def test_save_load(self):
# Create a temporary directory
os.makedirs("tmp", exist_ok=True)
# Save the dataset to disk
self.testbed.dataset.save_to_disk(path="tmp")
# Load the dataset from disk
dataset = Dataset.load_from_disk(path="tmp")
# Remove the temporary directory
shutil.rmtree("tmp")
self.assertEqual(dataset.features, self.testbed.dataset.features)
def load(cls, path: str) -> DevBench:
"""Load a devbench from disk.
Args:
path: string path to the devbench directory
Returns:
"""
# Path to the save directory
savedir = pathlib.Path(path)
# Load all the slices
slices = []
for sl_path in tqdm(list((savedir / "slices").glob("*"))):
try:
slices.append(Slice.load_from_disk(str(sl_path)))
except FileNotFoundError:
continue
# Load dataset
dataset = Dataset.load_from_disk(str(savedir / "dataset"))
# Load metrics
metrics = dill.load(open(str(savedir / "metrics.dill"), "rb"))
# Load metrics
aggregators = dill.load(open(str(savedir / "aggregators.dill"), "rb"))
# Load metadata
_ = dill.load(open(str(savedir / "metadata.dill"), "rb"))
# Create the devbench
devbench = cls(dataset=dataset, )
# Set previously stored metrics
devbench.metrics = metrics
# Set previously stored aggregators
devbench.aggregators = aggregators
# Set the slices
devbench.add_slices(slices)
# Load version info
with open(str(savedir / "version.dill"), "rb") as f:
devbench._loads_version(f.read())
return devbench