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




class  __magic_name__  (		snake_case_    ):





   """simple docstring"""




   lowerCAmelCase      :    Optional[Any]  			=   """ClapFeatureExtractor"""
   lowerCAmelCase      :    Any  			=   ("""RobertaTokenizer""", """RobertaTokenizerFast""")



   def __init__(	self					:  str		,  _lowercase					:  Optional[int]		,  _lowercase					:  str							):



    """simple docstring"""



    super().__init__(_lowercase		,  _lowercase							)



   def __call__(	self					:  Optional[int]		,  _lowercase					:  str=None		,  _lowercase					:  Optional[Any]=None		,  _lowercase					:  Dict=None		,  **_lowercase					:  Tuple							):



    """simple docstring"""



    _UpperCamelCase:     Dict							= kwargs.pop('''sampling_rate'''		,  _lowercase							)

    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:     int							= self.tokenizer(_lowercase		,  return_tensors=_lowercase		,  **_lowercase							)

    if audios is not None:
     _UpperCamelCase:     List[str]							= self.feature_extractor(
         _lowercase		,  sampling_rate=_lowercase		,  return_tensors=_lowercase		,  **_lowercase							)

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



   def   lowerCAmelCase						(	self					:  List[Any]		,  *_lowercase					:  Optional[Any]		,  **_lowercase					:  Tuple							):



    """simple docstring"""



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



   def   lowerCAmelCase						(	self					:  Optional[Any]		,  *_lowercase					:  Union[str, Any]		,  **_lowercase					:  Union[str, Any]							):



    """simple docstring"""



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



   @property
   def   lowerCAmelCase						(	self					:  Dict							):



    """simple docstring"""



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

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


UpperCAmelCase_			    =							logging.get_logger(__name__)




class  __magic_name__  (		__a    ):





   """simple docstring"""




   def __init__(	self					:  str		,  *_lowercase					:  str		,  **_lowercase					:  int							):



    """simple docstring"""



    warnings.warn(
        '''The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers.'''
        ''' Please use PerceiverImageProcessor instead.'''		,  _lowercase		,  )
    super().__init__(*_lowercase		,  **_lowercase							)