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[AUTOGENERATED] [release/2.5] Cherry-pick PR-1767 #1794

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[AUTOGENERATED] [release/2.5] Cherry-pick PR-1767 #1794

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Cherry-pick of #1767

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[release/2.2] [ROCm] Correct numerical issues in layer norm backwards…
da78ffb 
… 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
@rocm-mici rocm-mici mentioned this pull request Dec 13, 2024
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@rocm-mici @jataylo