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Contributing

Interested in contributing to TensorFlow Addons? We appreciate all kinds of help and are working to make this guide as comprehensive as possible. Please let us know if you think of something we could do to help lower the barrier to contributing.

Pull Requests

We gladly welcome pull requests.

Before making any changes, we recommend opening an issue (if it doesn't already exist) and discussing your proposed changes. This will let us give you advice on the proposed changes. If the changes are minor, then feel free to make them without discussion.

Want to contribute but not sure of what? Here are a few suggestions:

  1. Add a new example or tutorial. Located in tensorflow_addons/examples/, these are a great way to familiarize yourself and others with TF-Addons.
  2. Solve an existing issue. These range from low-level software bugs to higher-level design problems. Check out the label help wanted. If you're a new contributor, the label good first issue can be a good place to start.

All submissions, including submissions by project members, require review.

Requirements for New Contributions to the Repository

The tensorflow/addons repository contains additional functionality fitting the following criteria:

  • The functionality is not otherwise available in TensorFlow
  • Addons have to be compatible with TensorFlow 2.x.
  • The addon conforms to the code and documentation standards
  • The addon is impactful to the community (e.g. an implementation used in widely cited paper)
  • Lastly, the functionality conforms to the contribution guidelines of its API pattern:

Note: New contributions often require team-members to read a research paper and understand how it fits into the TensorFlow community. This process can take longer than typical commit reviews so please bare with us

Development Environment

It is recommended that development is done in the latest nightly-custom-op docker image.

docker run --rm -it -v ${PWD}:/addons -w /addons tensorflow/tensorflow:nightly-custom-op /bin/bash

Try those commands below:

  1. Format codes automatically: make code-format
  2. Sanity check: make sanity-check
  3. Run unit test: make unit-test
  4. All of the above: make

Coding style

Addons provides make code-format command to format your changes automatically, don't forget to use it before pushing your codes.

Please see our Style Guide for more details.

Code Testing

CI Testing

We're in the process of setting up our nightly CI testing. Because this project will contain CUDA kernels, we need to make sure that the hardware will be available from our CI provider.

Locally Testing

docker run --rm -it -v ${PWD}:/addons -w /addons tensorflow/tensorflow:nightly-custom-op make unit-test

or run manually:

docker run --rm -it -v ${PWD}:/addons -w /addons tensorflow/tensorflow:nightly-custom-op /bin/bash

./configure.sh  # Links project with TensorFlow dependency

bazel test -c opt -k \
--test_timeout 300,450,1200,3600 \
--test_output=errors \
//tensorflow_addons/...

Code Reviews

All submissions, including submissions by project members, require review. We use Github pull requests for this purpose.

Contributor License Agreement

Contributions to this project must be accompanied by a Contributor License Agreement. You (or your employer) retain the copyright to your contribution; this simply gives us permission to use and redistribute your contributions as part of the project. Head over to https://cla.developers.google.com/ to see your current agreements on file or to sign a new one.

You generally only need to submit a CLA once, so if you've already submitted one (even if it was for a different project), you probably don't need to do it again.