What are you using the PyTorch C++ API for?
Integrating it directly into the workflow of a large C++ image-processing application for the purpose of on-the-fly classification of cell morphologies from microscope images. Have a quite successful SVM classifier in place which uses sets of geometric descriptors computed from individual cell pixel sets, but the demands on the classifier are increasing to the point where a deep-learning approach applied to full cell images looks promising.


Software stack?
linux + gcc/clang


JIT or torch::nn models?
No/ have build a dynamically configurable replacement for Sequential, which will be my baseline “model”. Hope to do the same with dataset/optimizer/etc. specifications.


Are you training models in C++?
Not yet, but hopefully soon.


PyTorch C++ API review: Still new to it (a month or two). Like the previous commenter, I often end up digging through the source code (KDevelop is awesome for that, BTW). I understand that the various namespaces–e.g., c10::, at::, torch:: have a largely historical basis. Still, the documentation could use some meat.
As a model, I would point to the astoundingly elegant and useful documentation for the open source finite-element package “dealii”; this has been created and maintained largely by a single academic group in Germany (AFAIK), but the class references and very extensive set of tutorials are substantial and beautifully integrated.