Comments (1)
asarigun
commented on July 28, 2024
Hi @Stephenlove,
Thank you so much for being so interested in the repo! When I started to implement, I used v2.0 of the paper. The results are different since the hyperparameter I used wasn't too many comparing to the original implementation. Also, there is limited computational power&GPU to train the model, and I have ongoing projects that's why I couldn't further develop performance. Therefore, the FID score is different from the reported results! However, qualitative results are reasonable, and it shows that it is open to developing the performance. I hope this could answer your question!
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Related Issues (15)
- Maybe you can tell how to train it HOT 1
- Hi, I found that hinge loss doesn't work well, is that right? HOT 2
- GPU memory, Modifying batch size HOT 10
- Is there a pre-trained model? HOT 3
- Can you resume training at breakpoints? HOT 2
- sir,I have a question about the DiffAug, the paper said they used the Data Augmentation to get excellent improvement. It is about translation, cutout, color. So, in your code, did you use the DiffAug？ HOT 1
- Hello, I can't download the file fid_stats_cifar10_train.npz that you provided in readme! HOT 1
- when i train my own data , i meet FID score :nan ,what's wrong with it HOT 2
- Could you give me a pretrained model, please? HOT 1
- FID score: nan HOT 1
- Create your own FID stats file HOT 2
- How do you test on your own dataset with the checkpoint.pth generated?
- question about argumentation
- Questions about multi-GPU training
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