Torch is an open platform for scientific computing in the Lua language, with a focus on machine learning, in particular deep learning. Torch is distinguished from other array libraries by having first-class support for GPU computation, and a clear, interactive and imperative style. Further, through the "NN" library, Torch has broad support for building and training neural networks by composing primitive blocks or layers together in compute graphs. Torch, although benefitting from extensive industry support, is a community owned and community developed ecosystem.

All neural net libraries, including Torch NN, rely on automatic differentiation (AD) to manage the computation of gradients of complex compositions of functions. I will also present some general background on automatic differentiation (AD), which is the fundamental abstraction of gradient-based optimization, and demonstrate Twitter's flexible implementation of AD in the library torch-autograd.