Awesome

A neural machine translation model written in pytorch.

For a up-to-date PyTorch implementation of basic vanilla attentional NMT, please refer to this repo

With 256-dimensional LSTM hidden size, it achieves a training speed of 14000 words/sec and 26.9 BLEU score on the IWSLT 2014 Germen-English dataset (Ranzato et al., 2015).

File Structure

• nmt.py: main file
• vocab.py: script used to generate .bin vocabulary file from parallel corpus
• util.py: script containing helper functions
• run_raml_exp.py|test_raml_models.py: helper scripts to train|test RAML models with different temperature settings (refer to [Norouzi et al., 2016] for details)

Usage

• Generate Vocabulary Files

python vocab.py

• Vanilla Maximum Likelihood Training

. scripts/run_mle.sh

• Reward Augmented Maximum Likelihood Training (Norouzi et al., 2016)

. scripts/run_raml.sh

• Reinforcement Learning (Coming soon)

TODO:

• batched decoding as in openNMT

License

This work is licensed under a Creative Commons Attribution 4.0 International License.