pytorch

112f2494 - Port `pow` operator from the TH code to Aten (#23492)

Port `pow` operator from the TH code to Aten (#23492) Summary: Fixing https://github.com/pytorch/pytorch/issues/24750 ``` DEBUG = 0 OMP_NUM_THREADS = 1 import torch base = torch.randn(1000000) exp = torch.randn(1000000) out = torch.empty_like(base) timeit base.pow(0) +30x old 6.26 ms ± 35.9 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 213 µs ± 3.38 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(1/3) +6x old 56 ms ± 911 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.41 ms ± 237 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit base.pow(-1/3) +6x old 57 ms ± 1.65 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.49 ms ± 293 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit base.pow(1/2) +6x old 4.04 ms ± 14.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 620 µs ± 3.35 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(-1/2) +5x old 6.56 ms ± 43 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 1.24 ms ± 19.3 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(1) no diff old 322 µs ± 4.7 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) new 331 µs ± 7.26 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(-1) +3.5x old 2.48 ms ± 15.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 717 µs ± 130 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(2) no diff old 328 µs ± 7.42 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) new 324 µs ± 4.93 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(-2) +3.5x old 2.45 ms ± 11.8 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 662 µs ± 3.83 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(3) +7x old 2.39 ms ± 60.7 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 334 µs ± 7.26 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit base.pow(-3) +9x old 93.7 ms ± 5.27 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 10.3 ms ± 666 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit base.pow(123456.789) +5x old 46.5 ms ± 418 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.68 ms ± 325 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit base.pow(-123456.789) +5x old 46.5 ms ± 784 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) new 10 ms ± 541 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit base.pow(exp) +6x old 60.6 ms ± 4 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.7 ms ± 379 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit torch.pow(0, exp) no diff old 18.3 ms ± 859 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 21.2 ms ± 333 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) timeit torch.pow(1, exp) +30x old 6.01 ms ± 81.6 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 203 µs ± 1.08 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit torch.pow(-1, exp) +3x old 30.8 ms ± 5.51 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.67 ms ± 441 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit torch.pow(42, exp) +8x old 80.1 ms ± 1.57 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.51 ms ± 103 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit torch.pow(-42, exp) +2x old 21.8 ms ± 4.37 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.5 ms ± 89.1 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit torch.pow(0, exp, out=out) no diff old 20.2 ms ± 3.04 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 22.1 ms ± 648 µs per loop (mean ± std. dev. of 7 runs, 10 loops each) timeit torch.pow(1, exp, out=out) +30x old 6.7 ms ± 397 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) new 203 µs ± 4.64 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each) timeit torch.pow(-1, exp, out=out) +3x old 32.5 ms ± 3.61 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.4 ms ± 99.1 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit torch.pow(42, exp, out=out) +10x old 91 ms ± 7.45 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 9.64 ms ± 291 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) timeit torch.pow(-42, exp, out=out) +2.5x old 25.9 ms ± 5.03 ms per loop (mean ± std. dev. of 7 runs, 10 loops each) new 10.1 ms ± 698 µs per loop (mean ± std. dev. of 7 runs, 100 loops each) ``` BC: enforce stronger shape requirements on the output tensor (out= keyword argument) and do not allow output tensor to be resized if it is also used as one of the inputs. BC: enforce stronger integer tensor base power integer exponent requirement on CPU and CUDA: `Integers to negative integer powers are not allowed.` Pull Request resolved: https://github.com/pytorch/pytorch/pull/23492 Differential Revision: D16731583 Pulled By: pbelevich fbshipit-source-id: 4e5bf689357fe82a19371e42d48abbb7b4c1c3ca