code: def test_in_memory_sparse_tensor_dataset():
      x = torch.randn(11, 16)
      adj = SparseTensor(
          row=torch.tensor([4, 1, 3, 2, 2, 3]),
          col=torch.tensor([1, 3, 2, 3, 3, 2]),
          sparse_sizes=(11, 11),
      )
      data = Data(x=x, adj=adj)
  
      dataset = MyTestDataset([data, data])
      assert len(dataset) == 2
      assert torch.allclose(dataset[0].x, x)
      assert dataset[0].adj.sparse_sizes() == (11, 11)
      assert torch.allclose(dataset[1].x, x)
      assert dataset[1].adj.sparse_sizes() == (11, 11)
  
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 8 for calling a global function with example usage: test_in_memory_sparse_tensor_dataset() without return types