Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/9848#discussion_r45527878
--- Diff:
mllib/src/main/scala/org/apache/spark/ml/tuning/CrossValidator.scala ---
@@ -131,6 +137,181 @@ class CrossValidator(override val uid: String)
extends Estimator[CrossValidatorM
}
copied
}
+
+ // Currently, this only works if all [[Param]]s in
[[estimatorParamMaps]] are simple types.
+ // E.g., this may fail if a [[Param]] is an instance of an [[Estimator]].
+ // However, this case should be unusual.
+ @Since("1.6.0")
+ override def write: MLWriter = new
CrossValidator.CrossValidatorWriter(this)
+}
+
+@Since("1.6.0")
+object CrossValidator extends MLReadable[CrossValidator] {
+
+ @Since("1.6.0")
+ override def read: MLReader[CrossValidator] = new CrossValidatorReader
+
+ @Since("1.6.0")
+ override def load(path: String): CrossValidator = super.load(path)
+
+ private[CrossValidator] class CrossValidatorWriter(instance:
CrossValidator) extends MLWriter {
+
+ SharedReadWrite.validateParams(instance)
+
+ override protected def saveImpl(path: String): Unit =
+ SharedReadWrite.saveImpl(path, instance, sc, JNothing)
+ }
+
+ private class CrossValidatorReader extends MLReader[CrossValidator] {
+
+ /** Checked against metadata when loading model */
+ private val className = classOf[CrossValidator].getName
+
+ override def load(path: String): CrossValidator = {
+ val (metadata, estimator, evaluator, estimatorParamMaps, numFolds) =
+ SharedReadWrite.load(path, sc, className)
+ new CrossValidator(metadata.uid)
+ .setEstimator(estimator)
+ .setEvaluator(evaluator)
+ .setEstimatorParamMaps(estimatorParamMaps)
+ .setNumFolds(numFolds)
+ }
+ }
+
+ private object CrossValidatorReader {
+ /**
+ * Examine the given estimator (which may be a compound estimator) and
extract a mapping
+ * from UIDs to corresponding [[Params]] instances.
+ */
+ def getUidMap(instance: Params): Map[String, Params] = {
+ val subStages: Array[Params] = instance match {
+ case p: Pipeline => p.getStages.asInstanceOf[Array[Params]]
+ case pm: PipelineModel => pm.stages.asInstanceOf[Array[Params]]
+ case v: ValidatorParams => Array(v.getEstimator, v.getEvaluator)
+ case _: Params => Array()
--- End diff --
Shall we add checks for `OneVSRest` and other meta-algorithms? It is okay
to create a JIRA and leave a TODO here.
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