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# serving
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#### Description
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A flexible, high-performance serving system for deep learning models
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#### Software Architecture
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Software architecture description
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#### Installation
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#### Instructions
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#### Contribution
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1. Fork the repository
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2. Create Feat_xxx branch
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3. Commit your code
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4. Create Pull Request
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#### Gitee Feature
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1. You can use Readme\_XXX.md to support different languages, such as Readme\_en.md, Readme\_zh.md
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2. Gitee blog [blog.gitee.com](https://blog.gitee.com)
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3. Explore open source project [https://gitee.com/explore](https://gitee.com/explore)
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4. The most valuable open source project [GVP](https://gitee.com/gvp)
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5. The manual of Gitee [https://gitee.com/help](https://gitee.com/help)
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6. The most popular members [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)
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# serving
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# 基于MindSpore部署预测服务
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#### 介绍
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A flexible, high-performance serving system for deep learning models
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#### 软件架构
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软件架构说明
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#### 安装教程
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<!-- TOC -->
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- [基于MindSpore部署预测服务](#基于mindspore部署预测服务)
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- [概述](#概述)
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- [启动Serving服务](#启动serving服务)
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3. xxxx
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- [应用示例](#应用示例)
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- [导出模型](#导出模型)
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#### 使用说明
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- [启动Serving推理服务](#启动serving推理服务)
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- [客户端示例](#客户端示例)
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#### 参与贡献
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1. Fork 本仓库
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2. 新建 Feat_xxx 分支
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3. 提交代码
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4. 新建 Pull Request
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#### 码云特技
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## 概述
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MindSpore Serving是一个轻量级、高性能的服务模块，旨在帮助MindSpore开发者在生产环境中高效部署在线预测服务。当用户使用MindSpore完成模型训练后，导出MindSpore模型，即可使用MindSpore Serving创建该模型的预测服务。当前Serving仅支持Ascend 910。
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## 启动Serving服务
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通过pip安装MindSpore后，Serving可执行程序位于`/{your python path}/lib/python3.7/site-packages/mindspore/ms_serving` 。
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启动Serving服务命令如下
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```bash
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ms_serving [--help] [--model_path <MODEL_PATH>] [--model_name <MODEL_NAME>]
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[--port <PORT>] [--device_id <DEVICE_ID>]
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```
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参数含义如下
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|参数名|属性|功能描述|参数类型|默认值|取值范围|
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|`--help`|可选|显示启动命令的帮助信息。|-|-|-|
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|`--model_path <MODEL_PATH>`|必选|指定待加载模型的存放路径。|str|空|-|
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|`--model_name <MODEL_NAME>`|必选|指定待加载模型的文件名。|str|空|-|
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|`--port <PORT>`|可选|指定Serving对外的端口号。|int|5500|1~65535|
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|`--device_id <DEVICE_ID>`|可选|指定使用的设备号|int|0|0~7|
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> 执行启动命令前，需将`/{your python path}/lib:/{your python path}/lib/python3.7/site-packages/mindspore/lib`对应的路径加入到环境变量LD_LIBRARY_PATH中 。
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## 应用示例
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下面以一个简单的网络为例，演示MindSpore Serving如何使用。
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### 导出模型
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使用[add_model.py](https://gitee.com/mindspore/mindspore/blob/master/serving/example/export_model/add_model.py)，构造一个只有Add算子的网络，并导出MindSpore推理部署模型。
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```python
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python add_model.py
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```
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执行脚本，生成add.pb文件，该模型的输入为两个shape为[4]的一维Tensor，输出结果是两个输入Tensor之和。
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### 启动Serving推理服务
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```bash
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ms_serving --model_path={current path} --model_name=add.pb
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```
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当服务端打印日志`MS Serving Listening on 0.0.0.0:5500`时，表示Serving服务已加载推理模型完毕。
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### 客户端示例
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执行如下命令，编译一个客户端示例程序，并向Serving服务发送推理请求。
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```bash
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cd mindspore/serving/example/cpp_client
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mkdir build
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cmake ..
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make
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./ms_client --target=localhost:5500
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```
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显示如下返回值说明Serving服务已正确执行Add网络的推理。
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```
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Compute [1, 2, 3, 4] + [1, 2, 3, 4]
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Add result is [2, 4, 6, 8]
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client received: RPC OK
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```
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> 编译客户端要求用户本地已安装c++版本的[gRPC](https://gRPC.io)，并将对应路径加入到环境变量`PATH`中。
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客户端代码主要包含以下几个部分：
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1. 基于MSService::Stub实现Client，并创建Client实例。
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```
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class MSClient {
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public:
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explicit MSClient(std::shared_ptr<Channel> channel) : stub_(MSService::NewStub(channel)) {}
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private:
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std::unique_ptr<MSService::Stub> stub_;
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};MSClient client(grpc::CreateChannel(target_str, grpc::InsecureChannelCredentials()));
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MSClient client(grpc::CreateChannel(target_str, grpc::InsecureChannelCredentials()));
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```
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2. 根据网络的实际输入构造请求的入参Request、出参Reply和gRPC的客户端Context。
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```
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PredictRequest request;
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PredictReply reply;
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ClientContext context;
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//construct tensor
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Tensor data;
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//set shape
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TensorShape shape;
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shape.add_dims(4);
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*data.mutable_tensor_shape() = shape;
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//set type
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data.set_tensor_type(ms_serving::MS_FLOAT32);
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std::vector<float> input_data{1, 2, 3, 4};
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//set datas
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data.set_data(input_data.data(), input_data.size());
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//add tensor to request
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*request.add_data() = data;
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*request.add_data() = data;
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```
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3. 调用gRPC接口和已经启动的Serving服务通信，并取回返回值。
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```
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Status status = stub_->Predict(&context, request, &reply);
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```
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完整代码参考[ms_client](https://gitee.com/mindspore/mindspore/blob/master/serving/example/cpp_client/ms_client.cc)。
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1. 使用 Readme\_XXX.md 来支持不同的语言，例如 Readme\_en.md, Readme\_zh.md
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2. 码云官方博客 [blog.gitee.com](https://blog.gitee.com)
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3. 你可以 [https://gitee.com/explore](https://gitee.com/explore) 这个地址来了解码云上的优秀开源项目
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4. [GVP](https://gitee.com/gvp) 全称是码云最有价值开源项目，是码云综合评定出的优秀开源项目
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5. 码云官方提供的使用手册 [https://gitee.com/help](https://gitee.com/help)
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6. 码云封面人物是一档用来展示码云会员风采的栏目 [https://gitee.com/gitee-stars/](https://gitee.com/gitee-stars/)
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