code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Paddle Face Predictor"
      )
  
      parser.add_argument(
          "--export_type", type=str, help="export type, paddle or onnx"
      )
      parser.add_argument(
          "--model_file",
          type=str,
          required=False,
          help="paddle save inference model filename",
      )
      parser.add_argument(
          "--params_file",
          type=str,
          required=False,
          help="paddle save inference parameter filename",
      )
      parser.add_argument(
          "--onnx_file",
          type=str,
          required=False,
          help="onnx model filename",
      )
      parser.add_argument(
          "--image_path", type=str, help="path to test image"
      )
      parser.add_argument(
          "--benchmark",
          type=str2bool,
          default=False,
          help="Is benchmark mode",
      )
      # params for paddle inferece engine
      parser.add_argument("--use_gpu", type=str2bool, default=True)
      parser.add_argument("--ir_optim", type=str2bool, default=True)
      parser.add_argument(
          "--use_tensorrt", type=str2bool, default=False
      )
      parser.add_argument("--min_subgraph_size", type=int, default=15)
      parser.add_argument("--max_batch_size", type=int, default=1)
      parser.add_argument("--precision", type=str, default="fp32")
      parser.add_argument("--gpu_mem", type=int, default=500)
      parser.add_argument(
          "--enable_mkldnn", type=str2bool, default=False
      )
      parser.add_argument("--cpu_threads", type=int, default=10)
      args = parser.parse_args()
      return args
  
file_path: insightface/recognition/arcface_paddle/tools/inference.py
imports: import sys
  import os
  import cv2
  import time
  import json
  import argparse
  import numpy
label_desc: Use image node_id 2 for calling a global function with example usage: parse_args() and returns: args