code: def forward(self, graph):
      # node and relation features
      n_feats = self.n_embds
      if self.num_bases > 0:
          r_embds = th.mm(self.weights, self.basis)
          r_feats = r_embds
      else:
          r_feats = self.rel_embds
  
      for layer, dropout in zip(self.layers, self.dropouts):
          n_feats, r_feats = layer(graph, n_feats, r_feats)
          n_feats = dropout(n_feats)
  
      return n_feats, r_feats
  
file_path: dgl/examples/pytorch/compGCN/models.py
imports: import dgl
  import dgl.function
  import torch
  import torch.nn
  import torch.nn.functional
  import torch.optim
  from utils import ccorr
label_desc: Use image node_id 2 for calling the CompGCN obj's underlying member method code with example usage: obj.forward(graph) and returns: n_feats,  r_feats