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Fix non-tuple return in wmma backward benchmark #18

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Merged
merged 1 commit into from
Oct 9, 2025
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Fix non-tuple return in wmma backward benchmark #18

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2 changes: 1 addition & 1 deletion warpconvnet/nn/functional/sparse_conv/detail/implicit_wmma.py
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Original file line number Diff line number Diff line change
Expand Up @@ -89,7 +89,7 @@ def _wmma_implicit_gemm_backward_logic(
min_dtype = _min_dtype(in_features.dtype, weight.dtype, grad_output.dtype)
if min_dtype not in [torch.float16, torch.bfloat16]:
# wmma not supported for data types other than float16 and bfloat16
return int(_C.gemm.GemmStatus.kErrorInvalidParameters)
return int(_C.gemm.GemmStatus.kErrorInvalidParameters), -1
_grad_output_detached = grad_output.contiguous().detach().to(dtype=min_dtype)
_in_features_detached = in_features.contiguous().detach().to(dtype=min_dtype)
_weight_detached = weight.contiguous().detach().to(dtype=min_dtype)
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