code: def test_normalize(self):
      video = thwc_to_cthw(create_dummy_video_frames(10, 30, 40)).to(
          dtype=torch.float32
      )
      transform = Normalize(video.mean(), video.std())
  
      actual = transform(video)
      self.assertAlmostEqual(actual.mean().item(), 0)
      self.assertAlmostEqual(actual.std().item(), 1)
  
imports: import unittest
  from collections import Counter
  from itertools import permutations
  import numpy
  import torch
  from pytorchvideo.data.utils import thwc_to_cthw
  from pytorchvideo.transforms import ApplyTransformToKey, AugMix, create_video_transform, CutMix, MixUp, MixVideo, Normalize, OpSampler, Permute, RandAugment, RandomResizedCrop, RandomShortSideScale, ShortSideScale, UniformCropVideo, UniformTemporalSubsample
  from pytorchvideo.transforms.functional import clip_boxes_to_image, convert_to_one_hot, div_255, horizontal_flip_with_boxes, random_crop_with_boxes, random_short_side_scale_with_boxes, short_side_scale, short_side_scale_with_boxes, uniform_crop, uniform_crop_with_boxes, uniform_temporal_subsample, uniform_temporal_subsample_repeated
  from torchvision.transforms import Compose
  from torchvision.transforms._transforms_video import CenterCropVideo, NormalizeVideo, RandomCropVideo, RandomHorizontalFlipVideo
  from utils import create_dummy_video_frames, create_random_bbox
label_desc: Use image node_id 19 for calling the TestTransforms obj's underlying member method code with example usage: obj.test_normalize() without return types