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Fix target-length qualification metadata - #112
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Summary
target_lengthreward metadata through the fail-closed Parquet validatorcharacterstarget as a bounded non-boolean integerReproduction
The exact-main GPU qualification reached the v0.12 RL workload and failed before trainer construction because
reward_model.characterswas rejected by the older exact/rule-only field whitelist: run 34187325636.Validation
ruff check .ruff format --check .mypy src/miniverlpytest -q -m "not gpu and not network" --cov=miniverl: 2572 passed, 10 skipped, 24 deselected; 83% branch coverage53fc1d4d5b7adee09618d77ad62d4086ba56b78569832d6fc7c3bcd5c2695bbcThe failed qualification is not release evidence. After this PR is green and merged, the release will use a fresh workflow dispatch against the new exact main SHA.