I am new to Glow and PyTorch (trying to learn both). I have trained a very simple Neural network based classifier in PyTorch(C++). I want to do inferencing on PI3 and want to take advantage of glow. Requesting you to please let me know what all steps I need to follow to achieve this.

I think the best way here would be to use our AOT executable bundles, see here 31 for more info.

While checking example/mnist.cpp I observed that training, testing and validation is done using glow, however I was under the impression that glow has inference support only?

Glow supports training to some extent – we support autograd and execution of many grad ops. However we have focused much more on inference.

Is there any example where glow is applied on computational graph?

Not sure what you’re asking about specifically here – you can find lots of simple examples of computational graphs we build directly in Glow IR in our OperatorTest.cpp 6.