That sequence right there was what I was looking for! I’m pretty sure that argmax isn’t the only way to represent the result of some model evaluation in the whole machine learning ecosystem, but all I need to know is what the model is doing for graph traversal on the inside.
I’m familiar with the serialization semantics and I’ve known about them for a while. I’m sure this will be considered a separate question - I see that there is a C++ version of each of load and save, torch::load and torch::save. But the C/++ and python respective functions don’t use the same format, and the python version pickles the code so that it’s not easily accessible from C++. 1) Is there an easy way I can load and traverse over the model in C++, and 2) will there be any future effort to try and use something a little more portable, like protobuf, for saving models?