How to calculate the number of parameters of an LSTM network?

Question

Is there a way to calculate the total number of parameters in a LSTM network.

I have found a example but I\'m unsure of how correct this is or If I have understood i

Answer 1

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num_params = [(num_units + input_dim + 1) * num_units] * 4

num_units + input_dim: concat [h(t-1), x(t)]

+ 1: bias

* 4: there are 4 neural network layers (yellow box) {W_forget, W_input, W_output, W_cell}

model.add(LSTM(units=256, input_dim=4096, input_length=16))

[(256 + 4096 + 1) * 256] * 4 = 4457472

PS: num_units = num_hidden_units = output_dims