Currently the examples in C++ such as the mnist, and the custom-dataset, dcgan creating the models in the C++ and compile to run the training and validation. This means the model is “fixed” once the source is compiled and any changes on the network structure would require to recompile the code again.
Any examples to have a compiled executable to accept network model such as mnist CNN in a file format (json/prototxt/etc…) and trained the model from the external file? This will allow user to modify the network structure in the file and retrain the model without recompiling the code.
A close example is the caffe (not caffe2) which have the model defined in prototxt.
Thanks.
Regard,
CL