PyTorch is an open-source machine learning library developed by Facebook’s AI Research lab. It’s widely used in academic research and industry, and its popularity continues to grow due to its flexibility, performance, and the support of a thriving community.
If you’re interested in contributing to PyTorch, there are a few things you should know before getting started. In this tutorial, we’ll cover the basics of PyTorch contribution and provide links to helpful resources to help you get started.
1. Familiarize yourself with PyTorch: Before you start contributing to PyTorch, it’s important to have a good understanding of how the library works and its key features. PyTorch provides extensive documentation on its website, including tutorials, API references, and examples. Make sure to go through these resources to familiarize yourself with the library.
2. Join the PyTorch community: PyTorch has a vibrant community of developers and researchers who are actively contributing to the library. Joining the community is a great way to connect with other contributors, learn from their experiences, and get help with your contributions. You can join the PyTorch discussion forum, subscribe to the PyTorch developer mailing list, and follow PyTorch on social media platforms like Twitter and GitHub.
3. Understand the contribution guidelines: Before you start contributing to PyTorch, it’s important to familiarize yourself with the project’s contribution guidelines. The PyTorch GitHub repository has detailed guidelines on how to contribute, including how to report bugs, submit feature requests, and make code contributions. Make sure to read these guidelines carefully to ensure that your contributions are in line with the project’s standards.
4. Start with small contributions: If you’re new to contributing to PyTorch or open-source projects in general, it’s a good idea to start with small contributions. This could include fixing typos in the documentation, writing tests for existing code, or working on small bug fixes. Starting with small contributions can help you get familiar with the PyTorch codebase and the contribution process.
5. Contribute to PyTorch codebase: Once you’re comfortable with the basics of PyTorch contribution, you can start working on more substantial contributions to the PyTorch codebase. This could include adding new features, fixing bugs, optimizing existing code, or improving the documentation. Before you start working on a new feature or a bug fix, make sure to discuss your ideas with the PyTorch community to get feedback and guidance.
6. Stay up-to-date with PyTorch development: PyTorch is constantly evolving, with new features and improvements being added regularly. To stay up-to-date with the latest developments, make sure to follow the PyTorch GitHub repository, subscribe to the PyTorch blog, and participate in community events like PyTorch conferences and hackathons. Staying informed about PyTorch development can help you identify areas where you can make meaningful contributions.
7. Get involved in PyTorch roadmap discussions: PyTorch has a public roadmap that outlines the upcoming features and improvements planned for the library. Getting involved in roadmap discussions can help you understand the direction of PyTorch development and identify opportunities to contribute. You can participate in roadmap discussions on the PyTorch discussion forum or the PyTorch GitHub repository.
By following these steps and staying engaged with the PyTorch community, you can make meaningful contributions to the library and help shape its future. And remember, contributing to PyTorch is not just about writing code – it’s also about collaborating with others, sharing knowledge, and learning from each other. Good luck on your PyTorch contribution journey!
Links:
– PyTorch website: https://pytorch.org/
– PyTorch GitHub repository: https://github.com/pytorch/pytorch
– PyTorch discussion forum: https://discuss.pytorch.org/
– PyTorch developer mailing list: https://lists.openai.com/sympa/subscribe/pytorch-ai-research
– PyTorch blog: https://pytorch.org/blog/
– PyTorch roadmap: https://github.com/pytorch/pytorch/projects/2
Good job man! Do you have any video regarding the step by step process of making the contribution like a walkthrough guide not a detailed one but general Idea. This would really helpful given that MPS you have a contribution. So you can walkthrough how you did yourself. If that make sense. Good video by the way.
Thanks Raman for this information! This is great.
Good Work. You could organize the Google doc(with links and little description), and give the links in description.