Class ExplanationMetadata.OutputMetadata.Builder (2.5.3)

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

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.OutputMetadata.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

build()

public ExplanationMetadata.OutputMetadata build()
Returns
TypeDescription
ExplanationMetadata.OutputMetadata

buildPartial()

public ExplanationMetadata.OutputMetadata buildPartial()
Returns
TypeDescription
ExplanationMetadata.OutputMetadata

clear()

public ExplanationMetadata.OutputMetadata.Builder clear()
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

clearDisplayNameMapping()

public ExplanationMetadata.OutputMetadata.Builder clearDisplayNameMapping()
Returns
TypeDescription
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
TypeDescription
ExplanationMetadata.OutputMetadata.Builder

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ExplanationMetadata.OutputMetadata.Builder clearField(Descriptors.FieldDescriptor field)
Parameter
NameDescription
fieldFieldDescriptor
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

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
TypeDescription
ExplanationMetadata.OutputMetadata.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

public ExplanationMetadata.OutputMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)
Parameter
NameDescription
oneofOneofDescriptor
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

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
TypeDescription
ExplanationMetadata.OutputMetadata.Builder

This builder for chaining.

clone()

public ExplanationMetadata.OutputMetadata.Builder clone()
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

getDefaultInstanceForType()

public ExplanationMetadata.OutputMetadata getDefaultInstanceForType()
Returns
TypeDescription
ExplanationMetadata.OutputMetadata

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()
Returns
TypeDescription
Descriptor

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
Descriptor
Overrides

getDisplayNameMappingCase()

public ExplanationMetadata.OutputMetadata.DisplayNameMappingCase getDisplayNameMappingCase()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
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
TypeDescription
boolean

Whether the indexDisplayNameMapping field is set.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ExplanationMetadata.OutputMetadata other)

public ExplanationMetadata.OutputMetadata.Builder mergeFrom(ExplanationMetadata.OutputMetadata other)
Parameter
NameDescription
otherExplanationMetadata.OutputMetadata
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public ExplanationMetadata.OutputMetadata.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
Parameters
NameDescription
inputCodedInputStream
extensionRegistryExtensionRegistryLite
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides Exceptions
TypeDescription
IOException

mergeFrom(Message other)

public ExplanationMetadata.OutputMetadata.Builder mergeFrom(Message other)
Parameter
NameDescription
otherMessage
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

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
NameDescription
valueValue
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.OutputMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

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
NameDescription
valueString

The displayNameMappingKey to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for displayNameMappingKey to set.

Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public ExplanationMetadata.OutputMetadata.Builder setField(Descriptors.FieldDescriptor field, Object value)
Parameters
NameDescription
fieldFieldDescriptor
valueObject
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

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
NameDescription
valueValue
Returns
TypeDescription
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
NameDescription
builderForValueBuilder
Returns
TypeDescription
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
NameDescription
valueString

The outputTensorName to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for outputTensorName to set.

Returns
TypeDescription
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
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.OutputMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
ExplanationMetadata.OutputMetadata.Builder
Overrides