Google Cloud Ai Platform V1 Client - Class ExplanationMetadata (1.0.0)

Version 1.0.0

• 1.13.1 (latest)
• 1.13.0
• 1.12.0
• 1.11.0
• 1.10.0
• 1.9.0
• 1.8.0
• 1.7.0
• 1.6.0
• 1.5.0
• 1.4.0
• 1.3.0
• 1.2.0
• 1.1.0
• 1.0.0
• 0.39.0
• 0.38.0
• 0.37.1
• 0.32.0
• 0.31.0
• 0.30.0
• 0.29.0
• 0.28.0
• 0.27.0
• 0.26.2
• 0.25.0
• 0.24.0
• 0.23.0
• 0.22.0
• 0.21.0
• 0.20.0
• 0.19.0
• 0.18.0
• 0.17.0
• 0.16.0
• 0.15.0
• 0.13.0
• 0.12.0
• 0.11.1
• 0.10.0

Reference documentation and code samples for the Google Cloud Ai Platform V1 Client class ExplanationMetadata.

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

Generated from protobuf message google.cloud.aiplatform.v1.ExplanationMetadata

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name	Description
data	array Optional. Data for populating the Message object.
↳ inputs	array|Google\Protobuf\Internal\MapField 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.
↳ outputs	array|Google\Protobuf\Internal\MapField 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.
↳ feature_attributions_schema_uri	string 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.
↳ latent_space_source	string Name of the source to generate embeddings for example based explanations.

getInputs

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.

Returns
Type	Description
Google\Protobuf\Internal\MapField

setInputs

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.

Parameter
Name	Description
var	array|Google\Protobuf\Internal\MapField

Returns
Type	Description
$this

getOutputs

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.

Returns
Type	Description
Google\Protobuf\Internal\MapField

setOutputs

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.

Parameter
Name	Description
var	array|Google\Protobuf\Internal\MapField

Returns
Type	Description
$this

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.

Returns
Type	Description
string

setFeatureAttributionsSchemaUri

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.

Parameter
Name	Description
var	string

Returns
Type	Description
$this

getLatentSpaceSource

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

Returns
Type	Description
string

setLatentSpaceSource

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

Parameter
Name	Description
var	string

Returns
Type	Description
$this