code: def pad(image, target, padding):
      # assumes that we only pad on the bottom right corners
      padded_image = F.pad(image, (0, 0, padding[0], padding[1]))
      if target is None:
          return padded_image, None
      target = target.copy()
      # should we do something wrt the original size?
      target["size"] = torch.tensor(padded_image.size[::-1])
      if "masks" in target:
          target["masks"] = torch.nn.functional.pad(
              target["masks"], (0, padding[0], 0, padding[1])
          )
      return padded_image, target
  
imports: import random
  import PIL
  import torch
  import torchvision.transforms
  import torchvision.transforms.functional
  from util.box_ops import box_xyxy_to_cxcywh
  from util.misc import interpolate
label_desc: Use image node_id 4 for calling a global function with example usage: pad(image, target, padding) and returns: padded_image,  target, padded_image,  None