

DNNGraph – A deep neural network model generation DSL in Haskell - psoto
https://github.com/ajtulloch/dnngraph

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ajtulloch
Hi folks, author here - thanks for the interest in the project. It's literally
~1,000 lines of Haskell that I wrote a couple of weekends ago (and don't use
at all in production), but LMK if you find it useful in any way (or have
feature requests). Thanks!

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sinwave
This is really cool work. There is a lackluster theano feature which allows
you to print a flowchart figure for the "computation graph" corresponding to
the symbolic representation of your model.

@ajtulloch's library provides what I imagined the feature would be at first
glance - a comprehensible, elegant graphical representation of your NN model.
And on top of that, all in Haskell, with Haskell DSL for running torch - so
cool.

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soup10
Ok, how does this compare to machine learning tools in packages like R and the
other api's out there.

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shabadoop
I think the idea is it sets up Neural Networks that are then run in Torch,
with some nice diagram generating tools. I don't know if that's something
people will actually use, but it looks like a pretty concise way to generate a
pretty complicated Neural Network, which could be a worthwhile idea
considering how complex the more advanced ones are.

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soup10
Ah I see. I guess Haskell wrapper for Torch with diagrams doesn't sound as
impressive.

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shabadoop
It's not exactly a wrapper, since you presumably still use the generated NN in
LuaJIT. AI isn't my field, but it seems like a useful tool - actually setting
up a complex neural network seems to be a lot of grunt work, comparatively
speaking. There's probably a place for a tool that nicely abstracts over that
part of the process.

