code: def test_training(self):
      set_determinism(seed=0)
      with tempfile.TemporaryDirectory() as tempdir:
          output_file = run_test(
              batch_size=2,
              img_name=self.img_name,
              seg_name=self.seg_name,
              output_dir=tempdir,
              device=self.device,
          )
          output_image = nib.load(output_file).get_fdata()
          np.testing.assert_allclose(np.sum(output_image), 33621)
          np.testing.assert_allclose(output_image.shape, (28, 25, 63))
  
imports: from __future__ import annotations
  import os
  import tempfile
  import unittest
  import nibabel
  import numpy
  import torch
  from ignite.engine import Engine, Events
  from torch.utils.data import DataLoader
  from monai.data import ImageDataset, create_test_image_3d
  from monai.inferers import sliding_window_inference
  from monai.networks import eval_mode, predict_segmentation
  from monai.networks.nets import UNet
  from monai.transforms import EnsureChannelFirst, SaveImage
  from monai.utils import pytorch_after, set_determinism
  from tests.utils import DistTestCase, TimedCall, make_nifti_image, skip_if_quick
label_desc: Use image node_id 3 for calling the TestIntegrationSlidingWindow obj's underlying member method code with example usage: obj.test_training() without return types