code: def test_zoom_2(self):
      affine = torch.as_tensor(
          [[2.0, 0.0, 0.0], [0.0, 2.0, 0.0]], dtype=torch.float32
      )
      image = (
          torch.arange(1.0, 13.0)
          .view(1, 1, 3, 4)
          .to(device=torch.device("cpu:0"))
      )
      out = AffineTransform((1, 2))(image, affine)
      expected = [[[[1.458333, 4.958333]]]]
      np.testing.assert_allclose(out, expected, atol=1e-5, rtol=_rtol)
  
imports: from __future__ import annotations
  import unittest
  import numpy
  import torch
  from parameterized import parameterized
  from monai.networks import normalize_transform, to_norm_affine
  from monai.networks.layers import AffineTransform
  from tests.utils import is_tf32_env
label_desc: Use image node_id 6 for calling the TestAffineTransform obj's underlying member method code with example usage: obj.test_zoom_2() without return types