# 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