深度学习层的构建能帮我加个注释吗

# 定义网络结构
def train_bilstm_att(n_symbols, embedding_weights, x_train, y_train, ATT_SIZE):
    #创建序列模型
    model = Sequential()
    #添加嵌入层
    model.add(Embedding(output_dim=vocab_dim,
                        input_dim=n_symbols,
                        weights=[embedding_weights],
                        input_length=maxlen))
    # 1
    model.add(Bidirectional(LSTM(output_dim=30, dropout=0.5, return_sequences=True)))
    #2
    model.add(AttentionLayer(attention_size=ATT_SIZE))
    #3
    model.add(Dense(2, activation='softmax')) 
    #4
    model.compile(loss='categorical_crossentropy',optimizer='adam', metrics=['accuracy'])
    #训练模型
    model.fit(x_train, y_train, batch_size=batch_size, epochs=n_epoch,verbose=1)

能帮忙加下1234的注释吗，最好详细一点，谢谢