code: def test_script(self):
      loss = DeepSupervisionLoss(DiceCELoss())
      test_input = torch.ones(2, 2, 8, 8)
      test_script_save(loss, test_input, test_input)
  
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.losses import DeepSupervisionLoss, DiceCELoss, DiceFocalLoss, DiceLoss
  from tests.utils import SkipIfBeforePyTorchVersion, test_script_save
label_desc: Use image node_id 4 for calling the TestDSLossDiceCE obj's underlying member method code with example usage: obj.test_script() without return types