Github user avulanov commented on the pull request:
https://github.com/apache/spark/pull/9614#issuecomment-168854243
@jkbradley If we want to follow the logic "users think they are still using
the existing optimizer when they access the optimizer", then there should be
two private variables for each optimizer instead of one. The proposed fix
creates a new optimizer if user switches from SGD to LBFGS and the mentioned
logic breaks.
By the way, `FeedForwardTrainer` is `ML` private, so it should not be used
by users. In practice, the creation of new optimizer never happens because the
public class `MultilayerPerceptronClassifier` uses LBFGS only.
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