Awesome
CAUTION
Now that chainer official implementation is updated. Please refer it.
chainer-VAE
implementation of https://github.com/pfnet/chainer/tree/master/examples/vae using Trainer.
result/loss.png was compiled by using Viz.js.
If you use homebrew and wanna dump image file, brew install graphviz
, then dot -T <jpeg, png , etc> <computational_graph.dot> -o <output_image>
.
beta-VAE
As you can see in http://openreview.net/forum?id=Sy2fzU9gl, you can impose stronger regularization on latent space when define model via net.VAE(C=beta)
, where, beta > 1.
Execute train_vae.py
Argument Parser
- resume: resume from snapshot. Basically, snapshots are
chainer-VAE/result/snapshot_epoch_{epoch}
- interval: save images & snapshot intervals, default is
5