Audit fixed D18 credit and conditional MBON transfer (Phase 4AL)

2026-09-30 13:58:39 +08:00
parent c6444255fe
commit 6d5f66bcc3
1058 changed files with 120679 additions and 18 deletions
@@ -0,0 +1,61 @@
+"""Rerun old deterministic-v2 references without changing their semantics."""
+import json
+import os
+import sys
+import time
+import urllib.request
+import numpy as np
+import pandas as pd
+import yaml
+from context import ROOT, EXP, check, save, bit_equal
+
+
+def preflight():
+    os.environ['CUDA_VISIBLE_DEVICES'] = 'GPU-79f3a85d-adce-7833-7003-6488140ca596'
+    os.environ['CUDA_HOME'] = '/usr/local/cuda'
+    os.environ['PATH'] = str(ROOT / 'models/male-cns-lif/.venv/bin') + ':/usr/local/cuda/bin:' + os.environ['PATH']
+    os.environ['MAX_JOBS'] = '2'
+    os.environ['TORCH_CUDA_ARCH_LIST'] = '8.9'
+    for port in (8188, 8189, 8190):
+        with urllib.request.urlopen(f'http://192.168.10.51:{port}/queue', timeout=5) as response:
+            queue = json.load(response)
+        assert not queue['queue_running'] and not queue['queue_pending'], 'Comfy busy: defer, do not evict'
+
+
+def main():
+    check(); preflight()
+    assert not (EXP / 'regression/frozen-five.json').exists()
+    runtime_path = ROOT / 'models/male-cns-lif/deterministic-runtime-v2'
+    config = yaml.safe_load((runtime_path / 'phase4p.yaml').read_text())
+    sys.path.insert(0, str(ROOT / 'models/male-cns-lif'))
+    sys.path.insert(0, str(runtime_path))
+    import torch
+    import phase4p
+    assert torch.cuda.mem_get_info()[0] > 2 * 1024**3
+    torch.cuda.reset_peak_memory_stats()
+    started = time.perf_counter()
+    runtime = phase4p.CanonicalRuntime(config, runtime_path, EXP)
+    rows = []
+    for spec in config['reference_trials']:
+        preflight()
+        reference_dir = ROOT / 'experiments/phase4p-deterministic-runtime/phase4c-v2/reference' / spec['name']
+        events = pd.read_parquet(reference_dir / 'spike-events.parquet')
+        reference = dict(step=events.step.to_numpy(), neuron_idx=events.neuron_idx.to_numpy(),
+            counts=np.load(reference_dir / 'per-neuron-spike-counts.int32.npy'),
+            v=np.load(reference_dir / 'final-voltage.float32.npy'), g=np.load(reference_dir / 'final-g.float32.npy'))
+        result = runtime.run(np.flatnonzero(runtime.pops[spec['population']]), spec['rate_hz'], spec['seed'], spec['duration_ms'])
+        row = dict(trial=spec['name'], exact={k: bit_equal(v, result[k]) for k, v in reference.items()},
+            dtype_shape={k: dict(reference_dtype=str(v.dtype), actual_dtype=str(result[k].dtype),
+                reference_shape=list(v.shape), actual_shape=list(result[k].shape)) for k, v in reference.items()},
+            wall_seconds=result['metrics']['wall_seconds'])
+        rows.append(row)
+        print(row, flush=True)
+    passed = len(rows) == 5 and all(all(row['exact'].values()) for row in rows)
+    save(EXP / 'regression/frozen-five.json', dict(pass_all=passed, trials=rows,
+        wall_seconds=time.perf_counter() - started, peak_allocated_vram=int(torch.cuda.max_memory_allocated()),
+        scope='Old frozen deterministic-v2 reference only, not D18 equality to old dynamics'))
+    assert passed
+
+
+if __name__ == '__main__':
+    main()