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[inductor] Fix torch.bernoulli decomposition return type (#115699)

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Strangely enough, `torch.bernoulli` doesn't return a boolean and instead
it matches the output type of the inplace bernoulli.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/115699
Approved by: https://github.com/lezcano
ghstack dependencies: #115677
This commit is contained in:
Peter Bell 2023-12-12 22:48:54 +00:00 committed by PyTorch MergeBot
parent 0e0dd8f985
commit 9cdc80d581
2 changed files with 1 additions and 3 deletions
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2
test/inductor/test_torchinductor_opinfo.py
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@ -203,7 +203,6 @@ inductor_expected_failures_single_sample["cpu"] = {
f16 f16
}, # half_to_float is only valid for the CUDA implementation }, # half_to_float is only valid for the CUDA implementation
"_upsample_bilinear2d_aa": {f32, f64}, "_upsample_bilinear2d_aa": {f32, f64},
"bernoulli": {f16, f32, f64},
"cholesky": {f32, f64}, "cholesky": {f32, f64},
"complex": {f16}, "complex": {f16},
"cross": {f16}, "cross": {f16},
@ -229,7 +228,6 @@ inductor_expected_failures_single_sample["cpu"] = {
inductor_expected_failures_single_sample["cuda"] = { inductor_expected_failures_single_sample["cuda"] = {
"_upsample_bilinear2d_aa": {f16, f32, f64}, "_upsample_bilinear2d_aa": {f16, f32, f64},
"atanh": {f32}, "atanh": {f32},
"bernoulli": {f16, f32, f64},
"cholesky": {f32, f64}, "cholesky": {f32, f64},
"multinomial": {f16, f32, f64}, "multinomial": {f16, f32, f64},
"nn.functional.normalize": {f16}, "nn.functional.normalize": {f16},

2
torch/_inductor/decomposition.py
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@ -297,7 +297,7 @@ def lift(self):
@register_decomposition([aten.bernoulli.default]) @register_decomposition([aten.bernoulli.default])
def bernoulli(self, *, generator=None): def bernoulli(self, *, generator=None):
assert generator is None assert generator is None
return torch.rand_like(self, dtype=torch.float32) < self return (torch.rand_like(self, dtype=torch.float32) < self).to(self.dtype)
@register_decomposition([aten.fmin, prims.fmin]) @register_decomposition([aten.fmin, prims.fmin])