import tensorflow as tf

        .inference_with_all_cores)
  else:
    save_checkpoints_steps = (FLAGS.save_checkpoints_steps or
                              FLAGS.iterations_per_loop)
    run_config = tf.estimator.RunConfig(
        model_dir=FLAGS.model_dir,
        save_checkpoints_steps=save_checkpoints_steps)
    image_classifier = tf.estimator.Estimator(
        model_fn=model.model_fn,
        config=run_config,
        params=estimator_parmas)

  # Input pipelines are slightly different (with regards to shuffling and
  # preprocessing) between training and evaluation.
