Source code :

src/  
    datasets.py - Different datasets classes that share common interface, it loads data and provides generators
    to iterate over minibatches  
    model_***.py - Classes that implement AAE architectures. Dense neural networks, convolution neural networks,
    networks that use Subpix layers.  
    aae_**_solver.py - Classes that implement different training procedures. Pixel Matching AAE, Feature matching
    AAE using GAN network  
    utils.py - Functions providing higher level abstraction over pure tensorflow ops.  
    
    
train_aae.py - Training procedure with different scenarios  
interface.py - Little GUI program, used for sampling from models and traversing latent space  
draw_samples.py - Visualize samples from input encoded into latent representation  
draw_images_**.py - Scripts to generate images from models produced during training.  
create_*.py - Scripts used to create datasets  

Models and Images: https://drive.google.com/drive/folders/0B2ZqB_V870aATHF5UmVrR1VCZGc?usp=sharing

Note:
Mnist dataset will be downloaded automatically
Celeb dataset has to be added manually to the CELEB folder