
from math import sqrt






def 						lowerCAmelCase_		(      _snake_case   :						int     )       ->	int:







	'''simple docstring'''


	__magic_name__	:	Tuple			     =  [1]
	for i in range(2   ,     int(sqrt(_SCREAMING_SNAKE_CASE     )     ) + 1   ,     1     ):
		if number % i == 0:
			values.append(_SCREAMING_SNAKE_CASE     )
			if int(number // i     ) != i:
				values.append(int(number // i     )     )
	return sorted(_SCREAMING_SNAKE_CASE     )






def 						lowerCAmelCase_		(      _snake_case   :						int     )       ->	Dict:







	'''simple docstring'''


	return sum(factors(_SCREAMING_SNAKE_CASE     )     ) > n






def 						lowerCAmelCase_		(      _snake_case   :						int     )       ->	int:







	'''simple docstring'''


	__magic_name__	:	List[Any]			     =  factors(_SCREAMING_SNAKE_CASE     )
	__magic_name__	:	int			     =  len(_SCREAMING_SNAKE_CASE     )
	__magic_name__	:	Dict			     =  [[0 for i in range(number + 1     )] for j in range(r + 1     )]
	for i in range(r + 1     ):
		__magic_name__	:	int			     =  True

	for i in range(1   ,     number + 1     ):
		__magic_name__	:	Dict			     =  False

	for i in range(1   ,     r + 1     ):
		for j in range(1   ,     number + 1     ):
			if j < values[i - 1]:
				__magic_name__	:	List[Any]			     =  subset[i - 1][j]
			else:
				__magic_name__	:	Any			     =  subset[i - 1][j] or subset[i - 1][j - values[i - 1]]

	return subset[r][number] != 0






def 						lowerCAmelCase_		(      _snake_case   :						int     )       ->	Union[str, Any]:







	'''simple docstring'''


	return abundant(_SCREAMING_SNAKE_CASE     ) and not semi_perfect(_SCREAMING_SNAKE_CASE     )


if __name__ == "__main__":
				import doctest

				doctest.testmod(verbose=True)
				for number in (69, 70, 71):
								print(F"{number} is {'' if weird(number) else 'not '}weird.")


from typing import TYPE_CHECKING

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


snake_case				:	Optional[int]							   =						{
    "configuration_mobilevitv2": [
        "MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "MobileViTV2Config",
        "MobileViTV2OnnxConfig",
    ],
}


try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case				:	Optional[int]							   =						[
				    "MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "MobileViTV2ForImageClassification",
				    "MobileViTV2ForSemanticSegmentation",
				    "MobileViTV2Model",
				    "MobileViTV2PreTrainedModel",
				]

if TYPE_CHECKING:
				from .configuration_mobilevitva import (
				    MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
				    MobileViTVaConfig,
				    MobileViTVaOnnxConfig,
				)

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_mobilevitva import (
								    MOBILEVITV2_PRETRAINED_MODEL_ARCHIVE_LIST,
								    MobileViTVaForImageClassification,
								    MobileViTVaForSemanticSegmentation,
								    MobileViTVaModel,
								    MobileViTVaPreTrainedModel,
								)

else:
				import sys

				snake_case				:	Tuple							   =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)
