Merge pull request #35 from nbei/0.2.0

Bump to version v0.2.0

Author: nbei

README.md

@@ -57,9 +57,10 @@ MMGeneration is a powerful toolkit for generative models, especially for GANs no
 ## Highlight
 
 * **Positional Encoding as Spatial Inductive Bias in GANs (CVPR2021)** has been released in `MMGeneration`.  [\[Config\]](configs/positional_encoding_in_gans/README.md), [\[Project Page\]](https://nbei.github.io/gan-pos-encoding.html)
+* Mixed-precision training (FP16) for StyleGAN2 has been supported. Please check [the comparison](configs/styleganv2/README.md) between different implementations.
 ## Changelog
 
-v0.1.0 was released on 20/04/2021. Please refer to [changelog.md](docs/changelog.md) for details and release history.
+v0.2.0 was released on 30/05/2021. Please refer to [changelog.md](docs/changelog.md) for details and release history.
 
 ## ModelZoo
 
@@ -71,6 +72,8 @@ These methods have been carefully studied and supported in our frameworks:
 
 - ✅ [DCGAN](configs/dcgan/README.md) (ICLR'2016)
 - ✅ [WGAN-GP](configs/wgan-gp/README.md) (NIPS'2017)
+- ✅ [LSGAN](configs/lsgan/README.md) (ICCV'2017)
+- ✅ [GGAN](configs/ggan/README.md) (Axiv'2017)
 - ✅ [PGGAN](configs/pggan/README.md) (ICLR'2018)
 - ✅ [StyleGANV1](configs/styleganv1/README.md) (CVPR'2019)
 - ✅ [StyleGANV2](configs/styleganv2/README.md) (CVPR'2020)

README_zh-CN.md

@@ -58,9 +58,10 @@ MMGeneration 是一个基于 PyTorch 和[MMCV](https://github.com/open-mmlab/mmc
 ## 亮点
 
 * **Positional Encoding as Spatial Inductive Bias in GANs (CVPR2021)** 已在 `MMGeneration` 中发布.  [\[配置文件\]](configs/positional_encoding_in_gans/README.md), [\[项目主页\]](https://nbei.github.io/gan-pos-encoding.html)
+* 混合精度训练已经在 `StyleGAN2` 中进行了初步支持，请到[这里](configs/styleganv2/README.md)查看各种实现方式的详细比较。
 ## 更新日志
 
-v0.1.0 在 20/04/2021 发布。 关于细节和发布历史，请参考 [changelog.md](docs/changelog.md)。
+v0.2.0 在 30/05/2021 发布。 关于细节和发布历史，请参考 [changelog.md](docs/changelog.md)。
 
 ## 模型库
 
@@ -72,6 +73,8 @@ v0.1.0 在 20/04/2021 发布。 关于细节和发布历史，请参考 [changel
 
 - ✅ [DCGAN](configs/dcgan/README.md) (ICLR'2016)
 - ✅ [WGAN-GP](configs/wgan-gp/README.md) (NIPS'2017)
+- ✅ [LSGAN](configs/lsgan/README.md) (ICCV'2017)
+- ✅ [GGAN](configs/ggan/README.md) (Axiv'2017)
 - ✅ [PGGAN](configs/pggan/README.md) (ICLR'2018)
 - ✅ [StyleGANV1](configs/styleganv1/README.md) (CVPR'2019)
 - ✅ [StyleGANV2](configs/styleganv2/README.md) (CVPR'2020)

docs/changelog.md

@@ -12,3 +12,23 @@
 - 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.
+
+
+## v0.2.0 (30/05/2021)
+
+#### Highlights
+- Support new methods: LSGAN, GGAN.
+- Support mixed-precision training (FP16): official PyTorch Implementation and APEX (#11, #20)
+
+#### New Features
+
+- Add the experiment of MNIST in DCGAN (#24)
+- Add support for uploading checkpoints to `Ceph` system (cloud server) (#27)
+- Add the functionality of saving the best checkpoint in GenerativeEvalHook (#21)
+
+#### Fix bugs and Improvements
+
+- Fix loss of sample-cfg argument (#13)
+- Add `pbar` to 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)

mmgen/version.py

@@ -1,4 +1,4 @@
-__version__ = '0.1.0'
+__version__ = '0.2.0'
 
 
 def parse_version_info(version_str):