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Fix torch.pow when the scalar base is a complex number #45259

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Fix torch.pow when the scalar base is a complex number #45259

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5fca1f0
Fix checking logic for complex scalar base
RockingJavaBean Sep 24, 2020
e387d43
add tests for scalar complex bases
RockingJavaBean Sep 25, 2020
1fd1e52
skip xla tests for complex base torch.pow
RockingJavaBean Sep 26, 2020
903d525
Merge branch 'master' of https://github.com/pytorch/pytorch into fix_…
RockingJavaBean Sep 28, 2020
9c9101e
Merge branch 'master' of https://github.com/pytorch/pytorch into fix_…
RockingJavaBean Sep 28, 2020
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4 changes: 3 additions & 1 deletion aten/src/ATen/native/Pow.cpp
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Expand Up @@ -43,7 +43,9 @@ Tensor& pow_out(Tensor& result, const Tensor& base, Scalar exp) {
}

Tensor& pow_out(Tensor& result, Scalar base, const Tensor& exp) {
if (base.toDouble() == 1.0) {
if (base.isComplex() && base.toComplexDouble() == 1.0) {
result.resize_as_(exp).fill_(1);
} else if (!base.isComplex() && base.toDouble() == 1.0) {
result.resize_as_(exp).fill_(1);
} else {
native::pow_out(result, c10::scalar_to_tensor(base, exp.device()), exp);
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9 changes: 9 additions & 0 deletions test/test_torch.py
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Expand Up @@ -13716,6 +13716,15 @@ def test_float_scalar_pow_float_tensor(self, device):
for base in floats:
self._test_pow(base, tensor)

@onlyOnCPUAndCUDA
@unittest.skipIf(not TEST_NUMPY, 'Numpy not found')
@dtypes(*(torch.testing.get_all_dtypes(include_bool=False, include_bfloat16=False)))
def test_complex_scalar_pow_tensor(self, device, dtype):
complexes = [0.5j, 1. + 1.j, -1.5j, 2.2 - 1.6j]
tensor = torch.rand(100).to(dtype=dtype, device=device)
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For integer dtypes this resolves to a tensor full of zeros, which may not be the most interesting test case. We have a make_tensor function to generate a random tensor that would be nicer to use:

pytorch/torch/testing/_internal/common_utils.py

Lines 1441 to 1442 in ecdbea7

def make_tensor(size, device: torch.device, dtype: torch.dtype, *,
low, high, requires_grad: bool = False) -> torch.Tensor:

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Thanks so much for pointing out this issue, and offering the kind tip of using the make_tensor function.
#47101 has been created to address this comment and special cases of zero exponents and the 1 + 0j base are added as well, please kindly help review.

for base in complexes:
self._test_pow(base, tensor)

@unittest.skipIf(not TEST_NUMPY, 'Numpy not found')
def test_tensor_pow_tensor(self, dev):
def rotate(l, n):
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