code: def norm_tree(r_list, tgt_vocab):
      q = [Tree.convert_to_tree(r_list, 0, len(r_list), tgt_vocab)]
      head = 0
      while head < len(q):
          t = q[head]
          exchangeable_symbol_idx_list = (
              tgt_vocab.get_symbol_idx_for_list(["and", "or"])
          )
          if len(t.children) > 0 and (
              t.children[0] in exchangeable_symbol_idx_list
          ):
              k = []
              for i in range(1, len(t.children)):
                  if isinstance(t.children[i], Tree):
                      k.append((t.children[i].to_string(), i))
                  else:
                      k.append((str(t.children[i]), i))
              sorted_t_dict = []
              k.sort(key=itemgetter(0))
              for key1 in k:
                  sorted_t_dict.append(t.children[key1[1]])
  
              for i in range(t.num_children - 1):
                  t.children[i + 1] = sorted_t_dict[i]
          for i in range(len(t.children)):
              if isinstance(t.children[i], Tree):
                  q.append(t.children[i])
  
          head = head + 1
      return q[0].to_list(tgt_vocab)
  
imports: from operator import itemgetter
  import numpy
label_desc: Use image node_id 7 for calling the Tree obj's underlying member method code with example usage: obj.norm_tree(r_list, tgt_vocab) and returns: q