| | import os |
| |
|
| | import datasets as ds |
| | import pytest |
| |
|
| |
|
| | @pytest.fixture |
| | def dataset_path() -> str: |
| | return "PubLayNet.py" |
| |
|
| |
|
| | @pytest.mark.skipif( |
| | condition=bool(os.environ.get("CI", False)), |
| | reason=( |
| | "Because this loading script downloads a large dataset, " |
| | "we will skip running it on CI." |
| | ), |
| | ) |
| | @pytest.mark.parametrize( |
| | argnames=("decode_rle"), |
| | argvalues=(False, True), |
| | ) |
| | @pytest.mark.parametrize( |
| | argnames=("expected_num_train", "expected_num_valid", "expected_num_test"), |
| | argvalues=((335703, 11245, 11405),), |
| | ) |
| | def test_load_dataset( |
| | dataset_path: str, |
| | decode_rle: bool, |
| | expected_num_train: int, |
| | expected_num_valid: int, |
| | expected_num_test: int, |
| | ): |
| | dataset = ds.load_dataset(path=dataset_path, decode_rle=decode_rle) |
| | assert dataset["train"].num_rows == expected_num_train |
| | assert dataset["validation"].num_rows == expected_num_valid |
| | assert dataset["test"].num_rows == expected_num_test |
| |
|