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From Chris Olivier <cjolivie...@gmail.com>
Subject Re: Turning CUDNN on/off in anaconda distribution
Date Thu, 11 Jul 2019 17:34:41 GMT
the problem is that additional training of a pretrained model on a
relatively simple vision-type model (not a complex model like resnet, but
it has some convolutions), is converging on CPU but not GPU — validation
does not converge, anyway.

is there an anaconda or pip package without cudnn to try without a rebuild?
i don’t think rebuild is an option.

On Thu, Jul 11, 2019 at 10:22 AM kellen sunderland <
kellen.sunderland@gmail.com> wrote:

> Having runtime loadable / plugable operators might help with this.
>
> On Thu, Jul 11, 2019 at 10:20 AM kellen sunderland <
> kellen.sunderland@gmail.com> wrote:
>
> > Once it's compiled the forward / backward, etc kernel implementations are
> > hard coded to use cuDNN.  In theory we could support raw CUDA in addition
> > to cuDNN but the additional CUDA kernel code would bloat the binary (it
> > targets several GPU types).
> >
> > On Thu, Jul 11, 2019 at 9:36 AM Chris Olivier <cjolivier01@gmail.com>
> > wrote:
> >
> >> Is there an environment variable or some other way to not use CUDNN in
> the
> >> anaconda distribution of mxnet?
> >>
> >
>

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