Class ExplanationMetadata.Builder (1.15.0)

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

Metadata describing the Model's input and output for explanation.

Protobuf type google.cloud.vertexai.v1.ExplanationMetadata

Inheritance

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

Implements

ExplanationMetadataOrBuilder

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)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(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.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

build()

public ExplanationMetadata build()

Returns
Type	Description
ExplanationMetadata

buildPartial()

public ExplanationMetadata buildPartial()

Returns
Type	Description
ExplanationMetadata

clear()

public ExplanationMetadata.Builder clear()

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

clearFeatureAttributionsSchemaUri()

public ExplanationMetadata.Builder clearFeatureAttributionsSchemaUri()

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 Schema Object. 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
Type	Description
ExplanationMetadata.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public ExplanationMetadata.Builder clearField(Descriptors.FieldDescriptor field)

Parameter
Name	Description
field	FieldDescriptor

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

clearInputs()

public ExplanationMetadata.Builder clearInputs()

Returns
Type	Description
ExplanationMetadata.Builder

clearLatentSpaceSource()

public ExplanationMetadata.Builder clearLatentSpaceSource()

Name of the source to generate embeddings for example based explanations.

string latent_space_source = 5;

Returns
Type	Description
ExplanationMetadata.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public ExplanationMetadata.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter
Name	Description
oneof	OneofDescriptor

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

clearOutputs()

public ExplanationMetadata.Builder clearOutputs()

Returns
Type	Description
ExplanationMetadata.Builder

clone()

public ExplanationMetadata.Builder clone()

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

containsInputs(String key)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
boolean

containsOutputs(String key)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
boolean

getDefaultInstanceForType()

public ExplanationMetadata getDefaultInstanceForType()

Returns
Type	Description
ExplanationMetadata

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns
Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

getFeatureAttributionsSchemaUri()

public String getFeatureAttributionsSchemaUri()

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 Schema Object. 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
Type	Description
String	The featureAttributionsSchemaUri.

getFeatureAttributionsSchemaUriBytes()

public ByteString getFeatureAttributionsSchemaUriBytes()

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 Schema Object. 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
Type	Description
ByteString	The bytes for featureAttributionsSchemaUri.

getInputs() (deprecated)

public Map<String,ExplanationMetadata.InputMetadata> getInputs()

Use #getInputsMap() instead.

Returns
Type	Description
Map<String,InputMetadata>

getInputsCount()

public int getInputsCount()

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
int

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
Map<String,InputMetadata>

getInputsOrDefault(String key, ExplanationMetadata.InputMetadata defaultValue)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
key	String
defaultValue	ExplanationMetadata.InputMetadata

Returns
Type	Description
ExplanationMetadata.InputMetadata

getInputsOrThrow(String key)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
ExplanationMetadata.InputMetadata

getLatentSpaceSource()

public String getLatentSpaceSource()

Name of the source to generate embeddings for example based explanations.

string latent_space_source = 5;

Returns
Type	Description
String	The latentSpaceSource.

getLatentSpaceSourceBytes()

public ByteString getLatentSpaceSourceBytes()

Name of the source to generate embeddings for example based explanations.

string latent_space_source = 5;

Returns
Type	Description
ByteString	The bytes for latentSpaceSource.

getMutableInputs() (deprecated)

public Map<String,ExplanationMetadata.InputMetadata> getMutableInputs()

Use alternate mutation accessors instead.

Returns
Type	Description
Map<String,InputMetadata>

getMutableOutputs() (deprecated)

public Map<String,ExplanationMetadata.OutputMetadata> getMutableOutputs()

Use alternate mutation accessors instead.

Returns
Type	Description
Map<String,OutputMetadata>

getOutputs() (deprecated)

public Map<String,ExplanationMetadata.OutputMetadata> getOutputs()

Use #getOutputsMap() instead.

Returns
Type	Description
Map<String,OutputMetadata>

getOutputsCount()

public int getOutputsCount()

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
int

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type	Description
Map<String,OutputMetadata>

getOutputsOrDefault(String key, ExplanationMetadata.OutputMetadata defaultValue)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
key	String
defaultValue	ExplanationMetadata.OutputMetadata

Returns
Type	Description
ExplanationMetadata.OutputMetadata

getOutputsOrThrow(String key)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
ExplanationMetadata.OutputMetadata

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

internalGetMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMapFieldReflection(int number)

Parameter
Name	Description
number	int

Returns
Type	Description
com.google.protobuf.MapFieldReflectionAccessor

Overrides

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMapFieldReflection(int)

internalGetMutableMapFieldReflection(int number)

protected MapFieldReflectionAccessor internalGetMutableMapFieldReflection(int number)

Parameter
Name	Description
number	int

Returns
Type	Description
com.google.protobuf.MapFieldReflectionAccessor

Overrides

com.google.protobuf.GeneratedMessageV3.Builder.internalGetMutableMapFieldReflection(int)

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(ExplanationMetadata other)

public ExplanationMetadata.Builder mergeFrom(ExplanationMetadata other)

Parameter
Name	Description
other	ExplanationMetadata

Returns
Type	Description
ExplanationMetadata.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

Exceptions
Type	Description
IOException

mergeFrom(Message other)

public ExplanationMetadata.Builder mergeFrom(Message other)

Parameter
Name	Description
other	Message

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

putAllInputs(Map<String,ExplanationMetadata.InputMetadata> values)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
values	Map<String,InputMetadata>

Returns
Type	Description
ExplanationMetadata.Builder

putAllOutputs(Map<String,ExplanationMetadata.OutputMetadata> values)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
values	Map<String,OutputMetadata>

Returns
Type	Description
ExplanationMetadata.Builder

putInputs(String key, ExplanationMetadata.InputMetadata value)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
key	String
value	ExplanationMetadata.InputMetadata

Returns
Type	Description
ExplanationMetadata.Builder

putInputsBuilderIfAbsent(String key)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
ExplanationMetadata.InputMetadata.Builder

putOutputs(String key, ExplanationMetadata.OutputMetadata value)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameters
Name	Description
key	String
value	ExplanationMetadata.OutputMetadata

Returns
Type	Description
ExplanationMetadata.Builder

putOutputsBuilderIfAbsent(String key)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
ExplanationMetadata.OutputMetadata.Builder

removeInputs(String key)

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. 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 are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in instance.

map<string, .google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
ExplanationMetadata.Builder

removeOutputs(String key)

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.vertexai.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name	Description
key	String

Returns
Type	Description
ExplanationMetadata.Builder

setFeatureAttributionsSchemaUri(String value)

public ExplanationMetadata.Builder setFeatureAttributionsSchemaUri(String value)

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 Schema Object. 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;

Parameter
Name	Description
value	String The featureAttributionsSchemaUri to set.

Returns
Type	Description
ExplanationMetadata.Builder	This builder for chaining.

setFeatureAttributionsSchemaUriBytes(ByteString value)

public ExplanationMetadata.Builder setFeatureAttributionsSchemaUriBytes(ByteString value)

Points to a YAML file stored on Google Cloud Storage describing the format of the feature attributions. The schema is defined as an OpenAPI 3.0.2 Schema Object. 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;

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

Returns
Type	Description
ExplanationMetadata.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

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

Parameters
Name	Description
field	FieldDescriptor
value	Object

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

setLatentSpaceSource(String value)

public ExplanationMetadata.Builder setLatentSpaceSource(String value)

Name of the source to generate embeddings for example based explanations.

string latent_space_source = 5;

Parameter
Name	Description
value	String The latentSpaceSource to set.

Returns
Type	Description
ExplanationMetadata.Builder	This builder for chaining.

setLatentSpaceSourceBytes(ByteString value)

public ExplanationMetadata.Builder setLatentSpaceSourceBytes(ByteString value)

Name of the source to generate embeddings for example based explanations.

string latent_space_source = 5;

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

Returns
Type	Description
ExplanationMetadata.Builder	This builder for chaining.

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

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

Parameters
Name	Description
field	FieldDescriptor
index	int
value	Object

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter
Name	Description
unknownFields	UnknownFieldSet

Returns
Type	Description
ExplanationMetadata.Builder

Overrides

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