code: def parse_args():
      parser = argparse.ArgumentParser(
          description="Validate Pre-trained RelDN Model."
      )
      parser.add_argument(
          "--gpus",
          type=str,
          default="0",
          help="Training with GPUs, you can specify 1,3 for example.",
      )
      parser.add_argument(
          "--batch-size",
          type=int,
          default=8,
          help="Total batch-size for training.",
      )
      parser.add_argument(
          "--metric",
          type=str,
          default="sgdet",
          help="Evaluation metric, could be 'predcls', 'phrcls', 'sgdet' or 'sgdet+'.",
      )
      parser.add_argument(
          "--pretrained-faster-rcnn-params",
          type=str,
          required=True,
          help="Path to saved Faster R-CNN model parameters.",
      )
      parser.add_argument(
          "--reldn-params",
          type=str,
          required=True,
          help="Path to saved Faster R-CNN model parameters.",
      )
      parser.add_argument(
          "--faster-rcnn-params",
          type=str,
          required=True,
          help="Path to saved Faster R-CNN model parameters.",
      )
      parser.add_argument(
          "--log-dir",
          type=str,
          default="reldn_output.log",
          help="Path to save training logs.",
      )
      parser.add_argument(
          "--freq-prior",
          type=str,
          default="freq_prior.pkl",
          help="Path to saved frequency prior data.",
      )
      parser.add_argument(
          "--verbose-freq",
          type=int,
          default=100,
          help="Frequency of log printing in number of iterations.",
      )
      args = parser.parse_args()
      return args
  
file_path: dgl/examples/mxnet/scenegraph/validate_reldn.py
imports: import argparse
  import logging
  import time
  import mxnet
  import numpy
  from data import *
  from gluoncv.data.batchify import Pad
  from model import faster_rcnn_resnet101_v1d_custom, RelDN
  from mxnet import gluon, nd
  from utils import *
  import dgl
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: args