L4T-ML:r35.1.0-py3 broken Scikit-Learn libraries

When I import the sklearn libraries within the L4T-ML docker image (via jupyter notebook), I get an ImportError:
‘Contents of /usr/local/lib/python3.8/dist-packages/sklearn/__check_build/…/…/scikit_learn.libs…’ … It seems taht scikit-learn has not been built correctly.

As a potential fix, I tried to pip install sklearn in the docker, but that just reports that the package is already there and requirements are already there.

Furhtermore, what I find strange is that if I check the python version via ‘python --version’, it reports ‘2.7.18’ while the packages mention python 3.8 and jupyter kernel says ‘python 3’. Is 2.7.18 a special built for Jetpack that is actually a 3.x version???


We can import sklearn without issue.

Could you try it again or share the way to reproduce this?


hmm, that is weird, the sklearn import now succeeds, but the
import cv2
now gives ImportError /usr/lib/aarch64-linux-gnu/libgomp.so.1: cannot allocate memory in static TLS block

Maybe the sklearn issue pops up in specific combinations or order of imports, I’ll try a bit more to reproduce

Ok, after more trial and error I can reproduce the issue

from tensorflow.keras.utils import to_categorical
from sklearn.model_selection import train_test_split

Hi @michael.janus, please see this thread:

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