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# Copyright 2020 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Utils to set Owner annotations on benchmarks.
@owner_utils.Owner('owner_team/user') can be set either at the benchmark class
level / benchmark method level or both.
Runner frameworks can use owner_utils.GetOwner(benchmark_method) to get the
actual owner. Python inheritance for the owner attribute is respected. (E.g
method level owner takes precedence over class level).
See owner_utils_test for associated tests and more examples.
The decorator can be applied both at the method level and at the class level.
Simple example:
===============
class MLBenchmark:
@Owner('example_id')
def benchmark_method_1_gpu(self):
return True
"""
def Owner(owner_name):
"""Sets the owner attribute on a decorated method or class."""
def _Wrapper(func_or_class):
"""Sets the benchmark owner attribute."""
func_or_class.__benchmark__owner__ = owner_name
return func_or_class
return _Wrapper
def GetOwner(benchmark_method_or_class):
"""Gets the inherited owner attribute for this benchmark.
Checks for existence of __benchmark__owner__. If it's not present, looks for
it in the parent class's attribute list.
Args:
benchmark_method_or_class: A benchmark method or class.
Returns:
string - the associated owner if present / None.
"""
if hasattr(benchmark_method_or_class, '__benchmark__owner__'):
return benchmark_method_or_class.__benchmark__owner__
elif hasattr(benchmark_method_or_class, '__self__'):
if hasattr(benchmark_method_or_class.__self__, '__benchmark__owner__'):
return benchmark_method_or_class.__self__.__benchmark__owner__
return None
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