


'''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    _snake_case  (	A					,       A			)		->       Union[str, Any]:
							assert isinstance(A					,       A			)
							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    _snake_case  (	A					,       A					,       A			)		->       Any:
							lowerCAmelCase__			  =      tmp_path / '''cache'''
							lowerCAmelCase__			  =      {'''text''': '''string'''}
							with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
														lowerCAmelCase__			  =      TextDatasetReader(A					,       cache_dir=A					,       keep_in_memory=A			).read()
							_check_text_dataset(A					,       A			)


@pytest.mark.parametrize(
    '''features'''					,       [
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]					,       )
def    _snake_case  (	A					,       A					,       A			)		->       int:
							lowerCAmelCase__			  =      tmp_path / '''cache'''
							lowerCAmelCase__			  =      {'''text''': '''string'''}
							lowerCAmelCase__			  =      features.copy() if features else default_expected_features
							lowerCAmelCase__			  =      (
							    Features({feature: Value(A			) for feature, dtype in features.items()}			) if features is not None else None
							)
							lowerCAmelCase__			  =      TextDatasetReader(A					,       features=A					,       cache_dir=A			).read()
							_check_text_dataset(A					,       A			)


@pytest.mark.parametrize('''split'''					,       [None, NamedSplit('''train'''			), '''train''', '''test''']			)
def    _snake_case  (	A					,       A					,       A			)		->       List[str]:
							lowerCAmelCase__			  =      tmp_path / '''cache'''
							lowerCAmelCase__			  =      {'''text''': '''string'''}
							lowerCAmelCase__			  =      TextDatasetReader(A					,       cache_dir=A					,       split=A			).read()
							_check_text_dataset(A					,       A			)
							assert dataset.split == split if split else "train"


@pytest.mark.parametrize('''path_type'''					,       [str, list]			)
def    _snake_case  (	A					,       A					,       A			)		->       str:
							if issubclass(A					,       A			):
														lowerCAmelCase__			  =      text_path
							elif issubclass(A					,       A			):
														lowerCAmelCase__			  =      [text_path]
							lowerCAmelCase__			  =      tmp_path / '''cache'''
							lowerCAmelCase__			  =      {'''text''': '''string'''}
							lowerCAmelCase__			  =      TextDatasetReader(A					,       cache_dir=A			).read()
							_check_text_dataset(A					,       A			)


def    _snake_case  (	A					,       A					,       A=("train",)			)		->       Any:
							assert isinstance(A					,       A			)
							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    _snake_case  (	A					,       A					,       A			)		->       Tuple:
							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=A					,       keep_in_memory=A			).read()
							_check_text_datasetdict(A					,       A			)


@pytest.mark.parametrize(
    '''features'''					,       [
        None,
        {'''text''': '''string'''},
        {'''text''': '''int32'''},
        {'''text''': '''float32'''},
    ]					,       )
def    _snake_case  (	A					,       A					,       A			)		->       Union[str, Any]:
							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(A			) for feature, dtype in features.items()}			) if features is not None else None
							)
							lowerCAmelCase__			  =      TextDatasetReader({'''train''': text_path}					,       features=A					,       cache_dir=A			).read()
							_check_text_datasetdict(A					,       A			)






@pytest.mark.parametrize('''split'''					,       [None, NamedSplit('''train'''			), '''train''', '''test''']			)
def    _snake_case  (	A					,       A					,       A			)		->       Any:
							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(A					,       cache_dir=A			).read()
							_check_text_datasetdict(A					,       A					,       splits=list(path.keys()			)			)
							assert all(dataset[split].split == split for split in path.keys()			)

'''simple docstring'''



_lowercase          =						"""
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""

_lowercase          =						[{"""type""": """code""", """content""": INSTALL_CONTENT}]
_lowercase          =						{
    """{processor_class}""": """FakeProcessorClass""",
    """{model_class}""": """FakeModelClass""",
    """{object_class}""": """FakeObjectClass""",
}
