我用tensorflow实现RNN为什么在初始化变量的时候会invalid syntax

Question

我是小白一个，刚刚开始学tensorflow，在我用tensorflow实现RNN的时候init = tf.global_variables_initializer()报错，好懵逼啊-- 求大神！！ 感谢！！

    import tensorflow as tf
    from tensorflow.examples.tutorials.mnist import input_data
    
    mnist = input_data.read_data_sets('MNIST_data',one_hot=True)
    
    n_inputs = 28
    max_time = 28
    lstm_size = 100
    batch_size = 50
    n_batch = mnist.train.num_examples // batch_size
    n_class = 10 
    
    x= tf.placeholder(tf.float32,[None,784])
    y= tf.placeholder(tf.float32,[None,10])
    
    weight = tf.Variable(tf.truncated_normal([lstm_size,n_class],stddev=0.1))###
    bias = tf.Variable(tf.constant(0.1,shape=[n_class]))
    
    def rnn(X,weight,bias):
        #inputs = [batch_size,max_time,n_inputs]
    
        inputs = tf.reshape(X,[-1,max_time,n_inputs])
        lstm_cell = tf.contrib.rnn.BasicLSTMCell(lstm_size)
        #final_state[0]是cell_state
        #final_state[1]是hidden_state
        outputs,final_state = tf.nn.dynamic_rnn(lstm_cell,inputs,dtype=tf.float32)
        results = tf.nn.softmax(tf.matmul(final_state[1],weight) + bias)
        return results
    
    prediction = rnn(x,weight,bias)
    cross_entropy = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(labels=y,logits=prediction))
    train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
    
    correct_prediction = tf.equal(tf.argmax(prediction,1),tf.argmax(y,1))
    acc = tf.reduce_mean(tf.cast(correct_prediction,tf.float32)
    
--> init = tf.global_variables_initializer()
    
    with tf.Session() as sess:
        sess.run(init)
        for epoch in range(6):
            for batch in range(n_batch):
                batch_xs,batch_ys = mnist.train.next_batch(batch_size)
                sess.run(train_step,feed_dict={x:batch_xs,y:batch_ys})
                
            train_acc = sess.run(accuracy,feed_dict={x:mnist.train.images[:10000],y:mnist.train.labels[:10000]})
            test_acc = sess.run(accuracy,feed_dict={x:mnist.test.images,y:mnist.test.labels})
            print('Iter: ' + str(i) + ' , Train_acc: ' + str(train_acc) + ' , Test_acc' + str(test_acc))
    

报错信息是

  File "u8.py", line 47
    init = tf.global_variables_initializer()
       ^
SyntaxError: invalid syntax

Answer 1

是粗心了，在上一行代码中漏打一个)