Comments (3)
I've been reading the code for two weeks now, and my understanding is that VH_decompose() performs spatial decomposition of the layers (splits them into 2 new layers with different shapes), ITQ _decompose() carries out channel decomposition @yihui-he explained a bit in issue #15. dictionary_kernel() is a function wrapper of dictionary(), which in charge of performing the lasso regression and minimizing the error reconstruction when selecting feature maps to prune.
Honestly I don't know why is there references to fully connected layers in the code, but from what I have read, fc_kernel and nonlinear_fc are not used during the execution of train.py. I have added more comment to the code in a fork I made. Feel free to check it out.
from channel-pruning.
@slothkong Thanks, you could create a pull request, so that I can merge your comments to master.
from channel-pruning.
from channel-pruning.
Related Issues (20)
- has AMC released? HOT 4
- the model size is not descreased after channel pruning? HOT 1
- GPU HOT 2
- HI, @yihui-he ,i have a queation to ask you:
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- KeyError: 'conv1_2_V'
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from channel-pruning.