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// Copyright Vespa.ai. 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.Tensor;
import com.yahoo.tensor.TensorType;
import org.junit.Test;
import java.util.Arrays;
import java.util.Optional;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.fail;
/**
* Tests for the dense binary format.
*
* @author bratseth
*/
public class DenseBinaryFormatTestCase {
@Test
public void testSerialization() {
assertSerialization("{-5.37}");
assertSerialization("tensor(x[]):{{x:0}:2.0}");
assertSerialization("tensor(x[],y[]):{{x:0,y:0}:2.0}");
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(x[1],y[2],z[3]):{{y:0,x:0,z:0}:2.0}");
}
@Test
public void testSerializationToSeparateType() {
assertSerialization(Tensor.from("tensor(x[1],y[1]):{{x:0,y:0}:2.0}"), TensorType.fromSpec("tensor(x[],y[])"));
try {
assertSerialization(Tensor.from("tensor(x[2],y[2]):{{x:0,y:0}:2.0}"), TensorType.fromSpec("tensor(x[1],y[1])"));
fail("Expected exception");
}
catch (IllegalArgumentException expected) {
assertEquals("Type/instance mismatch: A tensor of type tensor(x[2],y[2]) cannot be assigned to type tensor(x[1],y[1])", expected.getMessage());
}
}
@Test
public void requireThatDefaultSerializationFormatDoesNotChange() {
byte[] encodedTensor = new byte[]{2, // binary format type
2, // dimension count
2, (byte) 'x', (byte) 'y', 2, // dimension xy with size
1, (byte) 'z', 1, // dimension z with size
64, 0, 0, 0, 0, 0, 0, 0, // value 1
64, 8, 0, 0, 0, 0, 0, 0 // value 2
};
assertEquals(Arrays.toString(encodedTensor),
Arrays.toString(TypedBinaryFormat.encode(Tensor.from("tensor(xy[],z[]):{{xy:0,z:0}:2.0,{xy:1,z:0}:3.0}"))));
}
@Test
public void requireThatFloatSerializationFormatDoesNotChange() {
byte[] encodedTensor = new byte[]{6, // binary format type
1, // float type
2, // dimension count
2, (byte) 'x', (byte) 'y', 2, // dimension xy with size
1, (byte) 'z', 1, // dimension z with size
64, 0, 0, 0, // value 1
64, 64, 0, 0, // value 2
};
Tensor tensor = Tensor.from("tensor<float>(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 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) {
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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