models.py 文件源码

def _compute_rnn_outputs(self):

        reversed_inputs = tf.reverse(self.inputs, [False, True, False])
        reversed_resets = tf.reverse(self.resets, [False, True, False])
        with tf.variable_scope('fw'):
            self._fw_lstm = LSTM(self.inputs, self.resets, self.training,
                                 self.num_layers, self.hidden_layer_size,
                                 self.init_scale, self.dropout_keep_prob)
        with tf.variable_scope('rv'):
            self._rv_lstm = LSTM(reversed_inputs, reversed_resets,
                                 self.training, self.num_layers,
                                 self.hidden_layer_size, self.init_scale,
                                 self.dropout_keep_prob)

        fw_outputs = self._fw_lstm.outputs
        rv_outputs = tf.reverse(self._rv_lstm.outputs, [False, True, False])
        outputs = tf.concat(2, [fw_outputs, rv_outputs])
        return outputs