def _Run(args, version):
tensorboard_time_series_ref = args.CONCEPTS.tensorboard_time_series.Parse()
region = tensorboard_time_series_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version=version,
region=region):
response = client.TensorboardTimeSeriesClient(
version=version).Get(tensorboard_time_series_ref)
return response
def _Run(args, version):
tensorboard_run_ref = args.CONCEPTS.tensorboard_run_id.Parse()
region = tensorboard_run_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(
version=version, region=region):
return client.TensorboardTimeSeriesClient(version=version).List(
tensorboard_run_ref=tensorboard_run_ref,
limit=args.limit,
page_size=args.page_size,
sort_by=args.sort_by)
def _Run(args, version):
tensorboard_time_series_ref = args.CONCEPTS.tensorboard_time_series.Parse()
region = tensorboard_time_series_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version=version,
region=region):
operation = client.TensorboardTimeSeriesClient(
version=version).Delete(tensorboard_time_series_ref)
return operations_util.WaitForOpMaybe(
operations_client=operations.OperationsClient(),
op=operation,
op_ref=tensorboards_util.ParseTensorboardOperation(operation.name))
def _Run(args, version):
"""Create a new Vertex AI Tensorboard time series."""
validation.ValidateDisplayName(args.display_name)
tensorboard_run_ref = args.CONCEPTS.tensorboard_run.Parse()
region = tensorboard_run_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version, region=region):
tensorboard_runs_client = client.TensorboardTimeSeriesClient(
version=version)
response = tensorboard_runs_client.Create(tensorboard_run_ref, args)
response_msg = encoding.MessageToPyValue(response)
if 'name' in response_msg:
log.status.Print(
('Created Vertex AI Tensorboard time series: {}.').format(
response_msg['name']))
return response
def _Run(args, version):
"""Update an existing Vertex AI Tensorboard time series."""
tensorboard_time_series_ref = args.CONCEPTS.tensorboard_time_series.Parse()
args.region = tensorboard_time_series_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version, region=args.region):
try:
op = client.TensorboardTimeSeriesClient(version=version).Patch(
tensorboard_time_series_ref, args)
except errors.NoFieldsSpecifiedError:
available_update_args = [
'display_name', 'description', 'plugin_name', 'plugin_data'
]
if not any(args.IsSpecified(arg) for arg in available_update_args):
raise
log.status.Print('No update to perform.')
return None
else:
log.UpdatedResource(op.name, kind='Vertex AI Tensorboard time series')
return op