furkan_ahmed asked . 2021-05-26

Is it possible to implement a LSTM layer after a CNN layer?

layers = [ ...
    sequenceInputLayer(inputSize)    

      convolution2dLayer(3,8,'Padding','same')
      batchNormalizationLayer
      reluLayer 

      maxPooling2dLayer(2,'Stride',2)

      lstmLayer(numHiddenUnits,'OutputMode','last')

      fullyConnectedLayer(numClasses)
      softmaxLayer
      classificationLayer
      ];

Error:

Error using trainNetwork (line 154)
Invalid network.

Caused by:
    Network: Incompatible layer types. The network contains layer types not supported with recurrent layers.
    Detected recurrent layers:
        layer 6 (LSTM)
    Detected incompatible layers:
        layer 2 (Convolution)
        layer 3 (Batch Normalization)
        layer 5 (Max Pooling)
    Layer 2: Input size mismatch. Size of input to this layer is different from the expected input size.
    Inputs to this layer:
        from layer 1 (output size 500)

deep learning , matlab , simulink , programming