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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.functions;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorAddress;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.evaluation.EvaluationContext;
import com.yahoo.tensor.evaluation.Name;
import org.junit.Ignore;
import org.junit.Test;
import java.util.Collections;
import java.util.HashMap;
import java.util.List;
import static org.junit.Assert.assertEquals;
/**
* @author bratseth
*/
public class DynamicTensorTestCase {
@Test
public void testDynamicIndexedRank1TensorFunction() {
TensorType dense = TensorType.fromSpec("tensor(x[3])");
DynamicTensor<Name> t1 = DynamicTensor.from(dense,
List.of(new Constant(1), new Constant(2), new Constant(3)));
assertEquals(Tensor.from(dense, "[1, 2, 3]"), t1.evaluate());
assertEquals("tensor(x[3]):{{x:0}:1.0,{x:1}:2.0,{x:2}:3.0}", t1.toString());
}
@Test
public void testDynamicMappedRank1TensorFunction() {
TensorType sparse = TensorType.fromSpec("tensor(x{})");
DynamicTensor<Name> t2 = DynamicTensor.from(sparse,
Collections.singletonMap(new TensorAddress.Builder(sparse).add("x", "a").build(),
new Constant(5)));
assertEquals(Tensor.from(sparse, "{{x:a}:5}"), t2.evaluate());
assertEquals("tensor(x{}):{{x:a}:5.0}", t2.toString());
}
@Test
public void testDynamicMappedRank2TensorFunction() {
TensorType sparse = TensorType.fromSpec("tensor(x{},y{})");
HashMap<TensorAddress, ScalarFunction<Name>> values = new HashMap<>();
values.put(new TensorAddress.Builder(sparse).add("x", "a").add("y", "b").build(),
new Constant(5));
values.put(new TensorAddress.Builder(sparse).add("x", "a").add("y", "c").build(),
new Constant(7));
DynamicTensor<Name> t2 = DynamicTensor.from(sparse, values);
assertEquals(Tensor.from(sparse, "{{x:a,y:b}:5, {x:a,y:c}:7}"), t2.evaluate());
}
@Ignore // Enable for benchmarking
public void benchMarkTensorAddressBuilder() {
long start = System.nanoTime();
TensorType sparse = TensorType.fromSpec("tensor(x{})");
for (int i=0; i < 10000; i++) {
TensorAddress.Builder builder = new TensorAddress.Builder(sparse);
for (int j=0; j < 1000; j++) {
builder.add("x", String.valueOf(j));
}
}
System.out.println("Took " + (System.nanoTime() - start) + " ns");
}
private static class Constant implements ScalarFunction<Name> {
private final double value;
public Constant(double value) { this.value = value; }
@Override
public Double apply(EvaluationContext<Name> evaluationContext) { return value; }
@Override
public String toString() { return String.valueOf(value); }
}
}
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