class_docstr: Testing data loader working with the randomizable interface
class_docstr_tok: ["Testing","data","loader","working","with","the","randomizable","interface"]
code: def test_zipdataset(self):
      dataset = ZipDataset(
          [
              _RandomDataset(),
              ZipDataset([_RandomDataset(), _RandomDataset()]),
          ]
      )
      dataloader = DataLoader(dataset, batch_size=2, num_workers=2)
      output = []
      for _ in range(2):
          for batch in dataloader:
              output.extend(
                  [convert_to_numpy(batch, wrap_sequence=False)]
              )
      assert_allclose(
          np.stack(output).flatten()[:7],
          np.array([594, 170, 594, 170, 594, 170, 524]),
      )
  
imports: from __future__ import annotations
  import sys
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.data import CacheDataset, DataLoader, Dataset, ZipDataset
  from monai.transforms import Compose, DataStatsd, Randomizable, SimulateDelayd
  from monai.utils import convert_to_numpy, set_determinism
  from tests.utils import assert_allclose
label_desc: Use image node_id 4 for calling the TestLoaderRandom obj's underlying member method code with example usage: obj.test_zipdataset() without return types