OpenSeq2Seq: Extensible Toolkit for Distributed and Mixed Precision Training of Sequence-to-Sequence Models

TLDR

OpenSeq2Seq is an open‑source toolkit designed to enable researchers to efficiently explore diverse sequence‑to‑sequence architectures and is planned to support additional modalities. The toolkit achieves efficiency through full support for distributed and mixed‑precision training and supplies building blocks for encoder‑decoder models in neural machine translation and automatic speech recognition.

Abstract

We present OpenSeq2Seq – an open-source toolkit for training sequence-to-sequence models. The main goal of our toolkit is to allow researchers to most effectively explore different sequence-to-sequence 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.