
'''simple docstring'''
def 							A_  (    __SCREAMING_SNAKE_CASE    :	Union[str, Any] = 30			)					->							int:





  """simple docstring"""

  __A		:  Dict       				=		exponent + 2
  __A		:  List[Any]       				=		(1 + 5**0.5) / 2
  __A		:  Any       				=		(phi**fibonacci_index - (phi - 1) ** fibonacci_index) / 5**0.5

  return int(__lowerCamelCase			)


if __name__ == "__main__":
     print(F"{solution() = }")







import copy

from transformers.configuration_utils import PretrainedConfig
from transformers.utils import logging


a					:				Optional[Any]       =      logging.get_logger(__name__)

class   lowerCamelCase						(	SCREAMING_SNAKE_CASE  ):
       _UpperCamelCase     		=   """hybrid-clip"""
       _UpperCamelCase     		=   True

       def __init__(      self						,    a__=5_12						,    **a__       ):






        '''simple docstring'''






        super().__init__(**a__       )

        if "text_config" not in kwargs:
         raise ValueError('''`text_config` can not be `None`.'''       )

        if "vision_config" not in kwargs:
         raise ValueError('''`vision_config` can not be `None`.'''       )

        snake_case :			int							=   kwargs.pop('''text_config'''       )
        snake_case :			Optional[int]							=   kwargs.pop('''vision_config'''       )

        snake_case :			Optional[Any]							=   text_config.pop('''model_type'''       )
        snake_case :			str							=   vision_config.pop('''model_type'''       )

        from transformers import AutoConfig

        snake_case :			List[Any]							=   AutoConfig.for_model(a__						,    **a__       )

        if vision_model_type == "clip":
         snake_case :			Dict							=   AutoConfig.for_model(a__						,    **a__       ).vision_config
        elif vision_model_type == "clip_vision_model":
         from transformers import CLIPVisionConfig

         snake_case :			str							=   CLIPVisionConfig(**a__       )
        else:
         snake_case :			Any							=   AutoConfig.for_model(a__						,    **a__       )

        snake_case :			Optional[Any]							=   projection_dim
        snake_case :			int							=   1.0

       @classmethod
       def 					UpperCAmelCase					(      cls						,    a__						,    a__						,    **a__       ):






        '''simple docstring'''






        return cls(text_config=text_config.to_dict()						,    vision_config=vision_config.to_dict()						,    **a__       )



       def 					UpperCAmelCase					(      self       ):






        '''simple docstring'''






        snake_case :			Dict							=   copy.deepcopy(self.__dict__       )
        snake_case :			Dict							=   self.text_config.to_dict()
        snake_case :			int							=   self.vision_config.to_dict()
        snake_case :			List[Any]							=   self.__class__.model_type
        return output






