Class ExplanationMetadata.OutputMetadata.Builder (1.35.0)

publicstaticfinalclass ExplanationMetadata.OutputMetadata.BuilderextendsGeneratedMessageV3.Builder<ExplanationMetadata.OutputMetadata.Builder>implementsExplanationMetadata.OutputMetadataOrBuilder

Metadata of the prediction output to be explained.

Protobuf type google.cloud.vertexai.v1.ExplanationMetadata.OutputMetadata

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > ExplanationMetadata.OutputMetadata.Builder

Implements

ExplanationMetadata.OutputMetadataOrBuilder

Inherited Members

publicstaticfinalDescriptors.DescriptorgetDescriptor()

publicExplanationMetadata.OutputMetadata.BuilderaddRepeatedField(Descriptors.FieldDescriptorfield,Objectvalue)

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

publicExplanationMetadata.OutputMetadatabuild()

publicExplanationMetadata.OutputMetadatabuildPartial()

publicExplanationMetadata.OutputMetadata.Builderclear()

GeneratedMessageV3.Builder<BuilderType>.clear()

publicExplanationMetadata.OutputMetadata.BuilderclearDisplayNameMapping()

publicExplanationMetadata.OutputMetadata.BuilderclearDisplayNameMappingKey()

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 for a specific output.

string display_name_mapping_key = 2;

publicExplanationMetadata.OutputMetadata.BuilderclearField(Descriptors.FieldDescriptorfield)

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

publicExplanationMetadata.OutputMetadata.BuilderclearIndexDisplayNameMapping()

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicExplanationMetadata.OutputMetadata.BuilderclearOneof(Descriptors.OneofDescriptoroneof)

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

publicExplanationMetadata.OutputMetadata.BuilderclearOutputTensorName()

Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.

string output_tensor_name = 3;

publicExplanationMetadata.OutputMetadata.Builderclone()

GeneratedMessageV3.Builder<BuilderType>.clone()

publicExplanationMetadata.OutputMetadatagetDefaultInstanceForType()

publicDescriptors.DescriptorgetDescriptorForType()

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

publicExplanationMetadata.OutputMetadata.DisplayNameMappingCasegetDisplayNameMappingCase()

publicStringgetDisplayNameMappingKey()

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 for a specific output.

string display_name_mapping_key = 2;

publicByteStringgetDisplayNameMappingKeyBytes()

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 for a specific output.

string display_name_mapping_key = 2;

publicValuegetIndexDisplayNameMapping()

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicValue.BuildergetIndexDisplayNameMappingBuilder()

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicValueOrBuildergetIndexDisplayNameMappingOrBuilder()

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicStringgetOutputTensorName()

Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.

string output_tensor_name = 3;

publicByteStringgetOutputTensorNameBytes()

Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.

string output_tensor_name = 3;

publicbooleanhasDisplayNameMappingKey()

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 for a specific output.

string display_name_mapping_key = 2;

publicbooleanhasIndexDisplayNameMapping()

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

protectedGeneratedMessageV3.FieldAccessorTableinternalGetFieldAccessorTable()

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

publicfinalbooleanisInitialized()

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

publicExplanationMetadata.OutputMetadata.BuildermergeFrom(ExplanationMetadata.OutputMetadataother)

publicExplanationMetadata.OutputMetadata.BuildermergeFrom(CodedInputStreaminput,ExtensionRegistryLiteextensionRegistry)

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

publicExplanationMetadata.OutputMetadata.BuildermergeFrom(Messageother)

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

publicExplanationMetadata.OutputMetadata.BuildermergeIndexDisplayNameMapping(Valuevalue)

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicfinalExplanationMetadata.OutputMetadata.BuildermergeUnknownFields(UnknownFieldSetunknownFields)

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

publicExplanationMetadata.OutputMetadata.BuildersetDisplayNameMappingKey(Stringvalue)

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 for a specific output.

string display_name_mapping_key = 2;

publicExplanationMetadata.OutputMetadata.BuildersetDisplayNameMappingKeyBytes(ByteStringvalue)

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 for a specific output.

string display_name_mapping_key = 2;

publicExplanationMetadata.OutputMetadata.BuildersetField(Descriptors.FieldDescriptorfield,Objectvalue)

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

publicExplanationMetadata.OutputMetadata.BuildersetIndexDisplayNameMapping(Valuevalue)

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicExplanationMetadata.OutputMetadata.BuildersetIndexDisplayNameMapping(Value.BuilderbuilderForValue)

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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

publicExplanationMetadata.OutputMetadata.BuildersetOutputTensorName(Stringvalue)

Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.

string output_tensor_name = 3;

publicExplanationMetadata.OutputMetadata.BuildersetOutputTensorNameBytes(ByteStringvalue)

Name of the output tensor. Required and is only applicable to Vertex AI provided images for Tensorflow.

string output_tensor_name = 3;

publicExplanationMetadata.OutputMetadata.BuildersetRepeatedField(Descriptors.FieldDescriptorfield,intindex,Objectvalue)

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

publicfinalExplanationMetadata.OutputMetadata.BuildersetUnknownFields(UnknownFieldSetunknownFields)

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)