Package com.google.cloud.aiplatform.v1

Class ExplanationMetadata.InputMetadata

  • All Implemented Interfaces:
    ExplanationMetadata.InputMetadataOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable
    Enclosing class:
    ExplanationMetadata
    public static final class ExplanationMetadata.InputMetadata
extends com.google.protobuf.GeneratedMessageV3
implements ExplanationMetadata.InputMetadataOrBuilder
     Metadata of the input of a feature.

 Fields other than
 [InputMetadata.input_baselines][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.input_baselines]
 are applicable only for Models that are using Vertex AI-provided images for
 Tensorflow.
    Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata
    See Also:
    Serialized Form

    • Field Detail

      • INPUT_BASELINES_FIELD_NUMBER

        public static final int INPUT_BASELINES_FIELD_NUMBER
        See Also:
        Constant Field Values

      • INPUT_TENSOR_NAME_FIELD_NUMBER

        public static final int INPUT_TENSOR_NAME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • FEATURE_VALUE_DOMAIN_FIELD_NUMBER

        public static final int FEATURE_VALUE_DOMAIN_FIELD_NUMBER
        See Also:
        Constant Field Values

      • INDICES_TENSOR_NAME_FIELD_NUMBER

        public static final int INDICES_TENSOR_NAME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER

        public static final int DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • INDEX_FEATURE_MAPPING_FIELD_NUMBER

        public static final int INDEX_FEATURE_MAPPING_FIELD_NUMBER
        See Also:
        Constant Field Values

      • ENCODED_TENSOR_NAME_FIELD_NUMBER

        public static final int ENCODED_TENSOR_NAME_FIELD_NUMBER
        See Also:
        Constant Field Values

      • ENCODED_BASELINES_FIELD_NUMBER

        public static final int ENCODED_BASELINES_FIELD_NUMBER
        See Also:
        Constant Field Values

      • VISUALIZATION_FIELD_NUMBER

        public static final int VISUALIZATION_FIELD_NUMBER
        See Also:
        Constant Field Values

      • GROUP_NAME_FIELD_NUMBER

        public static final int GROUP_NAME_FIELD_NUMBER
        See Also:
        Constant Field Values

    • Method Detail

      • newInstance

        protected Object newInstance​(com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)
        Overrides:
        newInstance in class com.google.protobuf.GeneratedMessageV3

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3

      • getInputBaselinesList

        public List<com.google.protobuf.Value> getInputBaselinesList()
         Baseline inputs for this feature.

 If no baseline is specified, Vertex AI chooses the baseline for this
 feature. If multiple baselines are specified, Vertex AI returns the
 average attributions across them in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].

 For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape
 of each baseline must match the shape of the input tensor. If a scalar is
 provided, we broadcast to the same shape as the input tensor.

 For custom images, the element of the baselines must be in the same
 format as the feature's input in the
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
        repeated .google.protobuf.Value input_baselines = 1;
        Specified by:
        getInputBaselinesList in interface ExplanationMetadata.InputMetadataOrBuilder

      • getInputBaselinesOrBuilderList

        public List<? extends com.google.protobuf.ValueOrBuilder> getInputBaselinesOrBuilderList()
         Baseline inputs for this feature.

 If no baseline is specified, Vertex AI chooses the baseline for this
 feature. If multiple baselines are specified, Vertex AI returns the
 average attributions across them in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].

 For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape
 of each baseline must match the shape of the input tensor. If a scalar is
 provided, we broadcast to the same shape as the input tensor.

 For custom images, the element of the baselines must be in the same
 format as the feature's input in the
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
        repeated .google.protobuf.Value input_baselines = 1;
        Specified by:
        getInputBaselinesOrBuilderList in interface ExplanationMetadata.InputMetadataOrBuilder

      • getInputBaselinesCount

        public int getInputBaselinesCount()
         Baseline inputs for this feature.

 If no baseline is specified, Vertex AI chooses the baseline for this
 feature. If multiple baselines are specified, Vertex AI returns the
 average attributions across them in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].

 For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape
 of each baseline must match the shape of the input tensor. If a scalar is
 provided, we broadcast to the same shape as the input tensor.

 For custom images, the element of the baselines must be in the same
 format as the feature's input in the
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
        repeated .google.protobuf.Value input_baselines = 1;
        Specified by:
        getInputBaselinesCount in interface ExplanationMetadata.InputMetadataOrBuilder

      • getInputBaselines

        public com.google.protobuf.Value getInputBaselines​(int index)
         Baseline inputs for this feature.

 If no baseline is specified, Vertex AI chooses the baseline for this
 feature. If multiple baselines are specified, Vertex AI returns the
 average attributions across them in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].

 For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape
 of each baseline must match the shape of the input tensor. If a scalar is
 provided, we broadcast to the same shape as the input tensor.

 For custom images, the element of the baselines must be in the same
 format as the feature's input in the
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
        repeated .google.protobuf.Value input_baselines = 1;
        Specified by:
        getInputBaselines in interface ExplanationMetadata.InputMetadataOrBuilder

      • getInputBaselinesOrBuilder

        public com.google.protobuf.ValueOrBuilder getInputBaselinesOrBuilder​(int index)
         Baseline inputs for this feature.

 If no baseline is specified, Vertex AI chooses the baseline for this
 feature. If multiple baselines are specified, Vertex AI returns the
 average attributions across them in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].

 For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape
 of each baseline must match the shape of the input tensor. If a scalar is
 provided, we broadcast to the same shape as the input tensor.

 For custom images, the element of the baselines must be in the same
 format as the feature's input in the
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
        repeated .google.protobuf.Value input_baselines = 1;
        Specified by:
        getInputBaselinesOrBuilder in interface ExplanationMetadata.InputMetadataOrBuilder

      • getInputTensorNameBytes

        public com.google.protobuf.ByteString getInputTensorNameBytes()
         Name of the input tensor for this feature. Required and is only
 applicable to Vertex AI-provided images for Tensorflow.
        string input_tensor_name = 2;
        Specified by:
        getInputTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The bytes for inputTensorName.

      • getEncodingValue

        public int getEncodingValue()
         Defines how the feature is encoded into the input tensor. Defaults to
 IDENTITY.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
        Specified by:
        getEncodingValue in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The enum numeric value on the wire for encoding.

      • getModalityBytes

        public com.google.protobuf.ByteString getModalityBytes()
         Modality of the feature. Valid values are: numeric, image. Defaults to
 numeric.
        string modality = 4;
        Specified by:
        getModalityBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The bytes for modality.

      • hasFeatureValueDomain

        public boolean hasFeatureValueDomain()
         The domain details of the input feature value. Like min/max, original
 mean or standard deviation if normalized.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
        Specified by:
        hasFeatureValueDomain in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        Whether the featureValueDomain field is set.

      • getIndicesTensorName

        public String getIndicesTensorName()
         Specifies the index of the values of the input tensor.
 Required when the input tensor is a sparse representation. Refer to
 Tensorflow documentation for more details:
 https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
        string indices_tensor_name = 6;
        Specified by:
        getIndicesTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The indicesTensorName.

      • getIndicesTensorNameBytes

        public com.google.protobuf.ByteString getIndicesTensorNameBytes()
         Specifies the index of the values of the input tensor.
 Required when the input tensor is a sparse representation. Refer to
 Tensorflow documentation for more details:
 https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
        string indices_tensor_name = 6;
        Specified by:
        getIndicesTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The bytes for indicesTensorName.

      • getDenseShapeTensorName

        public String getDenseShapeTensorName()
         Specifies the shape of the values of the input if the input is a sparse
 representation. Refer to Tensorflow documentation for more details:
 https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
        string dense_shape_tensor_name = 7;
        Specified by:
        getDenseShapeTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The denseShapeTensorName.

      • getDenseShapeTensorNameBytes

        public com.google.protobuf.ByteString getDenseShapeTensorNameBytes()
         Specifies the shape of the values of the input if the input is a sparse
 representation. Refer to Tensorflow documentation for more details:
 https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.
        string dense_shape_tensor_name = 7;
        Specified by:
        getDenseShapeTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The bytes for denseShapeTensorName.

      • getIndexFeatureMappingList

        public com.google.protobuf.ProtocolStringList getIndexFeatureMappingList()
         A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
        repeated string index_feature_mapping = 8;
        Specified by:
        getIndexFeatureMappingList in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        A list containing the indexFeatureMapping.

      • getIndexFeatureMappingCount

        public int getIndexFeatureMappingCount()
         A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
        repeated string index_feature_mapping = 8;
        Specified by:
        getIndexFeatureMappingCount in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The count of indexFeatureMapping.

      • getIndexFeatureMapping

        public String getIndexFeatureMapping​(int index)
         A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
        repeated string index_feature_mapping = 8;
        Specified by:
        getIndexFeatureMapping in interface ExplanationMetadata.InputMetadataOrBuilder
        Parameters:
        index - The index of the element to return.
        Returns:
        The indexFeatureMapping at the given index.

      • getIndexFeatureMappingBytes

        public com.google.protobuf.ByteString getIndexFeatureMappingBytes​(int index)
         A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.
        repeated string index_feature_mapping = 8;
        Specified by:
        getIndexFeatureMappingBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Parameters:
        index - The index of the value to return.
        Returns:
        The bytes of the indexFeatureMapping at the given index.

      • getEncodedTensorName

        public String getEncodedTensorName()
         Encoded tensor is a transformation of the input tensor. Must be provided
 if choosing
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution]
 or [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution]
 and the input tensor is not differentiable.

 An encoded tensor is generated if the input tensor is encoded by a lookup
 table.
        string encoded_tensor_name = 9;
        Specified by:
        getEncodedTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The encodedTensorName.

      • getEncodedTensorNameBytes

        public com.google.protobuf.ByteString getEncodedTensorNameBytes()
         Encoded tensor is a transformation of the input tensor. Must be provided
 if choosing
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution]
 or [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.xrai_attribution]
 and the input tensor is not differentiable.

 An encoded tensor is generated if the input tensor is encoded by a lookup
 table.
        string encoded_tensor_name = 9;
        Specified by:
        getEncodedTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The bytes for encodedTensorName.

      • getEncodedBaselinesList

        public List<com.google.protobuf.Value> getEncodedBaselinesList()
         A list of baselines for the encoded tensor.

 The shape of each baseline should match the shape of the encoded tensor.
 If a scalar is provided, Vertex AI broadcasts to the same shape as the
 encoded tensor.
        repeated .google.protobuf.Value encoded_baselines = 10;
        Specified by:
        getEncodedBaselinesList in interface ExplanationMetadata.InputMetadataOrBuilder

      • getEncodedBaselinesOrBuilderList

        public List<? extends com.google.protobuf.ValueOrBuilder> getEncodedBaselinesOrBuilderList()
         A list of baselines for the encoded tensor.

 The shape of each baseline should match the shape of the encoded tensor.
 If a scalar is provided, Vertex AI broadcasts to the same shape as the
 encoded tensor.
        repeated .google.protobuf.Value encoded_baselines = 10;
        Specified by:
        getEncodedBaselinesOrBuilderList in interface ExplanationMetadata.InputMetadataOrBuilder

      • getEncodedBaselinesCount

        public int getEncodedBaselinesCount()
         A list of baselines for the encoded tensor.

 The shape of each baseline should match the shape of the encoded tensor.
 If a scalar is provided, Vertex AI broadcasts to the same shape as the
 encoded tensor.
        repeated .google.protobuf.Value encoded_baselines = 10;
        Specified by:
        getEncodedBaselinesCount in interface ExplanationMetadata.InputMetadataOrBuilder

      • getEncodedBaselines

        public com.google.protobuf.Value getEncodedBaselines​(int index)
         A list of baselines for the encoded tensor.

 The shape of each baseline should match the shape of the encoded tensor.
 If a scalar is provided, Vertex AI broadcasts to the same shape as the
 encoded tensor.
        repeated .google.protobuf.Value encoded_baselines = 10;
        Specified by:
        getEncodedBaselines in interface ExplanationMetadata.InputMetadataOrBuilder

      • getEncodedBaselinesOrBuilder

        public com.google.protobuf.ValueOrBuilder getEncodedBaselinesOrBuilder​(int index)
         A list of baselines for the encoded tensor.

 The shape of each baseline should match the shape of the encoded tensor.
 If a scalar is provided, Vertex AI broadcasts to the same shape as the
 encoded tensor.
        repeated .google.protobuf.Value encoded_baselines = 10;
        Specified by:
        getEncodedBaselinesOrBuilder in interface ExplanationMetadata.InputMetadataOrBuilder

      • hasVisualization

        public boolean hasVisualization()
         Visualization configurations for image explanation.
        .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
        Specified by:
        hasVisualization in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        Whether the visualization field is set.

      • getGroupName

        public String getGroupName()
         Name of the group that the input belongs to. Features with the same group
 name will be treated as one feature when computing attributions. Features
 grouped together can have different shapes in value. If provided, there
 will be one single attribution generated in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions],
 keyed by the group name.
        string group_name = 12;
        Specified by:
        getGroupName in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The groupName.

      • getGroupNameBytes

        public com.google.protobuf.ByteString getGroupNameBytes()
         Name of the group that the input belongs to. Features with the same group
 name will be treated as one feature when computing attributions. Features
 grouped together can have different shapes in value. If provided, there
 will be one single attribution generated in
 [Attribution.feature_attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions],
 keyed by the group name.
        string group_name = 12;
        Specified by:
        getGroupNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
        Returns:
        The bytes for groupName.

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3

      • writeTo

        public void writeTo​(com.google.protobuf.CodedOutputStream output)
             throws IOException
        Specified by:
        writeTo in interface com.google.protobuf.MessageLite
        Overrides:
        writeTo in class com.google.protobuf.GeneratedMessageV3
        Throws:
        IOException

      • getSerializedSize

        public int getSerializedSize()
        Specified by:
        getSerializedSize in interface com.google.protobuf.MessageLite
        Overrides:
        getSerializedSize in class com.google.protobuf.GeneratedMessageV3

      • equals

        public boolean equals​(Object obj)
        Specified by:
        equals in interface com.google.protobuf.Message
        Overrides:
        equals in class com.google.protobuf.AbstractMessage

      • hashCode

        public int hashCode()
        Specified by:
        hashCode in interface com.google.protobuf.Message
        Overrides:
        hashCode in class com.google.protobuf.AbstractMessage

      • parseFrom

        public static ExplanationMetadata.InputMetadata parseFrom​(ByteBuffer data,
                                                          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                                   throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static ExplanationMetadata.InputMetadata parseFrom​(com.google.protobuf.ByteString data)
                                                   throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static ExplanationMetadata.InputMetadata parseFrom​(com.google.protobuf.ByteString data,
                                                          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                                   throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static ExplanationMetadata.InputMetadata parseFrom​(byte[] data)
                                                   throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • parseFrom

        public static ExplanationMetadata.InputMetadata parseFrom​(byte[] data,
                                                          com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                                   throws com.google.protobuf.InvalidProtocolBufferException
        Throws:
        com.google.protobuf.InvalidProtocolBufferException

      • newBuilderForType

        public ExplanationMetadata.InputMetadata.Builder newBuilderForType()
        Specified by:
        newBuilderForType in interface com.google.protobuf.Message
        Specified by:
        newBuilderForType in interface com.google.protobuf.MessageLite

      • toBuilder

        public ExplanationMetadata.InputMetadata.Builder toBuilder()
        Specified by:
        toBuilder in interface com.google.protobuf.Message
        Specified by:
        toBuilder in interface com.google.protobuf.MessageLite

      • newBuilderForType

        protected ExplanationMetadata.InputMetadata.Builder newBuilderForType​(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)
        Specified by:
        newBuilderForType in class com.google.protobuf.GeneratedMessageV3

      • getParserForType

        public com.google.protobuf.Parser<ExplanationMetadata.InputMetadata> getParserForType()
        Specified by:
        getParserForType in interface com.google.protobuf.Message
        Specified by:
        getParserForType in interface com.google.protobuf.MessageLite
        Overrides:
        getParserForType in class com.google.protobuf.GeneratedMessageV3

      • getDefaultInstanceForType

        public ExplanationMetadata.InputMetadata getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder