code: def parse_args():
      parser = argparse.ArgumentParser()
      parser.add_argument(
          "--dataroot", required=True, help="path to images"
      )
      parser.add_argument(
          "--batchSize", type=int, default=16, help="input batch size"
      )
      parser.add_argument(
          "--gpu_ids",
          type=str,
          default="0",
          help="gpu ids: e.g. 0  0,1,2, 0,2. use -1 for CPU",
      )
      parser.add_argument(
          "--workers",
          type=int,
          help="number of data loading workers",
          default=6,
      )
      parser.add_argument(
          "--experiment", default=None, help="Where to store models"
      )
      parser.add_argument(
          "--fineSize",
          type=int,
          default=384,
          help="then crop to this size",
      )
      parser.add_argument(
          "--n_epoch_init",
          type=int,
          default=100,
          help="# of iter at pretrained",
      )
      parser.add_argument(
          "--n_epoch",
          type=int,
          default=20000,
          help="# of iter at training",
      )
      parser.add_argument(
          "--beta1",
          type=float,
          default=0.9,
          help="momentum term of adam",
      )
      parser.add_argument(
          "--lr_init",
          type=float,
          default=1e-4,
          help="initial learning rate for pretrain",
      )
      parser.add_argument(
          "--lr_decay",
          type=float,
          default=0.1,
          help="initial learning rate for adam",
      )
      opt = parser.parse_args()
      return opt
  
imports: import argparse
  import random
  from mxnet import gluon, image, autograd
  from mxnet.gluon.data.vision import transforms
  from mxnet.gluon.data import DataLoader
  from mxnet.gluon import nn
  import mxnet.ndarray
  import mxnet
  from mxboard import SummaryWriter
  import os
  from mxnet.gluon.model_zoo import vision
label_desc: Use image node_id 5 for calling a global function with example usage: parse_args() and returns: opt