feat: Constraints on Tuner

[toby-coleman]

Summary

Closes #149 and allows optimisation runs to apply constraints during a run.

Changes

• Adds ConstraintError, which can be raised by a Component when a constraint is breached.
• Handle constraint breaches in optimisation.

[gemini-code-assist]

Summary of Changes

Hello @toby-coleman, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request enhances the Tuner's capabilities by introducing a robust mechanism for handling constraints during optimization runs. It defines a dedicated exception for constraint violations and integrates its handling directly into the optimization process, ensuring that trials breaching specified constraints are appropriately penalized and logged. This allows for more controlled and effective optimization by guiding the Tuner away from invalid or undesirable parameter configurations.

Highlights

• New Exception Type: Introduced a new ConstraintError exception class in plugboard/exceptions/__init__.py. This exception is intended to be raised by Component instances when a defined constraint is violated during an optimization run.
• Tuner Constraint Handling: Modified the Tuner's internal objective function (_build_objective in plugboard/tune/tune.py) to catch ConstraintError exceptions. When a constraint is violated, a warning is logged, and the objective value for that trial is set to math.inf (for minimization) or -math.inf (for maximization) to effectively penalize the trial and guide the optimization away from invalid parameter spaces.
• Ray Tune Integration for Early Stopping: Configured the underlying ray.tune.Tuner instance to stop trials early when a constraint_hit signal is received. This integrates the new ConstraintError handling with Ray Tune's stopping mechanisms, allowing for more efficient optimization by terminating unpromising trials.
• Integration Tests for Constraints: Added a new integration test (test_tune_with_constraint in tests/integration/test_tuner.py) to validate the Tuner's behavior with constraints. This test uses a custom ConstrainedB component that raises ConstraintError under specific conditions, ensuring that the Tuner correctly handles these violations, penalizes the objective, and maintains valid results.

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[gemini-code-assist]

Code Review

This pull request introduces a mechanism to handle constraints in the Tuner. It adds a ConstraintError and updates the optimization objective function to catch this error, assigning a very poor score to trials that violate constraints. This allows the optimizer to avoid invalid regions of the parameter space. I've identified a bug in the multi-objective optimization logic and a disconnected early-stopping configuration. The provided suggestions aim to fix these issues to make the constraint handling more robust and effective.

[codecov]

Codecov Report

❌ Patch coverage is 57.14286% with 6 lines in your changes missing coverage. Please review.

Files with missing lines	Patch %	Lines
plugboard/tune/tune.py	50.00%	3 Missing and 3 partials ⚠️

📢 Thoughts on this report? Let us know!

[chrisk314]

LGTM