code: def test_unbatch_nested(self):
      dims = [2, 3]
      G_sizes = [10, 5]
      G_list = []
      for i, size in enumerate(G_sizes):
          G = Graph()
          G.G = nx.complete_graph(i + 1)
          G.node_property = {
              "node_prop0": torch.ones(size, dims[0]) * i,
              "node_prop1": torch.ones(size, dims[1]) * i,
          }
          G_list.append(G)
  
      batch = Batch.from_data_list(G_list)
  
      # reconstruct graph list
      G_list_recon = batch.to_data_list()
      self.assertEqual(
          G_list_recon[0].node_property["node_prop0"].size(0),
          10,
      )
      self.assertEqual(
          G_list_recon[0].node_property["node_prop0"].size(1),
          2,
      )
      self.assertEqual(
          G_list_recon[1].node_property["node_prop1"].size(0),
          5,
      )
      self.assertEqual(
          G_list_recon[1].node_property["node_prop1"].size(1),
          3,
      )
  
file_path: deepsnap/tests/test_batch.py
imports: import math
  import unittest
  from copy import deepcopy
  import torch
  import networkx
  from torch.utils.data import DataLoader
  from torch_geometric.datasets import TUDataset
  from deepsnap.graph import Graph
  from deepsnap.batch import Batch
  from deepsnap.dataset import GraphDataset
  from tests.utils import simple_networkx_graph
label_desc: Use image node_id 4 for calling the TestBatch obj's underlying member method code with example usage: obj.test_unbatch_nested() without return types