num_proc=os.cpu_count() when counting unused tokens
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…n-counting-unused-tokens `num_proc=os.cpu_count()` when counting unused tokens
| @@ -416,7 +417,7 @@ def mapping(examples): | |||
| counter = np.fromiter(itertools.chain.from_iterable(input_ids), dtype = np.int32) | |||
| np.add.at(final_counts, counter, 1) | |||
| pass | |||
| train_dataset.map(mapping, batched = True, desc = "Counting untrained tokens") | |||
| train_dataset.map(mapping, batched = True, desc = "Counting untrained tokens", num_proc = os.cpu_count()) | |||
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This will break IterableDataset supports as they do not support the num_proc argument.
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This just sets num_proc=os.cpu_count() when counting unused tokens. Tested on a 64-core machine. Runs approximately 64 times faster.
This should be the default for all those HF map functions imho.