




import itertools
import math



def 					UpperCAmelCase__     (   lowerCamelCase      ):

  if 1 < number < 4:
    # 2 and 3 are primes
    return True
  elif number < 2 or number % 2 == 0 or number % 3 == 0:
    # Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
    return False

  # All primes number are in format of 6k +/- 1
  for i in range(5,	int(math.sqrt(lowerCamelCase      ) + 1      ),	6      ):
    if number % i == 0 or number % (i + 2) == 0:
      return False
  return True



def 					UpperCAmelCase__     (   ):
  lowercase			:Union[str, Any]							=  2
  while True:
    if is_prime(lowerCamelCase      ):
      yield num
    num += 1



def 					UpperCAmelCase__     (   lowerCamelCase = 10001      ):
  return next(itertools.islice(prime_generator(),	nth - 1,	lowerCamelCase      )      )


if __name__ == "__main__":
     print(f'''{solution() = }''')









from typing import TYPE_CHECKING

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


_UpperCAmelCase		:  int	=   {"configuration_swin": ["SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP", "SwinConfig", "SwinOnnxConfig"]}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  List[str]	=   [
         "SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "SwinForImageClassification",
         "SwinForMaskedImageModeling",
         "SwinModel",
         "SwinPreTrainedModel",
         "SwinBackbone",
     ]

try:
     if not is_tf_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCAmelCase		:  int	=   [
         "TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST",
         "TFSwinForImageClassification",
         "TFSwinForMaskedImageModeling",
         "TFSwinModel",
         "TFSwinPreTrainedModel",
     ]

if TYPE_CHECKING:
     from .configuration_swin import SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinConfig, SwinOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_swin import (
              SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwinBackbone,
              SwinForImageClassification,
              SwinForMaskedImageModeling,
              SwinModel,
              SwinPreTrainedModel,
          )

     try:
          if not is_tf_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_tf_swin import (
              TF_SWIN_PRETRAINED_MODEL_ARCHIVE_LIST,
              TFSwinForImageClassification,
              TFSwinForMaskedImageModeling,
              TFSwinModel,
              TFSwinPreTrainedModel,
          )

else:
     import sys

     _UpperCAmelCase		:  int	=   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



