code: def test_shape(self):
      buffer = ShuffleBuffer([1, 2, 3, 4], seed=0)
      num_workers = 2 if sys.platform == "linux" else 0
      dataloader = DataLoader(
          dataset=buffer,
          batch_size=2,
          num_workers=num_workers,
          persistent_workers=num_workers > 0,
      )
      output = [convert_data_type(x, np.ndarray)[0] for x in dataloader]
      buffer.seed += 1
      output2 = [
          convert_data_type(x, np.ndarray)[0] for x in dataloader
      ]  # test repeating
      if num_workers == 0:
          np.testing.assert_allclose(output, [[2, 1], [3, 4]])
          np.testing.assert_allclose(output2, [[3, 1], [2, 4]])
      else:  # multiprocess shuffle
          np.testing.assert_allclose(
              output, [[2, 3], [1, 4]], err_msg=f"seed {buffer.seed}"
          )
          np.testing.assert_allclose(
              output2, [[1, 4], [2, 3]], err_msg=f"seed {buffer.seed}"
          )
  
file_path: MONAI/tests/test_shuffle_buffer.py
imports: from __future__ import annotations
  import sys
  import unittest
  import numpy
  from monai.data import DataLoader, ShuffleBuffer
  from monai.utils import convert_data_type
  from tests.utils import SkipIfBeforePyTorchVersion
label_desc: Use image node_id 1 for calling the TestShuffleBuffer obj's underlying member method code with example usage: obj.test_shape() without return types