


"""simple docstring"""







from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding


class       SCREAMING_SNAKE_CASE__				(		lowercase				):
       """simple docstring"""


       a  :				int   ="ClapFeatureExtractor"
       a  :				Dict   =("RobertaTokenizer", "RobertaTokenizerFast")

       def __init__(						self		,     snake_case__		,     snake_case__						):






         """simple docstring"""





         super().__init__(snake_case__		,     snake_case__						)

       def __call__(						self		,     snake_case__=None		,     snake_case__=None		,     snake_case__=None		,     **snake_case__						):






         """simple docstring"""





         lowerCAmelCase     :     Union[str, Any]								=							kwargs.pop("sampling_rate"		,     snake_case__						)

         if text is None and audios is None:
           raise ValueError("You have to specify either text or audios. Both cannot be none."						)

         if text is not None:
           lowerCAmelCase     :     int								=							self.tokenizer(snake_case__		,     return_tensors=snake_case__		,     **snake_case__						)

         if audios is not None:
           lowerCAmelCase     :     Tuple								=							self.feature_extractor(
               snake_case__		,     sampling_rate=snake_case__		,     return_tensors=snake_case__		,     **snake_case__						)

         if text is not None and audios is not None:
           lowerCAmelCase     :     Union[str, Any]								=							audio_features.input_features
           return encoding
         elif text is not None:
           return encoding
         else:
           return BatchEncoding(data=dict(**snake_case__						)		,     tensor_type=snake_case__						)

       def        lowercase__							(						self		,     *snake_case__		,     **snake_case__						):






         """simple docstring"""





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

       def        lowercase__							(						self		,     *snake_case__		,     **snake_case__						):






         """simple docstring"""





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







       @property
       def        lowercase__							(						self						):






         """simple docstring"""





         lowerCAmelCase     :     List[Any]								=							self.tokenizer.model_input_names
         lowerCAmelCase     :     Optional[int]								=							self.feature_extractor.model_input_names
         return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names						)						)









"""simple docstring"""







def 					a__			(				SCREAMING_SNAKE_CASE    :    int				,      SCREAMING_SNAKE_CASE    :    List[Any]				,      SCREAMING_SNAKE_CASE    :    str				,      SCREAMING_SNAKE_CASE    :    List[Any]				):


  '''simple docstring'''







  if height >= 1:
    move_tower(height - 1				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
    move_disk(SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
    move_tower(height - 1				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				SCREAMING_SNAKE_CASE    :    Tuple				,      SCREAMING_SNAKE_CASE    :    Optional[int]				):


  '''simple docstring'''







  print("moving disk from"				,      SCREAMING_SNAKE_CASE				,      "to"				,      SCREAMING_SNAKE_CASE				)
def 					a__			(				):


  '''simple docstring'''







  lowerCAmelCase     :     Optional[int]								=							int(input("Height of hanoi: "				).strip()				)
  move_tower(SCREAMING_SNAKE_CASE				,      "A"				,      "B"				,      "C"				)


if __name__ == "__main__":
     main()





