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d500ba4e9e
The filament-group golden harness landed with H2C/A2L support (#14685). Its "FilamentGroup golden regression" / stress_66 case fails intermittently on Windows x64, on main and on unrelated PRs alike. The test depends on how fast the runner is. The k-medoids clustering these goldens exercise is an anytime search bounded by a 3 second wall clock. Every restart is seeded from its own index, so nothing about it is random. What varies is how many restarts fit in the budget, and the best cost is a minimum over completed restarts, so a slower runner is never better. Grading a score produced that way measures the machine as much as the code. Add a ClusteringBudget struct and let the tests set it. The defaults are the current 3 seconds and 30 restarts, so slicing behavior is unchanged. A non-positive timeout removes the wall clock and bounds the search by restart count alone. The goldens are then graded under a fixed budget of four restarts, where every one of them reaches the BambuStudio reference within 3%, so the score becomes a property of the code. This retires the machine-specific 125103 lock on stress_66. The default wall-clock path keeps its own test, asserting the grouping is valid and the search does not run away. It makes no score assertion, because under a wall clock that number is not a property of the code. The golden test also checks the run fits in ten times the default wall clock. Slicing quality depends on how many restarts fit in the budget, so a search an order of magnitude slower would degrade real groupings while a fixed-budget score gate stayed green. The 3% tolerance stays as the parity allowance against the goldens. It also covers a small spread across standard libraries: the k-medoids search seeds each restart with std::shuffle, whose algorithm the C++ standard leaves unspecified, so libstdc++, libc++ and the MSVC STL permute the same seed differently, start from different medoids, and settle on slightly different groupings, about 3e-4 apart and only on the goldens heavy enough to reach the k-medoids search.