Thank you for reaching out. Does your application require that you insert the folding and unfolding layers explicitly for a particular reason? Notice that you can completely avoid the insertion of these layers if you use dlnetwork instead of DAG networks. For instance, you can construct a convolution + LSTM network as:
layers = [
sequenceInputLayer([8 8 3], 'name','seq')
convolution2dLayer(3,3, 'Name', 'convolution1','Padding','same')
lstmLayer(20,'name','lstm')
fullyConnectedLayer(10,'Name','fc')
];
dlnet = dlnetwork(layers);
and the above network does support generic C/C++ code generation. On the other hand, when using DAG networks, you would need to insert sequence folding/unfolding layers (around convolution), which are not currently supported for generic C/C++ code generation.
Can the network you are working with be expressed as a dlnetwork to avoid the use of the unsupported layers? If so, I would recommend using a dlnetwork since it will soon become the recommended workflow. Otherwise, please let me know more about your use case to be able to further assist you
