code: def compare(self) -> None:
      actual, expected = self.actual, self.expected
  
      self._compare_attributes(actual, expected)
      actual, expected = self._equalize_attributes(actual, expected)
  
      if self.mae:
          if actual.dtype is torch.uint8:
              actual, expected = actual.to(torch.int), expected.to(
                  torch.int
              )
          mae = float(torch.abs(actual - expected).float().mean())
          if mae > self.atol:
              self._fail(
                  AssertionError,
                  f"The MAE of the images is {mae}, but only {self.atol} is allowed.",
              )
      else:
          super()._compare_values(actual, expected)
  
imports: import contextlib
  import functools
  import itertools
  import os
  import pathlib
  import random
  import re
  import shutil
  import sys
  import tempfile
  import warnings
  from subprocess import CalledProcessError, check_output, STDOUT
  import numpy
  import PIL.Image
  import pytest
  import torch
  import torch.testing
  from PIL import Image
  from torch.testing._comparison import BooleanPair, NonePair, not_close_error_metas, NumberPair, TensorLikePair
  from torchvision import io, tv_tensors
  from torchvision.transforms._functional_tensor import _max_value
  from torchvision.transforms.v2.functional import to_image, to_pil_image
label_desc: Use image node_id 2 for calling the ImagePair obj's underlying member method code with example usage: obj.compare() without return types