From ffcbf6153c9b66c8d785584bd622785e0ee5b0aa Mon Sep 17 00:00:00 2001 From: heliqi <1101791222@qq.com> Date: Wed, 30 Nov 2022 06:30:58 +0000 Subject: [PATCH] serving doc update version to 1.0.0 --- examples/text/ernie-3.0/serving/README.md | 6 +++--- examples/text/uie/serving/README.md | 4 ++-- .../vision/classification/paddleclas/serving/README.md | 4 ++-- examples/vision/detection/yolov5/serving/README.md | 4 ++-- examples/vision/detection/yolov5/serving/README_EN.md | 6 +++--- examples/vision/ocr/PP-OCRv3/serving/README.md | 10 +++++++--- serving/README_CN.md | 4 ++-- serving/README_EN.md | 4 ++-- serving/docs/EN/compile-en.md | 9 ++++++--- serving/docs/zh_CN/compile.md | 9 ++++++--- 10 files changed, 35 insertions(+), 25 deletions(-) diff --git a/examples/text/ernie-3.0/serving/README.md b/examples/text/ernie-3.0/serving/README.md index 6edc1b7907..8b7fbdd9af 100644 --- a/examples/text/ernie-3.0/serving/README.md +++ b/examples/text/ernie-3.0/serving/README.md @@ -51,10 +51,10 @@ models # GPU镜像 docker pull paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 # CPU镜像 -docker pull paddlepaddle/fastdeploy:z.y.z-cpu-only-21.10 +docker pull paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 # 运行 -docker run -it --net=host --name fastdeploy_server --shm-size="1g" -v /path/serving/models:/models paddlepaddle/fastdeploy:0.6.0-cpu-only-21.10 bash +docker run -it --net=host --name fastdeploy_server --shm-size="1g" -v /path/serving/models:/models paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 bash ``` ## 部署模型 @@ -67,7 +67,7 @@ token_cls_rpc_client.py # 序列标注任务发送pipeline预测请求的脚 ``` *注意*:启动服务时，Server的每个python后端进程默认申请`64M`内存，默认启动的docker无法启动多个python后端节点。有两个解决方案： -- 1.启动容器时设置`shm-size`参数, 比如:`docker run -it --net=host --name fastdeploy_server --shm-size="1g" -v /path/serving/models:/models paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 bash` +- 1.启动容器时设置`shm-size`参数, 比如:`docker run -it --net=host --name fastdeploy_server --shm-size="1g" -v /path/serving/models:/models paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 bash` - 2.启动服务时设置python后端的`shm-default-byte-size`参数, 设置python后端的默认内存为10M： `tritonserver --model-repository=/models --backend-config=python,shm-default-byte-size=10485760` ### 分类任务 diff --git a/examples/text/uie/serving/README.md b/examples/text/uie/serving/README.md index c2ade2a547..f38ff7c5e0 100644 --- a/examples/text/uie/serving/README.md +++ b/examples/text/uie/serving/README.md @@ -34,10 +34,10 @@ models # GPU镜像 docker pull paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 # CPU镜像 -docker pull paddlepaddle/fastdeploy:z.y.z-cpu-only-21.10 +docker pull paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 # 运行容器.容器名字为 fd_serving, 并挂载当前目录为容器的 /uie_serving 目录 -docker run -it --net=host --name fastdeploy_server --shm-size="1g" -v `pwd`/:/uie_serving paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 bash +docker run -it --net=host --name fastdeploy_server --shm-size="1g" -v `pwd`/:/uie_serving paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 bash # 启动服务(不设置CUDA_VISIBLE_DEVICES环境变量，会拥有所有GPU卡的调度权限) CUDA_VISIBLE_DEVICES=0 fastdeployserver --model-repository=/uie_serving/models --backend-config=python,shm-default-byte-size=10485760 diff --git a/examples/vision/classification/paddleclas/serving/README.md b/examples/vision/classification/paddleclas/serving/README.md index 971e9bbd0f..0b4771717e 100644 --- a/examples/vision/classification/paddleclas/serving/README.md +++ b/examples/vision/classification/paddleclas/serving/README.md @@ -28,10 +28,10 @@ mv ResNet50_vd_infer/inference.pdiparams models/runtime/1/model.pdiparams # GPU镜像 docker pull paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 # CPU镜像 -docker pull paddlepaddle/fastdeploy:z.y.z-cpu-only-21.10 +docker pull paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 # 运行容器.容器名字为 fd_serving, 并挂载当前目录为容器的 /serving 目录 -nvidia-docker run -it --net=host --name fd_serving -v `pwd`/:/serving paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 bash +nvidia-docker run -it --net=host --name fd_serving -v `pwd`/:/serving paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 bash # 启动服务(不设置CUDA_VISIBLE_DEVICES环境变量，会拥有所有GPU卡的调度权限) CUDA_VISIBLE_DEVICES=0 fastdeployserver --model-repository=/serving/models --backend-config=python,shm-default-byte-size=10485760 diff --git a/examples/vision/detection/yolov5/serving/README.md b/examples/vision/detection/yolov5/serving/README.md index 3e341ff6d2..fd85e50ce8 100644 --- a/examples/vision/detection/yolov5/serving/README.md +++ b/examples/vision/detection/yolov5/serving/README.md @@ -22,10 +22,10 @@ mv yolov5s.onnx models/runtime/1/model.onnx # GPU镜像 docker pull paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 # CPU镜像 -docker pull paddlepaddle/fastdeploy:z.y.z-cpu-only-21.10 +docker pull paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 # 运行容器.容器名字为 fd_serving, 并挂载当前目录为容器的 /yolov5_serving 目录 -nvidia-docker run -it --net=host --name fd_serving -v `pwd`/:/yolov5_serving paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 bash +nvidia-docker run -it --net=host --name fd_serving -v `pwd`/:/yolov5_serving paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 bash # 启动服务(不设置CUDA_VISIBLE_DEVICES环境变量，会拥有所有GPU卡的调度权限) CUDA_VISIBLE_DEVICES=0 fastdeployserver --model-repository=/yolov5_serving/models --backend-config=python,shm-default-byte-size=10485760 diff --git a/examples/vision/detection/yolov5/serving/README_EN.md b/examples/vision/detection/yolov5/serving/README_EN.md index cc85355d89..cb4630463a 100644 --- a/examples/vision/detection/yolov5/serving/README_EN.md +++ b/examples/vision/detection/yolov5/serving/README_EN.md @@ -9,11 +9,11 @@ wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov5s.onnx # Save the model under models/infer/1 and rename it as model.onnx mv yolov5s.onnx models/infer/1/ -# Pull fastdeploy image -docker pull paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 +# Pull fastdeploy image, x.y.z is FastDeploy version, example 1.0.0. +docker pull paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 # Run the docker. The docker name is fd_serving, and the current directory is mounted as the docker's /yolov5_serving directory -nvidia-docker run -it --net=host --name fd_serving -v `pwd`/:/yolov5_serving paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 bash +nvidia-docker run -it --net=host --name fd_serving -v `pwd`/:/yolov5_serving paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 bash # Start the service (Without setting the CUDA_VISIBLE_DEVICES environment variable, it will have scheduling privileges for all GPU cards) CUDA_VISIBLE_DEVICES=0 fastdeployserver --model-repository=models --backend-config=python,shm-default-byte-size=10485760 diff --git a/examples/vision/ocr/PP-OCRv3/serving/README.md b/examples/vision/ocr/PP-OCRv3/serving/README.md index ec53fb8d6a..0762a2359f 100644 --- a/examples/vision/ocr/PP-OCRv3/serving/README.md +++ b/examples/vision/ocr/PP-OCRv3/serving/README.md @@ -1,5 +1,9 @@ # PP-OCR服务化部署示例 +在服务化部署前，需确认 + +- 1. 服务化镜像的软硬件环境要求和镜像拉取命令请参考[FastDeploy服务化部署](../../../../../serving/README_CN.md) + ## 介绍 本文介绍了使用FastDeploy搭建OCR文字识别服务的方法. @@ -48,9 +52,9 @@ mv ppocr_keys_v1.txt models/rec_postprocess/1/ wget https://gitee.com/paddlepaddle/PaddleOCR/raw/release/2.6/doc/imgs/12.jpg - -docker pull paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 -docker run -dit --net=host --name fastdeploy --shm-size="1g" -v $PWD:/ocr_serving paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 bash +# x.y.z为镜像版本号，需参照serving文档替换为数字 +docker pull paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 +docker run -dit --net=host --name fastdeploy --shm-size="1g" -v $PWD:/ocr_serving paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 bash docker exec -it -u root fastdeploy bash ``` diff --git a/serving/README_CN.md b/serving/README_CN.md index edf12b5202..84017b399d 100644 --- a/serving/README_CN.md +++ b/serving/README_CN.md @@ -17,13 +17,13 @@ FastDeploy基于[Triton Inference Server](https://github.com/triton-inference-se #### CPU镜像 CPU镜像仅支持Paddle/ONNX模型在CPU上进行服务化部署，支持的推理后端包括OpenVINO、Paddle Inference和ONNX Runtime ``` shell -docker pull paddlepaddle/fastdeploy:0.6.0-cpu-only-21.10 +docker pull paddlepaddle/fastdeploy:1.0.0-cpu-only-21.10 ``` #### GPU镜像 GPU镜像支持Paddle/ONNX模型在GPU/CPU上进行服务化部署，支持的推理后端包括OpenVINO、TensorRT、Paddle Inference和ONNX Runtime ``` -docker pull paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 +docker pull paddlepaddle/fastdeploy:1.0.0-gpu-cuda11.4-trt8.4-21.10 ``` 用户也可根据自身需求，参考如下文档自行编译镜像 diff --git a/serving/README_EN.md b/serving/README_EN.md index 88037ba014..b901567e18 100644 --- a/serving/README_EN.md +++ b/serving/README_EN.md @@ -20,7 +20,7 @@ FastDeploy builds an end-to-end serving deployment based on [Triton Inference Se CPU images only support Paddle/ONNX models for serving deployment on CPUs, and supported inference backends include OpenVINO, Paddle Inference, and ONNX Runtime ```shell -docker pull paddlepaddle/fastdeploy:0.6.0-cpu-only-21.10 +docker pull paddlepaddle/fastdeploy:1.0.0-cpu-only-21.10 ``` #### GPU Image @@ -28,7 +28,7 @@ docker pull paddlepaddle/fastdeploy:0.6.0-cpu-only-21.10 GPU images support Paddle/ONNX models for serving deployment on GPU and CPU, and supported inference backends including OpenVINO, TensorRT, Paddle Inference, and ONNX Runtime ``` -docker pull paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 +docker pull paddlepaddle/fastdeploy:1.0.0-gpu-cuda11.4-trt8.4-21.10 ``` Users can also compile the image by themselves according to their own needs, referring to the following documents: diff --git a/serving/docs/EN/compile-en.md b/serving/docs/EN/compile-en.md index 32476c19a8..74e4d17930 100644 --- a/serving/docs/EN/compile-en.md +++ b/serving/docs/EN/compile-en.md @@ -12,8 +12,9 @@ cd serving bash scripts/build.sh # Exit to the FastDeploy home directory and create the image +# x.y.z is FastDeploy version, example: 1.0.0 cd ../ -docker build -t paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 -f serving/Dockerfile . +docker build -t paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 -f serving/Dockerfile . ``` ## CPU Image @@ -25,8 +26,9 @@ cd serving bash scripts/build.sh OFF # Exit to the FastDeploy home directory and create the image +# x.y.z is FastDeploy version, example: 1.0.0 cd ../ -docker build -t paddlepaddle/fastdeploy:0.6.0-cpu-only-21.10 -f serving/Dockerfile_cpu . +docker build -t paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 -f serving/Dockerfile_cpu . ``` ## IPU Image @@ -37,6 +39,7 @@ 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: 1.0.0 cd ../ -docker build -t paddlepaddle/fastdeploy:0.6.0-ipu-only-21.10 -f serving/Dockerfile_ipu . +docker build -t paddlepaddle/fastdeploy:x.y.z-ipu-only-21.10 -f serving/Dockerfile_ipu . ``` diff --git a/serving/docs/zh_CN/compile.md b/serving/docs/zh_CN/compile.md index ebbb25da44..106700196b 100644 --- a/serving/docs/zh_CN/compile.md +++ b/serving/docs/zh_CN/compile.md @@ -12,8 +12,9 @@ cd serving bash scripts/build.sh # 退出到FastDeploy主目录，制作镜像 +# x.y.z为FastDeploy版本号，可根据情况自己确定。比如: 1.0.0 cd ../ -docker build -t paddlepaddle/fastdeploy:0.6.0-gpu-cuda11.4-trt8.4-21.10 -f serving/Dockerfile . +docker build -t paddlepaddle/fastdeploy:x.y.z-gpu-cuda11.4-trt8.4-21.10 -f serving/Dockerfile . ``` ## 制作CPU镜像 @@ -24,8 +25,9 @@ cd serving bash scripts/build.sh OFF # 退出到FastDeploy主目录，制作镜像 +# x.y.z为FastDeploy版本号，可根据情况自己确定。比如: 1.0.0 cd ../ -docker build -t paddlepaddle/fastdeploy:0.6.0-cpu-only-21.10 -f serving/Dockerfile_cpu . +docker build -t paddlepaddle/fastdeploy:x.y.z-cpu-only-21.10 -f serving/Dockerfile_cpu . ``` ## 制作IPU镜像 @@ -36,6 +38,7 @@ cd serving bash scripts/build_fd_ipu.sh # 退出到FastDeploy主目录，制作镜像 +# x.y.z为FastDeploy版本号，可根据情况自己确定。比如: 1.0.0 cd ../ -docker build -t paddlepaddle/fastdeploy:0.6.0-ipu-only-21.10 -f serving/Dockerfile_ipu . +docker build -t paddlepaddle/fastdeploy:x.y.z-ipu-only-21.10 -f serving/Dockerfile_ipu . ```