





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







class 			__A       (      __A  ):




      """simple docstring"""







      UpperCAmelCase__						=      """ClapFeatureExtractor"""
      UpperCAmelCase__						=      ("""RobertaTokenizer""", """RobertaTokenizerFast""")


      def __init__(		self      ,							a__      ,							a__):



             """simple docstring"""





             super().__init__(UpperCamelCase__      ,							UpperCamelCase__)


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



             """simple docstring"""





             _lowerCamelCase							:     List[Any]	=		kwargs.pop('''sampling_rate'''      ,							UpperCamelCase__)

             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							:     Optional[int]	=		self.tokenizer(UpperCamelCase__      ,							return_tensors=UpperCamelCase__      ,							**UpperCamelCase__)

             if audios is not None:
                    _lowerCamelCase							:     Optional[Any]	=		self.feature_extractor(
                        UpperCamelCase__      ,							sampling_rate=UpperCamelCase__      ,							return_tensors=UpperCamelCase__      ,							**UpperCamelCase__)

             if text is not None and audios is not None:
                    _lowerCamelCase							:     Dict	=		audio_features.input_features
                    return encoding
             elif text is not None:
                    return encoding
             else:
                    return BatchEncoding(data=dict(**UpperCamelCase__)      ,							tensor_type=UpperCamelCase__)


      def 				__snake_case			(		self      ,							*a__      ,							**a__):



             """simple docstring"""





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


      def 				__snake_case			(		self      ,							*a__      ,							**a__):



             """simple docstring"""





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



      @property
      def 				__snake_case			(		self):



             """simple docstring"""





             _lowerCamelCase							:     Dict	=		self.tokenizer.model_input_names
             _lowerCamelCase							:     Union[str, Any]	=		self.feature_extractor.model_input_names
             return list(dict.fromkeys(tokenizer_input_names + feature_extractor_input_names))








import math




def    __UpperCAmelCase(      lowercase_ ,    lowercase_      ):
       _lowerCamelCase							:     List[str]	=		len(lowercase_      )
       _lowerCamelCase							:     Optional[int]	=		int(math.floor(math.sqrt(lowercase_      )      )      )
       _lowerCamelCase							:     Tuple	=		0
       while arr[min(lowercase_ ,    lowercase_      ) - 1] < x:
              _lowerCamelCase							:     Optional[Any]	=		step
              step += int(math.floor(math.sqrt(lowercase_      )      )      )
              if prev >= n:
                     return -1

       while arr[prev] < x:
              _lowerCamelCase							:     int	=		prev + 1
              if prev == min(lowercase_ ,    lowercase_      ):
                     return -1
       if arr[prev] == x:
              return prev
       return -1


if __name__ == "__main__":
       _lowerCamelCase			       =      input('Enter numbers separated by a comma:\n').strip()
       _lowerCamelCase			       =      [int(item) for item in user_input.split(',')]
       _lowerCamelCase			       =      int(input('Enter the number to be searched:\n'))
       _lowerCamelCase			       =      jump_search(arr, x)
       if res == -1:
              print('Number not found!')
       else:
              print(F'''Number {x} is at index {res}''')

