pytorch

e40e4d36 - Fix test_profiler_seq_nr flakiness (on macos) (#91019)

Fix test_profiler_seq_nr flakiness (on macos) (#91019) Fixes https://github.com/pytorch/pytorch/issues/66893 On MacOS, two `aten::sum` calls are reported sometimes where there should be only one. This can be easily reproduced by running `pytest test_autograd.py -k test_profiler_seq_nr --verbose --flake-finder` to see the flakiness. The profile result when the test fails is as follows (sorted by CPU): ``` ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ Name Self CPU % Self CPU CPU total % CPU total CPU time avg # of Calls ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ aten::randn 16.67% 3.000us 27.78% 5.000us 2.500us 2 aten::sum 16.67% 3.000us 27.78% 5.000us 2.500us 2 aten::normal_ 11.11% 2.000us 11.11% 2.000us 1.000us 2 aten::add 11.11% 2.000us 11.11% 2.000us 2.000us 1 autograd::engine::evaluate_function: torch::autograd... 11.11% 2.000us 27.78% 5.000us 2.500us 2 torch::autograd::AccumulateGrad 11.11% 2.000us 16.67% 3.000us 1.500us 2 aten::ones_like 5.56% 1.000us 5.56% 1.000us 1.000us 1 autograd::engine::evaluate_function: SumBackward0 5.56% 1.000us 11.11% 2.000us 2.000us 1 aten::expand 5.56% 1.000us 5.56% 1.000us 1.000us 1 aten::copy_ 5.56% 1.000us 5.56% 1.000us 0.500us 2 aten::empty 0.00% 0.000us 0.00% 0.000us 0.000us 2 aten::as_strided 0.00% 0.000us 0.00% 0.000us 0.000us 2 aten::fill_ 0.00% 0.000us 0.00% 0.000us 0.000us 2 aten::empty_like 0.00% 0.000us 0.00% 0.000us 0.000us 1 aten::empty_strided 0.00% 0.000us 0.00% 0.000us 0.000us 3 SumBackward0 0.00% 0.000us 5.56% 1.000us 1.000us 1 autograd::engine::evaluate_function: AddBackward0 0.00% 0.000us 0.00% 0.000us 0.000us 1 AddBackward0 0.00% 0.000us 0.00% 0.000us 0.000us 1 aten::new_empty_strided 0.00% 0.000us 0.00% 0.000us 0.000us 2 ------------------------------------------------------- ------------ ------------ ------------ ------------ ------------ ------------ Self CPU time total: 18.000us ``` When it happens, the two `aten::sum` calls have different inputs: ``` aten::sum 4.35% 1.000us 13.04% 3.000us 3.000us 1 [[10, 10], []] aten::sum 8.70% 2.000us 8.70% 2.000us 2.000us 1 [[10, 10], [], [], []] ``` I'm not sure what is the internal difference between `z.sum()` and `z.sum(dim=None)` here on MacOS, I thought they are the same. ### Testing `pytest test_autograd.py -k test_profiler_seq_nr --verbose --flake-finder` to run the test 50 times, all pass. Pull Request resolved: https://github.com/pytorch/pytorch/pull/91019 Approved by: https://github.com/malfet