Using PyTorch + NumPy? A bug that plagues thousands of open-source ML projects.

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Using NumPy’s random number generator with multi-process data loading in PyTorch causes identical augmentations unless you specifically set seeds using the worker_init_fn option in the DataLoader. I didn’t and this bug silently regressed my model’s accuracy.

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