[Docs] Prepare for checkouting default branch and releasing new version

.circleci/config.yml

@@ -26,7 +26,7 @@ workflows:
             tools/.* lint_only false
             configs/.* lint_only false
             .circleci/.* lint_only false
-          base-revision: dev-1.x
+          base-revision: main
           # this is the path of the configuration we should trigger once
           # path filtering and pipeline parameter value updates are
           # complete. In this case, we are using the parent dynamic

.circleci/test.yml

@@ -67,10 +67,10 @@ jobs:
             pip install git+https://github.com/open-mmlab/mmengine.git@main
             pip install -U openmim
             mim install 'mmcv >= 2.0.0rc1'
-            pip install git+https://github.com/open-mmlab/mmclassification.git@dev-1.x
-            pip install git+https://github.com/open-mmlab/mmdetection.git@dev-3.x
-            pip install git+https://github.com/open-mmlab/mmsegmentation.git@dev-1.x
-            python -m pip install git+ssh://git@github.com/open-mmlab/mmpose.git@dev-1.x
+            pip install git+https://github.com/open-mmlab/mmpretrain.git@mmcls-1.x
+            pip install git+https://github.com/open-mmlab/mmdetection.git@main
+            pip install git+https://github.com/open-mmlab/mmsegmentation.git@main
+            python -m pip install git+ssh://git@github.com/open-mmlab/mmpose.git@main
             pip install -r requirements.txt
       - run:
           name: Build and install
@@ -139,7 +139,7 @@ workflows:
           filters:
             branches:
               ignore:
-                - dev-1.x
+                - main
                 - 1.x
   pr_stage_test:
     when:
@@ -150,7 +150,7 @@ workflows:
           filters:
             branches:
               ignore:
-                - dev-1.x
+                - main
       - build_cpu:
           name: minimum_version_cpu
           torch: 1.8.1
@@ -190,4 +190,4 @@ workflows:
           filters:
             branches:
               only:
-                - dev-1.x
+                - main

README.md

@@ -21,7 +21,7 @@
 <!--算法库 Badges-->
 
 [![PyPI](https://img.shields.io/pypi/v/mmrazor)](https://pypi.org/project/mmrazor)
-[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmrazor.readthedocs.io/en/quantize/)
+[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmrazor.readthedocs.io/en/main/)
 [![badge](https://github.com/open-mmlab/mmrazor/workflows/build/badge.svg)](https://github.com/open-mmlab/mmrazor/actions)
 [![codecov](https://codecov.io/gh/open-mmlab/mmrazor/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmrazor)
 [![license](https://img.shields.io/github/license/open-mmlab/mmrazor.svg)](https://github.com/open-mmlab/mmrazor/blob/master/LICENSE)
@@ -32,9 +32,9 @@
 
 <!--Note:请根据各算法库自身情况设置项目和链接-->
 
-[📘Documentation](https://mmrazor.readthedocs.io/en/quantize/) |
-[🛠️Installation](https://mmrazor.readthedocs.io/en/quantize/get_started/installation.html) |
-[👀Model Zoo](https://mmrazor.readthedocs.io/en/quantize/get_started/model_zoo.html) |
+[📘Documentation](https://mmrazor.readthedocs.io/en/main/) |
+[🛠️Installation](https://mmrazor.readthedocs.io/en/main/get_started/installation.html) |
+[👀Model Zoo](https://mmrazor.readthedocs.io/en/main/get_started/model_zoo.html) |
 [🤔Reporting Issues](https://github.com/open-mmlab/mmrazor/issues/new/choose)
 
 </div>
@@ -86,22 +86,23 @@ Major features:
 
   With better modular design, developers can implement new model compression algorithms with only a few codes, or even by simply modifying config files.
 
-Below is an overview of MMRazor's design and implementation, please refer to [tutorials](https://mmrazor.readthedocs.io/en/quantize/get_started/overview.html) for more details.
+About MMRazor's design and implementation, please refer to [tutorials](https://mmrazor.readthedocs.io/en/main/get_started/overview.html) for more details.
 
-<div align="center">
-  <img src="resources/design_and_implement.png" style="zoom:100%"/>
-</div>
-<br />
+## Latest Updates
 
-## What's new
+**The default branch is now `main` and the code on the branch has been upgraded to v1.0.0. The old `master` branch code now exists on the 0.x branch**
 
-MMRazor v1.0.0rc0 was released in 1/9/2022.
+MMRazor v1.0.0 was released in 2023-4-18, Major updates from 1.0.0rc2 include:
 
-Please refer to [changelog.md](/docs/en/notes/changelog.md) for more details and other release history.
+1. MMRazor quantization is released.
+2. Add a new pruning algorithm named GroupFisher.
+3. Support distilling rtmdet with MMRazor.
+
+To know more about the updates in MMRazor 1.0, please refer to [Changelog](https://mmrazor.readthedocs.io/en/main/notes/changelog.html) for more details!
 
 ## Benchmark and model zoo
 
-Results and models are available in the [model zoo](/docs/en/get_started/model_zoo.md).
+Results and models are available in the [model zoo](https://mmrazor.readthedocs.io/en/main/get_started/model_zoo.html).
 
 Supported algorithms:
 
@@ -121,6 +122,12 @@ Supported algorithms:
 
 - [x] [AutoSlim(NeurIPS'2019)](/configs/pruning/mmcls/autoslim)
 
+- [x] [L1-norm](/configs/pruning/mmcls/l1-norm)
+
+- [x] [Group Fisher](/configs/pruning/base/group_fisher)
+
+- [x] [DMCP](/configs/pruning/mmcls/dmcp)
+
 </details>
 
 <details open>
@@ -156,20 +163,31 @@ Supported algorithms:
 
 </details>
 
+<details open>
+<summary>Quantization</summary>
+
+- [x] [PTQ](/configs/quantization/ptq/base)
+
+- [x] [QAT](/configs/quantization/qat/base)
+
+- [x] [LSQ](/configs/quantization/qat/lsq)
+
+</details>
+
 ## Installation
 
 MMRazor depends on [PyTorch](https://pytorch.org/), [MMCV](https://github.com/open-mmlab/mmcv) and [MMEngine](https://github.com/open-mmlab/mmengine).
 
-Please refer to [installation.md](/docs/en/get_started/installation.md) for more detailed instruction.
+Please refer to [installation.md](https://mmrazor.readthedocs.io/en/main/get_started/installation.html) for more detailed instruction.
 
 ## Getting Started
 
-Please refer to [user guides](https://mmrazor.readthedocs.io/en/quantize/user_guides/index.html) for the basic usage of MMRazor. There are also [advanced guides](https://mmrazor.readthedocs.io/en/quantize/advanced_guides/index.html):
+Please refer to [user guides](https://mmrazor.readthedocs.io/en/main/user_guides/index.html) for the basic usage of MMRazor. There are also [advanced guides](https://mmrazor.readthedocs.io/en/main/advanced_guides/index.html):
 
 ## Contributing
 
 We appreciate all contributions to improve MMRazor.
-Please refer to [CONTRUBUTING.md](/docs/en/notes/contribution_guide.md) for the contributing guideline.
+Please refer to [CONTRUBUTING.md](https://mmrazor.readthedocs.io/en/main/notes/contribution_guide.html) for the contributing guideline.
 
 ## Acknowledgement
 

README_zh-CN.md

@@ -21,7 +21,7 @@
 <!--算法库 Badges-->
 
 [![PyPI](https://img.shields.io/pypi/v/mmrazor)](https://pypi.org/project/mmrazor)
-[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmrazor.readthedocs.io/en/latest/)
+[![docs](https://img.shields.io/badge/docs-latest-blue)](https://mmrazor.readthedocs.io/en/main/)
 [![badge](https://github.com/open-mmlab/mmrazor/workflows/build/badge.svg)](https://github.com/open-mmlab/mmrazor/actions)
 [![codecov](https://codecov.io/gh/open-mmlab/mmrazor/branch/master/graph/badge.svg)](https://codecov.io/gh/open-mmlab/mmrazor)
 [![license](https://img.shields.io/github/license/open-mmlab/mmrazor.svg)](https://github.com/open-mmlab/mmrazor/blob/master/LICENSE)
@@ -32,9 +32,9 @@
 
 <!--Note:请根据各算法库自身情况设置项目和链接-->
 
-[📘使用文档](https://mmrazor.readthedocs.io/) |
-[🛠️安装教程](https://mmrazor.readthedocs.io/en/latest/get_started.html) |
-[👀模型库](https://mmrazor.readthedocs.io/en/latest/model_zoo.html) |
+[📘使用文档](https://mmrazor.readthedocs.io/en/main/) |
+[🛠️安装教程](https://mmrazor.readthedocs.io/en/main/get_started/installation.html) |
+[👀👀模型库](https://mmrazor.readthedocs.io/en/main/get_started/model_zoo.html) |
 [🤔报告问题](https://github.com/open-mmlab/mmrazor/issues/new/choose)
 
 </div>
@@ -54,7 +54,7 @@ MMRazor是一个可用于模型瘦身和AutoML的模型压缩工具箱，包含
 - 网络结构搜索 (NAS)
 - 模型剪枝
 - 知识蒸馏 (KD)
-- 量化 (下个版本发布)
+- 量化
 
 MMRazor是[OpenMMLab](https://openmmlab.com/)项目的一部分。
 
@@ -72,20 +72,19 @@ MMRazor是[OpenMMLab](https://openmmlab.com/)项目的一部分。
 
   得益于更好的模块化设计，开发者仅用修改少量代码，甚至只用修改配置文件即可实现新的轻量化算法。
 
-下面是MMRazor设计和实现的概括图, 如果想了解更多的细节，请参考 [tutorials](/docs/en/tutorials/Tutorial_1_overview.md)。
+关于MMRazor设计和实现的概括图, 如果想了解更多的细节，请参考 [tutorials](/docs/en/tutorials/Tutorial_1_overview.md)。
 
-<div align="center">
-  <img src="resources/design_and_implement.png" style="zoom:100%"/>
-</div>
-<br />
+## 近期更新
+
+**默认分支目前为 main，且分支上的代码已经切换到 v1.0.0 版本。旧版 master 分支的代码现存在 0.x 分支上**
 
 ## 更新日志
 
 MMRazor v0.3.1 版本已经在 2022.5.4 发布。
 
 ## 基准测试和模型库
 
-测试结果可以在 [模型库](docs/en/model_zoo.md) 中找到.
+测试结果可以在 [模型库](https://mmrazor.readthedocs.io/en/main/get_started/model_zoo.html) 中找到.
 
 已经支持的算法：
 
@@ -99,37 +98,69 @@ Neural Architecture Search
 
 Pruning
 
-- [x] [AutoSlim(NeurIPS'2019)](/configs/pruning/autoslim)
+- [x] [AutoSlim(NeurIPS'2019)](/configs/pruning/mmcls/autoslim)
+
+- [x] [L1-norm](/configs/pruning/mmcls/l1-norm)
+
+- [x] [Group Fisher](/configs/pruning/base/group_fisher)
+
+- [x] [DMCP](/configs/pruning/mmcls/dmcp)
 
 Knowledge Distillation
 
-- [x] [CWD(ICCV'2021)](/configs/distill/cwd)
+- [x] [CWD(ICCV'2021)](/configs/distill/mmdet/cwd)
+
+- [x] [WSLD(ICLR'2021)](/configs/distill/mmcls/wsld)
+
+- [x] [ABLoss](/configs/distill/mmcls/abloss)
+
+- [x] [BYOT](/configs/distill/mmcls/byot)
+
+- [x] [DAFL](/configs/distill/mmcls/dafl)
+
+- [x] [DFAD](/configs/distill/mmcls/dfad)
+
+- [x] [DKD](/configs/distill/mmcls/dkd)
 
-- [x] [WSLD(ICLR'2021)](/configs/distill/wsld)
+- [x] [Factor Transfer](/configs/distill/mmcls/factor_transfer)
+
+- [x] [FitNets](/configs/distill/mmcls/fitnets)
+
+- [x] [KD](/configs/distill/mmcls/kd)
+
+- [x] [OFD](/configs/distill/mmcls/ofd)
+
+- [x] [RKD](/configs/distill/mmcls/rkd)
+
+- [x] [ZSKT](/configs/distill/mmcls/zskt)
+
+- [x] [FBKD](/configs/distill/mmdet/fbkd)
+
+<details open>
+<summary>Quantization</summary>
+
+- [x] [PTQ](/configs/quantization/ptq/base)
+
+- [x] [QAT](/configs/quantization/qat/base)
+
+- [x] [LSQ](/configs/quantization/qat/lsq)
+
+</details>
 
 ## 安装
 
 MMRazor 依赖 [PyTorch](https://pytorch.org/) 和 [MMCV](https://github.com/open-mmlab/mmcv)。
 
-请参考[get_started.md](/docs/en/get_started.md)获取更详细的安装指南。
+请参考[安装教程](https://mmrazor.readthedocs.io/en/main/get_started/installation.html)获取更详细的安装指南。
 
 ## 快速入门
 
-请参考 [get_started.md](/docs/en/get_started.md) 学习 MMRazor 的基本使用。 我们也提供了一些进阶教程:
-
-- [overview](/docs/en/tutorials/Tutorial_1_overview.md)
-- [learn about configs](/docs/en/tutorials/Tutorial_2_learn_about_configs.md)
-- [customize architectures](/docs/en/tutorials/Tutorial_3_customize_architectures.md)
-- [customize nas algorithms](/docs/en/tutorials/Tutorial_4_customize_nas_algorithms.md)
-- [customize pruning algorithms](/docs/en/tutorials/Tutorial_5_customize_pruning_algorithms.md)
-- [customize kd algorithms](/docs/en/tutorials/Tutorial_6_customize_kd_algorithms.md)
-- [customize mixed algorithms with our algorithm_components](/docs/en/tutorials/Tutorial_7_customize_mixed_algorithms_with_out_algorithms_components.md)
-- [apply existing algorithms to other existing tasks](/docs/en/tutorials/Tutorial_8_apply_existing_algorithms_to_new_tasks.md)
+请参考 [用户指引](https://mmrazor.readthedocs.io/en/main/user_guides/index.html) 学习 MMRazor 的基本使用。 我们也提供了一些[进阶教程](https://mmrazor.readthedocs.io/en/main/advanced_guides/index.html):
 
 ## 贡献指南
 
 我们感谢所有的贡献者为改进和提升 MMRazor 所作出的努力。
-请参考[贡献指南](/.github/CONTRIBUTING.md)来了解参与项目贡献的相关指引。
+请参考[贡献指南](https://mmrazor.readthedocs.io/en/main/notes/contribution_guide.html)来了解参与项目贡献的相关指引。
 
 ## 致谢
 

configs/quantization/deploy_cfgs/mmcls/classification_tensorrt-int8-explicit_dynamic-224x224.py

@@ -34,6 +34,6 @@
         ]),
     function_record_to_pop=[
         'mmcls.models.classifiers.ImageClassifier.forward',
-        'mmcls.models.classifiers.BaseClassifier.forward'
+        'mmcls.models.classifiers.BaseClassifier.forward', 'torch.cat'
     ],
 )

configs/quantization/deploy_cfgs/mmdet/detection_tensorrt-int8-explicit_dynamic-320x320-1344x1344.py

@@ -53,5 +53,6 @@
     function_record_to_pop=[
         'mmdet.models.detectors.single_stage.SingleStageDetector.forward',
         'mmdet.models.detectors.two_stage.TwoStageDetector.forward',
-        'mmdet.models.detectors.single_stage_instance_seg.SingleStageInstanceSegmentor.forward'  # noqa: E501
+        'mmdet.models.detectors.single_stage_instance_seg.SingleStageInstanceSegmentor.forward',  # noqa: E501
+        'torch.cat'
     ])

configs/quantization/ptq/base/README.md

@@ -56,4 +56,4 @@ python tools/ptq.py ${CONFIG}
 python tools/test.py ${CONFIG} ${CKPT}
 ```
 
-For more details, please refer to [Quantization User Guide](mmrazor/docs/en/user_guides/quantization_user_guide.md)
+For more details, please refer to [Quantization User Guide](https://mmrazor.readthedocs.io/en/main/user_guides/quantization_user_guide.html)

configs/quantization/ptq/base/ptq_openvino_mbv2_8xb32_in1k_calib32xb32.py

@@ -3,11 +3,11 @@
     '../../deploy_cfgs/mmcls/classification_openvino_dynamic-224x224.py'
 ]
 
-val_dataloader = dict(batch_size=32)
+_base_.val_dataloader.batch_size = 32
 
 test_cfg = dict(
     type='mmrazor.PTQLoop',
-    calibrate_dataloader=val_dataloader,
+    calibrate_dataloader=_base_.val_dataloader,
     calibrate_steps=32,
 )
 

configs/quantization/ptq/base/ptq_openvino_resnet18_8xb32_in1k_calib32xb32.py

@@ -3,11 +3,11 @@
     '../../deploy_cfgs/mmcls/classification_openvino_dynamic-224x224.py'
 ]
 
-val_dataloader = dict(batch_size=32)
+_base_.val_dataloader.batch_size = 32
 
 test_cfg = dict(
     type='mmrazor.PTQLoop',
-    calibrate_dataloader=val_dataloader,
+    calibrate_dataloader=_base_.val_dataloader,
     calibrate_steps=32,
 )
 

configs/quantization/ptq/base/ptq_openvino_resnet50_8xb32_in1k_calib32xb32.py

@@ -3,11 +3,11 @@
     '../../deploy_cfgs/mmcls/classification_openvino_dynamic-224x224.py'
 ]
 
-val_dataloader = dict(batch_size=32)
+_base_.val_dataloader.batch_size = 32
 
 test_cfg = dict(
     type='mmrazor.PTQLoop',
-    calibrate_dataloader=val_dataloader,
+    calibrate_dataloader=_base_.val_dataloader,
     calibrate_steps=32,
 )
 

configs/quantization/ptq/base/ptq_openvino_retina_r50_1x_coco_calib32xb32.py

@@ -3,11 +3,11 @@
     '../../deploy_cfgs/mmdet/detection_openvino_dynamic-800x1344.py'
 ]
 
-val_dataloader = dict(batch_size=32)
+_base_.val_dataloader.batch_size = 32
 
 test_cfg = dict(
     type='mmrazor.PTQLoop',
-    calibrate_dataloader=val_dataloader,
+    calibrate_dataloader=_base_.val_dataloader,
     calibrate_steps=32,
 )
 

configs/quantization/ptq/base/ptq_openvino_yolox_s_8xb8-300e_coco_calib32xb32.py

@@ -3,11 +3,11 @@
     '../../deploy_cfgs/mmdet/detection_openvino_dynamic-800x1344.py'
 ]
 
-val_dataloader = dict(batch_size=32)
+_base_.val_dataloader.batch_size = 32
 
 test_cfg = dict(
     type='mmrazor.PTQLoop',
-    calibrate_dataloader=val_dataloader,
+    calibrate_dataloader=_base_.val_dataloader,
     calibrate_steps=32,
 )
 

configs/quantization/ptq/base/ptq_tensorrt_mbv2_8xb32_in1k_calib32xb32.py

@@ -3,11 +3,11 @@
     '../../deploy_cfgs/mmcls/classification_tensorrt-int8-explicit_dynamic-224x224.py'  # noqa: E501
 ]
 
-val_dataloader = dict(batch_size=32)
+_base_.val_dataloader.batch_size = 32
 
 test_cfg = dict(
     type='mmrazor.PTQLoop',
-    calibrate_dataloader=val_dataloader,
+    calibrate_dataloader=_base_.val_dataloader,
     calibrate_steps=32,
 )