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I traced the process through StackGAN++ and subsequently this VaE design. The move is coined a "reparameterization trick" in sec 2.4 of the paper. It assists when the incoming noise is not entirely deterministic.
Hi @gagandaroach
Thanks for your asking
Yes, I also follow StackGAN instruction and their code.
As you mentioned it has a purpose for stable training.
This is also written StackGAN++ paper in page4 line4
Hello. Thank you for your great work.
Why do you save the model with the average G params?
https://github.com/HYOJINPARK/MC_GAN/blob/master/Model1/trainer.py#L449
Why not use the actual generator weights?
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