VQ-VAE
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Pytorch Implementation of "Neural Discrete Representation Learning"
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