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Description
Platforms: linux, slow
This test was disabled because it is failing in CI. See recent examples and the most recent trunk workflow logs.
Over the past 3 hours, it has been determined flaky in 3 workflow(s) with 6 failures and 3 successes.
Debugging instructions (after clicking on the recent samples link):
DO NOT ASSUME THINGS ARE OKAY IF THE CI IS GREEN. We now shield flaky tests from developers so CI will thus be green but it will be harder to parse the logs.
To find relevant log snippets:
- Click on the workflow logs linked above
- Click on the Test step of the job so that it is expanded. Otherwise, the grepping will not work.
- Grep for
test_foreach_l2_large_value_input__foreach_norm_cuda_float16 - There should be several instances run (as flaky tests are rerun in CI) from which you can study the logs.
Sample error message
Traceback (most recent call last):
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 1159, in test_wrapper
return test(*args, **kwargs)
File "/opt/conda/envs/py_3.10/lib/python3.10/unittest/mock.py", line 1833, in _inner
return f(*args, **kw)
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 1420, in only_fn
return fn(slf, *args, **kwargs)
File "/var/lib/jenkins/workspace/test/test_foreach.py", line 1004, in test_foreach_l2_large_value_input
actual = fn(
File "/var/lib/jenkins/workspace/test/test_foreach.py", line 91, in __call__
assert mta_called == (expect_fastpath and (not zero_size)), (
AssertionError: mta_called=False, expect_fastpath=True, zero_size=False, self.func.__name__='_foreach_norm', keys=('aten::_foreach_norm', 'Unrecognized', 'aten::zeros', 'aten::empty', 'aten::zero_', 'aten::fill_', 'cudaLaunchKernel', 'Lazy Function Loading', 'void at::native::lpnorm_cleanup<c10::Half, (at::native::NormType)1, c10::Half, float>(float const*, at::native::TensorListAddresses, int)', 'void at::native::vectorized_elementwise_kernel<8, at::native::FillFunctor<c10::Half>, std::array<char*, 1ul> >(int, at::native::FillFunctor<c10::Half>, std::array<char*, 1ul>)', 'cudaDeviceSynchronize')
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3153, in wrapper
method(*args, **kwargs)
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 3153, in wrapper
method(*args, **kwargs)
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 454, in instantiated_test
result = test(self, **param_kwargs)
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_utils.py", line 1612, in wrapper
fn(*args, **kwargs)
File "/opt/conda/envs/py_3.10/lib/python3.10/site-packages/torch/testing/_internal/common_device_type.py", line 1171, in test_wrapper
raise e_tracked from e
Exception: Caused by sample input at index 0: SampleInput(input=TensorList[Tensor[size=(0,), device="cuda:0", dtype=torch.float16], Tensor[size=(9, 9), device="cuda:0", dtype=torch.float16], Tensor[size=(8, 8), device="cuda:0", dtype=torch.float16], Tensor[size=(0,), device="cuda:0", dtype=torch.float16], Tensor[size=(6, 6), device="cuda:0", dtype=torch.float16], Tensor[size=(5, 5), device="cuda:0", dtype=torch.float16], Tensor[size=(0,), device="cuda:0", dtype=torch.float16], Tensor[size=(3, 3), device="cuda:0", dtype=torch.float16], Tensor[size=(0,), device="cuda:0", dtype=torch.float16], Tensor[size=(0,), device="cuda:0", dtype=torch.float16]], args=(), kwargs={'ord': '0', 'dtype': 'torch.float64'}, broadcasts_input=False, name='')
To execute this test, run the following from the base repo dir:
PYTORCH_OPINFO_SAMPLE_INPUT_INDEX=0 python test/test_foreach.py TestForeachCUDA.test_foreach_l2_large_value_input__foreach_norm_cuda_float16
This message can be suppressed by setting PYTORCH_PRINT_REPRO_ON_FAILURE=0
Test file path: test_foreach.py