lowercase_   				=       (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)
lowercase_   				=       (-1_53, -1, 0, 1.2, 2_00, "A", [], {}, None)







def  __lowerCAmelCase							(						__SCREAMING_SNAKE_CASE    : int					):







    '''simple docstring'''
    if not isinstance(__SCREAMING_SNAKE_CASE						,				__SCREAMING_SNAKE_CASE					) or n < 1:
        return False

    # Initialization of sum and number of digits.
    __snake_case    :							Dict             =  0
    __snake_case    :							Union[str, Any]             =  0
    __snake_case    :							str             =  n
    # Calculation of digits of the number
    while temp > 0:
        number_of_digits += 1
        temp //= 1_0
    # Dividing number into separate digits and find Armstrong number
    __snake_case    :							Any             =  n
    while temp > 0:
        __snake_case    :							str             =  temp % 1_0
        total += rem**number_of_digits
        temp //= 1_0
    return n == total







def  __lowerCAmelCase							(						__SCREAMING_SNAKE_CASE    : int					):







    '''simple docstring'''
    if not isinstance(__SCREAMING_SNAKE_CASE						,				__SCREAMING_SNAKE_CASE					) or n < 1:
        return False

    # Init a "histogram" of the digits
    __snake_case    :							Any             =  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
    __snake_case    :							List[str]             =  0
    __snake_case    :							Dict             =  0
    __snake_case    :							Tuple             =  n
    while temp > 0:
        __snake_case    :							int             =  divmod(__SCREAMING_SNAKE_CASE						,				1_0					)
        digit_histogram[rem] += 1
        digit_total += 1

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

    return n == total







def  __lowerCAmelCase							(						__SCREAMING_SNAKE_CASE    : int					):







    '''simple docstring'''
    if not isinstance(__SCREAMING_SNAKE_CASE						,				__SCREAMING_SNAKE_CASE					) or n < 1:
        return False
    __snake_case    :							Any             =  len(str(__SCREAMING_SNAKE_CASE					)					)  # 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(__SCREAMING_SNAKE_CASE					) ** expo for i in str(__SCREAMING_SNAKE_CASE					)					)







def  __lowerCAmelCase							(						):







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


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()






from typing import TYPE_CHECKING

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


SCREAMING_SNAKE_CASE_						=					{'configuration_hubert': ['HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'HubertConfig']}

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_						=					[
					    'HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'HubertForCTC',
					    'HubertForSequenceClassification',
					    'HubertModel',
					    'HubertPreTrainedModel',
					]


try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					SCREAMING_SNAKE_CASE_						=					[
					    'TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'TFHubertForCTC',
					    'TFHubertModel',
					    'TFHubertPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_hubert import HUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, HubertConfig

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_hubert import (
										    HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    HubertForCTC,
										    HubertForSequenceClassification,
										    HubertModel,
										    HubertPreTrainedModel,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_hubert import (
										    TF_HUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFHubertForCTC,
										    TFHubertModel,
										    TFHubertPreTrainedModel,
										)


else:
					import sys

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


