Question

我正在阅读tensorflow教程（https://www.tensorflow.org/get_started/mnist/pros）

具体来说：

with tf.Session() as sess:
  sess.run(tf.global_variables_initializer())
  for i in range(20000):
    batch = mnist.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))
    train_step.run(feed_dict={x: batch[0], y_: batch[1], keep_prob: 0.5})

到目前为止，一切都完美无缺。它完成了20,000步培训。但后来我达到了这一点：

  print('test accuracy %g' % accuracy.eval(feed_dict={
      x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))

发生了这种情况：

>>>  print('test accuracy %g' % accuracy.eval(feed_dict={
  File "<stdin>", line 1
    print('test accuracy %g' % accuracy.eval(feed_dict={
    ^
IndentationError: unexpected indent
>>>      x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))
  File "<stdin>", line 1
    x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))

现在，如果我尝试更改间距，并从for循环中单独打印最终精度，我会得到更令人不愉快的东西：

 print('test accuracy %g' % accuracy.eval(feed_dict={
...     x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))
Traceback (most recent call last):
 ...

tensorflow.python.framework.errors_impl.FailedPreconditionError: Attempting to use uninitialized value Variable_12

不确定发生了什么。任何建议或反馈将不胜感激。

谢谢

Deep MNIST for Experts教程trouble / FailedPreconditionError

0 个答案: