code: def train_and_infer(self, idx=0):
      results = []
      _readers = (None, None)
      _w = 2
      if idx == 1:
          _readers = ("itkreader", "itkreader")
          _w = 1
      elif idx == 2:
          _readers = ("itkreader", "nibabelreader")
          _w = 0
  
      results_expected = run_training_test(
          self.data_dir,
          device=self.device,
          cachedataset=0,
          readers=_readers,
          num_workers=_w,
          lazy=False,
      )
      results = run_training_test(
          self.data_dir,
          device=self.device,
          cachedataset=idx,
          readers=_readers,
          num_workers=_w,
          lazy=True,
      )
      self.assertFalse(np.allclose(results, [0]))
      self.assertFalse(np.allclose(results_expected, [0]))
      np.testing.assert_allclose(results, results_expected)
      lazy_files = glob(
          os.path.join(self.data_dir, "output", "*_True_*.nii.gz")
      )
      regular_files = glob(
          os.path.join(self.data_dir, "output", "*_False_*.nii.gz")
      )
      diffs = []
      for a, b in zip(sorted(lazy_files), sorted(regular_files)):
          img_lazy = mt.LoadImage(image_only=True)(a)
          img_regular = mt.LoadImage(image_only=True)(b)
          diff = np.size(img_lazy) - np.sum(
              np.isclose(img_lazy, img_regular, atol=1e-4)
          )
          diff_rate = diff / np.size(img_lazy)
          diffs.append(diff_rate)
          np.testing.assert_allclose(diff_rate, 0.0, atol=0.03)
      print("volume diff:", diffs)
  
imports: from __future__ import annotations
  import os
  import shutil
  import tempfile
  import unittest
  from glob import glob
  import nibabel
  import numpy
  import torch
  import monai
  import monai.transforms
  from monai.data import create_test_image_3d, decollate_batch
  from monai.transforms.utils import has_status_keys
  from monai.utils import TraceStatusKeys, set_determinism
  from tests.utils import HAS_CUPY, DistTestCase, SkipIfBeforePyTorchVersion, skip_if_quick
label_desc: Use image node_id 3 for calling the IntegrationLazyResampling obj's underlying member method code with example usage: obj.train_and_infer(idx) without return types