code: def test_stored_in_memory_dataset(tmp_path):
      x1 = torch.tensor([[1.0], [1.0], [1.0]])
      x2 = torch.tensor([[2.0], [2.0], [2.0], [2.0]])
      edge_index = torch.tensor([[0, 1, 1, 2], [1, 0, 2, 1]])
  
      data1 = Data(
          x1, edge_index, num_nodes=3, test_int=1, test_str="1"
      )
      data2 = Data(
          x2, edge_index, num_nodes=4, test_int=2, test_str="2"
      )
  
      dataset = MyStoredTestDataset(tmp_path, [data1, data2])
      assert dataset._data.num_nodes == 7
      assert dataset._data._num_nodes == [3, 4]
  
      assert torch.equal(dataset[0].x, x1)
      assert torch.equal(dataset[0].edge_index, edge_index)
      assert dataset[0].num_nodes == 3
      assert torch.equal(dataset[0].test_int, torch.tensor([1]))
      assert dataset[0].test_str == "1"
  
      assert torch.equal(dataset[1].x, x2)
      assert torch.equal(dataset[1].edge_index, edge_index)
      assert dataset[1].num_nodes == 4
      assert torch.equal(dataset[1].test_int, torch.tensor([2]))
      assert dataset[1].test_str == "2"
  
imports: import copy
  import pytest
  import torch
  from torch_geometric import EdgeIndex
  from torch_geometric.data import Data, HeteroData, InMemoryDataset
  from torch_geometric.datasets import KarateClub
  from torch_geometric.testing import withPackage
  from torch_geometric.transforms import BaseTransform
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 2 for calling a global function with example usage: test_stored_in_memory_dataset(tmp_path) without return types