Class ExplanationMetadata.Builder (3.48.0)

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.aiplatform.v1beta1.ExplanationMetadata

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

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

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

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

clearOutputs()

public ExplanationMetadata.Builder clearOutputs()
Returns
Type Description
ExplanationMetadata.Builder

clone()

public ExplanationMetadata.Builder clone()
Returns
Type Description
ExplanationMetadata.Builder
Overrides

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.aiplatform.v1beta1.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.aiplatform.v1beta1.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

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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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

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

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
Exceptions
Type Description
IOException

mergeFrom(Message other)

public ExplanationMetadata.Builder mergeFrom(Message other)
Parameter
Name Description
other Message
Returns
Type Description
ExplanationMetadata.Builder
Overrides

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
ExplanationMetadata.Builder
Overrides

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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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.aiplatform.v1beta1.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

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

setUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter
Name Description
unknownFields UnknownFieldSet
Returns
Type Description
ExplanationMetadata.Builder
Overrides