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# Simultaneous Machine Translation
This directory contains the code for the paper [Monotonic Multihead Attention](https://openreview.net/forum?id=Hyg96gBKPS)
## Prepare Data
[Please follow the instructions to download and preprocess the WMT'15 En-De dataset.](https://github.com/pytorch/fairseq/tree/simulastsharedtask/examples/translation#prepare-wmt14en2desh)
Another example of training an English to Japanese model can be found [here](docs/enja.md)
## Training
- MMA-IL
```shell
fairseq-train \
data-bin/wmt15_en_de_32k \
--simul-type infinite_lookback \
--user-dir $FAIRSEQ/example/simultaneous_translation \
--mass-preservation \
--criterion latency_augmented_label_smoothed_cross_entropy \
--latency-weight-avg 0.1 \
--max-update 50000 \
--arch transformer_monotonic_iwslt_de_en save_dir_key=lambda \
--optimizer adam --adam-betas '(0.9, 0.98)' \
--lr-scheduler 'inverse_sqrt' \
--warmup-init-lr 1e-7 --warmup-updates 4000 \
--lr 5e-4 --stop-min-lr 1e-9 --clip-norm 0.0 --weight-decay 0.0001\
--dropout 0.3 \
--label-smoothing 0.1\
--max-tokens 3584
```
- MMA-H
```shell
fairseq-train \
data-bin/wmt15_en_de_32k \
--simul-type hard_aligned \
--user-dir $FAIRSEQ/example/simultaneous_translation \
--mass-preservation \
--criterion latency_augmented_label_smoothed_cross_entropy \
--latency-weight-var 0.1 \
--max-update 50000 \
--arch transformer_monotonic_iwslt_de_en save_dir_key=lambda \
--optimizer adam --adam-betas '(0.9, 0.98)' \
--lr-scheduler 'inverse_sqrt' \
--warmup-init-lr 1e-7 --warmup-updates 4000 \
--lr 5e-4 --stop-min-lr 1e-9 --clip-norm 0.0 --weight-decay 0.0001\
--dropout 0.3 \
--label-smoothing 0.1\
--max-tokens 3584
```
- wait-k
```shell
fairseq-train \
data-bin/wmt15_en_de_32k \
--simul-type wait-k \
--waitk-lagging 3 \
--user-dir $FAIRSEQ/example/simultaneous_translation \
--mass-preservation \
--criterion latency_augmented_label_smoothed_cross_entropy \
--max-update 50000 \
--arch transformer_monotonic_iwslt_de_en save_dir_key=lambda \
--optimizer adam --adam-betas '(0.9, 0.98)' \
--lr-scheduler 'inverse_sqrt' \
--warmup-init-lr 1e-7 --warmup-updates 4000 \
--lr 5e-4 --stop-min-lr 1e-9 --clip-norm 0.0 --weight-decay 0.0001\
--dropout 0.3 \
--label-smoothing 0.1\
--max-tokens 3584
```
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