Datasets:
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import datasets as ds
import pytest
@pytest.fixture
def dataset_path() -> str:
return "wrime.py"
@pytest.mark.parametrize(
"dataset_name, expected_train_num_rows, expected_val_num_rows, expected_test_num_rows,",
(
("ver1", 40000, 1200, 2000),
("ver2", 30000, 2500, 2500),
),
)
def test_load_dataset(
dataset_path: str,
dataset_name: str,
expected_train_num_rows: int,
expected_val_num_rows: int,
expected_test_num_rows: int,
) -> None:
dataset = ds.load_dataset(path=dataset_path, name=dataset_name)
assert dataset["train"].num_rows == expected_train_num_rows # type: ignore
assert dataset["validation"].num_rows == expected_val_num_rows # type: ignore
assert dataset["test"].num_rows == expected_test_num_rows # type: ignore
writer_readers = [
"writer",
"reader1",
"reader2",
"reader3",
"avg_readers",
]
expected_keys = ["sentence", "user_id", "datetime"] + writer_readers
for split in ["train", "validation", "test"]:
split_dataset = dataset[split] # type: ignore
for data in split_dataset:
assert len(data.keys()) == len(expected_keys)
for expected_key in expected_keys:
assert expected_key in data.keys()
for k in writer_readers:
if dataset_name == "ver1":
assert len(data[k]) == 8 # 8 感情強度
elif dataset_name == "ver2":
assert len(data[k]) == 8 + 1 # 8 感情強度 + 1 感情極性
else:
raise ValueError(f"Invalid dataset version: {dataset_name}")
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