Add bfloat16 and int8 tensor cell types in Java

6 files changed, 183 insertions, 8 deletions

diff --git a/vespajlib/src/test/java/com/yahoo/tensor/TensorTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/TensorTestCase.java
index 5bd1bbdba37..b47c0873535 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/TensorTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/TensorTestCase.java
@@ -50,6 +50,35 @@ public class TensorTestCase {
         assertEquals(Tensor.from("tensor<float>(x[1]):{{x:0}:5}").getClass(), IndexedFloatTensor.class);
         assertEquals(Tensor.Builder.of(TensorType.fromSpec("tensor<float>(x[1])")).cell(5.0, 0).build().getClass(),
                      IndexedFloatTensor.class);
+
+        assertEquals(Tensor.from("tensor<bfloat16>(x[1]):[5]").getClass(), IndexedFloatTensor.class);
+        assertEquals(Tensor.Builder.of(TensorType.fromSpec("tensor<bfloat16>(x[1])")).cell(5.0, 0).build().getClass(),
+                IndexedFloatTensor.class);
+
+        assertEquals(Tensor.from("tensor<int8>(x[1]):[5]").getClass(), IndexedFloatTensor.class);
+        assertEquals(Tensor.Builder.of(TensorType.fromSpec("tensor<int8>(x[1])")).cell(5.0, 0).build().getClass(),
+                IndexedFloatTensor.class);
+    }
+
+    private void assertCellTypeResult(TensorType.Value valueType, String type1, String type2) {
+        Tensor t1 = Tensor.from("tensor<" + type1 + ">(x[1]):[3] }");
+        Tensor t2 = Tensor.from("tensor<" + type2 + ">(x[1]):[5] }");
+        assertEquals(valueType, t1.multiply(t2).type().valueType());
+        assertEquals(valueType, t2.multiply(t1).type().valueType());
+    }
+
+    @Test
+    public void testValueTypeResolving() {
+        assertCellTypeResult(TensorType.Value.DOUBLE, "double", "double");
+        assertCellTypeResult(TensorType.Value.DOUBLE, "double", "float");
+        assertCellTypeResult(TensorType.Value.DOUBLE, "double", "bfloat16");
+        assertCellTypeResult(TensorType.Value.DOUBLE, "double", "int8");
+        assertCellTypeResult(TensorType.Value.FLOAT, "float", "float");
+        assertCellTypeResult(TensorType.Value.FLOAT, "float", "bfloat16");
+        assertCellTypeResult(TensorType.Value.FLOAT, "float", "int8");
+        assertCellTypeResult(TensorType.Value.FLOAT, "bfloat16", "bfloat16");
+        assertCellTypeResult(TensorType.Value.FLOAT, "bfloat16", "int8");
+        assertCellTypeResult(TensorType.Value.FLOAT, "int8", "int8");
     }
 
     @Test
diff --git a/vespajlib/src/test/java/com/yahoo/tensor/TensorTypeTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/TensorTypeTestCase.java
index a547f941d8e..caa125dfef7 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/TensorTypeTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/TensorTypeTestCase.java
@@ -96,8 +96,12 @@ public class TensorTypeTestCase {
         assertValueType(TensorType.Value.DOUBLE, "tensor(x[])");
         assertValueType(TensorType.Value.DOUBLE, "tensor<double>(x[])");
         assertValueType(TensorType.Value.FLOAT, "tensor<float>(x[])");
+        assertValueType(TensorType.Value.BFLOAT16, "tensor<bfloat16>(x[])");
+        assertValueType(TensorType.Value.INT8, "tensor<int8>(x[])");
         assertEquals("tensor(x[])", TensorType.fromSpec("tensor<double>(x[])").toString());
         assertEquals("tensor<float>(x[])", TensorType.fromSpec("tensor<float>(x[])").toString());
+        assertEquals("tensor<bfloat16>(x[])", TensorType.fromSpec("tensor<bfloat16>(x[])").toString());
+        assertEquals("tensor<int8>(x[])", TensorType.fromSpec("tensor<int8>(x[])").toString());
     }
 
     private static void assertTensorType(String typeSpec) {
diff --git a/vespajlib/src/test/java/com/yahoo/tensor/serialization/DenseBinaryFormatTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/serialization/DenseBinaryFormatTestCase.java
index 5d1bc7b0c3f..3c79b0c769c 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/serialization/DenseBinaryFormatTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/serialization/DenseBinaryFormatTestCase.java
@@ -41,7 +41,7 @@ public class DenseBinaryFormatTestCase {
     }
 
     @Test
-    public void requireThatDefaultSerializationFormatDoNotChange() {
+    public void requireThatDefaultSerializationFormatDoesNotChange() {
         byte[] encodedTensor = new byte[]{2, // binary format type
                                           2, // dimension count
                                           2, (byte) 'x', (byte) 'y', 2, // dimension xy with size
@@ -54,7 +54,7 @@ public class DenseBinaryFormatTestCase {
     }
 
     @Test
-    public void requireThatFloatSerializationFormatDoNotChange() {
+    public void requireThatFloatSerializationFormatDoesNotChange() {
         byte[] encodedTensor = new byte[]{6, // binary format type
                 1, // float type
                 2, // dimension count
@@ -68,9 +68,44 @@ public class DenseBinaryFormatTestCase {
     }
 
     @Test
+    public void requireThatBFloat16SerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[]{6, // binary format type
+                2, // bfloat16 type
+                2, // dimension count
+                2, (byte) 'x', (byte) 'y', 2, // dimension xy with size
+                1, (byte) 'z', 1, // dimension z with size
+                64, 0,   // value 1
+                64, 64,  // value 2
+        };
+        Tensor tensor = Tensor.from("tensor<bfloat16>(xy[],z[]):{{xy:0,z:0}:2.0,{xy:1,z:0}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
+    public void requireThatInt8SerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[]{6, // binary format type
+                3, // int8 type
+                2, // dimension count
+                2, (byte) 'x', (byte) 'y', 2, // dimension xy with size
+                1, (byte) 'z', 1, // dimension z with size
+                2,  // value 1
+                3,  // value 2
+        };
+        Tensor tensor = Tensor.from("tensor<int8>(xy[],z[]):{{xy:0,z:0}:2.0,{xy:1,z:0}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
     public void testSerializationOfDifferentValueTypes() {
+        assertSerialization("tensor(x[],y[]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
         assertSerialization("tensor<double>(x[],y[]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
         assertSerialization("tensor<float>(x[],y[]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
+        assertSerialization("tensor<bfloat16>(x[],y[]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
+        assertSerialization("tensor<int8>(x[],y[]):{{x:0,y:0}:2, {x:0,y:1}:3, {x:1,y:0}:4, {x:1,y:1}:5}");
+        assertSerialization("tensor<double>(x[2],y[2]):[2.0, 3.0, 4.0, 5.0]");
+        assertSerialization("tensor<float>(x[2],y[2]):[2.0, 3.0, 4.0, 5.0]");
+        assertSerialization("tensor<bfloat16>(x[2],y[2]):[2.0, 3.0, 4.0, 5.0]");
+        assertSerialization("tensor<int8>(x[2],y[2]):[2, 3, 4, 5]");
     }
 
     private void assertSerialization(String tensorString) {
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 81de8a9db4c..3ca20661587 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/serialization/JsonFormatTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/serialization/JsonFormatTestCase.java
@@ -134,4 +134,19 @@ public class JsonFormatTestCase {
         }
     }
 
+    private void assertEncodeDecode(Tensor tensor) {
+        Tensor decoded = JsonFormat.decode(tensor.type(), JsonFormat.encodeWithType(tensor));
+        assertEquals(tensor, decoded);
+        assertEquals(tensor.type(), decoded.type());
+    }
+
+    @Test
+    public void testTensorCellTypes() {
+        assertEncodeDecode(Tensor.from("tensor(x[2],y[2]):[2.0, 3.0, 5.0 ,8.0]"));
+        assertEncodeDecode(Tensor.from("tensor<double>(x[2],y[2]):[2.0, 3.0, 5.0 ,8.0]"));
+        assertEncodeDecode(Tensor.from("tensor<float>(x[2],y[2]):[2.0, 3.0, 5.0 ,8.0]"));
+        assertEncodeDecode(Tensor.from("tensor<bfloat16>(x[2],y[2]):[2.0, 3.0, 5.0 ,8.0]"));
+        assertEncodeDecode(Tensor.from("tensor<int8>(x[2],y[2]):[2,3,5,8]"));
+    }
+
 }
diff --git a/vespajlib/src/test/java/com/yahoo/tensor/serialization/MixedBinaryFormatTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/serialization/MixedBinaryFormatTestCase.java
index 69ef4922d8d..e9f8c81f21b 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/serialization/MixedBinaryFormatTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/serialization/MixedBinaryFormatTestCase.java
@@ -8,6 +8,7 @@ import com.yahoo.tensor.Tensor;
 import com.yahoo.tensor.TensorType;
 import org.junit.Test;
 
+import java.util.Arrays;
 import java.util.Optional;
 
 import static org.junit.Assert.assertEquals;
@@ -78,9 +79,70 @@ public class MixedBinaryFormatTestCase {
     }
 
     @Test
+    public void requireThatDefaultSerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[] {3, // binary format type
+                1, // number of sparse dimensions
+                2, (byte)'x', (byte)'y',  // name of sparse dimension
+                1, // number of dense dimensions
+                1, (byte)'z', 1, // name and size of dense dimension
+                2, // num cells,
+                2, (byte)'a', (byte)'b', 64, 0, 0, 0, 0, 0, 0, 0, // cell 0
+                2, (byte)'c', (byte)'d', 64, 8, 0, 0, 0, 0, 0, 0}; // cell 1
+        Tensor tensor = Tensor.from("tensor(xy{},z[1]):{{xy:ab,z:0}:2.0,{xy:cd,z:0}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
+    public void requireThatFloatSerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[] {7, // binary format type
+                1, // float type
+                1, // number of sparse dimensions
+                2, (byte)'x', (byte)'y',  // name of sparse dimension
+                1, // number of dense dimensions
+                1, (byte)'z', 1, // name and size of dense dimension
+                2, // num cells,
+                2, (byte)'a', (byte)'b', 64, 0, 0, 0,  // cell 0
+                2, (byte)'c', (byte)'d', 64, 64, 0, 0}; // cell 1
+        Tensor tensor = Tensor.from("tensor<float>(xy{},z[1]):{{xy:ab,z:0}:2.0,{xy:cd,z:0}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
+    public void requireThatBFloat16SerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[] {7, // binary format type
+                2, // bfloat16 type
+                1, // number of sparse dimensions
+                2, (byte)'x', (byte)'y',  // name of sparse dimension
+                1, // number of dense dimensions
+                1, (byte)'z', 1, // name and size of dense dimension
+                2, // num cells,
+                2, (byte)'a', (byte)'b', 64, 0,  // cell 0
+                2, (byte)'c', (byte)'d', 64, 64}; // cell 1
+        Tensor tensor = Tensor.from("tensor<bfloat16>(xy{},z[1]):{{xy:ab,z:0}:2.0,{xy:cd,z:0}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
+    public void requireThatInt8SerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[] {7, // binary format type
+                3, // int8 type
+                1, // number of sparse dimensions
+                2, (byte)'x', (byte)'y',  // name of sparse dimension
+                1, // number of dense dimensions
+                1, (byte)'z', 1, // name and size of dense dimension
+                2, // num cells,
+                2, (byte)'a', (byte)'b', 2,  // cell 0
+                2, (byte)'c', (byte)'d', 3}; // cell 1
+        Tensor tensor = Tensor.from("tensor<int8>(xy{},z[1]):{{xy:ab,z:0}:2.0,{xy:cd,z:0}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
     public void testSerializationOfDifferentValueTypes() {
         assertSerialization("tensor<double>(x{},y[2]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
         assertSerialization("tensor<float>(x{},y[2]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
+        assertSerialization("tensor<bfloat16>(x{},y[2]):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
+        assertSerialization("tensor<int8>(x{},y[2]):{{x:0,y:0}:2, {x:0,y:1}:3, {x:1,y:0}:4, {x:1,y:1}:5}");
     }
 
     private void assertSerialization(String tensorString) {
diff --git a/vespajlib/src/test/java/com/yahoo/tensor/serialization/SparseBinaryFormatTestCase.java b/vespajlib/src/test/java/com/yahoo/tensor/serialization/SparseBinaryFormatTestCase.java
index 50b71024ddf..2a622b73513 100644
--- a/vespajlib/src/test/java/com/yahoo/tensor/serialization/SparseBinaryFormatTestCase.java
+++ b/vespajlib/src/test/java/com/yahoo/tensor/serialization/SparseBinaryFormatTestCase.java
@@ -55,19 +55,19 @@ public class SparseBinaryFormatTestCase {
     }
 
     @Test
-    public void requireThatSerializationFormatDoNotChange() {
+    public void requireThatSerializationFormatDoesNotChange() {
         byte[] encodedTensor = new byte[] {1, // binary format type
                 2, // num dimensions
                 2, (byte)'x', (byte)'y', 1, (byte)'z', // dimensions
                 2, // num cells,
                 2, (byte)'a', (byte)'b', 1, (byte)'e', 64, 0, 0, 0, 0, 0, 0, 0, // cell 0
                 2, (byte)'c', (byte)'d', 1, (byte)'e', 64, 8, 0, 0, 0, 0, 0, 0}; // cell 1
-        assertEquals(Arrays.toString(encodedTensor),
-                Arrays.toString(TypedBinaryFormat.encode(Tensor.from("tensor(xy{},z{}):{{xy:ab,z:e}:2.0,{xy:cd,z:e}:3.0}"))));
+        Tensor tensor = Tensor.from("tensor(xy{},z{}):{{xy:ab,z:e}:2.0,{xy:cd,z:e}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
     }
 
     @Test
-    public void requireThatFloatSerializationFormatDoNotChange() {
+    public void requireThatFloatSerializationFormatDoesNotChange() {
         byte[] encodedTensor = new byte[] {
                 5, // binary format type
                 1, // float type
@@ -76,14 +76,44 @@ public class SparseBinaryFormatTestCase {
                 2, // num cells,
                 2, (byte)'a', (byte)'b', 1, (byte)'e', 64, 0, 0, 0, // cell 0
                 2, (byte)'c', (byte)'d', 1, (byte)'e', 64, 64, 0, 0}; // cell 1
-        assertEquals(Arrays.toString(encodedTensor),
-                     Arrays.toString(TypedBinaryFormat.encode(Tensor.from("tensor<float>(xy{},z{}):{{xy:ab,z:e}:2.0,{xy:cd,z:e}:3.0}"))));
+        Tensor tensor = Tensor.from("tensor<float>(xy{},z{}):{{xy:ab,z:e}:2.0,{xy:cd,z:e}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
+    public void requireThatBFloat16SerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[] {
+                5, // binary format type
+                2, // bfloat16 type
+                2, // num dimensions
+                2, (byte)'x', (byte)'y', 1, (byte)'z', // dimensions
+                2, // num cells,
+                2, (byte)'a', (byte)'b', 1, (byte)'e', 64, 0,   // cell 0
+                2, (byte)'c', (byte)'d', 1, (byte)'e', 64, 64}; // cell 1
+        Tensor tensor = Tensor.from("tensor<bfloat16>(xy{},z{}):{{xy:ab,z:e}:2.0,{xy:cd,z:e}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
+    }
+
+    @Test
+    public void requireThatInt8SerializationFormatDoesNotChange() {
+        byte[] encodedTensor = new byte[] {
+                5, // binary format type
+                3, // int8 type
+                2, // num dimensions
+                2, (byte)'x', (byte)'y', 1, (byte)'z', // dimensions
+                2, // num cells,
+                2, (byte)'a', (byte)'b', 1, (byte)'e', 2,  // cell 0
+                2, (byte)'c', (byte)'d', 1, (byte)'e', 3}; // cell 1
+        Tensor tensor = Tensor.from("tensor<int8>(xy{},z{}):{{xy:ab,z:e}:2.0,{xy:cd,z:e}:3.0}");
+        assertEquals(Arrays.toString(encodedTensor), Arrays.toString(TypedBinaryFormat.encode(tensor)));
     }
 
     @Test
     public void testSerializationOfDifferentValueTypes() {
         assertSerialization("tensor<double>(x{},y{}):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
         assertSerialization("tensor<float>(x{},y{}):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
+        assertSerialization("tensor<bfloat16>(x{},y{}):{{x:0,y:0}:2.0, {x:0,y:1}:3.0, {x:1,y:0}:4.0, {x:1,y:1}:5.0}");
+        assertSerialization("tensor<int8>(x{},y{}):{{x:0,y:0}:2, {x:0,y:1}:3, {x:1,y:0}:4, {x:1,y:1}:5}");
     }
 
     private void assertSerialization(String tensorString) {