
"""simple docstring"""







from typing import TYPE_CHECKING

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


lowercase_         =       {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_         =       [
           "OPT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "OPTForCausalLM",
           "OPTModel",
           "OPTPreTrainedModel",
           "OPTForSequenceClassification",
           "OPTForQuestionAnswering",
       ]

try:
       if not is_tf_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_         =       ["TFOPTForCausalLM", "TFOPTModel", "TFOPTPreTrainedModel"]

try:
       if not is_flax_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowercase_         =       [
           "FlaxOPTForCausalLM",
           "FlaxOPTModel",
           "FlaxOPTPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_opt import OPT_PRETRAINED_CONFIG_ARCHIVE_MAP, OPTConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_opt import (
                  OPT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  OPTForCausalLM,
                  OPTForQuestionAnswering,
                  OPTForSequenceClassification,
                  OPTModel,
                  OPTPreTrainedModel,
              )

       try:
              if not is_tf_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_tf_opt import TFOPTForCausalLM, TFOPTModel, TFOPTPreTrainedModel

       try:
              if not is_flax_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_flax_opt import FlaxOPTForCausalLM, FlaxOPTModel, FlaxOPTPreTrainedModel

else:
       import sys

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



"""simple docstring"""







def       A_      (       lowercase   )  ->				int:


     """simple docstring"""







     return 1 if digit in (0, 1) else (digit * factorial(digit - 1   ))




def       A_      (       lowercase   )  ->				bool:


     """simple docstring"""







     UpperCAmelCase_    :     str            =	0
     UpperCAmelCase_    :     Union[str, Any]            =	number
     while duplicate > 0:
          UpperCAmelCase_       ,UpperCAmelCase_    :     Tuple            =	divmod(lowercase    ,			10   )
          fact_sum += factorial(lowercase   )
     return fact_sum == number


if __name__ == "__main__":
       print("Program to check whether a number is a Krisnamurthy Number or not.")
       lowercase_         =       int(input("Enter number: ").strip())
       print(
           f"""{number} is {'' if krishnamurthy(number) else 'not '}a Krishnamurthy Number."""
       )

