"""simple docstring"""
def 		__a  (      _SCREAMING_SNAKE_CASE = 998001  )      ->int:

  # fetches the next number
  for number in range(n - 1						,	9999						,	-1  ):
    a__:	Dict     				=      str(_SCREAMING_SNAKE_CASE  )

    # checks whether 'str_number' is a palindrome.
    if str_number == str_number[::-1]:
      a__:	Optional[int]     				=      999

      # if 'number' is a product of two 3-digit numbers
      # then number is the answer otherwise fetch next number.
      while divisor != 99:
        if (number % divisor == 0) and (len(str(number // divisor  )  ) == 3.0):
          return number
        divisor -= 1
  raise ValueError('That number is larger than our acceptable range.'  )


if __name__ == "__main__":
 print(f"{solution() = }")




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a__				:      List[Any]    		=     {
    '''configuration_decision_transformer''': [
        '''DECISION_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''DecisionTransformerConfig''',
    ],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      a__				:      List[str]    		=     [
          '''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

      a__				:      str    		=     _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
