?实验环境 
cpu-version
1. Precsion,Recall,f1_scorem
precision of mbnn is 0.8756 recall of mbnn is 0.8670 f1_score of mbnn is 0.8689?
precision of cnn is 0.8952 recall of cnn is 0.8943 f1_score of cnn is 0.8946
precision of mbnnst is 0.8835 recall of mbnnst is 0.8847 f1_score of mbnnst is 0.8835?
2.混淆矩阵
| CNN | MBNN | MBNNST |
 |  |  |
3.各类别准确率
Precission of each category when using CNN: 0 : 0.8748 1 : 0.8121 2 : 0.9960
Precission of each category when using MBNN: 0 : 0.8856 1 : 0.7306 2 : 0.9848
Precission of each category when using MBNNST: 0 : 0.8661 1 : 0.7888 2 : 0.9992
精度都差不多的情况下，MBNN可以减小推理时间的开销
4.效率验证
Average Time of MBNN using cpu for block is 0.4906
Max Time of MBNN using cpu for block is 0.6025
Min Time of MBNN using cpu for block is 0.5275
Average Time of CNN using cpu for block is 0.8985
Max Time of CNN using cpu for block is 1.0449
Min Time of CNN using cpu for block is 0.9649
Average Time of MBNN using cpu for block75 is 0.8868
Max Time of MBNN using cpu for block75 is 1.0955
Min Time of MBNN using cpu for block75 is 0.9644?
Average Time of CNN using cpu for block75 is 0.9319
Max Time of CNN using cpu for block75 is 1.1225
Min Time of CNN using cpu for block75 is 0.9826
Average Time of MBNN using cpu for common is 0.8949
Max Time of MBNN using cpu for common is 1.0635
Min Time of MBNN using cpu for common is 0.9661?
Average Time of CNN using cpu for common is 0.9518
Max Time of CNN using cpu for common is 1.1473
Min Time of CNN using cpu for common is 0.9678
分析一下，就模型MBNN而言，确实block的情况推理时间走的简单分支，相较common、block0.75的情况，就推理时间而言，自然就减小了许多
如何解释第二分支下的推理时间减少呢？与天放交流一下下,交流完毕，完全有可能是误差，因为这个时间差别不大
矩形代表平均值，上面这个工字型代表最大值与最小值的区间
gpu-version
Average Time of MBNN using cuda:0 for block is 0.0008
Max Time of MBNN using cuda:0 for block is 0.0012
Min Time of MBNN using cuda:0 for block is 0.0007
?
Average Time of MBNN using cuda:0 for block75 is 0.0010
Max Time of MBNN using cuda:0 for block75 is 0.0013
Min Time of MBNN using cuda:0 for block75 is 0.0011
?
Average Time of MBNN using cuda:0 for common is 0.0013
Max Time of MBNN using cuda:0 for common is 0.0021
Min Time of MBNN using cuda:0 for common is 0.0011
实验主要就做
不同模型推理速度的对比
模型精度的提升/混淆矩阵
不同平台下的推理速度对比
代码存在的问题没有添加Other逻辑