Skip unused candidate-pruning penalty escalation#4392
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Summary
Bug
prune_pairwise_cost_matrix()always called_effective_large_cost()before checking whether the candidate mask actually pruned anything. For a retained cost equal tonp.finfo(float).max,_effective_large_cost()attemptednp.nextafter(max_float, np.inf), obtained infinity, and raisedValueErroreven though no replacement cost was needed.This made a valid no-op pruning configuration fail solely because the input occupied the upper end of the floating-point range.
Fix
Build the mask first. When all entries are retained, return an owning copy of the validated costs and skip replacement-cost escalation. The existing behavior is unchanged whenever at least one entry must be replaced.
Validation
max_floatentry still raises because no larger finite replacement existspython -m py_compilepasses for the modified module and regression test