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How to start the training of a deep net from a given state?

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Sébastien Tosi
Sébastien Tosi on 17 Oct 2017
I would like to start the training of a deep net from the state it was in after a previous training. In my application the user iteratively adds annotations and I want to avoid training the netwrok from scratch at each iteration. Here is the code I use to define and train the network:
layers = [ ... imageInputLayer([2*BoxRad+1 2*BoxRad+1 1]) convolution2dLayer([9 9],100,'Stride',1) reluLayer maxPooling2dLayer(2,'Stride',2) convolution2dLayer([5 5],25,'Stride',1) reluLayer maxPooling2dLayer(2,'Stride',2) fullyConnectedLayer(2) softmaxLayer classificationLayer]; options = trainingOptions('sgdm', 'MaxEpochs', 30, 'MiniBatchSize', 32); net = trainNetwork(Images,Lbl,layers,options);


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