7d2045a907
Enables loading of model checkpoints from main node only via MPI. Until now the checkpoint needed to present in the same location on all nodes. That could be done either via writing to a shared filesystem (problematic due to bad syncing) or by manual copying to the same local location, e.g. /tmp on each node (while writing only happened to one main location). Now, marian can resume training from only one location on the main node. The remaining nodes do not need to have access. E.g. local /tmp on the main node can be used, or race conditons on shared storage are avoided. Also avoids creating files for logging on more than one node. This is a bit wonky, done via environment variable lookup. |
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| CHANGELOG.md | ||
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| CONTRIBUTING.md | ||
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Marian
Marian is an efficient Neural Machine Translation framework written in pure C++ with minimal dependencies.
Named in honour of Marian Rejewski, a Polish mathematician and cryptologist.
Main features:
- Efficient pure C++ implementation
- Fast multi-GPU training and GPU/CPU translation
- State-of-the-art NMT architectures: deep RNN and transformer
- Permissive open source license (MIT)
- more detail...
If you use this, please cite:
Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak, Hieu Hoang, Kenneth Heafield, Tom Neckermann, Frank Seide, Ulrich Germann, Alham Fikri Aji, Nikolay Bogoychev, André F. T. Martins, Alexandra Birch (2018). Marian: Fast Neural Machine Translation in C++ (http://www.aclweb.org/anthology/P18-4020)
@InProceedings{mariannmt,
title = {Marian: Fast Neural Machine Translation in {C++}},
author = {Junczys-Dowmunt, Marcin and Grundkiewicz, Roman and
Dwojak, Tomasz and Hoang, Hieu and Heafield, Kenneth and
Neckermann, Tom and Seide, Frank and Germann, Ulrich and
Fikri Aji, Alham and Bogoychev, Nikolay and
Martins, Andr\'{e} F. T. and Birch, Alexandra},
booktitle = {Proceedings of ACL 2018, System Demonstrations},
pages = {116--121},
publisher = {Association for Computational Linguistics},
year = {2018},
month = {July},
address = {Melbourne, Australia},
url = {http://www.aclweb.org/anthology/P18-4020}
}
Amun
The handwritten decoder for RNN models compatible with Marian and Nematus has been superseded by the Marian decoder. The code is available in a separate repository: https://github.com/marian-nmt/amun
Website
More information on https://marian-nmt.github.io
Acknowledgements
The development of Marian received funding from the European Union's Horizon 2020 Research and Innovation Programme under grant agreements 688139 (SUMMA; 2016-2019), 645487 (Modern MT; 2015-2017), 644333 (TraMOOC; 2015-2017), 644402 (HiML; 2015-2017), 825303 (Bergamot; 2019-2021), the European Union's Connecting Europe Facility project 2019-EU-IA-0045 (User-focused Marian; 2020-2022), the Amazon Academic Research Awards program, the World Intellectual Property Organization, and is based upon work supported in part by the Office of the Director of National Intelligence (ODNI), Intelligence Advanced Research Projects Activity (IARPA), via contract #FA8650-17-C-9117.
This software contains source code provided by NVIDIA Corporation.