import os import model import tensorflow as tf import input_data data = input_data.read_data_sets('MNIST_data', one_hot=True) #model with tf.variable_scope("convolutional"): x = tf.placeholder(tf.float32, [None,784], name='x') keep_prob = tf.placeholder(tf.float32) y, variables = model.convolutional(x, keep_prob) #train y_ = tf.placeholder(tf.float32, [None, 10], name='y') cross_entropy = -tf.reduce_sum(y_ * tf.log(y)) train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy) correct_prediction = tf.equal(tf.argmax(y, 1), tf.argmax(y_, 1)) accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32)) saver = tf.train.Saver(variables) with tf.Session( ) as sess: merged_summary_op = tf.summary.merge_all( ) summary_writer = tf.summary.FileWriter('/tmp/mnist log/1', sess.graph) summary_writer.add_graph(sess.graph) sess.run(tf.global_variables_initializer( )) for i in range(20000): batch = data.train.next_batch(50) if i % 100 == 0: train_accuracy = accuracy.eval(feed_dict={x: batch[0], y_:batch[1], keep_prob: 1.0}) print("step %d,training accuracy %g" % (i,train_accuracy)) sess.run(train_step, feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5}) print(sess.run(accuracy, feed_dict={x: data.test.images,y_ : data.test.labels, keep_prob: 1.0}) path = saver.save( sess, os.path.join(os.path.dirname(__file__), 'data', 'convolutional.ckpt'), write_meta_graph=False, write_state=False) print("saved:", path ) 运行出现 下面错误 C:\ProgramData\Anaconda3\envs\mnist_testdemo\python.exe C:/Users/dbgen/PycharmProjects/mnist_testdemo/mnist/convolutional.py File "C:/Users/dbgen/PycharmProjects/mnist_testdemo/mnist/convolutional.py", line 36 path = saver.save( ^SyntaxError: invalid syntaxProcess finished with exit code 1
少了个括号