code: def test_interpolation_type(self, device):
      tensor, pil_img = _create_data(26, 26, device=device)
  
      res1 = F.affine(
          tensor,
          45,
          translate=[0, 0],
          scale=1.0,
          shear=[0.0, 0.0],
          interpolation=PIL.Image.BILINEAR,
      )
      res2 = F.affine(
          tensor,
          45,
          translate=[0, 0],
          scale=1.0,
          shear=[0.0, 0.0],
          interpolation=BILINEAR,
      )
      assert_equal(res1, res2)
  
imports: import colorsys
  import itertools
  import math
  import os
  from functools import partial
  from typing import Sequence
  import numpy
  import PIL.Image
  import pytest
  import torch
  import torchvision.transforms
  import torchvision.transforms._functional_pil
  import torchvision.transforms._functional_tensor
  import torchvision.transforms.functional
  from common_utils import _assert_approx_equal_tensor_to_pil, _assert_equal_tensor_to_pil, _create_data, _create_data_batch, _test_fn_on_batch, assert_equal, cpu_and_cuda, needs_cuda
  from torchvision.transforms import InterpolationMode
label_desc: Use image node_id 7 for calling the TestAffine obj's underlying member method code with example usage: obj.test_interpolation_type(device) without return types