Support mixed tensor short form JSON

1 files changed, 18 insertions, 18 deletions

diff --git a/vespajlib/src/test/java/com/yahoo/tensor/serialization/JsonFormatTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/serialization/JsonFormatTestCase.java
index 32d62903af5..2878c82b7db 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/serialization/JsonFormatTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/serialization/JsonFormatTestCase.java
@@ -52,24 +52,6 @@ public class JsonFormatTestCase {
     }
 
     @Test
-    public void testMixedTensor() {
-        Tensor.Builder builder = Tensor.Builder.of(TensorType.fromSpec("tensor(x{},y[2])"));
-        builder.cell().label("x", "a").label("y", "0").value(1.0);
-        builder.cell().label("x", "a").label("y", "1").value(2.0);
-        builder.cell().label("x", "b").label("y", "0").value(3.0);
-        builder.cell().label("x", "b").label("y", "1").value(4.0);
-        Tensor tensor = builder.build();
-        byte[] json = JsonFormat.encode(tensor);
-        assertEquals("{\"cells\":[" +
-                     "{\"address\":{\"x\":\"a\"},\"values\":[1.0,2.0]}," +
-                     "{\"address\":{\"x\":\"b\"},\"values\":[3.0,4.0]}" +
-                     "]}",
-                     new String(json, StandardCharsets.UTF_8));
-        Tensor decoded = JsonFormat.decode(tensor.type(), json);
-        assertEquals(tensor, decoded);
-    }
-
-    @Test
     public void testDenseTensorInDenseForm() {
         Tensor.Builder builder = Tensor.Builder.of(TensorType.fromSpec("tensor(x[2],y[3])"));
         builder.cell().label("x", 0).label("y", 0).value(2.0);
@@ -85,6 +67,24 @@ public class JsonFormatTestCase {
     }
 
     @Test
+    public void testMixedTensorInMixedForm() {
+        Tensor.Builder builder = Tensor.Builder.of(TensorType.fromSpec("tensor(x{},y[3])"));
+        builder.cell().label("x", 0).label("y", 0).value(2.0);
+        builder.cell().label("x", 0).label("y", 1).value(3.0);
+        builder.cell().label("x", 0).label("y", 2).value(4.0);
+        builder.cell().label("x", 1).label("y", 0).value(5.0);
+        builder.cell().label("x", 1).label("y", 1).value(6.0);
+        builder.cell().label("x", 1).label("y", 2).value(7.0);
+        Tensor expected = builder.build();
+        String mixedJson = "{\"cells\":[" +
+                           "{\"address\":{\"x\":\"0\"},\"values\":[2.0,3.0,4.0]}," +
+                           "{\"address\":{\"x\":\"1\"},\"values\":[5.0,6.0,7.0]}" +
+                           "]}";
+        Tensor decoded = JsonFormat.decode(expected.type(), mixedJson.getBytes(StandardCharsets.UTF_8));
+        assertEquals(expected, decoded);
+    }
+
+    @Test
     public void testTooManyCells() {
         TensorType x2 = TensorType.fromSpec("tensor(x[2])");
         String json = "{\"cells\":[" +