



import math

def     __lowercase(	UpperCAmelCase__ ):


      """simple docstring"""



      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(UpperCAmelCase__ ) + 1 )   ,   6 ):
            if number % i == 0 or number % (i + 2) == 0:
                  return False
      return True

def     __lowercase(	UpperCAmelCase__ = 10001 ):


      """simple docstring"""



      try:
            lowerCamelCase								=		int(UpperCAmelCase__ )
      except (TypeError, ValueError):
            raise TypeError("Parameter nth must be int or castable to int." ) from None
      if nth <= 0:
            raise ValueError("Parameter nth must be greater than or equal to one." )
      lowerCamelCase								=		[]
      lowerCamelCase								=		2
      while len(UpperCAmelCase__ ) < nth:
            if is_prime(UpperCAmelCase__ ):
                  primes.append(UpperCAmelCase__ )
                  num += 1
            else:
                  num += 1
      return primes[len(UpperCAmelCase__ ) - 1]


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




from typing import TYPE_CHECKING

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


a_						:     int	     =		{'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}


try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     a_						:     Dict	     =		[
         'VAN_PRETRAINED_MODEL_ARCHIVE_LIST',
         'VanForImageClassification',
         'VanModel',
         'VanPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_van import (
              VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
              VanForImageClassification,
              VanModel,
              VanPreTrainedModel,
          )

else:
     import sys

     a_						:     Union[str, Any]	     =		_LazyModule(__name__, globals()['__file__'], _import_structure)