Package com.google.cloud.aiplatform.v1

Interface UpdateModelDeploymentMonitoringJobRequestOrBuilder

    • Method Detail

      • hasModelDeploymentMonitoringJob

        boolean hasModelDeploymentMonitoringJob()
         Required. The model monitoring configuration which replaces the resource on
 the server.
        .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob model_deployment_monitoring_job = 1 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        Whether the modelDeploymentMonitoringJob field is set.

      • getModelDeploymentMonitoringJob

        ModelDeploymentMonitoringJob getModelDeploymentMonitoringJob()
         Required. The model monitoring configuration which replaces the resource on
 the server.
        .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob model_deployment_monitoring_job = 1 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The modelDeploymentMonitoringJob.

      • getModelDeploymentMonitoringJobOrBuilder

        ModelDeploymentMonitoringJobOrBuilder getModelDeploymentMonitoringJobOrBuilder()
         Required. The model monitoring configuration which replaces the resource on
 the server.
        .google.cloud.aiplatform.v1.ModelDeploymentMonitoringJob model_deployment_monitoring_job = 1 [(.google.api.field_behavior) = REQUIRED];

      • hasUpdateMask

        boolean hasUpdateMask()
         Required. The update mask is used to specify the fields to be overwritten
 in the ModelDeploymentMonitoringJob resource by the update. The fields
 specified in the update_mask are relative to the resource, not the full
 request. A field will be overwritten if it is in the mask. If the user does
 not provide a mask then only the non-empty fields present in the request
 will be overwritten. Set the update_mask to `*` to override all fields. For
 the objective config, the user can either provide the update mask for
 model_deployment_monitoring_objective_configs or any combination of its
 nested fields, such as:
 model_deployment_monitoring_objective_configs.objective_config.training_dataset.

 Updatable fields:

   * `display_name`
   * `model_deployment_monitoring_schedule_config`
   * `model_monitoring_alert_config`
   * `logging_sampling_strategy`
   * `labels`
   * `log_ttl`
   * `enable_monitoring_pipeline_logs`
 .  and
   * `model_deployment_monitoring_objective_configs`
 .  or
   * `model_deployment_monitoring_objective_configs.objective_config.training_dataset`
   * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config`
   * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`
        .google.protobuf.FieldMask update_mask = 2 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        Whether the updateMask field is set.

      • getUpdateMask

        com.google.protobuf.FieldMask getUpdateMask()
         Required. The update mask is used to specify the fields to be overwritten
 in the ModelDeploymentMonitoringJob resource by the update. The fields
 specified in the update_mask are relative to the resource, not the full
 request. A field will be overwritten if it is in the mask. If the user does
 not provide a mask then only the non-empty fields present in the request
 will be overwritten. Set the update_mask to `*` to override all fields. For
 the objective config, the user can either provide the update mask for
 model_deployment_monitoring_objective_configs or any combination of its
 nested fields, such as:
 model_deployment_monitoring_objective_configs.objective_config.training_dataset.

 Updatable fields:

   * `display_name`
   * `model_deployment_monitoring_schedule_config`
   * `model_monitoring_alert_config`
   * `logging_sampling_strategy`
   * `labels`
   * `log_ttl`
   * `enable_monitoring_pipeline_logs`
 .  and
   * `model_deployment_monitoring_objective_configs`
 .  or
   * `model_deployment_monitoring_objective_configs.objective_config.training_dataset`
   * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config`
   * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`
        .google.protobuf.FieldMask update_mask = 2 [(.google.api.field_behavior) = REQUIRED];
        Returns:
        The updateMask.

      • getUpdateMaskOrBuilder

        com.google.protobuf.FieldMaskOrBuilder getUpdateMaskOrBuilder()
         Required. The update mask is used to specify the fields to be overwritten
 in the ModelDeploymentMonitoringJob resource by the update. The fields
 specified in the update_mask are relative to the resource, not the full
 request. A field will be overwritten if it is in the mask. If the user does
 not provide a mask then only the non-empty fields present in the request
 will be overwritten. Set the update_mask to `*` to override all fields. For
 the objective config, the user can either provide the update mask for
 model_deployment_monitoring_objective_configs or any combination of its
 nested fields, such as:
 model_deployment_monitoring_objective_configs.objective_config.training_dataset.

 Updatable fields:

   * `display_name`
   * `model_deployment_monitoring_schedule_config`
   * `model_monitoring_alert_config`
   * `logging_sampling_strategy`
   * `labels`
   * `log_ttl`
   * `enable_monitoring_pipeline_logs`
 .  and
   * `model_deployment_monitoring_objective_configs`
 .  or
   * `model_deployment_monitoring_objective_configs.objective_config.training_dataset`
   * `model_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_config`
   * `model_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config`
        .google.protobuf.FieldMask update_mask = 2 [(.google.api.field_behavior) = REQUIRED];