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public interface UpdateModelDeploymentMonitoringJobRequestOrBuilder extends MessageOrBuilder
Implements
MessageOrBuilderMethods
getModelDeploymentMonitoringJob()
public abstract ModelDeploymentMonitoringJob getModelDeploymentMonitoringJob()
Required. The model monitoring configuration which replaces the resource on the server.
.google.cloud.aiplatform.v1beta1.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.v1beta1.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_name
model_deployment_monitoring_schedule_config
model_monitoring_alert_config
logging_sampling_strategy
labels
log_ttl
enable_monitoring_pipeline_logs
. andmodel_deployment_monitoring_objective_configs
. ormodel_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 | |
---|---|
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_name
model_deployment_monitoring_schedule_config
model_monitoring_alert_config
logging_sampling_strategy
labels
log_ttl
enable_monitoring_pipeline_logs
. andmodel_deployment_monitoring_objective_configs
. ormodel_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 | |
---|---|
Type | Description |
FieldMaskOrBuilder |
hasModelDeploymentMonitoringJob()
public abstract boolean hasModelDeploymentMonitoringJob()
Required. The model monitoring configuration which replaces the resource on the server.
.google.cloud.aiplatform.v1beta1.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_name
model_deployment_monitoring_schedule_config
model_monitoring_alert_config
logging_sampling_strategy
labels
log_ttl
enable_monitoring_pipeline_logs
. andmodel_deployment_monitoring_objective_configs
. ormodel_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 | |
---|---|
Type | Description |
boolean |
Whether the updateMask field is set. |