Question

with tf.Session() as sess:
    sess.run(init)
    for epoch in range(training_epochs):
        avg_cost = 0.
        total_batch = int(mnist.train.num_examples/batch_size)
        for i in range(total_batch):
            batch_xs, batch_ys = mnist.train.next_batch(batch_size)
            _, c = sess.run([optimizer, cost], feed_dict={x: batch_xs,
                                                          y: batch_ys})
            avg_cost += c / total_batch
            if (epoch+1) % display_step == 0:
                 print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(avg_cost)) 


    print("Optimization Finished!")      

# Test model
correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))

 # Calculate accuracy
accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
print("Testing accuracy:", sess.run(accuracy, feed_dict={x: mnist.test.images, y: mnist.test.labels}))

Answer 1

在测试模型之前，您的会话对象已关闭。因此，当您尝试在最后一个打印语句中使用sess时，它将引发运行时错误。

所以，您可以做的是：

with tf.Session() as sess:
    sess.run(init)
    print("Testing accuracy:", sess.run(accuracy, feed_dict={x: mnist.test.images, y: mnist.test.labels}))

为了测试准确性而运行时，出现“ RuntimeError：试图使用封闭的会话”

1 个答案: