ExplanationMetadata.InputMetadata (proto-google-cloud-vertexai-v1 1.22.0 API)

java.lang.Object
- com.google.protobuf.AbstractMessageLite
- - com.google.protobuf.AbstractMessage
  - - com.google.protobuf.GeneratedMessageV3
    - - com.google.cloud.vertexai.api.ExplanationMetadata.InputMetadata

All Implemented Interfaces:: ExplanationMetadata.InputMetadataOrBuilder, com.google.protobuf.Message, com.google.protobuf.MessageLite, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Serializable

Enclosing class:: ExplanationMetadata

public static final class ExplanationMetadata.InputMetadata
extends com.google.protobuf.GeneratedMessageV3
implements ExplanationMetadata.InputMetadataOrBuilder

 Metadata of the input of a feature.

 Fields other than
 [InputMetadata.input_baselines][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.input_baselines]
 are applicable only for Models that are using Vertex AI-provided images for
 Tensorflow.

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

See Also:: Serialized Form

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`ExplanationMetadata.InputMetadata.Builder` Metadata of the input of a feature.
`static class`	`ExplanationMetadata.InputMetadata.Encoding` Defines how a feature is encoded.
`static class`	`ExplanationMetadata.InputMetadata.FeatureValueDomain` Domain details of the input feature value.
`static interface`	`ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder`
`static class`	`ExplanationMetadata.InputMetadata.Visualization` Visualization configurations for image explanation.
`static interface`	`ExplanationMetadata.InputMetadata.VisualizationOrBuilder`

Nested classes/interfaces inherited from class com.google.protobuf.GeneratedMessageV3
com.google.protobuf.GeneratedMessageV3.BuilderParent, com.google.protobuf.GeneratedMessageV3.ExtendableBuilder<MessageT extends com.google.protobuf.GeneratedMessageV3.ExtendableMessage<MessageT>,BuilderT extends com.google.protobuf.GeneratedMessageV3.ExtendableBuilder<MessageT,BuilderT>>, com.google.protobuf.GeneratedMessageV3.ExtendableMessage<MessageT extends com.google.protobuf.GeneratedMessageV3.ExtendableMessage<MessageT>>, com.google.protobuf.GeneratedMessageV3.ExtendableMessageOrBuilder<MessageT extends com.google.protobuf.GeneratedMessageV3.ExtendableMessage<MessageT>>, com.google.protobuf.GeneratedMessageV3.FieldAccessorTable, com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter

Nested classes/interfaces inherited from class com.google.protobuf.AbstractMessageLite
com.google.protobuf.AbstractMessageLite.InternalOneOfEnum

Field Summary

Fields
Modifier and Type	Field and Description
`static int`	`DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER`
`static int`	`ENCODED_BASELINES_FIELD_NUMBER`
`static int`	`ENCODED_TENSOR_NAME_FIELD_NUMBER`
`static int`	`ENCODING_FIELD_NUMBER`
`static int`	`FEATURE_VALUE_DOMAIN_FIELD_NUMBER`
`static int`	`GROUP_NAME_FIELD_NUMBER`
`static int`	`INDEX_FEATURE_MAPPING_FIELD_NUMBER`
`static int`	`INDICES_TENSOR_NAME_FIELD_NUMBER`
`static int`	`INPUT_BASELINES_FIELD_NUMBER`
`static int`	`INPUT_TENSOR_NAME_FIELD_NUMBER`
`static int`	`MODALITY_FIELD_NUMBER`
`static int`	`VISUALIZATION_FIELD_NUMBER`

Fields inherited from class com.google.protobuf.GeneratedMessageV3
alwaysUseFieldBuilders, unknownFields

Fields inherited from class com.google.protobuf.AbstractMessage
memoizedSize

Fields inherited from class com.google.protobuf.AbstractMessageLite
memoizedHashCode

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`equals(Object obj)`
`static ExplanationMetadata.InputMetadata`	`getDefaultInstance()`
`ExplanationMetadata.InputMetadata`	`getDefaultInstanceForType()`
`String`	`getDenseShapeTensorName()` Specifies the shape of the values of the input if the input is a sparse representation.
`com.google.protobuf.ByteString`	`getDenseShapeTensorNameBytes()` Specifies the shape of the values of the input if the input is a sparse representation.
`static com.google.protobuf.Descriptors.Descriptor`	`getDescriptor()`
`com.google.protobuf.Value`	`getEncodedBaselines(int index)` A list of baselines for the encoded tensor.
`int`	`getEncodedBaselinesCount()` A list of baselines for the encoded tensor.
`List<com.google.protobuf.Value>`	`getEncodedBaselinesList()` A list of baselines for the encoded tensor.
`com.google.protobuf.ValueOrBuilder`	`getEncodedBaselinesOrBuilder(int index)` A list of baselines for the encoded tensor.
`List<? extends com.google.protobuf.ValueOrBuilder>`	`getEncodedBaselinesOrBuilderList()` A list of baselines for the encoded tensor.
`String`	`getEncodedTensorName()` Encoded tensor is a transformation of the input tensor.
`com.google.protobuf.ByteString`	`getEncodedTensorNameBytes()` Encoded tensor is a transformation of the input tensor.
`ExplanationMetadata.InputMetadata.Encoding`	`getEncoding()` Defines how the feature is encoded into the input tensor.
`int`	`getEncodingValue()` Defines how the feature is encoded into the input tensor.
`ExplanationMetadata.InputMetadata.FeatureValueDomain`	`getFeatureValueDomain()` The domain details of the input feature value.
`ExplanationMetadata.InputMetadata.FeatureValueDomainOrBuilder`	`getFeatureValueDomainOrBuilder()` The domain details of the input feature value.
`String`	`getGroupName()` Name of the group that the input belongs to.
`com.google.protobuf.ByteString`	`getGroupNameBytes()` Name of the group that the input belongs to.
`String`	`getIndexFeatureMapping(int index)` A list of feature names for each index in the input tensor.
`com.google.protobuf.ByteString`	`getIndexFeatureMappingBytes(int index)` A list of feature names for each index in the input tensor.
`int`	`getIndexFeatureMappingCount()` A list of feature names for each index in the input tensor.
`com.google.protobuf.ProtocolStringList`	`getIndexFeatureMappingList()` A list of feature names for each index in the input tensor.
`String`	`getIndicesTensorName()` Specifies the index of the values of the input tensor.
`com.google.protobuf.ByteString`	`getIndicesTensorNameBytes()` Specifies the index of the values of the input tensor.
`com.google.protobuf.Value`	`getInputBaselines(int index)` Baseline inputs for this feature.
`int`	`getInputBaselinesCount()` Baseline inputs for this feature.
`List<com.google.protobuf.Value>`	`getInputBaselinesList()` Baseline inputs for this feature.
`com.google.protobuf.ValueOrBuilder`	`getInputBaselinesOrBuilder(int index)` Baseline inputs for this feature.
`List<? extends com.google.protobuf.ValueOrBuilder>`	`getInputBaselinesOrBuilderList()` Baseline inputs for this feature.
`String`	`getInputTensorName()` Name of the input tensor for this feature.
`com.google.protobuf.ByteString`	`getInputTensorNameBytes()` Name of the input tensor for this feature.
`String`	`getModality()` Modality of the feature.
`com.google.protobuf.ByteString`	`getModalityBytes()` Modality of the feature.
`com.google.protobuf.Parser<ExplanationMetadata.InputMetadata>`	`getParserForType()`
`int`	`getSerializedSize()`
`ExplanationMetadata.InputMetadata.Visualization`	`getVisualization()` Visualization configurations for image explanation.
`ExplanationMetadata.InputMetadata.VisualizationOrBuilder`	`getVisualizationOrBuilder()` Visualization configurations for image explanation.
`boolean`	`hasFeatureValueDomain()` The domain details of the input feature value.
`int`	`hashCode()`
`boolean`	`hasVisualization()` Visualization configurations for image explanation.
`protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable`	`internalGetFieldAccessorTable()`
`boolean`	`isInitialized()`
`static ExplanationMetadata.InputMetadata.Builder`	`newBuilder()`
`static ExplanationMetadata.InputMetadata.Builder`	`newBuilder(ExplanationMetadata.InputMetadata prototype)`
`ExplanationMetadata.InputMetadata.Builder`	`newBuilderForType()`
`protected ExplanationMetadata.InputMetadata.Builder`	`newBuilderForType(com.google.protobuf.GeneratedMessageV3.BuilderParent parent)`
`protected Object`	`newInstance(com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)`
`static ExplanationMetadata.InputMetadata`	`parseDelimitedFrom(InputStream input)`
`static ExplanationMetadata.InputMetadata`	`parseDelimitedFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(byte[] data)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(byte[] data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(ByteBuffer data)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(ByteBuffer data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(com.google.protobuf.ByteString data)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(com.google.protobuf.ByteString data, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(com.google.protobuf.CodedInputStream input)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(InputStream input)`
`static ExplanationMetadata.InputMetadata`	`parseFrom(InputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)`
`static com.google.protobuf.Parser<ExplanationMetadata.InputMetadata>`	`parser()`
`ExplanationMetadata.InputMetadata.Builder`	`toBuilder()`
`void`	`writeTo(com.google.protobuf.CodedOutputStream output)`

Methods inherited from class com.google.protobuf.GeneratedMessageV3
canUseUnsafe, computeStringSize, computeStringSizeNoTag, emptyBooleanList, emptyDoubleList, emptyFloatList, emptyIntList, emptyList, emptyLongList, getAllFields, getDescriptorForType, getField, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, isStringEmpty, makeExtensionsImmutable, makeMutableCopy, makeMutableCopy, mergeFromAndMakeImmutableInternal, mutableCopy, mutableCopy, mutableCopy, mutableCopy, mutableCopy, newBooleanList, newBuilderForType, newDoubleList, newFloatList, newIntList, newLongList, parseDelimitedWithIOException, parseDelimitedWithIOException, parseUnknownField, parseUnknownFieldProto3, parseWithIOException, parseWithIOException, parseWithIOException, parseWithIOException, serializeBooleanMapTo, serializeIntegerMapTo, serializeLongMapTo, serializeStringMapTo, writeReplace, writeString, writeStringNoTag

Methods inherited from class com.google.protobuf.AbstractMessage
findInitializationErrors, getInitializationErrorString, hashBoolean, hashEnum, hashEnumList, hashFields, hashLong, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite
addAll, addAll, checkByteStringIsUtf8, toByteArray, toByteString, writeDelimitedTo, writeTo

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLite
toByteArray, toByteString, writeDelimitedTo, writeTo

Field Detail
- INPUT_BASELINES_FIELD_NUMBER
```
public static final int INPUT_BASELINES_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- INPUT_TENSOR_NAME_FIELD_NUMBER
```
public static final int INPUT_TENSOR_NAME_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- ENCODING_FIELD_NUMBER
```
public static final int ENCODING_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- MODALITY_FIELD_NUMBER
```
public static final int MODALITY_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- FEATURE_VALUE_DOMAIN_FIELD_NUMBER
```
public static final int FEATURE_VALUE_DOMAIN_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- INDICES_TENSOR_NAME_FIELD_NUMBER
```
public static final int INDICES_TENSOR_NAME_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER
```
public static final int DENSE_SHAPE_TENSOR_NAME_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- INDEX_FEATURE_MAPPING_FIELD_NUMBER
```
public static final int INDEX_FEATURE_MAPPING_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- ENCODED_TENSOR_NAME_FIELD_NUMBER
```
public static final int ENCODED_TENSOR_NAME_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- ENCODED_BASELINES_FIELD_NUMBER
```
public static final int ENCODED_BASELINES_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- VISUALIZATION_FIELD_NUMBER
```
public static final int VISUALIZATION_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values
- GROUP_NAME_FIELD_NUMBER
```
public static final int GROUP_NAME_FIELD_NUMBER
```
  See Also:
  
  Constant Field Values

Method Detail

newInstance

protected Object newInstance(com.google.protobuf.GeneratedMessageV3.UnusedPrivateParameter unused)

Overrides:: newInstance in class com.google.protobuf.GeneratedMessageV3

getDescriptor

public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

internalGetFieldAccessorTable
```
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
```
Specified by:

internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3

getInputBaselinesList

public List<com.google.protobuf.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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

repeated .google.protobuf.Value input_baselines = 1;

Specified by:: getInputBaselinesList in interface ExplanationMetadata.InputMetadataOrBuilder

getInputBaselinesOrBuilderList

public List<? extends com.google.protobuf.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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

repeated .google.protobuf.Value input_baselines = 1;

Specified by:: getInputBaselinesOrBuilderList in interface ExplanationMetadata.InputMetadataOrBuilder

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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

repeated .google.protobuf.Value input_baselines = 1;

Specified by:: getInputBaselinesCount in interface ExplanationMetadata.InputMetadataOrBuilder

getInputBaselines

public com.google.protobuf.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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

repeated .google.protobuf.Value input_baselines = 1;

Specified by:: getInputBaselines in interface ExplanationMetadata.InputMetadataOrBuilder

getInputBaselinesOrBuilder

public com.google.protobuf.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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.ExplainRequest.instances][]. The
 schema of any single instance may be specified via Endpoint's
 DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].

repeated .google.protobuf.Value input_baselines = 1;

Specified by:: getInputBaselinesOrBuilder in interface ExplanationMetadata.InputMetadataOrBuilder

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;

Specified by:: getInputTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The inputTensorName.

getInputTensorNameBytes

public com.google.protobuf.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;

Specified by:: getInputTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The bytes for inputTensorName.

getEncodingValue
```
public int getEncodingValue()
```
```
 Defines how the feature is encoded into the input tensor. Defaults to
 IDENTITY.
 
```
.google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
Specified by:

getEncodingValue in interface ExplanationMetadata.InputMetadataOrBuilder

Returns:

The enum numeric value on the wire for encoding.

getEncoding
```
public ExplanationMetadata.InputMetadata.Encoding getEncoding()
```
```
 Defines how the feature is encoded into the input tensor. Defaults to
 IDENTITY.
 
```
.google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata.Encoding encoding = 3;
Specified by:

getEncoding in interface ExplanationMetadata.InputMetadataOrBuilder

Returns:

The encoding.

getModality
```
public String getModality()
```
```
 Modality of the feature. Valid values are: numeric, image. Defaults to
 numeric.
 
```
string modality = 4;
Specified by:

getModality in interface ExplanationMetadata.InputMetadataOrBuilder

Returns:

The modality.

getModalityBytes
```
public com.google.protobuf.ByteString getModalityBytes()
```
```
 Modality of the feature. Valid values are: numeric, image. Defaults to
 numeric.
 
```
string modality = 4;
Specified by:

getModalityBytes in interface ExplanationMetadata.InputMetadataOrBuilder

Returns:

The bytes for modality.

hasFeatureValueDomain
```
public boolean hasFeatureValueDomain()
```
```
 The domain details of the input feature value. Like min/max, original
 mean or standard deviation if normalized.
 
```
.google.cloud.vertexai.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
Specified by:

hasFeatureValueDomain in interface ExplanationMetadata.InputMetadataOrBuilder

Returns:

Whether the featureValueDomain field is set.

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.vertexai.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
Specified by:

getFeatureValueDomain in interface ExplanationMetadata.InputMetadataOrBuilder

Returns:

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.vertexai.v1.ExplanationMetadata.InputMetadata.FeatureValueDomain feature_value_domain = 5;
Specified by:

getFeatureValueDomainOrBuilder in interface ExplanationMetadata.InputMetadataOrBuilder

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;

Specified by:: getIndicesTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The indicesTensorName.

getIndicesTensorNameBytes

public com.google.protobuf.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;

Specified by:: getIndicesTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The bytes for indicesTensorName.

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;

Specified by:: getDenseShapeTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The denseShapeTensorName.

getDenseShapeTensorNameBytes

public com.google.protobuf.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;

Specified by:: getDenseShapeTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The bytes for denseShapeTensorName.

getIndexFeatureMappingList

public com.google.protobuf.ProtocolStringList getIndexFeatureMappingList()

 A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Specified by:: getIndexFeatureMappingList in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: A list containing the indexFeatureMapping.

getIndexFeatureMappingCount

public int getIndexFeatureMappingCount()

 A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Specified by:: getIndexFeatureMappingCount in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The count of indexFeatureMapping.

getIndexFeatureMapping

public String getIndexFeatureMapping(int index)

 A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Specified by:: getIndexFeatureMapping in interface ExplanationMetadata.InputMetadataOrBuilder
Parameters:: index - The index of the element to return.
Returns:: The indexFeatureMapping at the given index.

getIndexFeatureMappingBytes

public com.google.protobuf.ByteString getIndexFeatureMappingBytes(int index)

 A list of feature names for each index in the input tensor.
 Required when the input
 [InputMetadata.encoding][google.cloud.aiplatform.v1.ExplanationMetadata.InputMetadata.encoding]
 is BAG_OF_FEATURES, BAG_OF_FEATURES_SPARSE, INDICATOR.

repeated string index_feature_mapping = 8;

Specified by:: getIndexFeatureMappingBytes in interface ExplanationMetadata.InputMetadataOrBuilder
Parameters:: index - The index of the value to return.
Returns:: The bytes of the indexFeatureMapping at the given index.

getEncodedTensorName

public String getEncodedTensorName()

 Encoded tensor is a transformation of the input tensor. Must be provided
 if choosing
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution]
 or [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;

Specified by:: getEncodedTensorName in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The encodedTensorName.

getEncodedTensorNameBytes

public com.google.protobuf.ByteString getEncodedTensorNameBytes()

 Encoded tensor is a transformation of the input tensor. Must be provided
 if choosing
 [Integrated Gradients
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.integrated_gradients_attribution]
 or [XRAI
 attribution][google.cloud.aiplatform.v1.ExplanationParameters.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;

Specified by:: getEncodedTensorNameBytes in interface ExplanationMetadata.InputMetadataOrBuilder
Returns:: The bytes for encodedTensorName.