vae-ry exciting vae code
For all your TensorFlow Variational Autoencoder needs.
Description
This is the repository for the Variational Autoencoder (VAE) blogpost series from Fast Forward Labs. Start there, then check out the repo!
- Part I: Introducing Variational Autoencoders (in Prose and Code)
- Part II: Under the Hood of the Variational Autoencoder (in Prose and Code)
Usage:
To train a new model, edit main.py with your desired VAE ARCHITECTURE,
HYPERPARAMETERS, and paths/to/outdirs.
Then, simply:
$ python main.py
OR, restore a trained model from its saved meta_graph via:
$ python main.py <path/to/meta_graph_name>
(without the .meta suffix)