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https://github.com/tencentmusic/cube-studio.git
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添加部署推理服务模板
This commit is contained in:
pengluan
parent
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commit
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33
job-template/job/deploy-service/Dockerfile
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33
job-template/job/deploy-service/Dockerfile
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FROM ubuntu:18.04
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# 安装运维工具
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RUN apt-get update && apt install -y --force-yes --no-install-recommends vim apt-transport-https gnupg2 ca-certificates-java rsync jq wget git dnsutils iputils-ping net-tools curl locales zip
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# 安装python
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RUN apt install -y python3.6-dev python3-pip libsasl2-dev libpq-dev \
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&& ln -s /usr/bin/python3 /usr/bin/python \
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&& ln -s /usr/bin/pip3 /usr/bin/pip
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# 安装中文
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RUN apt install -y --force-yes --no-install-recommends locales ttf-wqy-microhei ttf-wqy-zenhei xfonts-wqy && locale-gen zh_CN && locale-gen zh_CN.utf8
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ENV LANG zh_CN.UTF-8
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ENV LC_ALL zh_CN.UTF-8
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ENV LANGUAGE zh_CN.UTF-8
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# 便捷操作
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RUN echo "alias ll='ls -alF'" >> /root/.bashrc && \
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echo "alias la='ls -A'" >> /root/.bashrc && \
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echo "alias vi='vim'" >> /root/.bashrc && \
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/bin/bash -c "source /root/.bashrc"
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RUN pip install kubernetes==12.0.1 pysnooper psutil
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COPY job/deploy-service/* /app/
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#COPY job/pkgs/config/ubuntu-sources.list /etc/apt/sources.list
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#COPY job/pkgs/config/pip.conf /root/.pip/pip.conf
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COPY job/pkgs /app/job/pkgs
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WORKDIR /app
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ENV PYTHONPATH=/app:$PYTHONPATH
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ENTRYPOINT ["python3", "launcher.py"]
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192
job-template/job/deploy-service/README.md
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192
job-template/job/deploy-service/README.md
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# deploy-service 模板
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镜像：ai.tencentmusic.com/tme-public/deploy-service:20211001
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启动参数：
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```bash
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{
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"shell": {
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"--project_name": {
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"type": "str",
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"item_type": "str",
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"label": "部署项目名",
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"require": 1,
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"choice": [],
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"range": "",
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"default": "public",
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"placeholder": "",
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"describe": "部署项目名",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--service_type": {
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"type": "str",
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"item_type": "str",
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"label": "推理服务类型",
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"require": 0,
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"choice": ['service','tfserving','torch-server','onnxruntime','triton-server'],
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"range": "",
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"default": "service",
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"placeholder": "",
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"describe": "推理服务类型",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--label": {
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"type": "str",
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"item_type": "str",
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"label": "推理服务描述",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "demo推理服务",
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"placeholder": "",
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"describe": "推理服务描述",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--model_name": {
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"type": "str",
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"item_type": "str",
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"label": "模型名",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "模型名",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--model_version": {
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"type": "str",
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"item_type": "str",
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"label": "模型版本号",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "v2022.10.01.1",
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"placeholder": "",
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"describe": "模型版本号",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--model_path": {
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"type": "str",
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"item_type": "str",
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"label": "模型地址",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "模型地址",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--images": {
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"type": "str",
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"item_type": "str",
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"label": "推理服务镜像",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "推理服务镜像",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--replicas": {
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"type": "str",
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"item_type": "str",
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"label": "pod副本数",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "1",
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"placeholder": "",
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"describe": "pod副本数",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--working_dir": {
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"type": "str",
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"item_type": "str",
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"label": "推理容器工作目录",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "推理容器工作目录",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--command": {
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"type": "str",
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"item_type": "str",
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"label": "推理容器启动命令",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "推理容器启动命令",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--args": {
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"type": "str",
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"item_type": "str",
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"label": "推理容器启动参数",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "推理容器启动参数",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--env": {
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"type": "text",
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"item_type": "str",
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"label": "推理容器环境变量",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "",
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"placeholder": "",
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"describe": "推理容器环境变量",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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"--ports": {
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"type": "str",
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"item_type": "str",
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"label": "推理容器暴露端口",
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"require": 0,
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"choice": [],
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"range": "",
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"default": "80",
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"placeholder": "",
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"describe": "推理容器暴露端口",
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"editable": 1,
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"condition": "",
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"sub_args": {}
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},
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}
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}
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```
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9
job-template/job/deploy-service/build.sh
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9
job-template/job/deploy-service/build.sh
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#!/bin/bash
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set -ex
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docker build -t ai.tencentmusic.com/tme-public/deploy-service:20211001 -f job/deploy-service/Dockerfile .
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docker push ai.tencentmusic.com/tme-public/deploy-service:20211001
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154
job-template/job/deploy-service/launcher.py
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154
job-template/job/deploy-service/launcher.py
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import os,sys
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base_dir = os.path.split(os.path.realpath(__file__))[0]
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sys.path.append(base_dir)
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import argparse
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import datetime
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import json
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import time
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import uuid
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import os
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import pysnooper
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import os,sys
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import re
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import requests
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import psutil
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import copy
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KFJ_CREATOR = os.getenv('KFJ_CREATOR', 'admin')
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host = 'http://kubeflow-dashboard.infra'
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# host = 'http://127.0.0.1:80'
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# host = 'http://9.135.92.226'
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@pysnooper.snoop()
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def deploy(**kwargs):
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# print(kwargs)
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headers = {
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'Content-Type': 'application/json',
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'Authorization': KFJ_CREATOR
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}
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# 获取项目组
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url = host + "/project_modelview/api/?form_data=" + json.dumps({
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"filters": [
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{
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"col": "name",
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"opr": "eq",
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"value": kwargs['project_name']
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}
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]
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})
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res = requests.get(url, headers=headers)
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exist_project = res.json().get('result', {}).get('data', [])
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if not exist_project:
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print('不存在项目组')
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return
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exist_project = exist_project[0]
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# 查询同名是否存在，创建者是不是指定用户
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url = host+"/inferenceservice_modelview/api/?form_data="+json.dumps({
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"filters":[
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{
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"col": "model_name",
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"opr": "eq",
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"value": kwargs['model_name']
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},
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{
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"col": "model_version",
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"opr": "eq",
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"value": kwargs['model_version']
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}
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]
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})
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# print(url)
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res = requests.get(url,headers=headers)
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# print(res.content)
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if res.status_code==200:
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payload = {
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'model_name': kwargs['model_name'],
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'model_version': kwargs['model_version'],
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'model_path':kwargs['model_path'],
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'label': kwargs['label'],
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'project': exist_project['id'],
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'images': kwargs['images'],
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'working_dir': kwargs['working_dir'],
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'command': kwargs['command'],
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'args': kwargs['args'],
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'env': kwargs['env'],
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'resource_memory': kwargs['resource_memory'],
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'resource_cpu': kwargs['resource_cpu'],
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'resource_gpu': kwargs['resource_gpu'],
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'min_replicas': kwargs['replicas'],
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'max_replicas': kwargs['replicas'],
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'ports': kwargs['ports'],
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'volume_mount': kwargs['volume_mount'],
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'host': kwargs['host'],
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'hpa': kwargs['hpa'],
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'service_type':kwargs['service_type']
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}
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exist_services = res.json().get('result',{}).get('data',[])
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new_service=None
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# 不存在就创建新的服务
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if not exist_services:
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url = host + "/inferenceservice_modelview/api/"
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res = requests.post(url, headers=headers,json=payload)
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if res.status_code==200:
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new_service = res.json().get('result', {})
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# print(res)
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else:
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exist_service=exist_services[0]
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# 更新服务
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url = host + "/inferenceservice_modelview/api/%s"%exist_service['id']
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res = requests.put(url, headers=headers, json=payload)
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if res.status_code==200:
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new_service = res.json().get('result',{})
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# print(res)
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if new_service:
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print(new_service)
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url = host + "/inferenceservice_modelview/deploy/prod/%s"%new_service['id']
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res = requests.post(url,headers=headers)
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if res.status_code==302 or res.status_code==200:
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print('部署成功')
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else:
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print('部署失败')
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if __name__ == "__main__":
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arg_parser = argparse.ArgumentParser("deploy service launcher")
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arg_parser.add_argument('--project_name', type=str, help="所属项目组", default='public')
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arg_parser.add_argument('--service_type', type=str, help="服务类型", default='service')
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arg_parser.add_argument('--label', type=str, help="服务中文名", default='演示服务')
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arg_parser.add_argument('--model_name', type=str, help="模型名", default='demo')
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arg_parser.add_argument('--model_version', type=str, help="模型版本号", default=datetime.datetime.now().strftime('v%Y.%m.%d.1'))
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arg_parser.add_argument('--model_path', type=str, help="模型地址", default='')
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arg_parser.add_argument('--images', type=str, help="镜像", default='nginx')
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arg_parser.add_argument('--resource_memory', type=str, help="内存", default='2G')
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arg_parser.add_argument('--resource_cpu', type=str, help="cpu", default='2')
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arg_parser.add_argument('--resource_gpu', type=str, help="gpu", default='0')
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arg_parser.add_argument('--replicas', type=str, help="副本数", default='1')
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arg_parser.add_argument('--host', type=str, help="域名", default='')
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arg_parser.add_argument('--command', type=str, help="启动命令", default='')
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arg_parser.add_argument('--args', type=str, help="启动参数", default='')
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arg_parser.add_argument('--working_dir', type=str, help="工作目录", default='')
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arg_parser.add_argument('--env', type=str, help="环境变量", default='')
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arg_parser.add_argument('--hpa', type=str, help="弹性伸缩", default='')
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arg_parser.add_argument('--ports', type=str, help="端口号", default='80')
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arg_parser.add_argument('--volume_mount', type=str, help="挂载", default='')
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args = arg_parser.parse_args()
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# print("{} args: {}".format(__file__, args))
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deploy(**args.__dict__)
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