code: def __init__(self, mean=None, std=None, n_frms=MAX_INT):
      if mean is None:
          mean = (0.48145466, 0.4578275, 0.40821073)
      if std is None:
          std = (0.26862954, 0.26130258, 0.27577711)
  
      self.normalize = transforms_video.NormalizeVideo(mean, std)
  
      self.n_frms = n_frms
  
imports: import torch
  from lavis.common.registry import registry
  from lavis.datasets.data_utils import load_video, load_clip
  from lavis.processors import transforms_video
  from lavis.processors.base_processor import BaseProcessor
  from lavis.processors.randaugment import VideoRandomAugment
  from lavis.processors import functional_video
  from omegaconf import OmegaConf
  from torchvision import transforms
label_desc: Use image node_id 1 to create a new AlproVideoBaseProcessor object from inherited base classes: BaseProcessor with example: obj = AlproVideoBaseProcessor(mean, std, n_frms)