I want to build a neural network where the two first layers are feedforward and the last one is recurrent.
here is my code :
model = Sequential()
adam =OP.Adam(lr=0.001, beta_1=0.9, beta_2=0.999, epsilon=1e-08)
Exception: Input 0 is incompatible with layer simplernn_11: expected ndim=3, found ndim=2.
In Keras, you cannot put a Reccurrent layer after a Dense layer because the Dense layer gives output as (nb_samples, output_dim). However, a Recurrent layer expects input as (nb_samples, time_steps, input_dim). So, a Dense layer gives a 2-D output, but a Recurrent layer expects a 3-D input. However, you can do the reverse, i.e., put a Dense layer after a Recurrent layer.