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View Code? Open in Web Editor NEWPyTorch inference for "Progressive Growing of GANs" with CelebA snapshot
PyTorch inference for "Progressive Growing of GANs" with CelebA snapshot
Hi @ptrblck ,
Thanks for this implementation!
I have a question, and I was wondering if I can get your thoughts: The paper mentions that their training is unsupervised - meaning that it was not label-conditioned. Then how come they were able to generate label-specific images for LSUN dataset? Did they train separate networks for each label or is their network a multi-class generator?
Thanks in advance!
From https://github.com/ptrblck/prog_gans_pytorch_inference/blob/master/network.py#L470, LeakyReLU is inserted after Conv. However, from https://github.com/ptrblck/prog_gans_pytorch_inference/blob/master/model.py#L52, LeakyReLU is inserted after WScale layer. So should LeakyReLU be inserted after Conv or WScale? You have checked the output in the transfer_weights.py script, did I miss something?
BTW, do you also have the script for the discriminator network? I am trying to implement the training of the "Progressive Growing of GANs" paper in PyTorch based on your script. Looking forward to hearing back from you.
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