diff --git a/java/examples/src/main/java/PaddleServingClientExample.java b/java/examples/src/main/java/PaddleServingClientExample.java
index cdc11df130095d668734ae0a23adb12ef735b2ea..5f5e3ff655e7450d12f562229ae4cb2481ab4a54 100644
--- a/java/examples/src/main/java/PaddleServingClientExample.java
+++ b/java/examples/src/main/java/PaddleServingClientExample.java
@@ -16,9 +16,11 @@ public class PaddleServingClientExample {
             0.0582f, -0.0727f, -0.1583f, -0.0584f,
             0.6283f, 0.4919f, 0.1856f, 0.0795f, -0.0332f};
         INDArray npdata = Nd4j.createFromArray(data);
+        long[] batch_shape = {1,13};
+        INDArray batch_npdata = npdata.reshape(batch_shape);
         HashMap<String, INDArray> feed_data
             = new HashMap<String, INDArray>() {{
-                put("x", npdata);
+                put("x", batch_npdata);
             }};
         List<String> fetch = Arrays.asList("price");
         
@@ -69,12 +71,16 @@ public class PaddleServingClientExample {
         
         // Div(255.0)
         INDArray image = RGBimage.divi(255.0);
-        
+        long[] batch_shape = {1,image.shape()[0],image.shape()[1],image.shape()[2]};
+        INDArray batch_image = image.reshape(batch_shape);        
+
         INDArray im_size = Nd4j.createFromArray(new int[]{height, width});
+        long[] batch_size_shape = {1,2};
+        INDArray batch_im_size = im_size.reshape(batch_size_shape);
         HashMap<String, INDArray> feed_data
             = new HashMap<String, INDArray>() {{
-                put("image", image);
-                put("im_size", im_size);
+                put("image", batch_image);
+                put("im_size", batch_im_size);
             }};
         List<String> fetch = Arrays.asList("save_infer_model/scale_0.tmp_0");
         
diff --git a/java/src/main/java/io/paddle/serving/client/Client.java b/java/src/main/java/io/paddle/serving/client/Client.java
index 742d4f91ce17555a2ea96f2a629717228ba18cef..aae7e6f8f50d4ca2baca877f2e51c8e71eb64af8 100644
--- a/java/src/main/java/io/paddle/serving/client/Client.java
+++ b/java/src/main/java/io/paddle/serving/client/Client.java
@@ -4,6 +4,9 @@ import java.util.*;
 import java.util.function.Function;
 import java.lang.management.ManagementFactory;
 import java.lang.management.RuntimeMXBean;
+import java.util.stream.Collectors;
+import java.util.List;
+import java.util.ArrayList;
 
 import io.grpc.ManagedChannel;
 import io.grpc.ManagedChannelBuilder;
@@ -238,7 +241,11 @@ public class Client {
                 } else {
                     throw new IllegalArgumentException("error tensor value type.");
                 }
-                tensor_builder.addAllShape(feedShapes_.get(name));
+                long[] longArray = variable.shape();
+                int[] intArray = Arrays.stream(longArray).mapToInt(i -> (int) i).toArray();
+                List<Integer> indarrayShapeList = Arrays.stream(intArray).boxed().collect(Collectors.toList());
+                //tensor_builder.addAllShape(feedShapes_.get(name));
+                tensor_builder.addAllShape(indarrayShapeList);
                 inst_builder.addTensorArray(tensor_builder.build());
             }
             req_builder.addInsts(inst_builder.build());