two GRU layers?

[chengzhanzhan]

Hi,

I have read your GRU code: https://github.com/dennybritz/rnn-tutorial-gru-lstm/blob/master/gru_theano.py, and there are two GRU layers added.
`
# GRU Layer 1
z_t1 = T.nnet.hard_sigmoid(U[0].dot(x_e) + W[0].dot(s_t1_prev) + b[0])
r_t1 = T.nnet.hard_sigmoid(U[1].dot(x_e) + W[1].dot(s_t1_prev) + b[1])
c_t1 = T.tanh(U[2].dot(x_e) + W[2].dot(s_t1_prev * r_t1) + b[2])
s_t1 = (T.ones_like(z_t1) - z_t1) * c_t1 + z_t1 * s_t1_prev

        # GRU Layer 2
        z_t2 = T.nnet.hard_sigmoid(U[3].dot(s_t1) + W[3].dot(s_t2_prev) + b[3])
        r_t2 = T.nnet.hard_sigmoid(U[4].dot(s_t1) + W[4].dot(s_t2_prev) + b[4])
        c_t2 = T.tanh(U[5].dot(s_t1) + W[5].dot(s_t2_prev * r_t2) + b[5])
        s_t2 = (T.ones_like(z_t2) - z_t2) * c_t2 + z_t2 * s_t2_prev

        # Final output calculation
        # Theano's softmax returns a matrix with one row, we only need the row
        o_t = T.nnet.softmax(V.dot(s_t2) + c)[0]

`
Can I set 'o_t = T.nnet.softmax(V.dot(s_t1) + c)[0]'?