机器翻译怎么创建

import tensorflow as tf
from tensorflow.keras.models import Model
from tensorflow.keras.layers import Input, LSTM, Dense

# 假设已准备好源语言和目标语言的嵌入矩阵及词汇表大小
latent_dim = 256
num_encoder_tokens = 10000
num_decoder_tokens = 10000

# 编码器
encoder_inputs = Input(shape=(None, num_encoder_tokens))
encoder = LSTM(latent_dim, return_state=True)
encoder_outputs, state_h, state_c = encoder(encoder_inputs)
encoder_states = [state_h, state_c]

# 解码器
decoder_inputs = Input(shape=(None, num_decoder_tokens))
decoder_lstm = LSTM(latent_dim, return_sequences=True, return_state=True)
decoder_outputs, _, _ = decoder_lstm(decoder_inputs, initial_state=encoder_states)
decoder_dense = Dense(num_decoder_tokens, activation='softmax')
decoder_outputs = decoder_dense(decoder_outputs)

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

# 编译模型
model.compile(optimizer='rmsprop', loss='categorical_crossentropy')

# 训练模型（此处省略数据准备部分）
model.fit([encoder_input_data, decoder_input_data], decoder_target_data,
          batch_size=64,
          epochs=100,
          validation_split=0.2)