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nmtpytorch
allows training of various end-to-end neural architectures including
but not limited to neural machine translation, image captioning and automatic
speech recognition systems. The initial codebase was in Theano
and was
inspired from the famous dl4mt-tutorial
codebase.
nmtpytorch
is mainly developed by the Language and Speech Team of Le Mans University but
receives valuable contributions from the Grounded Sequence-to-sequence Transduction Team
of Frederick Jelinek Memorial Summer Workshop 2018:
Loic Barrault, Ozan Caglayan, Amanda Duarte, Desmond Elliott, Spandana Gella, Nils Holzenberger, Chirag Lala, Jasmine (Sun Jae) Lee, Jindřich Libovický, Pranava Madhyastha, Florian Metze, Karl Mulligan, Alissa Ostapenko, Shruti Palaskar, Ramon Sanabria, Lucia Specia and Josiah Wang.
If you use nmtpytorch, you may want to cite the following paper:
@article{nmtpy2017,
author = {Ozan Caglayan and
Mercedes Garc\'{i}a-Mart\'{i}nez and
Adrien Bardet and
Walid Aransa and
Fethi Bougares and
Lo\"{i}c Barrault},
title = {NMTPY: A Flexible Toolkit for Advanced Neural Machine Translation Systems},
journal = {Prague Bull. Math. Linguistics},
volume = {109},
pages = {15--28},
year = {2017},
url = {https://ufal.mff.cuni.cz/pbml/109/art-caglayan-et-al.pdf},
doi = {10.1515/pralin-2017-0035},
timestamp = {Tue, 12 Sep 2017 10:01:08 +0100}
}
nmtpytorch
currently requires python>=3.6
and torch>=0.4.1
.
We are not planning to support Python 2.x.
IMPORTANT: After installing nmtpytorch
, you need to run nmtpy-install-extra
to download METEOR related files into your ${HOME}/.nmtpy
folder.
This step is only required once.
You can install nmtpytorch
from PyPI
using pip
(or pip3
depending on your
operating system and environment):
$ pip install nmtpytorch
This will automatically fetch and install the dependencies as well. For the torch
dependency it will specifically install the torch 1.0.0
package from PyPI
that
ships CUDA 9.0
within.
We provide an environment.yml
file in the repository that you can use to create
a ready-to-use anaconda environment for nmtpytorch
:
$ conda update --all
$ git clone https://github.com/lium-lst/nmtpytorch.git
$ conda env create -f nmtpytorch/environment.yml
For continuous development and testing, it is sufficient to run python setup.py develop
in the root folder of your GIT checkout. From now on, all modifications to the source
tree are directly taken into account without requiring reinstallation.
We currently only provide some preliminary documentation in our wiki.
See NEWS.md.