add java mutil-thread client and add annotation

java/README.md

@@ -91,7 +91,7 @@ as for input data type = INDArray，take uci_housing_model as an example，the s
 ```
 cd ../../python/examples/pipeline/simple_web_service
 sh get_data.sh
-python web_service_forJava.py &>log.txt &
+python web_service_java.py &>log.txt &
 ```
 
 Client prediction(Synchronous)

java/README_CN.md

@@ -93,7 +93,7 @@ java -cp paddle-serving-sdk-java-examples-0.0.1-jar-with-dependencies.jar Pipeli
 ```
 cd ../../python/examples/pipeline/simple_web_service
 sh get_data.sh
-python web_service_forJava.py &>log.txt &
+python web_service_java.py &>log.txt &
 ```
 
 客户端预测(同步)

java/examples/src/main/java/PipelineClientExample.java

@@ -10,8 +10,18 @@ import org.nd4j.linalg.api.ops.DynamicCustomOp;
 import org.nd4j.linalg.factory.Nd4j;
 import java.util.*;
 
+/**
+* this class give an example for using the client to predict(grpc)
+* StaticPipelineClient.client supports mutil-thread.
+* By setting StaticPipelineClient.client properties，you can change the Maximum concurrency
+* Do not need to generate multiple instances of client,Use the StaticPipelineClient.client or SingleTon instead.
+* @author HexToString
+*/
 public class PipelineClientExample {
 
+    /**
+   * This method gives an example of synchronous prediction whose input type is string.
+   */
     boolean string_imdb_predict() {
         HashMap<String, String> feed_data
             = new HashMap<String, String>() {{
@@ -20,15 +30,14 @@ public class PipelineClientExample {
         System.out.println(feed_data);
         List<String> fetch = Arrays.asList("prediction");
         System.out.println(fetch);
-        PipelineClient client = new PipelineClient();
-        String target = "172.17.0.2:18070";
-        boolean succ = client.connect(target);
-        if (succ != true) {
+        
+        if (StaticPipelineClient.succ != true) {
+            if(!StaticPipelineClient.initClient("172.17.0.2","18070")){
                 System.out.println("connect failed.");
                 return false;
             }
-
-        HashMap<String,String> result = client.predict(feed_data, fetch,false,0);
+        }
+        HashMap<String,String> result = StaticPipelineClient.client.predict(feed_data, fetch,false,0);
         if (result == null) {
             return false;
         }
@@ -36,6 +45,9 @@ public class PipelineClientExample {
         return true;
     }
 
+    /**
+   * This method gives an example of asynchronous prediction whose input type is string.
+   */
     boolean asyn_predict() {
         HashMap<String, String> feed_data
             = new HashMap<String, String>() {{
@@ -44,14 +56,13 @@ public class PipelineClientExample {
         System.out.println(feed_data);
         List<String> fetch = Arrays.asList("prediction");
         System.out.println(fetch);
-        PipelineClient client = new PipelineClient();
-        String target = "172.17.0.2:18070";
-        boolean succ = client.connect(target);
-        if (succ != true) {
+        if (StaticPipelineClient.succ != true) {
+            if(!StaticPipelineClient.initClient("172.17.0.2","18070")){
                 System.out.println("connect failed.");
                 return false;
             }
-        PipelineFuture future = client.asyn_predict(feed_data, fetch,false,0);
+        }
+        PipelineFuture future = StaticPipelineClient.client.asyn_pr::qedict(feed_data, fetch,false,0);
         HashMap<String,String> result = future.get();
         if (result == null) {
             return false;
@@ -60,24 +71,28 @@ public class PipelineClientExample {
         return true;
     }
 
+    /**
+   * This method gives an example of synchronous prediction whose input type is Array or list or matrix.
+   * use Nd4j.createFromArray method to convert Array to INDArray.
+   * use convertINDArrayToString method to convert INDArray to specified String type(for python Numpy eval method).
+   */
     boolean indarray_predict() {
         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<String, String> feed_data
             = new HashMap<String, String>() {{
-                put("x", "array("+npdata.toString()+")");
+                put("x", convertINDArrayToString(npdata));
             }};
         List<String> fetch = Arrays.asList("prediction");
-        PipelineClient client = new PipelineClient();
-        String target = "172.17.0.2:9998";
-        boolean succ = client.connect(target);
-        if (succ != true) {
+        if (StaticPipelineClient.succ != true) {
+            if(!StaticPipelineClient.initClient("172.17.0.2","9998")){
                 System.out.println("connect failed.");
                 return false;
             }
+        }
 
-        HashMap<String,String> result = client.predict(feed_data, fetch,false,0);
+        HashMap<String,String> result = StaticPipelineClient.client.predict(feed_data, fetch,false,0);
         if (result == null) {
             return false;
         }
@@ -85,8 +100,20 @@ public class PipelineClientExample {
         return true;
     }
 
-    public static void main( String[] args ) {
+    /**
+   * This method convert INDArray to specified String type.
+   * @param npdata INDArray type(The input data).
+   * @return String (specified String type for python Numpy eval method).
+   */
+    String convertINDArrayToString(INDArray npdata){
+        return "array("+npdata.toString()+")";
+    }
 
+    /**
+   * This method is entry function.
+   * @param args String[] type(Command line parameters)
+   */
+    public static void main( String[] args ) {
 
         PipelineClientExample e = new PipelineClientExample();
         boolean succ = false;
@@ -95,6 +122,7 @@ public class PipelineClientExample {
             System.out.println("<test-type>: fit_a_line bert model_ensemble asyn_predict batch_predict cube_local cube_quant yolov4");
             return;
         }
+        
         String testType = args[0];
         System.out.format("[Example] %s\n", testType);
         if ("string_imdb_predict".equals(testType)) {
@@ -114,12 +142,6 @@ public class PipelineClientExample {
             System.out.println("[Example] fail.");
         }
     }
-
-
 }
-//if list or array or matrix,please Convert to INDArray,for example:
-//INDArray npdata = Nd4j.createFromArray(data);
 
-//INDArray Convert to String,for example:
-//string value = "array("+npdata.toString()+")"
 

java/examples/src/main/java/StaticPipelineClient.java

+import io.paddle.serving.pipelineclient.*;
+import java.io.File;
+import java.io.IOException;
+import java.net.URL;
+import org.nd4j.linalg.api.iter.NdIndexIterator;
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.datavec.image.loader.NativeImageLoader;
+import org.nd4j.linalg.api.ops.CustomOp;
+import org.nd4j.linalg.api.ops.DynamicCustomOp;
+import org.nd4j.linalg.factory.Nd4j;
+import java.util.*;
+
+/**
+* static resource management class
+* @author HexToString
+*/
+public class StaticPipelineClient {
+    /**
+     * Static Variable PipelineClient
+     */
+    public static PipelineClient client = new PipelineClient();
+    /**
+     * the sign of connect status
+     */
+    public static boolean succ = false;
+
+    /**
+   * This method returns the sign of connect status.
+   * @param strIp String type(The server ipv4) such as "192.168.10.10".
+   * @param strPort String type(The server port) such as "8891".
+   * @return boolean (the sign of connect status).
+   */
+    public static boolean initClient(String strIp,String strPort){
+        String target = strIp+ ":"+ strPort;//"172.17.0.2:18070";
+        System.out.println("initial connect.");
+        if(succ){
+            System.out.println("already connect.");
+            return true;
+        }
+        succ = clieint.connect(target);
+        if (succ != true) {
+            System.out.println("connect failed.");
+            return false;
+        }
+        return true;
+    }
+}
+

java/src/main/java/io/paddle/serving/client/PipelineClient.java

@@ -19,6 +19,11 @@ import org.nd4j.linalg.factory.Nd4j;
 import io.paddle.serving.pipelineproto.*;
 import io.paddle.serving.pipelineclient.PipelineFuture;
 
+
+/**
+* PipelineClient class defination
+* @author HexToString
+*/
 public class PipelineClient {
     private ManagedChannel channel_;
     private PipelineServiceGrpc.PipelineServiceBlockingStub blockingStub_;
@@ -38,6 +43,11 @@ public class PipelineClient {
         _profile_key = "pipeline.profile";
     }
     
+    /**
+   * This method returns the sign of connect status.
+   * @param target String type(The server ipv4 and port) such as "192.168.10.10:8891".
+   * @return boolean (the sign of connect status).
+   */
     public boolean connect(String target) {
         try {
             String[] temp = target.split(":");
@@ -56,6 +66,13 @@ public class PipelineClient {
         return true;
     }
 
+    /**
+   * This method returns the Packaged Request.
+   * @param feed_dict HashMap<String, String>(input data).
+   * @param profile boolean(profile sign).
+   * @param logid int
+   * @return Request (the grpc protobuf Request).
+   */
     private Request _packInferenceRequest(
             HashMap<String, String> feed_dict,
             boolean profile,
@@ -80,11 +97,20 @@ public class PipelineClient {
         return req_builder.build();
     }
 
-
+    /**
+   * This method returns the HashMap which is unpackaged from Response.
+   * @param resp Response(the grpc protobuf Response).
+   * @return HashMap<String,String> (the output).
+   */
     private HashMap<String,String> _unpackResponse(Response resp) throws IllegalArgumentException{
         return PipelineClient._staitcUnpackResponse(resp);
     }
 
+    /**
+   * This static method returns the HashMap which is unpackaged from Response.
+   * @param resp Response(the grpc protobuf Response).
+   * @return HashMap<String,String> (the output).
+   */
     private static HashMap<String,String> _staitcUnpackResponse(Response resp) {
         HashMap<String,String> ret_Map = new HashMap<String,String>();
         int err_no  = resp.getErrNo();
@@ -99,6 +125,14 @@ public class PipelineClient {
         return ret_Map;
     }
 
+    /**
+   * The synchronous prediction method.
+   * @param feed_batch HashMap<String, String>(input data).
+   * @param fetch Iterable<String>(the output key list).
+   * @param profile boolean(profile sign).
+   * @param logid int
+   * @return HashMap<String,String> (the output).
+   */
     public HashMap<String,String> predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch,
@@ -115,12 +149,18 @@ public class PipelineClient {
         }
     }
 
+    /**
+   * The synchronous prediction overload function.
+   */
     public HashMap<String,String> predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch) {
                 return predict(feed_batch,fetch,false,0);
     }
 
+    /**
+   * The synchronous prediction overload function.
+   */
     public HashMap<String,String> predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch,
@@ -128,6 +168,9 @@ public class PipelineClient {
                 return predict(feed_batch,fetch,profile,0);
     }
 
+    /**
+   * The synchronous prediction overload function.
+   */
     public HashMap<String,String> predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch,
@@ -135,6 +178,14 @@ public class PipelineClient {
                 return predict(feed_batch,fetch,false,logid);
     }
 
+    /**
+   * The asynchronous prediction method.use future.get() to get the result.
+   * @param feed_batch HashMap<String, String>(input data).
+   * @param fetch Iterable<String>(the output key list).
+   * @param profile boolean(profile sign).
+   * @param logid int
+   * @return PipelineFuture(the output future). 
+   */
     public PipelineFuture asyn_predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch,
@@ -151,12 +202,18 @@ public class PipelineClient {
         return predict_future;
     }
 
+    /**
+   * The asynchronous prediction overload function.
+   */
     public PipelineFuture asyn_predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch) {
                 return asyn_predict(feed_batch,fetch,false,0);
     }
 
+    /**
+   * The asynchronous prediction overload function.
+   */
     public PipelineFuture asyn_predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch,
@@ -164,6 +221,9 @@ public class PipelineClient {
                 return asyn_predict(feed_batch,fetch,profile,0);
     }
 
+    /**
+   * The asynchronous prediction overload function.
+   */
     public PipelineFuture asyn_predict(
             HashMap<String, String> feed_batch,
             Iterable<String> fetch,

java/src/main/java/io/paddle/serving/client/PipelineFuture.java

@@ -9,6 +9,10 @@ import org.nd4j.linalg.api.ndarray.INDArray;
 import io.paddle.serving.pipelineclient.PipelineClient;
 import io.paddle.serving.pipelineproto.*;
 
+/**
+* PipelineFuture class is for asynchronous prediction
+* @author HexToString
+*/
 public class PipelineFuture {
     private ListenableFuture<Response> callFuture_;
     private Function<Response, 
@@ -21,6 +25,9 @@ public class PipelineFuture {
         callBackFunc_ = call_back_func;
     }
 
+    /**
+    * use this method to get the result of asynchronous prediction.
+    */
     public HashMap<String,String> get() {
         Response resp = null;
         try {