diff --git a/doc/JAVA_SDK.md b/doc/JAVA_SDK.md new file mode 100644 index 0000000000000000000000000000000000000000..ffec81c7c0e7435e91faa5aa5b0fe05d3d143837 --- /dev/null +++ b/doc/JAVA_SDK.md @@ -0,0 +1,94 @@ +# Paddle Serving Client Java SDK + +([简体中文](JAVA_SDK_CN.md)|English) + +Paddle Serving provides Java SDK,which supports predict on the Client side with Java language. This document shows how to use the Java SDK. + +## Getting started + +### Prerequisites + +``` +- Java 8 or higher +- Apache Maven +``` + +The following table shows compatibilities between Paddle Serving Server and Java SDK. + +| Paddle Serving Server version | Java SDK version | +| :---------------------------: | :--------------: | +| 0.3.2 | 0.0.1 | + +### Install Java SDK + +You can use Apache Maven to download the SDK. + +```shell + + io.paddle.serving.client + paddle-serving-sdk-java + 0.0.1 + +``` + + + +## Example + +Here we will show how to use Java SDK for Boston house price prediction. Please refer to [examples](../java/examples) folder for more examples. + +### Get model + +```shell +wget --no-check-certificate https://paddle-serving.bj.bcebos.com/uci_housing.tar.gz +tar -xzf uci_housing.tar.gz +``` + +### Start Python Server + +```shell +python -m paddle_serving_server.serve --model uci_housing_model --port 9393 --use_multilang +``` + +#### Client side code example + +```java +import io.paddle.serving.client.*; +import org.nd4j.linalg.api.ndarray.INDArray; +import org.nd4j.linalg.factory.Nd4j; +import java.util.*; + +public class PaddleServingClientExample { + public static void main( String[] args ) { + float[] data = {0.0137f, -0.1136f, 0.2553f, -0.0692f, + 0.0582f, -0.0727f, -0.1583f, -0.0584f, + 0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f}; + INDArray npdata = Nd4j.createFromArray(data); + HashMap feed_data + = new HashMap() {{ + put("x", npdata); + }}; + List fetch = Arrays.asList("price"); + + Client client = new Client(); + String target = "localhost:9393"; + boolean succ = client.connect(target); + if (succ != true) { + System.out.println("connect failed."); + return ; + } + + Map fetch_map = client.predict(feed_data, fetch); + if (fetch_map == null) { + System.out.println("predict failed."); + return ; + } + + for (Map.Entry e : fetch_map.entrySet()) { + System.out.println("Key = " + e.getKey() + ", Value = " + e.getValue()); + } + return ; + } +} +``` + diff --git a/doc/JAVA_SDK_CN.md b/doc/JAVA_SDK_CN.md new file mode 100644 index 0000000000000000000000000000000000000000..34ff232ebf97c0701226c9d6fac8cbe34e8e9192 --- /dev/null +++ b/doc/JAVA_SDK_CN.md @@ -0,0 +1,95 @@ +# Paddle Serving Client Java SDK + +(简体中文|[English](JAVA_SDK.md)) + +Paddle Serving 提供了 Java SDK,支持 Client 端用 Java 语言进行预测,本文档说明了如何使用 Java SDK。 + + + +## 快速开始 + +### 环境要求 + +``` +- Java 8 or higher +- Apache Maven +``` + +下表显示了 Paddle Serving Server 和 Java SDK 之间的兼容性 + +| Paddle Serving Server version | Java SDK version | +| :---------------------------: | :--------------: | +| 0.3.2 | 0.0.1 | + +### 安装 + +您可以使用 Apache Maven 下载该 SDK。 + +```shell + + io.paddle.serving.client + paddle-serving-sdk-java + 0.0.1 + +``` + + +## 使用样例 + +这里将展示如何使用 Java SDK 进行房价预测,更多例子详见 [examples](../java/examples) 文件夹。 + +### 获取房价预测模型 + +```shell +wget --no-check-certificate https://paddle-serving.bj.bcebos.com/uci_housing.tar.gz +tar -xzf uci_housing.tar.gz +``` + +### 启动 Python 端 Server + +```shell +python -m paddle_serving_server.serve --model uci_housing_model --port 9393 --use_multilang +``` + +### Client 端代码示例 + +```java +import io.paddle.serving.client.*; +import org.nd4j.linalg.api.ndarray.INDArray; +import org.nd4j.linalg.factory.Nd4j; +import java.util.*; + +public class PaddleServingClientExample { + public static void main( String[] args ) { + float[] data = {0.0137f, -0.1136f, 0.2553f, -0.0692f, + 0.0582f, -0.0727f, -0.1583f, -0.0584f, + 0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f}; + INDArray npdata = Nd4j.createFromArray(data); + HashMap feed_data + = new HashMap() {{ + put("x", npdata); + }}; + List fetch = Arrays.asList("price"); + + Client client = new Client(); + String target = "localhost:9393"; + boolean succ = client.connect(target); + if (succ != true) { + System.out.println("connect failed."); + return ; + } + + Map fetch_map = client.predict(feed_data, fetch); + if (fetch_map == null) { + System.out.println("predict failed."); + return ; + } + + for (Map.Entry e : fetch_map.entrySet()) { + System.out.println("Key = " + e.getKey() + ", Value = " + e.getValue()); + } + return ; + } +} +``` +