Digital Drosophila Archive
92 lines
5.8 KiB
Python
92 lines
5.8 KiB
Python
"""Register a two-arm timing intervention before new trajectory outcomes."""
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from datetime import datetime, timezone
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import difflib
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import platform
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import shutil
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import subprocess
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import sys
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import numpy as np
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from context import (ROOT, MODEL, EXP, AG, AG_MODEL, AI, AI_MODEL, AH_MODEL, META,
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COEFF, CFG, digest, read, save, sources, integrity, budget)
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def copy_exact(src, dst):
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dst.parent.mkdir(parents=True, exist_ok=True)
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with src.open('rb') as a, dst.open('xb') as b:
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shutil.copyfileobj(a, b)
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assert digest(src) == digest(dst)
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def main():
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assert not EXP.exists() or not any(EXP.iterdir()), 'Never reuse a populated experiment'
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assert shutil.disk_usage(EXP.parent).free > CFG['output_budget_bytes'] + 10 * 1024**3
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assert read(AI / 'audit/final-status.json')['status'] == 'PASS-CONDITIONAL-PN-APL-SOURCE-AUDIT'
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assert CFG['apl'] == read(AG_MODEL / 'config.json')['apl'] and CFG['delays_steps'] == [0, 18]
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for sub in ('protocol', 'cases', 'gpu', 'oracle', 'audit', 'logs', 'regression', 'component-audit', 'calibration', 'extension-build'):
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(EXP / sub).mkdir(parents=True, exist_ok=False)
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command = [sys.executable, '-B', '-m', 'unittest', 'discover', '-v', '-s', str(MODEL), '-p', 'test_*.py']
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tested = subprocess.run(command, cwd=MODEL, capture_output=True, text=True)
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with (EXP / 'regression/unit-tests.log').open('x') as f:
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f.write(tested.stdout + tested.stderr)
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save(EXP / 'regression/unit-tests.json', dict(command=command, exit_code=tested.returncode,
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pass_all=tested.returncode == 0, sha256=digest(EXP / 'regression/unit-tests.log')))
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assert tested.returncode == 0, 'Unit tests failed; stop before registration'
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inputs = [AI / 'manifest.json', AI / 'checksums.sha256', AI_MODEL / 'manifest.json',
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AG / 'manifest.json', AG_MODEL / 'manifest.json', META, COEFF,
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AH_MODEL / 'replay_core.py', AG_MODEL / 'legacy_apl_worker.py', AG_MODEL / 'gpu_apl.py',
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AG_MODEL / 'oracle_apl.py', AG_MODEL / 'compare.py', AG_MODEL / 'calibration.py',
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AG_MODEL / 'validate_components.py', AI / 'protocol/neuron-source-groups.parquet']
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save(EXP / 'protocol/preregistered.json', dict(timestamp_utc=datetime.now(timezone.utc).isoformat(),
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sources=sources(), config=CFG, inputs=[dict(path=str(p.relative_to(ROOT)), sha256=digest(p)) for p in inputs],
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parent_commit=subprocess.check_output(['git', '-C', str(ROOT), 'rev-parse', 'HEAD'], text=True).strip(),
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before_new_trajectories=True, prior_CAL_and_AI_outcomes_known=True,
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single_factor='generated graded-APL h applied at t versus t+18; nothing else',
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fixed_input_counts_and_amplitudes=True, actual_accepted_requests_may_change_due_to_closed_loop=True,
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formal_learning_claim=False, oracle_limit='Independent Brian LIF state with shared legacy Torch APL arithmetic; separate component audit',
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delay_biological_measurement=False, whole_brain_equal_total_inhibition_claim=False,
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timing_test_no_full_future_tail_claim=True, source_diffs_are_review_material_not_equivalence_proof=True,
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scope='Origin audit -> exact shift conservation -> two-arm fixtures -> fullgraph oracle probes -> complete two-arm fixed CAL -> frozen regression',
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python=sys.version, numpy=np.__version__, machine=platform.machine()))
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save(EXP / 'regression/old-integrity-before.json', integrity())
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for old, new in (('gpu_apl.py', 'gpu_timing.py'), ('oracle_apl.py', 'oracle_timing.py'), ('compare.py', 'compare_timing.py')):
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difference = ''.join(difflib.unified_diff((AG_MODEL / old).read_text().splitlines(True),
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(MODEL / new).read_text().splitlines(True), fromfile=str(AG_MODEL / old), tofile=str(MODEL / new)))
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with (EXP / 'protocol' / (new + '.diff')).open('x') as f:
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f.write(difference)
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records = read(AG / 'protocol/calibration-cases.json')
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assert len(records) == 60 and len({r['name'] for r in records}) == 60
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copy_exact(AG / 'protocol/calibration-cases.json', EXP / 'protocol/calibration-cases.json')
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copy_exact(AG / 'protocol/encoder-audit.json', EXP / 'protocol/encoder-audit.json')
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names = CFG['fixtures'] + [r['name'] for r in records]
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inventory = []
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for delay in CFG['delays_steps']:
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arm = 'delay' + str(delay)
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for sub in ('cases', 'gpu', 'oracle', 'component-audit', 'calibration'):
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(EXP / sub / arm).mkdir(exist_ok=False)
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for name in names:
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src = AG / 'cases' / name
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dst = EXP / 'cases' / arm / name
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dst.mkdir(exist_ok=False)
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spec = read(src / 'spec.json')
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old_spec = dict(spec)
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spec.update(apl_delay_steps=delay, budget_root=str(EXP), output_budget_bytes=CFG['output_budget_bytes'])
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save(dst / 'spec.json', spec)
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for key in set(old_spec) - {'budget_root', 'output_budget_bytes'}:
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assert old_spec[key] == spec[key]
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files = []
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for fname in ('requests.npz', 'arrays.npz', 'pn-drive.npz'):
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if (src / fname).exists():
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copy_exact(src / fname, dst / fname)
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files.append(dict(file=fname, sha256=digest(src / fname)))
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inventory.append(dict(arm=arm, delay_steps=delay, name=name, kind=spec['kind'],
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source_case=str(src.relative_to(ROOT)), unchanged_input_files=files))
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save(EXP / 'protocol/case-inventory.json', inventory)
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save(EXP / 'protocol/prepared-hashes.json', [dict(path=str(p.relative_to(EXP)), sha256=digest(p), bytes=p.stat().st_size)
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for sub in ('protocol', 'cases') for p in sorted((EXP / sub).rglob('*')) if p.is_file() and p.name != 'prepared-hashes.json'])
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budget()
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print('REGISTERED 2 delays, 8 fixtures + 60 CAL each; exact original inputs; no new trajectory yet', flush=True)
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if __name__ == '__main__':
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main()
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