diff options
author | Xiangrui Meng <meng@databricks.com> | 2015-06-19 09:46:51 -0700 |
---|---|---|
committer | Xiangrui Meng <meng@databricks.com> | 2015-06-19 10:05:07 -0700 |
commit | 1f2dafb77f9af52602885cd5767032a20b486b98 (patch) | |
tree | ae4d9b5bf3f102325f8d763fc4f3ba437726fb05 /mllib/src/test | |
parent | 164b9d32e764b2a67b372a3d685b57c4bbeccbfa (diff) | |
download | spark-1f2dafb77f9af52602885cd5767032a20b486b98.tar.gz spark-1f2dafb77f9af52602885cd5767032a20b486b98.tar.bz2 spark-1f2dafb77f9af52602885cd5767032a20b486b98.zip |
[SPARK-8151] [MLLIB] pipeline components should correctly implement copy
Otherwise, extra params get ignored in `PipelineModel.transform`. jkbradley
Author: Xiangrui Meng <meng@databricks.com>
Closes #6622 from mengxr/SPARK-8087 and squashes the following commits:
0e4c8c4 [Xiangrui Meng] fix merge issues
26fc1f0 [Xiangrui Meng] address comments
e607a04 [Xiangrui Meng] merge master
b85b57e [Xiangrui Meng] fix examples/compile
d6f7891 [Xiangrui Meng] rename defaultCopyWithParams to defaultCopy
84ec278 [Xiangrui Meng] remove setter checks due to generics
2cf2ed0 [Xiangrui Meng] snapshot
291814f [Xiangrui Meng] OneVsRest.copy
1dfe3bd [Xiangrui Meng] PipelineModel.copy should copy stages
(cherry picked from commit 43c7ec6384e51105dedf3a53354b6a3732cc27b2)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
Diffstat (limited to 'mllib/src/test')
24 files changed, 207 insertions, 19 deletions
diff --git a/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java b/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java index ff5929235a..3ae09d39ef 100644 --- a/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java +++ b/mllib/src/test/java/org/apache/spark/ml/param/JavaTestParams.java @@ -102,4 +102,9 @@ public class JavaTestParams extends JavaParams { setDefault(myDoubleArrayParam(), new double[] {1.0, 2.0}); setDefault(myDoubleArrayParam().w(new double[] {1.0, 2.0})); } + + @Override + public JavaTestParams copy(ParamMap extra) { + return defaultCopy(extra); + } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala index 05bf58e63a..a3c4f528da 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala @@ -22,6 +22,7 @@ import org.mockito.Mockito.when import org.scalatest.mock.MockitoSugar.mock import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.feature.HashingTF import org.apache.spark.ml.param.ParamMap import org.apache.spark.sql.DataFrame @@ -81,4 +82,13 @@ class PipelineSuite extends SparkFunSuite { pipeline.fit(dataset) } } + + test("PipelineModel.copy") { + val hashingTF = new HashingTF() + .setNumFeatures(100) + val model = new PipelineModel("pipeline", Array[Transformer](hashingTF)) + val copied = model.copy(ParamMap(hashingTF.numFeatures -> 10)) + require(copied.stages(0).asInstanceOf[HashingTF].getNumFeatures === 10, + "copy should handle extra stage params") + } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala index ae40b0b8ff..73b4805c4c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/DecisionTreeClassifierSuite.scala @@ -19,15 +19,15 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite import org.apache.spark.ml.impl.TreeTests +import org.apache.spark.ml.param.ParamsSuite +import org.apache.spark.ml.tree.LeafNode import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.regression.LabeledPoint -import org.apache.spark.mllib.tree.{DecisionTree => OldDecisionTree, - DecisionTreeSuite => OldDecisionTreeSuite} +import org.apache.spark.mllib.tree.{DecisionTree => OldDecisionTree, DecisionTreeSuite => OldDecisionTreeSuite} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.rdd.RDD import org.apache.spark.sql.DataFrame - class DecisionTreeClassifierSuite extends SparkFunSuite with MLlibTestSparkContext { import DecisionTreeClassifierSuite.compareAPIs @@ -55,6 +55,12 @@ class DecisionTreeClassifierSuite extends SparkFunSuite with MLlibTestSparkConte OldDecisionTreeSuite.generateCategoricalDataPointsForMulticlassForOrderedFeatures()) } + test("params") { + ParamsSuite.checkParams(new DecisionTreeClassifier) + val model = new DecisionTreeClassificationModel("dtc", new LeafNode(0.0, 0.0)) + ParamsSuite.checkParams(model) + } + ///////////////////////////////////////////////////////////////////////////// // Tests calling train() ///////////////////////////////////////////////////////////////////////////// diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala index 1302da3c37..82c345491b 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/GBTClassifierSuite.scala @@ -19,6 +19,9 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite import org.apache.spark.ml.impl.TreeTests +import org.apache.spark.ml.param.ParamsSuite +import org.apache.spark.ml.regression.DecisionTreeRegressionModel +import org.apache.spark.ml.tree.LeafNode import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.tree.{EnsembleTestHelper, GradientBoostedTrees => OldGBT} import org.apache.spark.mllib.tree.configuration.{Algo => OldAlgo} @@ -51,6 +54,14 @@ class GBTClassifierSuite extends SparkFunSuite with MLlibTestSparkContext { sc.parallelize(EnsembleTestHelper.generateOrderedLabeledPoints(numFeatures = 20, 80), 2) } + test("params") { + ParamsSuite.checkParams(new GBTClassifier) + val model = new GBTClassificationModel("gbtc", + Array(new DecisionTreeRegressionModel("dtr", new LeafNode(0.0, 0.0))), + Array(1.0)) + ParamsSuite.checkParams(model) + } + test("Binary classification with continuous features: Log Loss") { val categoricalFeatures = Map.empty[Int, Int] testCombinations.foreach { diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala index a755cac3ea..5a6265ea99 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/LogisticRegressionSuite.scala @@ -18,8 +18,9 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.classification.LogisticRegressionSuite._ -import org.apache.spark.mllib.linalg.Vector +import org.apache.spark.mllib.linalg.{Vectors, Vector} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{DataFrame, Row} @@ -62,6 +63,12 @@ class LogisticRegressionSuite extends SparkFunSuite with MLlibTestSparkContext { } } + test("params") { + ParamsSuite.checkParams(new LogisticRegression) + val model = new LogisticRegressionModel("logReg", Vectors.dense(0.0), 0.0) + ParamsSuite.checkParams(model) + } + test("logistic regression: default params") { val lr = new LogisticRegression assert(lr.getLabelCol === "label") diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala index 1d04ccb509..75cf5bd4ea 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/OneVsRestSuite.scala @@ -19,15 +19,18 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.NominalAttribute +import org.apache.spark.ml.param.{ParamMap, ParamsSuite} import org.apache.spark.ml.util.MetadataUtils import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS import org.apache.spark.mllib.classification.LogisticRegressionSuite._ import org.apache.spark.mllib.evaluation.MulticlassMetrics +import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.rdd.RDD import org.apache.spark.sql.DataFrame +import org.apache.spark.sql.types.Metadata class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext { @@ -52,6 +55,13 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext { dataset = sqlContext.createDataFrame(rdd) } + test("params") { + ParamsSuite.checkParams(new OneVsRest) + val lrModel = new LogisticRegressionModel("lr", Vectors.dense(0.0), 0.0) + val model = new OneVsRestModel("ovr", Metadata.empty, Array(lrModel)) + ParamsSuite.checkParams(model) + } + test("one-vs-rest: default params") { val numClasses = 3 val ova = new OneVsRest() @@ -102,6 +112,26 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext { val output = ovr.fit(dataset).transform(dataset) assert(output.schema.fieldNames.toSet === Set("label", "features", "prediction")) } + + test("OneVsRest.copy and OneVsRestModel.copy") { + val lr = new LogisticRegression() + .setMaxIter(1) + + val ovr = new OneVsRest() + withClue("copy with classifier unset should work") { + ovr.copy(ParamMap(lr.maxIter -> 10)) + } + ovr.setClassifier(lr) + val ovr1 = ovr.copy(ParamMap(lr.maxIter -> 10)) + require(ovr.getClassifier.getOrDefault(lr.maxIter) === 1, "copy should have no side-effects") + require(ovr1.getClassifier.getOrDefault(lr.maxIter) === 10, + "copy should handle extra classifier params") + + val ovrModel = ovr1.fit(dataset).copy(ParamMap(lr.threshold -> 0.1)) + ovrModel.models.foreach { case m: LogisticRegressionModel => + require(m.getThreshold === 0.1, "copy should handle extra model params") + } + } } private class MockLogisticRegression(uid: String) extends LogisticRegression(uid) { diff --git a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala index eee9355a67..1b6b69c7dc 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/classification/RandomForestClassifierSuite.scala @@ -19,6 +19,8 @@ package org.apache.spark.ml.classification import org.apache.spark.SparkFunSuite import org.apache.spark.ml.impl.TreeTests +import org.apache.spark.ml.param.ParamsSuite +import org.apache.spark.ml.tree.LeafNode import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.regression.LabeledPoint import org.apache.spark.mllib.tree.{EnsembleTestHelper, RandomForest => OldRandomForest} @@ -27,7 +29,6 @@ import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.rdd.RDD import org.apache.spark.sql.DataFrame - /** * Test suite for [[RandomForestClassifier]]. */ @@ -62,6 +63,13 @@ class RandomForestClassifierSuite extends SparkFunSuite with MLlibTestSparkConte compareAPIs(orderedLabeledPoints50_1000, newRF, categoricalFeatures, numClasses) } + test("params") { + ParamsSuite.checkParams(new RandomForestClassifier) + val model = new RandomForestClassificationModel("rfc", + Array(new DecisionTreeClassificationModel("dtc", new LeafNode(0.0, 0.0)))) + ParamsSuite.checkParams(model) + } + test("Binary classification with continuous features:" + " comparing DecisionTree vs. RandomForest(numTrees = 1)") { val rf = new RandomForestClassifier() diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala new file mode 100644 index 0000000000..def869fe66 --- /dev/null +++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/BinaryClassificationEvaluatorSuite.scala @@ -0,0 +1,28 @@ +/* + * Licensed to the Apache Software Foundation (ASF) under one or more + * contributor license agreements. See the NOTICE file distributed with + * this work for additional information regarding copyright ownership. + * The ASF licenses this file to You under the Apache License, Version 2.0 + * (the "License"); you may not use this file except in compliance with + * the License. You may obtain a copy of the License at + * + * http://www.apache.org/licenses/LICENSE-2.0 + * + * Unless required by applicable law or agreed to in writing, software + * distributed under the License is distributed on an "AS IS" BASIS, + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. + * See the License for the specific language governing permissions and + * limitations under the License. + */ + +package org.apache.spark.ml.evaluation + +import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite + +class BinaryClassificationEvaluatorSuite extends SparkFunSuite { + + test("params") { + ParamsSuite.checkParams(new BinaryClassificationEvaluator) + } +} diff --git a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala index 36a1ac6b79..aa722da323 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/evaluation/RegressionEvaluatorSuite.scala @@ -18,12 +18,17 @@ package org.apache.spark.ml.evaluation import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.ml.regression.LinearRegression import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext} import org.apache.spark.mllib.util.TestingUtils._ class RegressionEvaluatorSuite extends SparkFunSuite with MLlibTestSparkContext { + test("params") { + ParamsSuite.checkParams(new RegressionEvaluator) + } + test("Regression Evaluator: default params") { /** * Here is the instruction describing how to export the test data into CSV format diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala index 7953bd0417..2086043983 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BinarizerSuite.scala @@ -18,6 +18,7 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{DataFrame, Row} @@ -30,6 +31,10 @@ class BinarizerSuite extends SparkFunSuite with MLlibTestSparkContext { data = Array(0.1, -0.5, 0.2, -0.3, 0.8, 0.7, -0.1, -0.4) } + test("params") { + ParamsSuite.checkParams(new Binarizer) + } + test("Binarize continuous features with default parameter") { val defaultBinarized: Array[Double] = data.map(x => if (x > 0.0) 1.0 else 0.0) val dataFrame: DataFrame = sqlContext.createDataFrame( diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala index 507a8a7db2..ec85e0d151 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/BucketizerSuite.scala @@ -20,6 +20,7 @@ package org.apache.spark.ml.feature import scala.util.Random import org.apache.spark.{SparkException, SparkFunSuite} +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.linalg.Vectors import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ @@ -27,6 +28,10 @@ import org.apache.spark.sql.{DataFrame, Row} class BucketizerSuite extends SparkFunSuite with MLlibTestSparkContext { + test("params") { + ParamsSuite.checkParams(new Bucketizer) + } + test("Bucket continuous features, without -inf,inf") { // Check a set of valid feature values. val splits = Array(-0.5, 0.0, 0.5) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala index 7b2d70e644..4157b84b29 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/HashingTFSuite.scala @@ -28,8 +28,7 @@ import org.apache.spark.util.Utils class HashingTFSuite extends SparkFunSuite with MLlibTestSparkContext { test("params") { - val hashingTF = new HashingTF - ParamsSuite.checkParams(hashingTF, 3) + ParamsSuite.checkParams(new HashingTF) } test("hashingTF") { diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala index d83772e8be..08f80af034 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/IDFSuite.scala @@ -18,6 +18,8 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite +import org.apache.spark.mllib.feature.{IDFModel => OldIDFModel} import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ @@ -38,6 +40,12 @@ class IDFSuite extends SparkFunSuite with MLlibTestSparkContext { } } + test("params") { + ParamsSuite.checkParams(new IDF) + val model = new IDFModel("idf", new OldIDFModel(Vectors.dense(1.0))) + ParamsSuite.checkParams(model) + } + test("compute IDF with default parameter") { val numOfFeatures = 4 val data = Array( diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala index 2e5036a844..65846a846b 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/OneHotEncoderSuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.{AttributeGroup, BinaryAttribute, NominalAttribute} +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.linalg.Vector import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.DataFrame @@ -36,6 +37,10 @@ class OneHotEncoderSuite extends SparkFunSuite with MLlibTestSparkContext { indexer.transform(df) } + test("params") { + ParamsSuite.checkParams(new OneHotEncoder) + } + test("OneHotEncoder dropLast = false") { val transformed = stringIndexed() val encoder = new OneHotEncoder() diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala index feca866cd7..29eebd8960 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/PolynomialExpansionSuite.scala @@ -17,6 +17,7 @@ package org.apache.spark.ml.feature +import org.apache.spark.ml.param.ParamsSuite import org.scalatest.exceptions.TestFailedException import org.apache.spark.SparkFunSuite @@ -27,6 +28,10 @@ import org.apache.spark.sql.Row class PolynomialExpansionSuite extends SparkFunSuite with MLlibTestSparkContext { + test("params") { + ParamsSuite.checkParams(new PolynomialExpansion) + } + test("Polynomial expansion with default parameter") { val data = Array( Vectors.sparse(3, Seq((0, -2.0), (1, 2.3))), diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala index 5f557e16e5..99f82bea42 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/StringIndexerSuite.scala @@ -19,10 +19,17 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite import org.apache.spark.ml.attribute.{Attribute, NominalAttribute} +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.util.MLlibTestSparkContext class StringIndexerSuite extends SparkFunSuite with MLlibTestSparkContext { + test("params") { + ParamsSuite.checkParams(new StringIndexer) + val model = new StringIndexerModel("indexer", Array("a", "b")) + ParamsSuite.checkParams(model) + } + test("StringIndexer") { val data = sc.parallelize(Seq((0, "a"), (1, "b"), (2, "c"), (3, "a"), (4, "a"), (5, "c")), 2) val df = sqlContext.createDataFrame(data).toDF("id", "label") diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala index ac279cb321..e5fd21c3f6 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/TokenizerSuite.scala @@ -20,15 +20,27 @@ package org.apache.spark.ml.feature import scala.beans.BeanInfo import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.{DataFrame, Row} @BeanInfo case class TokenizerTestData(rawText: String, wantedTokens: Array[String]) +class TokenizerSuite extends SparkFunSuite { + + test("params") { + ParamsSuite.checkParams(new Tokenizer) + } +} + class RegexTokenizerSuite extends SparkFunSuite with MLlibTestSparkContext { import org.apache.spark.ml.feature.RegexTokenizerSuite._ + test("params") { + ParamsSuite.checkParams(new RegexTokenizer) + } + test("RegexTokenizer") { val tokenizer0 = new RegexTokenizer() .setGaps(false) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala index 489abb5af7..bb4d5b983e 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorAssemblerSuite.scala @@ -19,6 +19,7 @@ package org.apache.spark.ml.feature import org.apache.spark.{SparkException, SparkFunSuite} import org.apache.spark.ml.attribute.{AttributeGroup, NominalAttribute, NumericAttribute} +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.linalg.{DenseVector, SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.sql.Row @@ -26,6 +27,10 @@ import org.apache.spark.sql.functions.col class VectorAssemblerSuite extends SparkFunSuite with MLlibTestSparkContext { + test("params") { + ParamsSuite.checkParams(new VectorAssembler) + } + test("assemble") { import org.apache.spark.ml.feature.VectorAssembler.assemble assert(assemble(0.0) === Vectors.sparse(1, Array.empty, Array.empty)) diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala index 06affc7305..8c85c96d5c 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/VectorIndexerSuite.scala @@ -21,6 +21,7 @@ import scala.beans.{BeanInfo, BeanProperty} import org.apache.spark.{SparkException, SparkFunSuite} import org.apache.spark.ml.attribute._ +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.linalg.{SparseVector, Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.rdd.RDD @@ -91,6 +92,12 @@ class VectorIndexerSuite extends SparkFunSuite with MLlibTestSparkContext { private def getIndexer: VectorIndexer = new VectorIndexer().setInputCol("features").setOutputCol("indexed") + test("params") { + ParamsSuite.checkParams(new VectorIndexer) + val model = new VectorIndexerModel("indexer", 1, Map.empty) + ParamsSuite.checkParams(model) + } + test("Cannot fit an empty DataFrame") { val rdd = sqlContext.createDataFrame(sc.parallelize(Array.empty[Vector], 2).map(FeatureData)) val vectorIndexer = getIndexer diff --git a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala index 94ebc3aebf..aa6ce533fd 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/feature/Word2VecSuite.scala @@ -18,13 +18,21 @@ package org.apache.spark.ml.feature import org.apache.spark.SparkFunSuite +import org.apache.spark.ml.param.ParamsSuite import org.apache.spark.mllib.linalg.{Vector, Vectors} import org.apache.spark.mllib.util.MLlibTestSparkContext import org.apache.spark.mllib.util.TestingUtils._ import org.apache.spark.sql.{Row, SQLContext} +import org.apache.spark.mllib.feature.{Word2VecModel => OldWord2VecModel} class Word2VecSuite extends SparkFunSuite with MLlibTestSparkContext { + test("params") { + ParamsSuite.checkParams(new Word2Vec) + val model = new Word2VecModel("w2v", new OldWord2VecModel(Map("a" -> Array(0.0f)))) + ParamsSuite.checkParams(model) + } + test("Word2Vec") { val sqlContext = new SQLContext(sc) import sqlContext.implicits._ diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala index 96094d7a09..050d4170ea 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/param/ParamsSuite.scala @@ -205,19 +205,27 @@ class ParamsSuite extends SparkFunSuite { object ParamsSuite extends SparkFunSuite { /** - * Checks common requirements for [[Params.params]]: 1) number of params; 2) params are ordered - * by names; 3) param parent has the same UID as the object's UID; 4) param name is the same as - * the param method name. + * Checks common requirements for [[Params.params]]: + * - params are ordered by names + * - param parent has the same UID as the object's UID + * - param name is the same as the param method name + * - obj.copy should return the same type as the obj */ - def checkParams(obj: Params, expectedNumParams: Int): Unit = { + def checkParams(obj: Params): Unit = { + val clazz = obj.getClass + val params = obj.params - require(params.length === expectedNumParams, - s"Expect $expectedNumParams params but got ${params.length}: ${params.map(_.name).toSeq}.") val paramNames = params.map(_.name) - require(paramNames === paramNames.sorted) + require(paramNames === paramNames.sorted, "params must be ordered by names") params.foreach { p => assert(p.parent === obj.uid) assert(obj.getParam(p.name) === p) + // TODO: Check that setters return self, which needs special handling for generic types. } + + val copyMethod = clazz.getMethod("copy", classOf[ParamMap]) + val copyReturnType = copyMethod.getReturnType + require(copyReturnType === obj.getClass, + s"${clazz.getName}.copy should return ${clazz.getName} instead of ${copyReturnType.getName}.") } } diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala index a9e78366ad..2759248344 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/param/TestParams.scala @@ -38,7 +38,5 @@ class TestParams(override val uid: String) extends Params with HasMaxIter with H require(isDefined(inputCol)) } - override def copy(extra: ParamMap): TestParams = { - super.copy(extra).asInstanceOf[TestParams] - } + override def copy(extra: ParamMap): TestParams = defaultCopy(extra) } diff --git a/mllib/src/test/scala/org/apache/spark/ml/param/shared/SharedParamsSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/param/shared/SharedParamsSuite.scala index eb5408d3fe..b3af81a3c6 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/param/shared/SharedParamsSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/param/shared/SharedParamsSuite.scala @@ -18,13 +18,15 @@ package org.apache.spark.ml.param.shared import org.apache.spark.SparkFunSuite -import org.apache.spark.ml.param.Params +import org.apache.spark.ml.param.{ParamMap, Params} class SharedParamsSuite extends SparkFunSuite { test("outputCol") { - class Obj(override val uid: String) extends Params with HasOutputCol + class Obj(override val uid: String) extends Params with HasOutputCol { + override def copy(extra: ParamMap): Obj = defaultCopy(extra) + } val obj = new Obj("obj") diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala index 6fef0b6205..dcfe9f7e27 100644 --- a/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala +++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/CrossValidatorSuite.scala @@ -96,6 +96,8 @@ object CrossValidatorSuite { override def transformSchema(schema: StructType): StructType = { throw new UnsupportedOperationException } + + override def copy(extra: ParamMap): MyEstimator = defaultCopy(extra) } class MyEvaluator extends Evaluator { @@ -105,5 +107,7 @@ object CrossValidatorSuite { } override val uid: String = "eval" + + override def copy(extra: ParamMap): MyEvaluator = defaultCopy(extra) } } |