Transitioning From PyTorch to Burn

Deep learning development requires very high-level abstractions as well as extremely fast execution time, and this is exactly where Burn shines. Burn is a comprehensive deep learning framework in Rust which focuses on flexibility, compute efficiency and portability. It can easily be used with different backends to support many devices and use cases.

Implementing your model with Burn is pretty straightforward thanks to the provided building blocks. But what if you already have a model that you trained with PyTorch …

abstractions cases compute deep learning deeplearning deep learning development deep learning framework development devices efficiency flexibility framework opensource portability python pytorch rust support use cases