Highlights
- MMGeneration is released.
Main Features
- High-quality Training Performance: We currently support training on Unconditional GANs (
DCGAN,WGAN-GP,PGGAN,StyleGANV1,StyleGANV2,Positional Encoding in GANs), Internal GANs (SinGAN), and Image Translation Models (Pix2Pix,CycleGAN). Support for conditional models will come soon. - Powerful Application Toolkit: A plentiful toolkit containing multiple applications in GANs is provided to users. GAN interpolation, GAN projection, and GAN manipulations are integrated into our framework. It's time to play with your GANs!
- Efficient Distributed Training for Generative Models: For the highly dynamic training in generative models, we adopt a new way to train dynamic models with
MMDDP. - New Modular Design for Flexible Combination: A new design for complex loss modules is proposed for customizing the links between modules, which can achieve flexible combination among different modules.
- Support new methods: LSGAN, GGAN.
- Support mixed-precision training (FP16): official PyTorch Implementation and APEX (#11, #20)
- Add the experiment of MNIST in DCGAN (#24)
- Add support for uploading checkpoints to
Cephsystem (cloud server) (#27) - Add the functionality of saving the best checkpoint in GenerativeEvalHook (#21)
- Fix loss of sample-cfg argument (#13)
- Add
pbarto offline eval and fix bug in grayscale image evaluation/saving (#23) - Fix error when data_root option in val_cfg or test_cfg are set as None (#28)
- Change latex in quick_run.md to svg url and fix number of checkpoints in modelzoo_statistics.md (#34)
- Support conditional GANs: Projection GAN, SNGAN, SAGAN, and BigGAN
- Add support for persistent_workers in PyTorch >= 1.7.0 #71
- Support warm-up for EMA #55
- Fix failing to build docs #64
- Revise the logic of
num_classesin basic conditional gan #69 - Support dynamic eval internal in eval hook #73
- Add more experiments for conditional GANs: SNGAN, SAGAN, and BigGAN
- Refact Translation Model (#88, #126, #127, #145)
- Use PyTorch Sphinx theme #123
- Support torchserve for unconditional models #131
- Add CI for python3.9 #110
- Add support for PyTorch1.9 #115
- Add pre-commit hook for spell checking #135
- Support BigGAN style's Spectral Norm and update BigGAN with best FID and IS (#159)
- Support import projected latent and export video in interpolation (#167)
- Support Improved-DDPM model (#205)
- One face editing application build upon MMGen is released
- Support evaluation in distributed mode (#151)
- Support
presistent_workin validation dataloader (#179) - Support dockerfile (#200)
- Support
mim(#176)
- Fix bug in SinGAN dataset (#192)
- Fix SAGAN, SNGAN and BigGAN's default
sn_style(#199, #213)
- Support StyleGANv3 (#247, #253, #258)
- Support StyleCLIP (#236)
- Support training on CPU (#238)
- Speed up training (#231)
- Fix bug in non-distributed training/testing (#239)
- Fix typos and invalid links (#221, #226, #228, #244, #249)
- Add part of Chinese documentation (#250, #257)
- Support training of StyleGANv3 (#275, #277)
- Support adaptive discriminator augmentation (#276)
- Support passing training arguments in static unconditional gan (#275)
- Support dynamic EMA, now you can define momentum updating policy (#261)
- Add multi machine distribute train (#267)
- Add brief installation steps in README (#270)
- Support random seed for distributed sampler (#271)
- Use hyphen for command line args in apps (#273)
- Support train_dataloader, val_dataloader and test_dataloader settings (#281)
- Fix ada typo (#283)
- Add chinese application tutorial (#284)
- Add chinese document of ddp training (#286)
- Complete readme of StyleGAN-Ada (#391)
- Update limitation of MMCV's version (#397)
- Add Circle CI (#431)
- Update Chinese readme for
application.md(#425)
- Fix SiLU activation (#447)
- Support Perceptual Loss (#471)
- Fix tensor and index aren't on the same device error (#476)