Gradient Penalty is very high in the start about gigagan-pytorch HOT 10 CLOSED

hey! i closed it because the results were fine, but i did not train it for long, i'm borrowing different ideas from various GAN implementations for some experiments. GigaGan discriminator is definitely not the most stable and D/MSD/GP are fluctuating a lot

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Haha I'm long time past that age i believe :) Just freelance researcher and technical adviser for CV/ML stuff

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@inspirit ah got it :) well, glad to have you reviewing my code from time to time!

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@inspirit i think it is necessary to achieve the paper's results

in my opinion adaptive mod-conv is more useful and can be fitted in lots of ideas...

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@inspirit hey, so i also noticed that. however, i believe when i turned off the multi-scale (one of the main contributions of the paper), the gradients resembled stylegan, so i attributed it to that

did you close the issue because your training was successful?

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@inspirit yes, i think it is the multi-scale causing it, last i was training on my toy datasets. if you turn it off by setting the loss weight to 0, the training resembles stylegan a lot (could be remembering wrong)

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so whats the main purpose of having Multi Scale Discriminator in this case?

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@inspirit i think it is necessary to achieve the paper's results

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@inspirit are you a phd student btw? we run into each other a lot

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@inspirit yea i think both may be important

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