code: def read_image_file(path: str) -> torch.Tensor:
      x = read_sn3_pascalvincent_tensor(path, strict=False)
      if x.dtype != torch.uint8:
          raise TypeError(
              f"x should be of dtype torch.uint8 instead of {x.dtype}"
          )
      if x.ndimension() != 3:
          raise ValueError(
              f"x should have 3 dimension instead of {x.ndimension()}"
          )
      return x
  
imports: import codecs
  import os
  import os.path
  import shutil
  import string
  import sys
  import warnings
  from typing import Any, Callable, Dict, List, Optional, Tuple
  from urllib.error import URLError
  import numpy
  import torch
  from PIL import Image
  from .utils import _flip_byte_order, check_integrity, download_and_extract_archive, extract_archive, verify_str_arg
  from .vision import VisionDataset
label_desc: Use image node_id 4 for calling a global function with example usage: read_image_file(path) and returns: x