Use op.dtype to create aten.empty.memory_format during decomposition. #3941
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Hi @ramiro050, I see that I am reverting your change here. It's not clear to me why the |
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Hello @ramiro050 and @vivekkhandelwal1 can you please review this PR when you have a chance? Thanks! |
| func.func @torch.aten.empty.memory_format$noneDtype() -> !torch.vtensor<[200,200,26],f64> attributes {torch.assume_strict_symbolic_shapes} { | ||
| %int200 = torch.constant.int 200 | ||
| %int26 = torch.constant.int 26 | ||
| %false = torch.constant.bool false | ||
| %none = torch.constant.none | ||
| %0 = torch.prim.ListConstruct %int200, %int200, %int26 : (!torch.int, !torch.int, !torch.int) -> !torch.list<int> | ||
| %1 = torch.aten.empty.memory_format %0, %none, %none, %none, %false, %none : !torch.list<int>, !torch.none, !torch.none, !torch.none, !torch.bool, !torch.none -> !torch.vtensor<[200,200,26],f64> | ||
| return %1 : !torch.vtensor<[200,200,26],f64> | ||
| } |
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Hi @sahas3, the above test case is an invalid test since the tensor element type is f32 when none is specifed for the aten.empty.memory_format op.
I just tried it. See:
>>> a = torch.ops.aten.empty.memory_format([2, 3])
>>> a
tensor([[-3.4054e+29, 4.2543e-41, -3.4085e+29],
[ 4.2543e-41, -3.4086e+29, 4.2543e-41]])
>>> a.dtype
torch.float32
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Also, the changes that you've done are not correct and hence this patch should not be merged.
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Great flag, @vivekkhandelwal1. I missed that torch.ops.aten.empty.memory_format produces f32 for dtype=none in PyTorch as I assumed the aten.empty.memory_format op being produced during conversion of ExportedProgram to torch dialect was correct.
Upon further investigation, I think the bug is instead in the DecomposeComplexOps pass where we decompose different torch ops to aten.empty.memory_format. For empty_like op if dtype is not specified then it defaults to input dtype as per https://pytorch.org/docs/stable/generated/torch.empty_like.html. This was not being captured when decomposing to empty.memory_format.
I have pushed new changes, reverting the original change that addresses this issue. Can you please take another look at these new changes? Thanks!
sahas3
changed the title
Prior to the change in this PR
torch-mlir-opt --convert-torch-to-linalgwas running into the following error:This is because when
dtypeof theaten.empty.memory_formatisnone, by defaultf32was being selected as the element type of the resulting tensor which doesn't match with the actual element type of the result.