Merge pull request #13521 from vespa-engine/bratseth/disallow-unbound-dimensions

Bratseth/disallow unbound dimensions

24 files changed, 162 insertions, 133 deletions

diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java b/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java
index 8b2a190feb9..d309f48d6df 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/RankProfile.java
@@ -304,6 +304,12 @@ public class RankProfile implements Cloneable {
     }
 
     public void addConstant(String name, Value value) {
+        if (value instanceof TensorValue) {
+            TensorType type = ((TensorValue)value).type();
+            if (type.dimensions().stream().anyMatch(d -> d.isIndexed() && d.size().isEmpty()))
+                throw new IllegalArgumentException("Illegal type of constant " + name + " type " + type +
+                                                   ": Dense tensor dimensions must have a size");
+        }
         constants.put(name, value.freeze());
     }
 
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstant.java b/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstant.java
index 7b7265e02ae..b41cf582204 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstant.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/RankingConstant.java
@@ -56,7 +56,9 @@ public class RankingConstant {
         this.pathType = PathType.URI;
     }
 
-    public void setType(TensorType tensorType) { this.tensorType = tensorType; }
+    public void setType(TensorType type) {
+        this.tensorType = type;
+    }
 
     /** Initiate sending of this constant to some services over file distribution */
     public void sendTo(Collection<? extends AbstractService> services) {
@@ -78,6 +80,9 @@ public class RankingConstant {
             throw new IllegalArgumentException("Ranking constants must have a file or uri.");
         if (tensorType == null)
             throw new IllegalArgumentException("Ranking constant '" + name + "' must have a type.");
+        if (tensorType.dimensions().stream().anyMatch(d -> d.isIndexed() && d.size().isEmpty()))
+            throw new IllegalArgumentException("Illegal type in field " + name + " type " + tensorType +
+                                               ": Dense tensor dimensions must have a size");
     }
 
     public String toString() {
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/document/SDField.java b/config-model/src/main/java/com/yahoo/searchdefinition/document/SDField.java
index 30ce142d503..e36635ba6b8 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/document/SDField.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/document/SDField.java
@@ -7,12 +7,14 @@ import com.yahoo.document.DocumentType;
 import com.yahoo.document.Field;
 import com.yahoo.document.MapDataType;
 import com.yahoo.document.StructDataType;
+import com.yahoo.document.TensorDataType;
 import com.yahoo.language.Linguistics;
 import com.yahoo.language.simple.SimpleLinguistics;
 import com.yahoo.searchdefinition.Index;
 import com.yahoo.searchdefinition.Search;
 import com.yahoo.searchdefinition.fieldoperation.FieldOperation;
 import com.yahoo.searchdefinition.fieldoperation.FieldOperationContainer;
+import com.yahoo.tensor.TensorType;
 import com.yahoo.vespa.documentmodel.SummaryField;
 import com.yahoo.vespa.indexinglanguage.ExpressionSearcher;
 import com.yahoo.vespa.indexinglanguage.ExpressionVisitor;
@@ -116,9 +118,10 @@ public class SDField extends Field implements TypedKey, FieldOperationContainer,
     private boolean isExtraField = false;
 
     /**
-     * Creates a new field. This method is only used to create reserved fields
-     * @param name The name of the field
-     * @param dataType The datatype of the field
+     * Creates a new field. This method is only used to create reserved fields.
+     *
+     * @param name the name of the field
+     * @param dataType the datatype of the field
     */
     protected SDField(SDDocumentType repo, String name, int id, DataType dataType, boolean populate) {
         super(name, id, dataType);
@@ -129,64 +132,36 @@ public class SDField extends Field implements TypedKey, FieldOperationContainer,
         this(repo, name, id, dataType, true);
     }
 
-    /**
-       Creates a new field.
-
-       @param name The name of the field
-       @param dataType The datatype of the field
-    */
+    /** Creates a new field */
     public SDField(SDDocumentType repo, String name, DataType dataType, boolean populate) {
-        super(name,dataType);
+        super(name, dataType);
         populate(populate, repo, name, dataType);
     }
 
-    private void populate(boolean populate, SDDocumentType repo, String name, DataType dataType) {
-        populate(populate,repo, name, dataType, null, 0);
-    }
-
-    private void populate(boolean populate, SDDocumentType repo, String name, DataType dataType, Matching fieldMatching,  int recursion) {
-        if (populate || (dataType instanceof MapDataType)) {
-            populateWithStructFields(repo, name, dataType, recursion);
-            populateWithStructMatching(repo, name, dataType, fieldMatching);
-        }
-    }
-
-
-    /**
-     * Creates a new field.
-     *
-     * @param name The name of the field
-     * @param dataType The datatype of the field
-     * @param owner the owning document (used to check for id collisions)
-     */
+    /** Creates a new field */
     protected SDField(SDDocumentType repo, String name, DataType dataType, SDDocumentType owner, boolean populate) {
         super(name, dataType, owner == null ? null : owner.getDocumentType());
-        this.ownerDocType=owner;
+        this.ownerDocType = owner;
         populate(populate, repo, name, dataType);
     }
 
     /**
-     * Creates a new field.
+     * Creates a new field
      *
-     * @param name The name of the field
-     * @param dataType The datatype of the field
-     * @param owner The owning document (used to check for id collisions)
-     * @param fieldMatching The matching object to set for the field
+     * @param name the name of the field
+     * @param dataType the datatype of the field
+     * @param owner the owning document (used to check for id collisions)
+     * @param fieldMatching the matching object to set for the field
      */
     protected SDField(SDDocumentType repo, String name, DataType dataType, SDDocumentType owner,
                       Matching fieldMatching, boolean populate, int recursion) {
         super(name, dataType, owner == null ? null : owner.getDocumentType());
-        this.ownerDocType=owner;
+        this.ownerDocType = owner;
         if (fieldMatching != null)
             this.setMatching(fieldMatching);
         populate(populate, repo, name, dataType, fieldMatching, recursion);
     }
 
-    /**
-     *
-     * @param name The name of the field
-     * @param dataType The datatype of the field
-     */
     public SDField(SDDocumentType repo,  String name, DataType dataType) {
         this(repo, name,dataType, true);
     }
@@ -194,6 +169,23 @@ public class SDField extends Field implements TypedKey, FieldOperationContainer,
         this(null, name,dataType);
     }
 
+    private void populate(boolean populate, SDDocumentType repo, String name, DataType dataType) {
+        populate(populate, repo, name, dataType, null, 0);
+    }
+
+    private void populate(boolean populate, SDDocumentType repo, String name, DataType dataType, Matching fieldMatching,  int recursion) {
+        if (dataType instanceof TensorDataType) {
+            TensorType type = ((TensorDataType)dataType).getTensorType();
+            if (type.dimensions().stream().anyMatch(d -> d.isIndexed() && d.size().isEmpty()))
+                throw new IllegalArgumentException("Illegal type in field " + name + " type " + type +
+                                                   ": Dense tensor dimensions must have a size");
+        }
+        if (populate || (dataType instanceof MapDataType)) {
+            populateWithStructFields(repo, name, dataType, recursion);
+            populateWithStructMatching(repo, name, dataType, fieldMatching);
+        }
+    }
+
     public void setIsExtraField(boolean isExtra) {
         isExtraField = isExtra;
     }
diff --git a/config-model/src/main/java/com/yahoo/searchdefinition/document/TemporarySDField.java b/config-model/src/main/java/com/yahoo/searchdefinition/document/TemporarySDField.java
index 04d11792379..2921253461d 100644
--- a/config-model/src/main/java/com/yahoo/searchdefinition/document/TemporarySDField.java
+++ b/config-model/src/main/java/com/yahoo/searchdefinition/document/TemporarySDField.java
@@ -4,7 +4,7 @@ package com.yahoo.searchdefinition.document;
 import com.yahoo.document.DataType;
 
 /**
- * @author <a href="mailto:einarmr@yahoo-inc.com">Einar M R Rosenvinge</a>
+ * @author Einar M R Rosenvinge
  */
 public class TemporarySDField extends SDField {
 
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidator.java b/config-model/src/main/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidator.java
index c6bf54af760..75e6922ad15 100644
--- a/config-model/src/main/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidator.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidator.java
@@ -90,7 +90,7 @@ public class ConstantTensorJsonValidator {
                         validateTensorValue();
                     }
                 } else {
-                    throw new InvalidConstantTensor(parser, "Only \"address\" or \"value\" fields are permitted within a cell object");
+                    throw new InvalidConstantTensor(parser, "Only 'address' or 'value' fields are permitted within a cell object");
                 }
             }
 
@@ -110,55 +110,52 @@ public class ConstantTensorJsonValidator {
             String dimensionName = parser.getCurrentName();
             TensorType.Dimension dimension = tensorDimensions.get(dimensionName);
             if (dimension == null) {
-                throw new InvalidConstantTensor(parser, String.format("Tensor dimension \"%s\" does not exist", parser.getCurrentName()));
+                throw new InvalidConstantTensor(parser, String.format("Tensor dimension '%s' does not exist", parser.getCurrentName()));
             }
 
             if (!cellDimensions.contains(dimensionName)) {
-                throw new InvalidConstantTensor(parser, String.format("Duplicate tensor dimension \"%s\"", parser.getCurrentName()));
+                throw new InvalidConstantTensor(parser, String.format("Duplicate tensor dimension '%s'", parser.getCurrentName()));
             }
 
             cellDimensions.remove(dimensionName);
-            validateTensorCoordinate(dimension);
+            validateLabel(dimension);
         }
 
         if (!cellDimensions.isEmpty()) {
-            throw new InvalidConstantTensor(parser, String.format("Tensor address missing dimension(s): %s", Joiner.on(", ").join(cellDimensions)));
+            throw new InvalidConstantTensor(parser, String.format("Tensor address missing dimension(s) %s", Joiner.on(", ").join(cellDimensions)));
         }
     }
 
-    /*
-     * Tensor coordinates are always strings. Coordinates for a mapped dimension can be any string,
+    /**
+     * Tensor labels are always strings. Labels for a mapped dimension can be any string,
      * but those for indexed dimensions needs to be able to be interpreted as integers, and,
      * additionally, those for indexed bounded dimensions needs to fall within the dimension size.
      */
-    private void validateTensorCoordinate(TensorType.Dimension dimension) throws IOException {
+    private void validateLabel(TensorType.Dimension dimension) throws IOException {
         JsonToken token = parser.nextToken();
-        if (token != JsonToken.VALUE_STRING) {
-            throw new InvalidConstantTensor(parser, String.format("Tensor coordinate is not a string (%s)", token.toString()));
-        }
+        if (token != JsonToken.VALUE_STRING)
+            throw new InvalidConstantTensor(parser, String.format("Tensor label is not a string (%s)", token.toString()));
 
         if (dimension instanceof TensorType.IndexedBoundDimension) {
-            validateBoundedCoordinate((TensorType.IndexedBoundDimension) dimension);
+            validateBoundIndex((TensorType.IndexedBoundDimension) dimension);
         } else if (dimension instanceof TensorType.IndexedUnboundDimension) {
-            validateUnboundedCoordinate(dimension);
+            validateUnboundIndex(dimension);
         }
     }
 
-    private void validateBoundedCoordinate(TensorType.IndexedBoundDimension dimension) {
+    private void validateBoundIndex(TensorType.IndexedBoundDimension dimension) {
         wrapIOException(() -> {
             try {
                 int value = Integer.parseInt(parser.getValueAsString());
-                if (value >= dimension.size().get()) {
-                    throw new InvalidConstantTensor(parser, String.format("Coordinate \"%s\" not within limits of bounded dimension %s", value, dimension.name()));
-
-                }
+                if (value >= dimension.size().get())
+                    throw new InvalidConstantTensor(parser, String.format("Index %s not within limits of bound dimension '%s'", value, dimension.name()));
             } catch (NumberFormatException e) {
                 throwCoordinateIsNotInteger(parser.getValueAsString(), dimension.name());
             }
         });
     }
 
-    private void validateUnboundedCoordinate(TensorType.Dimension dimension) {
+    private void validateUnboundIndex(TensorType.Dimension dimension) {
         wrapIOException(() -> {
             try {
                 Integer.parseInt(parser.getValueAsString());
@@ -169,7 +166,7 @@ public class ConstantTensorJsonValidator {
     }
 
     private void throwCoordinateIsNotInteger(String value, String dimensionName) {
-        throw new InvalidConstantTensor(parser, String.format("Coordinate \"%s\" for dimension %s is not an integer", value, dimensionName));
+        throw new InvalidConstantTensor(parser, String.format("Index '%s' for dimension '%s' is not an integer", value, dimensionName));
     }
 
     private void validateTensorValue() throws IOException {
@@ -198,11 +195,12 @@ public class ConstantTensorJsonValidator {
         String actualFieldName = parser.getCurrentName();
 
         if (!actualFieldName.equals(wantedFieldName)) {
-            throw new InvalidConstantTensor(parser, String.format("Expected field name \"%s\", got \"%s\"", wantedFieldName, actualFieldName));
+            throw new InvalidConstantTensor(parser, String.format("Expected field name '%s', got '%s'", wantedFieldName, actualFieldName));
         }
     }
 
     static class InvalidConstantTensor extends RuntimeException {
+
         InvalidConstantTensor(JsonParser parser, String message) {
             super(message + " " + parser.getCurrentLocation().toString());
         }
@@ -210,6 +208,7 @@ public class ConstantTensorJsonValidator {
         InvalidConstantTensor(JsonParser parser, Exception base) {
             super("Failed to parse JSON stream " + parser.getCurrentLocation().toString(), base);
         }
+
     }
 
     @FunctionalInterface
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidator.java b/config-model/src/main/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidator.java
index 9568ea5c27c..cf8a9201668 100644
--- a/config-model/src/main/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidator.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidator.java
@@ -31,7 +31,7 @@ public class RankingConstantsValidator extends Validator {
 
         public ExceptionMessageCollector add(Throwable throwable, String rcName, String rcFilename) {
             exceptionsOccurred = true;
-            combinedMessage += String.format("\nRanking constant \"%s\" (%s): %s", rcName, rcFilename, throwable.getMessage());
+            combinedMessage += String.format("\nRanking constant '%s' (%s): %s", rcName, rcFilename, throwable.getMessage());
             return this;
         }
     }
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/container/search/QueryProfiles.java b/config-model/src/main/java/com/yahoo/vespa/model/container/search/QueryProfiles.java
index 0a9618e7b08..079baf6fe7d 100644
--- a/config-model/src/main/java/com/yahoo/vespa/model/container/search/QueryProfiles.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/container/search/QueryProfiles.java
@@ -9,6 +9,7 @@ import com.yahoo.search.query.profile.SubstituteString;
 import com.yahoo.search.query.profile.types.FieldDescription;
 import com.yahoo.search.query.profile.types.QueryProfileType;
 import com.yahoo.search.query.profile.config.QueryProfilesConfig;
+import com.yahoo.tensor.TensorType;
 
 import java.io.Serializable;
 import java.util.ArrayList;
@@ -56,6 +57,7 @@ public class QueryProfiles implements Serializable, QueryProfilesConfig.Producer
         Set<String> tensorFields = new HashSet<>();
         for (QueryProfileType type : registry.getTypeRegistry().allComponents()) {
             for (var fieldEntry : type.fields().entrySet()) {
+                validateTensorField(fieldEntry.getKey(), fieldEntry.getValue().getType().asTensorType());
                 if (fieldEntry.getValue().getType().asTensorType().rank() > 0)
                     tensorFields.add(fieldEntry.getKey());
             }
@@ -73,6 +75,12 @@ public class QueryProfiles implements Serializable, QueryProfilesConfig.Producer
 
     }
 
+    private void validateTensorField(String fieldName, TensorType type) {
+        if (type.dimensions().stream().anyMatch(d -> d.isIndexed() && d.size().isEmpty()))
+            throw new IllegalArgumentException("Illegal type in field " + fieldName + " type " + type +
+                                               ": Dense tensor dimensions must have a size");
+    }
+
     @Override
     public void getConfig(QueryProfilesConfig.Builder builder) {
         for (QueryProfile profile : registry.allComponents()) {
diff --git a/config-model/src/main/java/com/yahoo/vespa/model/ml/ConvertedModel.java b/config-model/src/main/java/com/yahoo/vespa/model/ml/ConvertedModel.java
index c3d6f457ce8..f8b48da291d 100644
--- a/config-model/src/main/java/com/yahoo/vespa/model/ml/ConvertedModel.java
+++ b/config-model/src/main/java/com/yahoo/vespa/model/ml/ConvertedModel.java
@@ -448,7 +448,7 @@ public class ConvertedModel {
                         int i = rename.fromDimensions().indexOf(dimension.name());
                         if (i < 0) {
                             throw new IllegalArgumentException("Rename does not contain dimension '" +
-                                    dimension + "' in child expression type: " + childType);
+                                                               dimension + "' in child expression type: " + childType);
                         }
                         from.add((String)rename.fromDimensions().get(i));
                         to.add((String)rename.toDimensions().get(i));
diff --git a/config-model/src/test/cfg/application/ml_models/searchdefinitions/test.sd b/config-model/src/test/cfg/application/ml_models/searchdefinitions/test.sd
index 247df8a0241..6d10c50e80a 100644
--- a/config-model/src/test/cfg/application/ml_models/searchdefinitions/test.sd
+++ b/config-model/src/test/cfg/application/ml_models/searchdefinitions/test.sd
@@ -2,7 +2,7 @@
 search test {
 
     document test {
-        field argument type tensor<float>(d0[],d1[784]) {
+        field argument type tensor<float>(d0[1],d1[784]) {
             indexing: attribute
         }
     }
diff --git a/config-model/src/test/cfg/application/validation/ranking_constants_fail/searchdefinitions/simple.sd b/config-model/src/test/cfg/application/validation/ranking_constants_fail/searchdefinitions/simple.sd
index 126f8d00724..8b782a01946 100644
--- a/config-model/src/test/cfg/application/validation/ranking_constants_fail/searchdefinitions/simple.sd
+++ b/config-model/src/test/cfg/application/validation/ranking_constants_fail/searchdefinitions/simple.sd
@@ -4,12 +4,12 @@ search simple {
 
   constant constant_tensor_1 {
     file: tensors/constant_tensor_1.json
-    type: tensor(x[], y[])
+    type: tensor(x[4], y[3])
   }
 
   constant constant_tensor_2 {
     file: tensors/constant_tensor_2.json
-    type: tensor(x[])
+    type: tensor(x[6])
   }
 
   constant constant_tensor_3 {
@@ -24,6 +24,6 @@ search simple {
 
   constant constant_tensor_5 {
     file: tensors/constant_tensor_5.json
-    type: tensor(x[], y[], z[])
+    type: tensor(x[33], y[10], z[46])
   }
 }
diff --git a/config-model/src/test/cfg/application/validation/ranking_constants_ok/searchdefinitions/simple.sd b/config-model/src/test/cfg/application/validation/ranking_constants_ok/searchdefinitions/simple.sd
index 126f8d00724..8b782a01946 100644
--- a/config-model/src/test/cfg/application/validation/ranking_constants_ok/searchdefinitions/simple.sd
+++ b/config-model/src/test/cfg/application/validation/ranking_constants_ok/searchdefinitions/simple.sd
@@ -4,12 +4,12 @@ search simple {
 
   constant constant_tensor_1 {
     file: tensors/constant_tensor_1.json
-    type: tensor(x[], y[])
+    type: tensor(x[4], y[3])
   }
 
   constant constant_tensor_2 {
     file: tensors/constant_tensor_2.json
-    type: tensor(x[])
+    type: tensor(x[6])
   }
 
   constant constant_tensor_3 {
@@ -24,6 +24,6 @@ search simple {
 
   constant constant_tensor_5 {
     file: tensors/constant_tensor_5.json
-    type: tensor(x[], y[], z[])
+    type: tensor(x[33], y[10], z[46])
   }
 }
diff --git a/config-model/src/test/derived/tensor/documenttypes.cfg b/config-model/src/test/derived/tensor/documenttypes.cfg
index 68bd394c9d6..bbf9759659b 100644
--- a/config-model/src/test/derived/tensor/documenttypes.cfg
+++ b/config-model/src/test/derived/tensor/documenttypes.cfg
@@ -23,7 +23,7 @@ documenttype[].datatype[].sstruct.compression.minsize 200
 documenttype[].datatype[].sstruct.field[].name "f1"
 documenttype[].datatype[].sstruct.field[].id 26661415
 documenttype[].datatype[].sstruct.field[].datatype 21
-documenttype[].datatype[].sstruct.field[].detailedtype "tensor(x[])"
+documenttype[].datatype[].sstruct.field[].detailedtype "tensor(x[3])"
 documenttype[].datatype[].sstruct.field[].name "f2"
 documenttype[].datatype[].sstruct.field[].id 2080644671
 documenttype[].datatype[].sstruct.field[].datatype 21
diff --git a/config-model/src/test/derived/tensor/tensor.sd b/config-model/src/test/derived/tensor/tensor.sd
index a7248fe3200..44a84a3cbb3 100644
--- a/config-model/src/test/derived/tensor/tensor.sd
+++ b/config-model/src/test/derived/tensor/tensor.sd
@@ -2,7 +2,7 @@
 search tensor {
 
   document tensor {
-    field f1 type tensor(x[]) {
+    field f1 type tensor(x[3]) {
       indexing: summary
     }
     field f2 type tensor<float>(x[2],y[1]) {
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/RankProfileTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/RankProfileTestCase.java
index e2f2c1fd407..0f83a4db98f 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/RankProfileTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/RankProfileTestCase.java
@@ -125,7 +125,7 @@ public class RankProfileTestCase extends SchemaTestCase {
                 "  document test { \n" +
                 "    field a type tensor(x[10]) { indexing: attribute }\n" +
                 "    field b type tensor(y{}) { indexing: attribute }\n" +
-                "    field c type tensor(x[]) { indexing: attribute }\n" +
+                "    field c type tensor(x[5]) { indexing: attribute }\n" +
                 "  }\n" +
                 "  rank-profile p1 {}\n" +
                 "  rank-profile p2 {}\n" +
@@ -140,11 +140,28 @@ public class RankProfileTestCase extends SchemaTestCase {
         assertAttributeTypeSettings(registry.get(search, "p2"), search);
     }
 
+    @Test
+    public void requireThatDenseDimensionsMustBeBound() throws ParseException {
+        try {
+            SearchBuilder builder = new SearchBuilder(new RankProfileRegistry());
+            builder.importString("search test {\n" +
+                                 "  document test { \n" +
+                                 "    field a type tensor(x[]) { indexing: attribute }\n" +
+                                 "  }\n" +
+                                 "}");
+            builder.build();
+        }
+        catch (IllegalArgumentException e) {
+            assertEquals("Illegal type in field a type tensor(x[]): Dense tensor dimensions must have a size",
+                         e.getMessage());
+        }
+    }
+
     private static void assertAttributeTypeSettings(RankProfile profile, Search search) {
         RawRankProfile rawProfile = new RawRankProfile(profile, new QueryProfileRegistry(), new ImportedMlModels(), new AttributeFields(search));
         assertEquals("tensor(x[10])", findProperty(rawProfile.configProperties(), "vespa.type.attribute.a").get());
         assertEquals("tensor(y{})", findProperty(rawProfile.configProperties(), "vespa.type.attribute.b").get());
-        assertEquals("tensor(x[])", findProperty(rawProfile.configProperties(), "vespa.type.attribute.c").get());
+        assertEquals("tensor(x[5])", findProperty(rawProfile.configProperties(), "vespa.type.attribute.c").get());
     }
 
     @Test
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/RankingExpressionShadowingTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/RankingExpressionShadowingTestCase.java
index e4ca83640e9..02d1c3fc3b0 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/RankingExpressionShadowingTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/RankingExpressionShadowingTestCase.java
@@ -159,7 +159,7 @@ public class RankingExpressionShadowingTestCase extends SchemaTestCase {
     public void testNeuralNetworkSetup() throws ParseException {
         // Note: the type assigned to query profile and constant tensors here is not the correct type
         RankProfileRegistry rankProfileRegistry = new RankProfileRegistry();
-        QueryProfileRegistry queryProfiles = queryProfileWith("query(q)", "tensor(x[])");
+        QueryProfileRegistry queryProfiles = queryProfileWith("query(q)", "tensor(x[1])");
         SearchBuilder builder = new SearchBuilder(rankProfileRegistry, queryProfiles);
         builder.importString(
                 "search test {\n" +
@@ -184,19 +184,19 @@ public class RankingExpressionShadowingTestCase extends SchemaTestCase {
                         "        }\n" +
                         "    }\n" +
                         "    constant W_hidden {\n" +
-                        "        type: tensor(x[])\n" +
+                        "        type: tensor(x[1])\n" +
                         "        file: ignored.json\n" +
                         "    }\n" +
                         "    constant b_input {\n" +
-                        "        type: tensor(x[])\n" +
+                        "        type: tensor(x[1])\n" +
                         "        file: ignored.json\n" +
                         "    }\n" +
                         "    constant W_final {\n" +
-                        "        type: tensor(x[])\n" +
+                        "        type: tensor(x[1])\n" +
                         "        file: ignored.json\n" +
                         "    }\n" +
                         "    constant b_final {\n" +
-                        "        type: tensor(x[])\n" +
+                        "        type: tensor(x[1])\n" +
                         "        file: ignored.json\n" +
                         "    }\n" +
                         "}\n");
@@ -211,11 +211,11 @@ public class RankingExpressionShadowingTestCase extends SchemaTestCase {
                 censorBindingHash(testRankProperties.get(0).toString()));
         assertEquals("(rankingExpression(hidden_layer).rankingScript,rankingExpression(relu@))",
                 censorBindingHash(testRankProperties.get(1).toString()));
-        assertEquals("(rankingExpression(hidden_layer).type,tensor(x[]))",
+        assertEquals("(rankingExpression(hidden_layer).type,tensor(x[1]))",
                 censorBindingHash(testRankProperties.get(2).toString()));
         assertEquals("(rankingExpression(final_layer).rankingScript,sigmoid(reduce(rankingExpression(hidden_layer) * constant(W_final), sum, hidden) + constant(b_final)))",
                 testRankProperties.get(3).toString());
-        assertEquals("(rankingExpression(final_layer).type,tensor(x[]))",
+        assertEquals("(rankingExpression(final_layer).type,tensor(x[1]))",
                 testRankProperties.get(4).toString());
         assertEquals("(rankingExpression(relu).rankingScript,max(1.0,x))",
                      testRankProperties.get(5).toString());
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/FastAccessValidatorTest.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/FastAccessValidatorTest.java
index 994538deed6..71277f136f8 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/FastAccessValidatorTest.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/FastAccessValidatorTest.java
@@ -39,7 +39,7 @@ public class FastAccessValidatorTest {
                         "            indexing: attribute ",
                         "            attribute: fast-access",
                         "        }",
-                        "        field tensor_attribute type tensor(x[]) {",
+                        "        field tensor_attribute type tensor(x[5]) {",
                         "            indexing: attribute ",
                         "            attribute: fast-access",
                         "        }",
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/ImportedFieldsResolverTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/ImportedFieldsResolverTestCase.java
index c679bb7e61f..b7db9134b88 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/ImportedFieldsResolverTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/ImportedFieldsResolverTestCase.java
@@ -114,7 +114,7 @@ public class ImportedFieldsResolverTestCase {
             parentSearch.getDocument().addField(createField("attribute_field", DataType.INT, "{ attribute }"));
             parentSearch.getDocument().addField(createField("attribute_and_index", DataType.INT, "{ attribute | index }"));
             parentSearch.getDocument().addField(new TemporarySDField("not_attribute", DataType.INT));
-            parentSearch.getDocument().addField(createField("tensor_field", new TensorDataType(TensorType.fromSpec("tensor(x[])")), "{ attribute }"));
+            parentSearch.getDocument().addField(createField("tensor_field", new TensorDataType(TensorType.fromSpec("tensor(x[5])")), "{ attribute }"));
             parentSearch.getDocument().addField(createField("predicate_field", DataType.PREDICATE, "{ attribute }"));
             addRefField(parentSearch, grandParentSearch, "ref");
             addImportedField(parentSearch, "ancient_field", "ref", "ancient_field");
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionTypeResolverTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionTypeResolverTestCase.java
index a306e0f2c90..96f12a47a2f 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionTypeResolverTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionTypeResolverTestCase.java
@@ -37,7 +37,7 @@ public class RankingExpressionTypeResolverTestCase {
             builder.importString(joinLines(
                     "search test {",
                     "  document test { ",
-                    "    field a type tensor(x[],y[]) {",
+                    "    field a type tensor(x[10],y[3]) {",
                     "      indexing: attribute",
                     "    }",
                     "  }",
@@ -52,7 +52,7 @@ public class RankingExpressionTypeResolverTestCase {
             fail("Expected exception");
         }
         catch (IllegalArgumentException expected) {
-            assertEquals("In search definition 'test', rank profile 'my_rank_profile': The first-phase expression must produce a double (a tensor with no dimensions), but produces tensor(x[],y[])",
+            assertEquals("In search definition 'test', rank profile 'my_rank_profile': The first-phase expression must produce a double (a tensor with no dimensions), but produces tensor(x[10],y[3])",
                          Exceptions.toMessageString(expected));
         }
     }
@@ -64,7 +64,7 @@ public class RankingExpressionTypeResolverTestCase {
             builder.importString(joinLines(
                     "search test {",
                     "  document test { ",
-                    "    field a type tensor(x[],y[]) {",
+                    "    field a type tensor(x[10],y[3]) {",
                     "      indexing: attribute",
                     "    }",
                     "  }",
@@ -82,7 +82,7 @@ public class RankingExpressionTypeResolverTestCase {
             fail("Expected exception");
         }
         catch (IllegalArgumentException expected) {
-            assertEquals("In search definition 'test', rank profile 'my_rank_profile': The second-phase expression must produce a double (a tensor with no dimensions), but produces tensor(x[],y[])",
+            assertEquals("In search definition 'test', rank profile 'my_rank_profile': The second-phase expression must produce a double (a tensor with no dimensions), but produces tensor(x[10],y[3])",
                          Exceptions.toMessageString(expected));
         }
     }
@@ -94,7 +94,7 @@ public class RankingExpressionTypeResolverTestCase {
             searchBuilder.importString(joinLines(
                     "search test {",
                     "  document test { ",
-                    "    field a type tensor(x[],y[]) {",
+                    "    field a type tensor(x[10],y[5]) {",
                     "      indexing: attribute",
                     "    }",
                     "    field b type tensor(z[10]) {",
@@ -112,7 +112,7 @@ public class RankingExpressionTypeResolverTestCase {
             fail("Expected exception");
         }
         catch (IllegalArgumentException expected) {
-            assertEquals("In search definition 'test', rank profile 'my_rank_profile': The first-phase expression is invalid: An if expression must produce compatible types in both alternatives, but the 'true' type is tensor(x[],y[]) while the 'false' type is tensor(z[10])" +
+            assertEquals("In search definition 'test', rank profile 'my_rank_profile': The first-phase expression is invalid: An if expression must produce compatible types in both alternatives, but the 'true' type is tensor(x[10],y[5]) while the 'false' type is tensor(z[10])" +
                          "\n'true' branch: attribute(a)" +
                          "\n'false' branch: attribute(b)",
                          Exceptions.toMessageString(expected));
@@ -126,7 +126,7 @@ public class RankingExpressionTypeResolverTestCase {
         builder.importString(joinLines(
                 "search test {",
                 "  document test { ",
-                "    field a type tensor(x[],y[]) {",
+                "    field a type tensor(x[10],y[3]) {",
                 "      indexing: attribute",
                 "    }",
                 "    field b type tensor(z[10]) {",
@@ -147,7 +147,7 @@ public class RankingExpressionTypeResolverTestCase {
         builder.build();
         RankProfile profile =
                 builder.getRankProfileRegistry().get(builder.getSearch(), "my_rank_profile");
-        assertEquals(TensorType.fromSpec("tensor(x[],y[])"),
+        assertEquals(TensorType.fromSpec("tensor(x[10],y[3])"),
                      summaryFeatures(profile).get("macro1(a)").type(profile.typeContext(builder.getQueryProfileRegistry())));
         assertEquals(TensorType.fromSpec("tensor(z[10])"),
                      summaryFeatures(profile).get("macro1(b)").type(profile.typeContext(builder.getQueryProfileRegistry())));
@@ -159,7 +159,7 @@ public class RankingExpressionTypeResolverTestCase {
         builder.importString(joinLines(
                 "search test {",
                 "  document test { ",
-                "    field a type tensor(x[],y[]) {",
+                "    field a type tensor(x[10],y[1]) {",
                 "      indexing: attribute",
                 "    }",
                 "    field b type tensor(z[10]) {",
@@ -189,7 +189,7 @@ public class RankingExpressionTypeResolverTestCase {
         builder.build();
         RankProfile profile =
                 builder.getRankProfileRegistry().get(builder.getSearch(), "my_rank_profile");
-        assertEquals(TensorType.fromSpec("tensor(x[],y[])"),
+        assertEquals(TensorType.fromSpec("tensor(x[10],y[1])"),
                      summaryFeatures(profile).get("return_a").type(profile.typeContext(builder.getQueryProfileRegistry())));
         assertEquals(TensorType.fromSpec("tensor(z[10])"),
                      summaryFeatures(profile).get("return_b").type(profile.typeContext(builder.getQueryProfileRegistry())));
@@ -201,7 +201,7 @@ public class RankingExpressionTypeResolverTestCase {
         builder.importString(joinLines(
                 "search parent {",
                 "  document parent {",
-                "    field a type tensor(x[],y[]) {",
+                "    field a type tensor(x[5],y[1000]) {",
                 "      indexing: attribute",
                 "    }",
                 "  }",
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithOnnxTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithOnnxTestCase.java
index 4387d19c474..1fe1ebf2bb3 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithOnnxTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithOnnxTestCase.java
@@ -29,6 +29,7 @@ public class RankingExpressionWithOnnxTestCase {
     private final static String name = "mnist_softmax";
 
     private final static String vespaExpression = "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(" + name + "_Variable), f(a,b)(a * b)), sum, d2), constant(" + name + "_Variable_1), f(a,b)(a + b))";
+    private final static String vespaExpressionWithBatchReduce = "join(join(reduce(join(reduce(rename(Placeholder, (d0, d1), (d0, d2)), sum, d0), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b)), tensor<float>(d0[1])(1.0), f(a,b)(a * b))";
 
     @After
     public void removeGeneratedModelFiles() {
@@ -93,10 +94,10 @@ public class RankingExpressionWithOnnxTestCase {
         RankProfileSearchFixture search = fixtureWith("attribute(mytensor)",
                 "onnx('mnist_softmax.onnx')",
                 null,
-                "field mytensor type tensor<float>(d0[],d1[784]) { indexing: attribute }",
+                "field mytensor type tensor<float>(d0[1],d1[784]) { indexing: attribute }",
                 "Placeholder",
                 application);
-        search.assertFirstPhaseExpression(vespaExpression, "my_profile");
+        search.assertFirstPhaseExpression(vespaExpressionWithBatchReduce, "my_profile");
     }
 
 
@@ -105,18 +106,16 @@ public class RankingExpressionWithOnnxTestCase {
         String queryProfile = "<query-profile id='default' type='root'/>";
         String queryProfileType =
                 "<query-profile-type id='root'>" +
-                "  <field name='query(mytensor)' type='tensor&lt;float&gt;(d0[3],d1[784],d2[10])'/>" +
+                "  <field name='query(mytensor)' type='tensor&lt;float&gt;(d0[1],d1[784],d2[10])'/>" +
                 "</query-profile-type>";
-        StoringApplicationPackage application = new StoringApplicationPackage(applicationDir,
-                queryProfile,
-                queryProfileType);
+        StoringApplicationPackage application = new StoringApplicationPackage(applicationDir, queryProfile, queryProfileType);
         RankProfileSearchFixture search = fixtureWith("sum(query(mytensor) * attribute(mytensor) * constant(mytensor),d2)",
                 "onnx('mnist_softmax.onnx')",
-                "constant mytensor { file: ignored\ntype: tensor<float>(d0[7],d1[784]) }",
-                "field mytensor type tensor<float>(d0[],d1[784]) { indexing: attribute }",
+                "constant mytensor { file: ignored\ntype: tensor<float>(d0[1],d1[784]) }",
+                "field mytensor type tensor<float>(d0[1],d1[784]) { indexing: attribute }",
                 "Placeholder",
                 application);
-        search.assertFirstPhaseExpression(vespaExpression, "my_profile");
+        search.assertFirstPhaseExpression(vespaExpressionWithBatchReduce, "my_profile");
     }
 
 
diff --git a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java
index 680f2dd9659..126a41e14ad 100644
--- a/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java
+++ b/config-model/src/test/java/com/yahoo/searchdefinition/processing/RankingExpressionWithTensorFlowTestCase.java
@@ -44,6 +44,7 @@ public class RankingExpressionWithTensorFlowTestCase {
     private final String name = "mnist_softmax_saved";
 
     private final String vespaExpression = "join(reduce(join(rename(Placeholder, (d0, d1), (d0, d2)), constant(" + name + "_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(" + name + "_layer_Variable_1_read), f(a,b)(a + b))";
+    private final static String vespaExpressionWithBatchReduce = "join(join(reduce(join(reduce(rename(Placeholder, (d0, d1), (d0, d2)), sum, d0), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))";
 
     @After
     public void removeGeneratedModelFiles() {
@@ -114,28 +115,28 @@ public class RankingExpressionWithTensorFlowTestCase {
         RankProfileSearchFixture search = fixtureWith("attribute(mytensor)",
                                                       "tensorflow('mnist_softmax/saved')",
                                                       null,
-                                                      "field mytensor type tensor(d0[],d1[784]) { indexing: attribute }",
+                                                      "field mytensor type tensor(d0[1],d1[784]) { indexing: attribute }",
                                                       "Placeholder",
                                                       application);
-        search.assertFirstPhaseExpression(vespaExpression, "my_profile");
+        search.assertFirstPhaseExpression(vespaExpressionWithBatchReduce, "my_profile");
     }
 
     @Test
     public void testTensorFlowReferenceWithFeatureCombination() {
         String queryProfile = "<query-profile id='default' type='root'/>";
         String queryProfileType = "<query-profile-type id='root'>" +
-                                  "  <field name='query(mytensor)' type='tensor(d0[3],d1[784],d2[10])'/>" +
+                                  "  <field name='query(mytensor)' type='tensor(d0[1],d1[784],d2[10])'/>" +
                                   "</query-profile-type>";
         StoringApplicationPackage application = new StoringApplicationPackage(applicationDir,
                                                                               queryProfile,
                                                                               queryProfileType);
         RankProfileSearchFixture search = fixtureWith("sum(query(mytensor) * attribute(mytensor) * constant(mytensor),d2)",
                                                       "tensorflow('mnist_softmax/saved')",
-                                                      "constant mytensor { file: ignored\ntype: tensor(d0[7],d1[784]) }",
-                                                      "field mytensor type tensor(d0[],d1[784]) { indexing: attribute }",
+                                                      "constant mytensor { file: ignored\ntype: tensor(d0[1],d1[784]) }",
+                                                      "field mytensor type tensor(d0[1],d1[784]) { indexing: attribute }",
                                                       "Placeholder",
                                                       application);
-        search.assertFirstPhaseExpression(vespaExpression, "my_profile");
+        search.assertFirstPhaseExpression(vespaExpressionWithBatchReduce, "my_profile");
     }
 
     @Test
diff --git a/config-model/src/test/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidatorTest.java b/config-model/src/test/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidatorTest.java
index 1f8dcc2da64..b594a3329d1 100644
--- a/config-model/src/test/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidatorTest.java
+++ b/config-model/src/test/java/com/yahoo/vespa/model/application/validation/ConstantTensorJsonValidatorTest.java
@@ -86,9 +86,9 @@ public class ConstantTensorJsonValidatorTest {
     }
 
     @Test
-    public void ensure_that_bounded_tensor_outside_limits_is_disallowed() {
+    public void ensure_that_bound_tensor_outside_limits_is_disallowed() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Coordinate \"5\" not within limits of bounded dimension x");
+        expectedException.expectMessage("Index 5 not within limits of bound dimension 'x'");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[5], y[10])"),
@@ -119,9 +119,9 @@ public class ConstantTensorJsonValidatorTest {
     }
 
     @Test
-    public void ensure_that_non_integer_strings_in_address_points_are_disallowed_unbounded() {
+    public void ensure_that_non_integer_strings_in_address_points_are_disallowed_unbound() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Coordinate \"a\" for dimension x is not an integer");
+        expectedException.expectMessage("Index 'a' for dimension 'x' is not an integer");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[])"),
@@ -139,7 +139,7 @@ public class ConstantTensorJsonValidatorTest {
     @Test
     public void ensure_that_tensor_coordinates_are_strings() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Tensor coordinate is not a string (VALUE_NUMBER_INT)");
+        expectedException.expectMessage("Tensor label is not a string (VALUE_NUMBER_INT)");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[])"),
@@ -157,7 +157,7 @@ public class ConstantTensorJsonValidatorTest {
     @Test
     public void ensure_that_non_integer_strings_in_address_points_are_disallowed_bounded() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Coordinate \"a\" for dimension x is not an integer");
+        expectedException.expectMessage("Index 'a' for dimension 'x' is not an integer");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[5])"),
@@ -175,7 +175,7 @@ public class ConstantTensorJsonValidatorTest {
     @Test
     public void ensure_that_missing_coordinates_fail() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Tensor address missing dimension(s): y, z");
+        expectedException.expectMessage("Tensor address missing dimension(s) y, z");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[], y[], z[])"),
@@ -211,7 +211,7 @@ public class ConstantTensorJsonValidatorTest {
     @Test
     public void ensure_that_extra_dimensions_are_disallowed() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Tensor dimension \"z\" does not exist");
+        expectedException.expectMessage("Tensor dimension 'z' does not exist");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[], y[])"),
@@ -229,7 +229,7 @@ public class ConstantTensorJsonValidatorTest {
     @Test
     public void ensure_that_duplicate_dimensions_are_disallowed() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Duplicate tensor dimension \"y\"");
+        expectedException.expectMessage("Duplicate tensor dimension 'y'");
 
         validateTensorJson(
                 TensorType.fromSpec("tensor(x[], y[])"),
@@ -265,7 +265,7 @@ public class ConstantTensorJsonValidatorTest {
     @Test
     public void ensure_that_invalid_json_not_in_tensor_format_fails() {
         expectedException.expect(InvalidConstantTensor.class);
-        expectedException.expectMessage("Expected field name \"cells\", got \"stats\"");
+        expectedException.expectMessage("Expected field name 'cells', got 'stats'");
 
         validateTensorJson(TensorType.fromSpec("tensor(x[], y[])"),
                 inputJsonToReader(
diff --git a/config-model/src/test/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidatorTest.java b/config-model/src/test/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidatorTest.java
index d99fd93d5eb..dbf6013b167 100644
--- a/config-model/src/test/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidatorTest.java
+++ b/config-model/src/test/java/com/yahoo/vespa/model/application/validation/RankingConstantsValidatorTest.java
@@ -9,6 +9,7 @@ import org.junit.rules.ExpectedException;
 import static com.yahoo.vespa.model.application.validation.RankingConstantsValidator.TensorValidationFailed;
 
 public class RankingConstantsValidatorTest {
+
     @Rule
     public ExpectedException expectedException = ExpectedException.none();
 
@@ -20,10 +21,11 @@ public class RankingConstantsValidatorTest {
     @Test
     public void ensure_that_failing_ranking_constants_fails() {
         expectedException.expect(TensorValidationFailed.class);
-        expectedException.expectMessage("Ranking constant \"constant_tensor_2\" (tensors/constant_tensor_2.json): Tensor coordinate is not a string (VALUE_NUMBER_INT)");
-        expectedException.expectMessage("Ranking constant \"constant_tensor_3\" (tensors/constant_tensor_3.json): Tensor dimension \"cd\" does not exist");
-        expectedException.expectMessage("Ranking constant \"constant_tensor_4\" (tensors/constant_tensor_4.json): Tensor dimension \"z\" does not exist");
+        expectedException.expectMessage("Ranking constant 'constant_tensor_2' (tensors/constant_tensor_2.json): Tensor label is not a string (VALUE_NUMBER_INT)");
+        expectedException.expectMessage("Ranking constant 'constant_tensor_3' (tensors/constant_tensor_3.json): Tensor dimension 'cd' does not exist");
+        expectedException.expectMessage("Ranking constant 'constant_tensor_4' (tensors/constant_tensor_4.json): Tensor dimension 'z' does not exist");
 
         new VespaModelCreatorWithFilePkg("src/test/cfg/application/validation/ranking_constants_fail/").create();
     }
+
 }
diff --git a/config-model/src/test/java/com/yahoo/vespa/model/application/validation/change/search/AttributeChangeValidatorTest.java b/config-model/src/test/java/com/yahoo/vespa/model/application/validation/change/search/AttributeChangeValidatorTest.java
index e32bd09bc08..5da36d82a62 100644
--- a/config-model/src/test/java/com/yahoo/vespa/model/application/validation/change/search/AttributeChangeValidatorTest.java
+++ b/config-model/src/test/java/com/yahoo/vespa/model/application/validation/change/search/AttributeChangeValidatorTest.java
@@ -119,12 +119,12 @@ public class AttributeChangeValidatorTest {
                         "Field 'f1' changed: tensor type: 'tensor(x[2])' -> 'tensor(x[3])'", Instant.now()));
 
         new Fixture(
-                "field f1 type tensor(x[]) { indexing: attribute }",
+                "field f1 type tensor(x[5]) { indexing: attribute }",
                 "field f1 type tensor(x[3]) { indexing: attribute }")
                 .assertValidation(newRefeedAction(
                         "tensor-type-change",
                         ValidationOverrides.empty,
-                        "Field 'f1' changed: tensor type: 'tensor(x[])' -> 'tensor(x[3])'", Instant.now()));
+                        "Field 'f1' changed: tensor type: 'tensor(x[5])' -> 'tensor(x[3])'", Instant.now()));
     }
 
     @Test
diff --git a/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java b/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java
index 57dbf132883..5b38e09537d 100644
--- a/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java
+++ b/config-model/src/test/java/com/yahoo/vespa/model/ml/MlModelsTest.java
@@ -63,17 +63,17 @@ public class MlModelsTest {
 
     private final String testProfile =
             "rankingExpression(input).rankingScript: attribute(argument)\n" +
-            "rankingExpression(input).type: tensor<float>(d0[],d1[784])\n" +
-            "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).rankingScript: join(reduce(join(rename(rankingExpression(input), (d0, d1), (d0, d4)), constant(mnist_saved_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(mnist_saved_dnn_hidden1_bias_read), f(a,b)(a + b))\n" +
+            "rankingExpression(input).type: tensor<float>(d0[1],d1[784])\n" +
+            "rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add).rankingScript: join(reduce(join(reduce(rename(rankingExpression(input), (d0, d1), (d0, d4)), sum, d0), constant(mnist_saved_dnn_hidden1_weights_read), f(a,b)(a * b)), sum, d4), constant(mnist_saved_dnn_hidden1_bias_read), f(a,b)(a + b))\n" +
             "rankingExpression(mnist_tensorflow).rankingScript: join(reduce(join(map(join(reduce(join(join(join(0.009999999776482582, rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(a * b)), rankingExpression(imported_ml_function_mnist_saved_dnn_hidden1_add), f(a,b)(max(a,b))), constant(mnist_saved_dnn_hidden2_weights_read), f(a,b)(a * b)), sum, d3), constant(mnist_saved_dnn_hidden2_bias_read), f(a,b)(a + b)), f(a)(1.0507009873554805 * if (a >= 0, a, 1.6732632423543772 * (exp(a) - 1)))), constant(mnist_saved_dnn_outputs_weights_read), f(a,b)(a * b)), sum, d2), constant(mnist_saved_dnn_outputs_bias_read), f(a,b)(a + b))\n" +
             "rankingExpression(Placeholder).rankingScript: attribute(argument)\n" +
-            "rankingExpression(Placeholder).type: tensor<float>(d0[],d1[784])\n" +
-            "rankingExpression(mnist_softmax_tensorflow).rankingScript: join(reduce(join(rename(rankingExpression(Placeholder), (d0, d1), (d0, d2)), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b))\n" +
-            "rankingExpression(mnist_softmax_onnx).rankingScript: join(reduce(join(rename(rankingExpression(Placeholder), (d0, d1), (d0, d2)), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b))\n" +
+            "rankingExpression(Placeholder).type: tensor<float>(d0[1],d1[784])\n" +
+            "rankingExpression(mnist_softmax_tensorflow).rankingScript: join(join(reduce(join(reduce(rename(rankingExpression(Placeholder), (d0, d1), (d0, d2)), sum, d0), constant(mnist_softmax_saved_layer_Variable_read), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_saved_layer_Variable_1_read), f(a,b)(a + b)), tensor(d0[1])(1.0), f(a,b)(a * b))\n" +
+            "rankingExpression(mnist_softmax_onnx).rankingScript: join(join(reduce(join(reduce(rename(rankingExpression(Placeholder), (d0, d1), (d0, d2)), sum, d0), constant(mnist_softmax_Variable), f(a,b)(a * b)), sum, d2), constant(mnist_softmax_Variable_1), f(a,b)(a + b)), tensor<float>(d0[1])(1.0), f(a,b)(a * b))\n" +
             "rankingExpression(my_xgboost).rankingScript: if (f29 < -0.1234567, if (!(f56 >= -0.242398), 1.71218, -1.70044), if (f109 < 0.8723473, -1.94071, 1.85965)) + if (!(f60 >= -0.482947), if (f29 < -4.2387498, 0.784718, -0.96853), -6.23624)\n" +
             "rankingExpression(my_lightgbm).rankingScript: if (!(numerical_2 >= 0.46643291586559305), 2.1594397038037663, if (categorical_2 in [\"k\", \"l\", \"m\"], 2.235297305276056, 2.1792953471546546)) + if (categorical_1 in [\"d\", \"e\"], 0.03070842919354316, if (!(numerical_1 >= 0.5102250691730842), -0.04439151147520909, 0.005117411709368601)) + if (!(numerical_2 >= 0.668665477622446), if (!(numerical_2 >= 0.008118820676863816), -0.15361238490967524, -0.01192330846157292), 0.03499044894987518) + if (!(numerical_1 >= 0.5201391072644542), -0.02141000620783247, if (categorical_1 in [\"a\", \"b\"], -0.004121485787596721, 0.04534090904886873)) + if (categorical_2 in [\"k\", \"l\", \"m\"], if (!(numerical_2 >= 0.27283279016959255), -0.01924803254356527, 0.03643772842347651), -0.02701711918923075)\n" +
             "vespa.rank.firstphase: rankingExpression(firstphase)\n" +
             "rankingExpression(firstphase).rankingScript: rankingExpression(mnist_tensorflow) + rankingExpression(mnist_softmax_tensorflow) + rankingExpression(mnist_softmax_onnx) + rankingExpression(my_xgboost) + rankingExpression(my_lightgbm)\n" +
-            "vespa.type.attribute.argument: tensor<float>(d0[],d1[784])\n";
+            "vespa.type.attribute.argument: tensor<float>(d0[1],d1[784])\n";
 
 }