Indexed tensor implementation

4 files changed, 13 insertions, 15 deletions

diff --git a/container-search/src/main/java/com/yahoo/search/query/profile/types/TensorFieldType.java b/container-search/src/main/java/com/yahoo/search/query/profile/types/TensorFieldType.java
index 747cf73acb3..c45520423e0 100644
--- a/container-search/src/main/java/com/yahoo/search/query/profile/types/TensorFieldType.java
+++ b/container-search/src/main/java/com/yahoo/search/query/profile/types/TensorFieldType.java
@@ -41,7 +41,7 @@ public class TensorFieldType extends FieldType {
     @Override
     public Object convertFrom(Object o, QueryProfileRegistry registry) {
         if (o instanceof Tensor) return o;
-        if (o instanceof String) return MapTensor.from((String)o);
+        if (o instanceof String) return Tensor.from((String)o);
         return null;
     }
 
diff --git a/container-search/src/test/java/com/yahoo/fs4/test/RankFeaturesTestCase.java b/container-search/src/test/java/com/yahoo/fs4/test/RankFeaturesTestCase.java
index 6984af2457f..4044ed80d64 100644
--- a/container-search/src/test/java/com/yahoo/fs4/test/RankFeaturesTestCase.java
+++ b/container-search/src/test/java/com/yahoo/fs4/test/RankFeaturesTestCase.java
@@ -4,7 +4,6 @@ package com.yahoo.fs4.test;
 import com.yahoo.io.GrowableByteBuffer;
 import com.yahoo.search.query.ranking.RankFeatures;
 import com.yahoo.search.query.ranking.RankProperties;
-import com.yahoo.tensor.MapTensor;
 import com.yahoo.tensor.Tensor;
 import com.yahoo.tensor.serialization.TypedBinaryFormat;
 import com.yahoo.text.Utf8;
@@ -31,15 +30,15 @@ public class RankFeaturesTestCase {
 
     @Test
     public void requireThatSingleTensorIsBinaryEncoded() {
-        Tensor tensor = MapTensor.from("{ {x:a, y:b, z:c}:2.0, {x:a, y:b, z:c2}:3.0 }");
+        Tensor tensor = Tensor.from("{ {x:a, y:b, z:c}:2.0, {x:a, y:b, z:c2}:3.0 }");
         assertTensorEncodingAndDecoding("query(my_tensor)", "my_tensor", tensor);
         assertTensorEncodingAndDecoding("$my_tensor", "my_tensor", tensor);
     }
 
     @Test
     public void requireThatMultipleTensorsAreBinaryEncoded() {
-        Tensor tensor1 = MapTensor.from("{ {x:a, y:b, z:c}:2.0, {x:a, y:b, z:c2}:3.0 }");
-        Tensor tensor2 = MapTensor.from("{ {x:a, y:b, z:c}:5.0 }");
+        Tensor tensor1 = Tensor.from("{ {x:a, y:b, z:c}:2.0, {x:a, y:b, z:c2}:3.0 }");
+        Tensor tensor2 = Tensor.from("{ {x:a, y:b, z:c}:5.0 }");
         assertTensorEncodingAndDecoding(Arrays.asList(
                 new Entry("query(tensor1)", "tensor1", tensor1),
                 new Entry("$tensor2", "tensor2", tensor2)));
diff --git a/container-search/src/test/java/com/yahoo/search/query/profile/types/test/QueryProfileTypeTestCase.java b/container-search/src/test/java/com/yahoo/search/query/profile/types/test/QueryProfileTypeTestCase.java
index dce3cfe0d67..6e2ee721752 100644
--- a/container-search/src/test/java/com/yahoo/search/query/profile/types/test/QueryProfileTypeTestCase.java
+++ b/container-search/src/test/java/com/yahoo/search/query/profile/types/test/QueryProfileTypeTestCase.java
@@ -4,7 +4,6 @@ package com.yahoo.search.query.profile.types.test;
 import com.yahoo.component.ComponentId;
 import com.yahoo.container.jdisc.HttpRequest;
 import com.yahoo.prelude.query.QueryException;
-import com.yahoo.tensor.MapTensor;
 import com.yahoo.tensor.Tensor;
 import com.yahoo.yolean.Exceptions;
 import com.yahoo.search.Query;
@@ -393,8 +392,8 @@ public class QueryProfileTypeTestCase extends junit.framework.TestCase {
                                                               "=" + encode(tensorString),
                                                               com.yahoo.jdisc.http.HttpRequest.Method.GET), cRegistry.getComponent("test"));
         assertEquals(0, query.errors().size());
-        assertEquals(MapTensor.from(tensorString), query.properties().get("ranking.features.query(myTensor1)"));
-        assertEquals(MapTensor.from(tensorString), query.getRanking().getFeatures().getTensor("query(myTensor1)").get());
+        assertEquals(Tensor.from(tensorString), query.properties().get("ranking.features.query(myTensor1)"));
+        assertEquals(Tensor.from(tensorString), query.getRanking().getFeatures().getTensor("query(myTensor1)").get());
     }
 
     private String encode(String s) throws UnsupportedEncodingException {
diff --git a/container-search/src/test/java/com/yahoo/search/rendering/JsonRendererTestCase.java b/container-search/src/test/java/com/yahoo/search/rendering/JsonRendererTestCase.java
index 75363074a00..f49cb8d569f 100644
--- a/container-search/src/test/java/com/yahoo/search/rendering/JsonRendererTestCase.java
+++ b/container-search/src/test/java/com/yahoo/search/rendering/JsonRendererTestCase.java
@@ -15,7 +15,7 @@ import java.util.concurrent.ExecutionException;
 import com.yahoo.document.datatypes.TensorFieldValue;
 import com.yahoo.document.predicate.Predicate;
 
-import com.yahoo.tensor.MapTensor;
+import com.yahoo.tensor.Tensor;
 import org.json.JSONArray;
 import org.json.JSONException;
 import org.json.JSONObject;
@@ -72,7 +72,7 @@ import org.mockito.Mockito;
 /**
  * Functional testing of {@link JsonRenderer}.
  *
- * @author <a href="mailto:steinar@yahoo-inc.com">Steinar Knutsen</a>
+ * @author Steinar Knutsen
  */
 public class JsonRendererTestCase {
 
@@ -172,13 +172,13 @@ public class JsonRendererTestCase {
         Result r = newEmptyResult();
         Hit h = new Hit("datatypestuff");
         // the floating point values are chosen to get a deterministic string representation
-        h.setField("double", Double.valueOf(0.00390625d));
-        h.setField("float", Float.valueOf(14.29f));
-        h.setField("integer", Integer.valueOf(1));
-        h.setField("long", Long.valueOf(4398046511104L));
+        h.setField("double", 0.00390625d);
+        h.setField("float", 14.29f);
+        h.setField("integer", 1);
+        h.setField("long", 4398046511104L);
         h.setField("string", "stuff");
         h.setField("predicate", Predicate.fromString("a in [b]"));
-        h.setField("tensor", new TensorFieldValue(MapTensor.from("{ {x:a}: 2.0}")));
+        h.setField("tensor", new TensorFieldValue(Tensor.from("{ {x:a}: 2.0}")));
         h.setField("object", new Thingie());
         r.hits().add(h);
         r.setTotalHitCount(1L);