code: def test_random_crop_video(self):
      numFrames = random.randint(4, 128)
      height = random.randint(10, 32) * 2
      width = random.randint(10, 32) * 2
      oheight = random.randint(5, (height - 2) / 2) * 2
      owidth = random.randint(5, (width - 2) / 2) * 2
      clip = torch.randint(
          0, 256, (numFrames, height, width, 3), dtype=torch.uint8
      )
      result = Compose(
          [
              transforms.ToTensorVideo(),
              transforms.RandomCropVideo((oheight, owidth)),
          ]
      )(clip)
      assert result.size(2) == oheight
      assert result.size(3) == owidth
  
      transforms.RandomCropVideo((oheight, owidth)).__repr__()
  
file_path: vision/test/test_transforms_video.py
imports: import random
  import warnings
  import numpy
  import pytest
  import torch
  from common_utils import assert_equal
  from torchvision.transforms import Compose
label_desc: Use image node_id 1 for calling the TestVideoTransforms obj's underlying member method code with example usage: obj.test_random_crop_video() without return types