async def sample_create_tensorboard_time_series(): # Create a client client = aiplatform_v1.TensorboardServiceAsyncClient() # Initialize request argument(s) tensorboard_time_series = aiplatform_v1.TensorboardTimeSeries() tensorboard_time_series.display_name = "display_name_value" tensorboard_time_series.value_type = "BLOB_SEQUENCE" request = aiplatform_v1.CreateTensorboardTimeSeriesRequest( parent="parent_value", tensorboard_time_series=tensorboard_time_series, ) # Make the request response = await client.create_tensorboard_time_series(request=request) # Handle the response print(response)
def sample_batch_create_tensorboard_time_series(): # Create a client client = aiplatform_v1.TensorboardServiceClient() # Initialize request argument(s) requests = aiplatform_v1.CreateTensorboardTimeSeriesRequest() requests.parent = "parent_value" requests.tensorboard_time_series.display_name = "display_name_value" requests.tensorboard_time_series.value_type = "BLOB_SEQUENCE" request = aiplatform_v1.BatchCreateTensorboardTimeSeriesRequest( parent="parent_value", requests=requests, ) # Make the request response = client.batch_create_tensorboard_time_series(request=request) # Handle the response print(response)