I am developing a mobile application that uses neural networks to detect a certain pattern in a sequence.
In order to train the network, the example of "Sequence-to-Sequence Classification Using 1-D Convolutions" was largely followed.
My goal is to convert the SeriesNetwork object of the trained network to .onnx format, using exportONNXNetwork, but in this example this SeriesNetwork object is never created. Instead, for the training and inference phase we rely on parameters and hyperparameters identified during the training phase.
Is there a known strategy to perform the same sequence of operations (Training and Inference), but having as a result of training a Series Network object representing the neural network?