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This was referenced Nov 1, 2026
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Parameter sampling reused the last Python attribute-assignment timestamp. In-place optimizer updates could therefore record changed parameter values at unchanged or backdated times, corrupting observation chronology and derived variable lifetimes.
Both subclass and legacy proxy samples now capture observation-start time for
sampleandselective-sample, preserving mutation bookkeeping, non-sampling event times, registry eligibility, suppression, and exceptions. Repeating inference/checking also exposed a separate coverage-observer bug: valid NumPy integer lifetime endpoints were rejected. A separate signed commit adds an exact, finite numeric conversion at that dataframe boundary; generic JSON validators and checker predicates remain unchanged.Measured correctness improvement: on a fresh matched 2×A16, four-update Transformer trial, invalid after-update times fall from 216/216 to 0/216; equal before/after times despite changed hashes fall from 54/216 to 0/216. API/VAR record counts remain 7,504/594 in both versions, with no duplicate API event keys. Across six fixed subclass trials, 1,080/1,080 parameter/update pairs have complete samples and correct chronology.
All nine GPU phases complete successfully. All eight full checkpoint comparisons pass, covering 274 tensor pairs per comparison and matching whole-file hashes, including FP32/BF16, both resume directions, and the deliberately faulty normalization run. This is a correctness change, not a performance claim.
Validation:
2**53, observer-on/off parity, missing/malformed values, booleans, nonfinite values, and datetime/duration rejection are covered.Fresh API+VAR checking finishes with 596/605 active rules, zero dormant/error/unknown outcomes. Healthy/fault violations are 9/8 on rank 0 and 15/17 on rank 1. Two rank-1 fault-only metadata-distinctness alarms do not establish normalization detection. The raw-data diagnosis shows the applied scale was not captured, numeric loss data was excluded, and existing rules do not encode global-token normalization. Healthy object-ID-based false alarms remain visible. Frozen inputs match; every previously completed per-rule report is exactly unchanged after the observer fix.
Full experiment report · Normalization coverage diagnosis
Limits: observation times do not imply exact mutation times or atomic snapshots; an explicit after-update sample remains outside the optimizer API interval. No FSDP, stochastic/dropout, changed topology, partial accumulation windows, or agent-benefit claim. Large evidence stays outside Git: the local archive has 185 hash-verified files; both source snapshots match their committed Python files exactly. Final audit finds no remaining study processes and idle GPUs.
Dependency: stacked on #166 (
codex/ring18-distributed-probe), itself stacked on #164. All four commits are signed. No merge performed.