RAZOR is a library that bridges PyTorch and TVM. Currently users have to make substantial changes to their existing PyTorch training scripts in order to convert it to a TVM model. Built upon PyTorch Lazy Tensor, RAZOR aims to provide smooth user experience by running PyTorch training scripts on TVM with little (2-3 lines) or no code change. It allows users to benefit from the performance boost and heterogeneous backends supported by TVM while retaining the PyTorch imperative programming experience.
This session is broken into two parts, a 10 minute talk followed by a 5 minute breakout session.