MATLAB Answers

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

8 views (last 30 days)
SC
SC on 27 Nov 2019
Answered: Sourav Bairagya on 10 Dec 2019
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
  1 Comment
SC
SC on 30 Nov 2019
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

Sign in to comment.

Answers (1)

Sourav Bairagya
Sourav Bairagya on 10 Dec 2019
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.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!