code: def forward(self, mol_trees):
      mol_tree_batch = batch(mol_trees)
  
      # Build line graph to prepare for belief propagation
      mol_tree_batch_lg = line_graph(
          mol_tree_batch, backtracking=False, shared=True
      )
  
      return self.run(mol_tree_batch, mol_tree_batch_lg)
  
file_path: dgl/examples/pytorch/jtnn/jtnn/jtnn_enc.py
imports: import dgl.function
  import numpy
  import torch
  import torch.nn
  from dgl import batch, bfs_edges_generator, line_graph
  from .nnutils import cuda, GRUUpdate, tocpu
label_desc: Use image node_id 2 for calling the DGLJTNNEncoder obj's underlying member method code with example usage: obj.forward(mol_trees) and returns: self