
'''simple docstring'''

UpperCAmelCase__      :       Optional[Any] 		=						(1, 1_53, 3_70, 3_71, 16_34, 24_67_80_51, 1_15_13_22_19_01_87_63_99_25_65_09_55_97_97_39_71_52_24_01)
UpperCAmelCase__      :       int 		=						(-1_53, -1, 0, 1.2, 2_00, "A", [], {}, None)







def      A   (					UpperCamelCase_    :   int					)    ->				List[Any]:







			'''simple docstring'''



			if not isinstance(lowerCamelCase_  ,		lowerCamelCase_					) or n < 1:
						return False

			# Initialization of sum and number of digits.
			lowerCAmelCase__									=							0
			lowerCAmelCase__									=							0
			lowerCAmelCase__									=							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
			lowerCAmelCase__									=							n
			while temp > 0:
						lowerCAmelCase__									=							temp % 10
						total += rem**number_of_digits
						temp //= 10
			return n == total







def      A   (					UpperCamelCase_    :   int					)    ->				str:







			'''simple docstring'''



			if not isinstance(lowerCamelCase_  ,		lowerCamelCase_					) or n < 1:
						return False

			# Init a "histogram" of the digits
			lowerCAmelCase__									=							[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
			lowerCAmelCase__									=							0
			lowerCAmelCase__									=							0
			lowerCAmelCase__									=							n
			while temp > 0:
						lowerCAmelCase__		,lowerCAmelCase__									=							divmod(lowerCamelCase_  ,		10					)
						digit_histogram[rem] += 1
						digit_total += 1

			for cnt, i in zip(lowerCamelCase_  ,		range(len(lowerCamelCase_					)					)					):
						total += cnt * i**digit_total

			return n == total







def      A   (					UpperCamelCase_    :   int					)    ->				str:







			'''simple docstring'''



			if not isinstance(lowerCamelCase_  ,		lowerCamelCase_					) or n < 1:
						return False
			lowerCAmelCase__									=							len(str(lowerCamelCase_					)					)  # 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(lowerCamelCase_					) ** expo for i in str(lowerCamelCase_					)					)







def      A   (					)    ->				Tuple:







			'''simple docstring'''



			lowerCAmelCase__									=							int(input("Enter an integer to see if it is an Armstrong number: "					).strip()					)
			print(F"""{num} is {"" if armstrong_number(lowerCamelCase_					) else "not "}an Armstrong number."""					)
			print(F"""{num} is {"" if narcissistic_number(lowerCamelCase_					) else "not "}an Armstrong number."""					)
			print(F"""{num} is {"" if pluperfect_number(lowerCamelCase_					) else "not "}an Armstrong number."""					)


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		main()












'''simple docstring'''



from typing import TYPE_CHECKING

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


_SCREAMING_SNAKE_CASE    =			{
    '''configuration_deformable_detr''': ['''DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeformableDetrConfig'''],
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE    =			['''DeformableDetrFeatureExtractor''']
	_SCREAMING_SNAKE_CASE    =			['''DeformableDetrImageProcessor''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	_SCREAMING_SNAKE_CASE    =			[
	    '''DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST''',
	    '''DeformableDetrForObjectDetection''',
	    '''DeformableDetrModel''',
	    '''DeformableDetrPreTrainedModel''',
	]


if TYPE_CHECKING:
	from .configuration_deformable_detr import DEFORMABLE_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP, DeformableDetrConfig

	try:
		if not is_vision_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .feature_extraction_deformable_detr import DeformableDetrFeatureExtractor
		from .image_processing_deformable_detr import DeformableDetrImageProcessor

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_deformable_detr import (
		    DEFORMABLE_DETR_PRETRAINED_MODEL_ARCHIVE_LIST,
		    DeformableDetrForObjectDetection,
		    DeformableDetrModel,
		    DeformableDetrPreTrainedModel,
		)

else:
	import sys

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





