Skip to content

Pytorch Lightning implementation of adverserial autoencoder (AAE)

Notifications You must be signed in to change notification settings

Aiden-Jeon/AdversarialAutoencoder

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

8 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

AdversarialAutoencoder

Pytorch Lightning implementation of adverserial autoencoder (AAE)

Result of code

In paper, figure 4 shows the example latent for MNIST dataset. It can be a gaussian mixture or swill roll. paper-figure-4

My code can generate each of latent.

  • Gaussian Mixture

gaussian-mixture

  • Swiss roll

swiss-roll

Requirements

  • python==3.8.7

How to use

  1. Install requirements
pip install -r requirements.txt
  1. Run
python src/train.py 

train.py has --sample_latent argument.

2.1) Latent with swiss_roll

python src/train.py --sample_latent swiss_roll

2.2) Latent with gaussian_mixture

python src/train.py --sample_latent gaussian_mixture

About

Pytorch Lightning implementation of adverserial autoencoder (AAE)

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages