Github user mengxr commented on a diff in the pull request:
https://github.com/apache/spark/pull/9848#discussion_r45527882
--- 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()
+ }
+ val subStageMaps =
subStages.map(getUidMap).foldLeft(Map.empty[String, Params])(_ ++ _)
+ Map(instance.uid -> instance) ++ subStageMaps
+ }
+ }
+
+ private[tuning] object SharedReadWrite {
+
+ /**
+ * Check that [[CrossValidator.evaluator]] and
[[CrossValidator.estimator]] are Writable.
+ * This does not check [[CrossValidator.estimatorParamMaps]].
+ */
+ def validateParams(instance: ValidatorParams): Unit = {
+ def checkElement(elem: Params, name: String): Unit = elem match {
+ case stage: MLWritable => // good
+ case other =>
+ throw new UnsupportedOperationException("CrossValidator write
will fail " +
+ s" because it contains $name which does not implement
Writable." +
+ s" Non-Writable $name: ${other.uid} of type ${other.getClass}")
+ }
+ checkElement(instance.getEvaluator, "evaluator")
+ checkElement(instance.getEstimator, "estimator")
+ // Check to make sure all Params apply to this estimator. Throw an
error if any do not.
+ // Extraneous Params would cause problems when loading the
estimatorParamMaps.
+ val uidToInstance: Map[String, Params] =
CrossValidatorReader.getUidMap(instance)
+ instance.getEstimatorParamMaps.foreach { case pMap: ParamMap =>
+ pMap.toSeq.foreach { case ParamPair(p, v) =>
+ require(uidToInstance.contains(p.parent), s"CrossValidator save
requires all Params in" +
+ s" estimatorParamMaps to apply to this CrossValidator, its
Estimator, or its" +
+ s" Evaluator. An extraneous Param was found: $p")
+ }
+ }
+ }
+
+ private[tuning] def saveImpl(
+ path: String,
+ instance: CrossValidatorParams,
+ sc: SparkContext,
+ extraMetadata: JValue): Unit = {
+ import org.json4s.JsonDSL._
+
+ val uid = instance.uid
+ val cls = instance.getClass.getName
+ val estimatorParamMapsJson = compact(render(
+ instance.getEstimatorParamMaps.map { case paramMap =>
+ paramMap.toSeq.map { case ParamPair(p, v) =>
+ Map("parent" -> p.parent, "name" -> p.name, "value" ->
p.jsonEncode(v))
+ }
+ }.toSeq
+ ))
+ val jsonParams = List(
+ "numFolds" ->
parse(instance.numFolds.jsonEncode(instance.getNumFolds)),
+ "estimatorParamMaps" -> parse(estimatorParamMapsJson)
+ )
+ val metadata = ("class" -> cls) ~
+ ("timestamp" -> System.currentTimeMillis()) ~
+ ("sparkVersion" -> sc.version) ~
+ ("uid" -> uid) ~
+ ("paramMap" -> jsonParams) ~
+ ("extraMetadata" -> extraMetadata)
--- End diff --
It is not easy to understand what `extraMetadata` means by looking at the
generated JSON file. Since this is `avgMetrics`, shall we call it `avgMetrics`
or save it as part of `data`?
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