



from collections import defaultdict


def 						UpperCAmelCase__   (   UpperCAmelCase__			:int = 5       ):






 '''simple docstring'''

 a							=		defaultdict(UpperCAmelCase__       )
 a							=		0

 while True:
  a							=		get_digits(UpperCAmelCase__       )
  freqs[digits].append(UpperCAmelCase__       )

  if len(freqs[digits]       ) == max_base:
   a							=		freqs[digits][0] ** 3
   return base

  num += 1


def 						UpperCAmelCase__   (   UpperCAmelCase__			:int       ):






 '''simple docstring'''

 return "".join(sorted(str(num**3       )       )       )


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






from typing import TYPE_CHECKING

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


A_		:  Any										=  {
    '''configuration_videomae''': ['''VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''VideoMAEConfig'''],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  List[Any]										=  [
         '''VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''VideoMAEForPreTraining''',
         '''VideoMAEModel''',
         '''VideoMAEPreTrainedModel''',
         '''VideoMAEForVideoClassification''',
     ]

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     A_		:  str										=  ['''VideoMAEFeatureExtractor''']
     A_		:  Union[str, Any]										=  ['''VideoMAEImageProcessor''']

if TYPE_CHECKING:
     from .configuration_videomae import VIDEOMAE_PRETRAINED_CONFIG_ARCHIVE_MAP, VideoMAEConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_videomae import (
              VIDEOMAE_PRETRAINED_MODEL_ARCHIVE_LIST,
              VideoMAEForPreTraining,
              VideoMAEForVideoClassification,
              VideoMAEModel,
              VideoMAEPreTrainedModel,
          )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .feature_extraction_videomae import VideoMAEFeatureExtractor
          from .image_processing_videomae import VideoMAEImageProcessor

else:
     import sys

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

