": 96, "009642": 96, "999": 96, "013067": 96, "013841": 96, "433": 96, "014722": 96, "989": 96, "018224": 96, "6070": 96, "160": [96, 108], "095724": 96, "148": 96, "006237": 96, "546": [96, 100], "099341": 96, "514": 96, "006485": 96, "481": 96, "123418": 96, "008165": 96, "313": [96, 100, 105], "564102": 96, "572258": 96, "574915": 96, "31": [96, 97, 98, 100, 101, 103, 105], "575507": 96, "575874": 96, "792090": 96, "257611": 96, "698710": 96, "182121": 96, "771619": 96, "data_with_suggested_label": 96, "suggested_label": 96, "withdraw": 96, "monei": 96, "lowest_quality_outli": 96, "OR": 96, "636c65616e6c616220697320617765736f6d6521": 96, "phone": [96, 98], "gone": 96, "samp": 96, "br": 96, "press": [96, 110], "nonsens": 96, "sens": 96, "detriment": 96, "duplicate_issu": 96, "fee": 96, "go": [96, 97, 98, 101], "p_valu": 96, "benign": 96, "curat": [96, 102], "bigger": 97, "make_classif": 97, "5000": [97, 106], "n_featur": 97, "n_inform": 97, "n_redund": 97, "n_repeat": 97, "n_class": 97, "n_clusters_per_class": 97, "flip_i": 97, "class_sep": 97, "faiss": 97, "x_faiss": 97, "float32": [97, 105], "normalize_l2": 97, "index_factori": 97, "hnsw32": 97, "flat": [97, 98], "metric_inner_product": 97, "a_min": 97, "a_max": 97, "create_knn_graph": 97, "assert": 97, "indices_1d": 97, "ravel": 97, "distances_1d": 97, "sort_graph_by_row_valu": 97, "warn_when_not_sort": 97, "50000": 97, "523": [97, 100], "991400": 97, "356958": 97, "362": 97, "619565": 97, "108": [97, 105], "500000": 97, "651838": 97, "999827": 97, "031217": 97, "933716": 97, "627345": 97, "998540": 97, "530909": 97, "296974": 97, "646765": 97, "942721": 97, "332824": 97, "803246": 97, "625202": 97, "999816": 97, "474031": 97, "706253": 97, "655108": 97, "997703": 97, "131466": 97, "912389": 97, "639200": 97, "4995": 97, "998646": 97, "504755": 97, "746777": 97, "680033": 97, "4996": 97, "894230": 97, "340986": 97, "816472": 97, "640711": 97, "4997": 97, "999100": 97, "428545": 97, "592421": 97, "658949": 97, "4998": 97, "986792": 97, "273710": 97, "618033": 97, "4999": 97, "986776": 97, "273524": 97, "618084": 97, "instabl": 97, "proxim": 97, "analys": 97, "comfort": 97, "explor": [97, 105, 106], "third": 97, "parti": [97, 110], "newsgroup": 97, "alt": [97, 98], "atheism": [97, 98], "sci": [97, 98], "fetch_20newsgroup": 97, "newsgroups_train": 97, "header": 97, "footer": 97, "quot": 97, "df_text": 97, "target_nam": 97, "enlighten": 97, "omnipot": 97, "19apr199320262420": 97, "kelvin": 97, "jpl": 97, "nasa": 97, "gov": 97, "baa": 97, "nhenri": 97, "he": 97, "nno": 97, "ge": 97, "nlucki": 97, "babi": [97, 98], "tfidfvector": 97, "feature_extract": 97, "x_vector": 97, "data_valuation_issu": 97, "147": [97, 101, 105], "500047": 97, "500093": 97, "499953": 97, "1068": 97, "1069": 97, "1070": 97, "1071": 97, "1072": 97, "1073": 97, "concentr": 97, "seaborn": 97, "sn": 97, "distinguish": [97, 100], "strip": 97, "stripplot": 97, "hue": [97, 108], "dodg": 97, "jitter": 97, "axvlin": [97, 106], "xlabel": 97, "ourselv": 97, "make_blob": 97, "center": [97, 98], "cluster_std": 97, "n_noisy_label": 97, "meaning": [97, 99, 100, 106], "silhouette_scor": 97, "gridsearchcv": 97, "silhouett": 97, "cluster_label": 97, "fit_predict": 97, "param_grid": [97, 100], "grid_search": 97, "best_kmean": 97, "best_estimator_": 97, "underperforming_group_issu": 97, "328308": 97, "tab10": 97, "domain": 97, "knowledg": [97, 101], "dataset_tsv": 97, "ag": [97, 108], "gender": 97, "educ": 97, "experi": 97, "highsalari": 97, "indiana": 97, "phd": 97, "male": 97, "bachelor": 97, "femal": 97, "kansa": 97, "school": [97, 98], "ohio": 97, "57": [97, 98, 100, 101], "california": 97, "59": [97, 98, 105], "34": [97, 98, 101, 103, 105, 110], "63": [97, 100, 101, 105, 108], "47": [97, 98, 105], "stringio": 97, "sep": [97, 110], "easier": [97, 101], "simplic": [97, 104], "ordinalencod": 97, "columns_to_encod": 97, "encoded_df": 97, "salari": 97, "573681": 97, "underpin": 97, "caught": 97, "whenev": 97, "generate_data_depend": 97, "num_sampl": 97, "a1": 97, "a2": 97, "a3": 97, "375": 97, "975": 97, "non_iid_issu": 97, "796474": 97, "842432": 97, "922562": 97, "820759": 97, "873136": 97, "887373": 97, "825101": 97, "855875": 97, "751795": 97, "835796": 97, "ylabel": [97, 106], "coolwarm": 97, "colorbar": [97, 108], "strong": 97, "evid": [97, 100], "inter": 97, "mitig": 97, "risk": [97, 100], "deeper": 97, "tsv": 97, "tab": 97, "pars": 97, "annual_spend": 97, "number_of_transact": 97, "last_purchase_d": 97, "rural": 97, "4099": 97, "2024": [97, 110], "6421": 97, "nat": 97, "suburban": 97, "5436": 97, "4046": 97, "66": [97, 98, 100], "3467": 97, "67": [97, 98, 100, 105, 108], "4757": 97, "4199": 97, "4991": 97, "4655": 97, "82": [97, 98, 100, 101, 105, 108, 110], "5584": 97, "urban": 97, "3102": 97, "6637": 97, "9167": 97, "6790": 97, "5327": 97, "parse_d": 97, "lose": 97, "intact": 97, "encode_categorical_column": 97, "placehold": 97, "dropna": [97, 103], "category_to_numb": 97, "_encod": 97, "gender_encod": 97, "location_encod": 97, "focus": [97, 100, 101, 103, 104, 108], "null_issu": 97, "833333": 97, "sorted_indic": [97, 105], "sorted_df": 97, "nice": 97, "styler": 97, "combined_df": 97, "concat": [97, 100, 108], "highlight_null_valu": 97, "val": [97, 101], "yellow": [97, 98], "highlight_datalab_column": 97, "lightblu": 97, "highlight_is_null_issu": 97, "orang": [97, 98], "styled_df": 97, "nbsp": [97, 99, 100, 101], "160000": 97, "820000": 97, "460000": 97, "470000": 97, "960000": 97, "620000": 97, "550000": 97, "660000": 97, "670000": [97, 98], "370000": 97, "530000": 97, "710000": 97, "020000": 97, "320000": 97, "990000": 97, "rarer": 97, "fairer": 97, "randomli": [97, 100, 101], "class_imbalance_issu": 97, "countplot": 97, "xtick": 97, "rotat": 97, "ytick": 97, "filtered_df": 97, "xy": 97, "va": 97, "textual": 97, "get_ytick": 97, "nbar": 97, "nimbal": 97, "get_legend_handles_label": 97, "title_fonts": 97, "aspect": 97, "anomali": [97, 105], "enhanc": [97, 101, 103, 105], "artifici": 97, "directori": [97, 110], "subdirectori": 97, "nc": [97, 105, 109, 110], "unzip": [97, 105, 110], "09": [97, 100, 104, 105, 108, 110], "199": [97, 100, 105], "111": [97, 103, 108], "153": [97, 100, 105], "110": [97, 105], "connect": [97, 110], "443": [97, 110], "await": [97, 110], "ok": [97, 107, 110], "986707": 97, "964k": 97, "963": 97, "58k": 97, "kb": [97, 110], "005": 97, "mb": [97, 110], "imagefold": 97, "load_image_dataset": 97, "data_dir": 97, "root": [97, 106], "image_dataset": 97, "img": [97, 106, 108], "from_dict": [97, 99], "darkened_imag": 97, "job": 97, "015": 97, "label_uncorrelatedness_scor": 97, "image_issu": 97, "nimag": 97, "237196": 97, "197229": 97, "254188": 97, "229170": 97, "208907": 97, "793840": 97, "196": [97, 100, 101, 105], "197": [97, 101, 105], "971560": 97, "198": [97, 101, 105], "862236": 97, "973533": 97, "stronger": 97, "frog": [97, 98, 106], "darken": 97, "concept": 97, "notabl": 97, "preval": 97, "warrant": 97, "programmat": 97, "plot_scores_label": 97, "issues_copi": 97, "boxplot": 97, "refin": 98, "instruct": [98, 99, 100], "studi": [98, 105], "mnist_test_set": 98, "imagenet_val_set": 98, "tench": 98, "goldfish": 98, "white": [98, 110], "shark": 98, "tiger": 98, "hammerhead": 98, "electr": 98, "rai": 98, "stingrai": 98, "cock": 98, "hen": 98, "ostrich": 98, "brambl": 98, "goldfinch": 98, "hous": 98, "finch": 98, "junco": 98, "indigo": 98, "bunt": 98, "american": [98, 110], "robin": 98, "bulbul": 98, "jai": 98, "magpi": 98, "chickade": 98, "dipper": 98, "kite": 98, "bald": 98, "eagl": 98, "vultur": 98, "grei": 98, "owl": 98, "salamand": 98, "smooth": 98, "newt": 98, "spot": [98, 99, 105], "axolotl": 98, "bullfrog": 98, "tree": 98, "tail": 98, "loggerhead": 98, "sea": 98, "turtl": 98, "leatherback": 98, "mud": 98, "terrapin": 98, "band": 98, "gecko": 98, "green": [98, 110], "iguana": 98, "carolina": 98, "anol": 98, "desert": 98, "grassland": 98, "whiptail": 98, "lizard": 98, "agama": 98, "frill": 98, "neck": 98, "allig": 98, "gila": 98, "monster": 98, "european": 98, "chameleon": 98, "komodo": 98, "dragon": 98, "nile": 98, "crocodil": 98, "triceratop": 98, "worm": 98, "snake": 98, "ring": 98, "eastern": 98, "hog": 98, "nose": 98, "kingsnak": 98, "garter": 98, "water": 98, "vine": 98, "night": 98, "boa": 98, "constrictor": 98, "african": 98, "rock": 98, "indian": 98, "cobra": 98, "mamba": 98, "saharan": 98, "horn": 98, "viper": 98, "diamondback": 98, "rattlesnak": 98, "sidewind": 98, "trilobit": 98, "harvestman": 98, "scorpion": 98, "garden": 98, "spider": 98, "barn": 98, "southern": 98, "widow": 98, "tarantula": 98, "wolf": 98, "tick": 98, "centiped": 98, "grous": 98, "ptarmigan": 98, "ruf": 98, "prairi": 98, "peacock": 98, "quail": 98, "partridg": 98, "parrot": 98, "macaw": 98, "sulphur": 98, "crest": 98, "cockatoo": 98, "lorikeet": 98, "coucal": 98, "bee": 98, "eater": 98, "hornbil": 98, "hummingbird": 98, "jacamar": 98, "toucan": 98, "breast": 98, "mergans": 98, "goos": 98, "swan": 98, "tusker": 98, "echidna": 98, "platypu": 98, "wallabi": 98, "koala": 98, "wombat": 98, "jellyfish": 98, "anemon": 98, "brain": 98, "coral": 98, "flatworm": 98, "nematod": 98, "conch": 98, "snail": 98, "slug": 98, "chiton": 98, "chamber": 98, "nautilu": 98, "dung": 98, "crab": 98, "fiddler": 98, "king": 98, "lobster": 98, "spini": 98, "crayfish": 98, "hermit": 98, "isopod": 98, "stork": 98, "spoonbil": 98, "flamingo": 98, "heron": 98, "egret": 98, "bittern": 98, "crane": 98, "bird": [98, 106], "limpkin": 98, "gallinul": 98, "coot": 98, "bustard": 98, "ruddi": 98, "turnston": 98, "dunlin": 98, "redshank": 98, "dowitch": 98, "oystercatch": 98, "pelican": 98, "penguin": 98, "albatross": 98, "whale": 98, "killer": 98, "dugong": 98, "lion": 98, "chihuahua": 98, "japanes": 98, "chin": 98, "maltes": 98, "pekinges": 98, "shih": 98, "tzu": 98, "charl": 98, "spaniel": 98, "papillon": 98, "terrier": 98, "rhodesian": 98, "ridgeback": 98, "afghan": [98, 110], "hound": 98, "basset": 98, "beagl": 98, "bloodhound": 98, "bluetick": 98, "coonhound": 98, "tan": 98, "walker": 98, "foxhound": 98, "redbon": 98, "borzoi": 98, "irish": 98, "wolfhound": 98, "italian": 98, "greyhound": 98, "whippet": 98, "ibizan": 98, "norwegian": 98, "elkhound": 98, "otterhound": 98, "saluki": 98, "scottish": 98, "deerhound": 98, "weimaran": 98, "staffordshir": 98, "bull": 98, "bedlington": 98, "border": 98, "kerri": 98, "norfolk": 98, "norwich": 98, "yorkshir": 98, "wire": 98, "fox": 98, "lakeland": 98, "sealyham": 98, "airedal": 98, "cairn": 98, "australian": 98, "dandi": 98, "dinmont": 98, "boston": 98, "miniatur": 98, "schnauzer": 98, "giant": 98, "tibetan": 98, "silki": 98, "wheaten": 98, "west": 98, "highland": 98, "lhasa": 98, "apso": 98, "retriev": 98, "curli": 98, "golden": 98, "labrador": 98, "chesapeak": 98, "bai": 98, "german": [98, 110], "shorthair": 98, "pointer": 98, "vizsla": 98, "setter": 98, "gordon": 98, "brittani": 98, "clumber": 98, "springer": 98, "welsh": 98, "cocker": 98, "sussex": 98, "kuvasz": 98, "schipperk": 98, "groenendael": 98, "malinoi": 98, "briard": 98, "kelpi": 98, "komondor": 98, "sheepdog": 98, "shetland": 98, "colli": 98, "bouvier": 98, "de": 98, "flandr": 98, "rottweil": 98, "shepherd": 98, "dobermann": 98, "pinscher": 98, "swiss": [98, 110], "mountain": 98, "bernes": 98, "appenzel": 98, "sennenhund": 98, "entlebuch": 98, "boxer": 98, "bullmastiff": 98, "mastiff": 98, "french": 98, "bulldog": 98, "dane": 98, "st": 98, "bernard": 98, "huski": 98, "alaskan": 98, "malamut": 98, "siberian": 98, "dalmatian": 98, "affenpinsch": 98, "basenji": 98, "pug": 98, "leonberg": 98, "newfoundland": 98, "pyrenean": 98, "samoi": 98, "pomeranian": 98, "chow": 98, "keeshond": 98, "griffon": 98, "bruxelloi": 98, "pembrok": 98, "corgi": 98, "cardigan": 98, "poodl": 98, "mexican": 98, "hairless": 98, "tundra": 98, "coyot": 98, "dingo": 98, "dhole": 98, "wild": 98, "hyena": 98, "kit": 98, "arctic": 98, "tabbi": 98, "persian": 98, "siames": 98, "egyptian": 98, "mau": 98, "cougar": 98, "lynx": 98, "leopard": 98, "snow": 98, "jaguar": 98, "cheetah": 98, "brown": [98, 109], "bear": 98, "polar": 98, "sloth": 98, "mongoos": 98, "meerkat": 98, "beetl": 98, "ladybug": 98, "longhorn": 98, "leaf": 98, "rhinocero": 98, "weevil": 98, "fly": 98, "ant": 98, "grasshopp": 98, "cricket": 98, "stick": 98, "insect": 98, "cockroach": 98, "manti": 98, "cicada": 98, "leafhopp": 98, "lacew": 98, "dragonfli": 98, "damselfli": 98, "admir": 98, "ringlet": 98, "monarch": 98, "butterfli": 98, "gossam": 98, "wing": 98, "starfish": 98, "urchin": 98, "cucumb": 98, "cottontail": 98, "rabbit": 98, "hare": 98, "angora": 98, "hamster": 98, "porcupin": 98, "squirrel": 98, "marmot": 98, "beaver": 98, "guinea": 98, "pig": 98, "sorrel": 98, "zebra": 98, "boar": 98, "warthog": 98, "hippopotamu": 98, "ox": 98, "buffalo": 98, "bison": 98, "bighorn": 98, "sheep": 98, "alpin": 98, "ibex": 98, "hartebeest": 98, "impala": 98, "gazel": 98, "dromedari": 98, "llama": 98, "weasel": 98, "mink": 98, "polecat": 98, "foot": 98, "ferret": 98, "otter": 98, "skunk": 98, "badger": 98, "armadillo": 98, "toed": 98, "orangutan": 98, "gorilla": 98, "chimpanze": 98, "gibbon": 98, "siamang": 98, "guenon": 98, "pata": 98, "monkei": 98, "baboon": 98, "macaqu": 98, "langur": 98, "colobu": 98, "probosci": 98, "marmoset": 98, "capuchin": 98, "howler": 98, "titi": 98, "geoffroi": 98, "lemur": 98, "indri": 98, "asian": 98, "eleph": 98, "bush": 98, "snoek": 98, "eel": 98, "coho": 98, "salmon": 98, "beauti": 98, "clownfish": 98, "sturgeon": 98, "garfish": 98, "lionfish": 98, "pufferfish": 98, "abacu": 98, "abaya": 98, "academ": 98, "gown": 98, "accordion": 98, "acoust": 98, "guitar": 98, "aircraft": 98, "carrier": 98, "airlin": 98, "airship": 98, "altar": 98, "ambul": 98, "amphibi": 98, "clock": [98, 110], "apiari": 98, "apron": 98, "wast": 98, "assault": 98, "rifl": 98, "backpack": 98, "bakeri": 98, "balanc": 98, "beam": 98, "balloon": 98, "ballpoint": 98, "pen": 98, "aid": 98, "banjo": 98, "balust": 98, "barbel": 98, "barber": 98, "chair": [98, 105], "barbershop": 98, "baromet": 98, "barrel": 98, "wheelbarrow": 98, "basebal": 98, "basketbal": 98, "bassinet": 98, "bassoon": 98, "swim": 98, "cap": 98, "bath": 98, "towel": 98, "bathtub": 98, "station": 98, "wagon": 98, "lighthous": 98, "beaker": 98, "militari": 98, "beer": 98, "bottl": 98, "glass": 98, "bell": 98, "cot": 98, "bib": 98, "bicycl": [98, 109], "bikini": 98, "binder": 98, "binocular": 98, "birdhous": 98, "boathous": 98, "bobsleigh": 98, "bolo": 98, "tie": 98, "poke": 98, "bonnet": 98, "bookcas": 98, "bookstor": 98, "bow": 98, "brass": 98, "bra": 98, "breakwat": 98, "breastplat": 98, "broom": 98, "bucket": 98, "buckl": 98, "bulletproof": 98, "vest": 98, "butcher": 98, "shop": 98, "taxicab": 98, "cauldron": 98, "candl": 98, "cannon": 98, "cano": 98, "mirror": [98, 105], "carousel": 98, "carton": 98, "wheel": 98, "teller": 98, "cassett": 98, "player": 98, "castl": 98, "catamaran": 98, "cd": 98, "cello": 98, "mobil": [98, 110], "chain": 98, "fenc": [98, 109], "mail": 98, "chainsaw": 98, "chest": 98, "chiffoni": 98, "chime": 98, "china": 98, "cabinet": 98, "christma": 98, "stock": 98, "church": 98, "movi": 98, "theater": 98, "cleaver": 98, "cliff": 98, "dwell": 98, "cloak": 98, "clog": 98, "cocktail": 98, "shaker": 98, "coffe": 98, "mug": 98, "coffeemak": 98, "coil": 98, "lock": 98, "keyboard": 98, "confectioneri": 98, "ship": [98, 106], "corkscrew": 98, "cornet": 98, "cowboi": 98, "boot": 98, "hat": 98, "cradl": 98, "crash": 98, "helmet": 98, "crate": 98, "infant": 98, "bed": 98, "crock": 98, "pot": 98, "croquet": 98, "crutch": 98, "cuirass": 98, "dam": 98, "desk": 98, "desktop": 98, "rotari": 98, "dial": 98, "telephon": 98, "diaper": 98, "watch": 98, "dine": 98, "dishcloth": 98, "dishwash": 98, "disc": 98, "brake": 98, "dock": 98, "sled": 98, "dome": 98, "doormat": 98, "drill": 98, "rig": 98, "drum": 98, "drumstick": 98, "dumbbel": 98, "dutch": 98, "oven": 98, "fan": 98, "locomot": 98, "entertain": 98, "envelop": 98, "espresso": 98, "powder": 98, "feather": 98, "fireboat": 98, "engin": [98, 109], "screen": 98, "sheet": 98, "flagpol": 98, "flute": 98, "footbal": 98, "forklift": 98, "fountain": 98, "poster": 98, "freight": 98, "fry": 98, "pan": 98, "fur": 98, "garbag": 98, "ga": 98, "pump": 98, "goblet": 98, "kart": 98, "golf": 98, "cart": 98, "gondola": 98, "gong": 98, "grand": 98, "piano": 98, "greenhous": 98, "grill": 98, "groceri": 98, "guillotin": 98, "barrett": 98, "hair": 98, "sprai": 98, "hammer": 98, "dryer": 98, "hand": [98, 101], "handkerchief": 98, "drive": 98, "harmonica": 98, "harp": 98, "harvest": 98, "hatchet": 98, "holster": 98, "honeycomb": 98, "hoop": 98, "skirt": 98, "horizont": 98, "bar": 98, "drawn": 98, "hourglass": 98, "ipod": 98, "cloth": 98, "iron": 98, "jack": 98, "lantern": 98, "jean": 98, "jeep": 98, "jigsaw": 98, "puzzl": 98, "pull": 98, "rickshaw": 98, "joystick": 98, "kimono": 98, "knee": 98, "pad": 98, "knot": 98, "ladl": 98, "lampshad": 98, "laptop": 98, "lawn": 98, "mower": 98, "knife": 98, "lifeboat": 98, "lighter": 98, "limousin": 98, "ocean": 98, "liner": 98, "lipstick": 98, "slip": 98, "shoe": 98, "lotion": 98, "speaker": 98, "loup": 98, "sawmil": 98, "magnet": 98, "compass": 98, "mailbox": 98, "tight": 98, "tank": 98, "manhol": 98, "maraca": 98, "marimba": 98, "maypol": 98, "maze": 98, "cup": [98, 105], "medicin": 98, "megalith": 98, "microphon": 98, "microwav": 98, "milk": 98, "minibu": 98, "miniskirt": 98, "minivan": 98, "missil": 98, "mitten": [98, 99], "mix": 98, "bowl": 98, "modem": 98, "monasteri": 98, "monitor": 98, "mope": 98, "mortar": 98, "mosqu": 98, "mosquito": 98, "scooter": 98, "bike": 98, "tent": 98, "mous": [98, 99], "mousetrap": 98, "van": 98, "muzzl": 98, "nail": 98, "brace": 98, "necklac": 98, "nippl": 98, "obelisk": 98, "obo": 98, "ocarina": 98, "odomet": 98, "oil": 98, "oscilloscop": 98, "overskirt": 98, "bullock": 98, "oxygen": 98, "packet": 98, "paddl": 98, "padlock": 98, "paintbrush": 98, "pajama": 98, "palac": [98, 110], "parachut": 98, "park": 98, "bench": 98, "meter": 98, "passeng": 98, "patio": 98, "payphon": 98, "pedest": 98, "pencil": 98, "perfum": 98, "petri": 98, "dish": 98, "photocopi": 98, "plectrum": 98, "pickelhaub": 98, "picket": 98, "pickup": 98, "pier": 98, "piggi": 98, "pill": 98, "pillow": 98, "ping": 98, "pong": 98, "pinwheel": 98, "pirat": 98, "pitcher": 98, "plane": 98, "planetarium": 98, "plastic": 98, "plate": 98, "rack": 98, "plow": 98, "plunger": 98, "polaroid": 98, "camera": 98, "pole": [98, 109], "polic": 98, "poncho": 98, "billiard": 98, "soda": 98, "potter": 98, "prayer": 98, "rug": 98, "printer": 98, "prison": 98, "projectil": 98, "projector": 98, "hockei": 98, "puck": 98, "punch": 98, "purs": 98, "quill": 98, "quilt": 98, "race": 98, "racket": 98, "radiat": 98, "radio": 98, "telescop": 98, "rain": 98, "recreat": 98, "reel": 98, "reflex": 98, "refriger": 98, "remot": 98, "restaur": 98, "revolv": 98, "rotisseri": 98, "eras": 98, "rugbi": 98, "ruler": 98, "safe": 98, "safeti": 98, "salt": 98, "sarong": 98, "saxophon": 98, "scabbard": 98, "bu": [98, 109], "schooner": 98, "scoreboard": 98, "crt": 98, "screw": 98, "screwdriv": 98, "seat": 98, "belt": 98, "sew": 98, "shield": 98, "shoji": 98, "basket": 98, "shovel": 98, "shower": 98, "curtain": 98, "ski": 98, "sleep": 98, "door": 98, "slot": 98, "snorkel": 98, "snowmobil": 98, "snowplow": 98, "soap": 98, "dispens": 98, "soccer": [98, 110], "sock": [98, 99], "solar": 98, "thermal": 98, "collector": 98, "sombrero": 98, "soup": 98, "heater": 98, "shuttl": 98, "spatula": 98, "motorboat": 98, "web": 98, "spindl": 98, "sport": [98, 110], "spotlight": 98, "stage": 98, "steam": 98, "arch": 98, "bridg": 98, "steel": 98, "stethoscop": 98, "scarf": 98, "stone": 98, "wall": [98, 109], "stopwatch": 98, "stove": 98, "strainer": 98, "tram": 98, "stretcher": 98, "couch": 98, "stupa": 98, "submarin": 98, "sundial": 98, "sunglass": 98, "sunscreen": 98, "suspens": 98, "mop": 98, "sweatshirt": 98, "swimsuit": 98, "swing": 98, "switch": 98, "syring": 98, "lamp": 98, "tape": 98, "teapot": 98, "teddi": 98, "televis": [98, 110], "tenni": 98, "thatch": 98, "roof": 98, "thimbl": 98, "thresh": 98, "throne": 98, "tile": 98, "toaster": 98, "tobacco": 98, "toilet": 98, "totem": 98, "tow": 98, "tractor": 98, "semi": 98, "trailer": 98, "trai": 98, "trench": 98, "tricycl": 98, "trimaran": 98, "tripod": 98, "triumphal": 98, "trolleybu": 98, "trombon": 98, "tub": 98, "turnstil": 98, "typewrit": 98, "umbrella": 98, "unicycl": 98, "upright": 98, "vacuum": 98, "cleaner": [98, 100], "vase": 98, "vault": 98, "velvet": 98, "vend": 98, "vestment": 98, "viaduct": 98, "violin": 98, "volleybal": 98, "waffl": 98, "wallet": 98, "wardrob": 98, "sink": 98, "wash": 98, "jug": 98, "tower": 98, "whiskei": 98, "whistl": 98, "wig": 98, "shade": [98, 109], "windsor": 98, "wine": 98, "wok": 98, "wooden": 98, "spoon": 98, "wool": 98, "rail": 98, "shipwreck": 98, "yawl": 98, "yurt": 98, "websit": 98, "comic": 98, "book": 98, "crossword": 98, "traffic": [98, 105, 109], "sign": [98, 109, 110], "dust": 98, "jacket": [98, 105], "menu": 98, "guacamol": 98, "consomm": 98, "trifl": 98, "ic": 98, "cream": 98, "pop": 98, "baguett": 98, "bagel": 98, "pretzel": 98, "cheeseburg": 98, "mash": 98, "potato": 98, "cabbag": 98, "broccoli": 98, "cauliflow": 98, "zucchini": 98, "spaghetti": 98, "squash": 98, "acorn": 98, "butternut": 98, "artichok": 98, "pepper": [98, 99], "cardoon": 98, "mushroom": 98, "granni": 98, "smith": 98, "strawberri": 98, "lemon": 98, "pineappl": 98, "banana": 98, "jackfruit": 98, "custard": 98, "appl": 98, "pomegran": 98, "hai": 98, "carbonara": 98, "chocol": 98, "syrup": 98, "dough": 98, "meatloaf": 98, "pizza": 98, "pie": 98, "burrito": 98, "eggnog": 98, "alp": 98, "bubbl": 98, "reef": 98, "geyser": 98, "lakeshor": 98, "promontori": 98, "shoal": 98, "seashor": 98, "vallei": 98, "volcano": 98, "bridegroom": 98, "scuba": 98, "diver": 98, "rapese": 98, "daisi": 98, "ladi": 98, "slipper": 98, "corn": 98, "rose": 98, "hip": 98, "chestnut": 98, "fungu": 98, "agar": 98, "gyromitra": 98, "stinkhorn": 98, "earth": 98, "star": 98, "wood": 98, "bolet": 98, "ear": 98, "cifar10_test_set": 98, "airplan": [98, 106], "automobil": [98, 106], "deer": [98, 106], "cifar100_test_set": 98, "aquarium_fish": 98, "boi": 98, "camel": 98, "caterpillar": 98, "cattl": [98, 110], "cloud": 98, "dinosaur": 98, "dolphin": 98, "flatfish": 98, "forest": 98, "girl": 98, "kangaroo": 98, "lawn_mow": 98, "man": 98, "maple_tre": 98, "motorcycl": [98, 109], "oak_tre": 98, "orchid": 98, "palm_tre": 98, "pear": 98, "pickup_truck": 98, "pine_tre": 98, "plain": 98, "poppi": 98, "possum": 98, "raccoon": 98, "road": [98, 109], "rocket": 98, "seal": 98, "shrew": 98, "skyscrap": 98, "streetcar": 98, "sunflow": 98, "sweet_pepp": 98, "trout": 98, "tulip": 98, "willow_tre": 98, "woman": [98, 105], "caltech256": 98, "ak47": 98, "bat": 98, "glove": 98, "birdbath": 98, "blimp": 98, "bonsai": 98, "boom": 98, "breadmak": 98, "buddha": 98, "bulldoz": 98, "cactu": 98, "cake": 98, "tire": 98, "cartman": 98, "cereal": 98, "chandeli": 98, "chess": 98, "board": 98, "chimp": 98, "chopstick": 98, "coffin": 98, "coin": 98, "comet": 98, "cormor": 98, "globe": 98, "diamond": 98, "dice": 98, "doorknob": 98, "drink": 98, "straw": 98, "dumb": 98, "eiffel": 98, "elk": 98, "ewer": 98, "eyeglass": 98, "fern": 98, "fighter": 98, "jet": [98, 108], "extinguish": 98, "hydrant": 98, "firework": 98, "flashlight": 98, "floppi": 98, "fri": 98, "frisbe": 98, "galaxi": 98, "giraff": 98, "goat": 98, "gate": 98, "grape": 98, "pick": [98, 99], "hamburg": 98, "hammock": 98, "harpsichord": 98, "hawksbil": 98, "helicopt": 98, "hibiscu": 98, "homer": 98, "simpson": 98, "horsesho": 98, "air": 98, "skeleton": 98, "ibi": 98, "cone": 98, "iri": 98, "jesu": 98, "christ": 98, "joi": 98, "kayak": 98, "ketch": 98, "ladder": 98, "lath": 98, "licens": 98, "lightbulb": 98, "lightn": 98, "mandolin": 98, "mar": 98, "mattress": 98, "megaphon": 98, "menorah": 98, "microscop": 98, "minaret": 98, "minotaur": 98, "motorbik": 98, "mussel": 98, "neckti": 98, "octopu": 98, "palm": 98, "pilot": 98, "paperclip": 98, "shredder": 98, "pci": 98, "peopl": [98, 105], "pez": 98, "picnic": 98, "pram": 98, "prai": 98, "pyramid": 98, "rainbow": 98, "roulett": 98, "saddl": 98, "saturn": 98, "segwai": 98, "propel": 98, "sextant": 98, "music": 98, "skateboard": 98, "smokestack": 98, "sneaker": 98, "boat": 98, "stain": 98, "steer": 98, "stirrup": 98, "superman": 98, "sushi": 98, "armi": [98, 110], "sword": 98, "tambourin": 98, "teepe": 98, "court": 98, "theodolit": 98, "tomato": 98, "tombston": 98, "tour": 98, "pisa": 98, "treadmil": 98, "fork": 98, "tweezer": 98, "unicorn": 98, "vcr": 98, "waterfal": 98, "watermelon": 98, "weld": 98, "windmil": 98, "xylophon": 98, "yarmulk": 98, "yo": 98, "toad": 98, "twenty_news_test_set": 98, "comp": 98, "graphic": [98, 109], "misc": [98, 110], "sy": 98, "ibm": 98, "pc": 98, "hardwar": 98, "mac": 98, "forsal": 98, "rec": 98, "crypt": 98, "electron": 98, "med": 98, "soc": 98, "religion": 98, "christian": [98, 110], "talk": [98, 110], "polit": 98, "gun": 98, "mideast": 98, "amazon": 98, "neutral": 98, "imdb_test_set": 98, "all_class": 98, "20news_test_set": 98, "_load_classes_predprobs_label": 98, "dataset_nam": 98, "labelerror": 98, "url_bas": 98, "5392f6c71473055060be3044becdde1cbc18284d": 98, "url_label": 98, "original_test_label": 98, "_original_label": 98, "url_prob": 98, "cross_validated_predicted_prob": 98, "_pyx": 98, "num_part": 98, "datatset": 98, "bytesio": 98, "allow_pickl": 98, "pred_probs_part": 98, "url": 98, "_of_": 98, "nload": 98, "imdb": 98, "ve": [98, 99, 100, 101, 103, 105], "capit": 98, "29780": 98, "256": [98, 99, 100, 105], "780": 98, "medic": [98, 110], "doctor": 98, "254": [98, 105], "359223": 98, "640777": 98, "184": [98, 101], "258427": 98, "341176": 98, "263158": 98, "658824": 98, "337349": 98, "246575": 98, "662651": 98, "248": 98, "330000": 98, "355769": 98, "251": [98, 105], "167": [98, 101, 105, 110], "252": [98, 100], "112": [98, 100], "253": [98, 105], "022989": 98, "049505": 98, "190": [98, 101, 105], "002216": 98, "000974": 98, "000873": 98, "000739": 98, "32635": 98, "32636": 98, "32637": 98, "32638": 98, "32639": 98, "32640": 98, "051": 98, "002242": 98, "997758": 98, "002088": 98, "001045": 98, "997912": 98, "002053": 98, "997947": 98, "001980": 98, "000991": 98, "998020": 98, "001946": 98, "002915": 98, "998054": 98, "001938": 98, "002904": 98, "998062": 98, "001020": 98, "998980": 98, "001018": 98, "002035": 98, "998982": 98, "999009": 98, "0003": 98, "0002": 98, "071": 98, "067269": 98, "929": 98, "046": 98, "058243": 98, "954": 98, "035": 98, "032096": 98, "965": 98, "031": 98, "012232": 98, "969": 98, "022": 98, "025896": 98, "978": 98, "020": [98, 101], "013092": 98, "018": 98, "013065": 98, "016": 98, "030542": 98, "984": 98, "013": 98, "020833": 98, "987": 98, "012": 98, "010020": 98, "988": 98, "0073": 98, "0020": 98, "0016": 98, "0015": 98, "0014": 98, "0013": 98, "0012": 98, "0010": 98, "0008": 98, "0007": 98, "0006": 98, "0005": 98, "0004": 98, "244": [98, 105], "452381": 98, "459770": 98, "523364": 98, "460784": 98, "446602": 98, "103774": 98, "030612": 98, "110092": 98, "049020": 98, "0034": 98, "0032": 98, "0026": 98, "0025": 98, "4945": 98, "4946": 98, "4947": 98, "4948": 98, "4949": 98, "4950": 98, "846": 98, "7532": 98, "532": 98, "034483": 98, "009646": 98, "965517": 98, "030457": 98, "020513": 98, "969543": 98, "028061": 98, "035443": 98, "971939": 98, "025316": 98, "005168": 98, "974684": 98, "049751": 98, "979487": 98, "019920": 98, "042802": 98, "980080": 98, "017677": 98, "005115": 98, "982323": 98, "012987": 98, "005236": 98, "987013": 98, "012723": 98, "025126": 98, "987277": 98, "010989": 98, "008264": 98, "989011": 98, "010283": 98, "027778": 98, "989717": 98, "009677": 98, "990323": 98, "007614": 98, "010127": 98, "992386": 98, "005051": 98, "994949": 98, "005025": 98, "994975": 98, "005013": 98, "994987": 98, "001859": 98, "001328": 98, "000929": 98, "000664": 98, "186": [98, 101], "188": [98, 101, 104], "189": [98, 101], "snippet": 99, "nlp": [99, 110], "mind": [99, 101], "alphanumer": 99, "facilit": 99, "seamless": 99, "classlabel": 99, "guidanc": 99, "labels_str": 99, "datalab_str": 99, "labels_int": 99, "remap": 99, "datalab_int": 99, "my_dict": 99, "pet_nam": 99, "rover": 99, "rocki": 99, "speci": 99, "datalab_dataset": 99, "number_of_class": 99, "total_number_of_data_point": 99, "feed": 99, "alphabet": 99, "labels_proper_format": 99, "your_classifi": 99, "issues_datafram": 99, "class_predicted_for_flagged_exampl": 99, "class_predicted_for_all_exampl": 99, "grant": 99, "On": [99, 100, 101, 105], "merged_dataset": 99, "label_column_nam": 99, "datataset": 99, "fair": [99, 101], "game": 99, "speedup": [99, 106], "tempfil": 99, "mkdtemp": 99, "sped": 99, "anywai": 99, "pred_probs_merg": 99, "merge_rare_class": 99, "count_threshold": 99, "class_mapping_orig2new": 99, "heath_summari": 99, "num_examples_per_class": 99, "rare_class": 99, "num_classes_merg": 99, "other_class": 99, "labels_merg": 99, "new_c": 99, "merged_prob": 99, "new_class": 99, "original_class": 99, "num_check": 99, "ones_array_ref": 99, "isclos": 99, "though": [99, 101, 110], "successfulli": 99, "virtuou": [99, 103], "cycl": [99, 103], "jointli": 99, "junk": 99, "clutter": 99, "unknown": 99, "caltech": 99, "combined_boolean_mask": 99, "mask1": 99, "mask2": 99, "gradientboostingclassifi": [99, 101], "true_error": [99, 101, 104], "101": [99, 100, 105], "102": [99, 104, 105], "104": [99, 101, 105], "model_to_find_error": 99, "model_to_return": 99, "cl0": 99, "randomizedsearchcv": 99, "expens": 99, "param_distribut": 99, "learning_r": [99, 100, 101], "max_depth": [99, 100, 101], "magnitud": 99, "coeffici": [99, 108], "optin": 99, "environ": [99, 100, 101], "rerun": [99, 100, 101], "cell": [99, 100, 101], "unabl": [99, 100, 101], "render": [99, 100, 101], "nbviewer": [99, 100, 101], "cleanlearninginot": [99, 101], "fittedcleanlearn": [99, 101], "linearregressionlinearregress": 99, "unexpectedli": 99, "emphas": 99, "crucial": 99, "merge_duplicate_set": 99, "merge_kei": 99, "construct_group_kei": 99, "merged_set": 99, "consolidate_set": 99, "issubset": 99, "frozenset": [99, 100], "sets_list": 99, "mutabl": 99, "new_set": 99, "current_set": 99, "intersecting_set": 99, "lowest_score_strategi": 99, "sub_df": 99, "filter_near_dupl": 99, "strategy_fn": 99, "strategy_kwarg": 99, "duplicate_row": 99, "group_kei": 99, "to_keep_indic": 99, "groupbi": 99, "explod": 99, "to_remov": 99, "isin": [99, 106], "kept": 99, "ids_to_remove_seri": 99, "assist": 99, "streamlin": [99, 100], "ux": 99, "agpl": 99, "compani": 99, "commerci": 99, "alter": [99, 100], "email": 99, "team": 99, "anywher": 99, "profession": 99, "expert": 99, "recogn": 100, "vital": 100, "leakag": 100, "comparion": 100, "leak": 100, "blueprint": 100, "divers": 100, "parameter": 100, "tldr": 100, "answer": [100, 101], "subtl": 100, "faith": 100, "danger": 100, "inevit": [100, 106], "xgbclassifi": 100, "123456": 100, "df_train": 100, "s3": [100, 105, 109, 110], "amazonaw": [100, 105, 109, 110], "clos_train_data": 100, "df_test": 100, "clos_test_data": 100, "noisy_letter_grad": 100, "018bff": 100, "076d92": 100, "c80059": 100, "e38f8a": 100, "d57e1a": 100, "grade_l": 100, "notes_l": 100, "train_featur": 100, "train_features_v2": 100, "train_labels_v2": 100, "test_featur": 100, "preprocessed_train_data": 100, "preprocessed_test_data": 100, "haven": 100, "features_df": 100, "heterogenou": 100, "full_df": 100, "reset_index": [100, 103], "749": 100, "583745": 100, "291382": 100, "5837": 100, "748": 100, "604": 100, "510": 100, "227": [100, 104, 105], "719": 100, "690": 100, "444": 100, "547": 100, "647": 100, "2914": 100, "611": 100, "687869": 100, "610": 100, "687883": 100, "612": 100, "688146": 100, "609": 100, "688189": 100, "613": 100, "688713": 100, "2913818469137725": 100, "came": [100, 110], "full_duplicate_result": 100, "train_idx_cutoff": 100, "nd_set_has_index_over_training_cutoff": 100, "exact_dupl": 100, "627": 100, "678": 100, "615": 100, "292": 100, "620": 100, "420": 100, "704": 100, "431": 100, "459": 100, "672": 100, "564": 100, "696": 100, "605": 100, "exact_duplicates_indic": 100, "indices_of_duplicates_to_drop": 100, "4a3f75": 100, "d030b5": 100, "ddd0ba": 100, "8e6d24": 100, "464aab": 100, "ee3387": 100, "61e807": 100, "71d7b9": 100, "83e31f": 100, "edeb53": 100, "cd52b5": 100, "84": [100, 105, 108, 110], "454e51": 100, "042686": 100, "12a73f": 100, "tree_method": 100, "hist": [100, 106], "enable_categor": 100, "booster": 100, "callback": 100, "colsample_bylevel": 100, "colsample_bynod": 100, "colsample_bytre": 100, "early_stopping_round": 100, "eval_metr": 100, "feature_typ": 100, "gamma": 100, "grow_polici": 100, "importance_typ": 100, "interaction_constraint": 100, "max_bin": 100, "max_cat_threshold": 100, "max_cat_to_onehot": 100, "max_delta_step": 100, "max_leav": 100, "min_child_weight": 100, "monotone_constraint": 100, "multi_strategi": 100, "n_estim": [100, 101], "num_parallel_tre": 100, "x27": [100, 101], "softprob": 100, "xgbclassifierifittedxgbclassifi": 100, "test_pred_prob": [100, 106], "test_lab": 100, "test_features_arrai": 100, "134": 100, "798507": 100, "370259": 100, "625352": 100, "524042": 100, "097015": 100, "7985": 100, "000537": 100, "000903": 100, "001743": 100, "106": 100, "001853": 100, "002121": 100, "3703": 100, "752463e": 100, "784418e": 100, "477741e": 100, "134230e": 100, "153555e": 100, "6254": 100, "143272": 100, "146501": 100, "161431": 100, "5240": 100, "765240": 100, "771221": 100, "801589": 100, "801652": 100, "810735": 100, "5240417899434826": 100, "0970": 100, "na": [100, 103], "test_label_issue_result": 100, "test_label_issues_ord": 100, "2bd759": 100, "34ccdd": 100, "bb3bab": 100, "103": [100, 101, 105], "bf1b14": 100, "4787de": 100, "865cbd": 100, "32d53f": 100, "5b2f76": 100, "28f8b4": 100, "df814d": 100, "f17261": 100, "1db3ff": 100, "ded944": 100, "124": [100, 105], "343dd3": 100, "homework": [100, 108], "8d904d": 100, "e4f0d5": 100, "d6d208": 100, "76c083": 100, "695f96": 100, "745c23": 100, "13b36e": 100, "5ba892": 100, "9f0216": 100, "003628": 100, "004006": 100, "004031": 100, "007930": 100, "013226": 100, "015255": 100, "017692": 100, "019767": 100, "036197": 100, "054746": 100, "055110": 100, "062675": 100, "112695": 100, "121059": 100, "171280": 100, "181689": 100, "208001": 100, "275028": 100, "346032": 100, "396350": 100, "401493": 100, "474349": 100, "mislead": 100, "breviti": 100, "indices_to_drop_from_test_data": 100, "df_test_clean": 100, "acc_origin": 100, "tediou": 100, "train_features_arrai": 100, "train_lab": 100, "318": [100, 108], "601": 100, "740433": 100, "344154": 100, "588290": 100, "437267": 100, "146423": 100, "977223": 100, "7404": 100, "162": 100, "000072": 100, "348": 100, "000161": 100, "232": [100, 105], "000256": 100, "205": [100, 105], "000458": 100, "000738": 100, "3442": 100, "588": 100, "358961e": 100, "336": [100, 105], "490911e": 100, "269": 100, "122475e": 100, "321": [100, 105], "374139e": 100, "311": 100, "358617e": 100, "5883": 100, "600": 100, "592": 100, "593": 100, "594": 100, "595": 100, "596": 100, "598": 100, "599": 100, "221": 100, "222": [100, 101], "315": 100, "332": [100, 105], "791060e": 100, "243": [100, 105], "540": 100, "379106e": 100, "396": 100, "397": 100, "398": 100, "399": 100, "4373": 100, "165": [100, 104], "550374": 100, "627357": 100, "627496": 100, "627502": 100, "627919": 100, "43726734378061227": 100, "1464": 100, "506": 100, "393": 100, "508": 100, "9772": 100, "402": 100, "401": 100, "aggress": 100, "faithfulli": 100, "label_issue_result": 100, "566": 100, "568": 100, "571": 100, "572": 100, "574": 100, "576": 100, "578": 100, "585": 100, "587": 100, "590": 100, "near_duplicates_idx": 100, "117": [100, 101, 108], "122": [100, 101, 105], "146": 100, "155": [100, 101, 105], "156": [100, 101], "173": [100, 105], "224": [100, 105], "272": 100, "277": [100, 105], "279": [100, 105], "288": 100, "300": [100, 103, 110], "342": 100, "352": 100, "363": 100, "365": 100, "366": 100, "384": 100, "388": 100, "394": 100, "404": 100, "474": 100, "480": 100, "494": 100, "515": 100, "536": 100, "537": 100, "539": 100, "542": 100, "outliers_idx": 100, "143": [100, 104, 105], "159": [100, 104, 105], "163": [100, 101], "193": [100, 101, 110], "194": [100, 101], "208": 100, "240": [100, 105], "241": 100, "242": [100, 105], "247": [100, 105], "287": [100, 105], "295": [100, 105], "299": [100, 105], "307": [100, 105], "350": 100, "361": 100, "378": 100, "379": 100, "392": 100, "419": 100, "432": 100, "479": 100, "484": 100, "485": 100, "489": 100, "492": 100, "504": 100, "511": 100, "522": 100, "535": 100, "543": 100, "567": 100, "579": 100, "591": 100, "idx_to_drop": 100, "276": [100, 105], "df_train_cur": 100, "clean_clf": 100, "clean_pr": 100, "acc_clean": 100, "inaccur": 100, "hybrid": 100, "quantit": 100, "hyper": 100, "default_edit_param": 100, "drop_label_issu": 100, "drop_outli": 100, "drop_near_dupl": 100, "candid": [100, 105], "edit_data": 100, "percentag": [100, 101], "num_label_issues_to_drop": 100, "num_outliers_to_drop": 100, "dedupl": 100, "unique_clust": 100, "unique_clusters_list": 100, "near_duplicates_idx_to_drop": 100, "n_drop": 100, "label_issues_idx_to_drop": 100, "outliers_idx_to_drop": 100, "train_features_clean": 100, "train_labels_clean": 100, "itertool": 100, "finer": 100, "param_combin": 100, "best_scor": 100, "best_param": 100, "train_features_preprocess": 100, "train_labels_preprocess": 100, "depth": 101, "survei": [101, 110], "scienc": 101, "multivariate_norm": [101, 103, 104], "make_data": [101, 103], "cov": [101, 103, 104], "avg_trac": [101, 104], "py_tru": 101, "noise_matrix_tru": 101, "noise_marix": 101, "s_test": 101, "noisy_test_label": 101, "purpl": 101, "namespac": 101, "exec": 101, "markerfacecolor": [101, 104], "markeredgecolor": [101, 104, 108], "markers": [101, 104, 108], "markeredgewidth": [101, 104, 108], "realist": 101, "7560": 101, "637318e": 101, "896262e": 101, "548391e": 101, "923417e": 101, "375075e": 101, "3454": 101, "014051": 101, "020451": 101, "249": [101, 105, 110], "042594": 101, "043859": 101, "045954": 101, "6120": 101, "023714": 101, "007136": 101, "119": [101, 105], "107266": 101, "033738": 101, "238": [101, 105], "119505": 101, "236": [101, 105], "037843": 101, "614915": 101, "624422": 101, "625965": 101, "626079": 101, "118": 101, "627675": 101, "695223": 101, "323529": 101, "523015": 101, "013720": 101, "675727": 101, "646521": 101, "magic": 101, "liter": 101, "identif": 101, "logisticregressionlogisticregress": 101, "ever": 101, "092": 101, "040": 101, "024": 101, "004": 101, "surpris": 101, "1705": 101, "01936": 101, "ton": 101, "yourfavoritemodel1": 101, "merged_label": 101, "merged_test_label": 101, "newli": [101, 103], "yourfavoritemodel2": 101, "yourfavoritemodel3": 101, "cl3": 101, "takeawai": 101, "my_test_pred_prob": 101, "my_test_pr": 101, "issues_test": 101, "corrected_test_label": 101, "pretend": 101, "cl_test_pr": 101, "fairli": 101, "label_acc": 101, "offset": 101, "nquestion": 101, "overestim": 101, "experienc": 101, "prioiri": 101, "known": 101, "versatil": 101, "label_issues_indic": 101, "213": [101, 105], "218": [101, 105], "152": 101, "170": 101, "214": 101, "164": [101, 104], "191": [101, 105], "206": [101, 105], "115": [101, 105], "201": [101, 105, 110], "174": 101, "150": [101, 103, 105, 110], "169": [101, 110], "151": [101, 105], "168": 101, "precision_scor": 101, "recall_scor": 101, "f1_score": 101, "true_label_issu": 101, "filter_by_list": 101, "718750": [101, 103], "807018": 101, "733333": 101, "800000": 101, "721311": 101, "792793": 101, "908": 101, "676923": 101, "765217": 101, "892": 101, "567901": 101, "702290": 101, "844": 101, "gaug": 101, "label_issues_count": 101, "172": [101, 104], "157": 101, "easiest": 101, "modular": 101, "penalti": 101, "l2": 101, "model3": 101, "cv_pred_probs_1": 101, "cv_pred_probs_2": 101, "cv_pred_probs_3": 101, "label_quality_scores_best": 101, "cv_pred_probs_ensembl": 101, "label_quality_scores_bett": 101, "superior": [101, 107], "timm": 102, "glad": 103, "multiannotator_label": 103, "noisier": 103, "local_data": [103, 104], "true_labels_train": [103, 104], "noise_matrix_bett": 103, "noise_matrix_wors": 103, "transpos": [103, 106], "zfill": 103, "row_na_check": 103, "notna": 103, "a0001": 103, "a0002": 103, "a0003": 103, "a0004": 103, "a0005": 103, "a0006": 103, "a0007": 103, "a0008": 103, "a0009": 103, "a0010": 103, "a0041": 103, "a0042": 103, "a0043": 103, "a0044": 103, "a0045": 103, "a0046": 103, "a0047": 103, "a0048": 103, "a0049": 103, "a0050": 103, "60856743": 103, "41693214": 103, "40908785": 103, "87147629": 103, "64941785": 103, "10774851": 103, "0524466": 103, "71853246": 103, "37169848": 103, "66031048": 103, "multiannotator_util": 103, "crude": 103, "straight": 103, "majority_vote_label": 103, "736118": 103, "757751": 103, "782232": 103, "715565": 103, "824256": 103, "quality_annotator_a0001": 103, "quality_annotator_a0002": 103, "quality_annotator_a0003": 103, "quality_annotator_a0004": 103, "quality_annotator_a0005": 103, "quality_annotator_a0006": 103, "quality_annotator_a0007": 103, "quality_annotator_a0008": 103, "quality_annotator_a0009": 103, "quality_annotator_a0010": 103, "quality_annotator_a0041": 103, "quality_annotator_a0042": 103, "quality_annotator_a0043": 103, "quality_annotator_a0044": 103, "quality_annotator_a0045": 103, "quality_annotator_a0046": 103, "quality_annotator_a0047": 103, "quality_annotator_a0048": 103, "quality_annotator_a0049": 103, "quality_annotator_a0050": 103, "070564": 103, "216078": 103, "119188": 103, "alongisd": 103, "244981": 103, "208333": 103, "295979": 103, "294118": 103, "324197": 103, "310345": 103, "355316": 103, "346154": 103, "439732": 103, "480000": 103, "a0031": 103, "523205": 103, "580645": 103, "a0034": 103, "535313": 103, "607143": 103, "a0021": 103, "606999": 103, "a0015": 103, "609526": 103, "678571": 103, "a0011": 103, "621103": 103, "692308": 103, "improved_consensus_label": 103, "majority_vote_accuraci": 103, "cleanlab_label_accuraci": 103, "8581081081081081": 103, "9797297297297297": 103, "besid": 103, "sorted_consensus_quality_scor": 103, "worst_qual": 103, "better_qu": 103, "worst_quality_accuraci": 103, "better_quality_accuraci": 103, "9893238434163701": 103, "improved_pred_prob": 103, "treat": [103, 104, 108, 110], "analzi": 103, "copyright": 104, "advertis": 104, "violenc": 104, "nsfw": 104, "celeba": 104, "make_multilabel_data": 104, "boxes_coordin": 104, "box_multilabel": 104, "make_multi": 104, "bx1": 104, "by1": 104, "bx2": 104, "by2": 104, "label_list": 104, "ur": 104, "upper": 104, "inidx": 104, "logical_and": 104, "inv_d": 104, "labels_idx": 104, "true_labels_test": 104, "dict_unique_label": 104, "get_color_arrai": 104, "dcolor": 104, "aa4400": 104, "55227f": 104, "55a100": 104, "00ff00": 104, "007f7f": 104, "386b55": 104, "0000ff": 104, "y_onehot": 104, "single_class_label": 104, "stratifi": [104, 107], "kf": 104, "train_index": 104, "test_index": 104, "clf_cv": 104, "x_train_cv": 104, "x_test_cv": 104, "y_train_cv": 104, "y_test_cv": 104, "y_pred_cv": 104, "saw": 104, "num_to_displai": 104, "275": 104, "267": 104, "225": 104, "171": 104, "234": 104, "262": [104, 105], "263": [104, 105], "266": [104, 105], "139": 104, "216": [104, 105], "265": 104, "despit": [104, 110], "suspect": 104, "888": 104, "8224": 104, "9632": 104, "968": 104, "6512": 104, "0444": 104, "774": 104, "labels_binary_format": 104, "labels_list_format": 104, "surround": 105, "scene": 105, "coco": 105, "everydai": 105, "has_label_issu": 105, "objectdetectionbenchmark": 105, "tutorial_obj": 105, "pkl": 105, "example_imag": 105, "_separate_label": 105, "_separate_predict": 105, "begin": 105, "image_path": 105, "rb": 105, "image_to_visu": 105, "seg_map": 105, "334": 105, "bboxes_ignor": 105, "290": 105, "286": 105, "285": 105, "231": [105, 110], "293": 105, "235": 105, "289": 105, "282": 105, "281": 105, "271": 105, "280": 105, "326": 105, "333": 105, "261": 105, "319": 105, "257": 105, "283": 105, "303": 105, "316": 105, "323": 105, "327": 105, "226": 105, "228": 105, "219": 105, "239": 105, "209": 105, "202": 105, "230": 105, "215": 105, "220": 105, "229": 105, "217": [105, 110], "237": 105, "207": 105, "204": 105, "223": 105, "149": 105, "140": 105, "246": 105, "268": 105, "273": 105, "284": 105, "136": 105, "145": 105, "297": 105, "317": 105, "192": 105, "324": 105, "203": 105, "320": 105, "314": 105, "291": 105, "000000481413": 105, "jpg": 105, "42398": 105, "44503": 105, "29968": 105, "21005": 105, "9978472": 105, "forgot": 105, "drew": 105, "label_issue_idx": 105, "num_examples_to_show": 105, "138": 105, "97489622": 105, "70610878": 105, "98764951": 105, "88899237": 105, "99085805": 105, "issue_idx": 105, "95569726e": 105, "03354841e": 105, "57510169e": 105, "58447666e": 105, "39755858e": 105, "issue_to_visu": 105, "000000009483": 105, "95569726168054e": 105, "addition": [105, 109], "visibl": 105, "missmatch": 105, "likelei": 105, "agnost": 105, "vaidat": 105, "inconsist": 105, "000000395701": 105, "033548411774308e": 105, "armchair": 105, "tv": 105, "000000154004": 105, "38300759625496356": 105, "foreground": 105, "000000448410": 105, "0008575101690203273": 105, "crowd": 105, "alon": 105, "resembl": [105, 106], "000000499768": 105, "9748962231208227": 105, "000000521141": 105, "8889923658893665": 105, "000000143931": 105, "9876495074395956": 105, "bonu": 105, "uncov": 105, "irregular": 105, "object_detection_util": 105, "calculate_bounding_box_area": 105, "num_imgs_to_show": 105, "lab_object_count": 105, "pred_object_count": 105, "000000430073": 105, "000000183709": 105, "000000189475": 105, "label_norm": 105, "pred_norm": 105, "area": [105, 109], "lab_area": 105, "pred_area": 105, "lab_area_mean": 105, "lab_area_std": 105, "max_deviation_valu": 105, "max_deviation_class": 105, "deviation_valu": 105, "deviation_class": 105, "mean_area": 105, "std_area": 105, "class_area": 105, "deviations_awai": 105, "max_deviation_index": 105, "num_imgs_to_show_per_class": 105, "class_num": 105, "000000422886": 105, "000000341828": 105, "000000461009": 105, "train_feature_embed": 106, "ood_train_feature_scor": 106, "test_feature_embed": 106, "ood_test_feature_scor": 106, "ood_train_predictions_scor": 106, "train_pred_prob": 106, "ood_test_predictions_scor": 106, "pylab": 106, "rcparam": 106, "baggingclassifi": 106, "therebi": 106, "rescal": 106, "transform_norm": 106, "totensor": 106, "animal_class": 106, "non_animal_class": 106, "animal_idx": 106, "test_idx": 106, "toronto": 106, "edu": 106, "kriz": 106, "170498071": 106, "46456493": 106, "64it": 106, "plot_imag": 106, "visualize_outli": 106, "txt_class": 106, "npimg": 106, "show_label": 106, "data_subset": 106, "resnet50": 106, "corpu": 106, "2048": 106, "embed_imag": 106, "create_model": 106, "strang": 106, "odd": 106, "train_ood_features_scor": 106, "top_train_ood_features_idx": 106, "fun": 106, "negat": 106, "homogen": 106, "bottom_train_ood_features_idx": 106, "test_ood_features_scor": 106, "top_ood_features_idx": 106, "trade": 106, "5th": 106, "percentil": 106, "fifth_percentil": 106, "plt_rang": 106, "train_outlier_scor": 106, "test_outlier_scor": 106, "ood_features_indic": 106, "revisit": 106, "return_invers": 106, "train_feature_embeddings_sc": 106, "test_feature_embeddings_sc": 106, "train_pred_label": 106, "9702": 106, "train_ood_predictions_scor": 106, "test_ood_predictions_scor": 106, "lost": 106, "unsuit": 107, "convention": 107, "aforement": 107, "hypothet": 107, "contrast": 107, "tradit": 107, "disjoint": 107, "out_of_sample_pred_probs_for_a": 107, "out_of_sample_pred_probs_for_b": 107, "out_of_sample_pred_probs_for_c": 107, "out_of_sample_pred_prob": 107, "unsur": 107, "price": 108, "incom": 108, "sensor": 108, "histgradientboostingregressor": 108, "r2_score": 108, "student_grades_r": 108, "final_scor": 108, "true_final_scor": 108, "3d": 108, "mpl_toolkit": 108, "mplot3d": 108, "axes3d": 108, "errors_idx": 108, "add_subplot": 108, "z": 108, "errors_mask": 108, "feature_column": 108, "predicted_column": 108, "x_train_raw": 108, "x_test_raw": 108, "randomforestregressor": 108, "385101": 108, "499503": 108, "698255": 108, "776647": 108, "109373": 108, "170547": 108, "481096": 108, "984759": 108, "645270": 108, "795928": 108, "141": 108, "659": 108, "367": 108, "305": 108, "560": 108, "657": 108, "view_datapoint": 108, "preds_og": 108, "r2_og": 108, "838": 108, "found_label_issu": 108, "preds_cl": 108, "r2_cl": 108, "926": 108, "favorit": 108, "968627e": 108, "228799": 108, "646674e": 108, "402962": 108, "323818e": 108, "952758": 108, "422144e": 108, "456908": 108, "465815e": 108, "753968": 108, "791186e": 108, "110719": 108, "485156e": 108, "670640": 108, "225300e": 108, "749976": 108, "499679e": 108, "947007": 108, "067882e": 108, "648396": 108, "synthia": 109, "imagesegment": 109, "given_mask": 109, "predicted_mask": 109, "set_printopt": [109, 110], "sky": 109, "sidewalk": 109, "veget": 109, "terrain": 109, "rider": 109, "pred_probs_filepath": 109, "1088": 109, "1920": 109, "label_filepath": 109, "synthia_class": 109, "maunal": 109, "100000": 109, "244800": 109, "leftmost": 109, "middl": [109, 110], "infact": 109, "rightmost": 109, "discrep": 109, "3263230": 109, "783381": 109, "275110": 109, "255917": 109, "78225": 109, "55990": 109, "54315": 109, "33591": 109, "24645": 109, "21054": 109, "15045": 109, "14171": 109, "13832": 109, "13498": 109, "11490": 109, "9164": 109, "8769": 109, "6999": 109, "6031": 109, "5011": 109, "mistakenli": 109, "class_issu": 109, "aim": [109, 110], "domin": 109, "bunch": 110, "conll": 110, "2003": 110, "love": 110, "n_i": 110, "optional_list_of_ordered_class_nam": 110, "deepai": 110, "conll2003": 110, "rm": 110, "tokenclassif": 110, "2400": 110, "52e0": 110, "1a01": 110, "907": 110, "982975": 110, "960k": 110, "959": 110, "94k": 110, "inflat": 110, "17045998": 110, "16m": 110, "octet": 110, "26m": 110, "4mb": 110, "bert": 110, "read_npz": 110, "filepath": 110, "corrsespond": 110, "iob2": 110, "given_ent": 110, "entity_map": 110, "readfil": 110, "startswith": 110, "docstart": 110, "isalpha": 110, "isupp": 110, "indices_to_preview": 110, "nsentenc": 110, "eu": 110, "reject": 110, "boycott": 110, "british": 110, "lamb": 110, "00030412": 110, "00023826": 110, "99936208": 110, "00007009": 110, "00002545": 110, "99998795": 110, "00000401": 110, "00000218": 110, "00000455": 110, "00000131": 110, "00000749": 110, "99996115": 110, "00001371": 110, "0000087": 110, "00000895": 110, "99998936": 110, "00000382": 110, "00000178": 110, "00000366": 110, "00000137": 110, "99999101": 110, "00000266": 110, "00000174": 110, "0000035": 110, "00000109": 110, "99998768": 110, "00000482": 110, "00000202": 110, "00000438": 110, "0000011": 110, "00000465": 110, "99996392": 110, "00001105": 110, "0000116": 110, "00000878": 110, "99998671": 110, "00000364": 110, "00000213": 110, "00000472": 110, "00000281": 110, "99999073": 110, "00000211": 110, "00000159": 110, "00000442": 110, "00000115": 110, "peter": 110, "blackburn": 110, "00000358": 110, "00000529": 110, "99995623": 110, "0000129": 110, "0000024": 110, "00001812": 110, "99994141": 110, "00001645": 110, "00002162": 110, "brussel": 110, "1996": 110, "00001172": 110, "00000821": 110, "00004661": 110, "0000618": 110, "99987167": 110, "99999061": 110, "00000201": 110, "00000195": 110, "00000408": 110, "00000135": 110, "2254": 110, "2907": 110, "19392": 110, "9962": 110, "8904": 110, "19303": 110, "12918": 110, "9256": 110, "11855": 110, "18392": 110, "20426": 110, "19402": 110, "14744": 110, "19371": 110, "4645": 110, "10331": 110, "9430": 110, "6143": 110, "18367": 110, "12914": 110, "todai": 110, "weather": 110, "march": 110, "scalfaro": 110, "northern": 110, "himself": 110, "said": 110, "germani": 110, "nastja": 110, "rysich": 110, "north": 110, "spla": 110, "fought": 110, "khartoum": 110, "govern": 110, "south": 110, "1983": 110, "autonomi": 110, "animist": 110, "region": 110, "moslem": 110, "arabis": 110, "mayor": 110, "antonio": 110, "gonzalez": 110, "garcia": 110, "revolutionari": 110, "wednesdai": 110, "troop": 110, "raid": 110, "farm": 110, "stole": 110, "rape": 110, "women": 110, "spring": 110, "chg": 110, "hrw": 110, "12pct": 110, "princ": 110, "photo": 110, "moment": 110, "spokeswoman": 110, "rainier": 110, "told": 110, "reuter": 110, "danila": 110, "carib": 110, "w224": 110, "equip": 110, "radiomet": 110, "earn": 110, "19996": 110, "london": 110, "denom": 110, "sale": 110, "uk": 110, "jp": 110, "fr": 110, "maccabi": 110, "hapoel": 110, "haifa": 110, "tel": 110, "aviv": 110, "hospit": 110, "rever": 110, "roman": 110, "cathol": 110, "nun": 110, "admit": 110, "calcutta": 110, "week": 110, "ago": 110, "fever": 110, "vomit": 110, "allianc": 110, "embattl": 110, "kabul": 110, "salang": 110, "highwai": 110, "mondai": 110, "tuesdai": 110, "suprem": 110, "council": 110, "led": 110, "jumbish": 110, "milli": 110, "movement": 110, "warlord": 110, "abdul": 110, "rashid": 110, "dostum": 110, "dollar": 110, "exchang": 110, "3570": 110, "12049": 110, "born": 110, "1937": 110, "provinc": 110, "anhui": 110, "dai": 110, "shanghai": 110, "citi": 110, "prolif": 110, "author": 110, "teacher": 110, "chines": 110, "16764": 110, "1990": 110, "historian": 110, "alan": 110, "john": 110, "percival": 110, "taylor": 110, "di": 110, "20446": 110, "pace": 110, "bowler": 110, "ian": 110, "harvei": 110, "claim": 110, "victoria": 110, "15514": 110, "cotti": 110, "osc": 110, "foreign": 110, "minist": 110, "7525": 110, "sultan": 110, "specter": 110, "crown": 110, "abdullah": 110, "defenc": 110, "aviat": 110, "jeddah": 110, "saudi": 110, "agenc": 110, "2288": 110, "hi": 110, "customari": 110, "outfit": 110, "champion": 110, "damp": 110, "scalp": 110, "canada": 110, "reign": 110, "olymp": 110, "donovan": 110, "bailei": 110, "1992": 110, "linford": 110, "christi": 110, "britain": 110, "1984": 110, "1988": 110, "carl": 110, "lewi": 110, "ambigi": 110, "punctuat": 110, "chicago": 110, "digest": 110, "philadelphia": 110, "usda": 110, "york": 110, "token_issu": 110, "471": 110, "kean": 110, "year": 110, "contract": 110, "manchest": 110, "19072": 110, "societi": 110, "bite": 110, "deliv": 110, "19910": 110, "father": 110, "clarenc": 110, "woolmer": 110, "renam": 110, "uttar": 110, "pradesh": 110, "india": 110, "ranji": 110, "trophi": 110, "nation": 110, "championship": 110, "captain": 110, "1949": 110, "15658": 110, "19879": 110, "iii": 110, "brian": 110, "shimer": 110, "randi": 110, "jone": 110, "19104": 110}, "objects": {"cleanlab": [[0, 0, 0, "-", "benchmarking"], [2, 0, 0, "-", "classification"], [3, 0, 0, "-", "count"], [4, 0, 0, "-", "data_valuation"], [12, 0, 0, "-", "datalab"], [39, 0, 0, "-", "dataset"], [42, 0, 0, "-", "experimental"], [46, 0, 0, "-", "filter"], [47, 0, 0, "-", "internal"], [61, 0, 0, "-", "models"], [63, 0, 0, "-", "multiannotator"], [66, 0, 0, "-", "multilabel_classification"], [69, 0, 0, "-", "object_detection"], [72, 0, 0, "-", "outlier"], [73, 0, 0, "-", "rank"], [74, 0, 0, "-", "regression"], [78, 0, 0, "-", "segmentation"], [82, 0, 0, "-", "token_classification"]], "cleanlab.benchmarking": [[1, 0, 0, "-", "noise_generation"]], "cleanlab.benchmarking.noise_generation": [[1, 1, 1, "", "generate_n_rand_probabilities_that_sum_to_m"], [1, 1, 1, "", "generate_noise_matrix_from_trace"], [1, 1, 1, "", "generate_noisy_labels"], [1, 1, 1, "", "noise_matrix_is_valid"], [1, 1, 1, "", "randomly_distribute_N_balls_into_K_bins"]], "cleanlab.classification": [[2, 2, 1, "", "CleanLearning"]], "cleanlab.classification.CleanLearning": [[2, 3, 1, "", "__init_subclass__"], [2, 3, 1, "", "find_label_issues"], [2, 3, 1, "", "fit"], [2, 3, 1, "", "get_label_issues"], [2, 3, 1, "", "get_metadata_routing"], [2, 3, 1, "", "get_params"], [2, 3, 1, "", "predict"], [2, 3, 1, "", "predict_proba"], [2, 3, 1, "", "save_space"], [2, 3, 1, "", "score"], [2, 3, 1, "", "set_fit_request"], [2, 3, 1, "", "set_params"], [2, 3, 1, "", "set_score_request"]], "cleanlab.count": [[3, 1, 1, "", "calibrate_confident_joint"], [3, 1, 1, "", "compute_confident_joint"], [3, 1, 1, "", "estimate_confident_joint_and_cv_pred_proba"], [3, 1, 1, "", "estimate_cv_predicted_probabilities"], [3, 1, 1, "", "estimate_joint"], [3, 1, 1, "", "estimate_latent"], [3, 1, 1, "", "estimate_noise_matrices"], [3, 1, 1, "", "estimate_py_and_noise_matrices_from_probabilities"], [3, 1, 1, "", "estimate_py_noise_matrices_and_cv_pred_proba"], [3, 1, 1, "", "get_confident_thresholds"], [3, 1, 1, "", "num_label_issues"]], "cleanlab.data_valuation": [[4, 1, 1, "", "data_shapley_knn"]], "cleanlab.datalab": [[5, 0, 0, "-", "datalab"], [18, 0, 0, "-", "internal"]], "cleanlab.datalab.datalab": [[5, 2, 1, "", "Datalab"]], "cleanlab.datalab.datalab.Datalab": [[5, 4, 1, "", "class_names"], [5, 3, 1, "", "find_issues"], [5, 3, 1, "", "get_info"], [5, 3, 1, "", "get_issue_summary"], [5, 3, 1, "", "get_issues"], [5, 4, 1, "", "has_labels"], [5, 4, 1, "", "info"], [5, 4, 1, "", "issue_summary"], [5, 4, 1, "", "issues"], [5, 4, 1, "", "labels"], [5, 3, 1, "", "list_default_issue_types"], [5, 3, 1, "", "list_possible_issue_types"], [5, 3, 1, "", "load"], [5, 3, 1, "", "report"], [5, 3, 1, "", "save"]], "cleanlab.datalab.internal.adapter": [[13, 0, 0, "-", "imagelab"]], "cleanlab.datalab.internal.adapter.imagelab": [[13, 2, 1, "", "CorrelationReporter"], [13, 2, 1, "", "CorrelationVisualizer"], [13, 2, 1, "", "ImagelabDataIssuesAdapter"], [13, 2, 1, "", "ImagelabIssueFinderAdapter"], [13, 2, 1, "", "ImagelabReporterAdapter"], [13, 1, 1, "", "create_imagelab"], [13, 1, 1, "", "handle_spurious_correlations"]], "cleanlab.datalab.internal.adapter.imagelab.CorrelationReporter": [[13, 3, 1, "", "report"]], "cleanlab.datalab.internal.adapter.imagelab.CorrelationVisualizer": [[13, 3, 1, "", "visualize"]], "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter": [[13, 3, 1, "", "collect_issues_from_imagelab"], [13, 3, 1, "", "collect_issues_from_issue_manager"], [13, 3, 1, "", "collect_statistics"], [13, 3, 1, "", "filter_based_on_max_prevalence"], [13, 3, 1, "", "get_info"], [13, 3, 1, "", "get_issue_summary"], [13, 3, 1, "", "get_issues"], [13, 3, 1, "", "set_health_score"], [13, 4, 1, "", "statistics"]], "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter": [[13, 3, 1, "", "find_issues"], [13, 3, 1, "", "get_available_issue_types"]], "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter": [[13, 3, 1, "", "get_report"], [13, 3, 1, "", "report"]], "cleanlab.datalab.internal": [[15, 0, 0, "-", "data"], [16, 0, 0, "-", "data_issues"], [19, 0, 0, "-", "issue_finder"], [17, 0, 0, "-", "issue_manager_factory"], [35, 0, 0, "-", "model_outputs"], [36, 0, 0, "-", "report"], [37, 0, 0, "-", "task"]], "cleanlab.datalab.internal.data": [[15, 2, 1, "", "Data"], [15, 5, 1, "", "DataFormatError"], [15, 5, 1, "", "DatasetDictError"], [15, 5, 1, "", "DatasetLoadError"], [15, 2, 1, "", "Label"], [15, 2, 1, "", "MultiClass"], [15, 2, 1, "", "MultiLabel"]], "cleanlab.datalab.internal.data.Data": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "has_labels"]], "cleanlab.datalab.internal.data.DataFormatError": [[15, 3, 1, "", "add_note"], [15, 6, 1, "", "args"], [15, 3, 1, "", "with_traceback"]], "cleanlab.datalab.internal.data.DatasetDictError": [[15, 3, 1, "", "add_note"], [15, 6, 1, "", "args"], [15, 3, 1, "", "with_traceback"]], "cleanlab.datalab.internal.data.DatasetLoadError": [[15, 3, 1, "", "add_note"], [15, 6, 1, "", "args"], [15, 3, 1, "", "with_traceback"]], "cleanlab.datalab.internal.data.Label": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "is_available"]], "cleanlab.datalab.internal.data.MultiClass": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "is_available"]], "cleanlab.datalab.internal.data.MultiLabel": [[15, 4, 1, "", "class_names"], [15, 4, 1, "", "is_available"]], "cleanlab.datalab.internal.data_issues": [[16, 2, 1, "", "DataIssues"], [16, 1, 1, "", "get_data_statistics"]], "cleanlab.datalab.internal.data_issues.DataIssues": [[16, 3, 1, "", "collect_issues_from_imagelab"], [16, 3, 1, "", "collect_issues_from_issue_manager"], [16, 3, 1, "", "collect_statistics"], [16, 3, 1, "", "get_info"], [16, 3, 1, "", "get_issue_summary"], [16, 3, 1, "", "get_issues"], [16, 6, 1, "", "info"], [16, 6, 1, "", "issue_summary"], [16, 6, 1, "", "issues"], [16, 3, 1, "", "set_health_score"], [16, 4, 1, "", "statistics"]], "cleanlab.datalab.internal.issue_finder": [[19, 2, 1, "", "IssueFinder"]], "cleanlab.datalab.internal.issue_finder.IssueFinder": [[19, 3, 1, "", "find_issues"], [19, 3, 1, "", "get_available_issue_types"]], "cleanlab.datalab.internal.issue_manager": [[21, 0, 0, "-", "data_valuation"], [22, 0, 0, "-", "duplicate"], [23, 0, 0, "-", "imbalance"], [25, 0, 0, "-", "issue_manager"], [26, 0, 0, "-", "label"], [29, 0, 0, "-", "noniid"], [30, 0, 0, "-", "null"], [31, 0, 0, "-", "outlier"], [34, 0, 0, "-", "underperforming_group"]], "cleanlab.datalab.internal.issue_manager.data_valuation": [[21, 2, 1, "", "DataValuationIssueManager"]], "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager": [[21, 6, 1, "", "DEFAULT_THRESHOLD"], [21, 3, 1, "", "collect_info"], [21, 6, 1, "", "description"], [21, 3, 1, "", "find_issues"], [21, 6, 1, "", "info"], [21, 6, 1, "", "issue_name"], [21, 6, 1, "", "issue_score_key"], [21, 6, 1, "", "issues"], [21, 3, 1, "", "make_summary"], [21, 3, 1, "", "report"], [21, 6, 1, "", "summary"], [21, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.duplicate": [[22, 2, 1, "", "NearDuplicateIssueManager"]], "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager": [[22, 3, 1, "", "collect_info"], [22, 6, 1, "", "description"], [22, 3, 1, "", "find_issues"], [22, 6, 1, "", "info"], [22, 6, 1, "", "issue_name"], [22, 6, 1, "", "issue_score_key"], [22, 6, 1, "", "issues"], [22, 3, 1, "", "make_summary"], [22, 6, 1, "", "near_duplicate_sets"], [22, 3, 1, "", "report"], [22, 6, 1, "", "summary"], [22, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.imbalance": [[23, 2, 1, "", "ClassImbalanceIssueManager"]], "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager": [[23, 3, 1, "", "collect_info"], [23, 6, 1, "", "description"], [23, 3, 1, "", "find_issues"], [23, 6, 1, "", "info"], [23, 6, 1, "", "issue_name"], [23, 6, 1, "", "issue_score_key"], [23, 6, 1, "", "issues"], [23, 3, 1, "", "make_summary"], [23, 3, 1, "", "report"], [23, 6, 1, "", "summary"], [23, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.issue_manager": [[25, 2, 1, "", "IssueManager"]], "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager": [[25, 3, 1, "", "collect_info"], [25, 6, 1, "", "description"], [25, 3, 1, "", "find_issues"], [25, 6, 1, "", "info"], [25, 6, 1, "", "issue_name"], [25, 6, 1, "", "issue_score_key"], [25, 6, 1, "", "issues"], [25, 3, 1, "", "make_summary"], [25, 3, 1, "", "report"], [25, 6, 1, "", "summary"], [25, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.label": [[26, 2, 1, "", "LabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager": [[26, 3, 1, "", "collect_info"], [26, 6, 1, "", "description"], [26, 3, 1, "", "find_issues"], [26, 3, 1, "", "get_health_summary"], [26, 6, 1, "", "health_summary_parameters"], [26, 6, 1, "", "info"], [26, 6, 1, "", "issue_name"], [26, 6, 1, "", "issue_score_key"], [26, 6, 1, "", "issues"], [26, 3, 1, "", "make_summary"], [26, 3, 1, "", "report"], [26, 6, 1, "", "summary"], [26, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.multilabel": [[28, 0, 0, "-", "label"]], "cleanlab.datalab.internal.issue_manager.multilabel.label": [[28, 2, 1, "", "MultilabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager": [[28, 3, 1, "", "collect_info"], [28, 6, 1, "", "description"], [28, 3, 1, "", "find_issues"], [28, 6, 1, "", "info"], [28, 6, 1, "", "issue_name"], [28, 6, 1, "", "issue_score_key"], [28, 6, 1, "", "issues"], [28, 3, 1, "", "make_summary"], [28, 3, 1, "", "report"], [28, 6, 1, "", "summary"], [28, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.noniid": [[29, 2, 1, "", "NonIIDIssueManager"], [29, 1, 1, "", "simplified_kolmogorov_smirnov_test"]], "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager": [[29, 3, 1, "", "collect_info"], [29, 6, 1, "", "description"], [29, 3, 1, "", "find_issues"], [29, 6, 1, "", "info"], [29, 6, 1, "", "issue_name"], [29, 6, 1, "", "issue_score_key"], [29, 6, 1, "", "issues"], [29, 3, 1, "", "make_summary"], [29, 3, 1, "", "report"], [29, 6, 1, "", "summary"], [29, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.null": [[30, 2, 1, "", "NullIssueManager"]], "cleanlab.datalab.internal.issue_manager.null.NullIssueManager": [[30, 3, 1, "", "collect_info"], [30, 6, 1, "", "description"], [30, 3, 1, "", "find_issues"], [30, 6, 1, "", "info"], [30, 6, 1, "", "issue_name"], [30, 6, 1, "", "issue_score_key"], [30, 6, 1, "", "issues"], [30, 3, 1, "", "make_summary"], [30, 3, 1, "", "report"], [30, 6, 1, "", "summary"], [30, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.outlier": [[31, 2, 1, "", "OutlierIssueManager"]], "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager": [[31, 6, 1, "", "DEFAULT_THRESHOLDS"], [31, 3, 1, "", "collect_info"], [31, 6, 1, "", "description"], [31, 3, 1, "", "find_issues"], [31, 6, 1, "", "info"], [31, 6, 1, "", "issue_name"], [31, 6, 1, "", "issue_score_key"], [31, 6, 1, "", "issues"], [31, 3, 1, "", "make_summary"], [31, 6, 1, "", "metric"], [31, 6, 1, "", "ood"], [31, 3, 1, "", "report"], [31, 6, 1, "", "summary"], [31, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.regression": [[33, 0, 0, "-", "label"]], "cleanlab.datalab.internal.issue_manager.regression.label": [[33, 2, 1, "", "RegressionLabelIssueManager"], [33, 1, 1, "", "find_issues_with_features"], [33, 1, 1, "", "find_issues_with_predictions"]], "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager": [[33, 3, 1, "", "collect_info"], [33, 6, 1, "", "description"], [33, 3, 1, "", "find_issues"], [33, 6, 1, "", "info"], [33, 6, 1, "", "issue_name"], [33, 6, 1, "", "issue_score_key"], [33, 6, 1, "", "issues"], [33, 3, 1, "", "make_summary"], [33, 3, 1, "", "report"], [33, 6, 1, "", "summary"], [33, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager.underperforming_group": [[34, 2, 1, "", "UnderperformingGroupIssueManager"]], "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager": [[34, 6, 1, "", "NO_UNDERPERFORMING_CLUSTER_ID"], [34, 6, 1, "", "OUTLIER_CLUSTER_LABELS"], [34, 3, 1, "", "collect_info"], [34, 6, 1, "", "description"], [34, 3, 1, "", "filter_cluster_ids"], [34, 3, 1, "", "find_issues"], [34, 3, 1, "", "get_underperforming_clusters"], [34, 6, 1, "", "info"], [34, 6, 1, "", "issue_name"], [34, 6, 1, "", "issue_score_key"], [34, 6, 1, "", "issues"], [34, 3, 1, "", "make_summary"], [34, 3, 1, "", "perform_clustering"], [34, 3, 1, "", "report"], [34, 6, 1, "", "summary"], [34, 6, 1, "", "verbosity_levels"]], "cleanlab.datalab.internal.issue_manager_factory": [[17, 7, 1, "", "REGISTRY"], [17, 1, 1, "", "list_default_issue_types"], [17, 1, 1, "", "list_possible_issue_types"], [17, 1, 1, "", "register"]], "cleanlab.datalab.internal.model_outputs": [[35, 2, 1, "", "ModelOutput"], [35, 2, 1, "", "MultiClassPredProbs"], [35, 2, 1, "", "MultiLabelPredProbs"], [35, 2, 1, "", "RegressionPredictions"]], "cleanlab.datalab.internal.model_outputs.ModelOutput": [[35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs": [[35, 6, 1, "", "argument"], [35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs": [[35, 6, 1, "", "argument"], [35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.model_outputs.RegressionPredictions": [[35, 6, 1, "", "argument"], [35, 3, 1, "", "collect"], [35, 6, 1, "", "data"], [35, 3, 1, "", "validate"]], "cleanlab.datalab.internal.report": [[36, 2, 1, "", "Reporter"]], "cleanlab.datalab.internal.report.Reporter": [[36, 3, 1, "", "get_report"], [36, 3, 1, "", "report"]], "cleanlab.datalab.internal.task": [[37, 2, 1, "", "Task"]], "cleanlab.datalab.internal.task.Task": [[37, 6, 1, "", "CLASSIFICATION"], [37, 6, 1, "", "MULTILABEL"], [37, 6, 1, "", "REGRESSION"], [37, 3, 1, "", "__contains__"], [37, 3, 1, "", "__getitem__"], [37, 3, 1, "", "__iter__"], [37, 3, 1, "", "__len__"], [37, 3, 1, "", "from_str"], [37, 4, 1, "", "is_classification"], [37, 4, 1, "", "is_multilabel"], [37, 4, 1, "", "is_regression"]], "cleanlab.dataset": [[39, 1, 1, "", "find_overlapping_classes"], [39, 1, 1, "", "health_summary"], [39, 1, 1, "", "overall_label_health_score"], [39, 1, 1, "", "rank_classes_by_label_quality"]], "cleanlab.experimental": [[40, 0, 0, "-", "cifar_cnn"], [41, 0, 0, "-", "coteaching"], [43, 0, 0, "-", "label_issues_batched"], [44, 0, 0, "-", "mnist_pytorch"], [45, 0, 0, "-", "span_classification"]], "cleanlab.experimental.cifar_cnn": [[40, 2, 1, "", "CNN"], [40, 1, 1, "", "call_bn"]], "cleanlab.experimental.cifar_cnn.CNN": [[40, 6, 1, "", "T_destination"], [40, 3, 1, "", "__call__"], [40, 3, 1, "", "add_module"], [40, 3, 1, "", "apply"], [40, 3, 1, "", "bfloat16"], [40, 3, 1, "", "buffers"], [40, 6, 1, "", "call_super_init"], [40, 3, 1, "", "children"], [40, 3, 1, "", "compile"], [40, 3, 1, "", "cpu"], [40, 3, 1, "", "cuda"], [40, 3, 1, "", "double"], [40, 6, 1, "", "dump_patches"], [40, 3, 1, "", "eval"], [40, 3, 1, "", "extra_repr"], [40, 3, 1, "", "float"], [40, 3, 1, "id0", "forward"], [40, 3, 1, "", "get_buffer"], [40, 3, 1, "", "get_extra_state"], [40, 3, 1, "", "get_parameter"], [40, 3, 1, "", "get_submodule"], [40, 3, 1, "", "half"], [40, 3, 1, "", "ipu"], [40, 3, 1, "", "load_state_dict"], [40, 3, 1, "", "modules"], [40, 3, 1, "", "named_buffers"], [40, 3, 1, "", "named_children"], [40, 3, 1, "", "named_modules"], [40, 3, 1, "", "named_parameters"], [40, 3, 1, "", "parameters"], [40, 3, 1, "", "register_backward_hook"], [40, 3, 1, "", "register_buffer"], [40, 3, 1, "", "register_forward_hook"], [40, 3, 1, "", "register_forward_pre_hook"], [40, 3, 1, "", "register_full_backward_hook"], [40, 3, 1, "", "register_full_backward_pre_hook"], [40, 3, 1, "", "register_load_state_dict_post_hook"], [40, 3, 1, "", "register_module"], [40, 3, 1, "", "register_parameter"], [40, 3, 1, "", "register_state_dict_pre_hook"], [40, 3, 1, "", "requires_grad_"], [40, 3, 1, "", "set_extra_state"], [40, 3, 1, "", "share_memory"], [40, 3, 1, "", "state_dict"], [40, 3, 1, "", "to"], [40, 3, 1, "", "to_empty"], [40, 3, 1, "", "train"], [40, 6, 1, "", "training"], [40, 3, 1, "", "type"], [40, 3, 1, "", "xpu"], [40, 3, 1, "", "zero_grad"]], "cleanlab.experimental.coteaching": [[41, 1, 1, "", "adjust_learning_rate"], [41, 1, 1, "", "evaluate"], [41, 1, 1, "", "forget_rate_scheduler"], [41, 1, 1, "", "initialize_lr_scheduler"], [41, 1, 1, "", "loss_coteaching"], [41, 1, 1, "", "train"]], "cleanlab.experimental.label_issues_batched": [[43, 2, 1, "", "LabelInspector"], [43, 7, 1, "", "adj_confident_thresholds_shared"], [43, 1, 1, "", "find_label_issues_batched"], [43, 7, 1, "", "labels_shared"], [43, 7, 1, "", "pred_probs_shared"], [43, 1, 1, "", "split_arr"]], "cleanlab.experimental.label_issues_batched.LabelInspector": [[43, 3, 1, "", "get_confident_thresholds"], [43, 3, 1, "", "get_label_issues"], [43, 3, 1, "", "get_num_issues"], [43, 3, 1, "", "get_quality_scores"], [43, 3, 1, "", "score_label_quality"], [43, 3, 1, "", "update_confident_thresholds"]], "cleanlab.experimental.mnist_pytorch": [[44, 2, 1, "", "CNN"], [44, 2, 1, "", "SimpleNet"], [44, 1, 1, "", "get_mnist_dataset"], [44, 1, 1, "", "get_sklearn_digits_dataset"]], "cleanlab.experimental.mnist_pytorch.CNN": [[44, 3, 1, "", "__init_subclass__"], [44, 6, 1, "", "batch_size"], [44, 6, 1, "", "dataset"], [44, 6, 1, "", "epochs"], [44, 3, 1, "id0", "fit"], [44, 3, 1, "", "get_metadata_routing"], [44, 3, 1, "", "get_params"], [44, 6, 1, "", "loader"], [44, 6, 1, "", "log_interval"], [44, 6, 1, "", "lr"], [44, 6, 1, "", "momentum"], [44, 6, 1, "", "no_cuda"], [44, 3, 1, "id1", "predict"], [44, 3, 1, "id4", "predict_proba"], [44, 6, 1, "", "seed"], [44, 3, 1, "", "set_fit_request"], [44, 3, 1, "", "set_params"], [44, 3, 1, "", "set_predict_proba_request"], [44, 3, 1, "", "set_predict_request"], [44, 6, 1, "", "test_batch_size"]], "cleanlab.experimental.mnist_pytorch.SimpleNet": [[44, 6, 1, "", "T_destination"], [44, 3, 1, "", "__call__"], [44, 3, 1, "", "add_module"], [44, 3, 1, "", "apply"], [44, 3, 1, "", "bfloat16"], [44, 3, 1, "", "buffers"], [44, 6, 1, "", "call_super_init"], [44, 3, 1, "", "children"], [44, 3, 1, "", "compile"], [44, 3, 1, "", "cpu"], [44, 3, 1, "", "cuda"], [44, 3, 1, "", "double"], [44, 6, 1, "", "dump_patches"], [44, 3, 1, "", "eval"], [44, 3, 1, "", "extra_repr"], [44, 3, 1, "", "float"], [44, 3, 1, "", "forward"], [44, 3, 1, "", "get_buffer"], [44, 3, 1, "", "get_extra_state"], [44, 3, 1, "", "get_parameter"], [44, 3, 1, "", "get_submodule"], [44, 3, 1, "", "half"], [44, 3, 1, "", "ipu"], [44, 3, 1, "", "load_state_dict"], [44, 3, 1, "", "modules"], [44, 3, 1, "", "named_buffers"], [44, 3, 1, "", "named_children"], [44, 3, 1, "", "named_modules"], [44, 3, 1, "", "named_parameters"], [44, 3, 1, "", "parameters"], [44, 3, 1, "", "register_backward_hook"], [44, 3, 1, "", "register_buffer"], [44, 3, 1, "", "register_forward_hook"], [44, 3, 1, "", "register_forward_pre_hook"], [44, 3, 1, "", "register_full_backward_hook"], [44, 3, 1, "", "register_full_backward_pre_hook"], [44, 3, 1, "", "register_load_state_dict_post_hook"], [44, 3, 1, "", "register_module"], [44, 3, 1, "", "register_parameter"], [44, 3, 1, "", "register_state_dict_pre_hook"], [44, 3, 1, "", "requires_grad_"], [44, 3, 1, "", "set_extra_state"], [44, 3, 1, "", "share_memory"], [44, 3, 1, "", "state_dict"], [44, 3, 1, "", "to"], [44, 3, 1, "", "to_empty"], [44, 3, 1, "", "train"], [44, 6, 1, "", "training"], [44, 3, 1, "", "type"], [44, 3, 1, "", "xpu"], [44, 3, 1, "", "zero_grad"]], "cleanlab.experimental.span_classification": [[45, 1, 1, "", "display_issues"], [45, 1, 1, "", "find_label_issues"], [45, 1, 1, "", "get_label_quality_scores"]], "cleanlab.filter": [[46, 1, 1, "", "find_label_issues"], [46, 1, 1, "", "find_label_issues_using_argmax_confusion_matrix"], [46, 1, 1, "", "find_predicted_neq_given"], [46, 7, 1, "", "pred_probs_by_class"], [46, 7, 1, "", "prune_count_matrix_cols"]], "cleanlab.internal": [[48, 0, 0, "-", "label_quality_utils"], [49, 0, 0, "-", "latent_algebra"], [50, 0, 0, "-", "multiannotator_utils"], [51, 0, 0, "-", "multilabel_scorer"], [52, 0, 0, "-", "multilabel_utils"], [53, 0, 0, "-", "neighbor"], [57, 0, 0, "-", "outlier"], [58, 0, 0, "-", "token_classification_utils"], [59, 0, 0, "-", "util"], [60, 0, 0, "-", "validation"]], "cleanlab.internal.label_quality_utils": [[48, 1, 1, "", "get_normalized_entropy"]], "cleanlab.internal.latent_algebra": [[49, 1, 1, "", "compute_inv_noise_matrix"], [49, 1, 1, "", "compute_noise_matrix_from_inverse"], [49, 1, 1, "", "compute_ps_py_inv_noise_matrix"], [49, 1, 1, "", "compute_py"], [49, 1, 1, "", "compute_py_inv_noise_matrix"], [49, 1, 1, "", "compute_pyx"]], "cleanlab.internal.multiannotator_utils": [[50, 1, 1, "", "assert_valid_inputs_multiannotator"], [50, 1, 1, "", "assert_valid_pred_probs"], [50, 1, 1, "", "check_consensus_label_classes"], [50, 1, 1, "", "compute_soft_cross_entropy"], [50, 1, 1, "", "find_best_temp_scaler"], [50, 1, 1, "", "format_multiannotator_labels"], [50, 1, 1, "", "temp_scale_pred_probs"]], "cleanlab.internal.multilabel_scorer": [[51, 2, 1, "", "Aggregator"], [51, 2, 1, "", "ClassLabelScorer"], [51, 2, 1, "", "MultilabelScorer"], [51, 1, 1, "", "exponential_moving_average"], [51, 1, 1, "", "get_cross_validated_multilabel_pred_probs"], [51, 1, 1, "", "get_label_quality_scores"], [51, 1, 1, "", "multilabel_py"], [51, 1, 1, "", "softmin"]], "cleanlab.internal.multilabel_scorer.Aggregator": [[51, 3, 1, "", "__call__"], [51, 6, 1, "", "possible_methods"]], "cleanlab.internal.multilabel_scorer.ClassLabelScorer": [[51, 6, 1, "", "CONFIDENCE_WEIGHTED_ENTROPY"], [51, 6, 1, "", "NORMALIZED_MARGIN"], [51, 6, 1, "", "SELF_CONFIDENCE"], [51, 3, 1, "", "__call__"], [51, 3, 1, "", "__contains__"], [51, 3, 1, "", "__getitem__"], [51, 3, 1, "", "__iter__"], [51, 3, 1, "", "__len__"], [51, 3, 1, "", "from_str"]], "cleanlab.internal.multilabel_scorer.MultilabelScorer": [[51, 3, 1, "", "__call__"], [51, 3, 1, "", "aggregate"], [51, 3, 1, "", "get_class_label_quality_scores"]], "cleanlab.internal.multilabel_utils": [[52, 1, 1, "", "get_onehot_num_classes"], [52, 1, 1, "", "int2onehot"], [52, 1, 1, "", "onehot2int"], [52, 1, 1, "", "stack_complement"]], "cleanlab.internal.neighbor": [[54, 0, 0, "-", "knn_graph"], [55, 0, 0, "-", "metric"], [56, 0, 0, "-", "search"]], "cleanlab.internal.neighbor.knn_graph": [[54, 7, 1, "", "DEFAULT_K"], [54, 1, 1, "", "construct_knn_graph_from_index"], [54, 1, 1, "", "correct_knn_distances_and_indices"], [54, 1, 1, "", "correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace"], [54, 1, 1, "", "correct_knn_graph"], [54, 1, 1, "", "create_knn_graph_and_index"], [54, 1, 1, "", "features_to_knn"]], "cleanlab.internal.neighbor.metric": [[55, 7, 1, "", "HIGH_DIMENSION_CUTOFF"], [55, 7, 1, "", "ROW_COUNT_CUTOFF"], [55, 1, 1, "", "decide_default_metric"], [55, 1, 1, "", "decide_euclidean_metric"]], "cleanlab.internal.neighbor.search": [[56, 1, 1, "", "construct_knn"]], "cleanlab.internal.outlier": [[57, 1, 1, "", "correct_precision_errors"], [57, 1, 1, "", "transform_distances_to_scores"]], "cleanlab.internal.token_classification_utils": [[58, 1, 1, "", "color_sentence"], [58, 1, 1, "", "filter_sentence"], [58, 1, 1, "", "get_sentence"], [58, 1, 1, "", "mapping"], [58, 1, 1, "", "merge_probs"], [58, 1, 1, "", "process_token"]], "cleanlab.internal.util": [[59, 1, 1, "", "append_extra_datapoint"], [59, 1, 1, "", "clip_noise_rates"], [59, 1, 1, "", "clip_values"], [59, 1, 1, "", "compress_int_array"], [59, 1, 1, "", "confusion_matrix"], [59, 1, 1, "", "csr_vstack"], [59, 1, 1, "", "estimate_pu_f1"], [59, 1, 1, "", "extract_indices_tf"], [59, 1, 1, "", "force_two_dimensions"], [59, 1, 1, "", "format_labels"], [59, 1, 1, "", "get_missing_classes"], [59, 1, 1, "", "get_num_classes"], [59, 1, 1, "", "get_unique_classes"], [59, 1, 1, "", "is_tensorflow_dataset"], [59, 1, 1, "", "is_torch_dataset"], [59, 1, 1, "", "num_unique_classes"], [59, 1, 1, "", "print_inverse_noise_matrix"], [59, 1, 1, "", "print_joint_matrix"], [59, 1, 1, "", "print_noise_matrix"], [59, 1, 1, "", "print_square_matrix"], [59, 1, 1, "", "remove_noise_from_class"], [59, 1, 1, "", "round_preserving_row_totals"], [59, 1, 1, "", "round_preserving_sum"], [59, 1, 1, "", "smart_display_dataframe"], [59, 1, 1, "", "subset_X_y"], [59, 1, 1, "", "subset_data"], [59, 1, 1, "", "subset_labels"], [59, 1, 1, "", "train_val_split"], [59, 1, 1, "", "unshuffle_tensorflow_dataset"], [59, 1, 1, "", "value_counts"], [59, 1, 1, "", "value_counts_fill_missing_classes"]], "cleanlab.internal.validation": [[60, 1, 1, "", "assert_indexing_works"], [60, 1, 1, "", "assert_nonempty_input"], [60, 1, 1, "", "assert_valid_class_labels"], [60, 1, 1, "", "assert_valid_inputs"], [60, 1, 1, "", "labels_to_array"], [60, 1, 1, "", "labels_to_list_multilabel"]], "cleanlab.models": [[62, 0, 0, "-", "keras"]], "cleanlab.models.keras": [[62, 2, 1, "", "KerasWrapperModel"], [62, 2, 1, "", "KerasWrapperSequential"]], "cleanlab.models.keras.KerasWrapperModel": [[62, 3, 1, "", "fit"], [62, 3, 1, "", "get_params"], [62, 3, 1, "", "predict"], [62, 3, 1, "", "predict_proba"], [62, 3, 1, "", "set_params"], [62, 3, 1, "", "summary"]], "cleanlab.models.keras.KerasWrapperSequential": [[62, 3, 1, "", "fit"], [62, 3, 1, "", "get_params"], [62, 3, 1, "", "predict"], [62, 3, 1, "", "predict_proba"], [62, 3, 1, "", "set_params"], [62, 3, 1, "", "summary"]], "cleanlab.multiannotator": [[63, 1, 1, "", "convert_long_to_wide_dataset"], [63, 1, 1, "", "get_active_learning_scores"], [63, 1, 1, "", "get_active_learning_scores_ensemble"], [63, 1, 1, "", "get_label_quality_multiannotator"], [63, 1, 1, "", "get_label_quality_multiannotator_ensemble"], [63, 1, 1, "", "get_majority_vote_label"]], "cleanlab.multilabel_classification": [[64, 0, 0, "-", "dataset"], [65, 0, 0, "-", "filter"], [67, 0, 0, "-", "rank"]], "cleanlab.multilabel_classification.dataset": [[64, 1, 1, "", "common_multilabel_issues"], [64, 1, 1, "", "multilabel_health_summary"], [64, 1, 1, "", "overall_multilabel_health_score"], [64, 1, 1, "", "rank_classes_by_multilabel_quality"]], "cleanlab.multilabel_classification.filter": [[65, 1, 1, "", "find_label_issues"], [65, 1, 1, "", "find_multilabel_issues_per_class"]], "cleanlab.multilabel_classification.rank": [[67, 1, 1, "", "get_label_quality_scores"], [67, 1, 1, "", "get_label_quality_scores_per_class"]], "cleanlab.object_detection": [[68, 0, 0, "-", "filter"], [70, 0, 0, "-", "rank"], [71, 0, 0, "-", "summary"]], "cleanlab.object_detection.filter": [[68, 1, 1, "", "find_label_issues"]], "cleanlab.object_detection.rank": [[70, 1, 1, "", "compute_badloc_box_scores"], [70, 1, 1, "", "compute_overlooked_box_scores"], [70, 1, 1, "", "compute_swap_box_scores"], [70, 1, 1, "", "get_label_quality_scores"], [70, 1, 1, "", "issues_from_scores"], [70, 1, 1, "", "pool_box_scores_per_image"]], "cleanlab.object_detection.summary": [[71, 1, 1, "", "bounding_box_size_distribution"], [71, 1, 1, "", "calculate_per_class_metrics"], [71, 1, 1, "", "class_label_distribution"], [71, 1, 1, "", "get_average_per_class_confusion_matrix"], [71, 1, 1, "", "get_sorted_bbox_count_idxs"], [71, 1, 1, "", "object_counts_per_image"], [71, 1, 1, "", "plot_class_distribution"], [71, 1, 1, "", "plot_class_size_distributions"], [71, 1, 1, "", "visualize"]], "cleanlab.outlier": [[72, 2, 1, "", "OutOfDistribution"]], "cleanlab.outlier.OutOfDistribution": [[72, 3, 1, "", "fit"], [72, 3, 1, "", "fit_score"], [72, 3, 1, "", "score"]], "cleanlab.rank": [[73, 1, 1, "", "find_top_issues"], [73, 1, 1, "", "get_confidence_weighted_entropy_for_each_label"], [73, 1, 1, "", "get_label_quality_ensemble_scores"], [73, 1, 1, "", "get_label_quality_scores"], [73, 1, 1, "", "get_normalized_margin_for_each_label"], [73, 1, 1, "", "get_self_confidence_for_each_label"], [73, 1, 1, "", "order_label_issues"]], "cleanlab.regression": [[75, 0, 0, "-", "learn"], [76, 0, 0, "-", "rank"]], "cleanlab.regression.learn": [[75, 2, 1, "", "CleanLearning"]], "cleanlab.regression.learn.CleanLearning": [[75, 3, 1, "", "__init_subclass__"], [75, 3, 1, "", "find_label_issues"], [75, 3, 1, "", "fit"], [75, 3, 1, "", "get_aleatoric_uncertainty"], [75, 3, 1, "", "get_epistemic_uncertainty"], [75, 3, 1, "", "get_label_issues"], [75, 3, 1, "", "get_metadata_routing"], [75, 3, 1, "", "get_params"], [75, 3, 1, "", "predict"], [75, 3, 1, "", "save_space"], [75, 3, 1, "", "score"], [75, 3, 1, "", "set_fit_request"], [75, 3, 1, "", "set_params"], [75, 3, 1, "", "set_score_request"]], "cleanlab.regression.rank": [[76, 1, 1, "", "get_label_quality_scores"]], "cleanlab.segmentation": [[77, 0, 0, "-", "filter"], [79, 0, 0, "-", "rank"], [80, 0, 0, "-", "summary"]], "cleanlab.segmentation.filter": [[77, 1, 1, "", "find_label_issues"]], "cleanlab.segmentation.rank": [[79, 1, 1, "", "get_label_quality_scores"], [79, 1, 1, "", "issues_from_scores"]], "cleanlab.segmentation.summary": [[80, 1, 1, "", "common_label_issues"], [80, 1, 1, "", "display_issues"], [80, 1, 1, "", "filter_by_class"]], "cleanlab.token_classification": [[81, 0, 0, "-", "filter"], [83, 0, 0, "-", "rank"], [84, 0, 0, "-", "summary"]], "cleanlab.token_classification.filter": [[81, 1, 1, "", "find_label_issues"]], "cleanlab.token_classification.rank": [[83, 1, 1, "", "get_label_quality_scores"], [83, 1, 1, "", "issues_from_scores"]], "cleanlab.token_classification.summary": [[84, 1, 1, "", "common_label_issues"], [84, 1, 1, "", "display_issues"], [84, 1, 1, "", "filter_by_token"]]}, "objtypes": {"0": "py:module", "1": "py:function", "2": "py:class", "3": "py:method", "4": "py:property", "5": "py:exception", "6": "py:attribute", "7": "py:data"}, "objnames": {"0": ["py", "module", "Python module"], "1": ["py", "function", "Python function"], "2": ["py", "class", "Python class"], "3": ["py", "method", "Python method"], "4": ["py", "property", "Python property"], "5": ["py", "exception", "Python exception"], "6": ["py", "attribute", "Python attribute"], "7": ["py", "data", "Python data"]}, "titleterms": {"benchmark": 0, "noise_gener": 1, "classif": [2, 88, 89, 93, 95, 96, 99, 101, 104, 110], "count": [3, 101], "data_valu": [4, 21], "datalab": [5, 7, 9, 10, 12, 90, 91, 92, 93, 94, 95, 96, 97, 99, 101, 104], "creat": [7, 91, 92, 101, 103], "your": [7, 85, 91, 92, 96, 97, 99, 101], "own": 7, "issu": [7, 9, 10, 24, 33, 85, 88, 90, 91, 92, 93, 95, 96, 97, 98, 99, 100, 101, 104, 105, 109, 110], "manag": [7, 24], "prerequisit": 7, "implement": 7, "issuemanag": [7, 91], "basic": 7, "check": [7, 85, 97, 100], "intermedi": 7, "advanc": [7, 91], "us": [7, 88, 89, 90, 92, 93, 95, 96, 97, 99, 100, 101, 103, 104, 105, 106, 108, 109, 110], "gener": [8, 97], "cluster": [8, 97, 99], "id": 8, "guid": [9, 12], "type": [9, 10, 101], "custom": [9, 91], "cleanlab": [9, 10, 85, 88, 89, 90, 93, 95, 96, 99, 101, 103, 104, 105, 106, 108, 109, 110], "studio": [9, 10], "easi": [9, 10, 85, 93], "mode": [9, 10, 85, 93], "can": [10, 92, 98, 99, 101, 103], "detect": [10, 90, 92, 93, 95, 96, 97, 99, 101, 105, 106], "estim": [10, 101, 103, 104], "each": 10, "input": 10, "label": [10, 26, 28, 33, 85, 88, 89, 90, 92, 93, 95, 96, 98, 99, 101, 103, 104, 105, 108, 109, 110], "is_label_issu": 10, "label_scor": 10, "given_label": 10, "predicted_label": 10, "outlier": [10, 31, 57, 72, 93, 95, 96, 104, 106], "is_outlier_issu": 10, "outlier_scor": 10, "Near": [10, 92, 93, 95, 96], "duplic": [10, 22, 92, 93, 95, 96, 99, 104], "is_near_duplicate_issu": 10, "near_duplicate_scor": 10, "near_duplicate_set": 10, "distance_to_nearest_neighbor": 10, "non": [10, 96, 97], "iid": [10, 96, 97], "is_non_iid_issu": 10, "non_iid_scor": 10, "class": [10, 86, 97, 101, 109], "imbal": [10, 23, 97], "is_class_imbalance_issu": 10, "class_imbalance_scor": 10, "imag": [10, 93, 97, 106], "specif": [10, 24, 109], "spuriou": [10, 97], "correl": [10, 97], "between": 10, "properti": 10, "score": [10, 97, 101, 103, 104, 105, 109, 110], "underperform": [10, 97, 99], "group": [10, 97, 99], "is_underperforming_group_issu": 10, "underperforming_group_scor": 10, "null": [10, 30, 97], "is_null_issu": 10, "null_scor": 10, "data": [10, 15, 85, 88, 89, 90, 91, 92, 95, 96, 97, 98, 99, 100, 101, 103, 104, 105, 106, 107, 108, 109, 110], "valuat": [10, 97], "is_data_valuation_issu": 10, "data_valuation_scor": 10, "option": [10, 97], "paramet": [10, 101], "get": [12, 91, 92, 103, 104, 105, 109, 110], "start": [12, 98], "api": 12, "refer": 12, "imagelab": 13, "adapt": 14, "data_issu": 16, "factori": 17, "intern": [18, 47], "issue_find": 19, "issue_manag": [24, 25], "regist": 24, "ml": [24, 99, 100, 101], "task": [24, 37], "multilabel": 27, "noniid": 29, "regress": [32, 74, 75, 76, 99, 108], "prioriti": 33, "order": 33, "find": [33, 88, 89, 90, 92, 93, 95, 96, 97, 99, 101, 103, 104, 105, 106, 108, 109, 110], "underperforming_group": 34, "model_output": 35, "report": [36, 93], "dataset": [39, 64, 85, 89, 90, 92, 93, 96, 97, 98, 99, 101, 104, 105, 106, 108, 109, 110], "cifar_cnn": 40, "coteach": 41, "experiment": 42, "label_issues_batch": 43, "mnist_pytorch": 44, "span_classif": 45, "filter": [46, 65, 68, 77, 81, 101], "label_quality_util": 48, "latent_algebra": 49, "multiannotator_util": 50, "multilabel_scor": 51, "multilabel_util": 52, "neighbor": 53, "knn_graph": 54, "metric": 55, "search": [56, 91], "token_classification_util": 58, "util": 59, "valid": [60, 93, 107], "model": [61, 85, 88, 89, 90, 93, 95, 96, 99, 100, 101, 103, 104, 105, 106, 108], "kera": 62, "multiannot": [63, 103], "multilabel_classif": 66, "rank": [67, 70, 73, 76, 79, 83, 101], "object_detect": 69, "summari": [71, 80, 84], "learn": [75, 92, 99, 101], "segment": [78, 109], "token_classif": [82, 110], "open": [85, 99], "sourc": [85, 99], "document": 85, "quickstart": 85, "1": [85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 108, 109, 110], "instal": [85, 88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "2": [85, 86, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 108, 109, 110], "all": [85, 92, 101], "sort": [85, 97], "3": [85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 104, 105, 106, 108, 109, 110], "handl": [85, 99], "error": [85, 89, 93, 99, 101, 103, 104, 105, 108, 109, 110], "train": [85, 88, 89, 90, 97, 99, 100, 106, 108], "robust": [85, 88, 89, 101, 108], "noisi": [85, 88, 89, 100, 101, 108], "4": [85, 88, 89, 90, 91, 92, 93, 95, 96, 97, 100, 101, 103, 105, 106, 108], "curat": [85, 100], "fix": [85, 99], "level": [85, 98, 101, 110], "5": [85, 88, 90, 92, 93, 95, 97, 100, 101, 103, 108], "improv": [85, 100, 103], "via": [85, 100, 101, 103], "mani": [85, 101], "other": [85, 103, 105, 108], "techniqu": [85, 100], "contribut": 85, "how": [86, 99, 101, 103, 104, 110], "migrat": 86, "version": 86, "0": 86, "from": [86, 88, 89, 91, 92, 100, 101, 108], "pre": [86, 90, 97, 99, 106], "function": [86, 91], "name": 86, "chang": 86, "modul": [86, 101], "new": 86, "remov": 86, "common": [86, 110], "argument": [86, 91], "variabl": 86, "cleanlearn": [87, 99, 101], "tutori": [87, 94, 98, 100, 102], "structur": 88, "tabular": [88, 95], "requir": [88, 89, 91, 92, 93, 95, 96, 103, 104, 105, 106, 108, 109, 110], "depend": [88, 89, 90, 91, 92, 93, 95, 96, 98, 100, 101, 103, 104, 105, 106, 108, 109, 110], "load": [88, 89, 90, 91, 92, 95, 96, 97, 108], "process": [88, 95, 106, 108], "select": [88, 95], "comput": [88, 90, 93, 95, 96, 97, 99, 100, 103, 107], "out": [88, 90, 91, 92, 93, 95, 96, 100, 103, 107], "sampl": [88, 90, 91, 92, 93, 95, 96, 100, 103, 107], "predict": [88, 90, 91, 92, 93, 95, 96, 97, 100, 103, 104, 105, 107], "probabl": [88, 90, 91, 92, 93, 95, 96, 97, 100, 103, 107], "more": [88, 89, 92, 101, 108], "spend": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "too": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "much": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "time": [88, 89, 92, 95, 96, 98, 101, 104, 106, 107, 108], "qualiti": [88, 89, 92, 95, 96, 98, 101, 103, 104, 105, 106, 107, 108, 109, 110], "text": [89, 96, 97, 110], "format": [89, 96, 99, 104, 105], "defin": [89, 93, 96, 97, 108], "potenti": [89, 103, 108], "an": [90, 93, 99], "audio": 90, "import": [90, 91, 92, 93, 98, 101, 103], "them": [90, 98, 100, 101], "speechbrain": 90, "featur": [90, 93, 106], "fit": 90, "linear": 90, "workflow": [91, 97, 101], "audit": [91, 92], "classifi": [91, 92, 97], "instanti": 91, "object": [91, 105], "increment": 91, "specifi": [91, 99], "nondefault": 91, "save": 91, "ad": 91, "A": 92, "unifi": 92, "kind": [92, 105], "skip": [92, 98, 101, 103], "detail": [92, 98, 101, 103], "about": 92, "addit": 92, "inform": [92, 93], "fetch": [93, 98], "normal": 93, "fashion": 93, "mnist": 93, "prepar": [93, 97], "k": [93, 95, 107], "fold": [93, 107], "cross": [93, 107], "embed": [93, 106], "7": [93, 100, 101], "view": 93, "most": [93, 110], "like": 93, "exampl": [93, 99, 101, 106], "sever": 93, "set": [93, 101], "dark": 93, "top": [93, 109], "low": 93, "numer": 95, "categor": [95, 97], "column": 95, "construct": 95, "nearest": 95, "neighbour": 95, "graph": [95, 97], "drift": [96, 104], "miscellan": 97, "acceler": 97, "knn": 97, "obtain": 97, "identifi": [97, 99, 100, 105], "explan": 97, "vector": 97, "perform": [97, 100], "visual": [97, 101, 105, 106, 109], "synthet": 97, "result": 97, "predefin": 97, "slice": [97, 99], "i": [97, 99, 101, 107], "catch": 97, "valu": 97, "encod": 97, "initi": [97, 103], "6": [97, 100, 101], "run": [97, 99], "analysi": [97, 105], "interpret": 97, "understand": 98, "evalu": [98, 100], "health": [98, 101], "8": [98, 100, 101], "popular": 98, "faq": 99, "what": [99, 101, 107], "do": [99, 101], "infer": 99, "correct": [99, 100], "ha": 99, "flag": 99, "should": 99, "v": [99, 100], "test": [99, 100, 101, 106], "big": 99, "limit": 99, "memori": 99, "why": [99, 100], "isn": 99, "t": 99, "work": [99, 101, 103, 110], "me": 99, "differ": [99, 105], "clean": [99, 100, 101], "final": 99, "hyperparamet": [99, 100], "tune": 99, "onli": 99, "one": [99, 101, 104, 109], "doe": [99, 103, 110], "take": 99, "so": 99, "long": 99, "when": [99, 101], "licens": 99, "under": 99, "answer": 99, "question": 99, "split": 100, "did": 100, "you": [100, 101], "make": 100, "thi": [100, 101], "preprocess": 100, "fundament": 100, "problem": 100, "setup": 100, "origin": 100, "baselin": 100, "manual": 100, "address": 100, "algorithm": 100, "better": [100, 103], "strategi": 100, "optim": 100, "9": 100, "conclus": 100, "The": 101, "centric": 101, "ai": 101, "machin": 101, "find_label_issu": 101, "line": 101, "code": 101, "twenti": 101, "lowest": 101, "see": 101, "now": 101, "let": 101, "": 101, "happen": 101, "we": 101, "merg": 101, "seafoam": 101, "green": 101, "yellow": 101, "re": 101, "One": 101, "rule": 101, "overal": [101, 109], "accur": 101, "directli": 101, "fulli": 101, "character": 101, "nois": 101, "matrix": [101, 104], "joint": 101, "prior": 101, "true": 101, "distribut": 101, "flip": 101, "rate": 101, "ani": 101, "again": 101, "support": 101, "lot": 101, "method": 101, "filter_bi": 101, "automat": 101, "everi": 101, "uniqu": 101, "num_label_issu": 101, "threshold": 101, "found": 101, "Not": 101, "sure": 101, "ensembl": 101, "multipl": [101, 103], "predictor": 101, "consensu": 103, "annot": 103, "major": 103, "vote": 103, "statist": 103, "compar": 103, "inspect": 103, "retrain": 103, "further": 103, "multi": 104, "beyond": 104, "mislabel": [104, 109, 110], "given": 104, "hot": 104, "binari": 104, "without": 104, "applic": 104, "real": 104, "download": [105, 109, 110], "objectlab": 105, "exploratori": 105, "pytorch": 106, "timm": 106, "cifar10": 106, "some": 106, "pred_prob": [106, 109, 110], "wai": 108, "semant": 109, "which": 109, "ar": 109, "commonli": 109, "focus": 109, "token": 110, "word": 110, "sentenc": 110, "contain": 110, "particular": 110}, "envversion": {"sphinx.domains.c": 3, "sphinx.domains.changeset": 1, "sphinx.domains.citation": 1, "sphinx.domains.cpp": 9, "sphinx.domains.index": 1, "sphinx.domains.javascript": 3, "sphinx.domains.math": 2, "sphinx.domains.python": 4, "sphinx.domains.rst": 2, "sphinx.domains.std": 2, "nbsphinx": 4, "sphinx.ext.viewcode": 1, "sphinx.ext.todo": 2, "sphinx": 58}, "alltitles": {"benchmarking": [[0, "module-cleanlab.benchmarking"]], "noise_generation": [[1, "module-cleanlab.benchmarking.noise_generation"]], "classification": [[2, "module-cleanlab.classification"]], "count": [[3, "module-cleanlab.count"]], "data_valuation": [[4, "module-cleanlab.data_valuation"], [21, "data-valuation"]], "datalab": [[5, "module-cleanlab.datalab.datalab"], [12, "module-cleanlab.datalab"]], "Creating Your Own Issues Manager": [[7, "creating-your-own-issues-manager"]], "Prerequisites": [[7, "prerequisites"]], "Implementing IssueManagers": [[7, "implementing-issuemanagers"]], "Basic Issue Check": [[7, "basic-issue-check"]], "Intermediate Issue Check": [[7, "intermediate-issue-check"]], "Advanced Issue Check": [[7, "advanced-issue-check"]], "Use with Datalab": [[7, "use-with-datalab"]], "Generating Cluster IDs": [[8, "generating-cluster-ids"]], "Datalab guides": [[9, "datalab-guides"]], "Types of issues": [[9, "types-of-issues"]], "Customizing issue types": [[9, "customizing-issue-types"]], "Cleanlab Studio (Easy Mode)": [[9, "cleanlab-studio-easy-mode"], [10, "cleanlab-studio-easy-mode"]], "Datalab Issue Types": [[10, "datalab-issue-types"]], "Types of issues Datalab can detect": [[10, "types-of-issues-datalab-can-detect"]], "Estimates for Each Issue Type": [[10, "estimates-for-each-issue-type"]], "Inputs to Datalab": [[10, "inputs-to-datalab"]], "Label Issue": [[10, "label-issue"]], "is_label_issue": [[10, "is-label-issue"]], "label_score": [[10, "label-score"]], "given_label": [[10, "given-label"], [10, "id6"]], "predicted_label": [[10, "predicted-label"]], "Outlier Issue": [[10, "outlier-issue"]], "is_outlier_issue": [[10, "is-outlier-issue"]], "outlier_score": [[10, "outlier-score"]], "(Near) Duplicate Issue": [[10, "near-duplicate-issue"]], "is_near_duplicate_issue": [[10, "is-near-duplicate-issue"]], "near_duplicate_score": [[10, "near-duplicate-score"]], "near_duplicate_sets": [[10, "near-duplicate-sets"]], "distance_to_nearest_neighbor": [[10, "distance-to-nearest-neighbor"]], "Non-IID Issue": [[10, "non-iid-issue"]], "is_non_iid_issue": [[10, "is-non-iid-issue"]], "non_iid_score": [[10, "non-iid-score"]], "Class Imbalance Issue": [[10, "class-imbalance-issue"]], "is_class_imbalance_issue": [[10, "is-class-imbalance-issue"]], "class_imbalance_score": [[10, "class-imbalance-score"]], "Image-specific Issues": [[10, "image-specific-issues"]], "Spurious Correlations between image-specific properties and labels": [[10, "spurious-correlations-between-image-specific-properties-and-labels"]], "property": [[10, "property"]], "score": [[10, "score"]], "Underperforming Group Issue": [[10, "underperforming-group-issue"]], "is_underperforming_group_issue": [[10, "is-underperforming-group-issue"]], "underperforming_group_score": [[10, "underperforming-group-score"]], "Null Issue": [[10, "null-issue"]], "is_null_issue": [[10, "is-null-issue"]], "null_score": [[10, "null-score"]], "Data Valuation Issue": [[10, "data-valuation-issue"]], "is_data_valuation_issue": [[10, "is-data-valuation-issue"]], "data_valuation_score": [[10, "data-valuation-score"]], "Optional Issue Parameters": [[10, "optional-issue-parameters"]], "Label Issue Parameters": [[10, "label-issue-parameters"]], "Outlier Issue Parameters": [[10, "outlier-issue-parameters"]], "Duplicate Issue Parameters": [[10, "duplicate-issue-parameters"]], "Non-IID Issue Parameters": [[10, "non-iid-issue-parameters"]], "Imbalance Issue Parameters": [[10, "imbalance-issue-parameters"]], "Underperforming Group Issue Parameters": [[10, "underperforming-group-issue-parameters"]], "Null Issue Parameters": [[10, "null-issue-parameters"]], "Data Valuation Issue Parameters": [[10, "data-valuation-issue-parameters"]], "Image Issue Parameters": [[10, "image-issue-parameters"]], "Spurious Correlations Issue Parameters": [[10, "spurious-correlations-issue-parameters"]], "Getting Started": [[12, "getting-started"]], "Guides": [[12, "guides"]], "API Reference": [[12, "api-reference"]], "imagelab": [[13, "module-cleanlab.datalab.internal.adapter.imagelab"]], "adapter": [[14, "adapter"]], "data": [[15, "module-cleanlab.datalab.internal.data"]], "data_issues": [[16, "module-cleanlab.datalab.internal.data_issues"]], "factory": [[17, "module-cleanlab.datalab.internal.issue_manager_factory"]], "internal": [[18, "internal"], [47, "internal"]], "issue_finder": [[19, "issue-finder"]], "duplicate": [[22, "module-cleanlab.datalab.internal.issue_manager.duplicate"]], "imbalance": [[23, "module-cleanlab.datalab.internal.issue_manager.imbalance"]], "issue_manager": [[24, "issue-manager"], [25, "module-cleanlab.datalab.internal.issue_manager.issue_manager"]], "Registered issue managers": [[24, "registered-issue-managers"]], "ML task-specific issue managers": [[24, "ml-task-specific-issue-managers"]], "label": [[26, "module-cleanlab.datalab.internal.issue_manager.label"], [28, "module-cleanlab.datalab.internal.issue_manager.multilabel.label"], [33, "module-cleanlab.datalab.internal.issue_manager.regression.label"]], "multilabel": [[27, "multilabel"]], "noniid": [[29, "module-cleanlab.datalab.internal.issue_manager.noniid"]], "null": [[30, "null"]], "outlier": [[31, "module-cleanlab.datalab.internal.issue_manager.outlier"], [57, "module-cleanlab.internal.outlier"], [72, "module-cleanlab.outlier"]], "regression": [[32, "regression"], [74, "regression"]], "Priority Order for finding issues:": [[33, null]], "underperforming_group": [[34, "underperforming-group"]], "model_outputs": [[35, "module-cleanlab.datalab.internal.model_outputs"]], "report": [[36, "report"]], "task": [[37, "task"]], "dataset": [[39, "module-cleanlab.dataset"], [64, "module-cleanlab.multilabel_classification.dataset"]], "cifar_cnn": [[40, "module-cleanlab.experimental.cifar_cnn"]], "coteaching": [[41, "module-cleanlab.experimental.coteaching"]], "experimental": [[42, "experimental"]], "label_issues_batched": [[43, "module-cleanlab.experimental.label_issues_batched"]], "mnist_pytorch": [[44, "module-cleanlab.experimental.mnist_pytorch"]], "span_classification": [[45, "module-cleanlab.experimental.span_classification"]], "filter": [[46, "module-cleanlab.filter"], [65, "module-cleanlab.multilabel_classification.filter"], [68, "filter"], [77, "filter"], [81, "module-cleanlab.token_classification.filter"]], "label_quality_utils": [[48, "module-cleanlab.internal.label_quality_utils"]], "latent_algebra": [[49, "module-cleanlab.internal.latent_algebra"]], "multiannotator_utils": [[50, "module-cleanlab.internal.multiannotator_utils"]], "multilabel_scorer": [[51, "module-cleanlab.internal.multilabel_scorer"]], "multilabel_utils": [[52, "module-cleanlab.internal.multilabel_utils"]], "neighbor": [[53, "neighbor"]], "knn_graph": [[54, "module-cleanlab.internal.neighbor.knn_graph"]], "metric": [[55, "module-cleanlab.internal.neighbor.metric"]], "search": [[56, "module-cleanlab.internal.neighbor.search"]], "token_classification_utils": [[58, "module-cleanlab.internal.token_classification_utils"]], "util": [[59, "module-cleanlab.internal.util"]], "validation": [[60, "module-cleanlab.internal.validation"]], "models": [[61, "models"]], "keras": [[62, "module-cleanlab.models.keras"]], "multiannotator": [[63, "module-cleanlab.multiannotator"]], "multilabel_classification": [[66, "multilabel-classification"]], "rank": [[67, "module-cleanlab.multilabel_classification.rank"], [70, "module-cleanlab.object_detection.rank"], [73, "module-cleanlab.rank"], [79, "module-cleanlab.segmentation.rank"], [83, "module-cleanlab.token_classification.rank"]], "object_detection": [[69, "object-detection"]], "summary": [[71, "summary"], [80, "module-cleanlab.segmentation.summary"], [84, "module-cleanlab.token_classification.summary"]], "regression.learn": [[75, "module-cleanlab.regression.learn"]], "regression.rank": [[76, "module-cleanlab.regression.rank"]], "segmentation": [[78, "segmentation"]], "token_classification": [[82, "token-classification"]], "cleanlab open-source documentation": [[85, "cleanlab-open-source-documentation"]], "Quickstart": [[85, "quickstart"]], "1. Install cleanlab": [[85, "install-cleanlab"]], "2. Check your data for all sorts of issues": [[85, "check-your-data-for-all-sorts-of-issues"]], "3. Handle label errors and train robust models with noisy labels": [[85, "handle-label-errors-and-train-robust-models-with-noisy-labels"]], "4. Dataset curation: fix dataset-level issues": [[85, "dataset-curation-fix-dataset-level-issues"]], "5. Improve your data via many other techniques": [[85, "improve-your-data-via-many-other-techniques"]], "Contributing": [[85, "contributing"]], "Easy Mode": [[85, "easy-mode"], [93, "Easy-Mode"]], "How to migrate to versions >= 2.0.0 from pre 1.0.1": [[86, "how-to-migrate-to-versions-2-0-0-from-pre-1-0-1"]], "Function and class name changes": [[86, "function-and-class-name-changes"]], "Module name changes": [[86, "module-name-changes"]], "New modules": [[86, "new-modules"]], "Removed modules": [[86, "removed-modules"]], "Common argument and variable name changes": [[86, "common-argument-and-variable-name-changes"]], "CleanLearning Tutorials": [[87, "cleanlearning-tutorials"]], "Classification with Structured/Tabular Data and Noisy Labels": [[88, "Classification-with-Structured/Tabular-Data-and-Noisy-Labels"]], "1. Install required dependencies": [[88, "1.-Install-required-dependencies"], [89, "1.-Install-required-dependencies"], [95, "1.-Install-required-dependencies"], [96, "1.-Install-required-dependencies"], [108, "1.-Install-required-dependencies"]], "2. Load and process the data": [[88, "2.-Load-and-process-the-data"], [95, "2.-Load-and-process-the-data"], [108, "2.-Load-and-process-the-data"]], "3. Select a classification model and compute out-of-sample predicted probabilities": [[88, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"], [95, "3.-Select-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find label issues": [[88, "4.-Use-cleanlab-to-find-label-issues"]], "5. Train a more robust model from noisy labels": [[88, "5.-Train-a-more-robust-model-from-noisy-labels"]], "Spending too much time on data quality?": [[88, "Spending-too-much-time-on-data-quality?"], [89, "Spending-too-much-time-on-data-quality?"], [92, "Spending-too-much-time-on-data-quality?"], [95, "Spending-too-much-time-on-data-quality?"], [96, "Spending-too-much-time-on-data-quality?"], [98, "Spending-too-much-time-on-data-quality?"], [101, "Spending-too-much-time-on-data-quality?"], [104, "Spending-too-much-time-on-data-quality?"], [106, "Spending-too-much-time-on-data-quality?"], [107, "spending-too-much-time-on-data-quality"], [108, "Spending-too-much-time-on-data-quality?"]], "Text Classification with Noisy Labels": [[89, "Text-Classification-with-Noisy-Labels"]], "2. Load and format the text dataset": [[89, "2.-Load-and-format-the-text-dataset"], [96, "2.-Load-and-format-the-text-dataset"]], "3. Define a classification model and use cleanlab to find potential label errors": [[89, "3.-Define-a-classification-model-and-use-cleanlab-to-find-potential-label-errors"]], "4. Train a more robust model from noisy labels": [[89, "4.-Train-a-more-robust-model-from-noisy-labels"], [108, "4.-Train-a-more-robust-model-from-noisy-labels"]], "Detecting Issues in an Audio Dataset with Datalab": [[90, "Detecting-Issues-in-an-Audio-Dataset-with-Datalab"]], "1. Install dependencies and import them": [[90, "1.-Install-dependencies-and-import-them"]], "2. Load the data": [[90, "2.-Load-the-data"]], "3. Use pre-trained SpeechBrain model to featurize audio": [[90, "3.-Use-pre-trained-SpeechBrain-model-to-featurize-audio"]], "4. Fit linear model and compute out-of-sample predicted probabilities": [[90, "4.-Fit-linear-model-and-compute-out-of-sample-predicted-probabilities"]], "5. Use cleanlab to find label issues": [[90, "5.-Use-cleanlab-to-find-label-issues"], [95, "5.-Use-cleanlab-to-find-label-issues"]], "Datalab: Advanced workflows to audit your data": [[91, "Datalab:-Advanced-workflows-to-audit-your-data"]], "Install and import required dependencies": [[91, "Install-and-import-required-dependencies"]], "Create and load the data": [[91, "Create-and-load-the-data"]], "Get out-of-sample predicted probabilities from a classifier": [[91, "Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "Instantiate Datalab object": [[91, "Instantiate-Datalab-object"]], "Functionality 1: Incremental issue search": [[91, "Functionality-1:-Incremental-issue-search"]], "Functionality 2: Specifying nondefault arguments": [[91, "Functionality-2:-Specifying-nondefault-arguments"]], "Functionality 3: Save and load Datalab objects": [[91, "Functionality-3:-Save-and-load-Datalab-objects"]], "Functionality 4: Adding a custom IssueManager": [[91, "Functionality-4:-Adding-a-custom-IssueManager"]], "Datalab: A unified audit to detect all kinds of issues in data and labels": [[92, "Datalab:-A-unified-audit-to-detect-all-kinds-of-issues-in-data-and-labels"]], "1. Install and import required dependencies": [[92, "1.-Install-and-import-required-dependencies"], [93, "1.-Install-and-import-required-dependencies"], [103, "1.-Install-and-import-required-dependencies"]], "2. Create and load the data (can skip these details)": [[92, "2.-Create-and-load-the-data-(can-skip-these-details)"]], "3. Get out-of-sample predicted probabilities from a classifier": [[92, "3.-Get-out-of-sample-predicted-probabilities-from-a-classifier"]], "4. Use Datalab to find issues in the dataset": [[92, "4.-Use-Datalab-to-find-issues-in-the-dataset"]], "5. Learn more about the issues in your dataset": [[92, "5.-Learn-more-about-the-issues-in-your-dataset"]], "Get additional information": [[92, "Get-additional-information"]], "Near duplicate issues": [[92, "Near-duplicate-issues"], [93, "Near-duplicate-issues"]], "Detecting Issues in an Image Dataset with Datalab": [[93, "Detecting-Issues-in-an-Image-Dataset-with-Datalab"]], "2. Fetch and normalize the Fashion-MNIST dataset": [[93, "2.-Fetch-and-normalize-the-Fashion-MNIST-dataset"]], "3. Define a classification model": [[93, "3.-Define-a-classification-model"]], "4. Prepare the dataset for K-fold cross-validation": [[93, "4.-Prepare-the-dataset-for-K-fold-cross-validation"]], "5. Compute out-of-sample predicted probabilities and feature embeddings": [[93, "5.-Compute-out-of-sample-predicted-probabilities-and-feature-embeddings"]], "7. Use cleanlab to find issues": [[93, "7.-Use-cleanlab-to-find-issues"]], "View report": [[93, "View-report"]], "Label issues": [[93, "Label-issues"], [95, "Label-issues"], [96, "Label-issues"]], "View most likely examples with label errors": [[93, "View-most-likely-examples-with-label-errors"]], "Outlier issues": [[93, "Outlier-issues"], [95, "Outlier-issues"], [96, "Outlier-issues"]], "View most severe outliers": [[93, "View-most-severe-outliers"]], "View sets of near duplicate images": [[93, "View-sets-of-near-duplicate-images"]], "Dark images": [[93, "Dark-images"]], "View top examples of dark images": [[93, "View-top-examples-of-dark-images"]], "Low information images": [[93, "Low-information-images"]], "Datalab Tutorials": [[94, "datalab-tutorials"]], "Detecting Issues in Tabular Data\u00a0(Numeric/Categorical columns) with Datalab": [[95, "Detecting-Issues-in-Tabular-Data\u00a0(Numeric/Categorical-columns)-with-Datalab"]], "4. Construct K nearest neighbours graph": [[95, "4.-Construct-K-nearest-neighbours-graph"]], "Near-duplicate issues": [[95, "Near-duplicate-issues"], [96, "Near-duplicate-issues"]], "Detecting Issues in a Text Dataset with Datalab": [[96, "Detecting-Issues-in-a-Text-Dataset-with-Datalab"]], "3. Define a classification model and compute out-of-sample predicted probabilities": [[96, "3.-Define-a-classification-model-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to find issues in your dataset": [[96, "4.-Use-cleanlab-to-find-issues-in-your-dataset"]], "Non-IID issues (data drift)": [[96, "Non-IID-issues-(data-drift)"]], "Miscellaneous workflows with Datalab": [[97, "Miscellaneous-workflows-with-Datalab"]], "Accelerate Issue Checks with Pre-computed kNN Graphs": [[97, "Accelerate-Issue-Checks-with-Pre-computed-kNN-Graphs"]], "1. Load and Prepare Your Dataset": [[97, "1.-Load-and-Prepare-Your-Dataset"]], "2. Compute kNN Graph": [[97, "2.-Compute-kNN-Graph"]], "3. Train a Classifier and Obtain Predicted Probabilities": [[97, "3.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"]], "4. Identify Data Issues Using Datalab": [[97, "4.-Identify-Data-Issues-Using-Datalab"]], "Explanation:": [[97, "Explanation:"]], "Data Valuation": [[97, "Data-Valuation"]], "1. Load and Prepare the Dataset": [[97, "1.-Load-and-Prepare-the-Dataset"], [97, "id2"], [97, "id5"]], "2. Vectorize the Text Data": [[97, "2.-Vectorize-the-Text-Data"]], "3. Perform Data Valuation with Datalab": [[97, "3.-Perform-Data-Valuation-with-Datalab"]], "4. (Optional) Visualize Data Valuation Scores": [[97, "4.-(Optional)-Visualize-Data-Valuation-Scores"]], "Find Underperforming Groups in a Dataset": [[97, "Find-Underperforming-Groups-in-a-Dataset"]], "1. Generate a Synthetic Dataset": [[97, "1.-Generate-a-Synthetic-Dataset"]], "2. Train a Classifier and Obtain Predicted Probabilities": [[97, "2.-Train-a-Classifier-and-Obtain-Predicted-Probabilities"], [97, "id3"]], "3. (Optional) Cluster the Data": [[97, "3.-(Optional)-Cluster-the-Data"]], "4. Identify Underperforming Groups with Datalab": [[97, "4.-Identify-Underperforming-Groups-with-Datalab"], [97, "id4"]], "5. (Optional) Visualize the Results": [[97, "5.-(Optional)-Visualize-the-Results"]], "Predefining Data Slices for Detecting Underperforming Groups": [[97, "Predefining-Data-Slices-for-Detecting-Underperforming-Groups"]], "3. Define a Data Slice": [[97, "3.-Define-a-Data-Slice"]], "Detect if your dataset is non-IID": [[97, "Detect-if-your-dataset-is-non-IID"]], "2. Detect Non-IID Issues Using Datalab": [[97, "2.-Detect-Non-IID-Issues-Using-Datalab"]], "3. (Optional) Visualize the Results": [[97, "3.-(Optional)-Visualize-the-Results"]], "Catch Null Values in a Dataset": [[97, "Catch-Null-Values-in-a-Dataset"]], "1. Load the Dataset": [[97, "1.-Load-the-Dataset"], [97, "id8"]], "2: Encode Categorical Values": [[97, "2:-Encode-Categorical-Values"]], "3. Initialize Datalab": [[97, "3.-Initialize-Datalab"]], "4. Detect Null Values": [[97, "4.-Detect-Null-Values"]], "5. Sort the Dataset by Null Issues": [[97, "5.-Sort-the-Dataset-by-Null-Issues"]], "6. (Optional) Visualize the Results": [[97, "6.-(Optional)-Visualize-the-Results"]], "Detect class imbalance in your dataset": [[97, "Detect-class-imbalance-in-your-dataset"]], "1. Prepare data": [[97, "1.-Prepare-data"]], "2. Detect class imbalance with Datalab": [[97, "2.-Detect-class-imbalance-with-Datalab"]], "3. (Optional) Visualize class imbalance issues": [[97, "3.-(Optional)-Visualize-class-imbalance-issues"]], "Identify Spurious Correlations in Image Datasets": [[97, "Identify-Spurious-Correlations-in-Image-Datasets"]], "2. Run Datalab Analysis": [[97, "2.-Run-Datalab-Analysis"]], "3. Interpret the Results": [[97, "3.-Interpret-the-Results"]], "Understanding Dataset-level Labeling Issues": [[98, "Understanding-Dataset-level-Labeling-Issues"]], "Install dependencies and import them": [[98, "Install-dependencies-and-import-them"], [101, "Install-dependencies-and-import-them"]], "Fetch the data (can skip these details)": [[98, "Fetch-the-data-(can-skip-these-details)"]], "Start of tutorial: Evaluate the health of 8 popular datasets": [[98, "Start-of-tutorial:-Evaluate-the-health-of-8-popular-datasets"]], "FAQ": [[99, "FAQ"]], "What data can cleanlab detect issues in?": [[99, "What-data-can-cleanlab-detect-issues-in?"]], "How do I format classification labels for cleanlab?": [[99, "How-do-I-format-classification-labels-for-cleanlab?"]], "How do I infer the correct labels for examples cleanlab has flagged?": [[99, "How-do-I-infer-the-correct-labels-for-examples-cleanlab-has-flagged?"]], "How should I handle label errors in train vs. test data?": [[99, "How-should-I-handle-label-errors-in-train-vs.-test-data?"]], "How can I find label issues in big datasets with limited memory?": [[99, "How-can-I-find-label-issues-in-big-datasets-with-limited-memory?"]], "Why isn\u2019t CleanLearning working for me?": [[99, "Why-isn\u2019t-CleanLearning-working-for-me?"]], "How can I use different models for data cleaning vs. final training in CleanLearning?": [[99, "How-can-I-use-different-models-for-data-cleaning-vs.-final-training-in-CleanLearning?"]], "How do I hyperparameter tune only the final model trained (and not the one finding label issues) in CleanLearning?": [[99, "How-do-I-hyperparameter-tune-only-the-final-model-trained-(and-not-the-one-finding-label-issues)-in-CleanLearning?"]], "Why does regression.learn.CleanLearning take so long?": [[99, "Why-does-regression.learn.CleanLearning-take-so-long?"]], "How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?": [[99, "How-do-I-specify-pre-computed-data-slices/clusters-when-detecting-the-Underperforming-Group-Issue?"]], "How to handle near-duplicate data identified by Datalab?": [[99, "How-to-handle-near-duplicate-data-identified-by-Datalab?"]], "What ML models should I run cleanlab with? How do I fix the issues cleanlab has identified?": [[99, "What-ML-models-should-I-run-cleanlab-with?-How-do-I-fix-the-issues-cleanlab-has-identified?"]], "What license is cleanlab open-sourced under?": [[99, "What-license-is-cleanlab-open-sourced-under?"]], "Can\u2019t find an answer to your question?": [[99, "Can't-find-an-answer-to-your-question?"]], "Improving ML Performance via Data Curation with Train vs Test Splits": [[100, "Improving-ML-Performance-via-Data-Curation-with-Train-vs-Test-Splits"]], "Why did you make this tutorial?": [[100, "Why-did-you-make-this-tutorial?"]], "1. Install dependencies": [[100, "1.-Install-dependencies"]], "2. Preprocess the data": [[100, "2.-Preprocess-the-data"]], "3. Check for fundamental problems in the train/test setup": [[100, "3.-Check-for-fundamental-problems-in-the-train/test-setup"]], "4. Train model with original (noisy) training data": [[100, "4.-Train-model-with-original-(noisy)-training-data"]], "Compute out-of-sample predicted probabilities for the test data from this baseline model": [[100, "Compute-out-of-sample-predicted-probabilities-for-the-test-data-from-this-baseline-model"]], "5. Check for issues in test data and manually address them": [[100, "5.-Check-for-issues-in-test-data-and-manually-address-them"]], "Use clean test data to evaluate the performance of model trained on noisy training data": [[100, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-noisy-training-data"]], "6. Check for issues in training data and algorithmically correct them": [[100, "6.-Check-for-issues-in-training-data-and-algorithmically-correct-them"]], "7. Train model on cleaned training data": [[100, "7.-Train-model-on-cleaned-training-data"]], "Use clean test data to evaluate the performance of model trained on cleaned training data": [[100, "Use-clean-test-data-to-evaluate-the-performance-of-model-trained-on-cleaned-training-data"]], "8. Identifying better training data curation strategies via hyperparameter optimization techniques": [[100, "8.-Identifying-better-training-data-curation-strategies-via-hyperparameter-optimization-techniques"]], "9. Conclusion": [[100, "9.-Conclusion"]], "The Workflows of Data-centric AI for Classification with Noisy Labels": [[101, "The-Workflows-of-Data-centric-AI-for-Classification-with-Noisy-Labels"]], "Create the data (can skip these details)": [[101, "Create-the-data-(can-skip-these-details)"]], "Workflow 1: Use Datalab to detect many types of issues": [[101, "Workflow-1:-Use-Datalab-to-detect-many-types-of-issues"]], "Workflow 2: Use CleanLearning for more robust Machine Learning": [[101, "Workflow-2:-Use-CleanLearning-for-more-robust-Machine-Learning"]], "Clean Learning = Machine Learning with cleaned data": [[101, "Clean-Learning-=-Machine-Learning-with-cleaned-data"]], "Workflow 3: Use CleanLearning to find_label_issues in one line of code": [[101, "Workflow-3:-Use-CleanLearning-to-find_label_issues-in-one-line-of-code"]], "Visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[101, "Visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 4: Use cleanlab to find dataset-level and class-level issues": [[101, "Workflow-4:-Use-cleanlab-to-find-dataset-level-and-class-level-issues"]], "Now, let\u2019s see what happens if we merge classes \u201cseafoam green\u201d and \u201cyellow\u201d": [[101, "Now,-let's-see-what-happens-if-we-merge-classes-%22seafoam-green%22-and-%22yellow%22"]], "Workflow 5: Clean your test set too if you\u2019re doing ML with noisy labels!": [[101, "Workflow-5:-Clean-your-test-set-too-if-you're-doing-ML-with-noisy-labels!"]], "Workflow 6: One score to rule them all \u2013 use cleanlab\u2019s overall dataset health score": [[101, "Workflow-6:-One-score-to-rule-them-all----use-cleanlab's-overall-dataset-health-score"]], "How accurate is this dataset health score?": [[101, "How-accurate-is-this-dataset-health-score?"]], "Workflow(s) 7: Use count, rank, filter modules directly": [[101, "Workflow(s)-7:-Use-count,-rank,-filter-modules-directly"]], "Workflow 7.1 (count): Fully characterize label noise (noise matrix, joint, prior of true labels, \u2026)": [[101, "Workflow-7.1-(count):-Fully-characterize-label-noise-(noise-matrix,-joint,-prior-of-true-labels,-...)"]], "Use cleanlab to estimate and visualize the joint distribution of label noise and noise matrix of label flipping rates:": [[101, "Use-cleanlab-to-estimate-and-visualize-the-joint-distribution-of-label-noise-and-noise-matrix-of-label-flipping-rates:"]], "Workflow 7.2 (filter): Find label issues for any dataset and any model in one line of code": [[101, "Workflow-7.2-(filter):-Find-label-issues-for-any-dataset-and-any-model-in-one-line-of-code"]], "Again, we can visualize the twenty examples with lowest label quality to see if Cleanlab works.": [[101, "Again,-we-can-visualize-the-twenty-examples-with-lowest-label-quality-to-see-if-Cleanlab-works."]], "Workflow 7.2 supports lots of methods to find_label_issues() via the filter_by parameter.": [[101, "Workflow-7.2-supports-lots-of-methods-to-find_label_issues()-via-the-filter_by-parameter."]], "Workflow 7.3 (rank): Automatically rank every example by a unique label quality score. Find errors using cleanlab.count.num_label_issues as a threshold.": [[101, "Workflow-7.3-(rank):-Automatically-rank-every-example-by-a-unique-label-quality-score.-Find-errors-using-cleanlab.count.num_label_issues-as-a-threshold."]], "Again, we can visualize the label issues found to see if Cleanlab works.": [[101, "Again,-we-can-visualize-the-label-issues-found-to-see-if-Cleanlab-works."]], "Not sure when to use Workflow 7.2 or 7.3 to find label issues?": [[101, "Not-sure-when-to-use-Workflow-7.2-or-7.3-to-find-label-issues?"]], "Workflow 8: Ensembling label quality scores from multiple predictors": [[101, "Workflow-8:-Ensembling-label-quality-scores-from-multiple-predictors"]], "Tutorials": [[102, "tutorials"]], "Estimate Consensus and Annotator Quality for Data Labeled by Multiple Annotators": [[103, "Estimate-Consensus-and-Annotator-Quality-for-Data-Labeled-by-Multiple-Annotators"]], "2. Create the data (can skip these details)": [[103, "2.-Create-the-data-(can-skip-these-details)"]], "3. Get initial consensus labels via majority vote and compute out-of-sample predicted probabilities": [[103, "3.-Get-initial-consensus-labels-via-majority-vote-and-compute-out-of-sample-predicted-probabilities"]], "4. Use cleanlab to get better consensus labels and other statistics": [[103, "4.-Use-cleanlab-to-get-better-consensus-labels-and-other-statistics"]], "Comparing improved consensus labels": [[103, "Comparing-improved-consensus-labels"]], "Inspecting consensus quality scores to find potential consensus label errors": [[103, "Inspecting-consensus-quality-scores-to-find-potential-consensus-label-errors"]], "5. Retrain model using improved consensus labels": [[103, "5.-Retrain-model-using-improved-consensus-labels"]], "Further improvements": [[103, "Further-improvements"]], "How does cleanlab.multiannotator work?": [[103, "How-does-cleanlab.multiannotator-work?"]], "Find Label Errors in Multi-Label Classification Datasets": [[104, "Find-Label-Errors-in-Multi-Label-Classification-Datasets"]], "1. Install required dependencies and get dataset": [[104, "1.-Install-required-dependencies-and-get-dataset"]], "2. Format data, labels, and model predictions": [[104, "2.-Format-data,-labels,-and-model-predictions"], [105, "2.-Format-data,-labels,-and-model-predictions"]], "3. Use cleanlab to find label issues": [[104, "3.-Use-cleanlab-to-find-label-issues"], [105, "3.-Use-cleanlab-to-find-label-issues"], [109, "3.-Use-cleanlab-to-find-label-issues"], [110, "3.-Use-cleanlab-to-find-label-issues"]], "Label quality scores": [[104, "Label-quality-scores"]], "Data issues beyond mislabeling (outliers, duplicates, drift, \u2026)": [[104, "Data-issues-beyond-mislabeling-(outliers,-duplicates,-drift,-...)"]], "How to format labels given as a one-hot (multi-hot) binary matrix?": [[104, "How-to-format-labels-given-as-a-one-hot-(multi-hot)-binary-matrix?"]], "Estimate label issues without Datalab": [[104, "Estimate-label-issues-without-Datalab"]], "Application to Real Data": [[104, "Application-to-Real-Data"]], "Finding Label Errors in Object Detection Datasets": [[105, "Finding-Label-Errors-in-Object-Detection-Datasets"]], "1. Install required dependencies and download data": [[105, "1.-Install-required-dependencies-and-download-data"], [109, "1.-Install-required-dependencies-and-download-data"], [110, "1.-Install-required-dependencies-and-download-data"]], "Get label quality scores": [[105, "Get-label-quality-scores"], [109, "Get-label-quality-scores"]], "4. Use ObjectLab to visualize label issues": [[105, "4.-Use-ObjectLab-to-visualize-label-issues"]], "Different kinds of label issues identified by ObjectLab": [[105, "Different-kinds-of-label-issues-identified-by-ObjectLab"]], "Other uses of visualize": [[105, "Other-uses-of-visualize"]], "Exploratory data analysis": [[105, "Exploratory-data-analysis"]], "Detect Outliers with Cleanlab and PyTorch Image Models (timm)": [[106, "Detect-Outliers-with-Cleanlab-and-PyTorch-Image-Models-(timm)"]], "1. Install the required dependencies": [[106, "1.-Install-the-required-dependencies"]], "2. Pre-process the Cifar10 dataset": [[106, "2.-Pre-process-the-Cifar10-dataset"]], "Visualize some of the training and test examples": [[106, "Visualize-some-of-the-training-and-test-examples"]], "3. Use cleanlab and feature embeddings to find outliers in the data": [[106, "3.-Use-cleanlab-and-feature-embeddings-to-find-outliers-in-the-data"]], "4. Use cleanlab and pred_probs to find outliers in the data": [[106, "4.-Use-cleanlab-and-pred_probs-to-find-outliers-in-the-data"]], "Computing Out-of-Sample Predicted Probabilities with Cross-Validation": [[107, "computing-out-of-sample-predicted-probabilities-with-cross-validation"]], "Out-of-sample predicted probabilities?": [[107, "out-of-sample-predicted-probabilities"]], "What is K-fold cross-validation?": [[107, "what-is-k-fold-cross-validation"]], "Find Noisy Labels in Regression Datasets": [[108, "Find-Noisy-Labels-in-Regression-Datasets"]], "3. Define a regression model and use cleanlab to find potential label errors": [[108, "3.-Define-a-regression-model-and-use-cleanlab-to-find-potential-label-errors"]], "5. Other ways to find noisy labels in regression datasets": [[108, "5.-Other-ways-to-find-noisy-labels-in-regression-datasets"]], "Find Label Errors in Semantic Segmentation Datasets": [[109, "Find-Label-Errors-in-Semantic-Segmentation-Datasets"]], "2. Get data, labels, and pred_probs": [[109, "2.-Get-data,-labels,-and-pred_probs"], [110, "2.-Get-data,-labels,-and-pred_probs"]], "Visualize top label issues": [[109, "Visualize-top-label-issues"]], "Classes which are commonly mislabeled overall": [[109, "Classes-which-are-commonly-mislabeled-overall"]], "Focusing on one specific class": [[109, "Focusing-on-one-specific-class"]], "Find Label Errors in Token Classification (Text) Datasets": [[110, "Find-Label-Errors-in-Token-Classification-(Text)-Datasets"]], "Most common word-level token mislabels": [[110, "Most-common-word-level-token-mislabels"]], "Find sentences containing a particular mislabeled word": [[110, "Find-sentences-containing-a-particular-mislabeled-word"]], "Sentence label quality score": [[110, "Sentence-label-quality-score"]], "How does cleanlab.token_classification work?": [[110, "How-does-cleanlab.token_classification-work?"]]}, "indexentries": {"cleanlab.benchmarking": [[0, "module-cleanlab.benchmarking"]], "module": [[0, "module-cleanlab.benchmarking"], [1, "module-cleanlab.benchmarking.noise_generation"], [2, "module-cleanlab.classification"], [3, "module-cleanlab.count"], [4, "module-cleanlab.data_valuation"], [5, "module-cleanlab.datalab.datalab"], [12, "module-cleanlab.datalab"], [13, "module-cleanlab.datalab.internal.adapter.imagelab"], [15, "module-cleanlab.datalab.internal.data"], [16, "module-cleanlab.datalab.internal.data_issues"], [17, "module-cleanlab.datalab.internal.issue_manager_factory"], [18, "module-cleanlab.datalab.internal"], [19, "module-cleanlab.datalab.internal.issue_finder"], [21, "module-cleanlab.datalab.internal.issue_manager.data_valuation"], [22, "module-cleanlab.datalab.internal.issue_manager.duplicate"], [23, "module-cleanlab.datalab.internal.issue_manager.imbalance"], [25, "module-cleanlab.datalab.internal.issue_manager.issue_manager"], [26, "module-cleanlab.datalab.internal.issue_manager.label"], [28, "module-cleanlab.datalab.internal.issue_manager.multilabel.label"], [29, "module-cleanlab.datalab.internal.issue_manager.noniid"], [30, "module-cleanlab.datalab.internal.issue_manager.null"], [31, "module-cleanlab.datalab.internal.issue_manager.outlier"], [33, "module-cleanlab.datalab.internal.issue_manager.regression.label"], [34, "module-cleanlab.datalab.internal.issue_manager.underperforming_group"], [35, "module-cleanlab.datalab.internal.model_outputs"], [36, "module-cleanlab.datalab.internal.report"], [37, "module-cleanlab.datalab.internal.task"], [39, "module-cleanlab.dataset"], [40, "module-cleanlab.experimental.cifar_cnn"], [41, "module-cleanlab.experimental.coteaching"], [42, "module-cleanlab.experimental"], [43, "module-cleanlab.experimental.label_issues_batched"], [44, "module-cleanlab.experimental.mnist_pytorch"], [45, "module-cleanlab.experimental.span_classification"], [46, "module-cleanlab.filter"], [47, "module-cleanlab.internal"], [48, "module-cleanlab.internal.label_quality_utils"], [49, "module-cleanlab.internal.latent_algebra"], [50, "module-cleanlab.internal.multiannotator_utils"], [51, "module-cleanlab.internal.multilabel_scorer"], [52, "module-cleanlab.internal.multilabel_utils"], [53, "module-cleanlab.internal.neighbor"], [54, "module-cleanlab.internal.neighbor.knn_graph"], [55, "module-cleanlab.internal.neighbor.metric"], [56, "module-cleanlab.internal.neighbor.search"], [57, "module-cleanlab.internal.outlier"], [58, "module-cleanlab.internal.token_classification_utils"], [59, "module-cleanlab.internal.util"], [60, "module-cleanlab.internal.validation"], [61, "module-cleanlab.models"], [62, "module-cleanlab.models.keras"], [63, "module-cleanlab.multiannotator"], [64, "module-cleanlab.multilabel_classification.dataset"], [65, "module-cleanlab.multilabel_classification.filter"], [66, "module-cleanlab.multilabel_classification"], [67, "module-cleanlab.multilabel_classification.rank"], [68, "module-cleanlab.object_detection.filter"], [69, "module-cleanlab.object_detection"], [70, "module-cleanlab.object_detection.rank"], [71, "module-cleanlab.object_detection.summary"], [72, "module-cleanlab.outlier"], [73, "module-cleanlab.rank"], [74, "module-cleanlab.regression"], [75, "module-cleanlab.regression.learn"], [76, "module-cleanlab.regression.rank"], [77, "module-cleanlab.segmentation.filter"], [78, "module-cleanlab.segmentation"], [79, "module-cleanlab.segmentation.rank"], [80, "module-cleanlab.segmentation.summary"], [81, "module-cleanlab.token_classification.filter"], [82, "module-cleanlab.token_classification"], [83, "module-cleanlab.token_classification.rank"], [84, "module-cleanlab.token_classification.summary"]], "cleanlab.benchmarking.noise_generation": [[1, "module-cleanlab.benchmarking.noise_generation"]], "generate_n_rand_probabilities_that_sum_to_m() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.generate_n_rand_probabilities_that_sum_to_m"]], "generate_noise_matrix_from_trace() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.generate_noise_matrix_from_trace"]], "generate_noisy_labels() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.generate_noisy_labels"]], "noise_matrix_is_valid() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.noise_matrix_is_valid"]], "randomly_distribute_n_balls_into_k_bins() (in module cleanlab.benchmarking.noise_generation)": [[1, "cleanlab.benchmarking.noise_generation.randomly_distribute_N_balls_into_K_bins"]], "cleanlearning (class in cleanlab.classification)": [[2, "cleanlab.classification.CleanLearning"]], "__init_subclass__() (cleanlab.classification.cleanlearning class method)": [[2, "cleanlab.classification.CleanLearning.__init_subclass__"]], "cleanlab.classification": [[2, "module-cleanlab.classification"]], "find_label_issues() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.find_label_issues"]], "fit() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.fit"]], "get_label_issues() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.get_label_issues"]], "get_metadata_routing() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.get_metadata_routing"]], "get_params() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.get_params"]], "predict() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.predict"]], "predict_proba() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.predict_proba"]], "save_space() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.save_space"]], "score() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.score"]], "set_fit_request() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.set_fit_request"]], "set_params() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.set_params"]], "set_score_request() (cleanlab.classification.cleanlearning method)": [[2, "cleanlab.classification.CleanLearning.set_score_request"]], "calibrate_confident_joint() (in module cleanlab.count)": [[3, "cleanlab.count.calibrate_confident_joint"]], "cleanlab.count": [[3, "module-cleanlab.count"]], "compute_confident_joint() (in module cleanlab.count)": [[3, "cleanlab.count.compute_confident_joint"]], "estimate_confident_joint_and_cv_pred_proba() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_confident_joint_and_cv_pred_proba"]], "estimate_cv_predicted_probabilities() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_cv_predicted_probabilities"]], "estimate_joint() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_joint"]], "estimate_latent() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_latent"]], "estimate_noise_matrices() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_noise_matrices"]], "estimate_py_and_noise_matrices_from_probabilities() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_py_and_noise_matrices_from_probabilities"]], "estimate_py_noise_matrices_and_cv_pred_proba() (in module cleanlab.count)": [[3, "cleanlab.count.estimate_py_noise_matrices_and_cv_pred_proba"]], "get_confident_thresholds() (in module cleanlab.count)": [[3, "cleanlab.count.get_confident_thresholds"]], "num_label_issues() (in module cleanlab.count)": [[3, "cleanlab.count.num_label_issues"]], "cleanlab.data_valuation": [[4, "module-cleanlab.data_valuation"]], "data_shapley_knn() (in module cleanlab.data_valuation)": [[4, "cleanlab.data_valuation.data_shapley_knn"]], "datalab (class in cleanlab.datalab.datalab)": [[5, "cleanlab.datalab.datalab.Datalab"]], "class_names (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.class_names"]], "cleanlab.datalab.datalab": [[5, "module-cleanlab.datalab.datalab"]], "find_issues() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.find_issues"]], "get_info() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.get_info"]], "get_issue_summary() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.get_issue_summary"]], "get_issues() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.get_issues"]], "has_labels (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.has_labels"]], "info (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.info"]], "issue_summary (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.issue_summary"]], "issues (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.issues"]], "labels (cleanlab.datalab.datalab.datalab property)": [[5, "cleanlab.datalab.datalab.Datalab.labels"]], "list_default_issue_types() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.list_default_issue_types"]], "list_possible_issue_types() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.list_possible_issue_types"]], "load() (cleanlab.datalab.datalab.datalab static method)": [[5, "cleanlab.datalab.datalab.Datalab.load"]], "report() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.report"]], "save() (cleanlab.datalab.datalab.datalab method)": [[5, "cleanlab.datalab.datalab.Datalab.save"]], "cleanlab.datalab": [[12, "module-cleanlab.datalab"]], "correlationreporter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationReporter"]], "correlationvisualizer (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationVisualizer"]], "imagelabdataissuesadapter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter"]], "imagelabissuefinderadapter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter"]], "imagelabreporteradapter (class in cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter"]], "cleanlab.datalab.internal.adapter.imagelab": [[13, "module-cleanlab.datalab.internal.adapter.imagelab"]], "collect_issues_from_imagelab() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.collect_issues_from_imagelab"]], "collect_issues_from_issue_manager() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.collect_issues_from_issue_manager"]], "collect_statistics() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.collect_statistics"]], "create_imagelab() (in module cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.create_imagelab"]], "filter_based_on_max_prevalence() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.filter_based_on_max_prevalence"]], "find_issues() (cleanlab.datalab.internal.adapter.imagelab.imagelabissuefinderadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter.find_issues"]], "get_available_issue_types() (cleanlab.datalab.internal.adapter.imagelab.imagelabissuefinderadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabIssueFinderAdapter.get_available_issue_types"]], "get_info() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.get_info"]], "get_issue_summary() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.get_issue_summary"]], "get_issues() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.get_issues"]], "get_report() (cleanlab.datalab.internal.adapter.imagelab.imagelabreporteradapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter.get_report"]], "handle_spurious_correlations() (in module cleanlab.datalab.internal.adapter.imagelab)": [[13, "cleanlab.datalab.internal.adapter.imagelab.handle_spurious_correlations"]], "report() (cleanlab.datalab.internal.adapter.imagelab.correlationreporter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationReporter.report"]], "report() (cleanlab.datalab.internal.adapter.imagelab.imagelabreporteradapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabReporterAdapter.report"]], "set_health_score() (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.set_health_score"]], "statistics (cleanlab.datalab.internal.adapter.imagelab.imagelabdataissuesadapter property)": [[13, "cleanlab.datalab.internal.adapter.imagelab.ImagelabDataIssuesAdapter.statistics"]], "visualize() (cleanlab.datalab.internal.adapter.imagelab.correlationvisualizer method)": [[13, "cleanlab.datalab.internal.adapter.imagelab.CorrelationVisualizer.visualize"]], "data (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.Data"]], "dataformaterror": [[15, "cleanlab.datalab.internal.data.DataFormatError"]], "datasetdicterror": [[15, "cleanlab.datalab.internal.data.DatasetDictError"]], "datasetloaderror": [[15, "cleanlab.datalab.internal.data.DatasetLoadError"]], "label (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.Label"]], "multiclass (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.MultiClass"]], "multilabel (class in cleanlab.datalab.internal.data)": [[15, "cleanlab.datalab.internal.data.MultiLabel"]], "add_note() (cleanlab.datalab.internal.data.dataformaterror method)": [[15, "cleanlab.datalab.internal.data.DataFormatError.add_note"]], "add_note() (cleanlab.datalab.internal.data.datasetdicterror method)": [[15, "cleanlab.datalab.internal.data.DatasetDictError.add_note"]], "add_note() (cleanlab.datalab.internal.data.datasetloaderror method)": [[15, "cleanlab.datalab.internal.data.DatasetLoadError.add_note"]], "args (cleanlab.datalab.internal.data.dataformaterror attribute)": [[15, "cleanlab.datalab.internal.data.DataFormatError.args"]], "args (cleanlab.datalab.internal.data.datasetdicterror attribute)": [[15, "cleanlab.datalab.internal.data.DatasetDictError.args"]], "args (cleanlab.datalab.internal.data.datasetloaderror attribute)": [[15, "cleanlab.datalab.internal.data.DatasetLoadError.args"]], "class_names (cleanlab.datalab.internal.data.data property)": [[15, "cleanlab.datalab.internal.data.Data.class_names"]], "class_names (cleanlab.datalab.internal.data.label property)": [[15, "cleanlab.datalab.internal.data.Label.class_names"]], "class_names (cleanlab.datalab.internal.data.multiclass property)": [[15, "cleanlab.datalab.internal.data.MultiClass.class_names"]], "class_names (cleanlab.datalab.internal.data.multilabel property)": [[15, "cleanlab.datalab.internal.data.MultiLabel.class_names"]], "cleanlab.datalab.internal.data": [[15, "module-cleanlab.datalab.internal.data"]], "has_labels (cleanlab.datalab.internal.data.data property)": [[15, "cleanlab.datalab.internal.data.Data.has_labels"]], "is_available (cleanlab.datalab.internal.data.label property)": [[15, "cleanlab.datalab.internal.data.Label.is_available"]], "is_available (cleanlab.datalab.internal.data.multiclass property)": [[15, "cleanlab.datalab.internal.data.MultiClass.is_available"]], "is_available (cleanlab.datalab.internal.data.multilabel property)": [[15, "cleanlab.datalab.internal.data.MultiLabel.is_available"]], "with_traceback() (cleanlab.datalab.internal.data.dataformaterror method)": [[15, "cleanlab.datalab.internal.data.DataFormatError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetdicterror method)": [[15, "cleanlab.datalab.internal.data.DatasetDictError.with_traceback"]], "with_traceback() (cleanlab.datalab.internal.data.datasetloaderror method)": [[15, "cleanlab.datalab.internal.data.DatasetLoadError.with_traceback"]], "dataissues (class in cleanlab.datalab.internal.data_issues)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues"]], "cleanlab.datalab.internal.data_issues": [[16, "module-cleanlab.datalab.internal.data_issues"]], "collect_issues_from_imagelab() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.collect_issues_from_imagelab"]], "collect_issues_from_issue_manager() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.collect_issues_from_issue_manager"]], "collect_statistics() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.collect_statistics"]], "get_data_statistics() (in module cleanlab.datalab.internal.data_issues)": [[16, "cleanlab.datalab.internal.data_issues.get_data_statistics"]], "get_info() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.get_info"]], "get_issue_summary() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.get_issue_summary"]], "get_issues() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.get_issues"]], "info (cleanlab.datalab.internal.data_issues.dataissues attribute)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.info"]], "issue_summary (cleanlab.datalab.internal.data_issues.dataissues attribute)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.issue_summary"]], "issues (cleanlab.datalab.internal.data_issues.dataissues attribute)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.issues"]], "set_health_score() (cleanlab.datalab.internal.data_issues.dataissues method)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.set_health_score"]], "statistics (cleanlab.datalab.internal.data_issues.dataissues property)": [[16, "cleanlab.datalab.internal.data_issues.DataIssues.statistics"]], "registry (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.REGISTRY"]], "cleanlab.datalab.internal.issue_manager_factory": [[17, "module-cleanlab.datalab.internal.issue_manager_factory"]], "list_default_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.list_default_issue_types"]], "list_possible_issue_types() (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.list_possible_issue_types"]], "register() (in module cleanlab.datalab.internal.issue_manager_factory)": [[17, "cleanlab.datalab.internal.issue_manager_factory.register"]], "cleanlab.datalab.internal": [[18, "module-cleanlab.datalab.internal"]], "issuefinder (class in cleanlab.datalab.internal.issue_finder)": [[19, "cleanlab.datalab.internal.issue_finder.IssueFinder"]], "cleanlab.datalab.internal.issue_finder": [[19, "module-cleanlab.datalab.internal.issue_finder"]], "find_issues() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[19, "cleanlab.datalab.internal.issue_finder.IssueFinder.find_issues"]], "get_available_issue_types() (cleanlab.datalab.internal.issue_finder.issuefinder method)": [[19, "cleanlab.datalab.internal.issue_finder.IssueFinder.get_available_issue_types"]], "default_threshold (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.DEFAULT_THRESHOLD"]], "datavaluationissuemanager (class in cleanlab.datalab.internal.issue_manager.data_valuation)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager"]], "cleanlab.datalab.internal.issue_manager.data_valuation": [[21, "module-cleanlab.datalab.internal.issue_manager.data_valuation"]], "collect_info() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager class method)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.data_valuation.datavaluationissuemanager attribute)": [[21, "cleanlab.datalab.internal.issue_manager.data_valuation.DataValuationIssueManager.verbosity_levels"]], "nearduplicateissuemanager (class in cleanlab.datalab.internal.issue_manager.duplicate)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager"]], "cleanlab.datalab.internal.issue_manager.duplicate": [[22, "module-cleanlab.datalab.internal.issue_manager.duplicate"]], "collect_info() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.make_summary"]], "near_duplicate_sets (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.near_duplicate_sets"]], "report() (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager class method)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.duplicate.nearduplicateissuemanager attribute)": [[22, "cleanlab.datalab.internal.issue_manager.duplicate.NearDuplicateIssueManager.verbosity_levels"]], "classimbalanceissuemanager (class in cleanlab.datalab.internal.issue_manager.imbalance)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager"]], "cleanlab.datalab.internal.issue_manager.imbalance": [[23, "module-cleanlab.datalab.internal.issue_manager.imbalance"]], "collect_info() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager class method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager class method)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.imbalance.classimbalanceissuemanager attribute)": [[23, "cleanlab.datalab.internal.issue_manager.imbalance.ClassImbalanceIssueManager.verbosity_levels"]], "issuemanager (class in cleanlab.datalab.internal.issue_manager.issue_manager)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager"]], "cleanlab.datalab.internal.issue_manager.issue_manager": [[25, "module-cleanlab.datalab.internal.issue_manager.issue_manager"]], "collect_info() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager class method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager class method)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.issue_manager.issuemanager attribute)": [[25, "cleanlab.datalab.internal.issue_manager.issue_manager.IssueManager.verbosity_levels"]], "labelissuemanager (class in cleanlab.datalab.internal.issue_manager.label)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.label": [[26, "module-cleanlab.datalab.internal.issue_manager.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.find_issues"]], "get_health_summary() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.get_health_summary"]], "health_summary_parameters (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.health_summary_parameters"]], "info (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager class method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.label.labelissuemanager class method)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.label.labelissuemanager attribute)": [[26, "cleanlab.datalab.internal.issue_manager.label.LabelIssueManager.verbosity_levels"]], "multilabelissuemanager (class in cleanlab.datalab.internal.issue_manager.multilabel.label)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.multilabel.label": [[28, "module-cleanlab.datalab.internal.issue_manager.multilabel.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager class method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager class method)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.multilabel.label.multilabelissuemanager attribute)": [[28, "cleanlab.datalab.internal.issue_manager.multilabel.label.MultilabelIssueManager.verbosity_levels"]], "noniidissuemanager (class in cleanlab.datalab.internal.issue_manager.noniid)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager"]], "cleanlab.datalab.internal.issue_manager.noniid": [[29, "module-cleanlab.datalab.internal.issue_manager.noniid"]], "collect_info() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager class method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager class method)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.report"]], "simplified_kolmogorov_smirnov_test() (in module cleanlab.datalab.internal.issue_manager.noniid)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.simplified_kolmogorov_smirnov_test"]], "summary (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.noniid.noniidissuemanager attribute)": [[29, "cleanlab.datalab.internal.issue_manager.noniid.NonIIDIssueManager.verbosity_levels"]], "nullissuemanager (class in cleanlab.datalab.internal.issue_manager.null)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager"]], "cleanlab.datalab.internal.issue_manager.null": [[30, "module-cleanlab.datalab.internal.issue_manager.null"]], "collect_info() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager class method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.null.nullissuemanager class method)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.null.nullissuemanager attribute)": [[30, "cleanlab.datalab.internal.issue_manager.null.NullIssueManager.verbosity_levels"]], "default_thresholds (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.DEFAULT_THRESHOLDS"]], "outlierissuemanager (class in cleanlab.datalab.internal.issue_manager.outlier)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager"]], "cleanlab.datalab.internal.issue_manager.outlier": [[31, "module-cleanlab.datalab.internal.issue_manager.outlier"]], "collect_info() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.find_issues"]], "info (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager class method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.make_summary"]], "metric (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.metric"]], "ood (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.ood"]], "report() (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager class method)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.outlier.outlierissuemanager attribute)": [[31, "cleanlab.datalab.internal.issue_manager.outlier.OutlierIssueManager.verbosity_levels"]], "regressionlabelissuemanager (class in cleanlab.datalab.internal.issue_manager.regression.label)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager"]], "cleanlab.datalab.internal.issue_manager.regression.label": [[33, "module-cleanlab.datalab.internal.issue_manager.regression.label"]], "collect_info() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.description"]], "find_issues() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.find_issues"]], "find_issues_with_features() (in module cleanlab.datalab.internal.issue_manager.regression.label)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.find_issues_with_features"]], "find_issues_with_predictions() (in module cleanlab.datalab.internal.issue_manager.regression.label)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.find_issues_with_predictions"]], "info (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager class method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.make_summary"]], "report() (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager class method)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.regression.label.regressionlabelissuemanager attribute)": [[33, "cleanlab.datalab.internal.issue_manager.regression.label.RegressionLabelIssueManager.verbosity_levels"]], "no_underperforming_cluster_id (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.NO_UNDERPERFORMING_CLUSTER_ID"]], "outlier_cluster_labels (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.OUTLIER_CLUSTER_LABELS"]], "underperforminggroupissuemanager (class in cleanlab.datalab.internal.issue_manager.underperforming_group)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager"]], "cleanlab.datalab.internal.issue_manager.underperforming_group": [[34, "module-cleanlab.datalab.internal.issue_manager.underperforming_group"]], "collect_info() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.collect_info"]], "description (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.description"]], "filter_cluster_ids() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.filter_cluster_ids"]], "find_issues() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.find_issues"]], "get_underperforming_clusters() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.get_underperforming_clusters"]], "info (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.info"]], "issue_name (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.issue_name"]], "issue_score_key (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.issue_score_key"]], "issues (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.issues"]], "make_summary() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager class method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.make_summary"]], "perform_clustering() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.perform_clustering"]], "report() (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager class method)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.report"]], "summary (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.summary"]], "verbosity_levels (cleanlab.datalab.internal.issue_manager.underperforming_group.underperforminggroupissuemanager attribute)": [[34, "cleanlab.datalab.internal.issue_manager.underperforming_group.UnderperformingGroupIssueManager.verbosity_levels"]], "modeloutput (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput"]], "multiclasspredprobs (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs"]], "multilabelpredprobs (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs"]], "regressionpredictions (class in cleanlab.datalab.internal.model_outputs)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions"]], "argument (cleanlab.datalab.internal.model_outputs.multiclasspredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.argument"]], "argument (cleanlab.datalab.internal.model_outputs.multilabelpredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.argument"]], "argument (cleanlab.datalab.internal.model_outputs.regressionpredictions attribute)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.argument"]], "cleanlab.datalab.internal.model_outputs": [[35, "module-cleanlab.datalab.internal.model_outputs"]], "collect() (cleanlab.datalab.internal.model_outputs.modeloutput method)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput.collect"]], "collect() (cleanlab.datalab.internal.model_outputs.multiclasspredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.collect"]], "collect() (cleanlab.datalab.internal.model_outputs.multilabelpredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.collect"]], "collect() (cleanlab.datalab.internal.model_outputs.regressionpredictions method)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.collect"]], "data (cleanlab.datalab.internal.model_outputs.modeloutput attribute)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput.data"]], "data (cleanlab.datalab.internal.model_outputs.multiclasspredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.data"]], "data (cleanlab.datalab.internal.model_outputs.multilabelpredprobs attribute)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.data"]], "data (cleanlab.datalab.internal.model_outputs.regressionpredictions attribute)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.data"]], "validate() (cleanlab.datalab.internal.model_outputs.modeloutput method)": [[35, "cleanlab.datalab.internal.model_outputs.ModelOutput.validate"]], "validate() (cleanlab.datalab.internal.model_outputs.multiclasspredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiClassPredProbs.validate"]], "validate() (cleanlab.datalab.internal.model_outputs.multilabelpredprobs method)": [[35, "cleanlab.datalab.internal.model_outputs.MultiLabelPredProbs.validate"]], "validate() (cleanlab.datalab.internal.model_outputs.regressionpredictions method)": [[35, "cleanlab.datalab.internal.model_outputs.RegressionPredictions.validate"]], "reporter (class in cleanlab.datalab.internal.report)": [[36, "cleanlab.datalab.internal.report.Reporter"]], "cleanlab.datalab.internal.report": [[36, "module-cleanlab.datalab.internal.report"]], "get_report() (cleanlab.datalab.internal.report.reporter method)": [[36, "cleanlab.datalab.internal.report.Reporter.get_report"]], "report() (cleanlab.datalab.internal.report.reporter method)": [[36, "cleanlab.datalab.internal.report.Reporter.report"]], "classification (cleanlab.datalab.internal.task.task attribute)": [[37, "cleanlab.datalab.internal.task.Task.CLASSIFICATION"]], "multilabel (cleanlab.datalab.internal.task.task attribute)": [[37, "cleanlab.datalab.internal.task.Task.MULTILABEL"]], "regression (cleanlab.datalab.internal.task.task attribute)": [[37, "cleanlab.datalab.internal.task.Task.REGRESSION"]], "task (class in cleanlab.datalab.internal.task)": [[37, "cleanlab.datalab.internal.task.Task"]], "__contains__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__contains__"]], "__getitem__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__getitem__"]], "__iter__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__iter__"]], "__len__() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.__len__"]], "cleanlab.datalab.internal.task": [[37, "module-cleanlab.datalab.internal.task"]], "from_str() (cleanlab.datalab.internal.task.task class method)": [[37, "cleanlab.datalab.internal.task.Task.from_str"]], "is_classification (cleanlab.datalab.internal.task.task property)": [[37, "cleanlab.datalab.internal.task.Task.is_classification"]], "is_multilabel (cleanlab.datalab.internal.task.task property)": [[37, "cleanlab.datalab.internal.task.Task.is_multilabel"]], "is_regression (cleanlab.datalab.internal.task.task property)": [[37, "cleanlab.datalab.internal.task.Task.is_regression"]], "cleanlab.dataset": [[39, "module-cleanlab.dataset"]], "find_overlapping_classes() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.find_overlapping_classes"]], "health_summary() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.health_summary"]], "overall_label_health_score() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.overall_label_health_score"]], "rank_classes_by_label_quality() (in module cleanlab.dataset)": [[39, "cleanlab.dataset.rank_classes_by_label_quality"]], "cnn (class in cleanlab.experimental.cifar_cnn)": [[40, "cleanlab.experimental.cifar_cnn.CNN"]], "t_destination (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.T_destination"]], "__call__() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.__call__"]], "add_module() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.add_module"]], "apply() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.apply"]], "bfloat16() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.bfloat16"]], "buffers() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.buffers"]], "call_bn() (in module cleanlab.experimental.cifar_cnn)": [[40, "cleanlab.experimental.cifar_cnn.call_bn"]], "call_super_init (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.call_super_init"]], "children() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.children"]], "cleanlab.experimental.cifar_cnn": [[40, "module-cleanlab.experimental.cifar_cnn"]], "compile() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.compile"]], "cpu() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.cpu"]], "cuda() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.cuda"]], "double() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.double"]], "dump_patches (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.dump_patches"]], "eval() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.eval"]], "extra_repr() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.extra_repr"]], "float() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.float"]], "forward() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.forward"], [40, "id0"]], "get_buffer() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_buffer"]], "get_extra_state() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_extra_state"]], "get_parameter() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_parameter"]], "get_submodule() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.get_submodule"]], "half() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.half"]], "ipu() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.ipu"]], "load_state_dict() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.load_state_dict"]], "modules() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.modules"]], "named_buffers() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_buffers"]], "named_children() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_children"]], "named_modules() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_modules"]], "named_parameters() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.named_parameters"]], "parameters() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.parameters"]], "register_backward_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_backward_hook"]], "register_buffer() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_buffer"]], "register_forward_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_forward_hook"]], "register_forward_pre_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_forward_pre_hook"]], "register_full_backward_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_full_backward_hook"]], "register_full_backward_pre_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_full_backward_pre_hook"]], "register_load_state_dict_post_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_load_state_dict_post_hook"]], "register_module() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_module"]], "register_parameter() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_parameter"]], "register_state_dict_pre_hook() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.register_state_dict_pre_hook"]], "requires_grad_() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.requires_grad_"]], "set_extra_state() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.set_extra_state"]], "share_memory() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.share_memory"]], "state_dict() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.state_dict"]], "to() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.to"]], "to_empty() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.to_empty"]], "train() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.train"]], "training (cleanlab.experimental.cifar_cnn.cnn attribute)": [[40, "cleanlab.experimental.cifar_cnn.CNN.training"]], "type() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.type"]], "xpu() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.xpu"]], "zero_grad() (cleanlab.experimental.cifar_cnn.cnn method)": [[40, "cleanlab.experimental.cifar_cnn.CNN.zero_grad"]], "adjust_learning_rate() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.adjust_learning_rate"]], "cleanlab.experimental.coteaching": [[41, "module-cleanlab.experimental.coteaching"]], "evaluate() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.evaluate"]], "forget_rate_scheduler() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.forget_rate_scheduler"]], "initialize_lr_scheduler() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.initialize_lr_scheduler"]], "loss_coteaching() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.loss_coteaching"]], "train() (in module cleanlab.experimental.coteaching)": [[41, "cleanlab.experimental.coteaching.train"]], "cleanlab.experimental": [[42, "module-cleanlab.experimental"]], "labelinspector (class in cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector"]], "adj_confident_thresholds_shared (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.adj_confident_thresholds_shared"]], "cleanlab.experimental.label_issues_batched": [[43, "module-cleanlab.experimental.label_issues_batched"]], "find_label_issues_batched() (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.find_label_issues_batched"]], "get_confident_thresholds() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_confident_thresholds"]], "get_label_issues() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_label_issues"]], "get_num_issues() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_num_issues"]], "get_quality_scores() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.get_quality_scores"]], "labels_shared (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.labels_shared"]], "pred_probs_shared (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.pred_probs_shared"]], "score_label_quality() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.score_label_quality"]], "split_arr() (in module cleanlab.experimental.label_issues_batched)": [[43, "cleanlab.experimental.label_issues_batched.split_arr"]], "update_confident_thresholds() (cleanlab.experimental.label_issues_batched.labelinspector method)": [[43, "cleanlab.experimental.label_issues_batched.LabelInspector.update_confident_thresholds"]], "cnn (class in cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.CNN"]], "simplenet (class in cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet"]], "t_destination (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.T_destination"]], "__call__() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.__call__"]], "__init_subclass__() (cleanlab.experimental.mnist_pytorch.cnn class method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.__init_subclass__"]], "add_module() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.add_module"]], "apply() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.apply"]], "batch_size (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.batch_size"]], "bfloat16() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.bfloat16"]], "buffers() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.buffers"]], "call_super_init (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.call_super_init"]], "children() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.children"]], "cleanlab.experimental.mnist_pytorch": [[44, "module-cleanlab.experimental.mnist_pytorch"]], "compile() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.compile"]], "cpu() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.cpu"]], "cuda() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.cuda"]], "dataset (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.dataset"]], "double() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.double"]], "dump_patches (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.dump_patches"]], "epochs (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.epochs"]], "eval() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.eval"]], "extra_repr() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.extra_repr"]], "fit() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.fit"], [44, "id0"]], "float() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.float"]], "forward() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.forward"]], "get_buffer() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_buffer"]], "get_extra_state() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_extra_state"]], "get_metadata_routing() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.get_metadata_routing"]], "get_mnist_dataset() (in module cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.get_mnist_dataset"]], "get_parameter() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_parameter"]], "get_params() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.get_params"]], "get_sklearn_digits_dataset() (in module cleanlab.experimental.mnist_pytorch)": [[44, "cleanlab.experimental.mnist_pytorch.get_sklearn_digits_dataset"]], "get_submodule() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.get_submodule"]], "half() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.half"]], "ipu() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.ipu"]], "load_state_dict() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.load_state_dict"]], "loader (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.loader"]], "log_interval (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.log_interval"]], "lr (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.lr"]], "modules() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.modules"]], "momentum (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.momentum"]], "named_buffers() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_buffers"]], "named_children() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_children"]], "named_modules() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_modules"]], "named_parameters() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.named_parameters"]], "no_cuda (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.no_cuda"]], "parameters() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.parameters"]], "predict() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.predict"], [44, "id1"]], "predict_proba() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.predict_proba"], [44, "id4"]], "register_backward_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_backward_hook"]], "register_buffer() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_buffer"]], "register_forward_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_forward_hook"]], "register_forward_pre_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_forward_pre_hook"]], "register_full_backward_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_full_backward_hook"]], "register_full_backward_pre_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_full_backward_pre_hook"]], "register_load_state_dict_post_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_load_state_dict_post_hook"]], "register_module() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_module"]], "register_parameter() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_parameter"]], "register_state_dict_pre_hook() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.register_state_dict_pre_hook"]], "requires_grad_() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.requires_grad_"]], "seed (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.seed"]], "set_extra_state() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.set_extra_state"]], "set_fit_request() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_fit_request"]], "set_params() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_params"]], "set_predict_proba_request() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_predict_proba_request"]], "set_predict_request() (cleanlab.experimental.mnist_pytorch.cnn method)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.set_predict_request"]], "share_memory() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.share_memory"]], "state_dict() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.state_dict"]], "test_batch_size (cleanlab.experimental.mnist_pytorch.cnn attribute)": [[44, "cleanlab.experimental.mnist_pytorch.CNN.test_batch_size"]], "to() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.to"]], "to_empty() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.to_empty"]], "train() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.train"]], "training (cleanlab.experimental.mnist_pytorch.simplenet attribute)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.training"]], "type() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.type"]], "xpu() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.xpu"]], "zero_grad() (cleanlab.experimental.mnist_pytorch.simplenet method)": [[44, "cleanlab.experimental.mnist_pytorch.SimpleNet.zero_grad"]], "cleanlab.experimental.span_classification": [[45, "module-cleanlab.experimental.span_classification"]], "display_issues() (in module cleanlab.experimental.span_classification)": [[45, "cleanlab.experimental.span_classification.display_issues"]], "find_label_issues() (in module cleanlab.experimental.span_classification)": [[45, "cleanlab.experimental.span_classification.find_label_issues"]], "get_label_quality_scores() (in module cleanlab.experimental.span_classification)": [[45, "cleanlab.experimental.span_classification.get_label_quality_scores"]], "cleanlab.filter": [[46, "module-cleanlab.filter"]], "find_label_issues() (in module cleanlab.filter)": [[46, "cleanlab.filter.find_label_issues"]], "find_label_issues_using_argmax_confusion_matrix() (in module cleanlab.filter)": [[46, "cleanlab.filter.find_label_issues_using_argmax_confusion_matrix"]], "find_predicted_neq_given() (in module cleanlab.filter)": [[46, "cleanlab.filter.find_predicted_neq_given"]], "pred_probs_by_class (in module cleanlab.filter)": [[46, "cleanlab.filter.pred_probs_by_class"]], "prune_count_matrix_cols (in module cleanlab.filter)": [[46, "cleanlab.filter.prune_count_matrix_cols"]], "cleanlab.internal": [[47, "module-cleanlab.internal"]], "cleanlab.internal.label_quality_utils": [[48, "module-cleanlab.internal.label_quality_utils"]], "get_normalized_entropy() (in module cleanlab.internal.label_quality_utils)": [[48, "cleanlab.internal.label_quality_utils.get_normalized_entropy"]], "cleanlab.internal.latent_algebra": [[49, "module-cleanlab.internal.latent_algebra"]], "compute_inv_noise_matrix() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_inv_noise_matrix"]], "compute_noise_matrix_from_inverse() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_noise_matrix_from_inverse"]], "compute_ps_py_inv_noise_matrix() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_ps_py_inv_noise_matrix"]], "compute_py() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_py"]], "compute_py_inv_noise_matrix() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_py_inv_noise_matrix"]], "compute_pyx() (in module cleanlab.internal.latent_algebra)": [[49, "cleanlab.internal.latent_algebra.compute_pyx"]], "assert_valid_inputs_multiannotator() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.assert_valid_inputs_multiannotator"]], "assert_valid_pred_probs() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.assert_valid_pred_probs"]], "check_consensus_label_classes() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.check_consensus_label_classes"]], "cleanlab.internal.multiannotator_utils": [[50, "module-cleanlab.internal.multiannotator_utils"]], "compute_soft_cross_entropy() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.compute_soft_cross_entropy"]], "find_best_temp_scaler() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.find_best_temp_scaler"]], "format_multiannotator_labels() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.format_multiannotator_labels"]], "temp_scale_pred_probs() (in module cleanlab.internal.multiannotator_utils)": [[50, "cleanlab.internal.multiannotator_utils.temp_scale_pred_probs"]], "aggregator (class in cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.Aggregator"]], "confidence_weighted_entropy (cleanlab.internal.multilabel_scorer.classlabelscorer attribute)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.CONFIDENCE_WEIGHTED_ENTROPY"]], "classlabelscorer (class in cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer"]], "multilabelscorer (class in cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer"]], "normalized_margin (cleanlab.internal.multilabel_scorer.classlabelscorer attribute)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.NORMALIZED_MARGIN"]], "self_confidence (cleanlab.internal.multilabel_scorer.classlabelscorer attribute)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.SELF_CONFIDENCE"]], "__call__() (cleanlab.internal.multilabel_scorer.aggregator method)": [[51, "cleanlab.internal.multilabel_scorer.Aggregator.__call__"]], "__call__() (cleanlab.internal.multilabel_scorer.classlabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__call__"]], "__call__() (cleanlab.internal.multilabel_scorer.multilabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer.__call__"]], "__contains__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__contains__"]], "__getitem__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__getitem__"]], "__iter__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__iter__"]], "__len__() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.__len__"]], "aggregate() (cleanlab.internal.multilabel_scorer.multilabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer.aggregate"]], "cleanlab.internal.multilabel_scorer": [[51, "module-cleanlab.internal.multilabel_scorer"]], "exponential_moving_average() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.exponential_moving_average"]], "from_str() (cleanlab.internal.multilabel_scorer.classlabelscorer class method)": [[51, "cleanlab.internal.multilabel_scorer.ClassLabelScorer.from_str"]], "get_class_label_quality_scores() (cleanlab.internal.multilabel_scorer.multilabelscorer method)": [[51, "cleanlab.internal.multilabel_scorer.MultilabelScorer.get_class_label_quality_scores"]], "get_cross_validated_multilabel_pred_probs() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.get_cross_validated_multilabel_pred_probs"]], "get_label_quality_scores() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.get_label_quality_scores"]], "multilabel_py() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.multilabel_py"]], "possible_methods (cleanlab.internal.multilabel_scorer.aggregator attribute)": [[51, "cleanlab.internal.multilabel_scorer.Aggregator.possible_methods"]], "softmin() (in module cleanlab.internal.multilabel_scorer)": [[51, "cleanlab.internal.multilabel_scorer.softmin"]], "cleanlab.internal.multilabel_utils": [[52, "module-cleanlab.internal.multilabel_utils"]], "get_onehot_num_classes() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.get_onehot_num_classes"]], "int2onehot() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.int2onehot"]], "onehot2int() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.onehot2int"]], "stack_complement() (in module cleanlab.internal.multilabel_utils)": [[52, "cleanlab.internal.multilabel_utils.stack_complement"]], "cleanlab.internal.neighbor": [[53, "module-cleanlab.internal.neighbor"]], "default_k (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.DEFAULT_K"]], "cleanlab.internal.neighbor.knn_graph": [[54, "module-cleanlab.internal.neighbor.knn_graph"]], "construct_knn_graph_from_index() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.construct_knn_graph_from_index"]], "correct_knn_distances_and_indices() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.correct_knn_distances_and_indices"]], "correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.correct_knn_distances_and_indices_with_exact_duplicate_sets_inplace"]], "correct_knn_graph() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.correct_knn_graph"]], "create_knn_graph_and_index() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.create_knn_graph_and_index"]], "features_to_knn() (in module cleanlab.internal.neighbor.knn_graph)": [[54, "cleanlab.internal.neighbor.knn_graph.features_to_knn"]], "high_dimension_cutoff (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.HIGH_DIMENSION_CUTOFF"]], "row_count_cutoff (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.ROW_COUNT_CUTOFF"]], "cleanlab.internal.neighbor.metric": [[55, "module-cleanlab.internal.neighbor.metric"]], "decide_default_metric() (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.decide_default_metric"]], "decide_euclidean_metric() (in module cleanlab.internal.neighbor.metric)": [[55, "cleanlab.internal.neighbor.metric.decide_euclidean_metric"]], "cleanlab.internal.neighbor.search": [[56, "module-cleanlab.internal.neighbor.search"]], "construct_knn() (in module cleanlab.internal.neighbor.search)": [[56, "cleanlab.internal.neighbor.search.construct_knn"]], "cleanlab.internal.outlier": [[57, "module-cleanlab.internal.outlier"]], "correct_precision_errors() (in module cleanlab.internal.outlier)": [[57, "cleanlab.internal.outlier.correct_precision_errors"]], "transform_distances_to_scores() (in module cleanlab.internal.outlier)": [[57, "cleanlab.internal.outlier.transform_distances_to_scores"]], "cleanlab.internal.token_classification_utils": [[58, "module-cleanlab.internal.token_classification_utils"]], "color_sentence() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.color_sentence"]], "filter_sentence() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.filter_sentence"]], "get_sentence() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.get_sentence"]], "mapping() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.mapping"]], "merge_probs() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.merge_probs"]], "process_token() (in module cleanlab.internal.token_classification_utils)": [[58, "cleanlab.internal.token_classification_utils.process_token"]], "append_extra_datapoint() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.append_extra_datapoint"]], "cleanlab.internal.util": [[59, "module-cleanlab.internal.util"]], "clip_noise_rates() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.clip_noise_rates"]], "clip_values() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.clip_values"]], "compress_int_array() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.compress_int_array"]], "confusion_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.confusion_matrix"]], "csr_vstack() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.csr_vstack"]], "estimate_pu_f1() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.estimate_pu_f1"]], "extract_indices_tf() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.extract_indices_tf"]], "force_two_dimensions() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.force_two_dimensions"]], "format_labels() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.format_labels"]], "get_missing_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.get_missing_classes"]], "get_num_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.get_num_classes"]], "get_unique_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.get_unique_classes"]], "is_tensorflow_dataset() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.is_tensorflow_dataset"]], "is_torch_dataset() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.is_torch_dataset"]], "num_unique_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.num_unique_classes"]], "print_inverse_noise_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_inverse_noise_matrix"]], "print_joint_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_joint_matrix"]], "print_noise_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_noise_matrix"]], "print_square_matrix() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.print_square_matrix"]], "remove_noise_from_class() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.remove_noise_from_class"]], "round_preserving_row_totals() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.round_preserving_row_totals"]], "round_preserving_sum() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.round_preserving_sum"]], "smart_display_dataframe() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.smart_display_dataframe"]], "subset_x_y() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.subset_X_y"]], "subset_data() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.subset_data"]], "subset_labels() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.subset_labels"]], "train_val_split() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.train_val_split"]], "unshuffle_tensorflow_dataset() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.unshuffle_tensorflow_dataset"]], "value_counts() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.value_counts"]], "value_counts_fill_missing_classes() (in module cleanlab.internal.util)": [[59, "cleanlab.internal.util.value_counts_fill_missing_classes"]], "assert_indexing_works() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_indexing_works"]], "assert_nonempty_input() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_nonempty_input"]], "assert_valid_class_labels() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_valid_class_labels"]], "assert_valid_inputs() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.assert_valid_inputs"]], "cleanlab.internal.validation": [[60, "module-cleanlab.internal.validation"]], "labels_to_array() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.labels_to_array"]], "labels_to_list_multilabel() (in module cleanlab.internal.validation)": [[60, "cleanlab.internal.validation.labels_to_list_multilabel"]], "cleanlab.models": [[61, "module-cleanlab.models"]], "keraswrappermodel (class in cleanlab.models.keras)": [[62, "cleanlab.models.keras.KerasWrapperModel"]], "keraswrappersequential (class in cleanlab.models.keras)": [[62, "cleanlab.models.keras.KerasWrapperSequential"]], "cleanlab.models.keras": [[62, "module-cleanlab.models.keras"]], "fit() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.fit"]], "fit() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.fit"]], "get_params() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.get_params"]], "get_params() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.get_params"]], "predict() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.predict"]], "predict() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.predict"]], "predict_proba() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.predict_proba"]], "predict_proba() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.predict_proba"]], "set_params() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.set_params"]], "set_params() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.set_params"]], "summary() (cleanlab.models.keras.keraswrappermodel method)": [[62, "cleanlab.models.keras.KerasWrapperModel.summary"]], "summary() (cleanlab.models.keras.keraswrappersequential method)": [[62, "cleanlab.models.keras.KerasWrapperSequential.summary"]], "cleanlab.multiannotator": [[63, "module-cleanlab.multiannotator"]], "convert_long_to_wide_dataset() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.convert_long_to_wide_dataset"]], "get_active_learning_scores() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_active_learning_scores"]], "get_active_learning_scores_ensemble() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_active_learning_scores_ensemble"]], "get_label_quality_multiannotator() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_label_quality_multiannotator"]], "get_label_quality_multiannotator_ensemble() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_label_quality_multiannotator_ensemble"]], "get_majority_vote_label() (in module cleanlab.multiannotator)": [[63, "cleanlab.multiannotator.get_majority_vote_label"]], "cleanlab.multilabel_classification.dataset": [[64, "module-cleanlab.multilabel_classification.dataset"]], "common_multilabel_issues() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.common_multilabel_issues"]], "multilabel_health_summary() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.multilabel_health_summary"]], "overall_multilabel_health_score() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.overall_multilabel_health_score"]], "rank_classes_by_multilabel_quality() (in module cleanlab.multilabel_classification.dataset)": [[64, "cleanlab.multilabel_classification.dataset.rank_classes_by_multilabel_quality"]], "cleanlab.multilabel_classification.filter": [[65, "module-cleanlab.multilabel_classification.filter"]], "find_label_issues() (in module cleanlab.multilabel_classification.filter)": [[65, "cleanlab.multilabel_classification.filter.find_label_issues"]], "find_multilabel_issues_per_class() (in module cleanlab.multilabel_classification.filter)": [[65, "cleanlab.multilabel_classification.filter.find_multilabel_issues_per_class"]], "cleanlab.multilabel_classification": [[66, "module-cleanlab.multilabel_classification"]], "cleanlab.multilabel_classification.rank": [[67, "module-cleanlab.multilabel_classification.rank"]], "get_label_quality_scores() (in module cleanlab.multilabel_classification.rank)": [[67, "cleanlab.multilabel_classification.rank.get_label_quality_scores"]], "get_label_quality_scores_per_class() (in module cleanlab.multilabel_classification.rank)": [[67, "cleanlab.multilabel_classification.rank.get_label_quality_scores_per_class"]], "cleanlab.object_detection.filter": [[68, "module-cleanlab.object_detection.filter"]], "find_label_issues() (in module cleanlab.object_detection.filter)": [[68, "cleanlab.object_detection.filter.find_label_issues"]], "cleanlab.object_detection": [[69, "module-cleanlab.object_detection"]], "cleanlab.object_detection.rank": [[70, "module-cleanlab.object_detection.rank"]], "compute_badloc_box_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.compute_badloc_box_scores"]], "compute_overlooked_box_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.compute_overlooked_box_scores"]], "compute_swap_box_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.compute_swap_box_scores"]], "get_label_quality_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.issues_from_scores"]], "pool_box_scores_per_image() (in module cleanlab.object_detection.rank)": [[70, "cleanlab.object_detection.rank.pool_box_scores_per_image"]], "bounding_box_size_distribution() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.bounding_box_size_distribution"]], "calculate_per_class_metrics() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.calculate_per_class_metrics"]], "class_label_distribution() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.class_label_distribution"]], "cleanlab.object_detection.summary": [[71, "module-cleanlab.object_detection.summary"]], "get_average_per_class_confusion_matrix() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.get_average_per_class_confusion_matrix"]], "get_sorted_bbox_count_idxs() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.get_sorted_bbox_count_idxs"]], "object_counts_per_image() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.object_counts_per_image"]], "plot_class_distribution() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.plot_class_distribution"]], "plot_class_size_distributions() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.plot_class_size_distributions"]], "visualize() (in module cleanlab.object_detection.summary)": [[71, "cleanlab.object_detection.summary.visualize"]], "outofdistribution (class in cleanlab.outlier)": [[72, "cleanlab.outlier.OutOfDistribution"]], "cleanlab.outlier": [[72, "module-cleanlab.outlier"]], "fit() (cleanlab.outlier.outofdistribution method)": [[72, "cleanlab.outlier.OutOfDistribution.fit"]], "fit_score() (cleanlab.outlier.outofdistribution method)": [[72, "cleanlab.outlier.OutOfDistribution.fit_score"]], "score() (cleanlab.outlier.outofdistribution method)": [[72, "cleanlab.outlier.OutOfDistribution.score"]], "cleanlab.rank": [[73, "module-cleanlab.rank"]], "find_top_issues() (in module cleanlab.rank)": [[73, "cleanlab.rank.find_top_issues"]], "get_confidence_weighted_entropy_for_each_label() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_confidence_weighted_entropy_for_each_label"]], "get_label_quality_ensemble_scores() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_label_quality_ensemble_scores"]], "get_label_quality_scores() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_label_quality_scores"]], "get_normalized_margin_for_each_label() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_normalized_margin_for_each_label"]], "get_self_confidence_for_each_label() (in module cleanlab.rank)": [[73, "cleanlab.rank.get_self_confidence_for_each_label"]], "order_label_issues() (in module cleanlab.rank)": [[73, "cleanlab.rank.order_label_issues"]], "cleanlab.regression": [[74, "module-cleanlab.regression"]], "cleanlearning (class in cleanlab.regression.learn)": [[75, "cleanlab.regression.learn.CleanLearning"]], "__init_subclass__() (cleanlab.regression.learn.cleanlearning class method)": [[75, "cleanlab.regression.learn.CleanLearning.__init_subclass__"]], "cleanlab.regression.learn": [[75, "module-cleanlab.regression.learn"]], "find_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.find_label_issues"]], "fit() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.fit"]], "get_aleatoric_uncertainty() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_aleatoric_uncertainty"]], "get_epistemic_uncertainty() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_epistemic_uncertainty"]], "get_label_issues() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_label_issues"]], "get_metadata_routing() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_metadata_routing"]], "get_params() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.get_params"]], "predict() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.predict"]], "save_space() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.save_space"]], "score() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.score"]], "set_fit_request() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.set_fit_request"]], "set_params() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.set_params"]], "set_score_request() (cleanlab.regression.learn.cleanlearning method)": [[75, "cleanlab.regression.learn.CleanLearning.set_score_request"]], "cleanlab.regression.rank": [[76, "module-cleanlab.regression.rank"]], "get_label_quality_scores() (in module cleanlab.regression.rank)": [[76, "cleanlab.regression.rank.get_label_quality_scores"]], "cleanlab.segmentation.filter": [[77, "module-cleanlab.segmentation.filter"]], "find_label_issues() (in module cleanlab.segmentation.filter)": [[77, "cleanlab.segmentation.filter.find_label_issues"]], "cleanlab.segmentation": [[78, "module-cleanlab.segmentation"]], "cleanlab.segmentation.rank": [[79, "module-cleanlab.segmentation.rank"]], "get_label_quality_scores() (in module cleanlab.segmentation.rank)": [[79, "cleanlab.segmentation.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.segmentation.rank)": [[79, "cleanlab.segmentation.rank.issues_from_scores"]], "cleanlab.segmentation.summary": [[80, "module-cleanlab.segmentation.summary"]], "common_label_issues() (in module cleanlab.segmentation.summary)": [[80, "cleanlab.segmentation.summary.common_label_issues"]], "display_issues() (in module cleanlab.segmentation.summary)": [[80, "cleanlab.segmentation.summary.display_issues"]], "filter_by_class() (in module cleanlab.segmentation.summary)": [[80, "cleanlab.segmentation.summary.filter_by_class"]], "cleanlab.token_classification.filter": [[81, "module-cleanlab.token_classification.filter"]], "find_label_issues() (in module cleanlab.token_classification.filter)": [[81, "cleanlab.token_classification.filter.find_label_issues"]], "cleanlab.token_classification": [[82, "module-cleanlab.token_classification"]], "cleanlab.token_classification.rank": [[83, "module-cleanlab.token_classification.rank"]], "get_label_quality_scores() (in module cleanlab.token_classification.rank)": [[83, "cleanlab.token_classification.rank.get_label_quality_scores"]], "issues_from_scores() (in module cleanlab.token_classification.rank)": [[83, "cleanlab.token_classification.rank.issues_from_scores"]], "cleanlab.token_classification.summary": [[84, "module-cleanlab.token_classification.summary"]], "common_label_issues() (in module cleanlab.token_classification.summary)": [[84, "cleanlab.token_classification.summary.common_label_issues"]], "display_issues() (in module cleanlab.token_classification.summary)": [[84, "cleanlab.token_classification.summary.display_issues"]], "filter_by_token() (in module cleanlab.token_classification.summary)": [[84, "cleanlab.token_classification.summary.filter_by_token"]]}}) \ No newline at end of file diff --git a/master/tutorials/clean_learning/tabular.ipynb b/master/tutorials/clean_learning/tabular.ipynb index 5e85de9ac..9d1517aad 100644 --- a/master/tutorials/clean_learning/tabular.ipynb +++ b/master/tutorials/clean_learning/tabular.ipynb @@ -113,10 +113,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:32:59.587012Z", - "iopub.status.busy": "2024-09-05T19:32:59.586834Z", - "iopub.status.idle": "2024-09-05T19:33:00.869499Z", - "shell.execute_reply": "2024-09-05T19:33:00.868940Z" + "iopub.execute_input": "2024-09-06T19:32:51.069638Z", + "iopub.status.busy": "2024-09-06T19:32:51.069457Z", + "iopub.status.idle": "2024-09-06T19:32:52.310694Z", + "shell.execute_reply": "2024-09-06T19:32:52.310136Z" }, "nbsphinx": "hidden" }, @@ -126,7 +126,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -151,10 +151,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:00.872309Z", - "iopub.status.busy": "2024-09-05T19:33:00.871752Z", - "iopub.status.idle": "2024-09-05T19:33:00.890028Z", - "shell.execute_reply": "2024-09-05T19:33:00.889577Z" + "iopub.execute_input": "2024-09-06T19:32:52.313494Z", + "iopub.status.busy": "2024-09-06T19:32:52.312922Z", + "iopub.status.idle": "2024-09-06T19:32:52.331174Z", + "shell.execute_reply": "2024-09-06T19:32:52.330732Z" } }, "outputs": [], @@ -195,10 +195,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:00.892312Z", - "iopub.status.busy": "2024-09-05T19:33:00.892050Z", - "iopub.status.idle": "2024-09-05T19:33:01.003828Z", - "shell.execute_reply": "2024-09-05T19:33:01.003258Z" + "iopub.execute_input": "2024-09-06T19:32:52.333414Z", + "iopub.status.busy": "2024-09-06T19:32:52.333012Z", + "iopub.status.idle": "2024-09-06T19:32:52.616135Z", + "shell.execute_reply": "2024-09-06T19:32:52.615552Z" } }, "outputs": [ @@ -305,10 +305,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:01.036111Z", - "iopub.status.busy": "2024-09-05T19:33:01.035678Z", - "iopub.status.idle": "2024-09-05T19:33:01.039351Z", - "shell.execute_reply": "2024-09-05T19:33:01.038901Z" + "iopub.execute_input": "2024-09-06T19:32:52.647632Z", + "iopub.status.busy": "2024-09-06T19:32:52.647448Z", + "iopub.status.idle": "2024-09-06T19:32:52.650810Z", + "shell.execute_reply": "2024-09-06T19:32:52.650339Z" } }, "outputs": [], @@ -329,10 +329,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:01.041401Z", - "iopub.status.busy": "2024-09-05T19:33:01.041222Z", - "iopub.status.idle": "2024-09-05T19:33:01.049517Z", - "shell.execute_reply": "2024-09-05T19:33:01.049062Z" + "iopub.execute_input": "2024-09-06T19:32:52.652810Z", + "iopub.status.busy": "2024-09-06T19:32:52.652474Z", + "iopub.status.idle": "2024-09-06T19:32:52.660488Z", + "shell.execute_reply": "2024-09-06T19:32:52.660065Z" } }, "outputs": [], @@ -384,10 +384,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:01.051546Z", - "iopub.status.busy": "2024-09-05T19:33:01.051368Z", - "iopub.status.idle": "2024-09-05T19:33:01.054060Z", - "shell.execute_reply": "2024-09-05T19:33:01.053588Z" + "iopub.execute_input": "2024-09-06T19:32:52.662789Z", + "iopub.status.busy": "2024-09-06T19:32:52.662453Z", + "iopub.status.idle": "2024-09-06T19:32:52.664910Z", + "shell.execute_reply": "2024-09-06T19:32:52.664468Z" } }, "outputs": [], @@ -409,10 +409,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:01.055990Z", - "iopub.status.busy": "2024-09-05T19:33:01.055803Z", - "iopub.status.idle": "2024-09-05T19:33:01.581009Z", - "shell.execute_reply": "2024-09-05T19:33:01.580442Z" + "iopub.execute_input": "2024-09-06T19:32:52.667005Z", + "iopub.status.busy": "2024-09-06T19:32:52.666677Z", + "iopub.status.idle": "2024-09-06T19:32:53.186834Z", + "shell.execute_reply": "2024-09-06T19:32:53.186291Z" } }, "outputs": [], @@ -446,10 +446,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:01.583425Z", - "iopub.status.busy": "2024-09-05T19:33:01.583193Z", - "iopub.status.idle": "2024-09-05T19:33:03.549090Z", - "shell.execute_reply": "2024-09-05T19:33:03.548469Z" + "iopub.execute_input": "2024-09-06T19:32:53.189445Z", + "iopub.status.busy": "2024-09-06T19:32:53.189066Z", + "iopub.status.idle": "2024-09-06T19:32:55.090605Z", + "shell.execute_reply": "2024-09-06T19:32:55.089933Z" } }, "outputs": [ @@ -481,10 +481,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:03.551875Z", - "iopub.status.busy": "2024-09-05T19:33:03.551107Z", - "iopub.status.idle": "2024-09-05T19:33:03.561703Z", - "shell.execute_reply": "2024-09-05T19:33:03.561236Z" + "iopub.execute_input": "2024-09-06T19:32:55.093443Z", + "iopub.status.busy": "2024-09-06T19:32:55.092787Z", + "iopub.status.idle": "2024-09-06T19:32:55.103390Z", + "shell.execute_reply": "2024-09-06T19:32:55.102831Z" } }, "outputs": [ @@ -605,10 +605,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:03.563830Z", - "iopub.status.busy": "2024-09-05T19:33:03.563524Z", - "iopub.status.idle": "2024-09-05T19:33:03.567711Z", - "shell.execute_reply": "2024-09-05T19:33:03.567284Z" + "iopub.execute_input": "2024-09-06T19:32:55.105571Z", + "iopub.status.busy": "2024-09-06T19:32:55.105237Z", + "iopub.status.idle": "2024-09-06T19:32:55.109432Z", + "shell.execute_reply": "2024-09-06T19:32:55.108857Z" } }, "outputs": [], @@ -633,10 +633,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:03.569933Z", - "iopub.status.busy": "2024-09-05T19:33:03.569510Z", - "iopub.status.idle": "2024-09-05T19:33:03.578212Z", - "shell.execute_reply": "2024-09-05T19:33:03.577763Z" + "iopub.execute_input": "2024-09-06T19:32:55.111438Z", + "iopub.status.busy": "2024-09-06T19:32:55.111142Z", + "iopub.status.idle": "2024-09-06T19:32:55.120139Z", + "shell.execute_reply": "2024-09-06T19:32:55.119708Z" } }, "outputs": [], @@ -658,10 +658,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:03.580544Z", - "iopub.status.busy": "2024-09-05T19:33:03.579929Z", - "iopub.status.idle": "2024-09-05T19:33:03.693855Z", - "shell.execute_reply": "2024-09-05T19:33:03.693311Z" + "iopub.execute_input": "2024-09-06T19:32:55.122107Z", + "iopub.status.busy": "2024-09-06T19:32:55.121935Z", + "iopub.status.idle": "2024-09-06T19:32:55.235206Z", + "shell.execute_reply": "2024-09-06T19:32:55.234622Z" } }, "outputs": [ @@ -691,10 +691,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:03.696060Z", - "iopub.status.busy": "2024-09-05T19:33:03.695714Z", - "iopub.status.idle": "2024-09-05T19:33:03.698630Z", - "shell.execute_reply": "2024-09-05T19:33:03.698077Z" + "iopub.execute_input": "2024-09-06T19:32:55.237464Z", + "iopub.status.busy": "2024-09-06T19:32:55.237015Z", + "iopub.status.idle": "2024-09-06T19:32:55.240074Z", + "shell.execute_reply": "2024-09-06T19:32:55.239512Z" } }, "outputs": [], @@ -715,10 +715,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:03.700629Z", - "iopub.status.busy": "2024-09-05T19:33:03.700452Z", - "iopub.status.idle": "2024-09-05T19:33:05.867604Z", - "shell.execute_reply": "2024-09-05T19:33:05.866784Z" + "iopub.execute_input": "2024-09-06T19:32:55.242072Z", + "iopub.status.busy": "2024-09-06T19:32:55.241898Z", + "iopub.status.idle": "2024-09-06T19:32:57.303999Z", + "shell.execute_reply": "2024-09-06T19:32:57.303194Z" } }, "outputs": [], @@ -738,10 +738,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:05.870677Z", - "iopub.status.busy": "2024-09-05T19:33:05.870043Z", - "iopub.status.idle": "2024-09-05T19:33:05.882124Z", - "shell.execute_reply": "2024-09-05T19:33:05.881668Z" + "iopub.execute_input": "2024-09-06T19:32:57.307062Z", + "iopub.status.busy": "2024-09-06T19:32:57.306412Z", + "iopub.status.idle": "2024-09-06T19:32:57.318236Z", + "shell.execute_reply": "2024-09-06T19:32:57.317761Z" } }, "outputs": [ @@ -786,10 +786,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:05.884250Z", - "iopub.status.busy": "2024-09-05T19:33:05.884062Z", - "iopub.status.idle": "2024-09-05T19:33:05.935772Z", - "shell.execute_reply": "2024-09-05T19:33:05.935279Z" + "iopub.execute_input": "2024-09-06T19:32:57.320219Z", + "iopub.status.busy": "2024-09-06T19:32:57.320039Z", + "iopub.status.idle": "2024-09-06T19:32:57.425487Z", + "shell.execute_reply": "2024-09-06T19:32:57.424961Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/clean_learning/text.html b/master/tutorials/clean_learning/text.html index fceb6095b..9f22a5e70 100644 --- a/master/tutorials/clean_learning/text.html +++ b/master/tutorials/clean_learning/text.html @@ -821,7 +821,7 @@

    2. Load and format the text dataset
     This dataset has 10 classes.
    -Classes: {'beneficiary_not_allowed', 'change_pin', 'card_payment_fee_charged', 'cancel_transfer', 'apple_pay_or_google_pay', 'getting_spare_card', 'lost_or_stolen_phone', 'card_about_to_expire', 'visa_or_mastercard', 'supported_cards_and_currencies'}
    +Classes: {'cancel_transfer', 'change_pin', 'visa_or_mastercard', 'getting_spare_card', 'supported_cards_and_currencies', 'lost_or_stolen_phone', 'beneficiary_not_allowed', 'apple_pay_or_google_pay', 'card_about_to_expire', 'card_payment_fee_charged'}
     

    Let’s print the first example in the train set.

    @@ -884,43 +884,43 @@

    2. Load and format the text dataset
    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    -
    +
    @@ -1223,7 +1223,7 @@

    Spending too much time on data quality?Cleanlab Studio – an automated platform to find and fix issues in your dataset, 100x faster and more accurately. Cleanlab Studio automatically runs optimized data quality algorithms from this package on top of cutting-edge AutoML & Foundation models fit to your data, and helps you fix detected issues via a smart data correction interface. Try it for free!

    The modern AI pipeline automated with Cleanlab Studio

    diff --git a/master/tutorials/clean_learning/text.ipynb b/master/tutorials/clean_learning/text.ipynb index ac1d1b45f..7c3947e74 100644 --- a/master/tutorials/clean_learning/text.ipynb +++ b/master/tutorials/clean_learning/text.ipynb @@ -115,10 +115,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:09.191218Z", - "iopub.status.busy": "2024-09-05T19:33:09.191040Z", - "iopub.status.idle": "2024-09-05T19:33:12.593196Z", - "shell.execute_reply": "2024-09-05T19:33:12.592630Z" + "iopub.execute_input": "2024-09-06T19:33:00.675758Z", + "iopub.status.busy": "2024-09-06T19:33:00.675584Z", + "iopub.status.idle": "2024-09-06T19:33:03.510616Z", + "shell.execute_reply": "2024-09-06T19:33:03.510057Z" }, "nbsphinx": "hidden" }, @@ -135,7 +135,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -160,10 +160,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.595901Z", - "iopub.status.busy": "2024-09-05T19:33:12.595431Z", - "iopub.status.idle": "2024-09-05T19:33:12.598938Z", - "shell.execute_reply": "2024-09-05T19:33:12.598353Z" + "iopub.execute_input": "2024-09-06T19:33:03.513184Z", + "iopub.status.busy": "2024-09-06T19:33:03.512761Z", + "iopub.status.idle": "2024-09-06T19:33:03.516199Z", + "shell.execute_reply": "2024-09-06T19:33:03.515742Z" } }, "outputs": [], @@ -185,10 +185,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.600924Z", - "iopub.status.busy": "2024-09-05T19:33:12.600746Z", - "iopub.status.idle": "2024-09-05T19:33:12.603877Z", - "shell.execute_reply": "2024-09-05T19:33:12.603428Z" + "iopub.execute_input": "2024-09-06T19:33:03.518261Z", + "iopub.status.busy": "2024-09-06T19:33:03.517871Z", + "iopub.status.idle": "2024-09-06T19:33:03.520905Z", + "shell.execute_reply": "2024-09-06T19:33:03.520432Z" }, "nbsphinx": "hidden" }, @@ -219,10 +219,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.605996Z", - "iopub.status.busy": "2024-09-05T19:33:12.605665Z", - "iopub.status.idle": "2024-09-05T19:33:12.653121Z", - "shell.execute_reply": "2024-09-05T19:33:12.652645Z" + "iopub.execute_input": "2024-09-06T19:33:03.522785Z", + "iopub.status.busy": "2024-09-06T19:33:03.522608Z", + "iopub.status.idle": "2024-09-06T19:33:03.678565Z", + "shell.execute_reply": "2024-09-06T19:33:03.678029Z" } }, "outputs": [ @@ -312,10 +312,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.655283Z", - "iopub.status.busy": "2024-09-05T19:33:12.654920Z", - "iopub.status.idle": "2024-09-05T19:33:12.658505Z", - "shell.execute_reply": "2024-09-05T19:33:12.658052Z" + "iopub.execute_input": "2024-09-06T19:33:03.680851Z", + "iopub.status.busy": "2024-09-06T19:33:03.680423Z", + "iopub.status.idle": "2024-09-06T19:33:03.684124Z", + "shell.execute_reply": "2024-09-06T19:33:03.683591Z" } }, "outputs": [], @@ -330,10 +330,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.660524Z", - "iopub.status.busy": "2024-09-05T19:33:12.660198Z", - "iopub.status.idle": "2024-09-05T19:33:12.663440Z", - "shell.execute_reply": "2024-09-05T19:33:12.662933Z" + "iopub.execute_input": "2024-09-06T19:33:03.686150Z", + "iopub.status.busy": "2024-09-06T19:33:03.685759Z", + "iopub.status.idle": "2024-09-06T19:33:03.689186Z", + "shell.execute_reply": "2024-09-06T19:33:03.688640Z" } }, "outputs": [ @@ -342,7 +342,7 @@ "output_type": "stream", "text": [ "This dataset has 10 classes.\n", - "Classes: {'beneficiary_not_allowed', 'change_pin', 'card_payment_fee_charged', 'cancel_transfer', 'apple_pay_or_google_pay', 'getting_spare_card', 'lost_or_stolen_phone', 'card_about_to_expire', 'visa_or_mastercard', 'supported_cards_and_currencies'}\n" + "Classes: {'cancel_transfer', 'change_pin', 'visa_or_mastercard', 'getting_spare_card', 'supported_cards_and_currencies', 'lost_or_stolen_phone', 'beneficiary_not_allowed', 'apple_pay_or_google_pay', 'card_about_to_expire', 'card_payment_fee_charged'}\n" ] } ], @@ -365,10 +365,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.665438Z", - "iopub.status.busy": "2024-09-05T19:33:12.665102Z", - "iopub.status.idle": "2024-09-05T19:33:12.668366Z", - "shell.execute_reply": "2024-09-05T19:33:12.667863Z" + "iopub.execute_input": "2024-09-06T19:33:03.691223Z", + "iopub.status.busy": "2024-09-06T19:33:03.690802Z", + "iopub.status.idle": "2024-09-06T19:33:03.693946Z", + "shell.execute_reply": "2024-09-06T19:33:03.693394Z" } }, "outputs": [ @@ -409,10 +409,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.670364Z", - "iopub.status.busy": "2024-09-05T19:33:12.670023Z", - "iopub.status.idle": "2024-09-05T19:33:12.673337Z", - "shell.execute_reply": "2024-09-05T19:33:12.672869Z" + "iopub.execute_input": "2024-09-06T19:33:03.695918Z", + "iopub.status.busy": "2024-09-06T19:33:03.695618Z", + "iopub.status.idle": "2024-09-06T19:33:03.698740Z", + "shell.execute_reply": "2024-09-06T19:33:03.698281Z" } }, "outputs": [], @@ -453,17 +453,17 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:12.675382Z", - "iopub.status.busy": "2024-09-05T19:33:12.675048Z", - "iopub.status.idle": "2024-09-05T19:33:17.078869Z", - "shell.execute_reply": "2024-09-05T19:33:17.078217Z" + "iopub.execute_input": "2024-09-06T19:33:03.700642Z", + "iopub.status.busy": "2024-09-06T19:33:03.700468Z", + "iopub.status.idle": "2024-09-06T19:33:08.790650Z", + "shell.execute_reply": "2024-09-06T19:33:08.789991Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4d2c4ad5eacb4126bc698f579d4d28ae", + "model_id": "501ba738bb5947ccaad0e2cd1f842b14", "version_major": 2, "version_minor": 0 }, @@ -477,7 +477,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "393fbdb1c7654e43a3ed6f454efc540f", + "model_id": "31304fdb61a94d1eb88890ad65421b88", "version_major": 2, "version_minor": 0 }, @@ -491,7 +491,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "35db4effb4c04204b7551eff74a28dc8", + "model_id": "5a73d7a796fe45fca51bb3d3b1eb08df", "version_major": 2, "version_minor": 0 }, @@ -505,7 +505,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "3ca50b4b144e4abdaff387f54e7c1616", + "model_id": "b4b2323ffd9349f1ad2d4d50a0288dc5", "version_major": 2, "version_minor": 0 }, @@ -519,7 +519,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5fe0357646744b24b9dd07d88736919e", + "model_id": "620076f191a74b5c914c7a2b17db4f55", "version_major": 2, "version_minor": 0 }, @@ -533,7 +533,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "b45457b682634601809a638d2d51228a", + "model_id": "e6b938e7ce354e6ebb9c5105fe3bde01", "version_major": 2, "version_minor": 0 }, @@ -547,7 +547,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4478bdb14b2d46f09659ec72b6514d4b", + "model_id": "122704b7d1124989a50bdf83f04c3039", "version_major": 2, "version_minor": 0 }, @@ -601,10 +601,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:17.081636Z", - "iopub.status.busy": "2024-09-05T19:33:17.081277Z", - "iopub.status.idle": "2024-09-05T19:33:17.084159Z", - "shell.execute_reply": "2024-09-05T19:33:17.083592Z" + "iopub.execute_input": "2024-09-06T19:33:08.793264Z", + "iopub.status.busy": "2024-09-06T19:33:08.793080Z", + "iopub.status.idle": "2024-09-06T19:33:08.795949Z", + "shell.execute_reply": "2024-09-06T19:33:08.795369Z" } }, "outputs": [], @@ -626,10 +626,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:17.086157Z", - "iopub.status.busy": "2024-09-05T19:33:17.085840Z", - "iopub.status.idle": "2024-09-05T19:33:17.088592Z", - "shell.execute_reply": "2024-09-05T19:33:17.088024Z" + "iopub.execute_input": "2024-09-06T19:33:08.797847Z", + "iopub.status.busy": "2024-09-06T19:33:08.797676Z", + "iopub.status.idle": "2024-09-06T19:33:08.800380Z", + "shell.execute_reply": "2024-09-06T19:33:08.799925Z" } }, "outputs": [], @@ -644,10 +644,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:17.090704Z", - "iopub.status.busy": "2024-09-05T19:33:17.090390Z", - "iopub.status.idle": "2024-09-05T19:33:19.877083Z", - "shell.execute_reply": "2024-09-05T19:33:19.876407Z" + "iopub.execute_input": "2024-09-06T19:33:08.802410Z", + "iopub.status.busy": "2024-09-06T19:33:08.802073Z", + "iopub.status.idle": "2024-09-06T19:33:11.565675Z", + "shell.execute_reply": "2024-09-06T19:33:11.564900Z" }, "scrolled": true }, @@ -670,10 +670,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:19.880334Z", - "iopub.status.busy": "2024-09-05T19:33:19.879472Z", - "iopub.status.idle": "2024-09-05T19:33:19.887396Z", - "shell.execute_reply": "2024-09-05T19:33:19.886853Z" + "iopub.execute_input": "2024-09-06T19:33:11.569102Z", + "iopub.status.busy": "2024-09-06T19:33:11.568193Z", + "iopub.status.idle": "2024-09-06T19:33:11.576067Z", + "shell.execute_reply": "2024-09-06T19:33:11.575576Z" } }, "outputs": [ @@ -774,10 +774,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:19.889684Z", - "iopub.status.busy": "2024-09-05T19:33:19.889333Z", - "iopub.status.idle": "2024-09-05T19:33:19.893307Z", - "shell.execute_reply": "2024-09-05T19:33:19.892849Z" + "iopub.execute_input": "2024-09-06T19:33:11.578560Z", + "iopub.status.busy": "2024-09-06T19:33:11.578144Z", + "iopub.status.idle": "2024-09-06T19:33:11.582288Z", + "shell.execute_reply": "2024-09-06T19:33:11.581717Z" } }, "outputs": [], @@ -791,10 +791,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:19.895450Z", - "iopub.status.busy": "2024-09-05T19:33:19.895002Z", - "iopub.status.idle": "2024-09-05T19:33:19.898458Z", - "shell.execute_reply": "2024-09-05T19:33:19.897977Z" + "iopub.execute_input": "2024-09-06T19:33:11.584328Z", + "iopub.status.busy": "2024-09-06T19:33:11.583988Z", + "iopub.status.idle": "2024-09-06T19:33:11.587376Z", + "shell.execute_reply": "2024-09-06T19:33:11.586902Z" } }, "outputs": [ @@ -829,10 +829,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:19.900655Z", - "iopub.status.busy": "2024-09-05T19:33:19.900233Z", - "iopub.status.idle": "2024-09-05T19:33:19.903348Z", - "shell.execute_reply": "2024-09-05T19:33:19.902888Z" + "iopub.execute_input": "2024-09-06T19:33:11.589547Z", + "iopub.status.busy": "2024-09-06T19:33:11.589216Z", + "iopub.status.idle": "2024-09-06T19:33:11.592104Z", + "shell.execute_reply": "2024-09-06T19:33:11.591660Z" } }, "outputs": [], @@ -852,10 +852,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:19.905406Z", - "iopub.status.busy": "2024-09-05T19:33:19.904988Z", - "iopub.status.idle": "2024-09-05T19:33:19.912000Z", - "shell.execute_reply": "2024-09-05T19:33:19.911417Z" + "iopub.execute_input": "2024-09-06T19:33:11.594213Z", + "iopub.status.busy": "2024-09-06T19:33:11.593882Z", + "iopub.status.idle": "2024-09-06T19:33:11.600605Z", + "shell.execute_reply": "2024-09-06T19:33:11.600152Z" } }, "outputs": [ @@ -980,10 +980,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:19.914152Z", - "iopub.status.busy": "2024-09-05T19:33:19.913747Z", - "iopub.status.idle": "2024-09-05T19:33:20.177061Z", - "shell.execute_reply": "2024-09-05T19:33:20.176509Z" + "iopub.execute_input": "2024-09-06T19:33:11.602671Z", + "iopub.status.busy": "2024-09-06T19:33:11.602343Z", + "iopub.status.idle": "2024-09-06T19:33:11.828596Z", + "shell.execute_reply": "2024-09-06T19:33:11.828033Z" }, "scrolled": true }, @@ -1022,10 +1022,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:20.179797Z", - "iopub.status.busy": "2024-09-05T19:33:20.179252Z", - "iopub.status.idle": "2024-09-05T19:33:20.355280Z", - "shell.execute_reply": "2024-09-05T19:33:20.354741Z" + "iopub.execute_input": "2024-09-06T19:33:11.831240Z", + "iopub.status.busy": "2024-09-06T19:33:11.830841Z", + "iopub.status.idle": "2024-09-06T19:33:12.009186Z", + "shell.execute_reply": "2024-09-06T19:33:12.008615Z" }, "scrolled": true }, @@ -1073,10 +1073,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:20.358066Z", - "iopub.status.busy": "2024-09-05T19:33:20.357656Z", - "iopub.status.idle": "2024-09-05T19:33:20.361564Z", - "shell.execute_reply": "2024-09-05T19:33:20.361057Z" + "iopub.execute_input": "2024-09-06T19:33:12.011827Z", + "iopub.status.busy": "2024-09-06T19:33:12.011435Z", + "iopub.status.idle": "2024-09-06T19:33:12.015256Z", + "shell.execute_reply": "2024-09-06T19:33:12.014755Z" }, "nbsphinx": "hidden" }, @@ -1120,30 +1120,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "09d35fb89ede417e83cf05378f4c1d39": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6be25bacec524313800d853e93044293", - "placeholder": "​", - "style": "IPY_MODEL_e9a515918bfe4e808d9c5f1b3a7d1141", - "tabbable": null, - "tooltip": null, - "value": " 466k/466k [00:00<00:00, 14.7MB/s]" - } - }, - "0adfc109e92a46c9914db99c6c754136": { + "0459048c4f99420aa195e714b5d9a0fd": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1196,82 +1173,33 @@ "width": null } }, - "0f1399976ca44acfa9a462ec0e9dc906": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "10fad256ee4b4ffbab65a5972fa499b5": { + "0828f51c6fc84a0da65b7ec09b69d580": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "12f629c93c5b4b2aaae0ba809890c2b8": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "14de92ce42e5486488fc27bed6a386f3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", + "_view_name": "ProgressView", + "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_f5590a64e9214dd29b53569cfc71bf3b", - "placeholder": "​", - "style": "IPY_MODEL_fe60b61ef74d44e29e5cec5f3fb9019e", + "layout": "IPY_MODEL_60ed3679f364477387473b90089b8273", + "max": 391.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_9c60afb1733442418ab367430bbb0d68", "tabbable": null, "tooltip": null, - "value": "tokenizer.json: 100%" + "value": 391.0 } }, - "1ac06872854b4fa5ba01e8f6b0bb583e": { + "08df668bdad845f9a6fca994bd1ecd5d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1286,49 +1214,68 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_f2412463d1954925990846db01c4b70b", + "layout": "IPY_MODEL_66ad826330ec48dcbbb58f5f351a1112", "placeholder": "​", - "style": "IPY_MODEL_10fad256ee4b4ffbab65a5972fa499b5", + "style": "IPY_MODEL_8adb666a2a6e4976a7051e3074b29507", "tabbable": null, "tooltip": null, - "value": "tokenizer_config.json: 100%" - } - }, - "1d322b5da4c349b7ad65b5f30c24e940": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "value": "config.json: 100%" } }, - "1fe3817e6f6445c6b8fb7ef23736d705": { - "model_module": "@jupyter-widgets/controls", + "094ab3c4cb4649dbb35cf60d64c57d3d": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "204183d3290441edb23978e5eeb45947": { + "10da9ba1022e498b8f5f3f98c7898223": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1381,7 +1328,49 @@ "width": null } }, - "220e17f41c8144cd9e5d27641e122289": { + "122704b7d1124989a50bdf83f04c3039": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_f6577867a1c041f490b073388151f1be", + "IPY_MODEL_3e00fec335784d3d8f67aef8d5205c3a", + "IPY_MODEL_9692da0a0ad949f39b93867a9112ab58" + ], + "layout": "IPY_MODEL_c876ccec48d84a04bb874ff6b48f8030", + "tabbable": null, + "tooltip": null + } + }, + "154d34bbb18c4e6bb7471d21431c8407": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "18fbcd7e9e6f47f89dbd1bf8da0aac40": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1434,7 +1423,7 @@ "width": null } }, - "27908f5b762941f6961358e4efa65dce": { + "1b4847f4ce0741c391f613e88b131aaa": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1487,7 +1476,67 @@ "width": null } }, - "2ecb4625af794883a0a5e08d6df7fda3": { + "27cccac5127445d09232f53a08657063": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "290f1d04116240fbaa62e5ec4b1a24a2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "2b4d16d0c52d49b4b207e9e5d8450870": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_0459048c4f99420aa195e714b5d9a0fd", + "max": 466062.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_49e660a0942a4523b89e94f5b3f10d5e", + "tabbable": null, + "tooltip": null, + "value": 466062.0 + } + }, + "2fa841989e734ca59ab3392a1c472375": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1540,23 +1589,72 @@ "width": null } }, - "2f191c7cfb9648d4bbff86c6252e1451": { + "31304fdb61a94d1eb88890ad65421b88": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_87bd24bf12c243a6b9cca97e02ea6f70", + "IPY_MODEL_ea5aad74db984381a9502d15f7877dc9", + "IPY_MODEL_b917898a95b64706aca98aba5a2b9969" + ], + "layout": "IPY_MODEL_748657e3cb9543698e92e614f2b8352c", + "tabbable": null, + "tooltip": null + } + }, + "3248bde1a32e421da1664cd2d4d3419e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b8283fed28004000b84e2f53babadac1", + "placeholder": "​", + "style": "IPY_MODEL_8d94e369761f41d087d990935dbe60c2", + "tabbable": null, + "tooltip": null, + "value": "tokenizer.json: 100%" + } + }, + "34ddf006f73a4753b211a5999ec0d671": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "329bd1ed69d04a719ef8be4db50a967c": { + "390080de929440ada6a97f2e0d2dc60f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1574,31 +1672,86 @@ "text_color": null } }, - "35db4effb4c04204b7551eff74a28dc8": { + "3e00fec335784d3d8f67aef8d5205c3a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_62a36fc72b1e4c45badc0f845a1935ce", - "IPY_MODEL_e085586fcfed418eb8ebd9abb08a0974", - "IPY_MODEL_8a0123876e904069832ad5927f07fc8e" - ], - "layout": "IPY_MODEL_27908f5b762941f6961358e4efa65dce", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_908e91876b774d93a02042ae9035283d", + "max": 231508.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_290f1d04116240fbaa62e5ec4b1a24a2", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": 231508.0 } }, - "36f85cf1e9014355bc49f072d21fed52": { + "4071e96fc1124ad3bff4e7fe0f035295": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "470a184131ad4f9789eb904333469e81": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1616,7 +1769,39 @@ "text_color": null } }, - "37e0588b05bd4e82bbc0b13d6108f76e": { + "49e660a0942a4523b89e94f5b3f10d5e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "4bb99f8cedeb4182a94727c634341364": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "4cb28f8d4c2846bba02492de8371ef86": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1669,7 +1854,30 @@ "width": null } }, - "393fbdb1c7654e43a3ed6f454efc540f": { + "4dd3d95d46d846b98d4c8e1fca170cc1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_f7f7d73c85274703989c1a758316f306", + "placeholder": "​", + "style": "IPY_MODEL_96ad5243a28540c1bbd13701050cd8c8", + "tabbable": null, + "tooltip": null, + "value": " 466k/466k [00:00<00:00, 44.9MB/s]" + } + }, + "501ba738bb5947ccaad0e2cd1f842b14": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -1684,16 +1892,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_720a780490394b6da77f76b31c32de99", - "IPY_MODEL_cfcb99d1ea7046c6a9645e1361b08004", - "IPY_MODEL_aae1bd61a7504a71b7b6aa2dfc3774d7" + "IPY_MODEL_5b8638296ff64c2abc68c70b1b8b7469", + "IPY_MODEL_0828f51c6fc84a0da65b7ec09b69d580", + "IPY_MODEL_dc79b458bbac454fbab119272509e252" ], - "layout": "IPY_MODEL_bd3ca5b6f2154c3b89d837f999404304", + "layout": "IPY_MODEL_094ab3c4cb4649dbb35cf60d64c57d3d", "tabbable": null, "tooltip": null } }, - "3ca50b4b144e4abdaff387f54e7c1616": { + "5a73d7a796fe45fca51bb3d3b1eb08df": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -1708,42 +1916,55 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_5cbd210d855842eb8f85d760de6897d8", - "IPY_MODEL_647b3e44874d49b795446d0ad6d17df0", - "IPY_MODEL_887c402846f642a2aacff7d020b047a0" + "IPY_MODEL_08df668bdad845f9a6fca994bd1ecd5d", + "IPY_MODEL_88b14d6b576d4c358576ada8914fc9ae", + "IPY_MODEL_efcccd1f66e4459cb1a7709eadb26866" ], - "layout": "IPY_MODEL_97c2ddf30c1c4ff68739f5d5d4b76ccd", + "layout": "IPY_MODEL_18fbcd7e9e6f47f89dbd1bf8da0aac40", "tabbable": null, "tooltip": null } }, - "4433be0a8c424206af914515e961ee9c": { + "5b8638296ff64c2abc68c70b1b8b7469": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_9fad80c13d274d60a7a1ded9d3f95df9", - "max": 466062.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_c6bc382ab4dd4d2fa54736c9f11cce15", + "layout": "IPY_MODEL_dd603ce908534d83a9e5812536cbaecf", + "placeholder": "​", + "style": "IPY_MODEL_87f402b0764744998c823bf8713ee0ae", "tabbable": null, "tooltip": null, - "value": 466062.0 + "value": ".gitattributes: 100%" + } + }, + "5bed445f56a545b89b799f73d2462bd9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "446f6672d1b74b828dbd588c8352d80e": { + "5f624de673e9405cb01619e550cd02b5": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1796,31 +2017,7 @@ "width": null } }, - "4478bdb14b2d46f09659ec72b6514d4b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_7205dfdca188495e9dd703c5206fd644", - "IPY_MODEL_7d92e68a368d47d9af6828212846a908", - "IPY_MODEL_be833e8f5cff45b292b19ca38209e65c" - ], - "layout": "IPY_MODEL_733e3045825f4ca9be1696c7e613bf9d", - "tabbable": null, - "tooltip": null - } - }, - "460c4f37a9224f5188fb27a460758886": { + "60ed3679f364477387473b90089b8273": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1873,7 +2070,7 @@ "width": null } }, - "4d2c4ad5eacb4126bc698f579d4d28ae": { + "620076f191a74b5c914c7a2b17db4f55": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -1888,16 +2085,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_6b909b0223e946268cc3ca7e7448bc41", - "IPY_MODEL_6f78382944884d9e8744a34ecab2ec5f", - "IPY_MODEL_7a94ccf6df194426bb37dba27b924cc5" + "IPY_MODEL_3248bde1a32e421da1664cd2d4d3419e", + "IPY_MODEL_2b4d16d0c52d49b4b207e9e5d8450870", + "IPY_MODEL_4dd3d95d46d846b98d4c8e1fca170cc1" ], - "layout": "IPY_MODEL_6d84336e0bc54a529ae98aca184badd5", + "layout": "IPY_MODEL_4071e96fc1124ad3bff4e7fe0f035295", "tabbable": null, "tooltip": null } }, - "50b7c0409c64492eae519c364d30137d": { + "626cdb8c3d374c168811bd920a5a68f8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1950,25 +2147,23 @@ "width": null } }, - "52500c0b271b4bdc90670cc54f2fd9ec": { + "62cc1ededdbc4ebaa9a9455fc402d06e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" } }, - "5cbd210d855842eb8f85d760de6897d8": { + "65182ed5c6764915b44ed26f3452c6e8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1983,62 +2178,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_e57f3e7d66d6414d98f5e60ac001480f", + "layout": "IPY_MODEL_93a4c1dfcfc44589926437f1ffdd3a85", "placeholder": "​", - "style": "IPY_MODEL_81c54b14269546eab24143ae3f21efd5", + "style": "IPY_MODEL_c4c2ce7cae784b2093ba53e3609cc2c9", "tabbable": null, "tooltip": null, "value": "pytorch_model.bin: 100%" } }, - "5fe0357646744b24b9dd07d88736919e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_14de92ce42e5486488fc27bed6a386f3", - "IPY_MODEL_4433be0a8c424206af914515e961ee9c", - "IPY_MODEL_09d35fb89ede417e83cf05378f4c1d39" - ], - "layout": "IPY_MODEL_ce93583585d6448d8a89bb80c5739bfc", - "tabbable": null, - "tooltip": null - } - }, - "62a36fc72b1e4c45badc0f845a1935ce": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_c20471b83bb54067b606f37c337e9199", - "placeholder": "​", - "style": "IPY_MODEL_8386099c046b4e3ba5bddc0ce8fb1942", - "tabbable": null, - "tooltip": null, - "value": "config.json: 100%" - } - }, - "62e233345d5d4506a596f58deb0fc0ab": { + "66ad826330ec48dcbbb58f5f351a1112": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2091,7 +2239,25 @@ "width": null } }, - "6396d98831cd4b97aa468c71944171c7": { + "673761d4701d4ee5aaabc0e22e4ec6cb": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "6b23b979b2f7419a924a8685e13b11a7": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2144,109 +2310,25 @@ "width": null } }, - "647b3e44874d49b795446d0ad6d17df0": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6396d98831cd4b97aa468c71944171c7", - "max": 54245363.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_7ed0850b473743459ae5102842a1fe06", - "tabbable": null, - "tooltip": null, - "value": 54245363.0 - } - }, - "6b909b0223e946268cc3ca7e7448bc41": { + "73e88da4acc94040992fd88d0a0d19ed": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_2ecb4625af794883a0a5e08d6df7fda3", - "placeholder": "​", - "style": "IPY_MODEL_d0734afcec2e464abe0ac379e9f7a1e1", - "tabbable": null, - "tooltip": null, - "value": ".gitattributes: 100%" - } - }, - "6be25bacec524313800d853e93044293": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "2.0.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "6d84336e0bc54a529ae98aca184badd5": { + "748657e3cb9543698e92e614f2b8352c": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2299,79 +2381,49 @@ "width": null } }, - "6f78382944884d9e8744a34ecab2ec5f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_204183d3290441edb23978e5eeb45947", - "max": 391.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_2f191c7cfb9648d4bbff86c6252e1451", - "tabbable": null, - "tooltip": null, - "value": 391.0 - } - }, - "7205dfdca188495e9dd703c5206fd644": { + "766a43c7b32e464cb876b478a34ad457": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_37e0588b05bd4e82bbc0b13d6108f76e", - "placeholder": "​", - "style": "IPY_MODEL_faae78ced480410f86e4cf305f9f022b", - "tabbable": null, - "tooltip": null, - "value": "vocab.txt: 100%" + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "720a780490394b6da77f76b31c32de99": { + "84060f74615349bd9e7f70b839d37c3e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", + "_view_name": "ProgressView", + "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_460c4f37a9224f5188fb27a460758886", - "placeholder": "​", - "style": "IPY_MODEL_52500c0b271b4bdc90670cc54f2fd9ec", + "layout": "IPY_MODEL_6b23b979b2f7419a924a8685e13b11a7", + "max": 54245363.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_766a43c7b32e464cb876b478a34ad457", "tabbable": null, "tooltip": null, - "value": "README.md: 100%" + "value": 54245363.0 } }, - "733e3045825f4ca9be1696c7e613bf9d": { + "846cc1a5fbd9438da4609b439141f308": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2424,25 +2476,7 @@ "width": null } }, - "7a45d65746874a788d93b8dc4a69efff": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "7a94ccf6df194426bb37dba27b924cc5": { + "87bd24bf12c243a6b9cca97e02ea6f70": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2457,15 +2491,33 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_82d46b97203b473d86967baca44f2f6d", + "layout": "IPY_MODEL_fa4036e56d43472283e556f828cf84fd", "placeholder": "​", - "style": "IPY_MODEL_7a45d65746874a788d93b8dc4a69efff", + "style": "IPY_MODEL_470a184131ad4f9789eb904333469e81", "tabbable": null, "tooltip": null, - "value": " 391/391 [00:00<00:00, 65.6kB/s]" + "value": "README.md: 100%" + } + }, + "87f402b0764744998c823bf8713ee0ae": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "7d92e68a368d47d9af6828212846a908": { + "88b14d6b576d4c358576ada8914fc9ae": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -2481,51 +2533,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_220e17f41c8144cd9e5d27641e122289", - "max": 231508.0, + "layout": "IPY_MODEL_c634f1241a9e40659957b6a8dd57b66b", + "max": 665.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_0f1399976ca44acfa9a462ec0e9dc906", + "style": "IPY_MODEL_4bb99f8cedeb4182a94727c634341364", "tabbable": null, "tooltip": null, - "value": 231508.0 - } - }, - "7ed0850b473743459ae5102842a1fe06": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "81c54b14269546eab24143ae3f21efd5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "value": 665.0 } }, - "82d46b97203b473d86967baca44f2f6d": { + "89c1af10a3bf46378b2d5ad1570f4844": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2578,7 +2596,7 @@ "width": null } }, - "8386099c046b4e3ba5bddc0ce8fb1942": { + "8adb666a2a6e4976a7051e3074b29507": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2596,53 +2614,25 @@ "text_color": null } }, - "887c402846f642a2aacff7d020b047a0": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_50b7c0409c64492eae519c364d30137d", - "placeholder": "​", - "style": "IPY_MODEL_329bd1ed69d04a719ef8be4db50a967c", - "tabbable": null, - "tooltip": null, - "value": " 54.2M/54.2M [00:00<00:00, 190MB/s]" - } - }, - "8a0123876e904069832ad5927f07fc8e": { + "8d94e369761f41d087d990935dbe60c2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_e569ddc2204f482ea62bedcc240f7f9c", - "placeholder": "​", - "style": "IPY_MODEL_f226342980e94bc5b313958fa8521f8d", - "tabbable": null, - "tooltip": null, - "value": " 665/665 [00:00<00:00, 112kB/s]" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "97c2ddf30c1c4ff68739f5d5d4b76ccd": { + "908e91876b774d93a02042ae9035283d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2695,7 +2685,7 @@ "width": null } }, - "9fad80c13d274d60a7a1ded9d3f95df9": { + "93a4c1dfcfc44589926437f1ffdd3a85": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2748,7 +2738,7 @@ "width": null } }, - "aae1bd61a7504a71b7b6aa2dfc3774d7": { + "9692da0a0ad949f39b93867a9112ab58": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2763,68 +2753,56 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_0adfc109e92a46c9914db99c6c754136", + "layout": "IPY_MODEL_d4493c8ca6d74012b8cda7556ffcfcbb", "placeholder": "​", - "style": "IPY_MODEL_1d322b5da4c349b7ad65b5f30c24e940", + "style": "IPY_MODEL_154d34bbb18c4e6bb7471d21431c8407", "tabbable": null, "tooltip": null, - "value": " 2.21k/2.21k [00:00<00:00, 403kB/s]" + "value": " 232k/232k [00:00<00:00, 3.64MB/s]" } }, - "ac1a3a5a7e344e189e814f4df1968771": { - "model_module": "@jupyter-widgets/base", + "96ad5243a28540c1bbd13701050cd8c8": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "HTMLStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "98a1dc889ed543ddb76c46e918f80a38": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_2fa841989e734ca59ab3392a1c472375", + "placeholder": "​", + "style": "IPY_MODEL_73e88da4acc94040992fd88d0a0d19ed", + "tabbable": null, + "tooltip": null, + "value": "tokenizer_config.json: 100%" } }, - "acdce822381f476590c651c7909c20cf": { + "99072ca746ea485cbb170400eb0e5a45": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2877,7 +2855,23 @@ "width": null } }, - "b0e5e57d6d8b488e86de00432d971a0c": { + "9c60afb1733442418ab367430bbb0d68": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "aa7d45a4b72346af98fb57bd52e6b237": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2930,7 +2924,43 @@ "width": null } }, - "b45457b682634601809a638d2d51228a": { + "ae26881588fc4f9695b5cbd0549eb30a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "af41f929d6ed42e8b6fa4fd762ea4ebe": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "b4b2323ffd9349f1ad2d4d50a0288dc5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -2945,32 +2975,39 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_1ac06872854b4fa5ba01e8f6b0bb583e", - "IPY_MODEL_e898d89a2dee43af80061aebeb4e0678", - "IPY_MODEL_ea77af57f6204512a6205d0aaaf3e3bd" + "IPY_MODEL_65182ed5c6764915b44ed26f3452c6e8", + "IPY_MODEL_84060f74615349bd9e7f70b839d37c3e", + "IPY_MODEL_b76df53d2353433cb2fea0cde0c2d1dd" ], - "layout": "IPY_MODEL_62e233345d5d4506a596f58deb0fc0ab", + "layout": "IPY_MODEL_626cdb8c3d374c168811bd920a5a68f8", "tabbable": null, "tooltip": null } }, - "bc8cd9b955174427802da599715e80bb": { + "b76df53d2353433cb2fea0cde0c2d1dd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_4cb28f8d4c2846bba02492de8371ef86", + "placeholder": "​", + "style": "IPY_MODEL_673761d4701d4ee5aaabc0e22e4ec6cb", + "tabbable": null, + "tooltip": null, + "value": " 54.2M/54.2M [00:00<00:00, 206MB/s]" } }, - "bd3ca5b6f2154c3b89d837f999404304": { + "b8283fed28004000b84e2f53babadac1": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3023,7 +3060,30 @@ "width": null } }, - "be833e8f5cff45b292b19ca38209e65c": { + "b917898a95b64706aca98aba5a2b9969": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_846cc1a5fbd9438da4609b439141f308", + "placeholder": "​", + "style": "IPY_MODEL_af41f929d6ed42e8b6fa4fd762ea4ebe", + "tabbable": null, + "tooltip": null, + "value": " 2.21k/2.21k [00:00<00:00, 314kB/s]" + } + }, + "bc14afac06eb4c26bf5c7c100334328e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -3038,15 +3098,33 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b0e5e57d6d8b488e86de00432d971a0c", + "layout": "IPY_MODEL_10da9ba1022e498b8f5f3f98c7898223", "placeholder": "​", - "style": "IPY_MODEL_36f85cf1e9014355bc49f072d21fed52", + "style": "IPY_MODEL_34ddf006f73a4753b211a5999ec0d671", "tabbable": null, "tooltip": null, - "value": " 232k/232k [00:00<00:00, 34.8MB/s]" + "value": " 48.0/48.0 [00:00<00:00, 8.65kB/s]" + } + }, + "c4c2ce7cae784b2093ba53e3609cc2c9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "c20471b83bb54067b606f37c337e9199": { + "c634f1241a9e40659957b6a8dd57b66b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3099,23 +3177,7 @@ "width": null } }, - "c6bc382ab4dd4d2fa54736c9f11cce15": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "ce93583585d6448d8a89bb80c5739bfc": { + "c876ccec48d84a04bb874ff6b48f8030": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3168,77 +3230,7 @@ "width": null } }, - "cfcb99d1ea7046c6a9645e1361b08004": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_446f6672d1b74b828dbd588c8352d80e", - "max": 2211.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_ef8447b2458e4ddf8e0e2eaf3e1bb8da", - "tabbable": null, - "tooltip": null, - "value": 2211.0 - } - }, - "d0734afcec2e464abe0ac379e9f7a1e1": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "e085586fcfed418eb8ebd9abb08a0974": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_fae238875bf74b01ac59cf3dbf815caf", - "max": 665.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_1fe3817e6f6445c6b8fb7ef23736d705", - "tabbable": null, - "tooltip": null, - "value": 665.0 - } - }, - "e569ddc2204f482ea62bedcc240f7f9c": { + "d4493c8ca6d74012b8cda7556ffcfcbb": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3291,7 +3283,30 @@ "width": null } }, - "e57f3e7d66d6414d98f5e60ac001480f": { + "dc79b458bbac454fbab119272509e252": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_99072ca746ea485cbb170400eb0e5a45", + "placeholder": "​", + "style": "IPY_MODEL_ae26881588fc4f9695b5cbd0549eb30a", + "tabbable": null, + "tooltip": null, + "value": " 391/391 [00:00<00:00, 56.2kB/s]" + } + }, + "dd603ce908534d83a9e5812536cbaecf": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3344,51 +3359,57 @@ "width": null } }, - "e898d89a2dee43af80061aebeb4e0678": { + "e6b938e7ce354e6ebb9c5105fe3bde01": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_ac1a3a5a7e344e189e814f4df1968771", - "max": 48.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_bc8cd9b955174427802da599715e80bb", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_98a1dc889ed543ddb76c46e918f80a38", + "IPY_MODEL_fbbd836ae0ab4f63bed278c2565cd3f1", + "IPY_MODEL_bc14afac06eb4c26bf5c7c100334328e" + ], + "layout": "IPY_MODEL_aa7d45a4b72346af98fb57bd52e6b237", "tabbable": null, - "tooltip": null, - "value": 48.0 + "tooltip": null } }, - "e9a515918bfe4e808d9c5f1b3a7d1141": { + "ea5aad74db984381a9502d15f7877dc9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_5f624de673e9405cb01619e550cd02b5", + "max": 2211.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_62cc1ededdbc4ebaa9a9455fc402d06e", + "tabbable": null, + "tooltip": null, + "value": 2211.0 } }, - "ea77af57f6204512a6205d0aaaf3e3bd": { + "efcccd1f66e4459cb1a7709eadb26866": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -3403,49 +3424,38 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_acdce822381f476590c651c7909c20cf", + "layout": "IPY_MODEL_f94845de837b4883b0f99fb9f3b7ead2", "placeholder": "​", - "style": "IPY_MODEL_12f629c93c5b4b2aaae0ba809890c2b8", + "style": "IPY_MODEL_27cccac5127445d09232f53a08657063", "tabbable": null, "tooltip": null, - "value": " 48.0/48.0 [00:00<00:00, 8.23kB/s]" - } - }, - "ef8447b2458e4ddf8e0e2eaf3e1bb8da": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "value": " 665/665 [00:00<00:00, 124kB/s]" } }, - "f226342980e94bc5b313958fa8521f8d": { + "f6577867a1c041f490b073388151f1be": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HTMLModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HTMLModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_89c1af10a3bf46378b2d5ad1570f4844", + "placeholder": "​", + "style": "IPY_MODEL_390080de929440ada6a97f2e0d2dc60f", + "tabbable": null, + "tooltip": null, + "value": "vocab.txt: 100%" } }, - "f2412463d1954925990846db01c4b70b": { + "f7f7d73c85274703989c1a758316f306": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3498,7 +3508,7 @@ "width": null } }, - "f5590a64e9214dd29b53569cfc71bf3b": { + "f94845de837b4883b0f99fb9f3b7ead2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3551,25 +3561,7 @@ "width": null } }, - "faae78ced480410f86e4cf305f9f022b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "fae238875bf74b01ac59cf3dbf815caf": { + "fa4036e56d43472283e556f828cf84fd": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3622,22 +3614,30 @@ "width": null } }, - "fe60b61ef74d44e29e5cec5f3fb9019e": { + "fbbd836ae0ab4f63bed278c2565cd3f1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_1b4847f4ce0741c391f613e88b131aaa", + "max": 48.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_5bed445f56a545b89b799f73d2462bd9", + "tabbable": null, + "tooltip": null, + "value": 48.0 } } }, diff --git a/master/tutorials/datalab/audio.html b/master/tutorials/datalab/audio.html index 85ec9a685..f932534b5 100644 --- a/master/tutorials/datalab/audio.html +++ b/master/tutorials/datalab/audio.html @@ -1351,7 +1351,7 @@

    5. Use cleanlab to find label issues -{"state": {"cd18ca9fbef94a8db43306835e09a332": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "154e64bae12a4f2d8e65671c37840119": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "ee907f9a6e9c491ca136fbfda0e5e0a1": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_cd18ca9fbef94a8db43306835e09a332", "max": 2041.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_154e64bae12a4f2d8e65671c37840119", "tabbable": null, "tooltip": null, "value": 2041.0}}, "ad1fc452c5504c439e590428a469b666": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d566fdd37641491ab41bf206cde557e5": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "66e19c92c51b496db44b15a5b507b710": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ad1fc452c5504c439e590428a469b666", "placeholder": "\u200b", "style": "IPY_MODEL_d566fdd37641491ab41bf206cde557e5", "tabbable": null, "tooltip": null, "value": "hyperparams.yaml:\u2007100%"}}, "90fd78ffdd834ac9b5ffac06beb8ed03": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "16dc435309f84ebfb937af4723b9a019": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "f1525468540540bc9a15df1068e8130e": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_90fd78ffdd834ac9b5ffac06beb8ed03", "placeholder": "\u200b", "style": "IPY_MODEL_16dc435309f84ebfb937af4723b9a019", "tabbable": null, "tooltip": null, "value": "\u20072.04k/2.04k\u2007[00:00<00:00,\u2007479kB/s]"}}, "de761d347704476fa0a3e6b9e28080f8": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "cdb25710e5ba4e95b957897c0a8ff15e": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_66e19c92c51b496db44b15a5b507b710", "IPY_MODEL_ee907f9a6e9c491ca136fbfda0e5e0a1", "IPY_MODEL_f1525468540540bc9a15df1068e8130e"], "layout": "IPY_MODEL_de761d347704476fa0a3e6b9e28080f8", "tabbable": null, "tooltip": null}}, "f89d5ee8629d40ec8a14637207ab372f": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "1f3a028856264fee8e351bf1dd8383b1": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "3f1b31d22e0d49009bbdccee244e7881": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_f89d5ee8629d40ec8a14637207ab372f", "max": 16887676.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_1f3a028856264fee8e351bf1dd8383b1", "tabbable": null, "tooltip": null, "value": 16887676.0}}, "b7642133d8c34d4d912bd84e9ead2af8": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ba22209daa4c40a88430a8226b0f346a": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "e8a711cadf704f94a9e4ea158fab4c92": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_b7642133d8c34d4d912bd84e9ead2af8", "placeholder": "\u200b", "style": "IPY_MODEL_ba22209daa4c40a88430a8226b0f346a", "tabbable": null, "tooltip": null, "value": "embedding_model.ckpt:\u2007100%"}}, "5a797a83468b42199c5a1b04fad5c52f": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "928f774bbc7544fba8840c9d28c2974b": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "951b9232041b40c1a813db11789edb21": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_5a797a83468b42199c5a1b04fad5c52f", "placeholder": "\u200b", "style": "IPY_MODEL_928f774bbc7544fba8840c9d28c2974b", "tabbable": null, "tooltip": null, "value": "\u200716.9M/16.9M\u2007[00:00<00:00,\u2007185MB/s]"}}, "b22d55955fea4a6e81b4dad1f078f506": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "bf8df34d46b34a05ab2a83672aaed5e1": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_e8a711cadf704f94a9e4ea158fab4c92", "IPY_MODEL_3f1b31d22e0d49009bbdccee244e7881", "IPY_MODEL_951b9232041b40c1a813db11789edb21"], "layout": "IPY_MODEL_b22d55955fea4a6e81b4dad1f078f506", "tabbable": null, "tooltip": null}}, "0c9e0eca2bab4151953b7527eb340910": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "216b05e4aa5c4e1a8f3ee60f4f5a9dfe": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "c47b9c77e0794583b74618d47ea5718a": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_0c9e0eca2bab4151953b7527eb340910", "max": 3201.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_216b05e4aa5c4e1a8f3ee60f4f5a9dfe", "tabbable": null, "tooltip": null, "value": 3201.0}}, "5c917033034f40ff8b3f18838ec90fba": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e6d62d02ded84fd4990ce798c0b364a3": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "af9f54aad3474eac9227e6e4fb35da2d": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_5c917033034f40ff8b3f18838ec90fba", "placeholder": "\u200b", "style": "IPY_MODEL_e6d62d02ded84fd4990ce798c0b364a3", "tabbable": null, "tooltip": null, "value": "mean_var_norm_emb.ckpt:\u2007100%"}}, "6c722d72dc7646d9a5104acca236e442": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "af2cbf510ad04f7fa3b5df8cc9366792": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "a847230825a14abeae004419586a93d9": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_6c722d72dc7646d9a5104acca236e442", "placeholder": "\u200b", "style": "IPY_MODEL_af2cbf510ad04f7fa3b5df8cc9366792", "tabbable": null, "tooltip": null, "value": "\u20073.20k/3.20k\u2007[00:00<00:00,\u2007797kB/s]"}}, "1d83841509b44ed18468f978a2d28aaa": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "db3e5da7fa9a41caa7a4be04f016b2c6": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_af9f54aad3474eac9227e6e4fb35da2d", "IPY_MODEL_c47b9c77e0794583b74618d47ea5718a", "IPY_MODEL_a847230825a14abeae004419586a93d9"], "layout": "IPY_MODEL_1d83841509b44ed18468f978a2d28aaa", "tabbable": null, "tooltip": null}}, "443736061547483b9010861c93503201": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c7c5aa776a8d43ab92ef711ff33f3cfb": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "68ba7f342f464cc3947873e65c2d3569": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_443736061547483b9010861c93503201", "max": 15856877.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_c7c5aa776a8d43ab92ef711ff33f3cfb", "tabbable": null, "tooltip": null, "value": 15856877.0}}, "762087561b9d4154b5c585ba2d8e2f20": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c237ab4dd5ec46be8804717537efe6cd": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "fab2732c47074338930c0c8ddd90a324": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_762087561b9d4154b5c585ba2d8e2f20", "placeholder": "\u200b", "style": "IPY_MODEL_c237ab4dd5ec46be8804717537efe6cd", "tabbable": null, "tooltip": null, "value": "classifier.ckpt:\u2007100%"}}, "b083f3c18acd4001b212b89121e40255": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ff7877413d814a208f7f702e4e75a961": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "d0e1290fa89542e2811205d7ff27d396": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_b083f3c18acd4001b212b89121e40255", "placeholder": "\u200b", "style": "IPY_MODEL_ff7877413d814a208f7f702e4e75a961", "tabbable": null, "tooltip": null, "value": "\u200715.9M/15.9M\u2007[00:00<00:00,\u2007284MB/s]"}}, "c4fe1edeaea44a6cb2e00460ef8510ea": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "8ee8d7e516804bc8a1d41bb8519177d1": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_fab2732c47074338930c0c8ddd90a324", "IPY_MODEL_68ba7f342f464cc3947873e65c2d3569", "IPY_MODEL_d0e1290fa89542e2811205d7ff27d396"], "layout": "IPY_MODEL_c4fe1edeaea44a6cb2e00460ef8510ea", "tabbable": null, "tooltip": null}}, "0ac3ab7ed1fa4817ad8d2ff6240058c2": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "399de27fc5fb401bb57ec59469e9385b": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "c967786b2b46488789662efb4800e58e": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_0ac3ab7ed1fa4817ad8d2ff6240058c2", "max": 128619.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_399de27fc5fb401bb57ec59469e9385b", "tabbable": null, "tooltip": null, "value": 128619.0}}, "b420e431ecef46f9ab11cd0de264f596": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "fc55ef5dc3374f9893e79657e1ff3472": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "de6e8b7c78564371956a0428b0c94a2e": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_b420e431ecef46f9ab11cd0de264f596", "placeholder": "\u200b", "style": "IPY_MODEL_fc55ef5dc3374f9893e79657e1ff3472", "tabbable": null, "tooltip": null, "value": "label_encoder.txt:\u2007100%"}}, "adfc4c39485b47baa8219565f0ac4d12": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ec833e24c78e4e30811c165aa3d20da9": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "51b10ab6596944e4ae19611522f678ac": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_adfc4c39485b47baa8219565f0ac4d12", "placeholder": "\u200b", "style": "IPY_MODEL_ec833e24c78e4e30811c165aa3d20da9", "tabbable": null, "tooltip": null, "value": "\u2007129k/129k\u2007[00:00<00:00,\u200710.1MB/s]"}}, "bffab5547626456a909cb47e0bbb3bbc": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "243a883e57e44f36a54b859f5da85f4e": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_de6e8b7c78564371956a0428b0c94a2e", "IPY_MODEL_c967786b2b46488789662efb4800e58e", "IPY_MODEL_51b10ab6596944e4ae19611522f678ac"], "layout": "IPY_MODEL_bffab5547626456a909cb47e0bbb3bbc", "tabbable": null, "tooltip": null}}}, "version_major": 2, "version_minor": 0} +{"state": {"0e3467cf59954459ab486aee2ba9c3a5": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "6c036dfeb50042c8984a6a6692fc0f9b": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "318a448eedbf4c68b4b67978734a1ae9": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_0e3467cf59954459ab486aee2ba9c3a5", "max": 2041.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_6c036dfeb50042c8984a6a6692fc0f9b", "tabbable": null, "tooltip": null, "value": 2041.0}}, "700bb6482b2c4111b4ed9390c8470861": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "f9b3a44be9f34f6e93de758ee46b92ec": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "ef0ba41ae31d4fca866f944d42378821": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_700bb6482b2c4111b4ed9390c8470861", "placeholder": "\u200b", "style": "IPY_MODEL_f9b3a44be9f34f6e93de758ee46b92ec", "tabbable": null, "tooltip": null, "value": "hyperparams.yaml:\u2007100%"}}, "2741fbda14764533a6d7865887e84821": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "132a82bf8c9844f59e250a9598747c76": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "6fc0bc69349045329fcb28a46a2fe14b": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_2741fbda14764533a6d7865887e84821", "placeholder": "\u200b", "style": "IPY_MODEL_132a82bf8c9844f59e250a9598747c76", "tabbable": null, "tooltip": null, "value": "\u20072.04k/2.04k\u2007[00:00<00:00,\u2007482kB/s]"}}, "2a2e0134b1234019be47ad459a2c7e6e": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "53dafb78e671406e89f3754d23b34684": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_ef0ba41ae31d4fca866f944d42378821", "IPY_MODEL_318a448eedbf4c68b4b67978734a1ae9", "IPY_MODEL_6fc0bc69349045329fcb28a46a2fe14b"], "layout": "IPY_MODEL_2a2e0134b1234019be47ad459a2c7e6e", "tabbable": null, "tooltip": null}}, "8b0da1e1f92449e49814a4792b3a0a18": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "fa5d63111e8040c8a46a0ef606a7b541": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "9a1d64682df846808b68e96652571971": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_8b0da1e1f92449e49814a4792b3a0a18", "max": 16887676.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_fa5d63111e8040c8a46a0ef606a7b541", "tabbable": null, "tooltip": null, "value": 16887676.0}}, "f948f7fae2bd4b23b89c1a9f86de6cdc": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "0b18f93966c84db6bd40967285652faf": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "6a89c26dda78427781977305cd34e44b": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_f948f7fae2bd4b23b89c1a9f86de6cdc", "placeholder": "\u200b", "style": "IPY_MODEL_0b18f93966c84db6bd40967285652faf", "tabbable": null, "tooltip": null, "value": "embedding_model.ckpt:\u2007100%"}}, "d563179a4e534dd4b15465aa4a240b93": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c0dd17ee1b414e0dbba6940c708a7553": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "08327f8f533f49bb8518d3413af11e27": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_d563179a4e534dd4b15465aa4a240b93", "placeholder": "\u200b", "style": "IPY_MODEL_c0dd17ee1b414e0dbba6940c708a7553", "tabbable": null, "tooltip": null, "value": "\u200716.9M/16.9M\u2007[00:00<00:00,\u2007169MB/s]"}}, "819ab4db9b9249cfb05199eec4ffe2ae": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e4e9c1fa715d49009ec1097cf561d5f6": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_6a89c26dda78427781977305cd34e44b", "IPY_MODEL_9a1d64682df846808b68e96652571971", "IPY_MODEL_08327f8f533f49bb8518d3413af11e27"], "layout": "IPY_MODEL_819ab4db9b9249cfb05199eec4ffe2ae", "tabbable": null, "tooltip": null}}, "7ba99fd178de4f25867b6e37949a6d85": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "f321f0e3281b4b478dffcfb404472020": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "5aded6b96abc4bfebf8a38a3dcad2d6f": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_7ba99fd178de4f25867b6e37949a6d85", "max": 3201.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_f321f0e3281b4b478dffcfb404472020", "tabbable": null, "tooltip": null, "value": 3201.0}}, "71c1b39c84cf47b5a477e26da271fef9": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "7ca38434b4e44b5b86b173c7855b4ff3": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "b4b3cc9f4e4c408998a1c0ebec86d5bc": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_71c1b39c84cf47b5a477e26da271fef9", "placeholder": "\u200b", "style": "IPY_MODEL_7ca38434b4e44b5b86b173c7855b4ff3", "tabbable": null, "tooltip": null, "value": "mean_var_norm_emb.ckpt:\u2007100%"}}, "46e0a3db3d4b44aea458c9d15b1b45b8": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b420c63e4f174bba8f48175457a23dfe": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "4c2a6bff30b84735af3cf83ab6de7ddf": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_46e0a3db3d4b44aea458c9d15b1b45b8", "placeholder": "\u200b", "style": "IPY_MODEL_b420c63e4f174bba8f48175457a23dfe", "tabbable": null, "tooltip": null, "value": "\u20073.20k/3.20k\u2007[00:00<00:00,\u2007804kB/s]"}}, "6eec35a271e4402b8f28109615706306": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "5ee4ab99d955426daf559df8bf71c44f": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_b4b3cc9f4e4c408998a1c0ebec86d5bc", "IPY_MODEL_5aded6b96abc4bfebf8a38a3dcad2d6f", "IPY_MODEL_4c2a6bff30b84735af3cf83ab6de7ddf"], "layout": "IPY_MODEL_6eec35a271e4402b8f28109615706306", "tabbable": null, "tooltip": null}}, "c920632573cc4fe0976140070f9677ec": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b97eebf068ca4e9c85cbadbb4cc103c4": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "31da699ce27d4748a3b0908daaeff226": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_c920632573cc4fe0976140070f9677ec", "max": 15856877.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_b97eebf068ca4e9c85cbadbb4cc103c4", "tabbable": null, "tooltip": null, "value": 15856877.0}}, "dd83345f7f5c46a38920bb555c0f6b9a": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "0dc2781328864c55a124d3ba0119a934": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "30eda8d6d1724ca0a98cb1391ef57cf4": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_dd83345f7f5c46a38920bb555c0f6b9a", "placeholder": "\u200b", "style": "IPY_MODEL_0dc2781328864c55a124d3ba0119a934", "tabbable": null, "tooltip": null, "value": "classifier.ckpt:\u2007100%"}}, "4c6822f78a694818a65c111aed9cd2c2": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e3c6b0d1ab4745c796d69b14cb880bf5": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "c979e50a880a49aeaf6e580f1f3ff7e8": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_4c6822f78a694818a65c111aed9cd2c2", "placeholder": "\u200b", "style": "IPY_MODEL_e3c6b0d1ab4745c796d69b14cb880bf5", "tabbable": null, "tooltip": null, "value": "\u200715.9M/15.9M\u2007[00:00<00:00,\u2007212MB/s]"}}, "e41b0c6637564566b921cc1987c4bf9a": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "2a4a612a6d2846bca788bddf1043cc09": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_30eda8d6d1724ca0a98cb1391ef57cf4", "IPY_MODEL_31da699ce27d4748a3b0908daaeff226", "IPY_MODEL_c979e50a880a49aeaf6e580f1f3ff7e8"], "layout": "IPY_MODEL_e41b0c6637564566b921cc1987c4bf9a", "tabbable": null, "tooltip": null}}, "9f5000cf7d6a4079b14d5f3c666d8d9a": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c12a918e266b40caa2ad3eb5ba27297c": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "15a248e8576b4e1cace7306d79423606": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_9f5000cf7d6a4079b14d5f3c666d8d9a", "max": 128619.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_c12a918e266b40caa2ad3eb5ba27297c", "tabbable": null, "tooltip": null, "value": 128619.0}}, "701065566fa2417290be013d76599838": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "798cb5dd7eb545d5a4188e416dce6f88": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "a79c4f7046b44587aab8c79e98299302": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_701065566fa2417290be013d76599838", "placeholder": "\u200b", "style": "IPY_MODEL_798cb5dd7eb545d5a4188e416dce6f88", "tabbable": null, "tooltip": null, "value": "label_encoder.txt:\u2007100%"}}, "10945e8601a446f2bb59fa1211f86f5b": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "214135184cdb4c61851d09d4776b8681": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "de328081cf5143bda2f18a1f732277b0": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_10945e8601a446f2bb59fa1211f86f5b", "placeholder": "\u200b", "style": "IPY_MODEL_214135184cdb4c61851d09d4776b8681", "tabbable": null, "tooltip": null, "value": "\u2007129k/129k\u2007[00:00<00:00,\u200724.4MB/s]"}}, "b8e950254c7c4bfc904715885aa32fa1": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "f814d21bb5204a479acad09d629678fa": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_a79c4f7046b44587aab8c79e98299302", "IPY_MODEL_15a248e8576b4e1cace7306d79423606", "IPY_MODEL_de328081cf5143bda2f18a1f732277b0"], "layout": "IPY_MODEL_b8e950254c7c4bfc904715885aa32fa1", "tabbable": null, "tooltip": null}}}, "version_major": 2, "version_minor": 0} diff --git a/master/tutorials/datalab/audio.ipynb b/master/tutorials/datalab/audio.ipynb index b45848f49..29bf50217 100644 --- a/master/tutorials/datalab/audio.ipynb +++ b/master/tutorials/datalab/audio.ipynb @@ -78,10 +78,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:23.985917Z", - "iopub.status.busy": "2024-09-05T19:33:23.985402Z", - "iopub.status.idle": "2024-09-05T19:33:29.367561Z", - "shell.execute_reply": "2024-09-05T19:33:29.367003Z" + "iopub.execute_input": "2024-09-06T19:33:15.412497Z", + "iopub.status.busy": "2024-09-06T19:33:15.412315Z", + "iopub.status.idle": "2024-09-06T19:33:20.744505Z", + "shell.execute_reply": "2024-09-06T19:33:20.743930Z" }, "nbsphinx": "hidden" }, @@ -97,7 +97,7 @@ "os.environ[\"TF_CPP_MIN_LOG_LEVEL\"] = \"3\" \n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -131,10 +131,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:29.370261Z", - "iopub.status.busy": "2024-09-05T19:33:29.369732Z", - "iopub.status.idle": "2024-09-05T19:33:29.373038Z", - "shell.execute_reply": "2024-09-05T19:33:29.372567Z" + "iopub.execute_input": "2024-09-06T19:33:20.747320Z", + "iopub.status.busy": "2024-09-06T19:33:20.746730Z", + "iopub.status.idle": "2024-09-06T19:33:20.750172Z", + "shell.execute_reply": "2024-09-06T19:33:20.749624Z" }, "id": "LaEiwXUiVHCS" }, @@ -157,10 +157,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:29.375058Z", - "iopub.status.busy": "2024-09-05T19:33:29.374708Z", - "iopub.status.idle": "2024-09-05T19:33:29.379445Z", - "shell.execute_reply": "2024-09-05T19:33:29.379024Z" + "iopub.execute_input": "2024-09-06T19:33:20.752397Z", + "iopub.status.busy": "2024-09-06T19:33:20.751947Z", + "iopub.status.idle": "2024-09-06T19:33:20.756917Z", + "shell.execute_reply": "2024-09-06T19:33:20.756445Z" }, "nbsphinx": "hidden" }, @@ -208,10 +208,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:29.381661Z", - "iopub.status.busy": "2024-09-05T19:33:29.381318Z", - "iopub.status.idle": "2024-09-05T19:33:31.154738Z", - "shell.execute_reply": "2024-09-05T19:33:31.154062Z" + "iopub.execute_input": "2024-09-06T19:33:20.758862Z", + "iopub.status.busy": "2024-09-06T19:33:20.758684Z", + "iopub.status.idle": "2024-09-06T19:33:22.662809Z", + "shell.execute_reply": "2024-09-06T19:33:22.662142Z" }, "id": "GRDPEg7-VOQe", "outputId": "cb886220-e86e-4a77-9f3a-d7844c37c3a6" @@ -242,10 +242,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:31.157544Z", - "iopub.status.busy": "2024-09-05T19:33:31.157120Z", - "iopub.status.idle": "2024-09-05T19:33:31.168372Z", - "shell.execute_reply": "2024-09-05T19:33:31.167905Z" + "iopub.execute_input": "2024-09-06T19:33:22.665411Z", + "iopub.status.busy": "2024-09-06T19:33:22.665209Z", + "iopub.status.idle": "2024-09-06T19:33:22.675958Z", + "shell.execute_reply": "2024-09-06T19:33:22.675514Z" }, "id": "FDA5sGZwUSur", "outputId": "0cedc509-63fd-4dc3-d32f-4b537dfe3895" @@ -329,10 +329,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:31.170634Z", - "iopub.status.busy": "2024-09-05T19:33:31.170294Z", - "iopub.status.idle": "2024-09-05T19:33:31.177336Z", - "shell.execute_reply": "2024-09-05T19:33:31.176887Z" + "iopub.execute_input": "2024-09-06T19:33:22.677986Z", + "iopub.status.busy": "2024-09-06T19:33:22.677801Z", + "iopub.status.idle": "2024-09-06T19:33:22.684956Z", + "shell.execute_reply": "2024-09-06T19:33:22.684474Z" }, "nbsphinx": "hidden" }, @@ -380,10 +380,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:31.179446Z", - "iopub.status.busy": "2024-09-05T19:33:31.179118Z", - "iopub.status.idle": "2024-09-05T19:33:31.679312Z", - "shell.execute_reply": "2024-09-05T19:33:31.678789Z" + "iopub.execute_input": "2024-09-06T19:33:22.686790Z", + "iopub.status.busy": "2024-09-06T19:33:22.686606Z", + "iopub.status.idle": "2024-09-06T19:33:23.132191Z", + "shell.execute_reply": "2024-09-06T19:33:23.131660Z" }, "id": "dLBvUZLlII5w", "outputId": "c6a4917f-4a82-4a89-9193-415072e45550" @@ -435,10 +435,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:31.681541Z", - "iopub.status.busy": "2024-09-05T19:33:31.681189Z", - "iopub.status.idle": "2024-09-05T19:33:32.306849Z", - "shell.execute_reply": "2024-09-05T19:33:32.306228Z" + "iopub.execute_input": "2024-09-06T19:33:23.134446Z", + "iopub.status.busy": "2024-09-06T19:33:23.134077Z", + "iopub.status.idle": "2024-09-06T19:33:24.169658Z", + "shell.execute_reply": "2024-09-06T19:33:24.169048Z" }, "id": "vL9lkiKsHvKr" }, @@ -474,10 +474,10 @@ "height": 143 }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:32.309368Z", - "iopub.status.busy": "2024-09-05T19:33:32.309050Z", - "iopub.status.idle": "2024-09-05T19:33:32.327458Z", - "shell.execute_reply": "2024-09-05T19:33:32.326924Z" + "iopub.execute_input": "2024-09-06T19:33:24.172059Z", + "iopub.status.busy": "2024-09-06T19:33:24.171874Z", + "iopub.status.idle": "2024-09-06T19:33:24.191001Z", + "shell.execute_reply": "2024-09-06T19:33:24.190537Z" }, "id": "obQYDKdLiUU6", "outputId": "4e923d5c-2cf4-4a5c-827b-0a4fea9d87e4" @@ -557,10 +557,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:32.329740Z", - "iopub.status.busy": "2024-09-05T19:33:32.329293Z", - "iopub.status.idle": "2024-09-05T19:33:32.332721Z", - "shell.execute_reply": "2024-09-05T19:33:32.332184Z" + "iopub.execute_input": "2024-09-06T19:33:24.193080Z", + "iopub.status.busy": "2024-09-06T19:33:24.192898Z", + "iopub.status.idle": "2024-09-06T19:33:24.196091Z", + "shell.execute_reply": "2024-09-06T19:33:24.195633Z" }, "id": "I8JqhOZgi94g" }, @@ -582,10 +582,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:32.334695Z", - "iopub.status.busy": "2024-09-05T19:33:32.334412Z", - "iopub.status.idle": "2024-09-05T19:33:46.947908Z", - "shell.execute_reply": "2024-09-05T19:33:46.947343Z" + "iopub.execute_input": "2024-09-06T19:33:24.198156Z", + "iopub.status.busy": "2024-09-06T19:33:24.197822Z", + "iopub.status.idle": "2024-09-06T19:33:38.175563Z", + "shell.execute_reply": "2024-09-06T19:33:38.174995Z" }, "id": "2FSQ2GR9R_YA" }, @@ -617,10 +617,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:46.950681Z", - "iopub.status.busy": "2024-09-05T19:33:46.950277Z", - "iopub.status.idle": "2024-09-05T19:33:46.954313Z", - "shell.execute_reply": "2024-09-05T19:33:46.953812Z" + "iopub.execute_input": "2024-09-06T19:33:38.178313Z", + "iopub.status.busy": "2024-09-06T19:33:38.177918Z", + "iopub.status.idle": "2024-09-06T19:33:38.181776Z", + "shell.execute_reply": "2024-09-06T19:33:38.181209Z" }, "id": "kAkY31IVXyr8", "outputId": "fd70d8d6-2f11-48d5-ae9c-a8c97d453632" @@ -680,10 +680,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:46.956474Z", - "iopub.status.busy": "2024-09-05T19:33:46.956154Z", - "iopub.status.idle": "2024-09-05T19:33:47.649876Z", - "shell.execute_reply": "2024-09-05T19:33:47.649282Z" + "iopub.execute_input": "2024-09-06T19:33:38.183755Z", + "iopub.status.busy": "2024-09-06T19:33:38.183579Z", + "iopub.status.idle": "2024-09-06T19:33:38.879592Z", + "shell.execute_reply": "2024-09-06T19:33:38.878973Z" }, "id": "i_drkY9YOcw4" }, @@ -717,10 +717,10 @@ "base_uri": "https://localhost:8080/" }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.652693Z", - "iopub.status.busy": "2024-09-05T19:33:47.652256Z", - "iopub.status.idle": "2024-09-05T19:33:47.657423Z", - "shell.execute_reply": "2024-09-05T19:33:47.656894Z" + "iopub.execute_input": "2024-09-06T19:33:38.882730Z", + "iopub.status.busy": "2024-09-06T19:33:38.882295Z", + "iopub.status.idle": "2024-09-06T19:33:38.887349Z", + "shell.execute_reply": "2024-09-06T19:33:38.886834Z" }, "id": "_b-AQeoXOc7q", "outputId": "15ae534a-f517-4906-b177-ca91931a8954" @@ -767,10 +767,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.659937Z", - "iopub.status.busy": "2024-09-05T19:33:47.659554Z", - "iopub.status.idle": "2024-09-05T19:33:47.788740Z", - "shell.execute_reply": "2024-09-05T19:33:47.788068Z" + "iopub.execute_input": "2024-09-06T19:33:38.889963Z", + "iopub.status.busy": "2024-09-06T19:33:38.889560Z", + "iopub.status.idle": "2024-09-06T19:33:38.996371Z", + "shell.execute_reply": "2024-09-06T19:33:38.995754Z" } }, "outputs": [ @@ -807,10 +807,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.791246Z", - "iopub.status.busy": "2024-09-05T19:33:47.791038Z", - "iopub.status.idle": "2024-09-05T19:33:47.803816Z", - "shell.execute_reply": "2024-09-05T19:33:47.803324Z" + "iopub.execute_input": "2024-09-06T19:33:38.998935Z", + "iopub.status.busy": "2024-09-06T19:33:38.998516Z", + "iopub.status.idle": "2024-09-06T19:33:39.011487Z", + "shell.execute_reply": "2024-09-06T19:33:39.010948Z" }, "scrolled": true }, @@ -870,10 +870,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.805893Z", - "iopub.status.busy": "2024-09-05T19:33:47.805707Z", - "iopub.status.idle": "2024-09-05T19:33:47.813801Z", - "shell.execute_reply": "2024-09-05T19:33:47.813238Z" + "iopub.execute_input": "2024-09-06T19:33:39.013725Z", + "iopub.status.busy": "2024-09-06T19:33:39.013368Z", + "iopub.status.idle": "2024-09-06T19:33:39.021505Z", + "shell.execute_reply": "2024-09-06T19:33:39.020914Z" } }, "outputs": [ @@ -977,10 +977,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.815901Z", - "iopub.status.busy": "2024-09-05T19:33:47.815566Z", - "iopub.status.idle": "2024-09-05T19:33:47.819837Z", - "shell.execute_reply": "2024-09-05T19:33:47.819362Z" + "iopub.execute_input": "2024-09-06T19:33:39.023705Z", + "iopub.status.busy": "2024-09-06T19:33:39.023358Z", + "iopub.status.idle": "2024-09-06T19:33:39.027633Z", + "shell.execute_reply": "2024-09-06T19:33:39.027085Z" } }, "outputs": [ @@ -1018,10 +1018,10 @@ "height": 237 }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.821906Z", - "iopub.status.busy": "2024-09-05T19:33:47.821589Z", - "iopub.status.idle": "2024-09-05T19:33:47.827106Z", - "shell.execute_reply": "2024-09-05T19:33:47.826568Z" + "iopub.execute_input": "2024-09-06T19:33:39.029757Z", + "iopub.status.busy": "2024-09-06T19:33:39.029380Z", + "iopub.status.idle": "2024-09-06T19:33:39.035357Z", + "shell.execute_reply": "2024-09-06T19:33:39.034867Z" }, "id": "FQwRHgbclpsO", "outputId": "fee5c335-c00e-4fcc-f22b-718705e93182" @@ -1148,10 +1148,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.829139Z", - "iopub.status.busy": "2024-09-05T19:33:47.828942Z", - "iopub.status.idle": "2024-09-05T19:33:47.943778Z", - "shell.execute_reply": "2024-09-05T19:33:47.943280Z" + "iopub.execute_input": "2024-09-06T19:33:39.037583Z", + "iopub.status.busy": "2024-09-06T19:33:39.037235Z", + "iopub.status.idle": "2024-09-06T19:33:39.148961Z", + "shell.execute_reply": "2024-09-06T19:33:39.148428Z" }, "id": "ff1NFVlDoysO", "outputId": "8141a036-44c1-4349-c338-880432513e37" @@ -1205,10 +1205,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:47.946131Z", - "iopub.status.busy": "2024-09-05T19:33:47.945662Z", - "iopub.status.idle": "2024-09-05T19:33:48.054912Z", - "shell.execute_reply": "2024-09-05T19:33:48.054339Z" + "iopub.execute_input": "2024-09-06T19:33:39.151080Z", + "iopub.status.busy": "2024-09-06T19:33:39.150801Z", + "iopub.status.idle": "2024-09-06T19:33:39.254384Z", + "shell.execute_reply": "2024-09-06T19:33:39.253890Z" }, "id": "GZgovGkdiaiP", "outputId": "d76b2ccf-8be2-4f3a-df4c-2c5c99150db7" @@ -1253,10 +1253,10 @@ "height": 92 }, "execution": { - "iopub.execute_input": "2024-09-05T19:33:48.057270Z", - "iopub.status.busy": "2024-09-05T19:33:48.056812Z", - "iopub.status.idle": "2024-09-05T19:33:48.160591Z", - "shell.execute_reply": "2024-09-05T19:33:48.160001Z" + "iopub.execute_input": "2024-09-06T19:33:39.256524Z", + "iopub.status.busy": "2024-09-06T19:33:39.256169Z", + "iopub.status.idle": "2024-09-06T19:33:39.357567Z", + "shell.execute_reply": "2024-09-06T19:33:39.356999Z" }, "id": "lfa2eHbMwG8R", "outputId": "6627ebe2-d439-4bf5-e2cb-44f6278ae86c" @@ -1297,10 +1297,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:48.162787Z", - "iopub.status.busy": "2024-09-05T19:33:48.162458Z", - "iopub.status.idle": "2024-09-05T19:33:48.266360Z", - "shell.execute_reply": "2024-09-05T19:33:48.265774Z" + "iopub.execute_input": "2024-09-06T19:33:39.359754Z", + "iopub.status.busy": "2024-09-06T19:33:39.359388Z", + "iopub.status.idle": "2024-09-06T19:33:39.459179Z", + "shell.execute_reply": "2024-09-06T19:33:39.458626Z" } }, "outputs": [ @@ -1348,10 +1348,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:48.268741Z", - "iopub.status.busy": "2024-09-05T19:33:48.268263Z", - "iopub.status.idle": "2024-09-05T19:33:48.271596Z", - "shell.execute_reply": "2024-09-05T19:33:48.271058Z" + "iopub.execute_input": "2024-09-06T19:33:39.461397Z", + "iopub.status.busy": "2024-09-06T19:33:39.461068Z", + "iopub.status.idle": "2024-09-06T19:33:39.464273Z", + "shell.execute_reply": "2024-09-06T19:33:39.463742Z" }, "nbsphinx": "hidden" }, @@ -1392,7 +1392,66 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "0ac3ab7ed1fa4817ad8d2ff6240058c2": { + "08327f8f533f49bb8518d3413af11e27": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d563179a4e534dd4b15465aa4a240b93", + "placeholder": "​", + "style": "IPY_MODEL_c0dd17ee1b414e0dbba6940c708a7553", + "tabbable": null, + "tooltip": null, + "value": " 16.9M/16.9M [00:00<00:00, 169MB/s]" + } + }, + "0b18f93966c84db6bd40967285652faf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "0dc2781328864c55a124d3ba0119a934": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "0e3467cf59954459ab486aee2ba9c3a5": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1445,7 +1504,7 @@ "width": null } }, - "0c9e0eca2bab4151953b7527eb340910": { + "10945e8601a446f2bb59fa1211f86f5b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1498,23 +1557,51 @@ "width": null } }, - "154e64bae12a4f2d8e65671c37840119": { + "132a82bf8c9844f59e250a9598747c76": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "16dc435309f84ebfb937af4723b9a019": { + "15a248e8576b4e1cace7306d79423606": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_9f5000cf7d6a4079b14d5f3c666d8d9a", + "max": 128619.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_c12a918e266b40caa2ad3eb5ba27297c", + "tabbable": null, + "tooltip": null, + "value": 128619.0 + } + }, + "214135184cdb4c61851d09d4776b8681": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1532,7 +1619,7 @@ "text_color": null } }, - "1d83841509b44ed18468f978a2d28aaa": { + "2741fbda14764533a6d7865887e84821": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1585,79 +1672,133 @@ "width": null } }, - "1f3a028856264fee8e351bf1dd8383b1": { - "model_module": "@jupyter-widgets/controls", + "2a2e0134b1234019be47ad459a2c7e6e": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "216b05e4aa5c4e1a8f3ee60f4f5a9dfe": { + "2a4a612a6d2846bca788bddf1043cc09": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HBoxModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_30eda8d6d1724ca0a98cb1391ef57cf4", + "IPY_MODEL_31da699ce27d4748a3b0908daaeff226", + "IPY_MODEL_c979e50a880a49aeaf6e580f1f3ff7e8" + ], + "layout": "IPY_MODEL_e41b0c6637564566b921cc1987c4bf9a", + "tabbable": null, + "tooltip": null } }, - "243a883e57e44f36a54b859f5da85f4e": { + "30eda8d6d1724ca0a98cb1391ef57cf4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_de6e8b7c78564371956a0428b0c94a2e", - "IPY_MODEL_c967786b2b46488789662efb4800e58e", - "IPY_MODEL_51b10ab6596944e4ae19611522f678ac" - ], - "layout": "IPY_MODEL_bffab5547626456a909cb47e0bbb3bbc", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_dd83345f7f5c46a38920bb555c0f6b9a", + "placeholder": "​", + "style": "IPY_MODEL_0dc2781328864c55a124d3ba0119a934", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": "classifier.ckpt: 100%" } }, - "399de27fc5fb401bb57ec59469e9385b": { + "318a448eedbf4c68b4b67978734a1ae9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_0e3467cf59954459ab486aee2ba9c3a5", + "max": 2041.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_6c036dfeb50042c8984a6a6692fc0f9b", + "tabbable": null, + "tooltip": null, + "value": 2041.0 } }, - "3f1b31d22e0d49009bbdccee244e7881": { + "31da699ce27d4748a3b0908daaeff226": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -1673,17 +1814,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_f89d5ee8629d40ec8a14637207ab372f", - "max": 16887676.0, + "layout": "IPY_MODEL_c920632573cc4fe0976140070f9677ec", + "max": 15856877.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_1f3a028856264fee8e351bf1dd8383b1", + "style": "IPY_MODEL_b97eebf068ca4e9c85cbadbb4cc103c4", "tabbable": null, "tooltip": null, - "value": 16887676.0 + "value": 15856877.0 } }, - "443736061547483b9010861c93503201": { + "46e0a3db3d4b44aea458c9d15b1b45b8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1736,7 +1877,7 @@ "width": null } }, - "51b10ab6596944e4ae19611522f678ac": { + "4c2a6bff30b84735af3cf83ab6de7ddf": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1751,15 +1892,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_adfc4c39485b47baa8219565f0ac4d12", + "layout": "IPY_MODEL_46e0a3db3d4b44aea458c9d15b1b45b8", "placeholder": "​", - "style": "IPY_MODEL_ec833e24c78e4e30811c165aa3d20da9", + "style": "IPY_MODEL_b420c63e4f174bba8f48175457a23dfe", "tabbable": null, "tooltip": null, - "value": " 129k/129k [00:00<00:00, 10.1MB/s]" + "value": " 3.20k/3.20k [00:00<00:00, 804kB/s]" } }, - "5a797a83468b42199c5a1b04fad5c52f": { + "4c6822f78a694818a65c111aed9cd2c2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1812,7 +1953,120 @@ "width": null } }, - "5c917033034f40ff8b3f18838ec90fba": { + "53dafb78e671406e89f3754d23b34684": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_ef0ba41ae31d4fca866f944d42378821", + "IPY_MODEL_318a448eedbf4c68b4b67978734a1ae9", + "IPY_MODEL_6fc0bc69349045329fcb28a46a2fe14b" + ], + "layout": "IPY_MODEL_2a2e0134b1234019be47ad459a2c7e6e", + "tabbable": null, + "tooltip": null + } + }, + "5aded6b96abc4bfebf8a38a3dcad2d6f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_7ba99fd178de4f25867b6e37949a6d85", + "max": 3201.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_f321f0e3281b4b478dffcfb404472020", + "tabbable": null, + "tooltip": null, + "value": 3201.0 + } + }, + "5ee4ab99d955426daf559df8bf71c44f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_b4b3cc9f4e4c408998a1c0ebec86d5bc", + "IPY_MODEL_5aded6b96abc4bfebf8a38a3dcad2d6f", + "IPY_MODEL_4c2a6bff30b84735af3cf83ab6de7ddf" + ], + "layout": "IPY_MODEL_6eec35a271e4402b8f28109615706306", + "tabbable": null, + "tooltip": null + } + }, + "6a89c26dda78427781977305cd34e44b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_f948f7fae2bd4b23b89c1a9f86de6cdc", + "placeholder": "​", + "style": "IPY_MODEL_0b18f93966c84db6bd40967285652faf", + "tabbable": null, + "tooltip": null, + "value": "embedding_model.ckpt: 100%" + } + }, + "6c036dfeb50042c8984a6a6692fc0f9b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "6eec35a271e4402b8f28109615706306": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1865,7 +2119,7 @@ "width": null } }, - "66e19c92c51b496db44b15a5b507b710": { + "6fc0bc69349045329fcb28a46a2fe14b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1880,41 +2134,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_ad1fc452c5504c439e590428a469b666", + "layout": "IPY_MODEL_2741fbda14764533a6d7865887e84821", "placeholder": "​", - "style": "IPY_MODEL_d566fdd37641491ab41bf206cde557e5", - "tabbable": null, - "tooltip": null, - "value": "hyperparams.yaml: 100%" - } - }, - "68ba7f342f464cc3947873e65c2d3569": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_443736061547483b9010861c93503201", - "max": 15856877.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_c7c5aa776a8d43ab92ef711ff33f3cfb", + "style": "IPY_MODEL_132a82bf8c9844f59e250a9598747c76", "tabbable": null, "tooltip": null, - "value": 15856877.0 + "value": " 2.04k/2.04k [00:00<00:00, 482kB/s]" } }, - "6c722d72dc7646d9a5104acca236e442": { + "700bb6482b2c4111b4ed9390c8470861": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1967,7 +2195,7 @@ "width": null } }, - "762087561b9d4154b5c585ba2d8e2f20": { + "701065566fa2417290be013d76599838": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2020,31 +2248,7 @@ "width": null } }, - "8ee8d7e516804bc8a1d41bb8519177d1": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_fab2732c47074338930c0c8ddd90a324", - "IPY_MODEL_68ba7f342f464cc3947873e65c2d3569", - "IPY_MODEL_d0e1290fa89542e2811205d7ff27d396" - ], - "layout": "IPY_MODEL_c4fe1edeaea44a6cb2e00460ef8510ea", - "tabbable": null, - "tooltip": null - } - }, - "90fd78ffdd834ac9b5ffac06beb8ed03": { + "71c1b39c84cf47b5a477e26da271fef9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2097,7 +2301,7 @@ "width": null } }, - "928f774bbc7544fba8840c9d28c2974b": { + "798cb5dd7eb545d5a4188e416dce6f88": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2115,106 +2319,7 @@ "text_color": null } }, - "951b9232041b40c1a813db11789edb21": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_5a797a83468b42199c5a1b04fad5c52f", - "placeholder": "​", - "style": "IPY_MODEL_928f774bbc7544fba8840c9d28c2974b", - "tabbable": null, - "tooltip": null, - "value": " 16.9M/16.9M [00:00<00:00, 185MB/s]" - } - }, - "a847230825a14abeae004419586a93d9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6c722d72dc7646d9a5104acca236e442", - "placeholder": "​", - "style": "IPY_MODEL_af2cbf510ad04f7fa3b5df8cc9366792", - "tabbable": null, - "tooltip": null, - "value": " 3.20k/3.20k [00:00<00:00, 797kB/s]" - } - }, - "ad1fc452c5504c439e590428a469b666": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "2.0.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "adfc4c39485b47baa8219565f0ac4d12": { + "7ba99fd178de4f25867b6e37949a6d85": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2267,7 +2372,7 @@ "width": null } }, - "af2cbf510ad04f7fa3b5df8cc9366792": { + "7ca38434b4e44b5b86b173c7855b4ff3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2285,30 +2390,7 @@ "text_color": null } }, - "af9f54aad3474eac9227e6e4fb35da2d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_5c917033034f40ff8b3f18838ec90fba", - "placeholder": "​", - "style": "IPY_MODEL_e6d62d02ded84fd4990ce798c0b364a3", - "tabbable": null, - "tooltip": null, - "value": "mean_var_norm_emb.ckpt: 100%" - } - }, - "b083f3c18acd4001b212b89121e40255": { + "819ab4db9b9249cfb05199eec4ffe2ae": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2361,7 +2443,7 @@ "width": null } }, - "b22d55955fea4a6e81b4dad1f078f506": { + "8b0da1e1f92449e49814a4792b3a0a18": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2414,7 +2496,33 @@ "width": null } }, - "b420e431ecef46f9ab11cd0de264f596": { + "9a1d64682df846808b68e96652571971": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_8b0da1e1f92449e49814a4792b3a0a18", + "max": 16887676.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_fa5d63111e8040c8a46a0ef606a7b541", + "tabbable": null, + "tooltip": null, + "value": 16887676.0 + } + }, + "9f5000cf7d6a4079b14d5f3c666d8d9a": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2467,7 +2575,71 @@ "width": null } }, - "b7642133d8c34d4d912bd84e9ead2af8": { + "a79c4f7046b44587aab8c79e98299302": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_701065566fa2417290be013d76599838", + "placeholder": "​", + "style": "IPY_MODEL_798cb5dd7eb545d5a4188e416dce6f88", + "tabbable": null, + "tooltip": null, + "value": "label_encoder.txt: 100%" + } + }, + "b420c63e4f174bba8f48175457a23dfe": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "b4b3cc9f4e4c408998a1c0ebec86d5bc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_71c1b39c84cf47b5a477e26da271fef9", + "placeholder": "​", + "style": "IPY_MODEL_7ca38434b4e44b5b86b173c7855b4ff3", + "tabbable": null, + "tooltip": null, + "value": "mean_var_norm_emb.ckpt: 100%" + } + }, + "b8e950254c7c4bfc904715885aa32fa1": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2520,7 +2692,23 @@ "width": null } }, - "ba22209daa4c40a88430a8226b0f346a": { + "b97eebf068ca4e9c85cbadbb4cc103c4": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "c0dd17ee1b414e0dbba6940c708a7553": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2538,31 +2726,23 @@ "text_color": null } }, - "bf8df34d46b34a05ab2a83672aaed5e1": { + "c12a918e266b40caa2ad3eb5ba27297c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_e8a711cadf704f94a9e4ea158fab4c92", - "IPY_MODEL_3f1b31d22e0d49009bbdccee244e7881", - "IPY_MODEL_951b9232041b40c1a813db11789edb21" - ], - "layout": "IPY_MODEL_b22d55955fea4a6e81b4dad1f078f506", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "bffab5547626456a909cb47e0bbb3bbc": { + "c920632573cc4fe0976140070f9677ec": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2615,51 +2795,30 @@ "width": null } }, - "c237ab4dd5ec46be8804717537efe6cd": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c47b9c77e0794583b74618d47ea5718a": { + "c979e50a880a49aeaf6e580f1f3ff7e8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_0c9e0eca2bab4151953b7527eb340910", - "max": 3201.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_216b05e4aa5c4e1a8f3ee60f4f5a9dfe", + "layout": "IPY_MODEL_4c6822f78a694818a65c111aed9cd2c2", + "placeholder": "​", + "style": "IPY_MODEL_e3c6b0d1ab4745c796d69b14cb880bf5", "tabbable": null, "tooltip": null, - "value": 3201.0 + "value": " 15.9M/15.9M [00:00<00:00, 212MB/s]" } }, - "c4fe1edeaea44a6cb2e00460ef8510ea": { + "d563179a4e534dd4b15465aa4a240b93": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2712,49 +2871,7 @@ "width": null } }, - "c7c5aa776a8d43ab92ef711ff33f3cfb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "c967786b2b46488789662efb4800e58e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_0ac3ab7ed1fa4817ad8d2ff6240058c2", - "max": 128619.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_399de27fc5fb401bb57ec59469e9385b", - "tabbable": null, - "tooltip": null, - "value": 128619.0 - } - }, - "cd18ca9fbef94a8db43306835e09a332": { + "dd83345f7f5c46a38920bb555c0f6b9a": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2807,31 +2924,7 @@ "width": null } }, - "cdb25710e5ba4e95b957897c0a8ff15e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_66e19c92c51b496db44b15a5b507b710", - "IPY_MODEL_ee907f9a6e9c491ca136fbfda0e5e0a1", - "IPY_MODEL_f1525468540540bc9a15df1068e8130e" - ], - "layout": "IPY_MODEL_de761d347704476fa0a3e6b9e28080f8", - "tabbable": null, - "tooltip": null - } - }, - "d0e1290fa89542e2811205d7ff27d396": { + "de328081cf5143bda2f18a1f732277b0": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2846,15 +2939,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b083f3c18acd4001b212b89121e40255", + "layout": "IPY_MODEL_10945e8601a446f2bb59fa1211f86f5b", "placeholder": "​", - "style": "IPY_MODEL_ff7877413d814a208f7f702e4e75a961", + "style": "IPY_MODEL_214135184cdb4c61851d09d4776b8681", "tabbable": null, "tooltip": null, - "value": " 15.9M/15.9M [00:00<00:00, 284MB/s]" + "value": " 129k/129k [00:00<00:00, 24.4MB/s]" } }, - "d566fdd37641491ab41bf206cde557e5": { + "e3c6b0d1ab4745c796d69b14cb880bf5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2872,54 +2965,7 @@ "text_color": null } }, - "db3e5da7fa9a41caa7a4be04f016b2c6": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_af9f54aad3474eac9227e6e4fb35da2d", - "IPY_MODEL_c47b9c77e0794583b74618d47ea5718a", - "IPY_MODEL_a847230825a14abeae004419586a93d9" - ], - "layout": "IPY_MODEL_1d83841509b44ed18468f978a2d28aaa", - "tabbable": null, - "tooltip": null - } - }, - "de6e8b7c78564371956a0428b0c94a2e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b420e431ecef46f9ab11cd0de264f596", - "placeholder": "​", - "style": "IPY_MODEL_fc55ef5dc3374f9893e79657e1ff3472", - "tabbable": null, - "tooltip": null, - "value": "label_encoder.txt: 100%" - } - }, - "de761d347704476fa0a3e6b9e28080f8": { + "e41b0c6637564566b921cc1987c4bf9a": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2972,25 +3018,31 @@ "width": null } }, - "e6d62d02ded84fd4990ce798c0b364a3": { + "e4e9c1fa715d49009ec1097cf561d5f6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_6a89c26dda78427781977305cd34e44b", + "IPY_MODEL_9a1d64682df846808b68e96652571971", + "IPY_MODEL_08327f8f533f49bb8518d3413af11e27" + ], + "layout": "IPY_MODEL_819ab4db9b9249cfb05199eec4ffe2ae", + "tabbable": null, + "tooltip": null } }, - "e8a711cadf704f94a9e4ea158fab4c92": { + "ef0ba41ae31d4fca866f944d42378821": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -3005,82 +3057,55 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b7642133d8c34d4d912bd84e9ead2af8", + "layout": "IPY_MODEL_700bb6482b2c4111b4ed9390c8470861", "placeholder": "​", - "style": "IPY_MODEL_ba22209daa4c40a88430a8226b0f346a", + "style": "IPY_MODEL_f9b3a44be9f34f6e93de758ee46b92ec", "tabbable": null, "tooltip": null, - "value": "embedding_model.ckpt: 100%" + "value": "hyperparams.yaml: 100%" } }, - "ec833e24c78e4e30811c165aa3d20da9": { + "f321f0e3281b4b478dffcfb404472020": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "ee907f9a6e9c491ca136fbfda0e5e0a1": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_cd18ca9fbef94a8db43306835e09a332", - "max": 2041.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_154e64bae12a4f2d8e65671c37840119", - "tabbable": null, - "tooltip": null, - "value": 2041.0 + "bar_color": null, + "description_width": "" } }, - "f1525468540540bc9a15df1068e8130e": { + "f814d21bb5204a479acad09d629678fa": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_90fd78ffdd834ac9b5ffac06beb8ed03", - "placeholder": "​", - "style": "IPY_MODEL_16dc435309f84ebfb937af4723b9a019", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a79c4f7046b44587aab8c79e98299302", + "IPY_MODEL_15a248e8576b4e1cace7306d79423606", + "IPY_MODEL_de328081cf5143bda2f18a1f732277b0" + ], + "layout": "IPY_MODEL_b8e950254c7c4bfc904715885aa32fa1", "tabbable": null, - "tooltip": null, - "value": " 2.04k/2.04k [00:00<00:00, 479kB/s]" + "tooltip": null } }, - "f89d5ee8629d40ec8a14637207ab372f": { + "f948f7fae2bd4b23b89c1a9f86de6cdc": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3133,30 +3158,7 @@ "width": null } }, - "fab2732c47074338930c0c8ddd90a324": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_762087561b9d4154b5c585ba2d8e2f20", - "placeholder": "​", - "style": "IPY_MODEL_c237ab4dd5ec46be8804717537efe6cd", - "tabbable": null, - "tooltip": null, - "value": "classifier.ckpt: 100%" - } - }, - "fc55ef5dc3374f9893e79657e1ff3472": { + "f9b3a44be9f34f6e93de758ee46b92ec": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -3174,22 +3176,20 @@ "text_color": null } }, - "ff7877413d814a208f7f702e4e75a961": { + "fa5d63111e8040c8a46a0ef606a7b541": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" } } }, diff --git a/master/tutorials/datalab/datalab_advanced.html b/master/tutorials/datalab/datalab_advanced.html index 325bae147..5f0020f03 100644 --- a/master/tutorials/datalab/datalab_advanced.html +++ b/master/tutorials/datalab/datalab_advanced.html @@ -1295,7 +1295,7 @@

    Functionality 3: Save and load Datalab objects
    -
    +
    @@ -1570,7 +1570,7 @@

    Functionality 4: Adding a custom IssueManager -{"state": {"d874f116cf3c4dbbb9ebe04233c9f4c4": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "95eab14b7dbf4f61b9ccc05ac74d8bcf": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "f20430f0a23a450ba82d47e0db435359": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_d874f116cf3c4dbbb9ebe04233c9f4c4", "max": 132.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_95eab14b7dbf4f61b9ccc05ac74d8bcf", "tabbable": null, "tooltip": null, "value": 132.0}}, "1cc2bf6b970748e6861611eaa6a3bc8d": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c11e8e6c36d9470698b5e4f30ab57c43": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "fd73fc24b59540c2b09b86a70497ca80": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_1cc2bf6b970748e6861611eaa6a3bc8d", "placeholder": "\u200b", "style": "IPY_MODEL_c11e8e6c36d9470698b5e4f30ab57c43", "tabbable": null, "tooltip": null, "value": "Saving\u2007the\u2007dataset\u2007(1/1\u2007shards):\u2007100%"}}, "ba3943ede9804d09b17cca85b5dc5c1a": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "492d0243100b4918aa5d5b886805738f": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "e19f463e637d445eb4deccde754ebbb6": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ba3943ede9804d09b17cca85b5dc5c1a", "placeholder": "\u200b", "style": "IPY_MODEL_492d0243100b4918aa5d5b886805738f", "tabbable": null, "tooltip": null, "value": "\u2007132/132\u2007[00:00<00:00,\u200710900.52\u2007examples/s]"}}, "f66fdb10d529486cb82c871870bd5ab3": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "176d2317677745c2a258fde8d681c83c": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_fd73fc24b59540c2b09b86a70497ca80", "IPY_MODEL_f20430f0a23a450ba82d47e0db435359", "IPY_MODEL_e19f463e637d445eb4deccde754ebbb6"], "layout": "IPY_MODEL_f66fdb10d529486cb82c871870bd5ab3", "tabbable": null, "tooltip": null}}}, "version_major": 2, "version_minor": 0} +{"state": {"ec547a92716a409bb8eb86bc364258c9": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ba52f0b8569f404584f54443a28a0baf": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "4440624d361b4a39a470c6b36d42b8d3": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ec547a92716a409bb8eb86bc364258c9", "max": 132.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_ba52f0b8569f404584f54443a28a0baf", "tabbable": null, "tooltip": null, "value": 132.0}}, "55ed31e23a4a443bbb5e734bb143d697": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "fd6266d59b69432181af01e5eb3c389d": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "890c901184904e0883bb0bded31d86de": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_55ed31e23a4a443bbb5e734bb143d697", "placeholder": "\u200b", "style": "IPY_MODEL_fd6266d59b69432181af01e5eb3c389d", "tabbable": null, "tooltip": null, "value": "Saving\u2007the\u2007dataset\u2007(1/1\u2007shards):\u2007100%"}}, "eae4cf97733c4548920387dc447b9d98": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "1b84860876254aa29989a5bb614dca8d": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "8e898dc9dd204b2f8ba985adc383a396": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_eae4cf97733c4548920387dc447b9d98", "placeholder": "\u200b", "style": "IPY_MODEL_1b84860876254aa29989a5bb614dca8d", "tabbable": null, "tooltip": null, "value": "\u2007132/132\u2007[00:00<00:00,\u200713525.06\u2007examples/s]"}}, "94329361a5b3479e804741fa80c47e78": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e8a80b5b1ace4f0e9399969281df7d06": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_890c901184904e0883bb0bded31d86de", "IPY_MODEL_4440624d361b4a39a470c6b36d42b8d3", "IPY_MODEL_8e898dc9dd204b2f8ba985adc383a396"], "layout": "IPY_MODEL_94329361a5b3479e804741fa80c47e78", "tabbable": null, "tooltip": null}}}, "version_major": 2, "version_minor": 0} diff --git a/master/tutorials/datalab/datalab_advanced.ipynb b/master/tutorials/datalab/datalab_advanced.ipynb index 0c578e325..1028deca4 100644 --- a/master/tutorials/datalab/datalab_advanced.ipynb +++ b/master/tutorials/datalab/datalab_advanced.ipynb @@ -80,10 +80,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:51.639223Z", - "iopub.status.busy": "2024-09-05T19:33:51.639036Z", - "iopub.status.idle": "2024-09-05T19:33:52.898899Z", - "shell.execute_reply": "2024-09-05T19:33:52.898318Z" + "iopub.execute_input": "2024-09-06T19:33:42.774016Z", + "iopub.status.busy": "2024-09-06T19:33:42.773836Z", + "iopub.status.idle": "2024-09-06T19:33:43.987649Z", + "shell.execute_reply": "2024-09-06T19:33:43.987087Z" }, "nbsphinx": "hidden" }, @@ -93,7 +93,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"] # TODO: make sure this list is updated\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -118,10 +118,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:52.901515Z", - "iopub.status.busy": "2024-09-05T19:33:52.901051Z", - "iopub.status.idle": "2024-09-05T19:33:52.904212Z", - "shell.execute_reply": "2024-09-05T19:33:52.903723Z" + "iopub.execute_input": "2024-09-06T19:33:43.990323Z", + "iopub.status.busy": "2024-09-06T19:33:43.989863Z", + "iopub.status.idle": "2024-09-06T19:33:43.992901Z", + "shell.execute_reply": "2024-09-06T19:33:43.992377Z" } }, "outputs": [], @@ -252,10 +252,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:52.906199Z", - "iopub.status.busy": "2024-09-05T19:33:52.906021Z", - "iopub.status.idle": "2024-09-05T19:33:52.914901Z", - "shell.execute_reply": "2024-09-05T19:33:52.914437Z" + "iopub.execute_input": "2024-09-06T19:33:43.995557Z", + "iopub.status.busy": "2024-09-06T19:33:43.995114Z", + "iopub.status.idle": "2024-09-06T19:33:44.005313Z", + "shell.execute_reply": "2024-09-06T19:33:44.004712Z" }, "nbsphinx": "hidden" }, @@ -353,10 +353,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:52.916877Z", - "iopub.status.busy": "2024-09-05T19:33:52.916698Z", - "iopub.status.idle": "2024-09-05T19:33:52.921682Z", - "shell.execute_reply": "2024-09-05T19:33:52.921248Z" + "iopub.execute_input": "2024-09-06T19:33:44.007445Z", + "iopub.status.busy": "2024-09-06T19:33:44.007143Z", + "iopub.status.idle": "2024-09-06T19:33:44.012113Z", + "shell.execute_reply": "2024-09-06T19:33:44.011528Z" } }, "outputs": [], @@ -445,10 +445,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:52.923768Z", - "iopub.status.busy": "2024-09-05T19:33:52.923431Z", - "iopub.status.idle": "2024-09-05T19:33:53.109668Z", - "shell.execute_reply": "2024-09-05T19:33:53.109095Z" + "iopub.execute_input": "2024-09-06T19:33:44.014273Z", + "iopub.status.busy": "2024-09-06T19:33:44.013973Z", + "iopub.status.idle": "2024-09-06T19:33:44.198978Z", + "shell.execute_reply": "2024-09-06T19:33:44.198432Z" }, "nbsphinx": "hidden" }, @@ -517,10 +517,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:53.112201Z", - "iopub.status.busy": "2024-09-05T19:33:53.111801Z", - "iopub.status.idle": "2024-09-05T19:33:53.486912Z", - "shell.execute_reply": "2024-09-05T19:33:53.486234Z" + "iopub.execute_input": "2024-09-06T19:33:44.201674Z", + "iopub.status.busy": "2024-09-06T19:33:44.201189Z", + "iopub.status.idle": "2024-09-06T19:33:44.572697Z", + "shell.execute_reply": "2024-09-06T19:33:44.572078Z" } }, "outputs": [ @@ -569,10 +569,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:53.489255Z", - "iopub.status.busy": "2024-09-05T19:33:53.488885Z", - "iopub.status.idle": "2024-09-05T19:33:53.512031Z", - "shell.execute_reply": "2024-09-05T19:33:53.511558Z" + "iopub.execute_input": "2024-09-06T19:33:44.574957Z", + "iopub.status.busy": "2024-09-06T19:33:44.574618Z", + "iopub.status.idle": "2024-09-06T19:33:44.598417Z", + "shell.execute_reply": "2024-09-06T19:33:44.597853Z" } }, "outputs": [], @@ -608,10 +608,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:53.514134Z", - "iopub.status.busy": "2024-09-05T19:33:53.513789Z", - "iopub.status.idle": "2024-09-05T19:33:53.524954Z", - "shell.execute_reply": "2024-09-05T19:33:53.524500Z" + "iopub.execute_input": "2024-09-06T19:33:44.600565Z", + "iopub.status.busy": "2024-09-06T19:33:44.600242Z", + "iopub.status.idle": "2024-09-06T19:33:44.611542Z", + "shell.execute_reply": "2024-09-06T19:33:44.611124Z" } }, "outputs": [], @@ -642,10 +642,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:53.527001Z", - "iopub.status.busy": "2024-09-05T19:33:53.526670Z", - "iopub.status.idle": "2024-09-05T19:33:55.662115Z", - "shell.execute_reply": "2024-09-05T19:33:55.661472Z" + "iopub.execute_input": "2024-09-06T19:33:44.613571Z", + "iopub.status.busy": "2024-09-06T19:33:44.613277Z", + "iopub.status.idle": "2024-09-06T19:33:46.668917Z", + "shell.execute_reply": "2024-09-06T19:33:46.668293Z" } }, "outputs": [ @@ -714,10 +714,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.664771Z", - "iopub.status.busy": "2024-09-05T19:33:55.664277Z", - "iopub.status.idle": "2024-09-05T19:33:55.685806Z", - "shell.execute_reply": "2024-09-05T19:33:55.685335Z" + "iopub.execute_input": "2024-09-06T19:33:46.671429Z", + "iopub.status.busy": "2024-09-06T19:33:46.670969Z", + "iopub.status.idle": "2024-09-06T19:33:46.692283Z", + "shell.execute_reply": "2024-09-06T19:33:46.691706Z" } }, "outputs": [ @@ -830,10 +830,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.688099Z", - "iopub.status.busy": "2024-09-05T19:33:55.687744Z", - "iopub.status.idle": "2024-09-05T19:33:55.705725Z", - "shell.execute_reply": "2024-09-05T19:33:55.705227Z" + "iopub.execute_input": "2024-09-06T19:33:46.694643Z", + "iopub.status.busy": "2024-09-06T19:33:46.694120Z", + "iopub.status.idle": "2024-09-06T19:33:46.711969Z", + "shell.execute_reply": "2024-09-06T19:33:46.711526Z" } }, "outputs": [ @@ -937,10 +937,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.707922Z", - "iopub.status.busy": "2024-09-05T19:33:55.707593Z", - "iopub.status.idle": "2024-09-05T19:33:55.722195Z", - "shell.execute_reply": "2024-09-05T19:33:55.721729Z" + "iopub.execute_input": "2024-09-06T19:33:46.713865Z", + "iopub.status.busy": "2024-09-06T19:33:46.713694Z", + "iopub.status.idle": "2024-09-06T19:33:46.728067Z", + "shell.execute_reply": "2024-09-06T19:33:46.727609Z" } }, "outputs": [ @@ -1075,17 +1075,17 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.724401Z", - "iopub.status.busy": "2024-09-05T19:33:55.724049Z", - "iopub.status.idle": "2024-09-05T19:33:55.745888Z", - "shell.execute_reply": "2024-09-05T19:33:55.745312Z" + "iopub.execute_input": "2024-09-06T19:33:46.729970Z", + "iopub.status.busy": "2024-09-06T19:33:46.729797Z", + "iopub.status.idle": "2024-09-06T19:33:46.748313Z", + "shell.execute_reply": "2024-09-06T19:33:46.747746Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "176d2317677745c2a258fde8d681c83c", + "model_id": "e8a80b5b1ace4f0e9399969281df7d06", "version_major": 2, "version_minor": 0 }, @@ -1121,10 +1121,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.748017Z", - "iopub.status.busy": "2024-09-05T19:33:55.747658Z", - "iopub.status.idle": "2024-09-05T19:33:55.762168Z", - "shell.execute_reply": "2024-09-05T19:33:55.761701Z" + "iopub.execute_input": "2024-09-06T19:33:46.750540Z", + "iopub.status.busy": "2024-09-06T19:33:46.750202Z", + "iopub.status.idle": "2024-09-06T19:33:46.765277Z", + "shell.execute_reply": "2024-09-06T19:33:46.764810Z" } }, "outputs": [ @@ -1247,10 +1247,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.764365Z", - "iopub.status.busy": "2024-09-05T19:33:55.764037Z", - "iopub.status.idle": "2024-09-05T19:33:55.769869Z", - "shell.execute_reply": "2024-09-05T19:33:55.769425Z" + "iopub.execute_input": "2024-09-06T19:33:46.767376Z", + "iopub.status.busy": "2024-09-06T19:33:46.767048Z", + "iopub.status.idle": "2024-09-06T19:33:46.772946Z", + "shell.execute_reply": "2024-09-06T19:33:46.772447Z" } }, "outputs": [], @@ -1307,10 +1307,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:55.772010Z", - "iopub.status.busy": "2024-09-05T19:33:55.771653Z", - "iopub.status.idle": "2024-09-05T19:33:55.789767Z", - "shell.execute_reply": "2024-09-05T19:33:55.789194Z" + "iopub.execute_input": "2024-09-06T19:33:46.774871Z", + "iopub.status.busy": "2024-09-06T19:33:46.774606Z", + "iopub.status.idle": "2024-09-06T19:33:46.792743Z", + "shell.execute_reply": "2024-09-06T19:33:46.792272Z" } }, "outputs": [ @@ -1447,31 +1447,51 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "176d2317677745c2a258fde8d681c83c": { + "1b84860876254aa29989a5bb614dca8d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "4440624d361b4a39a470c6b36d42b8d3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_fd73fc24b59540c2b09b86a70497ca80", - "IPY_MODEL_f20430f0a23a450ba82d47e0db435359", - "IPY_MODEL_e19f463e637d445eb4deccde754ebbb6" - ], - "layout": "IPY_MODEL_f66fdb10d529486cb82c871870bd5ab3", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_ec547a92716a409bb8eb86bc364258c9", + "max": 132.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_ba52f0b8569f404584f54443a28a0baf", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": 132.0 } }, - "1cc2bf6b970748e6861611eaa6a3bc8d": { + "55ed31e23a4a443bbb5e734bb143d697": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1524,41 +1544,53 @@ "width": null } }, - "492d0243100b4918aa5d5b886805738f": { + "890c901184904e0883bb0bded31d86de": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HTMLModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HTMLModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_55ed31e23a4a443bbb5e734bb143d697", + "placeholder": "​", + "style": "IPY_MODEL_fd6266d59b69432181af01e5eb3c389d", + "tabbable": null, + "tooltip": null, + "value": "Saving the dataset (1/1 shards): 100%" } }, - "95eab14b7dbf4f61b9ccc05ac74d8bcf": { + "8e898dc9dd204b2f8ba985adc383a396": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_eae4cf97733c4548920387dc447b9d98", + "placeholder": "​", + "style": "IPY_MODEL_1b84860876254aa29989a5bb614dca8d", + "tabbable": null, + "tooltip": null, + "value": " 132/132 [00:00<00:00, 13525.06 examples/s]" } }, - "ba3943ede9804d09b17cca85b5dc5c1a": { + "94329361a5b3479e804741fa80c47e78": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1611,25 +1643,47 @@ "width": null } }, - "c11e8e6c36d9470698b5e4f30ab57c43": { + "ba52f0b8569f404584f54443a28a0baf": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" } }, - "d874f116cf3c4dbbb9ebe04233c9f4c4": { + "e8a80b5b1ace4f0e9399969281df7d06": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_890c901184904e0883bb0bded31d86de", + "IPY_MODEL_4440624d361b4a39a470c6b36d42b8d3", + "IPY_MODEL_8e898dc9dd204b2f8ba985adc383a396" + ], + "layout": "IPY_MODEL_94329361a5b3479e804741fa80c47e78", + "tabbable": null, + "tooltip": null + } + }, + "eae4cf97733c4548920387dc447b9d98": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1682,56 +1736,7 @@ "width": null } }, - "e19f463e637d445eb4deccde754ebbb6": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_ba3943ede9804d09b17cca85b5dc5c1a", - "placeholder": "​", - "style": "IPY_MODEL_492d0243100b4918aa5d5b886805738f", - "tabbable": null, - "tooltip": null, - "value": " 132/132 [00:00<00:00, 10900.52 examples/s]" - } - }, - "f20430f0a23a450ba82d47e0db435359": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_d874f116cf3c4dbbb9ebe04233c9f4c4", - "max": 132.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_95eab14b7dbf4f61b9ccc05ac74d8bcf", - "tabbable": null, - "tooltip": null, - "value": 132.0 - } - }, - "f66fdb10d529486cb82c871870bd5ab3": { + "ec547a92716a409bb8eb86bc364258c9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1784,27 +1789,22 @@ "width": null } }, - "fd73fc24b59540c2b09b86a70497ca80": { + "fd6266d59b69432181af01e5eb3c389d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_1cc2bf6b970748e6861611eaa6a3bc8d", - "placeholder": "​", - "style": "IPY_MODEL_c11e8e6c36d9470698b5e4f30ab57c43", - "tabbable": null, - "tooltip": null, - "value": "Saving the dataset (1/1 shards): 100%" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } } }, diff --git a/master/tutorials/datalab/datalab_quickstart.ipynb b/master/tutorials/datalab/datalab_quickstart.ipynb index 0682692ed..a75ce5d83 100644 --- a/master/tutorials/datalab/datalab_quickstart.ipynb +++ b/master/tutorials/datalab/datalab_quickstart.ipynb @@ -78,10 +78,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:58.621443Z", - "iopub.status.busy": "2024-09-05T19:33:58.621264Z", - "iopub.status.idle": "2024-09-05T19:33:59.859772Z", - "shell.execute_reply": "2024-09-05T19:33:59.859206Z" + "iopub.execute_input": "2024-09-06T19:33:49.692668Z", + "iopub.status.busy": "2024-09-06T19:33:49.692505Z", + "iopub.status.idle": "2024-09-06T19:33:50.890931Z", + "shell.execute_reply": "2024-09-06T19:33:50.890368Z" }, "nbsphinx": "hidden" }, @@ -91,7 +91,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"] # TODO: make sure this list is updated\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -116,10 +116,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:59.862442Z", - "iopub.status.busy": "2024-09-05T19:33:59.861951Z", - "iopub.status.idle": "2024-09-05T19:33:59.865116Z", - "shell.execute_reply": "2024-09-05T19:33:59.864648Z" + "iopub.execute_input": "2024-09-06T19:33:50.893481Z", + "iopub.status.busy": "2024-09-06T19:33:50.892976Z", + "iopub.status.idle": "2024-09-06T19:33:50.895994Z", + "shell.execute_reply": "2024-09-06T19:33:50.895546Z" } }, "outputs": [], @@ -250,10 +250,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:59.867239Z", - "iopub.status.busy": "2024-09-05T19:33:59.866893Z", - "iopub.status.idle": "2024-09-05T19:33:59.876133Z", - "shell.execute_reply": "2024-09-05T19:33:59.875647Z" + "iopub.execute_input": "2024-09-06T19:33:50.898095Z", + "iopub.status.busy": "2024-09-06T19:33:50.897919Z", + "iopub.status.idle": "2024-09-06T19:33:50.907050Z", + "shell.execute_reply": "2024-09-06T19:33:50.906577Z" }, "nbsphinx": "hidden" }, @@ -356,10 +356,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:59.878037Z", - "iopub.status.busy": "2024-09-05T19:33:59.877859Z", - "iopub.status.idle": "2024-09-05T19:33:59.882519Z", - "shell.execute_reply": "2024-09-05T19:33:59.882088Z" + "iopub.execute_input": "2024-09-06T19:33:50.908860Z", + "iopub.status.busy": "2024-09-06T19:33:50.908672Z", + "iopub.status.idle": "2024-09-06T19:33:50.913284Z", + "shell.execute_reply": "2024-09-06T19:33:50.912693Z" } }, "outputs": [], @@ -448,10 +448,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:33:59.884662Z", - "iopub.status.busy": "2024-09-05T19:33:59.884315Z", - "iopub.status.idle": "2024-09-05T19:34:00.070637Z", - "shell.execute_reply": "2024-09-05T19:34:00.070087Z" + "iopub.execute_input": "2024-09-06T19:33:50.915417Z", + "iopub.status.busy": "2024-09-06T19:33:50.915238Z", + "iopub.status.idle": "2024-09-06T19:33:51.099306Z", + "shell.execute_reply": "2024-09-06T19:33:51.098789Z" }, "nbsphinx": "hidden" }, @@ -520,10 +520,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:00.073480Z", - "iopub.status.busy": "2024-09-05T19:34:00.072974Z", - "iopub.status.idle": "2024-09-05T19:34:00.450121Z", - "shell.execute_reply": "2024-09-05T19:34:00.449499Z" + "iopub.execute_input": "2024-09-06T19:33:51.101790Z", + "iopub.status.busy": "2024-09-06T19:33:51.101450Z", + "iopub.status.idle": "2024-09-06T19:33:51.473593Z", + "shell.execute_reply": "2024-09-06T19:33:51.473003Z" } }, "outputs": [ @@ -559,10 +559,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:00.452506Z", - "iopub.status.busy": "2024-09-05T19:34:00.452151Z", - "iopub.status.idle": "2024-09-05T19:34:00.455103Z", - "shell.execute_reply": "2024-09-05T19:34:00.454519Z" + "iopub.execute_input": "2024-09-06T19:33:51.475866Z", + "iopub.status.busy": "2024-09-06T19:33:51.475414Z", + "iopub.status.idle": "2024-09-06T19:33:51.478399Z", + "shell.execute_reply": "2024-09-06T19:33:51.477816Z" } }, "outputs": [], @@ -602,10 +602,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:00.457413Z", - "iopub.status.busy": "2024-09-05T19:34:00.456957Z", - "iopub.status.idle": "2024-09-05T19:34:00.491429Z", - "shell.execute_reply": "2024-09-05T19:34:00.490831Z" + "iopub.execute_input": "2024-09-06T19:33:51.480745Z", + "iopub.status.busy": "2024-09-06T19:33:51.480341Z", + "iopub.status.idle": "2024-09-06T19:33:51.514306Z", + "shell.execute_reply": "2024-09-06T19:33:51.513859Z" } }, "outputs": [], @@ -638,10 +638,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:00.493928Z", - "iopub.status.busy": "2024-09-05T19:34:00.493522Z", - "iopub.status.idle": "2024-09-05T19:34:02.646706Z", - "shell.execute_reply": "2024-09-05T19:34:02.646060Z" + "iopub.execute_input": "2024-09-06T19:33:51.516441Z", + "iopub.status.busy": "2024-09-06T19:33:51.516020Z", + "iopub.status.idle": "2024-09-06T19:33:53.590850Z", + "shell.execute_reply": "2024-09-06T19:33:53.590263Z" } }, "outputs": [ @@ -685,10 +685,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.649221Z", - "iopub.status.busy": "2024-09-05T19:34:02.648683Z", - "iopub.status.idle": "2024-09-05T19:34:02.667394Z", - "shell.execute_reply": "2024-09-05T19:34:02.666809Z" + "iopub.execute_input": "2024-09-06T19:33:53.593403Z", + "iopub.status.busy": "2024-09-06T19:33:53.592894Z", + "iopub.status.idle": "2024-09-06T19:33:53.611543Z", + "shell.execute_reply": "2024-09-06T19:33:53.610984Z" } }, "outputs": [ @@ -821,10 +821,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.669753Z", - "iopub.status.busy": "2024-09-05T19:34:02.669304Z", - "iopub.status.idle": "2024-09-05T19:34:02.676014Z", - "shell.execute_reply": "2024-09-05T19:34:02.675457Z" + "iopub.execute_input": "2024-09-06T19:33:53.613666Z", + "iopub.status.busy": "2024-09-06T19:33:53.613354Z", + "iopub.status.idle": "2024-09-06T19:33:53.619845Z", + "shell.execute_reply": "2024-09-06T19:33:53.619296Z" } }, "outputs": [ @@ -935,10 +935,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.678030Z", - "iopub.status.busy": "2024-09-05T19:34:02.677711Z", - "iopub.status.idle": "2024-09-05T19:34:02.683562Z", - "shell.execute_reply": "2024-09-05T19:34:02.683103Z" + "iopub.execute_input": "2024-09-06T19:33:53.621866Z", + "iopub.status.busy": "2024-09-06T19:33:53.621559Z", + "iopub.status.idle": "2024-09-06T19:33:53.628504Z", + "shell.execute_reply": "2024-09-06T19:33:53.627959Z" } }, "outputs": [ @@ -1005,10 +1005,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.685598Z", - "iopub.status.busy": "2024-09-05T19:34:02.685423Z", - "iopub.status.idle": "2024-09-05T19:34:02.695863Z", - "shell.execute_reply": "2024-09-05T19:34:02.695434Z" + "iopub.execute_input": "2024-09-06T19:33:53.630721Z", + "iopub.status.busy": "2024-09-06T19:33:53.630404Z", + "iopub.status.idle": "2024-09-06T19:33:53.640976Z", + "shell.execute_reply": "2024-09-06T19:33:53.640522Z" } }, "outputs": [ @@ -1200,10 +1200,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.697910Z", - "iopub.status.busy": "2024-09-05T19:34:02.697731Z", - "iopub.status.idle": "2024-09-05T19:34:02.706917Z", - "shell.execute_reply": "2024-09-05T19:34:02.706369Z" + "iopub.execute_input": "2024-09-06T19:33:53.643037Z", + "iopub.status.busy": "2024-09-06T19:33:53.642719Z", + "iopub.status.idle": "2024-09-06T19:33:53.651678Z", + "shell.execute_reply": "2024-09-06T19:33:53.651115Z" } }, "outputs": [ @@ -1319,10 +1319,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.709149Z", - "iopub.status.busy": "2024-09-05T19:34:02.708833Z", - "iopub.status.idle": "2024-09-05T19:34:02.715398Z", - "shell.execute_reply": "2024-09-05T19:34:02.714928Z" + "iopub.execute_input": "2024-09-06T19:33:53.653852Z", + "iopub.status.busy": "2024-09-06T19:33:53.653447Z", + "iopub.status.idle": "2024-09-06T19:33:53.660374Z", + "shell.execute_reply": "2024-09-06T19:33:53.659816Z" }, "scrolled": true }, @@ -1447,10 +1447,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.717285Z", - "iopub.status.busy": "2024-09-05T19:34:02.717111Z", - "iopub.status.idle": "2024-09-05T19:34:02.726582Z", - "shell.execute_reply": "2024-09-05T19:34:02.726126Z" + "iopub.execute_input": "2024-09-06T19:33:53.662428Z", + "iopub.status.busy": "2024-09-06T19:33:53.662108Z", + "iopub.status.idle": "2024-09-06T19:33:53.671181Z", + "shell.execute_reply": "2024-09-06T19:33:53.670717Z" } }, "outputs": [ @@ -1553,10 +1553,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:02.728531Z", - "iopub.status.busy": "2024-09-05T19:34:02.728359Z", - "iopub.status.idle": "2024-09-05T19:34:02.744474Z", - "shell.execute_reply": "2024-09-05T19:34:02.744039Z" + "iopub.execute_input": "2024-09-06T19:33:53.673080Z", + "iopub.status.busy": "2024-09-06T19:33:53.672905Z", + "iopub.status.idle": "2024-09-06T19:33:53.689334Z", + "shell.execute_reply": "2024-09-06T19:33:53.688736Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/datalab/image.html b/master/tutorials/datalab/image.html index 1ff165966..116c9e30a 100644 --- a/master/tutorials/datalab/image.html +++ b/master/tutorials/datalab/image.html @@ -731,31 +731,31 @@

    2. Fetch and normalize the Fashion-MNIST dataset

    -
    +
    -
    +
    -
    +
    -
    +
    -
    +

    Convert the transformed dataset to a torch dataset. Torch datasets are more efficient with dataloading in practice.

    @@ -1068,7 +1068,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
    -
    +
    @@ -1100,7 +1100,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
    -
    +
    @@ -1132,7 +1132,7 @@

    5. Compute out-of-sample predicted probabilities and feature embeddings
    -
    +
    @@ -1924,35 +1924,35 @@

    Dark images - dark_score is_dark_issue + dark_score 34848 - 0.203922 True + 0.203922 50270 - 0.204588 True + 0.204588 3936 - 0.213098 True + 0.213098 733 - 0.217686 True + 0.217686 8094 - 0.230118 True + 0.230118 @@ -2046,35 +2046,35 @@

    Low information images - is_low_information_issue low_information_score + is_low_information_issue 53050 - True 0.067975 + True 40875 - True 0.089929 + True 9594 - True 0.092601 + True 34825 - True 0.107744 + True 37530 - True 0.108516 + True @@ -2102,7 +2102,7 @@

    Easy ModeCleanlab Studio which will automatically produce one for you. Super easy to use, Cleanlab Studio is no-code platform for data-centric AI that automatically: detects data issues (more types of issues than this cleanlab package), helps you quickly correct these data issues, confidently labels large subsets of an unlabeled dataset, and provides other smart metadata about each of your data points – all powered by a system that automatically trains/deploys the best ML model for your data. Try it for free!

    diff --git a/master/tutorials/datalab/image.ipynb b/master/tutorials/datalab/image.ipynb index f298fc6b0..d0e19982d 100644 --- a/master/tutorials/datalab/image.ipynb +++ b/master/tutorials/datalab/image.ipynb @@ -71,10 +71,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:05.525223Z", - "iopub.status.busy": "2024-09-05T19:34:05.525049Z", - "iopub.status.idle": "2024-09-05T19:34:08.556569Z", - "shell.execute_reply": "2024-09-05T19:34:08.555871Z" + "iopub.execute_input": "2024-09-06T19:33:56.342254Z", + "iopub.status.busy": "2024-09-06T19:33:56.341754Z", + "iopub.status.idle": "2024-09-06T19:33:59.356819Z", + "shell.execute_reply": "2024-09-06T19:33:59.356183Z" }, "nbsphinx": "hidden" }, @@ -112,10 +112,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:08.559158Z", - "iopub.status.busy": "2024-09-05T19:34:08.558850Z", - "iopub.status.idle": "2024-09-05T19:34:08.562674Z", - "shell.execute_reply": "2024-09-05T19:34:08.562129Z" + "iopub.execute_input": "2024-09-06T19:33:59.359528Z", + "iopub.status.busy": "2024-09-06T19:33:59.359236Z", + "iopub.status.idle": "2024-09-06T19:33:59.363077Z", + "shell.execute_reply": "2024-09-06T19:33:59.362504Z" } }, "outputs": [], @@ -152,17 +152,17 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:08.564917Z", - "iopub.status.busy": "2024-09-05T19:34:08.564578Z", - "iopub.status.idle": "2024-09-05T19:34:10.909350Z", - "shell.execute_reply": "2024-09-05T19:34:10.908728Z" + "iopub.execute_input": "2024-09-06T19:33:59.365205Z", + "iopub.status.busy": "2024-09-06T19:33:59.364886Z", + "iopub.status.idle": "2024-09-06T19:34:04.314293Z", + "shell.execute_reply": "2024-09-06T19:34:04.313807Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "8089a6f0e258484bb6eb86bd123e100b", + "model_id": "7bcf07287e5846bcade12829a0129e5a", "version_major": 2, "version_minor": 0 }, @@ -176,7 +176,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "613725cc273047398f27ac74f75f9fd9", + "model_id": "3273abc0b1474d17ad8e620a0b9cd685", "version_major": 2, "version_minor": 0 }, @@ -190,7 +190,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "222bd1aa4e7242f68a04db434eb3f8b5", + "model_id": "468f054b84de4a46abae17b5d6030a66", "version_major": 2, "version_minor": 0 }, @@ -204,7 +204,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "e1f7f496e0bd4db1ac83de92100a6631", + "model_id": "85a6da0e361d4bb78dac486525795dad", "version_major": 2, "version_minor": 0 }, @@ -218,7 +218,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "4ed7e0e009174ad3afb25e53f562b45b", + "model_id": "16923bdba0af47908931030b52eaedca", "version_major": 2, "version_minor": 0 }, @@ -260,10 +260,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:10.911450Z", - "iopub.status.busy": "2024-09-05T19:34:10.911254Z", - "iopub.status.idle": "2024-09-05T19:34:10.915393Z", - "shell.execute_reply": "2024-09-05T19:34:10.914911Z" + "iopub.execute_input": "2024-09-06T19:34:04.316479Z", + "iopub.status.busy": "2024-09-06T19:34:04.316130Z", + "iopub.status.idle": "2024-09-06T19:34:04.319984Z", + "shell.execute_reply": "2024-09-06T19:34:04.319538Z" } }, "outputs": [ @@ -288,17 +288,17 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:10.917527Z", - "iopub.status.busy": "2024-09-05T19:34:10.917215Z", - "iopub.status.idle": "2024-09-05T19:34:22.576299Z", - "shell.execute_reply": "2024-09-05T19:34:22.575694Z" + "iopub.execute_input": "2024-09-06T19:34:04.321997Z", + "iopub.status.busy": "2024-09-06T19:34:04.321665Z", + "iopub.status.idle": "2024-09-06T19:34:15.824023Z", + "shell.execute_reply": "2024-09-06T19:34:15.823467Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "60d20ce4cd714b879c7671b282199048", + "model_id": "bfcb4b6339d14370bc404a61e757edfd", "version_major": 2, "version_minor": 0 }, @@ -336,10 +336,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:22.579010Z", - "iopub.status.busy": "2024-09-05T19:34:22.578618Z", - "iopub.status.idle": "2024-09-05T19:34:40.816690Z", - "shell.execute_reply": "2024-09-05T19:34:40.816141Z" + "iopub.execute_input": "2024-09-06T19:34:15.826734Z", + "iopub.status.busy": "2024-09-06T19:34:15.826342Z", + "iopub.status.idle": "2024-09-06T19:34:34.591212Z", + "shell.execute_reply": "2024-09-06T19:34:34.590672Z" } }, "outputs": [], @@ -372,10 +372,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:40.819551Z", - "iopub.status.busy": "2024-09-05T19:34:40.819116Z", - "iopub.status.idle": "2024-09-05T19:34:40.824154Z", - "shell.execute_reply": "2024-09-05T19:34:40.823637Z" + "iopub.execute_input": "2024-09-06T19:34:34.593912Z", + "iopub.status.busy": "2024-09-06T19:34:34.593533Z", + "iopub.status.idle": "2024-09-06T19:34:34.599439Z", + "shell.execute_reply": "2024-09-06T19:34:34.598956Z" } }, "outputs": [], @@ -413,10 +413,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:40.826196Z", - "iopub.status.busy": "2024-09-05T19:34:40.825878Z", - "iopub.status.idle": "2024-09-05T19:34:40.830037Z", - "shell.execute_reply": "2024-09-05T19:34:40.829503Z" + "iopub.execute_input": "2024-09-06T19:34:34.601473Z", + "iopub.status.busy": "2024-09-06T19:34:34.601136Z", + "iopub.status.idle": "2024-09-06T19:34:34.604946Z", + "shell.execute_reply": "2024-09-06T19:34:34.604479Z" }, "nbsphinx": "hidden" }, @@ -553,10 +553,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:40.832239Z", - "iopub.status.busy": "2024-09-05T19:34:40.831883Z", - "iopub.status.idle": "2024-09-05T19:34:40.841147Z", - "shell.execute_reply": "2024-09-05T19:34:40.840689Z" + "iopub.execute_input": "2024-09-06T19:34:34.607009Z", + "iopub.status.busy": "2024-09-06T19:34:34.606678Z", + "iopub.status.idle": "2024-09-06T19:34:34.615441Z", + "shell.execute_reply": "2024-09-06T19:34:34.614962Z" }, "nbsphinx": "hidden" }, @@ -681,10 +681,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:40.843173Z", - "iopub.status.busy": "2024-09-05T19:34:40.842829Z", - "iopub.status.idle": "2024-09-05T19:34:40.869384Z", - "shell.execute_reply": "2024-09-05T19:34:40.868884Z" + "iopub.execute_input": "2024-09-06T19:34:34.617637Z", + "iopub.status.busy": "2024-09-06T19:34:34.617189Z", + "iopub.status.idle": "2024-09-06T19:34:34.644027Z", + "shell.execute_reply": "2024-09-06T19:34:34.643475Z" } }, "outputs": [], @@ -721,10 +721,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:34:40.871791Z", - "iopub.status.busy": "2024-09-05T19:34:40.871443Z", - "iopub.status.idle": "2024-09-05T19:35:14.975247Z", - "shell.execute_reply": "2024-09-05T19:35:14.974585Z" + "iopub.execute_input": "2024-09-06T19:34:34.646190Z", + "iopub.status.busy": "2024-09-06T19:34:34.645869Z", + "iopub.status.idle": "2024-09-06T19:35:07.856682Z", + "shell.execute_reply": "2024-09-06T19:35:07.856077Z" } }, "outputs": [ @@ -740,21 +740,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 4.999\n" + "epoch: 1 loss: 0.482 test acc: 86.720 time_taken: 4.923\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.733\n", + "epoch: 2 loss: 0.329 test acc: 88.195 time_taken: 4.597\n", "Computing feature embeddings ...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c31bcb9951714ea7b4d0d8e9793f409b", + "model_id": "60b6605a27b343f3a046b38e2ee92eb3", "version_major": 2, "version_minor": 0 }, @@ -775,7 +775,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6c99a5fc3f1d42269032bffe9d6a65ff", + "model_id": "328179309f4646028e9f8909eefb6c74", "version_major": 2, "version_minor": 0 }, @@ -798,21 +798,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 5.060\n" + "epoch: 1 loss: 0.493 test acc: 87.060 time_taken: 4.922\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.772\n", + "epoch: 2 loss: 0.330 test acc: 88.505 time_taken: 4.912\n", "Computing feature embeddings ...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ec9e629fd2904b8fbf99b7c637113a54", + "model_id": "958c94ac86804e8fbd31685a6f87d389", "version_major": 2, "version_minor": 0 }, @@ -833,7 +833,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "80768ed8be224e0ea7b3cc4f25feb960", + "model_id": "593399f7ed16479cabf5d6887e2046b5", "version_major": 2, "version_minor": 0 }, @@ -856,21 +856,21 @@ "name": "stdout", "output_type": "stream", "text": [ - "epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 5.210\n" + "epoch: 1 loss: 0.476 test acc: 86.340 time_taken: 4.879\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ - "epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.693\n", + "epoch: 2 loss: 0.328 test acc: 86.310 time_taken: 4.556\n", "Computing feature embeddings ...\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "506f569cc4834fd5b04e9abd3570d2f0", + "model_id": "0a3d18201bb14d5c9e73af43adbe2cd8", "version_major": 2, "version_minor": 0 }, @@ -891,7 +891,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f2c0fcf1952846d5b613a055c1f1e0bc", + "model_id": "cef86182d7ef449481f59dfea70aa34a", "version_major": 2, "version_minor": 0 }, @@ -970,10 +970,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:35:14.977942Z", - "iopub.status.busy": "2024-09-05T19:35:14.977466Z", - "iopub.status.idle": "2024-09-05T19:35:14.995105Z", - "shell.execute_reply": "2024-09-05T19:35:14.994526Z" + "iopub.execute_input": "2024-09-06T19:35:07.859270Z", + "iopub.status.busy": "2024-09-06T19:35:07.859022Z", + "iopub.status.idle": "2024-09-06T19:35:07.875302Z", + "shell.execute_reply": "2024-09-06T19:35:07.874880Z" } }, "outputs": [], @@ -998,10 +998,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:35:14.997437Z", - "iopub.status.busy": "2024-09-05T19:35:14.997093Z", - "iopub.status.idle": "2024-09-05T19:35:15.472222Z", - "shell.execute_reply": "2024-09-05T19:35:15.471571Z" + "iopub.execute_input": "2024-09-06T19:35:07.877195Z", + "iopub.status.busy": "2024-09-06T19:35:07.877017Z", + "iopub.status.idle": "2024-09-06T19:35:08.338418Z", + "shell.execute_reply": "2024-09-06T19:35:08.337844Z" } }, "outputs": [], @@ -1021,10 +1021,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:35:15.474780Z", - "iopub.status.busy": "2024-09-05T19:35:15.474581Z", - "iopub.status.idle": "2024-09-05T19:37:07.170464Z", - "shell.execute_reply": "2024-09-05T19:37:07.169763Z" + "iopub.execute_input": "2024-09-06T19:35:08.340738Z", + "iopub.status.busy": "2024-09-06T19:35:08.340554Z", + "iopub.status.idle": "2024-09-06T19:36:59.451053Z", + "shell.execute_reply": "2024-09-06T19:36:59.450444Z" } }, "outputs": [ @@ -1063,7 +1063,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2d18ac7cb0b941438d58c73413469ec9", + "model_id": "b8c0903ec57a4db09eef7c66d76ad798", "version_major": 2, "version_minor": 0 }, @@ -1109,10 +1109,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:07.173215Z", - "iopub.status.busy": "2024-09-05T19:37:07.172522Z", - "iopub.status.idle": "2024-09-05T19:37:07.637129Z", - "shell.execute_reply": "2024-09-05T19:37:07.636559Z" + "iopub.execute_input": "2024-09-06T19:36:59.453745Z", + "iopub.status.busy": "2024-09-06T19:36:59.453098Z", + "iopub.status.idle": "2024-09-06T19:36:59.910431Z", + "shell.execute_reply": "2024-09-06T19:36:59.909867Z" } }, "outputs": [ @@ -1258,10 +1258,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:07.639604Z", - "iopub.status.busy": "2024-09-05T19:37:07.639182Z", - "iopub.status.idle": "2024-09-05T19:37:07.701336Z", - "shell.execute_reply": "2024-09-05T19:37:07.700772Z" + "iopub.execute_input": "2024-09-06T19:36:59.913045Z", + "iopub.status.busy": "2024-09-06T19:36:59.912484Z", + "iopub.status.idle": "2024-09-06T19:36:59.974160Z", + "shell.execute_reply": "2024-09-06T19:36:59.973682Z" } }, "outputs": [ @@ -1365,10 +1365,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:07.703899Z", - "iopub.status.busy": "2024-09-05T19:37:07.703260Z", - "iopub.status.idle": "2024-09-05T19:37:07.712222Z", - "shell.execute_reply": "2024-09-05T19:37:07.711736Z" + "iopub.execute_input": "2024-09-06T19:36:59.976368Z", + "iopub.status.busy": "2024-09-06T19:36:59.976019Z", + "iopub.status.idle": "2024-09-06T19:36:59.984805Z", + "shell.execute_reply": "2024-09-06T19:36:59.984360Z" } }, "outputs": [ @@ -1498,10 +1498,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:07.714512Z", - "iopub.status.busy": "2024-09-05T19:37:07.714075Z", - "iopub.status.idle": "2024-09-05T19:37:07.719026Z", - "shell.execute_reply": "2024-09-05T19:37:07.718573Z" + "iopub.execute_input": "2024-09-06T19:36:59.986926Z", + "iopub.status.busy": "2024-09-06T19:36:59.986597Z", + "iopub.status.idle": "2024-09-06T19:36:59.991039Z", + "shell.execute_reply": "2024-09-06T19:36:59.990559Z" }, "nbsphinx": "hidden" }, @@ -1547,10 +1547,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:07.721051Z", - "iopub.status.busy": "2024-09-05T19:37:07.720871Z", - "iopub.status.idle": "2024-09-05T19:37:08.234485Z", - "shell.execute_reply": "2024-09-05T19:37:08.233873Z" + "iopub.execute_input": "2024-09-06T19:36:59.992932Z", + "iopub.status.busy": "2024-09-06T19:36:59.992715Z", + "iopub.status.idle": "2024-09-06T19:37:00.505081Z", + "shell.execute_reply": "2024-09-06T19:37:00.504451Z" } }, "outputs": [ @@ -1585,10 +1585,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:08.236757Z", - "iopub.status.busy": "2024-09-05T19:37:08.236519Z", - "iopub.status.idle": "2024-09-05T19:37:08.245226Z", - "shell.execute_reply": "2024-09-05T19:37:08.244765Z" + "iopub.execute_input": "2024-09-06T19:37:00.507663Z", + "iopub.status.busy": "2024-09-06T19:37:00.507293Z", + "iopub.status.idle": "2024-09-06T19:37:00.516488Z", + "shell.execute_reply": "2024-09-06T19:37:00.515888Z" } }, "outputs": [ @@ -1755,10 +1755,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:08.247312Z", - "iopub.status.busy": "2024-09-05T19:37:08.247037Z", - "iopub.status.idle": "2024-09-05T19:37:08.254096Z", - "shell.execute_reply": "2024-09-05T19:37:08.253625Z" + "iopub.execute_input": "2024-09-06T19:37:00.518970Z", + "iopub.status.busy": "2024-09-06T19:37:00.518520Z", + "iopub.status.idle": "2024-09-06T19:37:00.525985Z", + "shell.execute_reply": "2024-09-06T19:37:00.525525Z" }, "nbsphinx": "hidden" }, @@ -1834,10 +1834,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:08.256220Z", - "iopub.status.busy": "2024-09-05T19:37:08.255757Z", - "iopub.status.idle": "2024-09-05T19:37:08.724478Z", - "shell.execute_reply": "2024-09-05T19:37:08.723840Z" + "iopub.execute_input": "2024-09-06T19:37:00.528061Z", + "iopub.status.busy": "2024-09-06T19:37:00.527749Z", + "iopub.status.idle": "2024-09-06T19:37:00.996315Z", + "shell.execute_reply": "2024-09-06T19:37:00.995664Z" } }, "outputs": [ @@ -1874,10 +1874,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:08.726943Z", - "iopub.status.busy": "2024-09-05T19:37:08.726570Z", - "iopub.status.idle": "2024-09-05T19:37:08.742787Z", - "shell.execute_reply": "2024-09-05T19:37:08.742174Z" + "iopub.execute_input": "2024-09-06T19:37:00.998663Z", + "iopub.status.busy": "2024-09-06T19:37:00.998226Z", + "iopub.status.idle": "2024-09-06T19:37:01.014613Z", + "shell.execute_reply": "2024-09-06T19:37:01.014119Z" } }, "outputs": [ @@ -2034,10 +2034,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:08.744895Z", - "iopub.status.busy": "2024-09-05T19:37:08.744707Z", - "iopub.status.idle": "2024-09-05T19:37:08.750513Z", - "shell.execute_reply": "2024-09-05T19:37:08.750018Z" + "iopub.execute_input": "2024-09-06T19:37:01.016951Z", + "iopub.status.busy": "2024-09-06T19:37:01.016496Z", + "iopub.status.idle": "2024-09-06T19:37:01.022189Z", + "shell.execute_reply": "2024-09-06T19:37:01.021616Z" }, "nbsphinx": "hidden" }, @@ -2082,10 +2082,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:08.752659Z", - "iopub.status.busy": "2024-09-05T19:37:08.752244Z", - "iopub.status.idle": "2024-09-05T19:37:09.459291Z", - "shell.execute_reply": "2024-09-05T19:37:09.458714Z" + "iopub.execute_input": "2024-09-06T19:37:01.024335Z", + "iopub.status.busy": "2024-09-06T19:37:01.024003Z", + "iopub.status.idle": "2024-09-06T19:37:01.818216Z", + "shell.execute_reply": "2024-09-06T19:37:01.817601Z" } }, "outputs": [ @@ -2167,10 +2167,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.465380Z", - "iopub.status.busy": "2024-09-05T19:37:09.464389Z", - "iopub.status.idle": "2024-09-05T19:37:09.476151Z", - "shell.execute_reply": "2024-09-05T19:37:09.475607Z" + "iopub.execute_input": "2024-09-06T19:37:01.821086Z", + "iopub.status.busy": "2024-09-06T19:37:01.820573Z", + "iopub.status.idle": "2024-09-06T19:37:01.831141Z", + "shell.execute_reply": "2024-09-06T19:37:01.830605Z" } }, "outputs": [ @@ -2195,47 +2195,47 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 34848\n", - " 0.203922\n", " True\n", + " 0.203922\n", " \n", " \n", " 50270\n", - " 0.204588\n", " True\n", + " 0.204588\n", " \n", " \n", " 3936\n", - " 0.213098\n", " True\n", + " 0.213098\n", " \n", " \n", " 733\n", - " 0.217686\n", " True\n", + " 0.217686\n", " \n", " \n", " 8094\n", - " 0.230118\n", " True\n", + " 0.230118\n", " \n", " \n", "\n", "

    " ], "text/plain": [ - " dark_score is_dark_issue\n", - "34848 0.203922 True\n", - "50270 0.204588 True\n", - "3936 0.213098 True\n", - "733 0.217686 True\n", - "8094 0.230118 True" + " is_dark_issue dark_score\n", + "34848 True 0.203922\n", + "50270 True 0.204588\n", + "3936 True 0.213098\n", + "733 True 0.217686\n", + "8094 True 0.230118" ] }, "execution_count": 26, @@ -2298,10 +2298,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.479850Z", - "iopub.status.busy": "2024-09-05T19:37:09.478927Z", - "iopub.status.idle": "2024-09-05T19:37:09.484511Z", - "shell.execute_reply": "2024-09-05T19:37:09.484078Z" + "iopub.execute_input": "2024-09-06T19:37:01.833972Z", + "iopub.status.busy": "2024-09-06T19:37:01.833571Z", + "iopub.status.idle": "2024-09-06T19:37:01.839439Z", + "shell.execute_reply": "2024-09-06T19:37:01.838936Z" }, "nbsphinx": "hidden" }, @@ -2338,10 +2338,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.487390Z", - "iopub.status.busy": "2024-09-05T19:37:09.486635Z", - "iopub.status.idle": "2024-09-05T19:37:09.658646Z", - "shell.execute_reply": "2024-09-05T19:37:09.658024Z" + "iopub.execute_input": "2024-09-06T19:37:01.841836Z", + "iopub.status.busy": "2024-09-06T19:37:01.841454Z", + "iopub.status.idle": "2024-09-06T19:37:02.045788Z", + "shell.execute_reply": "2024-09-06T19:37:02.045180Z" } }, "outputs": [ @@ -2383,10 +2383,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.660921Z", - "iopub.status.busy": "2024-09-05T19:37:09.660563Z", - "iopub.status.idle": "2024-09-05T19:37:09.668286Z", - "shell.execute_reply": "2024-09-05T19:37:09.667818Z" + "iopub.execute_input": "2024-09-06T19:37:02.048026Z", + "iopub.status.busy": "2024-09-06T19:37:02.047682Z", + "iopub.status.idle": "2024-09-06T19:37:02.055980Z", + "shell.execute_reply": "2024-09-06T19:37:02.055509Z" } }, "outputs": [ @@ -2411,47 +2411,47 @@ " \n", " \n", " \n", - " is_low_information_issue\n", " low_information_score\n", + " is_low_information_issue\n", " \n", " \n", " \n", " \n", " 53050\n", - " True\n", " 0.067975\n", + " True\n", " \n", " \n", " 40875\n", - " True\n", " 0.089929\n", + " True\n", " \n", " \n", " 9594\n", - " True\n", " 0.092601\n", + " True\n", " \n", " \n", " 34825\n", - " True\n", " 0.107744\n", + " True\n", " \n", " \n", " 37530\n", - " True\n", " 0.108516\n", + " True\n", " \n", " \n", "\n", "
    " ], "text/plain": [ - " is_low_information_issue low_information_score\n", - "53050 True 0.067975\n", - "40875 True 0.089929\n", - "9594 True 0.092601\n", - "34825 True 0.107744\n", - "37530 True 0.108516" + " low_information_score is_low_information_issue\n", + "53050 0.067975 True\n", + "40875 0.089929 True\n", + "9594 0.092601 True\n", + "34825 0.107744 True\n", + "37530 0.108516 True" ] }, "execution_count": 29, @@ -2472,10 +2472,10 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.670466Z", - "iopub.status.busy": "2024-09-05T19:37:09.670128Z", - "iopub.status.idle": "2024-09-05T19:37:09.865056Z", - "shell.execute_reply": "2024-09-05T19:37:09.864458Z" + "iopub.execute_input": "2024-09-06T19:37:02.058027Z", + "iopub.status.busy": "2024-09-06T19:37:02.057684Z", + "iopub.status.idle": "2024-09-06T19:37:02.256206Z", + "shell.execute_reply": "2024-09-06T19:37:02.255652Z" } }, "outputs": [ @@ -2515,10 +2515,10 @@ "execution_count": 31, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:09.867524Z", - "iopub.status.busy": "2024-09-05T19:37:09.867164Z", - "iopub.status.idle": "2024-09-05T19:37:09.871703Z", - "shell.execute_reply": "2024-09-05T19:37:09.871128Z" + "iopub.execute_input": "2024-09-06T19:37:02.258543Z", + "iopub.status.busy": "2024-09-06T19:37:02.258213Z", + "iopub.status.idle": "2024-09-06T19:37:02.262761Z", + "shell.execute_reply": "2024-09-06T19:37:02.262194Z" }, "nbsphinx": "hidden" }, @@ -2555,7 +2555,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "00cc2bccf49e4abe8b47884216705c03": { + "024f58b175f14cdca925ad2ec59e5f75": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2608,7 +2608,43 @@ "width": null } }, - "0240b26e2e8347049e4a5df861bb7a0d": { + "0445112b7e674aa2a14ea027dc8bc2f8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "06c85507cf49495584b002e6aaa044e8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "06fc43e80ab4403ca27ca8d667aca1b3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2623,15 +2659,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1f3aa8b95cdd4842a621c7fe6c7a29fe", + "layout": "IPY_MODEL_4e22cd2b18d5465c8bfc301a968400ec", "placeholder": "​", - "style": "IPY_MODEL_49f52b7cadd644dfbe381087cf21b374", + "style": "IPY_MODEL_0445112b7e674aa2a14ea027dc8bc2f8", "tabbable": null, "tooltip": null, - "value": "100%" + "value": "Generating test split: 100%" } }, - "02bb02a3558642f7ae049fe605dabbea": { + "076942f2bb5542e9a9c126f736c4b427": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2684,7 +2720,7 @@ "width": null } }, - "0777e52962fe4e3c8c417ed705b0e27a": { + "07c128e462924e039bd30ffd94caeafe": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2702,60 +2738,49 @@ "text_color": null } }, - "07d8ecbe4aaf4a9ea4aa1e00be62b06b": { - "model_module": "@jupyter-widgets/base", + "0a3d18201bb14d5c9e73af43adbe2cd8": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "HBoxModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_e6d9313a802d4513bc93abf9ffa9fc9b", + "IPY_MODEL_6d3f4ee5439044088f65368ef798b3b6", + "IPY_MODEL_351c45295ff8422c8718ee4bdefa510f" + ], + "layout": "IPY_MODEL_7c5730df719649e6ae1137849667983e", + "tabbable": null, + "tooltip": null + } + }, + "0a606b97ecff4d89be8f66714f909ba3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "0a7f73a4ae2a4e5ab8db8790ef824541": { + "0b9bdabf441e4113805b54ee83d92f75": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2770,15 +2795,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_42c78a87167c4c7d8ffa3cc9532ac783", + "layout": "IPY_MODEL_34e238c0c2c24406adb5d978aec7e807", "placeholder": "​", - "style": "IPY_MODEL_2df53c624a43411fa4091264b5c130fb", + "style": "IPY_MODEL_511e7568ac814ea8846c93d586063e8e", "tabbable": null, "tooltip": null, - "value": "Downloading data: 100%" + "value": " 60000/60000 [00:00<00:00, 285192.56 examples/s]" } }, - "0bf8b4b0c9ce4e819a7f21eaed682092": { + "0c2a412a844140bd80a53f2ac3fc325d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2831,7 +2856,7 @@ "width": null } }, - "0e62ee29a15e4b038ba6a7584ca16961": { + "0f5233a082d94dddbdb0503eb9250ed4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -2847,17 +2872,40 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_0f93410bb3374b62a08a4c4560575830", - "max": 60000.0, + "layout": "IPY_MODEL_024f58b175f14cdca925ad2ec59e5f75", + "max": 10000.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_32aa1b55f20340c4b80b5c1a4bcf07b9", + "style": "IPY_MODEL_c0366a87be804af7bcf6f5cd7f11bc3b", "tabbable": null, "tooltip": null, - "value": 60000.0 + "value": 10000.0 + } + }, + "0f970e1142174368bfc637a6cd8d6fd5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_881dec995ffa41c3b5cbe3a2f2955ed3", + "placeholder": "​", + "style": "IPY_MODEL_7500e8476ee64140b7338f73ff7b6e53", + "tabbable": null, + "tooltip": null, + "value": "Downloading readme: 100%" } }, - "0f93410bb3374b62a08a4c4560575830": { + "10a3911ad0ae43f599855a0ad46d4195": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2910,7 +2958,7 @@ "width": null } }, - "10186f0c08c84916988b4064fb8fbbb6": { + "11645e47817743048239554d8f897a74": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2963,23 +3011,7 @@ "width": null } }, - "1403cd0920194d9f88d2e816c0e364a5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "195f6f44461b4637898d20c3f277f04c": { + "118d13a1737e460b986120e1cd8488c6": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3032,78 +3064,49 @@ "width": null } }, - "1a190a961ec641a28b3c636af3b264dc": { + "11c48316135a461ea55c3d08dc541755": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d54af3f6955d4b968858d238a0210190", + "max": 9015.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_f2fa408e34274722bd36f3791c967fb2", + "tabbable": null, + "tooltip": null, + "value": 9015.0 } }, - "1b516e69e31f4ff4a0ecb31c1298142e": { - "model_module": "@jupyter-widgets/base", + "13063e602ee246eb9b552b3b781fa85e": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "1c26fb9f22394b9299592a1f50ca98d5": { + "1510cd85e1a74691abd66fcc8f87c34c": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3156,7 +3159,7 @@ "width": null } }, - "1e80382ec0ec4737898dcc5f400fdb22": { + "156d3569cd004246a2f548957d78f2bc": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3209,20 +3212,125 @@ "width": null } }, - "1f3aa8b95cdd4842a621c7fe6c7a29fe": { - "model_module": "@jupyter-widgets/base", + "15c77a61cbac476e99fb0331858d1d8c": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "1658cd683cbd496c9ff193ba8d7c35ea": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b8a497f4724b458c8448b91e3ce44d15", + "placeholder": "​", + "style": "IPY_MODEL_3c640d11994b4372834d50a9621d95c5", + "tabbable": null, + "tooltip": null, + "value": " 60000/60000 [00:51<00:00, 1138.50it/s]" + } + }, + "16923bdba0af47908931030b52eaedca": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_06fc43e80ab4403ca27ca8d667aca1b3", + "IPY_MODEL_0f5233a082d94dddbdb0503eb9250ed4", + "IPY_MODEL_8efceb1c08634d06817a3fa57d1a8f06" + ], + "layout": "IPY_MODEL_a9b1da96fea74c509d14483d998a7cf8", + "tabbable": null, + "tooltip": null + } + }, + "1e5e214067f448fe820c272b4d8b60b6": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_929f19e8f15344c999957b2ce7569264", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_6c95b5f8fda84c369cae7cba5624ccfe", + "tabbable": null, + "tooltip": null, + "value": 40.0 + } + }, + "210dbd38b6ce4f9e9f8b810ac64d03bf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "23d399d3b46a4f8d82116059129fd43f": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, @@ -3262,30 +3370,7 @@ "width": null } }, - "1fa1bf487aa146f7b63aba1b37340dad": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_82aff8f27b4c41438fb70e6ac7827816", - "placeholder": "​", - "style": "IPY_MODEL_3852b37239ad47a8bea5bf09447ccb1b", - "tabbable": null, - "tooltip": null, - "value": "Generating test split: 100%" - } - }, - "209db2922df34007b2eea98c10204bb3": { + "25c0e4e85ebb41299102ad0b3e0880b4": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3338,139 +3423,30 @@ "width": null } }, - "21aa7e557ff2445fb6f9a8d7299a17ff": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "222bd1aa4e7242f68a04db434eb3f8b5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_68f553c7ffe64681af4d9d9b609619d2", - "IPY_MODEL_5ac7e0143087455db2057a05611b903a", - "IPY_MODEL_b57eeb2e85db4e6c90b70606981a862d" - ], - "layout": "IPY_MODEL_2fe068acde9747ab80cba22c22af96d4", - "tabbable": null, - "tooltip": null - } - }, - "24f5d44a2aba41bab7b5b00ccd550704": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "27d51d7d7c394b8ca5b9c6dc1f2f28ef": { + "26b545a844a84c278f68d51645f7e371": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "2a0e717d35f142e2ba3bffe16092cee4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "2d18ac7cb0b941438d58c73413469ec9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_30efd8b2b2434f878122eddd7664ec22", - "IPY_MODEL_0e62ee29a15e4b038ba6a7584ca16961", - "IPY_MODEL_63dacf2552ad40888642091c1d2b28f2" - ], - "layout": "IPY_MODEL_58df9bc980ff41e19f86d334f4e6affd", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_ac970746b6684c3ba6bb43eee4014e2b", + "placeholder": "​", + "style": "IPY_MODEL_c77f86be94734e2ba274bf4267c5a824", "tabbable": null, - "tooltip": null - } - }, - "2df53c624a43411fa4091264b5c130fb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "tooltip": null, + "value": " 2/2 [00:00<00:00, 680.45it/s]" } }, - "2fe068acde9747ab80cba22c22af96d4": { + "294184439d7d474cbfc6043c1efa9d3d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3523,96 +3499,7 @@ "width": null } }, - "30efd8b2b2434f878122eddd7664ec22": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_02bb02a3558642f7ae049fe605dabbea", - "placeholder": "​", - "style": "IPY_MODEL_83ed1ab9ea0a4965aa59eb8257d4f46b", - "tabbable": null, - "tooltip": null, - "value": "100%" - } - }, - "32aa1b55f20340c4b80b5c1a4bcf07b9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "35a155d26b984654ab25b9e85ccccd6f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "3852b37239ad47a8bea5bf09447ccb1b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "3e22696dc8414bd180d0e07a4a0a62a7": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "40c882020753475486c7353c336a7276": { + "29ace475fdbe4624840332dd0e509ed6": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3665,7 +3552,81 @@ "width": null } }, - "42c78a87167c4c7d8ffa3cc9532ac783": { + "2b755b9c572e43a396e62c74fba5329f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_11645e47817743048239554d8f897a74", + "max": 5175617.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_7c13df622dfc4f04853781143737296f", + "tabbable": null, + "tooltip": null, + "value": 5175617.0 + } + }, + "3273abc0b1474d17ad8e620a0b9cd685": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_a53594c87ee944d2ab253fdeb3aeae5f", + "IPY_MODEL_e38940706f02447996928468d3f523eb", + "IPY_MODEL_e127093a41b442febda97da50e709395" + ], + "layout": "IPY_MODEL_d9bfaf958ae54bdaa41267876482d6af", + "tabbable": null, + "tooltip": null + } + }, + "328179309f4646028e9f8909eefb6c74": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_471bce1ec58f4d4da4ed7ed290449c5f", + "IPY_MODEL_a8fc249e1ca44d4084ed4e8e978d6058", + "IPY_MODEL_f03a0d23baa4409abb0c7271bd76ab8a" + ], + "layout": "IPY_MODEL_bb2fc960507949aea6439fcd3c77de5b", + "tabbable": null, + "tooltip": null + } + }, + "33d5aee8319348e485ec3980bc726f23": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3718,7 +3679,7 @@ "width": null } }, - "44a4010eb7a944249e17c4373fb6fae1": { + "34b3d7273cdd4ceca25a11fbb32359ce": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3771,71 +3732,7 @@ "width": null } }, - "490e0855ef974a42b2647cfedac70b97": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_00cc2bccf49e4abe8b47884216705c03", - "placeholder": "​", - "style": "IPY_MODEL_7030838d622a49648a433355d555396d", - "tabbable": null, - "tooltip": null, - "value": "100%" - } - }, - "496cb780de334794994864ce22ab43f9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b330cae0665c496d9f38d6b6c39c32cf", - "placeholder": "​", - "style": "IPY_MODEL_94dbf69483ae44dc86b8e989c13af0b1", - "tabbable": null, - "tooltip": null, - "value": "Map (num_proc=4): 100%" - } - }, - "49f52b7cadd644dfbe381087cf21b374": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "4b14e0caa5af4f9688d2d2d294a95764": { + "34e238c0c2c24406adb5d978aec7e807": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3888,7 +3785,48 @@ "width": null } }, - "4ed7e0e009174ad3afb25e53f562b45b": { + "351c45295ff8422c8718ee4bdefa510f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_8e65bd8055fd45d8999b608481497477", + "placeholder": "​", + "style": "IPY_MODEL_82b18a92ec124a52a6892b31409db80e", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 64.40it/s]" + } + }, + "3c640d11994b4372834d50a9621d95c5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "468f054b84de4a46abae17b5d6030a66": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -3903,16 +3841,85 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_1fa1bf487aa146f7b63aba1b37340dad", - "IPY_MODEL_95d93d3f700940b592f8552c390c914b", - "IPY_MODEL_79aa1e210ebd44dfa879c72b499b33e4" + "IPY_MODEL_49329574ba97425f8b3b12f07b8d53cf", + "IPY_MODEL_2b755b9c572e43a396e62c74fba5329f", + "IPY_MODEL_861644c40333498094e62f8ac990f5a3" ], - "layout": "IPY_MODEL_cda1df54889f4e3bb275c8c2fd8ec82a", + "layout": "IPY_MODEL_0c2a412a844140bd80a53f2ac3fc325d", "tabbable": null, "tooltip": null } }, - "4fd6ca7a7dd446879a6f2f55860227d9": { + "471bce1ec58f4d4da4ed7ed290449c5f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d9b3afcffed047abb3d7c9215eacb041", + "placeholder": "​", + "style": "IPY_MODEL_d0dfbf919e5f422689492055a00be836", + "tabbable": null, + "tooltip": null, + "value": "100%" + } + }, + "49329574ba97425f8b3b12f07b8d53cf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_77caecf6cce84ac885a2c431ec321e76", + "placeholder": "​", + "style": "IPY_MODEL_df804279770c4bbdbba569e996a72047", + "tabbable": null, + "tooltip": null, + "value": "Downloading data: 100%" + } + }, + "4a900a7bd2894dc2905c92a999845c41": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_78ec8846971b49dc8ac35c9865ab7855", + "placeholder": "​", + "style": "IPY_MODEL_a1e0fb35ccfd46ac9b640c1e3a97a83e", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 58.88it/s]" + } + }, + "4e22cd2b18d5465c8bfc301a968400ec": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -3965,31 +3972,7 @@ "width": null } }, - "506f569cc4834fd5b04e9abd3570d2f0": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_dccf399c747d4d1d82bce77b5b675956", - "IPY_MODEL_e8f51e9d01d447c3b27b88d0c146d11b", - "IPY_MODEL_c701552093d1471bb9ace0f6dcd2c9bb" - ], - "layout": "IPY_MODEL_40c882020753475486c7353c336a7276", - "tabbable": null, - "tooltip": null - } - }, - "50c7134622e34fbb83b07d440594438c": { + "4e5be3b38c73499194dd5bfcb00e9476": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4042,48 +4025,7 @@ "width": null } }, - "51120e68bd384037a4668fe393f7be13": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_aff0b45e2c1f43a9bb8830f843804ede", - "placeholder": "​", - "style": "IPY_MODEL_6933130e7fa747cca85775e2390e2883", - "tabbable": null, - "tooltip": null, - "value": " 60000/60000 [00:00<00:00, 280070.61 examples/s]" - } - }, - "527d0aaee5894f2da400bf5690853965": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "53f7d5a3fe5045aea631347f5778ed5b": { + "50780f5c92b44525bf711232bc998378": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4136,7 +4078,25 @@ "width": null } }, - "5421281ef4324fc3960b976b5b1e7be1": { + "511e7568ac814ea8846c93d586063e8e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "5264eae69a4a44c5af270b7caaa7eeb4": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4189,7 +4149,7 @@ "width": null } }, - "5460c3ab53244166b5b83bce1568fb9a": { + "58bd914194a245c2b1a963606103a9bd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4204,33 +4164,39 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_5affd8364ad84dce9ccb9e64e3595daa", + "layout": "IPY_MODEL_65a24ce68aaf46d6b97c06a7d9ffc735", "placeholder": "​", - "style": "IPY_MODEL_f282b3d3edd34bd19404aa81c4bd2be9", + "style": "IPY_MODEL_ed24804748ab483289fec871eb4e7ebf", "tabbable": null, "tooltip": null, - "value": " 30.9M/30.9M [00:00<00:00, 82.2MB/s]" + "value": " 40/40 [00:00<00:00, 65.43it/s]" } }, - "56ab7eb7d7514ac4a5ca99fbec95176c": { + "593399f7ed16479cabf5d6887e2046b5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_9db52ec22ade4fc2a207b214ed54d964", + "IPY_MODEL_7774247051444f258f5cb5a4624a6d83", + "IPY_MODEL_f082a4eab5444b019ea911ae0fb7a92d" + ], + "layout": "IPY_MODEL_8a312c718675404cb5eaf36ae41d943d", + "tabbable": null, + "tooltip": null } }, - "57c3bbf911934c1b954d08e7df293a56": { + "5bc3a1038e00432097a539e27f83e00f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4283,7 +4249,7 @@ "width": null } }, - "57c3c61cde5d4837a1643acc4efaa530": { + "5cf6c3b877784057a47d544871ab0987": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -4301,86 +4267,95 @@ "text_color": null } }, - "58df9bc980ff41e19f86d334f4e6affd": { - "model_module": "@jupyter-widgets/base", + "5e5e4490daf942669f04f85596a7308d": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "HTMLModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_29ace475fdbe4624840332dd0e509ed6", + "placeholder": "​", + "style": "IPY_MODEL_f784e45cbe9248ae9c16491028d6bf8e", + "tabbable": null, + "tooltip": null, + "value": "100%" + } + }, + "606a0ff67cfd457c88c691c81de63a4c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "5ac7e0143087455db2057a05611b903a": { + "60b6605a27b343f3a046b38e2ee92eb3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_f9f45d26f74148d5aafa521c2e42894d", + "IPY_MODEL_f11e1a00f1c942a080552a095321e730", + "IPY_MODEL_b323c9ad204c424e81ad897a8a41faa8" + ], + "layout": "IPY_MODEL_f1c64d058ec34988a144f78b8ce7cbc8", + "tabbable": null, + "tooltip": null + } + }, + "612a34311c13432a923b885221f461b0": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_bf7b754fe88b42c2a0ebefbef27aaa5d", - "max": 5175617.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_3e22696dc8414bd180d0e07a4a0a62a7", + "layout": "IPY_MODEL_156d3569cd004246a2f548957d78f2bc", + "placeholder": "​", + "style": "IPY_MODEL_0a606b97ecff4d89be8f66714f909ba3", "tabbable": null, "tooltip": null, - "value": 5175617.0 + "value": "Generating train split: 100%" } }, - "5affd8364ad84dce9ccb9e64e3595daa": { + "62625d830bc54505aa74a2a30ef3af9d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4433,7 +4408,25 @@ "width": null } }, - "5d7fd3a699f145eaa96b37d43b96276e": { + "63223699d1124f63b67f209182bf8e11": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "65a24ce68aaf46d6b97c06a7d9ffc735": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4486,7 +4479,7 @@ "width": null } }, - "5e3bb0ee765649eb8ed9db6a7ad199b2": { + "6739176497a24677bed9ce1d499ce111": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4539,7 +4532,30 @@ "width": null } }, - "5f93eedb157d4345bc780bd62a65204e": { + "67956635d769462da5b0f8ec7ca4575b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_34b3d7273cdd4ceca25a11fbb32359ce", + "placeholder": "​", + "style": "IPY_MODEL_07c128e462924e039bd30ffd94caeafe", + "tabbable": null, + "tooltip": null, + "value": "Map (num_proc=4): 100%" + } + }, + "69af7b2b232142ffa08b9e4439628311": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4592,78 +4608,39 @@ "width": null } }, - "60d20ce4cd714b879c7671b282199048": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_496cb780de334794994864ce22ab43f9", - "IPY_MODEL_ae929a9d89e44834b81a2fd963b2c35f", - "IPY_MODEL_d37c5155b2a140bc9d293b5579737109" - ], - "layout": "IPY_MODEL_1c26fb9f22394b9299592a1f50ca98d5", - "tabbable": null, - "tooltip": null - } - }, - "613725cc273047398f27ac74f75f9fd9": { + "6c5276f1cdeb4d6dafd955e313dfb495": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0a7f73a4ae2a4e5ab8db8790ef824541", - "IPY_MODEL_b9de52fff41e480faf1069d54e51bb01", - "IPY_MODEL_5460c3ab53244166b5b83bce1568fb9a" - ], - "layout": "IPY_MODEL_5e3bb0ee765649eb8ed9db6a7ad199b2", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "63dacf2552ad40888642091c1d2b28f2": { + "6c95b5f8fda84c369cae7cba5624ccfe": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_5421281ef4324fc3960b976b5b1e7be1", - "placeholder": "​", - "style": "IPY_MODEL_713797fcd2e443099904db1582f72e04", - "tabbable": null, - "tooltip": null, - "value": " 60000/60000 [00:51<00:00, 1093.09it/s]" + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "6492748e048c4fe69d67f2f82d4e0597": { + "6d3f4ee5439044088f65368ef798b3b6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -4679,17 +4656,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1e80382ec0ec4737898dcc5f400fdb22", + "layout": "IPY_MODEL_10a3911ad0ae43f599855a0ad46d4195", "max": 40.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_6e9d6a9e82ee4cadaf4d6aae8966e15c", + "style": "IPY_MODEL_ac4bae02a5884435aa084f8524ec36ab", "tabbable": null, "tooltip": null, "value": 40.0 } }, - "65f9a6bec4e948baa940c3046dc97c27": { + "6dd2d74eb1d04d61844ec3c03149c90b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", @@ -4705,7 +4682,33 @@ "description_width": "" } }, - "68f553c7ffe64681af4d9d9b609619d2": { + "6e84e471535f4aa89081faaaa485d6c3": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_eec22da0f1c144399d3b96c5a790810e", + "max": 60000.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_747540cae7c946758cd31d80531063d5", + "tabbable": null, + "tooltip": null, + "value": 60000.0 + } + }, + "6e8d203ea1f24d86a8504e8c8f549098": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4720,33 +4723,121 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_c970b98ad16d4e058311518f87d4705f", + "layout": "IPY_MODEL_6fdd97c1ed34454aa0a60e98a62224d2", "placeholder": "​", - "style": "IPY_MODEL_d5f0f111e29b4da996f76d93a33612b5", + "style": "IPY_MODEL_9bec32080a844b95be00f98699eec0a5", "tabbable": null, "tooltip": null, - "value": "Downloading data: 100%" + "value": " 9.02k/9.02k [00:00<00:00, 1.14MB/s]" } }, - "6933130e7fa747cca85775e2390e2883": { - "model_module": "@jupyter-widgets/controls", + "6f0a00d7d264477684a40569e5e3fb89": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "6f4b003f65a3475b87ea4dfb49e22177": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "6954ba9a0a8544c8ab34caf9382b3919": { + "6fdd97c1ed34454aa0a60e98a62224d2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4799,46 +4890,67 @@ "width": null } }, - "69ec4f0b4df24afeb44979768207ccb2": { + "747540cae7c946758cd31d80531063d5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "7500e8476ee64140b7338f73ff7b6e53": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_961e00b1790446eab77bd4a467f184f2", - "placeholder": "​", - "style": "IPY_MODEL_c35a2bc3029c426483bd38115de30f66", - "tabbable": null, - "tooltip": null, - "value": " 40/40 [00:00<00:00, 58.82it/s]" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "6ac7f8c8c82c405ea6e0f563824be3e4": { + "7774247051444f258f5cb5a4624a6d83": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_23d399d3b46a4f8d82116059129fd43f", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_13063e602ee246eb9b552b3b781fa85e", + "tabbable": null, + "tooltip": null, + "value": 40.0 } }, - "6bd96238c24c4e66a330bba2b167695c": { + "77caecf6cce84ac885a2c431ec321e76": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4891,54 +5003,7 @@ "width": null } }, - "6c99a5fc3f1d42269032bffe9d6a65ff": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_490e0855ef974a42b2647cfedac70b97", - "IPY_MODEL_ad9ad38f87fc4507894591d2e971b931", - "IPY_MODEL_943f54a9f4ed4ae88c0921a8b76bf464" - ], - "layout": "IPY_MODEL_72c90d5012e24845b7a5539b09d24a76", - "tabbable": null, - "tooltip": null - } - }, - "6ce5166958664174ac671372b3559fa4": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6cecdf39711e44c98e32290468b92b89", - "placeholder": "​", - "style": "IPY_MODEL_aa92cf8d9af14ef481b63d80bff1ec7b", - "tabbable": null, - "tooltip": null, - "value": " 9.02k/9.02k [00:00<00:00, 1.13MB/s]" - } - }, - "6cecdf39711e44c98e32290468b92b89": { + "78ec8846971b49dc8ac35c9865ab7855": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4991,30 +5056,49 @@ "width": null } }, - "6de53660f780414f83690503c02977c3": { + "7acec2eb1b9b4c74860f49bf17a12246": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "7bcf07287e5846bcade12829a0129e5a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_74cac39f1ec9456089f019cf6afaf7b6", - "placeholder": "​", - "style": "IPY_MODEL_8e9c46198cc34d838d789c567dc8fb39", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_0f970e1142174368bfc637a6cd8d6fd5", + "IPY_MODEL_11c48316135a461ea55c3d08dc541755", + "IPY_MODEL_6e8d203ea1f24d86a8504e8c8f549098" + ], + "layout": "IPY_MODEL_6f4b003f65a3475b87ea4dfb49e22177", "tabbable": null, - "tooltip": null, - "value": "Downloading readme: 100%" + "tooltip": null } }, - "6e9d6a9e82ee4cadaf4d6aae8966e15c": { + "7c13df622dfc4f04853781143737296f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", @@ -5030,7 +5114,7 @@ "description_width": "" } }, - "6fa9185a75e4476a9f7bb3766fa59734": { + "7c5730df719649e6ae1137849667983e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5083,43 +5167,7 @@ "width": null } }, - "7030838d622a49648a433355d555396d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "713797fcd2e443099904db1582f72e04": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "72c90d5012e24845b7a5539b09d24a76": { + "7d5c3f6e3cdc47378b7a095dc828c708": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5172,7 +5220,30 @@ "width": null } }, - "73da71f202fa4d19a5b13c8abd8c3da4": { + "7e624075712f49aeb75f702d9f7850d8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_5264eae69a4a44c5af270b7caaa7eeb4", + "placeholder": "​", + "style": "IPY_MODEL_dac3e32ab9a846e79186067c2b27a96c", + "tabbable": null, + "tooltip": null, + "value": "Computing checksums: 100%" + } + }, + "82b18a92ec124a52a6892b31409db80e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -5190,7 +5261,7 @@ "text_color": null } }, - "74cac39f1ec9456089f019cf6afaf7b6": { + "85965cbbe5ef40678b86b3d3f8e4fc95": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5243,7 +5314,7 @@ "width": null } }, - "76b7a3bbd445436cbe99a45727980913": { + "85a6da0e361d4bb78dac486525795dad": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -5258,16 +5329,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_bdfc00756c4b4ea291b1b12d3c453adb", - "IPY_MODEL_beb7c925e927474da59521fcae36f1b5", - "IPY_MODEL_bbe8e85b50614b6895dfc5261cefbd3f" + "IPY_MODEL_612a34311c13432a923b885221f461b0", + "IPY_MODEL_c20bdfdc755d478c8d2c59d296af1748", + "IPY_MODEL_0b9bdabf441e4113805b54ee83d92f75" ], - "layout": "IPY_MODEL_07d8ecbe4aaf4a9ea4aa1e00be62b06b", + "layout": "IPY_MODEL_5bc3a1038e00432097a539e27f83e00f", "tabbable": null, "tooltip": null } }, - "79aa1e210ebd44dfa879c72b499b33e4": { + "861644c40333498094e62f8ac990f5a3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5282,41 +5353,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_6bd96238c24c4e66a330bba2b167695c", + "layout": "IPY_MODEL_a77a4e7f5f8140bf8475f4d847910210", "placeholder": "​", - "style": "IPY_MODEL_0777e52962fe4e3c8c417ed705b0e27a", - "tabbable": null, - "tooltip": null, - "value": " 10000/10000 [00:00<00:00, 247365.46 examples/s]" - } - }, - "79d0cd0446fb44d18bdfb6375cea394c": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_7bffdee10c6243ff866a02214b5a648a", - "max": 9015.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_65f9a6bec4e948baa940c3046dc97c27", + "style": "IPY_MODEL_5cf6c3b877784057a47d544871ab0987", "tabbable": null, "tooltip": null, - "value": 9015.0 + "value": " 5.18M/5.18M [00:00<00:00, 25.9MB/s]" } }, - "7bffdee10c6243ff866a02214b5a648a": { + "881dec995ffa41c3b5cbe3a2f2955ed3": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5369,94 +5414,25 @@ "width": null } }, - "803d8c89e37c4695af839e22e27d45ad": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_bf2c115cc0d44b6fa22a95924ce0e2c1", - "placeholder": "​", - "style": "IPY_MODEL_be908d64fea14e7a8dacc12ac0c6dd97", - "tabbable": null, - "tooltip": null, - "value": "Generating train split: 100%" - } - }, - "80768ed8be224e0ea7b3cc4f25feb960": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_c501ce55b0824b50bbbd81608041645c", - "IPY_MODEL_97dadb01cdf243fcb11e8a41b9d2c694", - "IPY_MODEL_a9318ad2f8454532a38c05af6ab2b318" - ], - "layout": "IPY_MODEL_4b14e0caa5af4f9688d2d2d294a95764", - "tabbable": null, - "tooltip": null - } - }, - "8089a6f0e258484bb6eb86bd123e100b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_6de53660f780414f83690503c02977c3", - "IPY_MODEL_79d0cd0446fb44d18bdfb6375cea394c", - "IPY_MODEL_6ce5166958664174ac671372b3559fa4" - ], - "layout": "IPY_MODEL_e8da8c5e504b47e9b752f785493250ce", - "tabbable": null, - "tooltip": null - } - }, - "81b854f5964b47979c3b45402b07d21d": { + "884d6ce901e24a3797e35af5711b0f35": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "82aff8f27b4c41438fb70e6ac7827816": { + "8a312c718675404cb5eaf36ae41d943d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5509,41 +5485,7 @@ "width": null } }, - "83ed1ab9ea0a4965aa59eb8257d4f46b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "8a031d58353a4a56b2ee095968c9120f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "8c1eafd77d904a36aa9f617ae2a33e13": { + "8cf5382c91f64f789a1af9c7918f14bb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5558,51 +5500,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_50c7134622e34fbb83b07d440594438c", + "layout": "IPY_MODEL_d5d9319b3ee0495d88f51937931cd00c", "placeholder": "​", - "style": "IPY_MODEL_527d0aaee5894f2da400bf5690853965", + "style": "IPY_MODEL_af8db4b8467844b8be9927dab8c5e3d9", "tabbable": null, "tooltip": null, - "value": " 40/40 [00:00<00:00, 61.56it/s]" - } - }, - "8e9c46198cc34d838d789c567dc8fb39": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "8ef171290e7f471a827e41fd51067134": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "value": "100%" } }, - "926a96fc307846809864b9a1f01356cf": { + "8e65bd8055fd45d8999b608481497477": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5655,7 +5561,7 @@ "width": null } }, - "943f54a9f4ed4ae88c0921a8b76bf464": { + "8efceb1c08634d06817a3fa57d1a8f06": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5670,59 +5576,68 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1b516e69e31f4ff4a0ecb31c1298142e", + "layout": "IPY_MODEL_85965cbbe5ef40678b86b3d3f8e4fc95", "placeholder": "​", - "style": "IPY_MODEL_8ef171290e7f471a827e41fd51067134", + "style": "IPY_MODEL_d86fc4609ac5440a807e454ed938d58e", "tabbable": null, "tooltip": null, - "value": " 40/40 [00:00<00:00, 61.32it/s]" + "value": " 10000/10000 [00:00<00:00, 249921.29 examples/s]" } }, - "94dbf69483ae44dc86b8e989c13af0b1": { - "model_module": "@jupyter-widgets/controls", + "92880a6894cd410ba97664fbbbbe340e": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "95d93d3f700940b592f8552c390c914b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_f9fd3a8802ff4c8799b62137434f622c", - "max": 10000.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_6ac7f8c8c82c405ea6e0f563824be3e4", - "tabbable": null, - "tooltip": null, - "value": 10000.0 + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "961e00b1790446eab77bd4a467f184f2": { + "929f19e8f15344c999957b2ce7569264": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5775,51 +5690,31 @@ "width": null } }, - "97dadb01cdf243fcb11e8a41b9d2c694": { + "958c94ac86804e8fbd31685a6f87d389": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_209db2922df34007b2eea98c10204bb3", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_24f5d44a2aba41bab7b5b00ccd550704", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_ac11acf9e07f48d1af94fcdf26f8c615", + "IPY_MODEL_a671667e5adf4b9798a98eda0ac57dc8", + "IPY_MODEL_4a900a7bd2894dc2905c92a999845c41" + ], + "layout": "IPY_MODEL_4e5be3b38c73499194dd5bfcb00e9476", "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "9ee9ae8ff5f64abd9dba00576d9248cd": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "tooltip": null } }, - "a0a0e34b0dda43afb7891d6f5af3db95": { + "97578dccf99646909cc139834ab78ea9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5872,7 +5767,25 @@ "width": null } }, - "a3cce43cc858462a882adcb42f8671a7": { + "9bec32080a844b95be00f98699eec0a5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "9db52ec22ade4fc2a207b214ed54d964": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5887,15 +5800,51 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_44a4010eb7a944249e17c4373fb6fae1", + "layout": "IPY_MODEL_62625d830bc54505aa74a2a30ef3af9d", "placeholder": "​", - "style": "IPY_MODEL_c5c385c1288d47d3b192dde525ec8305", + "style": "IPY_MODEL_afce32644b8041548c6a8fefb3255e26", "tabbable": null, "tooltip": null, "value": "100%" } }, - "a9318ad2f8454532a38c05af6ab2b318": { + "9fcb012408c9489cb4882ad5d8d37ecf": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "a1e0fb35ccfd46ac9b640c1e3a97a83e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "a53594c87ee944d2ab253fdeb3aeae5f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -5910,33 +5859,41 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b544909353d742da90404a2a70352fdf", + "layout": "IPY_MODEL_50780f5c92b44525bf711232bc998378", "placeholder": "​", - "style": "IPY_MODEL_b6f2ef3dc1a54297b205d90f139423c5", + "style": "IPY_MODEL_eefff7211ed94c5b90094ff9520c50b5", "tabbable": null, "tooltip": null, - "value": " 40/40 [00:00<00:00, 57.51it/s]" + "value": "Downloading data: 100%" } }, - "aa92cf8d9af14ef481b63d80bff1ec7b": { + "a671667e5adf4b9798a98eda0ac57dc8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_1510cd85e1a74691abd66fcc8f87c34c", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_15c77a61cbac476e99fb0331858d1d8c", + "tabbable": null, + "tooltip": null, + "value": 40.0 } }, - "abc24829115b46edb7572dc55403960a": { + "a77a4e7f5f8140bf8475f4d847910210": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5989,33 +5946,7 @@ "width": null } }, - "ad9ad38f87fc4507894591d2e971b931": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_0bf8b4b0c9ce4e819a7f21eaed682092", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_eda9c8fc9ec84b47b274aead1d312c12", - "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "ae860c8ab42f4e1a96dddec1fd6b7a29": { + "a88f012a925b438fbc901a161c09cf50": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6068,7 +5999,7 @@ "width": null } }, - "ae929a9d89e44834b81a2fd963b2c35f": { + "a8fc249e1ca44d4084ed4e8e978d6058": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -6084,17 +6015,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b0135714d63c4ad599890917e7581170", - "max": 60000.0, + "layout": "IPY_MODEL_076942f2bb5542e9a9c126f736c4b427", + "max": 40.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_2a0e717d35f142e2ba3bffe16092cee4", + "style": "IPY_MODEL_6c5276f1cdeb4d6dafd955e313dfb495", "tabbable": null, "tooltip": null, - "value": 60000.0 + "value": 40.0 } }, - "afb259c49ba34750a8a8814d7dc507b6": { + "a9b1da96fea74c509d14483d998a7cf8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6147,7 +6078,7 @@ "width": null } }, - "aff0b45e2c1f43a9bb8830f843804ede": { + "a9e701e6d5bf4ec2a9c900edea6104e5": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6200,7 +6131,7 @@ "width": null } }, - "b0135714d63c4ad599890917e7581170": { + "aba8cf45b54448a59ae5e30586981cc2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6253,7 +6184,7 @@ "width": null } }, - "b1d1946f6c3a4ee8bc68f10cfe33d799": { + "ac11acf9e07f48d1af94fcdf26f8c615": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -6268,15 +6199,31 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_10186f0c08c84916988b4064fb8fbbb6", + "layout": "IPY_MODEL_69af7b2b232142ffa08b9e4439628311", "placeholder": "​", - "style": "IPY_MODEL_73da71f202fa4d19a5b13c8abd8c3da4", + "style": "IPY_MODEL_9fcb012408c9489cb4882ad5d8d37ecf", "tabbable": null, "tooltip": null, "value": "100%" } }, - "b2edc3bafbc4407f8f9a8b986aa82b90": { + "ac4bae02a5884435aa084f8524ec36ab": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "ac970746b6684c3ba6bb43eee4014e2b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6329,7 +6276,43 @@ "width": null } }, - "b330cae0665c496d9f38d6b6c39c32cf": { + "af8db4b8467844b8be9927dab8c5e3d9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "afce32644b8041548c6a8fefb3255e26": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "b149b2726a33413c8e2fde403bed8e98": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6382,7 +6365,46 @@ "width": null } }, - "b544909353d742da90404a2a70352fdf": { + "b1625d60d8254709b2fbc8015a483069": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "b323c9ad204c424e81ad897a8a41faa8": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_294184439d7d474cbfc6043c1efa9d3d", + "placeholder": "​", + "style": "IPY_MODEL_63223699d1124f63b67f209182bf8e11", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 62.13it/s]" + } + }, + "b8a497f4724b458c8448b91e3ce44d15": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6435,97 +6457,31 @@ "width": null } }, - "b57eeb2e85db4e6c90b70606981a862d": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_926a96fc307846809864b9a1f01356cf", - "placeholder": "​", - "style": "IPY_MODEL_21aa7e557ff2445fb6f9a8d7299a17ff", - "tabbable": null, - "tooltip": null, - "value": " 5.18M/5.18M [00:00<00:00, 59.9MB/s]" - } - }, - "b6f2ef3dc1a54297b205d90f139423c5": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "b754e4894e834fc19df74d003d4ab747": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_a0a0e34b0dda43afb7891d6f5af3db95", - "placeholder": "​", - "style": "IPY_MODEL_c5ae7198f4aa46179022a46d7c59764e", - "tabbable": null, - "tooltip": null, - "value": " 40/40 [00:00<00:00, 58.46it/s]" - } - }, - "b9de52fff41e480faf1069d54e51bb01": { + "b8c0903ec57a4db09eef7c66d76ad798": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_ae860c8ab42f4e1a96dddec1fd6b7a29", - "max": 30931277.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_1403cd0920194d9f88d2e816c0e364a5", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_5e5e4490daf942669f04f85596a7308d", + "IPY_MODEL_c1960242d8a3445da3b5cfd12aa829f9", + "IPY_MODEL_1658cd683cbd496c9ff193ba8d7c35ea" + ], + "layout": "IPY_MODEL_6739176497a24677bed9ce1d499ce111", "tabbable": null, - "tooltip": null, - "value": 30931277.0 + "tooltip": null } }, - "ba89e00a862d448e8dc72d837a38fe5a": { + "bb2fc960507949aea6439fcd3c77de5b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6578,48 +6534,7 @@ "width": null } }, - "badfbcc018f64af28731edbb3cf0c438": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "bbe8e85b50614b6895dfc5261cefbd3f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_6954ba9a0a8544c8ab34caf9382b3919", - "placeholder": "​", - "style": "IPY_MODEL_9ee9ae8ff5f64abd9dba00576d9248cd", - "tabbable": null, - "tooltip": null, - "value": " 2/2 [00:00<00:00, 597.27it/s]" - } - }, - "bd82670a06d84e1fa6cb4197d311667d": { + "bcb6b4fdcebe40208119e7b000c67176": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6672,48 +6587,73 @@ "width": null } }, - "bdfc00756c4b4ea291b1b12d3c453adb": { + "bfcb4b6339d14370bc404a61e757edfd": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_53f7d5a3fe5045aea631347f5778ed5b", - "placeholder": "​", - "style": "IPY_MODEL_57c3c61cde5d4837a1643acc4efaa530", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_67956635d769462da5b0f8ec7ca4575b", + "IPY_MODEL_6e84e471535f4aa89081faaaa485d6c3", + "IPY_MODEL_f0cb3f6ef1cd478f8be08c7d0285e829" + ], + "layout": "IPY_MODEL_cc31bc3295e7426890cf527d78a13416", "tabbable": null, - "tooltip": null, - "value": "Computing checksums: 100%" + "tooltip": null } }, - "be908d64fea14e7a8dacc12ac0c6dd97": { + "c0366a87be804af7bcf6f5cd7f11bc3b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "ProgressStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" + } + }, + "c1960242d8a3445da3b5cfd12aa829f9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_92880a6894cd410ba97664fbbbbe340e", + "max": 60000.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_b1625d60d8254709b2fbc8015a483069", + "tabbable": null, + "tooltip": null, + "value": 60000.0 } }, - "beb7c925e927474da59521fcae36f1b5": { + "c20bdfdc755d478c8d2c59d296af1748": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -6729,17 +6669,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_d0cf2f4503034449b080c3b3081f634c", - "max": 2.0, + "layout": "IPY_MODEL_6f0a00d7d264477684a40569e5e3fb89", + "max": 60000.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_27d51d7d7c394b8ca5b9c6dc1f2f28ef", + "style": "IPY_MODEL_210dbd38b6ce4f9e9f8b810ac64d03bf", "tabbable": null, "tooltip": null, - "value": 2.0 + "value": 60000.0 } }, - "bf2c115cc0d44b6fa22a95924ce0e2c1": { + "c65df96729f9462e8df514c9d2bab3e8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6792,7 +6732,25 @@ "width": null } }, - "bf7b754fe88b42c2a0ebefbef27aaa5d": { + "c77f86be94734e2ba274bf4267c5a824": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "cc31bc3295e7426890cf527d78a13416": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -6845,33 +6803,23 @@ "width": null } }, - "c0f63161d8b64e1d88fb06474e6eb468": { + "cdf6adba96a64fc5a04910695f01468c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_afb259c49ba34750a8a8814d7dc507b6", - "max": 60000.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_8a031d58353a4a56b2ee095968c9120f", - "tabbable": null, - "tooltip": null, - "value": 60000.0 + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "c31bcb9951714ea7b4d0d8e9793f409b": { + "cef86182d7ef449481f59dfea70aa34a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -6886,75 +6834,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_b1d1946f6c3a4ee8bc68f10cfe33d799", - "IPY_MODEL_6492748e048c4fe69d67f2f82d4e0597", - "IPY_MODEL_b754e4894e834fc19df74d003d4ab747" + "IPY_MODEL_8cf5382c91f64f789a1af9c7918f14bb", + "IPY_MODEL_1e5e214067f448fe820c272b4d8b60b6", + "IPY_MODEL_58bd914194a245c2b1a963606103a9bd" ], - "layout": "IPY_MODEL_df6d40c4585b4191920844c6eef8bc16", + "layout": "IPY_MODEL_25c0e4e85ebb41299102ad0b3e0880b4", "tabbable": null, "tooltip": null } }, - "c35a2bc3029c426483bd38115de30f66": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c501ce55b0824b50bbbd81608041645c": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_57c3bbf911934c1b954d08e7df293a56", - "placeholder": "​", - "style": "IPY_MODEL_e777bd11a1bc40dbb3b01b6f0a31135b", - "tabbable": null, - "tooltip": null, - "value": "100%" - } - }, - "c5ae7198f4aa46179022a46d7c59764e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c5c385c1288d47d3b192dde525ec8305": { + "d0dfbf919e5f422689492055a00be836": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -6972,46 +6861,60 @@ "text_color": null } }, - "c701552093d1471bb9ace0f6dcd2c9bb": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_195f6f44461b4637898d20c3f277f04c", - "placeholder": "​", - "style": "IPY_MODEL_1a190a961ec641a28b3c636af3b264dc", - "tabbable": null, - "tooltip": null, - "value": " 40/40 [00:00<00:00, 62.73it/s]" - } - }, - "c87c43a894a24676985679a70e0b0d69": { - "model_module": "@jupyter-widgets/controls", + "d54af3f6955d4b968858d238a0210190": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "LayoutModel", "state": { - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "c970b98ad16d4e058311518f87d4705f": { + "d5d9319b3ee0495d88f51937931cd00c": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7064,7 +6967,25 @@ "width": null } }, - "cb746766609e4be886215339a1a76de1": { + "d86fc4609ac5440a807e454ed938d58e": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "d936e9a2111644719473853bc9465d85": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -7080,17 +7001,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_5d7fd3a699f145eaa96b37d43b96276e", - "max": 40.0, + "layout": "IPY_MODEL_aba8cf45b54448a59ae5e30586981cc2", + "max": 2.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_35a155d26b984654ab25b9e85ccccd6f", + "style": "IPY_MODEL_e06e8dd00ef946db9d9676c674e9f1ff", "tabbable": null, "tooltip": null, - "value": 40.0 + "value": 2.0 } }, - "cda1df54889f4e3bb275c8c2fd8ec82a": { + "d9b3afcffed047abb3d7c9215eacb041": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7143,7 +7064,7 @@ "width": null } }, - "d0cf2f4503034449b080c3b3081f634c": { + "d9bfaf958ae54bdaa41267876482d6af": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7196,7 +7117,77 @@ "width": null } }, - "d37c5155b2a140bc9d293b5579737109": { + "da5cdaff84244e95b85f4f6729933e89": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "dac3e32ab9a846e79186067c2b27a96c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "df804279770c4bbdbba569e996a72047": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "e06e8dd00ef946db9d9676c674e9f1ff": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "e127093a41b442febda97da50e709395": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -7211,15 +7202,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_6fa9185a75e4476a9f7bb3766fa59734", + "layout": "IPY_MODEL_7d5c3f6e3cdc47378b7a095dc828c708", "placeholder": "​", - "style": "IPY_MODEL_56ab7eb7d7514ac4a5ca99fbec95176c", + "style": "IPY_MODEL_7acec2eb1b9b4c74860f49bf17a12246", "tabbable": null, "tooltip": null, - "value": " 60000/60000 [00:11<00:00, 6991.32 examples/s]" + "value": " 30.9M/30.9M [00:00<00:00, 85.2MB/s]" } }, - "d4701b3f33d74bc4be0e3b87b63572da": { + "e38940706f02447996928468d3f523eb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -7235,17 +7226,40 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_4fd6ca7a7dd446879a6f2f55860227d9", - "max": 40.0, + "layout": "IPY_MODEL_97578dccf99646909cc139834ab78ea9", + "max": 30931277.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_c87c43a894a24676985679a70e0b0d69", + "style": "IPY_MODEL_cdf6adba96a64fc5a04910695f01468c", "tabbable": null, "tooltip": null, - "value": 40.0 + "value": 30931277.0 + } + }, + "e6d9313a802d4513bc93abf9ffa9fc9b": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_bcb6b4fdcebe40208119e7b000c67176", + "placeholder": "​", + "style": "IPY_MODEL_606a0ff67cfd457c88c691c81de63a4c", + "tabbable": null, + "tooltip": null, + "value": "100%" } }, - "d5f0f111e29b4da996f76d93a33612b5": { + "ed24804748ab483289fec871eb4e7ebf": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -7263,30 +7277,31 @@ "text_color": null } }, - "dccf399c747d4d1d82bce77b5b675956": { + "ee5568e238c045b59cf17074e12437c9": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_bd82670a06d84e1fa6cb4197d311667d", - "placeholder": "​", - "style": "IPY_MODEL_badfbcc018f64af28731edbb3cf0c438", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_7e624075712f49aeb75f702d9f7850d8", + "IPY_MODEL_d936e9a2111644719473853bc9465d85", + "IPY_MODEL_26b545a844a84c278f68d51645f7e371" + ], + "layout": "IPY_MODEL_33d5aee8319348e485ec3980bc726f23", "tabbable": null, - "tooltip": null, - "value": "100%" + "tooltip": null } }, - "df6d40c4585b4191920844c6eef8bc16": { + "eec22da0f1c144399d3b96c5a790810e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7339,49 +7354,120 @@ "width": null } }, - "e1f7f496e0bd4db1ac83de92100a6631": { + "eefff7211ed94c5b90094ff9520c50b5": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "f03a0d23baa4409abb0c7271bd76ab8a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_803d8c89e37c4695af839e22e27d45ad", - "IPY_MODEL_c0f63161d8b64e1d88fb06474e6eb468", - "IPY_MODEL_51120e68bd384037a4668fe393f7be13" - ], - "layout": "IPY_MODEL_ba89e00a862d448e8dc72d837a38fe5a", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_c65df96729f9462e8df514c9d2bab3e8", + "placeholder": "​", + "style": "IPY_MODEL_06c85507cf49495584b002e6aaa044e8", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": " 40/40 [00:00<00:00, 61.46it/s]" } }, - "e777bd11a1bc40dbb3b01b6f0a31135b": { + "f082a4eab5444b019ea911ae0fb7a92d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HTMLModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HTMLModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_a88f012a925b438fbc901a161c09cf50", + "placeholder": "​", + "style": "IPY_MODEL_f7b0cd88615641199d9599093664c3f3", + "tabbable": null, + "tooltip": null, + "value": " 40/40 [00:00<00:00, 63.47it/s]" + } + }, + "f0cb3f6ef1cd478f8be08c7d0285e829": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_118d13a1737e460b986120e1cd8488c6", + "placeholder": "​", + "style": "IPY_MODEL_884d6ce901e24a3797e35af5711b0f35", + "tabbable": null, + "tooltip": null, + "value": " 60000/60000 [00:11<00:00, 5023.35 examples/s]" + } + }, + "f11e1a00f1c942a080552a095321e730": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b149b2726a33413c8e2fde403bed8e98", + "max": 40.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_6dd2d74eb1d04d61844ec3c03149c90b", + "tabbable": null, + "tooltip": null, + "value": 40.0 } }, - "e8da8c5e504b47e9b752f785493250ce": { + "f1c64d058ec34988a144f78b8ce7cbc8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -7434,73 +7520,41 @@ "width": null } }, - "e8f51e9d01d447c3b27b88d0c146d11b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_abc24829115b46edb7572dc55403960a", - "max": 40.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_81b854f5964b47979c3b45402b07d21d", - "tabbable": null, - "tooltip": null, - "value": 40.0 - } - }, - "ec9e629fd2904b8fbf99b7c637113a54": { + "f2fa408e34274722bd36f3791c967fb2": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0240b26e2e8347049e4a5df861bb7a0d", - "IPY_MODEL_d4701b3f33d74bc4be0e3b87b63572da", - "IPY_MODEL_8c1eafd77d904a36aa9f617ae2a33e13" - ], - "layout": "IPY_MODEL_5f93eedb157d4345bc780bd62a65204e", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "eda9c8fc9ec84b47b274aead1d312c12": { + "f784e45cbe9248ae9c16491028d6bf8e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "f282b3d3edd34bd19404aa81c4bd2be9": { + "f7b0cd88615641199d9599093664c3f3": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -7518,81 +7572,27 @@ "text_color": null } }, - "f2c0fcf1952846d5b613a055c1f1e0bc": { + "f9f45d26f74148d5aafa521c2e42894d": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_a3cce43cc858462a882adcb42f8671a7", - "IPY_MODEL_cb746766609e4be886215339a1a76de1", - "IPY_MODEL_69ec4f0b4df24afeb44979768207ccb2" - ], - "layout": "IPY_MODEL_b2edc3bafbc4407f8f9a8b986aa82b90", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_a9e701e6d5bf4ec2a9c900edea6104e5", + "placeholder": "​", + "style": "IPY_MODEL_da5cdaff84244e95b85f4f6729933e89", "tabbable": null, - "tooltip": null - } - }, - "f9fd3a8802ff4c8799b62137434f622c": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "2.0.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "tooltip": null, + "value": "100%" } } }, diff --git a/master/tutorials/datalab/tabular.ipynb b/master/tutorials/datalab/tabular.ipynb index b3092f1d2..55a26f513 100644 --- a/master/tutorials/datalab/tabular.ipynb +++ b/master/tutorials/datalab/tabular.ipynb @@ -73,10 +73,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:13.469873Z", - "iopub.status.busy": "2024-09-05T19:37:13.469691Z", - "iopub.status.idle": "2024-09-05T19:37:14.643451Z", - "shell.execute_reply": "2024-09-05T19:37:14.642938Z" + "iopub.execute_input": "2024-09-06T19:37:06.951842Z", + "iopub.status.busy": "2024-09-06T19:37:06.951670Z", + "iopub.status.idle": "2024-09-06T19:37:08.104160Z", + "shell.execute_reply": "2024-09-06T19:37:08.103605Z" }, "nbsphinx": "hidden" }, @@ -86,7 +86,7 @@ "dependencies = [\"cleanlab\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -111,10 +111,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.646200Z", - "iopub.status.busy": "2024-09-05T19:37:14.645631Z", - "iopub.status.idle": "2024-09-05T19:37:14.663967Z", - "shell.execute_reply": "2024-09-05T19:37:14.663492Z" + "iopub.execute_input": "2024-09-06T19:37:08.106594Z", + "iopub.status.busy": "2024-09-06T19:37:08.106312Z", + "iopub.status.idle": "2024-09-06T19:37:08.124373Z", + "shell.execute_reply": "2024-09-06T19:37:08.123937Z" } }, "outputs": [], @@ -154,10 +154,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.666331Z", - "iopub.status.busy": "2024-09-05T19:37:14.665911Z", - "iopub.status.idle": "2024-09-05T19:37:14.706816Z", - "shell.execute_reply": "2024-09-05T19:37:14.706224Z" + "iopub.execute_input": "2024-09-06T19:37:08.126574Z", + "iopub.status.busy": "2024-09-06T19:37:08.126159Z", + "iopub.status.idle": "2024-09-06T19:37:08.148467Z", + "shell.execute_reply": "2024-09-06T19:37:08.148011Z" } }, "outputs": [ @@ -264,10 +264,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.709267Z", - "iopub.status.busy": "2024-09-05T19:37:14.708881Z", - "iopub.status.idle": "2024-09-05T19:37:14.712569Z", - "shell.execute_reply": "2024-09-05T19:37:14.712080Z" + "iopub.execute_input": "2024-09-06T19:37:08.150542Z", + "iopub.status.busy": "2024-09-06T19:37:08.150195Z", + "iopub.status.idle": "2024-09-06T19:37:08.153510Z", + "shell.execute_reply": "2024-09-06T19:37:08.153043Z" } }, "outputs": [], @@ -288,10 +288,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.714680Z", - "iopub.status.busy": "2024-09-05T19:37:14.714329Z", - "iopub.status.idle": "2024-09-05T19:37:14.721981Z", - "shell.execute_reply": "2024-09-05T19:37:14.721544Z" + "iopub.execute_input": "2024-09-06T19:37:08.155506Z", + "iopub.status.busy": "2024-09-06T19:37:08.155162Z", + "iopub.status.idle": "2024-09-06T19:37:08.163216Z", + "shell.execute_reply": "2024-09-06T19:37:08.162658Z" } }, "outputs": [], @@ -336,10 +336,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.724136Z", - "iopub.status.busy": "2024-09-05T19:37:14.723769Z", - "iopub.status.idle": "2024-09-05T19:37:14.726297Z", - "shell.execute_reply": "2024-09-05T19:37:14.725816Z" + "iopub.execute_input": "2024-09-06T19:37:08.165384Z", + "iopub.status.busy": "2024-09-06T19:37:08.164978Z", + "iopub.status.idle": "2024-09-06T19:37:08.167532Z", + "shell.execute_reply": "2024-09-06T19:37:08.167093Z" } }, "outputs": [], @@ -362,10 +362,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:14.728450Z", - "iopub.status.busy": "2024-09-05T19:37:14.728116Z", - "iopub.status.idle": "2024-09-05T19:37:17.842883Z", - "shell.execute_reply": "2024-09-05T19:37:17.842351Z" + "iopub.execute_input": "2024-09-06T19:37:08.169550Z", + "iopub.status.busy": "2024-09-06T19:37:08.169205Z", + "iopub.status.idle": "2024-09-06T19:37:11.232996Z", + "shell.execute_reply": "2024-09-06T19:37:11.232340Z" } }, "outputs": [], @@ -401,10 +401,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:17.845676Z", - "iopub.status.busy": "2024-09-05T19:37:17.845310Z", - "iopub.status.idle": "2024-09-05T19:37:17.854733Z", - "shell.execute_reply": "2024-09-05T19:37:17.854165Z" + "iopub.execute_input": "2024-09-06T19:37:11.235550Z", + "iopub.status.busy": "2024-09-06T19:37:11.235362Z", + "iopub.status.idle": "2024-09-06T19:37:11.244291Z", + "shell.execute_reply": "2024-09-06T19:37:11.243862Z" } }, "outputs": [], @@ -436,10 +436,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:17.857062Z", - "iopub.status.busy": "2024-09-05T19:37:17.856748Z", - "iopub.status.idle": "2024-09-05T19:37:19.875306Z", - "shell.execute_reply": "2024-09-05T19:37:19.874590Z" + "iopub.execute_input": "2024-09-06T19:37:11.246379Z", + "iopub.status.busy": "2024-09-06T19:37:11.246205Z", + "iopub.status.idle": "2024-09-06T19:37:13.219249Z", + "shell.execute_reply": "2024-09-06T19:37:13.218645Z" } }, "outputs": [ @@ -476,10 +476,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.877872Z", - "iopub.status.busy": "2024-09-05T19:37:19.877351Z", - "iopub.status.idle": "2024-09-05T19:37:19.896585Z", - "shell.execute_reply": "2024-09-05T19:37:19.895985Z" + "iopub.execute_input": "2024-09-06T19:37:13.221677Z", + "iopub.status.busy": "2024-09-06T19:37:13.221173Z", + "iopub.status.idle": "2024-09-06T19:37:13.240218Z", + "shell.execute_reply": "2024-09-06T19:37:13.239749Z" }, "scrolled": true }, @@ -609,10 +609,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.898896Z", - "iopub.status.busy": "2024-09-05T19:37:19.898559Z", - "iopub.status.idle": "2024-09-05T19:37:19.907000Z", - "shell.execute_reply": "2024-09-05T19:37:19.906535Z" + "iopub.execute_input": "2024-09-06T19:37:13.242381Z", + "iopub.status.busy": "2024-09-06T19:37:13.242042Z", + "iopub.status.idle": "2024-09-06T19:37:13.250225Z", + "shell.execute_reply": "2024-09-06T19:37:13.249765Z" } }, "outputs": [ @@ -716,10 +716,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.909010Z", - "iopub.status.busy": "2024-09-05T19:37:19.908684Z", - "iopub.status.idle": "2024-09-05T19:37:19.917678Z", - "shell.execute_reply": "2024-09-05T19:37:19.917096Z" + "iopub.execute_input": "2024-09-06T19:37:13.252315Z", + "iopub.status.busy": "2024-09-06T19:37:13.251975Z", + "iopub.status.idle": "2024-09-06T19:37:13.260671Z", + "shell.execute_reply": "2024-09-06T19:37:13.260195Z" } }, "outputs": [ @@ -848,10 +848,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.919930Z", - "iopub.status.busy": "2024-09-05T19:37:19.919439Z", - "iopub.status.idle": "2024-09-05T19:37:19.927966Z", - "shell.execute_reply": "2024-09-05T19:37:19.927364Z" + "iopub.execute_input": "2024-09-06T19:37:13.262712Z", + "iopub.status.busy": "2024-09-06T19:37:13.262373Z", + "iopub.status.idle": "2024-09-06T19:37:13.270531Z", + "shell.execute_reply": "2024-09-06T19:37:13.269960Z" } }, "outputs": [ @@ -965,10 +965,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.930006Z", - "iopub.status.busy": "2024-09-05T19:37:19.929680Z", - "iopub.status.idle": "2024-09-05T19:37:19.938743Z", - "shell.execute_reply": "2024-09-05T19:37:19.938175Z" + "iopub.execute_input": "2024-09-06T19:37:13.272557Z", + "iopub.status.busy": "2024-09-06T19:37:13.272379Z", + "iopub.status.idle": "2024-09-06T19:37:13.281035Z", + "shell.execute_reply": "2024-09-06T19:37:13.280557Z" } }, "outputs": [ @@ -1079,10 +1079,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.940940Z", - "iopub.status.busy": "2024-09-05T19:37:19.940628Z", - "iopub.status.idle": "2024-09-05T19:37:19.948170Z", - "shell.execute_reply": "2024-09-05T19:37:19.947590Z" + "iopub.execute_input": "2024-09-06T19:37:13.283068Z", + "iopub.status.busy": "2024-09-06T19:37:13.282889Z", + "iopub.status.idle": "2024-09-06T19:37:13.290486Z", + "shell.execute_reply": "2024-09-06T19:37:13.290023Z" } }, "outputs": [ @@ -1197,10 +1197,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.950230Z", - "iopub.status.busy": "2024-09-05T19:37:19.949916Z", - "iopub.status.idle": "2024-09-05T19:37:19.957426Z", - "shell.execute_reply": "2024-09-05T19:37:19.956989Z" + "iopub.execute_input": "2024-09-06T19:37:13.292532Z", + "iopub.status.busy": "2024-09-06T19:37:13.292191Z", + "iopub.status.idle": "2024-09-06T19:37:13.299536Z", + "shell.execute_reply": "2024-09-06T19:37:13.298963Z" } }, "outputs": [ @@ -1306,10 +1306,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:19.959710Z", - "iopub.status.busy": "2024-09-05T19:37:19.959220Z", - "iopub.status.idle": "2024-09-05T19:37:19.967448Z", - "shell.execute_reply": "2024-09-05T19:37:19.967010Z" + "iopub.execute_input": "2024-09-06T19:37:13.301807Z", + "iopub.status.busy": "2024-09-06T19:37:13.301492Z", + "iopub.status.idle": "2024-09-06T19:37:13.309949Z", + "shell.execute_reply": "2024-09-06T19:37:13.309476Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/datalab/text.html b/master/tutorials/datalab/text.html index 8b385d7f6..b51846d10 100644 --- a/master/tutorials/datalab/text.html +++ b/master/tutorials/datalab/text.html @@ -795,7 +795,7 @@

    2. Load and format the text dataset
     This dataset has 10 classes.
    -Classes: {'card_payment_fee_charged', 'cancel_transfer', 'apple_pay_or_google_pay', 'card_about_to_expire', 'change_pin', 'visa_or_mastercard', 'beneficiary_not_allowed', 'getting_spare_card', 'lost_or_stolen_phone', 'supported_cards_and_currencies'}
    +Classes: {'card_about_to_expire', 'card_payment_fee_charged', 'supported_cards_and_currencies', 'apple_pay_or_google_pay', 'beneficiary_not_allowed', 'lost_or_stolen_phone', 'visa_or_mastercard', 'cancel_transfer', 'getting_spare_card', 'change_pin'}
     

    Let’s view the i-th example in the dataset:

    diff --git a/master/tutorials/datalab/text.ipynb b/master/tutorials/datalab/text.ipynb index 9e0aa3195..0357de56a 100644 --- a/master/tutorials/datalab/text.ipynb +++ b/master/tutorials/datalab/text.ipynb @@ -75,10 +75,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:22.667514Z", - "iopub.status.busy": "2024-09-05T19:37:22.667337Z", - "iopub.status.idle": "2024-09-05T19:37:25.554239Z", - "shell.execute_reply": "2024-09-05T19:37:25.553659Z" + "iopub.execute_input": "2024-09-06T19:37:16.238148Z", + "iopub.status.busy": "2024-09-06T19:37:16.237968Z", + "iopub.status.idle": "2024-09-06T19:37:19.032647Z", + "shell.execute_reply": "2024-09-06T19:37:19.031997Z" }, "nbsphinx": "hidden" }, @@ -96,7 +96,7 @@ "os.environ[\"TOKENIZERS_PARALLELISM\"] = \"false\" # disable parallelism to avoid deadlocks with huggingface\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -121,10 +121,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.556973Z", - "iopub.status.busy": "2024-09-05T19:37:25.556474Z", - "iopub.status.idle": "2024-09-05T19:37:25.559630Z", - "shell.execute_reply": "2024-09-05T19:37:25.559168Z" + "iopub.execute_input": "2024-09-06T19:37:19.035274Z", + "iopub.status.busy": "2024-09-06T19:37:19.034943Z", + "iopub.status.idle": "2024-09-06T19:37:19.038478Z", + "shell.execute_reply": "2024-09-06T19:37:19.037992Z" } }, "outputs": [], @@ -145,10 +145,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.561758Z", - "iopub.status.busy": "2024-09-05T19:37:25.561422Z", - "iopub.status.idle": "2024-09-05T19:37:25.564391Z", - "shell.execute_reply": "2024-09-05T19:37:25.563936Z" + "iopub.execute_input": "2024-09-06T19:37:19.040624Z", + "iopub.status.busy": "2024-09-06T19:37:19.040295Z", + "iopub.status.idle": "2024-09-06T19:37:19.043522Z", + "shell.execute_reply": "2024-09-06T19:37:19.043021Z" }, "nbsphinx": "hidden" }, @@ -178,10 +178,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.566426Z", - "iopub.status.busy": "2024-09-05T19:37:25.566086Z", - "iopub.status.idle": "2024-09-05T19:37:25.606289Z", - "shell.execute_reply": "2024-09-05T19:37:25.605745Z" + "iopub.execute_input": "2024-09-06T19:37:19.045678Z", + "iopub.status.busy": "2024-09-06T19:37:19.045330Z", + "iopub.status.idle": "2024-09-06T19:37:19.065598Z", + "shell.execute_reply": "2024-09-06T19:37:19.065087Z" } }, "outputs": [ @@ -271,10 +271,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.608523Z", - "iopub.status.busy": "2024-09-05T19:37:25.608173Z", - "iopub.status.idle": "2024-09-05T19:37:25.611849Z", - "shell.execute_reply": "2024-09-05T19:37:25.611337Z" + "iopub.execute_input": "2024-09-06T19:37:19.067819Z", + "iopub.status.busy": "2024-09-06T19:37:19.067470Z", + "iopub.status.idle": "2024-09-06T19:37:19.071077Z", + "shell.execute_reply": "2024-09-06T19:37:19.070583Z" } }, "outputs": [ @@ -283,7 +283,7 @@ "output_type": "stream", "text": [ "This dataset has 10 classes.\n", - "Classes: {'card_payment_fee_charged', 'cancel_transfer', 'apple_pay_or_google_pay', 'card_about_to_expire', 'change_pin', 'visa_or_mastercard', 'beneficiary_not_allowed', 'getting_spare_card', 'lost_or_stolen_phone', 'supported_cards_and_currencies'}\n" + "Classes: {'card_about_to_expire', 'card_payment_fee_charged', 'supported_cards_and_currencies', 'apple_pay_or_google_pay', 'beneficiary_not_allowed', 'lost_or_stolen_phone', 'visa_or_mastercard', 'cancel_transfer', 'getting_spare_card', 'change_pin'}\n" ] } ], @@ -307,10 +307,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.613929Z", - "iopub.status.busy": "2024-09-05T19:37:25.613661Z", - "iopub.status.idle": "2024-09-05T19:37:25.616746Z", - "shell.execute_reply": "2024-09-05T19:37:25.616205Z" + "iopub.execute_input": "2024-09-06T19:37:19.073199Z", + "iopub.status.busy": "2024-09-06T19:37:19.072859Z", + "iopub.status.idle": "2024-09-06T19:37:19.075873Z", + "shell.execute_reply": "2024-09-06T19:37:19.075346Z" } }, "outputs": [ @@ -365,10 +365,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:25.618901Z", - "iopub.status.busy": "2024-09-05T19:37:25.618568Z", - "iopub.status.idle": "2024-09-05T19:37:29.268375Z", - "shell.execute_reply": "2024-09-05T19:37:29.267707Z" + "iopub.execute_input": "2024-09-06T19:37:19.077966Z", + "iopub.status.busy": "2024-09-06T19:37:19.077636Z", + "iopub.status.idle": "2024-09-06T19:37:23.171760Z", + "shell.execute_reply": "2024-09-06T19:37:23.171196Z" } }, "outputs": [ @@ -416,10 +416,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:29.271118Z", - "iopub.status.busy": "2024-09-05T19:37:29.270673Z", - "iopub.status.idle": "2024-09-05T19:37:30.169853Z", - "shell.execute_reply": "2024-09-05T19:37:30.169263Z" + "iopub.execute_input": "2024-09-06T19:37:23.174471Z", + "iopub.status.busy": "2024-09-06T19:37:23.174274Z", + "iopub.status.idle": "2024-09-06T19:37:24.103567Z", + "shell.execute_reply": "2024-09-06T19:37:24.102969Z" }, "scrolled": true }, @@ -451,10 +451,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:30.172922Z", - "iopub.status.busy": "2024-09-05T19:37:30.172351Z", - "iopub.status.idle": "2024-09-05T19:37:30.175456Z", - "shell.execute_reply": "2024-09-05T19:37:30.174947Z" + "iopub.execute_input": "2024-09-06T19:37:24.107438Z", + "iopub.status.busy": "2024-09-06T19:37:24.106451Z", + "iopub.status.idle": "2024-09-06T19:37:24.110626Z", + "shell.execute_reply": "2024-09-06T19:37:24.110110Z" } }, "outputs": [], @@ -474,10 +474,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:30.177920Z", - "iopub.status.busy": "2024-09-05T19:37:30.177550Z", - "iopub.status.idle": "2024-09-05T19:37:32.209250Z", - "shell.execute_reply": "2024-09-05T19:37:32.208579Z" + "iopub.execute_input": "2024-09-06T19:37:24.114244Z", + "iopub.status.busy": "2024-09-06T19:37:24.113304Z", + "iopub.status.idle": "2024-09-06T19:37:26.122882Z", + "shell.execute_reply": "2024-09-06T19:37:26.122195Z" }, "scrolled": true }, @@ -521,10 +521,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.212395Z", - "iopub.status.busy": "2024-09-05T19:37:32.211737Z", - "iopub.status.idle": "2024-09-05T19:37:32.235720Z", - "shell.execute_reply": "2024-09-05T19:37:32.235203Z" + "iopub.execute_input": "2024-09-06T19:37:26.126146Z", + "iopub.status.busy": "2024-09-06T19:37:26.125493Z", + "iopub.status.idle": "2024-09-06T19:37:26.149493Z", + "shell.execute_reply": "2024-09-06T19:37:26.148954Z" }, "scrolled": true }, @@ -654,10 +654,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.238297Z", - "iopub.status.busy": "2024-09-05T19:37:32.237890Z", - "iopub.status.idle": "2024-09-05T19:37:32.247569Z", - "shell.execute_reply": "2024-09-05T19:37:32.247122Z" + "iopub.execute_input": "2024-09-06T19:37:26.152122Z", + "iopub.status.busy": "2024-09-06T19:37:26.151750Z", + "iopub.status.idle": "2024-09-06T19:37:26.163613Z", + "shell.execute_reply": "2024-09-06T19:37:26.163031Z" }, "scrolled": true }, @@ -767,10 +767,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.249546Z", - "iopub.status.busy": "2024-09-05T19:37:32.249251Z", - "iopub.status.idle": "2024-09-05T19:37:32.253306Z", - "shell.execute_reply": "2024-09-05T19:37:32.252844Z" + "iopub.execute_input": "2024-09-06T19:37:26.165819Z", + "iopub.status.busy": "2024-09-06T19:37:26.165507Z", + "iopub.status.idle": "2024-09-06T19:37:26.169927Z", + "shell.execute_reply": "2024-09-06T19:37:26.169445Z" } }, "outputs": [ @@ -808,10 +808,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.255258Z", - "iopub.status.busy": "2024-09-05T19:37:32.255073Z", - "iopub.status.idle": "2024-09-05T19:37:32.261559Z", - "shell.execute_reply": "2024-09-05T19:37:32.261077Z" + "iopub.execute_input": "2024-09-06T19:37:26.171802Z", + "iopub.status.busy": "2024-09-06T19:37:26.171622Z", + "iopub.status.idle": "2024-09-06T19:37:26.178323Z", + "shell.execute_reply": "2024-09-06T19:37:26.177759Z" } }, "outputs": [ @@ -928,10 +928,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.263657Z", - "iopub.status.busy": "2024-09-05T19:37:32.263325Z", - "iopub.status.idle": "2024-09-05T19:37:32.269747Z", - "shell.execute_reply": "2024-09-05T19:37:32.269278Z" + "iopub.execute_input": "2024-09-06T19:37:26.180430Z", + "iopub.status.busy": "2024-09-06T19:37:26.180102Z", + "iopub.status.idle": "2024-09-06T19:37:26.186371Z", + "shell.execute_reply": "2024-09-06T19:37:26.185807Z" } }, "outputs": [ @@ -1014,10 +1014,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.271867Z", - "iopub.status.busy": "2024-09-05T19:37:32.271500Z", - "iopub.status.idle": "2024-09-05T19:37:32.277119Z", - "shell.execute_reply": "2024-09-05T19:37:32.276609Z" + "iopub.execute_input": "2024-09-06T19:37:26.188480Z", + "iopub.status.busy": "2024-09-06T19:37:26.188150Z", + "iopub.status.idle": "2024-09-06T19:37:26.194198Z", + "shell.execute_reply": "2024-09-06T19:37:26.193624Z" } }, "outputs": [ @@ -1125,10 +1125,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.279176Z", - "iopub.status.busy": "2024-09-05T19:37:32.278837Z", - "iopub.status.idle": "2024-09-05T19:37:32.287109Z", - "shell.execute_reply": "2024-09-05T19:37:32.286569Z" + "iopub.execute_input": "2024-09-06T19:37:26.196327Z", + "iopub.status.busy": "2024-09-06T19:37:26.195981Z", + "iopub.status.idle": "2024-09-06T19:37:26.204376Z", + "shell.execute_reply": "2024-09-06T19:37:26.203913Z" } }, "outputs": [ @@ -1239,10 +1239,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.289281Z", - "iopub.status.busy": "2024-09-05T19:37:32.288965Z", - "iopub.status.idle": "2024-09-05T19:37:32.294242Z", - "shell.execute_reply": "2024-09-05T19:37:32.293707Z" + "iopub.execute_input": "2024-09-06T19:37:26.206432Z", + "iopub.status.busy": "2024-09-06T19:37:26.206091Z", + "iopub.status.idle": "2024-09-06T19:37:26.211539Z", + "shell.execute_reply": "2024-09-06T19:37:26.211070Z" } }, "outputs": [ @@ -1310,10 +1310,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.296374Z", - "iopub.status.busy": "2024-09-05T19:37:32.296057Z", - "iopub.status.idle": "2024-09-05T19:37:32.301404Z", - "shell.execute_reply": "2024-09-05T19:37:32.300861Z" + "iopub.execute_input": "2024-09-06T19:37:26.213685Z", + "iopub.status.busy": "2024-09-06T19:37:26.213350Z", + "iopub.status.idle": "2024-09-06T19:37:26.218528Z", + "shell.execute_reply": "2024-09-06T19:37:26.218074Z" } }, "outputs": [ @@ -1392,10 +1392,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.303349Z", - "iopub.status.busy": "2024-09-05T19:37:32.303171Z", - "iopub.status.idle": "2024-09-05T19:37:32.306705Z", - "shell.execute_reply": "2024-09-05T19:37:32.306262Z" + "iopub.execute_input": "2024-09-06T19:37:26.220571Z", + "iopub.status.busy": "2024-09-06T19:37:26.220232Z", + "iopub.status.idle": "2024-09-06T19:37:26.223906Z", + "shell.execute_reply": "2024-09-06T19:37:26.223327Z" } }, "outputs": [ @@ -1449,10 +1449,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:32.308852Z", - "iopub.status.busy": "2024-09-05T19:37:32.308521Z", - "iopub.status.idle": "2024-09-05T19:37:32.313482Z", - "shell.execute_reply": "2024-09-05T19:37:32.313025Z" + "iopub.execute_input": "2024-09-06T19:37:26.226160Z", + "iopub.status.busy": "2024-09-06T19:37:26.225819Z", + "iopub.status.idle": "2024-09-06T19:37:26.231140Z", + "shell.execute_reply": "2024-09-06T19:37:26.230573Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/datalab/workflows.html b/master/tutorials/datalab/workflows.html index 11d3b5b97..bdff93976 100644 --- a/master/tutorials/datalab/workflows.html +++ b/master/tutorials/datalab/workflows.html @@ -3144,224 +3144,224 @@

    6. (Optional) Visualize the Results - +
    - - - - - - - - - + + + + + + + + + - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +
     AgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_scoreAgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_score
    8nannannannannanNaTTrue0.000000
    1nanFemaleRural6421.1600005.000000NaTFalse0.666667
    9nanMaleRural4655.8200001.000000NaTFalse0.666667
    14nanMaleRural6790.4600003.000000NaTFalse0.666667
    13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
    15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
    056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
    246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
    332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
    460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
    525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
    638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
    756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
    1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
    1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
    1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.0000008nannannannannanNaTTrue0.000000
    1nanFemaleRural6421.1600005.000000NaTFalse0.666667
    9nanMaleRural4655.8200001.000000NaTFalse0.666667
    14nanMaleRural6790.4600003.000000NaTFalse0.666667
    13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
    15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
    056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
    246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
    332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
    460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
    525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
    638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
    756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
    1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
    1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
    1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.000000
    @@ -3507,16 +3507,16 @@

    1. Load the Dataset
    ---2024-09-05 19:37:51--  https://s.cleanlab.ai/CIFAR-10-subset.zip
    -Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.109.153, 185.199.108.153, 185.199.111.153, ...
    -Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.109.153|:443... connected.
    +--2024-09-06 19:37:46--  https://s.cleanlab.ai/CIFAR-10-subset.zip
    +Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.111.153, 185.199.110.153, 185.199.109.153, ...
    +Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.111.153|:443... connected.
     HTTP request sent, awaiting response... 200 OK
     Length: 986707 (964K) [application/zip]
     Saving to: ‘CIFAR-10-subset.zip’
     
    -CIFAR-10-subset.zip 100%[===================>] 963.58K  --.-KB/s    in 0.03s
    +CIFAR-10-subset.zip 100%[===================>] 963.58K  --.-KB/s    in 0.005s
     
    -2024-09-05 19:37:51 (32.9 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]
    +2024-09-06 19:37:46 (176 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]
     
     
    @@ -3586,7 +3586,7 @@

    2. Run Datalab Analysis
    -
    +
    @@ -3809,35 +3809,35 @@

    3. Interpret the Results - dark_score is_dark_issue + dark_score 0 - 0.237196 True + 0.237196 1 - 0.197229 True + 0.197229 2 - 0.254188 True + 0.254188 3 - 0.229170 True + 0.229170 4 - 0.208907 True + 0.208907 ... @@ -3846,28 +3846,28 @@

    3. Interpret the ResultsFrog class (Class 0 in the plot) have been darkened, while 100 images from the Truck class (Class 1 in the plot) remain unchanged, as in the CIFAR-10 dataset. This creates a clear spurious correlation between the ‘darkness’ feature and the class labels: Frog images are dark, whereas Truck images are not. We can see that the dark_score values between the two classes are non-overlapping. This characteristic of the dataset is identified by Datalab.

    diff --git a/master/tutorials/datalab/workflows.ipynb b/master/tutorials/datalab/workflows.ipynb index b458579ea..0c93ce2cb 100644 --- a/master/tutorials/datalab/workflows.ipynb +++ b/master/tutorials/datalab/workflows.ipynb @@ -38,10 +38,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:35.608990Z", - "iopub.status.busy": "2024-09-05T19:37:35.608804Z", - "iopub.status.idle": "2024-09-05T19:37:36.049800Z", - "shell.execute_reply": "2024-09-05T19:37:36.049289Z" + "iopub.execute_input": "2024-09-06T19:37:29.604724Z", + "iopub.status.busy": "2024-09-06T19:37:29.604545Z", + "iopub.status.idle": "2024-09-06T19:37:30.035194Z", + "shell.execute_reply": "2024-09-06T19:37:30.034674Z" } }, "outputs": [], @@ -87,10 +87,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:36.052464Z", - "iopub.status.busy": "2024-09-05T19:37:36.052028Z", - "iopub.status.idle": "2024-09-05T19:37:36.185608Z", - "shell.execute_reply": "2024-09-05T19:37:36.185012Z" + "iopub.execute_input": "2024-09-06T19:37:30.037845Z", + "iopub.status.busy": "2024-09-06T19:37:30.037406Z", + "iopub.status.idle": "2024-09-06T19:37:30.168185Z", + "shell.execute_reply": "2024-09-06T19:37:30.167636Z" } }, "outputs": [ @@ -181,10 +181,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:36.188213Z", - "iopub.status.busy": "2024-09-05T19:37:36.187785Z", - "iopub.status.idle": "2024-09-05T19:37:36.211771Z", - "shell.execute_reply": "2024-09-05T19:37:36.211203Z" + "iopub.execute_input": "2024-09-06T19:37:30.170587Z", + "iopub.status.busy": "2024-09-06T19:37:30.170087Z", + "iopub.status.idle": "2024-09-06T19:37:30.193350Z", + "shell.execute_reply": "2024-09-06T19:37:30.192776Z" } }, "outputs": [], @@ -210,10 +210,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:36.214778Z", - "iopub.status.busy": "2024-09-05T19:37:36.214297Z", - "iopub.status.idle": "2024-09-05T19:37:39.119007Z", - "shell.execute_reply": "2024-09-05T19:37:39.118344Z" + "iopub.execute_input": "2024-09-06T19:37:30.195997Z", + "iopub.status.busy": "2024-09-06T19:37:30.195790Z", + "iopub.status.idle": "2024-09-06T19:37:32.997740Z", + "shell.execute_reply": "2024-09-06T19:37:32.997128Z" } }, "outputs": [ @@ -700,10 +700,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:39.121802Z", - "iopub.status.busy": "2024-09-05T19:37:39.121239Z", - "iopub.status.idle": "2024-09-05T19:37:48.039020Z", - "shell.execute_reply": "2024-09-05T19:37:48.038375Z" + "iopub.execute_input": "2024-09-06T19:37:33.000426Z", + "iopub.status.busy": "2024-09-06T19:37:32.999838Z", + "iopub.status.idle": "2024-09-06T19:37:42.839981Z", + "shell.execute_reply": "2024-09-06T19:37:42.839475Z" } }, "outputs": [ @@ -804,10 +804,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:48.041586Z", - "iopub.status.busy": "2024-09-05T19:37:48.041203Z", - "iopub.status.idle": "2024-09-05T19:37:48.208174Z", - "shell.execute_reply": "2024-09-05T19:37:48.207546Z" + "iopub.execute_input": "2024-09-06T19:37:42.842458Z", + "iopub.status.busy": "2024-09-06T19:37:42.842052Z", + "iopub.status.idle": "2024-09-06T19:37:43.014469Z", + "shell.execute_reply": "2024-09-06T19:37:43.013871Z" } }, "outputs": [], @@ -838,10 +838,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:48.210728Z", - "iopub.status.busy": "2024-09-05T19:37:48.210421Z", - "iopub.status.idle": "2024-09-05T19:37:49.609527Z", - "shell.execute_reply": "2024-09-05T19:37:49.609004Z" + "iopub.execute_input": "2024-09-06T19:37:43.016817Z", + "iopub.status.busy": "2024-09-06T19:37:43.016641Z", + "iopub.status.idle": "2024-09-06T19:37:44.396004Z", + "shell.execute_reply": "2024-09-06T19:37:44.395431Z" } }, "outputs": [ @@ -1000,10 +1000,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:49.611837Z", - "iopub.status.busy": "2024-09-05T19:37:49.611455Z", - "iopub.status.idle": "2024-09-05T19:37:50.149593Z", - "shell.execute_reply": "2024-09-05T19:37:50.149038Z" + "iopub.execute_input": "2024-09-06T19:37:44.398298Z", + "iopub.status.busy": "2024-09-06T19:37:44.397931Z", + "iopub.status.idle": "2024-09-06T19:37:44.810929Z", + "shell.execute_reply": "2024-09-06T19:37:44.810371Z" } }, "outputs": [ @@ -1082,10 +1082,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.152292Z", - "iopub.status.busy": "2024-09-05T19:37:50.151696Z", - "iopub.status.idle": "2024-09-05T19:37:50.165608Z", - "shell.execute_reply": "2024-09-05T19:37:50.165110Z" + "iopub.execute_input": "2024-09-06T19:37:44.813440Z", + "iopub.status.busy": "2024-09-06T19:37:44.812940Z", + "iopub.status.idle": "2024-09-06T19:37:44.826271Z", + "shell.execute_reply": "2024-09-06T19:37:44.825842Z" } }, "outputs": [], @@ -1115,10 +1115,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.167994Z", - "iopub.status.busy": "2024-09-05T19:37:50.167587Z", - "iopub.status.idle": "2024-09-05T19:37:50.186934Z", - "shell.execute_reply": "2024-09-05T19:37:50.186405Z" + "iopub.execute_input": "2024-09-06T19:37:44.828390Z", + "iopub.status.busy": "2024-09-06T19:37:44.828044Z", + "iopub.status.idle": "2024-09-06T19:37:44.847179Z", + "shell.execute_reply": "2024-09-06T19:37:44.846760Z" } }, "outputs": [], @@ -1146,10 +1146,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.189317Z", - "iopub.status.busy": "2024-09-05T19:37:50.189017Z", - "iopub.status.idle": "2024-09-05T19:37:50.417357Z", - "shell.execute_reply": "2024-09-05T19:37:50.416811Z" + "iopub.execute_input": "2024-09-06T19:37:44.849314Z", + "iopub.status.busy": "2024-09-06T19:37:44.848979Z", + "iopub.status.idle": "2024-09-06T19:37:45.077019Z", + "shell.execute_reply": "2024-09-06T19:37:45.076447Z" } }, "outputs": [], @@ -1189,10 +1189,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.420095Z", - "iopub.status.busy": "2024-09-05T19:37:50.419658Z", - "iopub.status.idle": "2024-09-05T19:37:50.440418Z", - "shell.execute_reply": "2024-09-05T19:37:50.439793Z" + "iopub.execute_input": "2024-09-06T19:37:45.079688Z", + "iopub.status.busy": "2024-09-06T19:37:45.079281Z", + "iopub.status.idle": "2024-09-06T19:37:45.098946Z", + "shell.execute_reply": "2024-09-06T19:37:45.098466Z" } }, "outputs": [ @@ -1390,10 +1390,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.442606Z", - "iopub.status.busy": "2024-09-05T19:37:50.442414Z", - "iopub.status.idle": "2024-09-05T19:37:50.615431Z", - "shell.execute_reply": "2024-09-05T19:37:50.614827Z" + "iopub.execute_input": "2024-09-06T19:37:45.101100Z", + "iopub.status.busy": "2024-09-06T19:37:45.100762Z", + "iopub.status.idle": "2024-09-06T19:37:45.277489Z", + "shell.execute_reply": "2024-09-06T19:37:45.276850Z" } }, "outputs": [ @@ -1460,10 +1460,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.617758Z", - "iopub.status.busy": "2024-09-05T19:37:50.617562Z", - "iopub.status.idle": "2024-09-05T19:37:50.628108Z", - "shell.execute_reply": "2024-09-05T19:37:50.627590Z" + "iopub.execute_input": "2024-09-06T19:37:45.279928Z", + "iopub.status.busy": "2024-09-06T19:37:45.279722Z", + "iopub.status.idle": "2024-09-06T19:37:45.290798Z", + "shell.execute_reply": "2024-09-06T19:37:45.290229Z" } }, "outputs": [ @@ -1729,10 +1729,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.630389Z", - "iopub.status.busy": "2024-09-05T19:37:50.630031Z", - "iopub.status.idle": "2024-09-05T19:37:50.640010Z", - "shell.execute_reply": "2024-09-05T19:37:50.639473Z" + "iopub.execute_input": "2024-09-06T19:37:45.292867Z", + "iopub.status.busy": "2024-09-06T19:37:45.292672Z", + "iopub.status.idle": "2024-09-06T19:37:45.302178Z", + "shell.execute_reply": "2024-09-06T19:37:45.301745Z" } }, "outputs": [ @@ -1919,10 +1919,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.642181Z", - "iopub.status.busy": "2024-09-05T19:37:50.641826Z", - "iopub.status.idle": "2024-09-05T19:37:50.671287Z", - "shell.execute_reply": "2024-09-05T19:37:50.670793Z" + "iopub.execute_input": "2024-09-06T19:37:45.304034Z", + "iopub.status.busy": "2024-09-06T19:37:45.303861Z", + "iopub.status.idle": "2024-09-06T19:37:45.329485Z", + "shell.execute_reply": "2024-09-06T19:37:45.329066Z" } }, "outputs": [], @@ -1956,10 +1956,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.673864Z", - "iopub.status.busy": "2024-09-05T19:37:50.673387Z", - "iopub.status.idle": "2024-09-05T19:37:50.676503Z", - "shell.execute_reply": "2024-09-05T19:37:50.675922Z" + "iopub.execute_input": "2024-09-06T19:37:45.331450Z", + "iopub.status.busy": "2024-09-06T19:37:45.331118Z", + "iopub.status.idle": "2024-09-06T19:37:45.333941Z", + "shell.execute_reply": "2024-09-06T19:37:45.333348Z" } }, "outputs": [], @@ -1981,10 +1981,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.678746Z", - "iopub.status.busy": "2024-09-05T19:37:50.678397Z", - "iopub.status.idle": "2024-09-05T19:37:50.698912Z", - "shell.execute_reply": "2024-09-05T19:37:50.698309Z" + "iopub.execute_input": "2024-09-06T19:37:45.336081Z", + "iopub.status.busy": "2024-09-06T19:37:45.335742Z", + "iopub.status.idle": "2024-09-06T19:37:45.354797Z", + "shell.execute_reply": "2024-09-06T19:37:45.354315Z" } }, "outputs": [ @@ -2142,10 +2142,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.701349Z", - "iopub.status.busy": "2024-09-05T19:37:50.700967Z", - "iopub.status.idle": "2024-09-05T19:37:50.705309Z", - "shell.execute_reply": "2024-09-05T19:37:50.704840Z" + "iopub.execute_input": "2024-09-06T19:37:45.356897Z", + "iopub.status.busy": "2024-09-06T19:37:45.356543Z", + "iopub.status.idle": "2024-09-06T19:37:45.360935Z", + "shell.execute_reply": "2024-09-06T19:37:45.360328Z" } }, "outputs": [], @@ -2178,10 +2178,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.707600Z", - "iopub.status.busy": "2024-09-05T19:37:50.707256Z", - "iopub.status.idle": "2024-09-05T19:37:50.737701Z", - "shell.execute_reply": "2024-09-05T19:37:50.737181Z" + "iopub.execute_input": "2024-09-06T19:37:45.363152Z", + "iopub.status.busy": "2024-09-06T19:37:45.362835Z", + "iopub.status.idle": "2024-09-06T19:37:45.390311Z", + "shell.execute_reply": "2024-09-06T19:37:45.389739Z" } }, "outputs": [ @@ -2327,10 +2327,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:50.740155Z", - "iopub.status.busy": "2024-09-05T19:37:50.739645Z", - "iopub.status.idle": "2024-09-05T19:37:51.096104Z", - "shell.execute_reply": "2024-09-05T19:37:51.095515Z" + "iopub.execute_input": "2024-09-06T19:37:45.392321Z", + "iopub.status.busy": "2024-09-06T19:37:45.392005Z", + "iopub.status.idle": "2024-09-06T19:37:45.759141Z", + "shell.execute_reply": "2024-09-06T19:37:45.758581Z" } }, "outputs": [ @@ -2397,10 +2397,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.098341Z", - "iopub.status.busy": "2024-09-05T19:37:51.098156Z", - "iopub.status.idle": "2024-09-05T19:37:51.101609Z", - "shell.execute_reply": "2024-09-05T19:37:51.101125Z" + "iopub.execute_input": "2024-09-06T19:37:45.761452Z", + "iopub.status.busy": "2024-09-06T19:37:45.761084Z", + "iopub.status.idle": "2024-09-06T19:37:45.764398Z", + "shell.execute_reply": "2024-09-06T19:37:45.763923Z" } }, "outputs": [ @@ -2451,10 +2451,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.103763Z", - "iopub.status.busy": "2024-09-05T19:37:51.103431Z", - "iopub.status.idle": "2024-09-05T19:37:51.117191Z", - "shell.execute_reply": "2024-09-05T19:37:51.116674Z" + "iopub.execute_input": "2024-09-06T19:37:45.766685Z", + "iopub.status.busy": "2024-09-06T19:37:45.766351Z", + "iopub.status.idle": "2024-09-06T19:37:45.779490Z", + "shell.execute_reply": "2024-09-06T19:37:45.779045Z" } }, "outputs": [ @@ -2733,10 +2733,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.119477Z", - "iopub.status.busy": "2024-09-05T19:37:51.119122Z", - "iopub.status.idle": "2024-09-05T19:37:51.136499Z", - "shell.execute_reply": "2024-09-05T19:37:51.135847Z" + "iopub.execute_input": "2024-09-06T19:37:45.781428Z", + "iopub.status.busy": "2024-09-06T19:37:45.781250Z", + "iopub.status.idle": "2024-09-06T19:37:45.796041Z", + "shell.execute_reply": "2024-09-06T19:37:45.795601Z" } }, "outputs": [ @@ -3003,10 +3003,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.138657Z", - "iopub.status.busy": "2024-09-05T19:37:51.138457Z", - "iopub.status.idle": "2024-09-05T19:37:51.148925Z", - "shell.execute_reply": "2024-09-05T19:37:51.148440Z" + "iopub.execute_input": "2024-09-06T19:37:45.798043Z", + "iopub.status.busy": "2024-09-06T19:37:45.797870Z", + "iopub.status.idle": "2024-09-06T19:37:45.807740Z", + "shell.execute_reply": "2024-09-06T19:37:45.807165Z" } }, "outputs": [], @@ -3031,10 +3031,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.151091Z", - "iopub.status.busy": "2024-09-05T19:37:51.150913Z", - "iopub.status.idle": "2024-09-05T19:37:51.161080Z", - "shell.execute_reply": "2024-09-05T19:37:51.160404Z" + "iopub.execute_input": "2024-09-06T19:37:45.809952Z", + "iopub.status.busy": "2024-09-06T19:37:45.809629Z", + "iopub.status.idle": "2024-09-06T19:37:45.818832Z", + "shell.execute_reply": "2024-09-06T19:37:45.818256Z" } }, "outputs": [ @@ -3206,10 +3206,10 @@ "execution_count": 27, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.163142Z", - "iopub.status.busy": "2024-09-05T19:37:51.162957Z", - "iopub.status.idle": "2024-09-05T19:37:51.166908Z", - "shell.execute_reply": "2024-09-05T19:37:51.166441Z" + "iopub.execute_input": "2024-09-06T19:37:45.821154Z", + "iopub.status.busy": "2024-09-06T19:37:45.820691Z", + "iopub.status.idle": "2024-09-06T19:37:45.824900Z", + "shell.execute_reply": "2024-09-06T19:37:45.824317Z" } }, "outputs": [], @@ -3241,10 +3241,10 @@ "execution_count": 28, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.168894Z", - "iopub.status.busy": "2024-09-05T19:37:51.168718Z", - "iopub.status.idle": "2024-09-05T19:37:51.221568Z", - "shell.execute_reply": "2024-09-05T19:37:51.220997Z" + "iopub.execute_input": "2024-09-06T19:37:45.826963Z", + "iopub.status.busy": "2024-09-06T19:37:45.826647Z", + "iopub.status.idle": "2024-09-06T19:37:45.876648Z", + "shell.execute_reply": "2024-09-06T19:37:45.876084Z" } }, "outputs": [ @@ -3252,230 +3252,230 @@ "data": { "text/html": [ "\n", - "\n", + "
    \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", " \n", " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", - " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", " \n", " \n", "
     AgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_scoreAgeGenderLocationAnnual_SpendingNumber_of_TransactionsLast_Purchase_Date|is_null_issuenull_score
    8nannannannannanNaTTrue0.000000
    1nanFemaleRural6421.1600005.000000NaTFalse0.666667
    9nanMaleRural4655.8200001.000000NaTFalse0.666667
    14nanMaleRural6790.4600003.000000NaTFalse0.666667
    13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
    15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
    056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
    246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
    332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
    460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
    525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
    638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
    756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
    1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
    1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
    1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.0000008nannannannannanNaTTrue0.000000
    1nanFemaleRural6421.1600005.000000NaTFalse0.666667
    9nanMaleRural4655.8200001.000000NaTFalse0.666667
    14nanMaleRural6790.4600003.000000NaTFalse0.666667
    13nanMaleUrban9167.4700004.0000002024-01-02 00:00:00False0.833333
    15nanOtherRural5327.9600008.0000002024-01-03 00:00:00False0.833333
    056.000000OtherRural4099.6200003.0000002024-01-03 00:00:00False1.000000
    246.000000MaleSuburban5436.5500003.0000002024-02-26 00:00:00False1.000000
    332.000000FemaleRural4046.6600003.0000002024-03-23 00:00:00False1.000000
    460.000000FemaleSuburban3467.6700006.0000002024-03-01 00:00:00False1.000000
    525.000000FemaleSuburban4757.3700004.0000002024-01-03 00:00:00False1.000000
    638.000000FemaleRural4199.5300006.0000002024-01-03 00:00:00False1.000000
    756.000000MaleSuburban4991.7100006.0000002024-04-03 00:00:00False1.000000
    1040.000000FemaleRural5584.0200007.0000002024-03-29 00:00:00False1.000000
    1128.000000FemaleUrban3102.3200002.0000002024-04-07 00:00:00False1.000000
    1228.000000MaleRural6637.99000011.0000002024-04-08 00:00:00False1.000000
    \n" ], "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -3551,10 +3551,10 @@ "execution_count": 29, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.224233Z", - "iopub.status.busy": "2024-09-05T19:37:51.223659Z", - "iopub.status.idle": "2024-09-05T19:37:51.229976Z", - "shell.execute_reply": "2024-09-05T19:37:51.229459Z" + "iopub.execute_input": "2024-09-06T19:37:45.878907Z", + "iopub.status.busy": "2024-09-06T19:37:45.878480Z", + "iopub.status.idle": "2024-09-06T19:37:45.884204Z", + "shell.execute_reply": "2024-09-06T19:37:45.883634Z" } }, "outputs": [], @@ -3593,10 +3593,10 @@ "execution_count": 30, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.232017Z", - "iopub.status.busy": "2024-09-05T19:37:51.231819Z", - "iopub.status.idle": "2024-09-05T19:37:51.243359Z", - "shell.execute_reply": "2024-09-05T19:37:51.242861Z" + "iopub.execute_input": "2024-09-06T19:37:45.886291Z", + "iopub.status.busy": "2024-09-06T19:37:45.885973Z", + "iopub.status.idle": "2024-09-06T19:37:45.897008Z", + "shell.execute_reply": "2024-09-06T19:37:45.896438Z" } }, "outputs": [ @@ -3632,10 +3632,10 @@ "execution_count": 31, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.245457Z", - "iopub.status.busy": "2024-09-05T19:37:51.245279Z", - "iopub.status.idle": "2024-09-05T19:37:51.475856Z", - "shell.execute_reply": "2024-09-05T19:37:51.475287Z" + "iopub.execute_input": "2024-09-06T19:37:45.899243Z", + "iopub.status.busy": "2024-09-06T19:37:45.898904Z", + "iopub.status.idle": "2024-09-06T19:37:46.075809Z", + "shell.execute_reply": "2024-09-06T19:37:46.075226Z" } }, "outputs": [ @@ -3687,10 +3687,10 @@ "execution_count": 32, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.478345Z", - "iopub.status.busy": "2024-09-05T19:37:51.477903Z", - "iopub.status.idle": "2024-09-05T19:37:51.486021Z", - "shell.execute_reply": "2024-09-05T19:37:51.485523Z" + "iopub.execute_input": "2024-09-06T19:37:46.078430Z", + "iopub.status.busy": "2024-09-06T19:37:46.077957Z", + "iopub.status.idle": "2024-09-06T19:37:46.085812Z", + "shell.execute_reply": "2024-09-06T19:37:46.085244Z" }, "nbsphinx": "hidden" }, @@ -3756,10 +3756,10 @@ "execution_count": 33, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.488092Z", - "iopub.status.busy": "2024-09-05T19:37:51.487894Z", - "iopub.status.idle": "2024-09-05T19:37:51.860873Z", - "shell.execute_reply": "2024-09-05T19:37:51.860210Z" + "iopub.execute_input": "2024-09-06T19:37:46.087762Z", + "iopub.status.busy": "2024-09-06T19:37:46.087589Z", + "iopub.status.idle": "2024-09-06T19:37:46.522443Z", + "shell.execute_reply": "2024-09-06T19:37:46.521749Z" } }, "outputs": [ @@ -3767,25 +3767,25 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-09-05 19:37:51-- https://s.cleanlab.ai/CIFAR-10-subset.zip\r\n", - "Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.109.153, 185.199.108.153, 185.199.111.153, ...\r\n", - "Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.109.153|:443... connected.\r\n", - "HTTP request sent, awaiting response... 200 OK\r\n", - "Length: 986707 (964K) [application/zip]\r\n", - "Saving to: ‘CIFAR-10-subset.zip’\r\n", - "\r\n", - "\r", - "CIFAR-10-subset.zip 0%[ ] 0 --.-KB/s " + "--2024-09-06 19:37:46-- https://s.cleanlab.ai/CIFAR-10-subset.zip\r\n", + "Resolving s.cleanlab.ai (s.cleanlab.ai)... 185.199.111.153, 185.199.110.153, 185.199.109.153, ...\r\n", + "Connecting to s.cleanlab.ai (s.cleanlab.ai)|185.199.111.153|:443... connected.\r\n", + "HTTP request sent, awaiting response... " ] }, { "name": "stdout", "output_type": "stream", "text": [ + "200 OK\r\n", + "Length: 986707 (964K) [application/zip]\r\n", + "Saving to: ‘CIFAR-10-subset.zip’\r\n", + "\r\n", "\r", - "CIFAR-10-subset.zip 100%[===================>] 963.58K --.-KB/s in 0.03s \r\n", + "CIFAR-10-subset.zip 0%[ ] 0 --.-KB/s \r", + "CIFAR-10-subset.zip 100%[===================>] 963.58K --.-KB/s in 0.005s \r\n", "\r\n", - "2024-09-05 19:37:51 (32.9 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]\r\n", + "2024-09-06 19:37:46 (176 MB/s) - ‘CIFAR-10-subset.zip’ saved [986707/986707]\r\n", "\r\n" ] } @@ -3801,10 +3801,10 @@ "execution_count": 34, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:51.863648Z", - "iopub.status.busy": "2024-09-05T19:37:51.863430Z", - "iopub.status.idle": "2024-09-05T19:37:53.857499Z", - "shell.execute_reply": "2024-09-05T19:37:53.856936Z" + "iopub.execute_input": "2024-09-06T19:37:46.525178Z", + "iopub.status.busy": "2024-09-06T19:37:46.524748Z", + "iopub.status.idle": "2024-09-06T19:37:48.452276Z", + "shell.execute_reply": "2024-09-06T19:37:48.451758Z" } }, "outputs": [], @@ -3850,10 +3850,10 @@ "execution_count": 35, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:53.860032Z", - "iopub.status.busy": "2024-09-05T19:37:53.859675Z", - "iopub.status.idle": "2024-09-05T19:37:54.515213Z", - "shell.execute_reply": "2024-09-05T19:37:54.514565Z" + "iopub.execute_input": "2024-09-06T19:37:48.454913Z", + "iopub.status.busy": "2024-09-06T19:37:48.454468Z", + "iopub.status.idle": "2024-09-06T19:37:49.092778Z", + "shell.execute_reply": "2024-09-06T19:37:49.092169Z" } }, "outputs": [ @@ -3868,7 +3868,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "6a8633562ced4f21b9e1b849b611603d", + "model_id": "a5793cf283c046f188f735beef4577a5", "version_major": 2, "version_minor": 0 }, @@ -4008,10 +4008,10 @@ "execution_count": 36, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:54.518192Z", - "iopub.status.busy": "2024-09-05T19:37:54.517837Z", - "iopub.status.idle": "2024-09-05T19:37:54.531474Z", - "shell.execute_reply": "2024-09-05T19:37:54.530950Z" + "iopub.execute_input": "2024-09-06T19:37:49.095580Z", + "iopub.status.busy": "2024-09-06T19:37:49.095115Z", + "iopub.status.idle": "2024-09-06T19:37:49.108940Z", + "shell.execute_reply": "2024-09-06T19:37:49.108334Z" } }, "outputs": [ @@ -4130,35 +4130,35 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 0\n", - " 0.237196\n", " True\n", + " 0.237196\n", " \n", " \n", " 1\n", - " 0.197229\n", " True\n", + " 0.197229\n", " \n", " \n", " 2\n", - " 0.254188\n", " True\n", + " 0.254188\n", " \n", " \n", " 3\n", - " 0.229170\n", " True\n", + " 0.229170\n", " \n", " \n", " 4\n", - " 0.208907\n", " True\n", + " 0.208907\n", " \n", " \n", " ...\n", @@ -4167,28 +4167,28 @@ " \n", " \n", " 195\n", - " 0.793840\n", " False\n", + " 0.793840\n", " \n", " \n", " 196\n", - " 1.000000\n", " False\n", + " 1.000000\n", " \n", " \n", " 197\n", - " 0.971560\n", " False\n", + " 0.971560\n", " \n", " \n", " 198\n", - " 0.862236\n", " False\n", + " 0.862236\n", " \n", " \n", " 199\n", - " 0.973533\n", " False\n", + " 0.973533\n", " \n", " \n", "\n", @@ -4196,18 +4196,18 @@ "

    " ], "text/plain": [ - " dark_score is_dark_issue\n", - "0 0.237196 True\n", - "1 0.197229 True\n", - "2 0.254188 True\n", - "3 0.229170 True\n", - "4 0.208907 True\n", - ".. ... ...\n", - "195 0.793840 False\n", - "196 1.000000 False\n", - "197 0.971560 False\n", - "198 0.862236 False\n", - "199 0.973533 False\n", + " is_dark_issue dark_score\n", + "0 True 0.237196\n", + "1 True 0.197229\n", + "2 True 0.254188\n", + "3 True 0.229170\n", + "4 True 0.208907\n", + ".. ... ...\n", + "195 False 0.793840\n", + "196 False 1.000000\n", + "197 False 0.971560\n", + "198 False 0.862236\n", + "199 False 0.973533\n", "\n", "[200 rows x 2 columns]" ] @@ -4257,10 +4257,10 @@ "execution_count": 37, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:54.534111Z", - "iopub.status.busy": "2024-09-05T19:37:54.533778Z", - "iopub.status.idle": "2024-09-05T19:37:54.685884Z", - "shell.execute_reply": "2024-09-05T19:37:54.685435Z" + "iopub.execute_input": "2024-09-06T19:37:49.112413Z", + "iopub.status.busy": "2024-09-06T19:37:49.112212Z", + "iopub.status.idle": "2024-09-06T19:37:49.262201Z", + "shell.execute_reply": "2024-09-06T19:37:49.261645Z" } }, "outputs": [ @@ -4325,10 +4325,10 @@ "execution_count": 38, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:54.688065Z", - "iopub.status.busy": "2024-09-05T19:37:54.687765Z", - "iopub.status.idle": "2024-09-05T19:37:55.189906Z", - "shell.execute_reply": "2024-09-05T19:37:55.189260Z" + "iopub.execute_input": "2024-09-06T19:37:49.264493Z", + "iopub.status.busy": "2024-09-06T19:37:49.264138Z", + "iopub.status.idle": "2024-09-06T19:37:49.776468Z", + "shell.execute_reply": "2024-09-06T19:37:49.775810Z" }, "nbsphinx": "hidden" }, @@ -4344,7 +4344,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "0491ab817f3e4abfae647f24171e651f", + "model_id": "e53b81d02870488ca1d70faf1534371f", "version_major": 2, "version_minor": 0 }, @@ -4473,35 +4473,35 @@ " \n", " \n", " \n", - " dark_score\n", " is_dark_issue\n", + " dark_score\n", " \n", " \n", " \n", " \n", " 0\n", - " 0.797509\n", " False\n", + " 0.797509\n", " \n", " \n", " 1\n", - " 0.663760\n", " False\n", + " 0.663760\n", " \n", " \n", " 2\n", - " 0.849826\n", " False\n", + " 0.849826\n", " \n", " \n", " 3\n", - " 0.773951\n", " False\n", + " 0.773951\n", " \n", " \n", " 4\n", - " 0.699518\n", " False\n", + " 0.699518\n", " \n", " \n", " ...\n", @@ -4510,28 +4510,28 @@ " \n", " \n", " 195\n", - " 0.793840\n", " False\n", + " 0.793840\n", " \n", " \n", " 196\n", - " 1.000000\n", " False\n", + " 1.000000\n", " \n", " \n", " 197\n", - " 0.971560\n", " False\n", + " 0.971560\n", " \n", " \n", " 198\n", - " 0.862236\n", " False\n", + " 0.862236\n", " \n", " \n", " 199\n", - " 0.973533\n", " False\n", + " 0.973533\n", " \n", " \n", "\n", @@ -4539,18 +4539,18 @@ "
    " ], "text/plain": [ - " dark_score is_dark_issue\n", - "0 0.797509 False\n", - "1 0.663760 False\n", - "2 0.849826 False\n", - "3 0.773951 False\n", - "4 0.699518 False\n", - ".. ... ...\n", - "195 0.793840 False\n", - "196 1.000000 False\n", - "197 0.971560 False\n", - "198 0.862236 False\n", - "199 0.973533 False\n", + " is_dark_issue dark_score\n", + "0 False 0.797509\n", + "1 False 0.663760\n", + "2 False 0.849826\n", + "3 False 0.773951\n", + "4 False 0.699518\n", + ".. ... ...\n", + "195 False 0.793840\n", + "196 False 1.000000\n", + "197 False 0.971560\n", + "198 False 0.862236\n", + "199 False 0.973533\n", "\n", "[200 rows x 2 columns]" ] @@ -4598,10 +4598,10 @@ "execution_count": 39, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:37:55.192457Z", - "iopub.status.busy": "2024-09-05T19:37:55.192089Z", - "iopub.status.idle": "2024-09-05T19:37:55.344435Z", - "shell.execute_reply": "2024-09-05T19:37:55.343755Z" + "iopub.execute_input": "2024-09-06T19:37:49.778901Z", + "iopub.status.busy": "2024-09-06T19:37:49.778528Z", + "iopub.status.idle": "2024-09-06T19:37:49.924980Z", + "shell.execute_reply": "2024-09-06T19:37:49.924477Z" }, "nbsphinx": "hidden" }, @@ -4653,31 +4653,83 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "0491ab817f3e4abfae647f24171e651f": { + "021a50164b8c491ebb069bd57b11ce1a": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "2cb88e5e7d0f4849b336950480e87a06": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_7e84cf312cfa4d80a5107dcdb0a45949", - "IPY_MODEL_7557f4205917445ca0c596993a114685", - "IPY_MODEL_dc9edc5341cb452cb27aada834ac562d" - ], - "layout": "IPY_MODEL_a1d59c28e7064efc92b1e3caf26f9346", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_5349f02a0bb24786bba46192aa1d90ff", + "placeholder": "​", + "style": "IPY_MODEL_b93c4b8b97f34f0b93a2d334e5065e1b", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": "100%" } }, - "37eeb5a0817c455a8d0efe07a3d6bd44": { + "313b234230ce4ce4850b3fa6a5e1b1ee": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4730,7 +4782,7 @@ "width": null } }, - "37f6d18ef4a24f62a2d67a08d8dae98c": { + "41bdd318b6d1453a8daca74a0776e419": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4783,39 +4835,7 @@ "width": null } }, - "3f81fed11b61470bac6f5d0b3b537a4f": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "4bbbb6bbcc9648459b5d261cb8ab6826": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "550c28ddb9cf43c3b62b1a0b54f7bd12": { + "5349f02a0bb24786bba46192aa1d90ff": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -4868,49 +4888,56 @@ "width": null } }, - "62793e1d0aa84395bb5ab3f9ff86c9b5": { + "5664879b48124f5cac1e0a8c43742995": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_da820a1ccd2b42d4a8c12ea0328d1169", + "max": 200.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_da8ad4a548a8409389fab7ddc0e601bc", + "tabbable": null, + "tooltip": null, + "value": 200.0 } }, - "6a8633562ced4f21b9e1b849b611603d": { + "6529bc3e5e35424f967dab0385030a5c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_db046a62f4e34aa594499d33fa68145f", - "IPY_MODEL_a6c8cc603a414e80a6ba376c29f15b21", - "IPY_MODEL_df91c80300534ab59fe080ab28475f7a" - ], - "layout": "IPY_MODEL_37f6d18ef4a24f62a2d67a08d8dae98c", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_41bdd318b6d1453a8daca74a0776e419", + "placeholder": "​", + "style": "IPY_MODEL_dfac24cbd04d4a6a9c6a2f3d7e34c87e", "tabbable": null, - "tooltip": null + "tooltip": null, + "value": " 200/200 [00:00<00:00, 682.83it/s]" } }, - "7557f4205917445ca0c596993a114685": { + "733b0d114c6e48e6af9ced8acfb5bf3a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -4926,17 +4953,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_daa6b8f2481040acb873f24cfbfedc9e", + "layout": "IPY_MODEL_953f4c82aabd472c9e8dfebdf70939d8", "max": 200.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_3f81fed11b61470bac6f5d0b3b537a4f", + "style": "IPY_MODEL_86445ca79c764836a406520c67b4b945", "tabbable": null, "tooltip": null, "value": 200.0 } }, - "7e84cf312cfa4d80a5107dcdb0a45949": { + "7b9c39c715b849dbb886ceaeb96e5c35": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -4951,33 +4978,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_550c28ddb9cf43c3b62b1a0b54f7bd12", + "layout": "IPY_MODEL_7fb3eb018b9d446294207573ca64cda2", "placeholder": "​", - "style": "IPY_MODEL_81f7fdaaa60c4cc5b1e29545f2666e55", + "style": "IPY_MODEL_ec3f09ac595d4dadbd0cf34793d57087", "tabbable": null, "tooltip": null, "value": "100%" } }, - "81f7fdaaa60c4cc5b1e29545f2666e55": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "a1d59c28e7064efc92b1e3caf26f9346": { + "7fb3eb018b9d446294207573ca64cda2": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5030,7 +5039,23 @@ "width": null } }, - "a4073ffc99c94224857f26d6f4931b59": { + "86445ca79c764836a406520c67b4b945": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "953f4c82aabd472c9e8dfebdf70939d8": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5083,33 +5108,30 @@ "width": null } }, - "a6c8cc603a414e80a6ba376c29f15b21": { + "9ffc7a8014b64edfad1dd643172601d1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_a4073ffc99c94224857f26d6f4931b59", - "max": 200.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_4bbbb6bbcc9648459b5d261cb8ab6826", + "layout": "IPY_MODEL_021a50164b8c491ebb069bd57b11ce1a", + "placeholder": "​", + "style": "IPY_MODEL_da74a2af2dfa4378a23a6009ae2f264c", "tabbable": null, "tooltip": null, - "value": 200.0 + "value": " 200/200 [00:00<00:00, 785.38it/s]" } }, - "ad306c43da45461c99570f45d29010bd": { + "a185cb088b4a4b50933699f586275482": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5162,7 +5184,31 @@ "width": null } }, - "ae6c7383e12f421aaeac59c5f8586ff1": { + "a5793cf283c046f188f735beef4577a5": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_7b9c39c715b849dbb886ceaeb96e5c35", + "IPY_MODEL_5664879b48124f5cac1e0a8c43742995", + "IPY_MODEL_9ffc7a8014b64edfad1dd643172601d1" + ], + "layout": "IPY_MODEL_313b234230ce4ce4850b3fa6a5e1b1ee", + "tabbable": null, + "tooltip": null + } + }, + "b93c4b8b97f34f0b93a2d334e5065e1b": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -5180,7 +5226,7 @@ "text_color": null } }, - "b54c1a0ec3ea4129adde7e57857e1a0e": { + "da74a2af2dfa4378a23a6009ae2f264c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -5198,7 +5244,7 @@ "text_color": null } }, - "c362069cd48048d7ac53b007e87189cb": { + "da820a1ccd2b42d4a8c12ea0328d1169": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -5251,126 +5297,80 @@ "width": null } }, - "daa6b8f2481040acb873f24cfbfedc9e": { - "model_module": "@jupyter-widgets/base", + "da8ad4a548a8409389fab7ddc0e601bc": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "db046a62f4e34aa594499d33fa68145f": { + "dfac24cbd04d4a6a9c6a2f3d7e34c87e": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_c362069cd48048d7ac53b007e87189cb", - "placeholder": "​", - "style": "IPY_MODEL_ae6c7383e12f421aaeac59c5f8586ff1", - "tabbable": null, - "tooltip": null, - "value": "100%" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "dc9edc5341cb452cb27aada834ac562d": { + "e53b81d02870488ca1d70faf1534371f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_ad306c43da45461c99570f45d29010bd", - "placeholder": "​", - "style": "IPY_MODEL_62793e1d0aa84395bb5ab3f9ff86c9b5", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_2cb88e5e7d0f4849b336950480e87a06", + "IPY_MODEL_733b0d114c6e48e6af9ced8acfb5bf3a", + "IPY_MODEL_6529bc3e5e35424f967dab0385030a5c" + ], + "layout": "IPY_MODEL_a185cb088b4a4b50933699f586275482", "tabbable": null, - "tooltip": null, - "value": " 200/200 [00:00<00:00, 716.02it/s]" + "tooltip": null } }, - "df91c80300534ab59fe080ab28475f7a": { + "ec3f09ac595d4dadbd0cf34793d57087": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_37eeb5a0817c455a8d0efe07a3d6bd44", - "placeholder": "​", - "style": "IPY_MODEL_b54c1a0ec3ea4129adde7e57857e1a0e", - "tabbable": null, - "tooltip": null, - "value": " 200/200 [00:00<00:00, 771.41it/s]" + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } } }, diff --git a/master/tutorials/dataset_health.ipynb b/master/tutorials/dataset_health.ipynb index a14eec2f4..e932968f7 100644 --- a/master/tutorials/dataset_health.ipynb +++ b/master/tutorials/dataset_health.ipynb @@ -70,10 +70,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:00.542736Z", - "iopub.status.busy": "2024-09-05T19:38:00.542299Z", - "iopub.status.idle": "2024-09-05T19:38:01.779270Z", - "shell.execute_reply": "2024-09-05T19:38:01.778627Z" + "iopub.execute_input": "2024-09-06T19:37:53.970574Z", + "iopub.status.busy": "2024-09-06T19:37:53.970388Z", + "iopub.status.idle": "2024-09-06T19:37:55.134808Z", + "shell.execute_reply": "2024-09-06T19:37:55.134157Z" }, "nbsphinx": "hidden" }, @@ -85,7 +85,7 @@ "dependencies = [\"cleanlab\", \"requests\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -110,10 +110,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:01.782074Z", - "iopub.status.busy": "2024-09-05T19:38:01.781768Z", - "iopub.status.idle": "2024-09-05T19:38:01.784644Z", - "shell.execute_reply": "2024-09-05T19:38:01.784156Z" + "iopub.execute_input": "2024-09-06T19:37:55.137505Z", + "iopub.status.busy": "2024-09-06T19:37:55.137230Z", + "iopub.status.idle": "2024-09-06T19:37:55.140659Z", + "shell.execute_reply": "2024-09-06T19:37:55.140221Z" }, "id": "_UvI80l42iyi" }, @@ -203,10 +203,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:01.786827Z", - "iopub.status.busy": "2024-09-05T19:38:01.786518Z", - "iopub.status.idle": "2024-09-05T19:38:01.798674Z", - "shell.execute_reply": "2024-09-05T19:38:01.798101Z" + "iopub.execute_input": "2024-09-06T19:37:55.142857Z", + "iopub.status.busy": "2024-09-06T19:37:55.142554Z", + "iopub.status.idle": "2024-09-06T19:37:55.154394Z", + "shell.execute_reply": "2024-09-06T19:37:55.153913Z" }, "nbsphinx": "hidden" }, @@ -285,10 +285,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:01.800785Z", - "iopub.status.busy": "2024-09-05T19:38:01.800454Z", - "iopub.status.idle": "2024-09-05T19:38:06.755445Z", - "shell.execute_reply": "2024-09-05T19:38:06.754955Z" + "iopub.execute_input": "2024-09-06T19:37:55.156367Z", + "iopub.status.busy": "2024-09-06T19:37:55.156193Z", + "iopub.status.idle": "2024-09-06T19:38:03.213180Z", + "shell.execute_reply": "2024-09-06T19:38:03.212490Z" }, "id": "dhTHOg8Pyv5G" }, diff --git a/master/tutorials/faq.html b/master/tutorials/faq.html index 5033d68f9..5da9f6de6 100644 --- a/master/tutorials/faq.html +++ b/master/tutorials/faq.html @@ -835,13 +835,13 @@

    How can I find label issues in big datasets with limited memory?
    -
    +
    -
    +
    @@ -1706,7 +1706,7 @@

    Can’t find an answer to your question?new Github issue. Our developers may also provide personalized assistance in our Slack Community.

    Professional support and services are also available from our ML experts, learn more by emailing: team@cleanlab.ai

    diff --git a/master/tutorials/faq.ipynb b/master/tutorials/faq.ipynb index c5223bdbd..cec52a458 100644 --- a/master/tutorials/faq.ipynb +++ b/master/tutorials/faq.ipynb @@ -18,10 +18,10 @@ "id": "2a4efdde", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:09.258191Z", - "iopub.status.busy": "2024-09-05T19:38:09.258029Z", - "iopub.status.idle": "2024-09-05T19:38:10.419368Z", - "shell.execute_reply": "2024-09-05T19:38:10.418813Z" + "iopub.execute_input": "2024-09-06T19:38:05.442254Z", + "iopub.status.busy": "2024-09-06T19:38:05.441754Z", + "iopub.status.idle": "2024-09-06T19:38:06.608058Z", + "shell.execute_reply": "2024-09-06T19:38:06.607439Z" }, "nbsphinx": "hidden" }, @@ -137,10 +137,10 @@ "id": "239d5ee7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:10.422097Z", - "iopub.status.busy": "2024-09-05T19:38:10.421633Z", - "iopub.status.idle": "2024-09-05T19:38:10.425143Z", - "shell.execute_reply": "2024-09-05T19:38:10.424685Z" + "iopub.execute_input": "2024-09-06T19:38:06.610846Z", + "iopub.status.busy": "2024-09-06T19:38:06.610375Z", + "iopub.status.idle": "2024-09-06T19:38:06.613802Z", + "shell.execute_reply": "2024-09-06T19:38:06.613322Z" } }, "outputs": [], @@ -176,10 +176,10 @@ "id": "28b324aa", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:10.427337Z", - "iopub.status.busy": "2024-09-05T19:38:10.427003Z", - "iopub.status.idle": "2024-09-05T19:38:13.858204Z", - "shell.execute_reply": "2024-09-05T19:38:13.857536Z" + "iopub.execute_input": "2024-09-06T19:38:06.615798Z", + "iopub.status.busy": "2024-09-06T19:38:06.615518Z", + "iopub.status.idle": "2024-09-06T19:38:09.981363Z", + "shell.execute_reply": "2024-09-06T19:38:09.980664Z" } }, "outputs": [], @@ -202,10 +202,10 @@ "id": "28b324ab", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.861501Z", - "iopub.status.busy": "2024-09-05T19:38:13.860747Z", - "iopub.status.idle": "2024-09-05T19:38:13.908095Z", - "shell.execute_reply": "2024-09-05T19:38:13.907257Z" + "iopub.execute_input": "2024-09-06T19:38:09.984620Z", + "iopub.status.busy": "2024-09-06T19:38:09.983724Z", + "iopub.status.idle": "2024-09-06T19:38:10.027299Z", + "shell.execute_reply": "2024-09-06T19:38:10.026694Z" } }, "outputs": [], @@ -228,10 +228,10 @@ "id": "90c10e18", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.911086Z", - "iopub.status.busy": "2024-09-05T19:38:13.910659Z", - "iopub.status.idle": "2024-09-05T19:38:13.954360Z", - "shell.execute_reply": "2024-09-05T19:38:13.953711Z" + "iopub.execute_input": "2024-09-06T19:38:10.030074Z", + "iopub.status.busy": "2024-09-06T19:38:10.029673Z", + "iopub.status.idle": "2024-09-06T19:38:10.069413Z", + "shell.execute_reply": "2024-09-06T19:38:10.068633Z" } }, "outputs": [], @@ -253,10 +253,10 @@ "id": "88839519", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.957448Z", - "iopub.status.busy": "2024-09-05T19:38:13.956977Z", - "iopub.status.idle": "2024-09-05T19:38:13.960154Z", - "shell.execute_reply": "2024-09-05T19:38:13.959671Z" + "iopub.execute_input": "2024-09-06T19:38:10.072131Z", + "iopub.status.busy": "2024-09-06T19:38:10.071875Z", + "iopub.status.idle": "2024-09-06T19:38:10.075127Z", + "shell.execute_reply": "2024-09-06T19:38:10.074582Z" } }, "outputs": [], @@ -278,10 +278,10 @@ "id": "558490c2", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.962224Z", - "iopub.status.busy": "2024-09-05T19:38:13.961891Z", - "iopub.status.idle": "2024-09-05T19:38:13.964636Z", - "shell.execute_reply": "2024-09-05T19:38:13.964076Z" + "iopub.execute_input": "2024-09-06T19:38:10.077352Z", + "iopub.status.busy": "2024-09-06T19:38:10.077011Z", + "iopub.status.idle": "2024-09-06T19:38:10.079576Z", + "shell.execute_reply": "2024-09-06T19:38:10.079132Z" } }, "outputs": [], @@ -363,10 +363,10 @@ "id": "41714b51", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.966749Z", - "iopub.status.busy": "2024-09-05T19:38:13.966438Z", - "iopub.status.idle": "2024-09-05T19:38:13.992059Z", - "shell.execute_reply": "2024-09-05T19:38:13.991451Z" + "iopub.execute_input": "2024-09-06T19:38:10.081910Z", + "iopub.status.busy": "2024-09-06T19:38:10.081719Z", + "iopub.status.idle": "2024-09-06T19:38:10.109741Z", + "shell.execute_reply": "2024-09-06T19:38:10.109183Z" } }, "outputs": [ @@ -380,7 +380,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "5e9f1ab6ba2a4e2299cdd03dc9abc834", + "model_id": "10e11ec38b13425280381ff5281c4450", "version_major": 2, "version_minor": 0 }, @@ -394,7 +394,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "c8b20d5d9286458984753646a34d3bf1", + "model_id": "7e2d5adb59434e2081db18c696100263", "version_major": 2, "version_minor": 0 }, @@ -452,10 +452,10 @@ "id": "20476c70", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:13.998276Z", - "iopub.status.busy": "2024-09-05T19:38:13.997819Z", - "iopub.status.idle": "2024-09-05T19:38:14.004565Z", - "shell.execute_reply": "2024-09-05T19:38:14.004112Z" + "iopub.execute_input": "2024-09-06T19:38:10.115104Z", + "iopub.status.busy": "2024-09-06T19:38:10.114762Z", + "iopub.status.idle": "2024-09-06T19:38:10.121297Z", + "shell.execute_reply": "2024-09-06T19:38:10.120726Z" }, "nbsphinx": "hidden" }, @@ -486,10 +486,10 @@ "id": "6983cdad", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.006609Z", - "iopub.status.busy": "2024-09-05T19:38:14.006302Z", - "iopub.status.idle": "2024-09-05T19:38:14.009865Z", - "shell.execute_reply": "2024-09-05T19:38:14.009315Z" + "iopub.execute_input": "2024-09-06T19:38:10.123497Z", + "iopub.status.busy": "2024-09-06T19:38:10.123043Z", + "iopub.status.idle": "2024-09-06T19:38:10.126503Z", + "shell.execute_reply": "2024-09-06T19:38:10.126056Z" }, "nbsphinx": "hidden" }, @@ -512,10 +512,10 @@ "id": "9092b8a0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.011915Z", - "iopub.status.busy": "2024-09-05T19:38:14.011613Z", - "iopub.status.idle": "2024-09-05T19:38:14.017930Z", - "shell.execute_reply": "2024-09-05T19:38:14.017490Z" + "iopub.execute_input": "2024-09-06T19:38:10.128505Z", + "iopub.status.busy": "2024-09-06T19:38:10.128204Z", + "iopub.status.idle": "2024-09-06T19:38:10.134549Z", + "shell.execute_reply": "2024-09-06T19:38:10.134003Z" } }, "outputs": [], @@ -565,10 +565,10 @@ "id": "b0a01109", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.019956Z", - "iopub.status.busy": "2024-09-05T19:38:14.019601Z", - "iopub.status.idle": "2024-09-05T19:38:14.064732Z", - "shell.execute_reply": "2024-09-05T19:38:14.063970Z" + "iopub.execute_input": "2024-09-06T19:38:10.136656Z", + "iopub.status.busy": "2024-09-06T19:38:10.136338Z", + "iopub.status.idle": "2024-09-06T19:38:10.179181Z", + "shell.execute_reply": "2024-09-06T19:38:10.178556Z" } }, "outputs": [], @@ -585,10 +585,10 @@ "id": "8b1da032", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.067600Z", - "iopub.status.busy": "2024-09-05T19:38:14.067120Z", - "iopub.status.idle": "2024-09-05T19:38:14.111610Z", - "shell.execute_reply": "2024-09-05T19:38:14.110852Z" + "iopub.execute_input": "2024-09-06T19:38:10.181945Z", + "iopub.status.busy": "2024-09-06T19:38:10.181555Z", + "iopub.status.idle": "2024-09-06T19:38:10.218200Z", + "shell.execute_reply": "2024-09-06T19:38:10.217453Z" }, "nbsphinx": "hidden" }, @@ -667,10 +667,10 @@ "id": "4c9e9030", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.114596Z", - "iopub.status.busy": "2024-09-05T19:38:14.114229Z", - "iopub.status.idle": "2024-09-05T19:38:14.248717Z", - "shell.execute_reply": "2024-09-05T19:38:14.248086Z" + "iopub.execute_input": "2024-09-06T19:38:10.220958Z", + "iopub.status.busy": "2024-09-06T19:38:10.220569Z", + "iopub.status.idle": "2024-09-06T19:38:10.349381Z", + "shell.execute_reply": "2024-09-06T19:38:10.348725Z" } }, "outputs": [ @@ -737,10 +737,10 @@ "id": "8751619e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:14.251515Z", - "iopub.status.busy": "2024-09-05T19:38:14.250905Z", - "iopub.status.idle": "2024-09-05T19:38:17.282534Z", - "shell.execute_reply": "2024-09-05T19:38:17.281859Z" + "iopub.execute_input": "2024-09-06T19:38:10.352202Z", + "iopub.status.busy": "2024-09-06T19:38:10.351437Z", + "iopub.status.idle": "2024-09-06T19:38:13.390257Z", + "shell.execute_reply": "2024-09-06T19:38:13.389586Z" } }, "outputs": [ @@ -826,10 +826,10 @@ "id": "623df36d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.284960Z", - "iopub.status.busy": "2024-09-05T19:38:17.284770Z", - "iopub.status.idle": "2024-09-05T19:38:17.345859Z", - "shell.execute_reply": "2024-09-05T19:38:17.345257Z" + "iopub.execute_input": "2024-09-06T19:38:13.392707Z", + "iopub.status.busy": "2024-09-06T19:38:13.392511Z", + "iopub.status.idle": "2024-09-06T19:38:13.450827Z", + "shell.execute_reply": "2024-09-06T19:38:13.450261Z" } }, "outputs": [ @@ -1285,10 +1285,10 @@ "id": "af3052ac", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.348231Z", - "iopub.status.busy": "2024-09-05T19:38:17.347702Z", - "iopub.status.idle": "2024-09-05T19:38:17.389681Z", - "shell.execute_reply": "2024-09-05T19:38:17.389132Z" + "iopub.execute_input": "2024-09-06T19:38:13.453108Z", + "iopub.status.busy": "2024-09-06T19:38:13.452688Z", + "iopub.status.idle": "2024-09-06T19:38:13.493414Z", + "shell.execute_reply": "2024-09-06T19:38:13.492941Z" } }, "outputs": [ @@ -1319,7 +1319,7 @@ }, { "cell_type": "markdown", - "id": "5ac521f4", + "id": "368f0547", "metadata": {}, "source": [ "### How do I specify pre-computed data slices/clusters when detecting the Underperforming Group Issue?" @@ -1327,7 +1327,7 @@ }, { "cell_type": "markdown", - "id": "eebcc205", + "id": "dc65d1a9", "metadata": {}, "source": [ "The instructions for specifying pre-computed data slices/clusters when detecting underperforming groups in a dataset are now covered in detail in the Datalab workflows tutorial.\n", @@ -1338,7 +1338,7 @@ }, { "cell_type": "markdown", - "id": "7a6303e8", + "id": "e31bf904", "metadata": {}, "source": [ "### How to handle near-duplicate data identified by Datalab?\n", @@ -1349,13 +1349,13 @@ { "cell_type": "code", "execution_count": 18, - "id": "cc272ead", + "id": "0365a86d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.392137Z", - "iopub.status.busy": "2024-09-05T19:38:17.391761Z", - "iopub.status.idle": "2024-09-05T19:38:17.399373Z", - "shell.execute_reply": "2024-09-05T19:38:17.398899Z" + "iopub.execute_input": "2024-09-06T19:38:13.495546Z", + "iopub.status.busy": "2024-09-06T19:38:13.495269Z", + "iopub.status.idle": "2024-09-06T19:38:13.502952Z", + "shell.execute_reply": "2024-09-06T19:38:13.502358Z" } }, "outputs": [], @@ -1457,7 +1457,7 @@ }, { "cell_type": "markdown", - "id": "02a9d389", + "id": "1c944acb", "metadata": {}, "source": [ "The functions above collect sets of near-duplicate examples. Within each\n", @@ -1472,13 +1472,13 @@ { "cell_type": "code", "execution_count": 19, - "id": "c59e687d", + "id": "c713e4cb", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.401606Z", - "iopub.status.busy": "2024-09-05T19:38:17.401261Z", - "iopub.status.idle": "2024-09-05T19:38:17.420424Z", - "shell.execute_reply": "2024-09-05T19:38:17.419931Z" + "iopub.execute_input": "2024-09-06T19:38:13.504946Z", + "iopub.status.busy": "2024-09-06T19:38:13.504608Z", + "iopub.status.idle": "2024-09-06T19:38:13.523104Z", + "shell.execute_reply": "2024-09-06T19:38:13.522534Z" } }, "outputs": [ @@ -1521,13 +1521,13 @@ { "cell_type": "code", "execution_count": 20, - "id": "01304147", + "id": "59184bfc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:17.422733Z", - "iopub.status.busy": "2024-09-05T19:38:17.422383Z", - "iopub.status.idle": "2024-09-05T19:38:17.425820Z", - "shell.execute_reply": "2024-09-05T19:38:17.425263Z" + "iopub.execute_input": "2024-09-06T19:38:13.525068Z", + "iopub.status.busy": "2024-09-06T19:38:13.524743Z", + "iopub.status.idle": "2024-09-06T19:38:13.528122Z", + "shell.execute_reply": "2024-09-06T19:38:13.527552Z" } }, "outputs": [ @@ -1622,7 +1622,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "1d1157c21ea1455bb4eba32221cfd80e": { + "0a20db80d8ee4c558ba192d544a0f48a": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1675,7 +1675,7 @@ "width": null } }, - "2bb52b5e34e0423ea8ebfa5fa2197991": { + "0e1e83d9b67447b1a76b3a2c668a8439": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1728,7 +1728,49 @@ "width": null } }, - "2ca77e6e6a914a409e7751bbd43cd433": { + "0ea8c549fffe4418b122c5d1daacdcf9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "10e11ec38b13425280381ff5281c4450": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_98a30ff8d08f40f5a59fa3959a1bfd7a", + "IPY_MODEL_9e361a1c4f7d49d28575030ed31684b4", + "IPY_MODEL_5d93e4fbfc844d82994983ca2900ac04" + ], + "layout": "IPY_MODEL_4c9d550f7159424fb6452da47b5cb51f", + "tabbable": null, + "tooltip": null + } + }, + "1989c2b222ef4983ba1d80fd96d80f9d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1781,33 +1823,23 @@ "width": null } }, - "2e05d5f980a44775b5be3782d3eb29a8": { + "278fa17d981b49c5a5afac9215c11437": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_519341eb823746dc9a9b5c92d467d3d1", - "max": 50.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_ae0adc12747d4f129ee5677a88c40300", - "tabbable": null, - "tooltip": null, - "value": 50.0 + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "519341eb823746dc9a9b5c92d467d3d1": { + "4c9d550f7159424fb6452da47b5cb51f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1860,7 +1892,30 @@ "width": null } }, - "58f64c5fbd2b49039759f382c08a00f5": { + "5d93e4fbfc844d82994983ca2900ac04": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_0a20db80d8ee4c558ba192d544a0f48a", + "placeholder": "​", + "style": "IPY_MODEL_85eb048e0015452a98d2585ecd3acea6", + "tabbable": null, + "tooltip": null, + "value": " 10000/? [00:00<00:00, 908211.86it/s]" + } + }, + "62148dc5598f487787910111c96b2850": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1913,25 +1968,7 @@ "width": null } }, - "5a2ddf974a63406796b88696f6a9e322": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "5d6f15bd3523470e8f8a7049768802e2": { + "663eab6313474ab4b43a56ac15375332": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1946,15 +1983,68 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_fbc3a6811fa1407b9fb04a0f39c1e560", + "layout": "IPY_MODEL_0e1e83d9b67447b1a76b3a2c668a8439", "placeholder": "​", - "style": "IPY_MODEL_5a2ddf974a63406796b88696f6a9e322", + "style": "IPY_MODEL_c8b6ee68eda04b79b9d7e8ba44708601", "tabbable": null, "tooltip": null, - "value": " 10000/? [00:00<00:00, 1587308.51it/s]" + "value": "number of examples processed for checking labels: " } }, - "5e9f1ab6ba2a4e2299cdd03dc9abc834": { + "71bf8e249c8e494a8293a1368b4cde75": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "7e2d5adb59434e2081db18c696100263": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HBoxModel", @@ -1969,16 +2059,16 @@ "_view_name": "HBoxView", "box_style": "", "children": [ - "IPY_MODEL_89998dc91f404fc1ae7b7f0af753e147", - "IPY_MODEL_2e05d5f980a44775b5be3782d3eb29a8", - "IPY_MODEL_af016b9649554c3aa9157c6db78c9c93" + "IPY_MODEL_663eab6313474ab4b43a56ac15375332", + "IPY_MODEL_cb19cecdebc048139ef9e5b0697091e8", + "IPY_MODEL_b09565a1c786456187dacb880907b06f" ], - "layout": "IPY_MODEL_e518b7c1bace4a43bdf2824bb3ce3af4", + "layout": "IPY_MODEL_62148dc5598f487787910111c96b2850", "tabbable": null, "tooltip": null } }, - "7a097385a6104b0280db3ea1bd2b3b67": { + "85eb048e0015452a98d2585ecd3acea6": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1996,30 +2086,7 @@ "text_color": null } }, - "80f0f3a7d63640f88804ff3d3f2dc1e3": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_58f64c5fbd2b49039759f382c08a00f5", - "placeholder": "​", - "style": "IPY_MODEL_7a097385a6104b0280db3ea1bd2b3b67", - "tabbable": null, - "tooltip": null, - "value": "number of examples processed for checking labels: " - } - }, - "85c3014ae8d449b685c081ae4fa6d4f6": { + "8a29c209506d4b1f809b0eee618845ff": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2037,7 +2104,60 @@ "text_color": null } }, - "89998dc91f404fc1ae7b7f0af753e147": { + "8a7564586c364ea6ab0b8036f15d75de": { + "model_module": "@jupyter-widgets/base", + "model_module_version": "2.0.0", + "model_name": "LayoutModel", + "state": { + "_model_module": "@jupyter-widgets/base", + "_model_module_version": "2.0.0", + "_model_name": "LayoutModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null + } + }, + "98a30ff8d08f40f5a59fa3959a1bfd7a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2052,65 +2172,41 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_2bb52b5e34e0423ea8ebfa5fa2197991", + "layout": "IPY_MODEL_cbbdcb4211b04decb44b6be6dae0e74f", "placeholder": "​", - "style": "IPY_MODEL_85c3014ae8d449b685c081ae4fa6d4f6", + "style": "IPY_MODEL_0ea8c549fffe4418b122c5d1daacdcf9", "tabbable": null, "tooltip": null, "value": "number of examples processed for estimating thresholds: " } }, - "96c604f720804752bdd7e004c2d5b976": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "a626f902bf2b447aa9efceb999cecea2": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "ae0adc12747d4f129ee5677a88c40300": { + "9e361a1c4f7d49d28575030ed31684b4": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "FloatProgressModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "FloatProgressModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_8a7564586c364ea6ab0b8036f15d75de", + "max": 50.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_278fa17d981b49c5a5afac9215c11437", + "tabbable": null, + "tooltip": null, + "value": 50.0 } }, - "af016b9649554c3aa9157c6db78c9c93": { + "b09565a1c786456187dacb880907b06f": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -2125,39 +2221,33 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1d1157c21ea1455bb4eba32221cfd80e", + "layout": "IPY_MODEL_71bf8e249c8e494a8293a1368b4cde75", "placeholder": "​", - "style": "IPY_MODEL_96c604f720804752bdd7e004c2d5b976", + "style": "IPY_MODEL_8a29c209506d4b1f809b0eee618845ff", "tabbable": null, "tooltip": null, - "value": " 10000/? [00:00<00:00, 891911.71it/s]" + "value": " 10000/? [00:00<00:00, 1197722.38it/s]" } }, - "c8b20d5d9286458984753646a34d3bf1": { + "c8b6ee68eda04b79b9d7e8ba44708601": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_80f0f3a7d63640f88804ff3d3f2dc1e3", - "IPY_MODEL_d492675a8a4b4225ab936898d59675f6", - "IPY_MODEL_5d6f15bd3523470e8f8a7049768802e2" - ], - "layout": "IPY_MODEL_2ca77e6e6a914a409e7751bbd43cd433", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "d492675a8a4b4225ab936898d59675f6": { + "cb19cecdebc048139ef9e5b0697091e8": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "FloatProgressModel", @@ -2173,17 +2263,17 @@ "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_de835bb464834a46b37dd59d97b91150", + "layout": "IPY_MODEL_1989c2b222ef4983ba1d80fd96d80f9d", "max": 50.0, "min": 0.0, "orientation": "horizontal", - "style": "IPY_MODEL_a626f902bf2b447aa9efceb999cecea2", + "style": "IPY_MODEL_cd96842c5f86404599e6a57c4439dccf", "tabbable": null, "tooltip": null, "value": 50.0 } }, - "de835bb464834a46b37dd59d97b91150": { + "cbbdcb4211b04decb44b6be6dae0e74f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2236,110 +2326,20 @@ "width": null } }, - "e518b7c1bace4a43bdf2824bb3ce3af4": { - "model_module": "@jupyter-widgets/base", - "model_module_version": "2.0.0", - "model_name": "LayoutModel", - "state": { - "_model_module": "@jupyter-widgets/base", - "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "fbc3a6811fa1407b9fb04a0f39c1e560": { - "model_module": "@jupyter-widgets/base", + "cd96842c5f86404599e6a57c4439dccf": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "ProgressStyleModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } } }, diff --git a/master/tutorials/improving_ml_performance.ipynb b/master/tutorials/improving_ml_performance.ipynb index 355de44f6..0126898fa 100644 --- a/master/tutorials/improving_ml_performance.ipynb +++ b/master/tutorials/improving_ml_performance.ipynb @@ -60,10 +60,10 @@ "id": "2d638465", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:20.938341Z", - "iopub.status.busy": "2024-09-05T19:38:20.938181Z", - "iopub.status.idle": "2024-09-05T19:38:22.134719Z", - "shell.execute_reply": "2024-09-05T19:38:22.134142Z" + "iopub.execute_input": "2024-09-06T19:38:17.966921Z", + "iopub.status.busy": "2024-09-06T19:38:17.966743Z", + "iopub.status.idle": "2024-09-06T19:38:19.153643Z", + "shell.execute_reply": "2024-09-06T19:38:19.153020Z" }, "nbsphinx": "hidden" }, @@ -73,7 +73,7 @@ "dependencies = [\"cleanlab\", \"xgboost\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -99,10 +99,10 @@ "id": "b0bbf715-47c6-44ea-b15e-89800e62ee04", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.137472Z", - "iopub.status.busy": "2024-09-05T19:38:22.137010Z", - "iopub.status.idle": "2024-09-05T19:38:22.141005Z", - "shell.execute_reply": "2024-09-05T19:38:22.140442Z" + "iopub.execute_input": "2024-09-06T19:38:19.156468Z", + "iopub.status.busy": "2024-09-06T19:38:19.155927Z", + "iopub.status.idle": "2024-09-06T19:38:19.159820Z", + "shell.execute_reply": "2024-09-06T19:38:19.159280Z" } }, "outputs": [], @@ -140,10 +140,10 @@ "id": "c58f8015-d051-411c-9e03-5659cf3ad956", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.143101Z", - "iopub.status.busy": "2024-09-05T19:38:22.142800Z", - "iopub.status.idle": "2024-09-05T19:38:22.317437Z", - "shell.execute_reply": "2024-09-05T19:38:22.316874Z" + "iopub.execute_input": "2024-09-06T19:38:19.161985Z", + "iopub.status.busy": "2024-09-06T19:38:19.161628Z", + "iopub.status.idle": "2024-09-06T19:38:19.848074Z", + "shell.execute_reply": "2024-09-06T19:38:19.847540Z" } }, "outputs": [ @@ -273,10 +273,10 @@ "id": "1b5f50e6-d125-4e61-b63e-4004f0c9099a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.319775Z", - "iopub.status.busy": "2024-09-05T19:38:22.319343Z", - "iopub.status.idle": "2024-09-05T19:38:22.325394Z", - "shell.execute_reply": "2024-09-05T19:38:22.324864Z" + "iopub.execute_input": "2024-09-06T19:38:19.850305Z", + "iopub.status.busy": "2024-09-06T19:38:19.849961Z", + "iopub.status.idle": "2024-09-06T19:38:19.855710Z", + "shell.execute_reply": "2024-09-06T19:38:19.855268Z" } }, "outputs": [], @@ -312,10 +312,10 @@ "id": "a36c21e9-1c32-4df9-bd87-fffeb8c2175f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.327562Z", - "iopub.status.busy": "2024-09-05T19:38:22.327255Z", - "iopub.status.idle": "2024-09-05T19:38:22.334139Z", - "shell.execute_reply": "2024-09-05T19:38:22.333587Z" + "iopub.execute_input": "2024-09-06T19:38:19.857664Z", + "iopub.status.busy": "2024-09-06T19:38:19.857483Z", + "iopub.status.idle": "2024-09-06T19:38:19.864510Z", + "shell.execute_reply": "2024-09-06T19:38:19.863928Z" } }, "outputs": [ @@ -418,10 +418,10 @@ "id": "5f856a3a-8aae-4836-b146-9ab68d8d1c7a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.336134Z", - "iopub.status.busy": "2024-09-05T19:38:22.335809Z", - "iopub.status.idle": "2024-09-05T19:38:22.340537Z", - "shell.execute_reply": "2024-09-05T19:38:22.339975Z" + "iopub.execute_input": "2024-09-06T19:38:19.866738Z", + "iopub.status.busy": "2024-09-06T19:38:19.866419Z", + "iopub.status.idle": "2024-09-06T19:38:19.871181Z", + "shell.execute_reply": "2024-09-06T19:38:19.870718Z" } }, "outputs": [], @@ -449,10 +449,10 @@ "id": "46275634-da56-4e58-9061-8108be2b585d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.342582Z", - "iopub.status.busy": "2024-09-05T19:38:22.342279Z", - "iopub.status.idle": "2024-09-05T19:38:22.348079Z", - "shell.execute_reply": "2024-09-05T19:38:22.347521Z" + "iopub.execute_input": "2024-09-06T19:38:19.873167Z", + "iopub.status.busy": "2024-09-06T19:38:19.872989Z", + "iopub.status.idle": "2024-09-06T19:38:19.879315Z", + "shell.execute_reply": "2024-09-06T19:38:19.878873Z" } }, "outputs": [], @@ -488,10 +488,10 @@ "id": "769c4c5e-a7ff-4e02-bee5-2b2e676aec14", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.350256Z", - "iopub.status.busy": "2024-09-05T19:38:22.349941Z", - "iopub.status.idle": "2024-09-05T19:38:22.354060Z", - "shell.execute_reply": "2024-09-05T19:38:22.353506Z" + "iopub.execute_input": "2024-09-06T19:38:19.881299Z", + "iopub.status.busy": "2024-09-06T19:38:19.881109Z", + "iopub.status.idle": "2024-09-06T19:38:19.885448Z", + "shell.execute_reply": "2024-09-06T19:38:19.884866Z" } }, "outputs": [], @@ -506,10 +506,10 @@ "id": "7ac47c3d-9e87-45b7-9064-bfa45578872e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.356038Z", - "iopub.status.busy": "2024-09-05T19:38:22.355647Z", - "iopub.status.idle": "2024-09-05T19:38:22.423064Z", - "shell.execute_reply": "2024-09-05T19:38:22.422472Z" + "iopub.execute_input": "2024-09-06T19:38:19.887541Z", + "iopub.status.busy": "2024-09-06T19:38:19.887226Z", + "iopub.status.idle": "2024-09-06T19:38:19.952333Z", + "shell.execute_reply": "2024-09-06T19:38:19.951659Z" } }, "outputs": [ @@ -609,10 +609,10 @@ "id": "6cef169e-d15b-4d18-9cb7-8ea589557e6b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.426072Z", - "iopub.status.busy": "2024-09-05T19:38:22.425579Z", - "iopub.status.idle": "2024-09-05T19:38:22.436851Z", - "shell.execute_reply": "2024-09-05T19:38:22.436355Z" + "iopub.execute_input": "2024-09-06T19:38:19.955055Z", + "iopub.status.busy": "2024-09-06T19:38:19.954571Z", + "iopub.status.idle": "2024-09-06T19:38:19.965639Z", + "shell.execute_reply": "2024-09-06T19:38:19.965092Z" } }, "outputs": [ @@ -724,10 +724,10 @@ "id": "b68e0418-86cf-431f-9107-2dd0a310ca42", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.439378Z", - "iopub.status.busy": "2024-09-05T19:38:22.438783Z", - "iopub.status.idle": "2024-09-05T19:38:22.460540Z", - "shell.execute_reply": "2024-09-05T19:38:22.459904Z" + "iopub.execute_input": "2024-09-06T19:38:19.968612Z", + "iopub.status.busy": "2024-09-06T19:38:19.968081Z", + "iopub.status.idle": "2024-09-06T19:38:19.989523Z", + "shell.execute_reply": "2024-09-06T19:38:19.988990Z" } }, "outputs": [ @@ -931,10 +931,10 @@ "id": "0e9bd131-429f-48af-b4fc-ed8b907950b9", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.463026Z", - "iopub.status.busy": "2024-09-05T19:38:22.462648Z", - "iopub.status.idle": "2024-09-05T19:38:22.466619Z", - "shell.execute_reply": "2024-09-05T19:38:22.466139Z" + "iopub.execute_input": "2024-09-06T19:38:19.992484Z", + "iopub.status.busy": "2024-09-06T19:38:19.991953Z", + "iopub.status.idle": "2024-09-06T19:38:19.996496Z", + "shell.execute_reply": "2024-09-06T19:38:19.995963Z" } }, "outputs": [ @@ -968,10 +968,10 @@ "id": "e72320ec-7792-4347-b2fb-630f2519127c", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.468979Z", - "iopub.status.busy": "2024-09-05T19:38:22.468612Z", - "iopub.status.idle": "2024-09-05T19:38:22.472717Z", - "shell.execute_reply": "2024-09-05T19:38:22.472228Z" + "iopub.execute_input": "2024-09-06T19:38:20.000004Z", + "iopub.status.busy": "2024-09-06T19:38:19.999084Z", + "iopub.status.idle": "2024-09-06T19:38:20.005225Z", + "shell.execute_reply": "2024-09-06T19:38:20.004698Z" } }, "outputs": [ @@ -1005,10 +1005,10 @@ "id": "8520ba4a-3ad6-408a-b377-3f47c32d745a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.476188Z", - "iopub.status.busy": "2024-09-05T19:38:22.475241Z", - "iopub.status.idle": "2024-09-05T19:38:22.486948Z", - "shell.execute_reply": "2024-09-05T19:38:22.486537Z" + "iopub.execute_input": "2024-09-06T19:38:20.008748Z", + "iopub.status.busy": "2024-09-06T19:38:20.007824Z", + "iopub.status.idle": "2024-09-06T19:38:20.018446Z", + "shell.execute_reply": "2024-09-06T19:38:20.018010Z" } }, "outputs": [ @@ -1205,10 +1205,10 @@ "id": "3c002665-c48b-4f04-91f7-ad112a49efc7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.489195Z", - "iopub.status.busy": "2024-09-05T19:38:22.488861Z", - "iopub.status.idle": "2024-09-05T19:38:22.493151Z", - "shell.execute_reply": "2024-09-05T19:38:22.492710Z" + "iopub.execute_input": "2024-09-06T19:38:20.020571Z", + "iopub.status.busy": "2024-09-06T19:38:20.020204Z", + "iopub.status.idle": "2024-09-06T19:38:20.024666Z", + "shell.execute_reply": "2024-09-06T19:38:20.024096Z" } }, "outputs": [], @@ -1234,10 +1234,10 @@ "id": "36319f39-f563-4f63-913f-821373180350", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.495336Z", - "iopub.status.busy": "2024-09-05T19:38:22.495008Z", - "iopub.status.idle": "2024-09-05T19:38:22.606998Z", - "shell.execute_reply": "2024-09-05T19:38:22.606408Z" + "iopub.execute_input": "2024-09-06T19:38:20.026677Z", + "iopub.status.busy": "2024-09-06T19:38:20.026505Z", + "iopub.status.idle": "2024-09-06T19:38:20.138981Z", + "shell.execute_reply": "2024-09-06T19:38:20.138473Z" } }, "outputs": [ @@ -1711,10 +1711,10 @@ "id": "044c0eb1-299a-4851-b1bf-268d5bce56c1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.609473Z", - "iopub.status.busy": "2024-09-05T19:38:22.609016Z", - "iopub.status.idle": "2024-09-05T19:38:22.617971Z", - "shell.execute_reply": "2024-09-05T19:38:22.617376Z" + "iopub.execute_input": "2024-09-06T19:38:20.141251Z", + "iopub.status.busy": "2024-09-06T19:38:20.140804Z", + "iopub.status.idle": "2024-09-06T19:38:20.147269Z", + "shell.execute_reply": "2024-09-06T19:38:20.146678Z" } }, "outputs": [], @@ -1738,10 +1738,10 @@ "id": "c43df278-abfe-40e5-9d48-2df3efea9379", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:22.620315Z", - "iopub.status.busy": "2024-09-05T19:38:22.620121Z", - "iopub.status.idle": "2024-09-05T19:38:24.659647Z", - "shell.execute_reply": "2024-09-05T19:38:24.659017Z" + "iopub.execute_input": "2024-09-06T19:38:20.149710Z", + "iopub.status.busy": "2024-09-06T19:38:20.149204Z", + "iopub.status.idle": "2024-09-06T19:38:22.175679Z", + "shell.execute_reply": "2024-09-06T19:38:22.175042Z" } }, "outputs": [ @@ -1953,10 +1953,10 @@ "id": "77c7f776-54b3-45b5-9207-715d6d2e90c0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.662641Z", - "iopub.status.busy": "2024-09-05T19:38:24.662119Z", - "iopub.status.idle": "2024-09-05T19:38:24.675048Z", - "shell.execute_reply": "2024-09-05T19:38:24.674550Z" + "iopub.execute_input": "2024-09-06T19:38:22.179907Z", + "iopub.status.busy": "2024-09-06T19:38:22.178817Z", + "iopub.status.idle": "2024-09-06T19:38:22.193599Z", + "shell.execute_reply": "2024-09-06T19:38:22.193081Z" } }, "outputs": [ @@ -2073,10 +2073,10 @@ "id": "7e218d04-0729-4f42-b264-51c73601ebe6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.677529Z", - "iopub.status.busy": "2024-09-05T19:38:24.677151Z", - "iopub.status.idle": "2024-09-05T19:38:24.680012Z", - "shell.execute_reply": "2024-09-05T19:38:24.679501Z" + "iopub.execute_input": "2024-09-06T19:38:22.197201Z", + "iopub.status.busy": "2024-09-06T19:38:22.196240Z", + "iopub.status.idle": "2024-09-06T19:38:22.200280Z", + "shell.execute_reply": "2024-09-06T19:38:22.199770Z" } }, "outputs": [], @@ -2090,10 +2090,10 @@ "id": "7e2bdb41-321e-4929-aa01-1f60948b9e8b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.682370Z", - "iopub.status.busy": "2024-09-05T19:38:24.681990Z", - "iopub.status.idle": "2024-09-05T19:38:24.686455Z", - "shell.execute_reply": "2024-09-05T19:38:24.685959Z" + "iopub.execute_input": "2024-09-06T19:38:22.203753Z", + "iopub.status.busy": "2024-09-06T19:38:22.202840Z", + "iopub.status.idle": "2024-09-06T19:38:22.208375Z", + "shell.execute_reply": "2024-09-06T19:38:22.207870Z" } }, "outputs": [], @@ -2117,10 +2117,10 @@ "id": "5ce2d89f-e832-448d-bfac-9941da15c895", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.688843Z", - "iopub.status.busy": "2024-09-05T19:38:24.688467Z", - "iopub.status.idle": "2024-09-05T19:38:24.725249Z", - "shell.execute_reply": "2024-09-05T19:38:24.724758Z" + "iopub.execute_input": "2024-09-06T19:38:22.211876Z", + "iopub.status.busy": "2024-09-06T19:38:22.210955Z", + "iopub.status.idle": "2024-09-06T19:38:22.243013Z", + "shell.execute_reply": "2024-09-06T19:38:22.242528Z" } }, "outputs": [ @@ -2160,10 +2160,10 @@ "id": "9f437756-112e-4531-84fc-6ceadd0c9ef5", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:24.727654Z", - "iopub.status.busy": "2024-09-05T19:38:24.727295Z", - "iopub.status.idle": "2024-09-05T19:38:25.269267Z", - "shell.execute_reply": "2024-09-05T19:38:25.268697Z" + "iopub.execute_input": "2024-09-06T19:38:22.246118Z", + "iopub.status.busy": "2024-09-06T19:38:22.245468Z", + "iopub.status.idle": "2024-09-06T19:38:22.754137Z", + "shell.execute_reply": "2024-09-06T19:38:22.753573Z" } }, "outputs": [], @@ -2194,10 +2194,10 @@ "id": "707625f6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.272182Z", - "iopub.status.busy": "2024-09-05T19:38:25.271755Z", - "iopub.status.idle": "2024-09-05T19:38:25.404404Z", - "shell.execute_reply": "2024-09-05T19:38:25.403688Z" + "iopub.execute_input": "2024-09-06T19:38:22.757125Z", + "iopub.status.busy": "2024-09-06T19:38:22.756730Z", + "iopub.status.idle": "2024-09-06T19:38:22.893326Z", + "shell.execute_reply": "2024-09-06T19:38:22.892578Z" } }, "outputs": [ @@ -2408,10 +2408,10 @@ "id": "25afe46c-a521-483c-b168-728c76d970dc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.408052Z", - "iopub.status.busy": "2024-09-05T19:38:25.407073Z", - "iopub.status.idle": "2024-09-05T19:38:25.415814Z", - "shell.execute_reply": "2024-09-05T19:38:25.415311Z" + "iopub.execute_input": "2024-09-06T19:38:22.896382Z", + "iopub.status.busy": "2024-09-06T19:38:22.896143Z", + "iopub.status.idle": "2024-09-06T19:38:22.903618Z", + "shell.execute_reply": "2024-09-06T19:38:22.903032Z" } }, "outputs": [ @@ -2441,10 +2441,10 @@ "id": "6efcf06f-cc40-4964-87df-5204d3b1b9d4", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.419323Z", - "iopub.status.busy": "2024-09-05T19:38:25.418402Z", - "iopub.status.idle": "2024-09-05T19:38:25.426295Z", - "shell.execute_reply": "2024-09-05T19:38:25.425789Z" + "iopub.execute_input": "2024-09-06T19:38:22.906322Z", + "iopub.status.busy": "2024-09-06T19:38:22.906102Z", + "iopub.status.idle": "2024-09-06T19:38:22.914842Z", + "shell.execute_reply": "2024-09-06T19:38:22.914319Z" } }, "outputs": [ @@ -2477,10 +2477,10 @@ "id": "7bc87d72-bbd5-4ed2-bc38-2218862ddfbd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.429748Z", - "iopub.status.busy": "2024-09-05T19:38:25.428807Z", - "iopub.status.idle": "2024-09-05T19:38:25.436120Z", - "shell.execute_reply": "2024-09-05T19:38:25.435593Z" + "iopub.execute_input": "2024-09-06T19:38:22.917418Z", + "iopub.status.busy": "2024-09-06T19:38:22.917212Z", + "iopub.status.idle": "2024-09-06T19:38:22.924586Z", + "shell.execute_reply": "2024-09-06T19:38:22.924068Z" } }, "outputs": [ @@ -2513,10 +2513,10 @@ "id": "9c70be3e-0ba2-4e3e-8c50-359d402ca1fe", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.439616Z", - "iopub.status.busy": "2024-09-05T19:38:25.438651Z", - "iopub.status.idle": "2024-09-05T19:38:25.444907Z", - "shell.execute_reply": "2024-09-05T19:38:25.444411Z" + "iopub.execute_input": "2024-09-06T19:38:22.927978Z", + "iopub.status.busy": "2024-09-06T19:38:22.927001Z", + "iopub.status.idle": "2024-09-06T19:38:22.932989Z", + "shell.execute_reply": "2024-09-06T19:38:22.932417Z" } }, "outputs": [ @@ -2542,10 +2542,10 @@ "id": "08080458-0cd7-447d-80e6-384cb8d31eaf", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.447298Z", - "iopub.status.busy": "2024-09-05T19:38:25.447124Z", - "iopub.status.idle": "2024-09-05T19:38:25.452420Z", - "shell.execute_reply": "2024-09-05T19:38:25.451830Z" + "iopub.execute_input": "2024-09-06T19:38:22.935455Z", + "iopub.status.busy": "2024-09-06T19:38:22.935286Z", + "iopub.status.idle": "2024-09-06T19:38:22.940366Z", + "shell.execute_reply": "2024-09-06T19:38:22.939926Z" } }, "outputs": [], @@ -2569,10 +2569,10 @@ "id": "009bb215-4d26-47da-a230-d0ccf4122629", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.454421Z", - "iopub.status.busy": "2024-09-05T19:38:25.454250Z", - "iopub.status.idle": "2024-09-05T19:38:25.536458Z", - "shell.execute_reply": "2024-09-05T19:38:25.535873Z" + "iopub.execute_input": "2024-09-06T19:38:22.942577Z", + "iopub.status.busy": "2024-09-06T19:38:22.942242Z", + "iopub.status.idle": "2024-09-06T19:38:23.018404Z", + "shell.execute_reply": "2024-09-06T19:38:23.017754Z" } }, "outputs": [ @@ -3052,10 +3052,10 @@ "id": "dcaeda51-9b24-4c04-889d-7e63563594fc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.538788Z", - "iopub.status.busy": "2024-09-05T19:38:25.538612Z", - "iopub.status.idle": "2024-09-05T19:38:25.547223Z", - "shell.execute_reply": "2024-09-05T19:38:25.546738Z" + "iopub.execute_input": "2024-09-06T19:38:23.021060Z", + "iopub.status.busy": "2024-09-06T19:38:23.020492Z", + "iopub.status.idle": "2024-09-06T19:38:23.034062Z", + "shell.execute_reply": "2024-09-06T19:38:23.033451Z" } }, "outputs": [ @@ -3111,10 +3111,10 @@ "id": "1d92d78d-e4a8-4322-bf38-f5a5dae3bf17", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.550442Z", - "iopub.status.busy": "2024-09-05T19:38:25.549562Z", - "iopub.status.idle": "2024-09-05T19:38:25.553319Z", - "shell.execute_reply": "2024-09-05T19:38:25.552755Z" + "iopub.execute_input": "2024-09-06T19:38:23.036553Z", + "iopub.status.busy": "2024-09-06T19:38:23.036240Z", + "iopub.status.idle": "2024-09-06T19:38:23.039008Z", + "shell.execute_reply": "2024-09-06T19:38:23.038465Z" } }, "outputs": [], @@ -3150,10 +3150,10 @@ "id": "941ab2a6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.555448Z", - "iopub.status.busy": "2024-09-05T19:38:25.555270Z", - "iopub.status.idle": "2024-09-05T19:38:25.565627Z", - "shell.execute_reply": "2024-09-05T19:38:25.565195Z" + "iopub.execute_input": "2024-09-06T19:38:23.041147Z", + "iopub.status.busy": "2024-09-06T19:38:23.040695Z", + "iopub.status.idle": "2024-09-06T19:38:23.050646Z", + "shell.execute_reply": "2024-09-06T19:38:23.050044Z" } }, "outputs": [], @@ -3261,10 +3261,10 @@ "id": "50666fb9", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.567569Z", - "iopub.status.busy": "2024-09-05T19:38:25.567400Z", - "iopub.status.idle": "2024-09-05T19:38:25.573998Z", - "shell.execute_reply": "2024-09-05T19:38:25.573414Z" + "iopub.execute_input": "2024-09-06T19:38:23.053067Z", + "iopub.status.busy": "2024-09-06T19:38:23.052637Z", + "iopub.status.idle": "2024-09-06T19:38:23.059254Z", + "shell.execute_reply": "2024-09-06T19:38:23.058781Z" }, "nbsphinx": "hidden" }, @@ -3346,10 +3346,10 @@ "id": "f5aa2883-d20d-481f-a012-fcc7ff8e3e7e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.576080Z", - "iopub.status.busy": "2024-09-05T19:38:25.575748Z", - "iopub.status.idle": "2024-09-05T19:38:25.579065Z", - "shell.execute_reply": "2024-09-05T19:38:25.578516Z" + "iopub.execute_input": "2024-09-06T19:38:23.061114Z", + "iopub.status.busy": "2024-09-06T19:38:23.060934Z", + "iopub.status.idle": "2024-09-06T19:38:23.064369Z", + "shell.execute_reply": "2024-09-06T19:38:23.063906Z" } }, "outputs": [], @@ -3373,10 +3373,10 @@ "id": "ce1c0ada-88b1-4654-b43f-3c0b59002979", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:25.581087Z", - "iopub.status.busy": "2024-09-05T19:38:25.580780Z", - "iopub.status.idle": "2024-09-05T19:38:29.675098Z", - "shell.execute_reply": "2024-09-05T19:38:29.674482Z" + "iopub.execute_input": "2024-09-06T19:38:23.066492Z", + "iopub.status.busy": "2024-09-06T19:38:23.066088Z", + "iopub.status.idle": "2024-09-06T19:38:27.075896Z", + "shell.execute_reply": "2024-09-06T19:38:27.075361Z" } }, "outputs": [ @@ -3419,10 +3419,10 @@ "id": "3f572acf-31c3-4874-9100-451796e35b06", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:29.678980Z", - "iopub.status.busy": "2024-09-05T19:38:29.678139Z", - "iopub.status.idle": "2024-09-05T19:38:29.682800Z", - "shell.execute_reply": "2024-09-05T19:38:29.682367Z" + "iopub.execute_input": "2024-09-06T19:38:27.079119Z", + "iopub.status.busy": "2024-09-06T19:38:27.078209Z", + "iopub.status.idle": "2024-09-06T19:38:27.082469Z", + "shell.execute_reply": "2024-09-06T19:38:27.082025Z" } }, "outputs": [ @@ -3460,10 +3460,10 @@ "id": "6a025a88", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:29.685051Z", - "iopub.status.busy": "2024-09-05T19:38:29.684864Z", - "iopub.status.idle": "2024-09-05T19:38:29.687798Z", - "shell.execute_reply": "2024-09-05T19:38:29.687349Z" + "iopub.execute_input": "2024-09-06T19:38:27.084613Z", + "iopub.status.busy": "2024-09-06T19:38:27.084277Z", + "iopub.status.idle": "2024-09-06T19:38:27.087400Z", + "shell.execute_reply": "2024-09-06T19:38:27.086984Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/indepth_overview.ipynb b/master/tutorials/indepth_overview.ipynb index ff39a0ce9..d4d06d3f8 100644 --- a/master/tutorials/indepth_overview.ipynb +++ b/master/tutorials/indepth_overview.ipynb @@ -53,10 +53,10 @@ "execution_count": 1, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:33.024311Z", - "iopub.status.busy": "2024-09-05T19:38:33.024154Z", - "iopub.status.idle": "2024-09-05T19:38:34.264701Z", - "shell.execute_reply": "2024-09-05T19:38:34.264082Z" + "iopub.execute_input": "2024-09-06T19:38:29.945055Z", + "iopub.status.busy": "2024-09-06T19:38:29.944859Z", + "iopub.status.idle": "2024-09-06T19:38:31.152677Z", + "shell.execute_reply": "2024-09-06T19:38:31.152154Z" }, "nbsphinx": "hidden" }, @@ -68,7 +68,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -95,10 +95,10 @@ "execution_count": 2, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.267586Z", - "iopub.status.busy": "2024-09-05T19:38:34.267100Z", - "iopub.status.idle": "2024-09-05T19:38:34.450638Z", - "shell.execute_reply": "2024-09-05T19:38:34.449996Z" + "iopub.execute_input": "2024-09-06T19:38:31.155349Z", + "iopub.status.busy": "2024-09-06T19:38:31.154914Z", + "iopub.status.idle": "2024-09-06T19:38:31.333867Z", + "shell.execute_reply": "2024-09-06T19:38:31.333299Z" }, "id": "avXlHJcXjruP" }, @@ -234,10 +234,10 @@ "execution_count": 3, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.453452Z", - "iopub.status.busy": "2024-09-05T19:38:34.453074Z", - "iopub.status.idle": "2024-09-05T19:38:34.464955Z", - "shell.execute_reply": "2024-09-05T19:38:34.464480Z" + "iopub.execute_input": "2024-09-06T19:38:31.336296Z", + "iopub.status.busy": "2024-09-06T19:38:31.336106Z", + "iopub.status.idle": "2024-09-06T19:38:31.347492Z", + "shell.execute_reply": "2024-09-06T19:38:31.347045Z" }, "nbsphinx": "hidden" }, @@ -340,10 +340,10 @@ "execution_count": 4, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.467204Z", - "iopub.status.busy": "2024-09-05T19:38:34.466843Z", - "iopub.status.idle": "2024-09-05T19:38:34.705791Z", - "shell.execute_reply": "2024-09-05T19:38:34.705183Z" + "iopub.execute_input": "2024-09-06T19:38:31.349587Z", + "iopub.status.busy": "2024-09-06T19:38:31.349239Z", + "iopub.status.idle": "2024-09-06T19:38:31.559000Z", + "shell.execute_reply": "2024-09-06T19:38:31.558435Z" } }, "outputs": [ @@ -393,10 +393,10 @@ "execution_count": 5, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.708181Z", - "iopub.status.busy": "2024-09-05T19:38:34.707976Z", - "iopub.status.idle": "2024-09-05T19:38:34.734780Z", - "shell.execute_reply": "2024-09-05T19:38:34.734318Z" + "iopub.execute_input": "2024-09-06T19:38:31.561389Z", + "iopub.status.busy": "2024-09-06T19:38:31.561027Z", + "iopub.status.idle": "2024-09-06T19:38:31.587035Z", + "shell.execute_reply": "2024-09-06T19:38:31.586568Z" } }, "outputs": [], @@ -428,10 +428,10 @@ "execution_count": 6, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:34.736860Z", - "iopub.status.busy": "2024-09-05T19:38:34.736672Z", - "iopub.status.idle": "2024-09-05T19:38:36.884795Z", - "shell.execute_reply": "2024-09-05T19:38:36.884146Z" + "iopub.execute_input": "2024-09-06T19:38:31.589259Z", + "iopub.status.busy": "2024-09-06T19:38:31.588898Z", + "iopub.status.idle": "2024-09-06T19:38:33.659672Z", + "shell.execute_reply": "2024-09-06T19:38:33.658986Z" } }, "outputs": [ @@ -474,10 +474,10 @@ "execution_count": 7, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:36.887499Z", - "iopub.status.busy": "2024-09-05T19:38:36.886853Z", - "iopub.status.idle": "2024-09-05T19:38:36.905206Z", - "shell.execute_reply": "2024-09-05T19:38:36.904650Z" + "iopub.execute_input": "2024-09-06T19:38:33.662234Z", + "iopub.status.busy": "2024-09-06T19:38:33.661770Z", + "iopub.status.idle": "2024-09-06T19:38:33.679880Z", + "shell.execute_reply": "2024-09-06T19:38:33.679304Z" }, "scrolled": true }, @@ -607,10 +607,10 @@ "execution_count": 8, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:36.907433Z", - "iopub.status.busy": "2024-09-05T19:38:36.907012Z", - "iopub.status.idle": "2024-09-05T19:38:38.506025Z", - "shell.execute_reply": "2024-09-05T19:38:38.505370Z" + "iopub.execute_input": "2024-09-06T19:38:33.682125Z", + "iopub.status.busy": "2024-09-06T19:38:33.681797Z", + "iopub.status.idle": "2024-09-06T19:38:35.246559Z", + "shell.execute_reply": "2024-09-06T19:38:35.245952Z" }, "id": "AaHC5MRKjruT" }, @@ -729,10 +729,10 @@ "execution_count": 9, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.508964Z", - "iopub.status.busy": "2024-09-05T19:38:38.508264Z", - "iopub.status.idle": "2024-09-05T19:38:38.522533Z", - "shell.execute_reply": "2024-09-05T19:38:38.522045Z" + "iopub.execute_input": "2024-09-06T19:38:35.249384Z", + "iopub.status.busy": "2024-09-06T19:38:35.248692Z", + "iopub.status.idle": "2024-09-06T19:38:35.262909Z", + "shell.execute_reply": "2024-09-06T19:38:35.262437Z" }, "id": "Wy27rvyhjruU" }, @@ -781,10 +781,10 @@ "execution_count": 10, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.524864Z", - "iopub.status.busy": "2024-09-05T19:38:38.524513Z", - "iopub.status.idle": "2024-09-05T19:38:38.607517Z", - "shell.execute_reply": "2024-09-05T19:38:38.606813Z" + "iopub.execute_input": "2024-09-06T19:38:35.265091Z", + "iopub.status.busy": "2024-09-06T19:38:35.264657Z", + "iopub.status.idle": "2024-09-06T19:38:35.347361Z", + "shell.execute_reply": "2024-09-06T19:38:35.346752Z" }, "id": "Db8YHnyVjruU" }, @@ -891,10 +891,10 @@ "execution_count": 11, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.610151Z", - "iopub.status.busy": "2024-09-05T19:38:38.609680Z", - "iopub.status.idle": "2024-09-05T19:38:38.823788Z", - "shell.execute_reply": "2024-09-05T19:38:38.823190Z" + "iopub.execute_input": "2024-09-06T19:38:35.349859Z", + "iopub.status.busy": "2024-09-06T19:38:35.349553Z", + "iopub.status.idle": "2024-09-06T19:38:35.568160Z", + "shell.execute_reply": "2024-09-06T19:38:35.567596Z" }, "id": "iJqAHuS2jruV" }, @@ -931,10 +931,10 @@ "execution_count": 12, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.826041Z", - "iopub.status.busy": "2024-09-05T19:38:38.825845Z", - "iopub.status.idle": "2024-09-05T19:38:38.843439Z", - "shell.execute_reply": "2024-09-05T19:38:38.842891Z" + "iopub.execute_input": "2024-09-06T19:38:35.570518Z", + "iopub.status.busy": "2024-09-06T19:38:35.570156Z", + "iopub.status.idle": "2024-09-06T19:38:35.587030Z", + "shell.execute_reply": "2024-09-06T19:38:35.586565Z" }, "id": "PcPTZ_JJG3Cx" }, @@ -1400,10 +1400,10 @@ "execution_count": 13, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.845804Z", - "iopub.status.busy": "2024-09-05T19:38:38.845404Z", - "iopub.status.idle": "2024-09-05T19:38:38.855289Z", - "shell.execute_reply": "2024-09-05T19:38:38.854744Z" + "iopub.execute_input": "2024-09-06T19:38:35.589095Z", + "iopub.status.busy": "2024-09-06T19:38:35.588739Z", + "iopub.status.idle": "2024-09-06T19:38:35.598220Z", + "shell.execute_reply": "2024-09-06T19:38:35.597755Z" }, "id": "0lonvOYvjruV" }, @@ -1550,10 +1550,10 @@ "execution_count": 14, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.857352Z", - "iopub.status.busy": "2024-09-05T19:38:38.857028Z", - "iopub.status.idle": "2024-09-05T19:38:38.948792Z", - "shell.execute_reply": "2024-09-05T19:38:38.948130Z" + "iopub.execute_input": "2024-09-06T19:38:35.600262Z", + "iopub.status.busy": "2024-09-06T19:38:35.599918Z", + "iopub.status.idle": "2024-09-06T19:38:35.692538Z", + "shell.execute_reply": "2024-09-06T19:38:35.691918Z" }, "id": "MfqTCa3kjruV" }, @@ -1634,10 +1634,10 @@ "execution_count": 15, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:38.951301Z", - "iopub.status.busy": "2024-09-05T19:38:38.950892Z", - "iopub.status.idle": "2024-09-05T19:38:39.093684Z", - "shell.execute_reply": "2024-09-05T19:38:39.093010Z" + "iopub.execute_input": "2024-09-06T19:38:35.694934Z", + "iopub.status.busy": "2024-09-06T19:38:35.694629Z", + "iopub.status.idle": "2024-09-06T19:38:35.833017Z", + "shell.execute_reply": "2024-09-06T19:38:35.832312Z" }, "id": "9ZtWAYXqMAPL" }, @@ -1697,10 +1697,10 @@ "execution_count": 16, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.096217Z", - "iopub.status.busy": "2024-09-05T19:38:39.095689Z", - "iopub.status.idle": "2024-09-05T19:38:39.099737Z", - "shell.execute_reply": "2024-09-05T19:38:39.099183Z" + "iopub.execute_input": "2024-09-06T19:38:35.835595Z", + "iopub.status.busy": "2024-09-06T19:38:35.835206Z", + "iopub.status.idle": "2024-09-06T19:38:35.839051Z", + "shell.execute_reply": "2024-09-06T19:38:35.838497Z" }, "id": "0rXP3ZPWjruW" }, @@ -1738,10 +1738,10 @@ "execution_count": 17, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.101881Z", - "iopub.status.busy": "2024-09-05T19:38:39.101611Z", - "iopub.status.idle": "2024-09-05T19:38:39.105429Z", - "shell.execute_reply": "2024-09-05T19:38:39.104857Z" + "iopub.execute_input": "2024-09-06T19:38:35.841055Z", + "iopub.status.busy": "2024-09-06T19:38:35.840887Z", + "iopub.status.idle": "2024-09-06T19:38:35.844523Z", + "shell.execute_reply": "2024-09-06T19:38:35.843987Z" }, "id": "-iRPe8KXjruW" }, @@ -1796,10 +1796,10 @@ "execution_count": 18, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.107547Z", - "iopub.status.busy": "2024-09-05T19:38:39.107212Z", - "iopub.status.idle": "2024-09-05T19:38:39.143655Z", - "shell.execute_reply": "2024-09-05T19:38:39.143146Z" + "iopub.execute_input": "2024-09-06T19:38:35.846624Z", + "iopub.status.busy": "2024-09-06T19:38:35.846289Z", + "iopub.status.idle": "2024-09-06T19:38:35.883516Z", + "shell.execute_reply": "2024-09-06T19:38:35.883025Z" }, "id": "ZpipUliyjruW" }, @@ -1850,10 +1850,10 @@ "execution_count": 19, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.145813Z", - "iopub.status.busy": "2024-09-05T19:38:39.145467Z", - "iopub.status.idle": "2024-09-05T19:38:39.185783Z", - "shell.execute_reply": "2024-09-05T19:38:39.185245Z" + "iopub.execute_input": "2024-09-06T19:38:35.885707Z", + "iopub.status.busy": "2024-09-06T19:38:35.885360Z", + "iopub.status.idle": "2024-09-06T19:38:35.926415Z", + "shell.execute_reply": "2024-09-06T19:38:35.925951Z" }, "id": "SLq-3q4xjruX" }, @@ -1922,10 +1922,10 @@ "execution_count": 20, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.187839Z", - "iopub.status.busy": "2024-09-05T19:38:39.187520Z", - "iopub.status.idle": "2024-09-05T19:38:39.289564Z", - "shell.execute_reply": "2024-09-05T19:38:39.288933Z" + "iopub.execute_input": "2024-09-06T19:38:35.928488Z", + "iopub.status.busy": "2024-09-06T19:38:35.928146Z", + "iopub.status.idle": "2024-09-06T19:38:36.031351Z", + "shell.execute_reply": "2024-09-06T19:38:36.030698Z" }, "id": "g5LHhhuqFbXK" }, @@ -1957,10 +1957,10 @@ "execution_count": 21, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.292121Z", - "iopub.status.busy": "2024-09-05T19:38:39.291892Z", - "iopub.status.idle": "2024-09-05T19:38:39.400843Z", - "shell.execute_reply": "2024-09-05T19:38:39.400129Z" + "iopub.execute_input": "2024-09-06T19:38:36.034301Z", + "iopub.status.busy": "2024-09-06T19:38:36.033912Z", + "iopub.status.idle": "2024-09-06T19:38:36.132017Z", + "shell.execute_reply": "2024-09-06T19:38:36.131369Z" }, "id": "p7w8F8ezBcet" }, @@ -2017,10 +2017,10 @@ "execution_count": 22, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.403530Z", - "iopub.status.busy": "2024-09-05T19:38:39.403100Z", - "iopub.status.idle": "2024-09-05T19:38:39.617987Z", - "shell.execute_reply": "2024-09-05T19:38:39.617380Z" + "iopub.execute_input": "2024-09-06T19:38:36.134718Z", + "iopub.status.busy": "2024-09-06T19:38:36.134254Z", + "iopub.status.idle": "2024-09-06T19:38:36.372737Z", + "shell.execute_reply": "2024-09-06T19:38:36.372155Z" }, "id": "WETRL74tE_sU" }, @@ -2055,10 +2055,10 @@ "execution_count": 23, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.620312Z", - "iopub.status.busy": "2024-09-05T19:38:39.619935Z", - "iopub.status.idle": "2024-09-05T19:38:39.847199Z", - "shell.execute_reply": "2024-09-05T19:38:39.846563Z" + "iopub.execute_input": "2024-09-06T19:38:36.374987Z", + "iopub.status.busy": "2024-09-06T19:38:36.374694Z", + "iopub.status.idle": "2024-09-06T19:38:36.587886Z", + "shell.execute_reply": "2024-09-06T19:38:36.587278Z" }, "id": "kCfdx2gOLmXS" }, @@ -2220,10 +2220,10 @@ "execution_count": 24, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.849646Z", - "iopub.status.busy": "2024-09-05T19:38:39.849312Z", - "iopub.status.idle": "2024-09-05T19:38:39.855523Z", - "shell.execute_reply": "2024-09-05T19:38:39.855075Z" + "iopub.execute_input": "2024-09-06T19:38:36.590343Z", + "iopub.status.busy": "2024-09-06T19:38:36.589956Z", + "iopub.status.idle": "2024-09-06T19:38:36.595878Z", + "shell.execute_reply": "2024-09-06T19:38:36.595334Z" }, "id": "-uogYRWFYnuu" }, @@ -2277,10 +2277,10 @@ "execution_count": 25, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:39.857741Z", - "iopub.status.busy": "2024-09-05T19:38:39.857296Z", - "iopub.status.idle": "2024-09-05T19:38:40.076699Z", - "shell.execute_reply": "2024-09-05T19:38:40.076059Z" + "iopub.execute_input": "2024-09-06T19:38:36.598057Z", + "iopub.status.busy": "2024-09-06T19:38:36.597740Z", + "iopub.status.idle": "2024-09-06T19:38:36.811700Z", + "shell.execute_reply": "2024-09-06T19:38:36.811079Z" }, "id": "pG-ljrmcYp9Q" }, @@ -2327,10 +2327,10 @@ "execution_count": 26, "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:40.079111Z", - "iopub.status.busy": "2024-09-05T19:38:40.078742Z", - "iopub.status.idle": "2024-09-05T19:38:41.162000Z", - "shell.execute_reply": "2024-09-05T19:38:41.161484Z" + "iopub.execute_input": "2024-09-06T19:38:36.813989Z", + "iopub.status.busy": "2024-09-06T19:38:36.813680Z", + "iopub.status.idle": "2024-09-06T19:38:37.873549Z", + "shell.execute_reply": "2024-09-06T19:38:37.872901Z" }, "id": "wL3ngCnuLEWd" }, diff --git a/master/tutorials/multiannotator.ipynb b/master/tutorials/multiannotator.ipynb index 872e74175..0b05cce8c 100644 --- a/master/tutorials/multiannotator.ipynb +++ b/master/tutorials/multiannotator.ipynb @@ -88,10 +88,10 @@ "id": "a3ddc95f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:44.675764Z", - "iopub.status.busy": "2024-09-05T19:38:44.675335Z", - "iopub.status.idle": "2024-09-05T19:38:45.838314Z", - "shell.execute_reply": "2024-09-05T19:38:45.837761Z" + "iopub.execute_input": "2024-09-06T19:38:41.455901Z", + "iopub.status.busy": "2024-09-06T19:38:41.455732Z", + "iopub.status.idle": "2024-09-06T19:38:42.611358Z", + "shell.execute_reply": "2024-09-06T19:38:42.610733Z" }, "nbsphinx": "hidden" }, @@ -101,7 +101,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -135,10 +135,10 @@ "id": "c4efd119", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.840955Z", - "iopub.status.busy": "2024-09-05T19:38:45.840492Z", - "iopub.status.idle": "2024-09-05T19:38:45.843468Z", - "shell.execute_reply": "2024-09-05T19:38:45.843021Z" + "iopub.execute_input": "2024-09-06T19:38:42.614152Z", + "iopub.status.busy": "2024-09-06T19:38:42.613703Z", + "iopub.status.idle": "2024-09-06T19:38:42.617474Z", + "shell.execute_reply": "2024-09-06T19:38:42.616914Z" } }, "outputs": [], @@ -263,10 +263,10 @@ "id": "c37c0a69", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.845741Z", - "iopub.status.busy": "2024-09-05T19:38:45.845402Z", - "iopub.status.idle": "2024-09-05T19:38:45.853153Z", - "shell.execute_reply": "2024-09-05T19:38:45.852719Z" + "iopub.execute_input": "2024-09-06T19:38:42.619686Z", + "iopub.status.busy": "2024-09-06T19:38:42.619396Z", + "iopub.status.idle": "2024-09-06T19:38:42.627253Z", + "shell.execute_reply": "2024-09-06T19:38:42.626804Z" }, "nbsphinx": "hidden" }, @@ -350,10 +350,10 @@ "id": "99f69523", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.855196Z", - "iopub.status.busy": "2024-09-05T19:38:45.854862Z", - "iopub.status.idle": "2024-09-05T19:38:45.900555Z", - "shell.execute_reply": "2024-09-05T19:38:45.900040Z" + "iopub.execute_input": "2024-09-06T19:38:42.629251Z", + "iopub.status.busy": "2024-09-06T19:38:42.628912Z", + "iopub.status.idle": "2024-09-06T19:38:42.675739Z", + "shell.execute_reply": "2024-09-06T19:38:42.675250Z" } }, "outputs": [], @@ -379,10 +379,10 @@ "id": "8f241c16", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.902601Z", - "iopub.status.busy": "2024-09-05T19:38:45.902427Z", - "iopub.status.idle": "2024-09-05T19:38:45.919866Z", - "shell.execute_reply": "2024-09-05T19:38:45.919444Z" + "iopub.execute_input": "2024-09-06T19:38:42.677746Z", + "iopub.status.busy": "2024-09-06T19:38:42.677566Z", + "iopub.status.idle": "2024-09-06T19:38:42.695187Z", + "shell.execute_reply": "2024-09-06T19:38:42.694600Z" } }, "outputs": [ @@ -597,10 +597,10 @@ "id": "4f0819ba", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.922151Z", - "iopub.status.busy": "2024-09-05T19:38:45.921714Z", - "iopub.status.idle": "2024-09-05T19:38:45.925609Z", - "shell.execute_reply": "2024-09-05T19:38:45.925082Z" + "iopub.execute_input": "2024-09-06T19:38:42.697240Z", + "iopub.status.busy": "2024-09-06T19:38:42.696927Z", + "iopub.status.idle": "2024-09-06T19:38:42.700805Z", + "shell.execute_reply": "2024-09-06T19:38:42.700357Z" } }, "outputs": [ @@ -671,10 +671,10 @@ "id": "d009f347", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.927793Z", - "iopub.status.busy": "2024-09-05T19:38:45.927382Z", - "iopub.status.idle": "2024-09-05T19:38:45.943665Z", - "shell.execute_reply": "2024-09-05T19:38:45.943100Z" + "iopub.execute_input": "2024-09-06T19:38:42.703011Z", + "iopub.status.busy": "2024-09-06T19:38:42.702619Z", + "iopub.status.idle": "2024-09-06T19:38:42.719152Z", + "shell.execute_reply": "2024-09-06T19:38:42.718696Z" } }, "outputs": [], @@ -698,10 +698,10 @@ "id": "cbd1e415", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.945827Z", - "iopub.status.busy": "2024-09-05T19:38:45.945552Z", - "iopub.status.idle": "2024-09-05T19:38:45.971204Z", - "shell.execute_reply": "2024-09-05T19:38:45.970648Z" + "iopub.execute_input": "2024-09-06T19:38:42.721153Z", + "iopub.status.busy": "2024-09-06T19:38:42.720797Z", + "iopub.status.idle": "2024-09-06T19:38:42.746197Z", + "shell.execute_reply": "2024-09-06T19:38:42.745739Z" } }, "outputs": [], @@ -738,10 +738,10 @@ "id": "6ca92617", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:45.973422Z", - "iopub.status.busy": "2024-09-05T19:38:45.973114Z", - "iopub.status.idle": "2024-09-05T19:38:47.957844Z", - "shell.execute_reply": "2024-09-05T19:38:47.957281Z" + "iopub.execute_input": "2024-09-06T19:38:42.748111Z", + "iopub.status.busy": "2024-09-06T19:38:42.747776Z", + "iopub.status.idle": "2024-09-06T19:38:44.708904Z", + "shell.execute_reply": "2024-09-06T19:38:44.708307Z" } }, "outputs": [], @@ -771,10 +771,10 @@ "id": "bf945113", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.960323Z", - "iopub.status.busy": "2024-09-05T19:38:47.960036Z", - "iopub.status.idle": "2024-09-05T19:38:47.966782Z", - "shell.execute_reply": "2024-09-05T19:38:47.966212Z" + "iopub.execute_input": "2024-09-06T19:38:44.711480Z", + "iopub.status.busy": "2024-09-06T19:38:44.710993Z", + "iopub.status.idle": "2024-09-06T19:38:44.717750Z", + "shell.execute_reply": "2024-09-06T19:38:44.717182Z" }, "scrolled": true }, @@ -885,10 +885,10 @@ "id": "14251ee0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.969001Z", - "iopub.status.busy": "2024-09-05T19:38:47.968670Z", - "iopub.status.idle": "2024-09-05T19:38:47.982271Z", - "shell.execute_reply": "2024-09-05T19:38:47.981722Z" + "iopub.execute_input": "2024-09-06T19:38:44.719963Z", + "iopub.status.busy": "2024-09-06T19:38:44.719631Z", + "iopub.status.idle": "2024-09-06T19:38:44.732695Z", + "shell.execute_reply": "2024-09-06T19:38:44.732259Z" } }, "outputs": [ @@ -1138,10 +1138,10 @@ "id": "efe16638", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.984470Z", - "iopub.status.busy": "2024-09-05T19:38:47.984002Z", - "iopub.status.idle": "2024-09-05T19:38:47.990230Z", - "shell.execute_reply": "2024-09-05T19:38:47.989775Z" + "iopub.execute_input": "2024-09-06T19:38:44.734719Z", + "iopub.status.busy": "2024-09-06T19:38:44.734386Z", + "iopub.status.idle": "2024-09-06T19:38:44.740630Z", + "shell.execute_reply": "2024-09-06T19:38:44.740080Z" }, "scrolled": true }, @@ -1315,10 +1315,10 @@ "id": "abd0fb0b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.992351Z", - "iopub.status.busy": "2024-09-05T19:38:47.992012Z", - "iopub.status.idle": "2024-09-05T19:38:47.994554Z", - "shell.execute_reply": "2024-09-05T19:38:47.994115Z" + "iopub.execute_input": "2024-09-06T19:38:44.742715Z", + "iopub.status.busy": "2024-09-06T19:38:44.742407Z", + "iopub.status.idle": "2024-09-06T19:38:44.745203Z", + "shell.execute_reply": "2024-09-06T19:38:44.744635Z" } }, "outputs": [], @@ -1340,10 +1340,10 @@ "id": "cdf061df", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:47.996534Z", - "iopub.status.busy": "2024-09-05T19:38:47.996204Z", - "iopub.status.idle": "2024-09-05T19:38:47.999737Z", - "shell.execute_reply": "2024-09-05T19:38:47.999187Z" + "iopub.execute_input": "2024-09-06T19:38:44.747300Z", + "iopub.status.busy": "2024-09-06T19:38:44.746906Z", + "iopub.status.idle": "2024-09-06T19:38:44.750594Z", + "shell.execute_reply": "2024-09-06T19:38:44.750021Z" }, "scrolled": true }, @@ -1395,10 +1395,10 @@ "id": "08949890", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.001908Z", - "iopub.status.busy": "2024-09-05T19:38:48.001582Z", - "iopub.status.idle": "2024-09-05T19:38:48.003999Z", - "shell.execute_reply": "2024-09-05T19:38:48.003506Z" + "iopub.execute_input": "2024-09-06T19:38:44.752864Z", + "iopub.status.busy": "2024-09-06T19:38:44.752447Z", + "iopub.status.idle": "2024-09-06T19:38:44.755290Z", + "shell.execute_reply": "2024-09-06T19:38:44.754743Z" } }, "outputs": [], @@ -1422,10 +1422,10 @@ "id": "6948b073", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.006110Z", - "iopub.status.busy": "2024-09-05T19:38:48.005783Z", - "iopub.status.idle": "2024-09-05T19:38:48.009935Z", - "shell.execute_reply": "2024-09-05T19:38:48.009399Z" + "iopub.execute_input": "2024-09-06T19:38:44.757347Z", + "iopub.status.busy": "2024-09-06T19:38:44.757015Z", + "iopub.status.idle": "2024-09-06T19:38:44.761164Z", + "shell.execute_reply": "2024-09-06T19:38:44.760669Z" } }, "outputs": [ @@ -1480,10 +1480,10 @@ "id": "6f8e6914", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.012094Z", - "iopub.status.busy": "2024-09-05T19:38:48.011735Z", - "iopub.status.idle": "2024-09-05T19:38:48.039799Z", - "shell.execute_reply": "2024-09-05T19:38:48.039323Z" + "iopub.execute_input": "2024-09-06T19:38:44.763225Z", + "iopub.status.busy": "2024-09-06T19:38:44.762830Z", + "iopub.status.idle": "2024-09-06T19:38:44.791503Z", + "shell.execute_reply": "2024-09-06T19:38:44.790922Z" } }, "outputs": [], @@ -1526,10 +1526,10 @@ "id": "b806d2ea", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:48.042183Z", - "iopub.status.busy": "2024-09-05T19:38:48.041817Z", - "iopub.status.idle": "2024-09-05T19:38:48.046713Z", - "shell.execute_reply": "2024-09-05T19:38:48.046238Z" + "iopub.execute_input": "2024-09-06T19:38:44.793778Z", + "iopub.status.busy": "2024-09-06T19:38:44.793374Z", + "iopub.status.idle": "2024-09-06T19:38:44.798051Z", + "shell.execute_reply": "2024-09-06T19:38:44.797497Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/multilabel_classification.ipynb b/master/tutorials/multilabel_classification.ipynb index 1509def8d..7626ff8d8 100644 --- a/master/tutorials/multilabel_classification.ipynb +++ b/master/tutorials/multilabel_classification.ipynb @@ -64,10 +64,10 @@ "id": "7383d024-8273-4039-bccd-aab3020d331f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:51.101575Z", - "iopub.status.busy": "2024-09-05T19:38:51.101202Z", - "iopub.status.idle": "2024-09-05T19:38:52.356767Z", - "shell.execute_reply": "2024-09-05T19:38:52.356160Z" + "iopub.execute_input": "2024-09-06T19:38:47.803342Z", + "iopub.status.busy": "2024-09-06T19:38:47.803172Z", + "iopub.status.idle": "2024-09-06T19:38:49.010459Z", + "shell.execute_reply": "2024-09-06T19:38:49.009894Z" }, "nbsphinx": "hidden" }, @@ -79,7 +79,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -105,10 +105,10 @@ "id": "bf9101d8-b1a9-4305-b853-45aaf3d67a69", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:52.359268Z", - "iopub.status.busy": "2024-09-05T19:38:52.358948Z", - "iopub.status.idle": "2024-09-05T19:38:52.562776Z", - "shell.execute_reply": "2024-09-05T19:38:52.562204Z" + "iopub.execute_input": "2024-09-06T19:38:49.013219Z", + "iopub.status.busy": "2024-09-06T19:38:49.012725Z", + "iopub.status.idle": "2024-09-06T19:38:49.210289Z", + "shell.execute_reply": "2024-09-06T19:38:49.209783Z" } }, "outputs": [], @@ -268,10 +268,10 @@ "id": "e8ff5c2f-bd52-44aa-b307-b2b634147c68", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:52.565447Z", - "iopub.status.busy": "2024-09-05T19:38:52.565141Z", - "iopub.status.idle": "2024-09-05T19:38:52.579312Z", - "shell.execute_reply": "2024-09-05T19:38:52.578691Z" + "iopub.execute_input": "2024-09-06T19:38:49.212873Z", + "iopub.status.busy": "2024-09-06T19:38:49.212501Z", + "iopub.status.idle": "2024-09-06T19:38:49.226305Z", + "shell.execute_reply": "2024-09-06T19:38:49.225843Z" }, "nbsphinx": "hidden" }, @@ -407,10 +407,10 @@ "id": "dac65d3b-51e8-4682-b829-beab610b56d6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:52.581436Z", - "iopub.status.busy": "2024-09-05T19:38:52.581245Z", - "iopub.status.idle": "2024-09-05T19:38:55.240942Z", - "shell.execute_reply": "2024-09-05T19:38:55.240413Z" + "iopub.execute_input": "2024-09-06T19:38:49.228339Z", + "iopub.status.busy": "2024-09-06T19:38:49.227999Z", + "iopub.status.idle": "2024-09-06T19:38:51.870134Z", + "shell.execute_reply": "2024-09-06T19:38:51.869617Z" } }, "outputs": [ @@ -454,10 +454,10 @@ "id": "b5fa99a9-2583-4cd0-9d40-015f698cdb23", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:55.243248Z", - "iopub.status.busy": "2024-09-05T19:38:55.242887Z", - "iopub.status.idle": "2024-09-05T19:38:56.591285Z", - "shell.execute_reply": "2024-09-05T19:38:56.590684Z" + "iopub.execute_input": "2024-09-06T19:38:51.872305Z", + "iopub.status.busy": "2024-09-06T19:38:51.872107Z", + "iopub.status.idle": "2024-09-06T19:38:53.221496Z", + "shell.execute_reply": "2024-09-06T19:38:53.220930Z" } }, "outputs": [], @@ -499,10 +499,10 @@ "id": "ac1a60df", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:56.593787Z", - "iopub.status.busy": "2024-09-05T19:38:56.593425Z", - "iopub.status.idle": "2024-09-05T19:38:56.597557Z", - "shell.execute_reply": "2024-09-05T19:38:56.597077Z" + "iopub.execute_input": "2024-09-06T19:38:53.223970Z", + "iopub.status.busy": "2024-09-06T19:38:53.223773Z", + "iopub.status.idle": "2024-09-06T19:38:53.227537Z", + "shell.execute_reply": "2024-09-06T19:38:53.226991Z" } }, "outputs": [ @@ -544,10 +544,10 @@ "id": "d09115b6-ad44-474f-9c8a-85a459586439", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:56.599600Z", - "iopub.status.busy": "2024-09-05T19:38:56.599258Z", - "iopub.status.idle": "2024-09-05T19:38:58.742931Z", - "shell.execute_reply": "2024-09-05T19:38:58.742243Z" + "iopub.execute_input": "2024-09-06T19:38:53.229541Z", + "iopub.status.busy": "2024-09-06T19:38:53.229360Z", + "iopub.status.idle": "2024-09-06T19:38:55.301308Z", + "shell.execute_reply": "2024-09-06T19:38:55.300645Z" } }, "outputs": [ @@ -594,10 +594,10 @@ "id": "c18dd83b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:58.745759Z", - "iopub.status.busy": "2024-09-05T19:38:58.745328Z", - "iopub.status.idle": "2024-09-05T19:38:58.754011Z", - "shell.execute_reply": "2024-09-05T19:38:58.753467Z" + "iopub.execute_input": "2024-09-06T19:38:55.303915Z", + "iopub.status.busy": "2024-09-06T19:38:55.303372Z", + "iopub.status.idle": "2024-09-06T19:38:55.311571Z", + "shell.execute_reply": "2024-09-06T19:38:55.311093Z" } }, "outputs": [ @@ -633,10 +633,10 @@ "id": "fffa88f6-84d7-45fe-8214-0e22079a06d1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:38:58.756118Z", - "iopub.status.busy": "2024-09-05T19:38:58.755779Z", - "iopub.status.idle": "2024-09-05T19:39:01.611717Z", - "shell.execute_reply": "2024-09-05T19:39:01.611077Z" + "iopub.execute_input": "2024-09-06T19:38:55.313528Z", + "iopub.status.busy": "2024-09-06T19:38:55.313186Z", + "iopub.status.idle": "2024-09-06T19:38:58.079187Z", + "shell.execute_reply": "2024-09-06T19:38:58.078607Z" } }, "outputs": [ @@ -671,10 +671,10 @@ "id": "c1198575", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:01.613917Z", - "iopub.status.busy": "2024-09-05T19:39:01.613717Z", - "iopub.status.idle": "2024-09-05T19:39:01.617617Z", - "shell.execute_reply": "2024-09-05T19:39:01.617137Z" + "iopub.execute_input": "2024-09-06T19:38:58.081586Z", + "iopub.status.busy": "2024-09-06T19:38:58.081221Z", + "iopub.status.idle": "2024-09-06T19:38:58.084505Z", + "shell.execute_reply": "2024-09-06T19:38:58.083969Z" } }, "outputs": [ @@ -721,10 +721,10 @@ "id": "49161b19-7625-4fb7-add9-607d91a7eca1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:01.619758Z", - "iopub.status.busy": "2024-09-05T19:39:01.619426Z", - "iopub.status.idle": "2024-09-05T19:39:01.622958Z", - "shell.execute_reply": "2024-09-05T19:39:01.622500Z" + "iopub.execute_input": "2024-09-06T19:38:58.086650Z", + "iopub.status.busy": "2024-09-06T19:38:58.086312Z", + "iopub.status.idle": "2024-09-06T19:38:58.089596Z", + "shell.execute_reply": "2024-09-06T19:38:58.089116Z" } }, "outputs": [], @@ -769,10 +769,10 @@ "id": "d1a2c008", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:01.625218Z", - "iopub.status.busy": "2024-09-05T19:39:01.624881Z", - "iopub.status.idle": "2024-09-05T19:39:01.628607Z", - "shell.execute_reply": "2024-09-05T19:39:01.628173Z" + "iopub.execute_input": "2024-09-06T19:38:58.091573Z", + "iopub.status.busy": "2024-09-06T19:38:58.091252Z", + "iopub.status.idle": "2024-09-06T19:38:58.095249Z", + "shell.execute_reply": "2024-09-06T19:38:58.094671Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/object_detection.ipynb b/master/tutorials/object_detection.ipynb index f25e1e63d..d7703f8af 100644 --- a/master/tutorials/object_detection.ipynb +++ b/master/tutorials/object_detection.ipynb @@ -70,10 +70,10 @@ "id": "0ba0dc70", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:04.529066Z", - "iopub.status.busy": "2024-09-05T19:39:04.528893Z", - "iopub.status.idle": "2024-09-05T19:39:05.764668Z", - "shell.execute_reply": "2024-09-05T19:39:05.764097Z" + "iopub.execute_input": "2024-09-06T19:39:00.696602Z", + "iopub.status.busy": "2024-09-06T19:39:00.696186Z", + "iopub.status.idle": "2024-09-06T19:39:01.907009Z", + "shell.execute_reply": "2024-09-06T19:39:01.906453Z" }, "nbsphinx": "hidden" }, @@ -83,7 +83,7 @@ "dependencies = [\"cleanlab\", \"matplotlib\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -109,10 +109,10 @@ "id": "c90449c8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:05.767346Z", - "iopub.status.busy": "2024-09-05T19:39:05.766811Z", - "iopub.status.idle": "2024-09-05T19:39:06.974939Z", - "shell.execute_reply": "2024-09-05T19:39:06.974219Z" + "iopub.execute_input": "2024-09-06T19:39:01.909568Z", + "iopub.status.busy": "2024-09-06T19:39:01.909050Z", + "iopub.status.idle": "2024-09-06T19:39:04.631163Z", + "shell.execute_reply": "2024-09-06T19:39:04.630426Z" } }, "outputs": [], @@ -130,10 +130,10 @@ "id": "df8be4c6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:06.977709Z", - "iopub.status.busy": "2024-09-05T19:39:06.977293Z", - "iopub.status.idle": "2024-09-05T19:39:06.980536Z", - "shell.execute_reply": "2024-09-05T19:39:06.980078Z" + "iopub.execute_input": "2024-09-06T19:39:04.633881Z", + "iopub.status.busy": "2024-09-06T19:39:04.633499Z", + "iopub.status.idle": "2024-09-06T19:39:04.637616Z", + "shell.execute_reply": "2024-09-06T19:39:04.637024Z" } }, "outputs": [], @@ -169,10 +169,10 @@ "id": "2e9ffd6f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:06.982537Z", - "iopub.status.busy": "2024-09-05T19:39:06.982351Z", - "iopub.status.idle": "2024-09-05T19:39:06.989001Z", - "shell.execute_reply": "2024-09-05T19:39:06.988551Z" + "iopub.execute_input": "2024-09-06T19:39:04.639736Z", + "iopub.status.busy": "2024-09-06T19:39:04.639557Z", + "iopub.status.idle": "2024-09-06T19:39:04.646473Z", + "shell.execute_reply": "2024-09-06T19:39:04.646014Z" } }, "outputs": [], @@ -198,10 +198,10 @@ "id": "56705562", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:06.990912Z", - "iopub.status.busy": "2024-09-05T19:39:06.990730Z", - "iopub.status.idle": "2024-09-05T19:39:07.491100Z", - "shell.execute_reply": "2024-09-05T19:39:07.490495Z" + "iopub.execute_input": "2024-09-06T19:39:04.648396Z", + "iopub.status.busy": "2024-09-06T19:39:04.648219Z", + "iopub.status.idle": "2024-09-06T19:39:05.143459Z", + "shell.execute_reply": "2024-09-06T19:39:05.142840Z" }, "scrolled": true }, @@ -242,10 +242,10 @@ "id": "b08144d7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:07.494085Z", - "iopub.status.busy": "2024-09-05T19:39:07.493615Z", - "iopub.status.idle": "2024-09-05T19:39:07.499172Z", - "shell.execute_reply": "2024-09-05T19:39:07.498620Z" + "iopub.execute_input": "2024-09-06T19:39:05.146327Z", + "iopub.status.busy": "2024-09-06T19:39:05.146000Z", + "iopub.status.idle": "2024-09-06T19:39:05.151442Z", + "shell.execute_reply": "2024-09-06T19:39:05.150979Z" } }, "outputs": [ @@ -497,10 +497,10 @@ "id": "3d70bec6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:07.501404Z", - "iopub.status.busy": "2024-09-05T19:39:07.500976Z", - "iopub.status.idle": "2024-09-05T19:39:07.504945Z", - "shell.execute_reply": "2024-09-05T19:39:07.504506Z" + "iopub.execute_input": "2024-09-06T19:39:05.153485Z", + "iopub.status.busy": "2024-09-06T19:39:05.153173Z", + "iopub.status.idle": "2024-09-06T19:39:05.157137Z", + "shell.execute_reply": "2024-09-06T19:39:05.156658Z" } }, "outputs": [ @@ -557,10 +557,10 @@ "id": "4caa635d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:07.507284Z", - "iopub.status.busy": "2024-09-05T19:39:07.506712Z", - "iopub.status.idle": "2024-09-05T19:39:08.384414Z", - "shell.execute_reply": "2024-09-05T19:39:08.383806Z" + "iopub.execute_input": "2024-09-06T19:39:05.159200Z", + "iopub.status.busy": "2024-09-06T19:39:05.158859Z", + "iopub.status.idle": "2024-09-06T19:39:06.019168Z", + "shell.execute_reply": "2024-09-06T19:39:06.018545Z" } }, "outputs": [ @@ -616,10 +616,10 @@ "id": "a9b4c590", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:08.386698Z", - "iopub.status.busy": "2024-09-05T19:39:08.386502Z", - "iopub.status.idle": "2024-09-05T19:39:08.587093Z", - "shell.execute_reply": "2024-09-05T19:39:08.586454Z" + "iopub.execute_input": "2024-09-06T19:39:06.021668Z", + "iopub.status.busy": "2024-09-06T19:39:06.021221Z", + "iopub.status.idle": "2024-09-06T19:39:06.237090Z", + "shell.execute_reply": "2024-09-06T19:39:06.236553Z" } }, "outputs": [ @@ -627,14 +627,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "Pruning 0 predictions out of 138 using threshold==0.0. These predictions are no longer considered as potential candidates for identifying label issues as their similarity with the given labels is no longer considered." - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n" + "Pruning 0 predictions out of 138 using threshold==0.0. These predictions are no longer considered as potential candidates for identifying label issues as their similarity with the given labels is no longer considered.\n" ] }, { @@ -667,10 +660,10 @@ "id": "ffd9ebcc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:08.589453Z", - "iopub.status.busy": "2024-09-05T19:39:08.589096Z", - "iopub.status.idle": "2024-09-05T19:39:08.593402Z", - "shell.execute_reply": "2024-09-05T19:39:08.592837Z" + "iopub.execute_input": "2024-09-06T19:39:06.239343Z", + "iopub.status.busy": "2024-09-06T19:39:06.238930Z", + "iopub.status.idle": "2024-09-06T19:39:06.243194Z", + "shell.execute_reply": "2024-09-06T19:39:06.242735Z" } }, "outputs": [ @@ -707,10 +700,10 @@ "id": "4dd46d67", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:08.595644Z", - "iopub.status.busy": "2024-09-05T19:39:08.595324Z", - "iopub.status.idle": "2024-09-05T19:39:09.054015Z", - "shell.execute_reply": "2024-09-05T19:39:09.053402Z" + "iopub.execute_input": "2024-09-06T19:39:06.245282Z", + "iopub.status.busy": "2024-09-06T19:39:06.244951Z", + "iopub.status.idle": "2024-09-06T19:39:06.697627Z", + "shell.execute_reply": "2024-09-06T19:39:06.697015Z" } }, "outputs": [ @@ -769,10 +762,10 @@ "id": "ceec2394", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:09.057259Z", - "iopub.status.busy": "2024-09-05T19:39:09.056867Z", - "iopub.status.idle": "2024-09-05T19:39:09.390945Z", - "shell.execute_reply": "2024-09-05T19:39:09.390389Z" + "iopub.execute_input": "2024-09-06T19:39:06.700924Z", + "iopub.status.busy": "2024-09-06T19:39:06.700539Z", + "iopub.status.idle": "2024-09-06T19:39:07.035472Z", + "shell.execute_reply": "2024-09-06T19:39:07.034925Z" } }, "outputs": [ @@ -819,10 +812,10 @@ "id": "94f82b0d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:09.393790Z", - "iopub.status.busy": "2024-09-05T19:39:09.393435Z", - "iopub.status.idle": "2024-09-05T19:39:09.732820Z", - "shell.execute_reply": "2024-09-05T19:39:09.732244Z" + "iopub.execute_input": "2024-09-06T19:39:07.038382Z", + "iopub.status.busy": "2024-09-06T19:39:07.038001Z", + "iopub.status.idle": "2024-09-06T19:39:07.401507Z", + "shell.execute_reply": "2024-09-06T19:39:07.400918Z" } }, "outputs": [ @@ -869,10 +862,10 @@ "id": "1ea18c5d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:09.736269Z", - "iopub.status.busy": "2024-09-05T19:39:09.735858Z", - "iopub.status.idle": "2024-09-05T19:39:10.156424Z", - "shell.execute_reply": "2024-09-05T19:39:10.155802Z" + "iopub.execute_input": "2024-09-06T19:39:07.404511Z", + "iopub.status.busy": "2024-09-06T19:39:07.404090Z", + "iopub.status.idle": "2024-09-06T19:39:07.846501Z", + "shell.execute_reply": "2024-09-06T19:39:07.845952Z" } }, "outputs": [ @@ -932,10 +925,10 @@ "id": "7e770d23", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:10.161076Z", - "iopub.status.busy": "2024-09-05T19:39:10.160681Z", - "iopub.status.idle": "2024-09-05T19:39:10.609859Z", - "shell.execute_reply": "2024-09-05T19:39:10.609188Z" + "iopub.execute_input": "2024-09-06T19:39:07.851154Z", + "iopub.status.busy": "2024-09-06T19:39:07.850706Z", + "iopub.status.idle": "2024-09-06T19:39:08.296657Z", + "shell.execute_reply": "2024-09-06T19:39:08.296063Z" } }, "outputs": [ @@ -978,10 +971,10 @@ "id": "57e84a27", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:10.612839Z", - "iopub.status.busy": "2024-09-05T19:39:10.612663Z", - "iopub.status.idle": "2024-09-05T19:39:10.829289Z", - "shell.execute_reply": "2024-09-05T19:39:10.828816Z" + "iopub.execute_input": "2024-09-06T19:39:08.300087Z", + "iopub.status.busy": "2024-09-06T19:39:08.299623Z", + "iopub.status.idle": "2024-09-06T19:39:08.513354Z", + "shell.execute_reply": "2024-09-06T19:39:08.512755Z" } }, "outputs": [ @@ -1024,10 +1017,10 @@ "id": "0302818a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:10.831596Z", - "iopub.status.busy": "2024-09-05T19:39:10.831265Z", - "iopub.status.idle": "2024-09-05T19:39:11.014176Z", - "shell.execute_reply": "2024-09-05T19:39:11.013572Z" + "iopub.execute_input": "2024-09-06T19:39:08.515572Z", + "iopub.status.busy": "2024-09-06T19:39:08.515168Z", + "iopub.status.idle": "2024-09-06T19:39:08.694654Z", + "shell.execute_reply": "2024-09-06T19:39:08.694085Z" } }, "outputs": [ @@ -1074,10 +1067,10 @@ "id": "5cacec81-2adf-46a8-82c5-7ec0185d4356", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:11.016423Z", - "iopub.status.busy": "2024-09-05T19:39:11.016076Z", - "iopub.status.idle": "2024-09-05T19:39:11.018873Z", - "shell.execute_reply": "2024-09-05T19:39:11.018432Z" + "iopub.execute_input": "2024-09-06T19:39:08.697419Z", + "iopub.status.busy": "2024-09-06T19:39:08.697030Z", + "iopub.status.idle": "2024-09-06T19:39:08.699909Z", + "shell.execute_reply": "2024-09-06T19:39:08.699453Z" } }, "outputs": [], @@ -1097,10 +1090,10 @@ "id": "3335b8a3-d0b4-415a-a97d-c203088a124e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:11.020936Z", - "iopub.status.busy": "2024-09-05T19:39:11.020606Z", - "iopub.status.idle": "2024-09-05T19:39:11.923610Z", - "shell.execute_reply": "2024-09-05T19:39:11.922981Z" + "iopub.execute_input": "2024-09-06T19:39:08.701948Z", + "iopub.status.busy": "2024-09-06T19:39:08.701622Z", + "iopub.status.idle": "2024-09-06T19:39:09.635839Z", + "shell.execute_reply": "2024-09-06T19:39:09.635227Z" } }, "outputs": [ @@ -1179,10 +1172,10 @@ "id": "9d4b7677-6ebd-447d-b0a1-76e094686628", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:11.925987Z", - "iopub.status.busy": "2024-09-05T19:39:11.925773Z", - "iopub.status.idle": "2024-09-05T19:39:12.101177Z", - "shell.execute_reply": "2024-09-05T19:39:12.100675Z" + "iopub.execute_input": "2024-09-06T19:39:09.637949Z", + "iopub.status.busy": "2024-09-06T19:39:09.637773Z", + "iopub.status.idle": "2024-09-06T19:39:09.767317Z", + "shell.execute_reply": "2024-09-06T19:39:09.766833Z" } }, "outputs": [ @@ -1221,10 +1214,10 @@ "id": "59d7ee39-3785-434b-8680-9133014851cd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:12.103362Z", - "iopub.status.busy": "2024-09-05T19:39:12.103006Z", - "iopub.status.idle": "2024-09-05T19:39:12.232243Z", - "shell.execute_reply": "2024-09-05T19:39:12.231719Z" + "iopub.execute_input": "2024-09-06T19:39:09.769238Z", + "iopub.status.busy": "2024-09-06T19:39:09.769067Z", + "iopub.status.idle": "2024-09-06T19:39:09.969227Z", + "shell.execute_reply": "2024-09-06T19:39:09.968617Z" } }, "outputs": [], @@ -1273,10 +1266,10 @@ "id": "47b6a8ff-7a58-4a1f-baee-e6cfe7a85a6d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:12.234678Z", - "iopub.status.busy": "2024-09-05T19:39:12.234336Z", - "iopub.status.idle": "2024-09-05T19:39:12.941539Z", - "shell.execute_reply": "2024-09-05T19:39:12.940835Z" + "iopub.execute_input": "2024-09-06T19:39:09.971377Z", + "iopub.status.busy": "2024-09-06T19:39:09.971032Z", + "iopub.status.idle": "2024-09-06T19:39:10.691109Z", + "shell.execute_reply": "2024-09-06T19:39:10.690570Z" } }, "outputs": [ @@ -1358,10 +1351,10 @@ "id": "8ce74938", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:12.943960Z", - "iopub.status.busy": "2024-09-05T19:39:12.943615Z", - "iopub.status.idle": "2024-09-05T19:39:12.947337Z", - "shell.execute_reply": "2024-09-05T19:39:12.946788Z" + "iopub.execute_input": "2024-09-06T19:39:10.693528Z", + "iopub.status.busy": "2024-09-06T19:39:10.693149Z", + "iopub.status.idle": "2024-09-06T19:39:10.697005Z", + "shell.execute_reply": "2024-09-06T19:39:10.696512Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/outliers.html b/master/tutorials/outliers.html index f9a88bab7..16e86eb51 100644 --- a/master/tutorials/outliers.html +++ b/master/tutorials/outliers.html @@ -784,7 +784,7 @@

    2. Pre-process the Cifar10 dataset
    -100%|██████████| 170498071/170498071 [00:01<00:00, 99832064.92it/s]
    +100%|██████████| 170498071/170498071 [00:03<00:00, 46456493.64it/s]
     

    -
    +
    @@ -1134,7 +1134,7 @@

    Spending too much time on data quality?Cleanlab Studio – an automated platform to find and fix issues in your dataset, 100x faster and more accurately. Cleanlab Studio automatically runs optimized data quality algorithms from this package on top of cutting-edge AutoML & Foundation models fit to your data, and helps you fix detected issues via a smart data correction interface. Try it for free!

    The modern AI pipeline automated with Cleanlab Studio

    diff --git a/master/tutorials/outliers.ipynb b/master/tutorials/outliers.ipynb index f57af3305..ab02f6a16 100644 --- a/master/tutorials/outliers.ipynb +++ b/master/tutorials/outliers.ipynb @@ -109,10 +109,10 @@ "id": "2bbebfc8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:15.405392Z", - "iopub.status.busy": "2024-09-05T19:39:15.405034Z", - "iopub.status.idle": "2024-09-05T19:39:18.302373Z", - "shell.execute_reply": "2024-09-05T19:39:18.301795Z" + "iopub.execute_input": "2024-09-06T19:39:13.100046Z", + "iopub.status.busy": "2024-09-06T19:39:13.099622Z", + "iopub.status.idle": "2024-09-06T19:39:15.925691Z", + "shell.execute_reply": "2024-09-06T19:39:15.925058Z" }, "nbsphinx": "hidden" }, @@ -125,7 +125,7 @@ "dependencies = [\"matplotlib\", \"torch\", \"torchvision\", \"timm\", \"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -159,10 +159,10 @@ "id": "4396f544", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:18.305069Z", - "iopub.status.busy": "2024-09-05T19:39:18.304571Z", - "iopub.status.idle": "2024-09-05T19:39:18.636404Z", - "shell.execute_reply": "2024-09-05T19:39:18.635775Z" + "iopub.execute_input": "2024-09-06T19:39:15.928762Z", + "iopub.status.busy": "2024-09-06T19:39:15.928196Z", + "iopub.status.idle": "2024-09-06T19:39:16.252610Z", + "shell.execute_reply": "2024-09-06T19:39:16.252054Z" } }, "outputs": [], @@ -188,10 +188,10 @@ "id": "3792f82e", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:18.639073Z", - "iopub.status.busy": "2024-09-05T19:39:18.638746Z", - "iopub.status.idle": "2024-09-05T19:39:18.643058Z", - "shell.execute_reply": "2024-09-05T19:39:18.642503Z" + "iopub.execute_input": "2024-09-06T19:39:16.255233Z", + "iopub.status.busy": "2024-09-06T19:39:16.254751Z", + "iopub.status.idle": "2024-09-06T19:39:16.259089Z", + "shell.execute_reply": "2024-09-06T19:39:16.258660Z" }, "nbsphinx": "hidden" }, @@ -225,10 +225,10 @@ "id": "fd853a54", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:18.645337Z", - "iopub.status.busy": "2024-09-05T19:39:18.644989Z", - "iopub.status.idle": "2024-09-05T19:39:23.136533Z", - "shell.execute_reply": "2024-09-05T19:39:23.136022Z" + "iopub.execute_input": "2024-09-06T19:39:16.261376Z", + "iopub.status.busy": "2024-09-06T19:39:16.260945Z", + "iopub.status.idle": "2024-09-06T19:39:23.300858Z", + "shell.execute_reply": "2024-09-06T19:39:23.300244Z" } }, "outputs": [ @@ -252,7 +252,7 @@ "output_type": "stream", "text": [ "\r", - " 1%| | 917504/170498071 [00:00<00:20, 8230282.28it/s]" + " 0%| | 32768/170498071 [00:00<09:50, 288460.96it/s]" ] }, { @@ -260,7 +260,7 @@ "output_type": "stream", "text": [ "\r", - " 6%|▌ | 10518528/170498071 [00:00<00:02, 57525326.14it/s]" + " 0%| | 229376/170498071 [00:00<02:31, 1124759.70it/s]" ] }, { @@ -268,7 +268,7 @@ "output_type": "stream", "text": [ "\r", - " 12%|█▏ | 21200896/170498071 [00:00<00:01, 79443214.95it/s]" + " 1%| | 884736/170498071 [00:00<00:52, 3225591.40it/s]" ] }, { @@ -276,7 +276,7 @@ "output_type": "stream", "text": [ "\r", - " 19%|█▊ | 31883264/170498071 [00:00<00:01, 90066862.77it/s]" + " 2%|▏ | 3571712/170498071 [00:00<00:14, 11574707.14it/s]" ] }, { @@ -284,7 +284,7 @@ "output_type": "stream", "text": [ "\r", - " 25%|██▌ | 42795008/170498071 [00:00<00:01, 96847189.42it/s]" + " 6%|▌ | 9633792/170498071 [00:00<00:06, 25807611.79it/s]" ] }, { @@ -292,7 +292,7 @@ "output_type": "stream", "text": [ "\r", - " 31%|███▏ | 53608448/170498071 [00:00<00:01, 100648722.32it/s]" + " 9%|▉ | 15892480/170498071 [00:00<00:04, 35393042.76it/s]" ] }, { @@ -300,7 +300,7 @@ "output_type": "stream", "text": [ "\r", - " 38%|███▊ | 64421888/170498071 [00:00<00:01, 103069662.64it/s]" + " 13%|█▎ | 22052864/170498071 [00:00<00:03, 41375940.12it/s]" ] }, { @@ -308,7 +308,7 @@ "output_type": "stream", "text": [ "\r", - " 44%|████▍ | 75497472/170498071 [00:00<00:00, 105497848.58it/s]" + " 16%|█▋ | 27918336/170498071 [00:00<00:03, 46336247.02it/s]" ] }, { @@ -316,7 +316,7 @@ "output_type": "stream", "text": [ "\r", - " 51%|█████ | 86540288/170498071 [00:00<00:00, 106981473.95it/s]" + " 19%|█▉ | 32604160/170498071 [00:01<00:03, 45410241.06it/s]" ] }, { @@ -324,7 +324,7 @@ "output_type": "stream", "text": [ "\r", - " 57%|█████▋ | 97484800/170498071 [00:01<00:00, 107701030.20it/s]" + " 22%|██▏ | 37978112/170498071 [00:01<00:02, 46512554.13it/s]" ] }, { @@ -332,7 +332,7 @@ "output_type": "stream", "text": [ "\r", - " 64%|██████▎ | 108363776/170498071 [00:01<00:00, 107950290.42it/s]" + " 26%|██▌ | 44072960/170498071 [00:01<00:02, 50196826.35it/s]" ] }, { @@ -340,7 +340,7 @@ "output_type": "stream", "text": [ "\r", - " 70%|██████▉ | 119177216/170498071 [00:01<00:00, 106306696.89it/s]" + " 29%|██▉ | 49217536/170498071 [00:01<00:02, 50515326.91it/s]" ] }, { @@ -348,7 +348,7 @@ "output_type": "stream", "text": [ "\r", - " 76%|███████▌ | 129826816/170498071 [00:01<00:00, 105708288.67it/s]" + " 32%|███▏ | 54296576/170498071 [00:01<00:02, 49331301.44it/s]" ] }, { @@ -356,7 +356,7 @@ "output_type": "stream", "text": [ "\r", - " 82%|████████▏ | 140410880/170498071 [00:01<00:00, 105156306.35it/s]" + " 35%|███▌ | 60129280/170498071 [00:01<00:02, 51745509.08it/s]" ] }, { @@ -364,7 +364,7 @@ "output_type": "stream", "text": [ "\r", - " 89%|████████▉ | 151355392/170498071 [00:01<00:00, 106351362.25it/s]" + " 38%|███▊ | 65339392/170498071 [00:01<00:02, 51498978.62it/s]" ] }, { @@ -372,7 +372,7 @@ "output_type": "stream", "text": [ "\r", - " 95%|█████████▌| 162004992/170498071 [00:01<00:00, 105346005.50it/s]" + " 41%|████▏ | 70516736/170498071 [00:01<00:01, 50172708.54it/s]" ] }, { @@ -380,7 +380,151 @@ "output_type": "stream", "text": [ "\r", - "100%|██████████| 170498071/170498071 [00:01<00:00, 99832064.92it/s] " + " 45%|████▍ | 76251136/170498071 [00:01<00:01, 52173671.62it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 48%|████▊ | 81559552/170498071 [00:01<00:01, 52429909.15it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 51%|█████ | 86835200/170498071 [00:02<00:01, 50316420.17it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 54%|█████▍ | 92438528/170498071 [00:02<00:01, 51729464.30it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 57%|█████▋ | 97878016/170498071 [00:02<00:01, 52469802.74it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 61%|██████ | 103153664/170498071 [00:02<00:01, 51263628.20it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 64%|██████▎ | 108396544/170498071 [00:02<00:01, 51439851.19it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 67%|██████▋ | 114130944/170498071 [00:02<00:01, 53113973.23it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 70%|███████ | 119472128/170498071 [00:02<00:00, 51879482.02it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 73%|███████▎ | 124682240/170498071 [00:02<00:00, 50047274.18it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 77%|███████▋ | 130547712/170498071 [00:02<00:00, 52494107.90it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 80%|███████▉ | 135823360/170498071 [00:03<00:00, 52004524.51it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 83%|████████▎ | 141066240/170498071 [00:03<00:00, 50983301.18it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 86%|████████▌ | 146636800/170498071 [00:03<00:00, 52034590.57it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 89%|████████▉ | 151879680/170498071 [00:03<00:00, 52140968.39it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 92%|█████████▏| 157122560/170498071 [00:03<00:00, 50962142.96it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 95%|█████████▌| 162463744/170498071 [00:03<00:00, 51228143.58it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + " 99%|█████████▊| 168329216/170498071 [00:03<00:00, 53366850.10it/s]" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\r", + "100%|██████████| 170498071/170498071 [00:03<00:00, 46456493.64it/s]" ] }, { @@ -498,10 +642,10 @@ "id": "9b64e0aa", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:23.138923Z", - "iopub.status.busy": "2024-09-05T19:39:23.138570Z", - "iopub.status.idle": "2024-09-05T19:39:23.143265Z", - "shell.execute_reply": "2024-09-05T19:39:23.142817Z" + "iopub.execute_input": "2024-09-06T19:39:23.303328Z", + "iopub.status.busy": "2024-09-06T19:39:23.302943Z", + "iopub.status.idle": "2024-09-06T19:39:23.307938Z", + "shell.execute_reply": "2024-09-06T19:39:23.307365Z" }, "nbsphinx": "hidden" }, @@ -552,10 +696,10 @@ "id": "a00aa3ed", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:23.145648Z", - "iopub.status.busy": "2024-09-05T19:39:23.145075Z", - "iopub.status.idle": "2024-09-05T19:39:23.692735Z", - "shell.execute_reply": "2024-09-05T19:39:23.692010Z" + "iopub.execute_input": "2024-09-06T19:39:23.310122Z", + "iopub.status.busy": "2024-09-06T19:39:23.309822Z", + "iopub.status.idle": "2024-09-06T19:39:23.850296Z", + "shell.execute_reply": "2024-09-06T19:39:23.849793Z" } }, "outputs": [ @@ -588,10 +732,10 @@ "id": "41e5cb6b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:23.695080Z", - "iopub.status.busy": "2024-09-05T19:39:23.694701Z", - "iopub.status.idle": "2024-09-05T19:39:24.214620Z", - "shell.execute_reply": "2024-09-05T19:39:24.214041Z" + "iopub.execute_input": "2024-09-06T19:39:23.852466Z", + "iopub.status.busy": "2024-09-06T19:39:23.852115Z", + "iopub.status.idle": "2024-09-06T19:39:24.358610Z", + "shell.execute_reply": "2024-09-06T19:39:24.358030Z" } }, "outputs": [ @@ -629,10 +773,10 @@ "id": "1cf25354", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:24.216960Z", - "iopub.status.busy": "2024-09-05T19:39:24.216573Z", - "iopub.status.idle": "2024-09-05T19:39:24.220264Z", - "shell.execute_reply": "2024-09-05T19:39:24.219778Z" + "iopub.execute_input": "2024-09-06T19:39:24.360839Z", + "iopub.status.busy": "2024-09-06T19:39:24.360464Z", + "iopub.status.idle": "2024-09-06T19:39:24.363781Z", + "shell.execute_reply": "2024-09-06T19:39:24.363295Z" } }, "outputs": [], @@ -655,17 +799,17 @@ "id": "85a58d41", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:24.222316Z", - "iopub.status.busy": "2024-09-05T19:39:24.221972Z", - "iopub.status.idle": "2024-09-05T19:39:36.692173Z", - "shell.execute_reply": "2024-09-05T19:39:36.691528Z" + "iopub.execute_input": "2024-09-06T19:39:24.365783Z", + "iopub.status.busy": "2024-09-06T19:39:24.365442Z", + "iopub.status.idle": "2024-09-06T19:39:36.716347Z", + "shell.execute_reply": "2024-09-06T19:39:36.715721Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "7c531849220347c4bbd1314510f1888e", + "model_id": "3ceaa047f5ed4611b974d3fa414e2507", "version_major": 2, "version_minor": 0 }, @@ -724,10 +868,10 @@ "id": "feb0f519", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:36.694834Z", - "iopub.status.busy": "2024-09-05T19:39:36.694331Z", - "iopub.status.idle": "2024-09-05T19:39:38.805431Z", - "shell.execute_reply": "2024-09-05T19:39:38.804752Z" + "iopub.execute_input": "2024-09-06T19:39:36.718898Z", + "iopub.status.busy": "2024-09-06T19:39:36.718487Z", + "iopub.status.idle": "2024-09-06T19:39:38.825920Z", + "shell.execute_reply": "2024-09-06T19:39:38.825316Z" } }, "outputs": [ @@ -771,10 +915,10 @@ "id": "089d5860", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:38.808473Z", - "iopub.status.busy": "2024-09-05T19:39:38.807868Z", - "iopub.status.idle": "2024-09-05T19:39:39.068245Z", - "shell.execute_reply": "2024-09-05T19:39:39.067640Z" + "iopub.execute_input": "2024-09-06T19:39:38.828812Z", + "iopub.status.busy": "2024-09-06T19:39:38.828333Z", + "iopub.status.idle": "2024-09-06T19:39:39.084401Z", + "shell.execute_reply": "2024-09-06T19:39:39.083812Z" } }, "outputs": [ @@ -810,10 +954,10 @@ "id": "78b1951c", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:39.070920Z", - "iopub.status.busy": "2024-09-05T19:39:39.070467Z", - "iopub.status.idle": "2024-09-05T19:39:39.749637Z", - "shell.execute_reply": "2024-09-05T19:39:39.749023Z" + "iopub.execute_input": "2024-09-06T19:39:39.087122Z", + "iopub.status.busy": "2024-09-06T19:39:39.086611Z", + "iopub.status.idle": "2024-09-06T19:39:39.754107Z", + "shell.execute_reply": "2024-09-06T19:39:39.753534Z" } }, "outputs": [ @@ -863,10 +1007,10 @@ "id": "e9dff81b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:39.752728Z", - "iopub.status.busy": "2024-09-05T19:39:39.752257Z", - "iopub.status.idle": "2024-09-05T19:39:40.092896Z", - "shell.execute_reply": "2024-09-05T19:39:40.092212Z" + "iopub.execute_input": "2024-09-06T19:39:39.756937Z", + "iopub.status.busy": "2024-09-06T19:39:39.756623Z", + "iopub.status.idle": "2024-09-06T19:39:40.092242Z", + "shell.execute_reply": "2024-09-06T19:39:40.091655Z" } }, "outputs": [ @@ -914,10 +1058,10 @@ "id": "616769f8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:40.095138Z", - "iopub.status.busy": "2024-09-05T19:39:40.094925Z", - "iopub.status.idle": "2024-09-05T19:39:40.341300Z", - "shell.execute_reply": "2024-09-05T19:39:40.340684Z" + "iopub.execute_input": "2024-09-06T19:39:40.094221Z", + "iopub.status.busy": "2024-09-06T19:39:40.094058Z", + "iopub.status.idle": "2024-09-06T19:39:40.335215Z", + "shell.execute_reply": "2024-09-06T19:39:40.334660Z" } }, "outputs": [ @@ -973,10 +1117,10 @@ "id": "40fed4ef", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:40.344290Z", - "iopub.status.busy": "2024-09-05T19:39:40.343761Z", - "iopub.status.idle": "2024-09-05T19:39:40.431779Z", - "shell.execute_reply": "2024-09-05T19:39:40.431283Z" + "iopub.execute_input": "2024-09-06T19:39:40.337846Z", + "iopub.status.busy": "2024-09-06T19:39:40.337645Z", + "iopub.status.idle": "2024-09-06T19:39:40.434888Z", + "shell.execute_reply": "2024-09-06T19:39:40.434380Z" } }, "outputs": [], @@ -997,10 +1141,10 @@ "id": "89f9db72", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:40.434261Z", - "iopub.status.busy": "2024-09-05T19:39:40.433923Z", - "iopub.status.idle": "2024-09-05T19:39:50.771833Z", - "shell.execute_reply": "2024-09-05T19:39:50.771095Z" + "iopub.execute_input": "2024-09-06T19:39:40.437135Z", + "iopub.status.busy": "2024-09-06T19:39:40.436969Z", + "iopub.status.idle": "2024-09-06T19:39:50.846992Z", + "shell.execute_reply": "2024-09-06T19:39:50.846365Z" } }, "outputs": [ @@ -1037,10 +1181,10 @@ "id": "874c885a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:50.774513Z", - "iopub.status.busy": "2024-09-05T19:39:50.774240Z", - "iopub.status.idle": "2024-09-05T19:39:53.048664Z", - "shell.execute_reply": "2024-09-05T19:39:53.048057Z" + "iopub.execute_input": "2024-09-06T19:39:50.849274Z", + "iopub.status.busy": "2024-09-06T19:39:50.849079Z", + "iopub.status.idle": "2024-09-06T19:39:53.085840Z", + "shell.execute_reply": "2024-09-06T19:39:53.085209Z" } }, "outputs": [ @@ -1071,10 +1215,10 @@ "id": "e110fc4b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:53.051447Z", - "iopub.status.busy": "2024-09-05T19:39:53.051056Z", - "iopub.status.idle": "2024-09-05T19:39:53.260971Z", - "shell.execute_reply": "2024-09-05T19:39:53.260424Z" + "iopub.execute_input": "2024-09-06T19:39:53.088386Z", + "iopub.status.busy": "2024-09-06T19:39:53.087986Z", + "iopub.status.idle": "2024-09-06T19:39:53.295938Z", + "shell.execute_reply": "2024-09-06T19:39:53.295309Z" } }, "outputs": [], @@ -1088,10 +1232,10 @@ "id": "85b60cbf", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:53.263397Z", - "iopub.status.busy": "2024-09-05T19:39:53.263043Z", - "iopub.status.idle": "2024-09-05T19:39:53.266100Z", - "shell.execute_reply": "2024-09-05T19:39:53.265661Z" + "iopub.execute_input": "2024-09-06T19:39:53.298578Z", + "iopub.status.busy": "2024-09-06T19:39:53.298149Z", + "iopub.status.idle": "2024-09-06T19:39:53.301396Z", + "shell.execute_reply": "2024-09-06T19:39:53.300847Z" } }, "outputs": [], @@ -1129,10 +1273,10 @@ "id": "17f96fa6", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:53.268739Z", - "iopub.status.busy": "2024-09-05T19:39:53.267783Z", - "iopub.status.idle": "2024-09-05T19:39:53.276580Z", - "shell.execute_reply": "2024-09-05T19:39:53.276119Z" + "iopub.execute_input": "2024-09-06T19:39:53.303545Z", + "iopub.status.busy": "2024-09-06T19:39:53.303235Z", + "iopub.status.idle": "2024-09-06T19:39:53.311553Z", + "shell.execute_reply": "2024-09-06T19:39:53.311013Z" }, "nbsphinx": "hidden" }, @@ -1177,7 +1321,7 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "1349f610634f47e3a436b32454886eaf": { + "2a68a2d432424faba9fe0b5e6944b5e9": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1230,25 +1374,47 @@ "width": null } }, - "17b81af4f234437a8808eadad363b86b": { + "3ceaa047f5ed4611b974d3fa414e2507": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_c213a022f9994559b2b3155f2f77656c", + "IPY_MODEL_d04af2b6417a48e88c2bb6ac7a1a352f", + "IPY_MODEL_d330cb5a3ec245d28c20140821dff479" + ], + "layout": "IPY_MODEL_8965ea1fe0204e49bbde2ee4ed6b5dbe", + "tabbable": null, + "tooltip": null + } + }, + "653de3cf6239488fa0adf55f2a1ae049": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "bar_color": null, + "description_width": "" } }, - "1faec7121f484abdb6d2297ca62c549d": { + "8965ea1fe0204e49bbde2ee4ed6b5dbe": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1301,7 +1467,7 @@ "width": null } }, - "26c77578263941ad9a13a20bef319656": { + "b06f361a24974d5a8b8c89476e47f817": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1354,54 +1520,7 @@ "width": null } }, - "39aa8065c5b8424498ce8391b1a41734": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_1faec7121f484abdb6d2297ca62c549d", - "placeholder": "​", - "style": "IPY_MODEL_810d42e3457741f5879220bcee73da3b", - "tabbable": null, - "tooltip": null, - "value": "model.safetensors: 100%" - } - }, - "7c531849220347c4bbd1314510f1888e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_39aa8065c5b8424498ce8391b1a41734", - "IPY_MODEL_9ebe6590bdfb470397e8cdde6f7f6b02", - "IPY_MODEL_b2a369aac2ff425a88c2e810df948da8" - ], - "layout": "IPY_MODEL_f8dbae4a023d4586b20790fd6be925eb", - "tabbable": null, - "tooltip": null - } - }, - "810d42e3457741f5879220bcee73da3b": { + "b895588a207f4f0ca89d7c4764c3d066": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -1419,49 +1538,7 @@ "text_color": null } }, - "9cc64681cf4a45ae867cf79d8b667320": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "9ebe6590bdfb470397e8cdde6f7f6b02": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_26c77578263941ad9a13a20bef319656", - "max": 102469840.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_9cc64681cf4a45ae867cf79d8b667320", - "tabbable": null, - "tooltip": null, - "value": 102469840.0 - } - }, - "b2a369aac2ff425a88c2e810df948da8": { + "c213a022f9994559b2b3155f2f77656c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1476,15 +1553,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_1349f610634f47e3a436b32454886eaf", + "layout": "IPY_MODEL_ccda1205dcc748f99c76cf1800b182ef", "placeholder": "​", - "style": "IPY_MODEL_17b81af4f234437a8808eadad363b86b", + "style": "IPY_MODEL_b895588a207f4f0ca89d7c4764c3d066", "tabbable": null, "tooltip": null, - "value": " 102M/102M [00:00<00:00, 257MB/s]" + "value": "model.safetensors: 100%" } }, - "f8dbae4a023d4586b20790fd6be925eb": { + "ccda1205dcc748f99c76cf1800b182ef": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1536,6 +1613,73 @@ "visibility": null, "width": null } + }, + "cd03cf3d325849b9a2597fce8db90de1": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "d04af2b6417a48e88c2bb6ac7a1a352f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_2a68a2d432424faba9fe0b5e6944b5e9", + "max": 102469840.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_653de3cf6239488fa0adf55f2a1ae049", + "tabbable": null, + "tooltip": null, + "value": 102469840.0 + } + }, + "d330cb5a3ec245d28c20140821dff479": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_b06f361a24974d5a8b8c89476e47f817", + "placeholder": "​", + "style": "IPY_MODEL_cd03cf3d325849b9a2597fce8db90de1", + "tabbable": null, + "tooltip": null, + "value": " 102M/102M [00:00<00:00, 304MB/s]" + } } }, "version_major": 2, diff --git a/master/tutorials/regression.ipynb b/master/tutorials/regression.ipynb index f384516c7..4e72a9c31 100644 --- a/master/tutorials/regression.ipynb +++ b/master/tutorials/regression.ipynb @@ -102,10 +102,10 @@ "id": "2e1af7d8", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:57.424289Z", - "iopub.status.busy": "2024-09-05T19:39:57.424123Z", - "iopub.status.idle": "2024-09-05T19:39:58.655592Z", - "shell.execute_reply": "2024-09-05T19:39:58.655038Z" + "iopub.execute_input": "2024-09-06T19:39:57.671183Z", + "iopub.status.busy": "2024-09-06T19:39:57.671012Z", + "iopub.status.idle": "2024-09-06T19:39:58.889426Z", + "shell.execute_reply": "2024-09-06T19:39:58.888863Z" }, "nbsphinx": "hidden" }, @@ -116,7 +116,7 @@ "dependencies = [\"cleanlab\", \"matplotlib>=3.6.0\", \"datasets\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = \" \".join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -142,10 +142,10 @@ "id": "4fb10b8f", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.658099Z", - "iopub.status.busy": "2024-09-05T19:39:58.657787Z", - "iopub.status.idle": "2024-09-05T19:39:58.676619Z", - "shell.execute_reply": "2024-09-05T19:39:58.676046Z" + "iopub.execute_input": "2024-09-06T19:39:58.892009Z", + "iopub.status.busy": "2024-09-06T19:39:58.891558Z", + "iopub.status.idle": "2024-09-06T19:39:58.909420Z", + "shell.execute_reply": "2024-09-06T19:39:58.908966Z" } }, "outputs": [], @@ -164,10 +164,10 @@ "id": "284dc264", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.679179Z", - "iopub.status.busy": "2024-09-05T19:39:58.678732Z", - "iopub.status.idle": "2024-09-05T19:39:58.681876Z", - "shell.execute_reply": "2024-09-05T19:39:58.681391Z" + "iopub.execute_input": "2024-09-06T19:39:58.911380Z", + "iopub.status.busy": "2024-09-06T19:39:58.911122Z", + "iopub.status.idle": "2024-09-06T19:39:58.914071Z", + "shell.execute_reply": "2024-09-06T19:39:58.913630Z" }, "nbsphinx": "hidden" }, @@ -198,10 +198,10 @@ "id": "0f7450db", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.684044Z", - "iopub.status.busy": "2024-09-05T19:39:58.683742Z", - "iopub.status.idle": "2024-09-05T19:39:58.780574Z", - "shell.execute_reply": "2024-09-05T19:39:58.779978Z" + "iopub.execute_input": "2024-09-06T19:39:58.916066Z", + "iopub.status.busy": "2024-09-06T19:39:58.915883Z", + "iopub.status.idle": "2024-09-06T19:39:59.147435Z", + "shell.execute_reply": "2024-09-06T19:39:59.146903Z" } }, "outputs": [ @@ -374,10 +374,10 @@ "id": "55513fed", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.782788Z", - "iopub.status.busy": "2024-09-05T19:39:58.782453Z", - "iopub.status.idle": "2024-09-05T19:39:58.968491Z", - "shell.execute_reply": "2024-09-05T19:39:58.967817Z" + "iopub.execute_input": "2024-09-06T19:39:59.149566Z", + "iopub.status.busy": "2024-09-06T19:39:59.149370Z", + "iopub.status.idle": "2024-09-06T19:39:59.331007Z", + "shell.execute_reply": "2024-09-06T19:39:59.330438Z" }, "nbsphinx": "hidden" }, @@ -417,10 +417,10 @@ "id": "df5a0f59", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:58.970900Z", - "iopub.status.busy": "2024-09-05T19:39:58.970711Z", - "iopub.status.idle": "2024-09-05T19:39:59.181624Z", - "shell.execute_reply": "2024-09-05T19:39:59.181029Z" + "iopub.execute_input": "2024-09-06T19:39:59.333486Z", + "iopub.status.busy": "2024-09-06T19:39:59.333040Z", + "iopub.status.idle": "2024-09-06T19:39:59.576590Z", + "shell.execute_reply": "2024-09-06T19:39:59.575968Z" } }, "outputs": [ @@ -456,10 +456,10 @@ "id": "7af78a8a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.183736Z", - "iopub.status.busy": "2024-09-05T19:39:59.183554Z", - "iopub.status.idle": "2024-09-05T19:39:59.187818Z", - "shell.execute_reply": "2024-09-05T19:39:59.187379Z" + "iopub.execute_input": "2024-09-06T19:39:59.578938Z", + "iopub.status.busy": "2024-09-06T19:39:59.578553Z", + "iopub.status.idle": "2024-09-06T19:39:59.582923Z", + "shell.execute_reply": "2024-09-06T19:39:59.582473Z" } }, "outputs": [], @@ -477,10 +477,10 @@ "id": "9556c624", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.189662Z", - "iopub.status.busy": "2024-09-05T19:39:59.189487Z", - "iopub.status.idle": "2024-09-05T19:39:59.195334Z", - "shell.execute_reply": "2024-09-05T19:39:59.194907Z" + "iopub.execute_input": "2024-09-06T19:39:59.584759Z", + "iopub.status.busy": "2024-09-06T19:39:59.584580Z", + "iopub.status.idle": "2024-09-06T19:39:59.590790Z", + "shell.execute_reply": "2024-09-06T19:39:59.590351Z" } }, "outputs": [], @@ -527,10 +527,10 @@ "id": "3c2f1ccc", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.197263Z", - "iopub.status.busy": "2024-09-05T19:39:59.197091Z", - "iopub.status.idle": "2024-09-05T19:39:59.199733Z", - "shell.execute_reply": "2024-09-05T19:39:59.199275Z" + "iopub.execute_input": "2024-09-06T19:39:59.592686Z", + "iopub.status.busy": "2024-09-06T19:39:59.592515Z", + "iopub.status.idle": "2024-09-06T19:39:59.595225Z", + "shell.execute_reply": "2024-09-06T19:39:59.594766Z" } }, "outputs": [], @@ -545,10 +545,10 @@ "id": "7e1b7860", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:39:59.201738Z", - "iopub.status.busy": "2024-09-05T19:39:59.201336Z", - "iopub.status.idle": "2024-09-05T19:40:08.299512Z", - "shell.execute_reply": "2024-09-05T19:40:08.298965Z" + "iopub.execute_input": "2024-09-06T19:39:59.597032Z", + "iopub.status.busy": "2024-09-06T19:39:59.596865Z", + "iopub.status.idle": "2024-09-06T19:40:08.597697Z", + "shell.execute_reply": "2024-09-06T19:40:08.597120Z" } }, "outputs": [], @@ -572,10 +572,10 @@ "id": "f407bd69", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.302415Z", - "iopub.status.busy": "2024-09-05T19:40:08.301779Z", - "iopub.status.idle": "2024-09-05T19:40:08.309417Z", - "shell.execute_reply": "2024-09-05T19:40:08.308954Z" + "iopub.execute_input": "2024-09-06T19:40:08.600635Z", + "iopub.status.busy": "2024-09-06T19:40:08.599991Z", + "iopub.status.idle": "2024-09-06T19:40:08.607726Z", + "shell.execute_reply": "2024-09-06T19:40:08.607259Z" } }, "outputs": [ @@ -678,10 +678,10 @@ "id": "f7385336", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.311541Z", - "iopub.status.busy": "2024-09-05T19:40:08.311201Z", - "iopub.status.idle": "2024-09-05T19:40:08.314649Z", - "shell.execute_reply": "2024-09-05T19:40:08.314198Z" + "iopub.execute_input": "2024-09-06T19:40:08.609816Z", + "iopub.status.busy": "2024-09-06T19:40:08.609470Z", + "iopub.status.idle": "2024-09-06T19:40:08.613036Z", + "shell.execute_reply": "2024-09-06T19:40:08.612542Z" } }, "outputs": [], @@ -696,10 +696,10 @@ "id": "59fc3091", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.316646Z", - "iopub.status.busy": "2024-09-05T19:40:08.316310Z", - "iopub.status.idle": "2024-09-05T19:40:08.319658Z", - "shell.execute_reply": "2024-09-05T19:40:08.319198Z" + "iopub.execute_input": "2024-09-06T19:40:08.615042Z", + "iopub.status.busy": "2024-09-06T19:40:08.614643Z", + "iopub.status.idle": "2024-09-06T19:40:08.618056Z", + "shell.execute_reply": "2024-09-06T19:40:08.617486Z" } }, "outputs": [ @@ -734,10 +734,10 @@ "id": "00949977", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.321765Z", - "iopub.status.busy": "2024-09-05T19:40:08.321376Z", - "iopub.status.idle": "2024-09-05T19:40:08.324503Z", - "shell.execute_reply": "2024-09-05T19:40:08.324037Z" + "iopub.execute_input": "2024-09-06T19:40:08.620104Z", + "iopub.status.busy": "2024-09-06T19:40:08.619791Z", + "iopub.status.idle": "2024-09-06T19:40:08.622907Z", + "shell.execute_reply": "2024-09-06T19:40:08.622416Z" } }, "outputs": [], @@ -756,10 +756,10 @@ "id": "b6c1ae3a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.326471Z", - "iopub.status.busy": "2024-09-05T19:40:08.326155Z", - "iopub.status.idle": "2024-09-05T19:40:08.333988Z", - "shell.execute_reply": "2024-09-05T19:40:08.333552Z" + "iopub.execute_input": "2024-09-06T19:40:08.624768Z", + "iopub.status.busy": "2024-09-06T19:40:08.624594Z", + "iopub.status.idle": "2024-09-06T19:40:08.632747Z", + "shell.execute_reply": "2024-09-06T19:40:08.632288Z" } }, "outputs": [ @@ -883,10 +883,10 @@ "id": "9131d82d", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.336061Z", - "iopub.status.busy": "2024-09-05T19:40:08.335706Z", - "iopub.status.idle": "2024-09-05T19:40:08.338225Z", - "shell.execute_reply": "2024-09-05T19:40:08.337767Z" + "iopub.execute_input": "2024-09-06T19:40:08.634564Z", + "iopub.status.busy": "2024-09-06T19:40:08.634392Z", + "iopub.status.idle": "2024-09-06T19:40:08.637116Z", + "shell.execute_reply": "2024-09-06T19:40:08.636642Z" }, "nbsphinx": "hidden" }, @@ -921,10 +921,10 @@ "id": "31c704e7", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.340281Z", - "iopub.status.busy": "2024-09-05T19:40:08.339935Z", - "iopub.status.idle": "2024-09-05T19:40:08.465417Z", - "shell.execute_reply": "2024-09-05T19:40:08.464849Z" + "iopub.execute_input": "2024-09-06T19:40:08.639192Z", + "iopub.status.busy": "2024-09-06T19:40:08.638877Z", + "iopub.status.idle": "2024-09-06T19:40:08.766647Z", + "shell.execute_reply": "2024-09-06T19:40:08.765685Z" } }, "outputs": [ @@ -963,10 +963,10 @@ "id": "0bcc43db", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.467579Z", - "iopub.status.busy": "2024-09-05T19:40:08.467388Z", - "iopub.status.idle": "2024-09-05T19:40:08.576982Z", - "shell.execute_reply": "2024-09-05T19:40:08.576322Z" + "iopub.execute_input": "2024-09-06T19:40:08.769173Z", + "iopub.status.busy": "2024-09-06T19:40:08.768972Z", + "iopub.status.idle": "2024-09-06T19:40:08.878186Z", + "shell.execute_reply": "2024-09-06T19:40:08.877593Z" } }, "outputs": [ @@ -1022,10 +1022,10 @@ "id": "7021bd68", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:08.579538Z", - "iopub.status.busy": "2024-09-05T19:40:08.579142Z", - "iopub.status.idle": "2024-09-05T19:40:09.091088Z", - "shell.execute_reply": "2024-09-05T19:40:09.090540Z" + "iopub.execute_input": "2024-09-06T19:40:08.880641Z", + "iopub.status.busy": "2024-09-06T19:40:08.880289Z", + "iopub.status.idle": "2024-09-06T19:40:09.386974Z", + "shell.execute_reply": "2024-09-06T19:40:09.386324Z" } }, "outputs": [], @@ -1041,10 +1041,10 @@ "id": "d49c990b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.093910Z", - "iopub.status.busy": "2024-09-05T19:40:09.093465Z", - "iopub.status.idle": "2024-09-05T19:40:09.190047Z", - "shell.execute_reply": "2024-09-05T19:40:09.189451Z" + "iopub.execute_input": "2024-09-06T19:40:09.389675Z", + "iopub.status.busy": "2024-09-06T19:40:09.389308Z", + "iopub.status.idle": "2024-09-06T19:40:09.485553Z", + "shell.execute_reply": "2024-09-06T19:40:09.484996Z" } }, "outputs": [ @@ -1079,10 +1079,10 @@ "id": "dbab6fb3", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.192506Z", - "iopub.status.busy": "2024-09-05T19:40:09.192090Z", - "iopub.status.idle": "2024-09-05T19:40:09.200751Z", - "shell.execute_reply": "2024-09-05T19:40:09.200261Z" + "iopub.execute_input": "2024-09-06T19:40:09.487964Z", + "iopub.status.busy": "2024-09-06T19:40:09.487496Z", + "iopub.status.idle": "2024-09-06T19:40:09.496128Z", + "shell.execute_reply": "2024-09-06T19:40:09.495570Z" } }, "outputs": [ @@ -1189,10 +1189,10 @@ "id": "5b39b8b5", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.202776Z", - "iopub.status.busy": "2024-09-05T19:40:09.202460Z", - "iopub.status.idle": "2024-09-05T19:40:09.205281Z", - "shell.execute_reply": "2024-09-05T19:40:09.204801Z" + "iopub.execute_input": "2024-09-06T19:40:09.498303Z", + "iopub.status.busy": "2024-09-06T19:40:09.497989Z", + "iopub.status.idle": "2024-09-06T19:40:09.500756Z", + "shell.execute_reply": "2024-09-06T19:40:09.500274Z" }, "nbsphinx": "hidden" }, @@ -1217,10 +1217,10 @@ "id": "df06525b", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:09.207302Z", - "iopub.status.busy": "2024-09-05T19:40:09.206969Z", - "iopub.status.idle": "2024-09-05T19:40:14.941265Z", - "shell.execute_reply": "2024-09-05T19:40:14.940657Z" + "iopub.execute_input": "2024-09-06T19:40:09.502626Z", + "iopub.status.busy": "2024-09-06T19:40:09.502453Z", + "iopub.status.idle": "2024-09-06T19:40:15.134668Z", + "shell.execute_reply": "2024-09-06T19:40:15.134055Z" } }, "outputs": [ @@ -1264,10 +1264,10 @@ "id": "05282559", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:14.943675Z", - "iopub.status.busy": "2024-09-05T19:40:14.943446Z", - "iopub.status.idle": "2024-09-05T19:40:14.952597Z", - "shell.execute_reply": "2024-09-05T19:40:14.952017Z" + "iopub.execute_input": "2024-09-06T19:40:15.137003Z", + "iopub.status.busy": "2024-09-06T19:40:15.136794Z", + "iopub.status.idle": "2024-09-06T19:40:15.145626Z", + "shell.execute_reply": "2024-09-06T19:40:15.145149Z" } }, "outputs": [ @@ -1392,10 +1392,10 @@ "id": "95531cda", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:14.954943Z", - "iopub.status.busy": "2024-09-05T19:40:14.954611Z", - "iopub.status.idle": "2024-09-05T19:40:15.024368Z", - "shell.execute_reply": "2024-09-05T19:40:15.023700Z" + "iopub.execute_input": "2024-09-06T19:40:15.147739Z", + "iopub.status.busy": "2024-09-06T19:40:15.147560Z", + "iopub.status.idle": "2024-09-06T19:40:15.212105Z", + "shell.execute_reply": "2024-09-06T19:40:15.211592Z" }, "nbsphinx": "hidden" }, diff --git a/master/tutorials/segmentation.html b/master/tutorials/segmentation.html index 81b3a34ee..9c9811712 100644 --- a/master/tutorials/segmentation.html +++ b/master/tutorials/segmentation.html @@ -804,13 +804,13 @@

    3. Use cleanlab to find label issues

    -
    +
    -
    +

    Beyond scoring the overall label quality of each image, the above method produces a (0 to 1) quality score for each pixel. We can apply a thresholding function to these scores in order to extract the same style True or False mask as find_label_issues().

    @@ -1200,7 +1200,7 @@

    Get label quality scores -{"state": {"8e787c2b073e463881f6c5e2cc8dc67a": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "df29b384d8354feea3a86fb145690034": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "19a073f2103145ff8d3edb1fc13352fd": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_8e787c2b073e463881f6c5e2cc8dc67a", "max": 30.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_df29b384d8354feea3a86fb145690034", "tabbable": null, "tooltip": null, "value": 30.0}}, "770a9991bd4f479da0fceb5900cbf417": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d654f626f86948388172098f7cc43d25": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "9d3137e0b66a43d2bd580b2b48653afc": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_770a9991bd4f479da0fceb5900cbf417", "placeholder": "\u200b", "style": "IPY_MODEL_d654f626f86948388172098f7cc43d25", "tabbable": null, "tooltip": null, "value": "number\u2007of\u2007examples\u2007processed\u2007for\u2007estimating\u2007thresholds:\u2007100%"}}, "ac3b63d4a32f44cdb880bf34eae8e38f": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "fe96e6f2b3d44ed9a068d86177dba9d9": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "6d920735297d48d5aa5fa76eb77c5faa": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_ac3b63d4a32f44cdb880bf34eae8e38f", "placeholder": "\u200b", "style": "IPY_MODEL_fe96e6f2b3d44ed9a068d86177dba9d9", "tabbable": null, "tooltip": null, "value": "\u200730/30\u2007[00:00<00:00,\u2007817.50it/s]"}}, "f612b67a99514134b4f6b0b836455efc": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "a4b3e7cfcb62474f9a340c5c39023be9": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_9d3137e0b66a43d2bd580b2b48653afc", "IPY_MODEL_19a073f2103145ff8d3edb1fc13352fd", "IPY_MODEL_6d920735297d48d5aa5fa76eb77c5faa"], "layout": "IPY_MODEL_f612b67a99514134b4f6b0b836455efc", "tabbable": null, "tooltip": null}}, "b18e4f016fcf408a98576f5ec0eaa44b": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c13620cfc24b48c0ba51a5593d66841e": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "2ff9cc8a4b654553be47d8b435944b7f": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_b18e4f016fcf408a98576f5ec0eaa44b", "max": 30.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_c13620cfc24b48c0ba51a5593d66841e", "tabbable": null, "tooltip": null, "value": 30.0}}, "44a2a05278754fb8b099f76a80aa6e48": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c2b264c49d234675bf6ed2efbeefbaef": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "45ed018ec81f4df08d861bcb58442dd3": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_44a2a05278754fb8b099f76a80aa6e48", "placeholder": "\u200b", "style": "IPY_MODEL_c2b264c49d234675bf6ed2efbeefbaef", "tabbable": null, "tooltip": null, "value": "number\u2007of\u2007examples\u2007processed\u2007for\u2007checking\u2007labels:\u2007100%"}}, "fd5942b1092f42aeaedd8058d4d911de": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "30327c6cf5554d71a80f362c0e3c517a": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "a8e5b9a64739480e863ba68bb4d8600f": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_fd5942b1092f42aeaedd8058d4d911de", "placeholder": "\u200b", "style": "IPY_MODEL_30327c6cf5554d71a80f362c0e3c517a", "tabbable": null, "tooltip": null, "value": "\u200730/30\u2007[00:25<00:00,\u2007\u20071.15it/s]"}}, "915659784e954336952dbe532ca9c568": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "fb3d14222f3f42b487321867e4e431ee": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_45ed018ec81f4df08d861bcb58442dd3", "IPY_MODEL_2ff9cc8a4b654553be47d8b435944b7f", "IPY_MODEL_a8e5b9a64739480e863ba68bb4d8600f"], "layout": "IPY_MODEL_915659784e954336952dbe532ca9c568", "tabbable": null, "tooltip": null}}, "a1e731438d6d45e5966433bcf063a059": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "72b3805a9e3b46659f904bc081e85a45": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "f5051711724c4bc0acdc14f8b27478fe": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_a1e731438d6d45e5966433bcf063a059", "max": 4997683.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_72b3805a9e3b46659f904bc081e85a45", "tabbable": null, "tooltip": null, "value": 4997683.0}}, "c8fa8dfe739640758359553a0e57be14": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "44c9f78d8aa147219badd49c88116bf5": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "a38a937b167f4ba482c62fb6f9795bb4": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_c8fa8dfe739640758359553a0e57be14", "placeholder": "\u200b", "style": "IPY_MODEL_44c9f78d8aa147219badd49c88116bf5", "tabbable": null, "tooltip": null, "value": "100%"}}, "b89d909a19a7460f81b9b346038cdfe0": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b9e08204838a45a489517f7aac01fcdb": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "780bdc9cdfc146f4b64fe526a99ff03b": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_b89d909a19a7460f81b9b346038cdfe0", "placeholder": "\u200b", "style": "IPY_MODEL_b9e08204838a45a489517f7aac01fcdb", "tabbable": null, "tooltip": null, "value": "\u20074997683/4997683\u2007[00:32<00:00,\u2007154657.78it/s]"}}, "154ab31a8edf479db912cbff400be313": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "ece025087d704900ab9e6ddd077e3061": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_a38a937b167f4ba482c62fb6f9795bb4", "IPY_MODEL_f5051711724c4bc0acdc14f8b27478fe", "IPY_MODEL_780bdc9cdfc146f4b64fe526a99ff03b"], "layout": "IPY_MODEL_154ab31a8edf479db912cbff400be313", "tabbable": null, "tooltip": null}}, "373286fca444445097e38e012eec4165": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "1c9c63d3b81344a393e31ec0b1420510": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "b1f2065c0c4643e5aecd80658d1aaa37": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_373286fca444445097e38e012eec4165", "max": 30.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_1c9c63d3b81344a393e31ec0b1420510", "tabbable": null, "tooltip": null, "value": 30.0}}, "b9ce6baf57594214a8a7669202c8db27": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "8141ad12728f457e8d88d842133942f9": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "0543eae296d34562bf713d819bab46fa": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_b9ce6baf57594214a8a7669202c8db27", "placeholder": "\u200b", "style": "IPY_MODEL_8141ad12728f457e8d88d842133942f9", "tabbable": null, "tooltip": null, "value": "images\u2007processed\u2007using\u2007softmin:\u2007100%"}}, "bd1a028a18b94bbbb600a39d327b5d2d": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "d102c214e0294328845f42c3a4fc31af": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "0271e3b5aa734c59a2c1e77ab40c0fdf": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_bd1a028a18b94bbbb600a39d327b5d2d", "placeholder": "\u200b", "style": "IPY_MODEL_d102c214e0294328845f42c3a4fc31af", "tabbable": null, "tooltip": null, "value": "\u200730/30\u2007[00:01<00:00,\u200720.22it/s]"}}, "acf13d87464e4f629212a388add13530": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "2ca8a72007b34f2fbd2f2ae6f2cb7931": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_0543eae296d34562bf713d819bab46fa", "IPY_MODEL_b1f2065c0c4643e5aecd80658d1aaa37", "IPY_MODEL_0271e3b5aa734c59a2c1e77ab40c0fdf"], "layout": "IPY_MODEL_acf13d87464e4f629212a388add13530", "tabbable": null, "tooltip": null}}}, "version_major": 2, "version_minor": 0} +{"state": {"fefad91592514c8b93cde6a9aa658432": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "26c9d71cd2b144f5a62f2e547396cf9d": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "5050585031b24c079460a52a9a4fc488": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_fefad91592514c8b93cde6a9aa658432", "max": 30.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_26c9d71cd2b144f5a62f2e547396cf9d", "tabbable": null, "tooltip": null, "value": 30.0}}, "08c7a2f2c6804a7da25a3555d45832fe": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "5428bca92792410db3731a76852725a2": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "42d03e2415284486b25cf67ccd387444": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_08c7a2f2c6804a7da25a3555d45832fe", "placeholder": "\u200b", "style": "IPY_MODEL_5428bca92792410db3731a76852725a2", "tabbable": null, "tooltip": null, "value": "number\u2007of\u2007examples\u2007processed\u2007for\u2007estimating\u2007thresholds:\u2007100%"}}, "474187191bb2423bbeaab8075807fc8d": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "5aa47fe7e6cf4464bcbe167e6d3ba68a": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "b1848abf52f742ed9f7657ba08af06f7": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_474187191bb2423bbeaab8075807fc8d", "placeholder": "\u200b", "style": "IPY_MODEL_5aa47fe7e6cf4464bcbe167e6d3ba68a", "tabbable": null, "tooltip": null, "value": "\u200730/30\u2007[00:00<00:00,\u2007787.55it/s]"}}, "d73b0ac161c9411fb176d09cfe007d5d": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "00ec60662f03441f8733d768775a0ed1": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_42d03e2415284486b25cf67ccd387444", "IPY_MODEL_5050585031b24c079460a52a9a4fc488", "IPY_MODEL_b1848abf52f742ed9f7657ba08af06f7"], "layout": "IPY_MODEL_d73b0ac161c9411fb176d09cfe007d5d", "tabbable": null, "tooltip": null}}, "71cc03f01ffb487095fef61fe310cb72": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "428890bcca0c4c398b4c85e7b197ef23": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "5e211e7a482d4ffc95757eed7f7aa9cc": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_71cc03f01ffb487095fef61fe310cb72", "max": 30.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_428890bcca0c4c398b4c85e7b197ef23", "tabbable": null, "tooltip": null, "value": 30.0}}, "733932bb0ae3401390e27945e01e9afa": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "72aa2b7d62f44bfba1fef33687cd2d9c": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "ac71e20e794944a5ad10d81bd3802d6a": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_733932bb0ae3401390e27945e01e9afa", "placeholder": "\u200b", "style": "IPY_MODEL_72aa2b7d62f44bfba1fef33687cd2d9c", "tabbable": null, "tooltip": null, "value": "number\u2007of\u2007examples\u2007processed\u2007for\u2007checking\u2007labels:\u2007100%"}}, "8b4141a6045142c1b9ba131103d924f0": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "62e07c87b8f14d10ae3081dc89c264cb": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "56086d38b6e24dd381b3d2d8adfc7dee": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_8b4141a6045142c1b9ba131103d924f0", "placeholder": "\u200b", "style": "IPY_MODEL_62e07c87b8f14d10ae3081dc89c264cb", "tabbable": null, "tooltip": null, "value": "\u200730/30\u2007[00:25<00:00,\u2007\u20071.19it/s]"}}, "71d9c9ff1e934321985ce73f6d70432d": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "af401850ebaa408dae00a90bb34bc54a": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_ac71e20e794944a5ad10d81bd3802d6a", "IPY_MODEL_5e211e7a482d4ffc95757eed7f7aa9cc", "IPY_MODEL_56086d38b6e24dd381b3d2d8adfc7dee"], "layout": "IPY_MODEL_71d9c9ff1e934321985ce73f6d70432d", "tabbable": null, "tooltip": null}}, "0555e6f1fc524e749446c0929d265eab": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "b4ff48b5ef42475cb8d931380feef05a": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "8c44f5cb10834552b9f054ccff28de8f": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_0555e6f1fc524e749446c0929d265eab", "max": 4997683.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_b4ff48b5ef42475cb8d931380feef05a", "tabbable": null, "tooltip": null, "value": 4997683.0}}, "31810f3656744673bb829bd7c19b4796": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "71684d8531234f3d9d16e15f5e2a1318": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "e7a051930ecf4f8da5a7114fa550bc7c": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_31810f3656744673bb829bd7c19b4796", "placeholder": "\u200b", "style": "IPY_MODEL_71684d8531234f3d9d16e15f5e2a1318", "tabbable": null, "tooltip": null, "value": "100%"}}, "23f68f6bcc9f4247ac306e707ae76a3e": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "0f26c903e03a409eb8eb23a06ad068a1": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "abb55722ee8a4e9383f54ba9776bfb21": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_23f68f6bcc9f4247ac306e707ae76a3e", "placeholder": "\u200b", "style": "IPY_MODEL_0f26c903e03a409eb8eb23a06ad068a1", "tabbable": null, "tooltip": null, "value": "\u20074997683/4997683\u2007[00:33<00:00,\u2007147431.29it/s]"}}, "44a941086c164d5bb775c41c7d4ac57f": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "a8ef1d6ee6da4d52bd3aa4ef30d9915f": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_e7a051930ecf4f8da5a7114fa550bc7c", "IPY_MODEL_8c44f5cb10834552b9f054ccff28de8f", "IPY_MODEL_abb55722ee8a4e9383f54ba9776bfb21"], "layout": "IPY_MODEL_44a941086c164d5bb775c41c7d4ac57f", "tabbable": null, "tooltip": null}}, "d8f70224ecee42f48ecf14d646040c54": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "e468d38bc9454ebf87117d355645f3f1": {"model_name": "ProgressStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "ProgressStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "bar_color": null, "description_width": ""}}, "90fef083c08c4c3c927458dfb8b00fe9": {"model_name": "FloatProgressModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "ProgressView", "bar_style": "success", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_d8f70224ecee42f48ecf14d646040c54", "max": 30.0, "min": 0.0, "orientation": "horizontal", "style": "IPY_MODEL_e468d38bc9454ebf87117d355645f3f1", "tabbable": null, "tooltip": null, "value": 30.0}}, "fa2dd8d15728476eac598aeb95576e3b": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "a247c69930644302aed767d71b7ec676": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "6901169080b04ad499942dc391b9b336": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_fa2dd8d15728476eac598aeb95576e3b", "placeholder": "\u200b", "style": "IPY_MODEL_a247c69930644302aed767d71b7ec676", "tabbable": null, "tooltip": null, "value": "images\u2007processed\u2007using\u2007softmin:\u2007100%"}}, "7b66b5652e59476aab6385c55f338eaf": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "c70c5f7b514a4120b47fe4694b8aa561": {"model_name": "HTMLStyleModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", "background": null, "description_width": "", "font_size": null, "text_color": null}}, "219cc478643a4ee5ac3bd50beeb53306": {"model_name": "HTMLModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HTMLView", "description": "", "description_allow_html": false, "layout": "IPY_MODEL_7b66b5652e59476aab6385c55f338eaf", "placeholder": "\u200b", "style": "IPY_MODEL_c70c5f7b514a4120b47fe4694b8aa561", "tabbable": null, "tooltip": null, "value": "\u200730/30\u2007[00:01<00:00,\u200721.35it/s]"}}, "571062df41e24ec2a51ede636c1c40ae": {"model_name": "LayoutModel", "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "state": {"_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, "grid_auto_rows": null, "grid_column": null, "grid_gap": null, "grid_row": null, "grid_template_areas": null, "grid_template_columns": null, "grid_template_rows": null, "height": null, "justify_content": null, "justify_items": null, "left": null, "margin": null, "max_height": null, "max_width": null, "min_height": null, "min_width": null, "object_fit": null, "object_position": null, "order": null, "overflow": null, "padding": null, "right": null, "top": null, "visibility": null, "width": null}}, "33547ea19ce34215b8f9bbd75c870924": {"model_name": "HBoxModel", "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "state": {"_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", "_view_name": "HBoxView", "box_style": "", "children": ["IPY_MODEL_6901169080b04ad499942dc391b9b336", "IPY_MODEL_90fef083c08c4c3c927458dfb8b00fe9", "IPY_MODEL_219cc478643a4ee5ac3bd50beeb53306"], "layout": "IPY_MODEL_571062df41e24ec2a51ede636c1c40ae", "tabbable": null, "tooltip": null}}}, "version_major": 2, "version_minor": 0} diff --git a/master/tutorials/segmentation.ipynb b/master/tutorials/segmentation.ipynb index f4a359b72..3d1ba85ed 100644 --- a/master/tutorials/segmentation.ipynb +++ b/master/tutorials/segmentation.ipynb @@ -61,10 +61,10 @@ "id": "ae8a08e0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:18.199733Z", - "iopub.status.busy": "2024-09-05T19:40:18.199551Z", - "iopub.status.idle": "2024-09-05T19:40:19.726748Z", - "shell.execute_reply": "2024-09-05T19:40:19.726012Z" + "iopub.execute_input": "2024-09-06T19:40:18.378801Z", + "iopub.status.busy": "2024-09-06T19:40:18.378438Z", + "iopub.status.idle": "2024-09-06T19:40:21.013953Z", + "shell.execute_reply": "2024-09-06T19:40:21.013191Z" } }, "outputs": [], @@ -79,10 +79,10 @@ "id": "58fd4c55", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:40:19.729634Z", - "iopub.status.busy": "2024-09-05T19:40:19.729307Z", - "iopub.status.idle": "2024-09-05T19:41:12.917082Z", - "shell.execute_reply": "2024-09-05T19:41:12.916305Z" + "iopub.execute_input": "2024-09-06T19:40:21.016497Z", + "iopub.status.busy": "2024-09-06T19:40:21.016297Z", + "iopub.status.idle": "2024-09-06T19:41:26.205588Z", + "shell.execute_reply": "2024-09-06T19:41:26.204905Z" } }, "outputs": [], @@ -97,10 +97,10 @@ "id": "439b0305", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:12.919767Z", - "iopub.status.busy": "2024-09-05T19:41:12.919563Z", - "iopub.status.idle": "2024-09-05T19:41:14.110304Z", - "shell.execute_reply": "2024-09-05T19:41:14.109686Z" + "iopub.execute_input": "2024-09-06T19:41:26.208261Z", + "iopub.status.busy": "2024-09-06T19:41:26.207954Z", + "iopub.status.idle": "2024-09-06T19:41:27.363762Z", + "shell.execute_reply": "2024-09-06T19:41:27.363213Z" }, "nbsphinx": "hidden" }, @@ -111,7 +111,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -137,10 +137,10 @@ "id": "a1349304", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.112987Z", - "iopub.status.busy": "2024-09-05T19:41:14.112652Z", - "iopub.status.idle": "2024-09-05T19:41:14.116314Z", - "shell.execute_reply": "2024-09-05T19:41:14.115719Z" + "iopub.execute_input": "2024-09-06T19:41:27.366273Z", + "iopub.status.busy": "2024-09-06T19:41:27.365850Z", + "iopub.status.idle": "2024-09-06T19:41:27.369197Z", + "shell.execute_reply": "2024-09-06T19:41:27.368626Z" } }, "outputs": [], @@ -203,10 +203,10 @@ "id": "07dc5678", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.118606Z", - "iopub.status.busy": "2024-09-05T19:41:14.118193Z", - "iopub.status.idle": "2024-09-05T19:41:14.122291Z", - "shell.execute_reply": "2024-09-05T19:41:14.121859Z" + "iopub.execute_input": "2024-09-06T19:41:27.371272Z", + "iopub.status.busy": "2024-09-06T19:41:27.370943Z", + "iopub.status.idle": "2024-09-06T19:41:27.374872Z", + "shell.execute_reply": "2024-09-06T19:41:27.374336Z" } }, "outputs": [ @@ -247,10 +247,10 @@ "id": "25ebe22a", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.124633Z", - "iopub.status.busy": "2024-09-05T19:41:14.124214Z", - "iopub.status.idle": "2024-09-05T19:41:14.128275Z", - "shell.execute_reply": "2024-09-05T19:41:14.127671Z" + "iopub.execute_input": "2024-09-06T19:41:27.377058Z", + "iopub.status.busy": "2024-09-06T19:41:27.376708Z", + "iopub.status.idle": "2024-09-06T19:41:27.380273Z", + "shell.execute_reply": "2024-09-06T19:41:27.379824Z" } }, "outputs": [ @@ -290,10 +290,10 @@ "id": "3faedea9", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.130477Z", - "iopub.status.busy": "2024-09-05T19:41:14.130083Z", - "iopub.status.idle": "2024-09-05T19:41:14.132962Z", - "shell.execute_reply": "2024-09-05T19:41:14.132498Z" + "iopub.execute_input": "2024-09-06T19:41:27.382286Z", + "iopub.status.busy": "2024-09-06T19:41:27.381955Z", + "iopub.status.idle": "2024-09-06T19:41:27.384835Z", + "shell.execute_reply": "2024-09-06T19:41:27.384366Z" } }, "outputs": [], @@ -333,17 +333,17 @@ "id": "2c2ad9ad", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:14.134947Z", - "iopub.status.busy": "2024-09-05T19:41:14.134627Z", - "iopub.status.idle": "2024-09-05T19:41:52.181715Z", - "shell.execute_reply": "2024-09-05T19:41:52.181015Z" + "iopub.execute_input": "2024-09-06T19:41:27.386838Z", + "iopub.status.busy": "2024-09-06T19:41:27.386506Z", + "iopub.status.idle": "2024-09-06T19:42:04.890778Z", + "shell.execute_reply": "2024-09-06T19:42:04.890135Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "a4b3e7cfcb62474f9a340c5c39023be9", + "model_id": "00ec60662f03441f8733d768775a0ed1", "version_major": 2, "version_minor": 0 }, @@ -357,7 +357,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "fb3d14222f3f42b487321867e4e431ee", + "model_id": "af401850ebaa408dae00a90bb34bc54a", "version_major": 2, "version_minor": 0 }, @@ -400,10 +400,10 @@ "id": "95dc7268", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:52.184254Z", - "iopub.status.busy": "2024-09-05T19:41:52.184042Z", - "iopub.status.idle": "2024-09-05T19:41:52.858875Z", - "shell.execute_reply": "2024-09-05T19:41:52.858345Z" + "iopub.execute_input": "2024-09-06T19:42:04.893407Z", + "iopub.status.busy": "2024-09-06T19:42:04.893064Z", + "iopub.status.idle": "2024-09-06T19:42:05.569760Z", + "shell.execute_reply": "2024-09-06T19:42:05.569193Z" } }, "outputs": [ @@ -446,10 +446,10 @@ "id": "57fed473", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:52.861209Z", - "iopub.status.busy": "2024-09-05T19:41:52.860921Z", - "iopub.status.idle": "2024-09-05T19:41:55.873081Z", - "shell.execute_reply": "2024-09-05T19:41:55.872487Z" + "iopub.execute_input": "2024-09-06T19:42:05.572221Z", + "iopub.status.busy": "2024-09-06T19:42:05.571699Z", + "iopub.status.idle": "2024-09-06T19:42:08.487750Z", + "shell.execute_reply": "2024-09-06T19:42:08.487151Z" } }, "outputs": [ @@ -519,17 +519,17 @@ "id": "e4a006bd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:41:55.875319Z", - "iopub.status.busy": "2024-09-05T19:41:55.874961Z", - "iopub.status.idle": "2024-09-05T19:42:28.673127Z", - "shell.execute_reply": "2024-09-05T19:42:28.672574Z" + "iopub.execute_input": "2024-09-06T19:42:08.490015Z", + "iopub.status.busy": "2024-09-06T19:42:08.489812Z", + "iopub.status.idle": "2024-09-06T19:42:42.122207Z", + "shell.execute_reply": "2024-09-06T19:42:42.121639Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ece025087d704900ab9e6ddd077e3061", + "model_id": "a8ef1d6ee6da4d52bd3aa4ef30d9915f", "version_major": 2, "version_minor": 0 }, @@ -769,10 +769,10 @@ "id": "c8f4e163", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:28.675297Z", - "iopub.status.busy": "2024-09-05T19:42:28.674959Z", - "iopub.status.idle": "2024-09-05T19:42:44.105535Z", - "shell.execute_reply": "2024-09-05T19:42:44.104946Z" + "iopub.execute_input": "2024-09-06T19:42:42.124501Z", + "iopub.status.busy": "2024-09-06T19:42:42.124158Z", + "iopub.status.idle": "2024-09-06T19:42:57.234866Z", + "shell.execute_reply": "2024-09-06T19:42:57.234293Z" } }, "outputs": [], @@ -786,10 +786,10 @@ "id": "716c74f3", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:44.108179Z", - "iopub.status.busy": "2024-09-05T19:42:44.107699Z", - "iopub.status.idle": "2024-09-05T19:42:47.883916Z", - "shell.execute_reply": "2024-09-05T19:42:47.883404Z" + "iopub.execute_input": "2024-09-06T19:42:57.237390Z", + "iopub.status.busy": "2024-09-06T19:42:57.237016Z", + "iopub.status.idle": "2024-09-06T19:43:00.971913Z", + "shell.execute_reply": "2024-09-06T19:43:00.971312Z" } }, "outputs": [ @@ -858,17 +858,17 @@ "id": "db0b5179", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:47.886159Z", - "iopub.status.busy": "2024-09-05T19:42:47.885812Z", - "iopub.status.idle": "2024-09-05T19:42:49.385378Z", - "shell.execute_reply": "2024-09-05T19:42:49.384804Z" + "iopub.execute_input": "2024-09-06T19:43:00.974009Z", + "iopub.status.busy": "2024-09-06T19:43:00.973827Z", + "iopub.status.idle": "2024-09-06T19:43:02.404764Z", + "shell.execute_reply": "2024-09-06T19:43:02.404239Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "2ca8a72007b34f2fbd2f2ae6f2cb7931", + "model_id": "33547ea19ce34215b8f9bbd75c870924", "version_major": 2, "version_minor": 0 }, @@ -898,10 +898,10 @@ "id": "390780a1", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:49.388228Z", - "iopub.status.busy": "2024-09-05T19:42:49.387773Z", - "iopub.status.idle": "2024-09-05T19:42:49.418203Z", - "shell.execute_reply": "2024-09-05T19:42:49.417626Z" + "iopub.execute_input": "2024-09-06T19:43:02.407222Z", + "iopub.status.busy": "2024-09-06T19:43:02.406914Z", + "iopub.status.idle": "2024-09-06T19:43:02.435740Z", + "shell.execute_reply": "2024-09-06T19:43:02.435223Z" } }, "outputs": [], @@ -915,10 +915,10 @@ "id": "933d6ef0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:49.420836Z", - "iopub.status.busy": "2024-09-05T19:42:49.420472Z", - "iopub.status.idle": "2024-09-05T19:42:55.430102Z", - "shell.execute_reply": "2024-09-05T19:42:55.429512Z" + "iopub.execute_input": "2024-09-06T19:43:02.438408Z", + "iopub.status.busy": "2024-09-06T19:43:02.438030Z", + "iopub.status.idle": "2024-09-06T19:43:08.523002Z", + "shell.execute_reply": "2024-09-06T19:43:08.522439Z" } }, "outputs": [ @@ -991,10 +991,10 @@ "id": "86bac686", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:55.432343Z", - "iopub.status.busy": "2024-09-05T19:42:55.431963Z", - "iopub.status.idle": "2024-09-05T19:42:55.487961Z", - "shell.execute_reply": "2024-09-05T19:42:55.487400Z" + "iopub.execute_input": "2024-09-06T19:43:08.525189Z", + "iopub.status.busy": "2024-09-06T19:43:08.524868Z", + "iopub.status.idle": "2024-09-06T19:43:08.580916Z", + "shell.execute_reply": "2024-09-06T19:43:08.580242Z" }, "nbsphinx": "hidden" }, @@ -1038,53 +1038,31 @@ "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { - "0271e3b5aa734c59a2c1e77ab40c0fdf": { + "00ec60662f03441f8733d768775a0ed1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_bd1a028a18b94bbbb600a39d327b5d2d", - "placeholder": "​", - "style": "IPY_MODEL_d102c214e0294328845f42c3a4fc31af", - "tabbable": null, - "tooltip": null, - "value": " 30/30 [00:01<00:00, 20.22it/s]" - } - }, - "0543eae296d34562bf713d819bab46fa": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HBoxModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "HBoxModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b9ce6baf57594214a8a7669202c8db27", - "placeholder": "​", - "style": "IPY_MODEL_8141ad12728f457e8d88d842133942f9", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_42d03e2415284486b25cf67ccd387444", + "IPY_MODEL_5050585031b24c079460a52a9a4fc488", + "IPY_MODEL_b1848abf52f742ed9f7657ba08af06f7" + ], + "layout": "IPY_MODEL_d73b0ac161c9411fb176d09cfe007d5d", "tabbable": null, - "tooltip": null, - "value": "images processed using softmin: 100%" + "tooltip": null } }, - "154ab31a8edf479db912cbff400be313": { + "0555e6f1fc524e749446c0929d265eab": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1137,117 +1115,101 @@ "width": null } }, - "19a073f2103145ff8d3edb1fc13352fd": { - "model_module": "@jupyter-widgets/controls", + "08c7a2f2c6804a7da25a3555d45832fe": { + "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "LayoutModel", "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", + "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "LayoutModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_8e787c2b073e463881f6c5e2cc8dc67a", - "max": 30.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_df29b384d8354feea3a86fb145690034", - "tabbable": null, - "tooltip": null, - "value": 30.0 + "_view_name": "LayoutView", + "align_content": null, + "align_items": null, + "align_self": null, + "border_bottom": null, + "border_left": null, + "border_right": null, + "border_top": null, + "bottom": null, + "display": null, + "flex": null, + "flex_flow": null, + "grid_area": null, + "grid_auto_columns": null, + "grid_auto_flow": null, + "grid_auto_rows": null, + "grid_column": null, + "grid_gap": null, + "grid_row": null, + "grid_template_areas": null, + "grid_template_columns": null, + "grid_template_rows": null, + "height": null, + "justify_content": null, + "justify_items": null, + "left": null, + "margin": null, + "max_height": null, + "max_width": null, + "min_height": null, + "min_width": null, + "object_fit": null, + "object_position": null, + "order": null, + "overflow": null, + "padding": null, + "right": null, + "top": null, + "visibility": null, + "width": null } }, - "1c9c63d3b81344a393e31ec0b1420510": { + "0f26c903e03a409eb8eb23a06ad068a1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", + "model_name": "HTMLStyleModel", "state": { "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "2ca8a72007b34f2fbd2f2ae6f2cb7931": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_0543eae296d34562bf713d819bab46fa", - "IPY_MODEL_b1f2065c0c4643e5aecd80658d1aaa37", - "IPY_MODEL_0271e3b5aa734c59a2c1e77ab40c0fdf" - ], - "layout": "IPY_MODEL_acf13d87464e4f629212a388add13530", - "tabbable": null, - "tooltip": null + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "2ff9cc8a4b654553be47d8b435944b7f": { + "219cc478643a4ee5ac3bd50beeb53306": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_b18e4f016fcf408a98576f5ec0eaa44b", - "max": 30.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_c13620cfc24b48c0ba51a5593d66841e", + "layout": "IPY_MODEL_7b66b5652e59476aab6385c55f338eaf", + "placeholder": "​", + "style": "IPY_MODEL_c70c5f7b514a4120b47fe4694b8aa561", "tabbable": null, "tooltip": null, - "value": 30.0 - } - }, - "30327c6cf5554d71a80f362c0e3c517a": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "value": " 30/30 [00:01<00:00, 21.35it/s]" } }, - "373286fca444445097e38e012eec4165": { + "23f68f6bcc9f4247ac306e707ae76a3e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1300,7 +1262,23 @@ "width": null } }, - "44a2a05278754fb8b099f76a80aa6e48": { + "26c9d71cd2b144f5a62f2e547396cf9d": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "31810f3656744673bb829bd7c19b4796": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1353,48 +1331,47 @@ "width": null } }, - "44c9f78d8aa147219badd49c88116bf5": { + "33547ea19ce34215b8f9bbd75c870924": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", + "model_name": "HBoxModel", "state": { + "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", + "_model_name": "HBoxModel", "_view_count": null, - "_view_module": "@jupyter-widgets/base", + "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_6901169080b04ad499942dc391b9b336", + "IPY_MODEL_90fef083c08c4c3c927458dfb8b00fe9", + "IPY_MODEL_219cc478643a4ee5ac3bd50beeb53306" + ], + "layout": "IPY_MODEL_571062df41e24ec2a51ede636c1c40ae", + "tabbable": null, + "tooltip": null } }, - "45ed018ec81f4df08d861bcb58442dd3": { + "428890bcca0c4c398b4c85e7b197ef23": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "ProgressStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "ProgressStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_44a2a05278754fb8b099f76a80aa6e48", - "placeholder": "​", - "style": "IPY_MODEL_c2b264c49d234675bf6ed2efbeefbaef", - "tabbable": null, - "tooltip": null, - "value": "number of examples processed for checking labels: 100%" + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" } }, - "6d920735297d48d5aa5fa76eb77c5faa": { + "42d03e2415284486b25cf67ccd387444": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1409,31 +1386,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_ac3b63d4a32f44cdb880bf34eae8e38f", + "layout": "IPY_MODEL_08c7a2f2c6804a7da25a3555d45832fe", "placeholder": "​", - "style": "IPY_MODEL_fe96e6f2b3d44ed9a068d86177dba9d9", + "style": "IPY_MODEL_5428bca92792410db3731a76852725a2", "tabbable": null, "tooltip": null, - "value": " 30/30 [00:00<00:00, 817.50it/s]" - } - }, - "72b3805a9e3b46659f904bc081e85a45": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" + "value": "number of examples processed for estimating thresholds: 100%" } }, - "770a9991bd4f479da0fceb5900cbf417": { + "44a941086c164d5bb775c41c7d4ac57f": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1486,48 +1447,7 @@ "width": null } }, - "780bdc9cdfc146f4b64fe526a99ff03b": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HTMLView", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_b89d909a19a7460f81b9b346038cdfe0", - "placeholder": "​", - "style": "IPY_MODEL_b9e08204838a45a489517f7aac01fcdb", - "tabbable": null, - "tooltip": null, - "value": " 4997683/4997683 [00:32<00:00, 154657.78it/s]" - } - }, - "8141ad12728f457e8d88d842133942f9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "8e787c2b073e463881f6c5e2cc8dc67a": { + "474187191bb2423bbeaab8075807fc8d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1580,60 +1500,51 @@ "width": null } }, - "915659784e954336952dbe532ca9c568": { - "model_module": "@jupyter-widgets/base", + "5050585031b24c079460a52a9a4fc488": { + "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "LayoutModel", + "model_name": "FloatProgressModel", "state": { - "_model_module": "@jupyter-widgets/base", + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "LayoutModel", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_fefad91592514c8b93cde6a9aa658432", + "max": 30.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_26c9d71cd2b144f5a62f2e547396cf9d", + "tabbable": null, + "tooltip": null, + "value": 30.0 + } + }, + "5428bca92792410db3731a76852725a2": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "LayoutView", - "align_content": null, - "align_items": null, - "align_self": null, - "border_bottom": null, - "border_left": null, - "border_right": null, - "border_top": null, - "bottom": null, - "display": null, - "flex": null, - "flex_flow": null, - "grid_area": null, - "grid_auto_columns": null, - "grid_auto_flow": null, - "grid_auto_rows": null, - "grid_column": null, - "grid_gap": null, - "grid_row": null, - "grid_template_areas": null, - "grid_template_columns": null, - "grid_template_rows": null, - "height": null, - "justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "9d3137e0b66a43d2bd580b2b48653afc": { + "56086d38b6e24dd381b3d2d8adfc7dee": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1648,15 +1559,15 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_770a9991bd4f479da0fceb5900cbf417", + "layout": "IPY_MODEL_8b4141a6045142c1b9ba131103d924f0", "placeholder": "​", - "style": "IPY_MODEL_d654f626f86948388172098f7cc43d25", + "style": "IPY_MODEL_62e07c87b8f14d10ae3081dc89c264cb", "tabbable": null, "tooltip": null, - "value": "number of examples processed for estimating thresholds: 100%" + "value": " 30/30 [00:25<00:00,  1.19it/s]" } }, - "a1e731438d6d45e5966433bcf063a059": { + "571062df41e24ec2a51ede636c1c40ae": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1709,54 +1620,69 @@ "width": null } }, - "a38a937b167f4ba482c62fb6f9795bb4": { + "5aa47fe7e6cf4464bcbe167e6d3ba68a": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HTMLModel", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "5e211e7a482d4ffc95757eed7f7aa9cc": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HTMLModel", + "_model_name": "FloatProgressModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "HTMLView", + "_view_name": "ProgressView", + "bar_style": "success", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_c8fa8dfe739640758359553a0e57be14", - "placeholder": "​", - "style": "IPY_MODEL_44c9f78d8aa147219badd49c88116bf5", + "layout": "IPY_MODEL_71cc03f01ffb487095fef61fe310cb72", + "max": 30.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_428890bcca0c4c398b4c85e7b197ef23", "tabbable": null, "tooltip": null, - "value": "100%" + "value": 30.0 } }, - "a4b3e7cfcb62474f9a340c5c39023be9": { + "62e07c87b8f14d10ae3081dc89c264cb": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "HBoxModel", + "model_name": "HTMLStyleModel", "state": { - "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", + "_model_name": "HTMLStyleModel", "_view_count": null, - "_view_module": "@jupyter-widgets/controls", + "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_9d3137e0b66a43d2bd580b2b48653afc", - "IPY_MODEL_19a073f2103145ff8d3edb1fc13352fd", - "IPY_MODEL_6d920735297d48d5aa5fa76eb77c5faa" - ], - "layout": "IPY_MODEL_f612b67a99514134b4f6b0b836455efc", - "tabbable": null, - "tooltip": null + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null } }, - "a8e5b9a64739480e863ba68bb4d8600f": { + "6901169080b04ad499942dc391b9b336": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLModel", @@ -1771,15 +1697,33 @@ "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_fd5942b1092f42aeaedd8058d4d911de", + "layout": "IPY_MODEL_fa2dd8d15728476eac598aeb95576e3b", "placeholder": "​", - "style": "IPY_MODEL_30327c6cf5554d71a80f362c0e3c517a", + "style": "IPY_MODEL_a247c69930644302aed767d71b7ec676", "tabbable": null, "tooltip": null, - "value": " 30/30 [00:25<00:00,  1.15it/s]" + "value": "images processed using softmin: 100%" } }, - "ac3b63d4a32f44cdb880bf34eae8e38f": { + "71684d8531234f3d9d16e15f5e2a1318": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "71cc03f01ffb487095fef61fe310cb72": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1832,7 +1776,7 @@ "width": null } }, - "acf13d87464e4f629212a388add13530": { + "71d9c9ff1e934321985ce73f6d70432d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1885,7 +1829,25 @@ "width": null } }, - "b18e4f016fcf408a98576f5ec0eaa44b": { + "72aa2b7d62f44bfba1fef33687cd2d9c": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "733932bb0ae3401390e27945e01e9afa": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -1938,33 +1900,7 @@ "width": null } }, - "b1f2065c0c4643e5aecd80658d1aaa37": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", - "description": "", - "description_allow_html": false, - "layout": "IPY_MODEL_373286fca444445097e38e012eec4165", - "max": 30.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_1c9c63d3b81344a393e31ec0b1420510", - "tabbable": null, - "tooltip": null, - "value": 30.0 - } - }, - "b89d909a19a7460f81b9b346038cdfe0": { + "7b66b5652e59476aab6385c55f338eaf": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2017,7 +1953,7 @@ "width": null } }, - "b9ce6baf57594214a8a7669202c8db27": { + "8b4141a6045142c1b9ba131103d924f0": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2070,7 +2006,210 @@ "width": null } }, - "b9e08204838a45a489517f7aac01fcdb": { + "8c44f5cb10834552b9f054ccff28de8f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_0555e6f1fc524e749446c0929d265eab", + "max": 4997683.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_b4ff48b5ef42475cb8d931380feef05a", + "tabbable": null, + "tooltip": null, + "value": 4997683.0 + } + }, + "90fef083c08c4c3c927458dfb8b00fe9": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "FloatProgressModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "FloatProgressModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "ProgressView", + "bar_style": "success", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_d8f70224ecee42f48ecf14d646040c54", + "max": 30.0, + "min": 0.0, + "orientation": "horizontal", + "style": "IPY_MODEL_e468d38bc9454ebf87117d355645f3f1", + "tabbable": null, + "tooltip": null, + "value": 30.0 + } + }, + "a247c69930644302aed767d71b7ec676": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "background": null, + "description_width": "", + "font_size": null, + "text_color": null + } + }, + "a8ef1d6ee6da4d52bd3aa4ef30d9915f": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_e7a051930ecf4f8da5a7114fa550bc7c", + "IPY_MODEL_8c44f5cb10834552b9f054ccff28de8f", + "IPY_MODEL_abb55722ee8a4e9383f54ba9776bfb21" + ], + "layout": "IPY_MODEL_44a941086c164d5bb775c41c7d4ac57f", + "tabbable": null, + "tooltip": null + } + }, + "abb55722ee8a4e9383f54ba9776bfb21": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_23f68f6bcc9f4247ac306e707ae76a3e", + "placeholder": "​", + "style": "IPY_MODEL_0f26c903e03a409eb8eb23a06ad068a1", + "tabbable": null, + "tooltip": null, + "value": " 4997683/4997683 [00:33<00:00, 147431.29it/s]" + } + }, + "ac71e20e794944a5ad10d81bd3802d6a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_733932bb0ae3401390e27945e01e9afa", + "placeholder": "​", + "style": "IPY_MODEL_72aa2b7d62f44bfba1fef33687cd2d9c", + "tabbable": null, + "tooltip": null, + "value": "number of examples processed for checking labels: 100%" + } + }, + "af401850ebaa408dae00a90bb34bc54a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HBoxModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HBoxModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HBoxView", + "box_style": "", + "children": [ + "IPY_MODEL_ac71e20e794944a5ad10d81bd3802d6a", + "IPY_MODEL_5e211e7a482d4ffc95757eed7f7aa9cc", + "IPY_MODEL_56086d38b6e24dd381b3d2d8adfc7dee" + ], + "layout": "IPY_MODEL_71d9c9ff1e934321985ce73f6d70432d", + "tabbable": null, + "tooltip": null + } + }, + "b1848abf52f742ed9f7657ba08af06f7": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "HTMLModel", + "state": { + "_dom_classes": [], + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "HTMLModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/controls", + "_view_module_version": "2.0.0", + "_view_name": "HTMLView", + "description": "", + "description_allow_html": false, + "layout": "IPY_MODEL_474187191bb2423bbeaab8075807fc8d", + "placeholder": "​", + "style": "IPY_MODEL_5aa47fe7e6cf4464bcbe167e6d3ba68a", + "tabbable": null, + "tooltip": null, + "value": " 30/30 [00:00<00:00, 787.55it/s]" + } + }, + "b4ff48b5ef42475cb8d931380feef05a": { + "model_module": "@jupyter-widgets/controls", + "model_module_version": "2.0.0", + "model_name": "ProgressStyleModel", + "state": { + "_model_module": "@jupyter-widgets/controls", + "_model_module_version": "2.0.0", + "_model_name": "ProgressStyleModel", + "_view_count": null, + "_view_module": "@jupyter-widgets/base", + "_view_module_version": "2.0.0", + "_view_name": "StyleView", + "bar_color": null, + "description_width": "" + } + }, + "c70c5f7b514a4120b47fe4694b8aa561": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "HTMLStyleModel", @@ -2088,7 +2227,7 @@ "text_color": null } }, - "bd1a028a18b94bbbb600a39d327b5d2d": { + "d73b0ac161c9411fb176d09cfe007d5d": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2141,41 +2280,7 @@ "width": null } }, - "c13620cfc24b48c0ba51a5593d66841e": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "ProgressStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "ProgressStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "bar_color": null, - "description_width": "" - } - }, - "c2b264c49d234675bf6ed2efbeefbaef": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "c8fa8dfe739640758359553a0e57be14": { + "d8f70224ecee42f48ecf14d646040c54": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2228,43 +2333,7 @@ "width": null } }, - "d102c214e0294328845f42c3a4fc31af": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "d654f626f86948388172098f7cc43d25": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } - }, - "df29b384d8354feea3a86fb145690034": { + "e468d38bc9454ebf87117d355645f3f1": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", "model_name": "ProgressStyleModel", @@ -2280,57 +2349,30 @@ "description_width": "" } }, - "ece025087d704900ab9e6ddd077e3061": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_a38a937b167f4ba482c62fb6f9795bb4", - "IPY_MODEL_f5051711724c4bc0acdc14f8b27478fe", - "IPY_MODEL_780bdc9cdfc146f4b64fe526a99ff03b" - ], - "layout": "IPY_MODEL_154ab31a8edf479db912cbff400be313", - "tabbable": null, - "tooltip": null - } - }, - "f5051711724c4bc0acdc14f8b27478fe": { + "e7a051930ecf4f8da5a7114fa550bc7c": { "model_module": "@jupyter-widgets/controls", "model_module_version": "2.0.0", - "model_name": "FloatProgressModel", + "model_name": "HTMLModel", "state": { "_dom_classes": [], "_model_module": "@jupyter-widgets/controls", "_model_module_version": "2.0.0", - "_model_name": "FloatProgressModel", + "_model_name": "HTMLModel", "_view_count": null, "_view_module": "@jupyter-widgets/controls", "_view_module_version": "2.0.0", - "_view_name": "ProgressView", - "bar_style": "success", + "_view_name": "HTMLView", "description": "", "description_allow_html": false, - "layout": "IPY_MODEL_a1e731438d6d45e5966433bcf063a059", - "max": 4997683.0, - "min": 0.0, - "orientation": "horizontal", - "style": "IPY_MODEL_72b3805a9e3b46659f904bc081e85a45", + "layout": "IPY_MODEL_31810f3656744673bb829bd7c19b4796", + "placeholder": "​", + "style": "IPY_MODEL_71684d8531234f3d9d16e15f5e2a1318", "tabbable": null, "tooltip": null, - "value": 4997683.0 + "value": "100%" } }, - "f612b67a99514134b4f6b0b836455efc": { + "fa2dd8d15728476eac598aeb95576e3b": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2383,31 +2425,7 @@ "width": null } }, - "fb3d14222f3f42b487321867e4e431ee": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HBoxModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HBoxModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/controls", - "_view_module_version": "2.0.0", - "_view_name": "HBoxView", - "box_style": "", - "children": [ - "IPY_MODEL_45ed018ec81f4df08d861bcb58442dd3", - "IPY_MODEL_2ff9cc8a4b654553be47d8b435944b7f", - "IPY_MODEL_a8e5b9a64739480e863ba68bb4d8600f" - ], - "layout": "IPY_MODEL_915659784e954336952dbe532ca9c568", - "tabbable": null, - "tooltip": null - } - }, - "fd5942b1092f42aeaedd8058d4d911de": { + "fefad91592514c8b93cde6a9aa658432": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", @@ -2459,24 +2477,6 @@ "visibility": null, "width": null } - }, - "fe96e6f2b3d44ed9a068d86177dba9d9": { - "model_module": "@jupyter-widgets/controls", - "model_module_version": "2.0.0", - "model_name": "HTMLStyleModel", - "state": { - "_model_module": "@jupyter-widgets/controls", - "_model_module_version": "2.0.0", - "_model_name": "HTMLStyleModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/base", - "_view_module_version": "2.0.0", - "_view_name": "StyleView", - "background": null, - "description_width": "", - "font_size": null, - "text_color": null - } } }, "version_major": 2, diff --git a/master/tutorials/token_classification.html b/master/tutorials/token_classification.html index db5cfd59d..bad7e549d 100644 --- a/master/tutorials/token_classification.html +++ b/master/tutorials/token_classification.html @@ -714,16 +714,16 @@

    1. Install required dependencies and download data

    diff --git a/master/tutorials/token_classification.ipynb b/master/tutorials/token_classification.ipynb index 49d76911a..c988c12c2 100644 --- a/master/tutorials/token_classification.ipynb +++ b/master/tutorials/token_classification.ipynb @@ -75,10 +75,10 @@ "id": "ae8a08e0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:57.901570Z", - "iopub.status.busy": "2024-09-05T19:42:57.901387Z", - "iopub.status.idle": "2024-09-05T19:42:59.034492Z", - "shell.execute_reply": "2024-09-05T19:42:59.033839Z" + "iopub.execute_input": "2024-09-06T19:43:11.117353Z", + "iopub.status.busy": "2024-09-06T19:43:11.117178Z", + "iopub.status.idle": "2024-09-06T19:43:13.210573Z", + "shell.execute_reply": "2024-09-06T19:43:13.209958Z" } }, "outputs": [ @@ -86,7 +86,7 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-09-05 19:42:57-- https://data.deepai.org/conll2003.zip\r\n", + "--2024-09-06 19:43:11-- https://data.deepai.org/conll2003.zip\r\n", "Resolving data.deepai.org (data.deepai.org)... " ] }, @@ -94,15 +94,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "169.150.236.98, 2400:52e0:1a00::1067:1\r\n", - "Connecting to data.deepai.org (data.deepai.org)|169.150.236.98|:443... " - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "connected.\r\n", + "169.150.249.167, 2400:52e0:1a01::907:1\r\n", + "Connecting to data.deepai.org (data.deepai.org)|169.150.249.167|:443... connected.\r\n", "HTTP request sent, awaiting response... " ] }, @@ -125,7 +118,7 @@ "\r", "conll2003.zip 100%[===================>] 959.94K --.-KB/s in 0.1s \r\n", "\r\n", - "2024-09-05 19:42:58 (6.36 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n", + "2024-09-06 19:43:11 (7.82 MB/s) - ‘conll2003.zip’ saved [982975/982975]\r\n", "\r\n", "mkdir: cannot create directory ‘data’: File exists\r\n" ] @@ -145,9 +138,22 @@ "name": "stdout", "output_type": "stream", "text": [ - "--2024-09-05 19:42:58-- https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n", - "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 3.5.17.152, 3.5.30.212, 54.231.228.65, ...\r\n", - "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|3.5.17.152|:443... connected.\r\n", + "--2024-09-06 19:43:11-- https://cleanlab-public.s3.amazonaws.com/TokenClassification/pred_probs.npz\r\n", + "Resolving cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)... 54.231.201.17, 52.217.193.233, 52.217.81.84, ...\r\n", + "Connecting to cleanlab-public.s3.amazonaws.com (cleanlab-public.s3.amazonaws.com)|54.231.201.17|:443... " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "connected.\r\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "HTTP request sent, awaiting response... " ] }, @@ -168,9 +174,33 @@ "output_type": "stream", "text": [ "\r", - "pred_probs.npz 100%[===================>] 16.26M --.-KB/s in 0.1s \r\n", + "pred_probs.npz 0%[ ] 142.53K 668KB/s " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "pred_probs.npz 8%[> ] 1.35M 3.16MB/s " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "pred_probs.npz 50%[=========> ] 8.28M 12.9MB/s " + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\r", + "pred_probs.npz 100%[===================>] 16.26M 20.4MB/s in 0.8s \r\n", "\r\n", - "2024-09-05 19:42:58 (169 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n", + "2024-09-06 19:43:13 (20.4 MB/s) - ‘pred_probs.npz’ saved [17045998/17045998]\r\n", "\r\n" ] } @@ -187,10 +217,10 @@ "id": "439b0305", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:42:59.037334Z", - "iopub.status.busy": "2024-09-05T19:42:59.036934Z", - "iopub.status.idle": "2024-09-05T19:43:00.344176Z", - "shell.execute_reply": "2024-09-05T19:43:00.343566Z" + "iopub.execute_input": "2024-09-06T19:43:13.213109Z", + "iopub.status.busy": "2024-09-06T19:43:13.212725Z", + "iopub.status.idle": "2024-09-06T19:43:14.513752Z", + "shell.execute_reply": "2024-09-06T19:43:14.513226Z" }, "nbsphinx": "hidden" }, @@ -201,7 +231,7 @@ "dependencies = [\"cleanlab\"]\n", "\n", "if \"google.colab\" in str(get_ipython()): # Check if it's running in Google Colab\n", - " %pip install git+https://github.com/cleanlab/cleanlab.git@bf41a3a84454bec7d8f3943f3af833aabd335529\n", + " %pip install git+https://github.com/cleanlab/cleanlab.git@9c563ed5c55574f3f6fa5ce0532b0ef711a5f774\n", " cmd = ' '.join([dep for dep in dependencies if dep != \"cleanlab\"])\n", " %pip install $cmd\n", "else:\n", @@ -227,10 +257,10 @@ "id": "a1349304", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:00.346737Z", - "iopub.status.busy": "2024-09-05T19:43:00.346278Z", - "iopub.status.idle": "2024-09-05T19:43:00.349652Z", - "shell.execute_reply": "2024-09-05T19:43:00.349193Z" + "iopub.execute_input": "2024-09-06T19:43:14.516436Z", + "iopub.status.busy": "2024-09-06T19:43:14.515941Z", + "iopub.status.idle": "2024-09-06T19:43:14.519305Z", + "shell.execute_reply": "2024-09-06T19:43:14.518871Z" } }, "outputs": [], @@ -280,10 +310,10 @@ "id": "ab9d59a0", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:00.351675Z", - "iopub.status.busy": "2024-09-05T19:43:00.351340Z", - "iopub.status.idle": "2024-09-05T19:43:00.354237Z", - "shell.execute_reply": "2024-09-05T19:43:00.353818Z" + "iopub.execute_input": "2024-09-06T19:43:14.521508Z", + "iopub.status.busy": "2024-09-06T19:43:14.521171Z", + "iopub.status.idle": "2024-09-06T19:43:14.524052Z", + "shell.execute_reply": "2024-09-06T19:43:14.523615Z" }, "nbsphinx": "hidden" }, @@ -301,10 +331,10 @@ "id": "519cb80c", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:00.356189Z", - "iopub.status.busy": "2024-09-05T19:43:00.355844Z", - "iopub.status.idle": "2024-09-05T19:43:09.562038Z", - "shell.execute_reply": "2024-09-05T19:43:09.561398Z" + "iopub.execute_input": "2024-09-06T19:43:14.526149Z", + "iopub.status.busy": "2024-09-06T19:43:14.525818Z", + "iopub.status.idle": "2024-09-06T19:43:23.627822Z", + "shell.execute_reply": "2024-09-06T19:43:23.627249Z" } }, "outputs": [], @@ -378,10 +408,10 @@ "id": "202f1526", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.564850Z", - "iopub.status.busy": "2024-09-05T19:43:09.564291Z", - "iopub.status.idle": "2024-09-05T19:43:09.570178Z", - "shell.execute_reply": "2024-09-05T19:43:09.569596Z" + "iopub.execute_input": "2024-09-06T19:43:23.630427Z", + "iopub.status.busy": "2024-09-06T19:43:23.630129Z", + "iopub.status.idle": "2024-09-06T19:43:23.635623Z", + "shell.execute_reply": "2024-09-06T19:43:23.635160Z" }, "nbsphinx": "hidden" }, @@ -421,10 +451,10 @@ "id": "a4381f03", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.572335Z", - "iopub.status.busy": "2024-09-05T19:43:09.571988Z", - "iopub.status.idle": "2024-09-05T19:43:09.932566Z", - "shell.execute_reply": "2024-09-05T19:43:09.931972Z" + "iopub.execute_input": "2024-09-06T19:43:23.637682Z", + "iopub.status.busy": "2024-09-06T19:43:23.637404Z", + "iopub.status.idle": "2024-09-06T19:43:23.985761Z", + "shell.execute_reply": "2024-09-06T19:43:23.985192Z" } }, "outputs": [], @@ -461,10 +491,10 @@ "id": "7842e4a3", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.935037Z", - "iopub.status.busy": "2024-09-05T19:43:09.934669Z", - "iopub.status.idle": "2024-09-05T19:43:09.939240Z", - "shell.execute_reply": "2024-09-05T19:43:09.938758Z" + "iopub.execute_input": "2024-09-06T19:43:23.988095Z", + "iopub.status.busy": "2024-09-06T19:43:23.987906Z", + "iopub.status.idle": "2024-09-06T19:43:23.992118Z", + "shell.execute_reply": "2024-09-06T19:43:23.991556Z" } }, "outputs": [ @@ -536,10 +566,10 @@ "id": "2c2ad9ad", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:09.941448Z", - "iopub.status.busy": "2024-09-05T19:43:09.941115Z", - "iopub.status.idle": "2024-09-05T19:43:12.624115Z", - "shell.execute_reply": "2024-09-05T19:43:12.623415Z" + "iopub.execute_input": "2024-09-06T19:43:23.994018Z", + "iopub.status.busy": "2024-09-06T19:43:23.993843Z", + "iopub.status.idle": "2024-09-06T19:43:26.637725Z", + "shell.execute_reply": "2024-09-06T19:43:26.636888Z" } }, "outputs": [], @@ -561,10 +591,10 @@ "id": "95dc7268", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.627139Z", - "iopub.status.busy": "2024-09-05T19:43:12.626540Z", - "iopub.status.idle": "2024-09-05T19:43:12.630609Z", - "shell.execute_reply": "2024-09-05T19:43:12.630068Z" + "iopub.execute_input": "2024-09-06T19:43:26.641128Z", + "iopub.status.busy": "2024-09-06T19:43:26.640324Z", + "iopub.status.idle": "2024-09-06T19:43:26.644620Z", + "shell.execute_reply": "2024-09-06T19:43:26.644038Z" } }, "outputs": [ @@ -600,10 +630,10 @@ "id": "e13de188", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.632540Z", - "iopub.status.busy": "2024-09-05T19:43:12.632364Z", - "iopub.status.idle": "2024-09-05T19:43:12.637863Z", - "shell.execute_reply": "2024-09-05T19:43:12.637338Z" + "iopub.execute_input": "2024-09-06T19:43:26.646963Z", + "iopub.status.busy": "2024-09-06T19:43:26.646497Z", + "iopub.status.idle": "2024-09-06T19:43:26.651999Z", + "shell.execute_reply": "2024-09-06T19:43:26.651546Z" } }, "outputs": [ @@ -781,10 +811,10 @@ "id": "e4a006bd", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.640008Z", - "iopub.status.busy": "2024-09-05T19:43:12.639588Z", - "iopub.status.idle": "2024-09-05T19:43:12.666041Z", - "shell.execute_reply": "2024-09-05T19:43:12.665536Z" + "iopub.execute_input": "2024-09-06T19:43:26.654071Z", + "iopub.status.busy": "2024-09-06T19:43:26.653731Z", + "iopub.status.idle": "2024-09-06T19:43:26.680854Z", + "shell.execute_reply": "2024-09-06T19:43:26.680272Z" } }, "outputs": [ @@ -886,10 +916,10 @@ "id": "c8f4e163", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.668048Z", - "iopub.status.busy": "2024-09-05T19:43:12.667853Z", - "iopub.status.idle": "2024-09-05T19:43:12.672253Z", - "shell.execute_reply": "2024-09-05T19:43:12.671653Z" + "iopub.execute_input": "2024-09-06T19:43:26.683063Z", + "iopub.status.busy": "2024-09-06T19:43:26.682748Z", + "iopub.status.idle": "2024-09-06T19:43:26.687165Z", + "shell.execute_reply": "2024-09-06T19:43:26.686677Z" } }, "outputs": [ @@ -963,10 +993,10 @@ "id": "db0b5179", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:12.674498Z", - "iopub.status.busy": "2024-09-05T19:43:12.674041Z", - "iopub.status.idle": "2024-09-05T19:43:14.136811Z", - "shell.execute_reply": "2024-09-05T19:43:14.136171Z" + "iopub.execute_input": "2024-09-06T19:43:26.689077Z", + "iopub.status.busy": "2024-09-06T19:43:26.688908Z", + "iopub.status.idle": "2024-09-06T19:43:28.095086Z", + "shell.execute_reply": "2024-09-06T19:43:28.094529Z" } }, "outputs": [ @@ -1138,10 +1168,10 @@ "id": "a18795eb", "metadata": { "execution": { - "iopub.execute_input": "2024-09-05T19:43:14.139136Z", - "iopub.status.busy": "2024-09-05T19:43:14.138650Z", - "iopub.status.idle": "2024-09-05T19:43:14.142973Z", - "shell.execute_reply": "2024-09-05T19:43:14.142382Z" + "iopub.execute_input": "2024-09-06T19:43:28.097561Z", + "iopub.status.busy": "2024-09-06T19:43:28.097109Z", + "iopub.status.idle": "2024-09-06T19:43:28.101190Z", + "shell.execute_reply": "2024-09-06T19:43:28.100749Z" }, "nbsphinx": "hidden" }, diff --git a/versioning.js b/versioning.js index 44a302a44..0d909dd7e 100644 --- a/versioning.js +++ b/versioning.js @@ -1,4 +1,4 @@ var Version = { version_number: "v2.6.6", - commit_hash: "bf41a3a84454bec7d8f3943f3af833aabd335529", + commit_hash: "9c563ed5c55574f3f6fa5ce0532b0ef711a5f774", }; \ No newline at end of file

    Ig;;w`n&a(QQBZs-E{>nDhQKFYnR5 zpn7tI4Ib$EokCMrbf1Gp_9Vd-C_U|;L51Z`I2$90oseHQ9wn&hfXsZp@pw-){Ov; z2@s=(`%K9~tH`8s<8KZMKY&5Y57N7;krq@4kGp@EDO3cJ@VuocgkVXG&}M<_J4;)5JC zj*5B9#e~8R&Fy*2xaT{@X8fa%8GrA^m!5Qpu> zEL&^~g3B`~DGp(sPNbbCtiUhogucO`Ii*C?OyF2#`$<{B>H+S3Dfn)&t(UTtD;I{C zM2A>Jh6pnp0?#O$f{7`E>X@)+QmSoil%dUdGqJeo+|}^I971R=$yucL{_6p*30^8F zwaj)~Im4AAK(-!_0qSO9+x@0!T-dMv-rYN1e5t2h>H*L1rlDrp!n0Yl-1MzybBR}Uil+#zDXxRZwbl3v9%Xjar ze0s<2vKpwHv$U@A3M)t5l4tDNfO=bPD+L(* zVnBbPIlxPvZNR*3wwVey2969IidRffR2OcyRhE@WT(@k=Z6;TW1nCExfgx*3X6V`r zqWsceB;+{4IqopNYu^4F-`n2yRXP`9Mc5d-koB;NxsZ0Mt+FKVqtMia?BSrX3vsRz zUC8=X#3cCD7el1+I)bsXfRg)d4@`8j!U5Y3zWh1`rs92-1IFTQmoAF8dAhH7jgiFj zTEi;!s}r`?vNDfj6lUM5vrAhki@8$l_vWcrPuij+-{yERf1OWru>Z6T=voWRF86HA zZhHnZTe~HluV?rnj%UJZ+IntHqG~pVbsyx`xnl+3F|Y?5DPHa3Lrw1dK~teUJRtUTbTJR0)*+9A?16 z>3rpPhKzhwndwygKMz=O0n9m(d2G&vl1MAXPKT;tUFH6!(2$nyp#K5|0VBWBe zpXUl&ElzU(v)VUebBrU2DObR(PII!agQ~5{gn)=IY#WqBNS!W#H+j4#TA9q1VwVq_ zf&9mNB6RHqwH*9xYPtL?ELU`uSXze|qur#efHhEYxY@8FuL@JhbJvX(@(Uk@{LG6j%@H4bZL@_-_YuN{DBfhs$6p9^o?6~7 zXL5v81Qc}3F}`-f)aZ%`D@Wzb2$#Y*SmD|UgY8J~v;IOf%zIkvj*kj{_77ChIADRX z9dpJjoz^g&W5MrbR?2i%?c50-cvkwdIf)GKee1fvWEsFfd?QJ>TZDJ{nb5 z880-K`huXYIX!f(1(n`IS;FB)HjTIfhAimZEe9>v;(NWBnC0FJ9IMgT#wxuMR$(VQ zzkAL;X$t|P+WZ~|hP4^25w&^c8l5&9BZfj*lwpy=J|!e* zyB(u@=A0=e{lP08e1(>~>%^4qJmv7iHM)I|-`0?Qk87xBao^+9HNGzJGQy7A_h|R5 z`yO%LJNJl9P#)Uu55C+SouNxo>SUOTvlgtv;-ofj9h|erPwoog&E|#W=|!to2xOl6 zNkUG0e|aDt(s*7NDT1Vr%(3{%V<3phu18#bF9?ukzVi`Rnqu-YD7_h8*)&v3b;a16zhosxKN_Few(<7D2_9#h z#{JEln6nlhL^SWO>ofJ2H3eHbzJ_>7uNxQ87{;c47FJ>1z}v$KZ|7W;<(m|mTKtb3 zG`9H5K5{vWWm?|BzzfHeK`Z8?z1NomMP{_Wi$1v955@VvjpGAy0|!}knlBv zGO{j#&QmYGle0~d+9I&0g|BfU?4vn3(UR1YgEb9b(==FJ2K8d5m_e1z^mQK`t8fNo ztd-z}`8iHy4kU~-0bVH=`YMqM*YZ4)vdkPP#TSU2&ft(@K}K`f%Rp7jBJ_*|zAu=E zS>z2jZZw*)4mycg=p%SF7v;PwNd*L$s^DP`7^~pMOfl#2Fb;<#JfN&*4QbdgR*q7rf3$4HNT<`#aQ#RfwJ5{ zNO3;!*<;N*PUL*7!B-~RW$9u~>nu}QwuDuDtl7Rc#}*(DhVW*w<{LWj00Nn(Ub5v3 zC?b!?LmJ1L`yz7{e*)oJkaxF=lVi zNi<27E9}UbtbEU5z*6OJSSfQ1>K{9D8q3OWtd2{S|Kdt9CBK22yK~ZYtp!TzQA)VM z2qjzr8y$>Qaahsrv%v?2uOEP6Y7yx5+tH3ez*LDV!z!%A_yY6Uy*Zyqtq3UfN6k4{ z?2oDg(H~U?I)7x0Ax?q~t2CeblJN~ic#xUWf_E`Sa|j7eX(S;=b4r&E=G-hI!5cD= z73_NqhM90D%I_4Q^G*u@@lNAW&!Tr434BA@FoYdvIM42#+HjKRy%Uq|K^;H#ne$^0 z;fMDG(1w~H-=HPuTpmcN^PzS2a9d4@mkU5>aG31vAJzN zHit=>?Ii`9+)NH1!Q`e9S~QbO{5WT0ptKf&w*>hwCYLi5^FGSo%(Y%?D>(69O9+NP zJ1`gZDH_|fwZ6tS1>yBv# zIAG*|BpWF3v-6jdVJ=z9&K@N&M378D468Ju^b{{8_mIES6Y@2Oi{N{%5<)cJ)3%6x zWHDJTe@|fpB^*zvI2EkGLZQ`5toP z^*T{DSZ^xI`mhR%lJ2>{H%o@AbHnY?vT6^tZ<6I+uq(6Kh?6oSo^+B2;PWMRb>a*5 zW&!e0jDqo$WS0mB-!ORtjrzX7JQ>27%}YMe;B;=N+j`7=x#@Z_#?@c%>+m%4aHZI%c@6f*t<)LhZ`MFRPZAvTewne>K<^vmVK(OwP5PryU5(w zWM}xni}p0-eXc_|@8F%^H4S;j2fXmc^~8Jxm{iA(*2L43T|MM)^lEht4PxvezJyiG zL%i9^9t^&!Yi}w4MSGxb;t|&aPE)?~5#g867`dei6C~04xM7v%C+_I{1R_VO3u2qt zwOy+hvrVa~0jnT2nw#hxW4{pq-*AB7#=C*PQyzEB)_IBc*(5!QM*WFiqDHo_u0|r9 zI9+}AxxhV6+Ps^94CtvNf2KM4(+K%mVzRcmeUS`PEl7SLiAfE5lQ@$==c&$C_VRwx zy9lh1{nrK}ScA6qu`+zQ4uZ7;*D5axGt39uXka?mu$pjOo|`SYhG_=uo+7aOe{c=q z6c6eeLJgG?Jn4XqYJRt6J)~cCVz_HAhFe}S;E6W0saK?6kkA8aFtw&)7N)`2n(q5h zeJlI_#+v#T<&_E3(Td zwnqJl*3<-~4-jH*Lxj?E8PjW;a4`j1u8-+Y)6t)5PX8i8zh+J+d)rS-QXT>?#GIDV zvE2kZPYrw3-U`_T1S`ax)`(!I``O`Y{wV}T%!zwGlFbn;UNFo??^d#ta9mzt!Pdm> zH7)XG_dB2a5E=|)yGIGtect2EN%M&}5ztdvDyHEpOp#7}9@>c|}7 z%{P1ag9dNe>ndHjDx5vE2mMCcHx>pm$QNYqTlSB2AVR{SQigCylJ!KcfME^hjK(gm zpa!S|THnozk{4QaIcXBYz&LrB1FN8epoc`hO0=iQ779!~-8v2!d%6^>=-=m9b)L=` zNqj`ixT?fB0sm8a{NLwL5FFewFa9*Az8AGS46GV&Zz6vO`!GwU&r|+>O`zfDRjcoA z1wNZ#e}P<~*fhc3TYi9%=xua;IqtI1!R?~p$X7#Z2a+2)MQrAI^%okXE_hzGlDzuA zKFmF4_03f{Hj*tku7K%yR!b^tQLP>`f8&w zHI&}0oSn<<3gYM3+bA52X#BrE6AobZT>BD}U4R$n*|(S+B>iHZJy%&IAV?Mq7P3-~ zb+?o36D1{s)rlvVB`RwU9G_rTkDS?5R1S7BNO~0kzs0kW6{8O66A$Pu9zO^H9G@O) zRh$RqU*kEVhwXq5GRsaIeUgU1^%DD##0>r)V;<73qY?~psZ3I)lmODc%{8w#M8%u@A1@R@9{7yygcI7 z5{FW*fT=l1SY@{t{<1;b6Y^3|qjdY~Fq79)@N+yE2k&z{_&>hS@ia$-B5K)lJWnGv zBe8i7d5)(ygiEWBp5uvyU&1cPut&)utH75@}W1Bq3;?hd_E{N);(jT?p(a z1LcK8@42UV-g^G0cml!QGQXAv73Smzmq|j1;Cvtbf(ZCL%A;>Vw0%tud6dVb4nNAX z+i9;s9_3kg{#IS`D9>g#8jz0J*|6qkLjq#R%^K>7(+Z{-*( z$n2FHFC74RZu=15c9(tH9roBGb?r*$*{gvP8|*!mA6R3A7Qt-DUzS0^5f*+YsNWQ_559WVoA0EmTptgh`py@{YAtlnT zNec5WJc1Rlw%Q2g;5ws!S#{of_T!Qg%bF4V7 zF{?6T7JZ|Krx!mG2mE%}?^M&}3+?fOQAL_uJ`~Dt}b9&}c`y8bO!iu;+VpvUC0b`BUYk!cwM=q<*KW1+tDV1q>@N;{&h2;^bMB+jMnlI>N$OR&T>9CaaH6 z+833S*XU)nii5_on(Yu}^)@KD#_diSBZ%c>Sfz2)#XY7IC+F*_IK<&0Xxx4;74#JH z#4GkrlKcgPhto&y9TnzDHWFj_i~#1T&A+s-mgHM_#NJ$T$so4tA^3~?=dRjkfD>2k z%jLge2XH&461)1(I@m`$K)gbq7}!;tTxsmo+dyaoR=@^Pi+*blkd&8Mo#<^&5^6bU zqP$!I>kj`Ymp=wL$qb$MHpZA@EjFyu82=?cr_Un19fU!n>;g-FK zr0ipLB(@c>0u2zV_QMV$JPV!zv8m!%E}VV|{T&9LK&(aXQ>2y~wM-5+-N!NXS( z7=NaOL6j3A#yqySmZcF0q9w4OPAZGUoQmDfv z%fY$G3G#;m828o+!0PMe9T9$VB?zLw6T?6}UJyZj?)#|ERUOB_5IA1=qvS>`Pu5tD zcP5^qe>)1-zt?g_v+a|MC8_COsc^^5NO=Nmr~l$AW5s@o(AZp^?v2hBb*~R_*d6-A zC_Uk5&!vF7G;Taa0qs7NS_!4vW?1D;jw+SqeNgE7b#g|jn_iLJLm>0iBf}gIs>r7c zQLURINWFy)|H|^`g{W2|darE{W|wyZY-g_Mm*7IU$j|WkCtn zJ_k&E&rx6fD%VlHi1HFE$GK8j2AV=ao2wJvbIkWsdJ9cMSkuL{X*?W%^@?^c;LtRdgIh-7 z(%fKvbz7)fd%pud)n#*|S4ca7Yt2hVaE+I<#tA{`?c{E5INMK;0r}Mv;V$_4sH3lPmlcC{$6!GbkEUs~-JN5OLArK=EVAf; zHwp6ck8b4WeAwh|_K7i@s)3Uy92TV!8y;&L$LF2R$IraAHs7}4p z&u4|In?7)aNJ_jgAX~MGTTch%KuO}s6>#F&ddgvz$wi-bSWHsttEV0NOcu>H|JN}| zN#gLs+4dY(zy?>-&N$K}Wd*Av*>)Byz|vfyo{=evU1CFC{R$k$6Bf8!jaoaA~()P|j41&rDpa79{HS?znt5hyDk zvlb#kdnrO(Cq#f;0qYfX``Dp>#`9N?cQS`(4tLQ=#xsXou!_y*Hh$t5<_}Np6x?>e zqpx%}S8M}=#uJA79&t8z%cGkx7-NYh3{i$vh!p&p#}9Rv#PPeh=vh*DVTWMkJ-owV zBrHrcfmM(mEi-}Nf*&KPx4v~;l|e-B0(}TJN*BT`^;SOyvk938K z;nfYgq^0);a!jr@8q4Qk&j#PE=Y|Mhy3F-IWzZjS`oL$0KOE^wU>?&6>>dMH0cY9={&XBu!dMlGb=AOoe>vJJ zRahxrkO<2Io&I)A)U`$~l5=$J>5WBhEaK?60yem2mYuy4CH{Ze|aTO6l9w`-_;^RlmT9qFs^Fm?_3mNC=rd&w*H{> zIkYer;2f>2V*DkG)5}?b0h1EY2dT?u6>)A=Y^))PW*%06qnQniEb1JqYbQu*7?l(^ zCW!!C0Yd^51Uj_{fFDLYs~6B|gn+StK7du4fYgW}XH7r(d%c9d;h?dE&ihE{gFJ5p z=v6(vP6(ryLlUp#8RD-AV6Iowd=^1U!GpQ_7ZQuVOA)8Xm@1TV-jrW_*L-H?y$D}} z0Oo;`dpEZNZTqGNs^>~OD@k$-2n?tHhF)+v6^Iv@UyeRs*4ZCKd>&F9Tq^5Kkh{We z%$5YQyxoBGrcSgd-Rt&|dhpOOd_1u`x13ZQRl^WW*ONG=k@Y05fH7F(qE&b8-G`NP zd{{Y)a72rmZhKI&!y_(U=c}-FVnS*vP1Krccc@j?31xPMX zdM`_JgOWhW6)+k!!-JPxFXW&%GjL*dZOZCMc`+0^cWW&fjcM$N=ff)Ih{IlXh8L0T z6q<%gD+i4oaq31fRL@;~o$W#A;M|(Q*BH8RWo8zL@}_KGZp3aPm@PSfuu+#bw@W)#CkR2)tQqaT z8PlSs$2&_%it-+7jCX_2^l+|L%5tSp1?kz63p?HA!TUX(Z_3JhWDkdj76P&NqBO@X z5{S71rU@Xnw{z1|rj2dM$L34*arO*1JanR|lZQ+&H}`RlSGwv+i4T2+6|nKu)V|J8 zNqL>skp$#TR)7)YK8tzxNkOtl>>p5 zX}(<&R`O#o^C&scnW5OZ?ywWFvI36m(u17vd%Ig$oj9ZRUc2YO$=F;0>krg@16u)p zK=i-w=`8pp8pPOwPrxc>!OMm?(`ETv3QaBeItPs{`0RV41)q4&H`z7D5+}RHRcD7e zSA`q$RnsnbL252M@85c?YlRZFiJ1>#b9h-+z}TXJ?gjH_J44jh$GM;;M6sqK*S%kM z=XxV&nV{RwuIj6KZ4}IAJ+g!1~i9`lXlU=)Fu?)w6pS$1!2OWjm~5?9Q9w>>nUs(AZrS zBzINLa?qIH`$T?kH{iD+x|rYLhE*CRkBED{Fv~gdDeS*Y3}9lCYqlb9)*C?R6UJi3 zE--zz^NLc6Yl{!sm1hNbCSGbY2$~C>7vE6ug%Z8@$PGjM5m&&CyL=w@NBFJ4Hk);} z&8Vjc#a4gpuL-WnLgu)mc zo2@#v*C4P{@TM@Co5gqE=21q`IUC0fGH2rom}E7z?V`K?>yv)n@!{4@LbNt#iw4fN zCFH;@=5w}Ql#+lgx;dM?MNGzSZq_AZ^G7AuR(?c^@;qyp-RS6u4Nxh~k2^GnBp>v%)HyqxkBiB}Ac)xn|GEIeP4Ly60_R$P@Okf$ z;;O5_Y4?|>z>drm=0EguPLC}*h3URURG22Dfo^Wx5F*U8`PnCPhcrHu$(*6u0mn(_ zHscf$j6CIZDLXhka5&n^3Yhk)(@#4qN=iPfBkATzR)8I1{uYvF^9==u=)I23jYHxV zSHK3=%%(2rbs4UsOb7U>%sW`V+J}#BA~cL$R7+1Y=+1NKW*eaSpeTWRi*JrX7@Clr3eK^`vGq^KDS3lY6 zxK*_8`dfYNn?n%0t5B|h@m>A>Q)i^4OhIE&XMks0oj-T3Q{Lf9q0aELtu9xbZ%I?Y z_AAbcI$%Kw`cl*3#wJmbD`3cg17A4Tnkez8FP%=4-O2E;oadAsdR*f}x3U5@f;#Z3 zbGDz7&+5cOFy&Fq7GH!?~=IT!lhYlc~r-W0NVmO*EM& zP_;ReF+>%cOq5}jM#bm48~#4=vfDP%f;vOoGz)^aeCh_e&Xtyj!**tCoL^J^CT!Ei z%Qv=(_SAWsuRV1{tazSy>Am!d*Z}c1kC&M~q^>5UYFm62E4yAVB5#4RGRvgK(TjZV z5y(9CVWjJ35%~xfuW=@oB!UdA!wMreZ|6E#O5O!gf>v*M=JzaR?{?H5IrEF2(1I`L!~eGeJ)18r z%B@?j-R^7pnTRLPWBMO(5-ybH?+j`F+AB7iE{DJBiYX#LhJu6UZ@9VjdNFeF_fG<; z+v0CG#5KT=Z1Hy-;)2J?OM>*-F5{QB*{o@d(4!hY%oSEd3g=*jm$n(~JPnq26VmU9 z*f{RvVqY8Z{;I(HXZI4l>FCr;gd19w7KT=Xf-U<(vd$_M{Sy81!1*z*ipHq~crwOy zRvEm5sRj=H16TnI)oP1zt~VrQ4674E|9Xlf2Tl?tu7LFi7EjQ80Dk;(2^NF*HSZKO zjxG~Z7P=+^Xko>)m`q(&N>;RU+52nC}{y8}<*gRhn}jbH^#!eGFB z*Ck~dt0ME#xvT(7VjB2%fh$wjPLRZ9DhX~BA_=a58+KGOmIQvj&Fz&0K7;2(LmL}e z4y;0=P#q~QC0IJF6T<-x4vS%fj~H@x>H@4WW>^A-Rhk6;2I&)AXfExOP2Yec=$B-^ zqc{V)RyQxh^+1+(nP-^(K_tXHCV+YBqfA$#B$t68W;ZT^1rTrrxW169K?t)1GgO1% zBZvIwPBFp!jYO&JNci^99E&DBUThjZjK?j7DBEz2f4Aq z^_9Q8w-5~(O9$LdAmK~Fn_ZIwm z5?TTLu-~=GWc?%W0Gxt^?`G?2;HCFnBXsQq>JIphK&az~Wd1+>0~{srvwXS0aS6w393>oRXyYhh zgH%Mg<+MZYo8M3yweAMBzN0c zSBp?%Sw1=IdRMu_c#35iag!A=S!!K>6$D~OCntm#-s)RWuoj?z#a?j>-lLn`7TaUW z&mypj@$>f!t~^<;PN6A7t8vhnp(XZ+3@x%p7kdryB`d(jRoyOQRq%xDNjkp{)NW|p|4D_MAQdkI*5BhLxA0b+cwhO;>1qaEOVLP+cKKSiP zeEIdmJ-XGt^LxbAzJ2h{-JdCyb=x+3kfuD(l)nNU9kHQMQj4gfV)&_4k?C}Q+fT0U zesZ{Kt{GG5V3i1Do|<&qb=XgifgonNSc(X;=NDH4Ke;UgF;k5!4Me9JFQ}qw_^G}O z{SQQqXXvvB+6fv*aiD#Q!|^EO4S{o?x)m_tch^)CXZGlKmqnS!A%}uz_-s~SpuC&F z_8HAWK-E877nS9#B?+aOtN;ZYdAUj!0QrU}+HjN5EtE2TRB|+{=U=W0lCqg~DXtrA z^92Rh{&w9|4sbB!ttVE1gWv(M@QJIht{s};X8Py0S1yZfGwr$EbxnnMxx)YryoAY< z#60&EDHknaZm)5?hx`{-Qf-Ux5gOV!U_O9V%)z(v%S{N7L-&&KKplLUy$l*V_{XZ~ z;2%JHjgyI z!?*&@(7?FZU6s|NrE?oe%5gLz^~C71DrYyheYFnGUEqyM;2)AZ6+A4PyHfek9Q>{k zc-8VNL)9{&xp9(mjRVCdbb}RO6S@Y%%H=-LwG-^(7vCXB9%)E7__I9LEtviEkW22< zB|gFXm}UzrKgD1bwhO%SGpIuDV!0Ltre;x{1IA`idY@<(#o&YI&tn!VDjAzaZ`iLs z@9E)1m*zctD(Ai-kAVoASX7^{Cwb z^1gi}i15&Ys)bVuxUmaUwbbglYa7fHD5?B7#O_Dc$=$2eU_FwM9L);w z5HlzB&tnWJn=4J#xre={E%Nhrh`x5zoxjQJm*|21~+k+KweCb|4_jgHo zlhuha{w0bF2TpL|3Rr&{E-wdr-vYz4sk<#elssp@&Z*2ogBl0h>9C3g+l+>}pqQLR zp{Z9{!$D)OGH<`=Ri^LPc@;y1$>9LQDvg$L!4MbI9dqdzNN=NiKrf$Qugw<1+U7>R zAb$a|G211aN}2o_>WW*N`xyPd0oXP>t2DPjm%rcF3mii1c%CW41WwL{kXr}7i7B|$ zpaWD`bjC1nP;RGSxyAu=pIWy#@u`snGEc2OI``vXxhVuOn=$kiL8eU0ts5-A0zu5Y z>KqM3=T##Ph+Z}5fGAdW4|Rdo=8XWLAf!cn2#P0N)fxvQlCj^p1FM+dX}>Brvxr;*em)W%aG-uiImn=~-+6dI^gDN;iE!DB zF_tLFk20*%{LUxE3o*pna?69FB{qY&K@j42f_3}u;hx+s!Q{H_q=4iy(ho%I#i4J_13^T+t62h}RWKpDnE?9TYv$0t0@| z6ZrY;o@f;vec=JJNl>`fl>}9zcZYzZ-{y{eO1|-4ad2_8H5$zRF83AXF^490RDZGp z&NySg&poCDA7Uzk)36X$fODkaLtxVnxnp$=1y540BoQ1p3~>rv0XJ^ZADL6Qa~nE^ zmWOo7NHc_iu~TRatFTi*GaPl)Pr1z{xi5vLPN5eEjhuq?66kd^m%jwm7%r}(Wj_9e zN@Gm%Qn_K3<{0V_5ly_6`^Hm56k3vqsM2jHqD73$BqdzP3OH6>yq$Yk$zW9^jkT}> z8cI6d&26h|CrGFvl@K=ymQXlXz=qX`YYs~Pn5!+r54OU@@t9s#`3MzbSsj8^OjaNN zl6wTcBdeFyXB;$^)d^8nhYsoeH=~@POIG0xDFJOC7|%wF92On6-(iX_osEuqnER0& z4!7*h+*Lf~X(a-fr{@2j3!lo3fgom?(`y0TcU^z^VIitfq7?DEmk7Vm^`$Of*Mo;lgoTRz2K-b7em;93yP`3aq|}D` z1-=Y-&o)V^$49u=D@~3txuQrF(U27wsA=s|pz22#|4GB=Nq)ib`KAlY~-AATGx*{m4%4kb9B zp@Y_-xrZfs`T~+9i0?_m7&v0xXy*g3$eat`9VNe*uajmCG?KA2BViSjrrgkdxv1Qp zLQ`qB;h?cJ>*Ql;au3l&g7j@}_8DYjEb+|9unI9BYi3fZLjCE4d@<0DCFpxY2RQnY zJ9=KzW(^uP8!~yq^q3*TCX9`#8xh%eh`ub=psayGSwn-eMh0b#`LcNvrpFo#jLUQl zCroc(&<>Xg?HU@i!(~FdMyQ>_Q4Ainc1H(b;z8Xu?l^%r&3L>i+D#40gmxH3p&c$0 z+F=xR?I3S(q0kWHt!p@8IxZ91HAeIa?QogUu8BcATsBW=*wmmQE)&`{GiZm)gm%ph z+Tk+VZk|^)W3g@uq>w_P%UG;9VoO{owltDUtWGdvsb$3aiUx|`NHnoVvLS`y@S=3U z^>*%#RQWEJTN47>w0F0r|F1H`-I@M8-`?Gg{tSQF9Y=podfDBV{yhD%dm#N;yMwzQ z{kf=vyA%C+v4gue{aLG{dpiBu_8qOkosRC8XlZOG?Ptl^+Rt9_XAtud@NBI+3|#2s z4glp|aaS&;)qtw&+~vUC+3sq5>)3(b*4eMPEATZFwVKagaaW-z{QZjiRr<4EXAQ^J zb2V&|=DOR`1}}DTx1m4Bb#ZrOea8|Uug!%xe$vHVjW&ARMeC()S9c3qIrV;d~*MBJQ(RPj@)&vwKgCk)EC!k}DQzNM2av zZq0gW1fsjZK_hxY%s?-`|3(C7Tyv$DhO=X_yS;a)-kMq1dTZ?avbQFLs(mzE-s$6h zg^k*n2sJ+yj`~9%o>W+aBnxYz=qPc0wf@rk@amQM zM`O^dCm97=(rcPjd%dQqz2!Cc%M^j6G#<1GVc69)4Z*Sfc&wTbte(6EN&C2;hSlHw zG^~2Ou3@#}b&a<1D>Po!?av!PQ_QQZRY*Yn-H{ZjBmFg1v#sQ{s3{g3Y+jqTtiMWM zjg$=c_QwEsJ=&)3Knl-E@sJmO+|BxIRb&D_E_$*9n99v6}&` z;B5yZ)(m#nWBSkxU`Mrnr})2|T9F38uKFQv#1^bAl0>`X{i-w!S;%-OL?Dm!xQa8M%A+yS=A=7%4rhMTxjWcIP z={Q3j{{@@77VS4-v^H?B9Cs@Y(*__S39`aI3KCI1QFExR5;a8DCc3-utc#6@?dv-r zWr1Tf%ZwT0ZqN1F5c!L8AjYBji$i00R~QSfC3}0RGgjlzZHK#uu9xfcNG}24zR~@g(b<}uG0$axGSlNgu8HTMiK|}Ov zt`1Sy3L)Cl%^LvJf!?rim0OD;9d?k@>Bdg&WL3j3x_4a|PX0fzA|sCkp@0;k=Wmf9G)j&f%JYf9G&o5(566!v%nU z=Wv=n{5yyHcMcZ@{++}9JBNz}|IXo>f&V|v;d+C=^4!7l61Zn)c8p^Q-R4Zm*B#?n zkdKdXaGx3-i}n}wpL-mQb|s(ZIN}0skG0TU$9+D#j(fbDru2Bv^;V0*K$}hO+9igK zY}&j@!{#HJ$JBW1?UrDEhee?vZIe4Th*f}gJJZU`AHqFWv%^3WOOwMG=gBa6p!@g9 ztw7FZcg(g43_CV|c#E@J*~a-j1=fyiees$;XFCxZPrSS5}nfPC=T_eugBG4u0hbK0^{_ zywMEuf7)FcJlgL5P^nqK6sUBby&Cv^hkJ=qpDTrD1lXOK@p8=qvf{@r7%Sk8HoU94cgV`ytWG>p zl0^yNz{$Y_u7LFix*l-9t*qd>!^bL?u>#gst$WbDL{coQP8>Uzj?IDNu_L$w)*t$X z&kSrV&7Wq;`VO8e+*hDG{;&s)X?*-)C#+(}AN=#(Cj#XUDKtI)aGrz4#~%(9h=*Br z7Wf`!F+`f2E;O#1b=p1ASZv_QX((dvGnadV>fS5@n5UNi$o+;S zufQZ4yV1J>2)KROeL=QC2s8iq$P0nkKyCx!1DMl~iXJinw+O72$iLOY@e3crG~v>= zPu;c%Lvz(k=4@#Yd-+&2uzcp8seFv&#+{0axWo#WUTLsJ%iuRRp3mj zYTK_=U+BjN@1kLhwe1#>!Ww{&n2q?ty}6hie2nNS)wW{C7&O+l`##!sOQ&syR1teL zt~&ICv9>iiCTd$lhzm3hatMk0#LYWDy4!=MZ^L`p-5Ivpz3kGjAFPM&n8A;#b9cZR z9`il0%Hc-@&lNBUf$=}Px0pDP*qcx%3jc~sMrm@%u+lB}TxBW3m(z*R#jJphs0QA4 zN6X4uR)<|WceL^4G9+u@!O79aqj%k_l#L7$pFQ`0P50b=6%Q-MABPENk3M!Z=r9lz z6n!ficz$tLlRf~aesR}SPH{a5-y(j6_Hg1D{>*OZQPz}E2GF;N!TDd^QPNl7w_n{a zD%V&uOeFW=-p;hgFP_$8cj-Q;ci-Jud1&5Q7uwmcPwT9b+U|iHK0#aJI1?34W4?Xp z&QQX*Qg0el44nGiJy$Mq9DU}wX_jAirL1PvUFonv$H~Ws4Y}g;@nJ77eZ;HI{KFj~ zDa|=7gcFY4>3|$4Ni?_uP997Ca?e)!aNVH@7}1jzu(ldaua^Pod*rg}s=wWjB_)Bi z6%&sE6c?^Lf(uu``p=x>Iit+rdc#jRPLn*fl_XY*PYT0UU{Y8A%D&Az$(~xuYJGEQ z1~@5us_PmH`Q?ab!W4Yr=b?}K)&}+cJ=NuX$8`aJ4?@7$1@DAaTEGV{1$b`BA5vg% zUc>>Dyy&=3UUXb{;lhxe*abgDlGC(k;uHJ-fb=7xC+K=H%h6a}|} zJryd)G@cR^)F7roqk1vT>&391BWlGqZ36BEd4~PJJ6t>P$52nO9D2e$y_rq*rpyT} z)jV*&xTmXt<*UF}!c*p-aVD;`r$Z6KLvZoG-@FRWhIs~q3ne{`p2D4~r99yOqj7tH zH;<&j`^%6`W>;#`L^h2p>!~83`|P@N^(j1o8q*A{3iVX}e`TbSy6Joq$PKgWLRO6% zI3@AU=S!XtFNHih?whl4woY;uu7LScu>A$*q5LaA4>cN#N4wKI5-O~ThZ;t7nI?&4 zDti75kQY#B>Z0ax(AY(dIU%~JVJCd2ZpNtMiHUL5;cA{1^85qj-C^SZRy)$OOxcO> z;nJ#zZLEMXMGIh;NdN=wqCAI`0@f7ZyOpO{0ZyI@!0zgvI9)p-dVE3!%8g3m99O{5 z0QYJz*%Ym_r@DMsFPmEk0psZL6RgsrhuXWA=dvUhdtaBp7kQsSW7+)TBb%R2=)#9F zmPjm5;o}|C@F6t>*Bg1-aWBEgK(sLCBzmZS)b(_hcYlv#9J#;8 z6)<^gYNwQi3^0Ed!!EMSN(k5PU|c+&F*hQiant4vhmCB|tl_YjMomV>HfuJrX~V`t zM~oQRsBzP#35~(UphZiyZjR&k}NRIy&NKp*;IhZvyr<}WsHKtF%CDxSo1)eOobbGQWS2$Nu6*(i=mz~a@CXOmb8;{ zy$S)$Q-Pl}=qfCLpH+NUt;q$#5& z`!H$(q1Q*qYesw8fL}|(4>2!+Eez$Ga#EDAdHIy%yGsajW_xK>YQ;@2Atmm|R zo=Da3+a#Y-hM%EQ<-W@YR*mL?O#X-h+Pr7`q5J_JZx&hV+o-Oj-LL~iz2BDMm zDIZDiESzOek@PK7Nk^O#O``HCY!W__evHid@f2vzhkkU|3~mCO8H&5%DN)>&;TZqB zmOe1WeYg+q2?TfVOD`a3y62oc=ajiQ|4sQnivZ?<`nNM$f%@Y;O+e3Cp5kD_Oiwu? z{3kO!YvdKMD>F0q4Y6f&korJA${_iPFgYLm%&WsC-H2sr2NybaW;C7N{ky7C_OSJI9T{%|30+#0f ztA^l(yQ~GCOr;iUN$%yBx&vRSI{3AxkrKnI@P+JJr$N7ko-sNQVFnaQ<;9IpWb$koS?;B_QG^K}3Ss(#dw;nRlM1XG4-eQFyKJ;?gm;0I@m%3dOZ{8RRxC>yXzvHzf;ozt3@WUt_2CQojPQ~OV zfbnczWpI4%lBQt6kDwYj$mUf7&4=!(v0(<=2*ezKnPYWFYk~!?J(W3v;VA8cfqR;A zKi%l(+?RLP0DYt1(gM|@{F>m@{=6z+LI3SFK<{_+V!)$0TWf+9@4~blk#DDgAJNmH zsw=946-AI4&i%ZIORENcD1!CP>AIp8s8gI5%az;o9xT`5<+me%citOS*@?w@+5b;z z1fWLs!Of048M@o?z)L%2yw!C^?anzh{=#BM^qc&yQS;;e1D7VyEdEuL{GI1sUX-L} zDw^eV&MbYA5;XoOFR|+ADI;v=$zw*0o-$=xMshNG2Bpmt;z6q}t0N*+Ej3z$+N6(E z19OWi@$k3WWYB0#ksAEFBFs$3vM3Es}7DI%uD${EPmU@yCOgS&Z#{>6Oz2dpy|7x!7oFL{%UZ?oc zQ-U@$H0je$DU+I6R{Z4(7 z2d}f(@J2LiSX9)ZYHd7nur(8RZ@xNmADFW7yAs2cP=RWCOFuE;=~0O6fa zY{BWgkEkev$OgW!NUCU53QjOmDm?dG_5@IR zI&T7K`AuGogjy!%Dqc)D*1HT}idSA29Tl%6CEkf-02ALB+AN+JWr}LBGrrAROGk|p zMUrn#Tcgla+}5=9-{nn?nk}Ow8hNb(WdvAQvZxhsU&ymlt3ZwK^Cm{Ek<~!7MlN3i zv~Q&5p_f7;e1M zx96TDk=e{9UXYVW`;NpVdcF)oxnPSudwv!ddmjA^w<08*Kz)m_6`|@0=yb}fJ(XdW zxY`r>Yo0lrZpBmc%RS8rYP{T2{e*nEr}Byao#mc`@k+}*b!&gvjDj4bo26dnB$q7} zXMu12%p1i_5M>tL_vGa6Y5}W}?OJ{Lg#Qqng#B>oj)?&r^;lV6NJ!LX#EO3vi%nwL zJ-DB4mzav<+-5NQZeE6e;po5ennxA+6<+rj42sG%f9hA5xeu2V{R-on&-)d=eLt_g zf8h}i^7K*H{0jg1Aa9YRFy6lLNLr5Ge1fxdQUuxR zP9oq;!jx&Y7;HAHDnqYQgPhD&@odSil`E*ERJ~qjG?*+pqgtcOOtqS=>I@aERHrrQ zG$s=$Te&ihU67UY9hDfIGl&gy^eK<=q;abnf|ABdqkt#O5t(Gjv}iLdDz(vKvgves zjY+3b8Bz^et68tJ+RUu_?~M~elQOK@OqI!OO*N(3bT+fiVpCZ&wK_OKvZWeSMiAS4 zQ+3ws-t43jEhekhWQ9{Ci&1B?Su94Q-kM>~u$c52sa7p0dwz3uc876k9#tM|kalR3 zI=LLq1`wNcL-tr3|QW#w%PPL zt=gc0O=trP+ppqvNes>#lpe~_l*_s7%cTu~s^{h^;K!kklooJdl?o zJh`4$t+i;hI*nFk&CtRBjHxP%Hq)#(r)H=v;MBTH32ez@&(P4s;2TI#3&gX1ElZbE z^MkilYCXucd*4AL())Dk+-pQRW-2RP4tDB#!TCGI|eO71HLp(F|=1h|{!)7#FGcBo>Of8$ktonmWE{C-dOlSn7 zg0UR7rL#AwK%a4rs6?&Kl&R8~RThgzXE5q57PC&THbKqQHj^roon*ZP&C~)n0YO8y zm<-U*GF9-WS!2^`bs4Ep8)(dB-)uTaC26eCzcNxY3^rA!4*Hu#tJRxQRXU?8!)P$8 zK-rGXaqPrbHtnOz;RplCP9y}YIIf@EOamu>dhvr-mJ;g+6)<5*pvoP`rS(CYBY=*by77Zi&YCX(WdHP z5H#rxHnT;gg*L8Lnb|`Vp|Z*4Fg1b0iAPk)t9rj)7m=$1S&QD7n zh2Cv?fU34$DD)(Xg{`Rhj=dx456Y7>Bd~zOqt_L1J zE=!5CqvxoM*CviNk2g;pJz;#Vy%V^Z?J!cyL6en^M5;CDw$jlwyzM?%t})oT#!+>B z_N{7>`5yE;bM$x{C|m2O4w9%_G2xZ-VPb8tg1S`)++FE-9YDeSnneaQ&+4Vv53bz_C*Wjl}vqMJP^ttfR@0it& zw$y##TUjV-dlU)UvE8dC=R~^L9hu|}H9z0&{XvhqNR|z0GL#}->Xtl=CBK`?V zVJ1$_m}s7y(ZXh)YR^9ELh^aJNQw+~jHFaiOthOA83e z*qKvCPsz1wK;0ZigZUj#Mm(2gp9L|?vg>xDzpWsyS$2eOmL1`mWk-l+**ihJvh2ff z`Q=XZ+|PKFs_wdP?2_|GaWCBK0}@Ve~ihMNf0V%(agC-Qe4{=j_8#LKuX@J_0?hL{B5p)AJAq4@VMchSMievJ`E^@f6k$&FVNFq^k)>x zJ&B$wK}_u#5K{YSl!iZ}`zuO&8U3-Nv_H_(81#fc$U7E2q5DI!E03LEwzZf#3fa*7 zspcseQ*-V3!<6Gu5&U7e3Frxbe{3R7Ltnp|gr4xXRVJe+d`rm`^n~vZn2Mh8WfjxV z6TW|7I(owA&u5?~eAsCpItYYMM!km87`$t6CVH&)1zR`QVWOf|qhI{`9(-rg9gM7) z5>CNrcJB>UD8dC4*s9f|)&XXNBQYLBB#$+0`wfmtRMcL-nlh;{+Tp7T0?SvmVWT54 z8AB|u3B@nGGPbcIIQ><0b70@-_%!Mhzly8P7e$1PgX?XN!drIe*wN!Na?{ULoMtzn z7bwjyjSf8|lXpTZfz@IJd>|Nz_9{ z4)=W=V7vKX@4Xemu6(#{;Z{e>2o(L{DkA(4di^&N;qJC?w>pkQ(A7`j?x>T{9c9~E zO&vE8{XcW`*v#pv)6K0k7MoUM)*0Y}M@ELu43{K~CIeg&fQtnxxay&|7%cEWkU9g5 zeA!zKB!_GZg?Ab|DucleM@*IYQ$DjnPf&pO0rlaLImz##O^6t8X$fw9zVRv0?-j2- zAwb^gSG;;~-07IgbR?<==8HM$3GIm#$Qm#A!|F;$~Xxq^d$-as^z-6V8p_A z8L)Szb09O2%*&a#CY|aF#_V%wr9=g(S?P(5QBh=rJ^63BOBiz(8vLB^cn!Rt@2E~q z184Ic>zNsn`kQ2>R~4(_zpXjt6nB1qB2kpo&d)mVWL zeG`*P1!ZTBHfa2Z;H(Nz_Qqb&8@-_bhwtSWsrG>-)Nzc+TDZHu$P}@Oz_x>qH<=+M zirB{o5-CLKJ%=3jgaCO>4m-YOCKGhnRR|2yInhXR3?94uh~pcITEL;VV}5ij@P>4V zBq;kSP$IiaBI^>xgiknZ4Dr3=i!J>io!W}(_w7q(HX}iOp-c9{55PPK_Bwzrast~w zb*!h};fT2xmCSyU_;AY=t?BKjs%Y3_9&@zK*j$Ss_+d~`XgjN)b)vmNiuNm6b} zpVA#c+U>(F!Iz&q#xTE;t%2G#=@%kJ1i(i-9$#BjKX{?3*bd8>we6^<*bZ9=U7KC> zl$l(UNvpz?1r^?DM_2kkij$}Qwr*?PN$Q; z#@Dxij{QS z{i%3{3!A*tfgTcs;Ya?Y+>uWyqCOM$wcw|mouo{6z8ou`>CM4r66e~Zk+@p%gvI?HL063M#z6P)f6o?Lft zob4P+9RllTJI%}yN!73$sUn)tDXs?iY0f#$jtTD*B?;k6QAdAvj`Jq-9Z>*BEuyN^ zTvgu$txDD<^Xy3lI17%P@4Um@lW;>rpxa>J0;iq1O=ie2IirLL+B5}TUFdYvac4la z*WvIg;SAv&>WtjF;LX>a%a}T3G91CQ1**==BS4lZP6NJL=!6@$7dfkhKw^+KimoB8 z1qnh7qQ2n-sd9!JL{%bcCa^uc7{c0-$diwozU8WE7rYvXE4PCwfB~|9EO9oYn4u&i ztaYbl&LNDAOcu5NbD6UvH56#Foc*PgNK>NMIqwfScES2&yNWu)C*14&2%{W7+S#+* z`4Y22CI!jj3ddrZqzD@BEL-6$Wj2w?c<8nv+i7HWlF7)Y=uKxptE}DepxsJmtOAud z`rfZZ+OI6Xrj$ws#8m|;iNQ;PICvqE0kQPX2?5#->{;z>2*1V&JLaaKQV&;sy5x*+ zBT?+jA9jvHat7#~FTgz9JL6+x;W`2}k-&gSvd z9!{e}O%_)pjzNhU_2)IpLv<1-Cf-87+k(EPiNB^jdG-j8pgLbr)cG7~L{R5RN1U%Su=@yZF4uUbH+|+Z zL?o!P;S`dT>%P81BVDBu7euG0;(ROV<63{Pl4{?NVI2@cjSlf#@!q*Lz@EwPI zW_KJ*2Qy9jfFEAPoYsOXj`+)Yp$dH(mXn_A6!DtIt8(HS-?>h7Zi)W#8~MS`Vu>b& zkde>1!2ier$McNKbwC=VY4?z~9zB&A#Y@bd%qY6nw}Fj<3gMin`nTAeoNT-5dpa|8 zb4VgRk0IhxS5ERUWlygtx-BG;9_$oJI{HY!&aQhB`5VZncqBe|-j}e8rxG+D$+w7CGe{W}Ldz;iFp0qLgaBfE_qO$)M}-#62^^@OdxxlZks4hEXp8^};=EK;>hLs}slZ#mYv> zDq}yIzGreIWkY2B6-Q5R2oz+GNI!p0e)B~msH%8%2$KTEm4N*0e%YC4J?HD7ewnpM z(J$#Oe%No6VUN2+st9AR2$zGGpn%67_lOj{tu83YUKthFD^jp02?X+c0)+%*w;#wG zr67}o1UywKXN-CzG^k&~3zm;bx{I*$*jNR>ytZ;rM*~$C?Cia_4G1_q{gT%v5miU{ zW-atv17vr#g`Jn!4GmdJ?B4AQnFzRtRh+h-Pe25nu|G0%B-iM@kli>UlrwoY*>Xa(5 z^Oe2i7_P;4Qm2HS+;6dvqp4S?V(#ckxxwml?y&IAQ8nhP6N%k+^ zyDX9}f+T?^i(d;QJ`+Kg(u{`JUJdxhzr{;D}O`j_Q*h5;u?|;EXKX>DOzg7WTzuz-j_B#UHe7cvR-w$Fw z-$ZgPdw@3|0K3tRWHq%z_U6leCvdlX9}i+<27b$hP%Z3hhY8j6Y)D@WVr`oRV$#~^ zVz{OSmnn#4!|g)zENp+NS(LnWp53oc@M!$A&h{ZF&=x8BbyZM0cVBI=X5IS@hw;9mKAiCa9YhxcWIc{qHLuLRy)PJO}4dyd}M zFpk=UbZQGaP>T~3=c&HvNT})F7v;gw2sI-5s%Le|Dbc~4l6Lyx^){!q z;E-Pw?i*EwJ`BqR>UQVws(f@&((S%~QQqyoEmdU~1W5wD zK&j4ucDwD4f!8{1p_D1WV14V4gHtHnX7Bw#+f8+v(Zc{fZZgFdWWwm8(avTsA9 ze9r;B!Vm3bGPJqwaCZ>2d-FK#A=PwMWhx`=SF`w`f4CLx_ zvhVH8KO0Stg(QI-Gm+msE|7$K^Y1hC97qzVi)=5Dka3$H@RNM#)E+8I44v9Sss5#7 z-V-3kqtkL6bGYz%T|dX%@7D%ivJK$of_aDX4^Z^+AZXio96lG&K9XOXrhf>6_5?Xe z?@#h`Df)U4v}X$>60|?{L)-fkEexpCdXo;eDBcgb=Bz+aHHd!60TYYsrd+2z6IL)My zw0Ljf>T@5CWxA8e;@-jzXT2|mKoYR?{D*C$N!kc-$QYjt#-GYpF~dn>ykj}7gjFXj zZ9^%r`zh{?&dfxTLS&bmwIh{E1I^FmH;_`I9egR`8pIj}CAq;ZIB_PwFGxF=|6*f> zZQSW=6$tTG)_V2k*x+5PMw8WKM)#qpOh%(h4-YZH+j7iS6}qH^J#{vJH$~@{fYaS_ z;|R##zxh9=wh!r$2;(8A_CWi;uV2V_1UmMG zPby=+zLU!Mhy0}ShlcY=QKan@`$2raLQHmS3L3> zRtiPJXCuPV6FwSJ0X^Xz^AYF?4CJNuk{ht3bGl0kfIKX{B@0~%+Ffv(;IJ2+kca26QP-uK> zWjwrPDmSiHOa7CIjk(26Nu_u@aSK!*d76(Di94`1_eTC`ig}G>jOD3%Gk-3#fJ_$U zDY=5yr8%^T#M>v47mo zUmwbRM38Y1yYJ`EVLm03MU`ef$RA351kOFkpR7PR{qOuK%=b!^6+!EV`NKjWGZ6FQ zhc%?MGB{GWW+L^$0YzC2u=7#=&HzZg@;Lu}Ci0SK&z!+kAW}r67CeDSDQ0bWn!ku? zKo9}cFNV~;6alDVJ!&xULGTzLQ>HDa3|TMk!HXBUdeF@CBqc;SJyA5pcK(#ym$KQ( zA+E6$^D;?`1cDnMjA1T2(_fN-PDqHAcHk=QeF+ZxSEa@GB#Mei>`e94V&{ju)`u{2 zhyt9}uR*QN-$&J8;De|&J^?U1+SQR+MJA&Y0JTv;pGQ*3lFygE2F69XIxss(8l*~M zFd8U8TAOikz{t4tOd&~%5AndSFf*>vfy6tiQ2y^|S9@uBcz!blv|(IY=39mGf5o_7 zl$OV#V0tB&m-$UnUO3G%y|QZ!3u zqKS~9y7%HM9}>L)F)o|&5hrZ#r9Vu}>XKW^-5CM}Qa?~pjEDf6kkyiWt)dus#~ zcCX4!T_c(E^5RhZFPbV=kHx>HP=0SS*L|rt_;~aqg`y)`K$n)lE;EN$1DQi|OV>q; zss1x*N$9v`+|S?@6*Rv%G6%y^S?wCjG$oVqc_m12PVMTdK+sd;>cO;CBDkq>t&tMQ z#I`GlodeHOu~9l#6vYfAE5)JwB``77wTpR4l7WtZiT*oQq0YcgxWV8;@2b#gV|xD2 zXemUv7EwD! zH|L4D^J!5{q{Li<((%8@&!|QJ;@_gmg5wq~N2%TTi*ev-7uPS$i%0@~0s_B02yapt zLZ;wO{zb5}o2#X?s0`jc0pL|`Y4BlppM&tH{$7`YI$w$l=_PYumH;YStEa0jMQ@R! zx=~8aqq^7+)j7|GYBgoVBfyT%i)(?%-mW>!5eatEe*9nnh{|cKPb3z2v(#Ik{z(ef zMX9TSQ=WDZ9m*Kl4iamal*5L<0D<0nNl)Y>?z=iY&Gze*=47`14auR zUrNYj@$5+en1hR#9tsX;#K(cRtga8r={lEz*s*W51o<}CN~ZD^!Xa?i8BL@JmdiRa zT+?YLk;voLu!UhtI>R4;BBav5l*d5{WXlqx`jCopM@>kiY7B*kN= z*5Ke+IKXaAX21dYIHoU|g1V7tR0et)UM#8yc8+n?10~~JF;ZGQTC6o5&TTF73gGR2 z?0DBp((sl9Tkl9bBhnb^o_u0o3Wh!g_1!+T)t43~*{ zPm+NqT&KtsEbn_@>T7V!Eh&n<=eO5fOPEWN^1__@qnWND)O(=jEZ2T1CDOEkXo2+= zB*)EOJrOJrbxh-)sqLE_H2VUL%FUFWjaPDMGcrA#=I`EOczM#48qJ9m`y;LYUP= z1>8k3A=z-c2gqb>s;hw`+hviK$IC^gm2kOek3#uRSHeX(|N0LWrVV7?S14a;HN@M$ zJf2^FrBJ@^8dq&;c|2(TNulW9Yg}ukMY)xSChv!W4|7~inKA{Uw6(68QX;q(k^(9f zrL|!~u8MBJ-Ep=W%wOlyNXyHtwIgpGWP5Ncykv^dj9^EutFiAwj*=;B>r+j^q&LNp zR3jvV@<=KLX5o<(zK`SSde@|IcqS7Q^Fyf)Qeu9v+59S=?hvPwQ$WF6kR|si=LAJL z`Kha79;meq>)`hee%w|0J_x%{X1~ig!1nE~ZXm1El4$VOc2{5c8EdGC-|lWPhS_=r)hP;K06^2P*evWQGKe+eSmC2yHBQ^_-wLbI=$3kUhuY;M+z6P9M#km#kK0 zsMYZEE=G$Qe$^yZV}zf3P-kYs2elPmIIaSxBbO{Izf{hhH>$(SE|6()$ev1gBZ)Y9 zE5fswhv(*1-_{(A&h@MEtvTl;=$u7{>YEjpd%XaD4afO}fY&^pF+vqOMZh~v==#^> zHko{l_apwR;;IIvX7JSIstC62b#0^DUXyRf5!GGIb2V{QIN3w{;M)s29g;}5Z$ndm>zioilUz2aiNrw6nTXO0^$t1`I-z%pC?J@yc z9LG|E8}82Fh70`Q&*iX_8m=KjV@ri!ibyr-;P+VIw`0{di`r<_o8ZN)Dve&t8E(0y zkm1r^$WpqqT7-2EubbhvLML14fNLa0NB$nzO5c-_fGh91F48q2MIZw`EKo=c^tPXY z{vd_&f*i_cH&B;=Ww4I6)`!ZSRKMTl0ipNr(tz;7N3KJ(9qKOKxGq}JabAE|IYKAs zacDWb(&&)uMNrwfI2!zVXn70ta|As*2*jgd}_`=bB@$b%odI#SF5sF)B%@SCXB!}^7T&s%k>3MQnuV!@D4Tuqom zWGOtJJOF@<$|Vn7*n>$|=Ckya>wUVrAD`cNKAkx}35tC1J6rC$ zz$DVH1nq@h`qyA{mEXR0y$WB-lk(xI_G|2(Z(Wn%{uD9?&jMDFDcIm%1Lw}WT1$&! z18Vo3s}r+Bq5Q?~TrO#O*?|7Gf&t+;6KJ5kxA|)HHfrbhu0GT;Q1-nzm_Lg6D-Y%m z!z^(y|J_B`kgD*?8BEL%=6{e9^Mm=%|B%1CIQ)nI!l-hqaPKaZ^Pr&Ul~a0SPiA^r<9CoHudnn5OGQ=I_LJcg4}NqM|1)bxpK0FxytFDwh4eB$a%O#tyv;o6fw zLYNYgjGMrttpmT2$r!&9@Th{jpR_#Q^62`vGvRhP$4$yo|Z;F2bVn zng3qXok2xkBDlbv>+P9jFt@h5F>{Sb2mQ3U>C`3gw6;4*Mi4tOvmQvV<8ID8k`si$ zsJ1QIszBHsW%mXE=f zWH;P*-;v~k8=%g?15=qEWHN4mj^K1XcP(joSpy86BDBq!&fUdtATqT%`75mu}+{+rgb9Es7eIcy~0JZ&VT# zG?{>3Fi3MZRK^O_>gYzV2qs-$--mv1(>DSy%U#?l>MtaO@{Hm(2LQjlZO#ksS1Zz0 z$~bC%2wtg7Ld_4sAKsJ?!EfK>))e^{1f=jn1^f#F#XPX8H`c)K1wq>~`Pz#Kii9T) z{9^1oecVoZ02CXpy%1MTiqr31Jfi(MLh`CfFutGrHEsoFazFP1IumQ(U-6Z|9$7WO z-rv27o(?GjEqE0O6p{t6K4tP1SyLG|fyshbR@;lf!cmKxG9*mg@(YDMCd;82E?_1HlU&1*J{b$FUs;y022qCq#Xmk7AGeicH2) z_7lJiaZgexzjp|X(?2Pce`%=ucWHT*^8iHVmD_Q}gapTT0ElOT;bt>$K;9`89WK+RnR+qNtp^ zl+#%EeUop}aSE>FHiO@NlpQec;uD|q8+Pk>_aU0LKm`IVT0Y^i9l=pL+0sewDk1a~ zth2I{MDSP03M6BuxtGxNB1i(gL~)6-s*eO=A}mo3y(M3w?1J+pOOzyT*hk7is}4|~ z{Wy-LX2Eg2vd@5)v)zZ7_fa#FE)#!%ND&QW=p5L4DQ2-h%yAdd%+~}Nx9Q=d`ED0; zflL;c58q$leuMg&O3>}y(6LK`-sQ4dUOOD^59Qlw!7m$2x^0b@&)4m(Odsl z2qSdB?k#M4$5aHoG`#C-`jj!M5O( zV{sU0QO&~-K3A-@)GJfjDrB8=ol}Etpr!vzV!PmuPnMh9@NKE`L}KK8O~9A`B5L zYVwMbHFMo!NF5KLn7Sk_j)un)JvOEZnT(@h-Me5(lBczlK*p@L5;MHVk7N&pJhfWrz8H#;iL!562nR5dY*?gHJT&lN1T~bVm_MmzbkLl9(Vs~ zG$|)K>OtA5?MgRu((51#>76!feB$#{wI3UKzNPY!{6V&DwdH}`!x1}KV-rs|iuw?d zk(Y9c6TD6`3UI%v=L701MBw)UC6Ov!pc32y-g8Xn-IdSI*4*_EOk^8#BTq6#XiuR} z835EVOXI-N7M^X&15b8FOHWOT3HysMZ@g|o6DdNy;Atz**m%V(c7e*X4ZeIJ$nc(Y z;)Qo6uepSt`-MwBeRc|dYLhE^x(a9>}cfR)2d1lb+zW`qHSCeIA-To+^ zS&P58!Cq6Mte_7I2YVf9W*Cu&gywl^jh=1vAfDGCvW$$^Xr9*qj#q*rFTWv%PeKw7 zE<}+jqO2QRdlIN}w(AZ7>UkSlf`@H9tC)?X#JEk@6DeZ7_u6`{hQ{al^47mhQO}|O z*=v@f*M$8Tw=WB&;IVEV*wN8bml0@ChAd9a;4vY2a@vt8f)v2}0*+HTi{I))fAg1Q z-19Z!uNVH~2dEc=fxq4nAI;`%50LPX5I?9r;dIQDA;m zNimPTV)ZPbnfQB9Zr>;Znibh+TvdVxZymp#>A6fZ^+{UXXN1^2My45=jQfoG_t5aa zp#lMXT@(gx*gfgY^GZ}3#&}+oQpsBIcO?;VPotGSLyp)9>O3rH3l`j6Uy-dm z(^HM2PGkMc*(97OuVwoz&k1<+6+zDLf(^7uxRH+(Ato$(ymwE&=&>8;OBOvyPa?QU*Jq2fTEB?;1a-Pp7S}WOvI%H{6`W47RI`DYOCqHi#F^fEx zsEJ4c@{1?pSfB&n9OF1TCwO(zhi&1v)YO;YlAvuSfY&6&p}Dc<;10^ZH>^!6vH4=S}=)PSk&k{<3SDo;UBbja_fynEt@Qq#Q5@-RDIR^ZZ zY+`=%DsL`iBe2ajdfuZ##y-H;oW;cx5D87kcabESkjJjx?1>1p7@EJu<7Qqb1;zF; zpGXlZ0-wDJhos6`-M4y{Qd_|3t)5oQR)Uxqm;b~wr8cZ zysYzHqQnX>LXj#7C`T1%<(5ug44*X-5=zhA2>CfoCgIVu6SA0!x_61l|xxU@&jL=MJ-htRBm|y$FsS zw~@)Byd8@@?Wqmm^Lz48 zG7LI)lJ(Mr&_q>+*=SAGnKCmoGjuvNJYA*HSW|8A0#38lW@RV!yL^aBG#SlWRc5Bq zrZQ&gRGCmuQ>IyKN;R3)mP`o9mm6!aJB&;7sPdRXU015h;R$lSxTFEsEtiIXq%S<- zbyQ}J$_5+2X3WUYSyNMu7PHy}kJRXNW>qFTDPrTK&?IAO22|3Rp;D<+b*UP&$!OE0 z!bGc0Yqn;XLD`PYaqOByOZQQUsWy`~LzijEv>J6fn^9vj=}bng)vPh8RAwtE=(aST zt-NdFUMe{#W1Z0q4ksQ_mCHKk&?W8vJO zYN{&JpoYhTG*B#Pcp95oXRxGNEvag*k&?jU`OnUT>37q~J`o#iI&d|_0FwLlgc9{vUiB;)RO{NUJIn@Bq{b@}$E11-Ab39wJ zYh^Z-Xi=N2u+=jxR%i}tttlhZl#yyt=}iWeNu2?xsat%mRt|R?=W5oVoUNIhtHGm* z8Ah$mWYHURu<6uhgWjSwYpi;`(QJfqptRklNujkZ`iu;{F~eq7=`045#bh&NKwE|c zDx)48ZoDd<9l3o=K9#7~W|%E{Ej;FE(3vedi%x4!)tjyARIMRZs|D1=mDM?KOD>16 z3DkY#k~+~CjIjz#igBosyR`=2zj3J+IPr%kJjnq4+L)n%G0m8vGwICGO|)jUR&TWE zAh-s$Y~{)c(CeVnST!nBs!DIuS=58;!AKdDcP5BUI${I~XFPRvYPHE=&}dp}jfCUr zHENyF2E&O7hBTwWU^JN2Dz#c|HR&xdLbGX~ZGsw>b1Dy%Wv+yl*M2E?6Fc4~OP0nbm7^8ddH7NT&^OJ|2~1->J^t(I{_E-f>*>%K?7yBa`M;j- zzn(7eDfR!GJ)J7^a$C^-1#e~g)Zcgy2=RRaaZPo%(wwp1Qb#NU}k zSHSmOz1^wFpg}k9^WpvBNv`bnAg11}_OQ$hu(zAHdAJkqM$LW^w5)$i3o3Q@)(bC& zo9ePBfT#6uwFZ;Adkxf6u&2AXP54^)Ml0J4wluia1XS(eZ4EyM-Mfdk9sFGO${ya4 z@QchhdU!R|FQ9HuZ|Zy`S{9Zn%YGEzpP6Nkgtt3o*(bwGDYEQHkSzNQxGg)&j`(NU z5z{RDQ}`-8%Z?aj**}IWd|CE6a4jm!{uuxL1=T5Dw*TBiI1k6Sgi`1U-y=?=CwSrL z{O9Z;=n>zW7>b_og+yWK37?7#M^E^eKn3)Kw;V^HC%o0NB6`9vx+BpOemxq6p77E$ zgP!mrV>Eig>svAC39S)Kv!8>9MM0BXM>@XQKLj>1D6l5g4QXt5vU8`dsvW{s>g#Sh;)2$7Bv{yhj|S$ z0({ff>0#bR%v65@w*PQ%14>4LKW(ymgxAh2@uvWzMtb)#q)gnK=8a@gywo`ud|~$X zQ>we0#oLS7OA?@U*brDLK98Y9(%R}B$$TIufg0bjdgn>SK`Uf+G^i-P-vP!rTMpE)0N0U(E16gY`y=^G!3OMnqmu3Et)xhsS_-2%MDRmVL8}0ps zxk?s6;#CpF<3COG3s`u`s|I~f)r*b4L=+cH0_>dOt-WE4_c*9F(OU)lIL5ml%$ewo z41w0h-KK`yxcVc}aIsN{#%L?SjDPEcJ;P3O|)L9q=UqKoXgOA+EpvlOg^ ztux2Fi;g}(2*95Ky%AH`m^nnGb7w#gfbsLa4U`BD&G+h_$^mw_MIF!1YyYPF=#}rOj3{;ZyO=C5W)F=op%wFLvq4Mt|C%|!tC)}Z#{~6 zi^$_PBy9)XHo$7OlNtDZgDPcPW2Tr)M%_vXEC|Z}Jo1W^LS})jI7LWF0KP$V_(tzl zivH>``oO~|LUXkO0eZ0yOSio+s`sPN)BPEZO{Y70J$Z=qS3A`=ft_S$MYu zzGiRto8I4PI_!yW(|4?XUC+oT5@LR{#Er-D%@V&p_S^LouP8G(yu)h`kkw(QcYcy$ z8w;Aky&UM8_^4gp9*hCW#*dEhC?-iqqzG~gv_tS+<#1uxdmq{#Q50`8BwAq@*9v59 zc;i_)^;?NnXbSKJ?-m}+CGdSH+gS!C*%CvcIJhNZUp>%-ZQ$_6(DZDfCF+93J)&Mi z5{vD~H-+tqyeWo0A@{AslUj%spjN1_m?gk970M&*Iv4M(-zTVqci%guQjt2n&FLiU zz8{hA?HxrQgW^d)K`Tbfxg79EpGY>}AAZ7ZzIUPeW5TizLNEe^`q3jt_-7Z^3?q9x$9DDJ_>#JR33#+ zKlSerNDV|8P$&u>S<_p9f(%zx_V$n7_bH~@a}`BHKyxJmD-D0470D?WR$EI&tkCxm zC>j1~SO$D>Q$u2ect%tO^fO3Xv0e-7kO1yza7r!7J0pNJ=S zrZz~xP9fD20Q3dy^fbx!lsIBzo#sk)nk5yBZ2uXYPC~?<_^bEj2zbvw!UVt_fqG&y zplF~yc+fXI2dKFp*MawUqBB#}IFcQZ&B!sBl{Fe791t-!F334N*2*Ns^`L7(Ilbw3UYow{a zIqYP6Fh#O$a63m|cFZ60qjJcDpN&$& zJX^p#n47hF=-tM&qlgBU`K|9xPSU`GRrtXp!Ef;=I))&;;JwOtNHP#HQg+$_FiQ+@ zwVrrCp{c2umiO67Qd-VusbOFZRS-wG>;Smgs34KNw=Ia<2FS{x3w~s_1Oeq60b8Qy z!}A~#CLs=h;h_aW;Kv{6I6$IOEY*y3`$7pSABGit6GELPQ8^){$=`ECihvLs6;mdv-|iVHrR7yP?x(_0 zs6tp_ZT@olXP4fTf~6;K(16DZno%L3ERXF_1y6DC3FXKT9(Dc(4ReEniSblJPu1;rT?!sYvctL*)QX}Es2;wzlHE%$R%Vq|#@_5#&?BDe zO3LswO+hqMor zXmKw<)+Xoy@+V`Xz{kX=6r@l^7-3)ESb#VwyQUjviLMzvwV)~mkD{WcrFhr;LQ2fr z^*bSQ*L1^X_(yh~qNsupXe#=j|3?}?{OLl!`VKs6)+X)8lj-9!aMyG zEv*WF=sqEo9LmyFLqX1;-qzKgq6+0>*?S5`cLxdeuLiSGyd(%Aaxm*_R~mjGYGIuM zVOG~8G+@Jag;}^^`7=d-F5GHmKU!K~pxI$d3wG1==ulAiM8R<4kdWxNLwGqdxk{Yy zqgh+GvlUkrbfdwk4R1uVGglV;Ow+SMLF~MPH(EO0Xlk?_C;O`ifbCG4=CFp8KQN?r6f~~P6#8iRi1sk z`;yQsK)vN1t8&a{2X8ER8-7`dWQWH9ElcB?f|obL{{B-k4-W)B0wtRZzLXNl!UzzU z6M6&*1)JZ*p#a_1OkbCp%QeJbISyQbS=e0gqVU751q(yz@G#EU_&^X6CZXoXgMZ>C zAj0t#XcYe&aUfq32e3MNULbzRuayc!1_2e!g6arCVBgyX7pl_z!vY6^Vjku`VUi%w zD~t;QMpU6Z2&lsRd!80ZDAL@Xc}D9d8k`IQ7=k5I2o?o~U;zh#FqysnL4hU~2KD3< z1*gM#n@Ll1LrO^K!82WoY=m;x-Xm$n5Z z5rucC=P_sb;bw8L;Jdv@Ang@d=!Pq_NM5v*>36tUB=ucX)T9Ctms(I2ux-&*;J?za z6v>tQpI8_8lPNqGJqy9c8y9}nUJu-jE^NuXPNZ|M+Gl~eF@>G{36cTcSdpthFtJi$ z3PW;`ZBa;%u?|D%vt&O9SIjO<*oI-#InuR>u(k%|bY%@a-=VR+GWuX7B=E~s1B zup&tAzc`xxtjIYOCuk~C$+%X-BT+2;B}Is#s4fSN_|b_OFk3e$HS6x7UdYRos=L3tYp_+kDI z19-7dp$?30RU8dIc;QBC@bu&23QR&p0&uhhoK%%a5jr+uZ6OgIAg{_M^)396Vp52r zcrys`N->$=4Ng|ay_z6X1P0*C{o4Y15~AaYfrS&t(RmdEPrh37aKBa27ya-Bj60x?a0MnI8&xQud@V-mO5Y|fL^6^7 z_snxIEz$0ZC|nRw=vVe`XIaybAe`ku5F%jS=Y=na(|=VAJcPbpfm?aK%~3kp1*Z!C z3a2YX1|C8`mXq8#SJ*t9t`-@13>_1}bHVWWR#k6uNYfYntm>>k%%|lrKYN(_l^48f zMQ-+`XpvxcN#Q%eUkIfqau-k7N((0k*p>QwX<-<=JRy=W4g9ib2$3Qmvb&*X|dl=jl=Sg$>bB8F0R2~AX$GwFK+pzy{it&)Nc)fN9^K&TZyK9}EVaYtaUh4seHtx475cS=(-^hF} zFCUF+hfRe)snQJ$kK6jPlvcLZJ4s1cw5X6oiti7{3~+cOK-Pn9(W7tjrp(XJuOq3H zqs%oR-k!Ukf zDiGNxkMn7RXQIaviiXitwnUpODKW3jG(T;|J(D)&^f8_&Fv-xWD!5&<$QiFVB4WL@ zifAgpxbs-;BKU2;Pm$z4|HR{?kBJn*77~lb#w%yNm*_K-K5)kgX(1(2SV&BNfLWr2 z)JiV;g`yrwFnu5;<}v-n57QqYro;$GSw>_W0mR=|AB*o7&Kt(a!+HG}NjL`$zbtMA zJjq2Gu%kgyG`RM|0S4^&vKW5ojZdpVw~q-N>re3R*p{o-3Dz7h9w5+$g3*nNs)Le- zMJ~E;OyKZ;R$j}%6U9xqT1GZ5nnaI;5(F9$eea_MX-%MC%mR47y(vaMAgYh^CA|O% zGae8nktu@R2m>N`k@9QCs%%NqqIMz7N~p15ba+1t+?PI6dtF9-4kqY7HoHz8gtZl6Nwxl_VjAlwEAZAgCmFPz)i|JkakliVlMp zS0eVk&GyO7Pmj8#6*WqwK_wh16!*N<<3Y{kC?$K|Dz7c7Sc}{A61TP}wifM#$^?3) zc}7+dyVX^6Uq>H+yaSCD--zZKG#6GYjup|m_2r^;qNAS8D)-{7xv(lqQw+LQpiVEZTJ)FBu8wBNo0y3gAl0Fz@$fb zjDUwdf8Hp<7d`(W4truN2eil-m?b*vy5Eb2;d`DDF>jDfrNq3iCRCRDY78*{RV2<< z6h-D%tCh31+z{Og>o6FU5jwmg6@%=UU-Id|TW5uvMQbT)IwBA9X5>X4?I|2Je7%0F z=nh3K#azpIGcr_8n{}sX6h#4o7Hz^LzIG&7|5`#AO&vHCBZ!w7~G>iaPhdf>w}_cXp=4`<~Qj|X?goN?x)Ame`z1DJ`(K% zsX$kbm4w~s*nmbJ3A3<~^9FL}anX(tx_NBifzCp{k(zLnPWB#Ed_RPKJ~nWmS}7-a zHN1Fw2%QeO1PWA}1rj1qwE$^}#ck*+vGR}~37N}ZkCCp#jcLdf|4@-9v4qbXzMVoZ zkis}OFpRT&Fk(~CMi*D5=uJE|A1pRVsd-~~-A|WUP#0nZtSEG_U{O}7SeWNwEk2cM z@v&46GFlw+X~7u-xY_*88tnAg;+zorQV@$cz_-;;9J!NS5noJ)(zk;CuKz~xf zETPi?-zOJ8rTg&2ydCtC67zOotRlB*Rh55e2jxV#D-yfL>dcXhKm( zmQvh{-dH7YbhyDc(|V532@W?XE~589T>_0_?#L;wH!Rjr?*_JnhXMg<3G`ZsAnGRO z`5`$Sa{sr{fda8tccaAyG?3Wv3yiUUNI|?B7{p(FAmZRKt!Z%?MTb@8ENU0PS0GfC z7!+?4H~cjDmDl87jryy#EWQ|E_8ifwcsFA}!blbobVP~}I6+NS@z{9ftSu_+K=5sD zQ*c97+<<3ek-E4MMUVUcSo`k4D2nfKcP}9!yOcl@N)nPl zs3|1W&*QXdMtF%jMv0%0x2zF*`N~J7(dyOvLdoCnG!kv) z&DX7C%c#M-wY+BCdOxl?IXSSIl%ij^Mpy`X-CsvIbvN+;Y1>Y9#t9Lev2gBch4UjR z(s`5s=DwHOePsL!#yzXbuGY$nLeg&)x(GjqKMtAuu|QZCjR5Xu?WObz9Xv;O&%no-SUW}RIz zO zKS!tf1*)fk$6d(#R-OtAptFyYK#GSuRB#ddNW(0p`ImWJeM)6RG_)qsRShXu@|wsw zAYGj%$wpni&U-_K2;k+Q?GRo&+iJlm>PcMC>wm(HHmf)``8Rp^ye0Bl$Zp&{q8QS}Q)|k;$mi~qPg8UD})$#MX5$?a}kZ)=` zWL=;4s|%qh(a-Af(G@FbdK8SPgK-w^k94)5`m?;PBEDCLA~PSIs6}SoF}#AlI|f(y z-@BtS!(zp;%s^74yFb$9{arrR2JO!aUeYU*pXYvFa~_yaSkMnj$PbTp5d`#2Db zB^N!EUvDYkJ*$4!9`OeEf2Dq6KwiBH4DI!^wiMP;RB&}Q4;J$cP*we#?{9rceizo3 z3t<;brb2iZ?I~#u)xr-Qg+|IQ2uj1&cPpUuTX)p3HJWqcFyMq$BH_zbt%c9cE8#Lg zMN`IR2P>x}Ywd91TY{R19y~e}g043y8wpB1WPr*_U0B=NT6kn$s?4r{g-xi29x%nb zQG?29!dbrlF(g^iX8hRcdOHSyw4vQQuXhivN38 zL0c28WO|auT zo@K{I;Qs^&fF~CG+vyWY!=VDq^k@ znqnOzh%aJ}&E{EO(xITgQmwbdCAbi?@!LEPhNjgASJJn7M_jCalF6&pO@={5-K`-) zFdU3|>>qlXZk;SUNNc&hDjjOsK#B)g`KpKYnpo;Hn5SMLf2X%~pZqyUS7W=+(4#)q z1S5oQeXTFbx4aRQ@P63v%CHFiz-9##8Dvo%MV;wy#Wx;51ypJ1*-7@P4C+S%wx`H4 z$a+wQu=;XVnU>Riuyu|_4ueFg7tRP?(p-*)$;1nbVU^M9OlzG|5P=Qv?qpgU$&DZe zxsjS+%ov6Rr^TT6qMsjT?JjqM7}R}ZjQPW@F*=L|7p&FLSHrE%gc(UYx37R;79*oFM*#ka;te01+5Y&ef@q1Q%R#~bUYQhJQl$7G5N)f{X6 zDuf<;Wcur&_!puNcFOAPc(h{FbF@# z@i&T?V67~cEs2^$VkKq(WgLxe=MbE37guoyj_ zXpO=5VMR@{W|XjEbzC_V&2921bN(Axs4D}8PntM<{PbyKCr!k+s~*R%Qp{UdE9*U+ zm7UcOA7;qTA`IZiHSle1*;!@r(VXn8?lk=X-r$#=l}~?H;OQs~i6=d?vli3ucPIr? zTy_>I2t3J=kN?c-{MURe8yoqgr}FINi(c+rK)&cbZVvKAPY^rF7d^z|B42d3WFh&Y zdr1$FFS>2)Ao-$8e22&voyJ-Hf zl~Lx*n^_?yc{gU>Y=ll z>(;91%FEXNQYDa@yvEud&AGd)qZk;9PS3Zt*5KT@ZA}aRfzXD}Qov%--i0^oqJ0aj zD}*Mfo4l42`| zY0o1Sh8iugrU|3b(k0fO(pYnXY#n6e^9h~`TM~c{EVYis`^f6NVx1{1FsI6<`sY5E zsq0w?H2Q7w#FRZ~z`f_Uzi?kP%M%CloYu3q< z4Wv@_ShLF7N7#$LTV;LM8zq0W^=0Xd7G=G-HxxZQi63^Jyu#vF3KWA)dV2KYcvLsX zT3foQ#cGMRlv-R8eVAkIC%l0U#4oNX9`Zp&AD1YvqmX$+4o2-AJ%aVzyeU1^l5CI0 zuC;czU%AC+KG|TMA!X`8=e%X@Bi0XNWAF_fq)<=aW^YeGb`v&QM+Ace&`CeoXnjXo0>~44 z6tR#ea9B?X(dgg@TZUCB7N!n8o`pVonq!wXa!A_yL1VF}5R}jz5u+wDo+58NZp>pulAjUV_}+c%VENtYH(4`Ju4jD9>7_An0|1Z^=DDM#<20p z>;qf61_0!!_pQyu6Jh!h%YiWO5jxsq;xN3%3p0*u`E6nDqYN4&iJ;TtDr4ex+Pn*T0QTFI`)QEq> zUX~XPgmpAn*|pnxr~TH!J*=9Lq)ZY zbPWJ#RLkEB*K7GZ;hJ%|Rvp|$5(SSi%<{C?HTSHV*A&j3aQz7VrpmIqg#(=nbCyNB zPFatl*{7A7(o?|m!V>oC?)i}?;VALb!Zz|y{4|6r+MAel-AGviOroN{@+Uus>+jXG zsIAUgrwMY+DxSVr8SU-rtcGr!vqnmFc`{1xjy+G!DriuVwVxLL;c-V4x>01UBPAQa zkNO;YDnK9UJk?zi2%K0S{IHT_ZW1?vzQpj1}7-Ifd1 zmeNZAhjcp(o^;U~t0_SjYu@)_sxsB!Dx`%xF*ef?k0Lx)k6ums(z?XN@cCb|9+BSH z@nhLmr6g)G=w5Sl|MNHeB>b1V3?i#`DB((AK=5Xs3i{6F%hqwmSxWz}tVyDDoTE`U z#^dSK66{W8K$$uwV|r-8H*^-tb63B33*SouZuPuDN;2-JS8*2Ur--hyT)S!=Y7zft z*laHCPk>Fk>zyk4?s~O~w^IVV1F2A_WSFJgziBOrFHwo`h`2H;>U%gErJUH*M2h9f zDDy{angzqDp&LM;`U}KZ%|MJa%FVoEebXYh<23O|tA{gPO5rKA6rmm3^P{yu0+8rI zf~_jrGksJeX^0Nmg2B+xwPm7F+Rr##hDcf+POWah7!9fnC4+X~^|UX!r(Rqdp=sVl zgb(B9osY9<^G40NQ5&s!74M*oxNkisZekQz6K@0*XcNC0p>N{(5gLnZ%&2+mqBReV zXG%{*=L7RBSJrg>T#H<&6$|5 zsuXjT?&mk92ozaau=@23^%LPw9L^W6l*LE5lG@2tPR#v2g_{`Kkn{Qz1@qMwhnJE1 zDOQfx-@^p$BW}lWB|<;NdK4F~cN{>>s^b6&yjQucTA_dQ+}cH`3FQRGn?~ zk2PLu3{puy66zw?Kh~-mXq~c-|8L5A_L)an5qUpA91^L~)`5frV{Pq+v#7R`U9>3e z>hgx-42H}U^+kY86*VJLuc-YZ|2IV~ZBfYTl~=&9HBzsro80WOHJ?U4N^TX=j&(tM z4Kmk-g-n!+ikYhntEO~`5Km&3&D8EkJxX+2WliT|+Zb(_<>|gxM9hn48#1rYtJ?Z30UYUumkSots9$Ca+qRjhieRgy5 z0~Iq@S+hVH<%6%cxUp6-zCVzQu%#Y%;!@?31#j%+xVonbIBpjYuBHdyRmCq}_R_#2 z1KFP;k^r(VenYa6@M9SpWuw#$$%fjCcC1hwQrD`yFgjz>f5H7h z!_btC3O~GQ$e%i$Vw|<&4P%$Fv#Q=@lFd7?PGSmb_sB8n8}*qpo*M} zTIXzQj?TR3D5=bSQ>iHk7l2Obp3dM@=Ig11zNOs3@3L#v5ggj&sIR(FiJUx#HeFSz zKLK*grTH3n0tBW8Fd%{Jg{Ql(LPZx3msiTZqqG*}a@9OKh1X`tNOs;PB|)mplhu)L zxoXINv(nxGe)eXimK19M|MzC)kp$@LM-FRQjRCjn01PB>_R-a?O1_D6+PO_RW8xxL zZC9>JBLH{QMP^hhxqkS)6!%;&{?pTo`H*ukPX%mbzlVF5VHWOPtzLSA^e%e+;U53qkbOtpCdkWvUW!K#3HTfi`8AAhwP+_ly>Hr*;dKNG`hn$}8`v*yyc&+e7FD2k7jwS61=F zs$zPyd7xWbPqD&^SH=_Md{NBAoM^YOaN|_jgQxM8O{3M*J2mkC+9MlPFcY9%_MUqq zCV)r@G|PW?l}|nGqPj{$B}Pd{l|Q66L1ENYzQGefXWn!S2fW5v5yz>&q3<{3dD^>Z z=8^WaBF5eLW3{E$BHE1?oKSiS;u(g#4GC8dcZJBb7b{+}`xwg(Y^XD4kIn)ZXT5yV z*i-%yt@o6VRd(TQZ2XnNX=^i%S4RCGt!jd9?6lRCN>}IV4W?!BdTCcpmqz=khJvH9Z}BbN_`1Hs^j*uw|!!zOmFBJUnp@}x>0#W(dhgac)EHT0H^b+9Z~P| zN*4`r-7vqaK?UfX6sQqU&s7&_OOl5ygtyScFLAuZPJSX%wy_Sb!&%&w+`ou}AF@Z1 zATv+02Ov`&e7m~7|E{b4FLf~5kaLeG8R!EID6I&-+5uGLI^ad;M7~ig;&CDoSCmeZ zgl80;ZM4KIT!!9c1e5bqqM~7zT3PI&(6&m9IwO%0(7q1s_9a3!|;{Waz z{23Q-L{qmAQM^VrQ12f8wtxP`U}FbzdO-eFlW6k5!2I)40pOVSdj;Jal;2BIKst{i zKjEpMXYU!Dzgf71x(~@8FMY)!=o&>3_q)wm)h^ahH|>1EK>;zmX(tSA9GX8>xQ|L_ z$SceYD$vQd=@wc&I)zKMb9F%Tgo6kVAE63^3&G zdI8~}hr{##kgDoR130Z&X%L6nPLKeEa%p5fnPMbQw+O9J`lx)5?QBlUFt(jda2Dxk zO5o`H#v<#dU*%XpdU`~DzxbCS*O^wwwW{l2J8D@E`W>3v!?z9TaG*ws% zSkYO{MQRm1R&&Pq{68h(U5fr3t2u~Ccq?g7G6bbD_$IY=Ge``+oDkO=&PBM^`d&Ss zFbI0}e>R-GL2E<9NriDqBa92?!uVVjhG#bF@|^rmC4^rIdNFeWc2@R76+2gXZ&Ci4 z5~6P{bK`kNkMdJ?etZcrxR$x`yy-!48&7i4pm2|iTlh+^V4oX^`m9dWP1oXO@|C{h zGhZAz6K_6kf;XRL(f38w=HOk#qi*}%vPQz|`6Gf2byJ!BdcMCPb*{zRRTrE+byESx zhi(Zey)J*M)K`ZX!HwKM-iUZ8op^Rkyi((h{0o9K8Q@ZbJ0A5$`QxPVAe{tSz;M36 zuBsnXi|mmMM|HmoD~sRy%YR*vRs$@$uwLn{{2>wosd!<%CCa!b`k)0zMBfS|+^*)43ZOVU5It0>n_4Z*5xKsv00A{hVr{M{bTzkBX_t&X*qR@We%_YfNeTe@WQ|M| zYa0o)B&*LqYJGzLGAa@^eK&s~@Dy$&z#pAh3IPe6;mYXmng_@Z9QvA26O@_HT}30p zrLn81kF#h@Mi=#0zMsF_U+AGCGk?(yAk#3rS#5nlRKK>yVHom9Cu|}Nvpnq-gVHZ- zGrWj?Zf*UbZJwxTBQ%iks7J)gMV#n{9|))23&*ttscPx32^!utfR87g~xNk#A` zDev1&^k`?SxDN_ef(9?B;uvi_7|<+=t842Q)@EVZ>D>;Hk~$L#5TU`M zuNxqy8eD$*CFr>+Y^B0Q3O@i9Hhw?8;iFJ7GsjZ1a5l8X| zNO2(D6Vyi3;i(4P3`S8uuNf9>2&9ZTntw--dT;_XLao9TU2ml-H_ntz$a(lFI^cJ8aFCn zRo&YP5&#Xi+TjGdd z3IH}WJUj5tUhPP1a~+N0G2~Y@Jce1MQnUx*8&6FP&-eIntoC-5+iuR;TxbEZRZ`Y| zonIu1LX7!P7P0pEM@7$7zQ2|~z#^85F^|T!=uzx9^UsN5Ra}bMQ1(L)ipK2xh3_@e zK3skqOHOZgfQ;1nEs((5AI<$f|5l{omTr$c2m7hFqwM}6f0r~QM%yPX17b=d|4H|T zptP=Q{UrRC$6$H7W^iAg%8OQ({e*`>@=G93UF`9>o8Me|nJ3f59(=LsTX*woNC2F! z-GEM7z{CYhLs88NM+9+Nym<8SJvtbp6X@int@mQI>Q0bM)E#G0b*D3`Wgq0@jX*Aj z?N)byt*U#Bm%3wR0aL1wYhE&)QZ>$U{6hKn+OP6`jF*zT`DNbq*00!H;d@)7O52L@ zuIJs_r()+S=YGroToCXDfu(Km8ZK@nujnxn6-2qVNp*XOl9FRcr>%@>tY7yRDLsuwKPw3bq#DQU#kIt5>iYu^I(4=8h_uan{Qv zY=#@64#ese%<1NqDcJjdwj-i&nJ`?8f(5a+gf6Psxyro&TRn^LBSAA(uqt|tH%r?- z6oo$tMllLj+k@s-u*7T>hhL7>nNcSem|nktXw>KpB=ANiU)1;1M}c>`mPhI3ZP~_F z58W?sdukl?tPi%Gl3K=b9VIc3rD+@v7pC27>RuPde;ZiX#ypjCg}w~2JrV|@&nnmo zrNJD6Dl|WZm)eZUr$5RJx3vlG!yy4JGNGr8sbp&_$S(o_bx-%D%C>lEE>EUMDe#eo zj8I#Q1i-1u4(46IIV*WGt|S>;qncs15yA$vGR!ts+6d_BXZaW&q8y9s;!x(cJ3+`6 zZo4S$Ge>L1&_42@;h}B!`n8*kDpa%C(LYsf*Tfg%RVvIR{0+!Zlkh{F z-Xz?J)0hN9mema}##zg%8=HhW@p_X`GoCTd0;@eWY<972ym?49fVE9)6%kv5nzm>` z>=kbwQf25+(DK^0E#e4Vh*?B6+JoV?1oR<|7V&yhP!kucHw8c>s;dDByv3EUSX&7} zdJ|W}J#wRCmvv}voNb)64y1bmq=+1z$|-qtXBtZX0dIhw7H@l7+QT8ij`VzxN@p(i z#G}mMTNO~ks#^X5Ad?OS&n@(emp%ijbVKkSv?amTUSB|l^tBGqf>}@pFpw8AfB~`C zbS7w6F?ups8CTEdF9?657wg*^O3!q(#lJA$^cG8e6p>G1&0y4ij|YRUR~p#-M5$6; zE@xsSz>L-`h80{_o%kwO*Kp#?4Tg!+iLYM)PjuodAj#H5!1ML(n%J63$)G$c=@yha z9)@W+p2Ny+QWtPMu&HgXC=CP@bR5rPSbZ7Cy#U9+Uc14XprSUmHj zYwhbFD;))8QEm?!a=Vz7>xA4kZEw3FNY?-b9k)vv))mI>C1Y;gU{1?NERz6@Gb)s&<*y?t3eH2rn~zBW1t?)e7A?qA&mokk`@D2WCddfAYx&(y-`;w z(F;EhBh3Yrzv)|)ys`r6@!1dmfD^BwC6En}~|7H4^)b0wp% z?PLjYAH!zO_+x-go$*F2O6`2d+60X=HfE5-=Mjck9`~@v9a?w|1;0+vyXDJn&RL}X zPlj!xulP8@+%H>M8$41mbCn09Y*&575{c%1`K%tL!vtG*Uoj-n+%f;)LD4wo`w4o- zd>IQ(@0fvjRL2YwxEd(SUbHDaF!>&Q_jz{WeegghRihSC4fyeX;`9OlLp|%AVPun zjvDf;#&(8TO6j?_mO?P>Y96kY%z3sjA;K`;@rYrX`k3!$FWZhw3J@}le)glE=G%ry z`$4)V`U&2{Q@MDNvcNV+I?J=vaA)X3+X(4PkV;Ih1%n}BaFK`K4sx@U>4tMD6ox&*seh(hD5aZ7EDq;mDR zo>3k#m>M=gc)}yFzf~EJj}mFf5`3SR3nWALRy=;iHcY68`n_r!Ej0jT>6~6QMlqq@ zb180GW}7N?H76C#NOe?6g%~pDwXMQkB_MXy`1f0Gn=Xw6#ZlS)x!jf^O#rDxcEU*X z$qHLD4K$G)=({z%TUVWw0p$V_UR_D;K6zeJTvyNCS?N4?4k_HYx30oj-0rtpWgA&S z+|96AZ~YKp)84wip1!xPs;9C0#thPV8RM*O>pAaVd3dL<$b-UlTQJVMS!aeHPjvq% zioew}H~eW#qQ9t^xk~MgwjLJI4^MI6Gi%`aGd`T}r$f2t_d@N3>&P`z!OGArwtj-r zXNzruAXcbv?g@r_XlOja11v`J1jyH3;yjPVsrLv#aH>ZD30w=5{Ox!$PU={n_f!%^ zM6}}x9GHC3DIRR+hTDfd2WS@X3EjjI^)(unN$4AE*btn>{Xz8|wqQY=$FP}(%?8+1 z!$#HDYuFInMqp~$us-TaieZ+gs*BvUfRRN`t#4!S?J~NBly_Ce4YutDqRl&PZP1j{ z)|!$N@D8@^iuU^Y+Z5i#RnWI8U{;-r0|^EVwE`Xd$QFe5?6y5Jb}@?b5gw{X7Vp;Z zJpd1f2F0O(J+=?zzX<K9j+St&bF}gB1Qk z8T)M2HGm$U82JY%$)hcvhRG?3lDpbsl-m1or;-`~%EbJGNPR8qO*l9$vL&MK=c)#V z#Bp#SHN(Y3H#*=(wW=V2(?GFSYMJPReDwLu!3{KuKY)~MtoVI#7B{W0DYo5`_!7g$ z59#b#+BEyk_I)xr~`4mNnWi%Ol?NB{3_W^O(Fk?`x~G9dM*G zw_DWecy_#vJ!VS_5DzslKWy?1YpFugQeb?{eEh>RUx~?&=-F)Bm!` z?IPoYNXS?UziFlLi@6jYs8aB3b&EKUC-}v34b7cSEPErpOha0Fu5#f^+b)Y(t)cm7 zqp=?4$rW2gi&!6*Vm1xf)`Oz)F>*uI$Nb@?SP#4feOD*w|Gr1KI^*IGZ2UG_hes5z zlWFMSDinm)+_2pVHndpEif?T#1nDI#Iky7P1%#;$OQJE0?~OubpU&`;@L!&68gRL8 z;ecxyNTtClL7KDVUKBceJ3))&F;T&jI1;x3O4&QMPef@8&(klT^-d=q&_S@Z>3XG4v3v6C{5t&4)QxOEBo$@Z5;yvVSbTm1rHQ}a@YwLv>zSFjcW zw`$0*I>Iu}vOnPFkygOc$X$VhH`cWeXk^O&-){a{^j71M?N?EZXk^}z<}xXVVWPO^ zxyq);wm}v#p^i^@;5(QEZJ%G3!V<9u!SSs?DLN z@^g*!5!-2%bFYZ)y8ED2w-WZ6(jCA&jM(rMq`LdBPUAZ0n-*}ZHZ4ft&9&a&{;jb! zLBIRkKbOK9Ya2bd5>Mb%P~!mm>-bue&jRd2r9=)v?GG4ZA7nZk*H|49*WsXm7#(B# z%l40i4oH#hi_w5`_5krByPD|kVSF#;v{Lp2sT;?p@gHhg&MqVW()PL(L%2w%SS3D2 zI)q&1>|KJ*OI1S3*xQKG6hN38>RBL_8fpxt&MH87-K@f4R^th3jYAB}_8Pdm90};h*I>);0J^%>w(!(0yac%lVA3hW)n7WtOY1=@oiZd>n2W2D(3VTi7BawL*Wyh) zw<|%~36Q8huTl;)v^N*L%eWS_w7uj6;Ixd$>@5vR8GD}|jMm@~K}T~V6yjYYED#bW zpfg|W>W)e_xA!!Be<0vG%)4;L^&2^d8i@G5 z>4$#Sbnqw+uW%JJ)RE}i{da;QpT|5(@3QW&&ppf_O1{0m0gCLj&L=YKcl`HC%k-&Z z*Ja^qy^xhwQNWj~XLZN_kpz@J8ZGQm zy3?`>>Gkp}pIg^;Sr`dT_RFp$v_!qy+EYqM_&Udx`26{&4{Hc-qtk8eabl?`^t7$L znJ@q)wX?UwCmQCpvnS#Er>*TU{0I1G&&uwoa5tV~I@{qhqrxg>R?Y03NW<2sjwRbbhKxbcn?psubhq!raYRC@7{lm zzVB!sBHTqCJK0AFrF61~qGtZ~aMZHLqtgECvUZa6 z7U(;Py+=!UwX z?PXT10Eh+Zd(j1b+937rI>x?o+3BKaYCTJnKnRj`rJw_0-@tp$$4t14h z5?IzF$ySjBH2H&W_?FNihl0_dZgx3|bPF~|b927?P?q6X-P5Dn_)i~}iITI$NPlt> z6SlxNQDA%jj;Ks`99(|j;ch!heAkhd_C8N=GqbY)|M*(LKi%!qg`3KY>Gl;u)1!p! zaq{yi`8i2`PLrRrv+1uMDptBnoOp3r%Lfcq?^2|4&x8I|m1?^t0wL8Prgzo@J+F|@Z;VrvWjP@?))XeW>_wD1-2yIMaI z`0wz~H1?iF7D>sTmQ|OUADWegOGO8wYtQ#5G_inxK{?fyRuOWQ_xsup`HN+nQm+A? ze;Dz97w7?(BMe<1@hA|*X4>U)rJB0yL%wj?Ue7;hAyn;(Y^py0V3J3le|USC-6b~# zwL24)mIZ{_!*NwH`^mz%xp_6mhM94ECb$T!N*!(dvS~|%d zf(i?J1)yKD>_PH;2vu}AKUJ8CGRN8LY0>FjQ3uA^Tgo{Qp7J~s^&4-0PYX|2F3(wJ z7xce~<&R&Z2$=$C0Ac1VvQ}2Unt(kJ`gN+k9J)MrO`yCVz^YqfhfT6ilGwidq2)fcM zsnr&m725#hMGK&4tkpD%mNN^x@A~M$EPIOF(2JEsN?(0*5D*GA)7a=a_K`v=T0X~~ zC3l0=gm4?wpKz5xSH^xP0IJoWQ1tm+`#NC+8a>axK^_I*kd9;(mE^F0LGtR$_B?S; zGj#m)p#*szq**lIzExfVQyvE5uxK7SwZJ}23#x072(|cG&o5pHUu5qf%J0KcbajbT ziES&Mn67o1Of{|h@W;c!$_GpBE>S)L%cFMT06MtL{zyImGpJd)o{jCoMVPF@D>Ikd z=LuQ_A_kxtRaMS4Ok_5(2crcm?MLK$kR~-jQ(m*j%fG>7YJ%>eC$Hf?sez}gOXdGklTEq;Gu$AN7)5Pyj5iD=7nj65A85yA=diceW>a~8xdmmH~gLX)xZIFhWAQv6{Jts+c{okrQWiCD1QV6N@9eFogl?qFM6r7V8sIsP#+)qJ_^X8^gnMzqsjLVRhLi0 zWMXc_qs`HS`-l2z5p>EtRIMT`U2TQW-?8r$@THZyR>(AfC(0iJDey|7d0Xs<ZQX^-`aq9m!Az<4SHqo7W#3da2G$i3-=G}YZC@kE2O(9Rvb|-1O6}@7p{x&@ zw%1-odG@jW3sF7`i7YIKr6caQH)Egvm6{ ztk{y>+0m>_0PqnXdsAnOkq3Ol2E{P8*Bg}>r6A>azI|Ca{8U8ullHNos620YRup-z zN9?5*1s>q`h%fa8cIi883)RNM6y7?h>}k8^p&oHsON|klOyuJp2I`E^1f0i>(8M$L z0zq8K(3ug+hUnA?O>e0;LK9kg8zB>Ji4m$`oL3TM{uUIf{9c4ZZFxUzRnlpya1n+6 zR}rP0=OTJ=V^1~loK{4qVI6fM`V5GuHrjc?-b?&JE1^3On@Z?&FA05yCB#>ELyQH0 zh;X8f^KcsyyP8@@!0qMPm&Biasnkl-=pn7l8@)Wv!$dqAlVUI1uZD>YThV@5g})rd z1zw*Cyk0BKmGE_2(KY@Gp@g7*V^aB6s!qVSqRSGl+)iZ5o`M#|-oHgBKbYdWs~-!R z-dGT0wSpK`j39=qg7EB3n*79mNfMW~(r>BYg1E_wU!-E@DyMu4TKbFYab2~KIB=BT z^(c!<7Yy?g-^ZnBw^VQxnO%IpNEM;`5r_GzxW#e!f9;lv;RdqK(962`-AP8m{@NpK zb$3$nnu%YfXkIP|4X;?RQvM1SuIs(kS?wUTVh!B2N(F8MN1wp?UE9LHlCn(f+e5XT z){?8QYonH-1vSL7t=;RaQD{jQxm0U_O*`)sFY!La;{A7>*Q{fg4cAto1!F?JHdSs4 znb6sv#yF3fXtwWXR+WNx1+jl?b0uxY1l&i(%vH8V7RaKQ)!JN1+v`!PS1VX9h_i7i zW=h)KgF^ecTSn1!vAZPv@tGUw>d=C=s;AX!buS@g}02m`wu`j>bwzzT)&Je zp`55ua6*uG64AL$3JrjEpdV`$*yJ6W3^E!$SGyoyc50IGpu~a!(GB0`<-Op=KTA zIj&(Oc|wE^=oibr$v`Z+4mgp~7alq@EHZz zO%UlgW|n7i^MV~F13M+IML}gj-VIr$BfAeligzDeii)1>9u`qN&I})L-Ug<4bFm&h%wJCSg3=I(J~nkDSrY-yt^j3pbPX7VQeYX_Z(swgV@5?(&#mP*qSo9eNvANJ;HbFw#ekYJOVGx~4J*|yi>K)qr|ByO< z!>WQ{(lOB2y$Y_#2nvuct*rwopqi>iN=Js0Gqb|U9a}Pt!;mDA$o{0!*o1lme)L^ z;H(@&%5(QR>b;XPv5~H?Nha1i289eO=%a<#HN|Z+ahhsd5moJ8Tl{HX#aa2JW zK^_QmNMS*Ii12_F*0-&?PSy*+0ukcd0n^dPoAU!rctC|?3dWh`wH`}@R?qVyud}vd zLF;N#q)AJ!#Cf!(b3S*~Mq9HA28cVgEu9OoX-ltbtMBP6+iK$OVj4NxI1e*O?bb8R z<7%D?UC~zP5@bmig2L)`?IG(er@X>I48&KYbM~D zlBd+ZAw>1#<_oyeAWVK3voA&>jJdV+|1@kC7#~DTxLrK+2Od$xw9}aJTJ6l+wmQzE zZOaBEDYFaO_=p|b(E$lK6Uvn}ot55B#ne1aH-BM4f04czqby!nkSU7&+L;eihU*9^ zgO(K3@)5`2vdxAmFL_X?Slz>v^CDLz;(!fM{AJcgV`=xZ zZtGBbQ^$zN;`Mcz1qoAp+B~)ll@%i2MhBIsLu@-94-fbZ8<@U{l_NsxXK?v&&M3wd$1to77NrXA5pZ|GY zZ4=`|Zy=~7UeripN->g{s7k^!qc&n+!PAPu8kBjmU?{kVnVW{*>>-lZRK#56*2#i* zD+^nJ>~yc%aom+UTzQY+)J62HifpGyhLDE@P-L`BwQOFIB7(NtX2K{XQ-31z*R7=^2> z_hZ8ed;gQ22xOe-?F4OChej5*Vq{@eW#O?C9jiE+`s0UZuwHoG7Ro#P5?1&H6+2h) zt?4-BFZ=*RXlg9B=y5wII3oRpCjeLXBr7l1>A}@li_cZ@3ogC3Sq((LUoZOqZY}1y zWluv0GhcnOsY8+DI)a9#3~Ia4oZA^eLT9?+A%_&1?kgq`%54N7@LF1 z*j$<94gRb!91U&b*eS08$f&6A;b^q_+ffzJ>7kCQ@|!S^+TS(!xPl{5i=>m!@2rln zWOe-mrT{(2%F17nsN#k80 z*Pv`79~04SPN(d9o!A}PNq=H@keg#R_&V0ZQ9}@C;;Ut~Pp)y}Rh`Llx{8^rOz!1a zg-N68xB-`9Hq2_^LD87Vsh#wfw++JO0=Go;NrIX{7lDi==vJd< zM2*TTIsF}qARi;`<92B}YvO*I3z92VjgkgA&~s+;epW3_*kFfM{vMW1EzNC^0-8Q~ zh+|xYah|(UJ!qxS)gg{t`5B<1H#vTtL4D~0%d<}COj}2S7E5Py`m*MMJgAa@DS+dw zOsbJ&en5Q*BEGYxSH%!EObkygoW~8%XTz}J>Bz8Ir)meWX~dR*5=UqvwpyJvc8AXL zned7`*4XDrceJW9-9|dr3i3oKLY>NtHxd+eUK2+9|@(6i7 zd46DnR>te0lysJBEzaYX>%ch21RrsqR>&VibSmVHdLggHLI%TU6E=x_&8l#Dim~PT zy0hMLU3PPSzU%=_3^zP9352>5iSKZ0?d$sP}Zoez8Os zbBp%6jtpAxlH*q~q>H&hd&`5NF=+QY>kZmvrl@eA3lt<>oqLXYZdD!Ql39*R7P)N~ z(8G1=`Tl=Zv6Pn`KbS>|UFSQ#G+O~#yJpo^Ik+{9;o0-Z1tGt-OhpV`7{(;ym7QRxNcL z6-7HkXVyu9=+xzJ@1l448?mwxHwF&ho7A1oK1CQ;0<%d2qYLWepH-JT)|oZPspXD& z^3PC!v@L!BDZJ83{tCx3i~J|ZL^*35QE0+yM}JxDiXq)DGd%b;lD6Ca>;|)s&<2Jm0W(g^VJ)VIXpy<9kuA2Wiuj6Ah80rQ8%I z(~}eR&}oF3*TR!U_nvP$mdhy+o<`#JP~#1bnOb-vgB@RQa0v1c2v21YyU|f#!PM0% zX^PQR>AGo^R=-Um+gXq{6?^n%$0&IrOr}MCwb{{Cn1yO=!4=jZ(GeTDqFr7Ok!ZbU zp-NjFS!VFL2JlJS9No0=x(d0UeAKiNR_`EGZo6Y}gu&^BEFNE8K~uiRLodg6%+yI( zI?>OF6Cj1_r(5susBU@hyNMf1t;6?B^mGQ`#|ld^*?khFzctEe&~1@VsdPgo}#CcbDyH8f9Oxq ze*B;6$vDQd#{|A%c|mxA{L9M0qwAF!qft@Mf($WhG@A0U zqoeP)IB;Bvu8n?F!*3|=`zuq%qH!-fQv9>-kiX)lqMR-F;>4_@Xu=*xs8}WiE#Kp4 zFuy_yIS`J^!oNH4{)KExJUeSNM#|12G_$h^xok=%JL@PGb9Po4f;F8Tv#pg?2mhHx zH6@08(Zd(9UX%v? zcS?VM;)wGn4UfG`f%|-MdYWUPUGyg!CvhbkeQ;W2pL!bx8 z9aYhcqmFo~0Hh|LaHQd@6P}TDFX#cs9KEE|-q8NX9pC7oJ4n~O0F^Z-@YqxXx$tw$ z#iyS-lB9cRBP}fgkT1|9Nw5YxH0xM}aOswln3tK_zLn4N*>@E|~JZM2<=g6wO z!sLrJmm8@ZRupjHPZ|tLzH!Ep7S8FjgRlcQ1lD14<}&lFLsaqA1AgK=srpkT9F?75g{bP`jguD~ zM?`UVDoQ_T9|J01O~$hLz^+ks2S1D zuN-;OH6S|DLo0mE6WlCh;Q~Pes zMrU$4`gSyZ^SB1i;vs#tlY!Qw7P&V21oqg@P~ z`Qmy!&6_&wo%GC?Q$+=5zBuX(Z&Wq1>wVwxrhJ-LI7QtnN6vgn7kD!9Q|(aemwW@n z(^z=7@U>`>xW{Po9B(HnvS0yIvnBR6IJ0sSqr@pSXuPoSIKVX zX6g@bR5}1IUdvKnKzm2-4pNo`Iuk5X)owt`utl%pkwU63JIn#w``^%)(B832JR5Dx zblF`^Y}HNEHJg({Rab*_U9$98M$It`yPT!foM`ylLmm1%XMRyh~u^u=#^0WPnHJFC0*5xvok-hn9% z#gE&o?KhwBslAXH@QR|cos&&C92()=XBKc}RdzK(W#U{jr89&RW=Mzwh&ag;paWo2 z3pG{s$c%Ef^^v~@plWX_s_smXZt-N^n=BX@B|pdvlK>Xl)72S`LVvy)Dg6eJNQ764 zfZ?`|#^K4zeW)nPxer~h=`5{5$FV{`$-g_V0SyzrMmuXc(+s$)QQMg&RR-XmzK-uO zIaAx2s3A`5B#N!$%#~sR3bn1#G0qhjWlxN=vj&ColMJ94Kh{_$(gRjSv*Vndq@G^T zN?5!TzeEJZM2s)!d$n2LgH5G|Q~T;V(?w|5MputGqk2$(4r|7{`G?&|LC(~a4s*26GMIg#v~ zB1-=0TFn)G($Tth&bE>d$lzV1GDsy|gn%z>@2nvM@Dvo4SJYLC1)v@!$M8!34$dZm zhCWr0mH?hcZ7GVu(g1N;hI)OW7C{9q&0vL zsjdZssoDzRb@lCOR9~`|gVuC&7D~B*CY9+PkU(Xco36f~NUjXfgI7g#$a6@CBjlp% z>A0inh*w1kA*&Ol^WM;MPiLqGT33nQrj^*=)A^P3GoVO@aKPyFHNq^Wv(D}9>8$ja zWl6jw$tTsN5r&W^t*^VCN;Y-115(RDQ7Yx;V0jeubS!R#TXu zhpE(Zl^H{vtwr%ATovsKJ4czTN2#0X#P12df=kh^uyd4U9u&ABB@87MOO;=L=#D=+ z<6^-AJ6SlDfEd*P1SIg70ev~bxhoiqMM2h^Bb}Qh7imNodKB;k4okl1s>TKqdXz^8 zM>+GQQydaZ7@P;Gw8x$50eYMcr=N632QHjK0b`w$G{kk?XCspu?tgvrbSAVDnB;rl-CW`1RCu z0%K0;0Mszc(*XP3p}W_{lI}hAL2s&?eYQL+O?F-q$M!VWdK;7MC>1eR89l|>1s@s4 zyqjtLK^+RJJRdhhFj^AKYKq;=&4_XO~s|^l^)23Dt!fz0JRm}eY7rA z`E9!MJyB9f3o#9+-ly)ITk%pMNF{12D5(1^=Uxpoo%)QQ?QAI(0ch$S6?AO2bC3pF zr=?&1M=cGU%e9oA!u!LcrSt;w$Aksr!0Hjs;%Yj1o^!Pz2KG{QoT+K)UL2dN>7QO| z`sm-PsYze^aDkz%7Mu0bD`yhsh%(J~J$=5=xeUJx-OF4%A25lgtC+dU)y2*S__$#& zbM5>?kJ8~4=R`rAj!Q99Pl27nO2=f${NQXv-;z%2rPt3S6+rV$4^T&{pCKRt=qLJW z#NjCAM7DFUAZ;Tp1J(2W70x8-Ly$_0G6O)+tVYun4B^9A>rSf8z%IKAT1|}Ok6Nw!4q$Vw`=XcLIG)6!PHHO{$3r1b3ItvTdxQ6uxx=I7_v$u z#R$VJkAU&DH|jxhFDH4-OCt`u*=KgB=@w@vLA=)6+zz=f*7#b*%tb|WHaAD*w>y!# zbLq}D=Q;5Ku8Nt@Oks`VCZNQ>>x>t~7y6i6rCuHsja9nbTW^&P8>lA`mKrL81g>K! zZHIHVN#FZshx3w@)JLbP4S515<7tFURaKKeaLy5>4jh!NSCFw&8c3y9t^=C3%emDX z`f1-INm7OmTI|pV)meF@sW-ShVRwo&RR@k=e7W(Fvw9F=<&8gl*_u1FymUOb#2f9{ z$Id>QLg=hi=RMB3(s}?*=W2rYI{V_1ChT?QXi#*Y{*?wjSizqqieJ z_EBv#*vVxq0d?4ESQm8N;k;5aw&iN)H*m}bGiu4vQf^IE{KsWY z#j`yiflqtlg{o6{+7m+4X-{?S?5G}xtexTcn%QTan>9GP?w7-=4Ea^NA57uO=3nGo zWFm;oMb5WO2H0tzJKvR_0v2gke8LmBjFgNoocOhxfPP%3bRK;(V;Q2W^UVjyb2Si? zstkRtCKAx2GNrH8RP3j|R#TDZvV}POT1_IP#HTGQ_EQcv#E*4I01458=#w=aIVnU7 zqEFV~g6NYq5QnrxG@k<5YEUg|3+R(I>FDY;XAf|vB1hbAfJhb@D?~PG+^|7rlf=di z8Z;QypkYG&%tpf-)*I1qSmO~55)&Jbq%YRIC!oM<&S1U{p1PaSn+j@zZ47&@hL^j; zpj?$<`dZD3esnbuyjH_eKQKe3uhj%cJcn=fv6`8fKloV9Li{&-tY$G`9X?ir6V%6Q zHj*4>de7c)#ywX?C>=jmQ;R=V!zB#*wT(e<%&fmE%(hdjP&*wqdtTnP*a ziR7uIc-loUNwOCX#WxEmsSN$iIZKohIT(5vbs#OQBuRj~wg4ftS8xTRq2J{ADx;q` zABl1+j@?h)v;E3b=Q61yPe#cNUG35J2fJjH^*5fOXoW8S?L035MD#Gp1&b}Eu1xES z4M9oIoJZtgoN_<9Cj3Ti*EuPRr>YX58!U$P=RpCeR#`9l3a(ZcL4KK2VU?+6aV?Tw z;mK-c{q?W}0|n6bqug)B z&F|g}9L^hsy;1_CgFVs0n{|<|pX;#TM4$S(R!N0`VsaN(RkXz4wMIGyQgJzHVj&Pv zd0qs2pQ3;=kQ|cF(KL#*$Qp_o2Dn}pzD1t|;A-6BaEKOKS8}}~{RC2Jp|^|+We9CuRaD!>cYu1KfJybps}9w?WCF!bdotXh z*Z?x1?Mm!bj6?uIb>VhdmqTg;QmNqRT3r{AN~_ZbGaP)Y0;21C5T_`musWJt;A$uh z(&3aMVA$T!T@E8rV4!OhYBklrl%`11{Xk9GqZfcx)n>7+i!Tn)?+M~Us;WvBqN@9k zh6cMHh{6)oy`pP0(B&Ei@N{O<>q!Ew+^I2xI~NyTb~M3{t&vNFym8Jo z!puhE?JN0`RVzzoRrm8$O=k#oy(t~xd1?osI~PxZRML*Z5p*fc)lUOWngGb9lgchE zOWn9w5bnAxh_|p_pR{*CUq`s2fL-h2g@s5ZBOn>>2;4@#4-#%I30H3>OcMsWhqdH+ zXK5e@*UvWojcY}Rwe&3VgD96|5yKd^I;52=L3DaB$#26fOsHC)xi&Yp_Ui!M4qR&@KP+TuJ~lfa1|*H)xjt{$Q|Ok0zo5S`Yft5;3h z4*dU8lQOZcPt4Tva;)nkX&vE3jU~9VkI3PvKrP*EJXhV?SuWny5zoqVP*qE*wfPXF zQfsqqAh0$Nhg%zm4hPR={G8xIGJsZnG}@EsYA&78f~&hAF;0hiu5lW!bn(E;s$PRC z(lA76R^K&4kneD+xUl-pnbJL;Lj3g#;SM_8&{bUvNe?lBiHOw zgsj_e;-^&VyXK-l8@ozNpg17Cihu^~<9CoV$yHket*g}nlUhw~;yNNo4YUN?q3f<` z5?a;FwOCHzSu9Fv+1#~H>cErLD5Z4^*Xu$8`l5xalNN`*ML=6*Ai%+Fvr?|Mbd8We zDf+l(kvHemn1TiZI*1Zm^S(*=3Jad`zBqbUX|=xDu^2y zIRRRr&f_h!J=OKQAXXdLbwD5Y#{&bkoNx<9LI>-;7=-E%aE+0U09a}%e;VNGh3U5* z=sK#Yflfc|-uj9AK(MlUkn2}bx(TRK+j$LrGZYUeu7Pwak~N1XHIN>IR0e$~!_~|i zntCLkVJpe+~-y|R949dGz=)=zCN zwa~$rB4phzrY^cZ*i{#$jl?d-tGMeACMQVUibJoDXEY{+qvoSr(T3>0Xu&a8jFhRP zAzVWhM!V|CphTt{FO7Chm8Jpk8^>K+#A~=Oopc1z18D|G-;8m6AT0w(SfMUcv6L-c zqq2rEorX9JH6#R;8|RuKZ3h&&BJ2dIv~O%5f@+>~wbOv>iYfFi=3f}fqi)keHU`tZ zhMy17c(AjC6%!A33g>z3Br5aiXg~DzL{}H_Cq{yKvF{-XYAeqV(c8*XL;kI;tN@G; zaK$Cj)7x9BtD(MHk%~jz6^UwctGzVTydLFn9<7IaEqSV|Vu;vaC|ygg#t)0}G1moE z*oi7)u5w|St5%5EeyD!&*n^S!3ER@*L7BeUwIf*UjSJCkY2hgA*t~NhCJVN-#1B>P zORbFm*Ip1+P6gC#Z2{7vrn>lOI&~T+ zo0G1d-q2L=Z+SzvKILlV4ZZ7>D^}X&4PEcFE6y8wRUj+qF%)p#^8BM{zl&dO9m> z*wQJw?LR8|>F-=S&E}p~eeZf(Dm9FY09Texi3adg5Ns$LesFCOq)?s-=1Z!9R4TR5 zVL)mShfA%Y0nX{4UAtre&cycqT~{rsqZXct4Hs1V9-iF=NOXP!n4#lLY@lB1!p(&H z*nbR#Wbs(P3fKKly%E{kO!foUIAJP!{J=F?dQnG!uS}$#WCSLoqKB?FArm+x5G=ya zxrd^5k6goqY_#K%YqYe2!_g%?K=Bl#`08^hDtCWz`QzC^b6Tevtxd(!qOW0dnYgQ@ z6J{`qoWI^zN&d~%2VbJg%Y+ShgeR*ro!$Q!BcTp|xPFoVhQ9UAdN%@{1`h!oKxsz( z$;~6(oc_}=jdlN?aA6YM-^O{K;9i;km+Kor^ck+AGaD}q2k6v3-5sX4@wbO*Y`h7h zbY{vp4;MkV(B43qek;h~XE+IxXnD1c7(ZM;3lf7F1ExK%Zs8w-*m1bIW&fTDww;QY zt30SxI0~PS9&T>g@99y_#1vi?#4)%Ovw;4w2SpRmClA-}293exl9{7yRP=ah9SI0V zjp0E8Xl}Qp{&Y)<9`>Z|zL7N?doSco*l;?x_=Z+?$Qe*LS5%6ToxpBR|Afg7IiK5O@|7(XrZ{Xtfr%-^@)LAQ#0K}+FDO0#v zkbFmAc`}!no>Z73l>!NS!wb_&5eTehbo~*JyfPw9dSq@mu>_bU{>p@G)19BRNajY2^kfW*CvbG$5ZMU zt%qS`-p!4H4mK?ev((CBhm0DHqy`*B<&gv;{Qt4{-tkow-Q%#kp=K{V2_Pj2q1Stp zn?~qGrGyYrX)2@wp;sxPgc1mZ5=w^NL30E_P)0RBe12rqHZgi z&%mcGuut}B@o_ubK91{4uqB_4r?GKb7MreKA1&$s)u|IZu^h}|IG91xpvo}b^l~5_ zx1Q>3>&9{G0oT<=f0;({)FqN|^9f>sxS*?TKgaDwGxpc@?Nw@wg6_8F9Cs37#DQ(+ z7u2M_MWal#QAT6ZjMY$lX!kuwBgQwO7}aS8rE#C$e(oh(mQmt9w1;iI(QdVJPum{h zF_N!xG}{e?Y>yP`D~*(`K|q{9?;#G+wHI=T3d0qAxD6dFRHYhlW>R4|$d0%5S3@=e z>vIbtg$6p{>-*SxFyPpMswCLVf>j56LxL@y0aq=q`y^#NQn(^_ey9c=Hj6;$rfjrN z!0)mQf#t@j=kWs(9R`l|3hcvU^t_p`Ms!%vpbCC{2bqhphJeYo1QUK!4KmOioM z!jC~;)q&Wv)XOEe1r!am(bd*AdMTD1DSD7CfaAsC#`~P}l1$$rm<8gc!M52Pe-6^j zzV)W~#AOumeeEh1tiK#w>kd1?yx$97+ znVct}Yqs0~an}eNyiQ6XsgD$X(w{R(Y?ooX!U=EEm)zb!~j)zD6cp4;F>peq(9# zAOmV~c5l#kak{Q6a!oyR8*CINO#8%qwgaz=1uW5~#YvR$p!l z;5&~rj%C%QkN0#S!xo4uGHr7?t{B_4+l1=E%=~I5rBdDsNVPhTp(yo9dcB11#3qgaT+TsX$sISSWjB~tzxNW!g=F)1^T5rzySH7`* zjlM)T>q>M3;a}q*gY)5f-=scV?~l-SK>J1^8n7$n78@YJ|JE(~th0R~+(1+5yT!O? zbc@;>uoTdDwYWctT}!9AztjAvyy90P4dNAKz1XzTR@sja7)3lw@{MYv)V}d|hT1oN zmDE?dZv^YRHk<7Ykm$&L3<#!mRPT%4nVX}j81tMHDf;fJ_DC2b@R}$>Y1hW9Z zb>U^udWWqaxHHQZNQymt{g&-GKVp<|+Pg|U3S2Ax;-|rRjh2b^G6wAleBvne>3$rX zmO9<1WQF5wDZ<-gD7*rV@ZKgO(D*{p9@|LM8CvC%8(8jaY6VMHT0XFKq1@nYNN{Ox zPzu$%L00CD0MWV6R*M&YKr`!m#ePYMv{3M!;`D>I%AD}X81tYGCR%1nA?zJssk|rv zWEI+W1W}1Ry&%OF+2#wiM^iM*NokPMN@KJ*Z2M7YqVxg0#co42;B>UfXz=L~+hGP$ zl~$gTxS}Q^C(JdD+In!pi`0;Kx1Dp$W)%{sR(xFbBB&|aK4YL&^PJI{2QSjp#59Lr z9mml~`6$`c(acIc36Wrs!;Xi2atbClqfE0{DAU zv5nIPzZG~3a$vOW{z{Gfk<0cQ{|lVXDE@pSW6<#j7UqM@XwuYUlJKN$HzgpF>roA~ z+6&L>N{kO1qmJ7lW3ZA{p=Tk;IA`k&dI!K|I2J<4CPFX6QNa8GvkZrfVd78X;sq`I zk%34d1m8f{Cs>3Z51qsbsc0(wfaCoHD1}e^3p#M{je8_KVE^70 zt$U0cq{f9#&;-rc2dw1V8+B;f|)$@+CV1hq%jBc<~&oTJUW7X$TEkM?fHu?6Ko?`^-8wi{M zr($pb_yJGQ;rSEgz`3vBIyVkYuJ0;lNqp3ZK3yg5Yb*}vDhYh?g~|Vn3mtA!UQSTgtfxMKkTqzT9N&H~QMVq|xRDFU1-+ znRVNi0G3^`l_$R9{bvpS`?1FBMh{8O-;!aabz@s)du?&{ZCfLb|6{E2x{;tp#x4UV z#x9e^R~&~|5Z&jSuX=H@Re4_tDjBPOx_N_6LLLHQ);CkYTt*H3znQ)jSI$=b^2AQ25_TkJ9ztY&}cUyU$|5`%d0T;+^y#yK?d+xb$>J`o|DN8B? z=D4)AMWDhOO(t^RV0{)KkvPCD0Nc;6MtjYyUP}`=6Yx~B7j8MmvghqdAhc}3Bn%&FGyfi-^;f5ORH&6lyDpBjZ4Yn)ysBoN!C(eqU1?7)>H#! zMP32#GZgR%jew64@o2JJv%kGF*mn*dz+R$lgUW9C3**(n>6mY_gY?M;^-OkjB}iiq ze`~0HtTl%=K&Wc34lY!(R{+Z@+57WB6O0$6cO?bZn1EdZ8^x>A0F~`q_$CvK*CU4- z7b?FQ!X3m%!zqn6Gv{P9TIXCk-Y}k>0`xIC@<;&h|=%V*y(3RcFOJ3rM!Spz8WaOU=#25p>FSY zVjYsYMHmChar~z~wCw$CsTT!6Ezje>^`T(zcRw9)RK=;eGkOXx@GUPR2WeSXSHXPX zM0LEZK2bm6sNxS3jyv_>LzO>%hCbZ_g6V0PZ#q%!)72+32?tuk{FOC~?6E1mQ{hOw z7HqG?3$LQNyqN?0;Pr3GHz<5^F@kEK2K2@^Kalw84zvPgkzvssLiWB!Q^s;LEqm^^p$!{ zqtqi_iizEe4V&4|aQvl-#&IsNJbA720>La0(_7dZ^ZZRnw9zq5s2ZhAYx_=)zXxYA z3T>@r6x#Cn4<@RYvm^iBhBjL4|ML^-O)|8hjuH`+l%K|ix_fP?sIfbNZ##)GpJ+6l zL1t)$eM&aD2sg{;sH(CAob>or2lgF^dn zPS>N4zSCWwq>iMYdr6iSoAC+ull(7}jD2pcB-48Yu|Pc7*WM7mX)@W^=QgTPz?|1$ zKDjx;9tQqNhrhNY*c*Va`oSm~Fxl7*cgUkKZus*gwHtmeiSOTKmAk#l*W_v4CaZMW7x(!eJI{7V=#)}I9aXuh5t^1rlI;0e4vrwT?2i;Hw@~#WB)TvOckc+>zgYJ z9HW?=@~&@UOW7rVY-FWe6q-nr4M#w_a5z`oyft_u)!rQZJ;>eyyq;>0<`bqEtNog! zgWhButoB#X0AXNdnteY%Y>Kh_f33#F?hmKL?*A%39?omD_I@YhdUaoI;Hg%KMfIj4 z0#fiV+^6$MUFCDzbj7%tu&>%wEC7Z6@G?(Oxs$PAcM|maV@6hRL~R9|A=T8A+Gj{R z!JX0e`N2A+2s4zs9vPtXYp_Df&N244wO$$#&THIEGMHpd~Go&0}ccK`xE{z!q3U50UsFUWX!?8zeDg-GTOk; zW6oOBG=rN8oeXo%qhGiTpC9^#-_w3rjdQ?O;>tPpVBYi! z)kmu6j>)mVVS1fzPAq`m4X(4q9?!i3uFkXHWs$htlkxRhA$WA6=l$L~JtxSUe)0`| z1{CS^lf6ut^w7nwPb*oqSu*)MXY!}K_~Rv(tgNxE5)$YC&Yi9MP{!ZgjP>WDI3 zqLJ=Hnz+N@^`-WXEPPSXiH4v`ro&?L=)e!iwYOv8k;JPj60b)1IY^|~_i}@3LHnq2 zWQ|Y7uWySJmf4qaCcifoBP4onu>$H{pqmpz9eu&iTkPFsI>36CNBtG^u1mo{I z8=0P)PI(AkKYs^_C+&k+cvU!>NQk9pBPFaO-?dla`C8La3F{G*IZoC=z~A1WhmZ+I zODlHgERc7MuK|Xgv5z-dXhK!4oNX|CpziSCj1BKmV0DOizRz^}2v6vRW+CYtT4m{% z&0d0C(E6ln8Fd}@_OMuzgiTKHgj5zg926!kt;qMCu0F+kX*$`ZP~Uk9(j|2&J_9g~dRk)GJo2d)nNQL7zI_gF+D-M5bY;|e`&iQB%|5ih!tDlg zK7>gbgM@>`tq<)7O>P7wscVpJ@?*<&wP)3$L=my+rFYQ`lvK z=oXpHso=D`Sgs?EYZd>^>i#hzLSOffV3(r%b;b5a{#+37{9yOKTOrh#!5~Yjf1*+S zBdB`nEYg5f^jtqsw-29Ul9;9U-;|==C*GO8+O_@99s%nuK<#!1`AhCHyh<@f|R z3wv0npwyF5yz;`I^lds*eNbB+&P$zoq3^6ewNEVi)qc!02lC-PFd-)znN*7`U9j&r z`{;(cU9#ZAIg+B8R(0U>p{U_kJM>~qe6++II~v9R2pwFKowC~VuAV=Zb?h~@$)s!w%M%~iL^I83 z|Jw#6mUq-);n7lGUlG+5BLaeS37871_~D8>a#80uGMO}Q2qHp%sUHZt@QR79@PU&R z9pm^nC1fefo6I6hOZ~7+b(S|UlUeEwD8*O!^!p%<(iOgMh zc5VwHUpi6myWEirZlJ^T6_p&Zp#BO+6G5cNPa5H9W&sHyvk%&8JSF=KEZu! zIGVz{A-H7R<-rHS_^?@ClSzE&?Cw8H;Z3zMs0X_gi#ZhF7{j-da3zb0WsxO|X*5f1 zG4*CWt;HDG{m6{dx_9EzXQ>S(g-}f!ib;TmGU&nbSa7ZqG?Yw=YT8hy!%8>o`*A6d z?tg12qn~#iE@drm2^?vG0U)uCW17K!=SCgJ7p9YlUaz&`{fZW$hsSHvxO3w9P{(wRMNrx0QOPc8+Hfol zrdwoc<#qLxH=$9A8k%N%Efihm6)Mh_vDAClaQT4$cPLEEl>+oabEK3V!Vn`Lm!@Ls%FB__cmqpKIP@n$m@nz>C%&STdd zZvMM8*CT>h09Ni^(++fxbKK#DImY?ojC8y;>3}orh$pBy|We_cxW!(^qZqL%7i&m ze2|1(+{y8P9|d`5udOJSR8``A1VJniU+m%-%<-8%1YA>v0%~`2T;+3p2sqe_0g}2q zU?FgTw?Aof)B;Yx{d5U%6D<*(rj!z081fZf2zcj^*4tq=eM=+Y=e8%n-QJFaEWBzxX)Otf;TWB* z2GT9c%8=U!hhA^tJ>E2zT}0+8psGBl9PCmSk)IPB&3L|%gza5KSZwbiGFP4Gl$*;W zI=YlfXP>%#z|kLbp)u`*xoXqy?WI~W?H^ut9OOsLH8$-Yl0ef4Vu4uaRYwTNPlqJK zOR#Np&i&&PR4DMFK{IqJ(ljFwa04A}!S4ec349Km)M%^!syqU-)lZ(Q-s<<3BqxPt zS~^c-=R?5#<4bh65+^j0J4OVcWQfbacS9VVL7NdUIlM$^nobTc%vC3c#~{V(AH6n8%wApt%@zR$4U>b^D>iwjjHb{{- z_h(P7Zlg6Htn718chL`?r&f5~d6;ZU;j1eZR{%YxIED$4u+MAUw7$dVsdL4;;Qk7@ zAD{}=KJ()HHVAE3JwQx+(@~uRU(a;-^UqHO-tB)J`Ul#Lf%TaV6KFQwaax8^DSNMx zvP)U~Vc8=%Klo*a<0n%NV%%$dUK%W>Jh~b04RgSTOh*h0ucGI;9zFMebOnNyWoMTW zlV>>+dD9+dWOUc+<{Zb%rXr>pS^FNae6Hg#3$L2+q~3)1T=YVgew&XP5 z&r|P6Zz2nPs=b{4Dg&A?(~ptO=Br(%@qCrbTm(&CgW<6wZ1*xsyGy(IYIkW261SD+ zE(T;?TIq0@GSEz3`^0PE={!e2(?q5jnM(#3xe9hL@G5ipPEY5^KE)STJ1%jiCG?<* zFRY@Qu`etUi`T+6jzv&S_PyR@KJwJibyz8=+!udhK4VtL5CQsTbp&=PW;JiU<8_|@ zSi+Xf>Jp1Bnbo`V)n;`BY3je2)soHnX7!iGto|TWOOd#6i{n?J`T~VV+M=o~P+Qa= z|JtI&HrpMuc~g5dmDi+HVZkJQv4ai*-I!gD<(w&v9u1p#(*j4TX$;ehOgs&ISKw%(f`9*1C}_LK(b6=B zhTr~9F@m@6alFpLRrN&h6wx*aSgyDNK)^xA$za`!L2_I!1eWwotwEhbj)|s^86wdVgKr{UXPS{f zKL$Mu9nma&-r*B{0w_q?EXBKpj&AVgAJvC%{!yB)FR^)vhQXS)9dRt+P0uZ)ERQ7i z=!#?orWq2(KerHYq9aKMVTA~T-1B+}?T$OP=pbO$Tk0XKI{_alFeG8)xOc+w#MFUC zz{b(>UB_ue*FWz%cCuJ1U5Dri0S7)>EV5WZ-f0{*l*(cw7BbN<4UwWB{gPpq68#>W zaa1hBXGz$w{6us~FMk$U3Vs<2)%%X*g(Qook9l>;m3Ha6ePF*^W+fliisBEloa|$X zp^thC7)~mkbsX^H-&q3I(*e z1bwOnoW$smVTg>u95R&2Rv$9lk+e@I^|WlrNdw&?o1`3olF)}#1HhKL)hmDxiyb!8 zK**ZB%qY%2jA=$uXdrm;6UQ_ic)SgqsD}501Cxl$%%JkZ^k?+K4WD{VH-TTD%{X8_ zqCnpPSHmu4C-~=Qj!GPVSi+Xlk3%fBWVRb&wI+7wzZ$Ck|HN$JTP+6P4f_(-Pi5`) znwNgbZojzhIL!a*!*0Ew+k8L}3&d()IvR6aIZ#~U&@Z~HoFUJXRN}=2hrV*GgV*X5 zR8`Sk1vN)TWi0uw#*(i=DXLE+XuBnku;~_Aw_@x~hnX{VT|}9!Dmz;9j7BxE1RE8q zD#Q)Ld~%TDiP_!#(IomNH5hhblghgVbMol~OR}Y@ESh9X$&1vsGVN*OW4q}N-3*`fb_YZMJ}rRv?>QFvK@|M$TNYOpeU3b% zp$vN9I9E!7R~KZpKGYhF{RQ5esJECR8$bDeo@$XzOMK~}V?1YSLG`IKHm5`=jSq0f zX1}n%9B+!Haj}3_e13YgsWaV-)1yvT3j6c1i@~<5r`xkw_<6_J%lplyS7|JKQz~|` z=!iTS$FUfAp05KIb~lZnG4MPgIol$+SWx(vqY;aQG(cT{a_cZgmRfM}ll^_yzUS<( zd-dt84j$S7)eMOak1?l2n^Vl;$*IvWWfm`A*}s$X+qoFp zNA9*7%5C`g%hH&u6>i8YUBiY{s7BFzUT1DX^V&S8mEXVE_;#K5)1b5-F=`sPe0Os| zslHCvO?!;_<|mgppFOj=A#N_cW|R8mSb1dWIU zj$6wD#gO*Pu5uyazNd}_8%)lZOP#vf`DJF%zLK+Qa7s#Qk|o?6nVOOkZH-BfjZKM; zN=diGn9a$SnD8`lLP`l_B{?QGGBO78Y>rO1rkhieVq#OHQ>@WZ)|7};a}>D0Z9{;# z(!OXPS3f1(5|LyM4~Ij=S|cN4lf#oEEQss$=;)|OxOZPyTih12Xct%7)F5x>`tW)_ zCk89+>%&3ESZ9OaWOGz{M3f~d+=^~FL?*=~$E3u>LJHI11&A06;3};P5a%Asd#y~p zR5MgcL~2BMWQ;X7IW{RgGB!FrB`qd3Io6yiZf~{7&IPANM3_^OBaSVaGN^xmD_h_#n76V8{)f7<#p#&KC;>oOz@!Wtt}u~XY6`F>10sR( z<#TFte}L_MoL$PThHqTuhJq?t55l;2K&1p{<8u4qeal=kxR>=HyxawNqL|wW%$fI~ z3tw|FIGW(>;CCMmF|@%#>zqH}+&LL&gq)0bAW}{SLe0rQNI4lbaW4d>OJG#Wfi&Y2 z)yn7>ei^R{`i0*zsfvE#Ys1yhFMJqY9sR-^#~SDtN=T+;e2(}9d-^&*F*QQ1@>b&T zDfl(kmz_1mpAwzrIdJ3^=Kvnon}Dwcn8Elx2^B&6H=KcBLw~2KIg+Y$sqWSsc(bk< zx?V@0zr%5*^y+ed=VDVI%|sIhIBSA)FFXGSUL2@9&)`>|ZJw2{Iv0cegPi!mY#!pJ z>|i*>;sH(@_^|$pIdIyxG57;($?U&bDvV2r-ndrexRO?KbwPJZUyhW=6u9`4sH&1_BNeG zP*S$aYBBU#6u9^eXX^^c-(bG_39gRNpceRgq_dYF!~mg(_y90#^n3yI&T!`YMZ>1N z5Bb`B@RIyd&eiOoXtP)EiA+xg;xr6B`15)(qn#N-KWbiu{RE|zV!!Gb=Q3VMRr(0~ z_~U}Z#7EqLDi3WAYaY}Cf;5|6xpRu6O=&=b-9}^VBC3MuAbw zoiQeQeB!&8mpgX}$<(;ecZ>ZX9P!wZE1e(uO@#kK&I+riCFVI_7N}7`VV?6ZVF8QZ z9sIS*S)>f&UhRD1w?-M{<{D>rmK2qgB%&E9;fpVYYn^9={nTvOY~U4jsW-b@O5zKykLW%A*~RdK-SmwY5;eEvj_ZC zN##AxRULKKxD3S#%Vg}Rjt`ew=0YEP2+1gU8Il<1NNxEym;I;4u~} zW!NxvSd5rD{0mbTBU6Xh5lkJnbWGhOnYy*;S2au?Ru>{K8B{ zYzp6|pK#dO1%5NV_%_Tr#~pM|%`bAs^L=xvL}ulVgg{d#C5w6jmLGC16K0|jaZ)Q~ z4k06Xe^^~i9tjq-=Zau{Gz|gb{OC!JYS>76Sg0#aa;9r);L9TC8u;-}O!^Ms81I5L z8KbKQW4+%$l49|L_5_B4ZDH^mdBcu4T@^SxBEOAGCc4MaY?D#ZKW0c!g9V0 z+Sr_<0(HB@LpEnxS%F*T)!u0ky3^IC?q!6HGq?Z}04QuwEzcb!Zha3Xa6%PhM5zcD zjp%9S3IgtP&R%@*GF*^O2&M2b7bt(?>n&5R2h~$Zkt%UfBjy5B>k4!`@B9TG^~ZeZ z{9TBnMntUCQ1GQ%Si+}MChl0f~>)=2H^er zhf;+>R4XLD5B$Jx$wlXU20CwqtB;_NP#3&g?Cjxl>aLfai{R6|4=+1&g_+b0DrTfQ zSZ|ijj2QW`a~CJ9qQ=Tw=k6zLpc)YQl@J89Q(S7TIk0@h zZUAY`52EAeT?{P{Jg2L@&=58YSEzLH9@@awevfUPhL*ylPU0#8u(oNh?>*X zCu7u)>ywE^B~CLZOrsbi3JYA&PMAxzA{F>SFtGcLg~?j@G4Gy<5mu?-;bQjwx6Vln zv`S1}3GEDFl$iGV5L0&zstA|PZ+ZSCkr1T}srs4DEV!1~c`^%ChD;IetD0H7dc>&L z32GBPJr35Ql9!WNI=rixclk&LoF||)xRTNwqGZVm{zYk}!mt;A1h9-;kW>l~ z{K6Tk1{Pw?nI%+Op?DfrzPaI+ra~aqij>b+S^@6ebq-{}kv6H7ZxZ2{qK{ba+AYU^ z;`ml8NGUT#xKlLnxmZGh)CdZP;Pfv}^g=$aHP(9tbC0M8qE=eFNj@`pK^3Z$!waw< zdY|;gi8{YJuW@{uG=y{kB$*u|j_Qz(^!fwlihxyyWCv@MRz*ta7fwU+i5>U`+61_77Stm`Z4PiHuXk9<7O`T1 znIbFMgRozbY{S2t<2e2!R#OB8p$4nl2vYK1?mzFkWj;PyJV(!LsH~7$no3# zq&gYP(_@w(4Ns2|PyGLQ#ZLmgPg{*|2a3`T1c(ztTwOTf3^h3p!Z$-*F~V7@ z6(>Pwz{CcwI5l)5@Kpm>N8zd#dTN;KECY=qc6~)|-r7err6dH?EwYV>EgHFIa>5_f zL`98VF9=*7BRZ1a!pBdEOPl3MaUF%Xj<`EiQmL?kb@R&FmFt1At0Z2|ejnw7bOnvMzb#hzOUfQs^40 z9UJln9Zf1%^@b0+lC-#Jl?@Unw{*2A$B%_G!h)dSzn>|YgNr(KSjFfz4o&Jqw=u9E>$ckPnmJAx?-<#v`X;!_fY^6V-~v83T^=bEO+V z_tQdu*&m8iGd31}suue5mtFH1Xe4~fB7TyDPw_<#F28-nb(0e^sS%Ykf(2A7<{=X- z9_X5(g+5ddmetDFLVq;KwMPw|Dio*y{ow2%>vn~@YS0E?$q-j>;iL+l%LL}vToV~+ zm95>;vMcRADFGn2a`!&maPggVR~b$iPIZvH8XXtT zqFRyFRz_fuF?^6)u@xvvsuRSZs$8YA^a3^|Wa28-N4iGv!dhy0Wzx-5D|VH&pwVd8 zUIXYuTId;LT%8zbl|_3CNl{c0i>^tx$Qp)^BjXwtp#m4EA`AZ+YYLyB`F+^*W!SHn z!irY?%7f2)Z>iNG`VOD6X_z3mt1lVCx&cr zP3HKm`NrpN?@C6piC`9pwKloFRFZn+fTZf3a|#I@)Z7X$IFgV?w~KrQ#?zM zhNqr1PhiqM*EoJ8%ThW!LLA>u!%|OBv>z_Fq#CRbZc16mA2AEL!qR${rF@nk4NI#D zOY(YN?T~AVKYtY9Geh0A;yLNE|6#x!<{yHL!o&Qajc7pilD?X#kv_{`i3s~oOZp#_ zS<_3pB8wkbS$tQDEN&55co%jN9_Htl;mfWw4kE8evf$TYV=oXZI9-j)@+Y2|%WCGUT+JbMdA)L)I4 z=TcVFTwIhv+-Qo?F3_y=h|f+cT@qXKpN#P>gQE$4(I3Ld^hMIA=$mAIkMu^hk;x3cSjf3CW0fe|HhaX(!i zQJ~~OPRXeTMRw>H-W^^eg;a{ab-g1jh8!_2i_hd%Qmx2k{U8{)_#oTLz^k10hSuDO z(=PudJDd~ttH&&WW7hpOyF`FLWExas-qaZrUn4B{Ki3UTa8sB#;9%-6P_3AH2nMSD zk)5oC-}*;(YvG0po^u2H9aoqZy6Rn5Tj8D-dgoo&DJ?Xnh2Nm?hJ&9Qgxz<|VxUzA z7$sVseYx$52iWXU2@t;72F7h0qse`^Z5ZrV-1gotuCF=1i!_AfwjJ3a;`kOD)Vsv6 z4NU&8YkT<6LO%+E8ISb+cJv0d-;VUsEBWn?-(5TSg&U0h_Ag14^9W)AsDF5EJ23mP zs}uU-SX=a~H=hsbH`)yFWyrH^d4Mi|y5{n`;FLytfr>H)vlp1NLA@6k38z)>1t{4) zjU!h96P~vP91Uas1p3ug%>_SD%0O11W3eD^AOXjueTz|0izBGeY`yYbg#T< zWsv?V2^>R?M}tmf+$)7&sp;j#G4O%XszfBvp{#qfewSz~>wdxsri}_Oih~DGt;nf( z(?&3_f_t+8cw-&#TNT}HOw{P`{_aZnrcXzI_g_K`3*R1?yDzB#mJ03yG*P6<-IAFI zUy6-qaWF}>E4hDX|2VPE;CoD;!cEj4U?+4dkV9t z0dUlr0m@c&zXlCLmNQm_?WkqgdZi)wB+C%mOVpes6k zxUHZ^4fi|3R;pb!iA9=ZBbg*ncM^Psm&#zglu;6ro=(s$N{}lEbfX9FxS-HyAT-D= z*Vg_7QRX8QUWWZjD6Cl1J(A<@k`bgx_!Bz54yV9eXKs6cpt0VCHq`g z5V|QF)m3*i1}#8`d-)Byx*#b`;i&c|-y8+Oe#{a6Ld$|W?i3#0g~cOC9EGzZ#PRjv z=_5P=q;}>(AgdXiQrgDqQcNB(>vqY^4Dd3eIpi6-Ngd>0^U^H^d13tNPGD%Ly9uZ| ze^VteXZ&dk`ey{P^)R=O1K8IkixA9kj{csHVz{AtR-L@ic z*=%@uF@A}pnbu%JH%T+-AqLk1{X4E^O*EkTz@y4$?GkQ6l>Mg@kNFZMNJbhtq_J{H zE=3MQi5$F#9pFuSetofHTlYMU+*~xbb#LbQtj)$L)F%=(v&l#WVq!b@DL;M{WZfuf zx}ib=1zGO?;+HY*j+|Jti+c;l?|>5;B~U-g*xm%HbG7_dSPT5{&FbWHsE!I=Q>oxz z9D-bsbwCb5eB0}1`N!Z#GAlI;9Mwc@q* z8?j4ocQejJflJxTx_I}y!app$l)b#w$32z*X0vh+k6LB_(vl@TN%74#4?2I)AwaC! z*PX))^|vTIVdCf3*%B@^rdkp4eh>^?+#6JvfyWtCj0%*mzeQ~NvKv0V)(nkzRz0=w z;NB}Rd(wcfebxPv@R|;I%m6pgg8wzZ9V3j@0beoD-JAheZQRP2C7T6WYUB|Y-J%4p zf*-p3-x@nDO3ZC?S3 zhd#~PuAiWT1H&-&nic&je89%m0R2=Vlzh{y0DPL{zRul8TS&sZLy!x^h!l5k zj^lv^1{2+-Izoj39;LeNTy=!tV?}P~#X{1cR^Al zyF|((GDHD@i}M2U(j50I9JyZ5;%t7TxMGfbJI4##j92Xas&PcPVw?T=I@^qw>Ekkr zcbUfLl@EzN_?sFdysD#&PgTnJ7c2D!SsOk=tr)w=eUldwwkf*DYt8_w0k5qI;PMjp z1_lr>W_V2)sfBKq>yFbxo5mdIEzHzHM=x_XVxTb*%d~(smb-VEC~Bqky+`5cOkpbv zF0Jo@MW+XF3BZ4)JCB`#J#siFOG}o72s4o5yl{pcR(g5iBnVsM9x0rpIx)?csRk^# zlc4KbcQXc1$pT8W(2erlZY?xk*dJ=4_XGEJ1{xDlZoA9`IfXb0+OJnr3;Cx~oe#DA zKUJ#pF|br#6abEFaPKm>M>}?-d#4c2QbZmM1-4OIl}(yBcawWOCv;N!)DM5IOSDqx zp%`hGwQmThh|fBan_$|~Fi#gny7D0;W!VfK43fzIzqqgs* z5eq1W;5(ESfJ^8qJNOdq%o54Cgsx+|@q0Mm7@?99y1}K84)SiEc9%H_>7y&?ityi3 z1>F;fbh?5rY#2!|4{fEuZxN%2TcuK9DN>DClL3)Pr9fCmrqJDn%L5$> z-3|Tfz{}Rbk2cpYmk$reb9;cI+y}kN--U~QZi~qvbjZ&w%4f8MGv!7BZux^4zu({} zxLDvnurVhi559bulL5zo|3w4jWFXWWjFOW9f$3s_)ptO$@yU7(^b5cE8-RY{`~89F z7k+#lgnr?}`{2$AfR6gYnsoo4xfKw{;3(l&kSi(XOOKi7;R4g&*!xc-eoQ8*WvwuBZ37q-< z4ou>w-zqP>s>}vL&$#;p^;a6uFKp&;@Vq(py5jaT?t(I=R0@Ke^G|iT`v{|zW;Bu% zy8_(q_LUF@WCY)Y9tg5tpH&mIs06>mbJy;U1)|$si5(Nwj;h-Z4ToPk7RWx3A`FDu zi&Mj>1_Ucn>cy%KC!`Bctft7@e#za3nm{UTu~LB$SDtkb=7sG_3vm4EZU8Q4m2WNV zp<1iGTil1+4z_;awrim)-z-iR-c>>S!9l^exwD&S;X^#d9fXfm@No2~3+_Q$=<&xK z(f(TC-XFQUYk@K0_f^oCl{}m!oXLR2Bb7%+hE0KFq7V0to;c=Xn5+#*@7jXMVe+U%0=558aUMaMGUrB!!z4R}#nXdP}`$-|`mO zyV940btwkhdwMbq#9#cC+gmFF)^@=ZNYvk^C{R)V4MTmKuifABemlwOyF~tTI~CS3 z`9EpM|K^#;y@H-_!&vr*P%9IOr2*!dogF_*ksz9rsl&G!D&2wa`cJx?j;klB4Ha(bBDsi3tbM#eCY0=g}(g|9_2pw zwjyTq`Zwv@ii+2mj6bDKQl0mg% zgG_##GDr;$)@G&(hf4-O9xQ&*L_up7h$R|f>>$hUsYAt8IDXCBz%$tSLjITS%2F%u zavdaG`nG3LaV#h7py)_^r?{K2mui6K*)2cI&mV^NmPd*$3@~ONvvP{Uz^1kXJpWE{ zO9mPbeUSpBhQ9kwabpHJ z4N(kg1iD&BHu&>B8^q%7oZ!Dp@gYc4BT(f;aTB3B)rtt?{da+)ipQR3z!m83~#XLrT3(cgT!)$|Hat$PC^Kg&Rcemn^O8gy2wc-HO7yR{M@n|jdM?GKeAY^EvTYXgAUJcy{+s zm5`~04!u}h$3#)0vExhnc5Jx5{G44-2P8~7Spg(mDjq0or>4Y_Z!_R77dJ6&R@yaF zUe}+p6w%(Kb5C5&<=k$@hu%X|>idurcF8^jCVyP~Gw+d*B^SCuA!8Rh52{^ZT*wJc zl6oar*AB1?8H&zxcUvQPk4)o40^HWJ4{9qENc2ih6!BScI^VFs*op2Fk%khy0#Nt! z;){G_fw2=kQXwQ=E$+>Chcg&CkyJ}66po3u!ZW~x=Br!5K;yY|w6|&1efWhh{56XT zq@TGJPl*cqkbWo@w_Gp&m=h*K7Q8t(Iu)od`*D0lsYC)b-VRhhwzU}eRdG)aeyerZ zjpCld5^4nGVU-pUso*mt7wCM>T?@4Ps(2rmI%jre0d;!k!(NJyUN%v!c!`E! z|H$1JkbP!6YF)QmC2+kkt{7`Iy zbx#yreBz{Jp7B++sN`^hrcaJ9-gqA$#FXs8b%oRv97B^#{VFKO&bo&*i<>x49ISW4s&Z9on z_%8_8DPU>n?Y|X|GEsmUlkrySqZuJ*loY zPvGAb`1dLN`wael4*#ygziaUCI{fMa~jWsD^)#T3RU(hE}}SnO{x{gh$?$QdUa1rEjZ4}o9Te}t>GD?1;1H%;w2$Y z1?~rlAX^uT8jX-GT2bvFJMf4=&thKaPmPK>X*2Vi*1`~~6|1v97+=fNRt+uXK4Y}d zNwqx<)X)vUJ#+cy!W=EM^?A=66GaK(f>L;dmJ1Rh3{)k(yoHF- z4-wm77Y-4jGd;}!U(a)uw@Jv}+@C_m5u#wPIznvQ%VaLPtl>E;Nl)sh|)9TAZl9TgKD9hqcKO9hU@ z2XaD60kVL+hYM@*W%sGyn^soWo|3lseco$I_*%>pc)jTZTNkR@-4Bv080Q(lpfdN%C~-^ZkVqPdX=eks1sKJ}$wh09l@ z$$AmY0$|^FU@^GYtfV67X!V4U`}MQ;ADAw;wd9BHQ{O*Q#`9L0l*ilF)bl+*4pIQ~ zLh3r0f{`p!;7ts%oL}0f&J4rhv?za;LD!8*9C%_NlFR7c14bR8oCr>m4Zz6`P{5w?EJb>@E?Qe0^@ku>(Vp+0_S!8hI*# zK=D9t^v~wJu;19AXGrr`*pKHg09B43m?s;rWYF&)KQKvdYsuH$Z*0(W)#Kehao`mh z*B>ODJn%C0&p8JVRN`Ag`V6)~@r%6UfyDM6RA32Pd)fVJYro6tZ!-#}sb#;vOoZ~ZnsAiQ!!E{MA;?lMrGsiFUA^mkK6cEwQ zbCBQcL%v(R7>sCT9@A@6%p@u@buz@i;yR8G{VOi z=RtlaPpEL7YR8$$H=R6D!cD3bXC~*tz#>h}Kxhxo%Y34QDJc?vT<&s9;5U~7! zIy6s{D3=yIiacVTRD&XE^b6Mpc;A~gYACm9C_iOD`Q^_mf*5~$EQqTPDgV@f@{cu? zpMsRD4?-zw$srEappXwn_w$?dgR}=F8om>2D zNc43L(VrU-U1b;~dSwSl^gRQjf7THFxlf`4btMh{NYalz^$)4#TjvnA3zdAGV0sTo zr4@F1?THqx<&Zk$)HzhTB=>e1a#1{J9h! z4*8?uZDIEH|5W(ukrMLt2}4OxL)|Vpv6jemX%k!;6xsxHA7DvLam87Awh0Ixw zt5ChPz|07VNm^R=BDwyTqnsv`WkBs2Z-)QS2<|sY;oes*r_J~5;HwuIZ+v5oMDZ@Rrh&PFC;uxzm7p~ino*>-(BVX0-fgV-{1Q)tYW#d3l1`Lp zm@7$Iv~TqISK-(A5U{sWu8h)UpJ#Dpey0x!FYwO7NO+b;!oyL2T|PsySxO){%`U~E zH!%*43uj+1@+PB+_fK^9hfEs8q$`AfuWyTOPkZjw;D3V>E`Ln_tnY1!r(cS^eu&FU z-zy@uD8EDls$c!Qg864Q>cxnr|KgWhWGlkHBKsxgzxiP=|2P?Ma@bG+4Ph5f#?e!D zQ^B3`&o#?hGiy!Lj6m_pRnMR@q%wowHBV9*{)NNFuG>W_Zq=2HS0H}>m8VNZe!yX4 zk9|#zvg5Yrcm;kqoW|o3ICrh8r=}iuinLlB56>fe|8U!lgMaZ zNM7@#3|3hr#djZgrg6eXYBtrg{Cs&BnV=nr+yHRqp=U)YSwjHmJoi*Sc~A1QUc3&HMTX2+68VViriK^h*U$wS37i;VeZm zwNvC=XuPh}L$3o8;nJ!@5l+sgs0PJOWG6ZelFBbdC9yPwKh!1sz5(I;{7X86eXn_% z2>$OVW=0Xtmw!jS#l8QZC_igNIUnOAgbh21VYWZB=X@aCxc==2R_-ESHV$S(N|_s>+_JA$Yn0!H=s!f>%_A1g|n6 zc!h@G>5yRc;z1GVi|U_hlq?U_-S&YM0VUbOIYflC2H}YPp3B2inx#A8&zDdN6X4qgAbvJHq!ACO+W*228145-EH`wc~3iPq;PBg~wDYB(WO^ z*_t7MAu(iFws@}dmI=teiVH!8Y}*uQSc z8eV8f4XoOYekbaGCkeN11Tn0ZpeL?&DyW67HizOAhgaC1iMK zJJZw4pTfoAzUxtSxQ{!^#7kX5$xQ^^F4-o2@q?7eX`ea@@r#bCeR%;P-ka;d#a1X&ZV&jYP(Z(yCC7RHW5#K4H5mg-%lr7{)=~8n*pGC? zd0r*XXHS3sk>yF!UtK#DN3`yPFjI_}fd>IniBDZ>F(ZNcUF+KE=92vL zqB!hJIv|&jL zPDAPt15)pIhNRYthonw6Aa#O<)FJ+0TDD}qivN@BsgeW7gsGNAVl4ZXK~(;KX72D0xB^7@{7 zCFh!h?eW@;P?O{O27IIPFBL&hxs$P=&oD@SCkUov#qf=MI4HdvYI0n=@=_H0vgD8Y zl(>aaXd-EqRwZe}4Pt9UYJ9~pWQmMHg;xu}ioPX-g45H|lTzWidTe;4#hMb692=36 zniiE5o0Jq48DotQEsxiYD-#?Zl@gm8ZAnQDPqtXC>5)nBf@OFbOmHG%qf*jiLGd?> z0>qm;mM!IiBhB!C@Df{uB{|%hVvdfrMwyc$!{Lb5^b~6h;3jVj5JTE8yT%3ko;neN}wmYKn!%#w=r%`qv_Nsz9Ts2H;~DLOSNJTfUFGBPsN8W|H24lcjGEKoFu zFB(!NIMNy(lbn(i8y*c4F^f4hIU+j3k_4}bMuta2B#|4x%*NHXhNqe%(jY)&c#PE= z6O|kunUWqAosyCo5fg0{JN>iB#s&MHG#z-N)>}%O4@{`I*aCh|E=dcvMq4d0(Uw?C zGL&9;L~?RkQc`k^IXV*lrKiLYL1QNBN5aP<(dlW?X;1@JYZSa9n4D&bg8xj7NKT3Z zD^1G-#g+C&`?%m_ON=!pDLFkdJU!YPo|YP$9vu}Kot$KjNlG_IrHd1eu7~WFGV_Gk z-H;KVbH;$ImzG(8J#kq%aPO0ns^CD)-PPN~M7NHN967noq}LnFn$B&~KABcp0 z7-dOMi?EnelEM9fkS}7Y&{AXI70{FvSlY^(5)m7d481fmEjrl}8=aOO4(_KflRYmj z++s?r&`m~Q(_~dBcs#OQlrzO|3CKLJ20vu`WN?J0twkbdT1d90)&#Vn`|1* zBs3L)P((pW3JDNEI)Wm_f`U|m91)}_AQm7f5=2U8H{USv@y8IModQtyUb|Pf-d$%>U zy+}M}otBu8iw%pj9iu5R&6tnIWlqXBn)1_f3Q88gwjA9^N-s5szo1XBnCX`^GM>TT&cq*(gQi;oDUS#(cy`Gn;dga)zRrrkZdwFx8kaG#M8A zEx;#fKX~^OtjnW|&VhXq`;Grv^sQrWHi4M|mXVRDVUyXElWa7jM@+~w<))#Wi6)aV zaVUC=f|86Qq$Nyo6+PUdgS~#HNyxjj3plskzDM zM}{I{%1y+YrsfPS$V(XtCzo6aE2+v`@Uir7rGjbxeAB-b3XAX0Pa&4)5BC>bY0xrF zu(}k}(6qd?f&y%gL~~+-DJ?ZAFFz%*AbDtt5&z9S_`NLyy&@ic3Yn>X=EfCoOEVtb zNI9NXl=SHCnWswqNX_Nvqs>LZq1kVS;v;8|u9@5FB8@m0l26v_!l-QD82>gXc*(DJGM-ASWpaT~A60+T|W8 z>d^(JB~wE~*Yd~`Qz0;NzY)g7FZYc|!0wk?kc`ePjp{ikFVUEspJGhO$xlf}yFK@& z%L^I{NCbkTu`v-(#;4`yrsn4+B<2{CbA}p|Q*%miAlNH4%*oA7N=ivc$j?v369Z|9 zsfh(i=G>gLl$7M$f|Bf>^Gl`3N0*t%#_NA64#w5~$OKtiuS9iBY&vRUTcfd!(b#I> zqy!wmOgMrkn&J~g+d~J2BOQ7I9Q5!=LvAkKM#(dq&;yur@{-_|mjy>LVtNf9d8z?2 znxaCgo_cq#G~-`dOl3@u?xU#%o~HLmHRdLm$Z+>f^#x&3kFHlr0qooMZu7{YsRb#< z1T?t3{CqPy{#5K_=rWTrE;JkSl1fevClO}8IXRU$N{k7T%=x)^amQpz8H(XsvN@?B zu>i1zUE^FDT44cNTOP(5zw(1P65TqFJjTW{bvH*?P7vr@z(OE%L0Gvd)D z!&uVRG`=jzNfR4Zm!cu#J`Qq^E;*SQpDV^}6mN=86r;D6~{WqaguR8oUp(AT4|4r!ro6u>mmHs!O`)@+0 zH-r3dLigW<&SRqb--PbJ3Eh7aI_-kP|9=y@ai#O0uk*&zSxcA6k4cY_|6WC} z3NbhSzZqUCnNzqK&qU8DB-!Q^0^v_8Z0${y8C$rM?5@&^eoZL)_VzA9(O0f^6N;WT z+(RgO*KRMN=)v?-LeX=JKKlrXyRKj=ikjg=)PY;96|T=R_`hH|?jxUOZ6l6 zy_uG^1|bvNT4n7KUO~{s&nyT9L-8!j5PUB`;8ly+kRsrsm_34&oV8i?6JhOaOJ+h@*fTuzyNdp z9q^MkEFJMU+Ko3XPZ*{>959dpPWgAhkT)&Y4ND%56vU7gJ`#yMyC*aiSGd?zra9PD zTVU}V%hQIfo~7}RPi-P4q(W3%e_sJAgcUDBVXGVA&|J$@yw~^m+t?xREwK1Xr{LBH zmPSzgwq=3glu*F9m6jgRV3DOMNr64ep!AC{Sh2|RWY|F^wYo!;ES_%}B^iEGQm|55 zEX1DtkH96RRKsNSBB*D2EK}%m^vR)G*M?mK~9YhcF=QyjRma;lDiD1A^HIE z3nQ&|x($+cXhF+OSqaUB6xd*4@Z&p{m4-F~ml%SOFIJn6wod3$%g=K6ose_!WCZvv zv$Qny7C?xy@atuZmsy$_dJ24Oz%GWN0)r>aE3%B#CY-EII2A1I)Cn6wfN7H#*uXN} z@Rllz+;gY$iBzGHTCi$$gN#qmVLYMa60}U8%!Dz^Ev520TG1yBA1eugioSu>af868 zb^Kaj@Pr#ySjHGM3BT7SEL~|asS`GWi1*R1E~!$>8}zH!l2s26R6n|U^-JcivYe}C zkiJ$r4i)zvtJgiDJX)_{orE7+9yh2GHiFW1hU&1lz#3<0qRldAoh4hHrHdg&n{erR zbb=b}nj0*!h9|YD-`;>uU6q=@N&37t_3)2Sp{msAUC5UcMr%`#+i1!6NPT&u<#WRf zRYLimetWcH?Q!Rk?V)n9yo+iqHvCh|dxq6Q!Ng)4E50ONW3kw$=`pZdAC-O}ZGz~n zmfpgrZj_uxZBFvmen?5~CQFe_K6$d$VuGsM`@^6-Eg(wpUuK=0{JWWQv_ci_8jc0Pt0H-&TUMLH)zO)RI8}3rRVxTlfKTT>jD1-|61z8tvx47Si zC!e>G+wAf~4|v3x4YeK-U^OP%Ej(WY8qyItzT)Mkjj zXi?4|>&x29Y%Q##`xDLt=KHVIec$?(UFs9aFS$e}R||r~o3|L0KG&f-WEeIC`zA-3 z(%P64+n7vnVV@brk2g}Wu1qFcTgO^Dh*QJxg8DDVts4DSjWKxLlO~;ElVlOS)mCER|%R*%Iy|E zFTak$Z?Lu7?#9rd(h_Cprm!gx{VY^RSXOCSY7nyUWeGBI7$oE%^C-FFZfLOWWXp$@ zFh)p^VLbit6v}HsyN)Dx`iVc3q#JG)qmZB4Ey@r$e22M+SJ>DJp z1YTd>B?2Iw_jQC#RhBIjx!E$ttoj-5(!HeK!r z7k;zEd!&}`;xz0#ZNgo@TQWQn(#4+^f8Z4FqBiyRKh#2CZ zlMX^xB&*oG$?u&G@`K%U9X?Lapnun*^C{O>@9iCA|2;IT@WoCgF1e%03UpoOr8|~s zhR8iiPo{cmCNOCKirfPm?^+`Lgp@njm#=0PKqo_*ke>7}NS|EYSH?`ethN-o5GPC= z?`cFqJx~Q0e_oI-cYj1J9%!)j<>GEh+ zjIiIKj zujdHd2Y%p*fIe`+9`$AQ*?ZWnFwqI>ic6hfnC?$IpvtnnVM!e?tCwUb6B?Bo?RPM# zy7hqJJAqHuL6z>`y|Gs5WNF<97i(BQk+1I℧2C=~rB#Q9hg3^xTnHN{0!_Ibe~ zAFI*ewO8q;JWKtW)H!%*L1sjA)>tJ53H!>pU- zOQ@-fCmX=0b*vo>RyFWt=vddf$Z%QU6JSB(uCK6M;2J-xB-Qkm&+A$H;pYxZJ-e=4 zqZINQSl>0&5PndV(vpiWm$G(!NGYmzb;+h`*D&bV(7MeKFBC`C^CFaP6sOe|TL+2} zpoHpSh3L!AiR4QK_(?D_cy%tNBT&4~;MF}<2VWe$o?&_QRt&qh)8=Kv*Q-(1MSl58 zrNlvLw8Ccb86A}JOO-)M7%tMaC3uWVvzT4b+PnOT_1r)%_}K2O`oVnxid~ za0$@nxRz#ZB1;1p0)N-W695~d<39D`XNL0>KZtkE9w9Ab$eO|_5FAG^?mB4 z(^)QYwT~A1ceK{^g1OaZ`;`QBv_^YL?~`hTL+O+AI>zXEko8>C?=j4cB_&<0dwlQ= z2hksUlXcDBc~QD~52*8A&$60*B#fEddCU6Ei)^S@?iE*FqBZwK8uqCt(zEFA9usL% zeRLunDRSH`P24JVrjNnp7Ry3POwU{Ykqp;JOY#XO?dP=5{wi>3KffmSb4?y<8`bwK zNOau3273luyLpy?-C79cs`E!H1$jv**Sci$5bLn&hFBG%9J3$B=384BVuT-1=q`pf z0t1Jf4%L<&@`mG5Xc)=TrNEj5QD0ZDsm>?v>^&_Y&>CaLx$7)L)OorX2J56;w%*cJ zow5(jrT~Spf_~zcLI?0fPO~PdQ#XO8f1HdqOw^{H_KLNYI&~MrY;D3m)2*{S z6M7DVb$J_!HD+6;A_tqEjcsm^7YVm^%q5RA(vP)lI^YqTd_v@S#9;Ul{;tfN8_lv# zl@D`-4`6ZKgWY^R0dO$fazGuKd~`q?ndr*QMnwIeo_@`G(QsW*n<~1Ff0%m0bn$jT zK*O)eHmm!i9li%WG~<2n(VFqX-`$!id1nXSFgX*W;p2BifFXQ=%>Y;(a zLtMjxBI`KWu#Gg0GV(Wp*2{4~*(Gr4IJoVg5aEh>a1pNw+*yw62FF!-q;2rhd)EEx z5*opX73gHjwW)tyVNKSirq1WKHuc4o)--MExK&m^$a)_=jn^TiV${2BgP-2Vs6iB- zhB}xf)exply>}H>$|JR>8yfmBJNuUoTIlMa^il5ihdhj}4Uyv!ZYTwRSBx!rt+lZv z_u~-U*!p-vps_uENNsE>hyL#v+eBAgG{!dbklNT@af!~2t<`#KLQ8r1A!=-`^`haI zxQ2^ZPH~I7WN(G_Xb9c#EjdtOJsBc@f>nB$3D)Fq6S{yt^84G`Ox}q_KgNlFOPNZ|@0NbMFCbtOZh@*7zq5vR3n zxddW%HlB+dw_UhBeTM6CH2OSu)?p7r>Q2gggdshJzq<_y#>H3MC>a`G;VsD{I1aa_ z0#6*Yrrw9u*7Ve24{OqunhsrcbbrDFLgg*q*8Qr(lEZ2%TI7`we$Vi*S3PqtD>KmoziT-zZ$#_c0mk`(k>s?kU9W^{ca89kXv%-~y=)}FEv*jE0iq3NSyT^)- zs2pY$B1dV+A$u$K{7cNy6im~L;-Rp#qMxDm5zNZ%N9m*ng)4N@_!YZ$_n-`Mn# zKByZbaOnsYegrxnsc5WCKDhCweuiXi@{%q`D*`0X^qvM<#gd&=Hpn&<~#sAd)=72%g2?sSyOeu%&s)N8eTSmgUJD0xzQ#ztPRt69J82$Px9R z@az$fK|xnuW(2xFxvOGvRYhY2YmTUm;C+|m9wF9OM;;zxIk|$jvz(6(vA)GBJ#5IB zQiHit7Z3}v&SKFI8!>#mT{%2Pj4zI;M~wHeSoMe@>WtZj$WhvNRhDh;Lp*l-Ubgo_ zbx+|yWiQ)iL;a(Ac2Y;-Ds}=seQXc>VuhdB+rcp13v)Z5?9*KtHR$Bib=8snLwnUR2hs=F zI!LWy#sFKgY(4-tM_OX4g+34`8Z)*%~SK8`H@4~EX+v9LD&(?U!XlGqmFxXZ@TF;nSb1>ESbL21xxZtcI z;TM)j($`)>?x@Z_wRi*WW$b=SkX<>%7A}3q7^iZPk?pjFN@p13=n!P=8fL32*%;&5 zSCBC{#}+UB${5+xka07|79%}|tKeAH{-MYSsBaIK@UR$RJV_XPO2qGe#d$_U3Qu1#qD=7&~SnvOE0Jz@M{wF!s}9kbV51zaM8m&)5^* zK=$_ylY$|>3+iJy^nsTT1^dCG zQP?vg7`NHm$UXk^wNR-gW7Hafj1Fa$b){6sXp@f&irl&A1=|zw;am9crw`X@$ZOS` zC3|-gvd^z{Ho)(25&@)NU|+Va5sVpwB8*~b8j!3DevI;iy(dxaQyF(4Q4?+R*^Ke| zOjOXNTf=L^gGx+>$ACzM-kOWadW^Hxk=8IqC<+XXpc;}OA z5mGzG*z^uEK5pCJ)y1D=?8~I7ZgdZJb*Fxe-46{OE*^`k&FhiJ*bQDoCB{v)1xsTY zBV;(Hqb>akW0YniV^z;Vjd;enj9vd#WN&!M7K9hSseDu3L`HcW_K0`TjJ7$*sH${^V&|aHe@!Kf>DWUm7~|+@WK6#` z!msGuNPnp6J*WorShv~FKMuy97woMJk{&R|gqN|FQEyq@EKM21dl51g%|A!lDA z{(kS^>yOJVIOl!hxR1|RfWvBYa#KBp^Zz1)&b@Psd%?{sH)_b8IC~dq6$GdY;qz?G zha=R85W*^7Iwx0k1I&UoS(mY=wuAiu#mUl1MD zUua8{-{G8pNJsIHx)CU^=A4$Kg<34K^_D+74mq=IIdEx_t&jW_|2cvfab z+55Y5eR-c??T|})=Zs|-$%JrD2=TOg95*tc?@C+3l0{YCFmr^>8#XLO{;nchS2>=h zY!8`W3!3q}7i#}q5=3kz)OtcKA=KxDT1Tk8gj!Fi?+E22)EPn@B$SO%hY9s7q0SQO zv2T$&K&V=TdWTT;33Y@}%?P!eQ08xEAo(pJGYInpp?VPNCZV1u)K`QWPN;o^nnb9z zgnE@we-dgTq4p4JC85?3>SIEc5o$Z3juGkrp&W!NBh*TyW)xl^BoO9RLfHxRC!zi( zl-Dt&ej`*Mq0SI0f>5P|YDuWi2$f2x8-(gis4ofCn@~RyY6zizA=D^BRT63{p?;o0 z$k~MagiuQe^&X+t5b9GxZ6eeqLhU5f3POEDsN;nCkx&l^b(v7R2z7%{w+Zz(p&rA_ zF@-+gA@vX8g%YZYP>sH;IpeXy4++_tFi#Px9ieU!>PbRfBUC>^-62#Sp*9d|ETJwC z>J>trCe&O)Eh7{V>H|WpBh+<5Z6(xBLhT{cUP8?{M#vIE{z9lCLRApzT|(U^)cb^b zK&bnK^7|gC&4j8)sLO7usH=q9NT|OE^(CP;5o$l7{vgx|LTx0}c|si`l#@{36Y38_ohMYa z<4Ao>r~ss96kZ`@L&E%yP%Q|xg-|JkDkoGYLTx8hFG4LP)L=p#CDcel-6hl%LhUBh z8-!X-sCNkUIiXe)%0{Tq2(_P3UlkJ4Lde5}`jt>W5bA3}l@sb5p{^5Z2chl~>IXu3 zpFrvhLWK~jm{8G#svuN6Qj_L+O&pUqfqr%McgQ&INP+7sY{TTI&;!-A7fM}W-%4Am zUuTku4g;AdVCyVPLwGRL-UFvEus1EgB7EKZe|Gsmf9l>iuj+xxDB>UX(MERfB_uE&VsTJ zY%%g>Ucg120(wd3bkTlMp{;G>%z~TiY^~+mWlUTH1b%Mo$|Svb#Nh|ND^NMbVUjoa zZLs-b)QP_*K=D3XLqW>w5O~a%3Zu9IGH@|)`^aD0x8SNCupD}Pi*dRZ5k*7tf02B)ObLRVW`#=6=~tE~ZR zs-Cc?{TrcBz6rvU6%b1)qPt^d6kpAPxj$7# z$-i>2DgmrR1%kc3&DIc%?P_>I`S4oaFzx3`U+KDnEwtHHMG=x6#+4}D>+!d2wP4kd z>OQb%tIc1Ef`A>iOu6An2)t*bbq|E^i?7kLVqp2_7`WF5<8E6|LGU^!>G>uP;GVGK z3tLO6JA->lgqyL=_5_-)3Z#=7B;(s_S+L=3Wh31Ar!u`LfE4|WBCXzTGh;-o0ve|V zT3lkAjxSVEjCBGA^gMMv zdslh8luew9C-n*DaW&>KHRia(wjmHdpoU*<@v#NYuq(*s`F8FH~Nu^q1e_;BN@vE*&(4taqn) zf&cYtwPEi!=&)YZEoO#ZF})7jrpaG&@XrPCD7(wD0*+3p19N{w+%3AepXuSE_%F&= zIPN6@*ClkCg!3jH{hrZ7Bkfjn+dBmOZdCfo{y#9k?FZ72>b6UlYQo|&TTj90YY+x& zG1*?mydOFl>iu>Thma|w7o-1NMgEBk1eMp?qBA4IAzixTvxNaaFi%)~<60n;t;YHA zvlN=l4g^2Y_Xpw<-45)Q1IL?pzQ@_sG%oj4CO5(aL676ML}{{G+Rz!0pd^r0GVjV_$&48pBCX=^C|#NmDr;PxJ>G(h2W zpAdYXF4YHSoWk}mQv-jm3w&}m0>clsrcyQ7cN$0X#~}I_Y$#gcn>!Kr?s4A;d?NtI zKzxeFv$gK(LQ-$D_B8ryBZG_+AP4 z=Uk%|$CVNAiG}t*-w48X)&uYRaPV_yY;B~u4E#+2e8vT={qD1*X&67xuXAOB5wV5c0*-?x3fhT-XJui5J<>#8-0>S8@>%B?zcx4zk-!@^X!cMO?%s zr{UH-M_U%5BR+9Q@}xFYu$Y`u*>?;aP?7-tWH>}xi&d{-mgpA^IG%BbDo{(=w8ti9RHPMb5Xo(bZvnOO@82c+OUVf^^-KdL; z?zu0l{tdTnE;6)p0-8(DMqK1oRs6Irn$mP9&IQ+|J2JB2XEu)dz}h?71~e`Uz%{Qw z(MMM&zl#kh6NaV%X{1UOQC1aP7go>4KAOslND_*O+G7ufsAU16aA{RQO(_1$9w;TK zi)gJ|L{9C>EZBV4R!`37z_|kOMQ?j!ShypgIz;_e+Z!&XJA84UL?!z`eP9yJe)5m4 zk^Bw^#s?$aN^y6(qLiBrVA0iJZx+$cQ-jaZ1;=r_FYLUJ^Vhu`e3t-Doo#lM!w0gT z4UL9?{-Hi#Jc^=!rAFVbi_YyPQm*_NGM;o~3eb;Npr#Qu6n^^09*X;jDqUD~0clq` zE!$1Fx}Q$H{KD(2v}xZf_x_>*BUo<0_pz&f6X$O<>?-)!^7q(xlP4 zkcAJ2Y*iB>*D%QUbs!rT`P#$q&0nf3l?K2KOXuF`R;hpgO?3L`uPO61clxKSIJp@+ zyq<~9&6B29x>jh|9`J8O5)%}^QrV2fqPIvH;?(@cFCKB|$r<((_~X04+7R`9U=6+< z6%2tP_O3-QRR+TB+V)0rz!@_9iep_Z%E^#@&%o9hcCs8p!{X*=0$p2L$qI&dfW5Vx zsKGE|ULhi;09OMLte=uKH_+Zx?xV??#f$Hbe_0f~_VXJlP!MEqf?Jzz;TJuL{?`#? zZ!S;PKupj;iaWu?L(XfpOnskje9&PEIA(hD_s6bf!2qJFg$<@xXkfb~Zn~Bal9)pt+ z9&LS(p?AewPR?$XQ5LQdx{jT&Kz-0YdEc&+FQz3Q zVULqHor7D?+PgzeoIQc92dBS>;bwkIdm~sEXHOG^UdPH_>lT`#jA>gTCE*i37U_O3ud!doNA12xD$x*#ceA+fyWOdKj+ zfVyk6H%7zSn(WaWv6MkqisiNESjR$*(T+vih^U&n=d^JlA#gmyUPCT8Px{lduprrP zC`z=~!AH0WsxS%3KJU>tsJ8Ae3uz7y5;6ZAF5PTFy3J;L4E&nxq4k-9Y_FVmxikv4 zGs)gc{*vQ-F5oOoM$frLUCYlrk*N8gjGncmPAxRmj!$;+3U+CS{bB6wTh(D>syzso z)Kt~9>QuA!4}i6!ye_~j38SOMo#-G&YdEs4 zJyA~M2+1Ns*LL<;Iq`yeFf{6be0(9K6&EI-LBTWW9=$!G1I~=zP4^IIpbpaT%OOb| zX)zaSfhbgybh}Z0TO-t43`)AddKN0oQ|Gj2?aZ*(mk(cHohmL9hx!8=pwbK49#y*| zj_6J8XpXUProOtk{*}2rb_U=TAcPL0kUyS3^x))uXv+g=*0j zKZ%3TFtt=enN&F!J#1yv+oACsZ#l;+QsW)%iamX4H>~OsHRvK;(1D9WV>sv`4!U0r zTF@Qw_NwuAx$&qOq6QSzDFZ@z57gaVuDgLfQFni;fqtVvY$PFGDtZeB1r0ZaK1mOj zNDU!lpv#Tc?q%;M)raV3JiJt$OIqc(J`)nO$^#MizEoO70bAptM$$AwjqMaw-oa~(qUzK*cA&kk+@ze@ z*Ybg=@J6t8um?^gEY8IVRTrR^_2M8LHJ&JE!+z&%kGefQ*d7gUWqZ`^aRQeqw=4Is zr>S{ijd|Cf$grewFe~5H*P3NxwEcowkdbaE+Uq0BRTZLP|0g;2X!&Dap)>htlK#Cu zs3UDqgW)2&P^;2~VXhJ9J6<=rz@u*0@^H-QT;Nf+15BV&&$`_oilfe7yjH&pwK|(` zkCkq#1-a=4p|$#u)k<#50|^WfX|pvTag)2FRt~c_lhZD%{_1F)67Gk97jW}|`i}80p#R>h2H2$s zKudpl43=KOOaEsKmVQN@`O-r(`;4=j@u0xT@vbgfG|t{eu6{)wLCBPoA-PpYi{3Pz z#*Iqu787vJ606DGM4daMJ^JIXqv|xJikEr_0+dX|Zq`i$@q`)z1sH(FrIg)yG6u>o zXflq}$(S70w9nW{<425{G$E?vnDOKDN99Z$G3JE{aBDOg=u!m~7m59Q+3SF50!AK- zHP{REuz^h6aK}TD?8J*WrP!v)y_Mybvo15=jXj%~gxr9e2u{JMiTtBX;wIm#6c$%n zOukAMS5)ikUKTd({(JJ(7+JEYTk`%DPx~R$<)bg-bh)vTFAzFR!zd|Aler<~WXSa` z?)mT?T-@LLb=_Lf;}tZaE+WXLSL_YsjtoRF#dNql(>@ALym-|=^qoo4WApq*ypT6) z($M^Z5u@@aEG=9H<7U~1$wiZ3-%fjQ@coGrfB2Js6K4?KCvxvOq+6KM6p1iy>?O|@ z<#>4}w%%(RIc5rS?AMXw8z#pQjT{ZwDWLa7Ic6$yP=AMNrj7ac6}GbR6P`c8wxVW3 zZYc0k;vAQA&3Aa8)N=aDr!~;0^r7E- z2V20Wg0*sW{OfMz(oB>Z)sP5d=hX9s(bXM6vRt8Vst5Y8*OuDb%1IS)@@7?^=i^B2YH|dy1zd3%gb^6 zS;(R1iO@6BnZRw~!5a}iaIrHs+#C(;Yz?fdOVo!K^6MMm#tOTiyo(p`l~{mF_EvCd zB|5I{8tg9=Y-;0Z9n{8exowQ@B`sWq?&f!1!fmkxx<}ut*ck}vJL-o+`UI3`=;5n@ z@=Z-yl@-MD8Uh|rqkFY@l%yBDxdsE1NXS`_Z5a-WKf^(r`hl6ns2U1c+~H;@tXhk6 zl6vHK&B1~&*t!8T2a`XkU_5R&V5d-5f*f5N{!#t@-equ)G+^ zJA5@r>a7$d%prQ(JZo@y4<0BJa^z{S6h8eJ2Ozkrd<+cSE+`cLnz;jadkId!V_W%sQ5St z@T%uilyNf{#v1B*!^p!|edW%YqB3!fOIVLM*#?hxUMaRG$&)zlcoBET4V1iWtNlrN zj0R~G7kUK#6~=+4U)VdzA0S9g9JWNP{?DLOiOOiu3VLqCMdXzlz~u@c)dGs@(t=n( zt?f9+JIAH{MJ(ac5tKITdfh;%`nhg6M3&ftbVKI12NA#|AmR;N03nH`Z{fR zRJ9J?pKdRZZb9izdq~iFOv2tp=d)@fEdc2L1!5CL;59!|DBTCxe#GexM9Aew7`_)h z0Xy^j9a;z3sDZ6}StKG@#Xu@%Jn(InoMY%DhV90<@pT8=j-N%!aGjq1&KU%_VV;Sn z5h#~zEDB&Rb1;4ioA%MJd$Esh=3t+y!Lp8_`40KR9t!C#!|OxMqiAg#6>P!U))Q`~ z{DH%xbLH(rr+kj1;|`;zs57_W&T!m*dpqg0F6Jp+%*hAr@v;wInj9ZAQ(Cv#)vwD<9878 z=NIBhr}E3#T&3;8!=O_-hDU8#NrIMBogNm8`}xm8z!6+W7|Ah*3z$XIQRH){?RX^l zd%JJZQCxS;*C6IPnY$T+f0^aFPEUA4>u+(;e3v6H6ObWb7q(r*36yqCCp?G{aSWw> zM}xgkgN?c>L9%CUl6xfNoxJrLX*@rmWAedURs6j?r=j zN4p}Tx!VfT?}dlL@%!O;&clvD;w25{c`pAMw~nbhn|BV~SZLvMC`%a0{e9h<00xH#Tpx#Y?M)<91?FZhPn;@auP%X~sz=CO;oY1>&TL@@5m zYaV)`3b$Xvnc^f4Hr^8~9-{g+tOHR`q3lF0(ijC+@J^!$H&Y&Q&DHzpA;I4-Bk%_Z zj6<_0EV_9wwC-J3>}_z>i>geejpYqNlp(MRW8v)DIDAn5y!pDlDJ%*IuMWjC z8~Q=yQw>>P!TnTs0fJKgp;eIYxRpZV%_$CCBT3*zv{n~!VkZtME%(^Npm=4&y71s8 z4p^;7BJo68bHZRJ(xf{~L8l(Bpa!2d4B|azBrkTjx>!_GQz-qWVRiWP8tzNxt4quU z)35eadis;7=|&~0X&DE5M-7H*dJ?Ztsf3y!Sp5& zU1V{;-~c7RW82dJM+&(fBl}(_4puxXXe5JUN~f8f-t)EvPMD9ST6n6GFssqZ^+2Yufc z9JAPsc`N2xIPAHALpK7~gqLj$GaIf106 zhq{3`XQP_wD~aFaRvx?rm9=!#Z)(%>k-mp1TUnq`n6 z=oRe9Bz8qdXf#(kLN|8X8STHvYB?IoeK~9|7p$wlHiYBTszRX32bcP)R^ou#L$|1I ztSE%0MWL^uMR{Fk>%xtXIo$Kco&~lLdC5&SW4wLL5d&VK4!R;N40iKzV@;Tb)B3lc z5b0V_{*sIPITIJ3-Os5Ehhv$J2uOb;vK~|h;St>}x{`jzB>niN%h^!uY9Wrg@)eGX zd#*&cBI=sGfq_u#V4x3OH;~TjLgV2>qHhHn=OS4U6y}JP{qbHT@veUOml*FpnE8>T zO;H_(S*}^7w$>U|%vu#7I(5vf>u4so<3MR{poPU)^}T`42q@2vstt=~U~`SwhUS{A z0ZvqaX)~dgNi*SLJ`|iyoFn%tM_I`;FY?P(tfe*`;^!OXDHKHRas}7s6{bx#1q2y5xmb_WAq7^Vv;{gJ0q`P^Hq zOK_Fb>qkSZkx@`O<$4YIb6%Y-ygCRK1iRZhTR_&T=;m;vIqK&#O-(+gm~Q1$!?m<< zB+BPG+!+yWh11ajjCC3%L7BfZNYbGF!1Yq*()Q(6j#+p?F~^KHT;n!tK`L0;DMYI3 zebbEJd~^oN)o!aB?y=jf;oMMk2$uGdMl#LpcI5o;FljBW1T1Wx1 zMF89~Y5|Lmp{8b>kFE;=iMVPyNP{;(jW=!#cBfb~y5dC)biN3B&+M2i&()y3sYbz0 z`8s}(ol3P+1YioUif+d?LrOGI+tg6Fx>^X4FE;Xr&+0h+@DL0IwTqxdV^R0%;~OR8 z2gR^cST&%RbwJ;c>-@@w$q*RV8T%`p6VbM$cr)KXJmX7_KwL7!-^IB~ZNlJl6?b#e zD-q+{J6g+~IBtd-7q_qaz~16U-ca^pV{f{UEp+Kpmi zdO&l$9P=7#^^h8TzX!P64@n;b(wXvxTgqNH8H@<;P0H&4JsmgPE4kz)Ie5AodNJzm zH{RyA0AX1-jROk!&BFnWtLN+mW9l}JWDY3xH`YJ!>QfKwAL*4hnnCx?*wtoQ!|*Yq z`i*_)#wNM?)WadZBhZ?{ditQqZs>z@IU?R^awDRqTf*2rjqxq2#~TMj*3%f3;1wrC z6sFz%34>2G`~BvMO6cav@a_(iypRLqeI_?BZfmxH>>iGEoHwfA@Jz7|9J&&`o7K~i zBJbjGc!9|cM=iI!TVpenXE}l-yvpP$;upG@wBtVLh2x}?W8xhqHzsappy9S}90T=x zJ3=6>5B3YZ(&PzTt_w_uz32Mkuow0_Yo=f@4RAG+qSUJVKmF)fDg}_=MWxn)UOCu_ z6n)Z-oDR=B>cg60js0N82RKXX$kEdUbnMPOSdxX4P!;Xfz-`pP)Yad34x|0C9B#A# zM~4n4Kcms9ZP;9Dbe20z1OlZ_Wz(gDt(-L|P#}PN;5A}%K;13oeD-BFtRpwAfJl-~? zfIUROTKSG)ayJdk6ABCl#F^4>EFNyfx+UI04wTW4kf;c@J?&u2Fa5jHxeSdzjU#Mz zp#Ml$L^L+b!LKDRr@&&2T=a*hKRRsd4aOxg%pc)IZ5#y)> z>373gLF+<146#Ea{g)Kd(-$=v=`c&U9Y<7J!O^hSVE-G1oGX98;+w_wp#KZkqv?}5 z!j$V0(*@3LdX1scCvE#NqtUm8{>kFnpg)OtuR?iA6AZ0>chr&n|5Ue(-=8cNa>HQM z@s^y)5gw-q&jAj@(x5C+qfl?UWiooxqa5lmhhmkp3gt0-1Qj0t9zV&$qdDA&~}w8473jAKUQznI^Q0%^LVD`3A20yF`x zu%S(AKxrPv#0|;Mnq>n#CO#X7So(I7yA^TKr8iXH(j)?oFUOfq7B8T?PylX*w;)}k zDXiJt1i#Pgb_q}E7SmO)7_{QvaAF4fn^$-VF9{`(Dv%OziyYkoc{yK4{E2$F)Fak< z6+Pl79QPvu_kE+2sYVH5*6CueRj}prXpdy$1Feuwn?C443j5l& zGT(%+#ir>k?+8`KvS^hJSSH)!rRQG{&%ws*E6V!xTy!bDG_v-1gse~M$lAjtYtKi^ z%Fi*56lKM-T(Z(OL{*c2OO><@=qh{qaq8yXEe16gyWD)$IhUK?psB@&ycVvd2689< z#LscTEbKgXhdI(C_?HZJh!h0MnVm&1nT+f}-Jv^bzq+3SyPZ8AWDcBINTHJFuD{0!NNf89q^@D&@cCDoz95*!2?fwU5bjmW!# zxOiFz0aKgCLHttmZsB*;lGeM+#%2YT9*XL+%+Xxx$pD`g0qJ0mfYCHYlAqK7cF_P* zPd5V`E%7uJm2j#ENZmv_G;IZo&PRK*>G5O@>I8k%ua{%JKW3;KL{vOIL+c$5Ck{G7 z&kg-8vpH&qm-pUVdGJ zI7@>_SG!MbKsAb&mTD#KpT9iDK+?qjWXgU-r%UoHQ?<{jwZO;PvN_% z;Bl%vM0!HO6Q;AB2{%*D#4EbYrBLJFxdn~?Wd=4y1%@4XFupfWE1=p{AFl?Z<9Ov( zM{9B{id1~P3XDuimd%W<3t2Ud__U?V{_!A^9{y@IK3yVfu?<~69+4vWr&RbDD~^^< z=z@Kx2BRBQWp7@s0W-Hdn#%G$7L?(`-5za)%FKk~PO*G0`;RX89W^-Z2U~Wa*|%o6 zax46cg9>eb^r;1M^LuI&ZhDWIu+lmdX4qawaM3P&{*q3M2Xegr0-iD<$?}ek!n6@` zKMi^x4LY5ab(n`5cz1a$?p1ypQv=E;JMacHFJrb)25}O!>5Q4i04VF%(woK4uW1UJ zsVT@+jd*!GNB%-U_LLrGE@~b^UvZI(HPD+h(9~nD*@qs}!lBCr=sVl-)aII>nl**7 z-mxsKmM>^f&uUQV@eRDuRejmf=0Pl`4!F}QpwcoQx^ zaiX*?jS_zFZeEX0wdMA_gf^-YXeG)HJ32@yy5MGAaJr@+egu1VA;-o0xE_+@koi2m zV?dcId2>7=sV_xWM5C~}q_4A`3h5tM`z@MBjV;`h1{;)vo#g8e@|X8n80;VB3Zy@$ z&_W=+<-QOFlgF=xDA+ni8wK0Puqe2h1Ao*+!7GvJaTN6!DX$%S91M%1RrrkX9*5tq zDQgAPBTwb?|Kt+$D3W%Te@-|W%aISjbj_X#mrwH^0*Hg_C1iZf z4vcChxcho6k;>hN;lWH{W0m^TpVl{T%p%AqAFwXiMO^@{V~vqIDu{x^$BRy<(c!np zM;iF)4RWBd`;WM2Jek8yP{Y+d?RWvd%0O$O>KLQdaC9{=zpQyIqz7Y=`yt1~PhfcJ z0C!bd6j>axYR~_^ZZYqvi=hjy_Fr)FT*gcIUR?qzp|{|uztsiCZ)i~`{$`xAYJj)B^|bSwF8VQtqb~7kevlsF^p{&a2E8Jj8F;NPy&Px%w1?or zL~p_I#XJV4u1@i7zv##CO$}#;(2i{Qx`flWXE|VB0T7p<3*}xKm>wFKeU}|mSD_Igqe^LLL zbKNmZp2B6E#AU?1L4d0``SN&;jAOWrxcr>cvyyC1(<766r6?AN%Ii7U2O`*(D#tVO zY7N**MGkTb&2bA`;RMhBotPiznw=nfVM{-aV&QAm#lI?xmXW_KLt1fEaKhQZemzixfg^a(^wy4VJ1h%+)OI({G+b505PnuP= zsAVUenJPJ#{e@1lA4lvXAY#39@D{QjPIpfn8eyHdi#V@woS6a+oz9hh)3O=eJ(cjY zH#(BNO)m^XAQOjI#{=i=XJ^;@3hwRaW<0{ zvoaQ_%lO{MIY@e27w;_rZ?P|`gxtEpbI?d<;)ksWtH{^cUG6SH^v~BiK-OU8fU5g* zTVSv47Lq7yvFav?70a92BCcPpa8{2eYAvtA6i90 z)+jXUM&x&KhcS{c__l4h7i|62;eG}BW`HwReue}0Rs*{lvllLgsW6|`#iW)K5$ueY zU*(uH)R@$0jAvSf!H|zyu>&EvGNwYGs*6qs*5^Wi5n{WCSXOBHymJSvXQQa@Is zZ_q`jF~qz&h<=`-noCefY^FYWd zZ^Z&LJj+AjvqgBN`k0PSO9yH22War=YSwd6&PI5choa6GQI$32tevfzK)}w{20D9` z=W3we)Ig&?vf$-L=;d}Z=$#@o)h(hX;CWD7|1Hq~ZqoqLY3QL3;_89%RowBt%24eJ zY6v`7Z?6wCn>gFcRt?}~1+dpx3{laJXSKPOA>D?{O|j+CXV8ECK>pbdK6&Xnc{G~7 z7jfd}YauYFrOWZue%^;VT|~p_TNj9G7H^=wMt+$A z33IF|MBGeVB%9U7$v?W%6N=&xZZm`XRD?rskSlN0fUH-6&>7E()=m@N^`|oZB7$Ia zK3qPn0Xd}tp|%q|Fg_OAB;XM)ABb*?x~lFi=!zazDSZ$Z4wwFl3xc+ZPQ2OgO?4$y z@qr4MF1ys~;tYW?W@j*dj)ejzh``iz)_fk1-^MVbX^u+55V17_7QB8dZ))!z%FBYc zld*f}GSDF+C|%~K(x#7(_kyAn1RbaW?XL!M*!}PWk7O!C4WNCxb0{9WF?Mx|r=x25sB}#S+ASG4(024;6QXnxg|;A7_Vl$L zN9WqBk=v+|(Wgw3$8yloBB*PCjf9!6-HaCYp$pZZ!_=UzPS;F+AAf4Esqs|Rvl%LW-NTJ2__j5K z%VWj&Yr0}ZYO8PcMf9III)0nPjgD(V6Y!fJdT`%A9PUg%XB)YiFRMPTYvjACU;M0d zDt^yH5ALom96i^T(%+dZ8#!E@0H@Sl*|=x{rXe07ax=ovRGS{2>5z?=V%<9qgLnx8 zgc9(K^CbMnfC{p&E+pNxnV4y8CG0TF<(O{@m^%hLr{EU_RG71LF4>{5*J+Zi9P_e(NzV$h{^Z(9z^@CafY0dy)2?)BC{7Uq4Xo|) z9P?=G+NIy(jWcq-iF8yGl)i^k83XxAoXYqRhNhk9IzW?Q&en1Vj)}*Y-I!F^?A@&s zp~rAMNtCL_Owz@qa*iH>3K+>T@es2cvu&YsEZ*f*Ntdf2N$*3}SPU=FLa7g&;Au-8 zM&UeT9R+S6FMAC39$yu{)GH95gH+1Eqtw(51cEWEbvO(jjl!=|7l}uv-3n34pibt^ z7touZKYpMzBSKzm8kEzk|2(=3xU%{spLQh7W_~|~}i8t-4 zOrf8~FHJ+zB%F8CQ_pL9xPsVPuywLW5bNuw1hG`r<>RqSB;fsR;tg9v^i1p$Y>L|h zgV;|eILG5{UF3>mIIbeQ775AXoHPkN%0Ld$Uk&lgBClamJfvL{N1FUaX37j>{;#8Z({_0O&1RDVe2%Md@TVZ2=~TzL~Ygs8o<`& zIQF8k20^<8&R3b|vl(QR$dqRL)zX(O_tP7W^3rC0Ygm-W# zpTglL32+!0;I*ro37y%cmGQd3V|0P3oNq66Cd%tM@CO1gK9~2Rv|1N#r7j!|x5|q! zAUahW*3Ng*+Hf5*DRUF?LI^qf`JFE8QC(PihB$S(Gf95HrNkpI?#974?OwuH3G^BV zk5`M0L&IU8N}K@Sn?biry?60s?!EUsORp%>vx65_I`LzaYq065H`tWTpGblU z$Ww*jo$xsh7SK}7PVa9Hc0ZeJT7ynvgg={tAqsB#^5=Z;t*>_y>%sNSW*_<`K)JwQ zy%3Ry?{~9}AG)X-yapFli-1Bd5g_T?EninvMMBiYL>$A8;9)5LwfMf@A`Rkvf3}J? z*Wcyi=_Ylv51fs0lY=6c3dj((4i`*Z(0&u_eu#7H-5Thf8fd!K)p;GRb>W3f zqKE4uH2uaJUW1Q<^uvh;SbZze2daKS(N`Zt(XVRo?F=6;8r@otGrT>K?IyHr+61nmJK?4eay3(lr~sGVaU%Q-T-=C@ z4t*F*mH>lGYR}KIHL$TLonj_))b-19ji52jPP=IUgE2b#Y><`n@v5@r5XpIR!CK^ZO$+)4x>}H$FpU{8vzivebQmz?Z0s z6a`CYOEckeXK%vC%2;efaWQr`!1EK#A<%uh(;x2%QIUsvmM{QEVYiF|ZjLT);11_B zT%({s_}H(z?)VlSzF9ZX90QA%V$;2gi)|fY#m(4>Zv7y`-RH(_NFH|Rh6Ax4 z(ASipZ$xqRq7?VE!=ntQj9?Dn&I!vqY)@ErM_}5e%fL^hll2~QbYbime1JQq5~d`X>djcRL$E;1Ae1 zb%WW!hzR(sa|K?xUsO@Q4twM=6mJiDo^=Td_Au%$-=SCS%z!dQAo@An&E>cVRXPg` zj9hus8^-Lc&#w2%k85z-p{v0&G*TLzbWlf42d=)y(Fu)b@MA>yu{Qj+GrkztULK`^ z8o{9Cv|#4oP-JQ^{=sb74^=|`4QsyVF~@_B%8YTrk5Tx3*GXIxcmC+o?YU0)D$q`f zD&7z&30A50{wXxAOHA7HTw2T<2%r6c)3-AkL4R`Vl8%{2f5iS(GlUwQTqA_F3eE3& zRv{3|ElE*u>}MRDtA(hW=CKf_!h0?i(sz5#{^SgolR0Xlh+6h{r5|LS$0nMY9_3r) zNb-dPKjQ|2QG*<(i){G?k@Glmwmx$4&7^R@$uW2hra8F_Ge`qHKo`35EJ82h(DOy; zMOi3x@i~l0=W4LtRAbS&>eutm#`12CwNu2xPeJ2jhQB2>fU@6{eBk;yd{U-FgSt(P zN*l}f5;oRVj%pWCm7ZTUA-N8IiW4I>s|NM58Wqn3Jp&P!o%N+UkmE$V3<(u_K>1-5 z74dMbw0?3R)V_i}AP}Ff@iflbp?W=_sl^#Cbz-0yBB)E34WRXE9De^7U)LR2Me+Q7 z3nZkFkkAQ`(0d5IlZ4(0y+aU!@aP>BNGOT|LQr9?KoC(;nu^kkh=?FXMN~jQCBSPT z`V|Z9_u1LIcYB2&f824GH=muGot>SXo!#A8sYxh5v%(wB+Srg=+K@$nqs|Q=Pm{=# z6=XWT9fz4VViRmg2bu*zLnRCHon}GM^2vf!`$4lHKV1qa z+wMR632g);x82Vl7sVg>Ziir7=H7q9i8`}K+YE*e&X?9&aYxFm`{%X@%F~=@asUof zDqr&ll%Y*YsSKc|eN&_PWN(v-{OTG{ENfZPst3(V$`MB6l6t>OvonM4AcIrY>Zw`;oIka(}Ec>1}b1$mFv%_{ImC6;L0aj&&O zzhr}^Vb;_C!!YYB34L6J#<}7+7Wpqk5{V(yc_n-!8gsIH5 z^eAQOhkM<>9mldXoCQ`K)JJK4r)qN?k@*m3o*yjJJe0S3K!Y0#s~Fb^R%c=pV#Q%2 z^lcjYRx5hMBedOji9tn`F?g{ft*z&YXFqE|7p*|pC{kl{WO|DtJnc!$TneL%!Hk7X zjAQKJyfyQbW1*#GEfwUcp{82O&hS)QSD`ruxbe6oE%AoCklq+-s;P%o+|+sA-n>IW z;5O25>sxWLi!myxyeE!7tlB)5ulULn?n<-**XB849-CZygm}uZQ5x_F1$g9ie{r6^ zGdGM!;Uio_t#E^!;R=J#RT|t11&*{-d_S)f<|*rX-U|1uBOGeI5FZroDarP0n0u_4 zhGL~RhfX#B0GqwqalA({PYG;^YGHA#Bj%Lip3>}14Gsqh z1-}>vv||_3{>>wKtt+|V2wPd;UbexBHMf&XLMu;da9=8Li3N}eTCbF+A;MG^q$5@& zYB-w*w=BwU?eRpiyBge|3f$EHq2Z*sJyHCKyG0rP&0bUr_D3^Uir)%Mb&M}A#IwqJ ziow|Ks^n?wO5lqsnp!(Py%iSe7Tg>gu88rhs^qEUx+rnKx8hP0%vu7-qy-pCeK;Ao=dHMBY`7v6G2=qZ;(Wnz z)O*1=zGj^dd-^7Mv^gEgv#|8Qt}NMoXobD!2>Vern2h>yvSlYe4l|ao{Ig{^zq1?$ ziHvb=`Af?{zlL~gv&f`aU)JyxVF-z$%s?r& zLi?2GB_Rd5Nj$n4NOC>vh`HE`NrUABbv%{W9u0H171OY&<2N)f#g7a`b$;ZCzQc-6 zYJD~lcJPLV{;L(;FoxUeLH(~f0$;WQQ%CT95^6QJ9Mvj|E+_q5Lrc;=ZB>pBKiVOb zr$pe`iO6zRXE&^zbapL1%Wn-JjbsfL5R`vKuyine1?DZnH@=@&o|nFW^HrMLV4K)r ziQBu4!0kj0cDxEp-pjco&5QGMd!c$wFT%!;wZV?I!O|c#q^YMedrgB~r^3?S_$}k$ zUhFKfvlNAj?IWt;J6K_ABl?t?{CE6S-8iM7pb06ektD=886y>ddN28l* z#hqrwMM7k6{!TkjU3k^RwFP|~ifOHhNe z9X-`uXRNrVthh8SSg^CFF>_Ur))>nS%vFP^egxNnamLeM&CBqOMLHIiGQi#d=9>D) zT7<3!l~|%yL~VYwzrFT%K4@N^_k0AWj%A3DO4}yBMlhbKx$@gGQpr1*frK8 zlOWI+;s2t03%=qz$9meahg#g~z)QwHo~zzViPa|6KNqET;zwT9xAI&!(PN$dIe=}< zv}LOzU^{O-THo(MZm&yjfe_2}2G|^llNOdQ$uIvgK@SR@f9_@)UpB#0jm1=y_CJc( zpDB5XMJ7aPer;D?nrMNuJ zQ-Zy!VXjp$$y7kkqIk-8Dbf7X=}_^P9MM-l9{s`$jP{Rf=$|X-h~h?wcoCt8^G82n zy}<67DB`eV5eLjgP{b7KA_Cju1dE9txvTkCbBsO1C#*{?t|=eFYtQIIx}^DDE!W(| z*DUr}v*RCDr0n==SIyb+eQp-8ZK5{(W&zqnt@;T3(Uu>7A-8~*A0H#ts4NvH^W#wp zu@2Wl)C+RvBY3|TeIh@e&d093a$B6ndv}HRI;(tDc=v_2hSL%IcgcoBvG@VkQmbjy zlLd8K>?w>-)uO-viQ#EEHzRq(LQf?=<;T=`UUNPqKTiBebw@HJ$7$y(#jqzU>FtTM z=3&PE5S)<3>tpXk33KF^^j@v){&!?Fm_)4me`k z!s}s2U~-`YAEj2(fd7)fe^`OnzkfTDPrd>_K5a4VV4fA-XGT{eo23zq1Lza55T^$#xnq0ci^q9Z>b{Q z8Wkw#hoE9&J&>g#E`1sC&#_gcx{OxJpriw8;b||m568iCsiC}U^4xG&x?_>Ul_F8Z z`DOmLSPM-?s-0ARGE#T*X%P=)Jbt*ly>4LN;ZxV)~CHdN8|oMIF2 zbHpZ2XpDa$83%o==p+#bKGwbr|K$dzQ*b(mgMHbD|iK3r%u}P^LOoIG-Fbc$83Uat-u#; zk>8HVHQ}3GI_#;!<1e%?%+I_D_c~7e-Ii}wx~d|LA^gN!@IAXpz|IOFgptG_t-?^W z@dG3-buh4$CfQcJ)zl@qs@~ogZSc&**;2$K7L*2gM2Z!5ZtdJ5oR6H>u?RoA5hi51 zBkmMOToOYd2f^5PB={x;Tz5o@@M~{&D9w}K>lnssE`f)-!Lful9ZMi5D*9hfIFH^8 zhxJ=o%vqxt>9vUhb~eCwJlc#;IPF-#Nyh@{6Dn+h(qN|^QHS>pY>x3F&cAKZp$IR# z24R6<U1Yb&O=25Z;@RBTd{_%4V$idikz*M^v8LnOC&@P}}VpVJVRsE7y#CGqTq9p!Wu z%d#OZup#P-fz;gcog#Slc7)VF*06V~*cM4796&w?1var>aW@8lxgoa23V{=Qd945XF7J;xx!n zHrNq%SaCESHK$8^&{@2qVXslK^-yS4?D^3NUeL1$@5H&V?0=Q5fEBg^AcG-1d1~>sBCw#~=0-hn+rp5_MRb$DG#9IZQz(oVkS;wk|qWytUa}gXMZhVYxa> zNTeLVrCn_uv6CIK$(Kz&h5+s?35!%i9abFCo5ato>QG7sxu!VcPISa2 zLooWdryBOoBnfO#aH+FMU)v#G&V9YYAdTh+yME|(7|z3IbdKg{>tMcMfCTTWfKzSO{Rp*5 zGhbLj;7|hA5jd2v=B#Hbme&!#SqkL(bDl1k=yd|Zq5%gWQj4ZPc(6m~kDUwiBHwzV zu-J}pw<)-!AUm6Op`V5FVMjY)l>p|xFazvV7S;|pltl?&AN+w1KmL19dDj(L%+E?O zw5$Xpzal*4s}70qu22Hj5;%wjYY7}m(7&b{7U$*sjCfmUEyd*1M+CC#S&b+fWm2sD|kXKZdYg*``p9F%o~2f=>qI z+?5VE7it{r{|FoMP#ZD@_xWW{J*58=zpE5Hj{NutG4$=hR@ktfw_%Y2$NN0R__dra zVSGeuPbAg?5bAyv6&l=|?XdywwgJ*0&wmXOf3JkWvR#_}B%g_9e5lJS`gaGM*mkEw zL4GG6Dn>JOH*EO7+VIK9m-`K~N-*pmRD6lr3O+UgA%7h^=ltCP8{GYdsTncv#bRq) z^&q;oRS#$xTmKuLMk1$NK(|$)vCXswofXm%=X;E89Vxj^wn4YDL8spIJTFqo1?m(P zHG2&rh)EAR)LXZ_O<}$vM4O{x6K$a5ZJ;EI?{6d31QuQ(zo{Z`^LWOv*K9EBY%sbC z)PT!PFegsVDlH(b?O zUkx=)MK!EeQnzl^`Sw3C9p1wR+tmhZbQ6cBb&KUgkHM?T(h69h7C;@v)JE{qH}-`) z`?L*vjtx8Ku4fk8rh#o$!E_(69edY?v)P8D+pEg#XASJ40;c;pI4b&I#K*q30iL%3 zk_ObchhK-*l{Hkbu2Mr3@;_JHi~RSl-6MGHeWbm(>RPMlp))Los}a2Q1EjGu(y;5R z*v5b)>#Mx7d}qIoNb?#BGmvO2pmtrW4iMiMOh)j&k37ZMD6N1IY5_E+yf(OFAwFy< zn(U$Jz#eMD9%RQBp7m&#w-{Tc!LCqYb-$)1d)@~2tQ`!)p5k+-&Z<%K71dwbuOaVI zk>TESV7qOgAK5@@0(M3rZzXn1!?~g2q@6-Qq;-flh5c#+yJ`c|2SDL`|Bmiqe0``l z67F}!qTaSFHc`<9qrMVOVlw*3j_w6{R$*@pi%zsEL}X&Hz9@`_xC;ffC}^a_b%F`b z*b1Kt?4}k-lX$;`dy`maTM2MS)LE-PBE01gb|H*eDu%4A>fU(XEviQZzZMC8r`yn` zNPe;1Vt!+9a0@V+yetsqErys2A#YNV^%-NF%uuyQEH7HJM=1Y23h*0j@NZh-X)3y4 zQSgkT+J&Ics>n3tyq5r;Zx;1dV5e<(C#`tY8e(I;#SvN|y!$Gio|H+PVw=HOF!`?y z^sWt5OkPG8_m+W8?p*=nbvWc@y%cZM<^o|Dn!`WGTiZwtanrJ1Ia0GowPZ;k4wi`U z!h?t}x-m)qs1m;VuJ}b?N7%H-!j>!TE$Mnr!om{|!eWXQ#}#bpQJmi^4f$j_!Y*)v zrGRPqvfc#O#}XEfco0@^VsY!@yj8J|7k{zIV5<`_`+)v6@GUR)sR7KdHmvM zN7##xg(Zb;T>*xxNRkY(Bq{CJq_D;K;cqajUm+g45Q-mLA}&ePel0aelkW3sd1G0N zBpG^9;gR2$%o^FCaOMuJ+A}vTN*v$xqpu`;DhXmhY+;OwrOTli8)X9=VFjdmda8jp zfxV((tx>TkvR!mxkAi&rN;J`^oE}j;aj*|T78~>m8??ynA5zU*jvdvY52?_)acRl+ z+pzXHVvVZ-tbm4vh?n7X>saxa_=TaWTRkI`A3l+bpo$Iph83E0%BY>V`Xo~L-fI%| z_DU--N{AOWHH{T-9h<6AOPw{y4hm$!y53TVr8q$*KL#?5*G%+QVY4)}=?a>jRi~NL z7tiJ)3+HNqP@a9u7w($kSPXW@wQ~;dus83RQ{Rd$21{!-E|PqYfi-&T6b0}=Co2wm4=YbNk_CV9nnOtH8QFS^TD%wM)8r2ypim_ zhWoFA8#Fr{8jUgkxjanGo}3#>TT>v!;>7-+P6Z+{aXzcrK(@VV4T6eTo)2yA#SVr| zz45Ga1FKy~Xkcl~G{S$e8H7DR!|H2b(ZcdxEX@YfL&C6$iE{ZZI&+$3+mC4@u>~n6 zt;k(?Q%(ud9N2=fUNKRBw54|-%V{7NWgVI3)n>k?r+BS-EpIf?J%pU)zNze31Ae_9 z!buJI(Q)2EV##}Ho=_*PIN$hVuUNiue?e&4H`~J5K^wRG8u0wZn3!vz&+*Xmvx&*x z^6ZZG(SC_a{x?7?^SmMpH9Q2VEXMVw6_3Uq-r8DkabB?p9Ei`ri4YyWI(0cQOPfVEenB2M|F5qr&c1-3% zfQGubNVDr^rIpoY+!jivo*||{PK%WzdD(?&ar~{0m}Q#l$k;5&*z|_F*kGm7_<>H| zDy|PC;(G>Sk{>w+VJp+(`MaHg_>LpuCM%+-Sgd&`nO!iz7I*bFfn(()t+Q4LlKq$6 zAp1hts1LGdJZA``EcWrDZ><;SiR3Nz7K~gs1>bw1JFEmw32~^1`&MYO%HQ?yCJW6G z(Df|P+k1NZ!M8$r>QsMCp4!)|oizjDQLUnKs6q4H z{h%~+vV2vrf>U59YXK)Tq68b>ZILg!)DTZWTUyN|PeCruCagXgf3&65{Cm5g`E0^v zq5$nw7GM)|cS;st`b_R1 zbi&`1Cl2z)p~0n&K^I8NE7JFPtMKE)Yz?G%W4(b;#V#J~O++Fo=-RU8jivnrX$+s- z9txAb&Kt%P((++rc%Kq{bxxnc{KYUh9ZisEX7;rjHkMBYAV_0~o%DdCS* z@hKfAYZyj~qitB}HZ0Qb?}kIa*Ga6GRV<{+VDs#2;5Dgx-%|YQmOe!lUbAiZFWT@) z7WpH+^^rnKydF{U52eFeAGE>jv%`q7M&&2r^WKp#egy_=#Y+fbmf__;gB+tqV+AsD zaV&DYX$KYgj8(^Y<5>A7(j&s+uJKAe;|MdcS3p`bA5~TykIaDaL9(d$k!3MZaq+e- zLoHE@gf>u@71LNQ9G>$DsTAdr-5Kkx$c8nMeN_A1P^Z@>NOe+legHrE6h==SIi;+0 z8|SUh7HV8Rqi_lG7`}5W^2YA<&9A^y>i4U}{avBeT6xJbeQAd&jYaP1X{i25s5e0(_AxsyN>=(OZZ8 zsNr9*;PZr9$oj&^#PhVK`^)h&o%)6H1($Dz!(uzh{j9Yp%BZ?B8ATLoDr*%cd!}Bi zBri%V>oFhSkTjqlJcKD|s*fDe?_1GnnjvzUw3fJboscE)KDG03P57+;0|u zS8BjGzup+3)Oq%F_&5OB)Iwo}C-d-+2bzC0Wk-(>|cq`FFv3!@9_q#{7r*brBC}E z$Ehia%X6MVEn~I*QuMUN(U<8OL8vs}0*&Z_ossBImP*2gu8UAf5zX`_L(@0!E%4Su zmN!ABS|MrqO6EduFIO8!NbKioh9pyYDbw2mT{S^YwnAbb@(6w~%R3mUqfT66J6AI# zg{(U-g^5U5;>9G&VsEtAZ&io@yR4c;fT(o@k9-TE+^p68%kY%9ys@rV9gA7}xMFI! zu-&Qv$0n=)4|oi}T6jPh@9`{*>2b#rKDU;DM%{-`e$HD9hl@}Ne_2bwVMkaByv*Ab z2NO8SCeI2<;^xo8PE>6!b*&Qb{USUhQV7g#^b`ASylD5R%W>BllP(xiKKx<-!bsJG z`Rt=%_EInn2~WL@fcA+M`2OyWMRc(ifo{4FzqQg^m1Szc^A%t?J=OTR7a^T_j&QSs zaH7>Bdq3xWe8Balx-yedTeTWSZI6b&TS2F}Q&{{?SnTN}j~x=-fFsF%yvAFK-O%8E zRp1Z@f}Y)jPjPL5vDyqQ$5-{AsC9_gqW4v=n&%sa(-@_Zpjymc>#f0BX|T<$uyn2~T({0Rszl%@ z-E~9pLd!f!YM~33;_#nx#No$lm}9M&7_k?ZTvp2+fL$NOrV^vA=;>y3vc2G(JPgQP z6Az6$qvHmZ(!{e#D|3UjOtPWp1`VvlvnoMh$%ej3Wh&8NiaMyKV zN}BPsQpnvEMuq=xzE>WE@X`CmPB|}a^;Ur4-nA9h_4%#-Dm;9Lt^fa{rQQ%}zRB|e z0!(FFQTt}4Fpd&uUw}4-XMTcEKvpTZmn4GYDI}ypPSSinp@5{4uR$I4X*d zI!4nrv}p6*Hki>)8gzRV+8FKt8m`LkgG%w!6@4)*)dtm5En+Zua3OTL zzHv2%;E%S5LF++?oA-p;o{>wE&v< zJ@tjR246UDNCj&-xc&;9?unBC8u5`Q;Mw+ZMDJxrrxpZFB87}^Efw<2yqgvHo!@iI zicyZ(M)T^axKsHx#f7) ztHL{4JhUo*;S_kq9{UcGz#jWSNo;GQt0wsXncksDQap`)!E!bH--7rJvC25%fy6J$ z@7>6Y;oE&fv8m=aa6GUFze7pbgWsVf3L3O5KP*A}_F~DhT@_8Hb|qx+GronQN9m=9 zRp)P27>13*<KdB-z@=!jokiGd=`uERCPx;Oz1_MAB0<^wvRiLsHqfd2oNvL!(>R zfSVe?RGW}L*~3-xo5&va|CiSIQDxShhvQr`lcgm*d`}BWviSs~TEcnBV(ZSPPy(?u zc-;le+vR9Hu9rM=kjHYGs*F2;NPWtL{1V)I0c^fuWAjyw&9&GbN}MYMbYgQhPq>Jf zX|d{bs!;G$HFizoFr}%!wx`Qwo38zwtm_)ZM9Tk!u?|a-we(2i5dfHmAs=*Nel?!( zGuXRtWA9&$y}QY}o{`&=e92p#)su(_RPXv-cdZDOW-Lk75+>#s=0(3BR+_i|0XmR; z8LC!O{9JXnu&4X)ddo&RR9pB062nC)hDQ-f(-VR1^}U8y($sHqifnp__==|Y#;-PU zj7!nQLH2w8Ra9BF#{7#0^CD)fDQ;WWax0h16fT#h=+Yp-)z{G>9Mk~!nE*%Sh*mue ztuAfz@Y;OG=;5J!-w?#KKC|L~;*1X!Tf1sRDBt;;w*>QOW!yBCk+l~sd(!XTb{OAT zM0?#CRD?ed-oP-eRH{&lw%93BxLFWDdaidci%GS%(x_C~N-ZD$ZY{vnM697$u$mmz+}acVq8Bc^+vpyf0-ap^@d( zlKpFgxod?X9W40=s-jL?*`?Ox)BcApl^9Gf<}1TnPtT9!zkCfny1eSsaEysk@0pq) zMo0hCnxMfR;kJ)SFB+xhrw!K1z%V9Q2JJODp_ngy1UvPI5f%BtA4e1xn~Wk=$HM*sCukaiH~9xc@Q*cUj9+wUj?||z zeDyCQiW#umtgu_1V3BA!gI&`QuPBImc%u=rb1eK_bOIvr_PFn@&5B@!FqS=WSD23~ zt-R=`TjDh3oCu$4C~;nLm`}PuMlDgJS$`heJx+hoX~=dUlGeO}06MAx9a4a3`+~_4P{6F{ks*BjkiC(7)ev}4`>o)6oWRMCUJ~M~ z$pRX;?z71&aagiSyqCV zkUz3SqGQF|wnoJh_~vkcch+f3uLkrhj)n1LCkMlKv zFXOAujT%pwn_rBtDuKhwDvQ6XO+7)pur_t7@efP->aYPCZeInL&ZR+kq!qTKw4n8H zLZja2>(Z#~B^p|mf`*1(hHoh2tAtfb7PP0G(7;<7KU>yUh3(YPwkc@YalRBRL9zh7 z>j)&mDZiBSm0?#jpq~{Ws0qyWy!;5hr#$3#(F*y!6C?$HE>`eWW#JuVeT4GVDyC+L zmEy&D(Jw|6;@9Tom*OYm0gi1-#E&d(2K)Y2u{Fb+2@qpb4ZM*RTyHb=a5%jaBvNwi zke*7=pD`NbC@Z9)M0JKdiImN`BSWcc#74jlJYx@FdjWq|K>=&D0#-e~fYlS#0#-N{ zfL(#j1&Aj4pc9?-#_ z^v{kg$Mb6XVqMrG*Z~}S0-KnYODJmlDznm^NKIIYPBKzNmRj%MF?amolO_0r+6WKE zcCvcP(Ve8H{3Sd(5r%^wDLhj4ZmJ9-lx<-|wXW60F|h+XNpCbg*{{u!_G#d=&XM-+ zq(q0Xu}x+L#h&lkz&X`Ig1I0cH9f_=Z9uQ{7x<8P|Q-=t3Z5Qe5d+ST{fU|Te> zw^cBT@!VUOkLK~)lSO!5Z6piK#=#G4qYe8l8#Y;m^oFns-)Y$ARBU6QIQ6e5Yw+QX z;5UC`gZ=uku%Uc@V_$jK6Feu`CwBT`4<3si%kTV|7tJR$L9P8~E8=gbB6{%`nnE+{ z2GMJEmg+!4hDj^V!FI&Du+dmCJ7shTpVg#t#7tu2IUK7Q2;_-eQ*CGO_Y#rgK z;fHFyii)9aNV*RhP-p&YfcU$zeb-T#@Vhk*(ZAWY_aJ_@6%SLKycVAmp zv5VfYbckZ>dXB;I6Ya76$q?)ybP{{dn6PTm-_LY_q3UM^?d<@X#seMEqLyi2xl}tf8q^nQC($?NANX+^cvSOEAY#w9~9;Z;~|Emlh_)vu=tTJzFbJWC66oCg&JRrn7q_e z9C(%9%a;H>Thz-pgLTr1YOfTPl8=KW-b{lBiz7F5Y-L8ZO;?jzUFz#A&9BzY2e9jU_q9^fm13=bz@Y!&7JOl_siAYUW) zj|Tjg0!&LG0bH9W4EB{qo`(}Kb_shNaEBqjL`*B3e+rIUC7z$5t4PtIzRt+?STokt zkjwG&W6+Q-g3TBPj6M>hmx7Tr92niL7+r!GWS*e_Wb*#*EWLtDnhE?-Gl7%dye-W2 zd69QI=<^Ky=)<=}aoT7x1qa5-Nw3*sZ2kf7rYjhwCsiBetB0NY=z9-HUO_H)SB&5f zM)|}ZeU@+jRPy_AH(i-%%DDSzWbFDR&TRvSQ_4-9F-RTHwF3QS1tOKfE>H#e^BKOX zt};A-JZhmNKkr5xJhJI_bq;fiyuXmKHTaz_W3gjcTZDLUSdQCNDL6*ZEt_WyGq@zR zdFv@(LkN#>+bOunyK;5KNtshKE(>z+7Xgm%&*7$s$s7+f}E;A!ltxyO|k;H z9f63qD-(Qmu)!Jup*FQ|t`@o0rR{0CvTzdGL03h&n)(baiL<(B&UESwoBI6JT~{B9?w6kGtIn{qD5cmulw2e2 zy*j7$|NB>B8u3mEcSSy;qCduk?e@(z^^d`_>o0zO8eAwXmo;@dY*V6!i=Fl7pdEs* zSWejognO>68(S$99*-3)c{pPRbAxm2rn)L$vk*EI1gCy$;Y{>fLp5-0rym5Twd9%0 zd}aBy;%=PEt{*6b&6u6Q`&huKKf>Zh+alW%4nBKSovN`;DNv)?@ z>{vo3mB9W&2ACKjK=@RhKS;Sz%=-N+w5A0UQ(f7K9&&(?_Pf5OrO85D4Ib^G*C4HF zxvjC9D_PC*c*}Ee+0aI4_*DV<;-(^rFG`szcXz-BzX=j~*u2_=s%%pV`Q z?$U&4ey7jy5MK1k?GV<#C&^&lD9r}4J_M)wt-X4Z-&*BWv)|frZip>Gp$DI`$mg!n z6MwRKt#{{yn9~y`^psvJ@MHR7{S4M4U-Y)&p&v>ITg)n~It*v>Ey*I!KB@WE{M%)= zYT`ZhY6@l#vBN#(VDo?`SOB0!ya3zP>senHw$~=gPc>0~j0%yJM494SoDFgv(#W^#c7)amt=UFOH0ss@u&9ld{^bFr8NO zsf&E$t9QoVY#I}Zm+m?^p|D$|OlaApaEU^Q%O&z%!e73inv>Riud%rPZ+$MR|5}^Y zoatrPn!B2K{}jNQjRy!#>B3Q8>nq96y#(=Qy)z5z%|w@aNB+_xUcY2ah?jYK=?X=C zSFN)CO0064ti}W$^QKZxc~L|QEK8%e7R<8ZZCeG7W}!!~!(b{+gX>|2qvbmq+eg++ zDZF;$os#^mu2VJEyE+!r$yyAV>gBJ(R4>qqdD>D8c|atbsjvBJWAAMz_Gemg$t8II zbwr)EYPj!Oa5)Xw2^j2`R#@NcSVWGs2x9$kdGz8!dj%{DD8+FRE`lE>YRaFLJ| z|2}%+#yn>$x@oaAjspYhur?*M#ioFd# z2=liB_enFZW)?r#DR5U!t$;OO7&DKw;tsRolC4d7$5$O2W)tpeD=rN%qPM`gTWLjm z!HT9kv^C*j6WReQ8Z9LTmpEMFJ;ZqSS|QvOH(aKO#rR9o9WfcBQ@Bik~zhTrR0U2Wla<4A*L2@QZ6QV}6x>33HysW+si{Omd_VCdNLttB%dkciVRHoWm5&bUjoU1{~DC7@|1dJy8E&zL=q% zZ+MSbSNgSo`snSHL{NGU3>}UT)G%xCoC9#X3GUh+L>Q{_{Ntt?uf*3JM6-pCZRK-S>{y_W7Cv(?hq zeRW9&y*0!hbl&qM??8aPJ4yp(iwJH@UUOAR_To1_ho2VTPd3GJJpTkVCi@@kq=~_0 z1V3~PNEjraFx5#(@j`2b7Py|L3WV^m<7kTAHOwvw=HcVM`tYkQaP1xs_uxy+3eD4y zW-CbPUc|U+h2FtP^>yJ=U`f0fA)EP}>Ih8k>BFz^*;_Q=w-sO+HF`52iH|3JNn)^U z#(c{WlXScMDFlqZ(=g8kF>CTWr+n?P>$nB!>&GLde&cJyp1|=uV%KqyX;ng&JWlYI zbOsZv|5*|LHY1WsLTgClBxbA?zJAfo)XLi;$jD^54z+%^1i!W|H-x?4U+VN09&^Fh2}gm9`ov$1pSy$P zxBY)ZwX-fD{`0o@qYS<(Hfv*ly`@pw@$w&h3G6!!?wk&H=Ra>biIkExx74~Nk%dKA zI~?^Kgj8arUklFLvJ?GHW-R&n+#-Da$U@lkYgcYGW{!5Vt&9}1Z?$4o;V~V(v-FqHBc&N1b5{b^|MAKMPIq& zOArKMy!^r3SWFM#7ivuv;uXEtni|2gZ$d{~YN*Xjs78Gy9nP%`@7My^zzPThxrmL^ zurf?olt4<&Cp~9wX&%T7iQxx<5jT^T+^Zg~|<*bzX+=x~~m!&?fcT5kY8rZyCK76K}O` zHefx-ro%pw<$R0Gp|qy3gyJ2)cF`vnJ{3P9k6H=~H06gE=ayqn4U+MaBHw9F26m7Y z*oxsBg|p*iGI`L&U@vHFKWDJb0TIi0{_X34&4itp&N7%5=f~cMz5<$f9w8oE@nIK@ zkm6SwW3_*Ti9b%H3QwO0d7?m$M`H&`$GQ|b2oX)bhw&0pj>TJx4AG`_8A9Ute_IAr zVh4jJ!OrJpZv~ek?Ou{wmes^UIgyq7QrxX7tlD4^EmXsMl?PLw$j6qu6UwqSi)c#*K2>CW@0E1NfDZ98ec`eyRg>gSMxkM-AynGw8906Szoqan^!5h1ix zHp_-M-9RKM;Y&$McQq+B+h9aM_YILsI`Ts;T*p2mYE@G|8KO67YCe}WR(`?{b9{qj zr0DB?S&ikcQa{-E`A*~K+z_duz$1Qk4Urm}Q-JMrZ$_8eu*=?Xw(Qax&b#=dt>H|-OH;$CKUA^>Tw*JBsAQ|Q@3yfzN{@jf&yvzvM$PWzg>k-sc8F9Z}3Bn22^aA?4XMB>$Ut^5Et|@oK6dR{mWk1Z!HB` z%thqiEk-t6ywy6Y&|&&FQ;SN`fLmLEX`yS~ikQb};fUGP5z}a5twt@5;HxY7BiSUa z2)C_>o7g7?yqD+cmHic6PdSz|##{~w7ZM`j-qM8I{yT5^b*Izf^m(De%W{+0hgfAT zx{2uT(RIB~D2mg+MS*>Ln7%xojClpVDwbcZ<_}?K42T%sraJ8HDJ#xbJg2%}?7@?> zIM9F>so}4{0@x)jD^Q}~t;?avH`}tfJTFwo-|UrwSdu&%K?nR9ACV+uKVU9~$JF#! z#V+cijuZ}WDIDGiRvK~G^vL1{e8<*62&*tW_>tHcz@J-?zXuc+H{9B|OAqJ0D+StO z2RF^0641fg{+=vV#TZk^--orak+-yx_udEJB{_UaBgw}Y6{C8hzYQB@!x&-3Skuej zf|oA8qyeAY2j8+x#kg3{pTd^fFc#S`gaN73a7l43qid@Q@>G3)MfR=@WOEQi+ZBOi z@m}*K`ug8*RFEGUpiaNGft(mF%uzfa)X?9f%5n4fd)M!F;PXS$q?J z%j%!vM>Zqc6*?o0=*x172wqcDe_v|>Cmjm-pD3UL=DP1R^7m?fSNtM;`lvahM@^kM ze#+!m+<*Q5<-Pj*VQ&Rlp*h7{6MvA{OyJw^S$4)Pd!i`jaQ&w?g zPY37IL6Ufjp^FCXJ9T%kjn1vlF;&p3kky25Y#hmLS+Y zfDn{%QQwi|NmaXSHVcyi_Et1A5XvX431n2Cg+JO_OFCXkb5Kxf(G*csTZRGze^|eP z$5#B@hlb9)Szu{dosoqp-4V@oIT*$R(ujMP;|)>dbKB0EA9gZSnC{zf>c z*&?WY^g_@P_>q6C zs{qgGXR00aphMw<1j{4hny)XdBm1428u3Rx5jVv#KW1W_@M9+Kg)u~TjU-{IzYu>i z4Jy&aN{8OuOeg9+``bWcHboVR6RmXPiH?0XQfd)IEH+XVGHAtrE^iEDZzp1t zf2yN*)1`iHuW+l1Yct^~b(E8CucI#wiWq*WzrQhdO|*RW5y{5EbiGlN(EJ1Z_1SHe zdd@%y4by^Vq5bAay>gI$1dALMi~wzy=?T|4SH(SkR~;n^*m;TKiPGfr=Gdh zRCgH<;}u)3p+1#YXqG#?8i2rdsi)yil6| z5(c@PRzX@n>94|0+CaW^25B=IBj7xh{>o^7H|Dd^-*%?|Z{6}9vN6U!DQg%Kh~*z; z_y=R-to+HQ7K#0_roseSzT=nU%e5xiScNF{DO3!b6`LXI1tF+nAX2ini$+On+hrc@ z4_JRZTI(bYEwI2Ndq0<((3Dp46k?mQ^CLaKv~g9E<_xYhh+}!*3I0~d?Xj@(oMdIm zlX|V>e1yJd(nNn%w&O`L=89u$EAhi;)>q&~^Ky%G@Da;>6a95uA6lW_w?Yv+e@*gt zVc)8Z25jgZ-sa_nPWY#N48VI?qat;Yizp%aRH|!F`_Wa{Rez z{wTx%Qs(-57ATEXD6UGYYimL(J(~BP>F+4NY}#}*#S){fjXIXzq%uWJ0zbcjj=ymG z>caf+41WmDLZw1FqmbL%S2xfK>8uv={!D*+*1=XtTjxTe8f%5Ddpf%?e>e+eJR{4P zi!vrWovqjQT(ykc+0fBhwlbzWmvOkMETf9H`sD*E!1W$qJr_>Idn$0kJj90Hu>o%~ zfJvvJlw@qiP)*Sc+O)cc6Y=2En%>eJ`bWzamy(E;8Xg<&&Cw?1&R&VZW+b1s0_{2gE<|5iPa(gu5ZYPCMqbmIyg-(}JLd0=(%;MS z_hr3o3Jzj;*zkzl3Gz ziaj{-<;(gh;(HWg{;aqq9Qp#TDuf=|}kzX*#Ne#dYnKny3 zkS`IQ5v=(bPJLKthP56G(i^Hr!h<>x-tVKOseEC8oJkNJBf7BCyxhv%>a4AXoSvag zC$MB2ax2UpDN+)O#YP!)vAosVKr$O)qZ_JmGzghjie@FR!kB-lN`G+`TKOUy{X%E@ ze^$f)d{?E<%Jw&6n{D(t&h#~Et!<&%ny*!q+AsM#vJ*CxFPu?&zU=SM{3`u}m;FPT z$3}nCpx0GYRKdw_*JAHA5tu1DR#q;mAeJ9k>uKpVO#6f+mAVAS zu&J(%x)!}jWz})-MXB@D#LxWjYzWUZR8vjQE?hVk2*{V8%}R9L)h%Yfp<#p|niF^QIIGU{x-V(bcLqLW{lB>69-Dra0tEN=bHN?hz|sBdw&RaP$fodZOYHQ19P@oLF=}~ zUke$H;(HV{cuRO8hsGv^CR{|zw9fJ)1?Ski{_?IJRvfrWDo#!>Y_qA!2WEr}8_W^O zt9gbrY~O!nq?>G6nH%rAD@)mM646|2qhMzA4!^V2Ke6g7=JB>`Zed#*Oxd}7(Fgvq z)#LCt+i?4Ta|)Y>+mSr~69_=$#E7hDNYdpOWw+vWUNnYtHD1gef*qXK?16UldPiG_ z>S{@}ilR0fXKL<`Fycl9>Qu3E)Qt*6iAo(H!Q&HDV83yC1&R?jHnuV7%60Q6VJg=` z_q3IcT0wBwjr1A=frj2lr!tp}bSiVngs^t(oAtDc|5AaN{s}@5$E*-Xf)J{S3XT;p zPj4_mLxo&IP=xlIS!fpP7B*g5Sx7yW3+sk#z>0@W@+&|u_>r26BXAai)(FTh)lrFs zUBZTA7Gi7(3p5KciDCXpn3G;Af-omo-e*C;0#OBlR2`p0s%}&%A(Bt9P(`F5!!uSy z98pJzA`c%B1PRp=kVqgAbx7W3iD}04^qfQR>Oa+>^QPUdBK8Xeh$82m<88{xE@%{w z=3`QtVnR4-4rGdU;xLpTGpB>%rSGA5!#^s-+=2e4h)-J}{&+k@p8zM1~9i(z6^Z!1~7mJo*}X zc|rkLe9B+X^@SDSs0kpaL_jlp%{czwmRTxSC@V~|!4>K1pH|R22B<(FU4^ERu5P1x zCtZDewc*9Sb{4);A~vrVb9d9S167c)nEIVbS8Ghr&jBC_`Od*U_K*~aTFyC-s6|&R zO{WQ_%3b;`+|5ZrntR{+J0P$i%2Aa2DS9Eh^)Wo=BIbeI9XXxPQQ>>cEM*7j7d5+C zjKA@{znbesE68$35Mq4&1^A{P2SJc$SB$6p;P2|%X$8TCV_;3;L@Y8VjBytc*#9Aj z@%u%Pe@DMoH2d5HlP~e>rW}2`>~4^<{ZIb-=vXZxxT6&8m;a~E@Ekw?tHBWd-xiCq zj92Z2v;>b(|E4_s66T5OPoyeE1$}V|EGJI1dc(CR>NP}j7{RMvT-Zr@2XRqo~JJ3r10LVWxST-j+hh{?_nXRl%m!h^)!uOX`Tij8=U zjhJRf-)*s}k>?(|p@*vsbAcsUt@_jepiG=V}uSxq0h!<^<_&VwjvSh@; z@mzmLY~!g>lg2)E6Do%jr_9vYIM7bL>K4lGrBfHU?Qe$;(?ZzAiEw+?+f8}W2dhF{ z({<|iJ^p^!Ps~C+(TVzJFI0Q2PT0@q?~LU=7D70~lHX~6!J0s3cJZ$Z;6uOAVUTWF zjBg3}d%BJimeSk~O>)*`q`+x{t8m9(1L>?591eh z$H{w$Fm#HiVuw1Y&%#D^Quu(P{a# zZs5Vi0@c|}8^SbaghB;?@VbFeAkczw8}Td7#LpKDB(Z}*VppL+C$`T<{FyWHPj%j@ z&C@~AqH*s@EGy9ctW2>?a}%gYI?{Hq=bs z-I-i?zd!x-PGf%LIRr3f=@`2L-eUZjB7qdXG$zno;R4?d+#na!72!J^BoH4RXal!Y zV=Djj?P7dyG&DVj5EL=24~ikE#=`lOA5$hKPy_bU@-c@LF7}&cQ6V-^6=ykVret00!#^1d7~yniK`b6)WR;R`Q=P?Qc%2T%fJE&0$-vD zg8ZEt(%-pOI}FDJ!aE~Rc9G8*b(LM6+gxk{fO2>bKL%ahr~pMaou>s=L_`n0r2-Aa zqD74$hR-e?XfEcv%xpa+*%~v=q$MlMz$4FAh|89Ra9*?$FSinli6Z1tro;u3aH`_8 zxIj+~4v)kI+OdzP$%!HG9>a%~3-pFxYGGxY6^#^@1_#(RBKRF5xQ*lh3-Og8F^Lz# zAn|sf-;p#~G$Q_*qZ^$Nh{0Gerv{|?O*CdlOT!f~Tg(#EP2xT=Rk>XUI_Ri$6s z2=%$vM*osC{o%%e@oc|Jzo-c~+GC^N?M#2BDZ1NVRQgfP(Eneu(f{a7pV=HO%Ei~D z$Tk?mqgn)7vWGVEdj>f*Z8S{Lv{~$Q8Qg7A)Y!+bR(5V5S96K^YOEGKWld&U6{F!y zebA5L;b<%{CN4k`%OAE5G-Um46n$oz%t5nPcE)RsVXi_vCOJ@>&9V_spULaLft}rE zDmDRm0V#pXI2O+++LIEf#a^{huXUhq!uv<=O4T^PW;Q~I#QsZdp#%GE7<(Ks4zvrT zVB}y>4`?6g$YZ+%n$tW)&o1cHX^W02keA3egcL~jy-`;V@H3CLQu@HJTQCDN{mqpeAw^xz}9!?(*+Ne^`o40g@8 zlFrjuxgH+@kI0x6X~JjM+g(p%VUvopq-UTdU)I;;DZOc+h|kf2Wmpj6@M-Ih?H;A! zo>y^yOAAbLow4$F%JgZMFYI>9^yqw*^h}??Y*)Za>Xl5Tq(7~E+WE|zO?jn$fwHXl zY^A=}^$S#FF|)1BEQ;QwV%u`#t4;;KiZlu>ku)l4CSP;bH(RfStJ%4I*&wZm_2-by z(BFpM2geL5lg`57VRH-;>G80cHo9pVSCe_gCj%6Pqk4}V5@^C+SLxpvf-auh=wGqX z3%7^8SAoY&43y!QhX$hAk=ZE))^V-%RDyJo3l;Px(4Ym(Pihzsv~Yrrw2OYn9>}# zsi_vH7d)xb3lZ{v)Yx$D=~y^;B)A}lV=GGzH#`XryU(HTW?km+M^Azw+$kT3iuz!5 zV5s;m6s7pB?dF&`+&d;PlFe2*oR$$7i#7ii4yQ`KXoIFn29FGIx2F|uPb%C3 z&fu1GkzDA8yy(P0O;&I&Nwa`!E=Cw%?CDi(ZGyIc--1_U3NOyOH{{!LQeXsj@30ho zPbu0gl=RxN=H8u*nrkG>V)f_p&?$ioaW{~UPl11xIM>>~YtJ=R-HH2q^c1ZTa}^bv zF%8KdLv7T9=uIl?k5i+?8AL!cWTC4UwsEOEBT$EBOZG4Z*)Ri*?M0Ql7BkTpmfP@` z;WzSxUy|wTyz?wrh=ZC;_d%u$>+XG$C(eec->2feI6Lq(`^<*-iTP_+^xL~oGsHL5 zujO+CE7g(Fq{-S*?(8%!Z!h6}33N8!otsnLTADOvVPpB(1PpUx4dEwljxwk)` z{0!JFiGD|<*-^9l=9$10?4Yyg1yi#sI?q%$dGiC4Si5;jt?XV9m)^m?1O9v_hJ@33R#u>7!9tC|_0FP*fz1PF6>hhp)ky`WgXtq% zHkQ@=6z#{Q#E-A<+FL=B-g1QmfKiJARoHa(16M2xOctRNGpC5Ef>UOeADi2lcbOH4 zTel=olI@eSL%#ReB|!L0^18e+iqA_I>kAUc>ybeH}Hilzv*N zEYI_Z`jp_iR+=g+mR?8~4M5bPf*rlK=oziRXjMTA!%j4nZNJ9~wEY23%igLl|8Pa1 z59|B1qFn=5!tY75mW+)W!HRUpEd3}=Jugw2rx81rikq3odT|8;9ZNG_v;<U~rqk7uD7=Cyq79;G}&=2es>%p<1IQH=uU`nm*M#=)V*{kxKIg8_q=3%xh zjw^ipn!r<7Fn)ebpm^+O_=Rbe#Cgf5=l~f|NthqeI|?g!)*CxAM!%Fhf)#j1)?0dx zwj(2EJ=Ux@G56qUlgd!KTqT1{rpt*PfY(Cy z*9DSs2#WEaVo^OuLkB|V>AoIlV%9bg5|%4Ve|?U_3MFwuIK5;O65HJ zjOqKYyb-9+K2XWVy@@cvd)7kVQ3~B;{{H!I1%|LQDn!zHWVW2LLSWx$$W)3D5Y$4z z4Ye4HNVjJlXeP62AE>x1HU`>bn-+^a{#I}e9GczTmIL27VSZ34VtI{Cff}s*d~0u7 zmfoZ?gP#1-x^D*>v34r`{GP#2zxciprJiV}fkudzxk)DH_vEY$VP)JmX( zlL8J>A%p@VK}SF+eD_(XJ6|+YkXQWIc&%5Ts}gtlU!V@3@wq7$Fx@B}K99ha-QuDz z&@JL)RCX42J*+L=epiLEIj2bG|6)7B)>52+LN(l^%9Dj?!G?v>nbuHF(oYoopr2s;=9 zU8%!vnI?G!zQTM8wuTfufhv|ieG)Z4$;y-4;E6qzX{xR4uQ4m~vVu_dRG2f+w=I-KTNMyYk2Ar`W#6zm_bhfdQW@7s1J+wwKjgUL?hp%YM_Yn3F%qbc&AfrhAQi&${TnfNd>G1=)K zRN}rr2U;M3%R-EFD-g3~kUnkCgK87$p5y3uB$8TZjj1xE2{mC+i+Jky+Uj2xvB>JV z6kcQ!gh)nab%{hS|7EpoB-QCnDyxEYM!E8X7XPMcR3Z(T^{`QOwNa7Se(HIwA3ygN zv~7k)KmR&b5>K_!PqNdS*ORVW#48pF4B_R6V#kP=ZS>i8dNJ2J`FA7_?A3~nzJUn* zr#8}$ok^+EE^DNsUu8epNPjR$sm35~>RAhcS+Oa6R$pU~bm$hkwBktmftmWZzdk&| zYJ-4Db)y!WYD{#ju7*J>tzS(dDy0{wOD|-B>RH`46v0R^XIKBT$Viu0)>4vFE!U)QT?I9C;%eShHFE?aSaa>TKE3=Bupiis7} zW-J#TgX@tM=)M7jS^JoRd79y$A^zXiRZDplC0`-S0Ai)azU6x(U-rPd+)k{cR^ZMH z$d_%$Q~xz-PRbIS=CBNdB8KnrAQj?CB2y|JtJnX9#Tv#_9~$OPC=GjFB_8VoGtXLy z7c0cp;lKwfdDI6mweJzRVyE9Rvpk{ZjYJ%E3u|#orOkYRRrp_7i#{%k{#@sK)I-Du z11epkM{t?jXHiS7<}`xdq_WSKNDB@A$wHfj zSEWyGqG_+m6a|@w6v#_ut!>aPH0WU(G-{KeTND4#hYQ`}tcd-CP~#4XDGlYBZNZbjW6ikr(F5VvUeZgGos{~&I~-9Hx0#J!-~CmxHq zFN)g}?ycfh$o;ywHFbX=ZlUh0;^uO{A#O$7XT+_S`;oX6bRQ765cePA=5jw#2sh@w zFP=i(cf_r*`)zS6<^ERO3c2&e&E@tMd?Hi)@n89Ni?}iO6>%%zz94R)?zQ5U;NB#k z#G!d0+$V0)?!)rsXW~}Ky-wT;xW)M-_{m%H>7lqWw>X0WFRzPRsQY_y3wN)_Efa+2 z#baT&*bNxJ`9<7{y5AKy=KfvYPRPG~B5noT9&sz^{zv|8oBZ2d`M3Av-^9i|-NM}8 zh+BwT>}Ue$_r)#L{i}R=THG>2+&jcQ%zaJXJ{7lEw^)+}ij(3N?*32S4vJeX_Xcq* zqxj`-{s!aTzQwLvhI<-Ni35 z-9u5i?&0DxQd~xf%V=@Q5SORKWxTjdz$JqenScl5EXMxgG7y&xx6o6RUIXVgjv|c| zKk9_@aNJ$Qr5i38q?F=)syN`Jow#(!#5IF7QT(AAHl%jfz$L>i6i~eSbtzu`E-tya zWVnU$iT4}DHiDbPWiu`rZlQnT{V8l;JKk#-nI|#*=7>#*=7~#*=88 z#*=8H#*=8Q#*=8Z#*=8i#?y^VG+^;4I=5_U!Qx3Y=xl1i;z_jVY--BJlW5b%lW5$= zlW6726B@605d<4G7G<4G7G@gxjVHd!L$Nth(#Nth(@B$`b&*(UKMIxg*1 zrZ82;FNDpq{6bhT%PV2eEU$!hv%C_v&hkoFKJ%+g7((kivWn)Pk&U#x5*E|)O4v`! zD`8E=D=7hCR*fgvS6Tn^kHXR#e-tLycoMePcoIg~coNpwcoJsWcoO#6coK%%coG(y z>R%QwY`5`8VZ@CmVa<&vVb+Z&Vc(4>Vd#w~VdBM;aEh|Y)*Da4)~_CfKMJFpO;%t0 zQ9cRtZ#;>9z<3fJg7GAJ2IEQe4)pZd#iDt=T!>6okIhSrEcSnteRn_=#}{r;=^#xI z5f$tW0ecq^H^T83o*&1f zedTCPm{F~gLmM=~9NuNH43kgCa{4~hsBXIdeax*LfC;^0;8E=!Wx5}9V2G1hW`x6U zB7XZ%q}5?Yj7$ICG`BuzDt-q~WqtK(eeaj!Nrg^CAKd7vc9^3z=I@S=-n$THRPm_w z&tgAJx-bWK{EJ`f*4JCOJ{Lt;4>P(x4iDtHkE6^I3JW)y#Fmr0{i&?sKUnMI@Px$a z@B$(tpCvRt+=wgBuSmFkTIPfY=#_AzHp=jHxG?~qGE|8$x>VRH7Ihtt%ZRq^m8UQm z-=^si#>hN=X@W1mG~vQ8O}OyziOX7j;g=@d@sNp20H%}aj?d(#uA|WmOb`9$0J_ct zytoKZV=*9a3E-XQ0p;=m?VNxb%K$km04-JmhOF{-ldW^1cSBb_0-k z8}Qa0w$Rge$HTi^6MvZIcke+z%>b-;0C@N(TcUY$o$>oB2f6qWG~NCN9C-?}^5;Ct zApV(U@N;rmzz5|3jXeQpyZ|9SfFr(uGC_bZ7={J&M4n%KIlRmeh!R5qjVl8FWVjaz zXcGkptPFTA8t`cqz>%te@iBnCwE%gw0iJnvI6QuX=J3A9onuE`K#fL#oeYEH0lzUc zO$5wt45;4(aH%Pva%;d61_PkqQIO%6%mClO#KkeG9iUzpwqe+l44Bvz@Lo60zq31j z2K4}JV5ry=Fsm0Jp$~^hW>9GZA*wM5&}tOmFvH|jfL|J58bh10fQlJ>I}T85JfL_2 zAR-g6fZ-0ndJ)2^K%V5gRW?-rFci-K6wCxHn+3Qs8}MK*;MP3Ay7??y1lYY8khlc! z9w5WP@q z6vJ~z0p*SX-Z_>B98d)KogwWw;4_A4CjqxV0&M;mko+lN*%`n?hSakhviSyyepVvb zcMh7|V!)`&fa?rvt^ne{1{mJ}qOStZGR(RLIQkRkzwXcYxt7821|Z}Pht10{oa(jr zAsS=={`Uu9;GY1`zW}c?41C15e*-@K2e9TbVC_?QXMIuzaJd}7=?Q4+4VV)E_=%xU zAivS_63@sy#1Rz)*&o4x-@^d&Dgd4^tPTf^js$$o(6JKW4TiQ+fbvxU&okU(7+4i> zi{XPHV_?lt&^MLH7fJym){1*U+mjQ090OSo_101*(aAh4JcO#%=6Cmv+z&9@g3bz7! zyaI^a0eEvK;L|q%=l23m9so>w2k`p)fWC(T!;UZ<1++W{NIwo(asrTZ65#bI;OrT| zkLNh)Wi9{){}1rZMZlCxTs*w0#|60hD~O)?8t~3lz$f1UHeLfbt^?H1Y^zsK9LYD! zVm#mlKz2NhJICQWfDXR^a_<5>?g3^#0sQWR843AedC}1|06$j-0@eoshK2yJW1}ts^c(yIz z*LHw=?E$OuIsnr;0%~;v#B>IMyAA3);)fY$~B!k+=G9s0D@*R%;x;xn~k3l^8l@L0d?jB4le{e zw-m6^33zWAz<&i`^-4hP)qpJw5f~jDI~khdmCtdKq5mep_YB!+YE{}!z?PVSo8qU?{~oQKLHp22Fyh=9FH)M&5$Kzwr%5w^|fw+fHFaVuwXz! zD9geCT`K_ghqD8+D{b`mh&;&FL;*I$0CvOz-l`5bQ3K#r3s9#H;3UJCx_~PTBkKWX z#Q`!C01uh~lA8g-TL4Ph0G4zB)a?XlkPP@=cfh)*IdYVQL|&y2M0uT3fbaDKR2u*o zIEYP3#Ke(|7yoo#1Q+{{ap(AB1YpNVKv6ni<5)mv2jI$Nz|0x!{g*3ub0A8}1;oz> zBye6+o?{DCvIIGA3ClV>&$6qgZ14(*7On)GUc>TBru^#-5KY_&7`PcQbPHhWc0k7+ zfRk^q?FQ3!`)-J0-v`Y705IVQ;Dcj;(361G9|6KY0aQH2@i+bq5Ox-@;XEMeBH#(b z(JuhGmjLs=1f*U8^#2BM{98cLRlu*;0Ih!jg!~A&#c=Z{K=m7dk8c9LzXkaBHlWg7 zz^i}^*)HHFllOuF*^*xYD}Mu&JOq68JK(iH0W%-5@jc0wBMM6`>9V!Jo&~sb-1Wes z>``yPFdx88hFpKZ$Uwk%hSlO2L>Eo~`kn@Scn+}hA|Nm1OJKkiK-M>aO+N#k{KCFlOy5es zLR9$y;Nm}k8D;Rs`=U250Hb4(W}FZJ(X3!V zVk`8B;y7bHM2|KA(q0C1*vU$ChNArYO^E*8#iG3;a;(LQTDk*0rszWtLjTTNfLTY_ z2wl6#OHS~5{`8LkbjJJzb}4>E_Fhu2VL2 zowA?nl8o_aLP`uQ`RJ$vKZl%WqYUW;yUG>+?gk@(oT6@cFKFQ zQ(lOj@;>a8w^*mVdpc#A-6^k)PI=>V%Hpn%6!c!6E&yIv79obJ7w&4%9^)RhGeIV!cG}q zoib?V%jo5l0m>;OlT(Hprwl1h8AS4B$Z$F~lgI;FF7N;l?|uF5GL zlT&&mr*uC~>2aLW)i|XSaY}dKltM<&6oYwd~Vadpx`#`l-<^RY0>%8pz~#`HD7jGowCuIFWap74sOf&(;Y26u;&UQ z%{{p0qT4`=R`rZ-G2Ct)J+RK^=n{y4r>$SO-cjg-+mmSObsY!jnfgY5Z`Vzs{l>R} zG1AgJ+rXG$-F(}?7+c%);qY6=0It_?g`Zv13V$7qYiP7F9oNwt4UG=g&HaW(XX~bA zoYBL&$&WKSS~taUMsMq;W+S7Qbu+V((bc;7sFBSqGTunBG+FUBvm^0FPfJri!KN9W zU<+V>f)Qz&?VxiBMlBb0*PfYTbA@HU?WaV;dWNt(y-T z8~v=C&?ZKA>n6R4Ewmj?jCN*$@8ALty9n6*rK`Yi@FJebZB$8DO_ z)M##of1BQDYP7R%?l!dw{5CahW^}SNx%Qh+n%R8(n%i#rG&j0fKAW0bReqbkX>JR; zMhh#4w<)KE)fjHm`z@>*yG=nYts=Tj87*z0y>7p`-O{MtKxZ2-FL>YK!vpSS{wA;V zYV~KVj-%GCjGkdOi7zh$H=E}{{R)ig1^G7{RIuA8^ZIbNRUY(Ytx=t>Z>iLPuD@L= z#vZ_CUOf(7>_GubVN&>Ur5>TS;H&epa^@1+*4wBd{srMto)MYjvant)PoE@fKCe6P zpwu=-jy>qNc_sS6QlxE|4!Q|tJ1hBxm+~#kE7c919<(~gOd_HPvj@}G35(EW9<*(| z+rl?`YN=qV^D=k(3J={s(Dr`u(VX5kr6ZdH14r$Z?w}e{Rz{S+J+|h&O5O@Z*5F0N zmh^s9G$l=q@(;D=_ZcjrI|fm9dtUv6h7}c~?Gq}gA z`uXscn2Yw`Y*e_#M9MIMrXUY9q%?QrNqug2fLV9{3$K$Y`7Y-#Pt=6V|UTFosHIJ?nK^! zcPf6^?Lpu5;bQG#RHUQ5qJ8ZlDmH0N^ST&GW|52M)4ZuMXE)b&9a2w6hf@4A(ZP0$ z7ue#9-5h6p!K2E4u0j|0Us)No&x}~ji;keaInjQ0|GKOubGHTH)Esh1$=_F0oZ4e@~3{^MMrZ9S8zQ!5=4F8hsl4BQ`wNxzP=gg zs#(!i`Aif8Gp zcHv#5!zU@LyAj9gFna*acz4O?Bpo-EUX)!_B_O_3k|MGBCG<8% z*~RH!LcEu@_BMvvPE4)uP_6kkziRa+lJQZ&CF_M7i zuz%->!?vBSk`H+UPglutu979+cu?wJs1l=(k!VIK3NPN|D}O_tzm}9zKgQSfc#66z zZ~u+FE!}NAT~CXtQA+*nZKz+l<3TBlkS3_h)9O4GZe~?NIEZaS$6)H0V$?E6`0bpa zAFzRF8{sS5$E{B9AFRGY+f$6rX8ns~DsL~o`j;M6f_sMGKd%0b38nervE|L^#B4cl zK>kE2{fr@vZQ=cfElJ0Qzg)#r!kdv=&HIy%DSVIl25ntvBv8th*m|y#7j;+Ow!9il z2L>9$Xj^~7)h~8A9SF5phjP-iHmr8M< zQWpFaQNv2N=o5JJH@^<2VGynEP$R$Q;kN z*%=oD?Mt<2%R*??h?@1yRv{tosRbp7U`JYgkcj8khWIzi9%-bS52lFA@jmz*fUcB2 zyd$nF<#Vo->-1=(G15$#NM2=&!EHFZi4-&WR-!9qqOINt+VzdNk`n3qd$sCQcCG5( zX7a>h2U{dlzf`Nyig-{w#6QMMumx||tVIbqxBRUJASMskq(&ljOtZ>L+u%8QWp0|0)lsbq$Z zqBa#4*7CH+5rs1Wj%lqW5YBjZe6pw+qLI&(pW}##nbfvvxh|@P2Ji zsSA53_<|h^tjW5S6}PM%Ywxrqq}|D|7y=r3lno_O?KpEV5#@xgP`=i!425)ZMN@Tu zEiZcv?{sjm7leUgGdQtYPx2&0)Xe0Pc#dz8>-WYCA$IM<3SL>tGft*&RZ8e+tm{lN-@qJ*C zGr&~^XZZ|Jixl4kSC1qHlla8PU-*P5%?u(ip|17*Ar`)Auoy!xJB(-S zaZhD&{js`MuTQJn(5y4@X+0K7uZ%L}G0I5bcngl)3M`edhzt&O9G9<7dP1j!5PJ|) z$HAb&cpU_#yYBbvD7V?DbC#=SU*p3sx@NJt zh&3?2=Wz!w+6j~v5>vyzn1rZxDA_>-*bh*!R1_F=`V8#J?PeKtTlXM=8o1&?pV(6;F6UiM&LV2cK{XSy-U?%0OUC7muX zgUue;pf24XQr%S*67v-{nYxj?pT<-)wLv8cp4-6cWyECBMwo0PHNzSkMO?TE;(nWL zo_)5}EpL{vSfp=;#Xm1n-$m%!3VSz*qGL}Qc)L19F$v&9Qk|&LETg|YKmGZ{)E-(h z%NS@6@Cb_|Ug3_-Ol-=?hOTLsgjXAah2_(y;yAGQ(W_D+Ze1wK!kq@0c+o=+ZH-c?W9mcgyG% zrUkWbH;l6vZAF|)bF2X9lFxY$x4Ptuxa7;dN8RRI!@7t*Ws^_NO5aN<4R2d-grZ$| z6xs(z^|)B{Bn~S#X!K@l5R0;W)NRKxnP?C!qNzB~n&*ne+icOPNY9hS;@Y2aq1H1l zHvNlW^K+3du5AY!RiW&rx4m353^94gCVh{a9dFv5xcZco)5z1TOfgC2!*z!!aiKBX zE1t3qNw+?N+W9e$mc7aLP)SUiK8CXCr#iior}_Bb z5__awK83{`>a)mtc*OAqKH>M%8Ot#?+*+Fu{co)AbC!qrL|vRuLL2$Gx;rr$h4X=q z_W`<&E1$=$uH*Y$$9w6e#YTpiQIX6mhQ(h$>lekM_u}JZ?qDWXEJj|2#d%t_#F%8Z zMG;?P@q#O5C~qCcDe<&T8N_7u6_`~0+7>nsGxo3>eGQB6$Zx6ftUXcpzk%5QDmj-L zS$274KEQb7D!;RiqNITOuD(oSJHyKH*JMo7>EZFmsyDHj$%h~J{v?wawn;3l{_rQL zEB>s5Nc%9pNojSRpP^p(v!2;Yj(I?;>>AxAhBa*S3qUG>m%xX(rX!;Fy#f7Gcl2y1 z;kRlbl#mh+@JsYFr+;D=jI)@IJ@;Jo_~brrbv?er^$1dvWk!}+k|G&sz~UYHewi`D zF23*w#GPrva$~w(Jm61=f1~@$jk$JlIX>FCmgcN57TU$Hu(&e?tTgf?ZHXB0hywv| zR%unw#+j~xLsC@kZ>Zm;hO3NRvkpc437;2T@R;IO855}RMq;QnLlE`q$51b%?yHTZ z_9U#~v!(ax`f6jQUHrHV#GlfHHO3r!9AA}#c$O!9zZ!8I`=_z1ok$G%d@i+yH_cxM zWpHp4_Y_6cO}wF=NdK-aUB0vV`07QO6UVuHUiLn1 z-C%Sxi$KJWSv)123O5Ww8^(sDKi{bu2fssr_(M^3y2b#{OZckHTfstb7 zR=lpTIDtaQ=xY}z@yT4GDP;7rC*gG#SBawYWOO%s4hf|VpW*$gYFSE{#Y6nGrZp*h zqv2;a39JH>=~dh&ajvE%AuM6_w{(A_(a)ZayDaWZDVwZSP_Z6R72?yhe^coay2;{2 zHMj_xQ}OwxL6rSe)Y1{dp`1#eXVJATK&;& zpHiva$TkMmd(r4+KH}o~gvHZwL|M0ylQnUxYyL8~k)~LTw{}TH(w5IIe-&4jR&_&M zMGKn+Q?-{2*9(Z4T;!9@Aq~sY{4Uxgx}`11*oM%aj&sH6!KavDS&DCAR9fF0Yx}jDm$!D$#N;raoo?KsEcM-Hgv(|UEl7&-E4bCn zz2PW^o%m?=p;Cs0Mzioz@ttOyq?TnVshN)NYL^(F(($FVgh_hqvXtE&`Azt(S>@9D zDSU3bLmRWm)YRq`OU2Na4|9J5_0`UBhdO|Yqni7 z5ZCD7s-&iTj9ga|AE$BnC6%?d>*|<|Ulj43V7QbvZZn$M#ncVr(e&LmqeUfKFgbi2 zy&;aHOXH(el@?WZ%@rlIwop0t4R@uYcm!^>J0It9R2o6K+pQ2qba5n129I)uxcyGo zNK#i?2APE>HshdnT)srxc3|r#=5b3O*U%{1M||}C;0!8$6WY|Y)`3=eiTVT|imy*E zzG78`h+Fds`Qn+BwF_R4YqhdAiA8&zwaqC0Ril|bA<2BA-ghp&^a`A!o3`>Tm5@qv zp)EI0Co`>8EB8C6gjr!8)F0a@TUQ%7gNKXMqFgZjP%K+V!FcG&Cl!7>^Z-UwMZnsyZDQO z)TNa0DndS%*~+U_v1KiVc38gly*j;BX{_Ple(Sk*Y?{k#I&?iBKd(bQfJL-+%S&TFMeD^C1Rkq+PwA5N{) z$(gwIKgqewUqnpCPChr(4_`+e+FSp;jnH1-#HndQ+xE2bF5OTSe?-xj7QAV+x7Swc zOAvoX=ifBi*~MSK4DnW~vdc)ai}!DZxFu!ovc>?(YWG(l_TEvJaz8Yxf|}BZqvxq;!pU4j-z|a((1zqa=~t+8WsJS>|3gY z&+UcHK?>eu^t31P1b+cCj3)1~<^vLl~wn+-np@w02K)MBU;T z)G5bxJ-4scI=EE6()jz7X>@L%(bk^Q#U~(6#}+mBDR~L4{VUn4e+qxf^6(Sg(^1II z4)sg54$n`aK5~Wv4j7FnsZHzu^d4ufdS`WcETG`#H*|8NeJsc07F^c>mSDp zH_S{d52ujREyLqnCf7J4jc>xln$0+VFZR=s7d$&2Iz{$i-nFLe9>o`3~a zOQI-&J<()JdE4l2mb8fH-Gx}un{Qhy@*;lf9>n9GP&z+SY1=y2u%1#; z&v*j$vy}FZwJ|2*hd%haku_{+9Z3=k^r5>`suYOvO7H z7LHtc`CVhM-FrnK#EXJl-hcDNB0m4{1_>YDel~&bc%+OmevV7}BkK9S(bY_iNFpo2qH~lhHSMY2l`b`@_qO8^#%7)3birc}tmC4q8LbPp@ zp-t_o8^YdWhHDxs%B-$XzR+DOf2r8LlyY--DF5xLi)TXm4aG1-vJ;feRZc0ThdRTKa@g55c$Gs7{ zpr8Hbj(-LF1N`p@Xpf94N4wwV0r-dHMx~#RGozsIou;#0bkcC`&PmWC)1aI*rW|GN zfphWqcN)14$BBCG7^tUCFcV05eaavT6BuVM?-tMmxCmRvNK@wnA&|} zt!;?7{7e?lqAl;@F+q{U(gJlS%<3++&1~3wOCFyZ-R-g7WwGZx9cy;euI|?d@d}>@ zb-i4g_aWN#lXhL*=Ql*%Di`XA`CL`5gP0<(Jswfk7(;@YZfbFzZDSY(Y@0~XM6Ok zRze)U+KfKtv{8kM_V@C%o77s(o-oNPL<8B@yRYj!poIG}Yxkbur!kI#=l3p0JT~PTK>)4Nk|Cp6;Q_@+ZjlCE@!cgo;e92u3VRY=Q z;W|$!o*i+pz;Og7+jp1+RdL+JX{BQBw-Y9*uSw!*-}2t2hm|aRz3E7Jod+GWGGO9O z<+uN*v_HfrTaGNSUvs4ue%RY}9#>KkfX{LqTVJ(mw0!A@X8)^DcckIxty7fZmBb$g zucrg&OFv6H-hg=Tn^IETJbWmr*l_I$ieny@GaNzhP-=1M2e=v*dmUdL=3W;s$t`{f zrmAoE_Kq)A8aEHaW-Gp@(NpDeALCX}Y@YDMX8cF^KiOcMoW6d{2&9;XDHUkj<-TF& z97aqAd;*u#V$UKPt>p?c>RLW$DBxs^^?ybUVPRSU*LHwz9Sspw>0#B)*G%! zS{B11-~w&^pV8P{nHPEV1;`bE6HX}wDYaaaL{UG*pG0R;%tfQA*=dS+{`U}H#`l7f z-Q^wVK%ZZdN;%$w(y@<@Uo@(iOIE*f!dl;f*ge%A^b2lvIWgg;a8OZg{ddH=(K2lBlYICb3Azmscp68)|R&?o&~j)K21q6;n= zuJih$O!*zk!as4Y{RVozgkA$G(zVz62U|@}jEeq*(Fs~}$yzoR@&EpY*g@)&wNNAC zIjAbfZBOc`jLH;~QW9;}peX;sSK*Eyd_B#)yvLt~>ykh&`26~dUmC;A!9XNk`J3^Q z^3>rPUUt$Z{ZiL8`ia(qKPE4OkIAJT(`jJ0XnSy>{F!+*d}gjItPAz)KClj*&-$fm zDYJO~5WRVr%dDd|OBy^d$|?t)7MNhIY{6yg8541G1&FtV)56Qx=ga(eU_~>-qTCk_ z<;xMS4ChqDtW4t9(uPa8f*~mn)ItmuO@D;l&&530OHzT9kGa+UJ7OVCAP5e51 z6E7KG(`a}&t)4ch2CY6bD9j$(tNhvgEBI_)hn7MT+P%DAtoIrT?jS522Wn8GZ;bX7 zv*;IV?j+jd{Kfr4iu=a;SV6>|{0)9Y9m@a4=w(k^ZT=$vAVAWV5s&BS8ot#X$Wk4@z{6ZK8h`Dn~gm1ZX{;p$Zh!{+Vd{?#AE{s}YFluT5au zlsbH8bhc-@OEZXnZ*FFKVZT9jD7*TgkWx9Xz!U^g$(-{z+BWo=N~J?qOinP3+F!Fy z)=PwoJ3w5q6K%d`j541Lk=N-2c|fuhR6*PSmQ#JEHaOm$mfyoun3OOml!`kH2{QXw z@xRa=7SB=Pbz`X6SBZEnm=GKv^)`#bv5Bb=bc02wh_|jjp0s5>`l@3F_f`9c#9H+u z`i?2Ef2|)?yMcJ2#$R9kG$hhYw^+Q(j0)uk(Dm=Fb!w4U9RPXfK`d`b`wtEAv-XWe zJzx;jzdqxtqLi?a6$&N~^|1z|5>8!XCStJqLPz6axYdbAABt=Z_0)R<-~M3KF>6m0 zzcY8kx{>bM3#Wu1jhc3oSD|(62eX5;YIHT>l>Ot-Cgz@jgmMg8$5QY<*jiC>{?H1f zGD<3&MK6W~8%JY`{mJNLKCB|{#B33#z!o9?%O_C!_>!)4{k37G5^|a8B*x7!6M{$o zY1hVt1Tq5}$IElfKpbP{;#L>IU((^=RK-m^S=XN%?tZdF(;*j@Rp(Rj&(`-ZB5%YD z71i+Sbi;Zx6?r@pM09wLlDH2_3 z42CfA#%PMVZLL&`IA=S=2{h@pHOCQg(hi6ZQqgUroB8~S_{19=3s^cN7DtsmxYhNy zfz!Ngx7mbWTAEs(3O^cE(R%(wAH&oh_{i;F1C@OL!_-i-fr@g@2T(o($`9Q@54<+K z0tJ6G%8!hjsXpeex)_dUT97x7xw1;>VRs{GwP%{OQzBM}VBqjLNt17*wAAmvSm%C4 z8^VMlc^}b}yGY5Z??#1{PUxzSpf2|b^}EW>OVT1J$&psh)n7^o6_|*`>y)lyn8doq ze$hspf;JWeC7c;5-jQZ~6e8+GXdGqE>VoLtao75CL$sl1p`f(vQOvy3@f-TSL{fa$ zn^at?m(_KOO+O}PDFiW#t=d!KQv+y0*j>+3C0+z0$NsB26EU+&Dww^N1as^vl;6`H z!+H-Eamh7^>(M`k(ZrsxRzE=e)Q>z3Y+=uGF!R8C1#stS+wfHPJHCW@la0RoiN}J< z+(JF+`s|WOdoVYCf<*|JWF#1rTokpNQ&OsEVwq>=?VCC?4M&WwU{Bsh%s*3nODk7p zjxLqc>$jl1OV>+`1pDLj4>Q&H+;x@Xnx(1M#}tz4NT?iZ@9HLR*j8vs)C4 zSJ>jxeKQ1ym%^=nxbf1519NolS8D-OB#W8;CYNF!SPQZuUhx~m*B|O9qp;JM>SoqN zsUAZ4$?sa3{cvMVW0>J9&T(){h1FZe$+V$3v%;uq%UnLuqH8tu)* zi}*uk?CIe{?H=Obb)T{BBLSiv$}B!#($^1-7G}>Z;u|cU400c7;LDrQ!X9JmQqqXA z)OD)97lC zuR9YHMOHQg4B4N7Z?0a<@U@%Nh1RhNtVI$hOj^2*K1#rELgT1yrWo`uOlYKQ>KND5 z2^#sA(ZkHSNX|3c(Gz;_FQd0v+9D2O{-f$`bTsRiH>MJ=agD9*CoyRZt>X~bk#vQ$ zp^(H0u8(TP;50KQ1$E`B2&3XhhU=t;D627}(s$(Zw>3o&@qKVCIp%>{Ndk5B>y2BT z{`WZjU(nRQje+L#Dv|@t!1N^;n8blP`bI#Gs6^5MlG`h_OW3MlT5kO z7QfmG2g@Xw*{t%SzBlpUUw>kKvM7oH%uCg0L#%S`@{4rTCP>e3$WpGQV3A&X5z^q- zXo`obOWB+5THn)%Hijv!`cV}R)yXVN5vMcBRUgXsP+iO;hdPGC5MMm%%J*B$d!_UJ z1*f;>F}m)dT(#mtJ;o?4etuJ>CJ_hFu_J>bcbGVZWuN_$r?BkCi}ptb(uhHM2c ziq+XZ^khqRW!HLxSnObWt*5}QCG8UHNd3HWI+_hv41%F^{C(Lppv1k|ZC$eo(feP4 zeiZ#xR<$rQF5=8@AkL?b<8p@iB9H z>2le^%v{!% zl(%wibc?tbxXiF8(8EVnGar?IIWwM2W9EKT&ho9!>vyc)5Rb#QJVx&JQLZsk6swr| zEQh}JQLf=m#7WGBb`)G_I#2O*Vb!dlnOMzd2!;45*ZPLYBbjUMC2*}t=|5RAC)w4Nih2*Tu)PTuHkUe{ zs=YI(qS-ve&tUOqX;k8^!srOis!sRwyh82a zea$3qKT@@T(&0T|+PB%18K7L>r%QNFCW79sKK{yEB8w$}#VTbq-dp!`CADhb>|b&`ZIpuGvTLWy?Hp4XD6{0$t1t{W~Ak%YfJmE^wvnQ>9upxq_{}bNS=L(*< z;t&;QHak&FW5T_NvlJAnT-)#>ugx5M(O*&T5Cs|)kA*&zR^wi9o|!l?X$Xcs$CGc& zD5pE#7mB;Ojv`zg#{tXzd&`-wOx%X9{At$bInwV$*0 zdL6q~zW3JJmstCHTbDMEY2V~qWUVGvr{ddWchK@ZtJY!zMSsug*2?#nTKgMoU&fc2 zZmoO_sI^yE%O3-}wfJBSq{Uh-A3K%9=V@-WeCwpO_t|;xIlETApwZfQSeu70YTUl^ zfri$8$=XWzV8gAIqxquE6PiOuQ=HXztK}TMcD~Ebe2(6&l>^*byNk6rz-`mY!D_AD zED__NwcA$?=V|S3)~?F?%C1g)!D>F&Sj|V?+|F|1O*><67%Q)(v~o&IYh|DGqlj`g zU)k!^+9&LbtxnPA>8DtBCbjwqtG~sbr90xG%dBMm%39tYbZcdIQ2V-e2W?u}{nJ|6 zP~+V{x9@v-et7-XYT15jjeECRcAvCX*7_et*tN3MueGw`j-`H^?|1G*mvEwasofp2 zthB>74^)S;42`9Bn_5<(b^$fjMZYdR+fUb_9{m_2us6mt*q&4 z?ImdQ99OX1>sHJ1saDGZ43TPq74+E?DLvCskE zJXb$1Z`WEaFRv%?w(WM7cUP^Ix5+Q?R_oTv%cRy8aE|dZY12M%C(C+Aw0!d%@{XvT z<#q3Uyh2)PhrI1+?PCtQ0p9-H+OimT%+_PQ;<>f*hNpeyg$i$YHeY$4`aDlYt}i&~ zns~u-JIiZ@cHY9;NW5mawKDtHTA4@3<88pL9pO%vHJx^AWj3vSzhh!io=)4GWzweA zdeVmJoZDGuXj-dhXqd6NwHw_LThlVPR%T_|S0-7Ql|6;}ceMbSWNEcblBQ$Q<<`m^ zNo(~S39~1+_APhB*1X8Am1&XomB~&Brb(u@0)`)%>}a)~?9kB4s#-lwxoh#4Zn);n z{H4qNvvab>XJxwxc$v?1du0`k|06$IS&eJvSn2l^{)WgAzy}p3<7Rn)p2fuU$Q+w7 zYyHyoqnEB^};oa-JPM)stW!ld1ka4BvPm z@Cq26kvV3SXaJf}OrQy<}rU(zzR1Vxl*AiiF zEtP@0AN5_A+G4V&wu*%iDd~x<=c^;I9-U8t`jak*1p_4C+CZ5yaI zK0EHvH4xoh%@EW$Yp-S*;G&y~A#^k9mpayYj1j5LVL)qP?8@L3@)bck2UI4pS zPDXZC&NTLVxse(I^WPh(R9ptftHHSJjhCSO5>WoPDKkM0!{u~>nuJTUL=^RH+LkDm zf9Ok}#wyC&oT^e*V>QMHCy6kzuK)(fgCRBPabwlomqo~!|0-(NM0NG}gcdhZ6LGoU zL_Lekh^A_ix42yhquAyO8)i*acOB4p1e8=hG?E54Q{7;@rJ1UsHNL@S6!)4bAMIWg zLNP5=q_^Wz7?{XDp~}rwkN>1+b#oPlV0JWDEp-Cwl4lE~R#H)oTD4G>ODAP+3svzy zNjca;Md+kdp&Kn!Z=bI@%L5`jsC=8yC>qpKwG3bpvfOSJo-lgcJ2c8y7_!|~U$#`u zv1b?9N+tQ9)W*p$rYR?JP^+kw3a0t3R0u3qw?b1pNvgG~MM16cP@SYctyOF78%;Y~ zt59uKg)X&LQQEY#*IG`~@Azn2)ufSaR1a?vcnzm1DXKD^YNML@u>@&MUFAm$AEPa1 zw^6awp{=Uvv6jZRRf}-B)mG);GQ1rc|5}>T5AE_&J3J(7XHQ2h|zBhxSKG_H{suSWC=)dStuS~~Cy zvXR?EL`Qp|+gMAnPfOC*=!-{BHAUCcW17`dWx^nMD5}f9mn1c1sH#m1dZ`r1FZ4o> zyq3E6mdml;YBBCIhoOjO^-(?X`|vO%_tX}hlUh`*FFO9UR8VjXlTy}a+`m-6+GIG$7NCOES=JC|>+5@tu=S<9+J~gIuR!&aFWK9cC-w#pY z^i5yY*VedN+uIdq9t|gfen?R<_>I=nfEx9~<0Va~T9CiAj2MZVYZMKt5p-xvd_gm6 zfD0-m9v8HfI9$+38smcY!51`*rnsOb)TGD(sw#e?In<&N15{=FMw_Tkn+M=2kcJUU zUk<>CB(0-9)f}jT@f%G9X9@DeCrV}n`EVZfSAdJFm z2`#1u%^D{Jy3}Quss}Y%30FTF2tR*l5&XDuWALa==?@;7Eg|Orza>l_u9{n2|C?xO zK0FSfLs>}Q4OdOQWK_ta$PucY{=Jokk5Fy&?+f(O2vyf*^VtXti(Y##=sA(8Ad*rcre=W6oYFS2Iuzlk zW`ISe&0@$n6^6Nqgd#-M0E#`LQNQtnn&R z$0x+p42aKO6R-%TfC;X`5Qb`i6=io?F+o+(IE$jO6sH3aiZF&V-fyo z2E;PcmMisDWOPk4S3*Y302`l)&!&$@FF4xN#nJN)?2qBpGuBjhpuhA^ADfo{d)Na46MT@PEsShaFUo$kguDhn)vW<*ndIiCaGc38^T?j zZ(<{q)(l9?a7xcq-Dt$KDu7l_R(=6uA?()e-lU{N6-jABqRZ2QDOez7s}RisEoQ=Y zO;r9_