




from ...processing_utils import ProcessorMixin




class       a__	( UpperCamelCase__				):
     a		:      Union[str, Any]		 =     """WhisperFeatureExtractor"""
     a		:      str		 =     """WhisperTokenizer"""







     def __init__(     self  ,		A  ,		A			)  ->   str:



          '''simple docstring'''



          super().__init__(A  ,		A			)
          a     =				self.feature_extractor
          a     =				False







     def       lowerCAmelCase_    (     self  ,		A=None  ,		A=None  ,		A=True			)  ->   Tuple:



          '''simple docstring'''



          return self.tokenizer.get_decoder_prompt_ids(task=A  ,		language=A  ,		no_timestamps=A			)







     def __call__(     self  ,		*A  ,		**A			)  ->   Dict:



          '''simple docstring'''



          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       lowerCAmelCase_    (     self  ,		*A  ,		**A			)  ->   Dict:



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self  ,		*A  ,		**A			)  ->   Any:



          '''simple docstring'''



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







     def       lowerCAmelCase_    (     self  ,		A  ,		A="np"			)  ->   Dict:



          '''simple docstring'''



          return self.tokenizer.get_prompt_ids(A  ,		return_tensors=A			)







from __future__ import annotations

def  SCREAMING_SNAKE_CASE							(       __UpperCamelCase)      ->					list[int]:
     a     =				2
     a     =				[]
     while i * i <= n:
          if n % i:
               i += 1
          else:
               n //= i
               factors.append(__UpperCamelCase)
     if n > 1:
          factors.append(__UpperCamelCase)
     return factors


if __name__ == "__main__":
   import doctest

   doctest.testmod()

