我是新的python,我的代码在以下行中崩溃
print("step %d, training accuracy %g"%(i, train_accuracy))
^
IndentationError: unindent does not match any outer indentation level
这里的整个代码是:
import input_data
mnist = input_data.read_data_sets('MNIST_data', one_hot=True)
import tensorflow as tf
x = tf.placeholder("float", shape=[None, 784])
y_ = tf.placeholder("float", shape=[None, 10])
x_image = tf.reshape(x, [-1,28,28,1])
print "x_image="
print x_image
def weight_variable(shape):
initial = tf.truncated_normal(shape, stddev=0.1)
return tf.Variable(initial)
def bias_variable(shape):
initial = tf.constant(0.1, shape=shape)
return tf.Variable(initial)
def conv2d(x, W):
return tf.nn.conv2d(x, W, strides=[1, 1, 1, 1], padding='SAME')
def max_pool_2x2(x):
return tf.nn.max_pool(x, ksize=[1, 2, 2, 1],
strides=[1, 2, 2, 1], padding='SAME')
W_conv1 = weight_variable([5, 5, 1, 32])
b_conv1 = bias_variable([32])
h_conv1 = tf.nn.relu(conv2d(x_image, W_conv1) + b_conv1)
h_pool1 = max_pool_2x2(h_conv1)
W_conv2 = weight_variable([5, 5, 32, 64])
b_conv2 = bias_variable([64])
h_conv2 = tf.nn.relu(conv2d(h_pool1, W_conv2) + b_conv2)
h_pool2 = max_pool_2x2(h_conv2)
W_fc1 = weight_variable([7 * 7 * 64, 1024])
b_fc1 = bias_variable([1024])
h_pool2_flat = tf.reshape(h_pool2, [-1, 7*7*64])
h_fc1 = tf.nn.relu(tf.matmul(h_pool2_flat, W_fc1) + b_fc1)
keep_prob = tf.placeholder("float")
h_fc1_drop = tf.nn.dropout(h_fc1, keep_prob)
W_fc2 = weight_variable([1024, 10])
b_fc2 = bias_variable([10])
y_conv=tf.nn.softmax(tf.matmul(h_fc1_drop, W_fc2) + b_fc2)
cross_entropy = -tf.reduce_sum(y_*tf.log(y_conv))
train_step = tf.train.AdamOptimizer(1e-4).minimize(cross_entropy)
correct_prediction = tf.equal(tf.argmax(y_conv,1), tf.argmax(y_,1))
accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
sess = tf.Session()
sess.run(tf.initialize_all_variables())
for i in range(200):
batch = mnist.train.next_batch(50)
if i%10 == 0:
train_accuracy = sess.run( accuracy, 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("test accuracy %g"% sess.run(accuracy, feed_dict={
x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))
我正在运行3.5版本的python,任何想法如何解决这个问题?
答案 0 :(得分:1)
这是一个Python缩进问题。
print
行的开头必须与train_accuracy
行的开头具有相同的缩进。
这样的事情:
if i%10 == 0:
train_accuracy = sess.run( accuracy, feed_dict={
x:batch[0], y_: batch[1], keep_prob: 1.0})
print("step %d, training accuracy %g"%(i, train_accuracy))
答案 1 :(得分:1)
这是一个身份问题。检查print语句前的空格数。它与上面一行的空格数不匹配(train_accuracy的声明)。在print语句之前再添加一个,它应该可以工作。