[WIP] use INDArray

java/paddle-serving-sdk-java/pom.xml

@@ -56,6 +56,8 @@
         <grpc.version>1.27.2</grpc.version>
         <protobuf.version>3.11.0</protobuf.version>
         <protoc.version>3.11.0</protoc.version>
+        <nd4j.backend>nd4j-native</nd4j.backend>
+        <nd4j.version>1.0.0-beta7</nd4j.version>
         <maven.compiler.source>1.8</maven.compiler.source>
         <maven.compiler.target>1.8</maven.compiler.target>
     </properties>
@@ -144,6 +146,11 @@
             <artifactId>log4j-slf4j-impl</artifactId>
             <version>2.12.1</version>
         </dependency>
+        <dependency>
+            <groupId>org.nd4j</groupId>
+            <artifactId>${nd4j.backend}</artifactId>
+            <version>${nd4j.version}</version>
+        </dependency>
 
     </dependencies>
 

java/paddle-serving-sdk-java/src/main/java/io/paddle/serving/client/Client.java

@@ -11,6 +11,9 @@ import com.google.common.util.concurrent.FutureCallback;
 import com.google.common.util.concurrent.Futures;
 import com.google.common.util.concurrent.ListenableFuture;
 
+import org.nd4j.linalg.api.ndarray.INDArray;
+import org.nd4j.linalg.factory.Nd4j;
+
 import io.paddle.serving.grpc.*;
 import io.paddle.serving.configure.*;
 
@@ -140,13 +143,8 @@ public class Client {
         }
     }
 
-    private List<? extends Number> _flattenList(List<? extends Number> x) {
-        // TODO
-        return x;
-    }
-
     private InferenceRequest _packInferenceRequest(
-            List<Map<String, List<? extends Number>>> feed_batch,
+            List<Map<String, INDArray>> feed_batch,
             Iterable<String> fetch) throws IllegalArgumentException {
         List<String> feed_var_names = new ArrayList<String>();
         feed_var_names.addAll(feed_batch.get(0).keySet());
@@ -155,24 +153,24 @@ public class Client {
             .addAllFeedVarNames(feed_var_names)
             .addAllFetchVarNames(fetch)
             .setIsPython(false);
-        for (Map<String, List<? extends Number>> feed_data: feed_batch) {
+        for (Map<String, INDArray> feed_data: feed_batch) {
             FeedInst.Builder inst_builder = FeedInst.newBuilder();
             for (String name: feed_var_names) {
                 Tensor.Builder tensor_builder = Tensor.newBuilder();
-                List<? extends Number> variable = feed_data.get(name);
-                List<? extends Number> flattened_list = _flattenList(variable);
+                INDArray variable = feed_data.get(name);
+                INDArray flattened_list = variable.reshape({-1});
                 int v_type = feedTypes_.get(name);
                 if (v_type == 0) { // int64
-                    for (Number x: flattened_list) {
-                        tensor_builder.addInt64Data((long)x);
+                    for (long x: flattened_list) {
+                        tensor_builder.addInt64Data(x);
                     }
                 } else if (v_type == 1) { // float32
-                    for (Number x: flattened_list) {
-                        tensor_builder.addFloatData((float)x);
+                    for (float x: flattened_list) {
+                        tensor_builder.addFloatData(x);
                     }
                 } else if (v_type == 2) { // int32
-                    for (Number x: flattened_list) {
-                        tensor_builder.addIntData((int)x);
+                    for (int x: flattened_list) {
+                        tensor_builder.addIntData(x);
                     }
                 } else {
                     throw new IllegalArgumentException("error tensor value type.");
@@ -185,7 +183,7 @@ public class Client {
         return req_builder.build();
     }
 
-    private Map<String, ? extends Map<String, List<? extends Number>>>
+    private Map<String, ? extends Map<String, INDArray>>
         _unpackInferenceResponse(
             InferenceResponse resp,
             Iterable<String> fetch,
@@ -194,7 +192,7 @@ public class Client {
                 resp, fetch, fetchTypes_, lodTensorSet_, need_variant_tag);
     }
 
-    private static Map<String, ? extends Map<String, List<? extends Number>>>
+    private static Map<String, ? extends Map<String, INDArray>>
         _staticUnpackInferenceResponse(
             InferenceResponse resp,
             Iterable<String> fetch,
@@ -205,12 +203,12 @@ public class Client {
             return null;
         }
         String tag = resp.getTag();
-        Map<String, ? extends Map<String, List<? extends Number>>> multi_result_map
-            = new HashMap<String, HashMap<String, List<? extends Number>>>();
+        Map<String, ? extends Map<String, INDArray>> multi_result_map
+            = new HashMap<String, HashMap<String, INDArray>>();
         for (ModelOutput model_result: resp.getOutputsList()) {
             FetchInst inst = model_result.getInsts(0);
-            Map<String, List<? extends Number>> result_map
-                = new HashMap<String, List<? extends Number>>();
+            Map<String, INDArray> result_map
+                = new HashMap<String, INDArray>();
             int index = 0;
             for (String name: fetch) {
                 Tensor variable = inst.getTensorArray(index);
@@ -237,29 +235,28 @@ public class Client {
         return multi_result_map;
     }
 
-    /*
-    public Map<String, ? extends Map<String, List<? extends Number>>> predict(
-            Map<String, List<? extends Number>> feed,
+    public Map<String, ? extends Map<String, INDArray>> predict(
+            Map<String, INDArray> feed,
             Iterable<String> fetch) {
         return predict(feed, fetch, false);
     }
-
+/*
     public PredictFuture async_predict(
-            Map<String, List<? extends Number>> feed,
+            Map<String, INDArray> feed,
             Iterable<String> fetch) {
         return async_predict(feed, fetch, false);
     }
-
-    public Map<String, ? extends Map<String, List<? extends Number>>> predict(
-            Map<String, List<? extends Number>> feed,
+*/
+    public Map<String, ? extends Map<String, INDArray>> predict(
+            Map<String, INDArray> feed,
             Iterable<String> fetch,
             Boolean need_variant_tag) {
-        List<? extends Map<String, List<? extends Number>>> feed_batch
-            = new ArrayList<? extends Map<String, List<? extends Number>>>();
+        List<? extends Map<String, INDArray>> feed_batch
+            = new ArrayList<? extends Map<String, INDArray>>();
         feed_batch.add(feed);
         return predict(feed_batch, fetch, need_variant_tag);
     }
-
+/*
     public PredictFuture async_predict(
             Map<String, List<? extends Number>> feed,
             Iterable<String> fetch,
@@ -269,22 +266,21 @@ public class Client {
         feed_batch.add(feed);
         return async_predict(feed_batch, fetch, need_variant_tag);
     }
-    */
-
-    public Map<String, ? extends Map<String, List<? extends Number>>> predict(
-            List<? extends Map<String, List<? extends Number>>> feed_batch,
+*/
+    public Map<String, ? extends Map<String, INDArray>> predict(
+            List<? extends Map<String, INDArray>> feed_batch,
             Iterable<String> fetch) {
         return predict(feed_batch, fetch, false);
     }
-
+    /*
     public PredictFuture async_predict(
             List<? extends Map<String, List<? extends Number>>> feed_batch,
             Iterable<String> fetch) {
         return async_predict(feed_batch, fetch, false);
     }
-
-    public Map<String, ? extends Map<String, List<? extends Number>>> predict(
-            List<? extends Map<String, List<? extends Number>>> feed_batch,
+*/
+    public Map<String, ? extends Map<String, INDArray>> predict(
+            List<? extends Map<String, INDArray>> feed_batch,
             Iterable<String> fetch,
             Boolean need_variant_tag) {
         InferenceRequest req = _packInferenceRequest(feed_batch, fetch);
@@ -297,7 +293,7 @@ public class Client {
             return Collections.emptyMap();
         }
     }
-
+    /*
     public PredictFuture async_predict(
             List<Map<String, List<? extends Number>>> feed_batch,
             Iterable<String> fetch,
@@ -311,24 +307,26 @@ public class Client {
                     resp, fetch, fetchTypes_, lodTensorSet_, need_variant_tag);
                 });
     }
+    */
 
     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.create(data);
+        System.out.println(npdata);
+
         Client client = new Client();
         List<String> endpoints = new ArrayList<String>()
             .add("182.61.111.54:9393");
         Client.connect(endpoints);
-        List<HashMap<String, List<Float>>> feed_batch
-            = new ArrayList<HashMap<String, List<Float>>>()
-            .add(new HashMap<String, ArrayList<Float>>()
-                    .put("x", new ArrayList<Float>()
-                        .add(0.0137f).add(-0.1136f).add(0.2553f)
-                        .add(-0.0692f).add(0.0582f).add(-0.0727f)
-                        .add(-0.1583f).add(-0.0584f).add(0.6283f)
-                        .add(0.4919f).add(0.1856f).add(0.0795f)
-                        .add(-0.0332f)));
+        List<HashMap<String, INDArray>> feed_batch
+            = new ArrayList<HashMap<String, INDArray>>()
+            .add(new HashMap<String, INDArray>()
+                    .put("x", npdata));
         List<String> fetch = new ArrayList<String>()
             .add("price");
-        Map<String, ? extends Map<String, List<?>>> fetch_map
+        Map<String, ? extends Map<String, INDArray>> fetch_map
             = client.predict(feed_batch, fetch);
         System.out.println( "Hello World!" );
     }