import tensorflow as tf

        global_step=tf.train.get_or_create_global_step())

    self._new_lr = tf.placeholder(
        tf.float32, shape=[], name="new_learning_rate")
    self._lr_update = tf.assign(self._lr, self._new_lr)

  def _build_rnn_graph(self, inputs, config, is_training):
    if config.rnn_mode == CUDNN:
