[SPARK-14671][ML] Pipeline setStages should handle subclasses of PipelineStage

## What changes were proposed in this pull request?

Pipeline.setStages failed for some code examples which worked in 1.5 but fail in 1.6.  This tends to occur when using a mix of transformers from ml.feature. It is because Java Arrays are non-covariant and the addition of MLWritable to some transformers means the stages0/1 arrays above are not of type Array[PipelineStage].  This PR modifies the following to accept subclasses of PipelineStage:
* Pipeline.setStages()
* Params.w()

## How was this patch tested?

Unit test which fails to compile before this fix.

Author: Joseph K. Bradley <joseph@databricks.com>

Closes #12430 from jkbradley/pipeline-setstages.

1 files changed, 8 insertions, 1 deletions

diff --git a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
index a8c4ac6d05..1de638f245 100644
--- a/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
+++ b/mllib/src/test/scala/org/apache/spark/ml/PipelineSuite.scala
@@ -27,7 +27,7 @@ import org.scalatest.mock.MockitoSugar.mock
 import org.apache.spark.SparkFunSuite
 import org.apache.spark.ml.Pipeline.SharedReadWrite
 import org.apache.spark.ml.feature.{HashingTF, MinMaxScaler}
-import org.apache.spark.ml.param.{IntParam, ParamMap}
+import org.apache.spark.ml.param.{IntParam, ParamMap, ParamPair}
 import org.apache.spark.ml.util._
 import org.apache.spark.mllib.linalg.Vectors
 import org.apache.spark.mllib.util.MLlibTestSparkContext
@@ -201,6 +201,13 @@ class PipelineSuite extends SparkFunSuite with MLlibTestSparkContext with Defaul
        pipeline.fit(df)
     }
   }
+
+  test("Pipeline.setStages should handle Java Arrays being non-covariant") {
+    val stages0 = Array(new UnWritableStage("b"))
+    val stages1 = Array(new WritableStage("a"))
+    val steps = stages0 ++ stages1
+    val p = new Pipeline().setStages(steps)
+  }
 }