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jaxtyping/CONTRIBUTING.md
Patrick Kidger e03c1c329e We now have Float[np.ndarray, ...] <: np.ndarray. Added basic torch tests. (#68)
This required quite a lot of refactoring! JAX supports virtual subclass registration (its metaclass is ABCMeta) but NumPy does not, so we have to actually subclass `np.ndarray`.
Simple stuff like __base__ hacking fails due to deallocator conflicts.
2023-03-04 17:29:04 +00:00

1.4 KiB

Contributing

Contributions (pull requests) are very welcome! Here's how to get started.


First fork the library on GitHub.

Then clone and install the library in development mode:

git clone https://github.com/your-username-here/jaxtyping.git
cd jaxtyping
pip install -e .

Then install the pre-commit hook:

pip install pre-commit
pre-commit install

These hooks use Black and isort to format the code, and flake8 to lint it.

Now make your changes. Make sure to include additional tests if necessary.

Next verify the tests all pass:

pip install pytest cloudpickle
pip install torch --extra-index-url https://download.pytorch.org/whl/cpu
pytest

Then push your changes back to your fork of the repository:

git push

Finally, open a pull request on GitHub!

Contributor License Agreement

Contributions to this project must be accompanied by a Contributor License Agreement (CLA). 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.