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Pytorch Implementation of "Neural Discrete Representation Learning"

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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

mnist

RESULT : CIFAR10

reconstruction of randomly selected, fixed images
cifar10_fixed
reconstruction of random samples
cifar10_random
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

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Pytorch Implementation of "Neural Discrete Representation Learning"


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