See https://github.com/scikit-learn/scikit-learn/issues/3584


FWIW: Now even the version that first seemed to complete (but I thought I lost 
output for an unrelated reason) crashes again with the same error. The only 
thing I changed was to call the script with


stdbuf -oL python ….py > ….log

On Fri, Aug 22, 2014 at 9:25 AM, László Sándor <sand...@gmail.com> wrote:

> Sorry for the update: but now one version of the job (same size, but 
> different data) still failed with the OS failing to provide memory, even with 
> n_jobs=8. The maximum RAM the job took was 119705224K, while it was allocated 
> 240 GB.
> I am not sure how to make this reproducible for a bug report without sharing 
> the data.
> On Fri, Aug 22, 2014 at 8:54 AM, László Sándor <sand...@gmail.com> wrote:
>> Oh, Mailbox failed with the attachment, sorry, here it is.
>> On Fri, Aug 22, 2014 at 8:43 AM, László Sándor <sand...@gmail.com> wrote:
>>> Sorry, Olivier, I am not sure I follow. In any case, I am happy to update
>>> skl, I was only using the latest 64-bit Linux from the conda distro (though
>>> using MKL wanted to downgrade me to 0.14, I am pretty sure I precluded
>>> that).
>>>
>>> That said, maybe it’s good I did not file a proper bug report: The job
>>> completes with specifying n_jobs = 8 [the Windows test in July was an
>>> 8-core server], while n_jobs = -1 might have meant that the 64-cores it was
>>> supposed to find blew the job out of memory. I am still not sure why this
>>> happened when the job currently occupied 120 GB out of 240, but this might
>>> not be a scikit-bug after all.
>>>
>>>
>>> On Fri, Aug 22, 2014 at 8:37 AM, Olivier Grisel <olivier.gri...@ensta.org>
>>> wrote:
>>>
>>>> Thread based enet CV has been merged after the 0.15 release.
>>>>
>>>
>>>
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