Digital Drosophila Archive
37 lines
2.4 KiB
Python
37 lines
2.4 KiB
Python
"""Seal interface evidence; never promote static transfer to learned memory."""
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import yaml
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from context import ROOT, MODEL, EXP, read, save, digest, check, integrity, budget, seal
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def main():
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check(full=True)
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from summarize import run
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result = run(verify_only=True)
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refs = read(EXP / 'regression/frozen-five.json')
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names = [r['name'] for r in yaml.safe_load((ROOT / 'models/male-cns-lif/deterministic-runtime-v2/phase4p.yaml').read_text())['reference_trials']]
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assert len(names) == len(set(names)) == 5
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assert refs['pass_all'] is True and [r['trial'] for r in refs['trials']] == names
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assert all(set(r['exact']) == {'step', 'neuron_idx', 'counts', 'v', 'g'} and
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all(v is True for v in r['exact'].values()) for r in refs['trials'])
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old = integrity(); save(EXP / 'regression/old-integrity-after.json', old)
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final = dict(status=result['status'], zero_overlay_exact=True, static25_repeat_exact=True,
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primary_trials_per_stage=120, repeats_per_stage=24, old_integrity_pass=all(r['pass'] for r in old.values()),
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frozen_five_reference_pass=True, frozen_eligibility_and_mask_unchanged=True,
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base_weights_unchanged=True, training=False, learned_candidate=False,
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scientific_summary_sha256=digest(EXP / 'audit/scientific-summary.json'),
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payload_bytes_before_manifest=budget(), next_required='Separately preregister finite olfactory paired/control conditioning; no automatic learning PASS')
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save(EXP / 'audit/final-status.json', final)
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with (EXP / 'REPORT.md').open('x', encoding='utf-8') as f:
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f.write('# Phase 4AM — whole-brain plastic interface\n\nStatus: `' + result['status'] + '`.\n\n')
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f.write('All 144 zero-overlay runs reproduce sealed AK D18 exactly. All 120 fixed-overlay primary runs and 24 repeats are retained.\n')
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f.write('The fixed overlay is the original float32 25% floor, added through the declared float64 SI bridge. No training occurred.\n\n')
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for name, block in result['blocks'].items():
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f.write('- ' + name + ': ' + '; '.join(pop + ' event changes ' + str(v['trials_event_change']) + '/30' for pop, v in block['populations'].items()) + '.\n')
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f.write('\nOld artifacts and five deterministic-v2 references pass integrity/regression. This does not complete the learning goal.\n')
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check(full=True); seal(MODEL); seal(EXP)
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print(final['status'], flush=True)
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if __name__ == '__main__':
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main()
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