- HyperGAN 0.10 released as a community project
- Configurable network architectures using a simple DSL
- Lots of new regularizers and losses
- Evolution based GangTrainer
- Curriculum trainer with progressive growing
- Optimistic loading
- New next-frame example
- More...
- API Documentation - https://s3.amazonaws.com/hypergan-apidocs/0.9.0/index.html
- Prepackaged configurations
- New viewer front-end!
- Examples, including the ability to randomly search for good configurations
See more here HyperGAN#66
- Tensorflow 1.0 support
- New configuration format and refactored api.
- New loss based on least squared GAN. See least squares GAN implementation.
- API example
2d-test
- tests a trainer/encoder/loss combination against a known distribution. - API example
2d-measure
- measure and report the above test by randomly combining options. - Updated default configuration.
- More
- New loss
wgan
- Initial Public API Release
- API example:
colorizer
- re-colorize an image! - API example:
inpainter
- remove a section of an image and have your GAN repaint it - API example:
super-resolution
- zoom in and enhance. We've caught the bad guy! - 4 new samplers.
--sampler
flag. Valid options are:batch
,progressive
,static_batch
,grid
.
- pip package released
- Initial private release