Use longs for dimensions lengths in all API's

This is to be able to support tensor dimensions with more than 2B elements in the future
without API change.

3 files changed, 6 insertions, 8 deletions

diff --git a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/tensorflow/TensorConverter.java b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/tensorflow/TensorConverter.java
index df43225c333..1960cf94591 100644
--- a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/tensorflow/TensorConverter.java
+++ b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/integration/tensorflow/TensorConverter.java
@@ -26,7 +26,7 @@ public class TensorConverter {
         int dimensionIndex = 0;
         for (long dimensionSize : shape) {
             if (dimensionSize == 0) dimensionSize = 1; // TensorFlow ...
-            b.indexed("d" + (dimensionIndex++), (int) dimensionSize);
+            b.indexed("d" + (dimensionIndex++), dimensionSize);
         }
         return b.build();
     }
diff --git a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/rule/GeneratorLambdaFunctionNode.java b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/rule/GeneratorLambdaFunctionNode.java
index d366c9bfbe5..9da1ba40144 100644
--- a/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/rule/GeneratorLambdaFunctionNode.java
+++ b/searchlib/src/main/java/com/yahoo/searchlib/rankingexpression/rule/GeneratorLambdaFunctionNode.java
@@ -1,7 +1,6 @@
 // Copyright 2017 Yahoo Holdings. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
 package com.yahoo.searchlib.rankingexpression.rule;
 
-import com.google.common.collect.ImmutableList;
 import com.yahoo.searchlib.rankingexpression.evaluation.Context;
 import com.yahoo.searchlib.rankingexpression.evaluation.MapContext;
 import com.yahoo.searchlib.rankingexpression.evaluation.Value;
@@ -10,7 +9,6 @@ import com.yahoo.tensor.TensorType;
 import java.util.Collections;
 import java.util.Deque;
 import java.util.List;
-import java.util.function.*;
 
 /**
  * A tensor generating function, whose arguments are determined by a tensor type
@@ -57,14 +55,14 @@ public class GeneratorLambdaFunctionNode extends CompositeNode {
     /**
      * Returns this as an operator which converts a list of integers into a double
      */
-    public IntegerListToDoubleLambda asIntegerListToDoubleOperator() {
-        return new IntegerListToDoubleLambda();
+    public LongListToDoubleLambda asLongListToDoubleOperator() {
+        return new LongListToDoubleLambda();
     }
 
-    private class IntegerListToDoubleLambda implements java.util.function.Function<List<Integer>, Double> {
+    private class LongListToDoubleLambda implements java.util.function.Function<List<Long>, Double> {
 
         @Override
-        public Double apply(List<Integer> arguments) {
+        public Double apply(List<Long> arguments) {
             MapContext context = new MapContext();
             for (int i = 0; i < type.dimensions().size(); i++)
                 context.put(type.dimensions().get(i).name(), arguments.get(i));
diff --git a/searchlib/src/main/javacc/RankingExpressionParser.jj b/searchlib/src/main/javacc/RankingExpressionParser.jj
index 7821ab88b86..541738db8e0 100755
--- a/searchlib/src/main/javacc/RankingExpressionParser.jj
+++ b/searchlib/src/main/javacc/RankingExpressionParser.jj
@@ -467,7 +467,7 @@ ExpressionNode tensorGenerate() :
 }
 {
     <TENSOR> type = tensorTypeArgument() <LBRACE> generator = expression() <RBRACE>
-    { return new TensorFunctionNode(new Generate(type, new GeneratorLambdaFunctionNode(type, generator).asIntegerListToDoubleOperator())); }
+    { return new TensorFunctionNode(new Generate(type, new GeneratorLambdaFunctionNode(type, generator).asLongListToDoubleOperator())); }
 }
 
 ExpressionNode tensorRange() :