Gate weights order for LSTM layers in Tensorflow

Question

I have a Keras model that includes some LSTM layers. I know that I can get the weights of the LSTM layer through the get_weights() method, and the result is a list made of three elements: kernel, recurrent kernel and bias.

As the documentation state, each element includes the weights for the 4 gates in the LSTM layer. However, it does not state which is the order in which they are stored. For instance, if LSTM layer has N units, the bias vector will be made of 4*N elements. Which of those elements correspond to the 1st/2nd/3rd/4th gate?

Answer 1

The order is i, f, c, o which stands for input gate, forget gate, cell gate and output gate respectively. You can get the information from LSTMCell implementation here.

lstm = LSTM(100)
lstm(np.zeros((64,10,5)))
kernel = lstm.weights[0]
w_i,w_f,w_c,w_o = tf.split(kernel,4,axis=1)

print(*(w.shape for w in (w_i,w_f,w_c,w_o)))#all are (5, 100)