Validate isolated author LIF semantics without changing frozen models

2026-09-30 07:23:09 +08:00
parent 5008cd85ca
commit 92241aea02
460 changed files with 46900 additions and 47 deletions
@@ -0,0 +1,47 @@
+"""Unchanged deterministic-v2 five-trial regression; old outputs are read only."""
+import os
+import sys
+import time
+import numpy as np
+import pandas as pd
+import yaml
+from context import ROOT,EXP,CFG,save,check_prereg
+
+
+def main():
+    check_prereg()
+    assert not (EXP/'regression/frozen-five.json').exists()
+    runtime=ROOT/'models/male-cns-lif/runtime-v2-deterministic-candidate'
+    # Discover the exact prior-audit runtime path from its immutable config.
+    prior=yaml.safe_load((ROOT/CFG['prior_model']/'config.yaml').read_text())
+    runtime=ROOT/prior['runtime'];pc=yaml.safe_load((runtime/'phase4p.yaml').read_text())
+    sys.path.insert(0,str(ROOT/'models/male-cns-lif/terminal-scope-diagnostic-v1'))
+    from diagnostic import queues
+    queues()
+    os.environ['CUDA_VISIBLE_DEVICES']=pc['device']['visible_gpu_uuid']
+    os.environ['CUDA_HOME']='/usr/local/cuda';os.environ['MAX_JOBS']='2';os.environ['TORCH_CUDA_ARCH_LIST']='8.9'
+    os.environ['PATH']=str(ROOT/'models/male-cns-lif/.venv/bin')+':/usr/local/cuda/bin:'+os.environ['PATH']
+    sys.path.insert(0,str(ROOT/'models/male-cns-lif'));sys.path.insert(0,str(runtime))
+    import torch,phase4p
+    free,total=torch.cuda.mem_get_info();assert free>2*1024**3
+    torch.cuda.reset_peak_memory_stats();t0=time.perf_counter()
+    rt=phase4p.CanonicalRuntime(pc,runtime,EXP)
+    rows=[]
+    for spec in pc['reference_trials']:
+        queues();base=ROOT/'experiments/phase4p-deterministic-runtime/phase4c-v2/reference'/spec['name']
+        ev=pd.read_parquet(base/'spike-events.parquet')
+        expected=dict(step=ev.step.to_numpy(),neuron_idx=ev.neuron_idx.to_numpy(),
+            counts=np.load(base/'per-neuron-spike-counts.int32.npy'),
+            v=np.load(base/'final-voltage.float32.npy'),g=np.load(base/'final-g.float32.npy'))
+        r=rt.run(np.flatnonzero(rt.pops[spec['population']]),spec['rate_hz'],spec['seed'],spec['duration_ms'])
+        eq={k:bool(np.array_equal(r[k],v)) for k,v in expected.items()}
+        row=dict(trial=spec['name'],exact=eq,wall_seconds=r['metrics']['wall_seconds'])
+        rows.append(row);save(EXP/'regression'/('frozen-'+spec['name']+'.json'),row)
+        print(row,flush=True)
+    save(EXP/'regression/frozen-five.json',dict(pass_all=all(all(x['exact'].values()) for x in rows),trials=rows,
+        oracle='frozen deterministic-v2, NOT author Brian2',wall_seconds=time.perf_counter()-t0,
+        peak_allocated_vram=int(torch.cuda.max_memory_allocated()),gpu=torch.cuda.get_device_name(),comfyui_modified=False))
+    assert all(all(x['exact'].values()) for x in rows)
+
+
+if __name__=='__main__':main()