We are exploring RL as a learning paradigm, and to that end, Twitter Cortex built a framework for RL development. Today, Twitter is open sourcing torch-twrl to the world.

We recently released Autograd for Torch, which greatly simplified our workflow when experimenting with complex deep learning architectures. The Twitter Cortex team is continuously investing in better tooling for manipulating our large datasets, and distributing training processes across machines in our cluster.

Today we’re open-sourcing four components of our training pipeline, so the community using Torch and/or Autograd can simplify their workflows when it comes to parallelizing training, and manipulating large, distributed datasets.

Simplifying neural nets with autograd for Torch.