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pytorch · Jan 29, 2025 · 3ae1e8b · 3ae1e8b
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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: -4.67 (r0 = -3.42), reward eval: reward: -5.46, reward normalized=-3.58/4.46, grad norm= 70.11, loss_value= 183.36, loss_actor= 23.07, target value: -25.11: : 10400it [00:18, 363.51it/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  28.713 seconds)
+   **Total running time of the script:** ( 0 minutes  28.464 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): 208.2
+    elapsed time (seconds): 208.6
     loss: 5.168
-    elapsed time (seconds): 116.5
+    elapsed time (seconds): 115.2
 
 
 
@@ -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  35.389 seconds)
+   **Total running time of the script:** ( 5 minutes  34.642 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
@@ -410,36 +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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@@ -760,22 +756,22 @@ Finally, we can run the algorithm.
 
     Optimizing..
     run [50]:
-    Style Loss : 4.116919 Content Loss: 4.180849
+    Style Loss : 4.103480 Content Loss: 4.095845
 
     run [100]:
-    Style Loss : 1.130904 Content Loss: 3.026069
+    Style Loss : 1.120694 Content Loss: 3.009445
 
     run [150]:
-    Style Loss : 0.709217 Content Loss: 2.653672
+    Style Loss : 0.707350 Content Loss: 2.644475
 
     run [200]:
-    Style Loss : 0.472506 Content Loss: 2.489412
+    Style Loss : 0.476449 Content Loss: 2.486541
 
     run [250]:
-    Style Loss : 0.342615 Content Loss: 2.401286
+    Style Loss : 0.344099 Content Loss: 2.402043
 
     run [300]:
-    Style Loss : 0.263712 Content Loss: 2.348886
+    Style Loss : 0.262806 Content Loss: 2.347914
 
 
 
@@ -784,7 +780,7 @@ Finally, we can run the algorithm.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  38.991 seconds)
+   **Total running time of the script:** ( 0 minutes  38.521 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  0.633 seconds)
+   **Total running time of the script:** ( 0 minutes  0.582 seconds)
 
 
 .. _sphx_glr_download_advanced_numpy_extensions_tutorial.py: