Package com.google.cloud.aiplatform.v1beta1

Interface ExplainRequestOrBuilder

All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder
All Known Implementing Classes:
ExplainRequest, ExplainRequest.Builder
@Generated public interface ExplainRequestOrBuilder extends com.google.protobuf.MessageOrBuilder

  • Method Details

    • 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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [instance_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [parameters_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [parameters_schema_uri][google.cloud.aiplatform.v1beta1.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.v1beta1.DeployedModel.model]
 [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata]
 [parameters_schema_uri][google.cloud.aiplatform.v1beta1.PredictSchemata.parameters_schema_uri].
      .google.protobuf.Value parameters = 4;

    • hasExplanationSpecOverride

      boolean hasExplanationSpecOverride()
       If specified, overrides the
 [explanation_spec][google.cloud.aiplatform.v1beta1.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.aiplatform.v1beta1.ExplanationSpecOverride explanation_spec_override = 5;
      Returns:
      Whether the explanationSpecOverride field is set.

    • getExplanationSpecOverride

      ExplanationSpecOverride getExplanationSpecOverride()
       If specified, overrides the
 [explanation_spec][google.cloud.aiplatform.v1beta1.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.aiplatform.v1beta1.ExplanationSpecOverride explanation_spec_override = 5;
      Returns:
      The explanationSpecOverride.

    • getExplanationSpecOverrideOrBuilder

      ExplanationSpecOverrideOrBuilder getExplanationSpecOverrideOrBuilder()
       If specified, overrides the
 [explanation_spec][google.cloud.aiplatform.v1beta1.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.aiplatform.v1beta1.ExplanationSpecOverride explanation_spec_override = 5;

    • getConcurrentExplanationSpecOverrideCount

      int getConcurrentExplanationSpecOverrideCount()
       Optional. This field is the same as the one above, but supports multiple
 explanations to occur in parallel. The key can be any string. Each override
 will be run against the model, then its explanations will be grouped
 together.

 Note - these explanations are run **In Addition** to the default
 Explanation in the deployed model.
      map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];

    • containsConcurrentExplanationSpecOverride

      boolean containsConcurrentExplanationSpecOverride(String key)
       Optional. This field is the same as the one above, but supports multiple
 explanations to occur in parallel. The key can be any string. Each override
 will be run against the model, then its explanations will be grouped
 together.

 Note - these explanations are run **In Addition** to the default
 Explanation in the deployed model.
      map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];

    • getConcurrentExplanationSpecOverride

      @Deprecated Map<String,ExplanationSpecOverride> getConcurrentExplanationSpecOverride()
      Deprecated.
      Use getConcurrentExplanationSpecOverrideMap() instead.

    • getConcurrentExplanationSpecOverrideMap

      Map<String,ExplanationSpecOverride> getConcurrentExplanationSpecOverrideMap()
       Optional. This field is the same as the one above, but supports multiple
 explanations to occur in parallel. The key can be any string. Each override
 will be run against the model, then its explanations will be grouped
 together.

 Note - these explanations are run **In Addition** to the default
 Explanation in the deployed model.
      map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];

    • getConcurrentExplanationSpecOverrideOrDefault

      ExplanationSpecOverride getConcurrentExplanationSpecOverrideOrDefault(String key, ExplanationSpecOverride defaultValue)
       Optional. This field is the same as the one above, but supports multiple
 explanations to occur in parallel. The key can be any string. Each override
 will be run against the model, then its explanations will be grouped
 together.

 Note - these explanations are run **In Addition** to the default
 Explanation in the deployed model.
      map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];

    • getConcurrentExplanationSpecOverrideOrThrow

      ExplanationSpecOverride getConcurrentExplanationSpecOverrideOrThrow(String key)
       Optional. This field is the same as the one above, but supports multiple
 explanations to occur in parallel. The key can be any string. Each override
 will be run against the model, then its explanations will be grouped
 together.

 Note - these explanations are run **In Addition** to the default
 Explanation in the deployed model.
      map<string, .google.cloud.aiplatform.v1beta1.ExplanationSpecOverride> concurrent_explanation_spec_override = 6 [(.google.api.field_behavior) = OPTIONAL];

    • getDeployedModelId

      String getDeployedModelId()
       If specified, this ExplainRequest will be served by the chosen
 DeployedModel, overriding
 [Endpoint.traffic_split][google.cloud.aiplatform.v1beta1.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.v1beta1.Endpoint.traffic_split].
      string deployed_model_id = 3;
      Returns:
      The bytes for deployedModelId.