





"""simple docstring"""





import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Any							,						SCREAMING_SNAKE_CASE     :						Any			):







      '''simple docstring'''




      assert isinstance(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)
      assert dataset.num_rows == 4
      assert dataset.num_columns == 1
      assert dataset.column_names == ["text"]
      for feature, expected_dtype in expected_features.items():
            assert dataset.features[feature].dtype == expected_dtype


@pytest.mark.parametrize("""keep_in_memory"""							,						[False, True]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Any							,						SCREAMING_SNAKE_CASE     :						List[str]							,						SCREAMING_SNAKE_CASE     :						int			):







      '''simple docstring'''




      lowerCAmelCase  						=       tmp_path / """cache"""
      lowerCAmelCase  						=       {"""text""": """string"""}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            lowerCAmelCase  						=       TextDatasetReader(SCREAMING_SNAKE_CASE							,						cache_dir=SCREAMING_SNAKE_CASE							,						keep_in_memory=SCREAMING_SNAKE_CASE			).read()
      _check_text_dataset(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)


@pytest.mark.parametrize(
    """features"""							,						[
        None,
        {"""text""": """string"""},
        {"""text""": """int32"""},
        {"""text""": """float32"""},
    ]							,						)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Optional[int]							,						SCREAMING_SNAKE_CASE     :						Dict							,						SCREAMING_SNAKE_CASE     :						int			):







      '''simple docstring'''




      lowerCAmelCase  						=       tmp_path / """cache"""
      lowerCAmelCase  						=       {"""text""": """string"""}
      lowerCAmelCase  						=       features.copy() if features else default_expected_features
      lowerCAmelCase  						=       (
          Features({feature: Value(SCREAMING_SNAKE_CASE			) for feature, dtype in features.items()}			) if features is not None else None
      )
      lowerCAmelCase  						=       TextDatasetReader(SCREAMING_SNAKE_CASE							,						features=SCREAMING_SNAKE_CASE							,						cache_dir=SCREAMING_SNAKE_CASE			).read()
      _check_text_dataset(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)


@pytest.mark.parametrize("""split"""							,						[None, NamedSplit("""train"""			), """train""", """test"""]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Optional[Any]							,						SCREAMING_SNAKE_CASE     :						str							,						SCREAMING_SNAKE_CASE     :						str			):







      '''simple docstring'''




      lowerCAmelCase  						=       tmp_path / """cache"""
      lowerCAmelCase  						=       {"""text""": """string"""}
      lowerCAmelCase  						=       TextDatasetReader(SCREAMING_SNAKE_CASE							,						cache_dir=SCREAMING_SNAKE_CASE							,						split=SCREAMING_SNAKE_CASE			).read()
      _check_text_dataset(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)
      assert dataset.split == split if split else "train"


@pytest.mark.parametrize("""path_type"""							,						[str, list]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Dict							,						SCREAMING_SNAKE_CASE     :						Union[str, Any]							,						SCREAMING_SNAKE_CASE     :						Union[str, Any]			):







      '''simple docstring'''




      if issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       text_path
      elif issubclass(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			):
            lowerCAmelCase  						=       [text_path]
      lowerCAmelCase  						=       tmp_path / """cache"""
      lowerCAmelCase  						=       {"""text""": """string"""}
      lowerCAmelCase  						=       TextDatasetReader(SCREAMING_SNAKE_CASE							,						cache_dir=SCREAMING_SNAKE_CASE			).read()
      _check_text_dataset(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)


def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Tuple							,						SCREAMING_SNAKE_CASE     :						Tuple							,						SCREAMING_SNAKE_CASE     :						Tuple=("train",)			):







      '''simple docstring'''




      assert isinstance(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)
      for split in splits:
            lowerCAmelCase  						=       dataset_dict[split]
            assert dataset.num_rows == 4
            assert dataset.num_columns == 1
            assert dataset.column_names == ["text"]
            for feature, expected_dtype in expected_features.items():
                  assert dataset.features[feature].dtype == expected_dtype


@pytest.mark.parametrize("""keep_in_memory"""							,						[False, True]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Union[str, Any]							,						SCREAMING_SNAKE_CASE     :						List[str]							,						SCREAMING_SNAKE_CASE     :						Tuple			):







      '''simple docstring'''




      lowerCAmelCase  						=       tmp_path / """cache"""
      lowerCAmelCase  						=       {"""text""": """string"""}
      with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
            lowerCAmelCase  						=       TextDatasetReader({"""train""": text_path}							,						cache_dir=SCREAMING_SNAKE_CASE							,						keep_in_memory=SCREAMING_SNAKE_CASE			).read()
      _check_text_datasetdict(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)


@pytest.mark.parametrize(
    """features"""							,						[
        None,
        {"""text""": """string"""},
        {"""text""": """int32"""},
        {"""text""": """float32"""},
    ]							,						)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						Dict							,						SCREAMING_SNAKE_CASE     :						List[str]							,						SCREAMING_SNAKE_CASE     :						str			):







      '''simple docstring'''




      lowerCAmelCase  						=       tmp_path / """cache"""
      # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
      lowerCAmelCase  						=       {"""text""": """string"""}
      lowerCAmelCase  						=       features.copy() if features else default_expected_features
      lowerCAmelCase  						=       (
          Features({feature: Value(SCREAMING_SNAKE_CASE			) for feature, dtype in features.items()}			) if features is not None else None
      )
      lowerCAmelCase  						=       TextDatasetReader({"""train""": text_path}							,						features=SCREAMING_SNAKE_CASE							,						cache_dir=SCREAMING_SNAKE_CASE			).read()
      _check_text_datasetdict(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE			)






@pytest.mark.parametrize("""split"""							,						[None, NamedSplit("""train"""			), """train""", """test"""]			)
def 			UpperCAmelCase__							(  SCREAMING_SNAKE_CASE     :						str							,						SCREAMING_SNAKE_CASE     :						Optional[int]							,						SCREAMING_SNAKE_CASE     :						Optional[Any]			):







      '''simple docstring'''




      if split:
            lowerCAmelCase  						=       {split: text_path}
      else:
            lowerCAmelCase  						=       """train"""
            lowerCAmelCase  						=       {"""train""": text_path, """test""": text_path}
      lowerCAmelCase  						=       tmp_path / """cache"""
      lowerCAmelCase  						=       {"""text""": """string"""}
      lowerCAmelCase  						=       TextDatasetReader(SCREAMING_SNAKE_CASE							,						cache_dir=SCREAMING_SNAKE_CASE			).read()
      _check_text_datasetdict(SCREAMING_SNAKE_CASE							,						SCREAMING_SNAKE_CASE							,						splits=list(path.keys()			)			)
      assert all(dataset[split].split == split for split in path.keys()			)










"""simple docstring"""


from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class   _UpperCamelCase  :
							'''simple docstring'''







							pass




