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From "Mike Dusenberry (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SYSTEMML-1965) Refactor nn layers to move the computation in forward/backward function known at compile time to init function
Date Tue, 17 Oct 2017 15:50:00 GMT

    [ https://issues.apache.org/jira/browse/SYSTEMML-1965?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16207814#comment-16207814
] 

Mike Dusenberry commented on SYSTEMML-1965:
-------------------------------------------

[~niketanpansare] I would strongly prefer to keep the sizes in the {{forward}} functions.
 The {{nn}} library is designed so that the {{init}} functions are just convenience initialization
functions that the user can either choose to use or not.  If we move the sizes to those functions,
then that forces the user to use the {{init}} functions at all times, and remember that those
sizes are associated with the output of the {{forward}} functions.  I think it would be better
to improve the constant propagation portion of the engine.

> Refactor nn layers to move the computation in forward/backward function known at compile
time to init function
> --------------------------------------------------------------------------------------------------------------
>
>                 Key: SYSTEMML-1965
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-1965
>             Project: SystemML
>          Issue Type: Bug
>            Reporter: Niketan Pansare
>
> Ideally, we should move the computation known at compile time to init layer, rather than
keep in the forward function. This reduces recompilation time and also potentially unnecessary
instructions. Here is an example snippet from our conv2d layer:
> {code}
> Hout = as.integer(floor((Hin + 2*padh - Hf)/strideh + 1))
> Wout = as.integer(floor((Win + 2*padw - Wf)/stridew + 1))
> {code}
> [~prithvi_r_s] [~dusenberrymw] [~reinwald] do you have any comments or concerns ?
> [~dusenberrymw] do you have free cycles to take this over ?



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