

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


class      a__						(							lowerCamelCase_						):
   _SCREAMING_SNAKE_CASE					:  List[Any]			 =							['image_processor', 'tokenizer']
   _SCREAMING_SNAKE_CASE					:  Optional[int]			 =							'EfficientNetImageProcessor'
   _SCREAMING_SNAKE_CASE					:  Union[str, Any]			 =							('BertTokenizer', 'BertTokenizerFast')


   def __init__(				self    ,       _UpperCamelCase    ,       _UpperCamelCase						):





      """simple docstring"""





      super().__init__(_UpperCamelCase    ,       _UpperCamelCase						)


   def __call__(				self    ,       _UpperCamelCase=None    ,       _UpperCamelCase=None    ,       _UpperCamelCase="max_length"    ,       _UpperCamelCase=64    ,       _UpperCamelCase=None    ,       **_UpperCamelCase						):





      """simple docstring"""





      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:
         _lowercase    :   Union[str, Any]      =     self.tokenizer(
             _UpperCamelCase    ,       padding=_UpperCamelCase    ,       max_length=_UpperCamelCase    ,       return_tensors=_UpperCamelCase    ,       **_UpperCamelCase						)

      if images is not None:
         _lowercase    :   int      =     self.image_processor(_UpperCamelCase    ,       return_tensors=_UpperCamelCase    ,       **_UpperCamelCase						)

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


   def 		_lowerCamelCase     (				self    ,       *_UpperCamelCase    ,       **_UpperCamelCase						):





      """simple docstring"""





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


   def 		_lowerCamelCase     (				self    ,       *_UpperCamelCase    ,       **_UpperCamelCase						):





      """simple docstring"""





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






   @property
   def 		_lowerCamelCase     (				self						):





      """simple docstring"""





      _lowercase    :   List[Any]      =     self.tokenizer.model_input_names
      _lowercase    :   Union[str, Any]      =     self.image_processor.model_input_names
      return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)









'''simple docstring'''
class      a__						:


   def __init__(				self    ,       _UpperCamelCase						):





      """simple docstring"""





      _lowercase    :   Tuple      =     data
      _lowercase    :   int
      _lowercase    :   Node







def       _A	(			snake_case  )    ->			None:
   _lowercase    :   Any      =     0
   _lowercase    :   str      =     x







def       _A	(			snake_case	,							snake_case  )    ->			None:
   _lowercase  ,   _lowercase    :   Any      =     find_set(snake_case  ), find_set(snake_case  )
   if x == y:
      return

   elif x.rank > y.rank:
      _lowercase    :   Dict      =     x
   else:
      _lowercase    :   Optional[int]      =     y
      if x.rank == y.rank:
         y.rank += 1







def       _A	(			snake_case  )    ->			Node:
   if x != x.parent:
      _lowercase    :   Optional[int]      =     find_set(x.parent  )
   return x.parent







def       _A	(			snake_case  )    ->			set:
   _lowercase    :   Any      =     ({0, 1, 2}, {3, 4, 5})
   for s in sets:
      if node.data in s:
         return s
   _lowercase    :   List[Any]      =     F'''{node.data} is not in {sets}'''
   raise ValueError(snake_case  )







def       _A	(			)    ->			None:
   _lowercase    :   Union[str, Any]      =     [Node(snake_case  ) for i in range(6  )]
   for v in vertex:
      make_set(snake_case  )

   union_set(vertex[0]	,							vertex[1]  )
   union_set(vertex[1]	,							vertex[2]  )
   union_set(vertex[3]	,							vertex[4]  )
   union_set(vertex[3]	,							vertex[5]  )

   for nodea in vertex:
      for nodea in vertex:
         if find_python_set(snake_case  ).isdisjoint(find_python_set(snake_case  )  ):
            assert find_set(snake_case  ) != find_set(snake_case  )
         else:
            assert find_set(snake_case  ) == find_set(snake_case  )


if __name__ == "__main__":
    test_disjoint_set()






