code: def test_gradient(self):
      network = nn.Conv2d(in_channels=1, out_channels=2, kernel_size=1)
      dvf2ddf = DVF2DDF(num_steps=1)
      optimizer = SGD(network.parameters(), lr=0.01)
      x = torch.ones((1, 1, 5, 5))
      x = network(x)
      x = dvf2ddf(x)
      loss = torch.sum(x)
      loss.backward()
      optimizer.step()
      np.testing.assert_allclose(
          network.weight.grad.cpu().numpy(),
          np.array([[[[22.471329]]], [[[22.552576]]]]),
      )
  
file_path: MONAI/tests/test_dvf2ddf.py
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from torch import nn
  from torch.optim import SGD
  from monai.networks.blocks.warp import DVF2DDF
  from monai.utils import set_determinism
label_desc: Use image node_id 4 for calling the TestDVF2DDF obj's underlying member method code with example usage: obj.test_gradient() without return types