Repository: ignite Updated Branches: refs/heads/master 59b3a4874 -> 2dc0d9f75
http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/regressions/linear/LinearRegressionModelTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/regressions/linear/LinearRegressionModelTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/regressions/linear/LinearRegressionModelTest.java index 36d0fc7..6739905 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/regressions/linear/LinearRegressionModelTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/regressions/linear/LinearRegressionModelTest.java @@ -43,19 +43,19 @@ public class LinearRegressionModelTest { assertTrue(!mdl.toString(false).isEmpty()); Vector observation = new DenseVector(new double[]{1.0, 1.0}); - TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{2.0, 1.0}); - TestUtils.assertEquals(1.0 + 2.0 * 2.0 + 3.0 * 1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 2.0 + 3.0 * 1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{1.0, 2.0}); - TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 2.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 2.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{-2.0, 1.0}); - TestUtils.assertEquals(1.0 - 2.0 * 2.0 + 3.0 * 1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 - 2.0 * 2.0 + 3.0 * 1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{1.0, -2.0}); - TestUtils.assertEquals(1.0 + 2.0 * 1.0 - 3.0 * 2.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 1.0 - 3.0 * 2.0, mdl.predict(observation), PRECISION); } /** */ @@ -67,6 +67,6 @@ public class LinearRegressionModelTest { Vector observation = new DenseVector(new double[]{1.0}); - mdl.apply(observation); + mdl.predict(observation); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionModelTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionModelTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionModelTest.java index 4fae638..e934e96 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionModelTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionModelTest.java @@ -62,25 +62,25 @@ public class LogisticRegressionModelTest { Vector observation = new DenseVector(new double[] {1.0}); - mdl.apply(observation); + mdl.predict(observation); } /** */ private void verifyPredict(LogisticRegressionModel mdl) { Vector observation = new DenseVector(new double[] {1.0, 1.0}); - TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 1.0 + 3.0 * 1.0), mdl.apply(observation), PRECISION); + TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 1.0 + 3.0 * 1.0), mdl.predict(observation), PRECISION); observation = new DenseVector(new double[] {2.0, 1.0}); - TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 2.0 + 3.0 * 1.0), mdl.apply(observation), PRECISION); + TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 2.0 + 3.0 * 1.0), mdl.predict(observation), PRECISION); observation = new DenseVector(new double[] {1.0, 2.0}); - TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 1.0 + 3.0 * 2.0), mdl.apply(observation), PRECISION); + TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 1.0 + 3.0 * 2.0), mdl.predict(observation), PRECISION); observation = new DenseVector(new double[] {-2.0, 1.0}); - TestUtils.assertEquals(sigmoid(1.0 - 2.0 * 2.0 + 3.0 * 1.0), mdl.apply(observation), PRECISION); + TestUtils.assertEquals(sigmoid(1.0 - 2.0 * 2.0 + 3.0 * 1.0), mdl.predict(observation), PRECISION); observation = new DenseVector(new double[] {1.0, -2.0}); - TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 1.0 - 3.0 * 2.0), mdl.apply(observation), PRECISION); + TestUtils.assertEquals(sigmoid(1.0 + 2.0 * 1.0 - 3.0 * 2.0), mdl.predict(observation), PRECISION); } /** http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionSGDTrainerTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionSGDTrainerTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionSGDTrainerTest.java index 681cb72..f018eba 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionSGDTrainerTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/regressions/logistic/LogisticRegressionSGDTrainerTest.java @@ -58,8 +58,8 @@ public class LogisticRegressionSGDTrainerTest extends TrainerTest { (k, v) -> v[0] ); - TestUtils.assertEquals(0, mdl.apply(VectorUtils.of(100, 10)), PRECISION); - TestUtils.assertEquals(1, mdl.apply(VectorUtils.of(10, 100)), PRECISION); + TestUtils.assertEquals(0, mdl.predict(VectorUtils.of(100, 10)), PRECISION); + TestUtils.assertEquals(1, mdl.predict(VectorUtils.of(10, 100)), PRECISION); } /** */ @@ -103,9 +103,9 @@ public class LogisticRegressionSGDTrainerTest extends TrainerTest { Vector v1 = VectorUtils.of(100, 10); Vector v2 = VectorUtils.of(10, 100); - TestUtils.assertEquals(originalMdl.apply(v1), updatedOnSameDS.apply(v1), PRECISION); - TestUtils.assertEquals(originalMdl.apply(v2), updatedOnSameDS.apply(v2), PRECISION); - TestUtils.assertEquals(originalMdl.apply(v2), updatedOnEmptyDS.apply(v2), PRECISION); - TestUtils.assertEquals(originalMdl.apply(v1), updatedOnEmptyDS.apply(v1), PRECISION); + TestUtils.assertEquals(originalMdl.predict(v1), updatedOnSameDS.predict(v1), PRECISION); + TestUtils.assertEquals(originalMdl.predict(v2), updatedOnSameDS.predict(v2), PRECISION); + TestUtils.assertEquals(originalMdl.predict(v2), updatedOnEmptyDS.predict(v2), PRECISION); + TestUtils.assertEquals(originalMdl.predict(v1), updatedOnEmptyDS.predict(v1), PRECISION); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMBinaryTrainerTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMBinaryTrainerTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMBinaryTrainerTest.java index ccde0d7..8b69b95 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMBinaryTrainerTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMBinaryTrainerTest.java @@ -50,8 +50,8 @@ public class SVMBinaryTrainerTest extends TrainerTest { (k, v) -> v[0] ); - TestUtils.assertEquals(0, mdl.apply(VectorUtils.of(100, 10)), PRECISION); - TestUtils.assertEquals(1, mdl.apply(VectorUtils.of(10, 100)), PRECISION); + TestUtils.assertEquals(0, mdl.predict(VectorUtils.of(100, 10)), PRECISION); + TestUtils.assertEquals(1, mdl.predict(VectorUtils.of(10, 100)), PRECISION); } /** */ @@ -90,7 +90,7 @@ public class SVMBinaryTrainerTest extends TrainerTest { ); Vector v = VectorUtils.of(100, 10); - TestUtils.assertEquals(originalMdl.apply(v), updatedOnSameDS.apply(v), PRECISION); - TestUtils.assertEquals(originalMdl.apply(v), updatedOnEmptyDS.apply(v), PRECISION); + TestUtils.assertEquals(originalMdl.predict(v), updatedOnSameDS.predict(v), PRECISION); + TestUtils.assertEquals(originalMdl.predict(v), updatedOnEmptyDS.predict(v), PRECISION); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMModelTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMModelTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMModelTest.java index 3bac790..c39c883 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMModelTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/svm/SVMModelTest.java @@ -39,19 +39,19 @@ public class SVMModelTest { SVMLinearClassificationModel mdl = new SVMLinearClassificationModel(weights, 1.0).withRawLabels(true); Vector observation = new DenseVector(new double[]{1.0, 1.0}); - TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{2.0, 1.0}); - TestUtils.assertEquals(1.0 + 2.0 * 2.0 + 3.0 * 1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 2.0 + 3.0 * 1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{1.0, 2.0}); - TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 2.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 1.0 + 3.0 * 2.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{-2.0, 1.0}); - TestUtils.assertEquals(1.0 - 2.0 * 2.0 + 3.0 * 1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 - 2.0 * 2.0 + 3.0 * 1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{1.0, -2.0}); - TestUtils.assertEquals(1.0 + 2.0 * 1.0 - 3.0 * 2.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0 + 2.0 * 1.0 - 3.0 * 2.0, mdl.predict(observation), PRECISION); Assert.assertTrue(mdl.isKeepingRawLabels()); @@ -67,25 +67,25 @@ public class SVMModelTest { SVMLinearClassificationModel mdl = new SVMLinearClassificationModel(weights, 1.0); Vector observation = new DenseVector(new double[]{1.0, 1.0}); - TestUtils.assertEquals(1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{3.0, 4.0}); - TestUtils.assertEquals(1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{-1.0, -1.0}); - TestUtils.assertEquals(0.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(0.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{-2.0, 1.0}); - TestUtils.assertEquals(0.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(0.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{-1.0, -2.0}); - TestUtils.assertEquals(0.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(0.0, mdl.predict(observation), PRECISION); final SVMLinearClassificationModel mdlWithNewData = mdl.withIntercept(-2.0).withWeights(new DenseVector(new double[] {-2.0, -2.0})); System.out.println("The SVM model is " + mdlWithNewData); observation = new DenseVector(new double[]{-1.0, -2.0}); - TestUtils.assertEquals(1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0, mdl.predict(observation), PRECISION); TestUtils.assertEquals(-2.0, mdl.intercept(), PRECISION); } @@ -96,10 +96,10 @@ public class SVMModelTest { SVMLinearClassificationModel mdl = new SVMLinearClassificationModel(weights, 1.0).withThreshold(5); Vector observation = new DenseVector(new double[]{1.0, 1.0}); - TestUtils.assertEquals(0.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(0.0, mdl.predict(observation), PRECISION); observation = new DenseVector(new double[]{3.0, 4.0}); - TestUtils.assertEquals(1.0, mdl.apply(observation), PRECISION); + TestUtils.assertEquals(1.0, mdl.predict(observation), PRECISION); TestUtils.assertEquals(5, mdl.threshold(), PRECISION); } @@ -113,6 +113,6 @@ public class SVMModelTest { Vector observation = new DenseVector(new double[]{1.0}); - mdl.apply(observation); + mdl.predict(observation); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTIntegrationTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTIntegrationTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTIntegrationTest.java index e0cdc96..7edcf2d 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTIntegrationTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTIntegrationTest.java @@ -97,7 +97,7 @@ public class DecisionTreeMNISTIntegrationTest extends GridCommonAbstractTest { int incorrectAnswers = 0; for (MnistUtils.MnistLabeledImage e : MnistMLPTestUtil.loadTestSet(10_000)) { - double res = mdl.apply(new DenseVector(e.getPixels())); + double res = mdl.predict(new DenseVector(e.getPixels())); if (res == e.getLabel()) correctAnswers++; http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTTest.java index 8a3f201..c7d2ef9 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/tree/performance/DecisionTreeMNISTTest.java @@ -61,7 +61,7 @@ public class DecisionTreeMNISTTest { int incorrectAnswers = 0; for (MnistUtils.MnistLabeledImage e : MnistMLPTestUtil.loadTestSet(10_000)) { - double res = mdl.apply(new DenseVector(e.getPixels())); + double res = mdl.predict(new DenseVector(e.getPixels())); if (res == e.getLabel()) correctAnswers++; http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestClassifierTrainerTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestClassifierTrainerTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestClassifierTrainerTest.java index e05139f..b999df3 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestClassifierTrainerTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestClassifierTrainerTest.java @@ -92,7 +92,7 @@ public class RandomForestClassifierTrainerTest extends TrainerTest { ModelsComposition updatedOnEmptyDS = trainer.update(originalMdl, new HashMap<double[], Double>(), parts, (k, v) -> VectorUtils.of(k), (k, v) -> v); Vector v = VectorUtils.of(5, 0.5, 0.05, 0.005); - assertEquals(originalMdl.apply(v), updatedOnSameDS.apply(v), 0.01); - assertEquals(originalMdl.apply(v), updatedOnEmptyDS.apply(v), 0.01); + assertEquals(originalMdl.predict(v), updatedOnSameDS.predict(v), 0.01); + assertEquals(originalMdl.predict(v), updatedOnEmptyDS.predict(v), 0.01); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestRegressionTrainerTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestRegressionTrainerTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestRegressionTrainerTest.java index 08ff95d..1e949a1 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestRegressionTrainerTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/RandomForestRegressionTrainerTest.java @@ -87,7 +87,7 @@ public class RandomForestRegressionTrainerTest extends TrainerTest { ModelsComposition updatedOnEmptyDS = trainer.update(originalMdl, new HashMap<double[], Double>(), parts, (k, v) -> VectorUtils.of(k), (k, v) -> v); Vector v = VectorUtils.of(5, 0.5, 0.05, 0.005); - assertEquals(originalMdl.apply(v), updatedOnSameDS.apply(v), 0.1); - assertEquals(originalMdl.apply(v), updatedOnEmptyDS.apply(v), 0.1); + assertEquals(originalMdl.predict(v), updatedOnSameDS.predict(v), 0.1); + assertEquals(originalMdl.predict(v), updatedOnEmptyDS.predict(v), 0.1); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/data/TreeNodeTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/data/TreeNodeTest.java b/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/data/TreeNodeTest.java index 943b5d8..eb420cc 100644 --- a/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/data/TreeNodeTest.java +++ b/modules/ml/src/test/java/org/apache/ignite/ml/tree/randomforest/data/TreeNodeTest.java @@ -73,7 +73,7 @@ public class TreeNodeTest { }); assertEquals(TreeNode.Type.CONDITIONAL, root.getType()); - assertEquals(0.0, root.apply(features1), 0.001); - assertEquals(1.0, root.apply(features2), 0.001); + assertEquals(0.0, root.predict(features1), 0.001); + assertEquals(1.0, root.predict(features2), 0.001); } } http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/XGModelComposition.java ---------------------------------------------------------------------- diff --git a/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/XGModelComposition.java b/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/XGModelComposition.java index b8ccff7..8001fcd 100644 --- a/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/XGModelComposition.java +++ b/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/XGModelComposition.java @@ -20,7 +20,7 @@ package org.apache.ignite.ml.xgboost; import java.util.HashMap; import java.util.List; import java.util.Map; -import org.apache.ignite.ml.Model; +import org.apache.ignite.ml.IgniteModel; import org.apache.ignite.ml.composition.ModelsComposition; import org.apache.ignite.ml.composition.predictionsaggregator.PredictionsAggregator; import org.apache.ignite.ml.math.primitives.vector.Vector; @@ -32,7 +32,7 @@ import static org.apache.ignite.ml.math.StorageConstants.RANDOM_ACCESS_MODE; /** * XGBoost model composition. */ -public class XGModelComposition implements Model<HashMap<String, Double>, Double> { +public class XGModelComposition implements IgniteModel<HashMap<String, Double>, Double> { /** Dictionary used for matching feature names and indexes. */ private final Map<String, Integer> dict; @@ -50,8 +50,8 @@ public class XGModelComposition implements Model<HashMap<String, Double>, Double } /** {@inheritDoc} */ - @Override public Double apply(HashMap<String, Double> map) { - return modelsComposition.apply(toVector(map)); + @Override public Double predict(HashMap<String, Double> map) { + return modelsComposition.predict(toVector(map)); } /** */ http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/parser/XGModelParser.java ---------------------------------------------------------------------- diff --git a/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/parser/XGModelParser.java b/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/parser/XGModelParser.java index 8d40a7e..c99b1ae 100644 --- a/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/parser/XGModelParser.java +++ b/modules/ml/xgboost-model-parser/src/main/java/org/apache/ignite/ml/xgboost/parser/XGModelParser.java @@ -23,7 +23,7 @@ import java.util.HashMap; import org.antlr.v4.runtime.CharStream; import org.antlr.v4.runtime.CharStreams; import org.antlr.v4.runtime.CommonTokenStream; -import org.apache.ignite.ml.inference.parser.InfModelParser; +import org.apache.ignite.ml.inference.parser.ModelParser; import org.apache.ignite.ml.xgboost.XGModelComposition; import org.apache.ignite.ml.xgboost.parser.visitor.XGModelVisitor; @@ -63,7 +63,7 @@ import org.apache.ignite.ml.xgboost.parser.visitor.XGModelVisitor; * xgModel : xgTree+ ; * </pre> */ -public class XGModelParser implements InfModelParser<HashMap<String, Double>, Double, XGModelComposition> { +public class XGModelParser implements ModelParser<HashMap<String, Double>, Double, XGModelComposition> { /** */ private static final long serialVersionUID = -5819843559270294718L; http://git-wip-us.apache.org/repos/asf/ignite/blob/2dc0d9f7/modules/ml/xgboost-model-parser/src/test/java/org/apache/ignite/ml/xgboost/parser/XGBoostModelParserTest.java ---------------------------------------------------------------------- diff --git a/modules/ml/xgboost-model-parser/src/test/java/org/apache/ignite/ml/xgboost/parser/XGBoostModelParserTest.java b/modules/ml/xgboost-model-parser/src/test/java/org/apache/ignite/ml/xgboost/parser/XGBoostModelParserTest.java index 1439a5a..6c8a65f 100644 --- a/modules/ml/xgboost-model-parser/src/test/java/org/apache/ignite/ml/xgboost/parser/XGBoostModelParserTest.java +++ b/modules/ml/xgboost-model-parser/src/test/java/org/apache/ignite/ml/xgboost/parser/XGBoostModelParserTest.java @@ -20,10 +20,10 @@ package org.apache.ignite.ml.xgboost.parser; import java.net.URL; import java.util.HashMap; import java.util.Scanner; -import org.apache.ignite.ml.inference.builder.SingleInfModelBuilder; -import org.apache.ignite.ml.inference.builder.SyncInfModelBuilder; -import org.apache.ignite.ml.inference.reader.FileSystemInfModelReader; -import org.apache.ignite.ml.inference.reader.InfModelReader; +import org.apache.ignite.ml.inference.builder.SingleModelBuilder; +import org.apache.ignite.ml.inference.builder.SyncModelBuilder; +import org.apache.ignite.ml.inference.reader.FileSystemModelReader; +import org.apache.ignite.ml.inference.reader.ModelReader; import org.apache.ignite.ml.xgboost.XGModelComposition; import org.junit.Test; @@ -41,7 +41,7 @@ public class XGBoostModelParserTest { private final XGModelParser parser = new XGModelParser(); /** Model builder. */ - private final SyncInfModelBuilder mdlBuilder = new SingleInfModelBuilder(); + private final SyncModelBuilder mdlBuilder = new SingleModelBuilder(); /** End-to-end test for {@code parse()} and {@code predict()} methods. */ @Test @@ -50,7 +50,7 @@ public class XGBoostModelParserTest { if (url == null) throw new IllegalStateException("File not found [resource_name=" + TEST_MODEL_RESOURCE + "]"); - InfModelReader reader = new FileSystemInfModelReader(url.getPath()); + ModelReader reader = new FileSystemModelReader(url.getPath()); try (XGModelComposition mdl = mdlBuilder.build(reader, parser); Scanner testDataScanner = new Scanner(XGBoostModelParserTest.class.getClassLoader() @@ -73,7 +73,7 @@ public class XGBoostModelParserTest { testObj.put("f" + keyVal[0], Double.parseDouble(keyVal[1])); } - double prediction = mdl.apply(testObj); + double prediction = mdl.predict(testObj); double expPrediction = Double.parseDouble(testExpResultsStr);
