'''simple docstring'''






from math import sqrt





def    _SCREAMING_SNAKE_CASE		(			__snake_case       : List[Any]							):
     _A								=     [1]
     for i in range(2      ,		int(sqrt(__A							)							) + 1      ,		1							):
          if number % i == 0:
               values.append(__A							)
               if int(number // i							) != i:
                    values.append(int(number // i							)							)
     return sorted(__A							)





def    _SCREAMING_SNAKE_CASE		(			__snake_case       : List[Any]							):
     return sum(factors(__A							)							) > n





def    _SCREAMING_SNAKE_CASE		(			__snake_case       : Any							):
     _A								=     factors(__A							)
     _A								=     len(__A							)
     _A								=     [[0 for i in range(number + 1							)] for j in range(r + 1							)]
     for i in range(r + 1							):
          _A								=     True

     for i in range(1      ,		number + 1							):
          _A								=     False

     for i in range(1      ,		r + 1							):
          for j in range(1      ,		number + 1							):
               if j < values[i - 1]:
                    _A								=     subset[i - 1][j]
               else:
                    _A								=     subset[i - 1][j] or subset[i - 1][j - values[i - 1]]

     return subset[r][number] != 0





def    _SCREAMING_SNAKE_CASE		(			__snake_case       : List[str]							):
     return abundant(__A							) and not semi_perfect(__A							)


if __name__ == "__main__":
  import doctest

  doctest.testmod(verbose=True)
  for number in (69, 70, 71):
    print(F'''{number} is {'' if weird(number) else 'not '}weird.''')




'''simple docstring'''






from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_UpperCAmelCase						:    Dict     					=					{
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _UpperCAmelCase						:    Union[str, Any]     					=					[
       '''DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''DecisionTransformerGPT2Model''',
       '''DecisionTransformerGPT2PreTrainedModel''',
       '''DecisionTransformerModel''',
       '''DecisionTransformerPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_decision_transformer import (
       DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
       DecisionTransformerConfig,
   )

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_decision_transformer import (
          DECISION_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          DecisionTransformerGPTaModel,
          DecisionTransformerGPTaPreTrainedModel,
          DecisionTransformerModel,
          DecisionTransformerPreTrainedModel,
      )


else:
   import sys

   _UpperCAmelCase						:    Dict     					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



