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CHIP_NeurIPS2021
Code for CHIP: CHannel Independence-based Pruning for Compact Neural Networks (NeruIPS 2021).
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Error When Generating Channel Independence
#17
dywu98
opened
1 year ago
1
有关计算flops和params的问题
#16
CY-GAO222
opened
1 year ago
1
Why is the resnet_56 model composed of basic blocks?
#15
jsleeg98
opened
1 year ago
1
How to decide sparsity on each layer for any model?
#14
leo811121
closed
1 year ago
1
Question about hook in ResNet50
#13
Bojue-Wang
closed
1 year ago
1
Hello, how do you calculate your Params and Flops?
#12
Zzz-zcy
closed
1 year ago
3
作者你好，请问计算vgg16在cifar10的ci大概需要多长时间？
#11
Lutong-Qin
closed
2 years ago
3
Some problem Figure.4 in your paper
#10
HXuan-Wang
closed
1 year ago
1
Code on MobileNet
#9
sscckk
closed
2 years ago
3
reproduce accuracy
#8
geyao-c
closed
2 years ago
1
weight decay question
#7
geyao-c
closed
2 years ago
1
Can't reproduce paper results
#6
ipwjincheng
closed
2 years ago
1
How long does it take to run python calculate_ci.py for imagenet?
#5
Jhongn
closed
2 years ago
1
预训练模型
#4
geyao-c
closed
2 years ago
1
Issues on calculate_ci.py
#3
zsureuk
closed
2 years ago
7
Why not prun the model directly using the predesigned desired number of filters in each layer?
#2
CeliaYin0510
closed
2 years ago
1
该方法需要手动指定每一层的prune ratio?
#1
PeiqinSun
closed
2 years ago
1