How to do the sum for 2 gradient objects in the deep learning toolbox?

SC
2019 11 27
1 个回答
更新时间：2019 12 10
3 次查看（30 天）

0 个投票

Hi,
I have gradients1 and gradients2 which have exactly same structure but different numerical values. How can I do the sum? Current I tried gradients1+gradients2 but I got error.
Thanks!
My code:
rng(123); % seed
X_ori=[4,163,80;5,164,75]; % data; #(number) = 2; #(features) = 3;
X=permute(X_ori,[3,4,2,1]);
dlX = dlarray(X, 'SSCB');
Y_ori=[0, 0, 0, 1; 0, 1, 0, 0]; % data labels (i.e. one-hot vectors for 4 classes)
myModel = [
imageInputLayer([1 1 3],'Normalization','none','Name','in')
fullyConnectedLayer(7,'Name','Layer 1')
fullyConnectedLayer(4,'Name','Layer 2')];
MyLGraph = layerGraph(myModel);
myDLnet = dlnetwork(MyLGraph);
gradients1 = dlfeval(@modelGradients1, myDLnet, dlX, Y_ori);
gradients2 = dlfeval(@modelGradients2, myDLnet, dlX, Y_ori);
gradients_sum = gradients1+gradients2;
function [gradients1] = modelGradients1(myModel, modelInput, CorrectLabels)
CorrectLabels_transpose=transpose(CorrectLabels);
[modelOutput,state] = forward(myModel,modelInput);
loss = -31*sum(sum(CorrectLabels_transpose.*log(sigmoid(modelOutput/100))));
gradients1 = dlgradient(loss, myModel.Learnables);
end
function [gradients2] = modelGradients2(myModel, modelInput, CorrectLabels)
CorrectLabels_transpose=transpose(CorrectLabels);
[modelOutput,state] = forward(myModel,modelInput);
loss = -42*sum(sum(CorrectLabels_transpose.*log(sigmoid(modelOutput/100))));
gradients2 = dlgradient(loss, myModel.Learnables);
end

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SC
SC 2019-11-30
编辑：SC 2019-11-30
I can change the line "gradients_sum = gradients1+gradients2;" to the followings and then I can get the sum. But I still want to know if there are some more efficient ways to do so.
gradients_sum = grad_sum(gradients1, gradients2);
function gradients_sum=grad_sum(gradients1, gradients2)
num_layers=size(gradients1,1);
gradients_sum=gradients1;
for i=1:num_layers
gradients_sum.Value{i,1}=gradients1.Value{i,1}+gradients2.Value{i,1};
end
end

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回答（1 个）

Sourav Bairagya
Sourav Bairagya 2019-12-10

0 个投票

As in this case, 'gradients1.Value' and 'gradients2.Value' both are cell arrays and each one contains another cell arrays as elements within it, hence, direct conversion of these two cell arrays into matrices using 'cell2mat' or direct addition of them using '+' operator is not possible. Hence, you have to access each element individually and add them.

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SC
SC
2019-11-27

回答：

Sourav Bairagya
Sourav Bairagya
2019-12-10

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