Metadata-Version: 2.1
Name: rtg
Version: 0.7.1
Summary: Reader Translator Generator(RTG), a Neural Machine Translator(NMT) toolkit based on Pytorch
Home-page: https://isi-nlp.github.io/rtg/
Author: Thamme Gowda
Author-email: tg@isi.edu
License: UNKNOWN
Platform: any
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: ruamel.yaml (>=0.17.10)
Requires-Dist: sacrebleu-macrof (==2.0.1)
Requires-Dist: sentencepiece (>=0.1.85)
Requires-Dist: tensorboard (>=2.6.0)
Requires-Dist: tqdm (>=4.45.0)
Requires-Dist: nlcodec (>=0.5)
Requires-Dist: torch (>=1.10)
Requires-Dist: sacremoses (>=0.0.45)
Requires-Dist: portalocker (>=2.0.0)
Requires-Dist: torchtext (>=0.10.0)
Requires-Dist: pyspark (>=3.0.0)

# Reader-Translator-Generator (RTG)  
[![image](http://img.shields.io/pypi/v/rtg.svg)](https://pypi.python.org/pypi/rtg/)


Reader-Translator-Generator (RTG) is a Neural Machine Translation toolkit based on pytorch. 

Documentation: https://isi-nlp.github.io/rtg/
> for editing/improving docs go to [docs/](docs/index.adoc) directory.

---------

### Questions or Issues 

Please use github issues to ask a question or report an issue :
1. https://github.com/isi-nlp/rtg/issues   (public/ external repo)
2. https://github.com/isi-nlp/rtg-in/issues (an internal fork, for ISI NLP)


### ACKNOWLEDGEMENTS

* The research is based upon work supported by the Office of the Director of
National Intelligence (ODNI), Intelligence Advanced Research Projects
Activity (IARPA), via AFRL Contract #FA8650-17-C-9116.
The views and conclusions contained herein are those of the authors and
should not be interpreted as necessarily representing the official policies or
endorsements, either expressed or implied, of the ODNI, IARPA, or the
U.S. Government. The U.S. Government is authorized to reproduce and
distribute reprints for Governmental purposes notwithstanding any
copyright annotation thereon.

* This material is based on research sponsored by
 Air Force Research Laboratory (AFRL) under agreement number FA8750-19-1-1000.
The U.S. Government is authorized to reproduce and distribute reprints for
Government purposes notwithstanding any copyright notation therein.


