Question

我最近开始对深度学习感兴趣。我复制了Tensorflow初学者教程我得到了语法错误，无法运行脚本

from tensorflow.examples.tutorials.mnist import input_data
mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)

import tensorflow as tf
x  = tf.placeholder(tf.float32, [None,784])
W = tf.Variable(tf.zeros([784, 10]))
b = tf.Variable(tf.zeros([10]))

y = tf.nn.softmax(tf.matmul(x, W) + b)


#TRAINING

y_ = tf.placeholder(tf.float32, [None, 10])

cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y).reduction_indices = [1]

train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)

#(SYNTAX ERROR IN "P" OF TRAIN_STEP)

sess = tf.InteractiveSession()

tf.global_variable_initializer().run()

for _ in range(1000):
    batch_xs, batch_ys = mnist.train.next_batch(100)
sess.run(train_step, feed_dict = {x: batch_xs, y_: batch_ys})

#EVALUATION

correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))

accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))

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

为什么会发生这种情况以及如何解决这个问题，以便继续我的学习。

Answer 1

看看这一行：

cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y).reduction_indices = [1]

您应该注意括号不会关闭，这不是有效的声明。

您是否可以尝试重新复制在线找到的代码并仔细检查您复制的内容？

祝你好运！

我在TensorFlow初学者教程中遇到了问题

1 个答案: