






"""simple docstring"""





from transformers import HfArgumentParser, PyTorchBenchmark, PyTorchBenchmarkArguments






def     A(  ):
       """simple docstring"""





       lowercase__:    Dict        =      HfArgumentParser(snake_case_		)
       try:
              lowercase__:    Tuple        =      parser.parse_args_into_dataclasses()[0]
       except ValueError as e:
              lowercase__:    Union[str, Any]        =      "Arg --no_{0} is no longer used, please use --no-{0} instead."
              lowercase__:    int        =      " ".join(str(snake_case_		).split(" "		)[:-1]		)
              lowercase__:    Optional[Any]        =      ""
              lowercase__:    int        =      eval(str(snake_case_		).split(" "		)[-1]		)
              lowercase__:    int        =      []
              for arg in depreciated_args:
                     # arg[2:] removes '--'
                     if arg[2:] in PyTorchBenchmarkArguments.deprecated_args:
                            # arg[5:] removes '--no_'
                            full_error_msg += arg_error_msg.format(arg[5:]		)
                     else:
                            wrong_args.append(snake_case_		)
              if len(snake_case_		) > 0:
                     lowercase__:    List[str]        =      full_error_msg + begin_error_msg + str(snake_case_		)
              raise ValueError(snake_case_		)

       lowercase__:    Tuple        =      PyTorchBenchmark(args=snake_case_		)
       benchmark.run()


if __name__ == "__main__":
  main()














"""simple docstring"""





from __future__ import annotations






def     A(  snake_case_						,       snake_case_		):
       """simple docstring"""





       lowercase__  ,     lowercase__:    Optional[int]        =      0, len(snake_case_		) - 1
       while start_ind <= end_ind:
              if array[start_ind] == search_item:
                     return start_ind
              elif array[end_ind] == search_item:
                     return end_ind
              else:
                     start_ind += 1
                     end_ind -= 1
    # returns -1 if search_item is not found in array
       return -1


if __name__ == "__main__":
  print(double_linear_search(list(range(1_00)), 40))






