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feat: add Vizier service to aiplatform v1 #671

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feat: add Vizier service to aiplatform v1 #671

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b9ac3ab
feat: add Vizier service to aiplatform v1
gcf-owl-bot[bot] Sep 1, 2021
08691f6
🦉 Updates from OwlBot
gcf-owl-bot[bot] Sep 1, 2021
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30 changes: 28 additions & 2 deletions google/cloud/aiplatform_v1/services/job_service/async_client.py
View file
Open in desktop
Expand Up @@ -2218,8 +2218,34 @@ async def update_model_deployment_monitoring_job(
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (:class:`google.protobuf.field_mask_pb2.FieldMask`):
Required. The update mask applies to
the resource.
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``

This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
Expand Down
30 changes: 28 additions & 2 deletions google/cloud/aiplatform_v1/services/job_service/client.py
View file
Open in desktop
Expand Up @@ -2574,8 +2574,34 @@ def update_model_deployment_monitoring_job(
on the ``request`` instance; if ``request`` is provided, this
should not be set.
update_mask (google.protobuf.field_mask_pb2.FieldMask):
Required. The update mask applies to
the resource.
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``

This corresponds to the ``update_mask`` field
on the ``request`` instance; if ``request`` is provided, this
Expand Down
28 changes: 26 additions & 2 deletions google/cloud/aiplatform_v1/types/job_service.py
View file
Open in desktop
Expand Up @@ -791,8 +791,32 @@ class UpdateModelDeploymentMonitoringJobRequest(proto.Message):
Required. The model monitoring configuration
which replaces the resource on the server.
update_mask (google.protobuf.field_mask_pb2.FieldMask):
Required. The update mask applies to the
resource.
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``
"""

model_deployment_monitoring_job = proto.Field(
Expand Down