Class ExplanationMetadata.Builder (2.7.4)

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.v1.ExplanationMetadata

Static Methods

getDescriptor()

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

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

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

build()

public ExplanationMetadata build()
Returns
TypeDescription
ExplanationMetadata

buildPartial()

public ExplanationMetadata buildPartial()
Returns
TypeDescription
ExplanationMetadata

clear()

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

This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

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

clearInputs()

public ExplanationMetadata.Builder clearInputs()
Returns
TypeDescription
ExplanationMetadata.Builder

clearOneof(Descriptors.OneofDescriptor oneof)

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

clearOutputs()

public ExplanationMetadata.Builder clearOutputs()
Returns
TypeDescription
ExplanationMetadata.Builder

clone()

public ExplanationMetadata.Builder clone()
Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
keyString
Returns
TypeDescription
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.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
keyString
Returns
TypeDescription
boolean

getDefaultInstanceForType()

public ExplanationMetadata getDefaultInstanceForType()
Returns
TypeDescription
ExplanationMetadata

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()
Returns
TypeDescription
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
TypeDescription
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
TypeDescription
ByteString

The bytes for featureAttributionsSchemaUri.

getInputs()

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

Use #getInputsMap() instead.

Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
keyString
defaultValueExplanationMetadata.InputMetadata
Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
keyString
Returns
TypeDescription
ExplanationMetadata.InputMetadata

getMutableInputs()

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

Use alternate mutation accessors instead.

Returns
TypeDescription
Map<String,InputMetadata>

getMutableOutputs()

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

Use alternate mutation accessors instead.

Returns
TypeDescription
Map<String,OutputMetadata>

getOutputs()

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

Use #getOutputsMap() instead.

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

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

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

Parameters
NameDescription
keyString
defaultValueExplanationMetadata.OutputMetadata
Returns
TypeDescription
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.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
keyString
Returns
TypeDescription
ExplanationMetadata.OutputMetadata

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
Returns
TypeDescription
FieldAccessorTable
Overrides

internalGetMapField(int number)

protected MapField internalGetMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

internalGetMutableMapField(int number)

protected MapField internalGetMutableMapField(int number)
Parameter
NameDescription
numberint
Returns
TypeDescription
MapField
Overrides

isInitialized()

public final boolean isInitialized()
Returns
TypeDescription
boolean
Overrides

mergeFrom(ExplanationMetadata other)

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

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

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

mergeFrom(Message other)

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

mergeUnknownFields(UnknownFieldSet unknownFields)

public final ExplanationMetadata.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter
NameDescription
unknownFieldsUnknownFieldSet
Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
valuesMap<String,InputMetadata>
Returns
TypeDescription
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.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
valuesMap<String,OutputMetadata>
Returns
TypeDescription
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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
keyString
valueExplanationMetadata.InputMetadata
Returns
TypeDescription
ExplanationMetadata.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.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameters
NameDescription
keyString
valueExplanationMetadata.OutputMetadata
Returns
TypeDescription
ExplanationMetadata.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.v1.ExplanationMetadata.InputMetadata> inputs = 1 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
keyString
Returns
TypeDescription
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.v1.ExplanationMetadata.OutputMetadata> outputs = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
NameDescription
keyString
Returns
TypeDescription
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
NameDescription
valueString

The featureAttributionsSchemaUri to set.

Returns
TypeDescription
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
NameDescription
valueByteString

The bytes for featureAttributionsSchemaUri to set.

Returns
TypeDescription
ExplanationMetadata.Builder

This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

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

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

public ExplanationMetadata.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)
Parameters
NameDescription
fieldFieldDescriptor
indexint
valueObject
Returns
TypeDescription
ExplanationMetadata.Builder
Overrides

setUnknownFields(UnknownFieldSet unknownFields)

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