code: def _setup_size(
      size,
      error_msg="Please provide only two dimensions (h, w) for size.",
  ):
      if isinstance(size, numbers.Number):
          return int(size), int(size)
  
      if isinstance(size, Sequence) and len(size) == 1:
          return size[0], size[0]
  
      if len(size) != 2:
          raise ValueError(error_msg)
  
      return size
  
imports: import math
  import numbers
  import random
  import warnings
  from typing import List, Sequence, Tuple, Union
  import torch
  import torchvision.transforms.functional
  from PIL import Image
  import numpy
label_desc: Use image node_id 4 for calling a global function with example usage: _setup_size(size, error_msg) and returns: size, int,  int, size,  size