[TorchToLinalg] Fix outType inconsistency in AtenTransposeInt op lowering #4403
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…oseInt op lowering This commit adds the support to handle output tensor type consistency in case of dynamic dims for AtenTransposeInt op lowering by adding a cast operation to ensure the output tensor type matches the expected type. Also, update tests in datamovement.mlir to reflect changes in tensor handling for dynamic dimensions in transpose operations. Example IR: """ %0 = torch.prim.ListConstruct %int1, %int8, %int7, %int8, %int7, %int96 : (!torch.int, !torch.int, !torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> %1 = torch.aten.view %arg0, %0 : !torch.vtensor<[1,56,56,96],f32>, !torch.list<int> -> !torch.vtensor<[?,?,?,?,?,?],f32> %2 = torch.aten.transpose.int %1, %int2, %int3 : !torch.vtensor<[?,?,?,?,?,?],f32>, !torch.int, !torch.int -> !torch.vtensor<[?,?,?,?,?,?],f32> """
sahas3
reviewed
Dec 11, 2025
| %int2 = torch.constant.int 2 | ||
| %int3 = torch.constant.int 3 | ||
| %0 = torch.prim.ListConstruct %int1, %int8, %int7, %int8, %int7, %int96 : (!torch.int, !torch.int, !torch.int, !torch.int, !torch.int, !torch.int) -> !torch.list<int> | ||
| %1 = torch.aten.view %arg0, %0 : !torch.vtensor<[1,56,56,96],f32>, !torch.list<int> -> !torch.vtensor<[?,?,?,?,?,?],f32> |
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Clarification: Is a similar change required for view op as well since the view output is dynamic shape in torch IR but fixed shape in the linalg IR as per the added test?
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This commit adds the support to handle output tensor type consistency in case of dynamic dims for AtenTransposeInt op lowering by adding a cast operation to ensure the output tensor type matches the expected type.
Also, update tests in datamovement.mlir to reflect changes in tensor handling for dynamic dimensions in transpose operations.
Example IR: