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mmdeploy/tools/package_tools
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Chen Xin a14177c0eb
[Feature]: Add github prebuild workflow after new release. (#1852) 
* add prebuild dockerfile

* add prebuild test workflw

* update

* update

* rm other workflow for test

* Update docker image

* add win1o prebuild

* add test prebuild

* add windows scripts in prebuilt package

* add linux scripts in prebuilt package

* generate_build_config.py

* fix cudnn search

* fix env

* fix script

* fix rpath

* fix cwd

* fix windows

* fix lint

* windows prebuild ci

* linux prebuild ci

* fix

* update trigger

* Revert "rm other workflow for test"

This reverts commit 0a0387275014efab71046d33a0e52904672b4012.

* update sdk build readme

* update prebuild

* fix dll deps for python >= 3.8 on windows

* fix ci

* test prebuild

* update test script to avoid modify upload folder

* add onnxruntime.dll to mmdeploy_python

* update prebuild workflow

* update prebuild

* Update loader.cpp.in

* remove exists prebuild files

* fix opencv env

* update cmake options for mmdeploy python build

* remove test code

* fix lint

---------

Co-authored-by: RunningLeon <mnsheng@yeah.net>
Co-authored-by: RunningLeon <maningsheng@sensetime.com>
2023-03-23 17:00:19 +08:00
..
configs
[Feature]: Add github prebuild workflow after new release. (#1852)
2023-03-23 17:00:19 +08:00
packaging
[Feature]: Add github prebuild workflow after new release. (#1852)
2023-03-23 17:00:19 +08:00
scripts
[Feature]: Add github prebuild workflow after new release. (#1852)
2023-03-23 17:00:19 +08:00
test
[Feature]: Add github prebuild workflow after new release. (#1852)
2023-03-23 17:00:19 +08:00
generate_build_config.py
[Feature]: Add github prebuild workflow after new release. (#1852)
2023-03-23 17:00:19 +08:00
mmdeploy_builder.py
[Feature]: Add github prebuild workflow after new release. (#1852)
2023-03-23 17:00:19 +08:00
README.md
[Enhancement] build sdk python api in standard-alone manner (#810)
2022-08-02 10:23:48 +08:00

README.md

Precompiled package

This document is going to describe the way to build MMDeploy package.

Prerequisites

  • Download and install Miniconda from the official website.

  • Create conda environments for python 3.6, 3.7, 3.8 and 3.9, respectively.

    for PYTHON_VERSION in 3.6 3.7 3.8 3.9
do
  conda create --name mmdeploy-$PYTHON_VERSION python=$PYTHON_VERSION -y
done

  • Prepare MMDeploy dependencies

    Please follow the build-on-Linux guide or build-on-Windows guide to install dependencies of MMDeploy, including PyTorch, MMCV, OpenCV, ppl.cv, ONNX Runtime and TensorRT.

    Make sure the environment variables pplcv_DIR, ONNXRUNTIME_DIR, TENSORRT_DIR, CUDNN_DIR and CUDA_TOOLKIT_ROOT_DIR are exported.

Run precompiled command

  • On Linux platform,

    conda activate mmdeploy-3.6
pip install pyyaml
cd the/root/path/of/mmdeploy
python tools/package_tools/mmdeploy_builder.py tools/package_tools/configs/linux_x64.yaml .

    You will get the precompiled packages mmdeploy-{version}-linux-x86_64-cuda11.1-tensorrt8.2.3.0 and mmdeploy-{version}-linux-x86_64-onnxruntime1.8.1 in the current directory if everything's going well.

  • On Windows platform, open Anaconda Powershell Prompt from the start menu and execute:

    conda activate mmdeploy-3.6
pip install pyyaml
cd the/root/path/of/MMDeploy
python tools/package_tools/mmdeploy_builder.py tools/package_tools/configs/windows_x64.yaml .

    When the build procedure finishes successfully, you will find mmdeploy-{version}-windows-amd64-cuda11.1-tensorrt8.2.3.0 and mmdeploy-{version}-windows-amd64-onnxruntime1.8.1 precompiled packages in the current directory.