code: def setUp(self):
      set_determinism(seed=0)
  
      im, seg = create_test_image_3d(
          28,
          25,
          63,
          rad_max=10,
          noise_max=1,
          num_objs=4,
          num_seg_classes=1,
      )
      self.img_name = make_nifti_image(im)
      self.seg_name = make_nifti_image(seg)
      self.device = torch.device(
          "cuda:0" if torch.cuda.is_available() else "cpu:0"
      )
  
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 1 for calling the TestIntegrationSlidingWindow obj's underlying member method code with example usage: obj.setUp() without return types