code: def decode(self, x_tree_vecs, x_mol_vecs, prob_decode):
      # currently do not support batch decoding
      assert x_tree_vecs.size(0) == 1 and x_mol_vecs.size(0) == 1
  
      pred_root, pred_nodes = self.decoder.decode(
          x_tree_vecs, prob_decode
      )
      if len(pred_nodes) == 0:
          return None
      elif len(pred_nodes) == 1:
          return pred_root.smiles
  
      # Mark nid & is_leaf & atommap
      for i, node in enumerate(pred_nodes):
          node.nid = i + 1
          node.is_leaf = len(node.neighbors) == 1
          if len(node.neighbors) > 1:
              set_atommap(node.mol, node.nid)
  
      scope = [(0, len(pred_nodes))]
      jtenc_holder, mess_dict = JTNNEncoder.tensorize_nodes(
          pred_nodes, scope
      )
      _, tree_mess = self.jtnn(*jtenc_holder)
      # Important: tree_mess is a matrix, mess_dict is a python dict
      tree_mess = (tree_mess, mess_dict)
  
      x_mol_vecs = self.A_assm(x_mol_vecs).squeeze()  # bilinear
  
      cur_mol = copy_edit_mol(pred_root.mol)
      global_amap = [{}] + [{} for node in pred_nodes]
      global_amap[1] = {
          atom.GetIdx(): atom.GetIdx() for atom in cur_mol.GetAtoms()
      }
  
      cur_mol, _ = self.dfs_assemble(
          tree_mess,
          x_mol_vecs,
          pred_nodes,
          cur_mol,
          global_amap,
          [],
          pred_root,
          None,
          prob_decode,
          check_aroma=True,
      )
      if cur_mol is None:
          cur_mol = copy_edit_mol(pred_root.mol)
          global_amap = [{}] + [{} for node in pred_nodes]
          global_amap[1] = {
              atom.GetIdx(): atom.GetIdx()
              for atom in cur_mol.GetAtoms()
          }
          cur_mol, pre_mol = self.dfs_assemble(
              tree_mess,
              x_mol_vecs,
              pred_nodes,
              cur_mol,
              global_amap,
              [],
              pred_root,
              None,
              prob_decode,
              check_aroma=False,
          )
          if cur_mol is None:
              cur_mol = pre_mol
  
      if cur_mol is None:
          return None
  
      cur_mol = cur_mol.GetMol()
      set_atommap(cur_mol)
      cur_mol = Chem.MolFromSmiles(Chem.MolToSmiles(cur_mol))
      return Chem.MolToSmiles(cur_mol) if cur_mol is not None else None
  
imports: import copy
  import math
  import torch
  import torch.nn
  import torch.nn.functional
  import rdkit
  import rdkit.Chem
  from .mol_tree import MolTree
  from .nnutils import create_var
  from .jtnn_enc import JTNNEncoder
  from .jtnn_dec import JTNNDecoder
  from .mpn import MPN
  from .jtmpn import JTMPN
  from .datautils import tensorize
  from .chemutils import enum_assemble, set_atommap, copy_edit_mol, attach_mols
label_desc: Use image node_id 9 for calling the JTNNVAE obj's underlying member method code with example usage: obj.decode(x_tree_vecs, x_mol_vecs, prob_decode) and returns: unknown, None, None, pred_root