


"""simple docstring"""






from ...processing_utils import ProcessorMixin


class     __lowerCamelCase  (					UpperCamelCase_				):

     '''simple docstring'''
     A_       :	Optional[int]    =		'WhisperFeatureExtractor'
     A_       :	List[str]    =		'WhisperTokenizer'


     def __init__(      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase							)       ->							Tuple:
          super().__init__(__a    ,				__a							)
          _a    	=				self.feature_extractor
          _a    	=				False


     def 							_UpperCAmelCase      (      self    ,				__UpperCAmelCase=None    ,				__UpperCAmelCase=None    ,				__UpperCAmelCase=True							)       ->							List[Any]:
          return self.tokenizer.get_decoder_prompt_ids(task=__a    ,				language=__a    ,				no_timestamps=__a							)


     def __call__(      self    ,				*__UpperCAmelCase    ,				**__UpperCAmelCase							)       ->							List[str]:






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

          _a    	=				kwargs.pop('''audio'''    ,				__a							)
          _a    	=				kwargs.pop('''sampling_rate'''    ,				__a							)
          _a    	=				kwargs.pop('''text'''    ,				__a							)
          if len(__a							) > 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(__a    ,				*__a    ,				sampling_rate=__a    ,				**__a							)
          if text is not None:
               _a    	=				self.tokenizer(__a    ,				**__a							)

          if text is None:
               return inputs

          elif audio is None:
               return encodings
          else:
               _a    	=				encodings['input_ids']
               return inputs


     def 							_UpperCAmelCase      (      self    ,				*__UpperCAmelCase    ,				**__UpperCAmelCase							)       ->							str:
          return self.tokenizer.batch_decode(*__a    ,				**__a							)


     def 							_UpperCAmelCase      (      self    ,				*__UpperCAmelCase    ,				**__UpperCAmelCase							)       ->							Any:
          return self.tokenizer.decode(*__a    ,				**__a							)





     def 							_UpperCAmelCase      (      self    ,				__UpperCAmelCase    ,				__UpperCAmelCase="np"							)       ->							Union[str, Any]:
          return self.tokenizer.get_prompt_ids(__a    ,				return_tensors=__a							)



"""simple docstring"""






def       A_   (   _lowerCAmelCase     :					Dict=2_81_23       ):






     """simple docstring"""

     _a    	=				[1] * (limit + 1)

     for i in range(2,     int(limit**0.5       ) + 1       ):
          sum_divs[i * i] += i
          for k in range(i + 1,     limit // i + 1       ):
               sum_divs[k * i] += k + i

     _a    	=				set()
     _a    	=				0

     for n in range(1,     limit + 1       ):
          if sum_divs[n] > n:
               abundants.add(_lowerCAmelCase       )

          if not any((n - a in abundants) for a in abundants       ):
               res += n

     return res


if __name__ == "__main__":
   print(solution())