code: def convert_images_from_uint8(
      images, drange=[-1, 1], nhwc_to_nchw=False
  ):
      """Convert a minibatch of images from uint8 to float32 with configurable dynamic range.
      Can be used as an input transformation for Network.run().
      """
      images = tf.cast(images, tf.float32)
      if nhwc_to_nchw:
          images = tf.transpose(images, [0, 3, 1, 2])
      return images * ((drange[1] - drange[0]) / 255) + drange[0]
  
imports: import os
  import numpy
  import tensorflow
  import logging
  import tensorflow.contrib
  from typing import Any, Iterable, List, Union
label_desc: Use image node_id 18 for calling a global function with example usage: convert_images_from_uint8(images, drange, nhwc_to_nchw) and returns: unknown