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)
