import sklearn
from sklearn.linear_model import LogisticRegression
import numpy as np
import time
import psutil
import os

if __name__ == "__main__":
    print("Sklearn version: %s" % sklearn.__version__)
    n_samples = 2
    n_features = 2
    data = np.arange(n_samples*n_features).reshape((n_samples,n_features))
    labels = np.arange(n_samples)
    last_output_time = 0
    process = psutil.Process(os.getpid())
    for i in range(10000000):
        clf = LogisticRegression()
        clf.fit(X=data, y=labels)
        del clf
        if time.time()-last_output_time >= 5:
            print(process.get_memory_info()[0] / float(2 ** 20))
            last_output_time = time.time()