code: def sample_prior(self, prob_decode=False):
      tree_vec = create_var(torch.randn(1, self.latent_size / 2), False)
      mol_vec = create_var(torch.randn(1, self.latent_size / 2), False)
      return self.decode(tree_vec, mol_vec, prob_decode)
  
imports: import torch
  import torch.nn
  from .mol_tree import Vocab, MolTree
  from .nnutils import create_var
  from .jtnn_enc_bo import JTNNEncoderBO
  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 9 for calling the JTNNVAEBO obj's underlying member method code with example usage: obj.sample_prior(prob_decode) and returns: self