code: def load_data(args):
      if args.dataset == "cora":
          data = CoraGraphDataset()
      elif args.dataset == "citeseer":
          data = CiteseerGraphDataset()
      else:
          raise ValueError("Unknown dataset: {}".format(args.dataset))
      g = data[0]
      if args.gpu < 0:
          cuda = False
      else:
          cuda = True
          g = g.int().to(args.gpu)
      features = g.ndata["feat"]
      labels = g.ndata["label"]
      train_mask = g.ndata["train_mask"]
      test_mask = g.ndata["test_mask"]
      g = dgl.add_self_loop(g)
      return (
          g,
          features,
          labels,
          train_mask,
          test_mask,
          data.num_classes,
          cuda,
      )
  
imports: import dgl
  import torch
  from dgl.data import CiteseerGraphDataset, CoraGraphDataset
label_desc: Use image node_id 1 for calling a global function with example usage: load_data(args) and returns: g,  features,  labels,  train_mask,  test_mask,  data,  cuda