code: def test_assert_image_tensor(device, func, args):
      shape = (100,)
      tensor = torch.rand(*shape, dtype=torch.float, device=device)
      with pytest.raises(
          Exception, match=r"Tensor is not a torch image."
      ):
          func(tensor, *args)
  
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 28 for calling a global function with example usage: test_assert_image_tensor(device, func, args) without return types