code: def normalize_dimensions(img_pil):
      if len(img_pil.shape) == 3:
          img_pil = img_pil.permute(2, 0, 1)
      else:
          img_pil = img_pil.unsqueeze(0)
      return img_pil
  
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 4 for calling a global function with example usage: normalize_dimensions(img_pil) and returns: img_pil