fixed apply_mask bug in losses #802
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fchollet
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Aug 27, 2023
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This fix ensures that losses evaluated with a
sample_weights == ops.cast(mask, "float32")are the same as those evaluated with either argument but not bothNone. Note thistotalis consistent with thebatch_sizeused inreduce_values, corresponding to the total size of all elements as opposed to the leading dimension. Another fix might be to leaveapply_maskalone and changereduce_valuesto divide by the leading dimension only rather than the total size.I'm unsure of a concise way to unit test this because AFAIK there's no way to pass a mask in using only the public API...