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PyTorch Community Reports Abnormal Attention Gradients on B300; Certain Short Sequences May Produce NaNs in cuDNN

A PyTorch community report on October 9 says that a combination of certain short sequences and Boolean masks on B300 may cause NaNs during cuDNN attention backpropagation, even though forward outputs remain normal. Maintainers said the issue did not reproduce with newer cuDNN and recommended testing a nightly build or 2.15 release candidate; the reporter’s environment has yet to be upgraded and verified.