class_docstr: BenchMarkArguments are arguments we use in our benchmark scripts **which relate to the training loop itself**.
  
  Using `HfArgumentParser` we can turn this class into argparse arguments to be able to specify them on the command
  line.
class_docstr_tok: ["BenchMarkArguments","are","arguments","we","use","in","our","benchmark","scripts","*","*","which","relate","to","the","training","loop","itself","*","*",".","Using","`","HfArgumentParser","`","we","can","turn","this","class","into","argparse","arguments","to","be","able","to","specify","them","on","the","command","line","."]
code: def do_multi_processing(self):
      if not self.multi_process:
          return False
      elif self.is_tpu:
          logger.info(
              "Multiprocessing is currently not possible on TPU."
          )
          return False
      else:
          return True
  
file_path: transformers/src/transformers/benchmark/benchmark_args_utils.py
imports: import dataclasses
  import json
  import warnings
  from dataclasses import dataclass, field
  from time import time
  from typing import List
  from ..utils import logging
label_desc: Use image node_id 4 for calling the BenchmarkArguments obj's underlying member method code with example usage: obj.do_multi_processing() and returns: False, False, True