import tensorflow as tf

		c_init = np.zeros((1, lstm_cell.state_size.c), np.float32)
		h_init = np.zeros((1, lstm_cell.state_size.h), np.float32)
		state_init = [c_init, h_init]
		c_in = tf.placeholder(tf.float32, [1, lstm_cell.state_size.c])
		h_in = tf.placeholder(tf.float32, [1, lstm_cell.state_size.h])
		state_in = (c_in, h_in)
		rnn_in = tf.expand_dims(self.h3, [0])
		step_size = tf.shape(inputs)[:1]
		state_in = tf.nn.rnn_cell.LSTMStateTuple(c_in, h_in)
		lstm_outputs, lstm_state = tf.nn.dynamic_rnn(
		lstm_cell, rnn_in, initial_state=state_in, sequence_length=step_size,
		time_major=False)
