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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.searchlib.rankingexpression.evaluation.tensoroptimization;
import com.yahoo.searchlib.rankingexpression.RankingExpression;
import com.yahoo.searchlib.rankingexpression.evaluation.ArrayContext;
import com.yahoo.searchlib.rankingexpression.evaluation.ExpressionOptimizer;
import com.yahoo.searchlib.rankingexpression.evaluation.OptimizationReport;
import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue;
import com.yahoo.searchlib.rankingexpression.parser.ParseException;
import com.yahoo.searchlib.rankingexpression.rule.TensorFunctionNode;
import com.yahoo.tensor.Tensor;
import com.yahoo.tensor.TensorType;
import com.yahoo.tensor.functions.Reduce;
import com.yahoo.tensor.functions.ReduceJoin;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
/**
* @author lesters
*/
public class TensorOptimizerTestCase {
@Test
public void testReduceJoinOptimization() throws ParseException {
assertWillOptimize("d0[3]", "d0[3]");
assertWillOptimize("d0[1]", "d0[1]", "d0");
assertWillOptimize("d0[2]", "d0[2]", "d0");
assertWillOptimize("d0[3]", "d0[3]", "d0");
assertWillOptimize("d0[3]", "d0[3],d1[2]", "d0");
assertWillOptimize("d0[3],d1[2]", "d0[3]", "d0");
assertWillOptimize("d1[3]", "d0[2],d1[3]", "d1");
assertWillOptimize("d0[2],d1[3]", "d1[3]", "d1");
assertWillOptimize("d0[2],d2[2]", "d1[3],d2[2]", "d2");
assertWillOptimize("d1[2],d2[2]", "d0[3],d2[2]", "d2");
assertWillOptimize("d0[1],d2[4]", "d1[3],d2[4]", "d2");
assertWillOptimize("d0[2],d2[4]", "d1[3],d2[4]", "d2");
assertWillOptimize("d0[2],d1[3]", "d0[2],d1[3]");
assertWillOptimize("d0[2],d1[3]", "d0[2],d1[3]", "d0,d1");
assertWillOptimize("d2[3],d3[4]", "d1[2],d2[3],d3[4]", "d2,d3");
assertWillOptimize("d0[1],d2[3],d3[4]", "d1[2],d2[3],d3[4]", "d2,d3");
assertWillOptimize("d0[1],d1[2],d2[3]", "d2[3],d3[4],d4[5]", "d2");
assertWillOptimize("d0[1],d1[2],d2[3]", "d1[2],d2[3],d4[4]", "d1,d2");
assertWillOptimize("d0[1],d1[2],d2[3]", "d0[1],d1[2],d2[3]");
assertWillOptimize("d0[1],d1[2],d2[3]", "d0[1],d1[2],d2[3]", "d0,d1,d2");
// Will not currently use reduce-join optimization
assertCantOptimize("d0[2],d1[3]", "d1[3]", "d0"); // reducing on a dimension not joining on
assertCantOptimize("d0[1],d1[2]", "d1[2],d2[3]", "d2"); // same
assertCantOptimize("d0[3]", "d0[3],d1[2]"); // reducing on more then we are combining
assertCantOptimize("d0[1],d2[3]", "d1[2],d2[3]"); // same
assertCantOptimize("d0[1],d1[2],d2[3]", "d0[1],d1[2],d2[3]", "d1,d2"); // reducing on less then joining on
}
private void assertWillOptimize(String aType, String bType) throws ParseException {
assertWillOptimize(aType, bType, "", "sum");
}
private void assertWillOptimize(String aType, String bType, String reduceDim) throws ParseException {
assertWillOptimize(aType, bType, reduceDim, "sum");
}
private void assertWillOptimize(String aType, String bType, String reduceDim, String aggregator) throws ParseException {
assertReduceJoin(aType, bType, reduceDim, aggregator, true);
}
private void assertCantOptimize(String aType, String bType) throws ParseException {
assertCantOptimize(aType, bType, "", "sum");
}
private void assertCantOptimize(String aType, String bType, String reduceDim) throws ParseException {
assertCantOptimize(aType, bType, reduceDim, "sum");
}
private void assertCantOptimize(String aType, String bType, String reduceDim, String aggregator) throws ParseException {
assertReduceJoin(aType, bType, reduceDim, aggregator, false);
}
private void assertReduceJoin(String aType, String bType, String reduceDim, String aggregator, boolean assertOptimize) throws ParseException {
Tensor a = generateRandomTensor(aType);
Tensor b = generateRandomTensor(bType);
RankingExpression expression = generateRankingExpression(reduceDim, aggregator);
assert ((TensorFunctionNode)expression.getRoot()).function() instanceof Reduce;
ArrayContext context = generateContext(a, b, expression);
Tensor result = expression.evaluate(context).asTensor();
ExpressionOptimizer optimizer = new ExpressionOptimizer();
OptimizationReport report = optimizer.optimize(expression, context);
assertEquals(1, report.getMetric("Replaced reduce->join"));
assert ((TensorFunctionNode)expression.getRoot()).function() instanceof ReduceJoin;
assertEquals(result, expression.evaluate(context).asTensor());
assertEquals(assertOptimize, ((ReduceJoin)((TensorFunctionNode)expression.getRoot()).function()).canOptimize(a, b));
}
private RankingExpression generateRankingExpression(String reduceDim, String aggregator) throws ParseException {
String dimensions = "";
if (reduceDim.length() > 0) {
dimensions = ", " + reduceDim;
}
return new RankingExpression("reduce(join(a, b, f(a,b)(a * b)), " + aggregator + dimensions + ")");
}
private ArrayContext generateContext(Tensor a, Tensor b, RankingExpression expression) {
ArrayContext context = new ArrayContext(expression);
context.put("a", new TensorValue(a));
context.put("b", new TensorValue(b));
return context;
}
private Tensor generateRandomTensor(String type) {
return Tensor.random(TensorType.fromSpec("tensor(" + type + ")"));
}
}
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