Class ExplanationMetadata.OutputMetadata.Builder (3.31.0)

Version 3.31.0

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public static final class ExplanationMetadata.OutputMetadata.Builder extends GeneratedMessageV3.Builder<ExplanationMetadata.OutputMetadata.Builder> implements ExplanationMetadata.OutputMetadataOrBuilder

Metadata of the prediction output to be explained.

Protobuf type google.cloud.aiplatform.v1beta1.ExplanationMetadata.OutputMetadata

Inheritance

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

Implements

ExplanationMetadata.OutputMetadataOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream)

AbstractMessageLite.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

com.google.protobuf.GeneratedMessageV3.Builder.getUnknownFieldSetBuilder()

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownLengthDelimitedField(int,com.google.protobuf.ByteString)

com.google.protobuf.GeneratedMessageV3.Builder.mergeUnknownVarintField(int,int)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

com.google.protobuf.GeneratedMessageV3.Builder.parseUnknownField(com.google.protobuf.CodedInputStream,com.google.protobuf.ExtensionRegistryLite,int)

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

com.google.protobuf.GeneratedMessageV3.Builder.setUnknownFieldSetBuilder(com.google.protobuf.UnknownFieldSet.Builder)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Methods

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.OutputMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

build()

public ExplanationMetadata.OutputMetadata build()

Returns
Type	Description
ExplanationMetadata.OutputMetadata

buildPartial()

public ExplanationMetadata.OutputMetadata buildPartial()

Returns
Type	Description
ExplanationMetadata.OutputMetadata

clear()

public ExplanationMetadata.OutputMetadata.Builder clear()

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearDisplayNameMapping()

public ExplanationMetadata.OutputMetadata.Builder clearDisplayNameMapping()

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

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 for a specific output.

string display_name_mapping_key = 2;

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ExplanationMetadata.OutputMetadata.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

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

.google.protobuf.Value index_display_name_mapping = 1;

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public ExplanationMetadata.OutputMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

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
Type	Description
ExplanationMetadata.OutputMetadata.Builder	This builder for chaining.

clone()

public ExplanationMetadata.OutputMetadata.Builder clone()

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

getDefaultInstanceForType()

public ExplanationMetadata.OutputMetadata getDefaultInstanceForType()

Returns
Type	Description
ExplanationMetadata.OutputMetadata

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getDisplayNameMappingCase()

public ExplanationMetadata.OutputMetadata.DisplayNameMappingCase getDisplayNameMappingCase()

Returns
Type	Description
ExplanationMetadata.OutputMetadata.DisplayNameMappingCase

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 for a specific output.

string display_name_mapping_key = 2;

Returns
Type	Description
String	The displayNameMappingKey.

getDisplayNameMappingKeyBytes()

public 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 for a specific output.

string display_name_mapping_key = 2;

Returns
Type	Description
ByteString	The bytes for displayNameMappingKey.

getIndexDisplayNameMapping()

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

.google.protobuf.Value index_display_name_mapping = 1;

Returns
Type	Description
Value	The indexDisplayNameMapping.

getIndexDisplayNameMappingBuilder()

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

.google.protobuf.Value index_display_name_mapping = 1;

Returns
Type	Description
Builder

getIndexDisplayNameMappingOrBuilder()

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

.google.protobuf.Value index_display_name_mapping = 1;

Returns
Type	Description
ValueOrBuilder

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;

Returns
Type	Description
String	The outputTensorName.

getOutputTensorNameBytes()

public ByteString getOutputTensorNameBytes()

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

string output_tensor_name = 3;

Returns
Type	Description
ByteString	The bytes for outputTensorName.

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 for a specific output.

string display_name_mapping_key = 2;

Returns
Type	Description
boolean	Whether the displayNameMappingKey field is set.

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

.google.protobuf.Value index_display_name_mapping = 1;

Returns
Type	Description
boolean	Whether the indexDisplayNameMapping field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(ExplanationMetadata.OutputMetadata other)

public ExplanationMetadata.OutputMetadata.Builder mergeFrom(ExplanationMetadata.OutputMetadata other)

Parameter
Name	Description
other	ExplanationMetadata.OutputMetadata

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ExplanationMetadata.OutputMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public ExplanationMetadata.OutputMetadata.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

mergeIndexDisplayNameMapping(Value value)

public ExplanationMetadata.OutputMetadata.Builder mergeIndexDisplayNameMapping(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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

Parameter
Name	Description
value	Value

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.OutputMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

setDisplayNameMappingKey(String value)

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 for a specific output.

string display_name_mapping_key = 2;

Parameter
Name	Description
value	String The displayNameMappingKey to set.

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder	This builder for chaining.

setDisplayNameMappingKeyBytes(ByteString value)

public ExplanationMetadata.OutputMetadata.Builder setDisplayNameMappingKeyBytes(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 for a specific output.

string display_name_mapping_key = 2;

Parameter
Name	Description
value	ByteString The bytes for displayNameMappingKey to set.

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.OutputMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

setIndexDisplayNameMapping(Value value)

public ExplanationMetadata.OutputMetadata.Builder setIndexDisplayNameMapping(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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

Parameter
Name	Description
value	Value

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

setIndexDisplayNameMapping(Value.Builder builderForValue)

public ExplanationMetadata.OutputMetadata.Builder setIndexDisplayNameMapping(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 is populated by locating in the mapping with Attribution.output_index.

.google.protobuf.Value index_display_name_mapping = 1;

Parameter
Name	Description
builderForValue	Builder

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

setOutputTensorName(String value)

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;

Parameter
Name	Description
value	String The outputTensorName to set.

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder	This builder for chaining.

setOutputTensorNameBytes(ByteString value)

public ExplanationMetadata.OutputMetadata.Builder setOutputTensorNameBytes(ByteString value)

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

string output_tensor_name = 3;

Parameter
Name	Description
value	ByteString The bytes for outputTensorName to set.

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public ExplanationMetadata.OutputMetadata.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.OutputMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

Overrides

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