code: def test_decode_jpeg_cuda_errors():
      data = read_file(next(get_images(IMAGE_ROOT, ".jpg")))
      with pytest.raises(
          RuntimeError,
          match="Expected a non empty 1-dimensional tensor",
      ):
          decode_jpeg(data.reshape(-1, 1), device="cuda")
      with pytest.raises(
          RuntimeError, match="input tensor must be on CPU"
      ):
          decode_jpeg(data.to("cuda"), device="cuda")
      with pytest.raises(
          RuntimeError, match="Expected a torch.uint8 tensor"
      ):
          decode_jpeg(data.to(torch.float), device="cuda")
      with pytest.raises(RuntimeError, match="Expected a cuda device"):
          torch.ops.image.decode_jpeg_cuda(
              data, ImageReadMode.UNCHANGED.value, "cpu"
          )
  
imports: import glob
  import io
  import os
  import sys
  from pathlib import Path
  import numpy
  import pytest
  import torch
  import torchvision.transforms.functional
  from common_utils import assert_equal, needs_cuda
  from PIL import __version__, Image
  from torchvision.io.image import _read_png_16, decode_image, decode_jpeg, decode_png, encode_jpeg, encode_png, ImageReadMode, read_file, read_image, write_file, write_jpeg, write_png
label_desc: Use image node_id 24 for calling a global function with example usage: test_decode_jpeg_cuda_errors() without return types