code: def preprocess(img1_batch, img2_batch):
      img1_batch = F.resize(
          img1_batch, size=[520, 960], antialias=False
      )
      img2_batch = F.resize(
          img2_batch, size=[520, 960], antialias=False
      )
      return transforms(img1_batch, img2_batch)
  
file_path: vision/gallery/others/plot_optical_flow.py
imports: import numpy
  import torch
  import matplotlib.pyplot
  import torchvision.transforms.functional
  import tempfile
  from pathlib import Path
  from urllib.request import urlretrieve
  from torchvision.io import read_video
  from torchvision.models.optical_flow import Raft_Large_Weights
  from torchvision.models.optical_flow import raft_large
  from torchvision.utils import flow_to_image
label_desc: Use image node_id 2 for calling a global function with example usage: preprocess(img1_batch, img2_batch) and returns: transforms