text: ################################################
  # Not used. Useful if visualization is desired #
  ################################################
  
  import numpy as np 
  
  mean_vec=[0.485, 0.456, 0.406]
  std_vec=[0.229, 0.224, 0.225]
  
  def normalize_np(data,mean,std):
      #input data B*W*H*C
      B,W,H,C=data.shape
      mean=np.array(mean).reshape([1,1,1,C])
      std=np.array(std).reshape([1,1,1,C])
      return (data-mean)/std
  
  def unnormalize_np(data,mean,std):
      #input data B*W*H*C
      B,W,H,C=data.shape
      mean=np.array(mean)#.reshape([1,1,1,C])
      std=np.array(std)#.reshape([1,1,1,C])
      return data*std+mean