I recently set up a new machine to aid in decreasing run times for fitting models and data wrangling.
I did some preliminary benchmarks and everything is mostly smoothe, but I ran into a snag when I tried enabling multi-process workers with in scikit learn.
I've simplified the error to not be associated with my original code as I enabled this feature without a problem on a different machine and a VM.
I've also done memory allocation checks to make sure my machine wasn't running out of available RAM. I have 16gb of RAM so there should be no issue, but I've left the output of the test incase I missed something.
Given the traceback error near I can tell my OS is killing this, but for the life of me I can't figure out why. Near as I can tell my code will ONLY run when it is just using a single CPU core.
I'm running Windows 10, AMD ryzen 7 2700x, 16GB RAM
Code
import sklearn
import numpy as np
import tracemalloc
import time
from sklearn.model_selection import cross_val_score
from numpy.random import randn
from sklearn.linear_model import Ridge
##################### memory allocation snapshot
tracemalloc.start()
start_time = time.time()
snapshot1 = tracemalloc.take_snapshot()
###################### model
X = randn(815000, 100)
y = randn(815000, 1)
mod = Ridge()
sc = cross_val_score(mod, X, y,verbose =10, n_jobs=3)
################### Second memory allocation snapshot
snapshot2 = tracemalloc.take_snapshot()
top_stats = snapshot2.compare_to(snapshot1, 'lineno')
print("[ Top 10 ]")
for stat in top_stats[:5]:
print(stat)
The expected results from this are pretty obvious, just a returned score with the fit model.
Error Output
[Parallel(n_jobs=3)]: Using backend LokyBackend with 3 concurrent workers.
[Parallel(n_jobs=3)]: Done 3 out of 3 | elapsed: 0.2s remaining: 0.0s
---------------------------------------------------------------------------
TerminatedWorkerError Traceback (most recent call last)
<ipython-input-18-b2bdfd425f82> in <module>
16 y = randn(815000, 1)
17 mod = Ridge()
---> 18 sc = cross_val_score(mod, X, y,verbose =10, n_jobs=3)
..........
TerminatedWorkerError: A worker process managed by the executor was unexpectedly terminated.
This could be caused by a segmentation fault while calling the function or by an excessive memory usage causing the Operating System to kill the worker.
Memory Output
[ Top 5 ]
<ipython-input-18-b2bdfd425f82>:15: size=622 MiB (+622 MiB), count=3 (+3), average=207 MiB
<ipython-input-18-b2bdfd425f82>:16: size=6367 KiB (+6367 KiB), count=3 (+3), average=2122 KiB
~python37libinspect.py:732: size=37.2 KiB (+26.2 KiB), count=596 (+419), average=64 B
~python37libsite-packagessklearnexternalsjoblib
umpy_pickle.py:292: size=7072 B (+3808 B), count=13 (+7), average=544 B
~python37libpickle.py:549: size=5728 B (+3408 B), count=14 (+8), average=409 B
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