code: def get_arguments():
      """Parse all the arguments provided from the CLI.
  
      Returns:
        A list of parsed arguments.
      """
      parser = argparse.ArgumentParser(description="DML_CSR Network")
      parser.add_argument(
          "--batch-size",
          type=int,
          default=1,
          help="Number of images sent to the network in one step.",
      )
      parser.add_argument(
          "--data-dir",
          type=str,
          default=DATA_DIRECTORY,
          help="Path to the directory containing the PASCAL VOC dataset.",
      )
      parser.add_argument(
          "--out-dir",
          type=str,
          default=DATA_DIRECTORY,
          help="Path to the directory containing the PASCAL VOC dataset.",
      )
      parser.add_argument(
          "--dataset",
          type=str,
          default="val",
          help="Path to the file listing the images in the dataset.",
      )
      parser.add_argument(
          "--ignore-label",
          type=int,
          default=IGNORE_LABEL,
          help="The index of the label to ignore during the training.",
      )
      parser.add_argument(
          "--num-classes",
          type=int,
          default=NUM_CLASSES,
          help="Number of classes to predict (including background).",
      )
      parser.add_argument(
          "--restore-from",
          type=str,
          help="Where restore model parameters from.",
      )
      parser.add_argument(
          "--gpu", type=str, default="7", help="choose gpu device."
      )
      parser.add_argument(
          "--input-size",
          type=str,
          default=INPUT_SIZE,
          help="Comma-separated string with height and width of images.",
      )
      parser.add_argument(
          "--local_rank", type=int, default=0, help="choose gpu numbers"
      )
      parser.add_argument(
          "--dist-backend",
          default="nccl",
          type=str,
          help="distributed backend",
      )
      parser.add_argument(
          "--model_type", type=int, default=0, help="choose model type"
      )
      return parser.parse_args()
  
file_path: insightface/parsing/dml_csr/test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import argparse
  import cv2
  import numpy
  import matplotlib.pyplot
  import os
  import torch
  import torch.backends.cudnn
  import torchvision.transforms
  from copy import deepcopy
  from inplace_abn import InPlaceABN
  from dataset import datasets
  from networks import dml_csr
  from utils import miou
label_desc: Use image node_id 1 for calling a global function with example usage: get_arguments() and returns: parser