





def    __UpperCamelCase	(	a    : int     ) ->list:
 snake_case				=			int(a     )
 if n_element < 1:
  snake_case				=			ValueError('''a should be a positive number'''     )
  raise my_error

 snake_case				=			[1]
 snake_case				,		snake_case				,		snake_case				=			(0, 0, 0)
 snake_case				=			1
 while index < n_element:
  while hamming_list[i] * 2 <= hamming_list[-1]:
   i += 1
  while hamming_list[j] * 3 <= hamming_list[-1]:
   j += 1
  while hamming_list[k] * 5 <= hamming_list[-1]:
   k += 1
  hamming_list.append(
      min(hamming_list[i] * 2					,   hamming_list[j] * 3					,   hamming_list[k] * 5     )     )
  index += 1
 return hamming_list


if __name__ == "__main__":
   _lowercase       						=			input('Enter the last number (nth term) of the Hamming Number Series: ')
   print('Formula of Hamming Number Series => 2^i * 3^j * 5^k')
   _lowercase       						=			hamming(int(n))
   print('-----------------------------------------------------')
   print(f'The list with nth numbers is: {hamming_numbers}')
   print('-----------------------------------------------------')








'''simple docstring'''







from ...processing_utils import ProcessorMixin
class 			_lowercase						(       __a					):
     _UpperCAmelCase										=					'''WhisperFeatureExtractor'''
     _UpperCAmelCase										=					'''WhisperTokenizer'''







     def __init__( self    ,   A__    ,   A__    ) ->	Optional[Any]:
      super().__init__(A__    ,   A__    )
      snake_case				=			self.feature_extractor
      snake_case				=			False







     def     UpperCamelCase			( self    ,   A__=None    ,   A__=None    ,   A__=True    ) ->	Union[str, Any]:
      return self.tokenizer.get_decoder_prompt_ids(task=A__    ,   language=A__    ,   no_timestamps=A__    )







     def __call__( self    ,   *A__    ,   **A__    ) ->	Dict:
      # For backward compatibility
      if self._in_target_context_manager:
       return self.current_processor(*A__    ,   **A__    )

      snake_case				=			kwargs.pop('''audio'''    ,   A__    )
      snake_case				=			kwargs.pop('''sampling_rate'''    ,   A__    )
      snake_case				=			kwargs.pop('''text'''    ,   A__    )
      if len(A__    ) > 0:
       snake_case				=			args[0]
       snake_case				=			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:
       snake_case				=			self.feature_extractor(A__    ,   *A__    ,   sampling_rate=A__    ,   **A__    )
      if text is not None:
       snake_case				=			self.tokenizer(A__    ,   **A__    )

      if text is None:
       return inputs

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







     def     UpperCamelCase			( self    ,   *A__    ,   **A__    ) ->	Optional[Any]:
      return self.tokenizer.batch_decode(*A__    ,   **A__    )







     def     UpperCamelCase			( self    ,   *A__    ,   **A__    ) ->	str:
      return self.tokenizer.decode(*A__    ,   **A__    )







     def     UpperCamelCase			( self    ,   A__    ,   A__="np"    ) ->	Optional[Any]:
      return self.tokenizer.get_prompt_ids(A__    ,   return_tensors=A__    )

