code: def ignore_jit_no_profile_information_warning():
      # Calling a scripted object often triggers a warning like
      # `UserWarning: operator() profile_node %$INT1 : int[] = prim::profile_ivalue($INT2) does not have profile information`
      # with varying `INT1` and `INT2`. Since these are uninteresting for us and only clutter the test summary, we ignore
      # them.
      with warnings.catch_warnings():
          warnings.filterwarnings(
              "ignore",
              message=re.escape("operator() profile_node %"),
              category=UserWarning,
          )
          yield
  
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 33 for calling a global function with example usage: ignore_jit_no_profile_information_warning() without return types