[mlpack] GSoC'22 Project Proposal: Better Stack Layering & Ready-to-Use Model

[Marcus Edel]

Okay, that makes it more clear; not sure did you already think about how the DAG
graph should look from a very high-level point of view? The pdf has some
pointers in that direction. I wondered if you have some further pseudo-code that
goes in that direction?

My recommendation is to select between 2-4 models, depending on the complexity;
we would have to implement some additional operations for some of the models, so
we should keep that in mind.

> On Apr 3, 2022, at 8:09 AM, Shubham Agrawal <shubham.agra1206 at gmail.com> wrote:
> 
> A gentle reminder, as you may have missed the previous email.
> 
> On Sun, Mar 27, 2022 at 1:13 PM Shubham Agrawal <shubham.agra1206 at gmail.com <mailto:shubham.agra1206 at gmail.com>> wrote:
> Hello Marcus,
> 
> By breaking API, I meant both old and new API as I am thinking about defining the link between layers.
> Example -
> Layer2 = Layer2Type(..PrevLayerRequired)
> Something on this line. So that people do not need to know complex API for making links between layers as it might be confusing for many people. I have thought about giving backward compatibility, and it probably will be easy to give backward compatibility as every ANN created earlier comes under DAG. 
> I will convert all std::vector to std::map in multi_layer.hpp file <https://github.com/shubham1206agra/mlpack/blob/ann-vtable/src/mlpack/methods/ann/layer/multi_layer.hpp <https://github.com/shubham1206agra/mlpack/blob/ann-vtable/src/mlpack/methods/ann/layer/multi_layer.hpp>> so that I can convert everything to DAG structure. I am thinking of storing graph edges in as adjacency lists format.
> 
> About the 2nd project, let us implement most of the models as in Pytorch. All models only for a forward pass don't take much memory. When GPU support comes, it will be helpful if we can give more variety of models architecture. And I will look for non-implemented layers too.
> 
> Regards
> Shubham Agrawal
> 
> On Sat, Mar 26, 2022 at 8:56 PM Marcus Edel <marcus.edel at fu-berlin.de <mailto:marcus.edel at fu-berlin.de>> wrote:
> Hello Shubham,
> 
> Thanks for your interest in the project. I think you are aware that Ryan is currently refactoring the ann codebase.
> So when you say "This project will introduce breaking changes in ANN API." is that based on the current API or
> the updated API, from the table PR? There was already some discussion on the mailing list about the DAG project:
> 
> http://knife.lugatgt.org/pipermail/mlpack/2022-March/004648.html <http://knife.lugatgt.org/pipermail/mlpack/2022-March/004648.html>
> 
> In case you haven't seen it already. It should be possible to implement DAG without breaking the new API,
> especially since it introdcues some new concepts, like the MultiLayer which we can build on.
> 
> I like the second idea as well, one thing you should keep in mind that we currently don't have GPU support
> (will change soonish), that is why we focused in the past on smaller models that you can run on a resource
> constrained device, mobilenet is one example. So in your proposal I would go through the list and select reasonable
> models, also, you should check if one of the models require the implemenation of a non implemented operation.
> 
> I hope anything I said was helpful, let me know if I should clarify anything further.
> 
> Thanks
> Marcus
> 
> 
> > On Mar 15, 2022, at 12:09 AM, Shubham Agrawal <shubham.agra1206 at gmail.com <mailto:shubham.agra1206 at gmail.com>> wrote:
> > 
> > Hello everyone
> > 
> > I hope this email finds you well. My name is Shubham Agrawal. I am currently doing my undergrad studies (3rd year) at IITD, India. I have been contributing to mlpack organization for the past 2 to 3 months, and I want to participate in GSoC '22 under this organization. I wanted to propose two large projects (~350 hours), and I wish to work on at least one of the ideas. Or any other idea can work too if there is some issue with my proposal.
> > 
> > I am attaching a pdf document that contains my proposal. I hope to get valuable feedback from the community for building my proposal with this thread. 
> > 
> > I am looking forward to hearing from you.
> > 
> > Regards
> > Shubham Agrawal
> > GitHub username - shubham1206agra
> > <gsoc_proposal_draft.pdf>_______________________________________________
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> > http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack <http://knife.lugatgt.org/cgi-bin/mailman/listinfo/mlpack>
> 
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