code: def convert_predictions_to_image_summaries(hook_args):
    
    decode_hparams = hook_args.decode_hparams
    if not decode_hparams.display_decoded_images:
      return []
    predictions = hook_args.predictions[0]
  
    # Display ten random inputs and outputs so that tensorboard does not hang.
    all_summaries = []
    rand_predictions = np.random.choice(predictions, size=10)
    for ind, prediction in enumerate(rand_predictions):
      output_summary = image_to_tf_summary_value(
          prediction["outputs"], tag="%d_output" % ind)
      input_summary = image_to_tf_summary_value(
          prediction["inputs"], tag="%d_input" % ind)
      all_summaries.append(input_summary)
      all_summaries.append(output_summary)
    return all_summaries
docs: Optionally converts images from hooks_args to image summaries.
  
    Args:
      hook_args: DecodeHookArgs namedtuple
    Returns:
      summaries: list of tf.Summary values if hook_args.decode_hpara