If you are interested in contributing to CLX, your contributions will fall into three categories:
- You want to report a bug, feature request, or documentation issue
- File an issue describing what you encountered or what you want to see changed.
- The RAPIDS team will evaluate the issues and triage them, scheduling them for a release. If you believe the issue needs priority attention comment on the issue to notify the team.
- You want to propose a new Feature and implement it
- Post about your intended feature, and we shall discuss the design and implementation.
- Once we agree that the plan looks good, go ahead and implement it, using the code contributions guide below.
- You want to implement a feature or bug-fix for an outstanding issue
- Follow the code contributions guide below.
- If you need more context on a particular issue, please ask and we shall provide.
- Read the project's README.md to learn how to setup the development environment
- Find an issue to work on. The best way is to look for the good first issue or help wanted labels
- Comment on the issue saying you are going to work on it
- Fork the CLX repo and Code! Make sure to update unit tests!
- When done, create your pull request
- Verify that CI passes all status checks. Fix if needed
- Wait for other developers to review your code and update code as needed
- Once reviewed and approved, a RAPIDS developer will merge your pull request
Remember, if you are unsure about anything, don't hesitate to comment on issues and ask for clarifications!
Once you have gotten your feet wet and are more comfortable with the code, you can look at the prioritized issues of our next release in our project boards.
Pro Tip: Always look at the release board with the highest number for issues to work on. This is where RAPIDS developers also focus their efforts.
Look at the unassigned issues, and find an issue you are comfortable with contributing to. Start with Step 3 from above, commenting on the issue to let others know you are working on it. If you have any questions related to the implementation of the issue, ask them in the issue instead of the PR.
CLX uses Black,
isort, and
flake8 to ensure a consistent code format
throughout the project. Black, isort, and flake8 can be installed with
conda or pip:
conda install black isort flake8pip install black isort flake8These tools are used to auto-format the Python code, as well as check the Cython code in the repository. Additionally, there is a CI check in place to enforce that committed code follows our standards. You can use the tools to automatically format your python code by running:
isort --atomic python/**/*.py
black pythonand then check the syntax of your Python code by running:
flake8 pythonAdditionally, many editors have plugins that will apply isort and Black as
you edit files, as well as use flake8 to report any style / syntax issues.
Optionally, you may wish to setup pre-commit hooks
to automatically run isort, Black, and flake8 when you make a git commit.
This can be done by installing pre-commit via conda or pip:
conda install -c conda-forge pre_commitpip install pre-commitand then running:
pre-commit installfrom the root of the CLX repository. Now isort, Black, and flake8 will be
run each time you commit changes.
The following instructions are for developers and contributors to CLX OSS development. These instructions are tested on Linux Ubuntu 18.04 & 20.04. Use these instructions to build CLX from source and contribute to its development. Other operating systems may be compatible, but are not currently tested.
The following instructions are tested on Linux systems.
CUDA requirement:
- CUDA 11.5
- NVIDIA driver 470.82+
- Pascal architecture or better
You can obtain CUDA from https://developer.nvidia.com/cuda-downloads.
To install CLX from source, ensure the dependencies are met and follow the steps below:
Clone the repository and submodules:
# Set the location to CLX in an environment variable CLX_HOME
export CLX_HOME=$(pwd)/clx
# Download the CLX repo
git clone https://github.com/rapidsai/clx.git $CLX_HOMECreate the conda development environment:
# create the conda environment (assuming in base `clx` directory)
mamba env create --name clx_dev --file conda/environments/clx_dev_cuda11.5.yml
# activate the environment
conda activate clx_dev
# to deactivate an environment
conda deactivateThe environment can be updated as development includes/changes the dependencies. To do so, run:
mamba env update --name clx_dev --file conda/environments/clx_dev_cuda11.5.yml
conda activate clx_devBuild the clx python package:
$ cd $CLX_HOME/python
$ python setup.py installPython API documentation can be generated from docs directory.
Portions adopted from https://github.com/pytorch/pytorch/blob/master/CONTRIBUTING.md