1 files changed, 15 insertions, 13 deletions
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/L2Normalize.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/L2Normalize.java
index 40edb8ba23f..a6b30d0b292 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/L2Normalize.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/L2Normalize.java
@@ -1,40 +1,42 @@
 // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 package com.yahoo.tensor.functions;
 
+import com.yahoo.tensor.evaluation.TypeContext;
+
 import java.util.Collections;
 import java.util.List;
 
 /**
  * @author bratseth
  */
-public class L2Normalize extends CompositeTensorFunction {
+public class L2Normalize<NAMETYPE extends TypeContext.Name> extends CompositeTensorFunction<NAMETYPE> {
 
-    private final TensorFunction argument;
+    private final TensorFunction<NAMETYPE> argument;
     private final String dimension;
 
-    public L2Normalize(TensorFunction argument, String dimension) {
+    public L2Normalize(TensorFunction<NAMETYPE> argument, String dimension) {
         this.argument = argument;
         this.dimension = dimension;
     }
 
     @Override
-    public List<TensorFunction> arguments() { return Collections.singletonList(argument); }
+    public List<TensorFunction<NAMETYPE>> arguments() { return Collections.singletonList(argument); }
 
     @Override
-    public TensorFunction withArguments(List<TensorFunction> arguments) {
+    public TensorFunction<NAMETYPE> withArguments(List<TensorFunction<NAMETYPE>> arguments) {
         if ( arguments.size() != 1)
             throw new IllegalArgumentException("L2Normalize must have 1 argument, got " + arguments.size());
-        return new L2Normalize(arguments.get(0), dimension);
+        return new L2Normalize<>(arguments.get(0), dimension);
     }
 
     @Override
-    public PrimitiveTensorFunction toPrimitive() {
-        TensorFunction primitiveArgument = argument.toPrimitive();
-        return new Join(primitiveArgument,
-                        new Map(new Reduce(new Map(primitiveArgument, ScalarFunctions.square()),
-                                           Reduce.Aggregator.sum,
-                                           dimension),
-                                ScalarFunctions.sqrt()),
+    public PrimitiveTensorFunction<NAMETYPE> toPrimitive() {
+        TensorFunction<NAMETYPE> primitiveArgument = argument.toPrimitive();
+        return new Join<>(primitiveArgument,
+                          new Map<>(new Reduce<>(new Map<>(primitiveArgument, ScalarFunctions.square()),
+                                                 Reduce.Aggregator.sum,
+                                                 dimension),
+                                    ScalarFunctions.sqrt()),
                         ScalarFunctions.divide());
     }