code: def two_hetero_batch_with_isolated_ntypes():
      g1 = dgl.heterograph(
          {
              ("user", "follows", "user"): ([0, 1], [1, 2]),
              ("user", "follows", "developer"): ([0, 1], [1, 2]),
              ("user", "plays", "game"): ([0, 1, 2, 3], [0, 0, 1, 1]),
          },
          num_nodes_dict={
              "user": 4,
              "game": 2,
              "developer": 3,
              "platform": 2,
          },
      )
      g2 = dgl.heterograph(
          {
              ("user", "follows", "user"): ([0, 1], [1, 2]),
              ("user", "follows", "developer"): ([0, 1], [1, 2]),
              ("user", "plays", "game"): ([0, 1, 2], [0, 0, 1]),
          },
          num_nodes_dict={
              "user": 3,
              "game": 2,
              "developer": 3,
              "platform": 3,
          },
      )
      return [g1, g2]
  
imports: from collections import defaultdict
  import backend
  import dgl
  import networkx
  import numpy
  import scipy.sparse
label_desc: Use image node_id 21 for calling a global function with example usage: two_hetero_batch_with_isolated_ntypes() and returns: list