1 files changed, 66 insertions, 2 deletions
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 2ae74a2090..51c1baf682 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
@@ -21,7 +21,7 @@ import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.attribute.NominalAttribute
 import org.apache.spark.ml.feature.StringIndexer
 import org.apache.spark.ml.param.{ParamMap, ParamsSuite}
-import org.apache.spark.ml.util.{MetadataUtils, MLTestingUtils}
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MetadataUtils, MLTestingUtils}
 import org.apache.spark.mllib.classification.LogisticRegressionSuite._
 import org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
 import org.apache.spark.mllib.evaluation.MulticlassMetrics
@@ -33,7 +33,7 @@ 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 {
+class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultReadWriteTest {
 
   @transient var dataset: DataFrame = _
   @transient var rdd: RDD[LabeledPoint] = _
@@ -160,6 +160,70 @@ class OneVsRestSuite extends SparkFunSuite with MLlibTestSparkContext {
       require(m.getThreshold === 0.1, "copy should handle extra model params")
     }
   }
+
+  test("read/write: OneVsRest") {
+    val lr = new LogisticRegression().setMaxIter(10).setRegParam(0.01)
+
+    val ova = new OneVsRest()
+      .setClassifier(lr)
+      .setLabelCol("myLabel")
+      .setFeaturesCol("myFeature")
+      .setPredictionCol("myPrediction")
+
+    val ova2 = testDefaultReadWrite(ova, testParams = false)
+    assert(ova.uid === ova2.uid)
+    assert(ova.getFeaturesCol === ova2.getFeaturesCol)
+    assert(ova.getLabelCol === ova2.getLabelCol)
+    assert(ova.getPredictionCol === ova2.getPredictionCol)
+
+    ova2.getClassifier match {
+      case lr2: LogisticRegression =>
+        assert(lr.uid === lr2.uid)
+        assert(lr.getMaxIter === lr2.getMaxIter)
+        assert(lr.getRegParam === lr2.getRegParam)
+      case other =>
+        throw new AssertionError(s"Loaded OneVsRest expected classifier of type" +
+          s" LogisticRegression but found ${other.getClass.getName}")
+    }
+  }
+
+  test("read/write: OneVsRestModel") {
+    def checkModelData(model: OneVsRestModel, model2: OneVsRestModel): Unit = {
+      assert(model.uid === model2.uid)
+      assert(model.getFeaturesCol === model2.getFeaturesCol)
+      assert(model.getLabelCol === model2.getLabelCol)
+      assert(model.getPredictionCol === model2.getPredictionCol)
+
+      val classifier = model.getClassifier.asInstanceOf[LogisticRegression]
+
+      model2.getClassifier match {
+        case lr2: LogisticRegression =>
+          assert(classifier.uid === lr2.uid)
+          assert(classifier.getMaxIter === lr2.getMaxIter)
+          assert(classifier.getRegParam === lr2.getRegParam)
+        case other =>
+          throw new AssertionError(s"Loaded OneVsRestModel expected classifier of type" +
+            s" LogisticRegression but found ${other.getClass.getName}")
+      }
+
+      assert(model.labelMetadata === model2.labelMetadata)
+      model.models.zip(model2.models).foreach {
+        case (lrModel1: LogisticRegressionModel, lrModel2: LogisticRegressionModel) =>
+          assert(lrModel1.uid === lrModel2.uid)
+          assert(lrModel1.coefficients === lrModel2.coefficients)
+          assert(lrModel1.intercept === lrModel2.intercept)
+        case other =>
+          throw new AssertionError(s"Loaded OneVsRestModel expected model of type" +
+            s" LogisticRegressionModel but found ${other.getClass.getName}")
+      }
+    }
+
+    val lr = new LogisticRegression().setMaxIter(10).setRegParam(0.01)
+    val ova = new OneVsRest().setClassifier(lr)
+    val ovaModel = ova.fit(dataset)
+    val newOvaModel = testDefaultReadWrite(ovaModel, testParams = false)
+    checkModelData(ovaModel, newOvaModel)
+  }
 }
 
 private class MockLogisticRegression(uid: String) extends LogisticRegression(uid) {