


"""simple docstring"""
def 						_a				(      _SCREAMING_SNAKE_CASE = 600_851_475_143				)    ->				int:

							try:
														snake_case_           =		int(_SCREAMING_SNAKE_CASE				)
							except (TypeError, ValueError):
														raise TypeError("""Parameter n must be int or castable to int."""				)
							if n <= 0:
														raise ValueError("""Parameter n must be greater than or equal to one."""				)
							snake_case_           =		1
							snake_case_           =		2
							while i * i <= n:
														while n % i == 0:
																					snake_case_           =		i
																					n //= i
														i += 1
							if n > 1:
														snake_case_           =		n
							return int(_SCREAMING_SNAKE_CASE				)


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







"""simple docstring"""
from typing import TYPE_CHECKING

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


__SCREAMING_SNAKE_CASE							:    Optional[Any]		=    {
    'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
    'tokenization_biogpt': ['BioGptTokenizer'],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				__SCREAMING_SNAKE_CASE							:    Optional[Any]		=    [
				    'BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST',
				    'BioGptForCausalLM',
				    'BioGptForTokenClassification',
				    'BioGptForSequenceClassification',
				    'BioGptModel',
				    'BioGptPreTrainedModel',
				]


if TYPE_CHECKING:
				from .configuration_biogpt import BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP, BioGptConfig
				from .tokenization_biogpt import BioGptTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_biogpt import (
								    BIOGPT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    BioGptForCausalLM,
								    BioGptForSequenceClassification,
								    BioGptForTokenClassification,
								    BioGptModel,
								    BioGptPreTrainedModel,
								)


else:
				import sys

				__SCREAMING_SNAKE_CASE							:    Dict		=    _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



