Is this telling the model that there are two dimensions (i.e. it’s a matrix) but we don’t yet know the size of that particular dimension? If so, how can the model be compiled? Doesn’t the size of each dimension affect the number of nodes in middle layers?
In keras, a
None dimension means that it can be any scalar number, so that you use this model to infer on an arbitrarily long input. This dimension does not affect the size of the network, it just denotes that you are free to select the length (number of samples) of your input during testing.