Comments (3)
yuhuixu1993
commented on July 18, 2024
Hi, we offer two kinds of implementations in this repo. One is the mentioned channel_shuffle (it induces fixed mask each layer while different within layers.) which is an approximation; The other is a totally random mask, you can check model_search_random.py, if you are interested.
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nabk89
commented on July 18, 2024
Thank you, but I don't understand that working of channel_shuffle is different within layers.
Would you explain this part in a detail?
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sjjdd
commented on July 18, 2024
请问固定和随机哪种效果更好一些啊?
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Related Issues (20)
- Is there any plan to release the pretrained imagenet model? HOT 1
- Why modifying architecture after epoch 15
- Data preparation of ImageNet
- How to change the channel proportion K? HOT 2
- Cannot re-implement your claimed result HOT 3
- GPU Utilization is Bad HOT 1
- We cannot obtain your claimed result on ImageNet after trying many configurations HOT 4
- Question about search on custom dataset HOT 5
- test.py运行报错
- Understanding the two sets of the architecture hyperparameter HOT 2
- how you report the final accuracy in evaluation? Possibly touch the test set for the best acc? HOT 2
- Learning rate schedule
- 你好,结果不一致 HOT 2
- Searched genotype remain / keep unchanged for a great number of epoch HOT 2
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cuda:1!
- 您好，想请问一下网络搜索完之后如何得到需要的网络结构代码？ HOT 3
- About the license of this repository
- Hello, whether PC-DARTS likes DARTS with extra dropout?
- Not Enough Comments in the Code
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