Automated tutorials push

pytorch · Jan 30, 2025 · fed6e56 · fed6e56
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diff --git a/_images/sphx_glr_char_rnn_classification_tutorial_001.png b/_images/sphx_glr_char_rnn_classification_tutorial_001.png
diff --git a/_images/sphx_glr_char_rnn_classification_tutorial_002.png b/_images/sphx_glr_char_rnn_classification_tutorial_002.png
diff --git a/_images/sphx_glr_coding_ddpg_001.png b/_images/sphx_glr_coding_ddpg_001.png
diff --git a/_images/sphx_glr_dqn_with_rnn_tutorial_001.png b/_images/sphx_glr_dqn_with_rnn_tutorial_001.png
diff --git a/_images/sphx_glr_neural_style_tutorial_004.png b/_images/sphx_glr_neural_style_tutorial_004.png
diff --git a/_images/sphx_glr_pinmem_nonblock_001.png b/_images/sphx_glr_pinmem_nonblock_001.png
diff --git a/_images/sphx_glr_pinmem_nonblock_002.png b/_images/sphx_glr_pinmem_nonblock_002.png
diff --git a/_images/sphx_glr_pinmem_nonblock_003.png b/_images/sphx_glr_pinmem_nonblock_003.png
diff --git a/_images/sphx_glr_pinmem_nonblock_004.png b/_images/sphx_glr_pinmem_nonblock_004.png
diff --git a/_images/sphx_glr_reinforcement_ppo_001.png b/_images/sphx_glr_reinforcement_ppo_001.png
diff --git a/_images/sphx_glr_reinforcement_q_learning_001.png b/_images/sphx_glr_reinforcement_q_learning_001.png
diff --git a/_images/sphx_glr_semi_structured_sparse_001.png b/_images/sphx_glr_semi_structured_sparse_001.png
diff --git a/_images/sphx_glr_semi_structured_sparse_002.png b/_images/sphx_glr_semi_structured_sparse_002.png
diff --git a/_images/sphx_glr_spatial_transformer_tutorial_001.png b/_images/sphx_glr_spatial_transformer_tutorial_001.png
diff --git a/_images/sphx_glr_torchvision_tutorial_002.png b/_images/sphx_glr_torchvision_tutorial_002.png
diff --git a/_sources/advanced/coding_ddpg.rst.txt b/_sources/advanced/coding_ddpg.rst.txt
@@ -1634,26 +1634,26 @@ modules we need.
 
 
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+    reward: -4.93 (r0 = -2.00), reward eval: reward: -5.98, reward normalized=-3.38/3.91, grad norm= 120.25, loss_value= 129.44, loss_actor= 15.23, target value: -23.98: : 10400it [00:18, 364.88it/s]
 
 
 
@@ -1723,7 +1723,7 @@ To iterate further on this loss module we might consider:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  28.464 seconds)
+   **Total running time of the script:** ( 0 minutes  29.005 seconds)
 
 
 .. _sphx_glr_download_advanced_coding_ddpg.py:

diff --git a/_sources/advanced/dynamic_quantization_tutorial.rst.txt b/_sources/advanced/dynamic_quantization_tutorial.rst.txt
@@ -517,9 +517,9 @@ models run single threaded.
  .. code-block:: none
 
     loss: 5.167
-    elapsed time (seconds): 208.6
+    elapsed time (seconds): 208.2
     loss: 5.168
-    elapsed time (seconds): 115.2
+    elapsed time (seconds): 115.8
 
 
 
@@ -541,7 +541,7 @@ Thanks for reading! As always, we welcome any feedback, so please create an issu
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 5 minutes  34.642 seconds)
+   **Total running time of the script:** ( 5 minutes  34.880 seconds)
 
 
 .. _sphx_glr_download_advanced_dynamic_quantization_tutorial.py:

diff --git a/_sources/advanced/neural_style_tutorial.rst.txt b/_sources/advanced/neural_style_tutorial.rst.txt
@@ -410,32 +410,32 @@ network to evaluation mode using ``.eval()``.
     Downloading: "https://download.pytorch.org/models/vgg19-dcbb9e9d.pth" to /var/lib/ci-user/.cache/torch/hub/checkpoints/vgg19-dcbb9e9d.pth
 
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@@ -756,22 +756,22 @@ Finally, we can run the algorithm.
 
     Optimizing..
     run [50]:
-    Style Loss : 4.103480 Content Loss: 4.095845
+    Style Loss : 4.243999 Content Loss: 4.230177
 
     run [100]:
-    Style Loss : 1.120694 Content Loss: 3.009445
+    Style Loss : 1.153091 Content Loss: 3.027826
 
     run [150]:
-    Style Loss : 0.707350 Content Loss: 2.644475
+    Style Loss : 0.714814 Content Loss: 2.653670
 
     run [200]:
-    Style Loss : 0.476449 Content Loss: 2.486541
+    Style Loss : 0.479303 Content Loss: 2.491420
 
     run [250]:
-    Style Loss : 0.344099 Content Loss: 2.402043
+    Style Loss : 0.347053 Content Loss: 2.402259
 
     run [300]:
-    Style Loss : 0.262806 Content Loss: 2.347914
+    Style Loss : 0.262986 Content Loss: 2.348989
 
 
 
@@ -780,7 +780,7 @@ Finally, we can run the algorithm.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  38.521 seconds)
+   **Total running time of the script:** ( 0 minutes  38.572 seconds)
 
 
 .. _sphx_glr_download_advanced_neural_style_tutorial.py:

diff --git a/_sources/advanced/numpy_extensions_tutorial.rst.txt b/_sources/advanced/numpy_extensions_tutorial.rst.txt
@@ -303,7 +303,7 @@ The backward pass computes the gradient ``wrt`` the input and the gradient ``wrt
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  0.582 seconds)
+   **Total running time of the script:** ( 0 minutes  0.602 seconds)
 
 
 .. _sphx_glr_download_advanced_numpy_extensions_tutorial.py: