Add support for cross-chunk shuffling in ChunkDataset #22347
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apaszke
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@pytorchbot merge this please. |
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@zhangguanheng66 merged this pull request in f0f2331. |
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Summary: This change adds one advanced support for cross-chunk shuffling. For training with static dataset, the default configuration is at user's disposal. However, in some user cases, over each epoch, new data is added to the current dataset, thus the dataset's size is dynamically changing/increasing. In order to mix the new data and the old data for better random sampling, one approach is to shuffle examples from more than 1 chunks. This feature is supported with this change. By specifying the `cross_chunk_shuffle_count_` on construction, advanced user can specify how many chunks to shuffle example from. Pull Request resolved: pytorch#22347 Differential Revision: D16081378 Pulled By: zhangguanheng66 fbshipit-source-id: fd001dfb9e66947839adecfb9893156fbbce80d0
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This change adds one advanced support for cross-chunk shuffling.
For training with static dataset, the default configuration is at user's disposal. However, in some user cases, over each epoch, new data is added to the current dataset, thus the dataset's size is dynamically changing/increasing. In order to mix the new data and the old data for better random sampling, one approach is to shuffle examples from more than 1 chunks. This feature is supported with this change. By specifying the
cross_chunk_shuffle_count_on construction, advanced user can specify how many chunks to shuffle example from.