code: def can_assemble(node_x, node_y):
      node_x.nid = 1
      node_x.is_leaf = False
      set_atommap(node_x.mol, node_x.nid)
  
      neis = node_x.neighbors + [node_y]
      for i, nei in enumerate(neis):
          nei.nid = i + 2
          nei.is_leaf = len(nei.neighbors) <= 1
          if nei.is_leaf:
              set_atommap(nei.mol, 0)
          else:
              set_atommap(nei.mol, nei.nid)
  
      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, aroma_scores = enum_assemble(node_x, neighbors)
      return len(cands) > 0
  
file_path: DIG/dig/ggraph/method/JTVAE/fast_jtnn/jtnn_dec.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .mol_tree import MolTree, MolTreeNode
  from .chemutils import enum_assemble, set_atommap
  from .nnutils import create_var, GRU
label_desc: Use image node_id 3 for calling a global function with example usage: can_assemble(node_x, node_y) and returns: unknown