code: def normalize(img, mean, std, max_pixel_value=255.0):
      mean = np.array(mean, dtype=np.float32)
      mean *= max_pixel_value
  
      std = np.array(std, dtype=np.float32)
      std *= max_pixel_value
  
      denominator = np.reciprocal(std, dtype=np.float32)
  
      if img.ndim == 3 and img.shape[-1] == 3:
          return normalize_cv2(img, mean, denominator)
      return normalize_numpy(img, mean, denominator)
  
imports: from __future__ import division
  from typing import Optional, Sequence, Union
  from warnings import warn
  import cv2
  import numpy
  import skimage
  from albumentations import random_utils
  from albumentations.augmentations.utils import MAX_VALUES_BY_DTYPE, _maybe_process_in_chunks, clip, clipped, ensure_contiguous, is_grayscale_image, is_rgb_image, non_rgb_warning, preserve_channel_dim, preserve_shape
label_desc: Use image node_id 3 for calling a global function with example usage: normalize(img, mean, std, max_pixel_value) and returns: normalize_numpy, normalize_cv2