caffe损失是nan或0

Question

我正在训练一个网络，我已经改为从0.1到0.00001的学习率。输出始终保持不变。没有意思是用于训练。 造成这种奇怪损失的原因是什么？

I1107 15:07:28.381621 12333 solver.cpp:404]  Test net output #0: loss = 3.37134e+11 (* 1 = 3.37134e+11 loss) 
I1107 15:07:28.549142 12333 solver.cpp:228] Iteration 0, loss = 1.28092e+11 
I1107 15:07:28.549201 12333 solver.cpp:244]  Train net output #0: loss = 1.28092e+11 (* 1 = 1.28092e+11 loss) 
I1107 15:07:28.549211 12333 sgd_solver.cpp:106] Iteration 0, lr = 1e-07 
I1107 15:07:59.490077 12333 solver.cpp:228] Iteration 50, loss = -nan 
I1107 15:07:59.490170 12333 solver.cpp:244]  Train net output #0: loss = 0 (* 1 = 0 loss) 
I1107 15:07:59.490176 12333 sgd_solver.cpp:106] Iteration 50, lr = 1e-07 
I1107 15:08:29.177093 12333 solver.cpp:228] Iteration 100, loss = -nan 
I1107 15:08:29.177119 12333 solver.cpp:244]  Train net output #0: loss = 0 (* 1 = 0 loss) 
I1107 15:08:29.177125 12333 sgd_solver.cpp:106] Iteration 100, lr = 1e-07 
I1107 15:08:59.758381 12333 solver.cpp:228] Iteration 150, loss = -nan 
I1107 15:08:59.758513 12333 solver.cpp:244]  Train net output #0: loss = 0 (* 1 = 0 loss) 
I1107 15:08:59.758545 12333 sgd_solver.cpp:106] Iteration 150, lr = 1e-07 
I1107 15:09:30.210208 12333 solver.cpp:228] Iteration 200, loss = -nan 
I1107 15:09:30.210304 12333 solver.cpp:244]  Train net output #0: loss = 0 (* 1 = 0 loss) 
I1107 15:09:30.210310 12333 sgd_solver.cpp:106] Iteration 200, lr = 1e-07 

Answer 1

你的损失不是0，甚至没有接近。你从​​（即〜10^11）开始，它看起来很快爆炸后，你得到nan。你需要大幅缩减你的损失值。如果您使用的是"EuclideanLoss"，则可能需要根据深度图的大小对损失进行平均，将预测值缩放至[-1,1]范围，或采用任何其他缩放方法来防止爆炸造成的损失。