输入文件：
train_log_sequence.txt 格式： timestamp + tag
输出文件:
template_to_int.txt
weights/weights-improvement-**-**-bigger.hdf5 有多个文件，选择一个loss值最小的文件，其他可以删掉
输入文件:
template_to_int.txt 是训练文件生成的
test_log_sequence.txt 格式： timestamp + tag
labels.txt 用于评价准确率
weights/weights-improvement-**-**-bigger.hdf5 loss值最小的文件
输出说明：
例如：anomaly detection result:
next tag is not in top1 candidates:
# of anomalous/total logs: 963/1990
Precision: 0.131880, Recall: 0.900709, F1_score: 0.230072
# of anomalous/total windows: 349/5096
Precision: 0.108883, Recall: 0.826087, F1_score: 0.192405
next tag is not in top2 candidates:
# of anomalous/total logs: 639/1990
Precision: 0.184664, Recall: 0.836879, F1_score: 0.302564
# of anomalous/total windows: 285/5096
Precision: 0.122807, Recall: 0.760870, F1_score: 0.211480
next tag is not in top3 candidates:
# of anomalous/total logs: 387/1990
Precision: 0.108527, Recall: 0.297872, F1_score: 0.159091
# of anomalous/total windows: 229/5096
Precision: 0.113537, Recall: 0.565217, F1_score: 0.189091
top1，top2指的是当下一个tag不是预测概率最大的topn时，认为该点为异常。
logs和windows分别表示的是日志级和窗口级的异常。