



from ...processing_utils import ProcessorMixin



class 							lowerCAmelCase_						(    SCREAMING_SNAKE_CASE__				):
       UpperCAmelCase__							:   List[str]  	=    "WhisperFeatureExtractor"
       UpperCAmelCase__							:   List[Any]  	=    "WhisperTokenizer"
       def __init__(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_			)	->						Union[str, Any]:
          super().__init__(__lowerCamelCase,     __lowerCamelCase			)
          UpperCamelCase       :    int		      =      self.feature_extractor
          UpperCamelCase       :    int		      =      False
       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_=None,     SCREAMING_SNAKE_CASE_=True			)	->						int:
          return self.tokenizer.get_decoder_prompt_ids(task=__lowerCamelCase,     language=__lowerCamelCase,     no_timestamps=__lowerCamelCase			)
       def __call__(     self,     *SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_			)	->						Optional[int]:




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

          UpperCamelCase       :    int		      =      kwargs.pop('audio',     __lowerCamelCase			)
          UpperCamelCase       :    Optional[int]		      =      kwargs.pop('sampling_rate',     __lowerCamelCase			)
          UpperCamelCase       :    List[str]		      =      kwargs.pop('text',     __lowerCamelCase			)
          if len(__lowerCamelCase			) > 0:
             UpperCamelCase       :    List[Any]		      =      args[0]
             UpperCamelCase       :    str		      =      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:
             UpperCamelCase       :    Optional[Any]		      =      self.feature_extractor(__lowerCamelCase,     *__lowerCamelCase,     sampling_rate=__lowerCamelCase,     **__lowerCamelCase			)
          if text is not None:
             UpperCamelCase       :    List[str]		      =      self.tokenizer(__lowerCamelCase,     **__lowerCamelCase			)

          if text is None:
             return inputs

          elif audio is None:
             return encodings
          else:
             UpperCamelCase       :    List[str]		      =      encodings['''input_ids''']
             return inputs
       def    snake_case_			(     self,     *SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_			)	->						Optional[Any]:
          return self.tokenizer.batch_decode(*__lowerCamelCase,     **__lowerCamelCase			)
       def    snake_case_			(     self,     *SCREAMING_SNAKE_CASE_,     **SCREAMING_SNAKE_CASE_			)	->						int:
          return self.tokenizer.decode(*__lowerCamelCase,     **__lowerCamelCase			)






       def    snake_case_			(     self,     SCREAMING_SNAKE_CASE_,     SCREAMING_SNAKE_CASE_="np"			)	->						List[Any]:
          return self.tokenizer.get_prompt_ids(__lowerCamelCase,     return_tensors=__lowerCamelCase			)










"""simple docstring"""



def 						__lowercase	(  snake_case_    :    int = 2000000		)  ->int:



    '''simple docstring'''







    __A       :		List[Any]							=	[0 for i in range(n + 1		)]
    __A       :		str							=	1
    __A       :		Dict							=	1

    for i in range(2							,int(n**0.5		) + 1		):
        if primality_list[i] == 0:
            for j in range(i * i							,n + 1							,snake_case_		):
                __A       :		List[Any]							=	1
    __A       :		Union[str, Any]							=	0
    for i in range(snake_case_		):
        if primality_list[i] == 0:
            sum_of_primes += i
    return sum_of_primes


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




