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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