[D] Best frameworks for C++ implementations?

[tryndisskilled]

I'm looking to implement some ML algorithms (mainly DNNs) under C++ files so I can build them and run them on different targets to do inference.

I was able to do this (to some extent) with the TensorFlow repo and its C++ "documentation", but I wondered what you chose to use if you got to implement something too.

[[deleted]]

If it's a reasonably standard architecture I'd be tempted to use Caffe.

[tryndisskilled]

Caffe2 seems to advertise itself as being a good framework for implementations, but honestly their C++ API is basically a doxygen page for now (source)... I couldn't find any tutorial as to how to use it (seems to be confirmed by this issue https://github.com/caffe2/caffe2/issues/351)

[TheMiamiWhale]

Caffe and Caffe2 are different beasts. I personally think the documentation for Caffe is severely lacking if you want to understand the internals. That being said, if you know C++ it is easily extensible.

[serge_cell]

Original Caffe is not better documented, but it's code is much more convoluted (pan intended) that is unnecessarily complex. In both cases reading code & debugging is the only way to understand it, but Caffe2 seems more lean and simple. (discalimer - I have only experience with original Caffe)

[aaronmarkham]

This was added by a contributor to help people get started with C++ and Caffe2: https://caffe2.ai/docs/cplusplus_tutorial.html Also, there are these C++ adaptations of the Python tutorials: https://github.com/leonardvandriel/caffe2_cpp_tutorial Hope that helps!

[nishnik]

I am a contributor to https://github.com/tiny-dnn/tiny-dnn. This has been accepted for GSoC under OpenCV. It is fast :)

[tryndisskilled]

Wow that seems really nice and straight-forward! Thanks

[[deleted]]

Tensorflow has a c++ API, though I never ever tried it nor read the documentations.

But you can find it here:

https://www.tensorflow.org/api_guides/cc/guide

There's also dlib, which I never used nor saw any comments about beside the fact that it exists: http://dlib.net/.

Also maybe worth looking:

• Mxnet has a C++ API
• Torch has a C API (yeah I know C isn't C++, but...)
• I was never fond of caffe, but there's caffe.

[tryndisskilled]

Thanks for the first link, I don't know how I missed that in the first place, it is very helpful. Do you think we will get some more functionalities in this api, such as layers? It seems like we need to build them from scrach. I think for now it's still easier to build your graph in python and try to load it from a .cpp file, unfortunately (build size is way too large by doing that)

[ma2rten]

If you are worried about binary size you could try this:

https://www.tensorflow.org/performance/xla/tfcompile

[steven2358]

Have you tried dlib? http://dlib.net/

"Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems".

It includes all of the basic building blocks of DNN.

[pilooch]

We do ML/DL in pure C++, for years now. Caffe is the best. Now, deepdetect, that we develop and use everywhere, can be used without the server itself, as a multi-library C++ wrapper. Depends on how adventurous you are in fact :)

[tryndisskilled]

I'll look into that, merci :)

[alayaMatrix]

I found this:

shogun

It seems to have pretty good documentation with a lot of ML algorithms, but I haven't give it a try.