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View Code? Open in Web Editor NEWA PyTorch implementation of Auxiliary Classifier GAN to generate CIFAR10 images.
A PyTorch implementation of Auxiliary Classifier GAN to generate CIFAR10 images.
The pictures I trained showed ten different categories of a picture,but I want to save them one by one. Is there any way ?
Hi, first of all, thanks for your amazing work!
I have a question regarding a difference between your implementation and a recommendation from the repository "ganhacks" that you referred to. In their repository they state to use an embedding layer for labels, and add as additional channels to images when implementing the conditional gan. I have often seen this done by concatenating the embedding and the noise vectors. However, in your code you use a multiplication, as below;
label_embedding = self.embedding(label)
x = torch.mul(noise,label_embedding)
x = x.view(-1,100,1,1)
Is this the same as the concatenation and if not, what is the difference and would you prefer one over the other?
Thank you in advance!
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