


'''simple docstring'''




def   _a		(lowercase__			:   int = 3							,   lowercase__			:   int = 7							,   lowercase__			:   int = 1_0_0_0_0_0_0						)			->			int:






     """simple docstring"""
     __snake_case           =						0
     __snake_case           =						1

     for current_denominator in range(1							,   limit + 1						):
          __snake_case           =						current_denominator * numerator // denominator
          if current_denominator % denominator == 0:
               current_numerator -= 1
          if current_numerator * max_denominator > current_denominator * max_numerator:
               __snake_case           =						current_numerator
               __snake_case           =						current_denominator
     return max_numerator


if __name__ == "__main__":
       print(solution(numerator=3, denominator=7, limit=1_000_000))











from ... import PretrainedConfig


__A							:			Optional[Any]         =			{
    "sijunhe/nezha-cn-base": "https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json",
}







class      lowerCamelCase(						__snake_case	):
     '''simple docstring'''


     __magic_name__   =			NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
     __magic_name__   =			'nezha'




     def __init__(    self				,     snake_case_=2_1128				,     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_=64				,     snake_case_=2				,     snake_case_=0.02				,     snake_case_=1E-12				,     snake_case_=0.1				,     snake_case_=0				,     snake_case_=2				,     snake_case_=3				,     snake_case_=True				,     **snake_case_				,     ):
         super().__init__(pad_token_id=snake_case_				,     bos_token_id=snake_case_				,     eos_token_id=snake_case_				,     **snake_case_							)

         _A     =							vocab_size
         _A     =							hidden_size
         _A     =							num_hidden_layers
         _A     =							num_attention_heads
         _A     =							hidden_act
         _A     =							intermediate_size
         _A     =							hidden_dropout_prob
         _A     =							attention_probs_dropout_prob
         _A     =							max_position_embeddings
         _A     =							max_relative_position
         _A     =							type_vocab_size
         _A     =							initializer_range
         _A     =							layer_norm_eps
         _A     =							classifier_dropout
         _A     =							use_cache





