Cloud AI Platform v1 API - Class ExplanationMetadata (2.6.0)

public sealed class ExplanationMetadata : IMessage<ExplanationMetadata>, IEquatable<ExplanationMetadata>, IDeepCloneable<ExplanationMetadata>, IBufferMessage, IMessage

Reference documentation and code samples for the Cloud AI Platform v1 API class ExplanationMetadata.

Metadata describing the Model's input and output for explanation.

Inheritance

Object > ExplanationMetadata

Implements

IMessage<ExplanationMetadata>, IEquatable<ExplanationMetadata>, IDeepCloneable<ExplanationMetadata>, IBufferMessage, IMessage

Inherited Members

Object.GetHashCode()

Object.GetType()

Object.MemberwiseClone()

Object.ToString()

Namespace

Google.Cloud.AIPlatform.V1

Assembly

Google.Cloud.AIPlatform.V1.dll

Constructors

ExplanationMetadata()

public ExplanationMetadata()

ExplanationMetadata(ExplanationMetadata)

public ExplanationMetadata(ExplanationMetadata other)

Parameter
Name	Description
`other`	`ExplanationMetadata`

Properties

FeatureAttributionsSchemaUri

public string FeatureAttributionsSchemaUri { get; set; }

Points to a YAML file stored on Google Cloud Storage describing the format of the [feature attributions][google.cloud.aiplatform.v1.Attribution.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.

Property Value
Type	Description
`String`

Inputs

public MapField<string, ExplanationMetadata.Types.InputMetadata> Inputs { get; }

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][google.cloud.aiplatform.v1.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][google.cloud.aiplatform.v1.Attribution.feature_attributions] are keyed by this key (if not grouped with another feature).

For custom images, the key must match with the key in [instance][google.cloud.aiplatform.v1.ExplainRequest.instances].

Property Value
Type	Description
`MapField<String, ExplanationMetadata.Types.InputMetadata>`

LatentSpaceSource

public string LatentSpaceSource { get; set; }

Name of the source to generate embeddings for example based explanations.

Property Value
Type	Description
`String`

Outputs

public MapField<string, ExplanationMetadata.Types.OutputMetadata> Outputs { get; }

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.

Property Value
Type	Description
`MapField<String, ExplanationMetadata.Types.OutputMetadata>`