import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin

class       snake_case					(      UpperCamelCase_						):
		lowercase_			=     'Speech2TextFeatureExtractor'
		lowercase_			=     'Speech2TextTokenizer'




		def __init__(      self     :	Union[str, Any]     , a_     :	Optional[int]     , a_     :	Any				)->       List[str]:




							"""simple docstring"""
							super().__init__(a_     , a_				)
							SCREAMING_SNAKE_CASE__				:				int			=		self.feature_extractor
							SCREAMING_SNAKE_CASE__				:				Dict			=		False




		def __call__(      self     :	Tuple     , *a_     :	Optional[Any]     , **a_     :	Dict				)->       Optional[int]:




							"""simple docstring"""
							# For backward compatibility
							if self._in_target_context_manager:
												return self.current_processor(*a_     , **a_				)

							if "raw_speech" in kwargs:
												warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'				)
												SCREAMING_SNAKE_CASE__				:				Any			=		kwargs.pop('raw_speech'				)
							else:
												SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		kwargs.pop('audio'     , a_				)
							SCREAMING_SNAKE_CASE__				:				int			=		kwargs.pop('sampling_rate'     , a_				)
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		kwargs.pop('text'     , a_				)
							if len(a_				) > 0:
												SCREAMING_SNAKE_CASE__				:				Optional[Any]			=		args[0]
												SCREAMING_SNAKE_CASE__				:				List[Any]			=		args[1:]

							if audio is None and text is None:
												raise ValueError('You need to specify either an `audio` or `text` input to process.'				)

							if audio is not None:
												SCREAMING_SNAKE_CASE__				:				int			=		self.feature_extractor(a_     , *a_     , sampling_rate=a_     , **a_				)
							if text is not None:
												SCREAMING_SNAKE_CASE__				:				Any			=		self.tokenizer(a_     , **a_				)

							if text is None:
												return inputs
							elif audio is None:
												return encodings
							else:
												SCREAMING_SNAKE_CASE__				:				List[str]			=		encodings['input_ids']
												return inputs




		def 	__lowercase(      self     :	int     , *a_     :	List[Any]     , **a_     :	str				)->       Union[str, Any]:




							"""simple docstring"""
							return self.tokenizer.batch_decode(*a_     , **a_				)




		def 	__lowercase(      self     :	Optional[int]     , *a_     :	Tuple     , **a_     :	str				)->       Union[str, Any]:




							"""simple docstring"""
							return self.tokenizer.decode(*a_     , **a_				)




		@contextmanager
		def 	__lowercase(      self     :	Dict				)->       List[Any]:




							"""simple docstring"""
							warnings.warn(
							    '`as_target_processor` is deprecated and will be removed in v5 of Transformers. You can process your '
							    'labels by using the argument `text` of the regular `__call__` method (either in the same call as '
							    'your audio inputs, or in a separate call.'				)
							SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		True
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		self.tokenizer
							yield
							SCREAMING_SNAKE_CASE__				:				Dict			=		self.feature_extractor
							SCREAMING_SNAKE_CASE__				:				Optional[int]			=		False




def     _a				(      lowercase__  :			Optional[int] ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		[]
     SCREAMING_SNAKE_CASE__				:				List[Any]			=		set({'(', '[', '{'} )
     SCREAMING_SNAKE_CASE__				:				Optional[int]			=		set({')', ']', '}'} )
     SCREAMING_SNAKE_CASE__				:				Union[str, Any]			=		{'{': '}', '[': ']', '(': ')'}

     for i in range(len(lowercase__ ) ):
          if s[i] in open_brackets:
               stack.append(s[i] )

          elif s[i] in closed_brackets and (
              len(lowercase__ ) == 0 or (len(lowercase__ ) > 0 and open_to_closed[stack.pop()] != s[i])
          ):
               return False

     return len(lowercase__ ) == 0







def     _a				(      ):







     '''simple docstring'''


     SCREAMING_SNAKE_CASE__				:				Tuple			=		input('Enter sequence of brackets: ' )
     if is_balanced(lowercase__ ):
          print(lowercase__     ,  'is balanced' )
     else:
          print(lowercase__     ,  'is not balanced' )


if __name__ == "__main__":
      main()



