def test_load_real_metric(self, metric_name):
with tempfile.TemporaryDirectory() as temp_data_dir:
download_config = DownloadConfig()
download_config.force_download = True
config_name = None
if metric_name == "glue":
config_name = "sst2"
metric = load_metric(
metric_name, config_name=config_name, data_dir=temp_data_dir, download_config=download_config
)
parameters = inspect.signature(metric._compute).parameters
self.assertTrue("predictions" in parameters)
self.assertTrue("references" in parameters)
self.assertTrue(all([p.kind != p.VAR_KEYWORD for p in parameters.values()])) # no **kwargs
def load_builder_class(self, dataset_name, is_local=False):
# Download/copy dataset script
if is_local is True:
module_path, _ = prepare_module("./datasets/" + dataset_name)
else:
module_path, _ = prepare_module(dataset_name, download_config=DownloadConfig(force_download=True))
# Get dataset builder class
builder_cls = import_main_class(module_path)
return builder_cls
def test_load_real_dataset(self, dataset_name):
path = dataset_name
module_path, hash = prepare_module(path, download_config=DownloadConfig(force_download=True), dataset=True)
builder_cls = import_main_class(module_path, dataset=True)
name = builder_cls.BUILDER_CONFIGS[0].name if builder_cls.BUILDER_CONFIGS else None
with tempfile.TemporaryDirectory() as temp_cache_dir:
dataset = load_dataset(
path, name=name, cache_dir=temp_cache_dir, download_mode=GenerateMode.FORCE_REDOWNLOAD
)
for split in dataset.keys():
self.assertTrue(len(dataset[split]) > 0)
del dataset
def test_load_real_dataset_all_configs(self, dataset_name):
path = "./datasets/" + dataset_name
module_path, hash = prepare_module(path, download_config=DownloadConfig(local_files_only=True), dataset=True)
builder_cls = import_main_class(module_path, dataset=True)
config_names = (
[config.name for config in builder_cls.BUILDER_CONFIGS] if len(builder_cls.BUILDER_CONFIGS) > 0 else [None]
)
for name in config_names:
with tempfile.TemporaryDirectory() as temp_cache_dir:
dataset = load_dataset(
path, name=name, cache_dir=temp_cache_dir, download_mode=GenerateMode.FORCE_REDOWNLOAD
)
for split in dataset.keys():
self.assertTrue(len(dataset[split]) > 0)
del dataset
