Comments (2)
Thanks for your attention,
We compared the effect of grafting and baseline using mobilenetv2 model on cifar100 dataset, and found that grafting works for both steplr and coslr(The initial learning rate we used is 0.1).
In addition, coslr and grafting are two different ways of optimizing training, and do not necessarily have the effect of 1 + 1> 2.
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Related Issues (20)
- Can this work extend to other domains like segmentation/detection ? HOT 1
- Hello author, I directly run the grafting.py file, the cifar10 dataset, and can't train normally, may I ask you, what should I do
- imagenet实验baseline使用step lr,而grafting使用cosine HOT 1
- batchnorm parameters HOT 5
- 你好,使用VGG模型运行grafting_cifar时,出现错误 HOT 3
- 作者你好,想问一个论文中的问题 HOT 1
- 您好,关于论文的一些细节请教。 HOT 1
- 您好,关于grafting.py中的grafting函数有个问题 HOT 2
- graft训练mbv2模型没有优化效果 HOT 9
- 您好,我有几个关于grafting.py代码的问题想请教您 HOT 2
- 请教一下代码中参数α的计算问题
- Is there something wrong? HOT 4
- 关于Grafting.py中的几个问题,盼复
- Ambiguous value for fuse-weight? HOT 1
- filter is batter than layer? HOT 1
- can not reproduce the results HOT 3
- Your baseline model do not converge HOT 2
- Adaptive Weighting公式中的A和c的值为0.4和500是否合适? HOT 3
- 作者你好,请问一下您,直接运行grafting.py,无法直接训练 数据集是CIFAR10 HOT 2
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