code: def PreStem(name=None):
      """Normalizes inputs with ImageNet-1k mean and std."""
      if name is None:
          name = "prestem" + str(backend.get_uid("prestem"))
  
      def apply(x):
          x = layers.Normalization(
              mean=[0.485 * 255, 0.456 * 255, 0.406 * 255],
              variance=[
                  (0.229 * 255) ** 2,
                  (0.224 * 255) ** 2,
                  (0.225 * 255) ** 2,
              ],
              name=name + "_prestem_normalization",
          )(x)
          return x
  
      return apply
  
imports: import numpy
  from keras import backend
  from keras import initializers
  from keras import layers
  from keras import ops
  from keras import random
  from keras.api_export import keras_export
  from keras.applications import imagenet_utils
  from keras.layers.layer import Layer
  from keras.models import Functional
  from keras.models import Sequential
  from keras.ops import operation_utils
  from keras.utils import file_utils
label_desc: Use image node_id 2 for calling a global function with example usage: PreStem(name) and returns: apply, x