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71 lines
2.2 KiB
Markdown
71 lines
2.2 KiB
Markdown
中文 ｜ [English](../EN/compile-en.md)
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# 服务化部署编译
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## 制作服务化部署镜像
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### 制作GPU镜像
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FastDploy发布的GPU镜像基于[Triton Inference Server](https://github.com/triton-inference-server/server)的21.10版本进行制作，如果有其他CUDA版本需求，可以参照[NVIDIA 官网](https://docs.nvidia.com/deeplearning/frameworks/support-matrix/index.html)中展示的版本信息修改Dockerfile和scripts中的脚本.
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```
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# 进入serving目录执行脚本编译fastdeploy和服务化的backend
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cd serving
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bash scripts/build.sh
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# 退出到FastDeploy主目录，制作镜像
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# x.y.z为FastDeploy版本号，可根据情况自己确定。比如: 1.0.3
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cd ../
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docker build -t paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.5-21.10 -f serving/Dockerfile .
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```
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目前默认 TensorRT 版本为 8.5.2.2，如果需要切换 TensorRT 版本，则可执行以下编译命令：
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```
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cd serving
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bash scripts/build.sh -tv 8.4.1.5
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cd ../
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docker build -t paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.5-21.10 -f serving/Dockerfile_CUDA_11_4_TRT_8_4 .
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```
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比如在ubuntu 20.04，cuda11.2环境下制作基于FastDeploy v1.0.3的GPU镜像
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```
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# 进入serving目录执行脚本编译fastdeploy和服务化的backend
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cd serving
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bash scripts/build_fd_cuda_11_2.sh
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# 退出到FastDeploy主目录，制作镜像
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cd ../
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docker build -t paddlepaddle/fastdeploy:1.0.3-gpu-cuda11.2-trt8.4-21.10 -f serving/Dockerfile_CUDA_11_2 .
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```
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### 制作CPU镜像
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```
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# 进入serving目录执行脚本编译fastdeploy和服务化的backend
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cd serving
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bash scripts/build.sh OFF
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# 退出到FastDeploy主目录，制作镜像
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# x.y.z为FastDeploy版本号，可根据情况自己确定。比如: 1.0.3
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cd ../
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docker build -t paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 -f serving/Dockerfile_cpu .
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```
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### 制作IPU镜像
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```
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# 进入serving目录执行脚本编译fastdeploy和服务化的backend
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cd serving
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bash scripts/build_fd_ipu.sh
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# 退出到FastDeploy主目录，制作镜像
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# x.y.z为FastDeploy版本号，可根据情况自己确定。比如: 1.0.3
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cd ../
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docker build -t paddlepaddle/fastdeploy:x.y.z-ipu-only-21.10 -f serving/Dockerfile_ipu .
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```
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## 非镜像方式编译
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- [FastDeploy Serving CentOS编译教程](./compile_without_docker_centos.md)
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