用matlab写一段CNN-LSTM-Attention模型的代码

以下是一个简单的CNN-LSTM-Attention模型的matlab代码：

% 定义输入维度
inputSize = [28 28 1];

% 定义CNN层
layers = [
    imageInputLayer(inputSize)
    convolution2dLayer(3,8,'Padding','same')
    batchNormalizationLayer
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
    convolution2dLayer(3,16,'Padding','same')
    batchNormalizationLayer
    reluLayer
    maxPooling2dLayer(2,'Stride',2)
];

% 定义LSTM层
numHiddenUnits = 64;
lstmLayer = lstmLayer(numHiddenUnits,'OutputMode','last');

% 定义Attention层
attentionLayer = attentionLayer(numHiddenUnits);

% 定义输出层
outputLayer = fullyConnectedLayer(10);
finalLayers = [
    lstmLayer
    attentionLayer
    outputLayer
    softmaxLayer
    classificationLayer
];

% 定义训练选项
options = trainingOptions('adam', ...
    'MaxEpochs',20, ...
    'InitialLearnRate',1e-3, ...
    'MiniBatchSize',128, ...
    'ValidationData',imdsValidation, ...
    'ValidationFrequency',30, ...
    'Verbose',false, ...
    'Plots','training-progress');

% 训练模型
net = trainNetwork(imdsTrain,layers,finalLayers,options);

请注意，这只是一个简单的示例，您需要根据您的数据和任务进行调整。此外，您需要正确定义并实现CNN层，LSTM层和Attention层。