Use tensor vocabulary

7 files changed, 16 insertions, 16 deletions

diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gather.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gather.java
index c66022975c7..7ac2f4bff84 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gather.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gather.java
@@ -92,7 +92,7 @@ public class Gather extends IntermediateOperation {
             ExpressionNode indexExpression = new ConstantNode(new DoubleValue(constantValue));
             if (constantValue < 0) {
                 ExpressionNode axisSize = new ConstantNode(new DoubleValue(dataType.dimensions().get(axis).size().get()));
-                indexExpression = new EmbracedNode(new OperationNode(indexExpression, Operator.PLUS, axisSize));
+                indexExpression = new EmbracedNode(new OperationNode(indexExpression, Operator.plus, axisSize));
             }
             addSliceDimension(dataSliceDimensions, dataType.dimensions().get(axis).name(), indexExpression);
         } else {
@@ -125,8 +125,8 @@ public class Gather extends IntermediateOperation {
     /** to support negative indexing */
     private ExpressionNode createIndexExpression(OrderedTensorType dataType, ExpressionNode slice) {
         ExpressionNode axisSize = new ConstantNode(new DoubleValue(dataType.dimensions().get(axis).size().get()));
-        ExpressionNode plus = new EmbracedNode(new OperationNode(slice, Operator.PLUS, axisSize));
-        ExpressionNode mod = new OperationNode(plus, Operator.MODULO, axisSize);
+        ExpressionNode plus = new EmbracedNode(new OperationNode(slice, Operator.plus, axisSize));
+        ExpressionNode mod = new OperationNode(plus, Operator.modulo, axisSize);
         return mod;
     }
 
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gemm.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gemm.java
index 81d633dea4b..97bfdda385e 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gemm.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Gemm.java
@@ -99,7 +99,7 @@ public class Gemm extends IntermediateOperation {
         TensorFunction<Reference> alphaxAxB = new TensorFunctionNode.ExpressionTensorFunction(
                 new OperationNode(
                         new TensorFunctionNode(AxB),
-                        Operator.MULTIPLY,
+                        Operator.multiply,
                         new ConstantNode(new DoubleValue(alpha))));
 
         if (inputs.size() == 3) {
@@ -107,7 +107,7 @@ public class Gemm extends IntermediateOperation {
             TensorFunction<Reference> betaxC = new TensorFunctionNode.ExpressionTensorFunction(
                     new OperationNode(
                             new TensorFunctionNode(cFunction.get()),
-                            Operator.MULTIPLY,
+                            Operator.multiply,
                             new ConstantNode(new DoubleValue(beta))));
             return new com.yahoo.tensor.functions.Join<>(alphaxAxB, betaxC, ScalarFunctions.add());
         }
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Range.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Range.java
index 66e810b954e..9a38ab9dfde 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Range.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Range.java
@@ -65,8 +65,8 @@ public class Range extends IntermediateOperation {
         ExpressionNode startExpr = new ConstantNode(new DoubleValue(start));
         ExpressionNode deltaExpr = new ConstantNode(new DoubleValue(delta));
         ExpressionNode dimExpr = new EmbracedNode(new ReferenceNode(dimensionName));
-        ExpressionNode stepExpr = new OperationNode(deltaExpr, Operator.MULTIPLY, dimExpr);
-        ExpressionNode addExpr = new OperationNode(startExpr, Operator.PLUS, stepExpr);
+        ExpressionNode stepExpr = new OperationNode(deltaExpr, Operator.multiply, dimExpr);
+        ExpressionNode addExpr = new OperationNode(startExpr, Operator.plus, stepExpr);
         TensorFunction<Reference> function = Generate.bound(type.type(), wrapScalar(addExpr));
         return function;
     }
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Reshape.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Reshape.java
index ce93461bff3..bc94fc6aa76 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Reshape.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Reshape.java
@@ -157,13 +157,13 @@ public class Reshape extends IntermediateOperation {
                 inputDimensionExpression = new EmbracedNode(new ConstantNode(DoubleValue.zero));
             } else if (dim == (inputType.rank() - 1)) {
                 ExpressionNode size = new ConstantNode(new DoubleValue(inputDimensionSize));
-                ExpressionNode div = new OperationNode(unrolled, Operator.MODULO, size);
+                ExpressionNode div = new OperationNode(unrolled, Operator.modulo, size);
                 inputDimensionExpression = new EmbracedNode(div);
             } else {
                 ExpressionNode size = new ConstantNode(new DoubleValue(innerSize));
                 ExpressionNode previousSize = new ConstantNode(new DoubleValue(previousInnerSize));
-                ExpressionNode mod = new OperationNode(unrolled, Operator.MODULO, previousSize);
-                ExpressionNode div = new OperationNode(new EmbracedNode(mod), Operator.DIVIDE, size);
+                ExpressionNode mod = new OperationNode(unrolled, Operator.modulo, previousSize);
+                ExpressionNode div = new OperationNode(new EmbracedNode(mod), Operator.divide, size);
                 inputDimensionExpression = new EmbracedNode(div);
             }
             dimensionValues.add(new com.yahoo.tensor.functions.Slice.DimensionValue<>(Optional.of(inputDimensionName), wrapScalar(inputDimensionExpression)));
@@ -187,12 +187,12 @@ public class Reshape extends IntermediateOperation {
             TensorType.Dimension dimension = type.dimensions().get(i);
             children.add(0, new ReferenceNode(dimension.name()));
             if (size > 1) {
-                operators.add(0, Operator.MULTIPLY);
+                operators.add(0, Operator.multiply);
                 children.add(0, new ConstantNode(new DoubleValue(size)));
             }
             size *= OrderedTensorType.dimensionSize(dimension);
             if (i > 0) {
-                operators.add(0, Operator.PLUS);
+                operators.add(0, Operator.plus);
             }
         }
         return new OperationNode(children, operators);
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Slice.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Slice.java
index 617e1f00c94..916e9980131 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Slice.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Slice.java
@@ -166,8 +166,8 @@ public class Slice extends IntermediateOperation {
 
             // step * (d0 + start)
             ExpressionNode reference = new ReferenceNode(outputDimensionName);
-            ExpressionNode plus = new EmbracedNode(new OperationNode(reference, Operator.PLUS, startIndex));
-            ExpressionNode mul = new OperationNode(stepSize, Operator.MULTIPLY, plus);
+            ExpressionNode plus = new EmbracedNode(new OperationNode(reference, Operator.plus, startIndex));
+            ExpressionNode mul = new OperationNode(stepSize, Operator.multiply, plus);
 
             dimensionValues.add(new com.yahoo.tensor.functions.Slice.DimensionValue<>(Optional.of(inputDimensionName), wrapScalar(new EmbracedNode(mul))));
         }
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Split.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Split.java
index 42901259821..ef46d222941 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Split.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Split.java
@@ -96,7 +96,7 @@ public class Split extends IntermediateOperation {
         for (int i = 0; i < inputType.rank(); ++i) {
             String inputDimensionName = inputType.dimensions().get(i).name();
             ExpressionNode reference = new ReferenceNode(inputDimensionName);
-            ExpressionNode offset = new OperationNode(reference, Operator.PLUS, new ConstantNode(new DoubleValue(i == axis ? start : 0)));
+            ExpressionNode offset = new OperationNode(reference, Operator.plus, new ConstantNode(new DoubleValue(i == axis ? start : 0)));
             dimensionValues.add(new com.yahoo.tensor.functions.Slice.DimensionValue<>(Optional.of(inputDimensionName), wrapScalar(new EmbracedNode(offset))));
         }
 
diff --git a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Tile.java b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Tile.java
index cd88c625d81..a880bff87be 100644
--- a/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Tile.java
+++ b/model-integration/src/main/java/ai/vespa/rankingexpression/importer/operations/Tile.java
@@ -77,7 +77,7 @@ public class Tile extends IntermediateOperation {
 
             ExpressionNode size = new ConstantNode(new DoubleValue(inputDimensionSize));
             ExpressionNode reference = new ReferenceNode(inputDimensionName);
-            ExpressionNode mod = new OperationNode(reference, Operator.MODULO, size);
+            ExpressionNode mod = new OperationNode(reference, Operator.modulo, size);
             dimensionValues.add(new com.yahoo.tensor.functions.Slice.DimensionValue<>(Optional.of(inputDimensionName), wrapScalar(new EmbracedNode(mod))));
         }