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CONTRIBUTING.md

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How to contribute code

Follow these steps to submit your code contribution.

You can find a list of issues that we are looking for contributors on here!

Step 1. Open an issue

Before making any changes, we recommend opening an issue (if one doesn't already exist) and discussing your proposed changes. This way, we can give you feedback and validate the proposed changes.

If your code change involves the fixing of a bug, please include a Colab notebook that shows how to reproduce the broken behavior.

If the changes are minor (simple bug fix or documentation fix), then feel free to open a PR without discussion.

Step 2. Make code changes

To make code changes, you need to fork the repository. You will need to setup a development environment and run the unit tests. This is covered in section "Setup environment".

If your code change involves introducing a new API change, please see our API Design Guidelines.

Step 3. Create a pull request

Once the change is ready, open a pull request from your branch in your fork to the master branch in keras-team/keras-cv.

Step 4. Sign the Contributor License Agreement

After creating the pull request, you will need to sign the Google CLA agreement. The agreement can be found at https://cla.developers.google.com/clas.

Step 5. Code review

CI tests will automatically be run directly on your pull request. Their status will be reported back via GitHub actions.

There may be several rounds of comments and code changes before the pull request gets approved by the reviewer.

Approval from reviewer

Step 6. Merging

Once the pull request is approved, a team member will take care of merging.

Setup environment

Setting up your KerasCV development environment requires you to fork the KerasCV repository, clone the repository, install dependencies, and execute python setup.py develop.

You can achieve this by running the following commands:

gh repo fork keras-team/keras-cv --clone --remote
cd keras-cv
pip install ".[tests]"
python setup.py develop

The first line relies on having an installation of the GitHub CLI.

Following these commands you should be able to run the tests using pytest keras_cv. Please report any issues running tests following these steps.

Run tests

KerasCV is tested using PyTest.

Run a test file

To run a test file, run pytest path/to/file from the root directory of keras_cv.

Run a single test case

To run a single test, you can use -k=<your_regex> to use regular expression to match the test you want to run. For example, you can use the following command to run all the tests in cut_mix_test.py, whose names contain label,

pytest keras_cv/layers/preprocessing/cut_mix_test.py -k="label"

Run all tests

You can run the unit tests for KerasCV by running:

pytest keras_cv/

Formatting the Code

We use flake8, isort and black for code formatting. You can run the following commands manually every time you want to format your code:

  • Run shell/format.sh to format your code
  • Run shell/lint.sh to check the result.

If after running these the CI flow is still failing, try updating flake8, isort and black. This can be done by running pip install --upgrade black, pip install --upgrade flake8, and pip install --upgrade isort.

Community Guidelines

This project follows Google's Open Source Community Guidelines.