Class ExplanationMetadata.InputMetadata (3.52.0)

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public static final class ExplanationMetadata.InputMetadata extends GeneratedMessageV3 implements ExplanationMetadata.InputMetadataOrBuilder

Metadata of the input of a feature.

Fields other than InputMetadata.input_baselines are applicable only for Models that are using Vertex AI-provided images for Tensorflow.

Protobuf type google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata

Inheritance

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

Implements

ExplanationMetadata.InputMetadataOrBuilder

Inherited Members

AbstractMessage.equals(Object)

AbstractMessage.findInitializationErrors()

AbstractMessage.getInitializationErrorString()

AbstractMessage.hashBoolean(boolean)

AbstractMessage.hashCode()

AbstractMessage.hashEnum(Internal.EnumLite)

AbstractMessage.hashEnumList(List<? extends Internal.EnumLite>)

AbstractMessage.hashFields(int,Map<Descriptors.FieldDescriptor,Object>)

AbstractMessage.hashLong(long)

AbstractMessage.toString()

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

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

AbstractMessageLite.checkByteStringIsUtf8(ByteString)

AbstractMessageLite.toByteArray()

AbstractMessageLite.toByteString()

AbstractMessageLite.writeDelimitedTo(OutputStream)

AbstractMessageLite.writeTo(OutputStream)

com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT)

com.google.protobuf.GeneratedMessageV3.<ListT>makeMutableCopy(ListT,int)

GeneratedMessageV3.<M>parseDelimitedWithIOException(Parser<M>,InputStream)

GeneratedMessageV3.<M>parseDelimitedWithIOException(Parser<M>,InputStream,ExtensionRegistryLite)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,CodedInputStream)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,CodedInputStream,ExtensionRegistryLite)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,InputStream)

GeneratedMessageV3.<M>parseWithIOException(Parser<M>,InputStream,ExtensionRegistryLite)

com.google.protobuf.GeneratedMessageV3.<T>emptyList(java.lang.Class<T>)

GeneratedMessageV3.<V>serializeBooleanMapTo(CodedOutputStream,MapField<Boolean,V>,MapEntry<Boolean,V>,int)

GeneratedMessageV3.<V>serializeIntegerMapTo(CodedOutputStream,MapField<Integer,V>,MapEntry<Integer,V>,int)

GeneratedMessageV3.<V>serializeLongMapTo(CodedOutputStream,MapField<Long,V>,MapEntry<Long,V>,int)

GeneratedMessageV3.<V>serializeStringMapTo(CodedOutputStream,MapField<String,V>,MapEntry<String,V>,int)

GeneratedMessageV3.canUseUnsafe()

GeneratedMessageV3.computeStringSize(int,Object)

GeneratedMessageV3.computeStringSizeNoTag(Object)

GeneratedMessageV3.emptyBooleanList()

GeneratedMessageV3.emptyDoubleList()

GeneratedMessageV3.emptyFloatList()

GeneratedMessageV3.emptyIntList()

GeneratedMessageV3.emptyLongList()

GeneratedMessageV3.getAllFields()

GeneratedMessageV3.getDescriptorForType()

GeneratedMessageV3.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.getParserForType()

GeneratedMessageV3.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.getSerializedSize()

GeneratedMessageV3.getUnknownFields()

GeneratedMessageV3.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.internalGetFieldAccessorTable()

GeneratedMessageV3.internalGetMapField(int)

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

GeneratedMessageV3.isInitialized()

GeneratedMessageV3.isStringEmpty(Object)

GeneratedMessageV3.makeExtensionsImmutable()

GeneratedMessageV3.mergeFromAndMakeImmutableInternal(CodedInputStream,ExtensionRegistryLite)

GeneratedMessageV3.mutableCopy(Internal.BooleanList)

GeneratedMessageV3.mutableCopy(Internal.DoubleList)

GeneratedMessageV3.mutableCopy(Internal.FloatList)

GeneratedMessageV3.mutableCopy(Internal.IntList)

GeneratedMessageV3.mutableCopy(Internal.LongList)

GeneratedMessageV3.newBooleanList()

GeneratedMessageV3.newBuilderForType(AbstractMessage.BuilderParent)

GeneratedMessageV3.newBuilderForType(GeneratedMessageV3.BuilderParent)

GeneratedMessageV3.newDoubleList()

GeneratedMessageV3.newFloatList()

GeneratedMessageV3.newInstance(GeneratedMessageV3.UnusedPrivateParameter)

GeneratedMessageV3.newIntList()

GeneratedMessageV3.newLongList()

GeneratedMessageV3.parseUnknownField(CodedInputStream,UnknownFieldSet.Builder,ExtensionRegistryLite,int)

GeneratedMessageV3.parseUnknownFieldProto3(CodedInputStream,UnknownFieldSet.Builder,ExtensionRegistryLite,int)

GeneratedMessageV3.writeReplace()

GeneratedMessageV3.writeString(CodedOutputStream,int,Object)

GeneratedMessageV3.writeStringNoTag(CodedOutputStream,Object)

GeneratedMessageV3.writeTo(CodedOutputStream)

Object.clone()

Object.finalize()

Object.getClass()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Static Fields

DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER

public static final int DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER

Field Value
Type	Description
int

ENCODED_BASELINES_FIELD_NUMBER

public static final int ENCODED_BASELINES_FIELD_NUMBER

Field Value
Type	Description
int

ENCODED_TENSOR_NAME_FIELD_NUMBER

public static final int ENCODED_TENSOR_NAME_FIELD_NUMBER

Field Value
Type	Description
int

ENCODING_FIELD_NUMBER

public static final int ENCODING_FIELD_NUMBER

Field Value
Type	Description
int

FEATURE_VALUE_DOMAIN_FIELD_NUMBER

public static final int FEATURE_VALUE_DOMAIN_FIELD_NUMBER

Field Value
Type	Description
int

GROUP_NAME_FIELD_NUMBER

public static final int GROUP_NAME_FIELD_NUMBER

Field Value
Type	Description
int

INDEX_FEATURE_MAPPING_FIELD_NUMBER

public static final int INDEX_FEATURE_MAPPING_FIELD_NUMBER

Field Value
Type	Description
int

INDICES_TENSOR_NAME_FIELD_NUMBER

public static final int INDICES_TENSOR_NAME_FIELD_NUMBER

Field Value
Type	Description
int

INPUT_BASELINES_FIELD_NUMBER

public static final int INPUT_BASELINES_FIELD_NUMBER

Field Value
Type	Description
int

INPUT_TENSOR_NAME_FIELD_NUMBER

public static final int INPUT_TENSOR_NAME_FIELD_NUMBER

Field Value
Type	Description
int

MODALITY_FIELD_NUMBER

public static final int MODALITY_FIELD_NUMBER

Field Value
Type	Description
int

VISUALIZATION_FIELD_NUMBER

public static final int VISUALIZATION_FIELD_NUMBER

Field Value
Type	Description
int

Static Methods

getDefaultInstance()

public static ExplanationMetadata.InputMetadata getDefaultInstance()

Returns
Type	Description
ExplanationMetadata.InputMetadata

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns
Type	Description
Descriptor

newBuilder()

public static ExplanationMetadata.InputMetadata.Builder newBuilder()

Returns
Type	Description
ExplanationMetadata.InputMetadata.Builder

newBuilder(ExplanationMetadata.InputMetadata prototype)

public static ExplanationMetadata.InputMetadata.Builder newBuilder(ExplanationMetadata.InputMetadata prototype)

Parameter
Name	Description
prototype	ExplanationMetadata.InputMetadata

Returns
Type	Description
ExplanationMetadata.InputMetadata.Builder

parseDelimitedFrom(InputStream input)

public static ExplanationMetadata.InputMetadata parseDelimitedFrom(InputStream input)

Parameter
Name	Description
input	InputStream

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
IOException

parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ExplanationMetadata.InputMetadata parseDelimitedFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	InputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
IOException

parseFrom(byte[] data)

public static ExplanationMetadata.InputMetadata parseFrom(byte[] data)

Parameter
Name	Description
data	byte[]

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

public static ExplanationMetadata.InputMetadata parseFrom(byte[] data, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
data	byte[]
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(ByteString data)

public static ExplanationMetadata.InputMetadata parseFrom(ByteString data)

Parameter
Name	Description
data	ByteString

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

public static ExplanationMetadata.InputMetadata parseFrom(ByteString data, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
data	ByteString
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(CodedInputStream input)

public static ExplanationMetadata.InputMetadata parseFrom(CodedInputStream input)

Parameter
Name	Description
input	CodedInputStream

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
IOException

parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public static ExplanationMetadata.InputMetadata parseFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
IOException

parseFrom(InputStream input)

public static ExplanationMetadata.InputMetadata parseFrom(InputStream input)

Parameter
Name	Description
input	InputStream

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
IOException

parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

public static ExplanationMetadata.InputMetadata parseFrom(InputStream input, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
input	InputStream
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
IOException

parseFrom(ByteBuffer data)

public static ExplanationMetadata.InputMetadata parseFrom(ByteBuffer data)

Parameter
Name	Description
data	ByteBuffer

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
InvalidProtocolBufferException

parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

public static ExplanationMetadata.InputMetadata parseFrom(ByteBuffer data, ExtensionRegistryLite extensionRegistry)

Parameters
Name	Description
data	ByteBuffer
extensionRegistry	ExtensionRegistryLite

Returns
Type	Description
ExplanationMetadata.InputMetadata

Exceptions
Type	Description
InvalidProtocolBufferException

parser()

public static Parser<ExplanationMetadata.InputMetadata> parser()

Returns
Type	Description
Parser<InputMetadata>

Methods

equals(Object obj)

public boolean equals(Object obj)

Parameter
Name	Description
obj	Object

Returns
Type	Description
boolean

Overrides

AbstractMessage.equals(Object other)

getDefaultInstanceForType()

public ExplanationMetadata.InputMetadata getDefaultInstanceForType()

Returns
Type	Description
ExplanationMetadata.InputMetadata

getDenseShapeTensorName()

public String getDenseShapeTensorName()

Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.

string dense_shape_tensor_name = 7;

Returns
Type	Description
String	The denseShapeTensorName.

getDenseShapeTensorNameBytes()

public ByteString getDenseShapeTensorNameBytes()

Specifies the shape of the values of the input if the input is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.

string dense_shape_tensor_name = 7;

Returns
Type	Description
ByteString	The bytes for denseShapeTensorName.

getEncodedBaselines(int index)

public Value getEncodedBaselines(int index)

A list of baselines for the encoded tensor.

The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.

repeated .google.protobuf.Value encoded_baselines = 10;

Parameter
Name	Description
index	int

Returns
Type	Description
Value

getEncodedBaselinesCount()

public int getEncodedBaselinesCount()

A list of baselines for the encoded tensor.

The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.

repeated .google.protobuf.Value encoded_baselines = 10;

Returns
Type	Description
int

getEncodedBaselinesList()

public List<Value> getEncodedBaselinesList()

A list of baselines for the encoded tensor.

The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.

repeated .google.protobuf.Value encoded_baselines = 10;

Returns
Type	Description
List<Value>

getEncodedBaselinesOrBuilder(int index)

public ValueOrBuilder getEncodedBaselinesOrBuilder(int index)

A list of baselines for the encoded tensor.

The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.

repeated .google.protobuf.Value encoded_baselines = 10;

Parameter
Name	Description
index	int

Returns
Type	Description
ValueOrBuilder

getEncodedBaselinesOrBuilderList()

public List<? extends ValueOrBuilder> getEncodedBaselinesOrBuilderList()

A list of baselines for the encoded tensor.

The shape of each baseline should match the shape of the encoded tensor. If a scalar is provided, Vertex AI broadcasts to the same shape as the encoded tensor.

repeated .google.protobuf.Value encoded_baselines = 10;

Returns
Type	Description
List<? extends com.google.protobuf.ValueOrBuilder>

getEncodedTensorName()

public String getEncodedTensorName()

Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable.

An encoded tensor is generated if the input tensor is encoded by a lookup table.

string encoded_tensor_name = 9;

Returns
Type	Description
String	The encodedTensorName.

getEncodedTensorNameBytes()

public ByteString getEncodedTensorNameBytes()

Encoded tensor is a transformation of the input tensor. Must be provided if choosing Integrated Gradients attribution or XRAI attribution and the input tensor is not differentiable.

An encoded tensor is generated if the input tensor is encoded by a lookup table.

string encoded_tensor_name = 9;

Returns
Type	Description
ByteString	The bytes for encodedTensorName.

getEncoding()

public ExplanationMetadata.InputMetadata.Encoding getEncoding()

Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;

Returns
Type	Description
ExplanationMetadata.InputMetadata.Encoding	The encoding.

getEncodingValue()

public int getEncodingValue()

Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;

Returns
Type	Description
int	The enum numeric value on the wire for encoding.

getFeatureValueDomain()

public ExplanationMetadata.InputMetadata.FeatureValueDomain getFeatureValueDomain()

The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;

Returns
Type	Description
ExplanationMetadata.InputMetadata.FeatureValueDomain	The featureValueDomain.

getFeatureValueDomainOrBuilder()

public ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder getFeatureValueDomainOrBuilder()

The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;

Returns
Type	Description
ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder

getGroupName()

public String getGroupName()

Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name.

string group_name = 12;

Returns
Type	Description
String	The groupName.

getGroupNameBytes()

public ByteString getGroupNameBytes()

Name of the group that the input belongs to. Features with the same group name will be treated as one feature when computing attributions. Features grouped together can have different shapes in value. If provided, there will be one single attribution generated in Attribution.feature_attributions, keyed by the group name.

string group_name = 12;

Returns
Type	Description
ByteString	The bytes for groupName.

getIndexFeatureMapping(int index)

public String getIndexFeatureMapping(int index)

A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Parameter
Name	Description
index	int The index of the element to return.

Returns
Type	Description
String	The indexFeatureMapping at the given index.

getIndexFeatureMappingBytes(int index)

public ByteString getIndexFeatureMappingBytes(int index)

A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Parameter
Name	Description
index	int The index of the value to return.

Returns
Type	Description
ByteString	The bytes of the indexFeatureMapping at the given index.

getIndexFeatureMappingCount()

public int getIndexFeatureMappingCount()

A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Returns
Type	Description
int	The count of indexFeatureMapping.

getIndexFeatureMappingList()

public ProtocolStringList getIndexFeatureMappingList()

A list of feature names for each index in the input tensor. Required when the input InputMetadata.encoding is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Returns
Type	Description
ProtocolStringList	A list containing the indexFeatureMapping.

getIndicesTensorName()

public String getIndicesTensorName()

Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.

string indices_tensor_name = 6;

Returns
Type	Description
String	The indicesTensorName.

getIndicesTensorNameBytes()

public ByteString getIndicesTensorNameBytes()

Specifies the index of the values of the input tensor. Required when the input tensor is a sparse representation. Refer to Tensorflow documentation for more details: https://www.tensorflow.org/api_docs/python/tf/sparse/SparseTensor.

string indices_tensor_name = 6;

Returns
Type	Description
ByteString	The bytes for indicesTensorName.

getInputBaselines(int index)

public Value getInputBaselines(int index)

Baseline inputs for this feature.

If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.

For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.

For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

repeated .google.protobuf.Value input_baselines = 1;

Parameter
Name	Description
index	int

Returns
Type	Description
Value

getInputBaselinesCount()

public int getInputBaselinesCount()

Baseline inputs for this feature.

If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.

For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.

For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

repeated .google.protobuf.Value input_baselines = 1;

Returns
Type	Description
int

getInputBaselinesList()

public List<Value> getInputBaselinesList()

Baseline inputs for this feature.

If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.

For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.

For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

repeated .google.protobuf.Value input_baselines = 1;

Returns
Type	Description
List<Value>

getInputBaselinesOrBuilder(int index)

public ValueOrBuilder getInputBaselinesOrBuilder(int index)

Baseline inputs for this feature.

If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.

For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.

For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

repeated .google.protobuf.Value input_baselines = 1;

Parameter
Name	Description
index	int

Returns
Type	Description
ValueOrBuilder

getInputBaselinesOrBuilderList()

public List<? extends ValueOrBuilder> getInputBaselinesOrBuilderList()

Baseline inputs for this feature.

If no baseline is specified, Vertex AI chooses the baseline for this feature. If multiple baselines are specified, Vertex AI returns the average attributions across them in Attribution.feature_attributions.

For Vertex AI-provided Tensorflow images (both 1.x and 2.x), the shape of each baseline must match the shape of the input tensor. If a scalar is provided, we broadcast to the same shape as the input tensor.

For custom images, the element of the baselines must be in the same format as the feature's input in the instance[]. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

repeated .google.protobuf.Value input_baselines = 1;

Returns
Type	Description
List<? extends com.google.protobuf.ValueOrBuilder>

getInputTensorName()

public String getInputTensorName()

Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.

string input_tensor_name = 2;

Returns
Type	Description
String	The inputTensorName.

getInputTensorNameBytes()

public ByteString getInputTensorNameBytes()

Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.

string input_tensor_name = 2;

Returns
Type	Description
ByteString	The bytes for inputTensorName.

getModality()

public String getModality()

Modality of the feature. Valid values are: numeric, image. Defaults to numeric.

string modality = 4;

Returns
Type	Description
String	The modality.

getModalityBytes()

public ByteString getModalityBytes()

Modality of the feature. Valid values are: numeric, image. Defaults to numeric.

string modality = 4;

Returns
Type	Description
ByteString	The bytes for modality.

getParserForType()

public Parser<ExplanationMetadata.InputMetadata> getParserForType()

Returns
Type	Description
Parser<InputMetadata>

Overrides

GeneratedMessageV3.getParserForType()

getSerializedSize()

public int getSerializedSize()

Returns
Type	Description
int

Overrides

GeneratedMessageV3.getSerializedSize()

getVisualization()

public ExplanationMetadata.InputMetadata.Visualization getVisualization()

Visualization configurations for image explanation.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;

Returns
Type	Description
ExplanationMetadata.InputMetadata.Visualization	The visualization.

getVisualizationOrBuilder()

public ExplanationMetadata.InputMetadata.VisualizationOrBuilder getVisualizationOrBuilder()

Visualization configurations for image explanation.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;

Returns
Type	Description
ExplanationMetadata.InputMetadata.VisualizationOrBuilder

hasFeatureValueDomain()

public boolean hasFeatureValueDomain()

The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;

Returns
Type	Description
boolean	Whether the featureValueDomain field is set.

hasVisualization()

public boolean hasVisualization()

Visualization configurations for image explanation.

.google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.Visualization visualization = 11;

Returns
Type	Description
boolean	Whether the visualization field is set.

hashCode()

public int hashCode()

Returns
Type	Description
int

Overrides

AbstractMessage.hashCode()

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns
Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns
Type	Description
boolean

Overrides

GeneratedMessageV3.isInitialized()

newBuilderForType()

public ExplanationMetadata.InputMetadata.Builder newBuilderForType()

Returns
Type	Description
ExplanationMetadata.InputMetadata.Builder

newBuilderForType(GeneratedMessageV3.BuilderParent parent)

protected ExplanationMetadata.InputMetadata.Builder newBuilderForType(GeneratedMessageV3.BuilderParent parent)

Parameter
Name	Description
parent	BuilderParent

Returns
Type	Description
ExplanationMetadata.InputMetadata.Builder

Overrides

GeneratedMessageV3.newBuilderForType(GeneratedMessageV3.BuilderParent parent)

newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

protected Object newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

Parameter
Name	Description
unused	UnusedPrivateParameter

Returns
Type	Description
Object

Overrides

GeneratedMessageV3.newInstance(GeneratedMessageV3.UnusedPrivateParameter unused)

toBuilder()

public ExplanationMetadata.InputMetadata.Builder toBuilder()

Returns
Type	Description
ExplanationMetadata.InputMetadata.Builder

writeTo(CodedOutputStream output)

public void writeTo(CodedOutputStream output)

Parameter
Name	Description
output	CodedOutputStream

Overrides

GeneratedMessageV3.writeTo(CodedOutputStream output)

Exceptions
Type	Description
IOException