Ao enfrentar dificuldades durante o treinamento (nans, perda não convergeetc.) às vezes é útil olhar para um registro de treinamento mais detalhado, definindodebug_info: true no'solver.prototxt' Arquivo.

O log de treinamento é semelhante a:

I1109 ...]     [Forward] Layer data, top blob data data: 0.343971    
I1109 ...]     [Forward] Layer conv1, top blob conv1 data: 0.0645037
I1109 ...]     [Forward] Layer conv1, param blob 0 data: 0.00899114
I1109 ...]     [Forward] Layer conv1, param blob 1 data: 0
I1109 ...]     [Forward] Layer relu1, top blob conv1 data: 0.0337982
I1109 ...]     [Forward] Layer conv2, top blob conv2 data: 0.0249297
I1109 ...]     [Forward] Layer conv2, param blob 0 data: 0.00875855
I1109 ...]     [Forward] Layer conv2, param blob 1 data: 0
I1109 ...]     [Forward] Layer relu2, top blob conv2 data: 0.0128249
. 
.
.
I1109 ...]     [Forward] Layer fc1, top blob fc1 data: 0.00728743
I1109 ...]     [Forward] Layer fc1, param blob 0 data: 0.00876866
I1109 ...]     [Forward] Layer fc1, param blob 1 data: 0
I1109 ...]     [Forward] Layer loss, top blob loss data: 2031.85
I1109 ...]     [Backward] Layer loss, bottom blob fc1 diff: 0.124506
I1109 ...]     [Backward] Layer fc1, bottom blob conv6 diff: 0.00107067
I1109 ...]     [Backward] Layer fc1, param blob 0 diff: 0.483772
I1109 ...]     [Backward] Layer fc1, param blob 1 diff: 4079.72
.
.
.
I1109 ...]     [Backward] Layer conv2, bottom blob conv1 diff: 5.99449e-06
I1109 ...]     [Backward] Layer conv2, param blob 0 diff: 0.00661093
I1109 ...]     [Backward] Layer conv2, param blob 1 diff: 0.10995
I1109 ...]     [Backward] Layer relu1, bottom blob conv1 diff: 2.87345e-06
I1109 ...]     [Backward] Layer conv1, param blob 0 diff: 0.0220984
I1109 ...]     [Backward] Layer conv1, param blob 1 diff: 0.0429201
E1109 ...]     [Backward] All net params (data, diff): L1 norm = (2711.42, 7086.66); L2 norm = (6.11659, 4085.07)

O que isso significa?