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// Copyright 2017 Yahoo Holdings. 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.TensorAddress;
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 sparse binary format.
*
* @author geirst
*/
public class SparseBinaryFormatTestCase {
@Test
public void testSerialization() {
assertSerialization("tensor(x{}):{}");
assertSerialization("tensor(x{}):{{x:0}:2.0}");
assertSerialization("tensor(dimX{},dimY{}):{{dimX:labelA,dimY:labelB}:2.0,{dimY:labelC,dimX:labelD}:3.0}");
assertSerialization("tensor(x{},y{}):{{x:0,y:1}:2.0}");
assertSerialization("tensor(x{},y{}):{{x:0,y:1}:2.0,{x:1,y:4}:3.0}");
assertSerialization("tensor(x{},y{},z{}):{{y:0,x:0,z:3}:2.0}");
assertSerialization("tensor(x{},y{},z{}):{{y:0,x:0,z:3}:2.0,{y:1,x:0,z:6}:3.0}");
}
@Test
public void testSerializationFormatIsDecidedByTensorTypeNotImplementationType() {
Tensor sparse = Tensor.Builder.of(TensorType.fromSpec("tensor(x{})"))
.cell(TensorAddress.ofLabels("key1"), 9.1).build();
Tensor sparseAsMixed = MixedTensor.Builder.of(TensorType.fromSpec("tensor(x{})"))
.cell(TensorAddress.ofLabels("key1"), 9.1).build();
byte[] sparseEncoded = TypedBinaryFormat.encode(sparse);
byte[] sparseAsMixedEncoded = TypedBinaryFormat.encode(sparseAsMixed);
assertEquals(Arrays.toString(sparseEncoded), Arrays.toString(sparseAsMixedEncoded));
}
@Test
public void testSerializationToSeparateType() {
try {
assertSerialization(Tensor.from("tensor(x{},y{}):{{x:0,y:0}:2.0}"), TensorType.fromSpec("tensor(x{})"));
fail("Expected exception");
}
catch (IllegalArgumentException expected) {
assertEquals("Type/instance mismatch: A tensor of type tensor(x{},y{}) cannot be assigned to type tensor(x{})", expected.getMessage());
}
}
@Test
public void requireThatSerializationFormatDoNotChange() {
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}"))));
}
@Test
public void requireThatFloatSerializationFormatDoNotChange() {
byte[] encodedTensor = new byte[] {
5, // binary format type
1, // float 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, // 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}"))));
}
@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}");
}
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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