import tensorflow as tf

    self._train_op = optimizer.apply_gradients(
        zip(grads, tvars),
        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)

