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


lowercase  : Optional[int]						   =							logging.get_logger(__name__)

lowercase  : str						   =							{
    """SCUT-DLVCLab/lilt-roberta-en-base""": (
        """https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/config.json"""
    ),
}

class __snake_case		(				lowerCAmelCase					):
    _a		:						Optional[int]=    "lilt"
    def __init__(  self		,snake_case=30522		,snake_case=768		,snake_case=12		,snake_case=12		,snake_case=3072		,snake_case="gelu"		,snake_case=0.1		,snake_case=0.1		,snake_case=512		,snake_case=2		,snake_case=0.02		,snake_case=1e-12		,snake_case=0		,snake_case="absolute"		,snake_case=None		,snake_case=4		,snake_case=1024		,**snake_case		,):



           '''simple docstring'''







           super().__init__(pad_token_id=snake_case		,**snake_case				)

           lowercase							:					str	     =				vocab_size
           lowercase							:					Tuple	     =				hidden_size
           lowercase							:					int	     =				num_hidden_layers
           lowercase							:					Optional[Any]	     =				num_attention_heads
           lowercase							:					Tuple	     =				hidden_act
           lowercase							:					List[str]	     =				intermediate_size
           lowercase							:					List[str]	     =				hidden_dropout_prob
           lowercase							:					Optional[Any]	     =				attention_probs_dropout_prob
           lowercase							:					List[str]	     =				max_position_embeddings
           lowercase							:					Dict	     =				type_vocab_size
           lowercase							:					Any	     =				initializer_range
           lowercase							:					str	     =				layer_norm_eps
           lowercase							:					Optional[Any]	     =				position_embedding_type
           lowercase							:					List[str]	     =				classifier_dropout
           lowercase							:					List[str]	     =				channel_shrink_ratio
           lowercase							:					Optional[Any]	     =				max_ad_position_embeddings


from collections.abc import Generator







def 						_snake_case(  )			->   Generator[int, None, None]:
       lowercase     ,      lowercase							:					List[str]	     =				0, 1
       while True:
              lowercase     ,      lowercase							:					Optional[int]	     =				b, a + b
              yield b







def 						_snake_case(  SCREAMING_SNAKE_CASE__ = 1_000    )			->   int:
       lowercase							:					List[Any]	     =				1
       lowercase							:					Tuple	     =				fibonacci_generator()
       while len(str(next(SCREAMING_SNAKE_CASE__    )    )    ) < n:
              answer += 1
       return answer + 1


if __name__ == "__main__":
  print(solution(int(str(input()).strip())))
