A finished 12-minute humaneval bench died at the save line: some scorer
detail carried a non-JSON object (Ellipsis) and report.save's json.dumps
had no default. Every dumps on the save path now stringifies exotic
objects instead of killing the run; verified by replaying the exact
crashed checkpoint end-to-end (pass 82.3%, 15s, no crash).
Co-Authored-By: Claude <noreply@anthropic.com>
User feedback: the out-dir report-reuse layer was one concept too many.
Now each checkpoint line carries {key, ts, pred, score}:
- --resume restores predictions AND their scores; when every sample's
cached score matches the scoring-setup fingerprint (recipe/extract/
scorers/judge), the report is replayed with NO scorer, extractor or
docker container touching anything
- fingerprint mismatch (recipe or judge changed) -> automatic re-eval
and backfill of the fresh scores
- no --resume -> nothing read, nothing written (full fresh run)
- --rescore = ignore cached scores, re-evaluate, refresh the cache
- aggregation always recomputed from cached per-sample scores (cheap,
survives aggregator changes without invalidating)
- legacy checkpoints without a score field backfill on first evaluation
Removed: the out-dir report-reuse block (superseded; also the source of
the UnboundLocalError path).
Co-Authored-By: Claude <noreply@anthropic.com>
The checkpoint stores predictions, not scores -- reruns re-executed the
whole docker scoring pass even when nothing could change. When the
saved report matches (same model, same sample count) and every
prediction is checkpointed, reuse it; --rescore forces evaluation
(recipe/judge changed).
Also fixes EvalReport.load: metric_groups declared Dict[str, float]
rejected the None perf values (and the repeats scores list) the file
format actually contains -- every load raised ValidationError, which
is what silently killed reuse in testing.
Repeats>1 benches never reuse: their whole point is fresh sampling.
Co-Authored-By: Claude <noreply@anthropic.com>
Scoring progress: docker-exec benches (humaneval etc.) score for
minutes with zero feedback -- the bar sat at 'generating 100%' and
looked hung. evaluate() now takes on_scored(i, n) (atomic counter,
fires from worker threads), run_eval passes it through, and the CLI
shows 'scoring 42/164' on the bar + milestone log lines every 10%
(also fixes the phase match: 'scoring' never matched the capitalized
'Scoring predictions...' status message, so the bar never even
switched its label).
PooledAdapter:
- one release per acquire: the exception path released True (inner
finally) AND False (except handler), double-decrementing _inflight
(over-admission) and applying the x0.7 backoff twice
- AdaptiveGate: rebuild the Condition + probe task when the event loop
changes -- pools are cached across benchmarks and the CLI runs
asyncio.run() per bench/repeat; a loop-bound Condition from a closed
loop raises 'bound to a different event loop' under contention
Co-Authored-By: Claude <noreply@anthropic.com>
