pytorch

a7802447 - Port `equal` from THC to ATen (CUDA) (#36483)

Port `equal` from THC to ATen (CUDA) (#36483) Summary: Fixes https://github.com/pytorch/pytorch/issues/24557 ASV benchmark: ``` import torch sizes = [ (10**6,), (1000, 1000), (10, 10), (1, 2, 3, 4, 5, 6, 7, 8, 9, 10), ] class EqualTrue: params = range(len(sizes)) def setup(self, n): dims = sizes[n] self.a = torch.rand(dims, device='cuda') self.b = self.a.clone() def time_equal(self, n): torch.equal(self.a, self.b) class EqualFalse: params = range(len(sizes)) def setup(self, n): dims = sizes[n] self.a = torch.rand(dims, device='cuda') self.b = torch.rand(dims, device='cuda') def time_equal(self, n): torch.equal(self.a, self.b) ``` Old results: ``` [ 75.00%] ··· equal.EqualFalse.time_equal [ 75.00%] ··· ======== ============ param1 -------- ------------ 0 67.7±7μs 1 74.0±2μs 2 24.4±0.1μs 3 135±0.2μs ======== ============ [100.00%] ··· equal.EqualTrue.time_equal [100.00%] ··· ======== ============ param1 -------- ------------ 0 59.8±0.2μs 1 59.9±0.3μs 2 25.0±0.5μs 3 136±0.2μs ======== ============ ``` New results: ``` [ 75.00%] ··· equal.EqualFalse.time_equal [ 75.00%] ··· ======== ============ param1 -------- ------------ 0 44.4±0.2μs 1 44.5±0.4μs 2 31.3±0.3μs 3 96.6±0.5μs ======== ============ [100.00%] ··· equal.EqualTrue.time_equal [100.00%] ··· ======== ============ param1 -------- ------------ 0 44.2±0.2μs 1 44.6±0.2μs 2 30.8±0.3μs 3 97.3±0.2μs ======== ============ ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/36483 Differential Revision: D21451829 Pulled By: VitalyFedyunin fbshipit-source-id: 033e8060192c54f139310aeafe8ba784bab94ded