




from itertools import compress, repeat
from math import ceil, sqrt

def      lowerCAmelCase_     (					lowerCamelCase:    int  )   ->     list[int]:


      '''simple docstring'''




      if num <= 2:
            return []
      if num == 3:
            return [2]

      # Odd sieve for numbers in range [3, num - 1]
      lowerCamelCase__ 					=			bytearray(b'\x01'  ) * ((num >> 1) - 1)

      for i in range(3       ,			int(sqrt(lowerCamelCase  )  ) + 1       ,			2  ):
            if sieve[(i >> 1) - 1]:
                  lowerCamelCase__ 					=			i**2
                  lowerCamelCase__ 					=			repeat(
                      0       ,			ceil((num - i_squared) / (i << 1)  )  )

      return [2] + list(compress(range(3       ,			lowerCamelCase       ,			2  )       ,			lowerCamelCase  )  )


if __name__ == "__main__":
      import doctest

      doctest.testmod()





from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__SCREAMING_SNAKE_CASE      :				int				      ={"""configuration_nat""": ["""NAT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NatConfig"""]}


try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __SCREAMING_SNAKE_CASE      :				Optional[int]				      =[
          """NAT_PRETRAINED_MODEL_ARCHIVE_LIST""",
          """NatForImageClassification""",
          """NatModel""",
          """NatPreTrainedModel""",
          """NatBackbone""",
      ]

if TYPE_CHECKING:
      from .configuration_nat import NAT_PRETRAINED_CONFIG_ARCHIVE_MAP, NatConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_nat import (
                NAT_PRETRAINED_MODEL_ARCHIVE_LIST,
                NatBackbone,
                NatForImageClassification,
                NatModel,
                NatPreTrainedModel,
            )

else:
      import sys

      __SCREAMING_SNAKE_CASE      :				Any				      =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)