I want to train a deep network by Automatic Differentiation. Is these any solution?
layer2 = [ imageInputLayer([9 36 1],'Normalization','none','Name','input1-fcc') convolution2dLayer([7,7],64,'Name','conv1-fcc') batchNormalizationLayer('Name','bn1-fcc') reluLayer('Name','relu1-fcc') globalAveragePooling2dLayer('Name','pool5-fcc') fullyConnectedLayer(1,'Name','fc1')];lgraph = layerGraph(layer2);dlnet = dlnetwork(lgraph);% Input
a = rand(9,36,1,10);a = dlarray(a,'SSCB');a_pre = forward(dlnet,a);% output
b = rand(1,10);loss = mse(a_pre,b);gradients = dlgradient(loss,dlnet.Learnables);
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