SparkTorch is a project that I have wanted to do for awhile, and after Pytorch released a variety of great updates to the distributed package, I decided to build a package that could easily orchestrate training on Apache Spark. The goal was to be able to easily integrate the training of Pytorch models to the Spark ML Pipeline. This was done by creating a custom estimator that could be saved and loaded for inference (or even additional training). Right now, there are two modes of training: distributed synchronous and Hogwild!. I will be continuing work on the project and would definitely enjoy collaboration.