
import math






def      _A				(UpperCamelCase		:      Optional[Any] )  ->list:



			'''simple docstring'''







			lowerCamelCase__ :      int								=		[True] * n
			lowerCamelCase__ :      Optional[int]								=		False
			lowerCamelCase__ :      Dict								=		False
			lowerCamelCase__ :      List[Any]								=		True

			for i in range(3      ,			int(n**0.5 + 1 )      ,			2 ):
						lowerCamelCase__ :      Optional[Any]								=		i * 2
						while index < n:
									lowerCamelCase__ :      Union[str, Any]								=		False
									lowerCamelCase__ :      Tuple								=		index + i

			lowerCamelCase__ :      str								=		[2]

			for i in range(3      ,			SCREAMING_SNAKE_CASE_      ,			2 ):
						if is_prime[i]:
									primes.append(SCREAMING_SNAKE_CASE_ )

			return primes






def      _A				(UpperCamelCase		:      Tuple = 999966663333 )  ->int:



			'''simple docstring'''







			lowerCamelCase__ :      Dict								=		math.floor(math.sqrt(SCREAMING_SNAKE_CASE_ ) ) + 100
			lowerCamelCase__ :      Any								=		prime_sieve(SCREAMING_SNAKE_CASE_ )

			lowerCamelCase__ :      int								=		0
			lowerCamelCase__ :      List[Any]								=		0
			lowerCamelCase__ :      Tuple								=		primes[prime_index]

			while (last_prime**2) <= limit:
						lowerCamelCase__ :      str								=		primes[prime_index + 1]

						lowerCamelCase__ :      Union[str, Any]								=		last_prime**2
						lowerCamelCase__ :      Any								=		next_prime**2

						# Get numbers divisible by lps(current)
						lowerCamelCase__ :      Union[str, Any]								=		lower_bound + last_prime
						while upper_bound > current <= limit:
									matches_sum += current
									current += last_prime

						# Reset the upper_bound
						while (upper_bound - next_prime) > limit:
									upper_bound -= next_prime

						# Add the numbers divisible by ups(current)
						lowerCamelCase__ :      str								=		upper_bound - next_prime
						while current > lower_bound:
									matches_sum += current
									current -= next_prime

						# Remove the numbers divisible by both ups and lps
						lowerCamelCase__ :      str								=		0
						while upper_bound > current <= limit:
									if current <= lower_bound:
												# Increment the current number
												current += last_prime * next_prime
												continue

									if current > limit:
												break

									# Remove twice since it was added by both ups and lps
									matches_sum -= current * 2

									# Increment the current number
									current += last_prime * next_prime

						# Setup for next pair
						lowerCamelCase__ :      int								=		next_prime
						prime_index += 1

			return matches_sum


if __name__ == "__main__":
				print(solution())








from ... import PretrainedConfig


_lowercase     							=						{
    '''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class 				__A					( A_      ):
			UpperCamelCase					:Optional[Any]     =			NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
			UpperCamelCase					:int     =			'''nezha'''





			def __init__(self							,    __magic_name__=21128							,    __magic_name__=768							,    __magic_name__=12							,    __magic_name__=12							,    __magic_name__=3072							,    __magic_name__="gelu"							,    __magic_name__=0.1							,    __magic_name__=0.1							,    __magic_name__=512							,    __magic_name__=64							,    __magic_name__=2							,    __magic_name__=0.02							,    __magic_name__=1E-12							,    __magic_name__=0.1							,    __magic_name__=0							,    __magic_name__=2							,    __magic_name__=3							,    __magic_name__=True							,    **__magic_name__							,    ):
						super().__init__(pad_token_id=__magic_name__							,    bos_token_id=__magic_name__							,    eos_token_id=__magic_name__							,    **__magic_name__				)

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



