Hi Matt,
Yes, you can convert a trained DAGNetwork object back into an editable LayerGraph object in MATLAB. The DAGNetwork object, obtained after training your network, contains the architecture and the trained weights, but as you've observed, it's not directly editable in the deepNetworkDesigner.
To convert the DAGNetwork back into an editable LayerGraph, you can use the layerGraph function provided by MATLAB. This function extracts the layer architecture (without the trained weights) from the DAGNetwork object. Here's how you can do it:
- Extract the layer architecture from the DAGNetwork object using layerGraph.
- Open the extracted layer graph in deepNetworkDesigner.
Here is the complete code for this process:
% Assuming 'net' is your trained DAGNetwork object
% Extract the layer architecture from the trained network
lgraph = layerGraph(net);
% Open the extracted layer graph in the Deep Network Designer
deepNetworkDesigner(lgraph);
This code will open the Deep Network Designer with the architecture of your trained network, where you can edit the properties of the input and other layers. Note that the trained weights are not included in the lgraph, so any changes you make and subsequent retraining will start from the beginning, unless you explicitly initialize the layers with the weights from the trained network.
Hope this helps!
