[NLPL Task Force (A)] CNN slow-dow

[Stephan Oepen]

dear PyTorch users,

i just installed PyTorch 1.1.0 (now with NumPy 1.16.3) on Abel, and
for all i can tell this upgrade resolves the exceedingly slow
convolutions.  could i encourage you to test-drive this new module a
little?  it is called 'nlpl-pytorch/1.1.0/3.7'.

with thanks in advance, oe


On Thu, Mar 28, 2019 at 2:38 PM Andrei Kutuzov <andreku at ifi.uio.no> wrote:
>
> Hi,
>
> I tested our solution code for Obligatories 1 and 2 with Pytorch 0.4.1,
> and it seems to work.
> Thus, the best we can do right now I think is to downgrade PyTorch in
> the IN5550 environment to this version.
> This should be announced on the course web page and on Piazza, of course.
>
> On 3/26/19 6:36 PM, Vinit Ravishankar wrote:
> > FWIW, I did try setting up a local environment with numpy==1.16.1 and torch==1.0.0, but it runs fine on my laptop. It’s plausible that there might be a version mismatch with some C library or other, especially because (I think) most optimisation-related code is written in C, right?
> >
> > – Vinit
> >
> >> On 26 Mar 2019, at 17:41, Andrei Kutuzov <andreku at ifi.uio.no> wrote:
> >>
> >> Note also that the fast nlpl-pytorch/0.4.1 environment has Numpy 1.15.1,
> >> while both slow environments have Numpy 1.16.1.
> >> Can be of importance as well.
> >>
> >> On 3/26/19 4:25 PM, Andrei Kutuzov wrote:
> >>> I checked, and it doesn't depend on the Python version: Pytorch 1.0 runs
> >>> equally slow on both Python 3.5 and Python 3.7
> >>> Pytorch 0.4.1 runs on Python 3.5, and it is fast.
> >>>
> >>>
> >>>
> >>> On 3/26/19 4:21 PM, Vinit Ravishankar wrote:
> >>>> Here’s a super tiny bit of code that just runs the same convolutional layer on the same input 10ish times.
> >>>>
> >>>> – Vinit
> >>>>
> >>>>> On 26 Mar 2019, at 15:58, Stephan Oepen <oe at ifi.uio.no> wrote:
> >>>>>
> >>>>> do you guys have a ready-to-run code snippet and some instructions on
> >>>>> how to replicate the problem of unduly slow CNN performance in our
> >>>>> newest PyTorch installation?  also, could you quickly summarize the
> >>>>> results of benchmarking you have done so far?
> >>>>>
> >>>>> NLPL has three PyTorch modules:
> >>>>>
> >>>>> nlpl-pytorch/0.4.1
> >>>>> nlpl-pytorch/1.0.0/3.5
> >>>>> nlpl-pytorch/1.0.0/3.7
> >>>>>
> >>>>> it actually could be very nice to work towards a set of standard
> >>>>> benchmarks, e.g. one each for a simple deep MLP, CNN, and RNN?
> >>>>>
> >>>>> cheers, oe
> >>>
> >>>
> >>
> >>
> >> --
> >> Andrei
> >> PhD Candidate at Language Technology Group (LTG)
> >> University of Oslo
> >
>
>
> --
> Andrei
> PhD Candidate at Language Technology Group (LTG)
> University of Oslo