TrainNetwork bug for 3D CNN

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

Answer 1

[cui,xingxing]

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?

Answer 2

[Amir Ebrahimi]

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.

[Duman]

Yes, that is right. I already used another CNN network without "crossChannelNormalizationLayer".

Thanks