code: def shape_as_image(images, labels, dummy_dim=False):
      target_shape = (
          (-1, 1, 28, 28, 1) if dummy_dim else (-1, 28, 28, 1)
      )
      return jnp.reshape(images, target_shape), labels
  
imports: import itertools
  import time
  import warnings
  from absl import app
  from absl import flags
  from jax import grad
  from jax import jit
  from jax import random
  from jax import vmap
  from jax.example_libraries import optimizers
  from jax.example_libraries import stax
  from jax.tree_util import tree_flatten, tree_unflatten
  import jax.numpy
  from examples import datasets
  import numpy.random
  from dp_accounting import dp_event
  from dp_accounting import rdp
label_desc: Use image node_id 5 for calling a global function with example usage: shape_as_image(images, labels, dummy_dim) and returns: jnp,  labels