

import warnings

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





class  __UpperCAmelCase					(	lowerCamelCase__						):
   UpperCamelCase       					=					["""image_processor""", """tokenizer"""]
   UpperCamelCase       					=					"""CLIPImageProcessor"""
   UpperCamelCase       					=					("""CLIPTokenizer""", """CLIPTokenizerFast""")



   def __init__(							self							:					Optional[Any],		__A							:					Tuple=None,		__A							:					List[Any]=None,		**__A							:					List[Any]						):
     UpperCAmelCase	:							Optional[int]						=			None
     if "feature_extractor" in kwargs:
       warnings.warn(
           '''The `feature_extractor` argument is deprecated and will be removed in v5, use `image_processor`'''
           ''' instead.''',		snake_case__,		)
       UpperCAmelCase	:							int						=			kwargs.pop('''feature_extractor'''						)

     UpperCAmelCase	:							Tuple						=			image_processor if image_processor is not None else feature_extractor
     if image_processor is None:
       raise ValueError('''You need to specify an `image_processor`.'''						)
     if tokenizer is None:
       raise ValueError('''You need to specify a `tokenizer`.'''						)

     super().__init__(snake_case__,		snake_case__						)



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





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

     if text is not None:
       UpperCAmelCase	:							List[Any]						=			self.tokenizer(snake_case__,		return_tensors=snake_case__,		**snake_case__						)

     if images is not None:
       UpperCAmelCase	:							Tuple						=			self.image_processor(snake_case__,		return_tensors=snake_case__,		**snake_case__						)

     if text is not None and images is not None:
       UpperCAmelCase	:							List[Any]						=			image_features.pixel_values
       return encoding
     elif text is not None:
       return encoding
     else:
       return BatchEncoding(data=dict(**snake_case__						),		tensor_type=snake_case__						)



   def 	__magic_name__   (							self							:					Dict,		*__A							:					int,		**__A							:					Optional[int]						):
     return self.tokenizer.batch_decode(*snake_case__,		**snake_case__						)



   def 	__magic_name__   (							self							:					Union[str, Any],		*__A							:					Tuple,		**__A							:					List[str]						):
     return self.tokenizer.decode(*snake_case__,		**snake_case__						)



   @property
   def 	__magic_name__   (							self							:					Optional[int]						):
     UpperCAmelCase	:							List[str]						=			self.tokenizer.model_input_names
     UpperCAmelCase	:							Union[str, Any]						=			self.image_processor.model_input_names
     return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)



   @property
   def 	__magic_name__   (							self							:					Union[str, Any]						):
     warnings.warn(
         '''`feature_extractor_class` is deprecated and will be removed in v5. Use `image_processor_class` instead.''',		snake_case__,		)
     return self.image_processor_class





   @property
   def 	__magic_name__   (							self							:					List[str]						):
     warnings.warn(
         '''`feature_extractor` is deprecated and will be removed in v5. Use `image_processor` instead.''',		snake_case__,		)
     return self.image_processor








def       a__					(		UpperCAmelCase							:      int    ,			UpperCAmelCase							:      int      )  ->						str:
  if a < 0 or b < 0:
    raise ValueError('''the value of both inputs must be positive'''      )
  UpperCAmelCase	:							List[Any]						=			str(bin(UpperCAmelCase      )      )[2:]  # remove the leading "0b"
  UpperCAmelCase	:							List[str]						=			str(bin(UpperCAmelCase      )      )[2:]
  UpperCAmelCase	:							Optional[Any]						=			max(len(UpperCAmelCase      )    ,			len(UpperCAmelCase      )      )
  return "0b" + "".join(
      str(int('''1''' in (char_a, char_b)      )      )
      for char_a, char_b in zip(a_binary.zfill(UpperCAmelCase      )    ,			b_binary.zfill(UpperCAmelCase      )      )      )


if __name__ == "__main__":
     import doctest

     doctest.testmod()





