code: def pad_examples(x, desired_batch_size):
      """Expand batch to desired size by zeros with the shape of last slice."""
      batch_pad = desired_batch_size - x.shape[0]
      # Padding with zeros to avoid that they get counted in compute_metrics.
      return np.concatenate(
          [x, np.tile(np.zeros_like(x[-1]), (batch_pad, 1))]
      )
  
imports: import functools
  import os
  import time
  from absl import app
  from absl import flags
  from absl import logging
  from flax import jax_utils
  from flax import linen
  from flax.metrics import tensorboard
  from flax.training import common_utils
  from flax.training import train_state
  import jax
  import jax.numpy
  from jax import random
  import numpy
  import optax
  import tensorflow
  import input_pipeline
  import models
label_desc: Use image node_id 6 for calling a global function with example usage: pad_examples(x, desired_batch_size) and returns: np