code: def test_script(self):
      for padding_flag in [True, False]:
          net = HoVerNet(
              mode=HoVerNet.Mode.FAST, decoder_padding=padding_flag
          )
      test_data = torch.randn(1, 3, 256, 256)
      test_script_save(net, test_data)
  
file_path: MONAI/tests/test_hovernet.py
imports: from __future__ import annotations
  import unittest
  import torch
  from parameterized import parameterized
  from monai.networks import eval_mode, train_mode
  from monai.networks.nets import HoVerNet
  from monai.networks.nets.hovernet import _DenseLayerDecoder
  from tests.utils import test_script_save
label_desc: Use image node_id 3 for calling the TestHoverNet obj's underlying member method code with example usage: obj.test_script() without return types