




import logging
import os
import sys
import threading
from logging import (
    CRITICAL,  # NOQA
    DEBUG,  # NOQA
    ERROR,  # NOQA
    FATAL,  # NOQA
    INFO,  # NOQA
    NOTSET,  # NOQA
    WARN,  # NOQA
    WARNING,  # NOQA
)
from typing import Optional

from tqdm import auto as tqdm_lib


__a  :		int			=    threading.Lock()
__a  :		Optional[logging.Handler]			=    None

__a  :		List[str]			=    {
    'debug': logging.DEBUG,
    'info': logging.INFO,
    'warning': logging.WARNING,
    'error': logging.ERROR,
    'critical': logging.CRITICAL,
}

__a  :		Optional[int]			=    logging.WARNING

__a  :		List[str]			=    True
def 					snake_case_     (		)			-> Dict:
							lowercase__  :       Any   					=							os.getenv("DIFFUSERS_VERBOSITY"				,A_				)
							if env_level_str:
														if env_level_str in log_levels:
																					return log_levels[env_level_str]
														else:
																					logging.getLogger().warning(
																					    F"""Unknown option DIFFUSERS_VERBOSITY={env_level_str}, """
																					    F"""has to be one of: { ", ".join(log_levels.keys()				) }"""				)
							return _default_log_level
def 					snake_case_     (		)			-> Any:
							return __name__.split("."				)[0]
def 					snake_case_     (		)			-> Union[str, Any]:
							return logging.getLogger(_get_library_name()				)
def 					snake_case_     (		)			-> int:
							global _default_handler

							with _lock:
														if _default_handler:
																					# This library has already configured the library root logger.
																					return
														lowercase__  :       Optional[int]   					=							logging.StreamHandler()  # Set sys.stderr as stream.
														lowercase__  :       str   					=							sys.stderr.flush

														# Apply our default configuration to the library root logger.
														lowercase__  :       Optional[Any]   					=							_get_library_root_logger()
														library_root_logger.addHandler(_default_handler				)
														library_root_logger.setLevel(_get_default_logging_level()				)
														lowercase__  :       Tuple   					=							False
def 					snake_case_     (		)			-> Dict:
							global _default_handler

							with _lock:
														if not _default_handler:
																					return

														lowercase__  :       Optional[Any]   					=							_get_library_root_logger()
														library_root_logger.removeHandler(_default_handler				)
														library_root_logger.setLevel(logging.NOTSET				)
														lowercase__  :       Any   					=							None
def 					snake_case_     (		)			-> Dict:
							return log_levels
def 					snake_case_     (		SCREAMING_SNAKE_CASE_ = None				)			-> List[str]:

							if name is None:
														lowercase__  :       int   					=							_get_library_name()

							_configure_library_root_logger()
							return logging.getLogger(A_				)
def 					snake_case_     (		)			-> Tuple:
							_configure_library_root_logger()
							return _get_library_root_logger().getEffectiveLevel()
def 					snake_case_     (		SCREAMING_SNAKE_CASE_				)			-> str:
							_configure_library_root_logger()
							_get_library_root_logger().setLevel(A_				)
def 					snake_case_     (		)			-> int:
							return set_verbosity(A_				)
def 					snake_case_     (		)			-> Union[str, Any]:
							return set_verbosity(A_				)
def 					snake_case_     (		)			-> Tuple:
							return set_verbosity(A_				)
def 					snake_case_     (		)			-> Tuple:
							return set_verbosity(A_				)
def 					snake_case_     (		)			-> List[str]:
							_configure_library_root_logger()

							assert _default_handler is not None
							_get_library_root_logger().removeHandler(_default_handler				)
def 					snake_case_     (		)			-> Optional[int]:
							_configure_library_root_logger()

							assert _default_handler is not None
							_get_library_root_logger().addHandler(_default_handler				)
def 					snake_case_     (		SCREAMING_SNAKE_CASE_				)			-> Union[str, Any]:
							_configure_library_root_logger()

							assert handler is not None
							_get_library_root_logger().addHandler(A_				)
def 					snake_case_     (		SCREAMING_SNAKE_CASE_				)			-> Union[str, Any]:
							_configure_library_root_logger()

							assert handler is not None and handler not in _get_library_root_logger().handlers
							_get_library_root_logger().removeHandler(A_				)
def 					snake_case_     (		)			-> Tuple:
							_configure_library_root_logger()
							lowercase__  :       Optional[Any]   					=							False
def 					snake_case_     (		)			-> List[Any]:
							_configure_library_root_logger()
							lowercase__  :       str   					=							True
def 					snake_case_     (		)			-> Optional[int]:
							lowercase__  :       Union[str, Any]   					=							_get_library_root_logger().handlers

							for handler in handlers:
														lowercase__  :       str   					=							logging.Formatter("[%(levelname)s|%(filename)s:%(lineno)s] %(asctime)s >> %(message)s"				)
														handler.setFormatter(A_				)
def 					snake_case_     (		)			-> Optional[int]:
							lowercase__  :       Dict   					=							_get_library_root_logger().handlers

							for handler in handlers:
														handler.setFormatter(A_				)
def 					snake_case_     (		self				,*SCREAMING_SNAKE_CASE_				,**SCREAMING_SNAKE_CASE_				)			-> Dict:
							lowercase__  :       Any   					=							os.getenv("DIFFUSERS_NO_ADVISORY_WARNINGS"				,A_				)
							if no_advisory_warnings:
														return
							self.warning(*A_				,**A_				)


__a  :		Optional[int]			=    warning_advice







class       UpperCAmelCase:



	"""simple docstring"""






	def __init__(     self       ,      *lowerCamelCase       ,      **lowerCamelCase				)					->			Any:  # pylint: disable=unused-argument





								"""simple docstring"""


								lowercase__  :       int   					=							args[0] if args else None

	def __iter__(     self				)					->			Dict:





								"""simple docstring"""


								return iter(self._iterator				)

	def __getattr__(     self       ,      lowerCamelCase				)					->			Optional[int]:





								"""simple docstring"""


								def empty_fn(*lowerCamelCase       ,      **lowerCamelCase				):  # pylint: disable=unused-argument
															return

								return empty_fn

	def __enter__(     self				)					->			Any:





								"""simple docstring"""


								return self







	def __exit__(     self       ,      lowerCamelCase       ,      lowerCamelCase       ,      lowerCamelCase				)					->			List[str]:





								"""simple docstring"""


								return







class       UpperCAmelCase:



	"""simple docstring"""






	def __call__(     self       ,      *lowerCamelCase       ,      **lowerCamelCase				)					->			str:





								"""simple docstring"""


								if _tqdm_active:
															return tqdm_lib.tqdm(*lowerCamelCase       ,      **lowerCamelCase				)
								else:
															return EmptyTqdm(*lowerCamelCase       ,      **lowerCamelCase				)

	def     __a	(     self       ,      *lowerCamelCase       ,      **lowerCamelCase				)					->			Union[str, Any]:





								"""simple docstring"""


								lowercase__  :       Any   					=							None
								if _tqdm_active:
															return tqdm_lib.tqdm.set_lock(*lowerCamelCase       ,      **lowerCamelCase				)







	def     __a	(     self				)					->			Tuple:





								"""simple docstring"""


								if _tqdm_active:
															return tqdm_lib.tqdm.get_lock()

__a  :		int			=    _tqdm_cls()
def 					snake_case_     (		)			-> str:
							global _tqdm_active
							return bool(_tqdm_active				)
def 					snake_case_     (		)			-> Optional[Any]:
							global _tqdm_active
							lowercase__  :       List[str]   					=							True




def 					snake_case_     (		)			-> int:
							global _tqdm_active
							lowercase__  :       int   					=							False







"""simple docstring"""


import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def 			snake_case  (A_      :Dict	,			A_      :Tuple      ):







  '''simple docstring'''

  assert isinstance(A_	,			A_      )
  assert dataset.num_rows == 4
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_1", "col_2", "col_3"]
  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_      :str	,			A_      :List[Any]	,			A_      :Optional[Any]      ):







  '''simple docstring'''

  a     :			List[Any]				=   tmp_path / 'cache'
  a     :			str				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    a     :			Union[str, Any]				=   CsvDatasetReader(A_	,			cache_dir=A_	,			keep_in_memory=A_      ).read()
  _check_csv_dataset(A_	,			A_      )




@pytest.mark.parametrize(
    'features'	,			[
        None,
        {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'},
        {'col_1': 'string', 'col_2': 'string', 'col_3': 'string'},
        {'col_1': 'int32', 'col_2': 'int32', 'col_3': 'int32'},
        {'col_1': 'float32', 'col_2': 'float32', 'col_3': 'float32'},
    ]	,			)
def 			snake_case  (A_      :List[str]	,			A_      :Union[str, Any]	,			A_      :Union[str, Any]      ):







  '''simple docstring'''

  a     :			str				=   tmp_path / 'cache'
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  a     :			Optional[int]				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			Dict				=   features.copy() if features else default_expected_features
  a     :			Dict				=   (
      Features({feature: Value(A_      ) for feature, dtype in features.items()}      ) if features is not None else None
  )
  a     :			Tuple				=   CsvDatasetReader(A_	,			features=A_	,			cache_dir=A_      ).read()
  _check_csv_dataset(A_	,			A_      )




@pytest.mark.parametrize('split'	,			[None, NamedSplit('train'      ), 'train', 'test']      )
def 			snake_case  (A_      :List[str]	,			A_      :str	,			A_      :int      ):







  '''simple docstring'''

  a     :			str				=   tmp_path / 'cache'
  a     :			Tuple				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			List[str]				=   CsvDatasetReader(A_	,			cache_dir=A_	,			split=A_      ).read()
  _check_csv_dataset(A_	,			A_      )
  assert dataset.split == split if split else "train"




@pytest.mark.parametrize('path_type'	,			[str, list]      )
def 			snake_case  (A_      :int	,			A_      :List[Any]	,			A_      :str      ):







  '''simple docstring'''

  if issubclass(A_	,			A_      ):
    a     :			Dict				=   csv_path
  elif issubclass(A_	,			A_      ):
    a     :			Optional[Any]				=   [csv_path]
  a     :			Tuple				=   tmp_path / 'cache'
  a     :			str				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			Any				=   CsvDatasetReader(A_	,			cache_dir=A_      ).read()
  _check_csv_dataset(A_	,			A_      )




def 			snake_case  (A_      :List[str]	,			A_      :Dict	,			A_      :Optional[Any]=("train",)      ):







  '''simple docstring'''

  assert isinstance(A_	,			A_      )
  for split in splits:
    a     :			List[Any]				=   dataset_dict[split]
    assert dataset.num_rows == 4
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_1", "col_2", "col_3"]
    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_      :str	,			A_      :Any	,			A_      :List[str]      ):







  '''simple docstring'''

  a     :			Any				=   tmp_path / 'cache'
  a     :			int				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    a     :			str				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_	,			keep_in_memory=A_      ).read()
  _check_csv_datasetdict(A_	,			A_      )




@pytest.mark.parametrize(
    'features'	,			[
        None,
        {'col_1': 'string', 'col_2': 'int64', 'col_3': 'float64'},
        {'col_1': 'string', 'col_2': 'string', 'col_3': 'string'},
        {'col_1': 'int32', 'col_2': 'int32', 'col_3': 'int32'},
        {'col_1': 'float32', 'col_2': 'float32', 'col_3': 'float32'},
    ]	,			)
def 			snake_case  (A_      :Optional[int]	,			A_      :List[Any]	,			A_      :Tuple      ):







  '''simple docstring'''

  a     :			Dict				=   tmp_path / 'cache'
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  a     :			Any				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			Tuple				=   features.copy() if features else default_expected_features
  a     :			Optional[int]				=   (
      Features({feature: Value(A_      ) for feature, dtype in features.items()}      ) if features is not None else None
  )
  a     :			Any				=   CsvDatasetReader({'train': csv_path}	,			features=A_	,			cache_dir=A_      ).read()
  _check_csv_datasetdict(A_	,			A_      )




@pytest.mark.parametrize('split'	,			[None, NamedSplit('train'      ), 'train', 'test']      )
def 			snake_case  (A_      :List[str]	,			A_      :Optional[Any]	,			A_      :str      ):







  '''simple docstring'''

  if split:
    a     :			List[Any]				=   {split: csv_path}
  else:
    a     :			str				=   {'train': csv_path, 'test': csv_path}
  a     :			Union[str, Any]				=   tmp_path / 'cache'
  a     :			Tuple				=   {'col_1': 'int64', 'col_2': 'int64', 'col_3': 'float64'}
  a     :			List[str]				=   CsvDatasetReader(A_	,			cache_dir=A_      ).read()
  _check_csv_datasetdict(A_	,			A_	,			splits=list(path.keys()      )      )
  assert all(dataset[split].split == split for split in path.keys()      )




def 			snake_case  (A_      :Dict      ):







  '''simple docstring'''

  with open(A_	,			encoding='utf-8'      ) as csvfile:
    yield from csv.reader(A_      )




def 			snake_case  (A_      :int	,			A_      :Optional[int]      ):







  '''simple docstring'''

  a     :			str				=   tmp_path / 'cache'
  a     :			List[str]				=   os.path.join(A_	,			'tmp.csv'      )
  a     :			Union[str, Any]				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_      ).read()
  CsvDatasetWriter(dataset['train']	,			A_	,			num_proc=1      ).write()

  a     :			int				=   iter_csv_file(A_      )
  a     :			Optional[Any]				=   iter_csv_file(A_      )

  for rowa, rowa in zip(A_	,			A_      ):
    assert rowa == rowa




def 			snake_case  (A_      :Tuple	,			A_      :Tuple      ):







  '''simple docstring'''

  a     :			Union[str, Any]				=   tmp_path / 'cache'
  a     :			List[Any]				=   os.path.join(A_	,			'tmp.csv'      )
  a     :			Union[str, Any]				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_      ).read()
  CsvDatasetWriter(dataset['train']	,			A_	,			num_proc=2      ).write()

  a     :			Dict				=   iter_csv_file(A_      )
  a     :			List[Any]				=   iter_csv_file(A_      )

  for rowa, rowa in zip(A_	,			A_      ):
    assert rowa == rowa






def 			snake_case  (A_      :Union[str, Any]	,			A_      :List[Any]      ):







  '''simple docstring'''

  a     :			List[Any]				=   tmp_path / 'cache'
  a     :			Dict				=   os.path.join(A_	,			'tmp.csv'      )
  a     :			Union[str, Any]				=   CsvDatasetReader({'train': csv_path}	,			cache_dir=A_      ).read()
  with pytest.raises(A_      ):
    CsvDatasetWriter(dataset['train']	,			A_	,			num_proc=0      )




