code: def convert_normalized_images(tensor):
      tensor = tensor * 0.225
      tensor = tensor + 0.45
  
      tensor = tensor.clamp(min=0.0, max=1.0)
  
      return tensor
  
imports: import json
  import logging
  import math
  import numpy
  import os
  from datetime import datetime
  import psutil
  import torch
  import torchvision.io
  from fvcore.nn.activation_count import activation_count
  from fvcore.nn.flop_count import flop_count
  from matplotlib import pyplot
  from torch import nn
  from torchvision.utils import make_grid
  import slowfast.utils.logging
  import slowfast.utils.multiprocessing
  from slowfast.datasets.utils import pack_pathway_output
  from slowfast.models.batchnorm_helper import SubBatchNorm3d
  from slowfast.utils.env import pathmgr
label_desc: Use image node_id 11 for calling a global function with example usage: convert_normalized_images(tensor) and returns: tensor