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<p class="caption" role="heading"><span class="caption-text">Community</span></p>
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<li class="toctree-l1 current"><a class="current reference internal" href="#">PyTorch Contribution Guide</a></li>
<li class="toctree-l1"><a class="reference internal" href="design.html">PyTorch Design Philosophy</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../notes/amp_examples.html">CUDA Automatic Mixed Precision examples</a></li>
<li class="toctree-l1"><a class="reference internal" href="../notes/autograd.html">Autograd mechanics</a></li>
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<p class="caption"><span class="caption-text">Python API</span></p>
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<section id="pytorch-contribution-guide">
<h1>PyTorch Contribution Guide<a class="headerlink" href="#pytorch-contribution-guide" title="Permalink to this heading">¶</a></h1>
<p>PyTorch is a GPU-accelerated Python tensor computation package for
building deep neural networks using a on tape-based autograd systems.</p>
<section id="contribution-process">
<h2>Contribution Process<a class="headerlink" href="#contribution-process" title="Permalink to this heading">¶</a></h2>
<p>The PyTorch organization is governed by <a class="reference internal" href="governance.html"><span class="doc">PyTorch
Governance</span></a> and the technical guide to contributing
can be found in <a class="reference external" href="https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md">CONTRIBUTING.md</a>.</p>
<p>The PyTorch development process involves a healthy amount of open
discussions between the core development team and the community.</p>
<p>PyTorch operates similarly to most open source projects on GitHub.
However, if you’ve never contributed to an open source project before,
here is the basic process.</p>
<ul class="simple">
<li><p><strong>Figure out what you’re going to work on.</strong> The majority of open
source contributions come from people scratching their own itches.
However, if you don’t know what you want to work on, or are just
looking to get more acquainted with the project, here are some tips
for how to find appropriate tasks:</p>
<ul>
<li><p>Look through the <a class="reference external" href="https://github.com/pytorch/pytorch/issues/">issue
tracker</a> and see if
there are any issues you know how to fix. Issues that are
confirmed by other contributors tend to be better to investigate.
We also maintain some labels for issues that are likely to be
good for new people, e.g., <strong>bootcamp</strong> and <strong>1hr</strong>, although
these labels are less well maintained.</p></li>
<li><p>Join us on <a class="reference external" href="https://dev-discuss.pytorch.org/">dev discuss</a>
and let us know you’re interested in getting to
know PyTorch. We’re very happy to help out researchers and
partners get up to speed with the codebase.</p></li>
</ul>
</li>
<li><p><strong>Figure out the scope of your change and reach out for design
comments on a GitHub issue if it’s large.</strong> The majority of pull
requests are small; in that case, no need to let us know about what
you want to do, just get cracking. But if the change is going to be
large, it’s usually a good idea to get some design comments about it
first by <a class="reference external" href="https://github.com/pytorch/rfcs/blob/master/README.md">submitting an RFC</a>.</p>
<ul>
<li><p>If you don’t know how big a change is going to be, we can help you
figure it out! Just post about it on
<a class="reference external" href="https://github.com/pytorch/pytorch/issues/">issues</a> or
<a class="reference external" href="https://dev-discuss.pytorch.org/">dev discuss</a>.</p></li>
<li><p>Some feature additions are very standardized; for example, lots of
people add new operators or optimizers to PyTorch. Design
discussion in these cases boils down mostly to, “Do we want this
operator/optimizer?” Giving evidence for its utility, e.g., usage
in peer reviewed papers, or existence in other frameworks, helps a
bit when making this case.</p>
<ul>
<li><p><strong>Adding operators / algorithms from recently-released research</strong>
is generally not accepted unless there is overwhelming evidence that
this newly published work has ground-breaking results and will eventually
become a standard in the field. If you are not sure where your method falls,
open an issue first before implementing a PR.</p></li>
</ul>
</li>
<li><p>Core changes and refactors can be quite difficult to coordinate
since the pace of development on PyTorch master is quite fast.
Definitely reach out about fundamental or cross-cutting changes;
we can often give guidance about how to stage such changes into
more easily reviewable pieces.</p></li>
</ul>
</li>
<li><p><strong>Code it out!</strong></p>
<ul>
<li><p>See the <a class="reference external" href="https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md">CONTRIBUTING.md</a> file for advice for working with PyTorch in a
technical form.</p></li>
</ul>
</li>
<li><p><strong>Open a pull request.</strong></p>
<ul>
<li><p>If you are not ready for the pull request to be reviewed, create a draft
pull request first - you can later convert it to a full PR by pressing
“Ready for review” button. You can also prepend the title of the PR with
“[WIP]” (“work in progress”) while it’s still in draft. We will ignore
draft PRs when doing review passes. If you are working on a complex change,
it’s good to start things off as a draft, because you will need to spend
time looking at CI results to see if things worked out or not.</p></li>
<li><p>Find an appropriate reviewer for your change. We have some folks
who regularly go through the PR queue and try to review
everything, but if you happen to know who the maintainer for a
given subsystem affected by your patch is, feel free to include
them directly on the pull request. You can learn more about
<a class="reference external" href="https://pytorch.org/docs/master/community/persons_of_interest.html">Persons of Interest</a>
that could review your code.</p></li>
</ul>
</li>
<li><p><strong>Iterate on the pull request until it’s accepted!</strong></p>
<ul>
<li><p>We’ll try our best to minimize the number of review round trips and
block PRs only when there are major issues. For the most common
issues in pull requests, take a look at <a class="reference external" href="#common-mistakes-to-avoid">Common Mistakes</a>.</p></li>
<li><p>Once a pull request is accepted and CI is passing, there is
nothing else you need to do; we will merge the PR for you.</p></li>
</ul>
</li>
</ul>
</section>
<section id="getting-started">
<h2>Getting Started<a class="headerlink" href="#getting-started" title="Permalink to this heading">¶</a></h2>
<section id="proposing-new-features">
<h3>Proposing New Features<a class="headerlink" href="#proposing-new-features" title="Permalink to this heading">¶</a></h3>
<p>New feature ideas are best discussed on a specific issue. Please include
as much information as you can, any accompanying data, and your proposed
solution. The PyTorch team and community frequently review new issues
and comments where they think they can help. If you feel confident in
your solution, go ahead and implement it.</p>
</section>
<section id="reporting-issues">
<h3>Reporting Issues<a class="headerlink" href="#reporting-issues" title="Permalink to this heading">¶</a></h3>
<p>If you’ve identified an issue, first search through the <a class="reference external" href="https://github.com/pytorch/pytorch/issues">list of
existing issues</a> on the
repo. If you are unable to find a similar issue, then create a new one.
Supply as much information you can to reproduce the problematic
behavior. Also, include any additional insights like the behavior you
expect.</p>
</section>
<section id="implementing-features-or-fixing-bugs">
<h3>Implementing Features or Fixing Bugs<a class="headerlink" href="#implementing-features-or-fixing-bugs" title="Permalink to this heading">¶</a></h3>
<p>If you want to fix a specific issue, it’s best to comment on the
individual issue with your intent. However, we do not lock or assign
issues except in cases where we have worked with the developer before.
It’s best to strike up a conversation on the issue and discuss your
proposed solution. The PyTorch team can provide guidance that saves you
time.</p>
<p>Issues that are labeled first-new-issue, low, or medium priority provide
the best entrance point are great places to start.</p>
</section>
<section id="adding-tutorials">
<h3>Adding Tutorials<a class="headerlink" href="#adding-tutorials" title="Permalink to this heading">¶</a></h3>
<p>A great deal of the tutorials on <a class="reference external" href="https://pytorch.org/">pytorch.org</a>
come from the community itself and we welcome additional contributions.
To learn more about how to contribute a new tutorial you can learn more
here: <a class="reference external" href="https://github.com/pytorch/tutorials/#contributing">PyTorch.org Tutorial Contribution Guide on
Github</a></p>
</section>
<section id="improving-documentation-tutorials">
<h3>Improving Documentation & Tutorials<a class="headerlink" href="#improving-documentation-tutorials" title="Permalink to this heading">¶</a></h3>
<p>We aim to produce high quality documentation and tutorials. On rare
occasions that content includes typos or bugs. If you find something you
can fix, send us a pull request for consideration.</p>
<p>Take a look at the <a class="reference external" href="#on-documentation">Documentation</a> section to learn how our system
works.</p>
</section>
<section id="participating-in-online-discussions">
<h3>Participating in Online Discussions<a class="headerlink" href="#participating-in-online-discussions" title="Permalink to this heading">¶</a></h3>
<p>You can find active discussions happening on the <a class="reference external" href="https://discuss.pytorch.org/">PyTorch Discussion
Forums</a> for users as well as the
<a class="reference external" href="https://dev-discuss.pytorch.org/">PyTorch Dev Discussion Forums</a>
for developers and maintainers.</p>
</section>
<section id="submitting-pull-requests-to-fix-open-issues">
<h3>Submitting Pull Requests to Fix Open Issues<a class="headerlink" href="#submitting-pull-requests-to-fix-open-issues" title="Permalink to this heading">¶</a></h3>
<p>You can view a list of all open issues
<a class="reference external" href="https://github.com/pytorch/pytorch/issues">here</a>. Commenting on an
issue is a great way to get the attention of the team. From here you can
share your ideas and how you plan to resolve the issue.</p>
<p>For more challenging issues, the team will provide feedback and
direction for how to best solve the issue.</p>
<p>If you’re not able to fix the issue yourself, commenting and sharing
whether you can reproduce the issue can help the team
identify problem areas.</p>
</section>
<section id="reviewing-open-pull-requests">
<h3>Reviewing Open Pull Requests<a class="headerlink" href="#reviewing-open-pull-requests" title="Permalink to this heading">¶</a></h3>
<p>We appreciate your help reviewing and commenting on pull requests. Our
team strives to keep the number of open pull requests at a manageable
size, we respond quickly for more information if we need it, and we
merge PRs that we think are useful. However, due to the high level of
interest, additional eyes on the pull requests are always appreciated.</p>
</section>
<section id="improving-code-readability">
<h3>Improving Code Readability<a class="headerlink" href="#improving-code-readability" title="Permalink to this heading">¶</a></h3>
<p>Improving code readability helps everyone. It is often better to submit a
small number of pull requests that touch a few files versus a large pull
request that touches many files. Starting a discussion in the PyTorch
forum <a class="reference external" href="https://discuss.pytorch.org/">here</a> or on an issue related to
your improvement is the best way to get started.</p>
</section>
<section id="adding-test-cases-to-make-the-codebase-more-robust">
<h3>Adding Test Cases to Make the Codebase More Robust<a class="headerlink" href="#adding-test-cases-to-make-the-codebase-more-robust" title="Permalink to this heading">¶</a></h3>
<p>Additional test coverage is appreciated.</p>
</section>
<section id="promoting-pytorch">
<h3>Promoting PyTorch<a class="headerlink" href="#promoting-pytorch" title="Permalink to this heading">¶</a></h3>
<p>Your use of PyTorch in your projects, research papers, write ups, blogs,
or general discussions around the internet helps to raise awareness for
PyTorch and our growing community. Please reach out to
<a class="reference external" href="mailto:marketing%40pytorch.org">marketing<span>@</span>pytorch<span>.</span>org</a>
for marketing support.</p>
</section>
<section id="triaging-issues">
<h3>Triaging Issues<a class="headerlink" href="#triaging-issues" title="Permalink to this heading">¶</a></h3>
<p>If you feel that an issue could benefit from a particular tag or level
of complexity, comment on the issue and share your opinion. If you
feel an issue isn’t categorized properly, comment and let the team know.</p>
</section>
</section>
<section id="about-open-source-development">
<h2>About Open Source Development<a class="headerlink" href="#about-open-source-development" title="Permalink to this heading">¶</a></h2>
<p>If this is your first time contributing to an open source project, some
aspects of the development process may seem unusual to you.</p>
<ul class="simple">
<li><p><strong>There is no way to “claim” issues.</strong> People often want to “claim”
an issue when they decide to work on it, to ensure that there isn’t
wasted work when someone else ends up working on it. This doesn’t
really work too well in open source, since someone may decide to work
on something, and end up not having time to do it. Feel free to give
information in an advisory fashion, but at the end of the day, we
will take running code and rough consensus to move forward quickly.</p></li>
<li><p><strong>There is a high bar for new functionality.</strong> Unlike
in a corporate environment, where the person who wrote code
implicitly “owns” it and can be expected to take care of it for the
code’s lifetime, once a pull request is merged into an open
source project, it immediately becomes the collective responsibility
of all maintainers on the project. When we merge code, we are saying
that we, the maintainers, can review subsequent changes and
make a bugfix to the code. This naturally leads to a higher standard
of contribution.</p></li>
</ul>
</section>
<section id="common-mistakes-to-avoid">
<h2>Common Mistakes To Avoid<a class="headerlink" href="#common-mistakes-to-avoid" title="Permalink to this heading">¶</a></h2>
<ul class="simple">
<li><p><strong>Did you add tests?</strong> (Or if the change is hard to test, did you
describe how you tested your change?)</p>
<ul>
<li><p>We have a few motivations for why we ask for tests:</p>
<ol class="arabic simple">
<li><p>to help us tell if we break it later</p></li>
<li><p>to help us tell if the patch is correct in the first place
(yes, we did review it, but as Knuth says, “beware of the
following code, for I have not run it, merely proven it
correct”)</p></li>
</ol>
</li>
<li><p>When is it OK not to add a test? Sometimes a change can’t be
conveniently tested, or the change is so obviously correct (and
unlikely to be broken) that it’s OK not to test it. On the
contrary, if a change seems likely (or is known to be likely)
to be accidentally broken, it’s important to put in the time to
work out a testing strategy.</p></li>
</ul>
</li>
<li><p><strong>Is your PR too long?</strong></p>
<ul>
<li><p>It’s easier for us to review and merge small PRs. The difficulty of
reviewing a PR scales nonlinearly with its size.</p></li>
<li><p>When is it OK to submit a large PR? It helps a lot if there was a
corresponding design discussion in an issue, with sign off from
the people who are going to review your diff. We can also help
give advice about how to split up a large change into individually
shippable parts. Similarly, it helps if there is a complete
description of the contents of the PR: it’s easier to review code
if we know what’s inside!</p></li>
</ul>
</li>
<li><p><strong>Comments for subtle things?</strong> In cases where the behavior of your code
is nuanced, please include extra comments and documentation to allow
us to better understand the intention of your code.</p></li>
<li><p><strong>Did you add a hack?</strong> Sometimes, the right answer is a hack. But
usually, we will have to discuss it.</p></li>
<li><p><strong>Do you want to touch a very core component?</strong> To prevent
major regressions, pull requests that touch core components receive
extra scrutiny. Make sure you’ve discussed your changes with the team
before undertaking major changes.</p></li>
<li><p><strong>Want to add a new feature?</strong> If you want to add new features,
comment your intention on the related issue. Our team tries to
comment on and provide feedback to the community. It’s better to have
an open discussion with the team and the rest of the community before
building new features. This helps us stay aware of what you’re
working on and increases the chance that it’ll be merged.</p></li>
<li><p><strong>Did you touch code unrelated to the PR?</strong> To aid in code review,
please only include files in your pull request that are directly
related to your changes.</p></li>
</ul>
</section>
<section id="frequently-asked-questions">
<h2>Frequently Asked Questions<a class="headerlink" href="#frequently-asked-questions" title="Permalink to this heading">¶</a></h2>
<ul class="simple">
<li><p><strong>How can I contribute as a reviewer?</strong> There is lots of value if
community developers reproduce issues, try out new functionality, or
otherwise help us identify or troubleshoot issues. Commenting on
tasks or pull requests with your environment details is helpful and
appreciated.</p></li>
<li><p><strong>CI tests failed, what does it mean?</strong> Maybe your PR is based
off a broken master? You can try to rebase your change on top
of the latest master. You can also see the current status of
master’s CI at <a class="reference external" href="https://hud.pytorch.org/">https://hud.pytorch.org/</a>.</p></li>
<li><p><strong>What are the most high risk changes?</strong> Anything that touches build
configuration is a risky area. Please avoid changing these unless
you’ve had a discussion with the team beforehand.</p></li>
<li><p><strong>Hey, a commit showed up on my branch, what’s up with that?</strong>
Sometimes another community member will provide a patch or fix to
your pull request or branch. This is often needed for getting CI tests
to pass.</p></li>
</ul>
</section>
<section id="on-documentation">
<h2>On Documentation<a class="headerlink" href="#on-documentation" title="Permalink to this heading">¶</a></h2>
<section id="python-docs">
<h3>Python Docs<a class="headerlink" href="#python-docs" title="Permalink to this heading">¶</a></h3>
<p>PyTorch documentation is generated from python source using
<a class="reference external" href="https://www.sphinx-doc.org/en/master/">Sphinx</a>. Generated HTML is
copied to the docs folder in the master branch of
<a class="reference external" href="https://github.com/pytorch/pytorch.github.io/tree/master/docs">pytorch.github.io</a>,
and is served via GitHub pages.</p>
<ul class="simple">
<li><p>Site: <a class="reference external" href="https://pytorch.org/docs">https://pytorch.org/docs</a></p></li>
<li><p>GitHub: <a class="reference external" href="https://github.com/pytorch/pytorch/tree/master/docs">https://github.com/pytorch/pytorch/tree/master/docs</a></p></li>
<li><p>Served from:
<a class="reference external" href="https://github.com/pytorch/pytorch.github.io/tree/master/docs">https://github.com/pytorch/pytorch.github.io/tree/master/doc</a></p></li>
</ul>
</section>
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<h3>C++ Docs<a class="headerlink" href="#c-docs" title="Permalink to this heading">¶</a></h3>
<p>For C++ code we use Doxygen to generate the content files. The C++ docs
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<li><p>Site: <a class="reference external" href="https://pytorch.org/cppdocs">https://pytorch.org/cppdocs</a></p></li>
<li><p>GitHub: <a class="reference external" href="https://github.com/pytorch/pytorch/tree/master/docs/cpp">https://github.com/pytorch/pytorch/tree/master/docs/cpp</a></p></li>
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<section id="tutorials">
<h2>Tutorials<a class="headerlink" href="#tutorials" title="Permalink to this heading">¶</a></h2>
<p>PyTorch tutorials are documents used to help understand using PyTorch to
accomplish specific tasks or to understand more holistic concepts.
Tutorials are built using
<a class="reference external" href="https://sphinx-gallery.readthedocs.io/en/latest/index.html">Sphinx-Gallery</a>
from executable python source files, or from restructured-text (rst)
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<ul class="simple">
<li><p>Site: <a class="reference external" href="https://pytorch.org/tutorials">https://pytorch.org/tutorials</a></p></li>
<li><p>GitHub: <a class="reference external" href="https://github.com/pytorch/tutorials">https://github.com/pytorch/tutorials</a></p></li>
</ul>
<section id="tutorials-build-overview">
<h3>Tutorials Build Overview<a class="headerlink" href="#tutorials-build-overview" title="Permalink to this heading">¶</a></h3>
<p>For tutorials, <a class="reference external" href="https://github.com/pytorch/tutorials/pulls">pull
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<section id="contributing-a-new-tutorial">
<h3>Contributing a New Tutorial<a class="headerlink" href="#contributing-a-new-tutorial" title="Permalink to this heading">¶</a></h3>
<p>See <a class="reference external" href="https://github.com/pytorch/tutorials/#contributing">PyTorch.org Tutorial Contribution
Guide</a>.</p>
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