[torchlib] native_layer_norm_float32 is failing on MacOS CI with significant absolute difference #1470
Description
Observations: Doesn't fail on other platforms. Started to fail only after the Mac runners on Github were down and brought back up a day ago. All failing tests have 1D single element inputs.
Example https://github.com/microsoft/onnxscript/actions/runs/8840793727/job/24276753517
_ TestOutputConsistencyEagerCPU.test_output_match_opinfo__native_layer_norm_cpu_float32 (inputs="['Tensor<torch.Size([1]), dtype=torch.float32>', (1,), 'Tensor<torch.Size([1]), dtype=torch.float32>', 'Tensor<torch.Size([1]), dtype=torch.float32>', 1e-05]", kwargs='{}', sample_num=8) _
[gw1] darwin -- Python 3.10.11 /Users/runner/work/onnxscript/onnxscript/.nox/test/bin/python
tests/function_libs/torch_lib/ops_test.py:279: in run_test_output_match
torch.testing.assert_close(
E AssertionError: Tensor-likes are not close!
E
E Mismatched elements: 1 / 1 (100.0%)
E Greatest absolute difference: 1.154693603515625 at index (0,) (up to 0.00018 allowed)
E Greatest relative difference: 0.0036514615640044212 at index (0,) (up to 3.7e-05 allowed)