code: def test_in_memory_dataset_copy():
      data_list = [Data(x=torch.randn(5, 16)) for _ in range(4)]
      dataset = MyTestDataset(data_list)
  
      copied_dataset = dataset.copy()
      assert id(copied_dataset) != id(dataset)
  
      assert len(copied_dataset) == len(dataset) == 4
      for copied_data, data in zip(copied_dataset, dataset):
          assert torch.equal(copied_data.x, data.x)
  
      copied_dataset = dataset.copy([1, 2])
      assert len(copied_dataset) == 2
      assert torch.equal(copied_dataset[0].x, data_list[1].x)
      assert torch.equal(copied_dataset[1].x, data_list[2].x)
  
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 6 for calling a global function with example usage: test_in_memory_dataset_copy() without return types