Check agreement between TF and Vespa execution

1 files changed, 17 insertions, 17 deletions

diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Reduce.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Reduce.java
index a51df12e522..de9f90a5804 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Reduce.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Reduce.java
@@ -19,7 +19,7 @@ import java.util.Objects;
 import java.util.Set;
 
 /**
- * The <i>reduce</i> tensor operation returns a tensor produced from the argument tensor where some dimensions 
+ * The <i>reduce</i> tensor operation returns a tensor produced from the argument tensor where some dimensions
  * are collapsed to a single value using an aggregator function.
  *
  * @author bratseth
@@ -45,7 +45,7 @@ public class Reduce extends PrimitiveTensorFunction {
 
     /**
      * Creates a reduce function.
-     * 
+     *
      * @param argument the tensor to reduce
      * @param aggregator the aggregator function to use
      * @param dimensions the list of dimensions to remove. If an empty list is given, all dimensions are reduced,
@@ -69,7 +69,7 @@ public class Reduce extends PrimitiveTensorFunction {
         }
         return b.build();
     }
-    
+
     public TensorFunction argument() { return argument; }
 
     @Override
@@ -91,7 +91,7 @@ public class Reduce extends PrimitiveTensorFunction {
     public String toString(ToStringContext context) {
         return "reduce(" + argument.toString(context) + ", " + aggregator + commaSeparated(dimensions) + ")";
     }
-    
+
     private String commaSeparated(List<String> list) {
         StringBuilder b = new StringBuilder();
         for (String element  : list)
@@ -103,7 +103,7 @@ public class Reduce extends PrimitiveTensorFunction {
     public Tensor evaluate(EvaluationContext context) {
         Tensor argument = this.argument.evaluate(context);
         if ( ! dimensions.isEmpty() && ! argument.type().dimensionNames().containsAll(dimensions))
-            throw new IllegalArgumentException("Cannot reduce " + argument + " over dimensions " + 
+            throw new IllegalArgumentException("Cannot reduce " + argument + " over dimensions " +
                                                dimensions + ": Not all those dimensions are present in this tensor");
 
         // Special case: Reduce all
@@ -112,14 +112,14 @@ public class Reduce extends PrimitiveTensorFunction {
                 return reduceIndexedVector((IndexedTensor)argument);
             else
                 return reduceAllGeneral(argument);
-        
+
         // Reduce type
         TensorType.Builder builder = new TensorType.Builder();
         for (TensorType.Dimension dimension : argument.type().dimensions())
             if ( ! dimensions.contains(dimension.name())) // keep
                 builder.dimension(dimension);
         TensorType reducedType = builder.build();
-        
+
         // Reduce cells
         Map<TensorAddress, ValueAggregator> aggregatingCells = new HashMap<>();
         for (Iterator<Tensor.Cell> i = argument.cellIterator(); i.hasNext(); ) {
@@ -131,10 +131,10 @@ public class Reduce extends PrimitiveTensorFunction {
         Tensor.Builder reducedBuilder = Tensor.Builder.of(reducedType);
         for (Map.Entry<TensorAddress, ValueAggregator> aggregatingCell : aggregatingCells.entrySet())
             reducedBuilder.cell(aggregatingCell.getKey(), aggregatingCell.getValue().aggregatedValue());
-        
+
         return reducedBuilder.build();
     }
-    
+
     private TensorAddress reduceDimensions(TensorAddress address, TensorType argumentType, TensorType reducedType) {
         Set<Integer> indexesToRemove = new HashSet<>();
         for (String dimensionToRemove : this.dimensions)
@@ -147,7 +147,7 @@ public class Reduce extends PrimitiveTensorFunction {
                 reducedLabels[reducedLabelIndex++] = address.label(i);
         return TensorAddress.of(reducedLabels);
     }
-    
+
     private Tensor reduceAllGeneral(Tensor argument) {
         ValueAggregator valueAggregator = ValueAggregator.ofType(aggregator);
         for (Iterator<Double> i = argument.valueIterator(); i.hasNext(); )
@@ -163,7 +163,7 @@ public class Reduce extends PrimitiveTensorFunction {
     }
 
     private static abstract class ValueAggregator {
-        
+
         private static ValueAggregator ofType(Aggregator aggregator) {
             switch (aggregator) {
                 case avg : return new AvgAggregator();
@@ -174,22 +174,22 @@ public class Reduce extends PrimitiveTensorFunction {
                 case min : return new MinAggregator();
                 default: throw new UnsupportedOperationException("Aggregator " + aggregator + " is not implemented");
             }
-                
+
         }
 
         /** Add a new value to those aggregated by this */
         public abstract void aggregate(double value);
-        
+
         /** Returns the value aggregated by this */
         public abstract double aggregatedValue();
-        
+
     }
-    
+
     private static class AvgAggregator extends ValueAggregator {
 
         private int valueCount = 0;
         private double valueSum = 0.0;
-        
+
         @Override
         public void aggregate(double value) {
             valueCount++;
@@ -197,7 +197,7 @@ public class Reduce extends PrimitiveTensorFunction {
         }
 
         @Override
-        public double aggregatedValue() { 
+        public double aggregatedValue() {
             return valueSum / valueCount;
         }