




"""simple docstring"""


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






def        lowerCAmelCase_       (		snake_case_		:      List[Any]      )       ->Tuple:
			if not isinstance(__UpperCamelCase							,   __UpperCamelCase      ) or n < 1:
						return False

			# Initialization of sum and number of digits.
			lowerCamelCase__     :					int		=0
			lowerCamelCase__     :					List[str]		=0
			lowerCamelCase__     :					int		=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
			lowerCamelCase__     :					List[Any]		=n
			while temp > 0:
						lowerCamelCase__     :					Any		=temp % 1_0
						total += rem**number_of_digits
						temp //= 1_0
			return n == total






def        lowerCAmelCase_       (		snake_case_		:      Union[str, Any]      )       ->Any:
			if not isinstance(__UpperCamelCase							,   __UpperCamelCase      ) or n < 1:
						return False

			# Init a "histogram" of the digits
			lowerCamelCase__     :					Optional[int]		=[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
			lowerCamelCase__     :					Optional[Any]		=0
			lowerCamelCase__     :					Optional[int]		=0
			lowerCamelCase__     :					str		=n
			while temp > 0:
						lowerCamelCase__	,    lowerCamelCase__     :					str		=divmod(__UpperCamelCase							,   1_0      )
						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        lowerCAmelCase_       (		snake_case_		:      List[str]      )       ->Any:
			if not isinstance(__UpperCamelCase							,   __UpperCamelCase      ) or n < 1:
						return False
			lowerCamelCase__     :					int		=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        lowerCAmelCase_       (		)       ->int:
			lowerCamelCase__     :					List[str]		=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()

"""simple docstring"""


from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


lowerCAmelCase								=						{
    """configuration_deberta_v2""": ["""DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """DebertaV2Config""", """DebertaV2OnnxConfig"""],
    """tokenization_deberta_v2""": ["""DebertaV2Tokenizer"""],
}

try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						["""DebertaV2TokenizerFast"""]

try:
							if not is_tf_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						[
							    """TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """TFDebertaV2ForMaskedLM""",
							    """TFDebertaV2ForQuestionAnswering""",
							    """TFDebertaV2ForSequenceClassification""",
							    """TFDebertaV2ForTokenClassification""",
							    """TFDebertaV2Model""",
							    """TFDebertaV2PreTrainedModel""",
							]

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							lowerCAmelCase								=						[
							    """DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST""",
							    """DebertaV2ForMaskedLM""",
							    """DebertaV2ForMultipleChoice""",
							    """DebertaV2ForQuestionAnswering""",
							    """DebertaV2ForSequenceClassification""",
							    """DebertaV2ForTokenClassification""",
							    """DebertaV2Model""",
							    """DebertaV2PreTrainedModel""",
							]


if TYPE_CHECKING:
							from .configuration_deberta_va import (
							    DEBERTA_V2_PRETRAINED_CONFIG_ARCHIVE_MAP,
							    DebertaVaConfig,
							    DebertaVaOnnxConfig,
							)
							from .tokenization_deberta_va import DebertaVaTokenizer

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_deberta_va_fast import DebertaVaTokenizerFast

							try:
														if not is_tf_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_tf_deberta_va import (
														    TF_DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    TFDebertaVaForMaskedLM,
														    TFDebertaVaForQuestionAnswering,
														    TFDebertaVaForSequenceClassification,
														    TFDebertaVaForTokenClassification,
														    TFDebertaVaModel,
														    TFDebertaVaPreTrainedModel,
														)

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_deberta_va import (
														    DEBERTA_V2_PRETRAINED_MODEL_ARCHIVE_LIST,
														    DebertaVaForMaskedLM,
														    DebertaVaForMultipleChoice,
														    DebertaVaForQuestionAnswering,
														    DebertaVaForSequenceClassification,
														    DebertaVaForTokenClassification,
														    DebertaVaModel,
														    DebertaVaPreTrainedModel,
														)

else:
							import sys

							lowerCAmelCase								=						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)