提交 9761200b 编写于 作者: T TeslaZhao

modify v0.8.0 doc

上级 367abfbb
......@@ -11,8 +11,8 @@
<a href="https://travis-ci.com/PaddlePaddle/Serving">
<img alt="Build Status" src="https://img.shields.io/travis/com/PaddlePaddle/Serving/develop?style=flat-square">
<img alt="Docs" src="https://img.shields.io/badge/docs-中文文档-brightgreen?style=flat-square">
<img alt="Release" src="https://img.shields.io/badge/release-0.7.0-blue?style=flat-square">
<img alt="Python" src="https://img.shields.io/badge/python-3.6+-blue?style=flat-square">
<img alt="Release" src="https://img.shields.io/badge/release-0.8.0-blue?style=flat-square">
<img alt="Python" src="https://img.shields.io/badge/python-3.6/3.7/3.8/3.9-blue?style=flat-square">
<img alt="License" src="https://img.shields.io/github/license/PaddlePaddle/Serving?color=blue&style=flat-square">
<img alt="Forks" src="https://img.shields.io/github/forks/PaddlePaddle/Serving?color=yellow&style=flat-square">
<img alt="Issues" src="https://img.shields.io/github/issues/PaddlePaddle/Serving?color=yellow&style=flat-square">
......@@ -31,7 +31,8 @@ The goal of Paddle Serving is to provide high-performance, flexible and easy-to-
- There are two frameworks, namely high-performance C++ Serving and high-easy-to-use Python pipeline. The C++ Serving is based on the bRPC network framework to create a high-throughput, low-latency inference service, and its performance indicators are ahead of competing products. The Python pipeline is based on the gRPC/gRPC-Gateway network framework and the Python language to build a highly easy-to-use and high-throughput inference service. How to choose which one please see [Techinical Selection](doc/Serving_Design_EN.md#21-design-selection).
- Support multiple [protocols](doc/C++_Serving/Inference_Protocols_CN.md) such as HTTP, gRPC, bRPC, and provide C++, Python, Java language SDK.
- Design and implement a high-performance inference service framework for asynchronous pipelines based on directed acyclic graph (DAG), with features such as multi-model combination, asynchronous scheduling, concurrent inference, dynamic batch, multi-card multi-stream inference, etc.
- Adapt to a variety of commonly used computing hardwares, such as x86 (Intel) CPU, ARM CPU, Nvidia GPU, Kunlun XPU, etc.; Integrate acceleration libraries of Intel MKLDNN and Nvidia TensorRT, and low-precision and quantitative inference.
- Adapt to a variety of commonly used computing hardwares, such as x86 (Intel) CPU, ARM CPU, Nvidia GPU, Kunlun XPU, HUAWEI Ascend 310/910, HYGON DCU、Nvidia Jetson etc.
- Integrate acceleration libraries of Intel MKLDNN and Nvidia TensorRT, and low-precision and quantitative inference.
- Provide a model security deployment solution, including encryption model deployment, and authentication mechanism, HTTPs security gateway, which is used in practice.
- Support cloud deployment, provide a deployment case of Baidu Cloud Intelligent Cloud kubernetes cluster.
- Provide more than 40 classic pre-model deployment examples, such as PaddleOCR, PaddleClas, PaddleDetection, PaddleSeg, PaddleNLP, PaddleRec and other suites, and more models continue to expand.
......@@ -43,7 +44,7 @@ The goal of Paddle Serving is to provide high-performance, flexible and easy-to-
- AIStudio tutorial(Chinese) : [Paddle Serving服务化部署框架](https://www.paddlepaddle.org.cn/tutorials/projectdetail/2538249)
- Video tutorial(Chinese) : [深度学习服务化部署-以互联网应用为例](https://aistudio.baidu.com/aistudio/course/introduce/19084)
- Edge AI solution based on Paddle Serving & Baidu Intelligent Edge(Chinese) : [基于Paddle Serving&百度智能边缘BIE的边缘AI解决方案](https://mp.weixin.qq.com/s/j0EVlQXaZ7qmoz9Fv96Yrw)
- Edge AI solution(Chinese) : [基于Paddle Serving&百度智能边缘BIE的边缘AI解决方案](https://mp.weixin.qq.com/s/j0EVlQXaZ7qmoz9Fv96Yrw)
<p align="center">
<img src="doc/images/demo.gif" width="700">
......@@ -128,7 +129,6 @@ If you want to communicate with developers and other users? Welcome to join us,
### Wechat
- WeChat scavenging
<p align="center">
<img src="doc/images/wechat_group_1.jpeg" width="250">
</p>
......
......@@ -11,8 +11,8 @@
<a href="https://travis-ci.com/PaddlePaddle/Serving">
<img alt="Build Status" src="https://img.shields.io/travis/com/PaddlePaddle/Serving/develop?style=flat-square">
<img alt="Docs" src="https://img.shields.io/badge/docs-中文文档-brightgreen?style=flat-square">
<img alt="Release" src="https://img.shields.io/badge/release-0.7.0-blue?style=flat-square">
<img alt="Python" src="https://img.shields.io/badge/python-3.6+-blue?style=flat-square">
<img alt="Release" src="https://img.shields.io/badge/release-0.8.0-blue?style=flat-square">
<img alt="Python" src="https://img.shields.io/badge/python-3.6/3.7/3.8/3.9-blue?style=flat-square">
<img alt="License" src="https://img.shields.io/github/license/PaddlePaddle/Serving?color=blue&style=flat-square">
<img alt="Forks" src="https://img.shields.io/github/forks/PaddlePaddle/Serving?color=yellow&style=flat-square">
<img alt="Issues" src="https://img.shields.io/github/issues/PaddlePaddle/Serving?color=yellow&style=flat-square">
......@@ -30,10 +30,11 @@ Paddle Serving依托深度学习框架PaddlePaddle旨在帮助深度学习开发
- 具有高性能C++和高易用Python 2套框架。C++框架基于高性能bRPC网络框架打造高吞吐、低延迟的推理服务,性能领先竞品。Python框架基于gRPC/gRPC-Gateway网络框架和Python语言构建高易用、高吞吐推理服务框架。技术选型参考[技术选型](doc/Serving_Design_CN.md#21-设计选型)
- 支持HTTP、gRPC、bRPC等多种[协议](doc/C++_Serving/Inference_Protocols_CN.md);提供C++、Python、Java语言SDK
- 设计并实现基于有向无环图(DAG)的异步流水线高性能推理框架,具有多模型组合、异步调度、并发推理、动态批量、多卡多流推理等特性
- 适配x86(Intel) CPU、ARM CPU、Nvidia GPU、昆仑XPU等多种硬件;集成Intel MKLDNN、Nvidia TensorRT加速库,以及低精度和量化推理
- 适配x86(Intel) CPU、ARM CPU、Nvidia GPU、昆仑XPU、华为昇腾310/910、海光DCU、Nvidia Jetson等多种硬件
- 集成Intel MKLDNN、Nvidia TensorRT加速库,以及低精度和量化推理
- 提供一套模型安全部署解决方案,包括加密模型部署、鉴权校验、HTTPs安全网关,并在实际项目中应用
- 支持云端部署,提供百度云智能云kubernetes集群部署Paddle Serving案例
- 提供丰富的经典预模型部署示例,如PaddleOCR、PaddleClas、PaddleDetection、PaddleSeg、PaddleNLP、PaddleRec等套件,共计40+个预训练精品模型,更多模型持续扩展
- 提供丰富的经典预模型部署示例,如PaddleOCR、PaddleClas、PaddleDetection、PaddleSeg、PaddleNLP、PaddleRec等套件,共计40+个预训练精品模型
- 支持大规模稀疏参数索引模型分布式部署,具有多表、多分片、多副本、本地高频cache等特性、可单机或云端部署
......@@ -41,7 +42,7 @@ Paddle Serving依托深度学习框架PaddlePaddle旨在帮助深度学习开发
- AIStudio教程-[Paddle Serving服务化部署框架](https://www.paddlepaddle.org.cn/tutorials/projectdetail/2538249)
- 视频教程-[深度学习服务化部署-以互联网应用为例](https://aistudio.baidu.com/aistudio/course/introduce/19084)
- Edge AI solution based on Paddle Serving & Baidu Intelligent Edge(Chinese) : [基于Paddle Serving&百度智能边缘BIE的边缘AI解决方案](https://mp.weixin.qq.com/s/j0EVlQXaZ7qmoz9Fv96Yrw)
- 边缘AI解决方案-[基于Paddle Serving&百度智能边缘BIE的边缘AI解决方案](https://mp.weixin.qq.com/s/j0EVlQXaZ7qmoz9Fv96Yrw)
<p align="center">
<img src="doc/images/demo.gif" width="700">
......
......@@ -15,8 +15,6 @@
此外,针对某些C++二次开发场景,我们也提供了OPENCV的联编方案。
## 编译环境准备
| 组件 | 版本要求 |
......@@ -40,7 +38,7 @@
推荐使用Docker编译,我们已经为您准备好了Paddle Serving编译环境并配置好了上述编译依赖,详见[该文档](Docker_Images_CN.md)
我们提供了五个环境的开发镜像,分别是CPU, Cuda10.1+Cudnn7, Cuda10.2+Cudnn7,Cuda10.2+Cudnn8, Cuda11.2+Cudnn8。我们提供了Serving开发镜像涵盖以上环境。与此同时,我们也支持Paddle开发镜像。
我们提供了五个环境的开发镜像,分别是CPU, CUDA10.1+CUDNN7, CUDA10.2+CUDNN7,CUDA10.2+CUDNN8, CUDA11.2+CUDNN8。我们提供了Serving开发镜像涵盖以上环境。与此同时,我们也支持Paddle开发镜像。
其中Serving镜像名是 **paddlepaddle/serving:${Serving开发镜像Tag}**(如果网络不佳可以访问**registry.baidubce.com/paddlepaddle/serving:${Serving开发镜像Tag}**), Paddle开发镜像名是 **paddlepaddle/paddle:${Paddle开发镜像Tag}**。为了防止用户对两套镜像出现混淆,我们分别解释一下两套镜像的由来。
......@@ -49,11 +47,11 @@ Serving开发镜像是Serving套件为了支持各个预测环境提供的用于
| 环境 | Serving开发镜像Tag | 操作系统 | Paddle开发镜像Tag | 操作系统 |
| :--------------------------: | :-------------------------------: | :-------------: | :-------------------: | :----------------: |
| CPU | 0.7.0-devel | Ubuntu 16.04 | 2.2.0 | Ubuntu 18.04. |
| Cuda10.1+Cudnn7 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda10.2+Cudnn7 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| Cuda10.2+Cudnn8 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda11.2+Cudnn8 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
| CPU | 0.8.0-devel | Ubuntu 16.04 | 2.2.2 | Ubuntu 18.04. |
| CUDA10.1 + CUDNN7 | 0.8.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| CUDA10.2 + CUDNN7 | 0.8.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| CUDA10.2 + CUDNN8 | 0.8.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| CUDA11.2 + CUDNN8 | 0.8.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
我们首先要针对自己所需的环境拉取相关镜像。上表**环境**一列下,除了CPU,其余(Cuda**+Cudnn**)都属于GPU环境。
您可以使用Serving开发镜像。
......
......@@ -37,7 +37,7 @@ In addition, for some C++ secondary development scenarios, we also provide OPENC
Docker compilation is recommended. We have prepared the Paddle Serving compilation environment for you and configured the above compilation dependencies. For details, please refer to [this document](DOCKER_IMAGES_CN.md).
We provide five environment development images, namely CPU, Cuda10.1+Cudnn7, Cuda10.2+Cudnn7, Cuda10.2+Cudnn8, Cuda11.2+Cudnn8. We provide a Serving development image to cover the above environment. At the same time, we also support Paddle development mirroring.
We provide five environment development images, namely CPU, CUDA10.1 + CUDNN7, CUDA10.2 + CUDNN7, CUDA10.2 + CUDNN8, CUDA11.2 + CUDNN8. We provide a Serving development image to cover the above environment. At the same time, we also support Paddle development mirroring.
The Serving image name is **paddlepaddle/serving:${Serving development image Tag}** (If the network is not good, you can visit **registry.baidubce.com/paddlepaddle/serving:${Serving development image Tag}**), The name of the Paddle development image is **paddlepaddle/paddle:${Paddle Development Image Tag}**. In order to prevent users from confusing the two sets of mirroring, we explain the origin of the two sets of mirroring separately.
......@@ -45,11 +45,11 @@ Serving development mirror is the mirror used to compile and debug prediction se
| Environment | Serving Dev Image Tag | OS | Paddle Dev Image Tag | OS |
| :--------------------------: | :-------------------------------: | :-------------: | :-------------------: | :----------------: |
| CPU | 0.7.0-devel | Ubuntu 16.04 | 2.2.0 | Ubuntu 18.04. |
| Cuda10.1+Cudnn7 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | Nan | Nan |
| Cuda10.2+Cudnn7 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| Cuda10.2+Cudnn8 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | Nan | Nan |
| Cuda11.2+Cudnn8 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
| CPU | 0.8.0-devel | Ubuntu 16.04 | 2.2.2 | Ubuntu 18.04. |
| CUDA10.1 + Cudnn7 | 0.8.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | Nan | Nan |
| CUDA10.2 + Cudnn7 | 0.8.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| CUDA10.2 + Cudnn8 | 0.8.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | Nan | Nan |
| CUDA11.2 + Cudnn8 | 0.8.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
We first need to pull related images for the environment we need. Under the **Environment** column in the above table, except for the CPU, the rest (Cuda**+Cudnn**) belong to the GPU environment.
......@@ -257,7 +257,7 @@ make -j10
| WITH_GPU | Compile Paddle Serving with NVIDIA GPU | OFF |
| WITH_TRT | Compile Paddle Serving with TensorRT | OFF |
| WITH_OPENCV | Compile Paddle Serving with OPENCV | OFF |
| CUDNN_LIBRARY | Define CuDNN library and header path | |
| CUDNN_LIBRARY | Define CUDNN library and header path | |
| CUDA_TOOLKIT_ROOT_DIR | Define CUDA PATH | |
| TENSORRT_ROOT | Define TensorRT PATH | |
| CLIENT | Compile Paddle Serving Client | OFF |
......@@ -272,26 +272,26 @@ Paddle Serving supports prediction on the GPU through the PaddlePaddle predictio
To compile the Paddle Serving GPU version on bare metal, you need to install these basic libraries:
-CUDA
-CuDNN
-CUDNN
To compile the TensorRT version, you need to install the TensorRT library.
The things to note here are:
1. Compile the basic library versions such as CUDA/CUDNN installed on the system where Serving is located, and need to be compatible with the actual GPU device. For example, Tesla V100 card requires at least CUDA 9.0. If the version of basic libraries such as CUDA used during compilation is too low, the Serving process cannot be started due to the incompatibility between the generated GPU code and the actual hardware device, or serious problems such as coredump may occur.
2. Install the CUDA driver compatible with the actual GPU device on the system running Paddle Serving, and install the basic library compatible with the CUDA/CuDNN version used during compilation. If the version of CUDA/CuDNN installed on the system running Paddle Serving is lower than the version used during compilation, it may cause strange cuda function call failures and other problems.
2. Install the CUDA driver compatible with the actual GPU device on the system running Paddle Serving, and install the basic library compatible with the CUDA/CUDNN version used during compilation. If the version of CUDA/CUDNN installed on the system running Paddle Serving is lower than the version used during compilation, it may cause strange cuda function call failures and other problems.
The following is the matching relationship between PaddleServing mirrored Cuda, Cudnn, and TensorRT for reference:
| | CUDA | CuDNN | TensorRT |
| | CUDA | CUDNN | TensorRT |
| :----: | :-----: | :----------: | :----: |
| post101 | 10.1 | CuDNN 7.6.5 | 6.0.1 |
| post102 | 10.2 | CuDNN 8.0.5 | 7.1.3 |
| post11 | 11.0 | CuDNN 8.0.4 | 7.1.3 |
| post101 | 10.1 | CUDNN 7.6.5 | 6.0.1 |
| post102 | 10.2 | CUDNN 8.0.5 | 7.1.3 |
| post11 | 11.0 | CUDNN 8.0.4 | 7.1.3 |
### Attachment: How to make the Paddle Serving compilation system detect the CuDNN library
### Attachment: How to make the Paddle Serving compilation system detect the CUDNN library
After downloading the corresponding version of CuDNN from the official website of NVIDIA developer and decompressing it locally, add the `-DCUDNN_LIBRARY` parameter to the cmake compilation command and specify the path of the CuDNN library.
After downloading the corresponding version of CUDNN from the official website of NVIDIA developer and decompressing it locally, add the `-DCUDNN_LIBRARY` parameter to the cmake compilation command and specify the path of the CUDNN library.
## Attachment: Compile and install OpenCV library
**Note:** You only need to do this when you need to include the OpenCV library in your C++ code.
......
......@@ -11,7 +11,7 @@
1. 通过 TAG 直接从 dockerhub 或 `registry.baidubce.com` 拉取镜像,具体TAG请参见下文的**镜像说明**章节的表格。
```shell
docker pull paddlepaddle/serving:<TAG> # 如果连接dockerhub网速不佳可以尝试registry.baidubce.com/paddlepaddle/serving:<TAG>
docker pull registry.baidubce.com/paddlepaddle/serving:<TAG>
```
2. 基于 Dockerfile 构建镜像
......@@ -23,7 +23,6 @@
```
## 镜像说明
若需要基于源代码二次开发编译,请使用后缀为-devel的版本。
......@@ -32,16 +31,16 @@
| 镜像选择 | 操作系统 | TAG | Dockerfile |
| :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: |
| CPU development | Ubuntu16 | 0.7.0-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn7-devel | [Dockerfile.cuda10.2-cudnn7.devel](../tools/Dockerfile.cuda10.2-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT8) development | Ubuntu16 | 0.7.0-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
| CPU development | Ubuntu16 | 0.8.0-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | 0.8.0-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | 0.8.0-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn7-tensorRT6) development | Ubuntu16 | 0.8.0-cuda10.2-cudnn7-devel | [Dockerfile.cuda10.2-cudnn7.devel](../tools/Dockerfile.cuda10.2-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | 0.8.0-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT8) development | Ubuntu16 | 0.8.0-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
**Java镜像:**
```
registry.baidubce.com/paddlepaddle/serving:latest-java
registry.baidubce.com/paddlepaddle/serving:0.8.0-cuda10.2-java
```
**XPU镜像:**
......@@ -66,15 +65,15 @@ registry.baidubce.com/paddlepaddle/serving:xpu-x86 # for x86 xpu user
| Env | Version | Docker images tag | OS | Gcc Version |
|----------|---------|------------------------------|-----------|-------------|
| CPU | >=0.5.0 | 0.7.0-devel | Ubuntu 16 | 8.2.0 |
| CPU | >=0.5.0 | 0.8.0-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-devel | CentOS 7 | 4.8.5 |
| Cuda10.1 | >=0.5.0 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.1 | >=0.5.0 | 0.8.0-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-cuda10.1-cudnn7-devel | CentOS 7 | 4.8.5 |
| Cuda10.2+Cudnn7 | >=0.5.0 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.2+Cudnn7 | >=0.5.0 | 0.8.0-cuda10.2-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda10.2+Cudnn8 | >=0.5.0 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.2+Cudnn8 | >=0.5.0 | 0.8.0-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda11.2 | >=0.5.0 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| Cuda11.2 | >=0.5.0 | 0.8.0-cuda11.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
运行镜像:
......
......@@ -11,7 +11,7 @@ You can get images in two ways:
1. Pull image directly from dockerhub or `registry.baidubce.com ` through TAG:
```shell
docker pull docker pull paddlepaddle/serving:<TAG> # if it is slow connection to dockerhub, please try registry.baidubce.com
docker pull registry.baidubce.com/paddlepaddle/serving:<TAG>
```
2. Building image based on dockerfile
......@@ -31,20 +31,20 @@ If you want to customize your Serving based on source code, use the version with
**cuda10.1-cudnn7-gcc54 image is not ready, you should run from dockerfile if you need it.**
If you need to develop and compile based on the source code, please use the version with the suffix -devel.
**In the TAG column, 0.7.0 can also be replaced with the corresponding version number, such as 0.5.0/0.4.1, etc., but it should be noted that some development environments only increase with a certain version iteration, so not all environments All have the corresponding version number can be used.**
**In the TAG column, 0.8.0 can also be replaced with the corresponding version number, such as 0.5.0/0.4.1, etc., but it should be noted that some development environments only increase with a certain version iteration, so not all environments All have the corresponding version number can be used.**
| Description | OS | TAG | Dockerfile |
| :----------------------------------------------------------: | :-----: | :--------------------------: | :----------------------------------------------------------: |
| CPU development | Ubuntu16 | 0.7.0-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn7-tensorRT6) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn7-devel | [Dockerfile.cuda10.2-cudnn7.devel](../tools/Dockerfile.cuda10.2-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | 0.7.0-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT8) development | Ubuntu16 | 0.7.0-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
| CPU development | Ubuntu16 | 0.8.0-devel | [Dockerfile.devel](../tools/Dockerfile.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6-gcc54) development | Ubuntu16 | 0.8.0-cuda10.1-cudnn7-gcc54-devel (not ready) | [Dockerfile.cuda10.1-cudnn7-gcc54.devel](../tools/Dockerfile.cuda10.1-cudnn7-gcc54.devel) |
| GPU (cuda10.1-cudnn7-tensorRT6) development | Ubuntu16 | 0.8.0-cuda10.1-cudnn7-devel | [Dockerfile.cuda10.1-cudnn7.devel](../tools/Dockerfile.cuda10.1-cudnn7.devel) |
| GPU (cuda10.2-cudnn7-tensorRT6) development | Ubuntu16 | 0.8.0-cuda10.2-cudnn7-devel | [Dockerfile.cuda10.2-cudnn7.devel](../tools/Dockerfile.cuda10.2-cudnn7.devel) |
| GPU (cuda10.2-cudnn8-tensorRT7) development | Ubuntu16 | 0.8.0-cuda10.2-cudnn8-devel | [Dockerfile.cuda10.2-cudnn8.devel](../tools/Dockerfile.cuda10.2-cudnn8.devel) |
| GPU (cuda11.2-cudnn8-tensorRT8) development | Ubuntu16 | 0.8.0-cuda11.2-cudnn8-devel | [Dockerfile.cuda11.2-cudnn8.devel](../tools/Dockerfile.cuda11.2-cudnn8.devel) |
**Java Client:**
```
registry.baidubce.com/paddlepaddle/serving:latest-java
registry.baidubce.com/paddlepaddle/serving:0.8.0-cuda10.2-java
```
**XPU:**
......@@ -67,15 +67,15 @@ Develop Images:
| Env | Version | Docker images tag | OS | Gcc Version |
|----------|---------|------------------------------|-----------|-------------|
| CPU | >=0.5.0 | 0.7.0-devel | Ubuntu 16 | 8.2.0 |
| CPU | >=0.5.0 | 0.8.0-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-devel | CentOS 7 | 4.8.5 |
| Cuda10.1 | >=0.5.0 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.1 | >=0.5.0 | 0.8.0-cuda10.1-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | 0.4.0-cuda10.1-cudnn7-devel | CentOS 7 | 4.8.5 |
| Cuda10.2+Cudnn7 | >=0.5.0 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.2+Cudnn7 | >=0.5.0 | 0.8.0-cuda10.2-cudnn7-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda10.2+Cudnn8 | >=0.5.0 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| Cuda10.2+Cudnn8 | >=0.5.0 | 0.8.0-cuda10.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
| Cuda11.2 | >=0.5.0 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| Cuda11.2 | >=0.5.0 | 0.8.0-cuda11.2-cudnn8-devel | Ubuntu 16 | 8.2.0 |
| | <=0.4.0 | Nan | Nan | Nan |
......
......@@ -4,7 +4,7 @@
**强烈建议**您在**Docker内构建**Paddle Serving,更多镜像请查看[Docker镜像列表](Docker_Images_CN.md)
**提示-1**:本项目仅支持<mark>**Python3.6/3.7/3.8**</mark>,接下来所有的与Python/Pip相关的操作都需要选择正确的Python版本。
**提示-1**:本项目仅支持<mark>**Python3.6/3.7/3.8/3.9**</mark>,接下来所有的与Python/Pip相关的操作都需要选择正确的Python版本。
**提示-2**:以下示例中GPU环境均为cuda10.2-cudnn7,如果您使用Python Pipeline来部署,并需要Nvidia TensorRT来优化预测性能,请参考[支持的镜像环境和说明](#4支持的镜像环境和说明)来选择其他版本。
......@@ -15,16 +15,16 @@
**CPU:**
```
# 启动 CPU Docker
docker pull paddlepaddle/serving:0.7.0-devel
docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-devel bash
docker pull paddlepaddle/serving:0.8.0-devel
docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.8.0-devel bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
**GPU:**
```
# 启动 GPU Docker
docker pull paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel bash
docker pull paddlepaddle/serving:0.8.0-cuda10.2-cudnn7-devel
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.8.0-cuda10.2-cudnn7-devel bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
......@@ -32,8 +32,8 @@ git clone https://github.com/PaddlePaddle/Serving
**CPU:**
```
# 启动 CPU Docker
docker pull paddlepaddle/paddle:2.2.0
docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0 bash
docker pull paddlepaddle/paddle:2.2.2
docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.2 bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
......@@ -43,8 +43,8 @@ bash Serving/tools/paddle_env_install.sh
**GPU:**
```
# 启动 GPU Docker
docker pull paddlepaddle/paddle:2.2.0-gpu-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0-gpu-cuda10.2-cudnn7 bash
docker pull paddlepaddle/paddle:2.2.2-gpu-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.2-gpu-cuda10.2-cudnn7 bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
......@@ -59,62 +59,71 @@ cd Serving
pip3 install -r python/requirements.txt
```
安装服务whl包,共有3种client、app、server,Server分为CPU和GPU,GPU包根据您的环境选择一种安装
- post102 = CUDA10.2 + Cudnn7 + TensorRT6(推荐)
- post101 = CUDA10.1 + TensorRT6
- post112 = CUDA11.2 + TensorRT8
```shell
pip3 install paddle-serving-client==0.7.0
pip3 install paddle-serving-server==0.7.0 # CPU
pip3 install paddle-serving-app==0.7.0
pip3 install paddle-serving-server-gpu==0.7.0.post102 #GPU with CUDA10.2 + Cudnn7 + TensorRT6
# 其他GPU环境需要确认环境再选择执行哪一条
pip3 install paddle-serving-server-gpu==0.7.0.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.7.0.post112 # GPU with CUDA11.2 + TensorRT8
pip3 install paddle-serving-client==0.8.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip3 install paddle-serving-app==0.8.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
# CPU Server
pip3 install paddle-serving-server==0.8.0 -i https://pypi.tuna.tsinghua.edu.cn/simple
# GPU Server,需要确认环境再选择执行哪一条,推荐使用CUDA 10.2的包
pip3 install paddle-serving-server-gpu==0.8.0.post102 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip3 install paddle-serving-server-gpu==0.8.0.post101 -i https://pypi.tuna.tsinghua.edu.cn/simple
pip3 install paddle-serving-server-gpu==0.8.0.post112 -i https://pypi.tuna.tsinghua.edu.cn/simple
```
您可能需要使用国内镜像源(例如清华源, 在pip命令中添加`-i https://pypi.tuna.tsinghua.edu.cn/simple`)来加速下载。
默认开启国内清华镜像源来加速下载,如果您使用HTTP代理可以关闭(`-i https://pypi.tuna.tsinghua.edu.cn/simple`)
如果需要使用develop分支编译的安装包,请从[最新安装包列表](./Latest_Packages_CN.md)中获取下载地址进行下载,使用`pip install`命令进行安装。如果您想自行编译,请参照[Paddle Serving编译文档](./Compile_CN.md)
paddle-serving-server和paddle-serving-server-gpu安装包支持Centos 6/7, Ubuntu 16/18和Windows 10。
paddle-serving-client和paddle-serving-app安装包支持Linux和Windows,其中paddle-serving-client仅支持python3.6/3.7/3.8。
paddle-serving-client和paddle-serving-app安装包支持Linux和Windows,其中paddle-serving-client仅支持python3.6/3.7/3.8/3.9
**如果您之前使用paddle serving 0.5.X 0.6.X的Cuda10.2环境,需要注意在0.7.0版本,paddle-serving-server-gpu==0.7.0.post102的使用Cudnn7和TensorRT6,而0.6.0.post102使用cudnn8和TensorRT7。如果0.6.0的cuda10.2用户需要升级安装,请使用paddle-serving-server-gpu==0.7.0.post1028**
**如果您之前使用paddle serving 0.5.X 0.6.X的Cuda10.2环境,需要注意在0.8.0版本,paddle-serving-server-gpu==0.8.0.post102的使用Cudnn7和TensorRT6,而0.6.0.post102使用cudnn8和TensorRT7。如果0.6.0的cuda10.2用户需要升级安装,请使用paddle-serving-server-gpu==0.8.0.post1028**
## 3.安装Paddle相关Python库
**当您使用`paddle_serving_client.convert`命令或者`Python Pipeline框架`时才需要安装。**
```
# CPU环境请执行
pip3 install paddlepaddle==2.2.0
pip3 install paddlepaddle==2.2.2
# GPU Cuda10.2环境请执行
pip3 install paddlepaddle-gpu==2.2.0
# GPU CUDA 10.2环境请执行
pip3 install paddlepaddle-gpu==2.2.2
```
**注意**: 如果您的Cuda版本不是10.2,或者您需要在GPU环境上使用TensorRT,请勿直接执行上述命令,需要参考[Paddle-Inference官方文档-下载安装Linux预测库](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python)选择相应的GPU环境的url链接并进行安装。举例假设您使用python3.6,请执行如下命令。
```
# Cuda10.1 + Cudnn7 + TensorRT6
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101-cp36-cp36m-linux_x86_64.whl
# CUDA10.1 + CUDNN7 + TensorRT6
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.2.post101-cp36-cp36m-linux_x86_64.whl
# Cuda10.2 + Cudnn7 + TensorRT6, 需要注意的是此环境和Cuda10.1+Cudnn7+TensorRT6使用同一个paddle whl包
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101-cp36-cp36m-linux_x86_64.whl
# CUDA10.2 + CUDNN7 + TensorRT6, 需要注意的是此环境和Cuda10.1+Cudnn7+TensorRT6使用同一个paddle whl包
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.2.post101-cp36-cp36m-linux_x86_64.whl
# Cuda10.2 + Cudnn8 + TensorRT7
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.2_cudnn8.1.1_trt7.2.3.4/paddlepaddle_gpu-2.2.0-cp36-cp36m-linux_x86_64.whl
# CUDA10.2 + CUDNN8 + TensorRT7
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.2_cudnn8.1.1_trt7.2.3.4/paddlepaddle_gpu-2.2.2-cp36-cp36m-linux_x86_64.whl
# Cuda11.2 + Cudnn8 + TensorRT8
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda11.2_cudnn8.2.1_trt8.0.3.4/paddlepaddle_gpu-2.2.0.post112-cp36-cp36m-linux_x86_64.whl
# CUDA11.2 + CUDNN8 + TensorRT8
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda11.2_cudnn8.2.1_trt8.0.3.4/paddlepaddle_gpu-2.2.2.post112-cp36-cp36m-linux_x86_64.whl
```
例如Cuda 10.1的Python3.6用户,请选择表格当中的`cp36-cp36m``linux-cuda10.1-cudnn7.6-trt6-gcc8.2`对应的url,复制下来并执行
例如CUDA 10.1的Python3.6用户,请选择表格当中的`cp36-cp36m``linux-cuda10.1-cudnn7.6-trt6-gcc8.2`对应的url,复制下来并执行
```
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101-cp36-cp36m-linux_x86_64.whl
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.2.post101-cp36-cp36m-linux_x86_64.whl
```
## 4.支持的镜像环境和说明
| 环境 | Serving开发镜像Tag | 操作系统 | Paddle开发镜像Tag | 操作系统 |
| :--------------------------: | :-------------------------------: | :-------------: | :-------------------: | :----------------: |
| CPU | 0.7.0-devel | Ubuntu 16.04 | 2.2.0 | Ubuntu 18.04. |
| Cuda10.1+Cudnn7 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda10.2+Cudnn7 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| Cuda10.2+Cudnn8 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda11.2+Cudnn8 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
| CPU | 0.8.0-devel | Ubuntu 16.04 | 2.2.2 | Ubuntu 18.04. |
| CUDA10.1 + CUDNN7 | 0.8.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| CUDA10.2 + CUDNN7 | 0.8.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| CUDA10.2 + CUDNN8 | 0.8.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| CUDA11.2 + CUDNN8 | 0.8.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
对于**Windows 10 用户**,请参考文档[Windows平台使用Paddle Serving指导](Windows_Tutorial_CN.md)
......@@ -4,7 +4,7 @@
**Strongly recommend** you build **Paddle Serving** in Docker. For more images, please refer to [Docker Image List](Docker_Images_CN.md).
**Tip-1**: This project only supports <mark>**Python3.6/3.7/3.8**</mark>, all subsequent operations related to Python/Pip need to select the correct Python version.
**Tip-1**: This project only supports <mark>**Python3.6/3.7/3.8/3.9**</mark>, all subsequent operations related to Python/Pip need to select the correct Python version.
**Tip-2**: The GPU environments in the following examples are all cuda10.2-cudnn7. If you use Python Pipeline to deploy and need Nvidia TensorRT to optimize prediction performance, please refer to [Supported Mirroring Environment and Instructions](#4.-Supported-Docker-Images-and-Instruction) to choose other versions.
......@@ -15,16 +15,16 @@
**CPU:**
```
# Start CPU Docker Container
docker pull paddlepaddle/serving:0.7.0-devel
docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-devel bash
docker pull paddlepaddle/serving:0.8.0-devel
docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.8.0-devel bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
**GPU:**
```
# Start GPU Docker Container
docker pull paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.7.0-cuda10.2-cudnn7-devel bash
docker pull paddlepaddle/serving:0.8.0-cuda10.2-cudnn7-devel
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/serving:0.8.0-cuda10.2-cudnn7-devel bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
```
......@@ -32,8 +32,8 @@ git clone https://github.com/PaddlePaddle/Serving
**CPU:**
```
# Start CPU Docker Container
docker pull paddlepaddle/paddle:2.2.0
docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0 bash
docker pull paddlepaddle/paddle:2.2.2
docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.2 bash
docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
......@@ -43,8 +43,8 @@ bash Serving/tools/paddle_env_install.sh
**GPU:**
```
# Start GPU Docker
docker pull paddlepaddle/paddle:2.2.0-gpu-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.0-gpu-cuda10.2-cudnn7 bash
docker pull paddlepaddle/paddle:2.2.2-gpu-cuda10.2-cudnn7
nvidia-docker run -p 9292:9292 --name test -dit paddlepaddle/paddle:2.2.2-gpu-cuda10.2-cudnn7 bash
nvidia-docker exec -it test bash
git clone https://github.com/PaddlePaddle/Serving
......@@ -60,14 +60,19 @@ cd Serving
pip3 install -r python/requirements.txt
```
Install the service whl package. There are three types of client, app and server. The server is divided into CPU and GPU. Choose one installation according to the environment.
- GPU with CUDA10.2 + Cudnn7 + TensorRT6(Recommended)
```shell
pip3 install paddle-serving-client==0.7.0
pip3 install paddle-serving-server==0.7.0 # CPU
pip3 install paddle-serving-app==0.7.0
pip3 install paddle-serving-server-gpu==0.7.0.post102 #GPU with CUDA10.2 + Cudnn7 + TensorRT6
pip3 install paddle-serving-client==0.8.0
pip3 install paddle-serving-app==0.8.0
# CPU Server
pip3 install paddle-serving-server==0.8.0
pip3 install paddle-serving-server-gpu==0.8.0.post102 #
# Other GPU environments need to confirm the environment before choosing which one to execute
pip3 install paddle-serving-server-gpu==0.7.0.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.7.0.post112 # GPU with CUDA11.2 + TensorRT8
pip3 install paddle-serving-server-gpu==0.8.0.post101 # GPU with CUDA10.1 + TensorRT6
pip3 install paddle-serving-server-gpu==0.8.0.post112 # GPU with CUDA11.2 + TensorRT8
```
If you are in China, You may need to use a chinese mirror source (such as Tsinghua source, add `-i https://pypi.tuna.tsinghua.edu.cn/simple` to the pip command) to speed up the download.
......@@ -76,33 +81,33 @@ If you need to use the installation package compiled by the develop branch, plea
The paddle-serving-server and paddle-serving-server-gpu installation packages support Centos 6/7, Ubuntu 16/18 and Windows 10.
The paddle-serving-client and paddle-serving-app installation packages support Linux and Windows, and paddle-serving-client only supports python3.6/3.7/3.8.
The paddle-serving-client and paddle-serving-app installation packages support Linux and Windows, and paddle-serving-client only supports python3.6/3.7/3.8/3.9.
**If you used the Cuda10.2 environment of paddle serving 0.5.X 0.6.X before, you need to pay attention to version 0.7.0, paddle-serving-server-gpu==0.7.0.post102 uses Cudnn7 and TensorRT6, and 0.6.0.post102 uses cudnn8 and TensorRT7. If 0.6.0 cuda10.2 users need to upgrade, please use paddle-serving-server-gpu==0.7.0.post1028**
**If you used the CUDA10.2 environment of paddle serving 0.5.X 0.6.X before, you need to pay attention to version 0.8.0, paddle-serving-server-gpu==0.8.0.post102 uses Cudnn7 and TensorRT6, and 0.6.0.post102 uses cudnn8 and TensorRT7. If 0.6.0 cuda10.2 users need to upgrade, please use paddle-serving-server-gpu==0.8.0.post1028**
## 3. Install Paddle related Python libraries
**You only need to install it when you use the `paddle_serving_client.convert` command or the `Python Pipeline framework`. **
```
# CPU environment please execute
pip3 install paddlepaddle==2.2.0
pip3 install paddlepaddle==2.2.2
# GPU Cuda10.2 environment please execute
pip3 install paddlepaddle-gpu==2.2.0
# GPU CUDA 10.2 environment please execute
pip3 install paddlepaddle-gpu==2.2.2
```
**Note**: If your Cuda version is not 10.2 or if you want to use TensorRT(Cuda10.2 included), please do not execute the above commands directly, you need to refer to [Paddle-Inference official document-download and install the Linux prediction library](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python) Select the URL link of the corresponding GPU environment and install it. Assuming that you use Python3.6, please follow the codeblock.
**Note**: If your CUDA version is not 10.2 or if you want to use TensorRT(CUDA10.2 included), please do not execute the above commands directly, you need to refer to [Paddle-Inference official document-download and install the Linux prediction library](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python) Select the URL link of the corresponding GPU environment and install it. Assuming that you use Python3.6, please follow the codeblock.
```
# Cuda10.1 + Cudnn7 + TensorRT6
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101-cp36-cp36m-linux_x86_64.whl
# CUDA10.1 + CUDNN7 + TensorRT6
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.2.post101-cp36-cp36m-linux_x86_64.whl
# Cuda10.2 + Cudnn7 + TensorRT6, Attenton that the paddle whl for this env is same to that of Cuda10.1 + Cudnn7 + TensorRT6
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.0.post101-cp36-cp36m-linux_x86_64.whl
# CUDA10.2 + CUDNN7 + TensorRT6, Attenton that the paddle whl for this env is same to that of CUDA10.1 + Cudnn7 + TensorRT6
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.1_cudnn7.6.5_trt6.0.1.5/paddlepaddle_gpu-2.2.2.post101-cp36-cp36m-linux_x86_64.whl
# Cuda10.2 + Cudnn8 + TensorRT7
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.2_cudnn8.1.1_trt7.2.3.4/paddlepaddle_gpu-2.2.0-cp36-cp36m-linux_x86_64.whl
# CUDA10.2 + Cudnn8 + TensorRT7
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda10.2_cudnn8.1.1_trt7.2.3.4/paddlepaddle_gpu-2.2.2-cp36-cp36m-linux_x86_64.whl
# Cuda11.2 + Cudnn8 + TensorRT8
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda11.2_cudnn8.2.1_trt8.0.3.4/paddlepaddle_gpu-2.2.0.post112-cp36-cp36m-linux_x86_64.whl
# CUDA11.2 + CUDNN8 + TensorRT8
pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.2/python/Linux/GPU/x86-64_gcc8.2_avx_mkl_cuda11.2_cudnn8.2.1_trt8.0.3.4/paddlepaddle_gpu-2.2.2.post112-cp36-cp36m-linux_x86_64.whl
```
## 4. Supported Docker Images and Instruction
......@@ -110,10 +115,10 @@ pip3 install https://paddle-inference-lib.bj.bcebos.com/2.2.0/python/Linux/GPU/x
| Environment | Serving Development Image Tag | Operating System | Paddle Development Image Tag | Operating System |
| :--------------------------: | :-------------------------------: | :-------------: | :-------------------: | :----------------: |
| CPU | 0.7.0-devel | Ubuntu 16.04 | 2.2.0 | Ubuntu 18.04. |
| Cuda10.1+Cudnn7 | 0.7.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda10.2+Cudnn7 | 0.7.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| Cuda10.2+Cudnn8 | 0.7.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| Cuda11.2+Cudnn8 | 0.7.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.0-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
| CPU | 0.8.0-devel | Ubuntu 16.04 | 2.2.2 | Ubuntu 18.04. |
| CUDA10.1 + CUDNN7 | 0.8.0-cuda10.1-cudnn7-devel | Ubuntu 16.04 | 无 | 无 |
| CUDA10.2 + CUDNN7 | 0.8.0-cuda10.2-cudnn7-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda10.2-cudnn7 | Ubuntu 16.04 |
| CUDA10.2 + CUDNN8 | 0.8.0-cuda10.2-cudnn8-devel | Ubuntu 16.04 | 无 | 无 |
| CUDA11.2 + CUDNN8 | 0.8.0-cuda11.2-cudnn8-devel | Ubuntu 16.04 | 2.2.2-gpu-cuda11.2-cudnn8 | Ubuntu 18.04 |
For **Windows 10 users**, please refer to the document [Paddle Serving Guide for Windows Platform](Windows_Tutorial_CN.md).
......@@ -17,7 +17,7 @@ Paddle Serving 提供了 Java SDK,支持 Client 端用 Java 语言进行预测
| Paddle Serving Server version | Java SDK version |
| :---------------------------: | :--------------: |
| 0.5.0 | 0.0.1 |
| 0.8.0 | 0.0.1 |
1. 直接使用提供的Java SDK作为Client进行预测
### 安装
......
......@@ -18,7 +18,7 @@ The following table shows compatibilities between Paddle Serving Server and Java
| Paddle Serving Server version | Java SDK version |
| :---------------------------: | :--------------: |
| 0.5.0 | 0.0.1 |
| 0.8.0 | 0.0.1 |
1. Directly use the provided Java SDK as the client for prediction
### Install Java SDK
......
......@@ -6,13 +6,13 @@ Check the following table, and copy the address of hyperlink then run `pip3 inst
| | develop whl | develop bin | stable whl | stable bin |
|---------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------|
| cpu-avx-mkl | [paddle_serving_server-0.0.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl) | [serving-cpu-avx-mkl-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-mkl-0.0.0.tar.gz) | [paddle_serving_server-0.7.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.7.0-py3-none-any.whl) | [serving-cpu-avx-mkl-0.7.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-mkl-0.7.0.tar.gz) |
| cpu-avx-openblas | [paddle_serving_server-0.0.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl) | [serving-cpu-avx-openblas-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-openblas-0.0.0.tar.gz) | [paddle_serving_server-0.7.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.7.0-py3-none-any.whl) | [serving-cpu-avx-openblas-0.7.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-openblas-0.7.0.tar.gz) |
| cpu-noavx-openblas | [paddle_serving_server-0.0.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl) | [ serving-cpu-noavx-openblas-0.0.0.tar.gz ]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-noavx-openblas-0.0.0.tar.gz) | [paddle_serving_server-0.7.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.7.0-py3-none-any.whl) | [ serving-cpu-noavx-openblas-0.7.0.tar.gz ]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-noavx-openblas-0.7.0.tar.gz) |
| cuda10.1-cudnn7-TensorRT6 | [paddle_serving_server_gpu-0.0.0.post101-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post101-py3-none-any.whl) | [serving-gpu-101-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-101-0.0.0.tar.gz) | [paddle_serving_server_gpu-0.7.0.post101-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post101-py3-none-any.whl) | [serving-gpu-101-0.7.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-101-0.7.0.tar.gz) |
| cuda10.2-cudnn7-TensorRT6 | [paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl) | [serving-gpu-102-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-102-0.0.0.tar.gz) | [paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl) | [serving-gpu-102-0.7.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-102-0.7.0.tar.gz) |
| cuda10.2-cudnn8-TensorRT7 | [paddle_serving_server_gpu-0.0.0.post1028-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl) | [ serving-gpu-1028-0.0.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-1028-0.0.0.tar.gz ) | [paddle_serving_server_gpu-0.7.0.post1028-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post102-py3-none-any.whl) | [ serving-gpu-1028-0.7.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-1028-0.7.0.tar.gz ) |
| cuda11.2-cudnn8-TensorRT8 | [paddle_serving_server_gpu-0.0.0.post112-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post112-py3-none-any.whl) | [ serving-gpu-112-0.0.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-112-0.0.0.tar.gz ) | [paddle_serving_server_gpu-0.7.0.post112-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.7.0.post112-py3-none-any.whl) | [ serving-gpu-112-0.7.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-112-0.7.0.tar.gz ) |
| cpu-avx-mkl | [paddle_serving_server-0.0.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl) | [serving-cpu-avx-mkl-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-mkl-0.0.0.tar.gz) | [paddle_serving_server-0.8.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.8.0-py3-none-any.whl) | [serving-cpu-avx-mkl-0.8.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-mkl-0.8.0.tar.gz) |
| cpu-avx-openblas | [paddle_serving_server-0.0.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl) | [serving-cpu-avx-openblas-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-openblas-0.0.0.tar.gz) | [paddle_serving_server-0.8.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.8.0-py3-none-any.whl) | [serving-cpu-avx-openblas-0.8.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-avx-openblas-0.8.0.tar.gz) |
| cpu-noavx-openblas | [paddle_serving_server-0.0.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.0.0-py3-none-any.whl) | [ serving-cpu-noavx-openblas-0.0.0.tar.gz ]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-noavx-openblas-0.0.0.tar.gz) | [paddle_serving_server-0.8.0-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server-0.8.0-py3-none-any.whl) | [ serving-cpu-noavx-openblas-0.8.0.tar.gz ]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-cpu-noavx-openblas-0.8.0.tar.gz) |
| cuda10.1-cudnn7-TensorRT6 | [paddle_serving_server_gpu-0.0.0.post101-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post101-py3-none-any.whl) | [serving-gpu-101-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-101-0.0.0.tar.gz) | [paddle_serving_server_gpu-0.8.0.post101-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.8.0.post101-py3-none-any.whl) | [serving-gpu-101-0.8.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-101-0.8.0.tar.gz) |
| cuda10.2-cudnn7-TensorRT6 | [paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl) | [serving-gpu-102-0.0.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-102-0.0.0.tar.gz) | [paddle_serving_server_gpu-0.8.0.post102-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.8.0.post102-py3-none-any.whl) | [serving-gpu-102-0.8.0.tar.gz](https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-102-0.8.0.tar.gz) |
| cuda10.2-cudnn8-TensorRT7 | [paddle_serving_server_gpu-0.0.0.post1028-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post102-py3-none-any.whl) | [ serving-gpu-1028-0.0.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-1028-0.0.0.tar.gz ) | [paddle_serving_server_gpu-0.8.0.post1028-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.8.0.post102-py3-none-any.whl) | [ serving-gpu-1028-0.8.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-1028-0.8.0.tar.gz ) |
| cuda11.2-cudnn8-TensorRT8 | [paddle_serving_server_gpu-0.0.0.post112-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.0.0.post112-py3-none-any.whl) | [ serving-gpu-112-0.0.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-112-0.0.0.tar.gz ) | [paddle_serving_server_gpu-0.8.0.post112-py3-none-any.whl ](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_server_gpu-0.8.0.post112-py3-none-any.whl) | [ serving-gpu-112-0.8.0.tar.gz]( https://paddle-serving.bj.bcebos.com/test-dev/bin/serving-gpu-112-0.8.0.tar.gz ) |
### Binary Package
for most users, we do not need to read this section. But if you deploy your Paddle Serving on a machine without network, you will encounter a problem that the binary executable tar file cannot be downloaded. Therefore, here we give you all the download links for various environment.
......@@ -27,15 +27,15 @@ for most users, we do not need to read this section. But if you deploy your Padd
| | develop whl | stable whl |
|-----------------------|--------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------|
| Python3.6 | [paddle_serving_client-0.0.0-cp36-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp36-none-any.whl) | [paddle_serving_client-0.7.0-cp36-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.7.0-cp36-none-any.whl)) |
| Python3.7 | [paddle_serving_client-0.0.0-cp37-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp37-none-any.whl) | [paddle_serving_client-0.7.0-cp37-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.7.0-cp37-none-any.whl) |
| Python3.8 | [paddle_serving_client-0.0.0-cp38-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp38-none-any.whl) | [paddle_serving_client-0.7.0-cp38-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.7.0-cp38-none-any.whl) |
| Python3.6 | [paddle_serving_client-0.0.0-cp36-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp36-none-any.whl) | [paddle_serving_client-0.8.0-cp36-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.8.0-cp36-none-any.whl) |
| Python3.7 | [paddle_serving_client-0.0.0-cp37-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp37-none-any.whl) | [paddle_serving_client-0.8.0-cp37-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.8.0-cp37-none-any.whl) |
| Python3.8 | [paddle_serving_client-0.0.0-cp38-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp38-none-any.whl) | [paddle_serving_client-0.8.0-cp38-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.8.0-cp38-none-any.whl) |
| Python3.9 | [paddle_serving_client-0.0.0-cp39-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.0.0-cp39-none-any.whl) | [paddle_serving_client-0.8.0-cp39-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_client-0.8.0-cp38-none-any.whl) |
## paddle-serving-app
| | develop whl | stable whl |
|---------|------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------|
| Python3 | [paddle_serving_app-0.0.0-py3-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.0.0-py3-none-any.whl) | [ paddle_serving_app-0.7.0-py3-none-any.whl ]( https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.7.0-py3-none-any.whl) |
| Python3 | [paddle_serving_app-0.0.0-py3-none-any.whl](https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.0.0-py3-none-any.whl) | [ paddle_serving_app-0.8.0-py3-none-any.whl ]( https://paddle-serving.bj.bcebos.com/test-dev/whl/paddle_serving_app-0.8.0-py3-none-any.whl) |
## Baidu Kunlun user
......@@ -59,9 +59,9 @@ https://paddle-serving.bj.bcebos.com/bin/serving-xpu-aarch64-0.0.0.tar.gz
for x86 kunlun user
```
https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_server_xpu-0.7.0.post2-cp36-cp36m-linux_x86_64.whl
https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_client-0.7.0-cp36-cp36m-linux_x86_64.whl
https://paddle-serving.bj.bcebos.com/whl/xpu/0.7.0/paddle_serving_app-0.7.0-cp36-cp36m-linux_x86_64.whl
https://paddle-serving.bj.bcebos.com/whl/xpu/0.8.0/paddle_serving_server_xpu-0.8.0.post2-cp36-cp36m-linux_x86_64.whl
https://paddle-serving.bj.bcebos.com/whl/xpu/0.8.0/paddle_serving_client-0.8.0-cp36-cp36m-linux_x86_64.whl
https://paddle-serving.bj.bcebos.com/whl/xpu/0.8.0/paddle_serving_app-0.8.0-cp36-cp36m-linux_x86_64.whl
```
......@@ -26,7 +26,7 @@ kubectl apply -f https://bit.ly/kong-ingress-dbless
我们提供了运行镜像的生成脚本在Serving代码库下`tools/generate_runtime_docker.sh`文件,通过以下命令可生成代码。
```bash
bash tools/generate_runtime_docker.sh --env cuda10.1 --python 3.7 --image_name serving_runtime:cuda10.1-py37 --paddle 2.2.0 --serving 0.7.0
bash tools/generate_runtime_docker.sh --env cuda10.1 --python 3.7 --image_name serving_runtime:cuda10.1-py37 --paddle 2.2.0 --serving 0.8.0
```
会生成 cuda10.1,python 3.7,serving版本0.7.0 还有 paddle版本2.2.0的运行镜像。如果有其他疑问,可以执行下列语句得到帮助信息。强烈建议您使用最新的paddle和serving的版本(2个版本是对应的如paddle 2.2.x 与serving 0.7.0对应,paddle 2.1.x 与 serving 0.6.x对应),因为更早的版本上出现的错误只在最新版本修复,无法在历史版本中修复。
......@@ -84,8 +84,8 @@ python3.6 web_service.py
web service模式本质上和pipeline模式类似,因此我们以`Serving/examples/C++/PaddleNLP/bert`为例
```bash
#假设您已经拥有Serving运行镜像,假设镜像名为registry.baidubce.com/paddlepaddle/serving:0.7.0-cpu-py36
docker run --rm -dit --name webservice_serving_demo registry.baidubce.com/paddlepaddle/serving:0.7.0-cpu-py36 bash
#假设您已经拥有Serving运行镜像,假设镜像名为registry.baidubce.com/paddlepaddle/serving:0.8.0-cpu-py36
docker run --rm -dit --name webservice_serving_demo registry.baidubce.com/paddlepaddle/serving:0.8.0-cpu-py36 bash
cd Serving/examples/C++/PaddleNLP/bert
### download model
wget https://paddle-serving.bj.bcebos.com/paddle_hub_models/text/SemanticModel/bert_chinese_L-12_H-768_A-12.tar.gz
......
......@@ -8,9 +8,9 @@ function usage
echo "usage: sh tools/generate_runtime_docker.sh --SOME_ARG ARG_VALUE"
echo " ";
echo " --env : running env, cpu/cuda10.1/cuda10.2/cuda11.2";
echo " --python : python version, 3.6/3.7/3.8 ";
echo " --serving : serving version(0.7.0/0.6.2)";
echo " --paddle : paddle version(2.2.0/2.1.2)"
echo " --python : python version, 3.6/3.7/3.8/3.9 ";
echo " --serving : serving version(v0.8.0/0.7.0)";
echo " --paddle : paddle version(2.2.2/2.2.0)"
echo " --image_name : image name(default serving_runtime:env-python)"
echo " -h | --help : helper";
}
......
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