Change nlpmodels.jl to use ConcreteStructs.jl #51
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Wait to hear from NLPModels developers before merging. |
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Something seems off in this variant. Any chance of an error in porting it from the source @odow? Maybe the new NLPModels sparsity detection does not work with this implementation? Running Current Correctness Check Table
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Same issue with the latest version of the deps, |
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TODO:
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@ccoffrin I think you need to take another look here. I couldn't reproduce this. variables: 5432, 5432, 5432
constraints: 7978, 7978, 7978
This is Ipopt version 3.14.4, running with linear solver ma27.
Number of nonzeros in equality constraint Jacobian...: 22203
Number of nonzeros in inequality constraint Jacobian.: 5478
Number of nonzeros in Lagrangian Hessian.............: 9695
Total number of variables............................: 5432
variables with only lower bounds: 0
variables with lower and upper bounds: 4639
variables with only upper bounds: 0
Total number of equality constraints.................: 5239
Total number of inequality constraints...............: 2739
inequality constraints with only lower bounds: 0
inequality constraints with lower and upper bounds: 913
inequality constraints with only upper bounds: 1826
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
0 2.4542765e+05 6.60e+00 1.08e+02 -1.0 0.00e+00 - 0.00e+00 0.00e+00 0
1 2.5958444e+05 5.99e+00 9.71e+01 -1.0 5.02e+00 - 6.28e-03 9.25e-02h 3
2 2.5712907e+05 5.94e+00 9.61e+01 -1.0 1.99e+01 - 1.40e-02 8.08e-03f 1
3 2.5242837e+05 5.80e+00 9.38e+01 -1.0 1.44e+01 - 2.41e-02 2.28e-02f 1
4 2.4964555e+05 5.62e+00 8.16e+01 -1.0 1.29e+01 - 1.36e-01 3.09e-02f 1
5 2.4950286e+05 5.03e+00 6.52e+01 -1.0 1.27e+01 - 2.02e-01 1.06e-01h 1
6 2.5036292e+05 4.43e+00 3.77e+01 -1.0 4.44e+01 - 4.17e-01 1.19e-01h 2
7 2.5136583e+05 3.68e+00 2.30e+01 -1.0 6.85e+01 - 3.79e-01 1.69e-01h 2
8 2.5268111e+05 2.92e+00 1.31e+01 -1.0 7.69e+01 - 4.53e-01 2.06e-01h 2
9 2.5559875e+05 1.59e+00 5.39e+00 -1.0 8.09e+01 - 9.09e-01 4.56e-01H 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
10 2.5814357e+05 5.50e-01 2.60e+00 -1.0 1.00e+02 - 4.32e-01 6.54e-01H 1
11 2.5909071e+05 3.60e-01 3.93e+00 -1.0 5.50e+01 - 1.48e-01 3.44e-01h 1
12 2.5977126e+05 2.55e-01 2.44e+00 -1.0 5.22e+01 - 3.89e-01 2.93e-01h 1
13 2.6077256e+05 1.08e-01 4.50e+00 -1.0 5.58e+01 - 2.04e-01 6.14e-01h 1
14 2.6145786e+05 2.99e-02 5.01e+00 -1.0 2.52e+01 - 4.13e-01 6.96e-01h 1
15 2.6173819e+05 5.04e-04 3.23e+00 -1.0 1.33e+01 - 5.39e-01 1.00e+00h 1
16 2.6169151e+05 1.43e-04 3.83e-02 -1.0 5.91e+00 - 1.00e+00 1.00e+00h 1
17 2.6118346e+05 2.63e-03 9.11e-01 -2.5 4.33e+00 - 4.31e-01 3.61e-01f 1
18 2.6072168e+05 5.93e-03 1.61e+00 -2.5 2.67e+00 - 3.63e-01 5.71e-01f 1
19 2.6047647e+05 4.95e-03 1.30e+00 -2.5 1.84e+00 - 4.83e-01 5.82e-01f 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
20 2.6038677e+05 5.26e-02 9.50e-01 -2.5 1.44e+00 - 7.34e-01 4.11e-01h 1
21 2.6028377e+05 3.97e-03 1.02e+00 -2.5 1.78e+00 - 1.00e+00 6.67e-01h 1
22 2.6024420e+05 2.16e-03 1.06e+00 -2.5 7.58e-01 - 1.00e+00 7.39e-01h 1
23 2.6023929e+05 5.90e-04 1.97e-02 -2.5 1.81e-01 - 1.00e+00 9.96e-01h 1
24 2.6021622e+05 4.24e-04 1.48e+00 -3.8 2.43e-01 - 6.47e-01 5.09e-01f 1
25 2.6020604e+05 1.09e-03 5.97e-01 -3.8 1.59e-01 - 4.81e-01 5.81e-01h 1
26 2.6020252e+05 4.10e-04 6.11e+00 -3.8 1.27e-01 - 3.10e-01 5.53e-01h 1
27 2.6019979e+05 2.16e-04 6.84e-01 -3.8 7.88e-02 - 9.63e-01 8.97e-01h 1
28 2.6019955e+05 1.79e-05 2.05e-04 -3.8 4.63e-02 - 1.00e+00 1.00e+00h 1
29 2.6019885e+05 1.95e-05 7.18e-01 -5.7 8.08e-02 - 8.74e-01 3.96e-01h 1
iter objective inf_pr inf_du lg(mu) ||d|| lg(rg) alpha_du alpha_pr ls
30 2.6019819e+05 3.04e-05 5.80e-01 -5.7 8.47e-02 - 8.53e-01 6.49e-01h 1
31 2.6019789e+05 1.63e-05 2.07e-01 -5.7 4.77e-02 - 1.00e+00 9.24e-01h 1
32 2.6019787e+05 7.90e-07 1.11e-03 -5.7 1.11e-02 - 1.00e+00 1.00e+00h 1
33 2.6019787e+05 1.85e-08 1.89e-05 -5.7 7.21e-04 - 1.00e+00 1.00e+00h 1
34 2.6019787e+05 5.33e-11 8.96e-10 -5.7 3.29e-05 - 1.00e+00 1.00e+00h 1
35 2.6019785e+05 1.02e-07 5.09e-02 -8.6 4.01e-03 - 9.94e-01 9.52e-01f 1
36 2.6019785e+05 3.30e-09 4.19e-06 -8.6 3.57e-04 - 1.00e+00 1.00e+00h 1
37 2.6019785e+05 2.36e-12 2.71e-10 -8.6 6.60e-06 - 1.00e+00 1.00e+00h 1
Number of Iterations....: 37
(scaled) (unscaled)
Objective...............: 3.5138129355658789e+03 2.6019784787865335e+05
Dual infeasibility......: 2.7073821764503351e-10 2.0048165016614731e-08
Constraint violation....: 1.9260149031197216e-12 2.3576973706695981e-12
Variable bound violation: 1.0894180668685749e-07 1.0894180668685749e-07
Complementarity.........: 2.5109936211354074e-09 1.8593907764507692e-07
Overall NLP error.......: 2.5109936211354074e-09 1.8593907764507692e-07
Number of objective function evaluations = 54
Number of objective gradient evaluations = 38
Number of equality constraint evaluations = 54
Number of inequality constraint evaluations = 54
Number of equality constraint Jacobian evaluations = 38
Number of inequality constraint Jacobian evaluations = 38
Number of Lagrangian Hessian evaluations = 37
Total seconds in IPOPT = 17.351
EXIT: Optimal Solution Found.
Summary
case........: data/pglib_opf_case793_goc.m
variables...: 5432
constraints.: 7978
feasible....: true
cost........: 260198
total time..: 45.31116199493408
data time.: 0.1353919506072998
build time: 27.82262921333313
solve time: 17.353139877319336
Dict{String, Any} with 10 entries:
"cost" => 2.60198e5
"variables" => 5432
"constraints" => 7978
"case" => "data/pglib_opf_case793_goc.m"
"time_total" => 45.3112
"time_build" => 27.8226
"solution" => Dict("p_775_11_54"=>0.147535, "p_279_311_279"=>-0.0537034, "va_765"=>-0.327553, "vm_304"=>1.04048, "p_290_301_287"=…
"time_solve" => 17.3531
"time_data" => 0.135392
"feasible" => trueCan you double check the error log for the first failing case? |
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Good to know! What OS were you testing on? |
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Intel MacOS. Using HSL from https://licences.stfc.ac.uk/product/libhsl |
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I think the linear solver issue is a red herring. I tried re-running with mumps, there were no crashes but time outs at mine shows, This is the exact file I am using, https://github.com/lanl-ansi/rosetta-opf/blob/cli-testing/variants/nlpmodels-cs.jl, maybe it is somehow different from the one you are using? |
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What is |
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Ah. I can reproduce with the current https://github.com/lanl-ansi/rosetta-opf/tree/7afb335764408e1d217799de30af0793ca997d83 So I guess some recent version broke sparsity detection? |
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Ok mystery solved. I did a diff with your version and mine and the difference was Data collection is underway! |
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Oh. I didn't even think to consider the new package extensions. This is one downside to automagical behavior happening if you use the right set of packages... |
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Agreed! |
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Here are the "total runtime" results I am getting now. These now seem correct to me, do you agree?
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Yes, that's more or less what I expected.
…On Thu, 1 Feb 2024, 6:20 pm Carleton Coffrin, ***@***.***> wrote:
Here are the "total runtime" results I am getting now. These now seem
correct to me, do you agree?
Case Vars Cons NLPModels NLPModels-CS
case3_lmbd 24 28 5.10e-02 2.89e-02
case5_pjm 44 53 1.58e-01 1.15e-01
case14_ieee 118 169 2.73e-01 1.99e-01
case24_ieee_rts 266 315 7.72e-01 5.81e-01
case30_ieee 236 348 7.03e-01 5.00e-01
case30_as 236 348 6.32e-01 5.69e-01
case39_epri 282 401 6.59e-01 4.05e-01
case57_ieee 448 675 1.05e+00 1.09e+00
case60_c 518 737 1.84e+00 9.22e-01
case73_ieee_rts 824 987 2.56e+00 1.53e+00
case89_pegase 1042 1649 6.96e+00 3.84e+00
case118_ieee 1088 1539 5.36e+00 2.45e+00
case162_ieee_dtc 1484 2313 6.69e+00 4.50e+00
case179_goc 1468 2200 9.79e+00 4.63e+00
case197_snem 1608 2397 6.88e+00 4.47e+00
case200_activ 1456 2116 5.47e+00 3.57e+00
case240_pserc 2558 3617 5.16e+01 1.82e+01
case300_ieee 2382 3478 1.22e+01 7.64e+00
case500_goc 4254 6097 3.01e+01 1.84e+01
case588_sdet 4110 5979 2.31e+01 1.56e+01
case793_goc 5432 7978 3.80e+01 2.64e+01
case1354_pegase 11192 16646 1.61e+02 1.12e+02
case1803_snem 15246 23172 3.37e+02 2.03e+02
case1888_rte 14480 21494 5.32e+02 N.D.
case1951_rte 15018 22075 3.30e+02 2.26e+02
case2000_goc 19008 29432 4.05e+02 3.30e+02
case2312_goc 17128 25716 3.14e+02 2.16e+02
case2383wp_k 17004 25039 2.76e+02 1.95e+02
case2736sp_k 19088 28356 3.04e+02 2.48e+02
case2737sop_k 18988 28358 2.89e+02 2.40e+02
case2742_goc 24540 38196 1.12e+03 7.05e+02
case2746wp_k 19520 28446 3.13e+02 2.45e+02
case2746wop_k 19582 28642 N.D. 2.56e+02
case2848_rte 21822 32129 6.41e+02 4.26e+02
case2853_sdet 23028 33154 8.73e+02 5.33e+02
case2868_rte 22090 32393 7.12e+02 4.80e+02
case2869_pegase 25086 37813 8.32e+02 6.72e+02
case3012wp_k 21082 31029 4.36e+02 3.44e+02
case3022_goc 23238 34990 7.99e+02 5.53e+02
case3120sp_k 21608 32092 4.61e+02 3.69e+02
case3375wp_k 24350 35876 6.49e+02 5.33e+02
case3970_goc 35270 54428 1.97e+03 1.53e+03
case4020_goc 36696 56957 2.07e+03 1.62e+03
case4601_goc 38814 59596 2.30e+03 1.95e+03
case4619_goc 42532 66289 2.47e+03 2.30e+03
case4661_sdet 34758 51302 1.51e+03 1.24e+03
case4837_goc 41398 64030 2.24e+03 2.05e+03
case4917_goc 37872 56917 2.12e+03 1.68e+03
case5658_epigrids 48552 74821 3.41e+03 3.04e+03
case6468_rte 49734 75937 4.18e+03 3.36e+03
case6470_rte 50482 75976 3.70e+03 3.24e+03
case6495_rte 50426 76124 4.59e+03 3.70e+03
case6515_rte 50546 76290 4.20e+03 3.40e+03
case7336_epigrids 62116 95306 5.35e+03 5.04e+03
case8387_pegase 78748 118702 N.D. N.D.
case9241_pegase 85568 130826 N.D. N.D.
case9591_goc 83572 130588 N.D. N.D.
case10000_goc 76804 112352 N.D. N.D.
case10192_epigrids 89850 139456 N.D. N.D.
case10480_goc 96750 150874 N.D. N.D.
case13659_pegase 117370 170588 N.D. N.D.
case19402_goc 179562 281733 N.D. N.D.
case20758_epigrids 179236 274918 N.D. N.D.
case24464_goc 203374 313641 N.D. N.D.
case30000_goc 208624 307752 N.D. N.D.
case78484_epigrids 674562 1039062 N.D. N.D.
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There's an argument for it to be the default since it looks faster across the board. But I guess it doesn't solve any new cases, so it's the same order of magnitude in performance. |
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Closes #50