CNN-LSTM architecture. (None, 150, 6, 3) in the input layer specifies that the CNN model can accept input data with variable batch sizes (None), where each sample has a length of 150 elements (fixed size input vector), a height of 6 rows (number of samples), and a width of 3 columns (number of channels). The Lambda layer is used to adjust the shape of the output from the CNN layer to input for the LSTM layer.

CNN-LSTM architecture. (None, 150, 6, 3) in the input layer specifies that the CNN model can accept input data with variable batch sizes (None), where each sample has a length of 150 elements (fixed size input vector), a height of 6 rows (number of samples), and a width of 3 columns (number of channels). The Lambda layer is used to adjust the shape of the output from the CNN layer to input for the LSTM layer.