参考:https://stackoverflow.com/questions/39076388/tensorflow-deep-mnist-resource-exhausted-oom-when-allocating-tensor-with-shape
训练mnist数据集,测试的时候报错,显存不足
解决办法:
(1)将
print("test accuracy %g"%accuracy.eval(feed_dict={ x: mnist.test.images, y_: mnist.test.labels, keep_prob: 1.0}))
改为:
for i in xrange(10): testSet = mnist.test.next_batch(50) print("test accuracy %g"%accuracy.eval(feed_dict={ x: testSet[0], y_: testSet[1], keep_prob: 1.0}))
(2)改为
accuracy_sum = tf.reduce_sum(tf.cast(correct_prediction, tf.float32))
good = 0
total = 0
for i in xrange(10):
testSet = mnist.test.next_batch(50)
good += accuracy_sum.eval(feed_dict={ x: testSet[0], y_: testSet[1], keep_prob: 1.0})
total += testSet[0].shape[0]
print("test accuracy %g"%(good/total))