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[Cherry-pick] Do manual type conversion for isnan op (#6110) #6173

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Merged
merged 1 commit into from
Dec 15, 2023
Merged

[Cherry-pick] Do manual type conversion for isnan op (#6110) #6173

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1 change: 0 additions & 1 deletion test/test_core_aten_ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2246,7 +2246,6 @@ def test_aten_isnan_1(self):
kwargs = dict()
run_export_and_compare(self, torch.ops.aten.isnan, args, kwargs)

@unittest.skip
def test_aten_isnan_2(self):
args = (torch.randint(0, 10, (10, 10)).to(torch.int32),)
kwargs = dict()
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6 changes: 6 additions & 0 deletions torch_xla/csrc/ops/ops_lower_fn.cpp
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Expand Up @@ -450,6 +450,12 @@ torch_xla::XlaOpVector Inverse::Lower(LoweringContext* loctx) const {

torch_xla::XlaOpVector Isnan::Lower(LoweringContext* loctx) const {
xla::XlaOp xla_input = loctx->GetOutputOp(operand(0));
// PyTorch allows integral types as input to torch.isnan, however XLA does
// not. So we do a manual type conversion for integral types only to keep our
// bevahior same as PyTorch.
if (xla::primitive_util::IsIntegralType(XlaHelpers::TypeOfXlaOp(xla_input))) {
xla_input = xla::ConvertElementType(xla_input, xla::PrimitiveType::F32);
}
return ReturnOp(xla::IsNan(xla_input), loctx);
}

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