code: def get_args():
      parser = argparse.ArgumentParser(
          description="Evaluate Whisper performance and accuracy"
      )
      parser.add_argument(
          "--model_path", required=True, help="pretrained model path"
      )
      parser.add_argument(
          "--data_type", required=True, help="clean, other"
      )
      parser.add_argument("--device", required=False, help="cpu, xpu")
  
      args = parser.parse_args()
      return args
  
file_path: BigDL/python/llm/test/benchmark/whisper/run_whisper.py
imports: from datasets import load_dataset
  from bigdl.llm.transformers import AutoModelForSpeechSeq2Seq
  from transformers import WhisperProcessor
  import torch
  from evaluate import load
  import time
  import argparse
  from bigdl.llm import optimize_model
  import intel_extension_for_pytorch
label_desc: Use image node_id 1 for calling a global function with example usage: get_args() and returns: args