code: def test_decode_png_errors():
      with pytest.raises(
          RuntimeError,
          match="Expected a non empty 1-dimensional tensor",
      ):
          decode_png(torch.empty((), dtype=torch.uint8))
      with pytest.raises(RuntimeError, match="Content is not png"):
          decode_png(torch.randint(3, 5, (300,), dtype=torch.uint8))
      with pytest.raises(
          RuntimeError, match="Out of bound read in decode_png"
      ):
          decode_png(
              read_file(os.path.join(DAMAGED_PNG, "sigsegv.png"))
          )
      with pytest.raises(
          RuntimeError, match="Content is too small for png"
      ):
          decode_png(
              read_file(os.path.join(TOOSMALL_PNG, "heapbof.png"))
          )
  
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 10 for calling a global function with example usage: test_decode_png_errors() without return types