Github user viirya commented on a diff in the pull request:
https://github.com/apache/spark/pull/9565#discussion_r59133802
--- Diff: mllib/src/main/scala/org/apache/spark/ml/Transformer.scala ---
@@ -90,7 +90,7 @@ abstract class UnaryTransformer[IN, OUT, T <:
UnaryTransformer[IN, OUT, T]]
* account of the embedded param map. So the param values should be
determined solely by the input
* param map.
*/
- protected def createTransformFunc: IN => OUT
+ protected val createTransformFunc: (T, IN) => OUT
--- End diff --
This change is to make non-code-generated evaluation of `ScalaUDF` works
with `RowEncoder` due to runtime mirror problem. I am thinking is it possible
that we only support code-generated evaluation of `ScalaUDF`? Then we can avoid
this change to `Transformer`. What you think? @rxin @davies Can you give some
suggestions? Thanks!
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