code: def preprocess_images(images):
      """Applies preprocessing operations for Inception images.
  
      Because this will run in model_fn, on the accelerator, we use operations
      that efficiently execute there.
  
      Args:
        images: A Tensor of shape [batch_size height, width, channel] with uint8
          values.
  
      Returns:
        A tensor of images of shape [batch_size height, width, channel]
        containing floating point values, with all points rescaled between
        -1 and 1 and possibly resized.
      """
      images = tf.cast(images, dtype=tf.float32)
      images = tf.subtract(images, 128.0)
      images = tf.math.divide(images, 128.0)
      return images
  
imports: import json
  from typing import Optional
  from absl import logging
  import numpy
  import tensorflow
  from deepvariant.protos import deepvariant_pb2
  from third_party.nucleus.io import sharded_file_utils
  from third_party.nucleus.io import tfrecord
  from third_party.nucleus.protos import variants_pb2
  from tensorflow.core.example import example_pb2
label_desc: Use image node_id 28 for calling a global function with example usage: preprocess_images(images) and returns: images