code: def inference(g, lg, deg_g, deg_lg, pm_pd):
      g = g.to(dev)
      lg = lg.to(dev)
      deg_g = deg_g.to(dev).unsqueeze(1)
      deg_lg = deg_lg.to(dev).unsqueeze(1)
      pm_pd = pm_pd.to(dev)
  
      z = model(g, lg, deg_g, deg_lg, pm_pd)
  
      return z
  
file_path: dgl/examples/pytorch/line_graph/train.py
imports: from __future__ import division
  import argparse
  import time
  from itertools import permutations
  import gnn
  import numpy
  import torch
  import torch.nn.functional
  import torch.optim
  from dgl.data import SBMMixtureDataset
  from torch.utils.data import DataLoader
label_desc: Use image node_id 4 for calling a global function with example usage: inference(g, lg, deg_g, deg_lg, pm_pd) and returns: z