pcyin / Pytorch_nmt
A neural machine translation model in PyTorch
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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.binvocabulary 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
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