Deep learning. Need the explanation along with answer

Below is a keras code that creates a fully connected neural network architecture. How many parameters are there in the model (ignore the biases)? model = Sequential () model.add (Dense (2, input_shape =(2,1)) ) model.add (Activation ('relu')) model.add (Dense (2)) model.add (Activation ('relu')) model.add (Dense (1)) model.add (Activation ('sigmoid')) 6 10 12 8