code: def test_normalize_arg(normalize):
      """Test that normalize argument works as expected."""
      metric = LearnedPerceptualImagePatchSimilarity(
          net_type="squeeze", normalize=normalize
      )
      res = metric(_inputs.img1[0], _inputs.img2[1])
      res2 = _compare_fn(
          _inputs.img1[0],
          _inputs.img2[1],
          net_type="squeeze",
          normalize=normalize,
      )
      assert res == res2
  
imports: from functools import partial
  from typing import NamedTuple
  import pytest
  import torch
  from lpips import LPIPS
  from torch import Tensor
  from torchmetrics.functional.image.lpips import learned_perceptual_image_patch_similarity
  from torchmetrics.image.lpip import LearnedPerceptualImagePatchSimilarity
  from torchmetrics.utilities.imports import _LPIPS_AVAILABLE, _TORCHVISION_AVAILABLE
  from unittests.helpers import seed_all
  from unittests.helpers.testers import MetricTester
label_desc: Use image node_id 2 for calling a global function with example usage: test_normalize_arg(normalize) without return types