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@OkonSamuel OkonSamuel commented May 19, 2024

@OkonSamuel OkonSamuel requested a review from ablaom May 19, 2024 20:18
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ablaom commented May 19, 2024

I'm happy to approve this PR after appropriate testing (see below). However, it's is essentially a patch on top of a hack, for which I am personally to blame. That said, I think there is a fair chance that the overloading of in for MLJType (which is at least 3 years old, according to the blame) was rendered redundant when I refactored the learning networks code. The only way to find out for sure, would be to remove it and locally run

  • MLJBase tests
  • MLJTuning tests
  • MLJ#dev tests, with MLJ_TEST_INTEGRATION="true".

Is this something you would consider doing? Even if we accept the current PR, we probably want to run those tests anyway, so it's the same work really.

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ablaom commented Jul 19, 2025

Update: Investigations show that the replace method in MLJBase actually does use the overloading of Base.in in MLJModelInterface, and in a new PR I will implement the suggestion here for addressing the posted issue.

@ablaom ablaom mentioned this pull request Jul 19, 2025
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ablaom commented Jul 19, 2025

Closing as rendered redundant by #220

@ablaom ablaom closed this Jul 19, 2025
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