Abstract
本文:描述automatic differentiation module of PyTorch
包括:Lua Torch, Chainer, HIPS Autograd
Task: Provides a high-performance environment on different devices(both CPUs and GPUs)
方法:不用symbolic differentiation, 而是使用differentiation on purely imperative programs
特点:focus on extensibility and low overhead