import tensorflow as tf

        input_size=config.hidden_size,
        dropout=1 - config.keep_prob if is_training else 0)
    params_size_t = self._cell.params_size()
    self._rnn_params = tf.get_variable(
        "lstm_params",
        initializer=tf.random_uniform(
            [params_size_t], -config.init_scale, config.init_scale),
        validate_shape=False)
    c = tf.zeros([config.num_layers, self.batch_size, config.hidden_size],
                 tf.float32)
