python - 获取属性错误: __exit__ when working with Tensorflow and MNIST data

Question

我是 Tensorflow 的初学者，正在使用 MNIST 数据。当尝试运行如下所示的 Tensorflow session 时，我收到属性错误。

有人可以研究一下吗？

我收到错误的代码片段如下。

    with tf.Session as sess:
        sess.run(init)
        for step in range(1000):
            batch_x, batch_y = mnist.train.next_batch(100)
            sess.run(train, feed_dict={x:batch_x, y:batch_y})

        # Evaluate the model
        matches = tf.equal(tf.argmax(y,1),tf.argmax(y_true,1))

        # Output will be like [True, False, True.....] --> Cast to [1.0, 0.0, 1.0.....]
        acc = tf.reduce_mean(tf.cast(matches,tf.float32))

        print(sess.run(acc, feed_dict={x:mnist.test.images, y_true:mnist.test.labels}))

我收到以下错误:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-59-c78b8b9359b3> in <module>()
----> 1 with tf.Session as sess:
      2     sess.run(init)
      3     for step in range(1000):
      4         batch_x, batch_y = mnist.train.next_batch(100)
      5         sess.run(train, feed_dict={x:batch_x, y:batch_y})

AttributeError: __exit__

Answer 1

为了创建新的 Session 对象/实例，您缺少 ():

将 tf.Session() 作为 sess:

tf.Session 仅引用 Session 类。