code: def augment(x, shift: int):
      y = tf.image.random_flip_left_right(x["image"])
      y = tf.pad(y, [[shift] * 2, [shift] * 2, [0] * 2], mode="REFLECT")
      return dict(
          image=tf.image.random_crop(y, tf.shape(x["image"])),
          label=x["label"],
      )
  
imports: import functools
  import os
  from typing import Callable
  import jax
  import jax.numpy
  import numpy
  import tensorflow
  import tensorflow_datasets
  from absl import app, flags
  from tqdm import tqdm, trange
  import objax
  from examples.image_classification.tfdata.data import DataSet
  from objax.jaxboard import SummaryWriter, Summary
  from objax.util import EasyDict
  from objax.zoo import convnet, wide_resnet
label_desc: Use image node_id 1 for calling a global function with example usage: augment(x, shift) and returns: dict