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How does the “ trainNetwork” function define input training data?

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cui
cui on 4 Nov 2019
No matter how I change the input data format of image3dInputLayer, custom datastore, table, etc., can't be effectively trained?
load a.mat
layers = [
image3dInputLayer([64 64 64 4],"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(8,"Name","fc")
softmaxLayer("Name","softmax")
classificationLayer("Name","classoutput")];
options = trainingOptions('sgdm', ...
'MiniBatchSize',2, ...
'MaxEpochs',2, ...
'InitialLearnRate',3e-4, ...
'Shuffle','every-epoch', ...
'Plots','training-progress');
[net, tr] = trainNetwork(a,layers,options);
my a.mat is like this:
a.png
错误使用 trainNetwork (line 165)
无法读取文件 '1'。没有此类文件或目录。

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