Bump version to v0.9.1 (#322)

* [Fix]: Set qkv bias to False for cae and True for mae (#303) * [Fix]: Add mmcls transformer layer choice * [Fix]: Fix transformer encoder layer bug * [Fix]: Change UT of cae * [Feature]: Change the file name of cosine annealing hook (#304) * [Feature]: Change cosine annealing hook file name * [Feature]: Add UT for cosine annealing hook * [Fix]: Fix lint * read tutorials and fix typo (#308) * [Fix] fix config errors in MAE (#307) * update readthedocs algorithm readme (#310) * [Docs] Replace markdownlint with mdformat (#311) * Replace markdownlint with mdformat to avoid installing ruby * fix typo * add 'ba' to codespell ignore-words-list * Configure Myst-parser to parse anchor tag (#309) * [Docs] rewrite install.md (#317) * rewrite the install.md * add faq.md * fix lint * add FAQ to README * add Chinese version * fix typo * fix format * remove modification * fix format * [Docs] refine README.md file (#318) * refine README.md file * fix lint * format language button * rename getting_started.md * revise index.rst * add model_zoo.md to index.rst * fix lint * refine readme Co-authored-by: Jiahao Xie <[email protected]> * [Enhance] update byol models and results (#319) * Update version information (#321) Co-authored-by: Yuan Liu <[email protected]> Co-authored-by: Yi Lu <[email protected]> Co-authored-by: RenQin <[email protected]> Co-authored-by: Jiahao Xie <[email protected]>
open-mmlab · Jun 1, 2022 · bbdf670 · bbdf670
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diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md
@@ -0,0 +1 @@
+We appreciate all contributions to improve MMSelfSup. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.
diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md
@@ -4,15 +4,14 @@ about: Suggest an idea for this project
 title: ''
 labels: ''
 assignees: ''
-
 ---
 
 **Describe the feature**
 
 **Motivation**
 A clear and concise description of the motivation of the feature.
-Ex1. It is inconvenient when [....].
-Ex2. There is a recent paper [....], which is very helpful for [....].
+Ex1. It is inconvenient when \[....\].
+Ex2. There is a recent paper \[....\], which is very helpful for \[....\].
 
 **Related resources**
 If there is an official code release or third-party implementations, please also provide the information here, which would be very helpful.

diff --git a/.github/ISSUE_TEMPLATE/general_questions.md b/.github/ISSUE_TEMPLATE/general_questions.md
@@ -4,7 +4,6 @@ about: Ask general questions to get help
 title: ''
 labels: ''
 assignees: ''
-
 ---
 
 **Checklist**

diff --git a/.github/ISSUE_TEMPLATE/unexpected_report.md b/.github/ISSUE_TEMPLATE/unexpected_report.md
@@ -4,7 +4,6 @@ about: Create a report to help us improve
 title: ''
 labels: ''
 assignees: ''
-
 ---
 
 Thanks for reporting the unexpected results and we appreciate it a lot.
@@ -31,8 +30,8 @@ A placeholder for the command.
 
 1. Please run `python -c "from mmselfsup.utils import collect_env; print(collect_env())"` to collect necessary environment information and paste it here.
 2. You may add addition that may be helpful for locating the problem, such as
-    - How you installed PyTorch [e.g., pip, conda, source]
-    - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
+   - How you installed PyTorch \[e.g., pip, conda, source\]
+   - Other environment variables that may be related (such as `$PATH`, `$LD_LIBRARY_PATH`, `$PYTHONPATH`, etc.)
 
 **Error traceback**
 If applicable, paste the error traceback here.

diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
@@ -1,7 +1,7 @@
 exclude: ^tests/data/
 repos:
-  - repo: https://gitlab.com/pycqa/flake8.git
-    rev: 3.8.3
+  - repo: https://github.com/PyCQA/flake8
+    rev: 4.0.1
     hooks:
       - id: flake8
   - repo: https://github.com/timothycrosley/isort
@@ -26,11 +26,6 @@ repos:
         args: ["--remove"]
       - id: mixed-line-ending
         args: ["--fix=lf"]
-  - repo: https://github.com/markdownlint/markdownlint
-    rev: v0.11.0
-    hooks:
-      - id: markdownlint
-        args: ["-r", "~MD002,~MD013,~MD024,~MD029,~MD033,~MD034,~MD036", "-t", "allow_different_nesting"]
   - repo: https://github.com/codespell-project/codespell
     rev: v2.1.0
     hooks:
@@ -40,6 +35,15 @@ repos:
     hooks:
       - id: docformatter
         args: ["--in-place", "--wrap-descriptions", "79"]
+  - repo: https://github.com/executablebooks/mdformat
+    rev: 0.7.14
+    hooks:
+      - id: mdformat
+        args: ["--number"]
+        additional_dependencies:
+          - mdformat-gfm
+          - mdformat_frontmatter
+          - linkify-it-py
   - repo: https://github.com/open-mmlab/pre-commit-hooks
     rev: v0.2.0
     hooks:

diff --git a/README.md b/README.md
@@ -30,17 +30,21 @@
 [👀Model Zoo](https://github.com/open-mmlab/mmselfsup/blob/master/docs/en/model_zoo.md) |
 [🆕Update News](https://mmselfsup.readthedocs.io/en/latest/changelog.html) |
 [🤔Reporting Issues](https://github.com/open-mmlab/mmselfsup/issues/new/choose)
+
 </div>
 
-## Introduction
+<div align="center">
 
 English | [简体中文](README_zh-CN.md)
 
+</div>
+
+## Introduction
+
 MMSelfSup is an open source self-supervised representation learning toolbox based on PyTorch. It is a part of the [OpenMMLab](https://openmmlab.com/) project.
 
 The master branch works with **PyTorch 1.5** or higher.
 
-
 ### Major features
 
 - **Methods All in One**
@@ -59,34 +63,52 @@ The master branch works with **PyTorch 1.5** or higher.
 
   Since MMSelfSup adopts similar design of modulars and interfaces as those in other OpenMMLab projects, it supports smooth evaluation on downstream tasks with other OpenMMLab projects like object detection and segmentation.
 
+## What's New
 
-## License
-
-This project is released under the [Apache 2.0 license](LICENSE).
-
-## ChangeLog
-
-MMSelfSup **v0.9.0** was released in 29/04/2022.
+MMSelfSup **v0.9.1** was released in 31/05/2022.
 
 Highlights of the new version:
 
-* Support **CAE**
-* Support **Barlow Twins**
+- Update **BYOL** model and results
+- Refine some documentation
 
 Please refer to [changelog.md](docs/en/changelog.md) for details and release history.
 
 Differences between MMSelfSup and OpenSelfSup codebases can be found in [compatibility.md](docs/en/compatibility.md).
 
-## Model Zoo and Benchmark
+## Installation
+
+MMSelfSup depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) and [MMClassification](https://github.com/open-mmlab/mmclassification).
+
+Please refer to [install.md](docs/en/install.md) for more detailed instruction.
+
+## Get Started
+
+Please refer to [prepare_data.md](docs/en/prepare_data.md) for dataset preparation and [get_started.md](docs/en/get_started.md) for the basic usage of MMSelfSup.
+
+We also provides tutorials for more details:
+
+- [config](docs/en/tutorials/0_config.md)
+- [add new dataset](docs/en/tutorials/1_new_dataset.md)
+- [data pipeline](docs/en/tutorials/2_data_pipeline.md)
+- [add new module](docs/en/tutorials/3_new_module.md)
+- [customize schedules](docs/en/tutorials/4_schedule.md)
+- [customize runtime](docs/en/tutorials/5_runtime.md)
+- [benchmarks](docs/en/tutorials/6_benchmarks.md)
+
+Besides, we provide [colab tutorial](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb) for basic usage.
+
+Please refer to [FAQ](docs/en/faq.md) for frequently asked questions.
+
+## Model Zoo
 
-### Model Zoo
 Please refer to [model_zoo.md](docs/en/model_zoo.md) for a comprehensive set of pre-trained models and benchmarks.
 
 Supported algorithms:
 
 - [x] [Relative Location (ICCV'2015)](https://arxiv.org/abs/1505.05192)
 - [x] [Rotation Prediction (ICLR'2018)](https://arxiv.org/abs/1803.07728)
-- [x] [DeepCLuster (ECCV'2018)](https://arxiv.org/abs/1807.05520)
+- [x] [DeepCluster (ECCV'2018)](https://arxiv.org/abs/1807.05520)
 - [x] [NPID (CVPR'2018)](https://arxiv.org/abs/1805.01978)
 - [x] [ODC (CVPR'2020)](https://arxiv.org/abs/2006.10645)
 - [x] [MoCo v1 (CVPR'2020)](https://arxiv.org/abs/1911.05722)
@@ -104,43 +126,32 @@ Supported algorithms:
 
 More algorithms are in our plan.
 
-### Benchmark
-
-  | Benchmarks                                         | Setting                                                                                                                                                              |
-  | -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-  | ImageNet Linear Classification (Multi-head)        | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
-  | ImageNet Linear Classification (Last)              |                                                                                                                                                                      |
-  | ImageNet Semi-Sup Classification                   |                                                                                                                                                                      |
-  | Places205 Linear Classification (Multi-head)       | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
-  | iNaturalist2018 Linear Classification (Multi-head) | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
-  | PASCAL VOC07 SVM                                   | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
-  | PASCAL VOC07 Low-shot SVM                          | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
-  | PASCAL VOC07+12 Object Detection                   | [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf)               |
-  | COCO17 Object Detection                            | [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf)               |
-  | Cityscapes Segmentation                            | [MMSeg](configs/benchmarks/mmsegmentation/cityscapes/fcn_r50-d8_769x769_40k_cityscapes.py)                                                                           |
-  | PASCAL VOC12 Aug Segmentation                      | [MMSeg](configs/benchmarks/mmsegmentation/voc12aug/fcn_r50-d8_512x512_20k_voc12aug.py)                                                                               |
-
-## Installation
+## Benchmark
+
+| Benchmarks                                         | Setting                                                                                                                                                              |
+| -------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| ImageNet Linear Classification (Multi-head)        | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
+| ImageNet Linear Classification (Last)              |                                                                                                                                                                      |
+| ImageNet Semi-Sup Classification                   |                                                                                                                                                                      |
+| Places205 Linear Classification (Multi-head)       | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
+| iNaturalist2018 Linear Classification (Multi-head) | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
+| PASCAL VOC07 SVM                                   | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
+| PASCAL VOC07 Low-shot SVM                          | [Goyal2019](http://openaccess.thecvf.com/content_ICCV_2019/papers/Goyal_Scaling_and_Benchmarking_Self-Supervised_Visual_Representation_Learning_ICCV_2019_paper.pdf) |
+| PASCAL VOC07+12 Object Detection                   | [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf)               |
+| COCO17 Object Detection                            | [MoCo](http://openaccess.thecvf.com/content_CVPR_2020/papers/He_Momentum_Contrast_for_Unsupervised_Visual_Representation_Learning_CVPR_2020_paper.pdf)               |
+| Cityscapes Segmentation                            | [MMSeg](configs/benchmarks/mmsegmentation/cityscapes/fcn_r50-d8_769x769_40k_cityscapes.py)                                                                           |
+| PASCAL VOC12 Aug Segmentation                      | [MMSeg](configs/benchmarks/mmsegmentation/voc12aug/fcn_r50-d8_512x512_20k_voc12aug.py)                                                                               |
 
-MMSelfSup depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) and [MMClassification](https://github.com/open-mmlab/mmclassification).
-
-Please refer to [install.md](docs/en/install.md) for more detailed instruction.
-
-## Get Started
+## Contributing
 
-Please refer to [prepare_data.md](docs/en/prepare_data.md) for dataset preparation and [getting_started.md](docs/en/getting_started.md) for the basic usage of MMSelfSup.
+We appreciate all contributions improving MMSelfSup. Please refer to [CONTRIBUTING.md](.github/CONTRIBUTING.md) for more details about the contributing guideline.
 
-We also provides tutorials for more details:
+## Acknowledgement
 
-- [config](docs/en/tutorials/0_config.md)
-- [add new dataset](docs/en/tutorials/1_new_dataset.md)
-- [data pipeline](docs/en/tutorials/2_data_pipeline.md)
-- [add new module](docs/en/tutorials/3_new_module.md)
-- [customize schedules](docs/en/tutorials/4_schedule.md)
-- [customize runtime](docs/en/tutorials/5_runtime.md)
-- [benchmarks](docs/en/tutorials/6_benchmarks.md)
+MMSelfSup is an open source project that is contributed by researchers and engineers from various colleges and companies. We appreciate all the contributors who implement their methods or add new features, as well as users who give valuable feedbacks.
+We wish that the toolbox and benchmark could serve the growing research community by providing a flexible toolkit to reimplement existing methods and develop their own new algorithms.
 
-Besides, we provide [colab tutorial](https://github.com/open-mmlab/mmselfsup/blob/master/demo/mmselfsup_colab_tutorial.ipynb) for basic usage.
+MMSelfSup originates from OpenSelfSup, and we appreciate all early contributions made to OpenSelfSup. A few contributors are listed here: Xiaohang Zhan ([@XiaohangZhan](http://github.com/XiaohangZhan)), Jiahao Xie ([@Jiahao000](https://github.com/Jiahao000)), Enze Xie ([@xieenze](https://github.com/xieenze)), Xiangxiang Chu ([@cxxgtxy](https://github.com/cxxgtxy)), Zijian He ([@scnuhealthy](https://github.com/scnuhealthy)).
 
 ## Citation
 
@@ -155,19 +166,9 @@ If you use this toolbox or benchmark in your research, please cite this project.
 }
 ```
 
-## Contributing
-
-We appreciate all contributions improving MMSelfSup. Please refer to [CONTRIBUTING.md](docs/en/community/CONTRIBUTING.md) for more details about the contributing guideline.
-
-## Acknowledgement
-
-Remarks:
+## License
 
-- MMSelfSup originates from OpenSelfSup, and we appreciate all early contributions made to OpenSelfSup. A few contributors are listed here: Xiaohang Zhan, Jiahao Xie, Enze Xie, Xiangxiang Chu, Zijian He.
-- The implementation of MoCo and the detection benchmark borrow the code from [MoCo](https://github.com/facebookresearch/moco).
-- The implementation of SwAV borrows the code from [SwAV](https://github.com/facebookresearch/swav).
-- The SVM benchmark borrows the code from [fair_self_supervision_benchmark](https://github.com/facebookresearch/fair_self_supervision_benchmark).
-- `mmselfsup/utils/clustering.py` is borrowed from [deepcluster](https://github.com/facebookresearch/deepcluster/blob/master/clustering.py).
+This project is released under the [Apache 2.0 license](LICENSE).
 
 ## Projects in OpenMMLab
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		We appreciate all contributions to improve MMSelfSup. Please refer to [CONTRIBUTING.md](https://github.com/open-mmlab/mmcv/blob/master/CONTRIBUTING.md) in MMCV for more details about the contributing guideline.