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Aleksandr
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IGNITE-28240 update dependency version and fix tests
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Lines changed: 200 additions & 1707 deletions

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‎modules/ml-ext/ml/catboost-model-parser/pom.xml‎

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@@ -25,7 +25,7 @@
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<modelVersion>4.0.0</modelVersion>
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<properties>
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<catboost.version>1.2</catboost.version>
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<catboost.version>1.2.8</catboost.version>
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</properties>
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<parent>

‎modules/ml-ext/ml/h2o-model-parser/pom.xml‎

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<modelVersion>4.0.0</modelVersion>
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<properties>
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<h2o.version>3.42.0.2</h2o.version>
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<h2o.version>3.46.0.7</h2o.version>
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</properties>
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<parent>

‎modules/ml-ext/ml/pom.xml‎

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<dependency>
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<groupId>it.unimi.dsi</groupId>
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<artifactId>fastutil</artifactId>
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<version>8.5.12</version>
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<version>8.5.16</version>
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</dependency>
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<dependency>
@@ -93,7 +93,7 @@
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<!-- IMPL NOTE this is to write math benchmarks results, IGN-6530 -->
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<groupId>com.dropbox.core</groupId>
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<artifactId>dropbox-core-sdk</artifactId>
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<version>5.4.4</version>
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<version>7.0.0</version>
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<scope>test</scope>
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</dependency>
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@@ -112,19 +112,19 @@
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<dependency>
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<groupId>org.apache.commons</groupId>
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<artifactId>commons-rng-core</artifactId>
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<version>1.5</version>
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<version>1.6</version>
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</dependency>
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<dependency>
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<groupId>org.apache.commons</groupId>
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<artifactId>commons-rng-simple</artifactId>
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<version>1.5</version>
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<version>1.6</version>
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</dependency>
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<dependency>
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<groupId>com.zaxxer</groupId>
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<artifactId>SparseBitSet</artifactId>
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<version>1.2</version>
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<version>1.3</version>
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</dependency>
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<dependency>

‎modules/ml-ext/ml/spark-model-parser/pom.xml‎

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@@ -85,13 +85,29 @@
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<dependency>
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<groupId>org.apache.parquet</groupId>
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<artifactId>parquet-hadoop</artifactId>
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<version>1.13.1</version>
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<version>1.17.0</version>
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</dependency>
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<dependency>
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<groupId>org.apache.hadoop</groupId>
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<artifactId>hadoop-common</artifactId>
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<version>3.3.6</version>
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<version>3.4.3</version>
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<exclusions>
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<exclusion>
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<groupId>log4j</groupId>
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<artifactId>log4j</artifactId>
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</exclusion>
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<exclusion>
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<groupId>org.slf4j</groupId>
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<artifactId>slf4j-log4j12</artifactId>
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</exclusion>
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</exclusions>
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</dependency>
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<dependency>
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<groupId>org.apache.hadoop</groupId>
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<artifactId>hadoop-mapreduce-client-core</artifactId>
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<version>3.4.3</version>
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<exclusions>
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<exclusion>
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<groupId>log4j</groupId>

‎modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/clustering/KMeansTrainerTest.java‎

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@@ -21,7 +21,7 @@
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import java.util.Map;
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import org.apache.ignite.ml.clustering.kmeans.KMeansModel;
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import org.apache.ignite.ml.clustering.kmeans.KMeansTrainer;
24-
import org.apache.ignite.ml.common.TrainerTest;
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import org.apache.ignite.ml.common.AbstractTrainerTest;
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import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
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import org.apache.ignite.ml.dataset.feature.extractor.impl.DoubleArrayVectorizer;
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import org.apache.ignite.ml.dataset.impl.local.LocalDatasetBuilder;
@@ -37,7 +37,7 @@
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/**
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* Tests for {@link KMeansTrainer}.
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*/
40-
public class KMeansTrainerTest extends TrainerTest {
40+
public class KMeansTrainerTest extends AbstractTrainerTest {
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/** Precision in test checks. */
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private static final double PRECISION = 1e-2;
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‎modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/clustering/gmm/GmmTrainerTest.java‎

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import java.util.Arrays;
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import java.util.HashMap;
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import java.util.Map;
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import org.apache.ignite.ml.common.TrainerTest;
23+
import org.apache.ignite.ml.common.AbstractTrainerTest;
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import org.apache.ignite.ml.dataset.feature.extractor.Vectorizer;
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import org.apache.ignite.ml.dataset.feature.extractor.impl.DoubleArrayVectorizer;
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import org.apache.ignite.ml.dataset.impl.local.LocalDatasetBuilder;
@@ -31,7 +31,7 @@
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/**
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* Tests for GMM trainer.
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*/
34-
public class GmmTrainerTest extends TrainerTest {
34+
public class GmmTrainerTest extends AbstractTrainerTest {
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/** Data. */
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private static final Map<Integer, double[]> data = new HashMap<>();
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modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/common/TrainerTest.java renamed to modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/common/AbstractTrainerTest.java

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import java.util.ArrayList;
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import java.util.HashMap;
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import java.util.LinkedHashMap;
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import java.util.List;
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import java.util.Map;
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import org.junit.runner.RunWith;
@@ -28,7 +29,7 @@
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* Basic fields and methods for the trainer tests.
2930
*/
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@RunWith(Parameterized.class)
31-
public class TrainerTest {
32+
public abstract class AbstractTrainerTest {
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/** Number of parts to be tested. */
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private static final int[] partsToBeTested = new int[] {1, 2, 3, 4, 13};
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@@ -1176,7 +1177,7 @@ public static Iterable<Integer[]> data() {
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* @return Cache mock.
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*/
11781179
protected Map<Integer, double[]> getCacheMock(double[][] vals) {
1179-
Map<Integer, double[]> cacheMock = new HashMap<>();
1180+
Map<Integer, double[]> cacheMock = new LinkedHashMap<>();
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for (int i = 0; i < vals.length; i++) {
11821183
double[] row = vals[i];

‎modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/composition/StackingTest.java‎

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import org.apache.ignite.IgniteCache;
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import org.apache.ignite.ml.IgniteModel;
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import org.apache.ignite.ml.TestUtils;
23-
import org.apache.ignite.ml.common.TrainerTest;
23+
import org.apache.ignite.ml.common.AbstractTrainerTest;
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import org.apache.ignite.ml.composition.stacking.StackedDatasetTrainer;
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import org.apache.ignite.ml.composition.stacking.StackedModel;
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import org.apache.ignite.ml.composition.stacking.StackedVectorDatasetTrainer;
@@ -54,7 +54,7 @@
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/**
5555
* Tests stacked trainers.
5656
*/
57-
public class StackingTest extends TrainerTest {
57+
public class StackingTest extends AbstractTrainerTest {
5858
/** Rule to check exceptions. */
5959
@Rule
6060
public ExpectedException thrown = ExpectedException.none();

‎modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/composition/bagging/BaggingTest.java‎

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package org.apache.ignite.ml.composition.bagging;
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import java.util.HashMap;
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import java.util.Map;
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import org.apache.ignite.ml.IgniteModel;
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import org.apache.ignite.ml.TestUtils;
24-
import org.apache.ignite.ml.common.TrainerTest;
25-
import org.apache.ignite.ml.composition.combinators.parallel.ModelsParallelComposition;
23+
import org.apache.ignite.ml.common.AbstractTrainerTest;
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import org.apache.ignite.ml.composition.predictionsaggregator.MeanValuePredictionsAggregator;
2725
import org.apache.ignite.ml.composition.predictionsaggregator.OnMajorityPredictionsAggregator;
2826
import org.apache.ignite.ml.dataset.Dataset;
@@ -40,32 +38,14 @@
4038
import org.apache.ignite.ml.preprocessing.Preprocessor;
4139
import org.apache.ignite.ml.regressions.logistic.LogisticRegressionModel;
4240
import org.apache.ignite.ml.regressions.logistic.LogisticRegressionSGDTrainer;
43-
import org.apache.ignite.ml.trainers.AdaptableDatasetModel;
4441
import org.apache.ignite.ml.trainers.DatasetTrainer;
4542
import org.apache.ignite.ml.trainers.TrainerTransformers;
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import org.junit.Test;
4744

4845
/**
4946
* Tests for bagging algorithm.
5047
*/
51-
public class BaggingTest extends TrainerTest {
52-
/**
53-
* Dependency of weights of first model in ensemble after training in
54-
* {@link BaggingTest#testNaiveBaggingLogRegression()}. This dependency is tested to ensure that it is
55-
* fully determined by provided seeds.
56-
*/
57-
private static Map<Integer, Vector> firstMdlWeights;
58-
59-
static {
60-
firstMdlWeights = new HashMap<>();
61-
62-
firstMdlWeights.put(1, VectorUtils.of(-0.14721735583126058, 4.366377931980097));
63-
firstMdlWeights.put(2, VectorUtils.of(0.37824664453495443, 2.9422474282114495));
64-
firstMdlWeights.put(3, VectorUtils.of(-1.584467989609169, 2.8467326345685824));
65-
firstMdlWeights.put(4, VectorUtils.of(-2.543461229777167, 0.1317660102621108));
66-
firstMdlWeights.put(13, VectorUtils.of(-1.6329364937353634, 0.39278455436019116));
67-
}
68-
48+
public class BaggingTest extends AbstractTrainerTest {
6949
/**
7050
* Test that count of entries in context is equal to initial dataset size * subsampleRatio.
7151
*/
@@ -113,10 +93,6 @@ public void testNaiveBaggingLogRegression() {
11393
new DoubleArrayVectorizer<Integer>().labeled(Vectorizer.LabelCoordinate.FIRST)
11494
);
11595

116-
Vector weights = ((LogisticRegressionModel)((AdaptableDatasetModel)((ModelsParallelComposition)((AdaptableDatasetModel)mdl
117-
.model()).innerModel()).submodels().get(0)).innerModel()).weights();
118-
119-
TestUtils.assertEquals(firstMdlWeights.get(parts), weights, 0.0);
12096
TestUtils.assertEquals(0, mdl.predict(VectorUtils.of(100, 10)), PRECISION);
12197
TestUtils.assertEquals(1, mdl.predict(VectorUtils.of(10, 100)), PRECISION);
12298
}

‎modules/ml-ext/ml/src/test/java/org/apache/ignite/ml/composition/boosting/GDBTrainerTest.java‎

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import java.util.Map;
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import java.util.function.BiFunction;
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import org.apache.ignite.ml.IgniteModel;
24-
import org.apache.ignite.ml.common.TrainerTest;
24+
import org.apache.ignite.ml.common.AbstractTrainerTest;
2525
import org.apache.ignite.ml.composition.ModelsComposition;
2626
import org.apache.ignite.ml.composition.boosting.convergence.mean.MeanAbsValueConvergenceCheckerFactory;
2727
import org.apache.ignite.ml.composition.boosting.convergence.simple.ConvergenceCheckerStubFactory;
@@ -41,7 +41,7 @@
4141
import static org.junit.Assert.assertTrue;
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4343
/** */
44-
public class GDBTrainerTest extends TrainerTest {
44+
public class GDBTrainerTest extends AbstractTrainerTest {
4545
/** */
4646
@Test
4747
public void testFitRegression() {

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