Update get_started.md(master) (#1950)

* update generate_build_config to support cxx11abi tag * test prebuild ci * update docs/zh_cn/get_started.md * update docs/en/get_started.md * fix prebuild ci * update prebuilt_package_windows.md * update prebuild ci deps * try to fix prebuild ci * fix prebuild ci * fix prebuild ci * remove trigger [no ci] * fix name [no ci] * fix typos * fix script
open-mmlab · Apr 4, 2023 · af16b9a · af16b9a
1 parent 1411ed3
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diff --git a/.github/workflows/prebuild.yml b/.github/workflows/prebuild.yml
@@ -29,6 +29,7 @@ jobs:
           export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
           echo $MMDEPLOY_VERSION
           echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
       - name: Build MMDeploy
         run: |
           source activate mmdeploy-3.6
@@ -51,17 +52,55 @@ jobs:
           cd pack
           python ../tools/package_tools/generate_build_config.py --backend 'ort;trt' \
             --system linux --output config.yml --device cuda --build-sdk --build-sdk-monolithic \
-            --build-sdk-python --sdk-dynamic-net
+            --build-sdk-python --sdk-dynamic-net --onnxruntime-dir=$ONNXRUNTIME_GPU_DIR
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Move artifact
+        run: |
+          mkdir -p /__w/mmdeploy/prebuild/$OUTPUT_DIR
+          cp -r pack/* /__w/mmdeploy/prebuild/$OUTPUT_DIR
+
+  linux_build_cxx11abi:
+    runs-on: [self-hosted, linux-3090]
+    container:
+      image: openmmlab/mmdeploy:build-ubuntu16.04-cuda11.3
+      options: "--gpus=all --ipc=host"
+      volumes:
+        - /data2/actions-runner/prebuild:/__w/mmdeploy/prebuild
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+        with:
+          submodules: recursive
+      - name: Get mmdeploy version
+        run: |
+          export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
+          echo $MMDEPLOY_VERSION
+          echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
+      - name: Build sdk cpu backend
+        run: |
+          mkdir pack; cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort' \
+            --system linux --output config.yml --device cpu --build-sdk --build-sdk-monolithic \
+            --sdk-dynamic-net --cxx11abi
+          python ../tools/package_tools/mmdeploy_builder.py --config config.yml
+      - name: Build sdk cuda backend
+        run: |
+          cd pack
+          python ../tools/package_tools/generate_build_config.py --backend 'ort;trt' \
+            --system linux --output config.yml --device cuda --build-sdk --build-sdk-monolithic \
+            --sdk-dynamic-net --cxx11abi --onnxruntime-dir=$ONNXRUNTIME_GPU_DIR --cudnn-dir /usr
           python ../tools/package_tools/mmdeploy_builder.py --config config.yml
       - name: Move artifact
         run: |
-          mkdir -p /__w/mmdeploy/prebuild/$MMDEPLOY_VERSION
-          rm -rf /__w/mmdeploy/prebuild/$MMDEPLOY_VERSION/*
-          mv pack/* /__w/mmdeploy/prebuild/$MMDEPLOY_VERSION
+          mkdir -p /__w/mmdeploy/prebuild/$OUTPUT_DIR
+          cp -r pack/* /__w/mmdeploy/prebuild/$OUTPUT_DIR
 
   linux_test:
     runs-on: [self-hosted, linux-3090]
-    needs: linux_build
+    needs:
+      - linux_build
+      - linux_build_cxx11abi
     container:
       image: openmmlab/mmdeploy:ubuntu20.04-cuda11.3
       options: "--gpus=all --ipc=host"
@@ -76,13 +115,14 @@ jobs:
           export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
           echo $MMDEPLOY_VERSION
           echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
       - name: Test python
         run: |
-          cd /__w/mmdeploy/prebuild/$MMDEPLOY_VERSION
+          cd /__w/mmdeploy/prebuild/$OUTPUT_DIR
           bash $GITHUB_WORKSPACE/tools/package_tools/test/test_sdk_python.sh
       - name: Test c/cpp
         run: |
-          cd /__w/mmdeploy/prebuild/$MMDEPLOY_VERSION
+          cd /__w/mmdeploy/prebuild/$OUTPUT_DIR
           bash $GITHUB_WORKSPACE/tools/package_tools/test/test_sdk.sh
 
   linux_upload:
@@ -100,20 +140,21 @@ jobs:
           export MMDEPLOY_VERSION=$(python3 -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
           echo $MMDEPLOY_VERSION
           echo "MMDEPLOY_VERSION=$MMDEPLOY_VERSION"  >> $GITHUB_ENV
+          echo "OUTPUT_DIR=$MMDEPLOY_VERSION-$GITHUB_RUN_ID" >> $GITHUB_ENV
       - name: Upload mmdeploy
         run: |
-          cd $PREBUILD_DIR/$MMDEPLOY_VERSION/mmdeploy
+          cd $PREBUILD_DIR/$OUTPUT_DIR/mmdeploy
           pip install twine
           # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
           twine upload * -u __token__ -p ${{ secrets.pypi_password }}
       - name: Upload mmdeploy_runtime
         run: |
-          cd $PREBUILD_DIR/$MMDEPLOY_VERSION/mmdeploy_runtime
+          cd $PREBUILD_DIR/$OUTPUT_DIR/mmdeploy_runtime
           # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
           twine upload * -u __token__ -p ${{ secrets.pypi_password }}
       - name: Zip mmdeploy sdk
         run: |
-          cd $PREBUILD_DIR/$MMDEPLOY_VERSION/sdk
+          cd $PREBUILD_DIR/$OUTPUT_DIR/sdk
           for folder in *
           do
             tar czf $folder.tar.gz $folder
@@ -122,7 +163,7 @@ jobs:
         uses: softprops/action-gh-release@v1
         with:
           files: |
-              $PREBUILD_DIR/$MMDEPLOY_VERSION/sdk/*.tar.gz
+              $PREBUILD_DIR/$OUTPUT_DIR/sdk/*.tar.gz
 
 
   windows_build:
@@ -138,6 +179,7 @@ jobs:
           $env:MMDEPLOY_VERSION=(python -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
           echo $env:MMDEPLOY_VERSION
           echo "MMDEPLOY_VERSION=$env:MMDEPLOY_VERSION"  >> $env:GITHUB_ENV
+          echo "OUTPUT_DIR=$env:MMDEPLOY_VERSION-$env:GITHUB_RUN_ID" >> $env:GITHUB_ENV
       - name: Build MMDeploy
         run: |
           . D:\DEPS\cienv\prebuild_gpu_env.ps1
@@ -166,9 +208,8 @@ jobs:
           python ../tools/package_tools/mmdeploy_builder.py --config config.yml
       - name: Move artifact
         run: |
-          New-Item "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION" -ItemType Directory -Force
-          Remove-Item "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION/*" -Force -Recurse
-          Move-Item pack/* "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION"
+          New-Item "D:/DEPS/ciartifact/$env:OUTPUT_DIR" -ItemType Directory -Force
+          Move-Item pack/* "D:/DEPS/ciartifact/$env:OUTPUT_DIR"
 
   windows_test:
     runs-on: [self-hosted, win10-3080]
@@ -182,15 +223,16 @@ jobs:
           $env:MMDEPLOY_VERSION=(python -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
           echo $env:MMDEPLOY_VERSION
           echo "MMDEPLOY_VERSION=$env:MMDEPLOY_VERSION"  >> $env:GITHUB_ENV
+          echo "OUTPUT_DIR=$env:MMDEPLOY_VERSION-$env:GITHUB_RUN_ID" >> $env:GITHUB_ENV
       - name: Test python
         run: |
-          cd "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION"
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR"
           . D:\DEPS\cienv\prebuild_cpu_env.ps1
           conda activate ci-test
           & "$env:GITHUB_WORKSPACE/tools/package_tools/test/test_sdk_python.ps1"
       - name: Test c/cpp
         run: |
-          cd "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION"
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR"
           . D:\DEPS\cienv\prebuild_cpu_env.ps1
           & "$env:GITHUB_WORKSPACE/tools/package_tools/test/test_sdk.ps1"
 
@@ -208,21 +250,22 @@ jobs:
           $env:MMDEPLOY_VERSION=(python -c "import sys; sys.path.append('mmdeploy');from version import __version__;print(__version__)")
           echo $env:MMDEPLOY_VERSION
           echo "MMDEPLOY_VERSION=$env:MMDEPLOY_VERSION"  >> $env:GITHUB_ENV
+          echo "OUTPUT_DIR=$env:MMDEPLOY_VERSION-$env:GITHUB_RUN_ID" >> $env:GITHUB_ENV
       - name: Upload mmdeploy
         run: |
-          cd "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION/mmdeploy"
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR/mmdeploy"
           conda activate mmdeploy-3.8
           # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
           twine upload * -u __token__ -p ${{ secrets.pypi_password }}
       - name: Upload mmdeploy_runtime
         run: |
-          cd "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION/mmdeploy_runtime"
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR/mmdeploy_runtime"
           conda activate mmdeploy-3.8
           # twine upload * --repository testpypi -u __token__ -p ${{ secrets.test_pypi_password }}
           twine upload * -u __token__ -p ${{ secrets.pypi_password }}
       - name: Zip mmdeploy sdk
         run: |
-          cd "D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION/sdk"
+          cd "D:/DEPS/ciartifact/$env:OUTPUT_DIR/sdk"
           $folders = $(ls).Name
           foreach ($folder in $folders) {
             Compress-Archive -Path $folder -DestinationPath "$folder.zip"
@@ -231,4 +274,4 @@ jobs:
         uses: softprops/action-gh-release@v1
         with:
           files: |
-              D:/DEPS/ciartifact/$env:MMDEPLOY_VERSION/sdk/*.zip
+              D:/DEPS/ciartifact/$env:OUTPUT_DIR/sdk/*.zip
diff --git a/docs/en/02-how-to-run/prebuilt_package_windows.md b/docs/en/02-how-to-run/prebuilt_package_windows.md
@@ -21,26 +21,27 @@
 
 ______________________________________________________________________
 
-This tutorial takes `mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1.zip` and `mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0.zip` as examples to show how to use the prebuilt packages.
+This tutorial takes `mmdeploy-0.13.0-windows-amd64.zip` and `mmdeploy-0.13.0-windows-amd64-cuda11.3.zip` as examples to show how to use the prebuilt packages. The former supports onnxruntime cpu inference, the latter supports onnxruntime-gpu and tensorrt inference.
 
 The directory structure of the prebuilt package is as follows, where the `dist` folder is about model converter, and the `sdk` folder is related to model inference.
 
 ```
 .
-|-- dist
-`-- sdk
-    |-- bin
-    |-- example
-    |-- include
-    |-- lib
-    `-- python
+├── build_sdk.ps1
+├── example
+├── include
+├── install_opencv.ps1
+├── lib
+├── README.md
+├── set_env.ps1
+└── thirdparty
 ```
 
 ## Prerequisite
 
 In order to use the prebuilt package, you need to install some third-party dependent libraries.
 
-1. Follow the [get_started](../get_started.md) documentation to create a virtual python environment and install pytorch, torchvision and mmcv-full. To use the C interface of the SDK, you need to install [vs2019+](https://visualstudio.microsoft.com/), [OpenCV](https://github.com/opencv/opencv/releases).
+1. Follow the [get_started](../get_started.md) documentation to create a virtual python environment and install pytorch, torchvision and mmcv. To use the C interface of the SDK, you need to install [vs2019+](https://visualstudio.microsoft.com/), [OpenCV](https://github.com/opencv/opencv/releases).
 
    :point_right: It is recommended to use `pip` instead of `conda` to install pytorch and torchvision
 
@@ -80,9 +81,8 @@ In order to use `ONNX Runtime` backend, you should also do the following steps.
 5. Install `mmdeploy` (Model Converter) and `mmdeploy_runtime` (SDK Python API).
 
    ```bash
-   # download mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1.zip
-   pip install .\mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1\dist\mmdeploy-0.13.0-py38-none-win_amd64.whl
-   pip install .\mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1\sdk\python\mmdeploy_runtime-0.13.0-cp38-none-win_amd64.whl
+   pip install mmdeploy==0.13.0
+   pip install mmdeploy-runtime==0.13.0
    ```
 
    :point_right: If you have installed it before, please uninstall it first.
@@ -100,16 +100,17 @@ In order to use `ONNX Runtime` backend, you should also do the following steps.
    ![sys-path](https://user-images.githubusercontent.com/16019484/181463801-1d7814a8-b256-46e9-86f2-c08de0bc150b.png)
    :exclamation: Restart powershell to make the environment variables setting take effect. You can check whether the settings are in effect by `echo $env:PATH`.
 
+8. Download SDK C/cpp Library mmdeploy-0.13.0-windows-amd64.zip
+
 ### TensorRT
 
 In order to use `TensorRT` backend, you should also do the following steps.
 
 5. Install `mmdeploy` (Model Converter) and `mmdeploy_runtime` (SDK Python API).
 
    ```bash
-   # download mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0.zip
-   pip install .\mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0\dist\mmdeploy-0.13.0-py38-none-win_amd64.whl
-   pip install .\mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0\sdk\python\mmdeploy_runtime-0.13.0-cp38-none-win_amd64.whl
+   pip install mmdeploy==0.13.0
+   pip install mmdeploy-runtime-gpu==0.13.0
    ```
 
    :point_right: If you have installed it before, please uninstall it first.
@@ -128,6 +129,8 @@ In order to use `TensorRT` backend, you should also do the following steps.
 
 7. Install pycuda by `pip install pycuda`
 
+8. Download SDK C/cpp Library mmdeploy-0.13.0-windows-amd64-cuda11.3.zip
+
 ## Model Convert
 
 ### ONNX Runtime Example
@@ -138,7 +141,7 @@ After preparation work, the structure of the current working directory should be
 
 ```
 ..
-|-- mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1
+|-- mmdeploy-0.13.0-windows-amd64
 |-- mmclassification
 |-- mmdeploy
 `-- resnet18_8xb32_in1k_20210831-fbbb1da6.pth
@@ -186,7 +189,7 @@ After installation of mmdeploy-tensorrt prebuilt package, the structure of the c
 
 ```
 ..
-|-- mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0
+|-- mmdeploy-0.13.0-windows-amd64-cuda11.3
 |-- mmclassification
 |-- mmdeploy
 `-- resnet18_8xb32_in1k_20210831-fbbb1da6.pth
@@ -299,7 +302,7 @@ python .\mmdeploy\demo\python\image_classification.py cpu .\work_dir\onnx\resnet
 
 #### TensorRT
 
-```
+```bash
  python .\mmdeploy\demo\python\image_classification.py cuda .\work_dir\trt\resnet\ .\mmclassification\demo\demo.JPEG
 ```
 
@@ -309,71 +312,39 @@ The following describes how to use the SDK's C API for inference
 
 #### ONNXRuntime
 
-1. Build examples
-
-   Under `mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1\sdk\example` directory
-
-   ```
-   // Path should be modified according to the actual location
-   mkdir build
-   cd build
-   cmake ..\cpp -A x64 -T v142 `
-     -DOpenCV_DIR=C:\Deps\opencv\build\x64\vc15\lib `
-     -DMMDeploy_DIR=C:\workspace\mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1\sdk\lib\cmake\MMDeploy `
-     -DONNXRUNTIME_DIR=C:\Deps\onnxruntime\onnxruntime-win-gpu-x64-1.8.1
-
-   cmake --build . --config Release
-   ```
+1. Add environment variables
 
-2. Add environment variables or copy the runtime libraries to the same level directory of exe
+   Refer to the README.md in sdk folder
 
-   :point_right: The purpose is to make the exe find the relevant dll
+2. Build examples
 
-   If choose to add environment variables, add the runtime libraries path of `mmdeploy` (`mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1\sdk\bin`) to the `PATH`.
-
-   If choose to copy the dynamic libraries, copy the dll in the bin directory to the same level directory of the just compiled exe (build/Release).
+   Refer to the README.md in sdk folder
 
 3. Inference：
 
    It is recommended to use `CMD` here.
 
-   Under `mmdeploy-0.13.0-windows-amd64-onnxruntime1.8.1\\sdk\\example\\build\\Release` directory：
+   Under `mmdeploy-0.13.0-windows-amd64\\example\\cpp\\build\\Release` directory：
 
    ```
    .\image_classification.exe cpu C:\workspace\work_dir\onnx\resnet\ C:\workspace\mmclassification\demo\demo.JPEG
    ```
 
 #### TensorRT
 
-1. Build examples
-
-   Under `mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0\\sdk\\example` directory
-
-   ```
-   // Path should be modified according to the actual location
-   mkdir build
-   cd build
-   cmake ..\cpp -A x64 -T v142 `
-     -DOpenCV_DIR=C:\Deps\opencv\build\x64\vc15\lib `
-     -DMMDeploy_DIR=C:\workspace\mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8 2.3.0\sdk\lib\cmake\MMDeploy `
-     -DTENSORRT_DIR=C:\Deps\tensorrt\TensorRT-8.2.3.0 `
-     -DCUDNN_DIR=C:\Deps\cudnn\8.2.1
-   cmake --build . --config Release
-   ```
-
-2. Add environment variables or copy the runtime libraries to the same level directory of exe
+1. Add environment variables
 
-   :point_right: The purpose is to make the exe find the relevant dll
+   Refer to the README.md in sdk folder
 
-   If choose to add environment variables, add the runtime libraries path of `mmdeploy` (`mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0\sdk\bin`) to the `PATH`.
+2. Build examples
 
-   If choose to copy the dynamic libraries, copy the dll in the bin directory to the same level directory of the just compiled exe (build/Release).
+   Refer to the README.md in sdk folder
 
 3. Inference
 
    It is recommended to use `CMD` here.
 
-   Under `mmdeploy-0.13.0-windows-amd64-cuda11.1-tensorrt8.2.3.0\\sdk\\example\\build\\Release` directory
+   Under `mmdeploy-0.13.0-windows-amd64-cuda11.3\\example\\cpp\\build\\Release` directory
 
    ```
    .\image_classification.exe cuda C:\workspace\work_dir\trt\resnet C:\workspace\mmclassification\demo\demo.JPEG