Class ExplanationMetadata.OutputMetadata.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.OutputMetadata.Builder>
com.google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata.Builder
All Implemented Interfaces:
ExplanationMetadata.OutputMetadataOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
ExplanationMetadata.OutputMetadata

public static final class ExplanationMetadata.OutputMetadata.Builder extends com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.OutputMetadata.Builder> implements ExplanationMetadata.OutputMetadataOrBuilder
 Metadata of the prediction output to be explained.
 
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata
  • 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.Builder<ExplanationMetadata.OutputMetadata.Builder>
    • clear

      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.OutputMetadata.Builder>
    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.OutputMetadata.Builder>
    • getDefaultInstanceForType

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

      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder
    • buildPartial

      public ExplanationMetadata.OutputMetadata buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder
    • mergeFrom

      public ExplanationMetadata.OutputMetadata.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ExplanationMetadata.OutputMetadata.Builder>
    • mergeFrom

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.OutputMetadata.Builder>
    • mergeFrom

      public ExplanationMetadata.OutputMetadata.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ExplanationMetadata.OutputMetadata.Builder>
      Throws:
      IOException
    • getDisplayNameMappingCase

      Specified by:
      getDisplayNameMappingCase in interface ExplanationMetadata.OutputMetadataOrBuilder
    • clearDisplayNameMapping

      public ExplanationMetadata.OutputMetadata.Builder clearDisplayNameMapping()
    • hasIndexDisplayNameMapping

      public boolean hasIndexDisplayNameMapping()
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
      Specified by:
      hasIndexDisplayNameMapping in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      Whether the indexDisplayNameMapping field is set.
    • getIndexDisplayNameMapping

      public com.google.protobuf.Value getIndexDisplayNameMapping()
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
      Specified by:
      getIndexDisplayNameMapping in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      The indexDisplayNameMapping.
    • setIndexDisplayNameMapping

      public ExplanationMetadata.OutputMetadata.Builder setIndexDisplayNameMapping(com.google.protobuf.Value value)
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
    • setIndexDisplayNameMapping

      public ExplanationMetadata.OutputMetadata.Builder setIndexDisplayNameMapping(com.google.protobuf.Value.Builder builderForValue)
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
    • mergeIndexDisplayNameMapping

      public ExplanationMetadata.OutputMetadata.Builder mergeIndexDisplayNameMapping(com.google.protobuf.Value value)
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
    • clearIndexDisplayNameMapping

      public ExplanationMetadata.OutputMetadata.Builder clearIndexDisplayNameMapping()
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
    • getIndexDisplayNameMappingBuilder

      public com.google.protobuf.Value.Builder getIndexDisplayNameMappingBuilder()
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
    • getIndexDisplayNameMappingOrBuilder

      public com.google.protobuf.ValueOrBuilder getIndexDisplayNameMappingOrBuilder()
       Static mapping between the index and display name.
      
       Use this if the outputs are a deterministic n-dimensional array, e.g. a
       list of scores of all the classes in a pre-defined order for a
       multi-classification Model. It's not feasible if the outputs are
       non-deterministic, e.g. the Model produces top-k classes or sort the
       outputs by their values.
      
       The shape of the value must be an n-dimensional array of strings. The
       number of dimensions must match that of the outputs to be explained.
       The
       [Attribution.output_display_name][google.cloud.aiplatform.v1.Attribution.output_display_name]
       is populated by locating in the mapping with
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index].
       
      .google.protobuf.Value index_display_name_mapping = 1;
      Specified by:
      getIndexDisplayNameMappingOrBuilder in interface ExplanationMetadata.OutputMetadataOrBuilder
    • hasDisplayNameMappingKey

      public boolean hasDisplayNameMappingKey()
       Specify a field name in the prediction to look for the display name.
      
       Use this if the prediction contains the display names for the outputs.
      
       The display names in the prediction must have the same shape of the
       outputs, so that it can be located by
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
       for a specific output.
       
      string display_name_mapping_key = 2;
      Specified by:
      hasDisplayNameMappingKey in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      Whether the displayNameMappingKey field is set.
    • getDisplayNameMappingKey

      public String getDisplayNameMappingKey()
       Specify a field name in the prediction to look for the display name.
      
       Use this if the prediction contains the display names for the outputs.
      
       The display names in the prediction must have the same shape of the
       outputs, so that it can be located by
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
       for a specific output.
       
      string display_name_mapping_key = 2;
      Specified by:
      getDisplayNameMappingKey in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      The displayNameMappingKey.
    • getDisplayNameMappingKeyBytes

      public com.google.protobuf.ByteString getDisplayNameMappingKeyBytes()
       Specify a field name in the prediction to look for the display name.
      
       Use this if the prediction contains the display names for the outputs.
      
       The display names in the prediction must have the same shape of the
       outputs, so that it can be located by
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
       for a specific output.
       
      string display_name_mapping_key = 2;
      Specified by:
      getDisplayNameMappingKeyBytes in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      The bytes for displayNameMappingKey.
    • setDisplayNameMappingKey

      public ExplanationMetadata.OutputMetadata.Builder setDisplayNameMappingKey(String value)
       Specify a field name in the prediction to look for the display name.
      
       Use this if the prediction contains the display names for the outputs.
      
       The display names in the prediction must have the same shape of the
       outputs, so that it can be located by
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
       for a specific output.
       
      string display_name_mapping_key = 2;
      Parameters:
      value - The displayNameMappingKey to set.
      Returns:
      This builder for chaining.
    • clearDisplayNameMappingKey

      public ExplanationMetadata.OutputMetadata.Builder clearDisplayNameMappingKey()
       Specify a field name in the prediction to look for the display name.
      
       Use this if the prediction contains the display names for the outputs.
      
       The display names in the prediction must have the same shape of the
       outputs, so that it can be located by
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
       for a specific output.
       
      string display_name_mapping_key = 2;
      Returns:
      This builder for chaining.
    • setDisplayNameMappingKeyBytes

      public ExplanationMetadata.OutputMetadata.Builder setDisplayNameMappingKeyBytes(com.google.protobuf.ByteString value)
       Specify a field name in the prediction to look for the display name.
      
       Use this if the prediction contains the display names for the outputs.
      
       The display names in the prediction must have the same shape of the
       outputs, so that it can be located by
       [Attribution.output_index][google.cloud.aiplatform.v1.Attribution.output_index]
       for a specific output.
       
      string display_name_mapping_key = 2;
      Parameters:
      value - The bytes for displayNameMappingKey to set.
      Returns:
      This builder for chaining.
    • getOutputTensorName

      public String getOutputTensorName()
       Name of the output tensor. Required and is only applicable to Vertex
       AI provided images for Tensorflow.
       
      string output_tensor_name = 3;
      Specified by:
      getOutputTensorName in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      The outputTensorName.
    • getOutputTensorNameBytes

      public com.google.protobuf.ByteString getOutputTensorNameBytes()
       Name of the output tensor. Required and is only applicable to Vertex
       AI provided images for Tensorflow.
       
      string output_tensor_name = 3;
      Specified by:
      getOutputTensorNameBytes in interface ExplanationMetadata.OutputMetadataOrBuilder
      Returns:
      The bytes for outputTensorName.
    • setOutputTensorName

      public ExplanationMetadata.OutputMetadata.Builder setOutputTensorName(String value)
       Name of the output tensor. Required and is only applicable to Vertex
       AI provided images for Tensorflow.
       
      string output_tensor_name = 3;
      Parameters:
      value - The outputTensorName to set.
      Returns:
      This builder for chaining.
    • clearOutputTensorName

      public ExplanationMetadata.OutputMetadata.Builder clearOutputTensorName()
       Name of the output tensor. Required and is only applicable to Vertex
       AI provided images for Tensorflow.
       
      string output_tensor_name = 3;
      Returns:
      This builder for chaining.
    • setOutputTensorNameBytes

      public ExplanationMetadata.OutputMetadata.Builder setOutputTensorNameBytes(com.google.protobuf.ByteString value)
       Name of the output tensor. Required and is only applicable to Vertex
       AI provided images for Tensorflow.
       
      string output_tensor_name = 3;
      Parameters:
      value - The bytes for outputTensorName to set.
      Returns:
      This builder for chaining.