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* Switched to pytorch * Almost a complete rewrite * Faster, cleaner, more stable * Model definition language formalized * New custom train hooks not available in other projects * More...
* Initial private release !(https://raw.githubusercontent.com/255BITS/HyperGAN/master/doc/legacy-0.1.png) !(https://raw.githubusercontent.com/255BITS/HyperGAN/master/doc/legacy-0.1-2.png)
* 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](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 [https://github.com/255BITS/HyperGAN/pull/66](https://github.com/255BITS/HyperGAN/pull/66)
* Tensorflow 1.0 support * New configuration format and refactored api. * New loss based on least squared GAN. See [least squares GAN implementation](changelog.mdLeast-Squares-GAN). * 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 !(https://raw.githubusercontent.com/255BITS/HyperGAN/master/doc/face-manifold-0-5-6.png) !(https://raw.githubusercontent.com/255BITS/HyperGAN/master/doc/face-manifold.png)