

'''simple docstring'''

import math
from collections.abc import Generator





def 				A_					(	snake_case	):
  SCREAMING_SNAKE_CASE:Generator   =   (i for i in range(1 ,    (max_n + 1)	))
  for i in (n for n in numbers if n > 1):
    for j in range(2 ,    snake_case	):
      if (i % j) == 0:
        break
    else:
      yield i





def 				A_					(	snake_case	):
  SCREAMING_SNAKE_CASE:Generator   =   (i for i in range(1 ,    (max_n + 1)	))
  for i in (n for n in numbers if n > 1):
    # only need to check for factors up to sqrt(i)
    SCREAMING_SNAKE_CASE:str   =   int(math.sqrt(snake_case	)	) + 1
    for j in range(2 ,    snake_case	):
      if (i % j) == 0:
        break
    else:
      yield i





def 				A_					(	snake_case	):
  SCREAMING_SNAKE_CASE:Generator   =   (i for i in range(1 ,    (max_n + 1) ,    2	))
  # It's useless to test even numbers as they will not be prime
  if max_n > 2:
    yield 2  # Because 2 will not be tested, it's necessary to yield it now
  for i in (n for n in numbers if n > 1):
    SCREAMING_SNAKE_CASE:Any   =   int(math.sqrt(snake_case	)	) + 1
    for j in range(3 ,    snake_case ,    2	):
      # As we removed the even numbers, we don't need them now
      if (i % j) == 0:
        break
    else:
      yield i





def 				A_					(	):
  from timeit import timeit

  SCREAMING_SNAKE_CASE:Union[str, Any]   =   "from __main__ import slow_primes, primes, fast_primes"
  print(timeit("slow_primes(1_000_000_000_000)" ,    setup=snake_case ,    number=1000000	)	)
  print(timeit("primes(1_000_000_000_000)" ,    setup=snake_case ,    number=1000000	)	)
  print(timeit("fast_primes(1_000_000_000_000)" ,    setup=snake_case ,    number=1000000	)	)


if __name__ == "__main__":
    A_      =							int(input("Calculate primes up to:\n>> ").strip())
    for ret in primes(number):
        print(ret)
    benchmark()









'''simple docstring'''

from typing import TYPE_CHECKING

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


A_      =							{"configuration_yoso": ["YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP", "YosoConfig"]}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    A_      =							[
        "YOSO_PRETRAINED_MODEL_ARCHIVE_LIST",
        "YosoForMaskedLM",
        "YosoForMultipleChoice",
        "YosoForQuestionAnswering",
        "YosoForSequenceClassification",
        "YosoForTokenClassification",
        "YosoLayer",
        "YosoModel",
        "YosoPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_yoso import YOSO_PRETRAINED_CONFIG_ARCHIVE_MAP, YosoConfig

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_yoso import (
            YOSO_PRETRAINED_MODEL_ARCHIVE_LIST,
            YosoForMaskedLM,
            YosoForMultipleChoice,
            YosoForQuestionAnswering,
            YosoForSequenceClassification,
            YosoForTokenClassification,
            YosoLayer,
            YosoModel,
            YosoPreTrainedModel,
        )


else:
    import sys

    A_      =							_LazyModule(__name__, globals()["__file__"], _import_structure)






