TrainNetwork bug for 3D CNN

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Duman
Duman 2019-6-28
评论： Duman 2019-11-20
I have a train data set with the size as follows:
size(X_train)= 512*512*14*1*200
size(Y_train)=200*1
I designed a 3D CNN network3D CNN network (3D convolution) and I am trying to train the designed 3D model using trainNetwork function:
[net, tr] = trainNetwork(X_train,Y_train,layers,options);
When the 'MiniBatchSize' is bigger than one (MiniBatchSize>1), I get the following Error:
Error using trainNetwork (line 165)
Invalid input array.
Caused by:
Error using builtin
Invalid input array.
But for 'MiniBatchSize of 1, it starts to train the model!
My designed network properties are as follows:
layers = [
image3dInputLayer([512 512 14 1],"Name","image3dinput")
convolution3dLayer([11 11 7],96,"Name","conv3d","BiasLearnRateFactor",2,"Padding",[1 1 1;1 1 1],"Stride",[4 4 7])
reluLayer("Name","relu1")
crossChannelNormalizationLayer(5,"Name","norm1","K",1)
averagePooling3dLayer([3 3 1],"Name","avgpool3d","Stride",[2 2 1])
fullyConnectedLayer(2,"Name","fc")
softmaxLayer("Name","softmax")
classificationLayer("Name","classoutput")];
options = trainingOptions('sgdm', ...
'MiniBatchSize',10, ...
'MaxEpochs',50, ...
'InitialLearnRate',3e-4, ...
'Shuffle','every-epoch', ...
'Plots','training-progress');
Can you please help me to solve this issue?
Thank you,
Dooman

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回答（2 个）

cui,xingxing
cui,xingxing 2019-8-12
编辑：cui,xingxing 2019-8-13
if i set your "X_train , Y_train" like this:
X_train = zeros(320,320,16,3,200);
Y_train = categorical(randi(2,[200,1]));
and use your code can wok!
but i use my self custum datastore , can't work,why?
Amir Ebrahimi
Amir Ebrahimi 2019-11-20
As it seems, "crossChannelNormalizationLayer" does not work in 3D workflow in MATLAB 2019b. You may train your model with "MiniBatchSize"=1 but it is not correct anyway. Try to use other 3D models without "crossChannelNormalizationLayer". This bug is reported to Mathworks and they may fix it in future releases.
  1 个评论
Duman
Duman 2019-11-20
Yes, that is right. I already used another CNN network without "crossChannelNormalizationLayer".
Thanks

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