Number of parameters for Keras SimpleRNN

Question

I have a simpleRNN like:

model.add(SimpleRNN(10, input_shape=(3, 1)))
model.add(Dense(1, activation=\"linear\"))
         


        

Answer 1

I visualize the SimpleRNN you add, I think the figure can explain a lot.

SimpleRNN layer, I'm a newbie here, can't post images directly, so you need to click the link.

From the unrolled version of SimpleRNN layer，it can be seen as a dense layer. And the previous layer is a concatenation of input and the current layer(previous step) itself.

So the number of parameters of SimpleRNN can be computed as a dense layer:

num_para = units_pre * units + num_bias

where:

units_pre is the sum of input neurons（1 in your settings） and units(see below),

units is the number of neurons（10 in your settings） in the current layer,

num_bias is the number of bias term in the current layer, which is the same as the units.

Plugging in your settings, we achieve the num_para = (1 + 10) * 10 + 10 = 120.