code: def test_to_tensor_video(self):
      numFrames, height, width = 64, 4, 4
      trans = transforms.ToTensorVideo()
  
      with pytest.raises(TypeError):
          np_rng = np.random.RandomState(0)
          trans(np_rng.rand(numFrames, height, width, 1).tolist())
      with pytest.raises(TypeError):
          trans(
              torch.rand(
                  (numFrames, height, width, 1), dtype=torch.float
              )
          )
  
      with pytest.raises(ValueError):
          trans(
              torch.ones(
                  (3, numFrames, height, width, 3), dtype=torch.uint8
              )
          )
      with pytest.raises(ValueError):
          trans(torch.ones((height, width, 3), dtype=torch.uint8))
      with pytest.raises(ValueError):
          trans(torch.ones((width, 3), dtype=torch.uint8))
      with pytest.raises(ValueError):
          trans(torch.ones((3), dtype=torch.uint8))
  
      trans.__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 5 for calling the TestVideoTransforms obj's underlying member method code with example usage: obj.test_to_tensor_video() without return types