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pr/caffe2-py2-cuda9.0-cudnn7-aten failures are compilation errors, so can not be related. |
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…e2_core_hip * 'caffe2_core_hip' of github.com:petrex/pytorch: Refactor cmake files to not add hip includes and libs globally Fix UB when converting negative floating values to uint8_t (pytorch#7644) [auto] Update onnx to 3fc5f43 - move finalize function to be public. (onnx/onnx#987) onnx/onnx@3fc5f43 Fix duplicated thread pool flag [caffe2] Fix warning in net_async_tracing.cc (pytorch#7646) [auto] Update onnx to 8d548e2 - Update shape inference methods to throw exception (onnx/onnx#986) onnx/onnx@8d548e2 Fix flaky atomic iter test (pytorch#7649) Fix onnx Pow export (pytorch#7657) [auto] Update onnx to 8356ad5 - Add unit test framework for the project C++ APIs (onnx/onnx#763) onnx/onnx@8356ad5 [caffe2][nomnigraph] Add registry for optimization passes (pytorch#7656) [auto] Update onnx to 94ca052 - Update mypy version (onnx/onnx#968) onnx/onnx@94ca052 fix nccl distributed documentation
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The atomic_iter key is not necessary at the first position.
Failure reproducible in #7566 with docker image
308535385114.dkr.ecr.us-east-1.amazonaws.com/caffe2/py2-gcc5-ubuntu16.04:116-build-test-4542via minimal test setspytest -s -v /code/caffe2/python/checkpoint_test.py /code/caffe2/python/hypothesis_test.py::TestOperators::test_atomic_iter_with_concurrent_steps. An inspection into thestats_keyshows:['temp_node/time_ns/count' 'temp_node/time_ns/sum'
'atomic_iter/stats/iter/num_iter'
'trainer_2/pipe/inc_total/builtin_function_or_method/NoOutput/time_ns/count'
'trainer_2/time_ns/count'
'trainer_2/pipe/inc_total/builtin_function_or_method/NoOutput/time_ns/sum'
'trainer_2/time_ns/sum'
'trainer_1/pipe/inc_total/builtin_function_or_method/NoOutput/time_ns/sum'
'trainer_0/time_ns/count' 'trainer_1/time_ns/count'
'trainer_1/pipe/inc_total/builtin_function_or_method/NoOutput/time_ns/count'
'trainer_0/time_ns/sum'
'trainer_0/pipe/inc_total/builtin_function_or_method/NoOutput/time_ns/sum'
'trainer_0/pipe/inc_total/builtin_function_or_method/NoOutput/time_ns/count'
'trainer_1/time_ns/sum']