Package com.google.cloud.aiplatform.v1

Class ExplanationMetadata.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.Builder>
com.google.cloud.aiplatform.v1.ExplanationMetadata.Builder
All Implemented Interfaces:
ExplanationMetadataOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
ExplanationMetadata
public static final class ExplanationMetadata.Builder extends com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.Builder> implements ExplanationMetadataOrBuilder
 Metadata describing the Model's input and output for explanation.
Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata

  • Method Details

    • getDescriptor

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

    • internalGetMapFieldReflection

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMapFieldReflection(int number)
      Overrides:
      internalGetMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.Builder>

    • internalGetMutableMapFieldReflection

      protected com.google.protobuf.MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)
      Overrides:
      internalGetMutableMapFieldReflection in class com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.Builder>

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ExplanationMetadata.Builder>

    • clear

      public ExplanationMetadata.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.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.Builder>

    • getDefaultInstanceForType

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

    • build

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

    • buildPartial

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

    • mergeFrom

      public ExplanationMetadata.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.Builder>

    • mergeFrom

      public ExplanationMetadata.Builder mergeFrom(ExplanationMetadata other)

    • isInitialized

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

    • mergeFrom

      public ExplanationMetadata.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.Builder>
      Throws:
      IOException

    • getInputsCount

      public int getInputsCount()
      Description copied from interface: ExplanationMetadataOrBuilder
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getInputsCount in interface ExplanationMetadataOrBuilder

    • containsInputs

      public boolean containsInputs(String key)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      containsInputs in interface ExplanationMetadataOrBuilder

    • getInputs

      @Deprecated public Map<String,ExplanationMetadata.InputMetadata> getInputs()
      Deprecated.
      Use getInputsMap() instead.
      Specified by:
      getInputs in interface ExplanationMetadataOrBuilder

    • getInputsMap

      public Map<String,ExplanationMetadata.InputMetadata> getInputsMap()
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getInputsMap in interface ExplanationMetadataOrBuilder

    • getInputsOrDefault

      public ExplanationMetadata.InputMetadata getInputsOrDefault(String key, ExplanationMetadata.InputMetadata defaultValue)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getInputsOrDefault in interface ExplanationMetadataOrBuilder

    • getInputsOrThrow

      public ExplanationMetadata.InputMetadata getInputsOrThrow(String key)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getInputsOrThrow in interface ExplanationMetadataOrBuilder

    • clearInputs

      public ExplanationMetadata.Builder clearInputs()

    • removeInputs

      public ExplanationMetadata.Builder removeInputs(String key)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

    • getMutableInputs

      @Deprecated public Map<String,ExplanationMetadata.InputMetadata> getMutableInputs()
      Deprecated.
      Use alternate mutation accessors instead.

    • putInputs

      public ExplanationMetadata.Builder putInputs(String key, ExplanationMetadata.InputMetadata value)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

    • putAllInputs

      public ExplanationMetadata.Builder putAllInputs(Map<String,ExplanationMetadata.InputMetadata> values)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

    • putInputsBuilderIfAbsent

      public ExplanationMetadata.InputMetadata.Builder putInputsBuilderIfAbsent(String key)
       Required. Map from feature names to feature input metadata. Keys are the
 name of the features. Values are the specification of the feature.

 An empty InputMetadata is valid. It describes a text feature which has the
 name specified as the key in
 [ExplanationMetadata.inputs][google.cloud.aiplatform.v1.ExplanationMetadata.inputs].
 The baseline of the empty feature is chosen by Vertex AI.

 For Vertex AI-provided Tensorflow images, the key can be any friendly
 name of the feature. Once specified,
 [featureAttributions][google.cloud.aiplatform.v1.Attribution.feature_attributions]
 are keyed by this key (if not grouped with another feature).

 For custom images, the key must match with the key in
 [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

    • getOutputsCount

      public int getOutputsCount()
      Description copied from interface: ExplanationMetadataOrBuilder
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getOutputsCount in interface ExplanationMetadataOrBuilder

    • containsOutputs

      public boolean containsOutputs(String key)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      containsOutputs in interface ExplanationMetadataOrBuilder

    • getOutputs

      @Deprecated public Map<String,ExplanationMetadata.OutputMetadata> getOutputs()
      Deprecated.
      Use getOutputsMap() instead.
      Specified by:
      getOutputs in interface ExplanationMetadataOrBuilder

    • getOutputsMap

      public Map<String,ExplanationMetadata.OutputMetadata> getOutputsMap()
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getOutputsMap in interface ExplanationMetadataOrBuilder

    • getOutputsOrDefault

      public ExplanationMetadata.OutputMetadata getOutputsOrDefault(String key, ExplanationMetadata.OutputMetadata defaultValue)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getOutputsOrDefault in interface ExplanationMetadataOrBuilder

    • getOutputsOrThrow

      public ExplanationMetadata.OutputMetadata getOutputsOrThrow(String key)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];
      Specified by:
      getOutputsOrThrow in interface ExplanationMetadataOrBuilder

    • clearOutputs

      public ExplanationMetadata.Builder clearOutputs()

    • removeOutputs

      public ExplanationMetadata.Builder removeOutputs(String key)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

    • getMutableOutputs

      @Deprecated public Map<String,ExplanationMetadata.OutputMetadata> getMutableOutputs()
      Deprecated.
      Use alternate mutation accessors instead.

    • putOutputs

      public ExplanationMetadata.Builder putOutputs(String key, ExplanationMetadata.OutputMetadata value)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

    • putAllOutputs

      public ExplanationMetadata.Builder putAllOutputs(Map<String,ExplanationMetadata.OutputMetadata> values)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

    • putOutputsBuilderIfAbsent

      public ExplanationMetadata.OutputMetadata.Builder putOutputsBuilderIfAbsent(String key)
       Required. Map from output names to output metadata.

 For Vertex AI-provided Tensorflow images, keys can be any user defined
 string that consists of any UTF-8 characters.

 For custom images, keys are the name of the output field in the prediction
 to be explained.

 Currently only one key is allowed.
      map<string, .google.cloud.aiplatform.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

    • getFeatureAttributionsSchemaUri

      public String getFeatureAttributionsSchemaUri()
       Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature
 attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML tabular Models always have this field populated by Vertex AI.
 Note: The URI given on output may be different, including the URI scheme,
 than the one given on input. The output URI will point to a location where
 the user only has a read access.
      string feature_attributions_schema_uri = 3;
      Specified by:
      getFeatureAttributionsSchemaUri in interface ExplanationMetadataOrBuilder
      Returns:
      The featureAttributionsSchemaUri.

    • getFeatureAttributionsSchemaUriBytes

      public com.google.protobuf.ByteString getFeatureAttributionsSchemaUriBytes()
       Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature
 attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML tabular Models always have this field populated by Vertex AI.
 Note: The URI given on output may be different, including the URI scheme,
 than the one given on input. The output URI will point to a location where
 the user only has a read access.
      string feature_attributions_schema_uri = 3;
      Specified by:
      getFeatureAttributionsSchemaUriBytes in interface ExplanationMetadataOrBuilder
      Returns:
      The bytes for featureAttributionsSchemaUri.

    • setFeatureAttributionsSchemaUri

      public ExplanationMetadata.Builder setFeatureAttributionsSchemaUri(String value)
       Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature
 attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML tabular Models always have this field populated by Vertex AI.
 Note: The URI given on output may be different, including the URI scheme,
 than the one given on input. The output URI will point to a location where
 the user only has a read access.
      string feature_attributions_schema_uri = 3;
      Parameters:
      value - The featureAttributionsSchemaUri to set.
      Returns:
      This builder for chaining.

    • clearFeatureAttributionsSchemaUri

      public ExplanationMetadata.Builder clearFeatureAttributionsSchemaUri()
       Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature
 attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML tabular Models always have this field populated by Vertex AI.
 Note: The URI given on output may be different, including the URI scheme,
 than the one given on input. The output URI will point to a location where
 the user only has a read access.
      string feature_attributions_schema_uri = 3;
      Returns:
      This builder for chaining.

    • setFeatureAttributionsSchemaUriBytes

      public ExplanationMetadata.Builder setFeatureAttributionsSchemaUriBytes(com.google.protobuf.ByteString value)
       Points to a YAML file stored on Google Cloud Storage describing the format
 of the [feature
 attributions][google.cloud.aiplatform.v1.Attribution.feature_attributions].
 The schema is defined as an OpenAPI 3.0.2 [Schema
 Object](https://github.com/OAI/OpenAPI-Specification/blob/main/versions/3.0.2.md#schemaObject).
 AutoML tabular Models always have this field populated by Vertex AI.
 Note: The URI given on output may be different, including the URI scheme,
 than the one given on input. The output URI will point to a location where
 the user only has a read access.
      string feature_attributions_schema_uri = 3;
      Parameters:
      value - The bytes for featureAttributionsSchemaUri to set.
      Returns:
      This builder for chaining.

    • getLatentSpaceSource

      public String getLatentSpaceSource()
       Name of the source to generate embeddings for example based explanations.
      string latent_space_source = 5;
      Specified by:
      getLatentSpaceSource in interface ExplanationMetadataOrBuilder
      Returns:
      The latentSpaceSource.

    • getLatentSpaceSourceBytes

      public com.google.protobuf.ByteString getLatentSpaceSourceBytes()
       Name of the source to generate embeddings for example based explanations.
      string latent_space_source = 5;
      Specified by:
      getLatentSpaceSourceBytes in interface ExplanationMetadataOrBuilder
      Returns:
      The bytes for latentSpaceSource.

    • setLatentSpaceSource

      public ExplanationMetadata.Builder setLatentSpaceSource(String value)
       Name of the source to generate embeddings for example based explanations.
      string latent_space_source = 5;
      Parameters:
      value - The latentSpaceSource to set.
      Returns:
      This builder for chaining.

    • clearLatentSpaceSource

      public ExplanationMetadata.Builder clearLatentSpaceSource()
       Name of the source to generate embeddings for example based explanations.
      string latent_space_source = 5;
      Returns:
      This builder for chaining.

    • setLatentSpaceSourceBytes

      public ExplanationMetadata.Builder setLatentSpaceSourceBytes(com.google.protobuf.ByteString value)
       Name of the source to generate embeddings for example based explanations.
      string latent_space_source = 5;
      Parameters:
      value - The bytes for latentSpaceSource to set.
      Returns:
      This builder for chaining.