(beta-)VAE

Tensorflow implementation of VAE and beta-VAE

Exemplar results

Celeba
- ConvNet (z_dim: 100, beta: 0.05)
  
  Generation Reconstruction
Mnist
- ConvNet (z_dim: 10, beta: 0.1)
  
  Generation Reconstruction
- MLP (z_dim: 10, beta: 0.1)
  
  Generation Reconstruction

Usage

Prerequisites
- Tensorflow 1.8
- Python 2.7 or 3.6

Examples of training

CUDA_VISIBLE_DEVICES=0 python train.py --z_dim 10 --beta 0.1 --dataset mnist --model mlp_mnist --experiment_name z10_beta0.1_mnist_mlp
CUDA_VISIBLE_DEVICES=0 python train.py --z_dim 10 --beta 0.1 --dataset mnist --model conv_mnist --experiment_name z10_beta0.1_mnist_conv
CUDA_VISIBLE_DEVICES=0 python train.py --z_dim 32 --beta 0.1 --dataset celeba --model conv_64 --experiment_name z32_beta0.1_celeba_conv

Datasets

Celeba should be prepared by yourself in *./data/celeba/img_align_celeba/.jpg
- Download the dataset: https://www.dropbox.com/sh/8oqt9vytwxb3s4r/AAB06FXaQRUNtjW9ntaoPGvCa?dl=0
- the above links might be inaccessible, the alternatives are
  - img_align_celeba.zip
    - https://pan.baidu.com/s/1eSNpdRG#list/path=%2FCelebA%2FImg or
    - https://drive.google.com/drive/folders/0B7EVK8r0v71pTUZsaXdaSnZBZzg
Mnist will be automatically downloaded