code: def test_flatten_unflatten():
      dataset1, dataset2 = [0, 1, 2], [0, 1, 2, 3, 4]
      datasets = [[dataset1, dataset2]]
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
      datasets = {"dataset1": [dataset1], "dataset2": dataset2}
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
  
      dataset1, dataset2 = (0.0, 1.0), (2.0, True)
      datasets = ((dataset1, dataset2),)
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
  
      dataset1, dataset2 = range(3), range(5)
      datasets = [[dataset1, dataset2]]
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
      datasets = {"datasets": {1: dataset1, 2: [dataset1, dataset2]}}
      assert_tree_flatten_unflatten(
          datasets, [dataset1, dataset1, dataset2]
      )
  
      dataset1, dataset2 = torch.randn(2, 3, 2), torch.randn(4, 5, 6)
      datasets = [[dataset1, dataset2]]
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
  
      dataset1, dataset2 = TensorDataset(dataset1), TensorDataset(
          dataset2
      )
      datasets = [[dataset1, dataset2]]
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
  
      dl1, dl2 = DataLoader(range(3), batch_size=4), DataLoader(
          range(5), batch_size=5
      )
      loaders = {"a": dl1, "b": dl2}
      assert_tree_flatten_unflatten(loaders, [dl1, dl2])
  
      dataset1, dataset2 = ["a", "b"], ["c"]
      datasets = [[dataset1, dataset2]]
      assert_tree_flatten_unflatten(datasets, [dataset1, dataset2])
  
imports: import torch
  from lightning.pytorch.utilities._pytree import _tree_flatten, tree_unflatten
  from torch.utils.data import DataLoader, TensorDataset
label_desc: Use image node_id 2 for calling a global function with example usage: test_flatten_unflatten() without return types