The Sockeye 2 Neural Machine Translation Toolkit at AMTA 2020

Tobias Domhan, Michael J. Denkowski, David Vilar, Xing Niu, Felix Hieber, Kenneth Heafield

Abstract: We present Sockeye 2, a modernized and streamlined version of the Sockeye neural machine translation (NMT) toolkit. New features include a simplified code base through the use of MXNet's Gluon API, a focus on state of the art model architectures, distributed mixed precision training, and efficient CPU decoding with 8-bit quantization. These improvements result in faster training and inference, higher automatic metric scores, and a shorter path from research to production.