def test_create_local_storage_config(self, accesskey, url): gas_client = GAS(access_key=accesskey, url=url) local_storage_name = "local_storage_config" local_storage = { "name": local_storage_name, "file_path": "file_path/", "endpoint": "http://192.168.0.1:9000", } gas_client.create_local_storage_config(**local_storage) gas_client.delete_storage_config(local_storage_name)
from tensorbay.dataset import Dataset from tensorbay.label import Classification # Use AuthData to organize a dataset by the "Dataset" class before importing. dataset = Dataset("<DATASET_NAME>") # TensorBay uses "segment" to separate different parts in a dataset. segment = dataset.create_segment() images = cloud_client.list_auth_data("<data/images/>") labels = cloud_client.list_auth_data("<data/labels/>") for auth_data, label in zip(images, labels): with label.open() as fp: auth_data.label.classification = Classification.loads(json.load(fp)) segment.append(auth_data) dataset_client = gas.upload_dataset(dataset, jobs=8) """""" """Create local storage config""" gas.create_local_storage_config( name="<LOCAL_STORAGE_CONFIG>", file_path="<path/to/dataset>", endpoint="<external IP address of the local storage service>", ) """""" """Create authorized local storage dataset""" dataset_client = gas.create_dataset("<DATASET_NAME>", config_name="<LOCAL_STORAGE_CONFIG>") """"""