code: def parse_opts():
      parser = argparse.ArgumentParser(
          description="Transfer learning on MINC-2500 dataset",
          formatter_class=argparse.ArgumentDefaultsHelpFormatter,
      )
      parser.add_argument(
          "--data",
          type=str,
          default="",
          help="directory for the prepared data folder",
      )
      parser.add_argument(
          "--model",
          required=True,
          type=str,
          help="name of the pretrained model from model zoo.",
      )
      parser.add_argument(
          "-j",
          "--workers",
          dest="num_workers",
          default=4,
          type=int,
          help="number of preprocessing workers",
      )
      parser.add_argument(
          "--num-gpus",
          default=0,
          type=int,
          help="number of gpus to use, 0 indicates cpu only",
      )
      parser.add_argument(
          "--epochs",
          default=40,
          type=int,
          help="number of training epochs",
      )
      parser.add_argument(
          "-b",
          "--batch-size",
          default=64,
          type=int,
          help="mini-batch size",
      )
      parser.add_argument(
          "--lr",
          "--learning-rate",
          default=0.001,
          type=float,
          help="initial learning rate",
      )
      parser.add_argument(
          "--momentum", default=0.9, type=float, help="momentum"
      )
      parser.add_argument(
          "--weight-decay",
          "--wd",
          dest="wd",
          default=1e-4,
          type=float,
          help="weight decay (default: 1e-4)",
      )
      parser.add_argument(
          "--lr-factor",
          default=0.75,
          type=float,
          help="learning rate decay ratio",
      )
      parser.add_argument(
          "--lr-steps",
          default="10,20,30",
          type=str,
          help="list of learning rate decay epochs as in str",
      )
      opts = parser.parse_args()
      return opts
  
file_path: gluon-cv/scripts/classification/finetune/finetune_minc.py
imports: import mxnet
  import numpy
  import os, time, logging, argparse, shutil
  from mxnet import gluon, image, init, nd
  from mxnet import autograd
  from mxnet.gluon import nn
  from mxnet.gluon.data.vision import transforms
  import gluoncv
  from gluoncv.utils import makedirs
  from gluoncv.model_zoo import get_model
label_desc: Use image node_id 1 for calling a global function with example usage: parse_opts() and returns: opts