I have a multiclass classification task, and I have tried to use 'trainSoftmaxLayer' in Matlab, but it's a CPU implementation version, and is slow. So I tried to read the documentation for a GPU option, like 'trainSoftmaxLayer('useGPU', 'yes')' in traditional neural network, but there isn't any related options.
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Finally, the problem is sovled by hacking the source code of trainSoftmaxLayer.m, which is provided by MATLAB. We can write our own GPU-enabled softmax layer like this:
function [net] = trainClassifier(x, t, use_gpu, showWindow)
net = network;
% define topology
net.numInputs = 1;
net.numLayers = 1;
net.biasConnect = 1;
net.inputConnect(1, 1) = 1;
net.outputConnect = 1;
% set values for labels
net.name = 'Softmax Classifier with GPU Option';
net.layers{1}.name = 'Softmax Layer';
% define transfer function
net.layers{1}.transferFcn = 'softmax';
% set parameters
net.performFcn = 'crossentropy';
net.trainFcn = 'trainscg';
net.trainParam.epochs = 1000;
net.trainParam.showWindow = showWindow;
net.divideFcn = 'dividetrain';
if use_gpu == 1
net = train(net, x, full(t), 'useGPU', 'yes');
else
net = train(net, x, full(t));
end
end

Kevin He
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