



from __future__ import annotations






def 					__lowerCAmelCase		(  __lowerCamelCase	:    int	)  ->						list[int]:
					__lowerCAmelCase	   =[True] * limit
					__lowerCAmelCase	   =False
					__lowerCAmelCase	   =False
					__lowerCAmelCase	   =True

					for i in range(3				,   int(limit**0.5 + 1	)				,   2	):
										__lowerCAmelCase	   =i * 2
										while index < limit:
															__lowerCAmelCase	   =False
															__lowerCAmelCase	   =index + i

					__lowerCAmelCase	   =[2]

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

					return primes






def 					__lowerCAmelCase		(  __lowerCamelCase	:    int = 1000000	)  ->						int:
					__lowerCAmelCase	   =prime_sieve(__lowerCamelCase	)
					__lowerCAmelCase	   =0
					__lowerCAmelCase	   =0

					for i in range(len(__lowerCamelCase	)	):
										for j in range(i + length				,   len(__lowerCamelCase	)	):
															__lowerCAmelCase	   =sum(primes[i:j]	)
															if sol >= ceiling:
																				break

															if sol in primes:
																				__lowerCAmelCase	   =j - i
																				__lowerCAmelCase	   =sol

					return largest


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









from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowercase_	       =			{
    '''configuration_blip_2''': [
        '''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''Blip2Config''',
        '''Blip2QFormerConfig''',
        '''Blip2VisionConfig''',
    ],
    '''processing_blip_2''': ['''Blip2Processor'''],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    '''BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST''',
				    '''Blip2Model''',
				    '''Blip2QFormerModel''',
				    '''Blip2PreTrainedModel''',
				    '''Blip2ForConditionalGeneration''',
				    '''Blip2VisionModel''',
				]

if TYPE_CHECKING:
				from .configuration_blip_a import (
				    BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    BlipaConfig,
				    BlipaQFormerConfig,
				    BlipaVisionConfig,
				)
				from .processing_blip_a import BlipaProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_blip_a import (
								    BLIP_2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BlipaForConditionalGeneration,
								    BlipaModel,
								    BlipaPreTrainedModel,
								    BlipaQFormerModel,
								    BlipaVisionModel,
								)

else:
				import sys

				lowercase_	       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)




