





UpperCAmelCase__    :      Optional[int]       					=(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__    :      tuple       					=(-1_53, -1, 0, 1.2, 2_00, "A", [], {}, None)





def   _lowercase       (    _UpperCAmelCase					)    ->	bool:
				if not isinstance(_UpperCAmelCase      ,   _UpperCAmelCase					) 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   _lowercase       (    _UpperCAmelCase					)    ->	bool:
				if not isinstance(_UpperCAmelCase      ,   _UpperCAmelCase					) 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(_UpperCAmelCase      ,   10					)
								digit_histogram[rem] += 1
								digit_total += 1

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

				return n == total





def   _lowercase       (    _UpperCAmelCase					)    ->	bool:
				if not isinstance(_UpperCAmelCase      ,   _UpperCAmelCase					) or n < 1:
								return False
				lowerCamelCase									=len(str(_UpperCAmelCase					)					)  # 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(_UpperCAmelCase					) ** expo for i in str(_UpperCAmelCase					)					)





def   _lowercase       (    )    ->	Optional[int]:
				lowerCamelCase									=int(input("""Enter an integer to see if it is an Armstrong number: """					).strip()					)
				print(F"""{num} is {"" if armstrong_number(_UpperCAmelCase					) else "not "}an Armstrong number."""					)
				print(F"""{num} is {"" if narcissistic_number(_UpperCAmelCase					) else "not "}an Armstrong number."""					)
				print(F"""{num} is {"" if pluperfect_number(_UpperCAmelCase					) 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


UpperCAmelCase__    :      int       					={
    '''configuration_flaubert''': ['''FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FlaubertConfig''', '''FlaubertOnnxConfig'''],
    '''tokenization_flaubert''': ['''FlaubertTokenizer'''],
}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      int       					=[
							    '''FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''FlaubertForMultipleChoice''',
							    '''FlaubertForQuestionAnswering''',
							    '''FlaubertForQuestionAnsweringSimple''',
							    '''FlaubertForSequenceClassification''',
							    '''FlaubertForTokenClassification''',
							    '''FlaubertModel''',
							    '''FlaubertWithLMHeadModel''',
							    '''FlaubertPreTrainedModel''',
							]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							UpperCAmelCase__    :      List[str]       					=[
							    '''TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
							    '''TFFlaubertForMultipleChoice''',
							    '''TFFlaubertForQuestionAnsweringSimple''',
							    '''TFFlaubertForSequenceClassification''',
							    '''TFFlaubertForTokenClassification''',
							    '''TFFlaubertModel''',
							    '''TFFlaubertPreTrainedModel''',
							    '''TFFlaubertWithLMHeadModel''',
							]


if TYPE_CHECKING:
							from .configuration_flaubert import FLAUBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, FlaubertConfig, FlaubertOnnxConfig
							from .tokenization_flaubert import FlaubertTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_flaubert import (
														    FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    FlaubertForMultipleChoice,
														    FlaubertForQuestionAnswering,
														    FlaubertForQuestionAnsweringSimple,
														    FlaubertForSequenceClassification,
														    FlaubertForTokenClassification,
														    FlaubertModel,
														    FlaubertPreTrainedModel,
														    FlaubertWithLMHeadModel,
														)

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_flaubert import (
														    TF_FLAUBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFFlaubertForMultipleChoice,
														    TFFlaubertForQuestionAnsweringSimple,
														    TFFlaubertForSequenceClassification,
														    TFFlaubertForTokenClassification,
														    TFFlaubertModel,
														    TFFlaubertPreTrainedModel,
														    TFFlaubertWithLMHeadModel,
														)

else:
							import sys

							UpperCAmelCase__    :      List[Any]       					=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





