OpenSeq2Seq: Extensible Toolkit for Distributed and Mixed Precision Training of Sequence-to-Sequence Models
Oleksii Kuchaiev, Boris Ginsburg, Igor Gitman, Vitaly Lavrukhin, Carl T. Case, Paulius Micikevicius · 2018
We present OpenSeq2Seq -an opensource toolkit for training sequence-tosequence models.The main goal of our toolkit is to allow researchers to most effectively explore different sequence-tosequence architectures.The efficiency is achieved by fully supporting distributed and mixed-precision training.OpenSeq2Seq provides building blocks for training encoder-decoder models for neural machine translation and automatic speech recognition.We plan to extend it with other modalities in the future.