code: def transform_video(
      video: numpy.ndarray, model_name: str = None, **kwargs
  ):
      if model_name:
          cfg = video_configs[model_name]
          cfg.update(model_name=model_name, **kwargs)
      else:
          cfg = get_configs(**kwargs)
      tsfm = VideoTransforms(cfg)
      output = tsfm(video)
      return output
  
imports: import os
  import logging
  import numpy
  import numbers
  import torch
  from torch import nn
  from torchvision.transforms import Compose
label_desc: Use image node_id 1 for calling a global function with example usage: transform_video(video, model_name) and returns: output