|
8 years ago | |
---|---|---|
.. | ||
data | 8 years ago | |
README.md | 8 years ago | |
dataloader.py | 8 years ago | |
vae_conf.py | 8 years ago | |
vae_train.py | 8 years ago |
README.md
#Variational Autoencoder (VAE)
This demo implements VAE training described in the original paper (https://arxiv.org/abs/1312.6114).
In order to run the model, first download the MNIST dataset by running the shell script in ./data.
Then you can run the command below. The flag --useGpu specifies whether to use gpu for training (0 is cpu, 1 is gpu).
$python vae_train.py [--use_gpu 1]
The generated images will be stored in ./samples/ The corresponding models will be stored in ./params/