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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