Note: it seems to happen only in code that uses the
multiprocessing.pool.ThreadPool class. However I still cannot
reproduce the failure on toy scripts.
Rich, can you reproduce the problem on randomly generated data? If so
could you please post such a notebook publicly?
--
Olivier
--
Needless to say, if you have a way to reproduce this one with a simpler
case, please let us know. We'd love to track down the origin of the problem
and fix it if it's possible within ipython...
On Mon, Jun 30, 2014 at 12:48 AM, Olivier Grisel
wrote:
> I could reproduce the "ZMQError: Address al
I could reproduce the "ZMQError: Address already in use" under Python
3.4, IPython 2.1.0 and scikit-learn master when using cross validation
with n_jobs != 1 in IPython notebook on long running jobs.
There might be a problem with IPython notebook and POSIX forks
triggered by the use of mulitprocess
2014-06-25 4:50 GMT+02:00 Sturla Molden :
> In general, only POSIX APIs are safe to use on both sides of a fork
Actually, "only a short list of async-signal-safe library routines"
[1, 2]. Practically all of POSIX is off-limits after fork in a
multithreaded program.
[1] http://pubs.opengroup.org/o
On 23/06/14 22:54, Greg Dhuse wrote:
> I see the same error using iPython on Linux with custom use of
> multiprocessing Pool/Queue (not scikit-learn).
I have no idea about this. The problem could be in iPython,
multiprocessing, libgomp (the GNU OpenMP runtime), your LAPACK or BLAS
libraries,
Sturla Molden writes:
>
> Rich Lewis wrote:
>
> > I have been running RandomForestRegressor models for a while now on my
> > MacBook using the n_jobs=-1 option, which has worked well in the past.
>
> The cue here might be "MacBook"...
>
> Which LAPACK is NumPy and SciPy linked against?
>
>
On 18/06/14 17:41, Sturla Molden wrote:
> Rich Lewis wrote:
>
>> I have been running RandomForestRegressor models for a while now on my
>> MacBook using the n_jobs=-1 option, which has worked well in the past.
>
> The cue here might be "MacBook"...
>
> Which LAPACK is NumPy and SciPy linked agains
Rich Lewis wrote:
> I have been running RandomForestRegressor models for a while now on my
> MacBook using the n_jobs=-1 option, which has worked well in the past.
The cue here might be "MacBook"...
Which LAPACK is NumPy and SciPy linked against?
If multiprocessing is used with Accelerate Fram
Which version of sklearn is this ? Have a look at sklearn.__version__.
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On Wed, Jun 18, 2014 at 12:06:28PM +0100, Rich Lewis wrote:
> However, I am trying now, but the python processes which start off using 100%
> of the CPU quickly become idle, without finishing building the model. I can
> see them in activity monitor. When I manually interrupt the training, I get
>
Dear all,
I have been running RandomForestRegressor models for a while now on my MacBook
using the n_jobs=-1 option, which has worked well in the past.
However, I am trying now, but the python processes which start off using 100%
of the CPU quickly become idle, without finishing building the mo
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