code: def test_itk_benchmark(self):
      img, ddf = load_img_and_sample_ddf()
      monai_result = monai_warp(img, ddf)
      itk_result = itk_warp(img, ddf)
      relative_diff = np.mean(
          np.divide(
              monai_result - itk_result,
              itk_result,
              out=np.zeros_like(itk_result),
              where=(itk_result != 0),
          )
      )
      self.assertTrue(relative_diff < 0.01)
  
imports: from __future__ import annotations
  import os
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from torch.autograd import gradcheck
  from monai.config.deviceconfig import USE_COMPILED
  from monai.networks.blocks.warp import Warp
  from monai.transforms import LoadImaged
  from monai.utils import GridSampleMode, GridSamplePadMode
  from tests.utils import SkipIfBeforePyTorchVersion, SkipIfNoModule, download_url_or_skip_test, skip_if_quick, testing_data_config
label_desc: Use image node_id 2 for calling the TestWarp obj's underlying member method code with example usage: obj.test_itk_benchmark() without return types