Good First Contributions

We welcome contributions to Flower! However, it is not always easy to know where to start. We therefore put together a few recommendations on where to start to increase your chances of getting your PR accepted into the Flower codebase.

Where to Start

Until the Flower core library matures it will be easier to get PR’s accepted if they only touch non-core areas of the codebase. Good candidates to get started are:

  • Documentation: What’s missing? What could be expressed more clearly?

  • Examples: See below.

Request for Examples

We wish we had more time to write usage examples because we believe they help users to get started with building what they want to build. Here are a few ideas where we’d be happy to accept a PR:

  • First scikit-learn example (MNIST)

  • First MXNet 1.6 example (MNIST)

  • ImageNet (PyTorch/TensorFlow)

  • LSTM (PyTorch/TensorFlow)

  • Transformer (PyTorch/TensorFlow)

  • BERT (PyTorch/TensorFlow)