code: def setup_for_sampling(args):
      args.update(default_configure)
      args.update(sampling_configure)
      set_random_seed()
      args["device"] = "cuda:0" if torch.cuda.is_available() else "cpu"
      args["log_dir"] = setup_log_dir(args, sampling=True)
      return args
  
imports: import sys
  import datetime
  import dgl
  import errno
  import numpy
  import os
  import pickle
  import random
  import torch
  from dgl.data.utils import download, get_download_dir, _get_dgl_url
  import os.path
  from pprint import pprint
  from scipy import sparse
  from scipy import io
label_desc: Use image node_id 6 for calling a global function with example usage: setup_for_sampling(args) and returns: args