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error "Error using nnet.inter​nal.cnn.la​yer.util.i​nferParame​ters>iInfe​rSize (line 86) The output of layer 13 is incompatible with the input expected by layer 14."

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Salma Hassan
Salma Hassan on 7 Jan 2018
Edited: Johannes Bergstrom on 31 May 2018
where is the error in this code ..i only use googlenet as deep tuning without change any thing in it's Layers except the last 3 layers . i changed the size of my images to be similar of googlenet (224 224) so what wrong
net=googlenet;
TransfereLayers= net.Layers(2:end-3);
%% my layers Layers =[...
imageInputLayer([224 224 3],'Name','input')
TransfereLayers
fullyConnectedLayer(2,'Name',fc)
softmaxLayer
classificationLayer('Name','coutput')];
%% define the weights and biase
Layers(142).Weights = randn([2 1024]) * 0.001;
Layers(142).Bias = randn([2 1])*0.001 + 1;
%% options opts=trainingOptions('sgdm','Initiallearnrate',0.0001,'maxEpoch',maxEpochs ,..... 'Minibatchsize',miniBatchSize ,... 'Plots','training-progress',.... 'LearnRateSchedule', 'piecewise', ... 'LearnRateDropFactor', 0.1, ... 'LearnRateDropPeriod', 1, ... 'ValidationData',valDigitData,'ValidationFrequency',50 );
[mynet, traininfo] = trainNetwork(trainingimages,Layers,opts);

  3 Comments

Nicholas Howe
Nicholas Howe on 19 Jan 2018
I'm encountering a similar problem when trying to use googlenet. Likewise, inceptionv3 gives a similar error between layers 24 and 25. What's going on?

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Answers (1)

Joakim Lindblad
Joakim Lindblad on 9 Mar 2018
It's because GoogLeNet is a DAG which matlab handles differently than a layered network.
You can try with
trainNetwork(trainingimages,layerGraph(Layers),opts);
but I'm not sure that will be enough in this case.

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