Add --seed CLI flag for reproducible active-learning batch selection - #851
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Markadrian6399 merged 2 commits intoSep 1, 2026
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…ction Add a --seed CLI flag to scripts/run_active_learning.py so contributors can reproduce a specific active-learning batch selection exactly when debugging a reported issue. The seed is forwarded to query strategies; BADGE (the randomised k-means++ strategy) now accepts a seed kwarg and threads it through _kmeans_pp_indices, defaulting to the previous hardcoded seed (42) when none is supplied to preserve existing behaviour.
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Closes #759
Summary
The active-learning query strategies (
detection/active_learning/query_strategies.py) involve randomness (e.g. BADGE's k-means++ seeding, and tie-breaking among equally-informative wallets), so a hardcoded or unexposed seed makes a specific batch selection impossible to reproduce when debugging a reported issue.This PR exposes a
--seedCLI flag onscripts/run_active_learning.pyso a contributor can reproduce a specific batch selection exactly.Changes
--seedargument toscripts/run_active_learning.py.BADGE.selectnow accepts aseedkwarg, threaded through_kmeans_pp_indices._kmeans_pp_indicesdefaults to the previous hardcoded seed (42) when none is supplied, preserving existing behaviour.--seedis passed to one that ignores it.Testing
No behaviour change when
--seedis omitted; existing tests are preserved.