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pytorch / FBGEMM

FB (Facebook) + GEMM (General Matrix-Matrix Multiplication) - https://code.fb.com/ml-applications/fbgemm/
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Use guard_size_oblivious in tbe_input_combine_abstract fake kernel #2923

Closed henryoier closed 2 months ago

henryoier commented 2 months ago

Summary: Encountered this error during export

torch.fx.experimental.symbolic_shapes.GuardOnDataDependentSymNode: Could not guard on data-dependent expression u5 > 0 (unhinted: u5 > 0).  (Size-like symbols: u5)

ATTENTION: guard_size_oblivious would fix the error, evaluating expression to True.
Maybe you need to add guard_size_oblivious to framework code, see doc below for more guidance.

Reviewed By: SherlockNoMad

Differential Revision: D60260290

Privacy Context Container: L1125031

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facebook-github-bot commented 2 months ago

This pull request was exported from Phabricator. Differential Revision: D60260290

facebook-github-bot commented 2 months ago

This pull request was exported from Phabricator. Differential Revision: D60260290

facebook-github-bot commented 2 months ago

This pull request was exported from Phabricator. Differential Revision: D60260290

facebook-github-bot commented 2 months ago

This pull request has been merged in pytorch/FBGEMM@0872841d944e6d7f9988edd629bbbb109242fe01.