






'''simple docstring'''





import math
def __UpperCAmelCase   (					A					:			int		)    ->   Any:
			UpperCAmelCase_      :       List[Any]          =       [True] * n
			UpperCAmelCase_      :       Dict          =       False
			UpperCAmelCase_      :       Optional[Any]          =       False
			UpperCAmelCase_      :       Any          =       True

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

			UpperCAmelCase_      :       str          =       [2]

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

			return primes
def __UpperCAmelCase   (					A					:			int = 9_9_9_9_6_6_6_6_3_3_3_3		)    ->   List[str]:
			UpperCAmelCase_      :       Optional[Any]          =       math.floor(math.sqrt(_SCREAMING_SNAKE_CASE		)		) + 1_0_0
			UpperCAmelCase_      :       Tuple          =       prime_sieve(_SCREAMING_SNAKE_CASE		)

			UpperCAmelCase_      :       Optional[int]          =       0
			UpperCAmelCase_      :       Optional[Any]          =       0
			UpperCAmelCase_      :       List[str]          =       primes[prime_index]

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

						UpperCAmelCase_      :       List[Any]          =       last_prime**2
						UpperCAmelCase_      :       Any          =       next_prime**2

						# Get numbers divisible by lps(current)
						UpperCAmelCase_      :       int          =       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)
						UpperCAmelCase_      :       Any          =       upper_bound - next_prime
						while current > lower_bound:
									matches_sum += current
									current -= next_prime

						# Remove the numbers divisible by both ups and lps
						UpperCAmelCase_      :       Union[str, Any]          =       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
						UpperCAmelCase_      :       Optional[Any]          =       next_prime
						prime_index += 1

			return matches_sum


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






'''simple docstring'''





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


UpperCAmelCase__  			=				logging.get_logger(__name__)

UpperCAmelCase__  			=				{
    '''facebook/xlm-roberta-xl''': '''https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json''',
    '''facebook/xlm-roberta-xxl''': '''https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json''',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}
class 						a__					(					a_   ):





			'''simple docstring'''

			A						:				Tuple					      =			'''xlm-roberta-xl'''
			def __init__(  self							:			Union[str, Any]			,    lowerCAmelCase_							:			Tuple=250_880			,    lowerCAmelCase_							:			Optional[int]=2_560			,    lowerCAmelCase_							:			Optional[Any]=36			,    lowerCAmelCase_							:			List[str]=32			,    lowerCAmelCase_							:			Optional[Any]=10_240			,    lowerCAmelCase_							:			Union[str, Any]="gelu"			,    lowerCAmelCase_							:			Optional[Any]=0.1			,    lowerCAmelCase_							:			Optional[Any]=0.1			,    lowerCAmelCase_							:			Optional[int]=514			,    lowerCAmelCase_							:			List[str]=1			,    lowerCAmelCase_							:			Optional[Any]=0.02			,    lowerCAmelCase_							:			List[str]=1E-05			,    lowerCAmelCase_							:			int=1			,    lowerCAmelCase_							:			List[str]=0			,    lowerCAmelCase_							:			List[Any]=2			,    lowerCAmelCase_							:			Optional[int]="absolute"			,    lowerCAmelCase_							:			List[Any]=True			,    lowerCAmelCase_							:			Tuple=None			,    **lowerCAmelCase_							:			List[str]			,    )      ->		str:
						super().__init__(pad_token_id=lowerCAmelCase_			,    bos_token_id=lowerCAmelCase_			,    eos_token_id=lowerCAmelCase_			,    **lowerCAmelCase_	)
						__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=	type_vocab_size
						__A=	initializer_range
						__A=	layer_norm_eps
						__A=	position_embedding_type
						__A=	use_cache
						__A=	classifier_dropout


class 						a__					(					a_   ):





			'''simple docstring'''

			@property
			def 					lowerCAmelCase     (  self							:			Optional[int]	)      ->		Mapping[str, Mapping[int, str]]:
						if self.task == "multiple-choice":
									__A=	{0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
									__A=	{0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ('input_ids', dynamic_axis),
						        ('attention_mask', dynamic_axis),
						    ]	)



