MXNet is an open-source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of devices, from cloud infrastructure to mobile devices. It is highly scalable, allowing for fast model training, and supports a flexible programming model and multiple languages. MXNet allows you to mix symbolic and imperative programming flavors to maximize both efficiency and productivity. MXNet is built on a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly. A graph optimization layer on top of that makes symbolic execution fast and memory efficient. The MXNet library is portable and lightweight, and it scales to multiple GPUs and multiple machines.
