rnn.py 文件源码

def evaluate(self, t_data, t_label, s):
        state = self.fit_next(t_data, s, train=False)
        label = tf.Variable(t_label, name="label", trainable=False, dtype=tf.float32)
        s.run(tf.initialize_variables([label]))
        with tf.name_scope('evaluate'):
            return self.output_layer.evaluate(tf.transpose(state[0]), label)