import warnings

from ...utils import logging
from .image_processing_maskformer import MaskFormerImageProcessor


lowerCamelCase__           =				logging.get_logger(__name__)




class 					UpperCamelCase	(     snake_case__      ):




					def __init__( self :					str      ,*_lowerCAmelCase :					Union[str, Any]      ,**_lowerCAmelCase :					Optional[int]						):


							"""simple docstring"""




							warnings.warn(
							    "The class MaskFormerFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
							    " Please use MaskFormerImageProcessor instead."      ,_lowerCAmelCase      ,)
							super().__init__(*_lowerCAmelCase      ,**_lowerCAmelCase						)






import os
from string import ascii_letters

lowerCamelCase__           =				ascii_letters + ' \t\n'



def 							_lowerCamelCase(				)  ->   dict[str, None]:
		__snake_case		       =     os.path.split(os.path.realpath(__snake_case	)	)
		__snake_case		       =     {}
		with open(path[0] + "/dictionary.txt"	) as dictionary_file:
				for word in dictionary_file.read().split("\n"	):
						__snake_case		       =     None
		return english_words


lowerCamelCase__           =				load_dictionary()



def 							_lowerCamelCase(				__snake_case	)  ->   float:
		__snake_case		       =     message.upper()
		__snake_case		       =     remove_non_letters(__snake_case	)
		__snake_case		       =     message.split()
		__snake_case		       =     len([word for word in possible_words if word in ENGLISH_WORDS]	)
		return float(__snake_case	) / len(__snake_case	)



def 							_lowerCamelCase(				__snake_case	)  ->   str:
		return "".join(symbol for symbol in message if symbol in LETTERS_AND_SPACE	)



def 							_lowerCamelCase(				__snake_case						,						__snake_case = 20						,						__snake_case = 85	)  ->   bool:
		__snake_case		       =     get_english_count(__snake_case	) * 100 >= word_percentage
		__snake_case		       =     len(remove_non_letters(__snake_case	)	)
		__snake_case		       =     (float(__snake_case	) / len(__snake_case	)) * 100
		__snake_case		       =     message_letters_percentage >= letter_percentage
		return words_match and letters_match


if __name__ == "__main__":
		import doctest

		doctest.testmod()





