code: def __init__(
      self,
      actual,
      expected,
      *,
      mae=False,
      **other_parameters,
  ):
      if all(
          isinstance(input, PIL.Image.Image)
          for input in [actual, expected]
      ):
          actual, expected = [
              to_image(input) for input in [actual, expected]
          ]
  
      super().__init__(actual, expected, **other_parameters)
      self.mae = mae
  
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 1 to create a new ImagePair object from inherited base classes: TensorLikePair with example: obj = ImagePair(actual, expected)