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Contributing to DragonNPU

First off, thank you for considering contributing to DragonNPU! We're building the future of AI acceleration on Linux, and every contribution helps.

🚀 How to Contribute

Reporting Bugs

  • Check if the bug has already been reported in Issues
  • Create a detailed bug report including:
    • NPU hardware (vendor, model)
    • Linux kernel version
    • Python version
    • Steps to reproduce
    • Expected vs actual behavior

Suggesting Enhancements

  • Open an issue with the enhancement label
  • Describe the feature and its use case
  • Explain how it benefits NPU acceleration

Pull Requests

  1. Fork the repository
  2. Create a feature branch (git checkout -b feature/amazing-feature)
  3. Make your changes
  4. Run tests (python3 -m pytest tests/)
  5. Commit with descriptive message
  6. Push to your fork
  7. Open a Pull Request

🏗️ Development Setup

# Clone repository
git clone https://github.com/dragonfire/dragon-npu.git
cd dragon-npu

# Install in development mode
pip install -e ".[dev]"

# Run tests
python3 -m pytest tests/

# Run benchmarks
python3 dragon_npu_cli.py benchmark

📝 Code Style

  • Follow PEP 8
  • Use type hints where possible
  • Add docstrings to all functions/classes
  • Keep functions focused and small
  • Comment complex NPU-specific logic

🧪 Testing

  • Write tests for new features
  • Ensure all tests pass before submitting PR
  • Include performance benchmarks for NPU operations

📚 Documentation

  • Update README.md for user-facing changes
  • Add docstrings for new APIs
  • Include examples for new features

🎯 Priority Areas

We especially welcome contributions in:

  • Support for new NPU vendors (Intel VPU, Qualcomm, etc.)
  • Model optimization techniques
  • Performance improvements
  • Documentation and examples
  • Cross-platform compatibility

🤝 Code of Conduct

  • Be respectful and inclusive
  • Welcome newcomers
  • Focus on constructive feedback
  • Celebrate the pioneering spirit of open-source NPU development

📬 Contact

🙏 Recognition

Contributors will be recognized in:

  • README.md contributors section
  • Release notes
  • The eternal gratitude of the Linux AI community!

Together, we're democratizing AI acceleration! 🐉🔥