29 lines
1.4 KiB
Python
29 lines
1.4 KiB
Python
from pathlib import Path
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import subprocess,threading,queue,json,time,atexit
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R=Path.home()/'run/fly-knp'
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class Worker:
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def __init__(self,mode='cpu'):self.mode=mode;self.p=None;atexit.register(self.close)
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def close(self):
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p=self.p;self.p=None
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if p:
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p.terminate()
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try:p.wait(timeout=2)
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except subprocess.TimeoutExpired:p.kill();p.wait()
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def start(self):
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self.close();self.q=queue.Queue();q=self.q;p=subprocess.Popen([str(R/'controller'),self.mode],stdin=subprocess.PIPE,stdout=subprocess.PIPE,stderr=subprocess.STDOUT,text=True,bufsize=1);self.p=p
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def read():
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with (R/('worker-'+self.mode+'.log')).open('a') as log:
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for line in p.stdout:
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if line.startswith('RESULT '):q.put(json.loads(line[7:]))
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else:log.write(line);log.flush()
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q.put(None)
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threading.Thread(target=read,daemon=True).start()
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def infer(self,sensors):
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if not isinstance(sensors,list) or len(sensors)!=9 or any(type(v) is not int or not 0<=v<=15 for v in sensors):raise ValueError('Nine integer sensors0..15 required')
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if self.p is None or self.p.poll() is not None:self.start()
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t=time.monotonic()
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try:
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self.p.stdin.write(' '.join(map(str,sensors))+'\n');self.p.stdin.flush();v=self.q.get(timeout=20)
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if v is None:raise RuntimeError('KNP worker stopped')
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return dict(v,backend='KNP '+self.mode,neuralMilliseconds=round((time.monotonic()-t)*1000,3))
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except Exception:self.close();raise
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