One more point. This is the stack when I do a KeyboardInterruption:
File ".../anaconda/envs/prod/lib/python2.7/multiprocessing/process.py",
line 114, in run
File ".../anaconda/envs/prod/lib/python2.7/multiprocessing/pool.py", line
102, in worker
self._target(*self._args, **self._kwargs)
File ".../anaconda/envs/prod/lib/python2.7/multiprocessing/pool.py", line
102, in worker
task = get()
File
".../anaconda/envs/prod/lib/python2.7/site-packages/sklearn/externals/joblib/pool.py",
line 343, in get
return recv()
KeyboardInterrupt
task = get()
File
".../anaconda/envs/prod/lib/python2.7/site-packages/sklearn/externals/joblib/pool.py",
line 341, in get
racquire()
KeyboardInterrupt
Regards,
Pedro
2014-10-20 10:55 GMT+02:00 Pedro Cardoso <karudoso+skle...@gmail.com>:
> Hi.
>
> I am getting some strange issues, using sklearn functions that use
> multiple jobs, when fitting a dense Matrix array.
>
> First time I saw the problem was with GridSearchCV, but now seeing the
> same with KMeans. The process just stays there, No Memory increase, no CPU
> usage. Stuck.
>
> The input data is a 600K by 200 dense matrix. The software is the latest
> anaconda version. All was working fine with sparse data.
>
> Any ideas ?
>
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