UpdateModelDeploymentMonitoringJobRequest(
mapping=None, *, ignore_unknown_fields=False, **kwargs
)Request message for JobService.UpdateModelDeploymentMonitoringJob.
Attributes |
|
|---|---|
| Name | Description |
model_deployment_monitoring_job |
google.cloud.aiplatform_v1.types.ModelDeploymentMonitoringJob
Required. The model monitoring configuration which replaces the resource on the server. |
update_mask |
google.protobuf.field_mask_pb2.FieldMask
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
|
Methods
UpdateModelDeploymentMonitoringJobRequest
UpdateModelDeploymentMonitoringJobRequest(
mapping=None, *, ignore_unknown_fields=False, **kwargs
)Request message for JobService.UpdateModelDeploymentMonitoringJob.