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Description

PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"

214 Stars 31 Forks BSD 3-Clause "New" or "Revised" License 1 Commits 3 Opened issues

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Non-Autoregressive Transformer

Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K. Li, and Richard Socher.

Requires PyTorch 0.3, torchtext 0.2.1, and SpaCy.

The pipeline for training a NAT model for a given language pair includes: 1.

run_alignment_wmt_LANG.sh
(runs
fast_align
for alignment supervision) 2.
run_LANG.sh
(trains an autoregressive model) 3.
run_LANG_decode.sh
(produces the distillation corpus for training the NAT) 4.
run_LANG_fast.sh
(trains the NAT model) 5.
run_LANG_fine.sh
(fine-tunes the NAT model)

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