com.google.cloud.vertexai.api

Interface ExplainRequestOrBuilder

All Superinterfaces:

com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder

All Known Implementing Classes:

ExplainRequest, ExplainRequest.Builder

public interface ExplainRequestOrBuilder
extends com.google.protobuf.MessageOrBuilder

Method Summary

Modifier and Type	Method and Description
String	getDeployedModelId() If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
com.google.protobuf.ByteString	getDeployedModelIdBytes() If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
String	getEndpoint() Required.
com.google.protobuf.ByteString	getEndpointBytes() Required.
ExplanationSpecOverride	getExplanationSpecOverride() If specified, overrides the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] of the DeployedModel.
ExplanationSpecOverrideOrBuilder	getExplanationSpecOverrideOrBuilder() If specified, overrides the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] of the DeployedModel.
com.google.protobuf.Value	getInstances(int index) Required.
int	getInstancesCount() Required.
List<com.google.protobuf.Value>	getInstancesList() Required.
com.google.protobuf.ValueOrBuilder	getInstancesOrBuilder(int index) Required.
List<? extends com.google.protobuf.ValueOrBuilder>	getInstancesOrBuilderList() Required.
com.google.protobuf.Value	getParameters() The parameters that govern the prediction.
com.google.protobuf.ValueOrBuilder	getParametersOrBuilder() The parameters that govern the prediction.
boolean	hasExplanationSpecOverride() If specified, overrides the [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] of the DeployedModel.
boolean	hasParameters() The parameters that govern the prediction.

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder

isInitialized

Method Detail

getEndpoint

String getEndpoint()

 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:

The endpoint.

getEndpointBytes

com.google.protobuf.ByteString getEndpointBytes()

 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:

The bytes for endpoint.

getInstancesList

List<com.google.protobuf.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][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
 

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

getInstances

com.google.protobuf.Value getInstances(int index)

 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][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
 

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

getInstancesCount

int getInstancesCount()

 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][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
 

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

getInstancesOrBuilderList

List<? extends com.google.protobuf.ValueOrBuilder> 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][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
 

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

getInstancesOrBuilder

com.google.protobuf.ValueOrBuilder getInstancesOrBuilder(int index)

 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][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
 

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

hasParameters

boolean hasParameters()

 The parameters that govern the prediction. The schema of the parameters may
 be specified via Endpoint's DeployedModels' [Model's
 ][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
 

.google.protobuf.Value parameters = 4;

Returns:

Whether the parameters field is set.

getParameters

com.google.protobuf.Value getParameters()

 The parameters that govern the prediction. The schema of the parameters may
 be specified via Endpoint's DeployedModels' [Model's
 ][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
 

.google.protobuf.Value parameters = 4;

Returns:

The parameters.

getParametersOrBuilder

com.google.protobuf.ValueOrBuilder getParametersOrBuilder()

 The parameters that govern the prediction. The schema of the parameters may
 be specified via Endpoint's DeployedModels' [Model's
 ][google.cloud.aiplatform.v1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
 [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
 

.google.protobuf.Value parameters = 4;

hasExplanationSpecOverride

boolean hasExplanationSpecOverride()

 If specified, overrides the
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.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:

Whether the explanationSpecOverride field is set.

getExplanationSpecOverride

ExplanationSpecOverride getExplanationSpecOverride()

 If specified, overrides the
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.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:

The explanationSpecOverride.

getExplanationSpecOverrideOrBuilder

ExplanationSpecOverrideOrBuilder getExplanationSpecOverrideOrBuilder()

 If specified, overrides the
 [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.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;

getDeployedModelId

String getDeployedModelId()

 If specified, this ExplainRequest will be served by the chosen
 DeployedModel, overriding
 [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
 

string deployed_model_id = 3;

Returns:

The deployedModelId.

getDeployedModelIdBytes

com.google.protobuf.ByteString getDeployedModelIdBytes()

 If specified, this ExplainRequest will be served by the chosen
 DeployedModel, overriding
 [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
 

string deployed_model_id = 3;

Returns:

The bytes for deployedModelId.