
import math

def 					SCREAMING_SNAKE_CASE  (   __UpperCamelCase			:    Optional[int]							)			->							List[Any]:

				"""simple docstring"""







				if not isinstance(__UpperCamelCase				,    __UpperCamelCase							):
								A__	:						List[Any]								=				F"Input value of [number={number}] must be an integer"
								raise TypeError(__UpperCamelCase							)
				if number < 1:
								A__	:						Optional[Any]								=				F"Input value of [number={number}] must be a positive integer"
								raise ValueError(__UpperCamelCase							)
				A__	:						Optional[int]								=				[number]
				while number != 1:
								if number % 2 == 0:
												A__	:						List[str]								=				math.floor(math.sqrt(__UpperCamelCase							)							)
								else:
												A__	:						Any								=				math.floor(
												    math.sqrt(__UpperCamelCase							) * math.sqrt(__UpperCamelCase							) * math.sqrt(__UpperCamelCase							)							)
								sequence.append(__UpperCamelCase							)
				return sequence


if __name__ == "__main__":
					import doctest

					doctest.testmod()







from typing import TYPE_CHECKING

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


a 			=							{
    'configuration_mobilevitv2': [
        'MOBILEVITV2_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'MobileViTV2Config',
        'MobileViTV2OnnxConfig',
    ],
}


try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a 			=							[
     '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

 a 			=							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)


