code: def pad_examples(x, desired_batch_size):
      """Expand batch to desired size by repeating last slice."""
      batch_pad = desired_batch_size - x.shape[0]
      return np.concatenate([x, np.tile(x[-1], (batch_pad, 1))], axis=0)
  
imports: import collections
  import os
  from absl import logging
  from clu import metric_writers
  from clu import periodic_actions
  from flax import linen
  from flax.training import checkpoints
  from flax.training import common_utils
  import jax
  from jax import random
  import jax.numpy
  from jax.sharding import PartitionSpec, Mesh, NamedSharding
  import ml_collections
  import numpy
  import optax
  import tensorflow
  import input_pipeline
  import models
  import temperature_sampler
  import utils
label_desc: Use image node_id 9 for calling a global function with example usage: pad_examples(x, desired_batch_size) and returns: np