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It's possible that you're overfitting. I just posted an issue about this, but I think the convolutional layers are supposed to get fewer channels toward the middle because it's an autoencoder, not more channels in the middle. Try reversing hidden_dims maybe and train again.
Edit: never mind, I missed the fact that there's a stride of two, so it does create a bottleneck in the middle. Also apparently increasing the channels toward the middle isn't uncommon.
i used the VanillaAE, used all the celeba img_align_celeba data, 200k
this is epoch 28 reconstructed image:
this is epoch 28 sample image:
i think the sample was very bad, how can it happen?
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