Training PixelCNN unclear

[Arksyd96]

Hi,

I'm using your implementation to generate MRIs. I have trained a VQ-VAE to reconstruct 3D MRIs, but I am unsure about which vectors to use for training the PixelCNN for sampling.

I attempted to understand your LMDB implementation, but it would take me a significant amount of time to fully grasp it. I'm not clear on what exactly is being stored in the LMDB database.

Given that the VQ-VAE encoder outputs multiple quantization vectors (one for each encoding block), what should be the specific input for the PixelCNN?

x = torch.randn(4, 3, 128, 128, 64).to('cuda')
decoded, (commitment_loss, quantizations, encoding_idx) = vqvae(x)

I think i'll have to modify the LMDB data module part.

Thank you!