[Abhinav Maurya (Fire162)]

Why are these changes needed?

In flaml/automl/model.py, SKLearnEstimator.fit() checks getattr(self, "limit_resource", None) before wrapping execution in the limit_resource context manager. While LRL2Classifier declares limit_resource = True, LRL1Classifier omitted this attribute.

Because lrl1 is included in the default classification estimator list, training LRL1Classifier with a specified time_budget bypassed resource and timeout limiting entirely, causing long-running fits to overrun budgets significantly on wide or many-class datasets.

This change:

1. Adds limit_resource = True to LRL1Classifier in flaml/automl/model.py, aligning it with LRL2Classifier.
2. Adds unit tests in test/automl/test_model.py verifying that LRL1Classifier.limit_resource is True, fit respects budget constraints, and limit_resource is invoked during execution.

Related issue number

Closes #1612

Checks

• I've used pre-commit to lint the changes in this PR (note the same in integrated in our CI checks).
• I've included any doc changes needed for https://microsoft.github.io/FLAML/. See https://microsoft.github.io/FLAML/docs/Contribute#documentation to build and test documentation locally.
• I've added tests (if relevant) corresponding to the changes introduced in this PR.
• I've made sure all auto checks have passed.

[Copilot]

🟡 Changes recommended

The new invocation test fails on Windows and needs to skip platforms without resource limiting.

1 open issue

• Skip invocation test when resource module is unavailable · New

What changed in this PR

Enables existing resource limiting for L1 logistic regression, addressing budget overruns reported in #1612.

Changes:

• Sets LRL1Classifier.limit_resource = True, matching L2.
• Adds tests for the flag, budgeted fitting, and limiter invocation.

File	Description
test/​automl/​test_model.py	Adds L1 resource-limiting regression tests.
flaml/​automl/​model.py	Enables resource limiting for LRL1Classifier.

_{Review effort: Balanced}

[Li Jiang (thinkall)]

Overall review of the complete PR: changes requested for a deterministic Windows test failure.

The LRL1 resource-limit flag matches LRL2 and reuses the existing production platform guard. The added invocation assertion does not respect that guard. Running the two new tests on Windows produced 1 passed and 1 failed: test_lrl1_resource_limit_called asserts a call even though resource is unavailable and BaseEstimator.fit intentionally bypasses the limiter. Please make that test capability-aware; do not remove the production guard. The review-code harness and current Balanced Copilot review agree on this blocker.

Posted by thinkall-agent-auto-reviewer

[Li Jiang (thinkall)]

This assertion fails on supported Windows platforms. model_mod.resource is None there, so BaseEstimator.fit deliberately does not enter limit_resource, regardless of the new LRL1 flag. I reproduced the failure with python -m pytest test/automl/test_model.py::test_lrl1 test/automl/test_model.py::test_lrl1_resource_limit_called -q (1 passed, 1 failed). Skip the invocation-specific case when resource is unavailable, or assert the appropriate call/no-call behavior for each capability while retaining the cross-platform fit smoke test.

Posted by thinkall-agent-auto-reviewer

[Copilot]

🔵 Needs a closer look

The invocation test needs to account for Windows, where resource limiting is intentionally unavailable.

1 open issue

• Skip invocation test when resource module is unavailable

_{Review effort: Balanced}

[Copilot]

🔵 Needs a closer look

The limiter-invocation test needs to account for Windows, where resource limiting is unavailable.

1 open issue

• Skip invocation test when resource module is unavailable

_{Review effort: Balanced}

[Copilot]

🔵 Needs a closer look

The limiter-invocation test needs to account for Windows, where resource limiting is unavailable.

1 open issue

• Skip invocation test when resource module is unavailable

_{Review effort: Balanced}

[Copilot]

🔵 Needs a closer look

The invocation test needs a platform guard because resource limiting is bypassed on Windows, causing its assertion to fail.

1 open issue

• Skip invocation test when resource module is unavailable

_{Review effort: Balanced}

[Li Jiang (thinkall)]

Re-reviewed commits 4d9553cefbb14233782ccfd928264bfde5ca739c -> 6d5a3a774153cf7836d651b90b73ad48e33694bb. The only delta is main's website/yarn.lock update of follow-redirects 1.16.0 -> 1.16.1. One explicitly head-bound review-code Low execution (actual runtime gpt-6.1-sol) found no new issue in this identical inherited patch. Controller Git comparisons verify all non-lockfile tree entries are unchanged. This is a scoped merge-delta review, not a fresh clean signoff for unchanged feature code.

Version/URL/caret/SRI shape checks pass. No independent local registry/tarball verification, package smoke test or website rebuild is claimed. Previous feature findings and runtime validation limits remain preserved.

Changes remain required. The existing Windows test blocker remains: test_lrl1_resource_limit_called still requires a limiter call when resource is unavailable and production deliberately bypasses that limiter. The test and production guard are unchanged by this merge. The prior Windows result was one passed and one failed; this cycle does not claim to rerun that native test. The original changes-requested review remains applicable.

At the 2026-10-26T12:13:44.943946+00:00 gate snapshot, actual current-head workflows were: Build in_progress/no conclusion; Code formatting completed/success; docs completed/success. Copilot has Balanced review without an Approval recommended verdict; 2 review thread(s) remain unresolved. Gate approval is not successful CI completion, and no new PR approval is being submitted while required gates remain unmet.

Posted by thinkall-agent-auto-reviewer