


'''simple docstring'''



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


__UpperCAmelCase     :Union[str, Any]												=  logging.get_logger(__name__)

__UpperCAmelCase     :List[Any]												=  {
    "tau/splinter-base": "https://huggingface.co/tau/splinter-base/resolve/main/config.json",
    "tau/splinter-base-qass": "https://huggingface.co/tau/splinter-base-qass/resolve/main/config.json",
    "tau/splinter-large": "https://huggingface.co/tau/splinter-large/resolve/main/config.json",
    "tau/splinter-large-qass": "https://huggingface.co/tau/splinter-large-qass/resolve/main/config.json",
    # See all Splinter models at https://huggingface.co/models?filter=splinter
}



class       a							(						_a			):


     """simple docstring"""






     SCREAMING_SNAKE_CASE			:					Optional[int]				  =  "splinter"

     def __init__(							self	:						Tuple				,					snake_case	:						Tuple=3_0522				,					snake_case	:						Optional[int]=768				,					snake_case	:						List[str]=12				,					snake_case	:						Tuple=12				,					snake_case	:						int=3072				,					snake_case	:						List[Any]="gelu"				,					snake_case	:						int=0.1				,					snake_case	:						Any=0.1				,					snake_case	:						Tuple=512				,					snake_case	:						int=2				,					snake_case	:						Dict=0.02				,					snake_case	:						int=1E-12				,					snake_case	:						Any=True				,					snake_case	:						Dict=0				,					snake_case	:						Optional[int]=104				,					**snake_case	:						Any				,					)		->				Any:
          super().__init__(pad_token_id=snake_case				,					**snake_case     )

          __UpperCAmelCase      :					str    				=     vocab_size
          __UpperCAmelCase      :					int    				=     max_position_embeddings
          __UpperCAmelCase      :					List[str]    				=     hidden_size
          __UpperCAmelCase      :					Any    				=     num_hidden_layers
          __UpperCAmelCase      :					Optional[int]    				=     num_attention_heads
          __UpperCAmelCase      :					Dict    				=     intermediate_size
          __UpperCAmelCase      :					Optional[Any]    				=     hidden_act
          __UpperCAmelCase      :					Union[str, Any]    				=     hidden_dropout_prob
          __UpperCAmelCase      :					List[str]    				=     attention_probs_dropout_prob
          __UpperCAmelCase      :					Any    				=     initializer_range
          __UpperCAmelCase      :					Optional[int]    				=     type_vocab_size
          __UpperCAmelCase      :					Any    				=     layer_norm_eps
          __UpperCAmelCase      :					Union[str, Any]    				=     use_cache
          __UpperCAmelCase      :					Tuple    				=     question_token_id



'''simple docstring'''



import math
from decimal import Decimal, getcontext




def       _a      (		_lowercase   :      int = 4000000    ):





     '''simple docstring'''






     try:
          __UpperCAmelCase      :					List[str]    				=     int(_lowercase    )
     except (TypeError, ValueError):
          raise TypeError('''Parameter n must be int or castable to int.'''    )
     if n <= 0:
          raise ValueError('''Parameter n must be greater than or equal to one.'''    )
     __UpperCAmelCase      :					Tuple    				=     100
     __UpperCAmelCase      :					Optional[Any]    				=     (Decimal(5    ) ** Decimal(0.5    ) + 1) / Decimal(2    )

     __UpperCAmelCase      :					Tuple    				=     (math.floor(math.log(n * (phi + 2)     ,   _lowercase    ) - 1    ) // 3) * 3 + 2
     __UpperCAmelCase      :					List[Any]    				=     Decimal(round(phi ** Decimal(index + 1    )    )    ) / (phi + 2)
     __UpperCAmelCase      :					List[str]    				=     num // 2
     return int(_lowercase    )


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