Any way to simplify the code of PTB tutorial when state_is_tuple ?

[zsdonghao]

When state_is_tuple, we need to feed the cell and hidden state seperately, the code will look like below. Is there any simple way to simplify the code?

# reset all states at the begining of every epoch
state1 = tl.layers.initialize_rnn_state(lstm1.initial_state)
state2 = tl.layers.initialize_rnn_state(lstm2.initial_state)
for step, (x, y) in enumerate(tl.iterate.ptb_iterator(train_data,
                                                    batch_size, num_steps)):
            feed_dict = {input_data: x, targets: y,
                        lstm1.initial_state.c: state1[0],
                        lstm1.initial_state.h: state1[1],
                        lstm2.initial_state.c: state2[0],
                        lstm2.initial_state.h: state2[1],
                        }
            # For training, enable dropout
            feed_dict.update( network.all_drop )
            _cost, state1_c, state1_h, state2_c, state2_h, _ = \
                                    sess.run([cost,
                                            lstm1.final_state.c,
                                            lstm1.final_state.h,
                                            lstm2.final_state.c,
                                            lstm2.final_state.h,
                                            train_op],
                                            feed_dict=feed_dict
                                            )
            state1 = (state1_c, state1_h)
            state2 = (state2_c, state2_h)

[zsdonghao]

Done