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public interface UpdateModelDeploymentMonitoringJobRequestOrBuilder extends MessageOrBuilderImplements
MessageOrBuilderMethods
getModelDeploymentMonitoringJob()
public abstract 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 | |
|---|---|
| Type | Description |
ModelDeploymentMonitoringJob |
The modelDeploymentMonitoringJob. |
getModelDeploymentMonitoringJobOrBuilder()
public abstract 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];
| Returns | |
|---|---|
| Type | Description |
ModelDeploymentMonitoringJobOrBuilder |
|
getUpdateMask()
public abstract 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_namemodel_deployment_monitoring_schedule_configmodel_monitoring_alert_configlogging_sampling_strategylabelslog_ttlenable_monitoring_pipeline_logs. andmodel_deployment_monitoring_objective_configs. ormodel_deployment_monitoring_objective_configs.objective_config.training_datasetmodel_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_configmodel_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config
.google.protobuf.FieldMask update_mask = 2 [(.google.api.field_behavior) = REQUIRED];
| Returns | |
|---|---|
| Type | Description |
FieldMask |
The updateMask. |
getUpdateMaskOrBuilder()
public abstract 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_namemodel_deployment_monitoring_schedule_configmodel_monitoring_alert_configlogging_sampling_strategylabelslog_ttlenable_monitoring_pipeline_logs. andmodel_deployment_monitoring_objective_configs. ormodel_deployment_monitoring_objective_configs.objective_config.training_datasetmodel_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_configmodel_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config
.google.protobuf.FieldMask update_mask = 2 [(.google.api.field_behavior) = REQUIRED];
| Returns | |
|---|---|
| Type | Description |
FieldMaskOrBuilder |
|
hasModelDeploymentMonitoringJob()
public abstract 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 | |
|---|---|
| Type | Description |
boolean |
Whether the modelDeploymentMonitoringJob field is set. |
hasUpdateMask()
public abstract 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_namemodel_deployment_monitoring_schedule_configmodel_monitoring_alert_configlogging_sampling_strategylabelslog_ttlenable_monitoring_pipeline_logs. andmodel_deployment_monitoring_objective_configs. ormodel_deployment_monitoring_objective_configs.objective_config.training_datasetmodel_deployment_monitoring_objective_configs.objective_config.training_prediction_skew_detection_configmodel_deployment_monitoring_objective_configs.objective_config.prediction_drift_detection_config
.google.protobuf.FieldMask update_mask = 2 [(.google.api.field_behavior) = REQUIRED];
| Returns | |
|---|---|
| Type | Description |
boolean |
Whether the updateMask field is set. |