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Did you test whether this actually makes the data loader fully deterministic? For very large model training it can be good to have a deterministic data loader to avoid re-training on data upon resuming (eg if you do a total of <=1 epoch), so having an option for determinism could be great even beyond debugging use cases. |
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@kpertsch I did some testing in a notebook and it seemed deterministic but have to write a full unit test. |
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I would find this addition useful, although possible we should also expose the arg in the |
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And of course I tested and can confirm this works. Having this hard-coded to false is extra scary because the TF docs say that if https://www.tensorflow.org/datasets/determinism#with_shuffle_filestrue |
For debugging and overfitting.