Revert "Bratseth/tensorflow models"

16 files changed, 129 insertions, 167 deletions

diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/CompositeTensorFunction.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/CompositeTensorFunction.java
index 191c7988443..8f4dbf014a7 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/CompositeTensorFunction.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/CompositeTensorFunction.java
@@ -8,7 +8,7 @@ import com.yahoo.tensor.evaluation.EvaluationContext;
 /**
  * A composite tensor function is a tensor function which can be expressed (less tersely)
  * as a tree of primitive tensor functions.
- *
+ * 
  * @author bratseth
  */
 @Beta
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Concat.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Concat.java
index faa0ca36cb6..1dbb94fdb20 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Concat.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Concat.java
@@ -15,7 +15,7 @@ import java.util.stream.Collectors;
 
 /**
  * Concatenation of two tensors along an (indexed) dimension
- *
+ * 
  * @author bratseth
  */
 @Beta
@@ -74,7 +74,7 @@ public class Concat extends PrimitiveTensorFunction {
         concatenateTo(bIndexed, aIndexed, 0, concatType, bToIndexes, aToIndexes, builder);
         return builder.build();
     }
-
+    
     private void concatenateTo(IndexedTensor a, IndexedTensor b, int offset, TensorType concatType,
                                int[] aToIndexes, int[] bToIndexes, Tensor.Builder builder) {
         Set<String> otherADimensions = a.type().dimensionNames().stream().filter(d -> !d.equals(dimension)).collect(Collectors.toSet());
@@ -112,7 +112,7 @@ public class Concat extends PrimitiveTensorFunction {
             Tensor unitTensor = Tensor.Builder.of(new TensorType.Builder().indexed(dimensionName, 1).build()).cell(1,0).build();
             return tensor.multiply(unitTensor);
         }
-
+        
     }
 
     /** Returns the type resulting from concatenating a and b */
@@ -144,7 +144,7 @@ public class Concat extends PrimitiveTensorFunction {
     /**
      * Combine two addresses, adding the offset to the concat dimension
      *
-     * @return the combined address or null if the addresses are incompatible
+     * @return the combined address or null if the addresses are incompatible 
      *         (in some other dimension than the concat dimension)
      */
     private TensorAddress combineAddresses(TensorAddress a, int[] aToIndexes, TensorAddress b, int[] bToIndexes,
@@ -161,7 +161,7 @@ public class Concat extends PrimitiveTensorFunction {
     /**
      * Returns the an array having one entry in order for each dimension of fromType
      * containing the index at which toType contains the same dimension name.
-     * That is, if the returned array contains n at index i then
+     * That is, if the returned array contains n at index i then 
      * fromType.dimensions().get(i).name.equals(toType.dimensions().get(n).name())
      * If some dimension in fromType is not present in toType, the corresponding index will be -1
      */
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/ConstantTensor.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/ConstantTensor.java
index 14ed38718ce..4ac7b21ba90 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/ConstantTensor.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/ConstantTensor.java
@@ -10,18 +10,18 @@ import java.util.List;
 
 /**
  * A function which returns a constant tensor.
- *
+ * 
  * @author bratseth
  */
 @Beta
 public class ConstantTensor extends PrimitiveTensorFunction {
 
     private final Tensor constant;
-
+    
     public ConstantTensor(String tensorString) {
         this.constant = Tensor.from(tensorString);
     }
-
+    
     public ConstantTensor(Tensor tensor) {
         this.constant = tensor;
     }
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Diag.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Diag.java
index c75d8ee4753..bbdbd5c3df1 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Diag.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Diag.java
@@ -11,19 +11,19 @@ import java.util.stream.Stream;
 
 /**
  * A tensor generator which returns a tensor of any dimension filled with 1 in the diagonal and 0 elsewhere.
- *
+ * 
  * @author bratseth
  */
 public class Diag extends CompositeTensorFunction {
 
     private final TensorType type;
     private final Function<List<Integer>, Double> diagFunction;
-
+    
     public Diag(TensorType type) {
         this.type = type;
         this.diagFunction = ScalarFunctions.equal(dimensionNames().collect(Collectors.toList()));
     }
-
+    
     @Override
     public List<TensorFunction> functionArguments() { return Collections.emptyList(); }
 
@@ -43,7 +43,7 @@ public class Diag extends CompositeTensorFunction {
     public String toString(ToStringContext context) {
         return "diag(" + dimensionNames().collect(Collectors.joining(",")) + ")" + diagFunction;
     }
-
+    
     private Stream<String> dimensionNames() {
         return type.dimensions().stream().map(TensorType.Dimension::name);
     }
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Generate.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Generate.java
index e42d25197e2..6ea73b7f310 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Generate.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Generate.java
@@ -15,7 +15,7 @@ import java.util.function.Function;
 
 /**
  * An indexed tensor whose values are generated by a function
- *
+ * 
  * @author bratseth
  */
 @Beta
@@ -26,7 +26,7 @@ public class Generate extends PrimitiveTensorFunction {
 
     /**
      * Creates a generated tensor
-     *
+     * 
      * @param type the type of the tensor
      * @param generator the function generating values from a list of ints specifying the indexes of the
      *                  tensor cell which will receive the value
@@ -39,7 +39,7 @@ public class Generate extends PrimitiveTensorFunction {
         this.type = type;
         this.generator = generator;
     }
-
+    
     private void validateType(TensorType type) {
         for (TensorType.Dimension dimension : type.dimensions())
             if (dimension.type() != TensorType.Dimension.Type.indexedBound)
@@ -58,7 +58,7 @@ public class Generate extends PrimitiveTensorFunction {
 
     @Override
     public PrimitiveTensorFunction toPrimitive() { return this; }
-
+    
     @Override
     public Tensor evaluate(EvaluationContext context) {
         Tensor.Builder builder = Tensor.Builder.of(type);
@@ -69,14 +69,14 @@ public class Generate extends PrimitiveTensorFunction {
         }
         return builder.build();
     }
-
+    
     private DimensionSizes dimensionSizes(TensorType type) {
         DimensionSizes.Builder b = new DimensionSizes.Builder(type.dimensions().size());
         for (int i = 0; i < b.dimensions(); i++)
             b.set(i, type.dimensions().get(i).size().get());
         return b.build();
     }
-
+    
     @Override
     public String toString(ToStringContext context) { return type + "(" + generator + ")"; }
 
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Join.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Join.java
index ff887e3e9a6..8c4dbfb0acb 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Join.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Join.java
@@ -28,12 +28,12 @@ import java.util.function.DoubleBinaryOperator;
  * The <i>join</i> tensor operation produces a tensor from the argument tensors containing the set of cells
  * given by the cross product of the cells of the given tensors, having as values the value produced by
  * applying the given combinator function on the values from the two source cells.
- *
+ * 
  * @author bratseth
  */
 @Beta
 public class Join extends PrimitiveTensorFunction {
-
+    
     private final TensorFunction argumentA, argumentB;
     private final DoubleBinaryOperator combinator;
 
@@ -46,30 +46,6 @@ public class Join extends PrimitiveTensorFunction {
         this.combinator = combinator;
     }
 
-    /** Returns the type resulting from applying Join to the two given types */
-    public static TensorType outputType(TensorType a, TensorType b) {
-        TensorType.Builder typeBuilder = new TensorType.Builder();
-        for (int i = 0; i < a.dimensions().size(); ++i) {
-            TensorType.Dimension aDim = a.dimensions().get(i);
-            for (int j = 0; j < b.dimensions().size(); ++j) {
-                TensorType.Dimension bDim = b.dimensions().get(j);
-                if (aDim.name().equals(bDim.name())) { // include
-                    if (aDim.isIndexed() && bDim.isIndexed()) {
-                        if (aDim.size().isPresent() || bDim.size().isPresent())
-                            typeBuilder.indexed(aDim.name(), Math.min(aDim.size().orElse(Integer.MAX_VALUE),
-                                                                      bDim.size().orElse(Integer.MAX_VALUE)));
-                        else
-                            typeBuilder.indexed(aDim.name());
-                    }
-                    else {
-                        typeBuilder.mapped(aDim.name());
-                    }
-                }
-            }
-        }
-        return typeBuilder.build();
-    }
-
     public TensorFunction argumentA() { return argumentA; }
     public TensorFunction argumentB() { return argumentB; }
     public DoubleBinaryOperator combinator() { return combinator; }
@@ -112,11 +88,11 @@ public class Join extends PrimitiveTensorFunction {
         else
             return generalJoin(a, b, joinedType);
     }
-
+    
     private boolean hasSingleIndexedDimension(Tensor tensor) {
         return tensor.type().dimensions().size() == 1 && tensor.type().dimensions().get(0).isIndexed();
     }
-
+    
     private Tensor indexedVectorJoin(IndexedTensor a, IndexedTensor b, TensorType type) {
         int joinedLength = Math.min(a.dimensionSizes().size(0), b.dimensionSizes().size(0));
         Iterator<Double> aIterator = a.valueIterator();
@@ -138,7 +114,7 @@ public class Join extends PrimitiveTensorFunction {
         }
         return builder.build();
     }
-
+    
     /** Join a tensor into a superspace */
     private Tensor subspaceJoin(Tensor subspace, Tensor superspace, TensorType joinedType, boolean reversedArgumentOrder) {
         if (subspace instanceof IndexedTensor && superspace instanceof IndexedTensor)
@@ -150,7 +126,7 @@ public class Join extends PrimitiveTensorFunction {
     private Tensor indexedSubspaceJoin(IndexedTensor subspace, IndexedTensor superspace, TensorType joinedType, boolean reversedArgumentOrder) {
         if (subspace.size() == 0 || superspace.size() == 0) // special case empty here to avoid doing it when finding sizes
             return Tensor.Builder.of(joinedType, new DimensionSizes.Builder(joinedType.dimensions().size()).build()).build();
-
+        
         DimensionSizes joinedSizes = joinedSize(joinedType, subspace, superspace);
 
         IndexedTensor.Builder builder = (IndexedTensor.Builder)Tensor.Builder.of(joinedType, joinedSizes);
@@ -158,14 +134,14 @@ public class Join extends PrimitiveTensorFunction {
         // Find dimensions which are only in the supertype
         Set<String> superDimensionNames = new HashSet<>(superspace.type().dimensionNames());
         superDimensionNames.removeAll(subspace.type().dimensionNames());
-
+        
         for (Iterator<IndexedTensor.SubspaceIterator> i = superspace.subspaceIterator(superDimensionNames, joinedSizes); i.hasNext(); ) {
             IndexedTensor.SubspaceIterator subspaceInSuper = i.next();
             joinSubspaces(subspace.valueIterator(), subspace.size(),
                           subspaceInSuper, subspaceInSuper.size(),
                           reversedArgumentOrder, builder);
         }
-
+        
         return builder.build();
     }
 
@@ -224,7 +200,7 @@ public class Join extends PrimitiveTensorFunction {
             subspaceIndexes[i] = supertype.indexOfDimension(subtype.dimensions().get(i).name()).get();
         return subspaceIndexes;
     }
-
+    
     private TensorAddress mapAddressToSubspace(TensorAddress superAddress, int[] subspaceIndexes) {
         String[] subspaceLabels = new String[subspaceIndexes.length];
         for (int i = 0; i < subspaceIndexes.length; i++)
@@ -259,7 +235,7 @@ public class Join extends PrimitiveTensorFunction {
         DimensionSizes bIterateSize = joinedSizeOf(b.type(), joinedType, joinedSize);
 
         // for each combination of dimensions only in a
-        for (Iterator<IndexedTensor.SubspaceIterator> ia = a.subspaceIterator(dimensionsOnlyInA, aIterateSize); ia.hasNext(); ) {
+        for (Iterator<IndexedTensor.SubspaceIterator> ia = a.subspaceIterator(dimensionsOnlyInA, aIterateSize); ia.hasNext(); ) { 
             IndexedTensor.SubspaceIterator aSubspace = ia.next();
             // for each combination of dimensions in a which is also in b
             while (aSubspace.hasNext()) {
@@ -276,7 +252,7 @@ public class Join extends PrimitiveTensorFunction {
             }
         }
     }
-
+    
     private PartialAddress partialAddress(TensorType addressType, TensorAddress address, Set<String> retainDimensions) {
         PartialAddress.Builder builder = new PartialAddress.Builder(retainDimensions.size());
         for (int i = 0; i < addressType.dimensions().size(); i++)
@@ -284,7 +260,7 @@ public class Join extends PrimitiveTensorFunction {
                 builder.add(addressType.dimensions().get(i).name(), address.intLabel(i));
         return builder.build();
     }
-
+    
     /** Returns the sizes from the joined sizes which are present in the type argument */
     private DimensionSizes joinedSizeOf(TensorType type, TensorType joinedType, DimensionSizes joinedSizes) {
         DimensionSizes.Builder builder = new DimensionSizes.Builder(type.dimensions().size());
@@ -295,7 +271,7 @@ public class Join extends PrimitiveTensorFunction {
         }
         return builder.build();
     }
-
+    
     private Tensor mappedGeneralJoin(Tensor a, Tensor b, TensorType joinedType) {
         int[] aToIndexes = mapIndexes(a.type(), joinedType);
         int[] bToIndexes = mapIndexes(b.type(), joinedType);
@@ -364,7 +340,7 @@ public class Join extends PrimitiveTensorFunction {
     /**
      * Returns the an array having one entry in order for each dimension of fromType
      * containing the index at which toType contains the same dimension name.
-     * That is, if the returned array contains n at index i then
+     * That is, if the returned array contains n at index i then 
      * fromType.dimensions().get(i).name.equals(toType.dimensions().get(n).name())
      * If some dimension in fromType is not present in toType, the corresponding index will be -1
      */
@@ -384,7 +360,7 @@ public class Join extends PrimitiveTensorFunction {
         return TensorAddress.of(joinedLabels);
     }
 
-    /**
+    /** 
      * Maps the content in the given list to the given array, using the given index map.
      *
      * @return true if the mapping was successful, false if one of the destination positions was
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Map.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Map.java
index a5e1a016a41..a9872bb42d8 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Map.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Map.java
@@ -6,7 +6,6 @@ import com.google.common.collect.ImmutableMap;
 import com.yahoo.tensor.MappedTensor;
 import com.yahoo.tensor.Tensor;
 import com.yahoo.tensor.TensorAddress;
-import com.yahoo.tensor.TensorType;
 import com.yahoo.tensor.evaluation.EvaluationContext;
 
 import java.util.Collections;
@@ -33,8 +32,6 @@ public class Map extends PrimitiveTensorFunction {
         this.mapper = mapper;
     }
 
-    public static TensorType outputType(TensorType inputType) { return inputType; }
-
     public TensorFunction argument() { return argument; }
     public DoubleUnaryOperator mapper() { return mapper; }
 
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Matmul.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Matmul.java
index 4071917c2b5..bb27e937699 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Matmul.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Matmul.java
@@ -3,7 +3,6 @@ package com.yahoo.tensor.functions;
 
 import com.google.common.annotations.Beta;
 import com.google.common.collect.ImmutableList;
-import com.yahoo.tensor.TensorType;
 
 import java.util.List;
 
@@ -15,17 +14,13 @@ public class Matmul extends CompositeTensorFunction {
 
     private final TensorFunction argument1, argument2;
     private final String dimension;
-
+    
     public Matmul(TensorFunction argument1, TensorFunction argument2, String dimension) {
         this.argument1 = argument1;
         this.argument2 = argument2;
         this.dimension = dimension;
     }
 
-    public static TensorType outputType(TensorType a, TensorType b, String dimension) {
-        return Join.outputType(a, b);
-    }
-
     @Override
     public List<TensorFunction> functionArguments() { return ImmutableList.of(argument1, argument2); }
 
@@ -44,7 +39,7 @@ public class Matmul extends CompositeTensorFunction {
                           Reduce.Aggregator.sum,
                           dimension);
     }
-
+    
     @Override
     public String toString(ToStringContext context) {
         return "matmul(" + argument1.toString(context) + ", " + argument2.toString(context) + ", " + dimension + ")";
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/PrimitiveTensorFunction.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/PrimitiveTensorFunction.java
index b7c9a5d2342..efb7b9e500c 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/PrimitiveTensorFunction.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/PrimitiveTensorFunction.java
@@ -8,10 +8,10 @@ import com.yahoo.tensor.Tensor;
  * A primitive tensor function is a tensor function which cannot be expressed in terms of other tensor functions.
  * All tensor implementations must implement all primitive tensor functions.
  * Primitive tensor functions are fully inspectable.
- *
+ * 
  * @author bratseth
  */
 @Beta
 public abstract class PrimitiveTensorFunction extends TensorFunction {
-
+    
 }
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Random.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Random.java
index 958ef85d1dc..457763e97ba 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Random.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Random.java
@@ -22,11 +22,11 @@ import java.util.stream.Stream;
 public class Random extends CompositeTensorFunction {
 
     private final TensorType type;
-
+    
     public Random(TensorType type) {
         this.type = type;
     }
-
+    
     @Override
     public List<TensorFunction> functionArguments() { return Collections.emptyList(); }
 
@@ -46,7 +46,7 @@ public class Random extends CompositeTensorFunction {
     public String toString(ToStringContext context) {
         return "random(" + dimensionNames().collect(Collectors.joining(",")) + ")";
     }
-
+    
     private Stream<String> dimensionNames() {
         return type.dimensions().stream().map(TensorType.Dimension::toString);
     }
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Range.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Range.java
index a56f82b026a..e2b39a2048d 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Range.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Range.java
@@ -12,19 +12,19 @@ import java.util.stream.Stream;
 /**
  * A tensor generator which returns a tensor of any dimension filled with the sum of the tensor
  * indexes of each position.
- *
+ * 
  * @author bratseth
  */
 public class Range extends CompositeTensorFunction {
 
     private final TensorType type;
     private final Function<List<Integer>, Double> rangeFunction;
-
+    
     public Range(TensorType type) {
         this.type = type;
         this.rangeFunction = ScalarFunctions.sum(dimensionNames().collect(Collectors.toList()));
     }
-
+    
     @Override
     public List<TensorFunction> functionArguments() { return Collections.emptyList(); }
 
@@ -44,7 +44,7 @@ public class Range extends CompositeTensorFunction {
     public String toString(ToStringContext context) {
         return "range(" + dimensionNames().collect(Collectors.joining(",")) + ")" + rangeFunction;
     }
-
+    
     private Stream<String> dimensionNames() {
         return type.dimensions().stream().map(TensorType.Dimension::toString);
     }
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 de9f90a5804..cfc78be7e0c 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,
@@ -61,15 +61,6 @@ public class Reduce extends PrimitiveTensorFunction {
         this.dimensions = ImmutableList.copyOf(dimensions);
     }
 
-    public static TensorType outputType(TensorType inputType, List<String> reduceDimensions) {
-        TensorType.Builder b = new TensorType.Builder();
-        for (TensorType.Dimension dimension : inputType.dimensions()) {
-            if ( ! reduceDimensions.contains(dimension.name()))
-                b.dimension(dimension);
-        }
-        return b.build();
-    }
-
     public TensorFunction argument() { return argument; }
 
     @Override
@@ -91,7 +82,7 @@ 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 +94,7 @@ 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 +103,14 @@ 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 +122,10 @@ 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 +138,7 @@ 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 +154,7 @@ 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 +165,22 @@ 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 +188,7 @@ public class Reduce extends PrimitiveTensorFunction {
         }
 
         @Override
-        public double aggregatedValue() {
+        public double aggregatedValue() { 
             return valueSum / valueCount;
         }
 
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Rename.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Rename.java
index ec9b762a41c..6b0daf1b49a 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Rename.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Rename.java
@@ -3,6 +3,8 @@ package com.yahoo.tensor.functions;
 
 import com.google.common.annotations.Beta;
 import com.google.common.collect.ImmutableList;
+import com.google.common.collect.ImmutableMap;
+import com.yahoo.tensor.MappedTensor;
 import com.yahoo.tensor.Tensor;
 import com.yahoo.tensor.TensorAddress;
 import com.yahoo.tensor.TensorType;
@@ -17,7 +19,7 @@ import java.util.Objects;
 
 /**
  * The <i>rename</i> tensor function returns a tensor where some dimensions are assigned new names.
- *
+ * 
  * @author bratseth
  */
 @Beta
@@ -27,10 +29,6 @@ public class Rename extends PrimitiveTensorFunction {
     private final List<String> fromDimensions;
     private final List<String> toDimensions;
 
-    public Rename(TensorFunction argument, String fromDimension, String toDimension) {
-        this(argument, ImmutableList.of(fromDimension), ImmutableList.of(toDimension));
-    }
-
     public Rename(TensorFunction argument, List<String> fromDimensions, List<String> toDimensions) {
         Objects.requireNonNull(argument, "The argument tensor cannot be null");
         Objects.requireNonNull(fromDimensions, "The 'from' dimensions cannot be null");
@@ -44,7 +42,7 @@ public class Rename extends PrimitiveTensorFunction {
         this.fromDimensions = ImmutableList.copyOf(fromDimensions);
         this.toDimensions = ImmutableList.copyOf(toDimensions);
     }
-
+    
     @Override
     public List<TensorFunction> functionArguments() { return Collections.singletonList(argument); }
 
@@ -64,7 +62,7 @@ public class Rename extends PrimitiveTensorFunction {
 
         Map<String, String> fromToMap = fromToMap();
         TensorType renamedType = rename(tensor.type(), fromToMap);
-
+        
         // an array which lists the index of each label in the renamed type
         int[] toIndexes = new int[tensor.type().dimensions().size()];
         for (int i = 0; i < tensor.type().dimensions().size(); i++) {
@@ -72,7 +70,7 @@ public class Rename extends PrimitiveTensorFunction {
             String newDimensionName = fromToMap.getOrDefault(dimensionName, dimensionName);
             toIndexes[i] = renamedType.indexOfDimension(newDimensionName).get();
         }
-
+            
         Tensor.Builder builder = Tensor.Builder.of(renamedType);
         for (Iterator<Tensor.Cell> i = tensor.cellIterator(); i.hasNext(); ) {
             Map.Entry<TensorAddress, Double> cell = i.next();
@@ -88,7 +86,7 @@ public class Rename extends PrimitiveTensorFunction {
             builder.dimension(dimension.withName(fromToMap.getOrDefault(dimension.name(), dimension.name())));
         return builder.build();
     }
-
+    
     private TensorAddress rename(TensorAddress address, int[] toIndexes) {
         String[] reorderedLabels = new String[toIndexes.length];
         for (int i = 0; i < toIndexes.length; i++)
@@ -97,18 +95,18 @@ public class Rename extends PrimitiveTensorFunction {
     }
 
     @Override
-    public String toString(ToStringContext context) {
-        return "rename(" + argument.toString(context) + ", " +
+    public String toString(ToStringContext context) { 
+        return "rename(" + argument.toString(context) + ", " + 
                        toVectorString(fromDimensions) + ", " + toVectorString(toDimensions) + ")";
     }
-
+    
     private Map<String, String> fromToMap() {
         Map<String, String> map = new HashMap<>();
         for (int i = 0; i < fromDimensions.size(); i++)
             map.put(fromDimensions.get(i), toDimensions.get(i));
         return map;
     }
-
+    
     private String toVectorString(List<String> elements) {
         if (elements.size() == 1)
             return elements.get(0);
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/ScalarFunctions.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/ScalarFunctions.java
index fb5029fbfd6..99f79cb735a 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/ScalarFunctions.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/ScalarFunctions.java
@@ -21,87 +21,101 @@ import java.util.stream.Collectors;
 @Beta
 public class ScalarFunctions {
 
-    public static DoubleBinaryOperator add() { return new Add(); }
-    public static DoubleBinaryOperator divide() { return new Divide(); }
+    public static DoubleBinaryOperator add() { return new Addition(); }
+    public static DoubleBinaryOperator multiply() { return new Multiplication(); }
+    public static DoubleBinaryOperator divide() { return new Division(); }
     public static DoubleBinaryOperator equal() { return new Equal(); }
-    public static DoubleBinaryOperator multiply() { return new Multiply(); }
-
-    public static DoubleUnaryOperator acos() { return new Acos(); }
-    public static DoubleUnaryOperator exp() { return new Exp(); }
-    public static DoubleUnaryOperator sqrt() { return new Sqrt(); }
     public static DoubleUnaryOperator square() { return new Square(); }
-
+    public static DoubleUnaryOperator sqrt() { return new Sqrt(); }
+    public static DoubleUnaryOperator exp() { return new Exponent(); }
     public static Function<List<Integer>, Double> random() { return new Random(); }
     public static Function<List<Integer>, Double> equal(List<String> argumentNames) { return new EqualElements(argumentNames); }
     public static Function<List<Integer>, Double> sum(List<String> argumentNames) { return new SumElements(argumentNames); }
 
-    // Binary operators -----------------------------------------------------------------------------
+    public static class Addition implements DoubleBinaryOperator {
 
-    public static class Add implements DoubleBinaryOperator {
         @Override
         public double applyAsDouble(double left, double right) { return left + right; }
+
         @Override
         public String toString() { return "f(a,b)(a + b)"; }
-    }
 
-    public static class Equal implements DoubleBinaryOperator {
-        @Override
-        public double applyAsDouble(double left, double right) { return left == right ? 1 : 0; }
-        @Override
-        public String toString() { return "f(a,b)(a==b)"; }
     }
 
-    public static class Exp implements DoubleUnaryOperator {
-        @Override
-        public double applyAsDouble(double operand) { return Math.exp(operand); }
-        @Override
-        public String toString() { return "f(a)(exp(a))"; }
-    }
+    public static class Multiplication implements DoubleBinaryOperator {
 
-    public static class Multiply implements DoubleBinaryOperator {
         @Override
-        public double applyAsDouble(double left, double right) { return left * right; }        
+        public double applyAsDouble(double left, double right) { return left * right; }
+        
         @Override
         public String toString() { return "f(a,b)(a * b)"; }
+
     }
 
-    public static class Divide implements DoubleBinaryOperator {
+    public static class Division implements DoubleBinaryOperator {
+
         @Override
         public double applyAsDouble(double left, double right) { return left / right; }
+
         @Override
         public String toString() { return "f(a,b)(a / b)"; }
     }
 
-    // Unary operators ------------------------------------------------------------------------------
+    public static class Equal implements DoubleBinaryOperator {
+
+        @Override
+        public double applyAsDouble(double left, double right) { return left == right ? 1 : 0; }
+
+        @Override
+        public String toString() { return "f(a,b)(a==b)"; }
+    }
+
+    public static class Square implements DoubleUnaryOperator {
 
-    public static class Acos implements DoubleUnaryOperator {
         @Override
-        public double applyAsDouble(double operand) { return Math.acos(operand); }
+        public double applyAsDouble(double operand) { return operand * operand; }
+
         @Override
-        public String toString() { return "f(a)(acos(a))"; }
+        public String toString() { return "f(a)(a * a)"; }
+
     }
 
     public static class Sqrt implements DoubleUnaryOperator {
+
         @Override
         public double applyAsDouble(double operand) { return Math.sqrt(operand); }
+
         @Override
         public String toString() { return "f(a)(sqrt(a))"; }
+
     }
 
-    public static class Square implements DoubleUnaryOperator {
+    public static class Exponent implements DoubleUnaryOperator {
 
         @Override
-        public double applyAsDouble(double operand) { return operand * operand; }
+        public double applyAsDouble(double operand) { return Math.exp(operand); }
 
         @Override
-        public String toString() { return "f(a)(a * a)"; }
+        public String toString() { return "f(a)(exp(a))"; }
 
     }
 
-    // Variable-length operators -----------------------------------------------------------------------------
+    public static class Random implements Function<List<Integer>, Double> {
+
+        @Override
+        public Double apply(List<Integer> values) {
+            return ThreadLocalRandom.current().nextDouble();
+        }
+
+        @Override
+        public String toString() { return "random"; }
 
-    public static class EqualElements implements Function<List<Integer>, Double> {        
-        private final ImmutableList<String> argumentNames;        
+    }
+
+    public static class EqualElements implements Function<List<Integer>, Double> {
+        
+        private final ImmutableList<String> argumentNames;
+        
         private EqualElements(List<String> argumentNames) {
             this.argumentNames = ImmutableList.copyOf(argumentNames);
         }
@@ -114,6 +128,7 @@ public class ScalarFunctions {
                     return 0.0;
             return 1.0;
         }
+
         @Override
         public String toString() { 
             if (argumentNames.size() == 0) return "1";
@@ -128,19 +143,13 @@ public class ScalarFunctions {
             }
             return b.toString();
         }
-    }
 
-    public static class Random implements Function<List<Integer>, Double> {
-        @Override
-        public Double apply(List<Integer> values) {
-            return ThreadLocalRandom.current().nextDouble();
-        }
-        @Override
-        public String toString() { return "random"; }
     }
 
     public static class SumElements implements Function<List<Integer>, Double> {
+
         private final ImmutableList<String> argumentNames;
+
         private SumElements(List<String> argumentNames) {
             this.argumentNames = ImmutableList.copyOf(argumentNames);
         }
@@ -152,10 +161,12 @@ public class ScalarFunctions {
                 sum += value;
             return (double)sum;
         }
+
         @Override
         public String toString() {
             return argumentNames.stream().collect(Collectors.joining("+"));
         }
+
     }
 
 }
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/Softmax.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/Softmax.java
index c856b548180..bf279eb24d8 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/Softmax.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/Softmax.java
@@ -2,8 +2,6 @@
 package com.yahoo.tensor.functions;
 
 import com.google.common.annotations.Beta;
-import com.google.common.collect.ImmutableList;
-import com.yahoo.tensor.TensorType;
 
 import java.util.Collections;
 import java.util.List;
@@ -21,10 +19,6 @@ public class Softmax extends CompositeTensorFunction {
         this.argument = argument;
         this.dimension = dimension;
     }
-    
-    public static TensorType outputType(TensorType inputType, String dimension) {
-        return Reduce.outputType(inputType, ImmutableList.of(dimension));
-    }
 
     @Override
     public List<TensorFunction> functionArguments() { return Collections.singletonList(argument); }
diff --git a/vespajlib/src/main/java/com/yahoo/tensor/functions/TensorFunction.java b/vespajlib/src/main/java/com/yahoo/tensor/functions/TensorFunction.java
index 533a46f87fe..cabcce198d1 100644
--- a/vespajlib/src/main/java/com/yahoo/tensor/functions/TensorFunction.java
+++ b/vespajlib/src/main/java/com/yahoo/tensor/functions/TensorFunction.java
@@ -12,7 +12,7 @@ import java.util.List;
  * A representation of a tensor function which is able to be translated to a set of primitive
  * tensor functions if necessary.
  * All tensor functions are immutable.
- *
+ * 
  * @author bratseth
  */
 @Beta
@@ -48,11 +48,11 @@ public abstract class TensorFunction {
 
     /**
      * Return a string representation of this context.
-     *
+     * 
      * @param context a context which must be passed to all nexted functions when requesting the string value
      */
     public abstract String toString(ToStringContext context);
-
+    
     @Override
     public String toString() { return toString(ToStringContext.empty()); }