Digital Drosophila Archive
36 lines
2.1 KiB
Python
36 lines
2.1 KiB
Python
"""Run old reference unchanged, writing only new experiment output."""
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import os
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import sys
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import time
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import numpy as np
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import pandas as pd
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import yaml
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from context import ROOT,EXP,CFG,save,check
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def main():
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check();assert not (EXP/'regression/frozen-five.json').exists()
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rtpath=ROOT/'models/male-cns-lif/deterministic-runtime-v2';pc=yaml.safe_load((rtpath/'phase4p.yaml').read_text())
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os.environ['CUDA_VISIBLE_DEVICES']=CFG['gpu_uuid'];os.environ['CUDA_HOME']='/usr/local/cuda'
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os.environ['PATH']=str(ROOT/'models/male-cns-lif/.venv/bin')+':/usr/local/cuda/bin:'+os.environ['PATH']
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os.environ['MAX_JOBS']='2';os.environ['TORCH_CUDA_ARCH_LIST']='8.9'
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sys.path.insert(0,str(ROOT/'models/male-cns-lif/terminal-scope-diagnostic-v1'))
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from diagnostic import queues
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queues();sys.path.insert(0,str(ROOT/'models/male-cns-lif'));sys.path.insert(0,str(rtpath))
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import torch,phase4p
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assert torch.cuda.mem_get_info()[0]>2*1024**3
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torch.cuda.reset_peak_memory_stats();t0=time.perf_counter();rt=phase4p.CanonicalRuntime(pc,rtpath,EXP);rows=[]
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for spec in pc['reference_trials']:
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queues();base=ROOT/'experiments/phase4p-deterministic-runtime/phase4c-v2/reference'/spec['name']
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ev=pd.read_parquet(base/'spike-events.parquet')
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ref=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'))
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result=rt.run(np.flatnonzero(rt.pops[spec['population']]),spec['rate_hz'],spec['seed'],spec['duration_ms'])
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row=dict(trial=spec['name'],exact={k:bool(np.array_equal(v,result[k])) for k,v in ref.items()},wall_seconds=result['metrics']['wall_seconds'])
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rows.append(row);print(row,flush=True)
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save(EXP/'regression/frozen-five.json',dict(pass_all=all(all(r['exact'].values()) for r in rows),trials=rows,
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wall_seconds=time.perf_counter()-t0,peak_allocated_vram=int(torch.cuda.max_memory_allocated()),oracle='old frozen deterministic-v2 only'))
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assert all(all(r['exact'].values()) for r in rows)
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if __name__=='__main__':main()
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