Package com.google.cloud.aiplatform.v1

Class 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.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>
implements ExplanationMetadataOrBuilder
     Metadata describing the Model's input and output for explanation.
    Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata

    • Method Detail

      • getDescriptor

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

      • internalGetMapField

        protected com.google.protobuf.MapField internalGetMapField​(int number)
        Overrides:
        internalGetMapField in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • internalGetMutableMapField

        protected com.google.protobuf.MapField internalGetMutableMapField​(int number)
        Overrides:
        internalGetMutableMapField in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • internalGetFieldAccessorTable

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

      • clone

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

      • setField

        public ExplanationMetadata.Builder setField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                            Object value)
        Specified by:
        setField in interface com.google.protobuf.Message.Builder
        Overrides:
        setField in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • clearField

        public ExplanationMetadata.Builder clearField​(com.google.protobuf.Descriptors.FieldDescriptor field)
        Specified by:
        clearField in interface com.google.protobuf.Message.Builder
        Overrides:
        clearField in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • clearOneof

        public ExplanationMetadata.Builder clearOneof​(com.google.protobuf.Descriptors.OneofDescriptor oneof)
        Specified by:
        clearOneof in interface com.google.protobuf.Message.Builder
        Overrides:
        clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • setRepeatedField

        public ExplanationMetadata.Builder setRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                    int index,
                                                    Object value)
        Specified by:
        setRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • addRepeatedField

        public ExplanationMetadata.Builder addRepeatedField​(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                    Object value)
        Specified by:
        addRepeatedField in interface com.google.protobuf.Message.Builder
        Overrides:
        addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.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>

      • isInitialized

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

      • 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

      • 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];

      • 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];

      • 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

      • 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

      • 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];

      • 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];

      • 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.

      • setUnknownFields

        public final ExplanationMetadata.Builder setUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        setUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>

      • mergeUnknownFields

        public final ExplanationMetadata.Builder mergeUnknownFields​(com.google.protobuf.UnknownFieldSet unknownFields)
        Specified by:
        mergeUnknownFields in interface com.google.protobuf.Message.Builder
        Overrides:
        mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<ExplanationMetadata.Builder>