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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.application.api.ApplicationPackage;
import com.yahoo.io.IOUtils;
import com.yahoo.path.Path;
import com.yahoo.vespa.config.search.RankProfilesConfig;
import com.yahoo.vespa.model.VespaModel;
import com.yahoo.vespa.model.container.ContainerCluster;
import org.junit.After;
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 Path appDir = Path.fromString("src/test/cfg/application/ml_serving");
@After
public void removeGeneratedModelFiles() {
IOUtils.recursiveDeleteDir(appDir.append(ApplicationPackage.MODELS_GENERATED_DIR).toFile());
}
@Test
public void testMl_ServingApplication() throws SAXException, IOException {
ApplicationPackageTester tester = ApplicationPackageTester.create(appDir.toString());
VespaModel model = new VespaModel(tester.app());
assertHasMlModels(model);
// At this point the expression is stored - copy application to another location which do not have a models dir
Path storedAppDir = appDir.append("copy");
try {
storedAppDir.toFile().mkdirs();
IOUtils.copy(appDir.append("services.xml").toString(), storedAppDir.append("services.xml").toString());
IOUtils.copyDirectory(appDir.append(ApplicationPackage.MODELS_GENERATED_DIR).toFile(),
storedAppDir.append(ApplicationPackage.MODELS_GENERATED_DIR).toFile());
ApplicationPackageTester storedTester = ApplicationPackageTester.create(storedAppDir.toString());
VespaModel storedModel = new VespaModel(storedTester.app());
assertHasMlModels(storedModel);
}
finally {
IOUtils.recursiveDeleteDir(storedAppDir.toFile());
}
}
private void assertHasMlModels(VespaModel model) {
ContainerCluster cluster = model.getContainerClusters().get("container");
RankProfilesConfig.Builder b = new RankProfilesConfig.Builder();
cluster.getConfig(b);
RankProfilesConfig config = new RankProfilesConfig(b);
assertEquals(4, config.rankprofile().size());
Set<String> modelNames = config.rankprofile().stream().map(v -> v.name()).collect(Collectors.toSet());
assertTrue(modelNames.contains("xgboost_2_2"));
assertTrue(modelNames.contains("mnist_softmax"));
assertTrue(modelNames.contains("mnist_softmax_saved"));
ModelsEvaluator evaluator = new ModelsEvaluator(config);
assertEquals(4, evaluator.models().size());
Model xgboost = evaluator.models().get("xgboost_2_2");
assertNotNull(xgboost);
assertNotNull(xgboost.evaluatorOf());
assertNotNull(xgboost.evaluatorOf("xgboost_2_2"));
Model onnx = evaluator.models().get("mnist_softmax");
assertNotNull(onnx);
assertNotNull(onnx.evaluatorOf());
assertNotNull(onnx.evaluatorOf("default"));
assertNotNull(onnx.evaluatorOf("default", "add"));
assertNotNull(onnx.evaluatorOf("default.add"));
assertNotNull(evaluator.evaluatorOf("mnist_softmax", "default.add"));
assertNotNull(evaluator.evaluatorOf("mnist_softmax", "default", "add"));
Model tensorflow = evaluator.models().get("mnist_softmax_saved");
assertNotNull(tensorflow);
assertNotNull(tensorflow.evaluatorOf());
assertNotNull(tensorflow.evaluatorOf("serving_default"));
assertNotNull(tensorflow.evaluatorOf("serving_default", "y"));
}
}
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