code: def interp_mode_to_str(mode):
      if has_interpolation_mode:
          return _torch_interpolation_to_str[mode]
      else:
          return _pil_interpolation_to_str[mode]
  
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 3 for calling a global function with example usage: interp_mode_to_str(mode) and returns: _torch_interpolation_to_str, _pil_interpolation_to_str