import tensorflow as tf

            self._train_op = tf.get_collection_ref('train_op')[0]
            self._lr = tf.get_collection_ref('lr')[0]
            self._new_lr = tf.get_collection_ref('new_lr')[0]
            self._lr_update = tf.get_collection_ref('lr_update')[0]
            rnn_params = tf.get_collection_ref('rnn_params')
            if self._cell and rnn_params:
                params_saveable = tf.contrib.cudnn_rnn.RNNParamsSaveable(
                    self._cell,
                    self._cell.params_to_canonical,
                    self._cell.canonical_to_params,
                    rnn_params,
                    base_variable_scope='Model/RNN')
