
def 			_SCREAMING_SNAKE_CASE      (	_lowerCamelCase				:    int = 600_851_475_143)      ->					int:






							'''simple docstring'''





							try:
														__UpperCamelCase			:     Dict         =      int(_lowerCamelCase)
							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.")
							__UpperCamelCase			:     Tuple         =      2
							__UpperCamelCase			:     List[str]         =      0
							if n == 2:
														return 2
							while n > 2:
														while n % i != 0:
																					i += 1
														__UpperCamelCase			:     str         =      i
														while n % i == 0:
																					__UpperCamelCase			:     str         =      n // i
														i += 1
							return int(_lowerCamelCase)


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

from typing import TYPE_CHECKING

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


lowercase						:      List[Any]									= {'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}


try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      Dict									= [
		    'SWIN_PRETRAINED_MODEL_ARCHIVE_LIST',
		    'SwinForImageClassification',
		    'SwinForMaskedImageModeling',
		    'SwinModel',
		    'SwinPreTrainedModel',
		    'SwinBackbone',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		lowercase						:      Optional[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

		lowercase						:      Optional[Any]									= _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)