如何从tensorflow中的双向rnn获取所有状态

import tensorflow as tf

# 假设输入数据是一个形状为[batch_size, sequence_length, input_dim]的三维张量
input_data = tf.placeholder(tf.float32, [None, sequence_length, input_dim])

# 定义双向RNN的参数
num_units = 128  # RNN单元的数量
cell_fw = tf.nn.rnn_cell.BasicRNNCell(num_units)
cell_bw = tf.nn.rnn_cell.BasicRNNCell(num_units)

# 使用tf.nn.bidirectional_dynamic_rnn函数创建双向RNN
outputs, states = tf.nn.bidirectional_dynamic_rnn(cell_fw, cell_bw, input_data, dtype=tf.float32)

# 获取正向RNN的所有状态
states_fw = states[0]

# 获取反向RNN的所有状态
states_bw = states[1]

import tensorflow as tf

# 定义输入数据和参数
input_data = tf.placeholder(tf.float32, [None, sequence_length, input_dim])
num_units = 128
cell_fw = tf.nn.rnn_cell.BasicRNNCell(num_units)
cell_bw = tf.nn.rnn_cell.BasicRNNCell(num_units)

# 创建双向RNN的网络结构
outputs, states = tf.nn.bidirectional_dynamic_rnn(cell_fw, cell_bw, input_data, dtype=tf.float32)

# 获取所有状态
states_fw = states[0]
states_bw = states[1]