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Merge branch 'main' into deprecate-tensorboard-tutorials
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.github/workflows/link_checkPR.yml

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#Checks links in a PR to ensure they are valid. If link is valid but failing, it can be added to the .lycheeignore file
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#Use the skip-link-check label on a PR to skip checking links on a PR
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name: link check on PR
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on:
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pull_request:
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branches: [main]
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jobs:
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linkChecker:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v4
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with:
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fetch-depth: 1
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- name: Get Changed Files
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id: changed-files
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uses: tj-actions/changed-files@v41
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- name: Check for Skip Label
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id: skip-label
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uses: actions/github-script@v6
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with:
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script: |
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const labels = await github.rest.issues.listLabelsOnIssue({
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owner: context.repo.owner,
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repo: context.repo.repo,
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issue_number: context.issue.number
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});
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return labels.data.some(label => label.name === 'skip-link-check');
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- name: Check Links
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if: steps.skip-label.outputs.result == 'false'
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uses: lycheeverse/lychee-action@v1
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with:
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args: --accept=200,403,429 --base . --verbose --no-progress ${{ steps.changed-files.outputs.all_changed_files }}
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token: ${{ secrets.CUSTOM_TOKEN }}
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fail: true
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- name: Skip Message
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if: steps.skip-label.outputs.result == 'true'
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run: echo "Link check was skipped due to the presence of the 'skip-link-check' label."
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- name: Suggestions
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if: failure()
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run: |
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echo -e "\nPlease review the links reported in the Check links step above."
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echo -e "If a link is valid but fails due to a CAPTCHA challenge, IP blocking, login requirements, etc.,
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consider adding such links to .lycheeignore file to bypass future checks.\n"
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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"
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exit 1

.lycheeignore

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# Used for links to be ignored during the link check.
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# Add link to file along with comment as to why it should be ignored
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#Example link in some of the tutorials that should be ignored
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file:///f:/libtmp/some_file
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#Ignore links with "file:///" to catch any other example links
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file:\/\/\/.*

advanced_source/cpp_export.rst

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Loading a TorchScript Model in C++
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=====================================
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.. note:: TorchScript is no longer in active development.
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As its name suggests, the primary interface to PyTorch is the Python
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programming language. While Python is a suitable and preferred language for
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many scenarios requiring dynamism and ease of iteration, there are equally many

advanced_source/torch-script-parallelism.rst

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Dynamic Parallelism in TorchScript
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==================================
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.. note:: TorchScript is no longer in active development.
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In this tutorial, we introduce the syntax for doing *dynamic inter-op parallelism*
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in TorchScript. This parallelism has the following properties:
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advanced_source/torch_script_custom_classes.rst

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Extending TorchScript with Custom C++ Classes
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===============================================
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.. note:: TorchScript is no longer in active development.
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This tutorial is a follow-on to the
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:doc:`custom operator <torch_script_custom_ops>`
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tutorial, and introduces the API we've built for binding C++ classes into TorchScript

beginner_source/Intro_to_TorchScript_tutorial.py

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**Authors:** James Reed (jamesreed@fb.com), Michael Suo (suo@fb.com), rev2
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.. note:: TorchScript is no longer in active development.
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This tutorial is an introduction to TorchScript, an intermediate
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representation of a PyTorch model (subclass of ``nn.Module``) that
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can then be run in a high-performance environment such as C++.

beginner_source/deploy_seq2seq_hybrid_frontend_tutorial.py

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Deploying a Seq2Seq Model with TorchScript
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==================================================
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**Author:** `Matthew Inkawhich <https://github.com/MatthewInkawhich>`_
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.. note:: TorchScript is no longer in active development.
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"""
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beginner_source/former_torchies/README.txt

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beginner_source/former_torchies/autograd_tutorial_old.py

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Autograd
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==============
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This tutorial is out of date. You'll be redirected to the new tutorial in 3 seconds: https://pytorch.org/tutorials/beginner/basics/autogradqs_tutorial.html
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.. raw:: html
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<meta http-equiv="Refresh" content="3; url='https://pytorch.org/tutorials/beginner/basics/autogradqs_tutorial.html'" />

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