[Torch] : Implement lowering of torch.frac op #3847
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Could you please review this pull request? @vivekkhandelwal1 |
vivekkhandelwal1
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Nov 12, 2024
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| class ElementwiseFracModule(torch.nn.Module): | ||
| def __init__(self): | ||
| super().__init__() | ||
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| @export | ||
| @annotate_args( | ||
| [ | ||
| None, | ||
| ([1, 6], torch.float32, True), | ||
| ] | ||
| ) | ||
| def forward(self, a): | ||
| return torch.frac(a) | ||
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| @register_test_case(module_factory=lambda: ElementwiseFracModule()) | ||
| def ElementwiseFracModule_basic(module, tu: TestUtils): | ||
| module.forward(torch.tensor([[-torch.inf, torch.inf, torch.nan, -2.3, 0.0, 1.5]])) | ||
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Does it take f64 input? If yes, can you please add a test for the same?
| @@ -8012,6 +8012,34 @@ class DecomposeAtenTruncOp : public OpRewritePattern<AtenTruncOp> { | |||
| }; | |||
| } // namespace | |||
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| namespace { | |||
| // decompose `frac(x)` to `x - sign(x) * floor(abs(x))` | |||
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The decomposition written below follows a different implementation. Better to either remove this comment or change it as per the decomposition.
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Implement lowering of torch.frac op.
Decompose op inside DecomposeComplexOps.cpp.
Add tests into elementwise.py.