Hi!
Sorry to contact you frequently recently! I'm very interested in your work!
I encountered some problems in the reproduction process. When I used my own 7k datasets to train with the following commands:
python train.py --outdir=training-runs --data=datasets/face7k.zip --aug=ada --warmup=5e5 --cfg=paper256_2fmap --gpus=2 --kimg=5000 --batch=16 --snap=25 --cv-loss=multilevel_sigmoid_s --augcv=ada --cv=input-clip-output-conv_multi_level --metrics=none
![Uploading image.png…]()
The probability of the adaptive discriminator enhancement increased rapidly during the training process. At present, the quality of the generated samples is very poor. Compared with stylegan2 ada, whether the problem of mode collapse and generator leakage is very serious. I don't know what details I missed.
I hope you can help me! Thank you again for answering my questions before!
Hi! Sorry to contact you frequently recently! I'm very interested in your work! I encountered some problems in the reproduction process. When I used my own 7k datasets to train with the following commands:
python train.py --outdir=training-runs --data=datasets/face7k.zip --aug=ada --warmup=5e5 --cfg=paper256_2fmap --gpus=2 --kimg=5000 --batch=16 --snap=25 --cv-loss=multilevel_sigmoid_s --augcv=ada --cv=input-clip-output-conv_multi_level --metrics=none![Uploading image.png…]()
The probability of the adaptive discriminator enhancement increased rapidly during the training process. At present, the quality of the generated samples is very poor. Compared with stylegan2 ada, whether the problem of mode collapse and generator leakage is very serious. I don't know what details I missed. I hope you can help me! Thank you again for answering my questions before!