dingmyu / HR-NAS

HR-NAS: Searching Efficient High-Resolution Neural Architectures with Lightweight Transformers (CVPR21 Oral)

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

The problem about importance factor

developerFanYu opened this issue · comments

Hello. I am master in Xi'an Jiaotong Universtiy. This is an outstanding paper, but I have one question about importance factor.
I read the source code and find that the importance factor is defined as the weight sum of each block.
loss_bn_l1 = prune.cal_bn_l1_loss(get_prune_weights(model), FLAGS._bn_to_prune.penalty, rho)
Do you think my understanding is correct?
I can not understand that importance factor is the weight sum of each block.
Thank you very much!