Package com.google.cloud.aiplatform.v1

Class ExplanationMetadata.InputMetadata

java.lang.Object
com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessage
com.google.protobuf.GeneratedMessage
com.google.cloud.aiplatform.v1.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.GeneratedMessage 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:

  • Field Details

    • INPUT_BASELINES_FIELD_NUMBER

      public static final int INPUT_BASELINES_FIELD_NUMBER
      See Also:

    • INPUT_TENSOR_NAME_FIELD_NUMBER

      public static final int INPUT_TENSOR_NAME_FIELD_NUMBER
      See Also:

    • ENCODING_FIELD_NUMBER

      public static final int ENCODING_FIELD_NUMBER
      See Also:

    • MODALITY_FIELD_NUMBER

      public static final int MODALITY_FIELD_NUMBER
      See Also:

    • FEATURE_VALUE_DOMAIN_FIELD_NUMBER

      public static final int FEATURE_VALUE_DOMAIN_FIELD_NUMBER
      See Also:

    • INDICES_TENSOR_NAME_FIELD_NUMBER

      public static final int INDICES_TENSOR_NAME_FIELD_NUMBER
      See Also:

    • DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER

      public static final int DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER
      See Also:

    • INDEX_FEATURE_MAPPING_FIELD_NUMBER

      public static final int INDEX_FEATURE_MAPPING_FIELD_NUMBER
      See Also:

    • ENCODED_TENSOR_NAME_FIELD_NUMBER

      public static final int ENCODED_TENSOR_NAME_FIELD_NUMBER
      See Also:

    • ENCODED_BASELINES_FIELD_NUMBER

      public static final int ENCODED_BASELINES_FIELD_NUMBER
      See Also:

    • VISUALIZATION_FIELD_NUMBER

      public static final int VISUALIZATION_FIELD_NUMBER
      See Also:

    • GROUP_NAME_FIELD_NUMBER

      public static final int GROUP_NAME_FIELD_NUMBER
      See Also:

  • Method Details

    • getDescriptor

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

    • internalGetFieldAccessorTable

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

    • 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

    • getInputTensorName

      public String getInputTensorName()
       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:
      getInputTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
      Returns:
      The inputTensorName.

    • 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.

    • getEncoding

      public ExplanationMetadata.InputMetadata.Encoding getEncoding()
       Defines how the feature is encoded into the input tensor. Defaults to
 IDENTITY.
      .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
      Specified by:
      getEncoding in interface ExplanationMetadata.InputMetadataOrBuilder
      Returns:
      The encoding.

    • getModality

      public String getModality()
       Modality of the feature. Valid values are: numeric, image. Defaults to
 numeric.
      string modality = 4;
      Specified by:
      getModality in interface ExplanationMetadata.InputMetadataOrBuilder
      Returns:
      The modality.

    • 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.

    • getFeatureValueDomain

      public ExplanationMetadata.InputMetadata.FeatureValueDomain getFeatureValueDomain()
       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:
      getFeatureValueDomain in interface ExplanationMetadata.InputMetadataOrBuilder
      Returns:
      The featureValueDomain.

    • getFeatureValueDomainOrBuilder

      public ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder getFeatureValueDomainOrBuilder()
       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:
      getFeatureValueDomainOrBuilder in interface ExplanationMetadata.InputMetadataOrBuilder

    • 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.

    • getVisualization

      public ExplanationMetadata.InputMetadata.Visualization getVisualization()
       Visualization configurations for image explanation.
      .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
      Specified by:
      getVisualization in interface ExplanationMetadata.InputMetadataOrBuilder
      Returns:
      The visualization.

    • getVisualizationOrBuilder

      public ExplanationMetadata.InputMetadata.VisualizationOrBuilder getVisualizationOrBuilder()
       Visualization configurations for image explanation.
      .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;
      Specified by:
      getVisualizationOrBuilder in interface ExplanationMetadata.InputMetadataOrBuilder

    • 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.GeneratedMessage

    • 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.GeneratedMessage
      Throws:
      IOException

    • getSerializedSize

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

    • 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) throws com.google.protobuf.InvalidProtocolBufferException
      Throws:
      com.google.protobuf.InvalidProtocolBufferException

    • 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

    • parseFrom

      public static ExplanationMetadata.InputMetadata parseFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

      public static ExplanationMetadata.InputMetadata parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static ExplanationMetadata.InputMetadata parseDelimitedFrom(InputStream input) throws IOException
      Throws:
      IOException

    • parseDelimitedFrom

      public static ExplanationMetadata.InputMetadata parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • parseFrom

      public static ExplanationMetadata.InputMetadata parseFrom(com.google.protobuf.CodedInputStream input) throws IOException
      Throws:
      IOException

    • parseFrom

      public static ExplanationMetadata.InputMetadata parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Throws:
      IOException

    • newBuilderForType

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

    • newBuilder

      public static ExplanationMetadata.InputMetadata.Builder newBuilder()

    • newBuilder

      public static ExplanationMetadata.InputMetadata.Builder newBuilder(ExplanationMetadata.InputMetadata prototype)

    • 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.AbstractMessage.BuilderParent parent)
      Overrides:
      newBuilderForType in class com.google.protobuf.AbstractMessage

    • getDefaultInstance

      public static ExplanationMetadata.InputMetadata getDefaultInstance()

    • parser

      public static com.google.protobuf.Parser<ExplanationMetadata.InputMetadata> parser()

    • 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.GeneratedMessage

    • getDefaultInstanceForType

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