LSTM GRU tensorflow代码 和 原理图中的箭头 的对应关系

上图为LSTMcell，
向上指的箭头h_t是output，
向右指的箭头h_t和C_t是state，

对于上图的GRU
output和state是同一个信息

import tensorflow as tffrom tensorflow.contrib import rnnx = tf.constant([[1]], dtype = tf.float32)lstm_cell = rnn.BasicLSTMCell(2)gru_cell = rnn.GRUCell(2)state0_lstm = lstm_cell.zero_state(1,dtype=tf.float32)output,state = lstm_cell(x,state0_lstm)state0_gru = gru_cell.zero_state(1,dtype=tf.float32)output2,state2 = gru_cell(x,state0_gru)init = tf.global_variables_initializer()with tf.Session() as sess:    sess.run(init)    print(sess.run(output))    print(sess.run(state))    print(sess.run(output2))    print(sess.run(state2))

结果：
[[ 0.05328973 -0.07351915]]
LSTMStateTuple(c=array([[ 0.11276773, -0.12946127]], dtype=float32), h=array([[ 0.05328973, -0.07351915]], dtype=float32))

[[ 0.30531788 -0.00426328]]
[[ 0.30531788 -0.00426328]]