# Copyright 2015 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. # ============================================================================== """Utility functions for comparing proto2 messages in Python. ProtoEq() compares two proto2 messages for equality. ClearDefaultValuedFields() recursively clears the fields that are set to their default values. This is useful for comparing protocol buffers where the semantics of unset fields and default valued fields are the same. assertProtoEqual() is useful for unit tests. It produces much more helpful output than assertEqual() for proto2 messages, e.g. this: outer { inner { - strings: "x" ? ^ + strings: "y" ? ^ } } ...compared to the default output from assertEqual() that looks like this: AssertionError: != Call it inside your unit test's googletest.TestCase subclasses like this: from tensorflow.python.util.protobuf import compare class MyTest(googletest.TestCase): ... def testXXX(self): ... compare.assertProtoEqual(self, a, b) Alternatively: from tensorflow.python.util.protobuf import compare class MyTest(compare.ProtoAssertions, googletest.TestCase): ... def testXXX(self): ... self.assertProtoEqual(a, b) """ from __future__ import absolute_import from __future__ import division from __future__ import print_function import collections import six from google.protobuf import descriptor from google.protobuf import descriptor_pool from google.protobuf import message from google.protobuf import text_format def assertProtoEqual(self, a, b, check_initialized=True, # pylint: disable=invalid-name normalize_numbers=False, msg=None): """Fails with a useful error if a and b aren't equal. Comparison of repeated fields matches the semantics of unittest.TestCase.assertEqual(), ie order and extra duplicates fields matter. Args: self: googletest.TestCase a: proto2 PB instance, or text string representing one. b: proto2 PB instance -- message.Message or subclass thereof. check_initialized: boolean, whether to fail if either a or b isn't initialized. normalize_numbers: boolean, whether to normalize types and precision of numbers before comparison. msg: if specified, is used as the error message on failure. """ pool = descriptor_pool.Default() if isinstance(a, six.string_types): a = text_format.Merge(a, b.__class__(), descriptor_pool=pool) for pb in a, b: if check_initialized: errors = pb.FindInitializationErrors() if errors: self.fail('Initialization errors: %s\n%s' % (errors, pb)) if normalize_numbers: NormalizeNumberFields(pb) self.assertMultiLineEqual( text_format.MessageToString(a, descriptor_pool=pool), text_format.MessageToString(b, descriptor_pool=pool), msg=msg) def NormalizeNumberFields(pb): """Normalizes types and precisions of number fields in a protocol buffer. Due to subtleties in the python protocol buffer implementation, it is possible for values to have different types and precision depending on whether they were set and retrieved directly or deserialized from a protobuf. This function normalizes integer values to ints and longs based on width, 32-bit floats to five digits of precision to account for python always storing them as 64-bit, and ensures doubles are floating point for when they're set to integers. Modifies pb in place. Recurses into nested objects. Args: pb: proto2 message. Returns: the given pb, modified in place. """ for desc, values in pb.ListFields(): is_repeated = True if desc.label is not descriptor.FieldDescriptor.LABEL_REPEATED: is_repeated = False values = [values] normalized_values = None # We force 32-bit values to int and 64-bit values to long to make # alternate implementations where the distinction is more significant # (e.g. the C++ implementation) simpler. if desc.type in (descriptor.FieldDescriptor.TYPE_INT64, descriptor.FieldDescriptor.TYPE_UINT64, descriptor.FieldDescriptor.TYPE_SINT64): normalized_values = [int(x) for x in values] elif desc.type in (descriptor.FieldDescriptor.TYPE_INT32, descriptor.FieldDescriptor.TYPE_UINT32, descriptor.FieldDescriptor.TYPE_SINT32, descriptor.FieldDescriptor.TYPE_ENUM): normalized_values = [int(x) for x in values] elif desc.type == descriptor.FieldDescriptor.TYPE_FLOAT: normalized_values = [round(x, 6) for x in values] elif desc.type == descriptor.FieldDescriptor.TYPE_DOUBLE: normalized_values = [round(float(x), 7) for x in values] if normalized_values is not None: if is_repeated: pb.ClearField(desc.name) getattr(pb, desc.name).extend(normalized_values) else: setattr(pb, desc.name, normalized_values[0]) if (desc.type == descriptor.FieldDescriptor.TYPE_MESSAGE or desc.type == descriptor.FieldDescriptor.TYPE_GROUP): if (desc.type == descriptor.FieldDescriptor.TYPE_MESSAGE and desc.message_type.has_options and desc.message_type.GetOptions().map_entry): # This is a map, only recurse if the values have a message type. if (desc.message_type.fields_by_number[2].type == descriptor.FieldDescriptor.TYPE_MESSAGE): for v in six.itervalues(values): NormalizeNumberFields(v) else: for v in values: # recursive step NormalizeNumberFields(v) return pb def _IsMap(value): return isinstance(value, collections.Mapping) def _IsRepeatedContainer(value): if isinstance(value, six.string_types): return False try: iter(value) return True except TypeError: return False def ProtoEq(a, b): """Compares two proto2 objects for equality. Recurses into nested messages. Uses list (not set) semantics for comparing repeated fields, ie duplicates and order matter. Args: a: A proto2 message or a primitive. b: A proto2 message or a primitive. Returns: `True` if the messages are equal. """ def Format(pb): """Returns a dictionary or unchanged pb bases on its type. Specifically, this function returns a dictionary that maps tag number (for messages) or element index (for repeated fields) to value, or just pb unchanged if it's neither. Args: pb: A proto2 message or a primitive. Returns: A dict or unchanged pb. """ if isinstance(pb, message.Message): return dict((desc.number, value) for desc, value in pb.ListFields()) elif _IsMap(pb): return dict(pb.items()) elif _IsRepeatedContainer(pb): return dict(enumerate(list(pb))) else: return pb a, b = Format(a), Format(b) # Base case if not isinstance(a, dict) or not isinstance(b, dict): return a == b # This list performs double duty: it compares two messages by tag value *or* # two repeated fields by element, in order. the magic is in the format() # function, which converts them both to the same easily comparable format. for tag in sorted(set(a.keys()) | set(b.keys())): if tag not in a or tag not in b: return False else: # Recursive step if not ProtoEq(a[tag], b[tag]): return False # Didn't find any values that differed, so they're equal! return True class ProtoAssertions(object): """Mix this into a googletest.TestCase class to get proto2 assertions. Usage: class SomeTestCase(compare.ProtoAssertions, googletest.TestCase): ... def testSomething(self): ... self.assertProtoEqual(a, b) See module-level definitions for method documentation. """ # pylint: disable=invalid-name def assertProtoEqual(self, *args, **kwargs): return assertProtoEqual(self, *args, **kwargs)