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package com.yahoo.config.model;
import ai.vespa.models.evaluation.Model;
import ai.vespa.models.evaluation.ModelsEvaluator;
import com.yahoo.config.model.application.provider.FilesApplicationPackage;
import com.yahoo.vespa.config.search.RankProfilesConfig;
import com.yahoo.vespa.model.VespaModel;
import com.yahoo.vespa.model.container.ContainerCluster;
import org.junit.Test;
import org.xml.sax.SAXException;
import java.io.IOException;
import java.util.Set;
import java.util.stream.Collectors;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertNotNull;
import static org.junit.Assert.assertTrue;
/**
* @author bratseth
*/
public class ModelEvaluationTest {
private static final String TESTDIR = "src/test/cfg/application/";
@Test
public void testMl_ServingApplication() throws SAXException, IOException {
ApplicationPackageTester tester = ApplicationPackageTester.create(TESTDIR + "ml_serving");
VespaModel model = new VespaModel(tester.app());
ContainerCluster cluster = model.getContainerClusters().get("container");
RankProfilesConfig.Builder b = new RankProfilesConfig.Builder();
cluster.getConfig(b);
RankProfilesConfig config = new RankProfilesConfig(b);
System.out.println(config.rankprofile(2).toString());
assertEquals(3, config.rankprofile().size());
Set<String> modelNames = config.rankprofile().stream().map(v -> v.name()).collect(Collectors.toSet());
assertTrue(modelNames.contains("xgboost_2_2_json"));
assertTrue(modelNames.contains("mnist_softmax_onnx"));
assertTrue(modelNames.contains("mnist_softmax_saved"));
ModelsEvaluator evaluator = new ModelsEvaluator(config);
assertEquals(3, evaluator.models().size());
Model xgboost = evaluator.models().get("xgboost_2_2_json");
assertNotNull(xgboost);
assertNotNull(xgboost.evaluatorOf());
assertNotNull(xgboost.evaluatorOf("xgboost_2_2_json"));
System.out.println("xgboost functions: " + xgboost.functions().stream().map(f -> f.getName()).collect(Collectors.joining(", ")));
Model onnx = evaluator.models().get("mnist_softmax_onnx");
assertNotNull(onnx);
assertNotNull(onnx.evaluatorOf());
assertNotNull(onnx.evaluatorOf("default"));
assertNotNull(onnx.evaluatorOf("default", "add"));
System.out.println("onnx functions: " + onnx.functions().stream().map(f -> f.getName()).collect(Collectors.joining(", ")));
Model tensorflow = evaluator.models().get("mnist_softmax_saved");
assertNotNull(tensorflow);
assertNotNull(tensorflow.evaluatorOf());
assertNotNull(tensorflow.evaluatorOf("serving_default"));
assertNotNull(tensorflow.evaluatorOf("serving_default", "y"));
System.out.println("tensorflow functions: " + tensorflow.functions().stream().map(f -> f.getName()).collect(Collectors.joining(", ")));
}
}
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