lstm_mlp_model.py 文件源码

def calc (self, xs):
        xs = tf.transpose(xs, [1, 0, 2])
        print "xs: " + str(xs)
        mlp_out = []
        for i in range(self.lstm_steps_count):
            v = self.mlp (tf.gather(xs, i))
            mlp_out.append (v)
        mlp_out = tf.transpose(tf.pack (mlp_out), [1, 0, 2])
        val, state = tf.nn.dynamic_rnn(tf.nn.rnn_cell.MultiRNNCell(self.layers, state_is_tuple=True), mlp_out, dtype=tf.float32)

        val = tf.transpose(val, [1, 0, 2])
        results = []
        for i in range(self.lstm_steps_count):
            v = self.out_mlp (tf.gather(val, i))
            results.append (v)
        return tf.transpose(tf.pack (results), [1, 0, 2])