code: def test_deep_supervision_shape(self):
      net = BasicUNetPlusPlus(
          spatial_dims=2,
          deep_supervision=True,
          in_channels=3,
          out_channels=3,
      )
      test_data = torch.randn(16, 3, 32, 32)
      with eval_mode(net):
          result = net(test_data)
      self.assertEqual(result[0].shape, test_data.shape)
  
file_path: MONAI/tests/test_basic_unetplusplus.py
imports: from __future__ import annotations
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import eval_mode
  from monai.networks.nets import BasicUNetPlusPlus
  from tests.utils import test_script_save
label_desc: Use image node_id 2 for calling the TestBasicUNETPlusPlus obj's underlying member method code with example usage: obj.test_deep_supervision_shape() without return types