[SPARK-14973][ML] The CrossValidator and TrainValidationSplit miss the seed when saving and loading

## What changes were proposed in this pull request?

https://issues.apache.org/jira/browse/SPARK-14973

Add seed support when saving/loading of CrossValidator and TrainValidationSplit.

## How was this patch tested?

Spark unit test.

Author: yinxusen <yinxusen@gmail.com>

Closes #12825 from yinxusen/SPARK-14973.

5 files changed, 30 insertions, 18 deletions

diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
index a41d02cde7..7d42da4a2f 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala
@@ -30,7 +30,6 @@ import org.apache.spark.internal.Logging
 import org.apache.spark.ml._
 import org.apache.spark.ml.evaluation.Evaluator
 import org.apache.spark.ml.param._
-import org.apache.spark.ml.param.shared.HasSeed
 import org.apache.spark.ml.util._
 import org.apache.spark.mllib.util.MLUtils
 import org.apache.spark.sql.{DataFrame, Dataset}
@@ -39,7 +38,7 @@ import org.apache.spark.sql.types.StructType
 /**
  * Params for [[CrossValidator]] and [[CrossValidatorModel]].
  */
-private[ml] trait CrossValidatorParams extends ValidatorParams with HasSeed {
+private[ml] trait CrossValidatorParams extends ValidatorParams {
   /**
    * Param for number of folds for cross validation.  Must be >= 2.
    * Default: 3
@@ -179,11 +178,13 @@ object CrossValidator extends MLReadable[CrossValidator] {
       val (metadata, estimator, evaluator, estimatorParamMaps) =
         ValidatorParams.loadImpl(path, sc, className)
       val numFolds = (metadata.params \ "numFolds").extract[Int]
+      val seed = (metadata.params \ "seed").extract[Long]
       new CrossValidator(metadata.uid)
         .setEstimator(estimator)
         .setEvaluator(evaluator)
         .setEstimatorParamMaps(estimatorParamMaps)
         .setNumFolds(numFolds)
+        .setSeed(seed)
     }
   }
 }
@@ -267,14 +268,16 @@ object CrossValidatorModel extends MLReadable[CrossValidatorModel] {
       val (metadata, estimator, evaluator, estimatorParamMaps) =
         ValidatorParams.loadImpl(path, sc, className)
       val numFolds = (metadata.params \ "numFolds").extract[Int]
+      val seed = (metadata.params \ "seed").extract[Long]
       val bestModelPath = new Path(path, "bestModel").toString
       val bestModel = DefaultParamsReader.loadParamsInstance[Model[_]](bestModelPath, sc)
       val avgMetrics = (metadata.metadata \ "avgMetrics").extract[Seq[Double]].toArray
-      val cv = new CrossValidatorModel(metadata.uid, bestModel, avgMetrics)
-      cv.set(cv.estimator, estimator)
-        .set(cv.evaluator, evaluator)
-        .set(cv.estimatorParamMaps, estimatorParamMaps)
-        .set(cv.numFolds, numFolds)
+      val model = new CrossValidatorModel(metadata.uid, bestModel, avgMetrics)
+      model.set(model.estimator, estimator)
+        .set(model.evaluator, evaluator)
+        .set(model.estimatorParamMaps, estimatorParamMaps)
+        .set(model.numFolds, numFolds)
+        .set(model.seed, seed)
     }
   }
 }
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 f2b7badbe5..f6f2bad401 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
@@ -30,7 +30,6 @@ import org.apache.spark.internal.Logging
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.evaluation.Evaluator
 import org.apache.spark.ml.param.{DoubleParam, ParamMap, ParamValidators}
-import org.apache.spark.ml.param.shared.HasSeed
 import org.apache.spark.ml.util._
 import org.apache.spark.sql.{DataFrame, Dataset}
 import org.apache.spark.sql.types.StructType
@@ -38,7 +37,7 @@ import org.apache.spark.sql.types.StructType
 /**
  * Params for [[TrainValidationSplit]] and [[TrainValidationSplitModel]].
  */
-private[ml] trait TrainValidationSplitParams extends ValidatorParams with HasSeed {
+private[ml] trait TrainValidationSplitParams extends ValidatorParams {
   /**
    * Param for ratio between train and validation data. Must be between 0 and 1.
    * Default: 0.75
@@ -177,11 +176,13 @@ object TrainValidationSplit extends MLReadable[TrainValidationSplit] {
       val (metadata, estimator, evaluator, estimatorParamMaps) =
         ValidatorParams.loadImpl(path, sc, className)
       val trainRatio = (metadata.params \ "trainRatio").extract[Double]
+      val seed = (metadata.params \ "seed").extract[Long]
       new TrainValidationSplit(metadata.uid)
         .setEstimator(estimator)
         .setEvaluator(evaluator)
         .setEstimatorParamMaps(estimatorParamMaps)
         .setTrainRatio(trainRatio)
+        .setSeed(seed)
     }
   }
 }
@@ -265,14 +266,16 @@ object TrainValidationSplitModel extends MLReadable[TrainValidationSplitModel] {
       val (metadata, estimator, evaluator, estimatorParamMaps) =
         ValidatorParams.loadImpl(path, sc, className)
       val trainRatio = (metadata.params \ "trainRatio").extract[Double]
+      val seed = (metadata.params \ "seed").extract[Long]
       val bestModelPath = new Path(path, "bestModel").toString
       val bestModel = DefaultParamsReader.loadParamsInstance[Model[_]](bestModelPath, sc)
       val validationMetrics = (metadata.metadata \ "validationMetrics").extract[Seq[Double]].toArray
-      val tvs = new TrainValidationSplitModel(metadata.uid, bestModel, validationMetrics)
-      tvs.set(tvs.estimator, estimator)
-        .set(tvs.evaluator, evaluator)
-        .set(tvs.estimatorParamMaps, estimatorParamMaps)
-        .set(tvs.trainRatio, trainRatio)
+      val model = new TrainValidationSplitModel(metadata.uid, bestModel, validationMetrics)
+      model.set(model.estimator, estimator)
+        .set(model.evaluator, evaluator)
+        .set(model.estimatorParamMaps, estimatorParamMaps)
+        .set(model.trainRatio, trainRatio)
+        .set(model.seed, seed)
     }
   }
 }
diff --git a/mllib/src/main/scala/org/apache/spark/ml/tuning/ValidatorParams.scala b/mllib/src/main/scala/org/apache/spark/ml/tuning/ValidatorParams.scala
index 7a4e106aeb..26fd73814d 100644
--- a/mllib/src/main/scala/org/apache/spark/ml/tuning/ValidatorParams.scala
+++ b/mllib/src/main/scala/org/apache/spark/ml/tuning/ValidatorParams.scala
@@ -25,15 +25,15 @@ import org.apache.spark.SparkContext
 import org.apache.spark.ml.{Estimator, Model}
 import org.apache.spark.ml.evaluation.Evaluator
 import org.apache.spark.ml.param.{Param, ParamMap, ParamPair, Params}
-import org.apache.spark.ml.util.{DefaultParamsReader, DefaultParamsWriter, MetaAlgorithmReadWrite,
-  MLWritable}
+import org.apache.spark.ml.param.shared.HasSeed
+import org.apache.spark.ml.util.{DefaultParamsReader, DefaultParamsWriter, MetaAlgorithmReadWrite, MLWritable}
 import org.apache.spark.ml.util.DefaultParamsReader.Metadata
 import org.apache.spark.sql.types.StructType
 
 /**
  * Common params for [[TrainValidationSplitParams]] and [[CrossValidatorParams]].
  */
-private[ml] trait ValidatorParams extends Params {
+private[ml] trait ValidatorParams extends HasSeed with Params {
 
   /**
    * param for the estimator to be validated
@@ -137,7 +137,8 @@ private[ml] object ValidatorParams {
     }
 
     val jsonParams = validatorSpecificParams ++ List(
-      "estimatorParamMaps" -> parse(estimatorParamMapsJson))
+      "estimatorParamMaps" -> parse(estimatorParamMapsJson),
+      "seed" -> parse(instance.seed.jsonEncode(instance.getSeed)))
 
     DefaultParamsWriter.saveMetadata(instance, path, sc, extraMetadata, Some(jsonParams))
 
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 3e734aabc5..061d04c932 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
@@ -136,6 +136,7 @@ class CrossValidatorSuite
 
     assert(cv.uid === cv2.uid)
     assert(cv.getNumFolds === cv2.getNumFolds)
+    assert(cv.getSeed === cv2.getSeed)
 
     assert(cv2.getEvaluator.isInstanceOf[BinaryClassificationEvaluator])
     val evaluator2 = cv2.getEvaluator.asInstanceOf[BinaryClassificationEvaluator]
@@ -186,6 +187,7 @@ class CrossValidatorSuite
 
     assert(cv.uid === cv2.uid)
     assert(cv.getNumFolds === cv2.getNumFolds)
+    assert(cv.getSeed === cv2.getSeed)
 
     assert(cv2.getEvaluator.isInstanceOf[BinaryClassificationEvaluator])
     assert(cv.getEvaluator.uid === cv2.getEvaluator.uid)
@@ -259,6 +261,7 @@ class CrossValidatorSuite
 
     assert(cv.uid === cv2.uid)
     assert(cv.getNumFolds === cv2.getNumFolds)
+    assert(cv.getSeed === cv2.getSeed)
 
     assert(cv2.getEvaluator.isInstanceOf[BinaryClassificationEvaluator])
     val evaluator2 = cv2.getEvaluator.asInstanceOf[BinaryClassificationEvaluator]
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 dbee47c847..df9ba418b8 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
@@ -127,6 +127,7 @@ class TrainValidationSplitSuite
     val tvs2 = testDefaultReadWrite(tvs, testParams = false)
 
     assert(tvs.getTrainRatio === tvs2.getTrainRatio)
+    assert(tvs.getSeed === tvs2.getSeed)
   }
 
   test("read/write: TrainValidationSplitModel") {
@@ -149,6 +150,7 @@ class TrainValidationSplitSuite
 
     assert(tvs.getTrainRatio === tvs2.getTrainRatio)
     assert(tvs.validationMetrics === tvs2.validationMetrics)
+    assert(tvs.getSeed === tvs2.getSeed)
   }
 }