Caffe Blob data structure
Caffe uses Blob data structure to store data/weights/parameters etc. It is important to note that Blob has two "parts": data and diff. The values of the Blob are stored in the data part. The diff part is used to store element-wise gradients for the backpropagation step.
You will understand all the layers from bottom to top listed in this part of the log. For each layer you'll see:
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
All the rest of the layers are listed in this part top to bottom. You can see that the L2 magnitudes reported now are of the diff part of the Blobs.
The last log line of this iteration:
[Backward] All net params (data, diff): L1 norm = (2711.42, 7086.66); L2 norm = (6.11659, 4085.07)
reports the total L1 and L2 magnitudes of both data and gradients.
Hope this answer helps you!