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FIX Pipeline to use metadata passed to transform_input in intermediate steps - #34201

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adrinjalali merged 2 commits into
scikit-learn:mainfrom
StefanieSenger:fix_routing_pipeline
Jun 8, 2026
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FIX Pipeline to use metadata passed to transform_input in intermediate steps#34201
adrinjalali merged 2 commits into
scikit-learn:mainfrom
StefanieSenger:fix_routing_pipeline

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@StefanieSenger

@StefanieSenger StefanieSenger commented Jun 5, 2026

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Reference Issues/PRs

found while working on #34179,

What does this implement/fix? Explain your changes.

After fixing the tests in #34179, sklearn/tests/test_pipeline.py::test_transform_input_pipeline[fit_transform] legitimately failed.

With transform_input=["sample_weight"] and metadata routing enabled, Pipeline did not transform inputs in intermediate steps. These use the user-passed sample_weight instead. It works for fit though.

This fixes the bug (and makes the tests in #34179 pass).

AI usage disclosure

I used AI assistance for:

  • Code generation (e.g., when writing an implementation or fixing a bug)
  • Research and understanding

CC @adrinjalali @OmarManzoor

@StefanieSenger StefanieSenger added the Metadata Routing all issues related to metadata routing, slep006, sample props label Jun 5, 2026
@github-project-automation github-project-automation Bot moved this to Todo in Labs Jun 5, 2026
@StefanieSenger StefanieSenger moved this from Todo to In progress in Labs Jun 5, 2026
@StefanieSenger StefanieSenger moved this to To Review in Metadata routing Jun 5, 2026
@adrinjalali
adrinjalali merged commit 6882ad0 into scikit-learn:main Jun 8, 2026
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@github-project-automation github-project-automation Bot moved this from To Review to Done in Metadata routing Jun 8, 2026
@github-project-automation github-project-automation Bot moved this from In progress to Done in Labs Jun 8, 2026
@StefanieSenger
StefanieSenger deleted the fix_routing_pipeline branch June 8, 2026 09:44
@U-C4N

U-C4N commented Aug 10, 2026

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On November 23, 2025, you closed my PR as AI spam without offering any technical review of the actual changes.

A few months later, you submitted PR #34201 and explicitly disclosed using AI for code generation and research. That PR was reviewed and merged.

So apparently AI-generated code is not the problem.

The problem seems to be who is submitting it.

If there is an objective standard that explains why my contribution was dismissed as spam while yours was given a proper review, I would genuinely like to know what that standard is..

👯

#32769
#34201

prady0t pushed a commit to prady0t/scikit-learn that referenced this pull request Sep 2, 2026
@jeremiedbb jeremiedbb mentioned this pull request Sep 8, 2026
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@lesteve

lesteve commented Sep 9, 2026

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See our automated contribution policy.

As human maintainers, we are doing our best while being kind of DDoS-attacked by a lot of accounts opening what seems like automated PRs.

As a personal opinion at the time of writing, when I see a PR from a new contributor I do a quick vibe-check: I look at a profile activity, if the account has opened a number of PRs in separate repos in a short amount of time, I am not interested in reviewing the PR and I'd rather try to help a slow human who is genuinely interested to contributing to the project. I may not reply, I may close the PR directly, I may block the user in the worst case. All of this is very fuzzy and I am not saying I am good at having a consistent rule.

If you are genuinely interested in contributing to scikit-learn and you haven't done it already, please have a look at our contributing doc and in particular the section Issues for new contributors.

I would suggest you look at the GitHub's How to contribute to Open-Source guide, which gives a good generic overview about how open-source works.

jeremiedbb pushed a commit that referenced this pull request Sep 10, 2026
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Metadata Routing all issues related to metadata routing, slep006, sample props module:pipeline

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4 participants