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Contributing to CoMLRL

Thanks for your interest in helping shape CoMLRL! This guide walks you through reporting issues, contributing changes, and keeping the codebase healthy.

Before You Start

  • Review existing issues and discussions to avoid duplicating work.
  • Be respectful and collaborative; assume good intent in reviews.
  • For non-trivial changes, open an issue or discussion first so we can align on the scope.

Reporting Issues

Provide as much context as possible:

  • Environment (python --version, torch --version, CUDA info).
  • Exact commands and minimal repro cases.
  • Logs, stack traces, or screenshots.

Development Workflow

  1. Stay in sync with main
    • You should fork and track the upstream repository: 
      git clone https://github.com/<your-username>/CoMLRL.git
cd CoMLRL
git remote add upstream https://github.com/OpenMLRL/CoMLRL.git
git fetch upstream
git checkout -b feature/<short-description> upstream/main
    • Periodically resync with git fetch upstream && git rebase upstream/main (or git merge upstream/main) so your branch stays current.
  2. Implement your change
    • Keep commits focused; document behaviour changes.
    • Update READMEs, examples, or tutorials when you alter user-facing workflows.
  3. Validate locally
    • Run tests and pre-commit hooks before pushing.
    • For training scripts, run a smoke test (small dataset/few steps) and capture key metrics for your PR description.
  4. Open a pull request
    • Reference related issues or discussions.
    • Summarize changes, note test evidence, and list follow-up items if any.
    • Expect collaborative review; feedback improves quality.