Google Cloud Ai Platform V1 Client - Class ExplainRequest (1.8.0)

Version 1.8.0

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

Request message for PredictionService.Explain.

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

Namespace

Google \ Cloud \ AIPlatform \ V1

Methods

__construct

Constructor.

Parameters
Name	Description
data	array Optional. Data for populating the Message object.
↳ endpoint	string Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}
↳ instances	array<Google\Protobuf\Value> Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
↳ parameters	Google\Protobuf\Value The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.
↳ explanation_spec_override	Google\Cloud\AIPlatform\V1\ExplanationSpecOverride If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as: - Explaining top-5 predictions results as opposed to top-1; - Increasing path count or step count of the attribution methods to reduce approximate errors; - Using different baselines for explaining the prediction results.
↳ deployed_model_id	string If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.

getEndpoint

Required. The name of the Endpoint requested to serve the explanation.

Format: projects/{project}/locations/{location}/endpoints/{endpoint}

Returns
Type	Description
string

setEndpoint

Required. The name of the Endpoint requested to serve the explanation.

Format: projects/{project}/locations/{location}/endpoints/{endpoint}

Parameter
Name	Description
var	string

Returns
Type	Description
$this

getInstances

Required. The instances that are the input to the explanation call.

A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

Returns
Type	Description
Google\Protobuf\Internal\RepeatedField

setInstances

Required. The instances that are the input to the explanation call.

A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.

Parameter
Name	Description
var	array<Google\Protobuf\Value>

Returns
Type	Description
$this

getParameters

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.

Returns
Type	Description
Google\Protobuf\Value|null

hasParameters

clearParameters

setParameters

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.

Parameter
Name	Description
var	Google\Protobuf\Value

Returns
Type	Description
$this

getExplanationSpecOverride

If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as:

• Explaining top-5 predictions results as opposed to top-1;
• Increasing path count or step count of the attribution methods to reduce approximate errors;
• Using different baselines for explaining the prediction results.

Returns
Type	Description
Google\Cloud\AIPlatform\V1\ExplanationSpecOverride|null

hasExplanationSpecOverride

clearExplanationSpecOverride

setExplanationSpecOverride

If specified, overrides the explanation_spec of the DeployedModel. Can be used for explaining prediction results with different configurations, such as:

• Explaining top-5 predictions results as opposed to top-1;
• Increasing path count or step count of the attribution methods to reduce approximate errors;
• Using different baselines for explaining the prediction results.

Parameter
Name	Description
var	Google\Cloud\AIPlatform\V1\ExplanationSpecOverride

Returns
Type	Description
$this

getDeployedModelId

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.

Returns
Type	Description
string

setDeployedModelId

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.

Parameter
Name	Description
var	string

Returns
Type	Description
$this

static::build

Parameters
Name	Description
endpoint	string Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint} Please see Google\Cloud\AIPlatform\V1\PredictionServiceClient::endpointName() for help formatting this field.
instances	array<Google\Protobuf\Value> Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' Model's PredictSchemata's instance_schema_uri.
parameters	Google\Protobuf\Value The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.
deployedModelId	string If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.

Returns
Type	Description
Google\Cloud\AIPlatform\V1\ExplainRequest