财政预测收入神经网络模型运行出错

这段神经网络模型预测的代码改到了现在这个样子，运行还是过不去
C:\Users\Administrator\Anaconda3\envs\pythonProject\python.exe C:/Users/Administrator/PycharmProjects/pythonProject1/1.py
File "C:/Users/Administrator/PycharmProjects/pythonProject1/1.py", line 19
model.add(Activation('relu'))
^
SyntaxError: invalid syntax

Process finished with exit code 1
总是提示无效的语法。

目前的keras是2.4.3，tensorflow是2.3.0，怎么解决呢？

import pandas as pd
inputfile =r'C:\Users\Administrator\Desktop\777\data1_GM11.xls' #灰色预测后保存的路径
outputfile =r'C:\Users\Administrator\Desktop\777\revenue.xls' #神经网络预测后保存的结果
modelfile =r'C:\Users\Administrator\Desktop\777\1-net.model' #模型保存路径
data = pd.read_excel(inputfile) #读取数据
feature = ['x1', 'x2', 'x3', 'x4', 'x5', 'x7'] #特征所在列
data.index = range(1994,2016)
data_train = data.loc[range(1994,2014)].copy() #取2014年前的数据建模
data_mean = data_train.mean()
data_std = data_train.std()
data_train = (data_train - data_mean)/data_std #数据标准化
x_train = data_train[feature].values #特征数据
y_train = data_train['y'].values #标签数据
from keras.models import Sequential
from keras.layers.core import Dense, Activation
#from tensorflow.keras.models import Sequential
model = Sequential() #建立模型
model.add(Dense(input_dim = 6, output_dim = 12)
model.add(Activation('relu'))
model.add(Dense(input_dim = 12, output_dim = 1))
model.compile(loss='mean_squared_error', optimizer='adam') #编译模型
model.fit(x_train, y_train, nb_epoch = 10000, batch_size = 16) #训练模型，学习一万次
model.save_weights(modelfile) #保存模型参数
#预测，并还原结果。
x = ((data[feature] - data_mean[feature])/data_std[feature]).as_matrix()
data[u'y_pred'] = model.predict(x) * data_std['y'] + data_mean['y']
data.to_excel(outputfile)

import matplotlib.pyplot as plt #画出预测结果图
p = data[['y','y_pred']].plot(subplots = True, style=['b-o','r-*'])
plt.show()
```python

```

18行少右括号

已经解决了，18行少括号了。并且keras版本太高了，我把keras降低到2.0.8，就可以了