






import math






def   UpperCamelCase  (       snake_case__     :   int  ):




     '''simple docstring'''






     __snake_case			:Any          =						[]
     __snake_case			:Optional[int]          =						2
     __snake_case			:Union[str, Any]          =						int(math.sqrt(snake_case__  )  )  # Size of every segment
     __snake_case			:Any          =						[True] * (end + 1)
     __snake_case			:Dict          =						[]

     while start <= end:
          if temp[start] is True:
               in_prime.append(snake_case__  )
               for i in range(start * start	,end + 1	,snake_case__  ):
                    __snake_case			:Union[str, Any]          =						False
          start += 1
     prime += in_prime

     __snake_case			:Any          =						end + 1
     __snake_case			:int          =						min(2 * end	,snake_case__  )

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

               for j in range(snake_case__	,high + 1	,snake_case__  ):
                    __snake_case			:str          =						False

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

          __snake_case			:Union[str, Any]          =						high + 1
          __snake_case			:Any          =						min(high + end	,snake_case__  )

     return prime



print(sieve(10**6))










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


lowerCamelCase__							=     {
    """configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
    """tokenization_canine""": ["""CanineTokenizer"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     [
         """CANINE_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """CanineForMultipleChoice""",
         """CanineForQuestionAnswering""",
         """CanineForSequenceClassification""",
         """CanineForTokenClassification""",
         """CanineLayer""",
         """CanineModel""",
         """CaninePreTrainedModel""",
         """load_tf_weights_in_canine""",
     ]


if TYPE_CHECKING:
     from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
     from .tokenization_canine import CanineTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_canine import (
              CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
              CanineForMultipleChoice,
              CanineForQuestionAnswering,
              CanineForSequenceClassification,
              CanineForTokenClassification,
              CanineLayer,
              CanineModel,
              CaninePreTrainedModel,
              load_tf_weights_in_canine,
          )


else:
     import sys

     lowerCamelCase__							=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


