Comments (2)
Hey! Yeah I did and I got worse results than gradient penalty. Then I read somewhere in the stylegan paper that they had noticed the same and decided to keep GP instead
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Thanks!
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Related Issues (20)
- Error(s) in loading state_dict for LightweightGAN HOT 2
- Batchnorm layer missing in the discriminator?
- showing results while training ? HOT 2
- G is showing up a negative number. What does that mean?
- Multi GPU utilization problem.
- TypeError: __init__() got an unexpected keyword argument 'hparams' HOT 1
- unable to load save model. please try downgrading the package to the version specified by the saved model HOT 7
- --load_strict=False failing to load model HOT 1
- Can't find "__main__" module (sorry if noob question) HOT 4
- loss implementation differs from paper HOT 1
- Doesn't detect CUDA from Nvidia GPU HOT 1
- Torchvision Assertion error while importing custom data
- Aim installation error HOT 4
- Discriminator Loss converges to 0 while Generator loss pretty high HOT 3
- Dont detects cuda HOT 1
- Using Lightweight GAN as a library
- Projecting generated Images to Latent Space HOT 1
- Executing with a trailing \ in the arguments sets the variable new to the truthy value '\\' and deletes all progress
- CUDA out of memory error while generating interpolations
- Minimum number data training
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