code: def get_parser():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--num-batches",
          type=int,
          default=50,
          help="",
      )
      parser.add_argument(
          "--batch-size",
          type=int,
          default=64,
          help="",
      )
      parser.add_argument(
          "--avg-seqlen",
          type=int,
          default=256,
          help="True average sequence length (the rest will be padding).",
      )
      parser.add_argument(
          "--max-seqlen",
          type=int,
          default=256,
          help="Input padded sequence length.",
      )
      parser.add_argument(
          "--model-name",
          type=str,
          default="bert-base-uncased",
          help="",
      )
      parser.add_argument(
          "--seqlen-stdev",
          type=int,
          default=10,
          help="",
      )
      parser.add_argument(
          "--use-cuda",
          action="store_true",
      )
      parser.add_argument(
          "--use-half",
          action="store_true",
      )
      parser.add_argument(
          "--use-mask",
          action="store_true",
      )
      parser.add_argument(
          "--is_decoder",
          action="store_true",
          help="Benchmark the generate method.",
      )
      parser.add_argument(
          "--sweep",
          action="store_true",
      )
      parser.add_argument(
          "--max_token",
          type=int,
          default=100,
          help="Number of new tokens, for autoregressive models using generate.",
      )
      return parser
  
file_path: optimum/tests/benchmark/benchmark_bettertransformer.py
imports: import argparse
  import numpy
  import pandas
  import torch
  from tqdm import tqdm
  from transformers import AutoModel, AutoModelForCausalLM, AutoModelForSeq2SeqLM, AutoTokenizer, GenerationConfig
  from optimum.bettertransformer import BetterTransformer
  from optimum.exporters import TasksManager
label_desc: Use image node_id 1 for calling a global function with example usage: get_parser() and returns: parser