auto-generating sphinx docs

pytorch · Jan 18, 2024 · 36ed339 · 36ed339
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diff --git a/_downloads/315c4c52fb68082a731b192d944e2ede/tutorials_python.zip b/_downloads/315c4c52fb68082a731b192d944e2ede/tutorials_python.zip
diff --git a/_downloads/a5659940aa3f8f568547d47752a43172/tutorials_jupyter.zip b/_downloads/a5659940aa3f8f568547d47752a43172/tutorials_jupyter.zip
diff --git a/_sources/sg_execution_times.rst.txt b/_sources/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:00.319** total execution time for 10 files **from all galleries**:
+**02:13.623** total execution time for 10 files **from all galleries**:
 
 .. container::
 
@@ -33,30 +33,30 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``reference/generated/tutorials/tensorclass_fashion.py``)
-     - 00:58.037
+     - 01:11.644
      - 0.0
    * - :ref:`sphx_glr_tutorials_data_fashion.py` (``reference/generated/tutorials/data_fashion.py``)
-     - 00:50.536
+     - 00:50.236
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_module.py` (``reference/generated/tutorials/tensordict_module.py``)
-     - 00:10.137
+     - 00:10.135
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``reference/generated/tutorials/tensorclass_imagenet.py``)
-     - 00:01.551
+     - 00:01.549
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_memory.py` (``reference/generated/tutorials/tensordict_memory.py``)
      - 00:00.024
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_keys.py` (``reference/generated/tutorials/tensordict_keys.py``)
-     - 00:00.010
+     - 00:00.009
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_shapes.py` (``reference/generated/tutorials/tensordict_shapes.py``)
      - 00:00.008
      - 0.0
-   * - :ref:`sphx_glr_tutorials_tensordict_module_functional.py` (``reference/generated/tutorials/tensordict_module_functional.py``)
+   * - :ref:`sphx_glr_tutorials_tensordict_slicing.py` (``reference/generated/tutorials/tensordict_slicing.py``)
      - 00:00.007
      - 0.0
-   * - :ref:`sphx_glr_tutorials_tensordict_slicing.py` (``reference/generated/tutorials/tensordict_slicing.py``)
+   * - :ref:`sphx_glr_tutorials_tensordict_module_functional.py` (``reference/generated/tutorials/tensordict_module_functional.py``)
      - 00:00.007
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_preallocation.py` (``reference/generated/tutorials/tensordict_preallocation.py``)

diff --git a/_sources/tutorials/data_fashion.rst.txt b/_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: 2.302349 [    0/60000]
-    loss: 2.292155 [ 6400/60000]
-    loss: 2.279292 [12800/60000]
-    loss: 2.269905 [19200/60000]
-    loss: 2.253458 [25600/60000]
-    loss: 2.229287 [32000/60000]
-    loss: 2.236283 [38400/60000]
-    loss: 2.200288 [44800/60000]
-    loss: 2.191704 [51200/60000]
-    loss: 2.176368 [57600/60000]
+    loss: 2.319057 [    0/60000]
+    loss: 2.307515 [ 6400/60000]
+    loss: 2.288502 [12800/60000]
+    loss: 2.271761 [19200/60000]
+    loss: 2.253284 [25600/60000]
+    loss: 2.229653 [32000/60000]
+    loss: 2.229388 [38400/60000]
+    loss: 2.203920 [44800/60000]
+    loss: 2.205996 [51200/60000]
+    loss: 2.154903 [57600/60000]
     Test Error: 
-     Accuracy: 47.5%, Avg loss: 2.160954 
+     Accuracy: 42.8%, Avg loss: 2.164313 
 
     Epoch 2
     -------------------------
-    loss: 2.168418 [    0/60000]
-    loss: 2.163257 [ 6400/60000]
-    loss: 2.107832 [12800/60000]
-    loss: 2.119736 [19200/60000]
-    loss: 2.074077 [25600/60000]
-    loss: 2.019675 [32000/60000]
-    loss: 2.051974 [38400/60000]
-    loss: 1.967863 [44800/60000]
-    loss: 1.974587 [51200/60000]
-    loss: 1.919502 [57600/60000]
+    loss: 2.186582 [    0/60000]
+    loss: 2.177081 [ 6400/60000]
+    loss: 2.120968 [12800/60000]
+    loss: 2.120533 [19200/60000]
+    loss: 2.074893 [25600/60000]
+    loss: 2.020216 [32000/60000]
+    loss: 2.042988 [38400/60000]
+    loss: 1.971030 [44800/60000]
+    loss: 1.984660 [51200/60000]
+    loss: 1.886740 [57600/60000]
     Test Error: 
-     Accuracy: 56.5%, Avg loss: 1.900616 
+     Accuracy: 47.5%, Avg loss: 1.901350 
 
     Epoch 3
     -------------------------
-    loss: 1.937026 [    0/60000]
-    loss: 1.910710 [ 6400/60000]
-    loss: 1.792469 [12800/60000]
-    loss: 1.823637 [19200/60000]
-    loss: 1.723727 [25600/60000]
-    loss: 1.680588 [32000/60000]
-    loss: 1.707139 [38400/60000]
-    loss: 1.599742 [44800/60000]
-    loss: 1.627458 [51200/60000]
-    loss: 1.533370 [57600/60000]
+    loss: 1.949938 [    0/60000]
+    loss: 1.920142 [ 6400/60000]
+    loss: 1.801825 [12800/60000]
+    loss: 1.823636 [19200/60000]
+    loss: 1.720579 [25600/60000]
+    loss: 1.675992 [32000/60000]
+    loss: 1.697468 [38400/60000]
+    loss: 1.601651 [44800/60000]
+    loss: 1.633352 [51200/60000]
+    loss: 1.512037 [57600/60000]
     Test Error: 
-     Accuracy: 59.6%, Avg loss: 1.532841 
+     Accuracy: 56.6%, Avg loss: 1.539323 
 
     Epoch 4
     -------------------------
-    loss: 1.605492 [    0/60000]
-    loss: 1.571617 [ 6400/60000]
-    loss: 1.417090 [12800/60000]
-    loss: 1.476092 [19200/60000]
-    loss: 1.365803 [25600/60000]
-    loss: 1.365700 [32000/60000]
-    loss: 1.378166 [38400/60000]
-    loss: 1.298959 [44800/60000]
-    loss: 1.335748 [51200/60000]
-    loss: 1.239009 [57600/60000]
+    loss: 1.616808 [    0/60000]
+    loss: 1.581996 [ 6400/60000]
+    loss: 1.432845 [12800/60000]
+    loss: 1.487019 [19200/60000]
+    loss: 1.373611 [25600/60000]
+    loss: 1.372638 [32000/60000]
+    loss: 1.385377 [38400/60000]
+    loss: 1.311550 [44800/60000]
+    loss: 1.347421 [51200/60000]
+    loss: 1.238779 [57600/60000]
     Test Error: 
-     Accuracy: 62.7%, Avg loss: 1.258708 
+     Accuracy: 61.9%, Avg loss: 1.271684 
 
     Epoch 5
     -------------------------
-    loss: 1.339855 [    0/60000]
-    loss: 1.326636 [ 6400/60000]
-    loss: 1.157792 [12800/60000]
-    loss: 1.248033 [19200/60000]
-    loss: 1.131166 [25600/60000]
-    loss: 1.161770 [32000/60000]
-    loss: 1.175744 [38400/60000]
-    loss: 1.115841 [44800/60000]
-    loss: 1.155938 [51200/60000]
-    loss: 1.072032 [57600/60000]
+    loss: 1.355753 [    0/60000]
+    loss: 1.337759 [ 6400/60000]
+    loss: 1.174064 [12800/60000]
+    loss: 1.263690 [19200/60000]
+    loss: 1.142055 [25600/60000]
+    loss: 1.170844 [32000/60000]
+    loss: 1.190354 [38400/60000]
+    loss: 1.129786 [44800/60000]
+    loss: 1.168260 [51200/60000]
+    loss: 1.075101 [57600/60000]
     Test Error: 
-     Accuracy: 64.8%, Avg loss: 1.091301 
+     Accuracy: 63.9%, Avg loss: 1.103376 
 
-    TensorDict training done! time:  8.5213 s
+    TensorDict training done! time:  8.4599 s
     Epoch 1
     -------------------------
-    loss: 2.294210 [    0/60000]
-    loss: 2.279696 [ 6400/60000]
-    loss: 2.267683 [12800/60000]
-    loss: 2.262969 [19200/60000]
-    loss: 2.233031 [25600/60000]
-    loss: 2.212615 [32000/60000]
-    loss: 2.212489 [38400/60000]
-    loss: 2.179382 [44800/60000]
-    loss: 2.179719 [51200/60000]
-    loss: 2.136611 [57600/60000]
+    loss: 2.308583 [    0/60000]
+    loss: 2.290137 [ 6400/60000]
+    loss: 2.262756 [12800/60000]
+    loss: 2.260080 [19200/60000]
+    loss: 2.254794 [25600/60000]
+    loss: 2.221688 [32000/60000]
+    loss: 2.230328 [38400/60000]
+    loss: 2.191736 [44800/60000]
+    loss: 2.184659 [51200/60000]
+    loss: 2.162518 [57600/60000]
     Test Error: 
-     Accuracy: 50.0%, Avg loss: 2.138040 
+     Accuracy: 45.8%, Avg loss: 2.149730 
 
     Epoch 2
     -------------------------
-    loss: 2.151348 [    0/60000]
-    loss: 2.134395 [ 6400/60000]
-    loss: 2.081725 [12800/60000]
-    loss: 2.094522 [19200/60000]
-    loss: 2.027879 [25600/60000]
-    loss: 1.979650 [32000/60000]
-    loss: 1.996313 [38400/60000]
-    loss: 1.919786 [44800/60000]
-    loss: 1.927947 [51200/60000]
-    loss: 1.838332 [57600/60000]
+    loss: 2.156572 [    0/60000]
+    loss: 2.145286 [ 6400/60000]
+    loss: 2.078282 [12800/60000]
+    loss: 2.099030 [19200/60000]
+    loss: 2.051957 [25600/60000]
+    loss: 1.992218 [32000/60000]
+    loss: 2.019222 [38400/60000]
+    loss: 1.929527 [44800/60000]
+    loss: 1.939709 [51200/60000]
+    loss: 1.874409 [57600/60000]
     Test Error: 
-     Accuracy: 57.3%, Avg loss: 1.848600 
+     Accuracy: 54.0%, Avg loss: 1.863746 
 
     Epoch 3
     -------------------------
-    loss: 1.888493 [    0/60000]
-    loss: 1.849777 [ 6400/60000]
-    loss: 1.738905 [12800/60000]
-    loss: 1.771605 [19200/60000]
-    loss: 1.652798 [25600/60000]
-    loss: 1.626325 [32000/60000]
-    loss: 1.627747 [38400/60000]
-    loss: 1.546794 [44800/60000]
-    loss: 1.574224 [51200/60000]
-    loss: 1.452840 [57600/60000]
+    loss: 1.894882 [    0/60000]
+    loss: 1.863074 [ 6400/60000]
+    loss: 1.734463 [12800/60000]
+    loss: 1.787276 [19200/60000]
+    loss: 1.686061 [25600/60000]
+    loss: 1.637819 [32000/60000]
+    loss: 1.664422 [38400/60000]
+    loss: 1.555976 [44800/60000]
+    loss: 1.594991 [51200/60000]
+    loss: 1.498887 [57600/60000]
     Test Error: 
-     Accuracy: 59.8%, Avg loss: 1.485457 
+     Accuracy: 60.4%, Avg loss: 1.507766 
 
     Epoch 4
     -------------------------
-    loss: 1.558212 [    0/60000]
-    loss: 1.521574 [ 6400/60000]
-    loss: 1.379552 [12800/60000]
-    loss: 1.438517 [19200/60000]
-    loss: 1.320122 [25600/60000]
-    loss: 1.335142 [32000/60000]
-    loss: 1.325283 [38400/60000]
-    loss: 1.272102 [44800/60000]
-    loss: 1.309086 [51200/60000]
-    loss: 1.196575 [57600/60000]
+    loss: 1.572207 [    0/60000]
+    loss: 1.538401 [ 6400/60000]
+    loss: 1.381309 [12800/60000]
+    loss: 1.466922 [19200/60000]
+    loss: 1.359111 [25600/60000]
+    loss: 1.352805 [32000/60000]
+    loss: 1.371536 [38400/60000]
+    loss: 1.285556 [44800/60000]
+    loss: 1.332420 [51200/60000]
+    loss: 1.239365 [57600/60000]
     Test Error: 
-     Accuracy: 62.5%, Avg loss: 1.232535 
+     Accuracy: 62.7%, Avg loss: 1.258575 
 
     Epoch 5
     -------------------------
-    loss: 1.312083 [    0/60000]
-    loss: 1.294409 [ 6400/60000]
-    loss: 1.134353 [12800/60000]
-    loss: 1.227952 [19200/60000]
-    loss: 1.105222 [25600/60000]
-    loss: 1.143569 [32000/60000]
-    loss: 1.141154 [38400/60000]
-    loss: 1.101211 [44800/60000]
-    loss: 1.143558 [51200/60000]
-    loss: 1.047670 [57600/60000]
+    loss: 1.331579 [    0/60000]
+    loss: 1.312265 [ 6400/60000]
+    loss: 1.144193 [12800/60000]
+    loss: 1.257466 [19200/60000]
+    loss: 1.141888 [25600/60000]
+    loss: 1.166334 [32000/60000]
+    loss: 1.186469 [38400/60000]
+    loss: 1.113989 [44800/60000]
+    loss: 1.162796 [51200/60000]
+    loss: 1.079952 [57600/60000]
     Test Error: 
-     Accuracy: 64.4%, Avg loss: 1.075799 
+     Accuracy: 63.9%, Avg loss: 1.098634 
 
-    Training done! time:  33.0176 s
+    Training done! time:  32.8518 s
 
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 50.536 seconds)
+   **Total running time of the script:** (0 minutes 50.236 seconds)
 
 
 .. _sphx_glr_download_tutorials_data_fashion.py:

diff --git a/_sources/tutorials/sg_execution_times.rst.txt b/_sources/tutorials/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:00.319** total execution time for 10 files **from tutorials**:
+**02:13.623** total execution time for 10 files **from tutorials**:
 
 .. container::
 
@@ -33,30 +33,30 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``tensorclass_fashion.py``)
-     - 00:58.037
+     - 01:11.644
      - 0.0
    * - :ref:`sphx_glr_tutorials_data_fashion.py` (``data_fashion.py``)
-     - 00:50.536
+     - 00:50.236
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_module.py` (``tensordict_module.py``)
-     - 00:10.137
+     - 00:10.135
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``tensorclass_imagenet.py``)
-     - 00:01.551
+     - 00:01.549
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_memory.py` (``tensordict_memory.py``)
      - 00:00.024
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_keys.py` (``tensordict_keys.py``)
-     - 00:00.010
+     - 00:00.009
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_shapes.py` (``tensordict_shapes.py``)
      - 00:00.008
      - 0.0
-   * - :ref:`sphx_glr_tutorials_tensordict_module_functional.py` (``tensordict_module_functional.py``)
+   * - :ref:`sphx_glr_tutorials_tensordict_slicing.py` (``tensordict_slicing.py``)
      - 00:00.007
      - 0.0
-   * - :ref:`sphx_glr_tutorials_tensordict_slicing.py` (``tensordict_slicing.py``)
+   * - :ref:`sphx_glr_tutorials_tensordict_module_functional.py` (``tensordict_module_functional.py``)
      - 00:00.007
      - 0.0
    * - :ref:`sphx_glr_tutorials_tensordict_preallocation.py` (``tensordict_preallocation.py``)