Re: [Kaldi-users] Maxout training runs very slowly

[Xingyu Na <asr...@gm...>]

Sure. I'll check it out.

On 07/22/2015 11:59 PM, Jan Trmal wrote:
> Xingu, could you please prepare a patch against master of 
> kaldi-asr/kaldi on github so that we can include your change?
> y.
>
> On Wed, Jul 22, 2015 at 2:58 AM, Xingyu Na <asr...@gm... 
> <mailto:asr...@gm...>> wrote:
>
>     I update the Maxout implementation on GPU in case anyone wants to
>     try it in Kaldi...
>     Please check out: https://github.com/naxingyu/kaldi-nn
>
>
>     On 04/02/2015 01:08 AM, Daniel Povey wrote:
>>     It looks to me like the MaxoutComponent has not been properly set
>>     up for efficient operation on GPU: there is a loop in the
>>     Propagate function.  We didn't do this because it wasn't giving
>>     great results.
>>     Incidentally, for the multi-splice networks (which we're now
>>     calling TDNN) we may end up moving back from p-norm to ReLU, as
>>     ReLU now seems to be giving better WERs.
>>     Dan
>>
>>
>>     On Tue, Mar 31, 2015 at 10:30 PM, Xingyu Na
>>     <asr...@gm... <mailto:asr...@gm...>> wrote:
>>
>>         Hi,
>>
>>         I tried maxout training by changing the train_pnorm_fast
>>         recipe into
>>         train_maxout_recipe, simply replacing the PnormComponent using
>>         MaxoutComponent, forming a run_4e procedure.
>>         The training runs extremely slow... e.g. a pnorm iteration
>>         per job takes
>>         113 seconds, while a maxout iteration per job takes 3396 seconds.
>>         Did you ever try this? Any suggestions?
>>
>>         Thank you and best regards,
>>         Xingyu
>>
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