Contribute to Avalanche

How to Contribute Back to the Avalanche Community

The last step to become a real continual learning super-hero ⚡ is to fall into a radioactive dump.☢️ Just kidding, it's much easier than that: you need to contribute back to Avalanche!

There are no superheroes that are not altruistic!

In order to contribute to Avalanche, first of all you need to become familiar with all its features and the codebase structure, so if you have not followed the "From Zero to Hero Tutorial" from the beginning we suggest to do it before starting to make changes.

First of all, install Avalanche in "Developer Mode" if you haven't already. After you've familiarized with the Avalanche codebase you have two roads ahead of you:

  1. You can start working on a open issue (we have dozen of them!)

  2. You can submit a feature-request and propose yourself to work on it.

Examples of Avalanche Issues available on GitHub

In any of the two cases you'd need to follow the steps below:

  1. Join our Slack and #avalanche-dev channel (optional but recommended)

  2. Star + 👁️watch the repository.

  3. Fork the repository.

  4. Create or assign an existing issue/feature to yourself.

  5. Make your changes.

  6. Make a Pull Request (PR).

The following rules should be respected:

  • Use PEP8 coding style and work within the 80 columns limit.

  • Always pull before pushing a commit.

  • Try to assign to yourself one issue at a time.

  • Try closing an issue within roughly 7 days. If you are not able to do that, please break it down into multiple ones you can tackle more easily, or you can always remove your assignment to the issue!

  • If you add a new feature, please include also a test and a usage example in your PR.

Also, before making your PR make sure that the following commands return without any errors:

pycodestyle avalanche tests examples
python -m unittest discover -v

Otherwise fix them and run again these commands until everything is working correctly. You should also check if everything is working on GPUs, using the env variable USE_GPU=True:

USE_GPU=True python -m unittest discover -v

Faster integrity checks can be run with the env variable FAST_TEST=True :

USE_GPU=False FAST_TEST=True python -m unittest discover -v

Contribute to the Avalanche documentation

Apart from the code, you can also contribute to the Avalanche documentation 📚! We use Jupyter notebooks to write the documentation, so both code and text can be smoothly inserted, and, as you may have noticed, all our documentation can be run on Google Colab!

To contribute to the documentation you need to follow the steps below:

  1. The notebooks are contained in the folder notebooks. The folder structure is specular to the documentation, so do not create or delete any folder.

  2. Detect the notebook that you want to edit and do all the modifications 📝

  3. Commit the changes and open a pull request (PR).

  4. If your pull request will be accepted, your edited notebooks will be automatically converted and uploaded to the official Avalanche website 🎊!

🤝 Run it on Google Colab

You can run this chapter and play with it on Google Colaboratory: Open In Colab