def PatchAlpha(self, tensorboard_time_series_ref, args):
"""Update a Tensorboard time series."""
tensorboard_time_series = (
self.messages.GoogleCloudAiplatformV1alpha1TensorboardTimeSeries())
update_mask = []
if args.display_name is not None:
tensorboard_time_series.displayName = args.display_name
update_mask.append('display_name')
if args.description is not None:
tensorboard_time_series.description = args.description
update_mask.append('description')
if args.plugin_name is not None:
tensorboard_time_series.pluginName = args.plugin_name
update_mask.append('plugin_name')
if args.plugin_data is not None:
tensorboard_time_series.pluginData = bytes(args.plugin_data,
encoding='utf8')
update_mask.append('plugin_data')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
request = self.messages.AiplatformProjectsLocationsTensorboardsExperimentsRunsTimeSeriesPatchRequest(
name=tensorboard_time_series_ref.RelativeName(),
googleCloudAiplatformV1alpha1TensorboardTimeSeries=
tensorboard_time_series,
updateMask=','.join(update_mask))
return self._service.Patch(request)
def PatchAlpha(self, tensorboard_run_ref, args):
"""Update a Tensorboard run."""
tensorboard_run = self.messages.GoogleCloudAiplatformV1alpha1TensorboardRun(
)
update_mask = []
def GetLabels():
return self.Get(tensorboard_run_ref).labels
labels_update = labels_util.ProcessUpdateArgsLazy(
args, self.messages.GoogleCloudAiplatformV1alpha1TensorboardRun.
LabelsValue, GetLabels)
if labels_update.needs_update:
tensorboard_run.labels = labels_update.labels
update_mask.append('labels')
if args.display_name is not None:
tensorboard_run.displayName = args.display_name
update_mask.append('display_name')
if args.description is not None:
tensorboard_run.description = args.description
update_mask.append('description')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
request = self.messages.AiplatformProjectsLocationsTensorboardsExperimentsRunsPatchRequest(
name=tensorboard_run_ref.RelativeName(),
googleCloudAiplatformV1alpha1TensorboardRun=tensorboard_run,
updateMask=','.join(update_mask))
return self._service.Patch(request)
def PatchBeta(self, index_endpoint_ref, args):
"""Update an index endpoint."""
index_endpoint = self.messages.GoogleCloudAiplatformV1beta1IndexEndpoint(
)
update_mask = []
if args.display_name is not None:
index_endpoint.displayName = args.display_name
update_mask.append('display_name')
if args.description is not None:
index_endpoint.description = args.description
update_mask.append('description')
def GetLabels():
return self.Get(index_endpoint_ref).labels
labels_update = labels_util.ProcessUpdateArgsLazy(
args, self.messages.GoogleCloudAiplatformV1beta1IndexEndpoint.
LabelsValue, GetLabels)
if labels_update.needs_update:
index_endpoint.labels = labels_update.labels
update_mask.append('labels')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
request = self.messages.AiplatformProjectsLocationsIndexEndpointsPatchRequest(
name=index_endpoint_ref.RelativeName(),
googleCloudAiplatformV1beta1IndexEndpoint=index_endpoint,
updateMask=','.join(update_mask))
return self._service.Patch(request)
def PatchBeta(self, endpoint_ref, args):
"""Update a endpoint."""
endpoint = self.messages.GoogleCloudAiplatformV1beta1Endpoint()
update_mask = []
def GetLabels():
return self.Get(endpoint_ref).labels
labels_update = labels_util.ProcessUpdateArgsLazy(
args,
self.messages.GoogleCloudAiplatformV1beta1Endpoint.LabelsValue,
GetLabels)
if labels_update.needs_update:
endpoint.labels = labels_update.labels
update_mask.append('labels')
if args.display_name is not None:
endpoint.displayName = args.display_name
update_mask.append('display_name')
if args.traffic_split is not None:
additional_properties = []
for key, value in sorted(args.traffic_split.items()):
additional_properties.append(
endpoint.TrafficSplitValue().AdditionalProperty(
key=key, value=value))
endpoint.trafficSplit = endpoint.TrafficSplitValue(
additionalProperties=additional_properties)
update_mask.append('traffic_split')
if args.clear_traffic_split:
endpoint.trafficSplit = None
update_mask.append('traffic_split')
if args.description is not None:
endpoint.description = args.description
update_mask.append('description')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
req = self.messages.AiplatformProjectsLocationsEndpointsPatchRequest(
name=endpoint_ref.RelativeName(),
googleCloudAiplatformV1beta1Endpoint=endpoint,
updateMask=','.join(update_mask))
return self.client.projects_locations_endpoints.Patch(req)
def Patch(self, tensorboard_ref, args):
"""Update a Tensorboard."""
if self._version == constants.ALPHA_VERSION:
tensorboard = self.messages.GoogleCloudAiplatformV1alpha1Tensorboard()
labels_value = self.messages.GoogleCloudAiplatformV1alpha1Tensorboard.LabelsValue
else:
tensorboard = self.messages.GoogleCloudAiplatformV1beta1Tensorboard()
labels_value = self.messages.GoogleCloudAiplatformV1beta1Tensorboard.LabelsValue
update_mask = []
def GetLabels():
return self.Get(tensorboard_ref).labels
labels_update = labels_util.ProcessUpdateArgsLazy(args, labels_value,
GetLabels)
if labels_update.needs_update:
tensorboard.labels = labels_update.labels
update_mask.append('labels')
if args.display_name is not None:
tensorboard.displayName = args.display_name
update_mask.append('display_name')
if args.description is not None:
tensorboard.description = args.description
update_mask.append('description')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
if self._version == constants.ALPHA_VERSION:
req = self.messages.AiplatformProjectsLocationsTensorboardsPatchRequest(
name=tensorboard_ref.RelativeName(),
googleCloudAiplatformV1alpha1Tensorboard=tensorboard,
updateMask=','.join(update_mask))
else:
req = self.messages.AiplatformProjectsLocationsTensorboardsPatchRequest(
name=tensorboard_ref.RelativeName(),
googleCloudAiplatformV1beta1Tensorboard=tensorboard,
updateMask=','.join(update_mask))
return self._service.Patch(req)
def Patch(args):
"""Update an instance config."""
client = apis.GetClientInstance('spanner', 'v1')
msgs = apis.GetMessagesModule('spanner', 'v1')
ref = resources.REGISTRY.Parse(
args.config,
params={'projectsId': properties.VALUES.core.project.GetOrFail},
collection='spanner.projects.instanceConfigs')
instance_config = msgs.InstanceConfig(name=ref.RelativeName())
update_mask = []
if args.display_name is not None:
instance_config.displayName = args.display_name
update_mask.append('display_name')
if args.etag is not None:
instance_config.etag = args.etag
def GetLabels():
req = msgs.SpannerProjectsInstanceConfigsGetRequest(
name=ref.RelativeName())
return client.projects_instanceConfigs.Get(req).labels
labels_update = labels_util.ProcessUpdateArgsLazy(
args, msgs.InstanceConfig.LabelsValue, GetLabels)
if labels_update.needs_update:
instance_config.labels = labels_update.labels
update_mask.append('labels')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
req = msgs.SpannerProjectsInstanceConfigsPatchRequest(
name=ref.RelativeName(),
updateInstanceConfigRequest=msgs.UpdateInstanceConfigRequest(
instanceConfig=instance_config,
updateMask=','.join(update_mask),
validateOnly=args.validate_only))
return client.projects_instanceConfigs.Patch(req)
def PatchBeta(self,
endpoint_ref,
labels_update,
display_name=None,
description=None,
traffic_split=None,
clear_traffic_split=False):
"""Updates an endpoint using v1beta1 API.
Args:
endpoint_ref: Resource, the parsed endpoint to be updated.
labels_update: UpdateResult, the result of applying the label diff
constructed from args.
display_name: str or None, the new display name of the endpoint.
description: str or None, the new description of the endpoint.
traffic_split: dict or None, the new traffic split of the endpoint.
clear_traffic_split: bool, whether or not clear traffic split of the
endpoint.
Returns:
The response message of Patch.
Raises:
NoFieldsSpecifiedError: An error if no updates requested.
"""
endpoint = self.messages.GoogleCloudAiplatformV1beta1Endpoint()
update_mask = []
if labels_update.needs_update:
endpoint.labels = labels_update.labels
update_mask.append('labels')
if display_name is not None:
endpoint.displayName = display_name
update_mask.append('display_name')
if traffic_split is not None:
additional_properties = []
for key, value in sorted(traffic_split.items()):
additional_properties.append(
endpoint.TrafficSplitValue().AdditionalProperty(
key=key, value=value))
endpoint.trafficSplit = endpoint.TrafficSplitValue(
additionalProperties=additional_properties)
update_mask.append('traffic_split')
if clear_traffic_split:
endpoint.trafficSplit = None
update_mask.append('traffic_split')
if description is not None:
endpoint.description = description
update_mask.append('description')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
req = self.messages.AiplatformProjectsLocationsEndpointsPatchRequest(
name=endpoint_ref.RelativeName(),
googleCloudAiplatformV1beta1Endpoint=endpoint,
updateMask=','.join(update_mask))
return self.client.projects_locations_endpoints.Patch(req)
def Patch(self, model_monitoring_job_ref, args):
"""Update a model deployment monitoring job."""
model_monitoring_job_to_update = self.messages.GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob(
)
update_mask = []
job_spec = self.messages.GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob(
)
if args.monitoring_config_from_file:
data = yaml.load_path(args.monitoring_config_from_file)
if data:
job_spec = messages_util.DictToMessageWithErrorCheck(
data, self.messages.
GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringJob)
model_monitoring_job_to_update.modelDeploymentMonitoringObjectiveConfigs = job_spec.modelDeploymentMonitoringObjectiveConfigs
update_mask.append(
'model_deployment_monitoring_objective_configs')
if args.feature_thresholds:
get_monitoring_job_req = self.messages.AiplatformProjectsLocationsModelDeploymentMonitoringJobsGetRequest(
name=model_monitoring_job_ref.RelativeName())
model_monitoring_job = self._service.Get(get_monitoring_job_req)
model_monitoring_job_to_update.modelDeploymentMonitoringObjectiveConfigs = self._ConstructObjectiveConfigForUpdate(
model_monitoring_job, args.feature_thresholds)
update_mask.append('model_deployment_monitoring_objective_configs')
if args.display_name:
model_monitoring_job_to_update.displayName = args.display_name
update_mask.append('display_name')
if args.emails:
model_monitoring_job_to_update.modelMonitoringAlertConfig = self.messages.GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfig(
emailAlertConfig=self.messages.
GoogleCloudAiplatformV1beta1ModelMonitoringAlertConfigEmailAlertConfig(
userEmails=args.emails))
update_mask.append('model_monitoring_alert_config')
# sampling rate
if args.prediction_sampling_rate:
model_monitoring_job_to_update.loggingSamplingStrategy = self.messages.GoogleCloudAiplatformV1beta1SamplingStrategy(
randomSampleConfig=self.messages.
GoogleCloudAiplatformV1beta1SamplingStrategyRandomSampleConfig(
sampleRate=args.prediction_sampling_rate))
update_mask.append('logging_sampling_strategy')
# schedule
if args.monitoring_frequency:
model_monitoring_job_to_update.modelDeploymentMonitoringScheduleConfig = self.messages.GoogleCloudAiplatformV1beta1ModelDeploymentMonitoringScheduleConfig(
monitorInterval='{}s'.format(
six.text_type(3600 * int(args.monitoring_frequency))))
update_mask.append('model_deployment_monitoring_schedule_config')
if args.analysis_instance_schema:
model_monitoring_job_to_update.analysisInstanceSchemaUri = args.analysis_instance_schema
update_mask.append('analysis_instance_schema_uri')
if args.log_ttl:
model_monitoring_job_to_update.logTtl = '{}s'.format(
six.text_type(86400 * int(args.log_ttl)))
update_mask.append('log_ttl')
if not update_mask:
raise errors.NoFieldsSpecifiedError('No updates requested.')
req = self.messages.AiplatformProjectsLocationsModelDeploymentMonitoringJobsPatchRequest(
name=model_monitoring_job_ref.RelativeName(),
googleCloudAiplatformV1beta1ModelDeploymentMonitoringJob=
model_monitoring_job_to_update,
updateMask=','.join(update_mask))
return self._service.Patch(req)