code: def decode(self, tree_vec, mol_vec, prob_decode):
      pred_root, pred_nodes = self.decoder.decode(tree_vec, prob_decode)
  
      # 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)
  
      tree_mess = self.jtnn([pred_root])[0]
  
      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,
          mol_vec,
          pred_nodes,
          cur_mol,
          global_amap,
          [],
          pred_root,
          None,
          prob_decode,
      )
      if cur_mol is None:
          return None
  
      cur_mol = cur_mol.GetMol()
      set_atommap(cur_mol)
      cur_mol = Chem.MolFromSmiles(Chem.MolToSmiles(cur_mol))
      if cur_mol is None:
          return None
  
      smiles2D = Chem.MolToSmiles(cur_mol)
      stereo_cands = decode_stereo(smiles2D)
      if len(stereo_cands) == 1:
          return stereo_cands[0]
      stereo_vecs = self.mpn(mol2graph(stereo_cands))
      stereo_vecs = self.G_mean(stereo_vecs)
      scores = nn.CosineSimilarity()(stereo_vecs, mol_vec)
      _, max_id = scores.max(dim=0)
      return stereo_cands[max_id.data]
  
imports: import torch
  import torch.nn
  from .mol_tree import Vocab, MolTree
  from .nnutils import create_var
  from .jtnn_enc import JTNNEncoder
  from .jtnn_dec import JTNNDecoder
  from .mpn import MPN, mol2graph
  from .jtmpn import JTMPN
  from .chemutils import enum_assemble, set_atommap, copy_edit_mol, attach_mols, atom_equal, decode_stereo
  import rdkit
  import rdkit.Chem
  from rdkit import DataStructs
  from rdkit.Chem import AllChem
  import copy
  import math
label_desc: Use image node_id 10 for calling the JTPropVAE obj's underlying member method code with example usage: obj.decode(tree_vec, mol_vec, prob_decode) and returns: stereo_cands, None, None, stereo_cands