Github user hhbyyh commented on a diff in the pull request:
https://github.com/apache/spark/pull/17326#discussion_r106765091
--- Diff:
mllib/src/test/scala/org/apache/spark/ml/classification/MultilayerPerceptronClassifierSuite.scala
---
@@ -74,6 +74,7 @@ class MultilayerPerceptronClassifierSuite
.setMaxIter(100)
.setSolver("l-bfgs")
val model = trainer.fit(dataset)
+ MLTestingUtils.checkCopy(model)
--- End diff --
Just something for consideration. Not sure if this is the best way to add
unit test for this. I don't think we need to add check only for the classes
included in this PR. And even if we do, maybe it's possible to do it in a more
uniform way, like in `testEstimatorAndModelReadWrite` or add a
`pipelineCompatibilityTest` as necessary.
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