support model ensemble

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

@@ -58,7 +58,7 @@ public class Client {
         try {
             resp = blockingStub_.setTimeout(timeout_req);
         } catch (StatusRuntimeException e) {
-            System.out.format("Set RPC timeout failed: %s", e.toString());
+            System.out.format("Set RPC timeout failed: %s\n", e.toString());
             return false;
         }
         return resp.getErrCode() == 0;
@@ -77,7 +77,7 @@ public class Client {
             blockingStub_ = MultiLangGeneralModelServiceGrpc.newBlockingStub(channel_);
             futureStub_ = MultiLangGeneralModelServiceGrpc.newFutureStub(channel_);
         } catch (Exception e) {
-            System.out.format("Connect failed: %s", e.toString());
+            System.out.format("Connect failed: %s\n", e.toString());
             return false;
         }
         GetClientConfigRequest get_client_config_req = GetClientConfigRequest.newBuilder().build();
@@ -85,7 +85,7 @@ public class Client {
         try {
             resp = blockingStub_.getClientConfig(get_client_config_req);
         } catch (StatusRuntimeException e) {
-            System.out.format("Get Client config failed: %s", e.toString());
+            System.out.format("Get Client config failed: %s\n", e.toString());
             return false;
         }
         String model_config_str = resp.getClientConfigStr();
@@ -98,7 +98,7 @@ public class Client {
         try {
             com.google.protobuf.TextFormat.getParser().merge(model_config_str, model_conf_builder);
         } catch (com.google.protobuf.TextFormat.ParseException e) {
-            System.out.format("Parse client config failed: %s", e.toString());
+            System.out.format("Parse client config failed: %s\n", e.toString());
         }
         GeneralModelConfig model_conf = model_conf_builder.build();
 
@@ -164,7 +164,9 @@ public class Client {
                 long[] flattened_shape = {-1};
                 INDArray flattened_list = variable.reshape(flattened_shape);
                 int v_type = feedTypes_.get(name);
+                System.out.println(flattened_list);
                 NdIndexIterator iter = new NdIndexIterator(flattened_list.shape());
+                //System.out.format("name: %s, type: %d\n", name, v_type);
                 if (v_type == 0) { // int64
                     while (iter.hasNext()) {
                         long[] next_index = iter.next();
@@ -231,39 +233,50 @@ public class Client {
             for (String name: fetch) {
                 Tensor variable = inst.getTensorArray(index);
                 int v_type = fetchTypes.get(name);
+                INDArray data = null; 
                 if (v_type == 0) { // int64
                     List<Long> list = variable.getInt64DataList();
                     long[] array = new long[list.size()];
                     for (int i = 0; i < list.size(); i++) {
                         array[i] = list.get(i);
                     }
-                    result_map.put(name, Nd4j.create(array));
+                    data = Nd4j.createFromArray(array);
                 } else if (v_type == 1) { // float32
                     List<Float> list = variable.getFloatDataList();
                     float[] array = new float[list.size()];
                     for (int i = 0; i < list.size(); i++) {
                         array[i] = list.get(i);
                     }
-                    result_map.put(name, Nd4j.create(array));
+                    data = Nd4j.createFromArray(array);
                 } else if (v_type == 2) { // int32
                     List<Integer> list = variable.getIntDataList();
                     int[] array = new int[list.size()];
                     for (int i = 0; i < list.size(); i++) {
                         array[i] = list.get(i);
                     }
-                    result_map.put(name, Nd4j.create(array));
+                    data = Nd4j.createFromArray(array);
                 } else {
                     throw new IllegalArgumentException("error tensor value type.");
                 }
-                // TODO: shape
+                // shape
+                List<Integer> shape_lsit = variable.getShapeList();
+                int[] shape_array = new int[shape_lsit.size()];
+                for (int i = 0; i < shape_lsit.size(); ++i) {
+                    shape_array[i] = shape_lsit.get(i);
+                }
+                data = data.reshape(shape_array);
+                
+                // put data to result_map
+                result_map.put(name, data);
 
+                // lod
                 if (lodTensorSet.contains(name)) {
                     List<Integer> list = variable.getLodList();
                     int[] array = new int[list.size()];
                     for (int i = 0; i < list.size(); i++) {
                         array[i] = list.get(i);
                     }
-                    result_map.put(name + ".lod", Nd4j.create(array));
+                    result_map.put(name + ".lod", Nd4j.createFromArray(array));
                 }
                 index += 1;
             }
@@ -353,12 +366,12 @@ public class Client {
                 = new ArrayList<Map.Entry<String, HashMap<String, INDArray>>>(
                     ensemble_result.entrySet());
             if (list.size() != 1) {
-                System.out.format("grpc failed: please use ensemble_predict impl.");
+                System.out.format("grpc failed: please use ensemble_predict impl.\n");
                 return null;
             }
             return list.get(0).getValue();
         } catch (StatusRuntimeException e) {
-            System.out.format("grpc failed: %s", e.toString());
+            System.out.format("grpc failed: %s\n", e.toString());
             return null;
         }
     }
@@ -373,7 +386,7 @@ public class Client {
             return _unpackInferenceResponse(
                     resp, fetch, need_variant_tag);
         } catch (StatusRuntimeException e) {
-            System.out.format("grpc failed: %s", e.toString());
+            System.out.format("grpc failed: %s\n", e.toString());
             return null;
         }
     }
@@ -394,30 +407,44 @@ public class Client {
     }
 
     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);
-
-        Client client = new Client();
-        List<String> endpoints = Arrays.asList("localhost:9393");
-        boolean succ = client.connect(endpoints);
-        if (succ != true) {
-            System.out.println("connect failed.");
-            return;
-        }
+        INDArray npdata = Nd4j.createFromArray(data);
         HashMap<String, INDArray> feed_data
             = new HashMap<String, INDArray>() {{
                 put("x", npdata);
         }};
         List<String> fetch = Arrays.asList("price");
+        */
+        /*
         Map<String, INDArray> fetch_map = client.predict(feed_data, fetch);
         for (Map.Entry<String, INDArray> e : fetch_map.entrySet()) {
             System.out.println("Key = " + e.getKey() + ", Value = " + e.getValue());
         }
-        /*
+        */
+        
+        //int[] data = {8, 233, 52, 601};
+        long[] data = {8, 233, 52, 601};
+        INDArray npdata = Nd4j.createFromArray(data);
+        //System.out.println(npdata);
+        HashMap<String, INDArray> feed_data
+            = new HashMap<String, INDArray>() {{
+                put("words", npdata);
+        }};
+        List<String> fetch = Arrays.asList("prediction");
+
+        Client client = new Client();
+        List<String> endpoints = Arrays.asList("localhost:9393");
+        boolean succ = client.connect(endpoints);
+        if (succ != true) {
+            System.out.println("connect failed.");
+            return;
+        }
+        
         Map<String, HashMap<String, INDArray>> fetch_map
-            = client.predict(feed_data, fetch);
+            = client.ensemble_predict(feed_data, fetch);
         for (Map.Entry<String, HashMap<String, INDArray>> entry : fetch_map.entrySet()) {
             System.out.println("Model = " + entry.getKey());
             HashMap<String, INDArray> tt = entry.getValue();
@@ -425,7 +452,7 @@ public class Client {
                 System.out.println("Key = " + e.getKey() + ", Value = " + e.getValue());
             }
         }
-        */
+        
     }
 }
 
@@ -446,7 +473,7 @@ class PredictFuture {
         try {
             resp = callFuture_.get();
         } catch (Exception e) {
-            System.out.format("grpc failed: %s", e.toString());
+            System.out.format("grpc failed: %s\n", e.toString());
             return null;
         }
         Map<String, HashMap<String, INDArray>> ensemble_result
@@ -455,18 +482,18 @@ class PredictFuture {
             = new ArrayList<Map.Entry<String, HashMap<String, INDArray>>>(
                     ensemble_result.entrySet());
         if (list.size() != 1) {
-            System.out.format("grpc failed: please use get_ensemble impl.");
+            System.out.format("grpc failed: please use get_ensemble impl.\n");
             return null;
         }
         return list.get(0).getValue();
     }
 
-    public Map<String, HashMap<String, INDArray>> get_ensemble() throws Exception {
+    public Map<String, HashMap<String, INDArray>> ensemble_get() throws Exception {
         InferenceResponse resp = null;
         try {
             resp = callFuture_.get();
         } catch (Exception e) {
-            System.out.format("grpc failed: %s", e.toString());
+            System.out.format("grpc failed: %s\n", e.toString());
             return null;
         }
         return callBackFunc_.apply(resp);