code: def tiny_parse(
      index: int, record: str, image_shape: Tuple[int, int, int]
  ):
      del image_shape
      features = tf.io.parse_single_example(
          record,
          features={
              "image": tf.io.FixedLenFeature([], tf.string),
              "label": tf.io.FixedLenFeature([], tf.int64),
          },
      )
      image = tf.reshape(
          tf.io.decode_raw(features["image"], tf.uint8), [3, 32, 32]
      )
      image = tf.transpose(image, [2, 1, 0])
      image = tf.cast(image, tf.float32) * (2.0 / 255) - 1.0
      return dict(index=index, image=image, label=features["label"])
  
imports: import os
  from typing import Callable, Optional, Tuple, List, Iterable
  import numpy
  import tensorflow
  from absl import flags
label_desc: Use image node_id 3 for calling a global function with example usage: tiny_parse(index, record, image_shape) and returns: dict