add tests & update documentation for ml‑assert core functionality #2
Description
As the maintainer of ml‑assert, I’m looking to expand and solidify our library through testing and documentation enhancements. We welcome contributors to help with the following:
✅ 1. Add/expand pytest unit tests
Cover key assertion functions—e.g., edge cases, expected failures, valid inputs.
Include ML‑specific scenarios like tensor shape mismatches or floating‑point tolerance.
Ensure CI catches regressions.
✍️ 2. Improve documentation or user guide
Provide clear examples: how to pip install, import, and use typical functions in pipelines.
Showcase common workflows (e.g. comparing arrays, validating model outputs).
Highlight troubleshooting tips or performance notes.
🎯 3. Add badges/configs (optional but valuable)
Integration with CI (GitHub Actions): tests + lint.
Coverage reports (e.g. Codecov).
Docs site readiness, if applicable.