def _Run(args, version):
tensorboard_run_ref = args.CONCEPTS.tensorboard_run.Parse()
region = tensorboard_run_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(
version=version, region=region):
response = client.TensorboardRunsClient(
version=version).Get(tensorboard_run_ref)
return response
def _Run(args, version):
tensorboard_exp_ref = args.CONCEPTS.tensorboard_experiment_id.Parse()
region = tensorboard_exp_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version=version,
region=region):
return client.TensorboardRunsClient(version=version).List(
tensorboard_exp_ref=tensorboard_exp_ref,
limit=args.limit,
page_size=args.page_size,
sort_by=args.sort_by)
def _Run(args, version):
tensorboard_run_ref = args.CONCEPTS.tensorboard_run.Parse()
region = tensorboard_run_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version=version,
region=region):
operation = client.TensorboardRunsClient(
version=version).Delete(tensorboard_run_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 run."""
tensorboard_exp_ref = args.CONCEPTS.tensorboard_experiment.Parse()
region = tensorboard_exp_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version, region=region):
tensorboard_runs_client = client.TensorboardRunsClient(version=version)
response = tensorboard_runs_client.Create(tensorboard_exp_ref, args)
response_msg = encoding.MessageToPyValue(response)
if 'name' in response_msg:
log.status.Print(('Created Vertex AI Tensorboard run: {}.').format(
response_msg['name']))
return response
def _Run(args, version):
"""Update an existing Vertex AI Tensorboard run."""
tensorboard_run_ref = args.CONCEPTS.tensorboard_run.Parse()
args.region = tensorboard_run_ref.AsDict()['locationsId']
with endpoint_util.AiplatformEndpointOverrides(version,
region=args.region):
try:
op = client.TensorboardRunsClient(version=version).Patch(
tensorboard_run_ref, args)
except errors.NoFieldsSpecifiedError:
available_update_args = [
'display_name', 'update_labels', 'clear_labels',
'remove_labels', 'description'
]
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 run')
return op