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Contributing guidelines

How to become a contributor and submit your own code

Contributor License Agreements

We'd love to accept your patches! Before we can take them, we have to jump a couple of legal hurdles.

Please fill out either the individual or corporate Contributor License Agreement (CLA).

  • If you are an individual writing original source code and you're sure you own the intellectual property, then you'll need to sign an individual CLA.
  • If you work for a company that wants to allow you to contribute your work, then you'll need to sign a corporate CLA.

Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.

NOTE: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.

Contributing code

If you have improvements to LiteRT, send us your pull requests! For those just getting started, Github has a howto.

LiteRT team members will be assigned to review your pull requests. Once the pull requests are approved and pass continuous integration checks, we will merge the pull requests. For some pull requests, we will apply the patch for each pull request to our internal version control system first, and export the change out as a new commit later, at which point the original pull request will be closed. The commits in the pull request will be squashed into a single commit with the pull request creator as the author. These pull requests will be labeled as pending merge internally.

C++ coding style

Changes to TensorFlow C++ code should conform to Google C++ Style Guide.

Use clang-tidy to check your C/C++ changes. To install clang-tidy on ubuntu:16.04, do:

apt-get install -y clang-tidy

You can check a C/C++ file by doing:

clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc
diff <my_cc_file> /tmp/my_cc_file.cc

Python coding style

Changes to TensorFlow Python code should conform to Google Python Style Guide

Use pylint to check your Python changes. To install pylint and check a file with pylint against TensorFlow's custom style definition:

pip install pylint
pylint --rcfile=tensorflow/tools/ci_build/pylintrc myfile.py

Note pylint --rcfile=tensorflow/tools/ci_build/pylintrc should run from the top level tensorflow directory.

Coding style for other languages

License

Include a license at the top of new files.