Interface ExplainRequestOrBuilder (0.6.0)

publicinterface ExplainRequestOrBuilderextendsMessageOrBuilder

Implements

MessageOrBuilder

Methods

getDeployedModelId()

publicabstractStringgetDeployedModelId()

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

string deployed_model_id = 3;

Returns
Type Description
String

The deployedModelId.

getDeployedModelIdBytes()

publicabstractByteStringgetDeployedModelIdBytes()

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

string deployed_model_id = 3;

Returns
Type Description
ByteString

The bytes for deployedModelId.

getEndpoint()

publicabstractStringgetEndpoint()

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type Description
String

The endpoint.

getEndpointBytes()

publicabstractByteStringgetEndpointBytes()

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

string endpoint = 1 [(.google.api.field_behavior) = REQUIRED, (.google.api.resource_reference) = { ... }

Returns
Type Description
ByteString

The bytes for endpoint.

getExplanationSpecOverride()

publicabstractExplanationSpecOverridegetExplanationSpecOverride()

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.

.google.cloud.vertexai.v1.ExplanationSpecOverride explanation_spec_override = 5;

Returns
Type Description
ExplanationSpecOverride

The explanationSpecOverride.

getExplanationSpecOverrideOrBuilder()

publicabstractExplanationSpecOverrideOrBuildergetExplanationSpecOverrideOrBuilder()

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.

.google.cloud.vertexai.v1.ExplanationSpecOverride explanation_spec_override = 5;

Returns
Type Description
ExplanationSpecOverrideOrBuilder

getInstances(int index)

publicabstractValuegetInstances(intindex)

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.

repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name Description
index int
Returns
Type Description
Value

getInstancesCount()

publicabstractintgetInstancesCount()

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.

repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
int

getInstancesList()

publicabstractList<Value>getInstancesList()

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.

repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
List<Value>

getInstancesOrBuilder(int index)

publicabstractValueOrBuildergetInstancesOrBuilder(intindex)

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.

repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];

Parameter
Name Description
index int
Returns
Type Description
ValueOrBuilder

getInstancesOrBuilderList()

publicabstractList<?extendsValueOrBuilder>getInstancesOrBuilderList()

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.

repeated .google.protobuf.Value instances = 2 [(.google.api.field_behavior) = REQUIRED];

Returns
Type Description
List<? extends com.google.protobuf.ValueOrBuilder>

getParameters()

publicabstractValuegetParameters()

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.

.google.protobuf.Value parameters = 4;

Returns
Type Description
Value

The parameters.

getParametersOrBuilder()

publicabstractValueOrBuildergetParametersOrBuilder()

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.

.google.protobuf.Value parameters = 4;

Returns
Type Description
ValueOrBuilder

hasExplanationSpecOverride()

publicabstractbooleanhasExplanationSpecOverride()

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.

.google.cloud.vertexai.v1.ExplanationSpecOverride explanation_spec_override = 5;

Returns
Type Description
boolean

Whether the explanationSpecOverride field is set.

hasParameters()

publicabstractbooleanhasParameters()

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.

.google.protobuf.Value parameters = 4;

Returns
Type Description
boolean

Whether the parameters field is set.

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Last updated 2025年11月19日 UTC.