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// Copyright Yahoo. Licensed under the terms of the Apache 2.0 license. See LICENSE in the project root.
package ai.vespa.rankingexpression.importer.xgboost;
import com.yahoo.searchlib.rankingexpression.RankingExpression;
import com.yahoo.searchlib.rankingexpression.evaluation.ArrayContext;
import com.yahoo.searchlib.rankingexpression.evaluation.Context;
import com.yahoo.searchlib.rankingexpression.evaluation.ContextIndex;
import com.yahoo.searchlib.rankingexpression.evaluation.DoubleValue;
import com.yahoo.searchlib.rankingexpression.evaluation.ExpressionOptimizer;
import com.yahoo.searchlib.rankingexpression.evaluation.TensorValue;
import com.yahoo.searchlib.rankingexpression.evaluation.gbdtoptimization.GBDTForestNode;
import com.yahoo.tensor.Tensor;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
/**
* @author lesters
*/
public class XGBoostImportEvaluationTestCase {
@Test
public void testXGBoostEvaluation() {
RankingExpression expression = new XGBoostImporter()
.importModel("xgb", "src/test/models/xgboost/xgboost.test.json")
.expressions().get("xgb");
ArrayContext context = new ArrayContext(expression, DoubleValue.NaN);
assertXGBoostEvaluation(1.0, expression, features(context, "f1", 0.0, "f2", 0.0));
assertXGBoostEvaluation(2.0, expression, features(context, "f1", 0.0, "f2", 1.0));
assertXGBoostEvaluation(3.0, expression, features(context, "f1", 1.0, "f2", 0.0));
assertXGBoostEvaluation(4.0, expression, features(context, "f1", 1.0, "f2", 1.0));
assertXGBoostEvaluation(5.0, expression, features(context, "f1", 0.0));
assertXGBoostEvaluation(6.0, expression, features(context, "f1", 1.0));
assertXGBoostEvaluation(7.0, expression, features(context, "f2", 0.0));
assertXGBoostEvaluation(9.0, expression, features(context, "f2", 1.0));
assertXGBoostEvaluation(11.0, expression, features(context));
assertXGBoostEvaluation(5.0, expression, features(context, "f1", Tensor.from(0.0)));
assertXGBoostEvaluation(6.0, expression, features(context, "f1", Tensor.from(1.0)));
ExpressionOptimizer optimizer = new ExpressionOptimizer();
optimizer.optimize(expression, (ContextIndex)context);
assertTrue(expression.getRoot() instanceof GBDTForestNode);
assertXGBoostEvaluation(1.0, expression, features(context, "f1", 0.0, "f2", 0.0));
assertXGBoostEvaluation(2.0, expression, features(context, "f1", 0.0, "f2", 1.0));
assertXGBoostEvaluation(3.0, expression, features(context, "f1", 1.0, "f2", 0.0));
assertXGBoostEvaluation(4.0, expression, features(context, "f1", 1.0, "f2", 1.0));
assertXGBoostEvaluation(5.0, expression, features(context, "f1", 0.0));
assertXGBoostEvaluation(6.0, expression, features(context, "f1", 1.0));
assertXGBoostEvaluation(7.0, expression, features(context, "f2", 0.0));
assertXGBoostEvaluation(9.0, expression, features(context, "f2", 1.0));
assertXGBoostEvaluation(11.0, expression, features(context));
assertXGBoostEvaluation(5.0, expression, features(context, "f1", Tensor.from(0.0)));
assertXGBoostEvaluation(6.0, expression, features(context, "f1", Tensor.from(1.0)));
}
private ArrayContext features(ArrayContext context) {
return context.clone();
}
private ArrayContext features(ArrayContext context, String f1, double v1) {
context = context.clone();
context.put(f1, v1);
return context;
}
private ArrayContext features(ArrayContext context, String f1, Tensor v1) {
context = context.clone();
context.put(f1, new TensorValue(v1));
return context;
}
private ArrayContext features(ArrayContext context, String f1, double v1, String f2, double v2) {
context = context.clone();
context.put(f1, v1);
context.put(f2, v2);
return context;
}
private void assertXGBoostEvaluation(double expected, RankingExpression expr, Context context) {
assertEquals(expected, expr.evaluate(context).asDouble(), 1e-9);
}
}
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