code: def can_assemble(mol_tree, u, v_node_dict):
      u_node_dict = mol_tree.nodes_dict[u]
      u_neighbors = mol_tree.graph.successors(u)
      u_neighbors_node_dict = [
          mol_tree.nodes_dict[_u]
          for _u in u_neighbors
          if _u in mol_tree.nodes_dict
      ]
      neis = u_neighbors_node_dict + [v_node_dict]
      for i, nei in enumerate(neis):
          nei["nid"] = i
  
      neighbors = [nei for nei in neis if nei["mol"].GetNumAtoms() > 1]
      neighbors = sorted(
          neighbors, key=lambda x: x["mol"].GetNumAtoms(), reverse=True
      )
      singletons = [
          nei for nei in neis if nei["mol"].GetNumAtoms() == 1
      ]
      neighbors = singletons + neighbors
      cands = enum_assemble_nx(u_node_dict, neighbors)
      return len(cands) > 0
  
file_path: dgl/examples/pytorch/jtnn/jtnn/jtnn_dec.py
imports: import dgl.function
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from dgl import batch, dfs_labeled_edges_generator, line_graph
  from .chemutils import enum_assemble_nx, get_mol
  from .mol_tree_nx import DGLMolTree
  from .nnutils import cuda, GRUUpdate, tocpu
label_desc: Use image node_id 4 for calling a global function with example usage: can_assemble(mol_tree, u, v_node_dict) and returns: unknown