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CONTRIBUTING.md

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Contributing to TorchONNX

Contributions are welcome from the community. Whether fixing bugs, adding features, improving documentation, or sharing ideas, all contributions are appreciated.

Development Setup

  1. Fork and clone the repository:

    git clone https://github.com/YOUR_USERNAME/torchonnx.git
cd torchonnx

  2. Install in development mode with dev dependencies:

    pip install -e ".[dev]"

  3. Install pre-commit hooks:

    pre-commit install

Code Quality Standards

  • Linting: Code must pass ruff check and ruff format --check
  • Type checking: Code must pass mypy static analysis
  • Testing: All tests must pass with pytest tests/
  • Coverage: New code should include tests to maintain coverage

Run quality checks locally:

# Lint check
ruff check src/torchonnx tests
ruff format --check src/torchonnx tests

# Type check
mypy .

# Run tests
pytest tests/

Pull Request Workflow

Note: Direct pushes to the main branch are restricted. All changes must go through Pull Requests.

  1. Create a feature branch:

    git checkout -b feature/your-feature-name

  2. Make your changes:

    • Write code following existing patterns
    • Add tests for new functionality
    • Update documentation if needed
    • Ensure all quality checks pass

  3. Commit your changes:

    git add .
git commit -m "Brief description of changes"

  4. Push to your fork:

    git push origin feature/your-feature-name

  5. Create a Pull Request:

    • Go to the original repository on GitHub
    • Click "New Pull Request"
    • Select your fork and branch
    • Provide a clear description of your changes
    • Reference any related issues

  6. Address review feedback:

    • Reviewers may request changes
    • Push additional commits to the same branch
    • The PR will update automatically

Testing

Testing Your Changes

Run the full test suite:

pytest tests/ -v

Run with coverage:

pytest tests/ --cov=src/torchonnx --cov-report=term-missing

Run specific test files:

pytest tests/test_units/test_torchonnx/test_pipeline.py -v

Code Style Guidelines

  • Follow PEP 8 conventions (enforced by ruff)
  • Use type hints for all function signatures
  • Write docstrings using reStructuredText format
  • Keep functions focused and single-purpose
  • Prefer explicit over implicit

Reporting Issues

When reporting bugs or requesting features:

  • Check if the issue already exists
  • Provide a minimal reproducible example
  • Include ONNX model details and error messages
  • Specify your environment (Python version, PyTorch version, OS)