torchmix 0.1.0rc6

A collection of useful PyTorch modules

torchmix

The missing component library for PyTorch

torchmix is a collection of PyTorch modules that aims to simplify your model development process with pre-made PyTorch components. We've included a range of operations, from basic ones like Repeat and Add, to more complex ones like WindowAttention in the Swin-Transformer. Our goal is to make it easy for you to use these various operations with minimal code, so you can focus on building your project rather than writing boilerplate.

We've designed torchmix to be as user-friendly as possible. Each implementation is kept minimal and easy to understand, using einops to avoid confusing tensor manipulation (such as permute, transpose, and reshape) and jaxtyping to clearly document the shapes of the input and output tensors. This means that you can use torchmix with confidence, knowing that the components you're working with are clean and reliable.

Note: torchmix is a prototype that is currently in development and has not been tested for production use. The API may change at any time.

Install

To use torchmix, you will need to have torch already installed on your environment.

pip install torchmix

Documentation

To learn more, check out our documentation.

Contributing

The development of torchmix is an open process, and we welcome any contributions or suggestions for improvement. If you have ideas for new components or ways to enhance the library, feel free to open an issue or start a discussion. We welcome all forms of feedback, including criticism and suggestions for significant design changes. Please note that torchmix is currently in the early stages of development and any contributions should be considered experimental. Thank you for your support of torchmix!

License

torchmix is licensed under the MIT License.