Error: Invalid network layer does not support sequence input

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ZEMIN HUANG
ZEMIN HUANG 2021-1-26
评论： ZEMIN HUANG 2021-1-31
hi, i am building a CNN training model. however, i got this error that do not know how to solve. i tried to insert a sequence folding layer then i got error again saying that "unconnected input and output". please help me with this
% Load training data and essential parameters
load('trainData.mat','XTrain','YTrain');
numSC = 64;
% Batch size
miniBatchSize = 4000;
% Iteration
maxEpochs = 10;
% Sturcture
inputSize = [6,64,1];
numHiddenUnits = 128;
numHiddenUnits2 = 64;
numHiddenUnits3 = numSC;
numClasses = 16;
% DNN Layers
layers = [ ...
sequenceInputLayer(inputSize,'Name','sequence')
convolution2dLayer(3,32,'Name','conv2')
reluLayer('Name','relu')
maxPooling2dLayer(2,'Name','maxpool')
flattenLayer('Name','flat')
lstmLayer(numHiddenUnits,'OutputMode','last','Name','lstm')
fullyConnectedLayer(numClasses,'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','class')];
% Training options
options = trainingOptions('adam',...
'InitialLearnRate',0.01,...
'ExecutionEnvironment','auto', ...
'GradientThreshold',1, ...
'LearnRateDropFactor',0.1,...
'MaxEpochs',maxEpochs, ...
'MiniBatchSize',miniBatchSize, ...
'Shuffle','every-epoch', ...
'Verbose',1,...
'Plots','training-progress');
% Train the neural network
tic;
net = trainNetwork(XTrain,YTrain,layers,options);
toc;
save('NN.mat','net');

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采纳的回答

Mahesh Taparia
Mahesh Taparia 2021-1-29
Hi
There is a requirement of sequenceFoldingLayer and sequenceUnfoldingLayer in the layer graph. For a sample layergraph, you can refer here. You can consider the below code for your case:
% DNN Layers
layers = [ ...
sequenceInputLayer(inputSize,'Name','sequence')
sequenceFoldingLayer('Name','fold')
convolution2dLayer(3,32,'Name','conv2')
reluLayer('Name','relu')
maxPooling2dLayer(2,'Name','maxpool')
sequenceUnfoldingLayer('Name','unfold')
flattenLayer('Name','flat')
lstmLayer(numHiddenUnits,'OutputMode','last','Name','lstm')
fullyConnectedLayer(numClasses,'Name','fc')
softmaxLayer('Name','sm')
classificationLayer('Name','class')];
lgraph = layerGraph(layers);
lgraph = connectLayers(lgraph,'fold/miniBatchSize','unfold/miniBatchSize');
analyzeNetwork(lgraph)
Hope it will help!

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