We present Marian, an efficient and self-contained Neural Machine Translation framework with an integrated automatic differentiation engine based on dynamic computation graphs. Marian is written entirely in C++. We describe the design of the encoder-decoder framework and demonstrate that a research-friendly toolkit can achieve high training and translation speed.
@article{arxiv.1804.00344,
title = {Marian: Fast Neural Machine Translation in C++},
author = {Marcin Junczys-Dowmunt and Roman Grundkiewicz and Tomasz Dwojak and Hieu Hoang and Kenneth Heafield and Tom Neckermann and Frank Seide and Ulrich Germann and Alham Fikri Aji and Nikolay Bogoychev and André F. T. Martins and Alexandra Birch},
journal= {arXiv preprint arXiv:1804.00344},
year = {2018}
}