code: def get_parser():
      parser = argparse.ArgumentParser()
  
      parser.add_argument(
          "--num-epochs",
          type=int,
          default=5,
          help="",
      )
  
      parser.add_argument(
          "--model-name",
          type=str,
          default="hf-internal-testing/tiny-random-gpt2",
          help="",
      )
  
      parser.add_argument(
          "--use-half",
          action="store_true",
      )
  
      parser.add_argument(
          "--use-cuda",
          action="store_true",
      )
  
      return parser
  
file_path: optimum/tests/benchmark/benchmark_bettertransformer_training.py
imports: import argparse
  import random
  import numpy
  import torch
  from datasets import load_dataset
  from torch.utils.data import DataLoader
  from tqdm.auto import tqdm
  from transformers import AutoModelForCausalLM, AutoTokenizer, get_scheduler
  from optimum.bettertransformer import BetterTransformer
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser