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License: Other
StarGAN2 for practice
License: Other
I managed to get an RTX3090 which has 16G. With Tensorflow version of Clovaai, I managed to get a batch size of 6 on dataset 512x512 (eats up 18G GPU) and still training as it run extremely slowly (and seems heavy) compares to StyleGan V2 on Pytorch.
What do you think of your codes on batch size 6 would it be worth trying? My dataset is purely indoor scene and furniture, close to million of images.
Anyhow, would you make your code work on multi GPUs, please ?
Thanks,
Steve
Thank you for your interesting comments, I find them very meaningfull.
Can you please clarify what exactly are you trying to achieve by lowmem parameter as from my perspective it just removes a style vector (matrix ~ [Bs x StyleDim]), which is pretty lightweight.
It would be interesting to hear some numbers (like gpu mem savings), how it helps.
Thanks!๐๐ป
Have you managed to run your code with multi-GPU ?
Thanks,
Steve
Hello,
Where to download pretrained celebA HQ to run with test.py ?
I have been attempting to train the StarGAN v2 model using an RTX 3090 GPU, but I encounter a persistent issue where the loss values turn to NaN, and the generated images are solely composed of noise. This is puzzling, especially since the same code and data work flawlessly on a Tesla P100 GPU.
Could you please shed some light on what might be causing these discrepancies between the two GPUs? Any insights or suggestions you could provide would be immensely appreciated, as I am quite perplexed by this behavior.
Do you broadcast this repo on Facebook or Reddit? I want to know how to access the wonderful repo for the first time.
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