  We present OpenSeq2Seq - a TensorFlow-based toolkit for training
sequence-to-sequence models that features distributed and mixed-precision
training. Benchmarks on machine translation and speech recognition tasks show
that models built using OpenSeq2Seq give state-of-the-art performance at 1.5-3x
less training time. OpenSeq2Seq currently provides building blocks for models
that solve a wide range of tasks including neural machine translation,
automatic speech recognition, and speech synthesis.
