如何在tensorflow2.0中导入'tf.contrib.seq2seq.dynamic_decoder‘？

import tensorflow as tf
from tensorflow.keras.layers import LSTM, Dense, Attention

# 定义编码器
encoder_inputs = tf.keras.Input(shape=(None, input_dim))
encoder = LSTM(units=hidden_units, return_state=True)
encoder_outputs, state_h, state_c = encoder(encoder_inputs)
encoder_states = [state_h, state_c]

# 定义解码器
decoder_inputs = tf.keras.Input(shape=(None, output_dim))
decoder = LSTM(units=hidden_units, return_sequences=True, return_state=True)
decoder_outputs, _, _ = decoder(decoder_inputs, initial_state=encoder_states)
attention = Attention()
context_vector, attention_weights = attention([decoder_outputs, encoder_outputs])
decoder_outputs = Dense(output_dim, activation='softmax')(context_vector)

# 构建模型
model = tf.keras.Model([encoder_inputs, decoder_inputs], decoder_outputs)