


import math
def      _a					( SCREAMING_SNAKE_CASE	):


		"""simple docstring"""




		lowercase__				= []
		lowercase__				= 2
		lowercase__				= int(math.sqrt(SCREAMING_SNAKE_CASE	)	)  # Size of every segment
		lowercase__				= [True] * (end + 1)
		lowercase__				= []

		while start <= end:
				if temp[start] is True:
						in_prime.append(SCREAMING_SNAKE_CASE	)
						for i in range(start * start		,							end + 1		,							SCREAMING_SNAKE_CASE	):
								lowercase__				= False
				start += 1
		prime += in_prime

		lowercase__				= end + 1
		lowercase__				= min(2 * end		,							SCREAMING_SNAKE_CASE	)

		while low <= n:
				lowercase__				= [True] * (high - low + 1)
				for each in in_prime:
						lowercase__				= math.floor(low / each	) * each
						if t < low:
								t += each

						for j in range(SCREAMING_SNAKE_CASE		,							high + 1		,							SCREAMING_SNAKE_CASE	):
								lowercase__				= False

				for j in range(len(SCREAMING_SNAKE_CASE	)	):
						if temp[j] is True:
								prime.append(j + low	)

				lowercase__				= high + 1
				lowercase__				= min(high + end		,							SCREAMING_SNAKE_CASE	)

		return prime
print(sieve(10**6))




'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


lowerCAmelCase					:    Optional[Any]           = {
    'configuration_falcon': ['FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FalconConfig'],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						lowerCAmelCase					:    str           = [
						    'FALCON_PRETRAINED_MODEL_ARCHIVE_LIST',
						    'FalconForCausalLM',
						    'FalconModel',
						    'FalconPreTrainedModel',
						    'FalconForSequenceClassification',
						    'FalconForTokenClassification',
						    'FalconForQuestionAnswering',
						]


if TYPE_CHECKING:
						from .configuration_falcon import FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP, FalconConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_falcon import (
												    FALCON_PRETRAINED_MODEL_ARCHIVE_LIST,
												    FalconForCausalLM,
												    FalconForQuestionAnswering,
												    FalconForSequenceClassification,
												    FalconForTokenClassification,
												    FalconModel,
												    FalconPreTrainedModel,
												)


else:
						import sys

						lowerCAmelCase					:    Tuple           = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)




