



'''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 lowerCAmelCase    (__A    ,      __A):



     """simple docstring"""



     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 lowerCAmelCase    (__A    ,      __A    ,      __A):



     """simple docstring"""



     _a           =    tmp_path / '''cache'''
     _a           =    {'''text''': '''string'''}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          _a           =    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 lowerCAmelCase    (__A    ,      __A    ,      __A):



     """simple docstring"""



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




@pytest.mark.parametrize('''split'''    ,      [None, NamedSplit('''train'''), '''train''', '''test'''])
def lowerCAmelCase    (__A    ,      __A    ,      __A):



     """simple docstring"""



     _a           =    tmp_path / '''cache'''
     _a           =    {'''text''': '''string'''}
     _a           =    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 lowerCAmelCase    (__A    ,      __A    ,      __A):



     """simple docstring"""



     if issubclass(__A    ,      __A):
          _a           =    text_path
     elif issubclass(__A    ,      __A):
          _a           =    [text_path]
     _a           =    tmp_path / '''cache'''
     _a           =    {'''text''': '''string'''}
     _a           =    TextDatasetReader(__A    ,      cache_dir=__A).read()
     _check_text_dataset(__A    ,      __A)




def lowerCAmelCase    (__A    ,      __A    ,      __A=("train",)):



     """simple docstring"""



     assert isinstance(__A    ,      __A)
     for split in splits:
          _a           =    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 lowerCAmelCase    (__A    ,      __A    ,      __A):



     """simple docstring"""



     _a           =    tmp_path / '''cache'''
     _a           =    {'''text''': '''string'''}
     with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
          _a           =    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 lowerCAmelCase    (__A    ,      __A    ,      __A):



     """simple docstring"""



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



     """simple docstring"""



     if split:
          _a           =    {split: text_path}
     else:
          _a           =    '''train'''
          _a           =    {'''train''': text_path, '''test''': text_path}
     _a           =    tmp_path / '''cache'''
     _a           =    {'''text''': '''string'''}
     _a           =    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'''

import unittest

from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class 							__lowerCAmelCase	(       unittest.TestCase					):






       """simple docstring"""





       def snake_case__		(				self  :						str	)       ->	Optional[int]:

            '''simple docstring'''




            debug_launcher(test_script.main	)







       def snake_case__		(				self  :						Any	)       ->	Optional[Any]:

            '''simple docstring'''




            debug_launcher(test_ops.main	)



