code: def forward(self, g, lg, pm_pd):
      # compute the degrees
      deg_g = g.in_degrees().float().unsqueeze(1)
      deg_lg = lg.in_degrees().float().unsqueeze(1)
      # use degree as the input feature
      x, lg_x = deg_g, deg_lg
      x, lg_x = self.layer1(g, lg, x, lg_x, deg_g, deg_lg, pm_pd)
      x, lg_x = self.layer2(g, lg, x, lg_x, deg_g, deg_lg, pm_pd)
      x, lg_x = self.layer3(g, lg, x, lg_x, deg_g, deg_lg, pm_pd)
      return self.linear(x)
  
imports: import os
  import dgl
  import torch
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl.data import citation_graph
  import matplotlib.pyplot
  import networkx
  import dgl.function
  from torch.utils.data import DataLoader
label_desc: Use image node_id 2 for calling the LGNN obj's underlying member method code with example usage: obj.forward(g, lg, pm_pd) and returns: self