code: 
  
  
  
  
  UpperCamelCase__				       =			(1, 153, 370, 371, 1_634, 24_678_051, 115_132_219_018_763_992_565_095_597_973_971_522_401)
  UpperCamelCase__				       =			(-153, -1, 0, 1.2, 200, 'A', [], {}, None)
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Dict:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         if not isinstance(lowercase__    ,     lowercase__			) or n < 1:
                return False
  
         # Initialization of sum and number of digits.
         _lowercase					:				List[Any]           =			0
         _lowercase					:				List[str]           =			0
         _lowercase					:				List[str]           =			n
         # Calculation of digits of the number
         while temp > 0:
                number_of_digits += 1
                temp //= 10
         # Dividing number into separate digits and find Armstrong number
         _lowercase					:				Optional[int]           =			n
         while temp > 0:
                _lowercase					:				Tuple           =			temp % 10
                total += rem**number_of_digits
                temp //= 10
         return n == total
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Any:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         if not isinstance(lowercase__    ,     lowercase__			) or n < 1:
                return False
  
         # Init a "histogram" of the digits
         _lowercase					:				str           =			[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
         _lowercase					:				int           =			0
         _lowercase					:				Tuple           =			0
         _lowercase					:				Tuple           =			n
         while temp > 0:
                _lowercase					:				List[str]           =			divmod(lowercase__    ,     10			)
                digit_histogram[rem] += 1
                digit_total += 1
  
         for cnt, i in zip(lowercase__    ,     range(len(lowercase__			)			)			):
                total += cnt * i**digit_total
  
         return n == total
  
  def   UpperCamelCase__   (    UpperCAmelCase_			)						->							Optional[Any]:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         if not isinstance(lowercase__    ,     lowercase__			) or n < 1:
                return False
         _lowercase					:				int           =			len(str(lowercase__			)			)  # the power that all digits will be raised to
         # check if sum of each digit multiplied expo times is equal to number
         return n == sum(int(lowercase__			) ** expo for i in str(lowercase__			)			)
  
  def   UpperCamelCase__   (    )						->							Tuple:
  
  
  
  
         '''simple docstring'''
  
  
  
  
  
  
         _lowercase					:				Any           =			int(input('''Enter an integer to see if it is an Armstrong number: '''			).strip()			)
         print(F'{num} is {"" if armstrong_number(lowercase__			) else "not "}an Armstrong number.'			)
         print(F'{num} is {"" if narcissistic_number(lowercase__			) else "not "}an Armstrong number.'			)
         print(F'{num} is {"" if pluperfect_number(lowercase__			) else "not "}an Armstrong number.'			)
  
  
  if __name__ == "__main__":
     import doctest
  
     doctest.testmod()
     main()
style_context: 
  
  
  from typing import TYPE_CHECKING
  
  from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
  
  
  UpperCamelCase__				       =			{
      'configuration_wav2vec2_conformer': [
          'WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
          'Wav2Vec2ConformerConfig',
      ],
  }
  
  
  try:
     if not is_torch_available():
        raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
     pass
  else:
     UpperCamelCase__				       =			[
         'WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
         'Wav2Vec2ConformerForAudioFrameClassification',
         'Wav2Vec2ConformerForCTC',
         'Wav2Vec2ConformerForPreTraining',
         'Wav2Vec2ConformerForSequenceClassification',
         'Wav2Vec2ConformerForXVector',
         'Wav2Vec2ConformerModel',
         'Wav2Vec2ConformerPreTrainedModel',
     ]
  
  if TYPE_CHECKING:
     from .configuration_wavaveca_conformer import (
         WAV2VEC2_CONFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
         WavaVecaConformerConfig,
     )
  
     try:
        if not is_torch_available():
           raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
        pass
     else:
        from .modeling_wavaveca_conformer import (
            WAV2VEC2_CONFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            WavaVecaConformerForAudioFrameClassification,
            WavaVecaConformerForCTC,
            WavaVecaConformerForPreTraining,
            WavaVecaConformerForSequenceClassification,
            WavaVecaConformerForXVector,
            WavaVecaConformerModel,
            WavaVecaConformerPreTrainedModel,
        )
  
  else:
     import sys
  
     UpperCamelCase__				       =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)