code: def normalize(x, dtype="float32"):
      """
      Normalizes the data to mean 0 and standard deviation 1
      """
      # x/=255.0 raises a TypeError
      # x = x/255.0
  
      # Converting to float32 and normalizing (float32 saves memory)
      x = x.astype(dtype) / 255
      return x
  
file_path: caer/caer/preprocess.py
imports: import os
  import random
  import time
  import numpy
  from .io import imread
  from ._internal import _check_target_size
  from .path import join, list_images
  from .color import to_gray
  from .annotations import Optional, List, Tuple
label_desc: Use image node_id 2 for calling a global function with example usage: normalize(x, dtype) and returns: x