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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.vespa.model.ml;
import ai.vespa.modelintegration.evaluator.OnnxRuntime;
import ai.vespa.models.evaluation.Model;
import ai.vespa.models.evaluation.ModelsEvaluator;
import ai.vespa.models.handler.ModelsEvaluationHandler;
import com.yahoo.component.ComponentId;
import com.yahoo.config.application.api.ApplicationPackage;
import com.yahoo.filedistribution.fileacquirer.FileAcquirer;
import com.yahoo.filedistribution.fileacquirer.MockFileAcquirer;
import com.yahoo.io.IOUtils;
import com.yahoo.path.Path;
import com.yahoo.tensor.TensorType;
import com.yahoo.vespa.config.search.RankProfilesConfig;
import com.yahoo.vespa.config.search.core.OnnxModelsConfig;
import com.yahoo.vespa.config.search.core.RankingConstantsConfig;
import com.yahoo.vespa.config.search.core.RankingExpressionsConfig;
import com.yahoo.vespa.model.VespaModel;
import com.yahoo.vespa.model.container.ApplicationContainerCluster;
import org.junit.jupiter.api.Test;
import java.io.File;
import java.io.IOException;
import java.util.HashMap;
import java.util.Map;
import java.util.Set;
import java.util.stream.Collectors;
import static org.junit.jupiter.api.Assertions.assertEquals;
import static org.junit.jupiter.api.Assertions.assertNotNull;
import static org.junit.jupiter.api.Assertions.assertNull;
import static org.junit.jupiter.api.Assertions.assertTrue;
import static org.junit.jupiter.api.Assumptions.assumeTrue;
/**
* Tests stateless model evaluation (turned on by the "model-evaluation" tag in "container")
*
* @author bratseth
*/
public class ModelEvaluationTest {
/** Tests that we do not load models (which would waste memory) when not requested */
@Test
void testMl_serving_not_activated() {
Path appDir = Path.fromString("src/test/cfg/application/ml_serving_not_activated");
try {
ImportedModelTester tester = new ImportedModelTester("ml_serving", appDir);
VespaModel model = tester.createVespaModel();
ApplicationContainerCluster cluster = model.getContainerClusters().get("container");
assertNull(cluster.getComponentsMap().get(new ComponentId(ModelsEvaluator.class.getName())));
RankProfilesConfig.Builder b = new RankProfilesConfig.Builder();
cluster.getConfig(b);
RankProfilesConfig config = new RankProfilesConfig(b);
assertEquals(0, config.rankprofile().size());
}
finally {
IOUtils.recursiveDeleteDir(appDir.append(ApplicationPackage.MODELS_GENERATED_DIR).toFile());
}
}
@Test
void testMl_serving() throws IOException {
assumeTrue(OnnxRuntime.isRuntimeAvailable());
Path appDir = Path.fromString("src/test/cfg/application/ml_serving");
Path storedAppDir = appDir.append("copy");
try {
ImportedModelTester tester = new ImportedModelTester("ml_serving", appDir);
assertHasMlModels(tester.createVespaModel(), appDir);
// At this point the expression is stored - copy application to another location which do not have a models dir
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());
ImportedModelTester storedTester = new ImportedModelTester("ml_serving", storedAppDir);
assertHasMlModels(storedTester.createVespaModel(), appDir);
}
finally {
IOUtils.recursiveDeleteDir(appDir.append(ApplicationPackage.MODELS_GENERATED_DIR).toFile());
IOUtils.recursiveDeleteDir(storedAppDir.toFile());
}
}
@Test
void testContainerSpecificModelSettings() {
Path appDir = Path.fromString("src/test/cfg/application/onnx_cluster_specific");
try {
ImportedModelTester tester = new ImportedModelTester("mul", appDir);
VespaModel model = tester.createVespaModel();
OnnxModelsConfig.Model c1Model = getOnnxModelsConfig(model.getContainerClusters().get("c1"));
OnnxModelsConfig.Model c2Model = getOnnxModelsConfig(model.getContainerClusters().get("c2"));
assertEquals(2, c1Model.stateless_intraop_threads());
assertEquals(4, c2Model.stateless_intraop_threads());
assertEquals(0, c1Model.gpu_device());
assertEquals(1, c2Model.gpu_device());
} finally {
IOUtils.recursiveDeleteDir(appDir.append(ApplicationPackage.MODELS_GENERATED_DIR).toFile());
}
}
private OnnxModelsConfig.Model getOnnxModelsConfig(ApplicationContainerCluster cluster) {
OnnxModelsConfig.Builder ob = new OnnxModelsConfig.Builder();
cluster.getConfig(ob);
return new OnnxModelsConfig(ob).model(0);
}
private void assertHasMlModels(VespaModel model, Path appDir) {
ApplicationContainerCluster cluster = model.getContainerClusters().get("container");
assertNotNull(cluster.getComponentsMap().get(new ComponentId(ModelsEvaluator.class.getName())));
assertNotNull(cluster.getComponentsMap().get(new ComponentId(ModelsEvaluationHandler.class.getName())));
assertTrue(cluster.getHandlers().stream()
.anyMatch(h -> h.getComponentId().toString().equals(ModelsEvaluationHandler.class.getName())));
RankProfilesConfig.Builder b = new RankProfilesConfig.Builder();
cluster.getConfig(b);
RankProfilesConfig config = new RankProfilesConfig(b);
RankingConstantsConfig.Builder cb = new RankingConstantsConfig.Builder();
cluster.getConfig(cb);
RankingConstantsConfig constantsConfig = new RankingConstantsConfig(cb);
RankingExpressionsConfig.Builder ce = new RankingExpressionsConfig.Builder();
cluster.getConfig(ce);
RankingExpressionsConfig expressionsConfig = ce.build();
OnnxModelsConfig.Builder ob = new OnnxModelsConfig.Builder();
cluster.getConfig(ob);
OnnxModelsConfig onnxModelsConfig = new OnnxModelsConfig(ob);
assertEquals(5, 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("lightgbm_regression"));
assertTrue(modelNames.contains("add_mul"));
assertTrue(modelNames.contains("small_constants_and_functions"));
assertTrue(modelNames.contains("sqrt"));
// Compare profile content in a denser format than config:
StringBuilder sb = new StringBuilder();
for (RankProfilesConfig.Rankprofile.Fef.Property p : findProfile("small_constants_and_functions", config).property())
sb.append(p.name()).append(": ").append(p.value()).append("\n");
assertEquals(profile, sb.toString());
Map<String, File> fileMap = new HashMap<>();
for (OnnxModelsConfig.Model onnxModel : onnxModelsConfig.model()) {
fileMap.put(onnxModel.fileref().value(), appDir.append(onnxModel.fileref().value()).toFile());
}
FileAcquirer fileAcquirer = MockFileAcquirer.returnFiles(fileMap);
ModelsEvaluator evaluator = new ModelsEvaluator(config, constantsConfig, expressionsConfig, onnxModelsConfig, fileAcquirer);
assertEquals(5, evaluator.models().size());
Model xgboost = evaluator.models().get("xgboost_2_2");
assertNotNull(xgboost);
assertNotNull(xgboost.evaluatorOf());
assertNotNull(xgboost.evaluatorOf("xgboost_2_2"));
Model lightgbm = evaluator.models().get("lightgbm_regression");
assertNotNull(lightgbm);
assertNotNull(lightgbm.evaluatorOf());
assertNotNull(lightgbm.evaluatorOf("lightgbm_regression"));
Model add_mul = evaluator.models().get("add_mul");
assertNotNull(add_mul);
assertEquals(2, add_mul.functions().size());
assertNotNull(add_mul.evaluatorOf("output1"));
assertNotNull(add_mul.evaluatorOf("output2"));
assertNotNull(add_mul.evaluatorOf("default.output1"));
assertNotNull(add_mul.evaluatorOf("default.output2"));
assertNotNull(add_mul.evaluatorOf("default", "output1"));
assertNotNull(add_mul.evaluatorOf("default", "output2"));
assertNotNull(evaluator.evaluatorOf("add_mul", "output1"));
assertNotNull(evaluator.evaluatorOf("add_mul", "output2"));
assertNotNull(evaluator.evaluatorOf("add_mul", "default.output1"));
assertNotNull(evaluator.evaluatorOf("add_mul", "default.output2"));
assertNotNull(evaluator.evaluatorOf("add_mul", "default", "output1"));
assertNotNull(evaluator.evaluatorOf("add_mul", "default", "output2"));
assertEquals(TensorType.fromSpec("tensor<float>(d0[1])"), add_mul.functions().get(0).getArgumentType("input1"));
assertEquals(TensorType.fromSpec("tensor<float>(d0[1])"), add_mul.functions().get(0).getArgumentType("input2"));
Model sqrt = evaluator.models().get("sqrt");
assertNotNull(sqrt);
assertEquals(1, sqrt.functions().size());
assertNotNull(sqrt.evaluatorOf());
assertNotNull(sqrt.evaluatorOf("out_layer_1_1")); // converted from "out/layer/1:1"
assertNotNull(evaluator.evaluatorOf("sqrt"));
assertNotNull(evaluator.evaluatorOf("sqrt", "out_layer_1_1"));
assertEquals(TensorType.fromSpec("tensor<float>(d0[1])"), sqrt.functions().get(0).getArgumentType("input"));
}
private final String profile =
"rankingExpression(output).rankingScript: onnx(small_constants_and_functions).output\n" +
"rankingExpression(output).type: tensor<float>(d0[3])\n";
private RankProfilesConfig.Rankprofile.Fef findProfile(String name, RankProfilesConfig config) {
for (RankProfilesConfig.Rankprofile profile : config.rankprofile()) {
if (profile.name().equals(name))
return profile.fef();
}
throw new IllegalArgumentException("No profile named " + name);
}
}
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