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[AUTOGENERATED] [release/2.5] Cherry-pick PR-1767 #1794
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… kernel (pytorch#140259) (#1767) It was raised that the backwards layer norm on AMD was slightly off the accuracy of the equivalent NVIDIA implementation. On AMD we call into a helper kernel `cuLoadWriteStridedInputs` which processes strided input and accumulates the partial gradients into shared memory. In this kernel (pytorch#87635) we truncated `mean` and `rstd` from T_ACC type to T which causes numerical issues in the warp buffers created in this kernel. This PR will use the correct accumulator type for mean and rstd. Note: Only AMD call into this call stack for backwards layer norm, so this was not an issue for NV. Pull Request resolved: pytorch#140259 Approved by: https://github.com/jianyuh (cherry picked from commit 001f736) Fixes #ISSUE_NUMBER
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Cherry-pick of #1767