safe_svc.py

from multiprocessing import Process
from time import time
import numpy as np
from exline.helpers import with_timeout
from sklearn.svm import SVC


def __SVC_fit(model, X, y, out):
    out['result'] = model.fit(X, y)


def SVC_fit(model, X, y, timeout=5):
    manager = multiprocessing.Manager()
    out     = manager.dict()
    
    p = Process(target=__SVC_fit, args=(model, X, y, out), kwargs=kwargs)
    p.start()
    
    p.join(timeout=timeout)
    if not p.is_alive():
        return out['result']
    else:
        print('SVC_fit: timeout', file=sys.stderr)
        p.terminate()
        return None



model = SVC(C=1000)
np.random.seed(123)
X = np.random.uniform(0, 1, (10000, 2))
y = np.random.choice((0, 1), 10000)
t = time()
model = model.fit(X, y)
time() - t
model.decision_function(X).sum()



model = SVC(C=1000)
np.random.seed(123)
X = np.random.uniform(0, 1, (100000, 2))
y = np.random.choice((0, 1), 100000)
t = time()
model = SVC_fit(model, X, y)
time() - t
model.decision_function(X).sum()