bi_lstm_model.py 文件源码

def bi_lstm_layer(self,inputs):
        if self.hidden_layer_num >1:
            lstm_fw = rnn.MultiRNNCell([self.lstm_cell() for _ in range(self.hidden_layer_num)])
            lstm_bw = rnn.MultiRNNCell([self.lstm_cell() for _ in range(self.hidden_layer_num)])
        else:
            lstm_fw = self.lstm_cell()
            lstm_bw = self.lstm_cell()

        outpus,_,_ = rnn.static_bidirectional_rnn(lstm_fw,lstm_bw,inputs,dtype=tf.float32)
        features = tf.reshape(outpus,[-1,self.hidden_neural_size *2])
        return  features