ExplanationMetadata_InputMetadata class final

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.

Inheritance
  • Object
  • ProtoMessage
  • ExplanationMetadata_InputMetadata

Constructors

ExplanationMetadata_InputMetadata({List<Value> inputBaselines = const [], String inputTensorName = '', ExplanationMetadata_InputMetadata_Encoding encoding = ExplanationMetadata_InputMetadata_Encoding.$default, String modality = '', ExplanationMetadata_InputMetadata_FeatureValueDomain? featureValueDomain, String indicesTensorName = '', String denseShapeTensorName = '', List<String> indexFeatureMapping = const [], String encodedTensorName = '', List<Value> encodedBaselines = const [], ExplanationMetadata_InputMetadata_Visualization? visualization, String groupName = ''})
ExplanationMetadata_InputMetadata.fromJson(Object? j)
factory

Properties

denseShapeTensorName → String
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.
final
encodedBaselines → List<Value>
A list of baselines for the encoded tensor.
final
encodedTensorName → String
Encoded tensor is a transformation of the input tensor. Must be provided if choosing google.cloud.aiplatform.v1beta1.ExplanationParameters.integrated_gradients_attribution or google.cloud.aiplatform.v1beta1.ExplanationParameters.xrai_attribution and the input tensor is not differentiable.
final
encoding → ExplanationMetadata_InputMetadata_Encoding
Defines how the feature is encoded into the input tensor. Defaults to IDENTITY.
final
featureValueDomain → ExplanationMetadata_InputMetadata_FeatureValueDomain?
The domain details of the input feature value. Like min/max, original mean or standard deviation if normalized.
final
groupName → String
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.
final
hashCode → int
The hash code for this object.
no setterinherited
indexFeatureMapping → List<String>
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.
final
indicesTensorName → String
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.
final
inputBaselines → List<Value>
Baseline inputs for this feature.
final
inputTensorName → String
Name of the input tensor for this feature. Required and is only applicable to Vertex AI-provided images for Tensorflow.
final
modality → String
Modality of the feature. Valid values are: numeric, image. Defaults to numeric.
final
qualifiedName → String
The fully qualified name of this message, i.e., google.protobuf.Duration or google.rpc.ErrorInfo.
finalinherited
runtimeType → Type
A representation of the runtime type of the object.
no setterinherited
visualization → ExplanationMetadata_InputMetadata_Visualization?
Visualization configurations for image explanation.
final

Methods

noSuchMethod(Invocation invocation) → dynamic
Invoked when a nonexistent method or property is accessed.
inherited
toJson() → Object
override
toString() → String
A string representation of this object.
override

Operators

operator ==(Object other) → bool
The equality operator.
inherited

Constants

fullyQualifiedName → const String