def sample_eval(self):
    tree_vec = create_var(torch.randn(1, (self.latent_size // 2)), False)
    mol_vec = create_var(torch.randn(1, (self.latent_size // 2)), False)
    all_smiles = []
    for i in range(100):
        s = self.decode(tree_vec, mol_vec, prob_decode=True)
        all_smiles.append(s)
    return all_smiles
def sample_eval(self):
    tree_vec = create_var(torch.randn(1, (self.latent_size // 2)), False)
    mol_vec = create_var(torch.randn(1, (self.latent_size // 2)), False)
    all_smiles = []
    for i in range(100):
        s = self.decode(tree_vec, mol_vec, prob_decode=True)
        all_smiles.append(s)
    return all_smiles