auto-generating sphinx docs

pytorch · Nov 20, 2024 · 5630453 · 5630453
1 parent bb88a0b
commit 5630453
Show file tree

Hide file tree

Showing 30 changed files with 557 additions and 558 deletions.
diff --git a/main/_downloads/0935354946f64f2fcf766478aa4572c3/tensordict_module.zip b/main/_downloads/0935354946f64f2fcf766478aa4572c3/tensordict_module.zip
diff --git a/main/_downloads/150528e38f6816824f1e81ed67476a9f/export.zip b/main/_downloads/150528e38f6816824f1e81ed67476a9f/export.zip
diff --git a/main/_downloads/30cf47ff46cc4701c97ed46f4d91a0f2/tensordict_keys.zip b/main/_downloads/30cf47ff46cc4701c97ed46f4d91a0f2/tensordict_keys.zip
diff --git a/main/_downloads/315c4c52fb68082a731b192d944e2ede/tutorials_python.zip b/main/_downloads/315c4c52fb68082a731b192d944e2ede/tutorials_python.zip
diff --git a/main/_downloads/5b6beccb0b7dcf81c69b35cec5a445ee/tensorclass_imagenet.zip b/main/_downloads/5b6beccb0b7dcf81c69b35cec5a445ee/tensorclass_imagenet.zip
diff --git a/main/_downloads/71264da051c82d595130ca8e60350024/tensordict_shapes.zip b/main/_downloads/71264da051c82d595130ca8e60350024/tensordict_shapes.zip
diff --git a/main/_downloads/777fb49680f0121bef451f089b823d24/tensorclass_fashion.zip b/main/_downloads/777fb49680f0121bef451f089b823d24/tensorclass_fashion.zip
diff --git a/main/_downloads/89ddb148138028541dafab3ced0e0421/tensordict_memory.zip b/main/_downloads/89ddb148138028541dafab3ced0e0421/tensordict_memory.zip
diff --git a/main/_downloads/a3a53a08487286803e7e9713be78fb54/tensordict_preallocation.zip b/main/_downloads/a3a53a08487286803e7e9713be78fb54/tensordict_preallocation.zip
diff --git a/main/_downloads/a5659940aa3f8f568547d47752a43172/tutorials_jupyter.zip b/main/_downloads/a5659940aa3f8f568547d47752a43172/tutorials_jupyter.zip
diff --git a/main/_downloads/bddca9d9cab285e6fedc82c7769291ef/data_fashion.zip b/main/_downloads/bddca9d9cab285e6fedc82c7769291ef/data_fashion.zip
diff --git a/main/_downloads/c1f74b953ed757c75e2d2bc64666eae1/streamed_tensordict.zip b/main/_downloads/c1f74b953ed757c75e2d2bc64666eae1/streamed_tensordict.zip
diff --git a/main/_downloads/c1fc5aa7548e6b1437d36fb47bc36ce5/tensordict_slicing.zip b/main/_downloads/c1fc5aa7548e6b1437d36fb47bc36ce5/tensordict_slicing.zip
diff --git a/main/_sources/sg_execution_times.rst.txt b/main/_sources/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:29.309** total execution time for 11 files **from all galleries**:
+**02:31.162** total execution time for 11 files **from all galleries**:
 
 .. container::
 
@@ -33,22 +33,22 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``reference/generated/tutorials/tensorclass_fashion.py``)
-     - 01:00.956
+     - 01:01.798
      - 0.0
    * - :ref:`sphx_glr_tutorials_data_fashion.py` (``reference/generated/tutorials/data_fashion.py``)
-     - 00:55.544
+     - 00:56.658
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_module.py` (``reference/generated/tutorials/tensordict_module.py``)
-     - 00:18.394
+     - 00:18.309
      - 0.0
    * - :ref:`sphx_glr_tutorials_streamed_tensordict.py` (``reference/generated/tutorials/streamed_tensordict.py``)
      - 00:11.022
      - 0.0
    * - :ref:`sphx_glr_tutorials_export.py` (``reference/generated/tutorials/export.py``)
-     - 00:01.693
+     - 00:01.717
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``reference/generated/tutorials/tensorclass_imagenet.py``)
-     - 00:01.672
+     - 00:01.630
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_keys.py` (``reference/generated/tutorials/tensordict_keys.py``)
      - 00:00.009

diff --git a/main/_sources/tutorials/data_fashion.rst.txt b/main/_sources/tutorials/data_fashion.rst.txt
@@ -423,164 +423,164 @@ adjust how we unpack the data to the more explicit key-based retrieval offered b
         is_shared=False)
     Epoch 1
     -------------------------
-    loss: 2.305232 [    0/60000]
-    loss: 2.297159 [ 6400/60000]
-    loss: 2.271554 [12800/60000]
-    loss: 2.272121 [19200/60000]
-    loss: 2.256718 [25600/60000]
-    loss: 2.222476 [32000/60000]
-    loss: 2.231866 [38400/60000]
-    loss: 2.196255 [44800/60000]
-    loss: 2.195788 [51200/60000]
-    loss: 2.167713 [57600/60000]
+    loss: 2.290581 [    0/60000]
+    loss: 2.286891 [ 6400/60000]
+    loss: 2.273570 [12800/60000]
+    loss: 2.269265 [19200/60000]
+    loss: 2.237093 [25600/60000]
+    loss: 2.216887 [32000/60000]
+    loss: 2.224329 [38400/60000]
+    loss: 2.194690 [44800/60000]
+    loss: 2.178041 [51200/60000]
+    loss: 2.161001 [57600/60000]
     Test Error: 
-     Accuracy: 47.7%, Avg loss: 2.164033 
+     Accuracy: 48.1%, Avg loss: 2.150304 
 
     Epoch 2
     -------------------------
-    loss: 2.173898 [    0/60000]
-    loss: 2.164319 [ 6400/60000]
-    loss: 2.103429 [12800/60000]
-    loss: 2.122802 [19200/60000]
-    loss: 2.074486 [25600/60000]
-    loss: 2.019262 [32000/60000]
-    loss: 2.042092 [38400/60000]
-    loss: 1.968997 [44800/60000]
-    loss: 1.970591 [51200/60000]
-    loss: 1.894359 [57600/60000]
+    loss: 2.148992 [    0/60000]
+    loss: 2.148512 [ 6400/60000]
+    loss: 2.093856 [12800/60000]
+    loss: 2.114375 [19200/60000]
+    loss: 2.048381 [25600/60000]
+    loss: 1.995552 [32000/60000]
+    loss: 2.024051 [38400/60000]
+    loss: 1.949065 [44800/60000]
+    loss: 1.939681 [51200/60000]
+    loss: 1.883461 [57600/60000]
     Test Error: 
-     Accuracy: 58.2%, Avg loss: 1.899916 
+     Accuracy: 61.1%, Avg loss: 1.876278 
 
     Epoch 3
     -------------------------
-    loss: 1.934343 [    0/60000]
-    loss: 1.898834 [ 6400/60000]
-    loss: 1.782747 [12800/60000]
-    loss: 1.826773 [19200/60000]
-    loss: 1.711670 [25600/60000]
-    loss: 1.671944 [32000/60000]
-    loss: 1.682947 [38400/60000]
-    loss: 1.591902 [44800/60000]
-    loss: 1.611233 [51200/60000]
-    loss: 1.500505 [57600/60000]
+    loss: 1.901713 [    0/60000]
+    loss: 1.876635 [ 6400/60000]
+    loss: 1.761282 [12800/60000]
+    loss: 1.806257 [19200/60000]
+    loss: 1.685305 [25600/60000]
+    loss: 1.650352 [32000/60000]
+    loss: 1.670475 [38400/60000]
+    loss: 1.584860 [44800/60000]
+    loss: 1.595296 [51200/60000]
+    loss: 1.497225 [57600/60000]
     Test Error: 
-     Accuracy: 63.0%, Avg loss: 1.525353 
+     Accuracy: 61.4%, Avg loss: 1.511452 
 
     Epoch 4
     -------------------------
-    loss: 1.593073 [    0/60000]
-    loss: 1.552191 [ 6400/60000]
-    loss: 1.404746 [12800/60000]
-    loss: 1.479431 [19200/60000]
-    loss: 1.353328 [25600/60000]
-    loss: 1.361179 [32000/60000]
-    loss: 1.359402 [38400/60000]
-    loss: 1.293564 [44800/60000]
-    loss: 1.320479 [51200/60000]
-    loss: 1.222734 [57600/60000]
+    loss: 1.579002 [    0/60000]
+    loss: 1.542169 [ 6400/60000]
+    loss: 1.396247 [12800/60000]
+    loss: 1.467509 [19200/60000]
+    loss: 1.343532 [25600/60000]
+    loss: 1.349106 [32000/60000]
+    loss: 1.360322 [38400/60000]
+    loss: 1.301135 [44800/60000]
+    loss: 1.322779 [51200/60000]
+    loss: 1.223910 [57600/60000]
     Test Error: 
-     Accuracy: 63.8%, Avg loss: 1.251255 
+     Accuracy: 63.4%, Avg loss: 1.249254 
 
     Epoch 5
     -------------------------
-    loss: 1.328827 [    0/60000]
-    loss: 1.307526 [ 6400/60000]
-    loss: 1.142457 [12800/60000]
-    loss: 1.252452 [19200/60000]
-    loss: 1.122104 [25600/60000]
-    loss: 1.157318 [32000/60000]
-    loss: 1.163311 [38400/60000]
-    loss: 1.109698 [44800/60000]
-    loss: 1.139067 [51200/60000]
-    loss: 1.063154 [57600/60000]
+    loss: 1.328406 [    0/60000]
+    loss: 1.305376 [ 6400/60000]
+    loss: 1.143668 [12800/60000]
+    loss: 1.248375 [19200/60000]
+    loss: 1.120490 [25600/60000]
+    loss: 1.149636 [32000/60000]
+    loss: 1.167744 [38400/60000]
+    loss: 1.123314 [44800/60000]
+    loss: 1.150277 [51200/60000]
+    loss: 1.062340 [57600/60000]
     Test Error: 
-     Accuracy: 65.0%, Avg loss: 1.084257 
+     Accuracy: 65.1%, Avg loss: 1.085596 
 
-    TensorDict training done! time:  8.5984 s
+    TensorDict training done! time:  8.6199 s
     Epoch 1
     -------------------------
-    loss: 2.303763 [    0/60000]
-    loss: 2.287339 [ 6400/60000]
-    loss: 2.266011 [12800/60000]
-    loss: 2.263364 [19200/60000]
-    loss: 2.243959 [25600/60000]
-    loss: 2.220486 [32000/60000]
-    loss: 2.227837 [38400/60000]
-    loss: 2.191855 [44800/60000]
-    loss: 2.190338 [51200/60000]
-    loss: 2.163693 [57600/60000]
+    loss: 2.299586 [    0/60000]
+    loss: 2.286984 [ 6400/60000]
+    loss: 2.270827 [12800/60000]
+    loss: 2.271013 [19200/60000]
+    loss: 2.237875 [25600/60000]
+    loss: 2.211051 [32000/60000]
+    loss: 2.227083 [38400/60000]
+    loss: 2.185654 [44800/60000]
+    loss: 2.187123 [51200/60000]
+    loss: 2.149412 [57600/60000]
     Test Error: 
-     Accuracy: 51.8%, Avg loss: 2.149941 
+     Accuracy: 33.3%, Avg loss: 2.149881 
 
     Epoch 2
     -------------------------
-    loss: 2.161630 [    0/60000]
-    loss: 2.147131 [ 6400/60000]
-    loss: 2.088360 [12800/60000]
-    loss: 2.105620 [19200/60000]
-    loss: 2.050159 [25600/60000]
-    loss: 1.999371 [32000/60000]
-    loss: 2.023862 [38400/60000]
-    loss: 1.943276 [44800/60000]
-    loss: 1.949624 [51200/60000]
-    loss: 1.879305 [57600/60000]
+    loss: 2.160917 [    0/60000]
+    loss: 2.152675 [ 6400/60000]
+    loss: 2.097842 [12800/60000]
+    loss: 2.114376 [19200/60000]
+    loss: 2.063478 [25600/60000]
+    loss: 1.999019 [32000/60000]
+    loss: 2.033733 [38400/60000]
+    loss: 1.951877 [44800/60000]
+    loss: 1.956176 [51200/60000]
+    loss: 1.878581 [57600/60000]
     Test Error: 
-     Accuracy: 59.1%, Avg loss: 1.868419 
+     Accuracy: 60.6%, Avg loss: 1.883789 
 
     Epoch 3
     -------------------------
-    loss: 1.909543 [    0/60000]
-    loss: 1.870345 [ 6400/60000]
-    loss: 1.754877 [12800/60000]
-    loss: 1.790990 [19200/60000]
-    loss: 1.679816 [25600/60000]
-    loss: 1.647892 [32000/60000]
-    loss: 1.664084 [38400/60000]
-    loss: 1.568835 [44800/60000]
-    loss: 1.592446 [51200/60000]
-    loss: 1.484370 [57600/60000]
+    loss: 1.917881 [    0/60000]
+    loss: 1.883869 [ 6400/60000]
+    loss: 1.773422 [12800/60000]
+    loss: 1.810349 [19200/60000]
+    loss: 1.701248 [25600/60000]
+    loss: 1.658187 [32000/60000]
+    loss: 1.676271 [38400/60000]
+    loss: 1.578213 [44800/60000]
+    loss: 1.599073 [51200/60000]
+    loss: 1.489316 [57600/60000]
     Test Error: 
-     Accuracy: 62.0%, Avg loss: 1.497423 
+     Accuracy: 61.7%, Avg loss: 1.511110 
 
     Epoch 4
     -------------------------
-    loss: 1.572861 [    0/60000]
-    loss: 1.531931 [ 6400/60000]
-    loss: 1.385219 [12800/60000]
-    loss: 1.447990 [19200/60000]
-    loss: 1.330326 [25600/60000]
-    loss: 1.338316 [32000/60000]
-    loss: 1.351982 [38400/60000]
-    loss: 1.277673 [44800/60000]
-    loss: 1.306639 [51200/60000]
-    loss: 1.210335 [57600/60000]
+    loss: 1.578337 [    0/60000]
+    loss: 1.535447 [ 6400/60000]
+    loss: 1.393195 [12800/60000]
+    loss: 1.463076 [19200/60000]
+    loss: 1.341187 [25600/60000]
+    loss: 1.347338 [32000/60000]
+    loss: 1.359601 [38400/60000]
+    loss: 1.280939 [44800/60000]
+    loss: 1.317099 [51200/60000]
+    loss: 1.215931 [57600/60000]
     Test Error: 
-     Accuracy: 64.2%, Avg loss: 1.230649 
+     Accuracy: 63.2%, Avg loss: 1.242755 
 
     Epoch 5
     -------------------------
-    loss: 1.308729 [    0/60000]
-    loss: 1.291877 [ 6400/60000]
-    loss: 1.127098 [12800/60000]
-    loss: 1.227528 [19200/60000]
-    loss: 1.103063 [25600/60000]
-    loss: 1.134138 [32000/60000]
-    loss: 1.163607 [38400/60000]
-    loss: 1.096929 [44800/60000]
-    loss: 1.129998 [51200/60000]
-    loss: 1.052666 [57600/60000]
+    loss: 1.317992 [    0/60000]
+    loss: 1.292555 [ 6400/60000]
+    loss: 1.136438 [12800/60000]
+    loss: 1.241214 [19200/60000]
+    loss: 1.114374 [25600/60000]
+    loss: 1.147638 [32000/60000]
+    loss: 1.168797 [38400/60000]
+    loss: 1.099635 [44800/60000]
+    loss: 1.142753 [51200/60000]
+    loss: 1.059056 [57600/60000]
     Test Error: 
-     Accuracy: 65.3%, Avg loss: 1.067841 
+     Accuracy: 64.7%, Avg loss: 1.079772 
 
-    Training done! time:  34.8498 s
+    Training done! time:  35.3950 s
 
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 55.544 seconds)
+   **Total running time of the script:** (0 minutes 56.658 seconds)
 
 
 .. _sphx_glr_download_tutorials_data_fashion.py:

diff --git a/main/_sources/tutorials/export.rst.txt b/main/_sources/tutorials/export.rst.txt
@@ -141,7 +141,7 @@ Let us run this model and see what the output looks like:
 
  .. code-block:: none
 
-    (tensor([[0.0000, 0.0000, 0.0491, 0.1301]], grad_fn=<ReluBackward0>), tensor([[ 0.0382, -0.4824,  0.0123,  0.4426]], grad_fn=<AddmmBackward0>), tensor([[ 0.0382, -0.4824]], grad_fn=<SplitBackward0>), tensor([[1.0077, 1.3000]], grad_fn=<ClampMinBackward0>), tensor([[ 0.0382, -0.4824]], grad_fn=<SplitBackward0>))
+    (tensor([[0.7307, 0.0000, 0.0000, 1.7378]], grad_fn=<ReluBackward0>), tensor([[-1.1394,  0.1979,  0.3784, -1.2743]], grad_fn=<AddmmBackward0>), tensor([[-1.1394,  0.1979]], grad_fn=<SplitBackward0>), tensor([[1.2539, 0.3973]], grad_fn=<ClampMinBackward0>), tensor([[-1.1394,  0.1979]], grad_fn=<SplitBackward0>))
 
 
 
@@ -266,8 +266,8 @@ This module can be run exactly like our original module (with a lower overhead):
 
  .. code-block:: none
 
-    Time for TDModule:  488.04 micro-seconds
-    Time for exported module:  353.81 micro-seconds
+    Time for TDModule:  549.79 micro-seconds
+    Time for exported module:  373.36 micro-seconds
 
 
 
@@ -450,7 +450,7 @@ distribution:
 
  .. code-block:: none
 
-    tensor([[ 0.0382, -0.4824]], grad_fn=<SplitBackward0>)
+    tensor([[-1.1394,  0.1979]], grad_fn=<SplitBackward0>)
 
 
 
@@ -655,7 +655,7 @@ Next steps and further reading
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.693 seconds)
+   **Total running time of the script:** (0 minutes 1.717 seconds)
 
 
 .. _sphx_glr_download_tutorials_export.py:

diff --git a/main/_sources/tutorials/sg_execution_times.rst.txt b/main/_sources/tutorials/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:29.309** total execution time for 11 files **from tutorials**:
+**02:31.162** total execution time for 11 files **from tutorials**:
 
 .. container::
 
@@ -33,22 +33,22 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``tensorclass_fashion.py``)
-     - 01:00.956
+     - 01:01.798
      - 0.0
    * - :ref:`sphx_glr_tutorials_data_fashion.py` (``data_fashion.py``)
-     - 00:55.544
+     - 00:56.658
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_module.py` (``tensordict_module.py``)
-     - 00:18.394
+     - 00:18.309
      - 0.0
    * - :ref:`sphx_glr_tutorials_streamed_tensordict.py` (``streamed_tensordict.py``)
      - 00:11.022
      - 0.0
    * - :ref:`sphx_glr_tutorials_export.py` (``export.py``)
-     - 00:01.693
+     - 00:01.717
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``tensorclass_imagenet.py``)
-     - 00:01.672
+     - 00:01.630
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_keys.py` (``tensordict_keys.py``)
      - 00:00.009