Python google.protobuf.text_format 模块，Merge() 实例源码

我们从Python开源项目中，提取了以下50个代码示例，用于说明如何使用google.protobuf.text_format.Merge()。

项目：facade-segmentation 作者：jfemiani | 项目源码 | 文件源码

def make_testable(train_model_path):
    # load the train net prototxt as a protobuf message
    with open(train_model_path) as f:
        train_str = f.read()
    train_net = caffe_pb2.NetParameter()
    text_format.Merge(train_str, train_net)

    # add the mean, var top blobs to all BN layers
    for layer in train_net.layer:
        if layer.type == "BN" and len(layer.top) == 1:
            layer.top.append(layer.top[0] + "-mean")
            layer.top.append(layer.top[0] + "-var")

    # remove the test data layer if present
    if train_net.layer[1].name == "data" and train_net.layer[1].include:
        train_net.layer.remove(train_net.layer[1])
        if train_net.layer[0].include:
            # remove the 'include {phase: TRAIN}' layer param
            train_net.layer[0].include.remove(train_net.layer[0].include[0])
    return train_net

项目：ngraph 作者：NervanaSystems | 项目源码 | 文件源码

def import_protobuf(self, pb_file, verbose=False):
        """
        Imports graph_def from protobuf file to ngraph.

        Arguments:
            pb_file: Protobuf file path.
            verbose: Prints graph_def at each node if True.
        """
        # read graph_def
        graph_def = tf.GraphDef()
        if mimetypes.guess_type(pb_file)[0] == 'text/plain':
            with open(pb_file, 'r') as f:
                text_format.Merge(f.read(), graph_def)
        else:
            with open(pb_file, 'rb') as f:
                graph_def.ParseFromString(f.read())

        self.import_graph_def(graph_def, verbose=verbose)

项目：transform 作者：tensorflow | 项目源码 | 文件源码

def _assert_encode_decode(self, coder, expected_proto_text, expected_decoded):
    example = tf.train.Example()
    text_format.Merge(expected_proto_text, example)
    data = example.SerializeToString()

    # Assert the data is decoded into the expected format.
    decoded = coder.decode(data)
    np.testing.assert_equal(expected_decoded, decoded)

    # Assert the decoded data can be encoded back into the original proto.
    encoded = coder.encode(decoded)
    parsed_example = tf.train.Example()
    parsed_example.ParseFromString(encoded)
    self.assertEqual(example, parsed_example)

    # Assert the data can be decoded from the encoded string.
    decoded_again = coder.decode(encoded)
    np.testing.assert_equal(expected_decoded, decoded_again)

项目：transform 作者：tensorflow | 项目源码 | 文件源码

def _assert_decode_encode(self, coder, expected_proto_text, expected_decoded):
    example = tf.train.Example()
    text_format.Merge(expected_proto_text, example)

    # Assert the expected decoded data can be encoded into the expected proto.
    encoded = coder.encode(expected_decoded)
    parsed_example = tf.train.Example()
    parsed_example.ParseFromString(encoded)
    self.assertEqual(example, parsed_example)

    # Assert the encoded data can be decoded into the original input.
    decoded = coder.decode(encoded)
    np.testing.assert_equal(expected_decoded, decoded)

    # Assert the decoded data can be encoded back into the expected proto.
    encoded_again = coder.encode(decoded)
    parsed_example_again = tf.train.Example()
    parsed_example_again.ParseFromString(encoded_again)
    np.testing.assert_equal(example, parsed_example_again)

项目：transform 作者：tensorflow | 项目源码 | 文件源码

def test_example_proto_coder_error(self):
    input_schema = dataset_schema.from_feature_spec({
        '2d_vector_feature': tf.FixedLenFeature(shape=[2, 2], dtype=tf.int64),
    })
    coder = example_proto_coder.ExampleProtoCoder(input_schema)

    example_decoded_value = {
        '2d_vector_feature': [1, 2, 3]
    }
    example_proto_text = """
    features {
      feature { key: "1d_vector_feature"
                value { int64_list { value: [ 1, 2, 3 ] } } }
    }
    """
    example = tf.train.Example()
    text_format.Merge(example_proto_text, example)

    # Ensure that we raise an exception for trying to encode invalid data.
    with self.assertRaisesRegexp(ValueError, 'got wrong number of values'):
      _ = coder.encode(example_decoded_value)

    # Ensure that we raise an exception for trying to parse invalid data.
    with self.assertRaisesRegexp(ValueError, 'got wrong number of values'):
      _ = coder.decode(example.SerializeToString())

项目：Vector-Tiles-Reader-QGIS-Plugin 作者：geometalab | 项目源码 | 文件源码

def testMergeExpandedAnyRepeated(self):
    message = any_test_pb2.TestAny()
    text = ('repeated_any_value {\n'
            '  [type.googleapis.com/protobuf_unittest.OneString] {\n'
            '    data: "string0"\n'
            '  }\n'
            '}\n'
            'repeated_any_value {\n'
            '  [type.googleapis.com/protobuf_unittest.OneString] {\n'
            '    data: "string1"\n'
            '  }\n'
            '}\n')
    text_format.Merge(text, message, descriptor_pool=descriptor_pool.Default())
    packed_message = unittest_pb2.OneString()
    message.repeated_any_value[0].Unpack(packed_message)
    self.assertEqual('string0', packed_message.data)
    message.repeated_any_value[1].Unpack(packed_message)
    self.assertEqual('string1', packed_message.data)

项目：Vector-Tiles-Reader-QGIS-Plugin 作者：geometalab | 项目源码 | 文件源码

def testParsingNestedClass(self):
    """Test that the generated class can parse a nested message."""
    file_descriptor = descriptor_pb2.FileDescriptorProto()
    file_descriptor.ParseFromString(self._GetSerializedFileDescriptor('C'))
    msg_descriptor = descriptor.MakeDescriptor(
        file_descriptor.message_type[0])
    msg_class = reflection.MakeClass(msg_descriptor)
    msg = msg_class()
    msg_str = (
        'bar {'
        '  baz {'
        '    deep: 4'
        '  }'
        '}')
    text_format.Merge(msg_str, msg)
    self.assertEqual(msg.bar.baz.deep, 4)

项目：CityHorizon 作者：CityStreetWander | 项目源码 | 文件源码

def make_testable(train_model_path):
    # load the train net prototxt as a protobuf message
    with open(train_model_path) as f:
        train_str = f.read()
    train_net = caffe_pb2.NetParameter()
    text_format.Merge(train_str, train_net)

    # add the mean, var top blobs to all BN layers
    for layer in train_net.layer:
        if layer.type == "BN" and len(layer.top) == 1:
            layer.top.append(layer.top[0] + "-mean")
            layer.top.append(layer.top[0] + "-var")

    # remove the test data layer if present
    if train_net.layer[1].name == "data" and train_net.layer[1].include:
        train_net.layer.remove(train_net.layer[1])
        if train_net.layer[0].include:
            # remove the 'include {phase: TRAIN}' layer param
            train_net.layer[0].include.remove(train_net.layer[0].include[0])
    return train_net

项目：cv4ag 作者：worldbank | 项目源码 | 文件源码

def make_testable(train_model_path):
    # load the train net prototxt as a protobuf message
    with open(train_model_path) as f:
        train_str = f.read()
    train_net = caffe_pb2.NetParameter()
    text_format.Merge(train_str, train_net)

    # add the mean, var top blobs to all BN layers
    for layer in train_net.layer:
        if layer.type == "BN" and len(layer.top) == 1:
            layer.top.append(layer.top[0] + "-mean")
            layer.top.append(layer.top[0] + "-var")

    # remove the test data layer if present
    if train_net.layer[1].name == "data" and train_net.layer[1].include:
        train_net.layer.remove(train_net.layer[1])
        if train_net.layer[0].include:
            # remove the 'include {phase: TRAIN}' layer param
            train_net.layer[0].include.remove(train_net.layer[0].include[0])
    return train_net

项目：protoc-gen-lua-bin 作者：u0u0 | 项目源码 | 文件源码

def testParsingNestedClass(self):
    """Test that the generated class can parse a nested message."""
    file_descriptor = descriptor_pb2.FileDescriptorProto()
    file_descriptor.ParseFromString(self._GetSerializedFileDescriptor('C'))
    msg_descriptor = descriptor.MakeDescriptor(
        file_descriptor.message_type[0])
    msg_class = reflection.MakeClass(msg_descriptor)
    msg = msg_class()
    msg_str = (
        'bar {'
        '  baz {'
        '    deep: 4'
        '  }'
        '}')
    text_format.Merge(msg_str, msg)
    self.assertEqual(msg.bar.baz.deep, 4)