code: def argsparser():
      parser = argparse.ArgumentParser("PatchCore")
      parser.add_argument(
          "--config",
          type=str,
          default=None,
          help="Path of config",
          required=True,
      )
      parser.add_argument("--device", type=str, default=None)
      parser.add_argument("--batch_size", type=int, default=None)
      parser.add_argument("--num_workers", type=int, default=None)
      parser.add_argument("--seed", type=int, default=None)
      parser.add_argument("--data_path", type=str, default=None)
      parser.add_argument("--save_path", type=str, default=None)
      parser.add_argument(
          "--category",
          type=str,
          default=None,
          help="category name for MvTec AD dataset",
      )
      parser.add_argument("--resize", type=list or tuple, default=None)
      parser.add_argument(
          "--crop_size", type=list or tuple, default=None
      )
      parser.add_argument(
          "--backbone",
          type=str,
          default=None,
          help="backbone model arch, one of [resnet18, resnet50, wide_resnet50_2]",
      )
      parser.add_argument(
          "--k", type=int, default=None, help="used feature channels"
      )
      parser.add_argument(
          "--method",
          type=str,
          default=None,
          choices=[
              "sample",
              "h_sample",
              "ortho",
              "svd_ortho",
              "gaussian",
              "coreset",
          ],
          help="projection method, one of [sample, ortho, svd_ortho, gaussian, coreset]",
      )
      parser.add_argument("--do_eval", type=bool, default=None)
      parser.add_argument("--save_pic", type=str2bool, default=None)
  
      parser.add_argument("--save_model", type=str2bool, default=True)
      parser.add_argument("--test_batch_size", type=int, default=1)
      parser.add_argument(
          "--inc",
          action="store_true",
          help="use incremental cov & mean",
      )
      parser.add_argument("--eval_PRO", type=bool, default=True)
      parser.add_argument(
          "--eval_threthold_step",
          type=int,
          default=500,
          help="threthold_step when computing PRO Score",
      )
      parser.add_argument("--einsum", action="store_true")
      parser.add_argument("--non_partial_AUC", action="store_true")
      return parser.parse_args()
  
file_path: PaddleSeg/contrib/QualityInspector/tools/uad/patchcore/train.py
imports: import os
  import sys
  import time
  import random
  import argparse
  import datetime
  import numpy
  import pandas
  from tqdm import tqdm
  import paddle
  from paddle.io import DataLoader
  import qinspector.uad.datasets.mvtec
  from qinspector.uad.models.patchcore import get_model
  from qinspector.uad.utils.utils import str2bool
  from qinspector.cvlib.uad_configs import ConfigParser
  from val import val
label_desc: Use image node_id 1 for calling a global function with example usage: argsparser() and returns: parser