kaiqzhan / admm-pruning Goto Github PK
View Code? Open in Web Editor NEWPrune DNN using Alternating Direction Method of Multipliers (ADMM)
License: BSD 2-Clause "Simplified" License
Prune DNN using Alternating Direction Method of Multipliers (ADMM)
License: BSD 2-Clause "Simplified" License
I read the codes in it and find that they just set the connection weights as zeros. And then use the whole matrix to calculate the output. I assume that when training and testing the network, the memory footprint(gpu memory) would not change.
Therefore, how pruning benefit the CNN when applying in resource limited machine?
Is a PyTorch implementation going to be provided?
When I change your code to pytorch, I found the loss doesn't convergence, and the conditions W-Z is also doesn't convergence.
我写了一个简单的pytorch实现,但是结果很奇怪,最近您是否有空给我一点指导?
I have a question: how to determine the prune ratio of each layer? by try-and-error?
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