Comments (5)
caopulan
commented on July 23, 2024
1
It costs 5 days to train FFHQ-1024x1024 (500k iterations) on 3090.
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caopulan
commented on July 23, 2024
1
@caopulan Thanks for sharing! Do you mean 50,000 iterations, I guess?
I'm sorry, I mean 500,000 iterations. I have corrected it.
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caopulan
commented on July 23, 2024
1
And I found distributed training is not effective. Training on 8 cards accelerates only 1.5~2x.
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shionhonda
commented on July 23, 2024
@caopulan Thanks for sharing! Do you mean 50,000 iterations, I guess?
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shionhonda
commented on July 23, 2024
Do you have any idea to reduce the time for training? I kind of suspect we could increase the learning rate to 0.001 or around and make the model converge faster
In my experiment learning rate could safely be raised to 0.001.
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Related Issues (20)
- is it possible to fine tune? HOT 2
- Resume training for cars
- Inference with sample size >1 fails HOT 1
- How to get figure 2 HOT 1
- Error while running inference.py HOT 2
- Training e4e for 512*256 stylegan HOT 2
- Regarding finding directions in W+ space
- Is released ffhq e4e model trained by inversion task? HOT 1
- whether the code is wrong?
- Stuck on Iteration_0
- Model parameters at other resolutions HOT 2
- How do I train an encoder with a resolution of 256*256 on the FFHQ dataset? HOT 1
- There is a problem with the pre-training weights
- Can I train an encoder using your e4e frame work on a StyleGAN2-ADA pretrained on my own dataset?
- Can I use my own pretrained StyleGAN2-ADA? HOT 1
- Is it possible to get more details in the images?
- is it possible to run this code for gender swap operations ?
- Is it possible to train the encoder which is segmap to face?
- Suggestions on training an encoder on FFHQ-256
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