PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"

Last update: Nov 12, 2022

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Overview

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:

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

Owner

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PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"

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Non-Autoregressive Transformer

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