Neural Discrete Representation Learning, VQ-VAE

Pytorch implementation of Neural Discrete Representation Learning

Requirements

• python 3.6
• pytorch 0.2.0_4
• visdom
  
  

RESULT : MNIST

RESULT : CIFAR10

reconstruction of randomly selected, fixed images

reconstruction of random samples

you can reproduce similar results by :

python main.py --dataset CIFAR10 --batch_size 100 --k_dim 256 --z_dim 256

To do:

• visdom -> tensorboardX
• learning prior p(z) using PixelCNN
• image sampling( dummy input => (PixelCNN) => Z_dec => (Decoder) => image )
• add references and acknowledgements