code: def test_img_pad_stack(records, pad_value):
      tfmed_records = tfms.batch.ImgPadStack(pad_value=pad_value)(
          records
      )
      imgs = np.asarray([record.img for record in tfmed_records])
  
      expected = np.ones((2, 3, 4, 3), dtype=np.float)
      expected *= np.array(pad_value).reshape(-1)
      expected[0, :2, :4, :3] = 1
      expected[1, :3, :2, :3] = 1
      np.testing.assert_equal(imgs, expected)
  
      before_shapes = [
          (record.height, record.width) for record in tfmed_records
      ]
      assert before_shapes == [(2, 4), (3, 2)]
  
label_desc: Use image node_id 2 for calling a global function with example usage: test_img_pad_stack(records, pad_value) without return types