Comments (2)
In our implemention, we do nothing to force all the tokens to be optimized while training, but we used to calculate the utilization rate of the tokens and it reached about 99%.
If you want to optimized all the tokens, more implementations are here
from restoreformer.
It addresses my concern.
Thanks!
from restoreformer.
Related Issues (20)
- About FID on test datasets HOT 1
- IDD evaluation script HOT 1
- 测试 HOT 1
- How does this compare to CodeFormer? HOT 3
- Use RestoreFormer with custom images HOT 1
- DICTIONARY MODEL
- Training settings in the paper differ from the code HOT 1
- HQDictionary model HOT 1
- Train dataset HOT 1
- When use the HQ dictionary for MHCA. HOT 1
- Could you add a licence?
- HQ_Dictionary model and RestoreFormer model use different number of attention heads HOT 1
- Recommend for large scale training dataset
- How long has the RestoreFormer model been trained? How to control model training time and save model?
- ONNX Conversion
- Training time of the RestoreFormer model
- 关于测试和训练 HOT 1
- 配置文件 HOT 1
- Can I train RestoreFormer on 1024x1024? HOT 2
- Pretrained Models Link not working HOT 1
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from restoreformer.