Automated tutorials push

pytorch · Jun 25, 2024 · 46674a2 · 46674a2
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diff --git a/_downloads/3195443a0ced3cabc0ad643537bdb5cd/introyt1_tutorial.ipynb b/_downloads/3195443a0ced3cabc0ad643537bdb5cd/introyt1_tutorial.ipynb
@@ -34,7 +34,7 @@
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-   "id": "9ba8ee83",
+   "id": "7990a69c",
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@@ -50,7 +50,7 @@
   },
   {
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-   "id": "05cc4f1b",
+   "id": "cd424fde",
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     "\n",

diff --git a/_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb b/_downloads/4355e2cef7d17548f1e25f97a62828c4/template_tutorial.ipynb
@@ -31,7 +31,7 @@
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-   "id": "4ffc4dc0",
+   "id": "41f06fa1",
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@@ -47,7 +47,7 @@
   },
   {
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-   "id": "146701e4",
+   "id": "a8f13a31",
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     "\n",

diff --git a/_downloads/63a0f0fc7b3ffb15d3a5ac8db3d521ee/tensors_deeper_tutorial.ipynb b/_downloads/63a0f0fc7b3ffb15d3a5ac8db3d521ee/tensors_deeper_tutorial.ipynb
@@ -34,7 +34,7 @@
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-   "id": "7ddb23c2",
+   "id": "e9a0317a",
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@@ -50,7 +50,7 @@
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   {
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+   "id": "cb107f47",
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     "\n",

diff --git a/_downloads/770632dd3941d2a51b831c52ded57aa2/trainingyt.ipynb b/_downloads/770632dd3941d2a51b831c52ded57aa2/trainingyt.ipynb
@@ -35,7 +35,7 @@
   {
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+   "id": "9e2a7722",
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@@ -51,7 +51,7 @@
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+   "id": "a175d8e7",
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     "\n",

diff --git a/_downloads/c28f42852d456daf9af72da6c6909556/captumyt.ipynb b/_downloads/c28f42852d456daf9af72da6c6909556/captumyt.ipynb
@@ -37,7 +37,7 @@
   {
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-   "id": "0c9495e6",
+   "id": "cea1749f",
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@@ -53,7 +53,7 @@
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   {
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-   "id": "765def5b",
+   "id": "9b221904",
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     "\n",

diff --git a/_downloads/e2e556f6b4693c2cef716dd7f40caaf6/tensorboardyt_tutorial.ipynb b/_downloads/e2e556f6b4693c2cef716dd7f40caaf6/tensorboardyt_tutorial.ipynb
@@ -35,7 +35,7 @@
   {
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@@ -51,7 +51,7 @@
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   {
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+   "id": "a5bc0df0",
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diff --git a/_downloads/ed9d4f94afb79f7dada6742a06c486a5/autogradyt_tutorial.ipynb b/_downloads/ed9d4f94afb79f7dada6742a06c486a5/autogradyt_tutorial.ipynb
@@ -34,7 +34,7 @@
   {
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+   "id": "99f4bac3",
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@@ -50,7 +50,7 @@
   },
   {
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-   "id": "ec6ff4d4",
+   "id": "17dc5c5a",
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     "\n",

diff --git a/_downloads/fe726e041160526cf828806536922cf6/modelsyt_tutorial.ipynb b/_downloads/fe726e041160526cf828806536922cf6/modelsyt_tutorial.ipynb
@@ -34,7 +34,7 @@
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@@ -50,7 +50,7 @@
   },
   {
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-   "id": "54aab864",
+   "id": "d4ef5611",
    "metadata": {},
    "source": [
     "\n",

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_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_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
@@ -1632,26 +1632,26 @@ modules we need.
 
 
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-    reward: -2.16 (r0 = -3.21), reward eval: reward: -0.00, reward normalized=-2.09/6.32, grad norm= 218.52, loss_value= 380.54, loss_actor= 14.07, target value: -11.24:  56%|#####6    | 5600/10000 [00:08<00:05, 859.06it/s]
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-    reward: -0.11 (r0 = -3.21), reward eval: reward: -0.00, reward normalized=-2.50/6.05, grad norm= 33.89, loss_value= 358.66, loss_actor= 14.75, target value: -15.00:  64%|######4   | 6400/10000 [00:10<00:05, 638.38it/s] 
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+    reward: -5.13 (r0 = -2.20), reward eval: reward:  0.53, reward normalized=-2.81/5.41, grad norm= 125.30, loss_value= 268.30, loss_actor= 16.89, target value: -19.89:  96%|#########6| 9600/10000 [00:22<00:01, 284.56it/s]
+    reward: -5.13 (r0 = -2.20), reward eval: reward:  0.53, reward normalized=-2.81/5.41, grad norm= 125.30, loss_value= 268.30, loss_actor= 16.89, target value: -19.89: : 10400it [00:25, 264.83it/s]                        
+    reward: -3.58 (r0 = -2.20), reward eval: reward:  0.53, reward normalized=-3.82/5.60, grad norm= 87.65, loss_value= 267.84, loss_actor= 23.16, target value: -27.36: : 10400it [00:26, 264.83it/s] 
 
 
 
@@ -1721,7 +1721,7 @@ To iterate further on this loss module we might consider:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  41.406 seconds)
+   **Total running time of the script:** ( 0 minutes  41.549 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
@@ -516,9 +516,9 @@ models run single threaded.
  .. code-block:: none
 
     loss: 5.167
-    elapsed time (seconds): 205.4
+    elapsed time (seconds): 206.3
     loss: 5.168
-    elapsed time (seconds): 113.9
+    elapsed time (seconds): 116.9
 
 
 
@@ -540,7 +540,7 @@ 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  27.914 seconds)
+   **Total running time of the script:** ( 5 minutes  32.168 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
@@ -410,38 +410,41 @@ 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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@@ -762,22 +765,22 @@ Finally, we can run the algorithm.
 
     Optimizing..
     run [50]:
-    Style Loss : 4.076185 Content Loss: 4.141464
+    Style Loss : 4.037464 Content Loss: 4.144108
 
     run [100]:
-    Style Loss : 1.117196 Content Loss: 3.007679
+    Style Loss : 1.150719 Content Loss: 3.040204
 
     run [150]:
-    Style Loss : 0.697977 Content Loss: 2.643763
+    Style Loss : 0.710417 Content Loss: 2.655678
 
     run [200]:
-    Style Loss : 0.472661 Content Loss: 2.485559
+    Style Loss : 0.479242 Content Loss: 2.487361
 
     run [250]:
-    Style Loss : 0.342390 Content Loss: 2.399799
+    Style Loss : 0.344841 Content Loss: 2.403615
 
     run [300]:
-    Style Loss : 0.261053 Content Loss: 2.347213
+    Style Loss : 0.262127 Content Loss: 2.350151
 
 
 
@@ -786,7 +789,7 @@ Finally, we can run the algorithm.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** ( 0 minutes  37.280 seconds)
+   **Total running time of the script:** ( 0 minutes  37.689 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  0.583 seconds)
+   **Total running time of the script:** ( 0 minutes  0.560 seconds)
 
 
 .. _sphx_glr_download_advanced_numpy_extensions_tutorial.py: