from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments





def 			lowercase(	)		->	Any:







 '''simple docstring'''
 UpperCamelCase			  =      HfArgumentParser(_UpperCamelCase       )
 UpperCamelCase			  =      parser.parse_args_into_dataclasses()[0]
 UpperCamelCase			  =      TensorFlowBenchmark(args=_UpperCamelCase       )
 try:
  UpperCamelCase			  =      parser.parse_args_into_dataclasses()[0]
 except ValueError as e:
  UpperCamelCase			  =      """Arg --no_{0} is no longer used, please use --no-{0} instead."""
  UpperCamelCase			  =      """ """.join(str(_UpperCamelCase       ).split(""" """       )[:-1]       )
  UpperCamelCase			  =      """"""
  UpperCamelCase			  =      eval(str(_UpperCamelCase       ).split(""" """       )[-1]       )
  UpperCamelCase			  =      []
  for arg in depreciated_args:
   # arg[2:] removes '--'
   if arg[2:] in TensorFlowBenchmark.deprecated_args:
    # arg[5:] removes '--no_'
    full_error_msg += arg_error_msg.format(arg[5:]       )
   else:
    wrong_args.append(_UpperCamelCase       )
  if len(_UpperCamelCase       ) > 0:
   UpperCamelCase			  =      full_error_msg + begin_error_msg + str(_UpperCamelCase       )
  raise ValueError(_UpperCamelCase       )
 benchmark.run()


if __name__ == "__main__":
     main()



def 							__lowerCAmelCase     (							_UpperCamelCase		:	List[str]=2_81_23						)		->				str:
 '''simple docstring'''


 SCREAMING_SNAKE_CASE		    =      [1] * (limit + 1)

 for i in range(2		,				int(limit**0.5						) + 1						):
  sum_divs[i * i] += i
  for k in range(i + 1		,				limit // i + 1						):
   sum_divs[k * i] += k + i

 SCREAMING_SNAKE_CASE		    =      set()
 SCREAMING_SNAKE_CASE		    =      0

 for n in range(1		,				limit + 1						):
  if sum_divs[n] > n:
   abundants.add(_UpperCamelCase						)

  if not any((n - a in abundants) for a in abundants						):
   res += n

 return res


if __name__ == "__main__":
      print(solution())

