Make catch exception more specific in tensor transformer

3 files changed, 28 insertions, 18 deletions

diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/ConstantTensorTransformer.java b/config-model/src/main/java/com/yahoo/searchdefinition/ConstantTensorTransformer.java
index b2cd8574076..c75864f81b7 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/ConstantTensorTransformer.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/ConstantTensorTransformer.java
@@ -21,6 +21,8 @@ import java.util.Map;
  */
 class ConstantTensorTransformer extends ExpressionTransformer {
 
+    public static final String CONSTANT = "constant";
+
     private final Map<String, Value> constants;
     private final Map<String, String> rankPropertiesOutput;
 
@@ -64,7 +66,7 @@ class ConstantTensorTransformer extends ExpressionTransformer {
             return node;
         }
         TensorValue tensorValue = (TensorValue)value;
-        String featureName = "constant(" + node.getName() + ")";
+        String featureName = CONSTANT + "(" + node.getName() + ")";
         String tensorType = tensorValue.asTensor().type().toString();
         rankPropertiesOutput.put(featureName + ".value", tensorValue.toString());
         rankPropertiesOutput.put(featureName + ".type", tensorType);
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/TensorTransformer.java b/config-model/src/main/java/com/yahoo/searchdefinition/TensorTransformer.java
index 4dc4db9645a..69e353ceb35 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/TensorTransformer.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/TensorTransformer.java
@@ -20,6 +20,7 @@ import com.yahoo.tensor.functions.Reduce;
 
 import java.util.List;
 import java.util.Map;
+import java.util.Optional;
 
 /**
  * Transforms and simplifies tensor expressions.
@@ -81,28 +82,31 @@ public class TensorTransformer extends ExpressionTransformer {
             return node;
         }
         ExpressionNode arg1 = node.children().get(0);
-        ExpressionNode arg2 = node.children().get(1);
-        if (!potentialDimensionName(arg2)) {
-            return node;
-        }
-        try {
-            String dimension = ((ReferenceNode) arg2).getName();
-            Context context = buildContext(arg1);
-            Value value = arg1.evaluate(context);
-            if (verifyTensorAndDimension(value, dimension)) {
-                return replaceMaxAndMinFunction(node);
+        Optional<String> dimension = dimensionName(node.children().get(1));
+        if (dimension.isPresent()) {
+            try {
+                Context context = buildContext(arg1);
+                Value value = arg1.evaluate(context);
+                if (isTensorWithDimension(value, dimension.get())) {
+                    return replaceMaxAndMinFunction(node);
+                }
+            } catch (IllegalArgumentException e) {
+                // Thrown from evaluate if some variables are not bound, for
+                // instance for a backend rank feature. Means we don't have
+                // enough information to replace expression.
             }
-        } catch (Exception e) {
-            // Don't replace the expression in case of any errors, e.g. unknown values or rank features
         }
         return node;
     }
 
-    private boolean potentialDimensionName(ExpressionNode arg) {
-        return arg instanceof ReferenceNode && ((ReferenceNode) arg).children().size() == 0;
+    private Optional<String> dimensionName(ExpressionNode arg) {
+        if (arg instanceof ReferenceNode && ((ReferenceNode)arg).children().size() == 0) {
+            return Optional.of(((ReferenceNode) arg).getName());
+        }
+        return Optional.empty();
     }
 
-    private boolean verifyTensorAndDimension(Value value, String dimension) {
+    private boolean isTensorWithDimension(Value value, String dimension) {
         if (value instanceof TensorValue) {
             Tensor tensor = ((TensorValue) value).asTensor();
             TensorType type = tensor.type();
@@ -175,6 +179,9 @@ public class TensorTransformer extends ExpressionTransformer {
         }
         String attribute = node.children().get(0).toString();
         Attribute a = search.getAttribute(attribute);
+        if (a == null) {
+            return;
+        }
         Value v;
         if (a.getType() == Attribute.Type.STRING) {
             v = emptyStringValue();
@@ -187,7 +194,7 @@ public class TensorTransformer extends ExpressionTransformer {
     }
 
     private void addIfConstant(ReferenceNode node, Context context) {
-        if (!node.getName().equals("constant")) {
+        if (!node.getName().equals(ConstantTensorTransformer.CONSTANT)) {
             return;
         }
         if (node.children().size() != 1) {
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/TensorTransformTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/TensorTransformTestCase.java
index aa3fd4e9aae..12bdd8d2b5c 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/TensorTransformTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/TensorTransformTestCase.java
@@ -63,7 +63,8 @@ public class TensorTransformTestCase extends SearchDefinitionTestCase {
         assertContainsExpression("min(attribute(double_field) + attribute(tensor_field_1),x)", "reduce(attribute(double_field)+attribute(tensor_field_1),min,x)");
         assertContainsExpression("min(attribute(tensor_field_1) * attribute(tensor_field_2),x)", "reduce(attribute(tensor_field_1)*attribute(tensor_field_2),min,x)");
         assertContainsExpression("min(join(attribute(tensor_field_1),attribute(tensor_field_2),f(x,y)(x*y)),x)", "reduce(join(attribute(tensor_field_1),attribute(tensor_field_2),f(x,y)(x*y)),min,x)");
-        assertContainsExpression("min(join(tensor_field_1,tensor_field_2,f(x,y)(x*y)),x)", "min(join(tensor_field_1,tensor_field_2,f(x,y)(x*y)),x)");
+        assertContainsExpression("min(join(tensor_field_1,tensor_field_2,f(x,y)(x*y)),x)", "min(join(tensor_field_1,tensor_field_2,f(x,y)(x*y)),x)"); // because tensor fields are not in attribute(...)
+        assertContainsExpression("min(join(attribute(tensor_field_1),backend_rank_feature,f(x,y)(x*y)),x)", "min(join(attribute(tensor_field_1),backend_rank_feature,f(x,y)(x*y)),x)");
     }
 
     @Test