






import math

def _UpperCAmelCase   (	a						:	int		):

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

def _UpperCAmelCase   (	a						:	int = 1_0001		):

							try:
														snake_case__	  =       int(a		)
							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."""		)
							snake_case__	  =       []
							snake_case__	  =       2
							while len(a		) < nth:
														if is_prime(a		):
																					primes.append(a		)
																					num += 1
														else:
																					num += 1
							return primes[len(a		) - 1]


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








from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__       =     {
    """configuration_autoformer""": [
        """AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AutoformerConfig""",
    ],
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	a__       =     [
	    """AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """AutoformerForPrediction""",
	    """AutoformerModel""",
	    """AutoformerPreTrainedModel""",
	]


if TYPE_CHECKING:
	from .configuration_autoformer import (
	    AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    AutoformerConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_autoformer import (
		    AUTOFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
		    AutoformerForPrediction,
		    AutoformerModel,
		    AutoformerPreTrainedModel,
		)

else:
	import sys

	a__       =     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)
