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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package com.yahoo.tensor.serialization;
import com.yahoo.io.GrowableByteBuffer;
import com.yahoo.tensor.MixedTensor;
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;
/**
* Tests for the mixed binary format.
*
* @author lesters
*/
public class MixedBinaryFormatTestCase {
@Test
public void testSerialization() {
assertSerialization("tensor(x{},y[3]):{{x:1,y:0}:1.0,{x:1,y:1}:2.0,{x:1,y:2}:0.0,{x:2,y:0}:4.0,{x:2,y:1}:5.0,{x:2,y:2}:6.0}");
assertSerialization("tensor(x{},y[]):{{x:1,y:0}:1.0,{x:1,y:1}:2.0,{x:1,y:2}:0.0,{x:2,y:0}:4.0,{x:2,y:1}:5.0,{x:2,y:2}:6.0}");
assertSerialization("tensor(x{},y[3],z{}):{{x:x1,y:0,z:z1}:1.0,{x:x1,y:0,z:z2}:2.0,{x:x1,y:1,z:z1}:3.0,{x:x1,y:1,z:z2}:4.0,{x:x1,y:2,z:z1}:5.0,{x:x1,y:2,z:z2}:6.0,{x:x2,y:0,z:z1}:11.0,{x:x2,y:0,z:z2}:12.0,{x:x2,y:1,z:z1}:13.0,{x:x2,y:1,z:z2}:14.0,{x:x2,y:2,z:z1}:15.0,{x:x2,y:2,z:z2}:16.0}");
assertSerialization("tensor(x{},y[],z{}):{{x:x1,y:0,z:z1}:1.0,{x:x1,y:0,z:z2}:2.0,{x:x1,y:1,z:z1}:3.0,{x:x1,y:1,z:z2}:4.0,{x:x1,y:2,z:z1}:5.0,{x:x1,y:2,z:z2}:6.0,{x:x2,y:0,z:z1}:11.0,{x:x2,y:0,z:z2}:12.0,{x:x2,y:1,z:z1}:13.0,{x:x2,y:1,z:z2}:14.0,{x:x2,y:2,z:z1}:15.0,{x:x2,y:2,z:z2}:16.0}");
assertSerialization("tensor(i{},j[2],k{},l[2]):{{i:a,j:0,k:c,l:0}:1.0,{i:a,j:0,k:c,l:1}:2.0,{i:a,j:0,k:d,l:0}:5.0,{i:a,j:0,k:d,l:1}:6.0,{i:a,j:1,k:c,l:0}:3.0,{i:a,j:1,k:c,l:1}:4.0,{i:a,j:1,k:d,l:0}:7.0,{i:a,j:1,k:d,l:1}:8.0,{i:b,j:0,k:c,l:0}:9.0,{i:b,j:0,k:c,l:1}:10.0,{i:b,j:0,k:d,l:0}:13.0,{i:b,j:0,k:d,l:1}:14.0,{i:b,j:1,k:c,l:0}:11.0,{i:b,j:1,k:c,l:1}:12.0,{i:b,j:1,k:d,l:0}:15.0,{i:b,j:1,k:d,l:1}:16.0}");
assertSerialization("tensor(i{},j[],k{},l[]):{{i:a,j:0,k:c,l:0}:1.0,{i:a,j:0,k:c,l:1}:2.0,{i:a,j:0,k:d,l:0}:5.0,{i:a,j:0,k:d,l:1}:6.0,{i:a,j:1,k:c,l:0}:3.0,{i:a,j:1,k:c,l:1}:4.0,{i:a,j:1,k:d,l:0}:7.0,{i:a,j:1,k:d,l:1}:8.0,{i:b,j:0,k:c,l:0}:9.0,{i:b,j:0,k:c,l:1}:10.0,{i:b,j:0,k:d,l:0}:13.0,{i:b,j:0,k:d,l:1}:14.0,{i:b,j:1,k:c,l:0}:11.0,{i:b,j:1,k:c,l:1}:12.0,{i:b,j:1,k:d,l:0}:15.0,{i:b,j:1,k:d,l:1}:16.0}");
}
@Test
public void testOneIndexedSerialization() {
TensorType type = new TensorType.Builder().indexed("y", 3).build();
Tensor tensor = MixedTensor.Builder.of(type).
cell().label("y", 0).value(1).
cell().label("y", 1).value(2).
build();
assertSerialization(tensor);
}
@Test
public void testTwoIndexedSerialization() {
TensorType type = new TensorType.Builder().indexed("x").indexed("y", 3).build();
Tensor tensor = MixedTensor.Builder.of(type).
cell().label("x", 0).label("y", 0).value(1).
cell().label("x", 0).label("y", 1).value(2).
cell().label("x", 1).label("y", 0).value(4).
cell().label("x", 1).label("y", 1).value(5).
cell().label("x", 1).label("y", 2).value(6).
build();
assertSerialization(tensor);
}
@Test
public void testOneMappedSerialization() {
TensorType type = new TensorType.Builder().mapped("x").build();
Tensor tensor = MixedTensor.Builder.of(type).
cell().label("x", "0").value(1).
cell().label("x", "1").value(2).
build();
assertSerialization(tensor);
}
@Test
public void testTwoMappedSerialization() {
TensorType type = new TensorType.Builder().mapped("x").mapped("y").build();
Tensor tensor = MixedTensor.Builder.of(type).
cell().label("x", "0").label("y", "0").value(1).
cell().label("x", "0").label("y", "1").value(2).
cell().label("x", "1").label("y", "0").value(4).
cell().label("x", "1").label("y", "1").value(5).
cell().label("x", "1").label("y", "2").value(6).
build();
assertSerialization(tensor);
}
@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) {
assertSerialization(Tensor.from(tensorString));
}
private void assertSerialization(Tensor tensor) {
assertSerialization(tensor, tensor.type());
}
private void assertSerialization(Tensor tensor, TensorType expectedType) {
byte[] encodedTensor = TypedBinaryFormat.encode(tensor);
Tensor decodedTensor = TypedBinaryFormat.decode(Optional.of(expectedType), GrowableByteBuffer.wrap(encodedTensor));
assertEquals(tensor, decodedTensor);
}
}
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