
"""simple docstring"""




import warnings
from contextlib import contextmanager

from ...processing_utils import ProcessorMixin







class 						lowercase(_lowercase					):
     __snake_case:  Optional[int]  				=    'AutoFeatureExtractor'
     __snake_case:  List[str]  				=    'Speech2Text2Tokenizer'



     def __init__(       self    ,							__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )		->    Union[str, Any]:







         """simple docstring"""



         super().__init__(__SCREAMING_SNAKE_CASE    ,							__SCREAMING_SNAKE_CASE      )
         a__    = self.feature_extractor
         a__    = False



     def __call__(       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )		->    Any:







         """simple docstring"""



         if self._in_target_context_manager:
             return self.current_processor(*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )

         if "raw_speech" in kwargs:
             warnings.warn('Using `raw_speech` as a keyword argument is deprecated. Use `audio` instead.'      )
             a__    = kwargs.pop('raw_speech'      )
         else:
             a__    = kwargs.pop('audio'    ,							__SCREAMING_SNAKE_CASE      )
         a__    = kwargs.pop('sampling_rate'    ,							__SCREAMING_SNAKE_CASE      )
         a__    = kwargs.pop('text'    ,							__SCREAMING_SNAKE_CASE      )
         if len(__SCREAMING_SNAKE_CASE      ) > 0:
             a__    = args[0]
             a__    = 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:
             a__    = self.feature_extractor(__SCREAMING_SNAKE_CASE    ,							*__SCREAMING_SNAKE_CASE    ,							sampling_rate=__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )
         if text is not None:
             a__    = self.tokenizer(__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )

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



     def  lowercase__     (       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )		->    str:







         """simple docstring"""



         return self.tokenizer.batch_decode(*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )



     def  lowercase__     (       self    ,							*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )		->    Dict:







         """simple docstring"""



         return self.tokenizer.decode(*__SCREAMING_SNAKE_CASE    ,							**__SCREAMING_SNAKE_CASE      )




     @contextmanager
     def  lowercase__     (       self      )		->    Optional[int]:







         """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.'      )
         a__    = True
         a__    = self.tokenizer
         yield
         a__    = self.feature_extractor
         a__    = False




"""simple docstring"""




from itertools import combinations, product



def 						__magic_name__		(				UpperCamelCase    :		int       ,		UpperCamelCase    :		int       ,		UpperCamelCase    :		int       ,		UpperCamelCase    :		int    )    ->	bool:
    if xa == ya == 0 or xa == ya == 0:
        return False
    a__    = xa * xa + ya * ya
    a__    = xa * xa + ya * ya
    a__    = (xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
    return (
        a_square + b_square == c_square
        or a_square + c_square == b_square
        or b_square + c_square == a_square
    )



def 						__magic_name__		(				UpperCamelCase    :		int = 50    )    ->	int:
    return sum(
        1
        for pta, pta in combinations(product(range(limit + 1    )       ,		repeat=2    )       ,		2    )
        if is_right(*UpperCamelCase       ,		*UpperCamelCase    )    )


if __name__ == "__main__":
    print(F'''{solution() = }''')


