[SPARK-18276][ML] ML models should copy the training summary and set parent

## What changes were proposed in this pull request?

Only some of the models which contain a training summary currently set the summaries in the copy method. Linear/Logistic regression do, GLR, GMM, KM, and BKM do not. Additionally, these copy methods did not set the parent pointer of the copied model. This patch modifies the copy methods of the four models mentioned above to copy the training summary and set the parent.

## How was this patch tested?

Add unit tests in Linear/Logistic/GeneralizedLinear regression and GaussianMixture/KMeans/BisectingKMeans to check the parent pointer of the copied model and check that the copied model has a summary.

Author: sethah <seth.hendrickson16@gmail.com>

Closes #15773 from sethah/SPARK-18276.

12 files changed, 62 insertions, 20 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
index 2718dd93dc..f8a606d60b 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/BisectingKMeans.scala
@@ -94,8 +94,9 @@ class BisectingKMeansModel private[ml] (
 
   @Since("2.0.0")
   override def copy(extra: ParamMap): BisectingKMeansModel = {
-    val copied = new BisectingKMeansModel(uid, parentModel)
-    copyValues(copied, extra)
+    val copied = copyValues(new BisectingKMeansModel(uid, parentModel), extra)
+    if (trainingSummary.isDefined) copied.setSummary(trainingSummary.get)
+    copied.setParent(this.parent)
   }
 
   @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
index 8fac63fefb..a0bd66e731 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/GaussianMixture.scala
@@ -89,8 +89,9 @@ class GaussianMixtureModel private[ml] (
 
   @Since("2.0.0")
   override def copy(extra: ParamMap): GaussianMixtureModel = {
-    val copied = new GaussianMixtureModel(uid, weights, gaussians)
-    copyValues(copied, extra).setParent(this.parent)
+    val copied = copyValues(new GaussianMixtureModel(uid, weights, gaussians), extra)
+    if (trainingSummary.isDefined) copied.setSummary(trainingSummary.get)
+    copied.setParent(this.parent)
   }
 
   @Since("2.0.0")
diff --git a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
index 85bb8c93b3..a0d481b294 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/clustering/KMeans.scala
@@ -108,8 +108,9 @@ class KMeansModel private[ml] (
 
   @Since("1.5.0")
   override def copy(extra: ParamMap): KMeansModel = {
-    val copied = new KMeansModel(uid, parentModel)
-    copyValues(copied, extra)
+    val copied = copyValues(new KMeansModel(uid, parentModel), extra)
+    if (trainingSummary.isDefined) copied.setSummary(trainingSummary.get)
+    copied.setParent(this.parent)
   }
 
   /** @group setParam */
diff --git a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
index 8656ecf609..1938e8ecc5 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/regression/GeneralizedLinearRegression.scala
@@ -776,8 +776,10 @@ class GeneralizedLinearRegressionModel private[ml] (
 
   @Since("2.0.0")
   override def copy(extra: ParamMap): GeneralizedLinearRegressionModel = {
-    copyValues(new GeneralizedLinearRegressionModel(uid, coefficients, intercept), extra)
-      .setParent(parent)
+    val copied = copyValues(new GeneralizedLinearRegressionModel(uid, coefficients, intercept),
+      extra)
+    if (trainingSummary.isDefined) copied.setSummary(trainingSummary.get)
+    copied.setParent(parent)
   }
 
   /**
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
index 0fdba1cb88..5d1a39f7c1 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/TrainValidationSplit.scala
@@ -221,7 +221,7 @@ class TrainValidationSplitModel private[ml] (
       uid,
       bestModel.copy(extra).asInstanceOf[Model[_]],
       validationMetrics.clone())
-    copyValues(copied, extra)
+    copyValues(copied, extra).setParent(parent)
   }
 
   @Since("2.0.0")
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 8771fd2e9d..2877285eb4 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
@@ -27,7 +27,7 @@ import org.apache.spark.ml.attribute.NominalAttribute
 import org.apache.spark.ml.classification.LogisticRegressionSuite._
 import org.apache.spark.ml.feature.{Instance, LabeledPoint}
 import org.apache.spark.ml.linalg.{DenseMatrix, Matrices, SparseMatrix, SparseVector, Vector, Vectors}
-import org.apache.spark.ml.param.ParamsSuite
+import org.apache.spark.ml.param.{ParamMap, ParamsSuite}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -141,6 +141,12 @@ class LogisticRegressionSuite
     assert(model.getProbabilityCol === "probability")
     assert(model.intercept !== 0.0)
     assert(model.hasParent)
+
+    // copied model must have the same parent.
+    MLTestingUtils.checkCopy(model)
+    assert(model.hasSummary)
+    val copiedModel = model.copy(ParamMap.empty)
+    assert(copiedModel.hasSummary)
   }
 
   test("empty probabilityCol") {
@@ -251,9 +257,6 @@ class LogisticRegressionSuite
     mlr.setFitIntercept(false)
     val mlrModel = mlr.fit(smallMultinomialDataset)
     assert(mlrModel.interceptVector === Vectors.sparse(3, Seq()))
-
-    // copied model must have the same parent.
-    MLTestingUtils.checkCopy(model)
   }
 
   test("logistic regression with setters") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala
index f2368a9f8d..49797d938d 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/BisectingKMeansSuite.scala
@@ -18,7 +18,8 @@
 package org.apache.spark.ml.clustering
 
 import org.apache.spark.SparkFunSuite
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Dataset
 
@@ -41,6 +42,13 @@ class BisectingKMeansSuite
     assert(bkm.getPredictionCol === "prediction")
     assert(bkm.getMaxIter === 20)
     assert(bkm.getMinDivisibleClusterSize === 1.0)
+    val model = bkm.setMaxIter(1).fit(dataset)
+
+    // copied model must have the same parent
+    MLTestingUtils.checkCopy(model)
+    assert(model.hasSummary)
+    val copiedModel = model.copy(ParamMap.empty)
+    assert(copiedModel.hasSummary)
   }
 
   test("setter/getter") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala
index 003fa6abf6..7165b63ed3 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/GaussianMixtureSuite.scala
@@ -18,7 +18,8 @@
 package org.apache.spark.ml.clustering
 
 import org.apache.spark.SparkFunSuite
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.Dataset
 
@@ -43,6 +44,13 @@ class GaussianMixtureSuite extends SparkFunSuite with MLlibTestSparkContext
     assert(gm.getPredictionCol === "prediction")
     assert(gm.getMaxIter === 100)
     assert(gm.getTol === 0.01)
+    val model = gm.setMaxIter(1).fit(dataset)
+
+    // copied model must have the same parent
+    MLTestingUtils.checkCopy(model)
+    assert(model.hasSummary)
+    val copiedModel = model.copy(ParamMap.empty)
+    assert(copiedModel.hasSummary)
   }
 
   test("set parameters") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
index ca39265355..73972557d2 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/clustering/KMeansSuite.scala
@@ -19,7 +19,8 @@ package org.apache.spark.ml.clustering
 
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.linalg.{Vector, Vectors}
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.param.ParamMap
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.mllib.clustering.{KMeans => MLlibKMeans}
 import org.apache.spark.mllib.util.MLlibTestSparkContext
 import org.apache.spark.sql.{DataFrame, Dataset, SparkSession}
@@ -47,6 +48,13 @@ class KMeansSuite extends SparkFunSuite with MLlibTestSparkContext with DefaultR
     assert(kmeans.getInitMode === MLlibKMeans.K_MEANS_PARALLEL)
     assert(kmeans.getInitSteps === 2)
     assert(kmeans.getTol === 1e-4)
+    val model = kmeans.setMaxIter(1).fit(dataset)
+
+    // copied model must have the same parent
+    MLTestingUtils.checkCopy(model)
+    assert(model.hasSummary)
+    val copiedModel = model.copy(ParamMap.empty)
+    assert(copiedModel.hasSummary)
   }
 
   test("set parameters") {
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
index ac1ef5feb9..111bc97464 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/GeneralizedLinearRegressionSuite.scala
@@ -24,7 +24,7 @@ import org.apache.spark.ml.classification.LogisticRegressionSuite._
 import org.apache.spark.ml.feature.Instance
 import org.apache.spark.ml.feature.LabeledPoint
 import org.apache.spark.ml.linalg.{BLAS, DenseVector, Vector, Vectors}
-import org.apache.spark.ml.param.ParamsSuite
+import org.apache.spark.ml.param.{ParamMap, ParamsSuite}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.random._
@@ -183,6 +183,9 @@ class GeneralizedLinearRegressionSuite
 
     // copied model must have the same parent.
     MLTestingUtils.checkCopy(model)
+    assert(model.hasSummary)
+    val copiedModel = model.copy(ParamMap.empty)
+    assert(copiedModel.hasSummary)
 
     assert(model.getFeaturesCol === "features")
     assert(model.getPredictionCol === "prediction")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
index c0e8afbf5e..df97d0b2ae 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/regression/LinearRegressionSuite.scala
@@ -23,7 +23,7 @@ import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.feature.Instance
 import org.apache.spark.ml.feature.LabeledPoint
 import org.apache.spark.ml.linalg.{DenseVector, Vector, Vectors}
-import org.apache.spark.ml.param.ParamsSuite
+import org.apache.spark.ml.param.{ParamMap, ParamsSuite}
 import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.ml.util.TestingUtils._
 import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
@@ -143,6 +143,9 @@ class LinearRegressionSuite
 
     // copied model must have the same parent.
     MLTestingUtils.checkCopy(model)
+    assert(model.hasSummary)
+    val copiedModel = model.copy(ParamMap.empty)
+    assert(copiedModel.hasSummary)
 
     model.transform(datasetWithDenseFeature)
       .select("label", "prediction")
diff --git a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
index 87100ae2e3..4463a9b6e5 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/tuning/TrainValidationSplitSuite.scala
@@ -22,11 +22,11 @@ import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.classification.{LogisticRegression, LogisticRegressionModel}
 import org.apache.spark.ml.classification.LogisticRegressionSuite.generateLogisticInput
 import org.apache.spark.ml.evaluation.{BinaryClassificationEvaluator, Evaluator, RegressionEvaluator}
-import org.apache.spark.ml.linalg.{DenseMatrix, Vectors}
+import org.apache.spark.ml.linalg.Vectors
 import org.apache.spark.ml.param.ParamMap
 import org.apache.spark.ml.param.shared.HasInputCol
 import org.apache.spark.ml.regression.LinearRegression
-import org.apache.spark.ml.util.DefaultReadWriteTest
+import org.apache.spark.ml.util.{DefaultReadWriteTest, MLTestingUtils}
 import org.apache.spark.mllib.util.{LinearDataGenerator, MLlibTestSparkContext}
 import org.apache.spark.sql.Dataset
 import org.apache.spark.sql.types.StructType
@@ -78,6 +78,10 @@ class TrainValidationSplitSuite
       .setTrainRatio(0.5)
       .setSeed(42L)
     val cvModel = cv.fit(dataset)
+
+    // copied model must have the same paren.
+    MLTestingUtils.checkCopy(cvModel)
+
     val parent = cvModel.bestModel.parent.asInstanceOf[LinearRegression]
     assert(parent.getRegParam === 0.001)
     assert(parent.getMaxIter === 10)