






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





def   SCREAMING_SNAKE_CASE__						(   snake_case_  )   ->  list[int]:


 """simple docstring"""



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

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

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

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


if __name__ == "__main__":
    import doctest

    doctest.testmod()













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


UpperCamelCase__						:      int								=					{
    """configuration_fsmt""": ["""FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FSMTConfig"""],
    """tokenization_fsmt""": ["""FSMTTokenizer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				UpperCamelCase__						:      Any								=					["""FSMTForConditionalGeneration""", """FSMTModel""", """PretrainedFSMTModel"""]


if TYPE_CHECKING:
				from .configuration_fsmt import FSMT_PRETRAINED_CONFIG_ARCHIVE_MAP, FSMTConfig
				from .tokenization_fsmt import FSMTTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_fsmt import FSMTForConditionalGeneration, FSMTModel, PretrainedFSMTModel

else:
				import sys

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





