def test_datasetdict_from_json( split, features, keep_in_memory, jsonl_path, tmp_path, ): file_path = jsonl_path field = None if split: path = {split: file_path} else: split = "train" path = {"train": file_path, "test": file_path} cache_dir = tmp_path / "cache" default_expected_features = {"col_1": "string", "col_2": "int64", "col_3": "float64"} expected_features = features.copy() if features else default_expected_features features = Features({feature: Value(dtype) for feature, dtype in features.items()}) if features else None with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase(): dataset = DatasetDict.from_json( path, features=features, cache_dir=cache_dir, keep_in_memory=keep_in_memory, field=field ) assert isinstance(dataset, DatasetDict) dataset = dataset[split] assert dataset.num_rows == 4 assert dataset.num_columns == 3 assert dataset.column_names == ["col_1", "col_2", "col_3"] assert dataset.split == split for feature, expected_dtype in expected_features.items(): assert dataset.features[feature].dtype == expected_dtype
def test_datasetdict_from_json_keep_in_memory(keep_in_memory, jsonl_path, tmp_path): cache_dir = tmp_path / "cache" expected_features = { "col_1": "string", "col_2": "int64", "col_3": "float64" } with assert_arrow_memory_increases( ) if keep_in_memory else assert_arrow_memory_doesnt_increase(): dataset = DatasetDict.from_json({"train": jsonl_path}, cache_dir=cache_dir, keep_in_memory=keep_in_memory) _check_json_datasetdict(dataset, expected_features)
def test_datasetdict_from_json_splits(split, jsonl_path, tmp_path): if split: path = {split: jsonl_path} else: split = "train" path = {"train": jsonl_path, "test": jsonl_path} cache_dir = tmp_path / "cache" expected_features = { "col_1": "string", "col_2": "int64", "col_3": "float64" } dataset = DatasetDict.from_json(path, cache_dir=cache_dir) _check_json_datasetdict(dataset, expected_features, splits=list(path.keys())) assert all(dataset[split].split == split for split in path.keys())
def test_datasetdict_from_json_features(features, jsonl_path, tmp_path): cache_dir = tmp_path / "cache" default_expected_features = { "col_1": "string", "col_2": "int64", "col_3": "float64" } expected_features = features.copy( ) if features else default_expected_features features = (Features({ feature: Value(dtype) for feature, dtype in features.items() }) if features is not None else None) dataset = DatasetDict.from_json({"train": jsonl_path}, features=features, cache_dir=cache_dir) _check_json_datasetdict(dataset, expected_features)