'''simple docstring'''






def 	_A				(lowerCAmelCase__  :str = "The quick brown fox jumps over the lazy dog"				,						)   ->  Union[str, Any]:




     '''simple docstring'''



     _a			      =							set()

     # Replace all the whitespace in our sentence
     _a			      =							input_str.replace(' '				,						''		)
     for alpha in input_str:
          if "a" <= alpha.lower() <= "z":
               frequency.add(alpha.lower()		)
     return len(a_		) == 26






def 	_A				(lowerCAmelCase__  :str = "The quick brown fox jumps over the lazy dog"				,						)   ->  int:




     '''simple docstring'''



     _a			      =							[False] * 26
     for char in input_str:
          if char.islower():
               _a			      =							True
          elif char.isupper():
               _a			      =							True
     return all(a_		)






def 	_A				(lowerCAmelCase__  :str = "The quick brown fox jumps over the lazy dog"				,						)   ->  Union[str, Any]:




     '''simple docstring'''



     return len({char for char in input_str.lower() if char.isalpha()}		) == 26






def 	_A				()   ->  Any:




     '''simple docstring'''



     from timeit import timeit

     _a			      =							'''from __main__ import is_pangram, is_pangram_faster, is_pangram_fastest'''
     print(timeit('is_pangram()'				,						setup=a_		)		)
     print(timeit('is_pangram_faster()'				,						setup=a_		)		)
     print(timeit('is_pangram_fastest()'				,						setup=a_		)		)
     # 5.348480500048026, 2.6477354579837993, 1.8470395830227062
     # 5.036091582966037, 2.644472333951853,  1.8869528750656173


if __name__ == "__main__":
 import doctest

 doctest.testmod()
 benchmark()





'''simple docstring'''






import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


a_					:    Optional[Any]          =    logging.get_logger(__name__)




class  a     (     _SCREAMING_SNAKE_CASE       ):
 def __init__( self      ,				*__magic_name__      ,				**__magic_name__						)					->							None:
      warnings.warn(
          'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
          ' use DonutImageProcessor instead.'      ,				__magic_name__      ,				)
      super().__init__(*__magic_name__      ,				**__magic_name__						)

