Merge branch 'main' into csl/typo_fix

Author: svekars

.ci/docker/requirements.txt

@@ -28,8 +28,8 @@ tensorboard
 jinja2==3.1.3
 pytorch-lightning
 torchx
-torchrl==0.6.0
-tensordict==0.6.0
+torchrl==0.7.2
+tensordict==0.7.2
 ax-platform>=0.4.0
 nbformat>=5.9.2
 datasets

.github/workflows/MonthlyLinkCheck.yml

@@ -0,0 +1,44 @@
+#Runs once a month and checks links in the repo to ensure they are valid 
+#If action fails, it creates an issue with the failing links and an "incorrect link" label
+#If link is valid but failing, it can be added to the .lycheeignore file
+#Action can also be run manually as needed.
+
+
+name: Monthly Link Check
+on:
+  schedule:
+    - cron: '0 0 1 * *'  # Runs at midnight on the first day of every month
+  workflow_dispatch:  # Allows manual triggering of the workflow
+jobs:
+  linkChecker:
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 1
+      - name: Check Links
+        id: lychee
+        uses: lycheeverse/lychee-action@v2
+        with:
+          args: --accept=200,403,429 --base . --verbose --no-progress './**/*.md' './**/*.html' './**/*.rst'
+          token: ${{ secrets.CUSTOM_TOKEN }}
+          fail: true
+
+      - name: Create Issue From File
+        if: failure() && (github.event_name == 'schedule' || github.event_name == 'workflow_dispatch')
+        uses: peter-evans/create-issue-from-file@v5
+        with:
+          title: Broken links detected in docs 🔗
+          content-filepath: ./lychee/out.md
+          labels: 'incorrect link'
+          #token: ${{ secrets.CUSTOM_TOKEN }}
+          
+    
+      - name: Suggestions
+        if: failure()
+        run: |
+          echo -e "\nPlease review the links reported in the Check links step above."
+          echo -e "If a link is valid but fails due to a CAPTCHA challenge, IP blocking, login requirements, etc., consider adding such links to .lycheeignore file to bypass future checks.\n"
+          exit 1

.github/workflows/link_checkPR.yml

@@ -18,7 +18,7 @@ jobs:
 
       - name: Get Changed Files
         id: changed-files
-        uses: tj-actions/changed-files@v41
+        uses: tj-actions/changed-files@d6e91a2266cdb9d62096cebf1e8546899c6aa18f # v45.0.6
 
       - name: Check for Skip Label
         id: skip-label

.jenkins/post_process_notebooks.py

@@ -12,7 +12,7 @@
 
 
 # Pattern to search ``` {.python .jupyter-code-cell}
-pattern = re.compile(r'(.*?)``` {.python .jupyter-code-cell}\n\n(from IPython.display import display, HTML\nhtml_code = """\n.*?\n"""\ndisplay\(HTML\(html_code\)\))\n```(.*)', re.DOTALL)
+pattern = re.compile(r'(.*?)``` {\.python \.jupyter-code-cell}\n(.*?from IPython\.display import display, HTML.*?display\(HTML\(html_code\)\))\n```(.*)', re.DOTALL)
 
 
 def process_video_cell(notebook_path):

.jenkins/validate_tutorials_built.py

@@ -50,6 +50,7 @@
     "intermediate_source/flask_rest_api_tutorial",
     "intermediate_source/text_to_speech_with_torchaudio",
     "intermediate_source/tensorboard_profiler_tutorial", # reenable after 2.0 release.
+    "advanced_source/semi_structured_sparse" # reenable after 3303 is fixed.
 ]
 
 def tutorial_source_dirs() -> List[Path]:

_templates/layout.html

@@ -24,7 +24,7 @@
   {
     var div = '<div class="admonition note"><p class="admonition-title">Note</p><p><i class="fa fa-flask" aria-hidden="true">&nbsp</i> This tutorial describes a prototype feature. Prototype features are typically not available as part of binary distributions like PyPI or Conda, except sometimes behind run-time flags, and are at an early stage for feedback and testing.</p></div>'
     document.getElementById("pytorch-article").insertAdjacentHTML('afterBegin', div)
-  } 
+  }
 </script>
 {%- endblock %}
 
@@ -102,9 +102,9 @@
         if (googleSearchboxText) {
           googleSearchboxText.placeholder = placeholderText;
           googleSearchboxText.style.fontFamily = 'FreightSans';
-          googleSearchboxText.style.fontSize = "1.2rem"; 
+          googleSearchboxText.style.fontSize = "1.2rem";
           googleSearchboxText.style.color = '#262626';
-        } 
+        }
       };
     });
   </script>
@@ -114,7 +114,7 @@
 {{ super() }}
 <script>
 
-// Helper function to make it easier to call dataLayer.push() 
+// Helper function to make it easier to call dataLayer.push()
 function gtag(){window.dataLayer.push(arguments);}
 
 //add microsoft link
@@ -148,7 +148,7 @@
     case"saveloadrun_tutorial":
       url="https://docs.microsoft.com/learn/modules/intro-machine-learning-pytorch/8-inference?WT.mc_id=aiml-7486-cxa";
     }
-    
+
     $(".pytorch-call-to-action-links").children().first().before("<a href="+url+' data-behavior="call-to-action-event" data-response="Run in Microsoft Learn" target="_blank"><div id="microsoft-learn-link" style="padding-bottom: 0.625rem;border-bottom: 1px solid #f3f4f7;padding-right: 2.5rem;display: -webkit-box;  display: -ms-flexbox; display: flex; -webkit-box-align: center;-ms-flex-align: center;align-items: center;"><img class="call-to-action-img" src="../../_static/images/microsoft-logo.svg"/><div class="call-to-action-desktop-view">Run in Microsoft Learn</div><div class="call-to-action-mobile-view">Learn</div></div></a>')
   }
 
@@ -210,4 +210,15 @@
 </script>
 
 <img height="1" width="1" style="border-style:none;" alt="" src="https://www.googleadservices.com/pagead/conversion/795629140/?label=txkmCPmdtosBENSssfsC&amp;guid=ON&amp;script=0"/>
+
+//temporarily add a link to survey
+<script>
+    var survey = '<div class="survey-banner"><p><i class="fas fa-poll" aria-hidden="true">&nbsp </i> Take the <a href="https://forms.gle/KZ4xGL65VRMYNbbG6">PyTorch Docs/Tutorials survey</a>.</p></div>'
+    if ($(".pytorch-call-to-action-links").length) {
+        $(".pytorch-call-to-action-links").before(survey);
+    } else {
+        $("#pytorch-article").prepend(survey);
+    }
+</script>
+
 {% endblock %}

advanced_source/coding_ddpg.py

@@ -1040,7 +1040,7 @@ def ceil_div(x, y):
 
 ###############################################################################
 # let's use the TD(lambda) estimator!
-loss_module.make_value_estimator(ValueEstimators.TDLambda, gamma=gamma, lmbda=lmbda)
+loss_module.make_value_estimator(ValueEstimators.TDLambda, gamma=gamma, lmbda=lmbda, device=device)
 
 ###############################################################################
 # .. note::

advanced_source/cpp_extension.rst

@@ -1207,3 +1207,5 @@ examples displayed in this note `here
 <https://github.com/pytorch/extension-cpp>`_. If you have questions, please use
 `the forums <https://discuss.pytorch.org>`_. Also be sure to check our `FAQ
 <https://pytorch.org/cppdocs/notes/faq.html>`_ in case you run into any issues.
+A blog on writing extensions for AMD ROCm can be found `here
+<https://rocm.blogs.amd.com/artificial-intelligence/cpp-extn/readme.html>`_.

advanced_source/python_custom_ops.py

@@ -112,7 +112,10 @@ def crop(pic: torch.Tensor, box: Sequence[int]) -> torch.Tensor:
 def _(pic, box):
     channels = pic.shape[0]
     x0, y0, x1, y1 = box
-    return pic.new_empty(channels, y1 - y0, x1 - x0)
+    result = pic.new_empty(y1 - y0, x1 - x0, channels).permute(2, 0, 1)
+    # The result should have the same metadata (shape/strides/``dtype``/device)
+    # as running the ``crop`` function above.
+    return result
 
 ######################################################################
 # After this, ``crop`` now works without graph breaks:

advanced_source/semi_structured_sparse.py

@@ -210,6 +210,8 @@
 SparseSemiStructuredTensor._FORCE_CUTLASS = True
 torch.manual_seed(100)
 
+# Set default device to "cuda:0"
+torch.set_default_device(torch.device("cuda:0" if torch.cuda.is_available() else "cpu"))
 
 ######################################################################
 # We’ll also need to define some helper functions that are specific to the

beginner_source/data_loading_tutorial.py

@@ -445,7 +445,7 @@ def show_landmarks_batch(sample_batched):
 #    from torchvision import transforms, datasets
 #
 #    data_transform = transforms.Compose([
-#            transforms.RandomSizedCrop(224),
+#            transforms.RandomResizedCrop(224),
 #            transforms.RandomHorizontalFlip(),
 #            transforms.ToTensor(),
 #            transforms.Normalize(mean=[0.485, 0.456, 0.406],

beginner_source/introyt/introyt_index.py

@@ -1,11 +1,11 @@
 """
-`Introduction <introyt/introyt1_tutorial.html>`_ ||
-`Tensors <introyt/tensors_deeper_tutorial.html>`_ ||
-`Autograd <introyt/autogradyt_tutorial.html>`_ ||
-`Building Models <introyt/modelsyt_tutorial.html>`_ ||
-`TensorBoard Support <introyt/tensorboardyt_tutorial.html>`_ ||
-`Training Models <introyt/trainingyt.html>`_ ||
-`Model Understanding <introyt/captumyt.html>`_
+`Introduction <introyt1_tutorial.html>`_ ||
+`Tensors <tensors_deeper_tutorial.html>`_ ||
+`Autograd <autogradyt_tutorial.html>`_ ||
+`Building Models <modelsyt_tutorial.html>`_ ||
+`TensorBoard Support <tensorboardyt_tutorial.html>`_ ||
+`Training Models <trainingyt.html>`_ ||
+`Model Understanding <captumyt.html>`_
 
 Introduction to PyTorch - YouTube Series
 ========================================

en-wordlist.txt

@@ -407,6 +407,7 @@ fuser
 geomean
 globals
 grayscale
+html
 handoff
 hardcode
 helpdesk
@@ -492,6 +493,7 @@ numericalize
 numpy
 nvFuser
 nvFuser's
+ok
 oneDNN
 opset
 optimizable
@@ -540,6 +542,7 @@ randint
 randn
 readably
 recomputation
+reenable
 regressor
 reimplement
 reimplementing

index.rst

@@ -265,10 +265,17 @@ Welcome to PyTorch Tutorials
    :tags: Production,ONNX,Backends
 
 .. customcarditem::
-   :header: Introduction to ONNX Registry
-   :card_description: Demonstrate end-to-end how to address unsupported operators by using ONNX Registry.
+   :header: Extending the ONNX exporter operator support
+   :card_description: Demonstrate end-to-end how to address unsupported operators in ONNX.
    :image: _static/img/thumbnails/cropped/Exporting-PyTorch-Models-to-ONNX-Graphs.png
-   :link: advanced/onnx_registry_tutorial.html
+   :link: beginner/onnx/onnx_registry_tutorial.html
+   :tags: Production,ONNX,Backends
+
+.. customcarditem::
+   :header: Exporting a model with control flow to ONNX
+   :card_description: Demonstrate how to handle control flow logic while exporting a PyTorch model to ONNX.
+   :image: _static/img/thumbnails/cropped/Exporting-PyTorch-Models-to-ONNX-Graphs.png
+   :link: beginner/onnx/export_control_flow_model_to_onnx_tutorial.html
    :tags: Production,ONNX,Backends
 
 .. Reinforcement Learning