code: def get_params(img, input_size):
      width, height = F.get_image_size(img)
      delta_width = max(input_size[1] - width, 0)
      delta_height = max(input_size[0] - height, 0)
      pad_left = random.randint(0, delta_width)
      pad_top = random.randint(0, delta_height)
      pad_right = delta_width - pad_left
      pad_bottom = delta_height - pad_top
      return pad_left, pad_top, pad_right, pad_bottom
  
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 2 for calling the RandomPad obj's underlying member method code with example usage: obj.get_params(img, input_size) and returns: pad_left,  pad_top,  pad_right,  pad_bottom