import tensorflow as tf

    with tf.name_scope("Test"):
      test_input = PTBInput(
          config=eval_config, data=test_data, name="TestInput")
      with tf.variable_scope("Model", reuse=True, initializer=initializer):
        mtest = PTBModel(is_training=False, config=eval_config,
                         input_=test_input)

    models = {"Train": m, "Valid": mvalid, "Test": mtest}
    for name, model in models.items():
      model.export_ops(name)
    metagraph = tf.train.export_meta_graph()
    if tf.__version__ < "1.1.0" and FLAGS.num_gpus > 1:
      raise ValueError("num_gpus > 1 is not supported for TensorFlow versions "
                       "below 1.1.0")
    soft_placement = False
    if FLAGS.num_gpus > 1:
      soft_placement = True
      util.auto_parallel(metagraph, m)

  with tf.Graph().as_default():
