code: def load_img_and_sample_ddf():
      # load image
      img = LoadImaged(keys="img")({"img": FILE_PATH})["img"]
      img = img.detach().numpy()
      # W, H, D -> D, H, W
      img = img.transpose((2, 1, 0)).copy()
  
      # randomly sample ddf such that maximum displacement in each direction equals to one-tenth of the image dimension in
      # that direction.
      ddf = np.random.random((3, *img.shape)).astype(
          np.float32
      )  # (3, D, H, W)
      ddf[0] = ddf[0] * img.shape[0] * 0.1
      ddf[1] = ddf[1] * img.shape[1] * 0.1
      ddf[2] = ddf[2] * img.shape[2] * 0.1
      return img, ddf
  
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 1 for calling a global function with example usage: load_img_and_sample_ddf() and returns: img,  ddf