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","."]
docstr: Serializes this instance to a JSON string.
docstr_tok: ["Serializes","this","instance","to","a","JSON","string","."]
code: def to_json_string(self):
      """
      Serializes this instance to a JSON string.
      """
      return json.dumps(dataclasses.asdict(self), indent=2)
  
file_path: H2O/h2o_flexgen/benchmark/third_party/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 2 for calling the BenchmarkArguments obj's underlying member method code with example usage: obj.to_json_string() and returns: json