server_develop/src_code/install_torchserve.sh

#!/bin/sh
{
  git clone https://github.com/pytorch/serve.git
  # if git clone takes to long time, you should change etc/hosts refer to https://blog.csdn.net/qq_47911262/article/details/121918174:
} || {
  echo "git clone https://github.com/pytorch/serve.git failed 🤢🤢🤢"
}
echo "git clone https://github.com/pytorch/serve.git successfully 😊😊😊"
cd serve/docker &&
echo "cd server/docker..."  &&
# -h, --help	Show script help
# -b, --branch_name	Specify a branch name to use. Default: master
# -g, --gpu	Build image with GPU based ubuntu base image
# -bt, --buildtype	Which type of docker image to build. Can be one of : production(default), dev, codebuild
# -t, --tag	Tag name for image. If not specified, script uses torchserve default tag names.
# -cv, --cudaversion	Specify to cuda version to use. Supported values cu92, cu101, cu102, cu111, cu113. Default cu102
# --codebuild	Set if you need AWS CodeBuild(https://aws.amazon.com/cn/codebuild/)
echo "./build_image.sh -g -cv cu111 -t torchserve:cuda11-1.0 -bt production -b master ..." &&
./build_image.sh -g -cv cu111 -t torchserve:1.0 -bt production -b master &&
echo "install torcher_server docker finally ~" &&
pip3 install torchserve -i https://pypi.tuna.tsinghua.edu.cn/simple &&
pip3 install torch-model-archiver -i https://pypi.tuna.tsinghua.edu.cn/simple &&
pip3 install torch-workflow-archiver -i https://pypi.tuna.tsinghua.edu.cn/simple &&
pip3 install chardet -i https://pypi.tuna.tsinghua.edu.cn/simple