Array inputs have incompatible channel dimensions.

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Ahmad
Ahmad 2023-2-19
回答： Govind KM 2024-10-17
im error using trainNetwork. i have no idea, im newbie here. im using matlab 2022a
layers = [ ...
sequenceInputLayer([n_samples,numFeatures])
convolution1dLayer(filterSize,numFilters,'Padding','same')
eluLayer
maxPooling1dLayer(3, 'Stride', 2)
flattenLayer
fullyConnectedLayer(numClasses)
softmaxLayer
classificationLayer];
miniBatchSize = 50;
options = trainingOptions("adam", ...
MiniBatchSize=miniBatchSize, ...
MaxEpochs=10, ...
L2Regularization=0.00005,...
Shuffle='every-epoch',...
ValidationFrequency=10,...
ValidationPatience=20,...% for early stop
SequencePaddingDirection="left", ...
ValidationData={XValidation,TValidation}, ...
Plots='none', ...% or "training-progress" , 'none'
Verbose=1);
net = trainNetwork(XTrain,TTrain,layers,options);

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回答（1 个）

Govind KM
Govind KM 2024-10-17
Hi Ahmad,
A common reason for the mentioned error is a mismatch between the dimensions of input data and the expected input dimensions specified by the network. Here are potential steps to debug the issue:
  • Verify that the inputs to the trainnetwork function are passed in the required format, i.e format for sequences and format for responses.
  • Ensure that the input data XTrain matches the dimensions specified in sequenceInputLayer, i.e. n_samples-by-numFeatures.
  • Ensure that the filterSize and numFilters are appropriate for the data.
  • Ensure that the sequencePaddingDirection has been set correctly.
A related MATLAB Answers post about the same error mentions that the issue is fixed in R2024a:
https://www.mathworks.com/matlabcentral/answers/2118461-c-rnn-regression-error-array-inputs-have-incompatible-channel-dimensions
If the issue still persists, providing the data used would help in debugging the issue further.
Hope this is helpful!

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