Clear output of Torch SDPA for masked pieces #360
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Since Torch 2.1, the Torch memory-efficient SDPA GPU kernel returns NaN for pieces that are completely masked out. This leads to NaN propagation in the next attention layer, because masked pieces get an attention of zero, but zero times NaN is still NaN. In this we fix this by setting masked tokens to zero to clear out any NaNs. We currently rely on the query dimension of the mask to be singular, but in the future we should probably redesign the `AttentionMask` class to account for the differences between attention masks and causal masks.
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shadeMe
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Feb 8, 2024
Co-authored-by: Madeesh Kannan <[email protected]>
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Description
Since Torch 2.1, the Torch memory-efficient SDPA GPU kernel returns NaN for pieces that are completely masked out. This leads to NaN propagation in the next attention layer, because masked pieces get an attention of zero, but zero times NaN is still NaN.
In this we fix this by setting masked tokens to zero to clear out any NaNs.
We currently rely on the query dimension of the mask to be singular, but in the future we should probably redesign the
AttentionMaskclass to account for the differences between attention masks and causal masks.Checklist