format md files with new precommit config

open-mmlab · Jun 16, 2022 · 9acd0ea · 9acd0ea
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diff --git a/.github/CODE_OF_CONDUCT.md b/.github/CODE_OF_CONDUCT.md
@@ -14,22 +14,22 @@ appearance, race, religion, or sexual identity and orientation.
 Examples of behavior that contributes to creating a positive environment
 include:
 
-* Using welcoming and inclusive language
-* Being respectful of differing viewpoints and experiences
-* Gracefully accepting constructive criticism
-* Focusing on what is best for the community
-* Showing empathy towards other community members
+- Using welcoming and inclusive language
+- Being respectful of differing viewpoints and experiences
+- Gracefully accepting constructive criticism
+- Focusing on what is best for the community
+- Showing empathy towards other community members
 
 Examples of unacceptable behavior by participants include:
 
-* The use of sexualized language or imagery and unwelcome sexual attention or
- advances
-* Trolling, insulting/derogatory comments, and personal or political attacks
-* Public or private harassment
-* Publishing others' private information, such as a physical or electronic
- address, without explicit permission
-* Other conduct which could reasonably be considered inappropriate in a
- professional setting
+- The use of sexualized language or imagery and unwelcome sexual attention or
+  advances
+- Trolling, insulting/derogatory comments, and personal or political attacks
+- Public or private harassment
+- Publishing others' private information, such as a physical or electronic
+  address, without explicit permission
+- Other conduct which could reasonably be considered inappropriate in a
+  professional setting
 
 ## Our Responsibilities
 
@@ -70,7 +70,7 @@ members of the project's leadership.
 This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
 available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
 
-[homepage]: https://www.contributor-covenant.org
-
 For answers to common questions about this code of conduct, see
 https://www.contributor-covenant.org/faq
+
+[homepage]: https://www.contributor-covenant.org
diff --git a/.github/ISSUE_TEMPLATE/bug-report.md b/.github/ISSUE_TEMPLATE/bug-report.md
@@ -4,7 +4,6 @@ about: Create a report to help us improve
 title: ''
 labels: ''
 assignees: ''
-
 ---
 
 Thanks for your bug report. We appreciate it a lot.
@@ -29,13 +28,12 @@ A placeholder for the command.
 
 2. Did you make any modifications on the code or config? Did you understand what you have modified?
 
-
 **Environment**
 
 1. Please run `python tools/check_env.py` 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**
 

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 [....].
+Ex1. It is inconvenient when \[....\].
 
 **Related resources**
 

diff --git a/.github/ISSUE_TEMPLATE/general_questions.md b/.github/ISSUE_TEMPLATE/general_questions.md
@@ -4,5 +4,4 @@ about: Ask general questions to get help
 title: ''
 labels: ''
 assignees: ''
-
 ---
diff --git a/README.md b/README.md
@@ -26,7 +26,6 @@
 [![issue resolution](https://img.shields.io/github/issues-closed-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)
 [![open issues](https://img.shields.io/github/issues-raw/open-mmlab/mmdeploy)](https://github.com/open-mmlab/mmdeploy/issues)
 
-
 English | [简体中文](README_zh-CN.md)
 
 ## Introduction
@@ -37,30 +36,28 @@ MMDeploy is an open-source deep learning model deployment toolset. It is a part
   <img src="resources/introduction.png">
 </div>
 
-
 ## Main features
 
 ### Fully support OpenMMLab models
 
 The currently supported codebases and models are as follows, and more will be included in the future
-  - [mmcls](docs/en/04-supported-codebases/mmcls.md)
-  - [mmdet](docs/en/04-supported-codebases/mmdet.md)
-  - [mmseg](docs/en/04-supported-codebases/mmseg.md)
-  - [mmedit](docs/en/04-supported-codebases/mmedit.md)
-  - [mmocr](docs/en/04-supported-codebases/mmocr.md)
-  - [mmpose](docs/en/04-supported-codebases/mmpose.md)
-  - [mmdet3d](docs/en/04-supported-codebases/mmdet3d.md)
-  - [mmrotate](docs/en/04-supported-codebases/mmrotate.md)
+
+- [mmcls](docs/en/04-supported-codebases/mmcls.md)
+- [mmdet](docs/en/04-supported-codebases/mmdet.md)
+- [mmseg](docs/en/04-supported-codebases/mmseg.md)
+- [mmedit](docs/en/04-supported-codebases/mmedit.md)
+- [mmocr](docs/en/04-supported-codebases/mmocr.md)
+- [mmpose](docs/en/04-supported-codebases/mmpose.md)
+- [mmdet3d](docs/en/04-supported-codebases/mmdet3d.md)
+- [mmrotate](docs/en/04-supported-codebases/mmrotate.md)
 
 ### Multiple inference backends are available
 
 Models can be exported and run in the following backends, and more will be compatible
 
 | ONNX Runtime | TensorRT | ppl.nn | ncnn | OpenVINO | LibTorch | more                                           |
 | ------------ | -------- | ------ | ---- | -------- | -------- | ---------------------------------------------- |
-| ✔️            | ✔️        | ✔️      | ✔️    | ✔️        | ✔️        | [benchmark](docs/en/03-benchmark/benchmark.md) |
-
-
+| ✔️           | ✔️       | ✔️     | ✔️   | ✔️       | ✔️       | [benchmark](docs/en/03-benchmark/benchmark.md) |
 
 ### Efficient and scalable C/C++ SDK Framework
 
@@ -70,22 +67,22 @@ All kinds of modules in the SDK can be extended, such as `Transform` for image p
 
 Please read [getting_started.md](docs/en/get_started.md) for the basic usage of MMDeploy. We also provide tutoials about:
 
-* [Build](docs/en/01-how-to-build/build_from_source.md)
-  * [Build from Docker](docs/en/01-how-to-build/build_from_docker.md)
-  * [Build for Linux](docs/en/01-how-to-build/linux-x86_64.md)
-  * [Build for Win10](docs/en/01-how-to-build/windows.md)
-  * [Build for Android](docs/en/01-how-to-build/android.md)
-  * [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
-* User Guide
-  * [How to convert model](docs/en/02-how-to-run/convert_model.md)
-  * [How to write config](docs/en/02-how-to-run/write_config.md)
-  * [How to evaluate deployed models](docs/en/02-how-to-run/how_to_evaluate_a_model.md)
-  * [How to measure performance of deployed models](docs/en/02-how-to-run/how_to_measure_performance_of_models.md)
-* Developer Guide
-  * [How to support new models](docs/en/06-developer-guide/support_new_model.md)
-  * [How to support new backends](docs/en/06-developer-guide/support_new_backend.md)
-* [FAQ](docs/en/faq.md)
-* [Contributing](.github/CONTRIBUTING.md)
+- [Build](docs/en/01-how-to-build/build_from_source.md)
+  - [Build from Docker](docs/en/01-how-to-build/build_from_docker.md)
+  - [Build for Linux](docs/en/01-how-to-build/linux-x86_64.md)
+  - [Build for Win10](docs/en/01-how-to-build/windows.md)
+  - [Build for Android](docs/en/01-how-to-build/android.md)
+  - [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
+- User Guide
+  - [How to convert model](docs/en/02-how-to-run/convert_model.md)
+  - [How to write config](docs/en/02-how-to-run/write_config.md)
+  - [How to evaluate deployed models](docs/en/02-how-to-run/how_to_evaluate_a_model.md)
+  - [How to measure performance of deployed models](docs/en/02-how-to-run/how_to_measure_performance_of_models.md)
+- Developer Guide
+  - [How to support new models](docs/en/06-developer-guide/support_new_model.md)
+  - [How to support new backends](docs/en/06-developer-guide/support_new_backend.md)
+- [FAQ](docs/en/faq.md)
+- [Contributing](.github/CONTRIBUTING.md)
 
 ## Benchmark and Model zoo
 
@@ -98,6 +95,7 @@ We appreciate all contributions to MMDeploy. Please refer to [CONTRIBUTING.md](.
 ## Acknowledgement
 
 We would like to sincerely thank the following teams for their contributions to [MMDeploy](https://github.com/open-mmlab/mmdeploy):
+
 - [OpenPPL](https://github.com/openppl-public)
 - [OpenVINO](https://github.com/openvinotoolkit/openvino)
 - [ncnn](https://github.com/Tencent/ncnn)

diff --git a/README_zh-CN.md b/README_zh-CN.md
@@ -41,6 +41,7 @@ MMDeploy 是 [OpenMMLab](https://openmmlab.com/) 模型部署工具箱，**为
 ## 特性简介
 
 ### 支持超多 OpenMMLab 算法库
+
 - [mmcls](docs/en/04-supported-codebases/mmcls.md)
 - [mmdet](docs/en/04-supported-codebases/mmdet.md)
 - [mmseg](docs/en/04-supported-codebases/mmseg.md)
@@ -51,38 +52,41 @@ MMDeploy 是 [OpenMMLab](https://openmmlab.com/) 模型部署工具箱，**为
 - [mmrotate](docs/en/04-supported-codebases/mmrotate.md)
 
 ### 支持多种推理后端
+
 | ONNX Runtime | TensorRT | ppl.nn | ncnn | OpenVINO | more                                              |
 | ------------ | -------- | ------ | ---- | -------- | ------------------------------------------------- |
-| ✔️            | ✔️        | ✔️      | ✔️    | ✔️        | [benchmark](docs/zh_cn/03-benchmark/benchmark.md) |
+| ✔️           | ✔️       | ✔️     | ✔️   | ✔️       | [benchmark](docs/zh_cn/03-benchmark/benchmark.md) |
 
 ### SDK 可高度定制化
+
 - Transform 数据预处理
 - Net 推理
 - Module 后处理
 
 ## [快速上手](docs/zh_cn/get_started.md)
 
-* [编译](docs/zh_cn/01-how-to-build/build_from_source.md)
-  * [Build from Docker](docs/zh_cn/01-how-to-build/build_from_docker.md)
-  * [Build for Linux](docs/zh_cn/01-how-to-build/linux-x86_64.md)
-  * [Build for Win10](docs/zh_cn/01-how-to-build/windows.md)
-  * [Build for Android](docs/zh_cn/01-how-to-build/android.md)
-  * [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
-* 使用
-  * [把模型转换到推理 Backend](docs/zh_cn/02-how-to-run/convert_model.md)
-  * [配置转换参数](docs/zh_cn/02-how-to-run/write_config.md)
-  * [量化](docs/zh_cn/02-how-to-run/quantize_model.md)
-  * [测试转换完成的模型](docs/zh_cn/02-how-to-run/profile_model.md)
-* 开发指南
-  * [支持新模型](docs/zh_cn/04-developer-guide/support_new_model.md)
-  * [增加推理 Backend](docs/zh_cn/04-developer-guide/support_new_backend.md)
-  * [回归测试](docs/zh_cn/04-developer-guide/do_regression_test.md)
-* [FAQ](docs/zh_cn/faq.md)
-* [贡献者手册](.github/CONTRIBUTING.md)
+- [编译](docs/zh_cn/01-how-to-build/build_from_source.md)
+  - [Build from Docker](docs/zh_cn/01-how-to-build/build_from_docker.md)
+  - [Build for Linux](docs/zh_cn/01-how-to-build/linux-x86_64.md)
+  - [Build for Win10](docs/zh_cn/01-how-to-build/windows.md)
+  - [Build for Android](docs/zh_cn/01-how-to-build/android.md)
+  - [Build for Jetson](docs/en/01-how-to-build/jetsons.md)
+- 使用
+  - [把模型转换到推理 Backend](docs/zh_cn/02-how-to-run/convert_model.md)
+  - [配置转换参数](docs/zh_cn/02-how-to-run/write_config.md)
+  - [量化](docs/zh_cn/02-how-to-run/quantize_model.md)
+  - [测试转换完成的模型](docs/zh_cn/02-how-to-run/profile_model.md)
+- 开发指南
+  - [支持新模型](docs/zh_cn/04-developer-guide/support_new_model.md)
+  - [增加推理 Backend](docs/zh_cn/04-developer-guide/support_new_backend.md)
+  - [回归测试](docs/zh_cn/04-developer-guide/do_regression_test.md)
+- [FAQ](docs/zh_cn/faq.md)
+- [贡献者手册](.github/CONTRIBUTING.md)
 
 ## 新人解说
-  * [01 术语解释、加载第一个模型](docs/zh_cn/05-tutorial/01_introduction_to_model_deployment.md)
-  * [02 转成 onnx](docs/zh_cn/05-tutorial/02_challenges.md)
+
+- [01 术语解释、加载第一个模型](docs/zh_cn/05-tutorial/01_introduction_to_model_deployment.md)
+- [02 转成 onnx](docs/zh_cn/05-tutorial/02_challenges.md)
 
 ## 基准与模型库
 
@@ -93,6 +97,7 @@ MMDeploy 是 [OpenMMLab](https://openmmlab.com/) 模型部署工具箱，**为
 我们感谢所有的贡献者为改进和提升 MMDeploy 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。
 
 ## 致谢
+
 - [OpenPPL](https://github.com/openppl-public/ppl.nn): 高性能推理框架底层库
 - [OpenVINO](https://github.com/openvinotoolkit/openvino): AI 推理优化和部署框架
 - [ncnn](https://github.com/tencent/ncnn): 为手机端极致优化的高性能神经网络前向计算框架

diff --git a/csrc/mmdeploy/apis/csharp/README.md b/csrc/mmdeploy/apis/csharp/README.md
@@ -6,18 +6,18 @@ We provide nuget package on our [release page](https://github.com/open-mmlab/mmd
 
 To use the nuget package, you also need to download the backend dependencies. For example, if you want to use the tensorrt backend, you should install cudatoolkit, cudnn and tensorrt, remember to add the dll directories to your system path. The version of backend dependencies that our prebuit nuget package used will be offered in release note.
 
-| backend  | dependencies |
-| ------------- | ------------- |
-| tensorrt  | cudatoolkit, cudnn, tensorrt   |
-| onnxruntime | onnxruntime / onnxruntime-gpu  |
+| backend     | dependencies                  |
+| ----------- | ----------------------------- |
+| tensorrt    | cudatoolkit, cudnn, tensorrt  |
+| onnxruntime | onnxruntime / onnxruntime-gpu |
 
 ## From Source
 
 ### Requirements
 
-* Environment required by building sdk
-* .NET Framework 4.8 / .NET core 3.1
-* Visual Studio 2019+
+- Environment required by building sdk
+- .NET Framework 4.8 / .NET core 3.1
+- Visual Studio 2019+
 
 ### Installation
 
@@ -34,6 +34,7 @@ There are two methods to build the nuget package.
 (*option 1*) Use the command.
 
 If your environment is well prepared, you can just go to the `csrc\apis\csharp` folder, open a terminal and type the following command, the nupkg will be built in `csrc\apis\csharp\MMDeploy\bin\Release\MMDeploy.1.0.0.nupkg`.
+
 ```shell
 dotnet build --configuration Release -p:Version=1.0.0
 ```

diff --git a/demo/README.md b/demo/README.md
@@ -1,16 +1,21 @@
 ## Demo
+
 We provide a demo showing what our mmdeploy can do for general model deployment.
 
 In `demo_rewrite.py`, a resnet18 model from `torchvision` is rewritten through mmdeploy tool. In our rewritten model, the forward function of resnet gets modified to only down sample the original input to 4x. Original onnx model of resnet18 and its rewritten are visualized through [netron](https://netron.app/).
 
 ### Prerequisite
+
 Before we run `demp_rewrite.py`, we need to install `pyppeteer` through:
+
 ```
 pip install pyppeteer
 ```
 
 ### Demo results
+
 The original resnet18 model and its modified one are visualized as follows. The left model is the original resnet18 while the right model is exported after rewritten.
-Original resnet18           |  Rewritten model
-:-------------------------:|:-------------------------:
-![](resources/original.png)  |  ![](resources/rewritten.png)
+
+|      Original resnet18      |       Rewritten model        |
+| :-------------------------: | :--------------------------: |
+| ![](resources/original.png) | ![](resources/rewritten.png) |
diff --git a/demo/csharp/README.md b/demo/csharp/README.md
@@ -10,11 +10,10 @@ If you built csharp api from source and didn't build static lib, you should add
 
 And don't forget to install backend dependencies. Take tensorrt backend as example, you have to install cudatoolkit, cudnn and tensorrt. The version of backend dependencies that our prebuit nuget package used will be offered in release note.
 
-| backend  | dependencies |
-| ------------- | ------------- |
-| tensorrt  | cudatoolkit, cudnn, tensorrt   |
-| onnxruntime | onnxruntime / onnxruntime-gpu  |
-
+| backend     | dependencies                  |
+| ----------- | ----------------------------- |
+| tensorrt    | cudatoolkit, cudnn, tensorrt  |
+| onnxruntime | onnxruntime / onnxruntime-gpu |
 
 **step 2.** Open Demo.sln and build solution.
 
@@ -23,7 +22,8 @@ And don't forget to install backend dependencies. Take tensorrt backend as examp
 You can either convert your model according to this [tutorial](../../docs/en/tutorials/how_to_convert_model.md) or download the test models from [OneDrive](https://1drv.ms/u/s!Aqis6w3rjKXSh2dXZ5OqbZIZSu9P?e=nefSdY) or [BaiduYun](https://pan.baidu.com/s/1VJkLo2oqHos6ZWDT7xamFg?pwd=STAR). The web drive contains onnx and tensorrt models and the test models are converted under environment of cuda11.1 + cudnn8.2.1 + tensorrt 8.2.3.0 + GTX2070s.
 
 *Note*:
-+ a) If you want to use the tensorrt model from the link, make sure your environment and your gpu architecture is same with above.
-+ b) When you use the downloaded onnx model, you have to edit `deploy.json`, edit `end2end.engine` to `end2end.onnx` and `tensorrt` to `onnxruntime`.
+
+- a) If you want to use the tensorrt model from the link, make sure your environment and your gpu architecture is same with above.
+- b) When you use the downloaded onnx model, you have to edit `deploy.json`, edit `end2end.engine` to `end2end.onnx` and `tensorrt` to `onnxruntime`.
 
 **step 4.** Set one project as startup project and run it.