[s2s] dynamic batch size with --max_tokens_per_batch (#7030)
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@@ -352,3 +352,33 @@ runtime: 13H on V-100 16GB GPU.
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```bash
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pytest examples/seq2seq/
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```
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## Experimental Features
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These features are harder to use and not always useful.
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### Dynamic Batch Size for MT
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`finetune.py` has a command line arg `--max_tokens_per_batch` that allows batches to be dynamically sized.
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This feature can only be used:
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- with fairseq installed
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- on 1 GPU
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- without sortish sampler
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- after calling `python save_len_file.py $tok $data_dir`
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For example,
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```bash
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python save_len_file.py Helsinki-NLP/opus-mt-en-ro wmt_en_ro
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./dynamic_bs_example.sh --max_tokens_per_batch=2000 --output_dir benchmark_dynamic_bs
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```
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splits `wmt_en_ro/train` into 11,197 uneven lengthed batches and can finish 1 epoch in 8 minutes on a v100.
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For comparison,
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```bash
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./dynamic_bs_example.sh --sortish_sampler --train_batch_size 48
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```
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uses 12,723 batches of length 48 and takes slightly more time 9.5 minutes.
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The feature is still experimental, because:
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+ we can make it much more robust if we have memory mapped/preprocessed datasets.
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+ The speedup over sortish sampler is not that large at the moment.
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