[Python] Python scikit-learn memory leak

This simple python code causes memory leak at each loop cycle. The leak only happens when when n_jobs parameter is not 1. Is there something I'm missing or any way to free memory leak caused by library?

import gc
import numpy as np
from sklearn.manifold import TSNE
from sklearn.cluster import OPTICS
import psutil
process = psutil.Process()


def main():
data = np.random.random((100, 100))
for _i in range(1, 50):
points = TSNE().fit_transform(data)
prediction = OPTICS(n_jobs=2).fit_predict(points) # n_jobs!=1
points = None
prediction = None
del prediction
del points
gc.collect()
print(process.memory_info().rss)


main()


I tried to manually free used variables and call garbage collector, but it doesn't work because it should be called within sub threads, which I don't have access to, I suppose.

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