Generate Network execution based on Training and Test data
Sometimes you want to execute your network with some training or test data examples and e.g. visualize how it performs. Therefore there is yet C++ Code generated which enables an execution of the network. Unfortunately, the loading of the data has to be done by hand, even if you want to execute the network with training data, for example when loading images or importing hdf5 data.
Therefore, the plan is to let the execution be generated (aditionally in python) and let the user of the framework only insert an index of the training or test data point which he wants to be executed, in order to then receive the prediciton and the label and compare in help of his code. In this context the DataLoader can be reused in the execution, but for that it must be available in the execution.