code: def test_resize_fn() -> None:
      bs = 2
      sz = (10, 8)
      c = 3
      t = 4
      new_sz = (6, 4)
      data = {
          "samples": {
              "video": torch.randn(bs, t, c, *sz),
              "mask": torch.rand(bs, t, *sz),
          }
      }
      new_data = _resize_fn(data, size=new_sz)
      video = data["samples"]["video"]
      mask = data["samples"]["mask"]
      assert video.shape == (bs, t, c, *new_sz)
      assert mask.shape == (bs, t, *new_sz)
  
file_path: ml-cvnets/tests/transforms/test_video.py
imports: import operator
  import os
  from pathlib import Path
  from typing import Dict, Tuple
  import pytest
  import torch
  from data.transforms.video import CropByBoundingBox, SaveInputs, ShuffleAudios, _resize_fn
  from data.video_reader.pyav_reader import PyAVReader
  from tests.configs import get_config
label_desc: Use image node_id 1 for calling a global function with example usage: test_resize_fn() without return types