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View Code? Open in Web Editor NEWpytorch implementation of VAE-Gumble-Softmax
License: MIT License
pytorch implementation of VAE-Gumble-Softmax
License: MIT License
Hi, there seems a redundant minus before the calculation of KLD.
KLD = torch.sum(qy * (log_qy - g)) # not -torch.sum(qy * (log_qy - g))
See this implementation.
I got better images after changing KLD. See my modifications
Hi @dev4488 , thanks for sharing your project with us.
I would like to know how do I modify the implementation to use Bernoulli variables. I need the network to generate codes consisting of 0s and 1s.
Thanks.
Hi,
Can you attach a license for the code so it's easier for others to reuse? Thank you very much.
Hi, thank you for sharing this project.
I think line 108 should be changed from
return self.decode(z),F.softmax(q)
to
return self.decode(z), F.softmax(q_y, dim=-1).view(-1, latent_dim * categorical_dim)
.
Since the softmax should be taken on categorical_dim
sized vectors, and not on latent_dim * categorical_dim
sized ones.
During test stage, should the temperature be a constant?
VAE_gumble_softmax/vae_gumbel_softmax.py
Lines 171 to 172 in 798d481
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