


'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding




class      lowerCamelCase_  (      __a ):
      lowerCAmelCase__							=	'ClapFeatureExtractor'
      lowerCAmelCase__							=	('RobertaTokenizer', 'RobertaTokenizerFast')






      def __init__(   self							:       Optional[Any]		,		_A							:       Dict		,		_A							:       int					):


          '''simple docstring'''


          super().__init__(_A		,		_A					)






      def __call__(   self							:       Union[str, Any]		,		_A							:       Dict=None		,		_A							:       Union[str, Any]=None		,		_A							:       Union[str, Any]=None		,		**_A							:       Union[str, Any]					):


          '''simple docstring'''


          UpperCAmelCase__     :						str						=							kwargs.pop('''sampling_rate'''		,		_A					)

          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:
              UpperCAmelCase__     :						Union[str, Any]						=							self.tokenizer(_A		,		return_tensors=_A		,		**_A					)

          if audios is not None:
              UpperCAmelCase__     :						str						=							self.feature_extractor(
                  _A		,		sampling_rate=_A		,		return_tensors=_A		,		**_A					)

          if text is not None and audios is not None:
              UpperCAmelCase__     :						Optional[Any]						=							audio_features.input_features
              return encoding
          elif text is not None:
              return encoding
          else:
              return BatchEncoding(data=dict(**_A					)		,		tensor_type=_A					)






      def lowercase_				(   self							:       Tuple		,		*_A							:       Tuple		,		**_A							:       Union[str, Any]					):


          '''simple docstring'''


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






      def lowercase_				(   self							:       Dict		,		*_A							:       Optional[Any]		,		**_A							:       Tuple					):


          '''simple docstring'''


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






      @property
      def lowercase_				(   self							:       str					):


          '''simple docstring'''


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


def  __lowerCamelCase					( _lowercase			)       ->      str:
     return "".join(chr(ord(_lowercase			) - 32			) if 'a' <= char <= 'z' else char for char in word			)


if __name__ == "__main__":
 from doctest import testmod

 testmod()


