Lagrangian VAE

Requirements

• click
• gputil
• tqdm

Files

• methods/infovae.py: InfoVAE implementation (does not optimize Lagrange multiplers)
• methods/lagvae.py: LagVAE implementation (optimization of Lagrange multipliers)

Examples

Please set environment variables EXP_LOG_PATH and DATA_PREFIX for logging experiments and downloading data prior to running the examples.

• InfoVAE: python examples/infovae.py --mi=1.0 --e1=1.0 --e2=1.0
• LagVAE: python examples/lagvae.py --mi=1.0 --e1=86.0 --e2=5.0

Note that we scale up MMD by 10000 in the implementation, so --e2=5.0 for LagVAE means MMD < 0.0005.

Feel free to play around with different VariationalEncoder, VariationalDecoder, optimizers, and datasets.

References

If you find the idea or code useful for your research, please consider citing our paper:

@article{zhao2018the,
  title={The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models},
  author={Zhao, Shengjia and Song, Jiaming and Ermon, Stefano},
  journal={arXiv preprint arXiv:1806.06514},
  year={2018}
}

Acknowledgements

utils/logger.py is based on an implementation in OpenAI Baselines.