Comments (4)
@NoOneUST , sorry for the late reply, I was quite busy those days. From your description, I guess your disappointing results may caused by taking the search results as the final evaluate result. First, you need to make sure that the whole search process is as followed: 1. search stage: use as mentioned 10% training set for training and 2.5% training set for validation which will takes about 50 epochs to get the searched architectures (corresponding python file traing_search_imagenet.py). 2. evaluate stage: change the architecture in genotypes.py by the searched architecture in the first stage and use the whole dataset which will takes about 250 epochs to get the final accuracy (corresponding python file traing_imagenet.py, genotypes.py). Please note that the python files are different in different stages.
If you have more questions, please let me know.
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@Christian-lyc Does the validate phase refer to evaluating the searched architectures on imagenet (traing_imagenet.py)? If yes, 1% is the training acc or the validate acc or both?
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@Christian-lyc, what I know is that if you use torch.utils.data.sampler.SubsetRandomSampler to generate the subset of imagenet which I have noted in the readme.md file, the results are similar. You need to write your own sampling file. I have not encountered other situations.
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Hi,guys, I run the train_imagenet.py myself. The code runs well in the first two epochs and I have attached the log. I only change the batchsize and lr into 256 and 0.1 due to the limit of GPU.
log.txt
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Related Issues (20)
- Is a channel sampling mask fixed? HOT 3
- 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
- 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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