need help to convert to a dlnetwork

I have this existing code

image = randi(255, [3,3,4]);
% create adder only network
inLayer = imageInputLayer(size(image), 'Name', 'data', 'Normalization', 'none');
addLayer = additionLayer(2, 'Name', 'add');
outLayer = regressionLayer('Name','output');
lgraph = layerGraph([inLayer, addLayer, outLayer]);
lgraph = connectLayers(lgraph, 'data', 'add/in2');
snet = assembleNetwork(lgraph);

I need to convert this to a dlnetwork and then train the dlnetwork using trainnet to replace the last regression output layer. How can I achieve the same?

Answer 1

[Ben]

The workflow for dlnetwork and trainnet would be something like the following:

image = randi(255,[3,3,4]);

% create network

net = [

imageInputLayer(size(image),Name="data",Normalization="none")

additionLayer(2,Name="add")];

% create as uninitialized so you can hook up the 2nd input to additionLayer before initializing

net = dlnetwork(net,Initialize = false);

net = connectLayers(net,"data","add/in2");

% initialize

net = initialize(net);

% train

opts = trainingOptions("adam");

% regressionLayer is not used, to specify loss you can use "mse" in trainnet

trainnet(image,image,net,"mse",opts);