






'''simple docstring'''

def 					lowercase__				(   __UpperCamelCase					)->				int:
      UpperCamelCase       						=      [1]

      UpperCamelCase						,UpperCamelCase						,UpperCamelCase       						=      0, 0, 0
      UpperCamelCase       						=      ugly_nums[ia] * 2
      UpperCamelCase       						=      ugly_nums[ia] * 3
      UpperCamelCase       						=      ugly_nums[ia] * 5

      for _ in range(1	,		__UpperCamelCase					):
            UpperCamelCase       						=      min(__UpperCamelCase	,		__UpperCamelCase	,		__UpperCamelCase					)
            ugly_nums.append(__UpperCamelCase					)
            if next_num == next_a:
                  ia += 1
                  UpperCamelCase       						=      ugly_nums[ia] * 2
            if next_num == next_a:
                  ia += 1
                  UpperCamelCase       						=      ugly_nums[ia] * 3
            if next_num == next_a:
                  ia += 1
                  UpperCamelCase       						=      ugly_nums[ia] * 5
      return ugly_nums[-1]


if __name__ == "__main__":
     from doctest import testmod

     testmod(verbose=True)
     print(f'{ugly_numbers(2_0_0) = }')








'''simple docstring'''

from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE__											=     {
    'configuration_swiftformer': [
        'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'SwiftFormerConfig',
        'SwiftFormerOnnxConfig',
    ]
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     SCREAMING_SNAKE_CASE__											=     [
         'SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'SwiftFormerForImageClassification',
         'SwiftFormerModel',
         'SwiftFormerPreTrainedModel',
     ]

if TYPE_CHECKING:
     from .configuration_swiftformer import (
         SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         SwiftFormerConfig,
         SwiftFormerOnnxConfig,
     )

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_swiftformer import (
              SWIFTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
              SwiftFormerForImageClassification,
              SwiftFormerModel,
              SwiftFormerPreTrainedModel,
          )

else:
     import sys

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