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English | 中文

FastDeploy Serving Deployment Image Compilation

This document is about how to create a FastDploy image.

GPU Image

The GPU images published by FastDploy are based on version 21.10 of Triton Inference Server. If developers need to use other CUDA versions, please refer to NVIDIA official website to modify the scripts in Dockerfile and scripts.

# Enter the serving directory and execute the script to compile the FastDeploy and serving backend
cd serving
bash scripts/build.sh

# Exit to the FastDeploy home directory and create the image
# x.y.z is FastDeploy version, example: 1.0.3
cd ../
docker build -t paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 -f serving/Dockerfile .

For example, create an GPU image based on FastDeploy v1.0.3 and ubuntu 20.04，cuda11.2 environment

# Enter the serving directory and execute the script to compile the FastDeploy and serving backend
cd serving
bash scripts/build_fd_cuda_11_2.sh

# Exit to the FastDeploy home directory and create the image
cd ../
docker build -t paddlepaddle/fastdeploy:1.0.3-gpu-cuda11.2-trt8.4-21.10 -f serving/Dockerfile_CUDA_11_2 .

CPU Image

# Enter the serving directory and execute the script to compile the FastDeploy and serving backend
cd serving
cd serving
bash scripts/build.sh OFF

# Exit to the FastDeploy home directory and create the image
# x.y.z is FastDeploy version, example: 1.0.3
cd ../
docker build -t paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 -f serving/Dockerfile_cpu .

IPU Image

# Enter the serving directory and execute the script to compile the FastDeploy and serving backend
cd serving
bash scripts/build_fd_ipu.sh

# Exit to the FastDeploy home directory and create the image
# x.y.z is FastDeploy version, example: 1.0.3
cd ../
docker build -t paddlepaddle/fastdeploy:x.y.z-ipu-only-21.10 -f serving/Dockerfile_ipu .