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auto-generating sphinx docs
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pytorchbot committed Jan 23, 2024
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16 changes: 8 additions & 8 deletions _sources/sg_execution_times.rst.txt
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Expand Up @@ -6,7 +6,7 @@

Computation times
=================
**02:01.082** total execution time for 10 files **from all galleries**:
**01:59.897** total execution time for 10 files **from all galleries**:

.. container::

Expand All @@ -33,22 +33,22 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``reference/generated/tutorials/tensorclass_fashion.py``)
- 00:58.981
- 00:58.373
- 0.0
* - :ref:`sphx_glr_tutorials_data_fashion.py` (``reference/generated/tutorials/data_fashion.py``)
- 00:50.364
- 00:49.828
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_module.py` (``reference/generated/tutorials/tensordict_module.py``)
- 00:10.144
- 00:10.137
- 0.0
* - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``reference/generated/tutorials/tensorclass_imagenet.py``)
- 00:01.535
- 00:01.501
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_memory.py` (``reference/generated/tutorials/tensordict_memory.py``)
- 00:00.023
- 00:00.025
- 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
Expand All @@ -57,7 +57,7 @@ Computation times
- 00:00.007
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_module_functional.py` (``reference/generated/tutorials/tensordict_module_functional.py``)
- 00:00.007
- 00:00.006
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_preallocation.py` (``reference/generated/tutorials/tensordict_preallocation.py``)
- 00:00.003
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226 changes: 113 additions & 113 deletions _sources/tutorials/data_fashion.rst.txt
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Expand Up @@ -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: 2.297689 [ 0/60000]
loss: 2.280892 [ 6400/60000]
loss: 2.274654 [12800/60000]
loss: 2.279074 [19200/60000]
loss: 2.246684 [25600/60000]
loss: 2.236528 [32000/60000]
loss: 2.231100 [38400/60000]
loss: 2.205158 [44800/60000]
loss: 2.201136 [51200/60000]
loss: 2.183861 [57600/60000]
loss: 2.300480 [ 0/60000]
loss: 2.293064 [ 6400/60000]
loss: 2.266259 [12800/60000]
loss: 2.261617 [19200/60000]
loss: 2.261147 [25600/60000]
loss: 2.215564 [32000/60000]
loss: 2.237646 [38400/60000]
loss: 2.195081 [44800/60000]
loss: 2.190470 [51200/60000]
loss: 2.164365 [57600/60000]
Test Error:
Accuracy: 46.9%, Avg loss: 2.167354
Accuracy: 41.1%, Avg loss: 2.155924
Epoch 2
-------------------------
loss: 2.171290 [ 0/60000]
loss: 2.158412 [ 6400/60000]
loss: 2.111888 [12800/60000]
loss: 2.133768 [19200/60000]
loss: 2.084503 [25600/60000]
loss: 2.034350 [32000/60000]
loss: 2.050703 [38400/60000]
loss: 1.979632 [44800/60000]
loss: 1.976614 [51200/60000]
loss: 1.923289 [57600/60000]
loss: 2.162857 [ 0/60000]
loss: 2.156318 [ 6400/60000]
loss: 2.098328 [12800/60000]
loss: 2.116032 [19200/60000]
loss: 2.078008 [25600/60000]
loss: 2.007684 [32000/60000]
loss: 2.046304 [38400/60000]
loss: 1.959306 [44800/60000]
loss: 1.963503 [51200/60000]
loss: 1.905034 [57600/60000]
Test Error:
Accuracy: 60.4%, Avg loss: 1.910134
Accuracy: 56.5%, Avg loss: 1.897783
Epoch 3
-------------------------
loss: 1.936399 [ 0/60000]
loss: 1.905847 [ 6400/60000]
loss: 1.795367 [12800/60000]
loss: 1.838003 [19200/60000]
loss: 1.743419 [25600/60000]
loss: 1.686000 [32000/60000]
loss: 1.699681 [38400/60000]
loss: 1.603609 [44800/60000]
loss: 1.619376 [51200/60000]
loss: 1.525605 [57600/60000]
loss: 1.922749 [ 0/60000]
loss: 1.898134 [ 6400/60000]
loss: 1.786096 [12800/60000]
loss: 1.830101 [19200/60000]
loss: 1.727412 [25600/60000]
loss: 1.672580 [32000/60000]
loss: 1.700479 [38400/60000]
loss: 1.590516 [44800/60000]
loss: 1.615487 [51200/60000]
loss: 1.517848 [57600/60000]
Test Error:
Accuracy: 61.5%, Avg loss: 1.536318
Accuracy: 61.8%, Avg loss: 1.532749
Epoch 4
-------------------------
loss: 1.596518 [ 0/60000]
loss: 1.559388 [ 6400/60000]
loss: 1.415173 [12800/60000]
loss: 1.491498 [19200/60000]
loss: 1.381014 [25600/60000]
loss: 1.365470 [32000/60000]
loss: 1.370804 [38400/60000]
loss: 1.300947 [44800/60000]
loss: 1.330507 [51200/60000]
loss: 1.238865 [57600/60000]
loss: 1.593874 [ 0/60000]
loss: 1.560890 [ 6400/60000]
loss: 1.416031 [12800/60000]
loss: 1.487803 [19200/60000]
loss: 1.369440 [25600/60000]
loss: 1.358816 [32000/60000]
loss: 1.374556 [38400/60000]
loss: 1.287937 [44800/60000]
loss: 1.326393 [51200/60000]
loss: 1.228221 [57600/60000]
Test Error:
Accuracy: 63.2%, Avg loss: 1.261017
Accuracy: 64.3%, Avg loss: 1.257580
Epoch 5
-------------------------
loss: 1.331413 [ 0/60000]
loss: 1.310852 [ 6400/60000]
loss: 1.153299 [12800/60000]
loss: 1.264552 [19200/60000]
loss: 1.141564 [25600/60000]
loss: 1.159877 [32000/60000]
loss: 1.169980 [38400/60000]
loss: 1.117384 [44800/60000]
loss: 1.152227 [51200/60000]
loss: 1.074354 [57600/60000]
loss: 1.331571 [ 0/60000]
loss: 1.314824 [ 6400/60000]
loss: 1.154153 [12800/60000]
loss: 1.257705 [19200/60000]
loss: 1.134324 [25600/60000]
loss: 1.153518 [32000/60000]
loss: 1.174747 [38400/60000]
loss: 1.101449 [44800/60000]
loss: 1.145374 [51200/60000]
loss: 1.062342 [57600/60000]
Test Error:
Accuracy: 64.7%, Avg loss: 1.091176
Accuracy: 65.2%, Avg loss: 1.087329
TensorDict training done! time: 8.2466 s
TensorDict training done! time: 8.1166 s
Epoch 1
-------------------------
loss: 2.302497 [ 0/60000]
loss: 2.293708 [ 6400/60000]
loss: 2.275291 [12800/60000]
loss: 2.277487 [19200/60000]
loss: 2.256965 [25600/60000]
loss: 2.226137 [32000/60000]
loss: 2.235041 [38400/60000]
loss: 2.204915 [44800/60000]
loss: 2.205817 [51200/60000]
loss: 2.175438 [57600/60000]
loss: 2.298001 [ 0/60000]
loss: 2.287161 [ 6400/60000]
loss: 2.270800 [12800/60000]
loss: 2.270414 [19200/60000]
loss: 2.245303 [25600/60000]
loss: 2.225265 [32000/60000]
loss: 2.231304 [38400/60000]
loss: 2.200896 [44800/60000]
loss: 2.198071 [51200/60000]
loss: 2.161562 [57600/60000]
Test Error:
Accuracy: 41.0%, Avg loss: 2.167767
Accuracy: 50.7%, Avg loss: 2.157821
Epoch 2
-------------------------
loss: 2.173955 [ 0/60000]
loss: 2.167189 [ 6400/60000]
loss: 2.113836 [12800/60000]
loss: 2.137049 [19200/60000]
loss: 2.091704 [25600/60000]
loss: 2.024699 [32000/60000]
loss: 2.058104 [38400/60000]
loss: 1.987428 [44800/60000]
loss: 1.997960 [51200/60000]
loss: 1.928781 [57600/60000]
loss: 2.168909 [ 0/60000]
loss: 2.158751 [ 6400/60000]
loss: 2.096658 [12800/60000]
loss: 2.108140 [19200/60000]
loss: 2.061918 [25600/60000]
loss: 2.008899 [32000/60000]
loss: 2.032122 [38400/60000]
loss: 1.955184 [44800/60000]
loss: 1.954244 [51200/60000]
loss: 1.873682 [57600/60000]
Test Error:
Accuracy: 57.3%, Avg loss: 1.920751
Accuracy: 58.9%, Avg loss: 1.876599
Epoch 3
-------------------------
loss: 1.947450 [ 0/60000]
loss: 1.923763 [ 6400/60000]
loss: 1.809623 [12800/60000]
loss: 1.859243 [19200/60000]
loss: 1.749499 [25600/60000]
loss: 1.684024 [32000/60000]
loss: 1.717253 [38400/60000]
loss: 1.618240 [44800/60000]
loss: 1.651242 [51200/60000]
loss: 1.544094 [57600/60000]
loss: 1.909632 [ 0/60000]
loss: 1.884026 [ 6400/60000]
loss: 1.755143 [12800/60000]
loss: 1.790438 [19200/60000]
loss: 1.690238 [25600/60000]
loss: 1.638952 [32000/60000]
loss: 1.660928 [38400/60000]
loss: 1.561142 [44800/60000]
loss: 1.582468 [51200/60000]
loss: 1.474488 [57600/60000]
Test Error:
Accuracy: 61.4%, Avg loss: 1.550630
Accuracy: 61.6%, Avg loss: 1.500441
Epoch 4
-------------------------
loss: 1.611791 [ 0/60000]
loss: 1.576542 [ 6400/60000]
loss: 1.422823 [12800/60000]
loss: 1.509073 [19200/60000]
loss: 1.374687 [25600/60000]
loss: 1.361015 [32000/60000]
loss: 1.386337 [38400/60000]
loss: 1.310513 [44800/60000]
loss: 1.355154 [51200/60000]
loss: 1.253993 [57600/60000]
loss: 1.560883 [ 0/60000]
loss: 1.537471 [ 6400/60000]
loss: 1.383097 [12800/60000]
loss: 1.453247 [19200/60000]
loss: 1.343728 [25600/60000]
loss: 1.335195 [32000/60000]
loss: 1.352697 [38400/60000]
loss: 1.274515 [44800/60000]
loss: 1.309380 [51200/60000]
loss: 1.211425 [57600/60000]
Test Error:
Accuracy: 63.9%, Avg loss: 1.267246
Accuracy: 63.2%, Avg loss: 1.241849
Epoch 5
-------------------------
loss: 1.339752 [ 0/60000]
loss: 1.319095 [ 6400/60000]
loss: 1.151958 [12800/60000]
loss: 1.273998 [19200/60000]
loss: 1.129366 [25600/60000]
loss: 1.151123 [32000/60000]
loss: 1.181103 [38400/60000]
loss: 1.123158 [44800/60000]
loss: 1.170845 [51200/60000]
loss: 1.086041 [57600/60000]
loss: 1.310621 [ 0/60000]
loss: 1.302632 [ 6400/60000]
loss: 1.136563 [12800/60000]
loss: 1.238647 [19200/60000]
loss: 1.124559 [25600/60000]
loss: 1.142481 [32000/60000]
loss: 1.167050 [38400/60000]
loss: 1.099875 [44800/60000]
loss: 1.140567 [51200/60000]
loss: 1.059313 [57600/60000]
Test Error:
Accuracy: 65.0%, Avg loss: 1.093209
Accuracy: 64.6%, Avg loss: 1.082458
Training done! time: 32.7524 s
Training done! time: 32.8354 s
.. rst-class:: sphx-glr-timing

**Total running time of the script:** (0 minutes 50.364 seconds)
**Total running time of the script:** (0 minutes 49.828 seconds)


.. _sphx_glr_download_tutorials_data_fashion.py:
Expand Down
16 changes: 8 additions & 8 deletions _sources/tutorials/sg_execution_times.rst.txt
Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@

Computation times
=================
**02:01.082** total execution time for 10 files **from tutorials**:
**01:59.897** total execution time for 10 files **from tutorials**:

.. container::

Expand All @@ -33,22 +33,22 @@ Computation times
- Time
- Mem (MB)
* - :ref:`sphx_glr_tutorials_tensorclass_fashion.py` (``tensorclass_fashion.py``)
- 00:58.981
- 00:58.373
- 0.0
* - :ref:`sphx_glr_tutorials_data_fashion.py` (``data_fashion.py``)
- 00:50.364
- 00:49.828
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_module.py` (``tensordict_module.py``)
- 00:10.144
- 00:10.137
- 0.0
* - :ref:`sphx_glr_tutorials_tensorclass_imagenet.py` (``tensorclass_imagenet.py``)
- 00:01.535
- 00:01.501
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_memory.py` (``tensordict_memory.py``)
- 00:00.023
- 00:00.025
- 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
Expand All @@ -57,7 +57,7 @@ Computation times
- 00:00.007
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_module_functional.py` (``tensordict_module_functional.py``)
- 00:00.007
- 00:00.006
- 0.0
* - :ref:`sphx_glr_tutorials_tensordict_preallocation.py` (``tensordict_preallocation.py``)
- 00:00.003
Expand Down
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