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Skip loading extra data for export #1051
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Summary: When performing a standalone model export, we just need one batch of data to pass through. But we currently get the data via `data.batches(...)` which could use PoolingBatcher, which loads many many examples, or could have `in_memory=True`, which loads all examples. This can take hours for a large dataset (especially since we also tokenize the data). Add a flag for `batches()` that forcibly skips loading all data into memory and using pooling. Differential Revision: D17920179 fbshipit-source-id: b878c9594d4f41752a8f0fb835d706602e68c1eb
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This pull request was exported from Phabricator. Differential Revision: D17920179 |
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This pull request has been merged in a0f6002. |
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Summary: When performing a standalone model export, we just need one batch of data to pass through. But we currently get the data via
data.batches(...)which could use PoolingBatcher, which loads many many examples, or could havein_memory=True, which loads all examples. This can take hours for a large dataset (especially since we also tokenize the data). Add a flag forbatches()that forcibly skips loading all data into memory and using pooling.Differential Revision: D17920179