Hi3559AV100 NNIE开发（4）mobilefacenet.cfg参数配置挖坑解决与SVP_NNIE_Cnn实现分析
2024-08-29 23:19:07
前面随笔给出了NNIE开发的基本知识，下面几篇随笔将着重于Mobilefacenet NNIE开发，实现mobilefacenet.wk的chip版本，并在Hi3559AV100上实现mobilefacenet网络功能，外接USB摄像头通过MPP平台输出至VO HDMI显示结果。下文是Hi3559AV100 NNIE开发（4）mobilefacenet.cfg参数配置挖坑解决与SVP_NNIE_Cnn实现分析，目前项目需要对mobilefacenet网络进行.wk的开发，下面给出在.wk生成过程中遇到的坑与解决方式，并给出SVP_NNIE_Cnn整体实现的各个step分析，为后面在板载上实现mobilefacenet网络打下基础。
1、mobilefacenet.cfg参数配置挖坑解决
CNN_convert_bin_and_print_featuremap.py和Get Caffe Output这里的预处理方式都是先乘以【data_scale】，再减均值【mean_file】，而在量化生成 .mk 文件时却是先减均值再乘以scale的。
给出预处理这一个环节对输入数据data的处理方式：
1 data = inputs
2 if norm_type == '4' or norm_type == '5':
3 data = data * float(data_scale)
data是uint8类型的array，是先乘以了【data_scale】的，也就是说和NNIE 生成wk中的操作顺序是不一致的，对于mobilefacenet.cfg网络输入数据预处理方法时，当norm_type = 5时，输入数据减通道均值后再乘以 data_scale，如下所示：
所在在实际操作中，需要对均值文件进行处理，转换方式如下：
(data - 128.0) * 0.0078125 <==> data * 0.0078125 - 1
因此这里需要做的修改就是需要将【mean_file】pixel_mean_compare.txt修设置为1.0：
最终生成mobilefacenet.wk，结果如下所示，具体的测试需要下一步进行。
1 begin parameter compressing....
2
3 end parameter compressing
4
5 begin compress index generating....
6
7 end compress index generating
8
9 begin binary code generating....
10
11 .........................................................................................................................
12 ....................................................................end binary code generating
13
14 begin quant files writing....
15
16 end quant files writing
17
18 .
19 ===============D:\Hi3559_NNIE\3559\mobileface\mobileface.cfg Successfully!===============
20
21 End [RuyiStudio Wk NNIE Mapper] [D:\Hi3559_NNIE\3559\mobileface\mobileface.cfg] mobileface
2、SVP_NNIE_Cnn实现分析
下面给出SAMPLE_SVP_NNIE_Cnn函数的执行过程，主要分为下面八个步骤：
1 HI_CHAR *pcSrcFile = "./data/nnie_image/y/0_28x28.y";
2 HI_CHAR *pcModelName = "./data/nnie_model/classification/inst_mnist_cycle.wk";
3
4
5 /*Set configuration parameter */
6 stNnieCfg.pszPic= pcSrcFile;
7 stNnieCfg.u32MaxInputNum = u32PicNum; //max input image num in each batch
8 stNnieCfg.u32MaxRoiNum = 0;
9 stNnieCfg.aenNnieCoreId[0] = SVP_NNIE_ID_0;//set NNIE core
10 s_stCnnSoftwareParam.u32TopN = 5;
11
12
13
14 /*Sys init ---step1*/
15 SAMPLE_COMM_SVP_CheckSysInit();
16
17 /*CNN Load model ------step2*/
18 s32Ret = SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel);
19
20
21 /*CNN parameter initialization -------step3*/
22 /*Cnn software parameters are set in SAMPLE_SVP_NNIE_Cnn_SoftwareParaInit,
23 if user has changed net struct, please make sure the parameter settings in
24 SAMPLE_SVP_NNIE_Cnn_SoftwareParaInit function are correct*/
25 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
26 s32Ret = SAMPLE_SVP_NNIE_Cnn_ParamInit(&stNnieCfg,&s_stCnnNnieParam,&s_stCnnSoftwareParam);
27
28
29 /*record tskBuf -------step4*/
30 s32Ret = HI_MPI_SVP_NNIE_AddTskBuf(&(s_stCnnNnieParam.astForwardCtrl[0].stTskBuf));
31
32
33 /*Fill src data -------step5*/
34 SAMPLE_SVP_TRACE_INFO("Cnn start!\n");
35 stInputDataIdx.u32SegIdx = 0;
36 stInputDataIdx.u32NodeIdx = 0;
37 s32Ret = SAMPLE_SVP_NNIE_FillSrcData(&stNnieCfg,&s_stCnnNnieParam,&stInputDataIdx);
38
39
40 /*NNIE process(process the 0-th segment) -------step6*/
41 stProcSegIdx.u32SegIdx = 0;
42 s32Ret = SAMPLE_SVP_NNIE_Forward(&s_stCnnNnieParam,&stInputDataIdx,&stProcSegIdx,HI_TRUE);
43
44
45
46 /*Software process --------step7*/
47 /*if user has changed net struct, please make sure SAMPLE_SVP_NNIE_Cnn_GetTopN
48 function's input datas are correct*/
49 s32Ret = SAMPLE_SVP_NNIE_Cnn_GetTopN(&s_stCnnNnieParam,&s_stCnnSoftwareParam);
50
51
52
53 /*Print result --------step8*/
54 SAMPLE_SVP_TRACE_INFO("Cnn result:\n");
55 s32Ret = SAMPLE_SVP_NNIE_Cnn_PrintResult(&(s_stCnnSoftwareParam.stGetTopN),
56 s_stCnnSoftwareParam.u32TopN);
（1）step1为SAMPLE_COMM_SVP_CheckSysInit()，完成的是MPP系统的初始化，主要实现的是Sys_Init和VB_Init，实现MPP内存池的配置，具体实现如下：
1 HI_VOID SAMPLE_COMM_SVP_CheckSysInit(HI_VOID)
2 {
3 ..............
4 SAMPLE_COMM_SVP_SysInit()
5 {
6 //省略了部分过程，列出实现关键函数
7 HI_MPI_SYS_Exit();
8 HI_MPI_VB_Exit();
9
10 memset(&struVbConf,0,sizeof(VB_CONFIG_S));
11
12 struVbConf.u32MaxPoolCnt = 2;
13 struVbConf.astCommPool[1].u64BlkSize = 768*576*2;
14 struVbConf.astCommPool[1].u32BlkCnt = 1;
15
16 s32Ret = HI_MPI_VB_SetConfig((const VB_CONFIG_S *)&struVbConf); //设置MPP视频缓存池属性
17
18
19 s32Ret = HI_MPI_VB_Init(); //初始化MPP缓存池
20
21
22 s32Ret = HI_MPI_SYS_Init(); //初始化MPP系统
23
24 }
25
26 .............
27 }
（2）step2为SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel)从用户事先加载到 buf 中的模型中解析出网络模型，其函数实现较为复杂，具体的函数参数解析和函数运行过程已经在前面随笔给出了，需要的话，可以参考随笔：
Hi3559AV100 NNIE开发（1）-RFCN(.wk)LoadModel函数参数解析 （https://www.cnblogs.com/iFrank/p/14500648.html）
Hi3559AV100 NNIE开发（2）-RFCN(.wk)LoadModel及NNIE Init函数运行过程分析 （https://www.cnblogs.com/iFrank/p/14503482.html）
（3）step3为SAMPLE_SVP_NNIE_Cnn_ParamInit，首先给出调用与定义，便于分析：
1 /*Set configuration parameter*/
2 stNnieCfg.pszPic= pcSrcFile;
3 stNnieCfg.u32MaxInputNum = u32PicNum; //max input image num in each batch
4 stNnieCfg.u32MaxRoiNum = 0;
5 stNnieCfg.aenNnieCoreId[0] = SVP_NNIE_ID_0;//set NNIE core
6
7 s_stCnnSoftwareParam.u32TopN = 5;
8
9 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
10 s32Ret = SAMPLE_SVP_NNIE_Cnn_ParamInit(&stNnieCfg,
11 &s_stCnnNnieParam,
12 &s_stCnnSoftwareParam);
13
14
15
16 static HI_S32 SAMPLE_SVP_NNIE_Cnn_ParamInit(SAMPLE_SVP_NNIE_CFG_S* pstNnieCfg,
17 SAMPLE_SVP_NNIE_PARAM_S *pstCnnPara,
18 SAMPLE_SVP_NNIE_CNN_SOFTWARE_PARAM_S* pstCnnSoftWarePara)
19 {
20 ........
21
22 /*init hardware para*/
23 s32Ret = SAMPLE_COMM_SVP_NNIE_ParamInit(pstNnieCfg,
24 pstCnnPara);
25
26
27 /*init software para*/
28 if(pstCnnSoftWarePara!=NULL)
29 {
30 s32Ret = SAMPLE_SVP_NNIE_Cnn_SoftwareParaInit(pstNnieCfg,
31 pstCnnPara,
32 pstCnnSoftWarePara);
33 "Error(%#x),SAMPLE_SVP_NNIE_Cnn_SoftwareParaInit failed!\n",s32Ret);
34 }
35
36 ........
37 }
其中SAMPLE_COMM_SVP_NNIE_ParamInit函数及参数分析可见之前随笔:
Hi3559AV100 NNIE开发（2）-RFCN(.wk)LoadModel及NNIE Init函数运行过程分析 （https://www.cnblogs.com/iFrank/p/14503482.html），之前的随笔介绍的很详细，这里就不在赘述了。
对SAMPLE_SVP_NNIE_Cnn_SoftwareParaInit函数，首先给出定义：
1 static HI_S32 SAMPLE_SVP_NNIE_Cnn_SoftwareParaInit(
2 SAMPLE_SVP_NNIE_CFG_S* pstNnieCfg,
3 SAMPLE_SVP_NNIE_PARAM_S *pstCnnPara,
SAMPLE_SVP_NNIE_CNN_SOFTWARE_PARAM_S* pstCnnSoftWarePara)
4 {
5 HI_U32 u32GetTopNMemSize = 0;
6 HI_U32 u32GetTopNAssistBufSize = 0;
7 HI_U32 u32GetTopNPerFrameSize = 0;
8 HI_U32 u32TotalSize = 0;
9 HI_U32 u32ClassNum = pstCnnPara->pstModel->astSeg[0].astDstNode[0].unShape.stWhc.u32Width;
10 HI_U64 u64PhyAddr = 0;
11 HI_U8* pu8VirAddr = NULL;
12 HI_S32 s32Ret = HI_SUCCESS;
13
14 /*get mem size*/
15 u32GetTopNPerFrameSize = pstCnnSoftWarePara->u32TopN*sizeof(SAMPLE_SVP_NNIE_CNN_GETTOPN_UNIT_S);
16 u32GetTopNMemSize = SAMPLE_SVP_NNIE_ALIGN16(u32GetTopNPerFrameSize)*pstNnieCfg->u32MaxInputNum;
17 u32GetTopNAssistBufSize = u32ClassNum*sizeof(SAMPLE_SVP_NNIE_CNN_GETTOPN_UNIT_S);
18 u32TotalSize = u32GetTopNMemSize+u32GetTopNAssistBufSize;
19
20 /*malloc mem*/
21 s32Ret = SAMPLE_COMM_SVP_MallocMem("SAMPLE_CNN_INIT",NULL,(HI_U64*)&u64PhyAddr,
22 (void**)&pu8VirAddr,u32TotalSize);
23 SAMPLE_SVP_CHECK_EXPR_RET(HI_SUCCESS != s32Ret,s32Ret,SAMPLE_SVP_ERR_LEVEL_ERROR,
24 "Error,Malloc memory failed!\n");
25 memset(pu8VirAddr, 0, u32TotalSize);
26
27 /*init GetTopn */
28 pstCnnSoftWarePara->stGetTopN.u32Num= pstNnieCfg->u32MaxInputNum;
29 pstCnnSoftWarePara->stGetTopN.unShape.stWhc.u32Chn = 1;
30 pstCnnSoftWarePara->stGetTopN.unShape.stWhc.u32Height = 1;
31 pstCnnSoftWarePara->stGetTopN.unShape.stWhc.u32Width = u32GetTopNPerFrameSize/sizeof(HI_U32);
32 pstCnnSoftWarePara->stGetTopN.u32Stride = SAMPLE_SVP_NNIE_ALIGN16(u32GetTopNPerFrameSize);
33 pstCnnSoftWarePara->stGetTopN.u64PhyAddr = u64PhyAddr;
34 pstCnnSoftWarePara->stGetTopN.u64VirAddr = (HI_U64)pu8VirAddr;
35
36 /*init AssistBuf */
37 pstCnnSoftWarePara->stAssistBuf.u32Size = u32GetTopNAssistBufSize;
38 pstCnnSoftWarePara->stAssistBuf.u64PhyAddr = u64PhyAddr+u32GetTopNMemSize;
39 pstCnnSoftWarePara->stAssistBuf.u64VirAddr = (HI_U64)pu8VirAddr+u32GetTopNMemSize;
40
41 return s32Ret;
42 }
函数体内最主要功能是实现s_stCnnSoftwareParam参数的赋值，包含大量赋值语句，其中s_stCnnSoftwareParam结构体各个元素赋值的意义等需要的时候再进行研讨，此外函数还实现在用户态分配 MMZ 内存。通过对两个函数的分析，step3 SAMPLE_SVP_NNIE_Cnn_ParamInit()完成。
（4）step4为HI_MPI_SVP_NNIE_AddTskBuf，为了记录 TskBuf 地址信息，其作用和注意事项：
①记录 TskBuf 地址信息，用于减少内核态内存映射次数，提升效率；
②TskBuf 地址信息的记录是通过链表进行管理，链表长度默认值为 32，链表长度可通过模块参数 nnie_max_tskbuf_num 进行配；
③若没调用 HI_MPI_SVP_NNIE_AddTskBuf 预先把 TskBuf 地址信息记录到系统，那么之后调用 Forward/ForwardWithBbox 每次都会 Map/Unmap 操作 TskBuf 内核态虚拟地址，效率会比较低。
给出函数调用和定义:
1 /*SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel);*/
2 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
3
4 s32Ret = HI_MPI_SVP_NNIE_AddTskBuf(&(s_stCnnNnieParam.astForwardCtrl[0].stTskBuf));
5
6
7 //定义
8 HI_S32 HI_MPI_SVP_NNIE_AddTskBuf(const SVP_MEM_INFO_S* pstTskBuf);
（5）step5为SAMPLE_SVP_NNIE_FillSrcData，实现src数据的填充，此函数十分关键，对所给图像数据：./data/nnie_image/y/0_28x28.y进行处理，为了更好的分析数据处理函数，首先给出函数调用信息：
1 stNnieCfg.pszPic= pcSrcFile;
2 stNnieCfg.u32MaxInputNum = u32PicNum; //max input image num in each batch
3 stNnieCfg.u32MaxRoiNum = 0;
4 stNnieCfg.aenNnieCoreId[0] = SVP_NNIE_ID_0;//set NNIE core
5
6 /*SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel);*/
7 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
8
9 stInputDataIdx.u32SegIdx = 0;
10 stInputDataIdx.u32NodeIdx = 0;
11 s32Ret = SAMPLE_SVP_NNIE_FillSrcData(&stNnieCfg,
&s_stCnnNnieParam,
&stInputDataIdx);
为了更加清楚函数功能，先给出函数定义，方便后面分析（忽略一些次要信息）：
1 static HI_S32 SAMPLE_SVP_NNIE_FillSrcData(SAMPLE_SVP_NNIE_CFG_S* pstNnieCfg,
2 SAMPLE_SVP_NNIE_PARAM_S *pstNnieParam,
3 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S* pstInputDataIdx)
总的来说，函数实现以下功能：
①open file fopen(pstNnieCfg->pszPic,"rb");
1 //定义文件名
2 HI_CHAR *pcSrcFile = "./data/nnie_image/y/0_28x28.y";
3
4 stNnieCfg.pszPic= pcSrcFile;
5
6 //函数定义
7 HI_S32 SAMPLE_SVP_NNIE_FillSrcData(SAMPLE_SVP_NNIE_CFG_S* pstNnieCfg,
8 SAMPLE_SVP_NNIE_PARAM_S *pstNnieParam,
9 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S* pstInputDataIdx)
10 //函数调用
11 SAMPLE_SVP_NNIE_FillSrcData(&stNnieCfg,
12 &s_stCnnNnieParam,
13 &stInputDataIdx);
14
15 fp = fopen(pstNnieCfg->pszPic,"rb");
②为后面fread读取数据量确定u32VarSize大小：
1 /*get data size s32Ret = fread(pu8PicAddr,u32Dim*u32VarSize,1,fp);*/
2 if(SVP_BLOB_TYPE_U8 <= pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].enType &&
3 SVP_BLOB_TYPE_YVU422SP >= pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].enType)
4 {
5 u32VarSize = sizeof(HI_U8);
6 }
7 else
8 {
9 u32VarSize = sizeof(HI_U32);
10 }
③随即通过pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].enType参数（参数找定义，应该是与输入模型.wk的模型参数有关，后面可以直接通过printf进行打印输出，看结果是啥）进行if-lese分支选择，之后通过fread对fp文件指针读取数据，确定数据内存地址，并刷新 cache 里的内容到内存并且使 cache 里的内容无效，最后fclose(fp)。
先给出enType参数类型：
代码实现：
1 /*fill src data*/
2 if(SVP_BLOB_TYPE_SEQ_S32 == pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].enType)
3 {
4 u32Dim = pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].unShape.stSeq.u32Dim;
5 u32Stride = pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Stride;
6 pu32StepAddr = (HI_U32*)(pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].unShape.stSeq.u64VirAddrStep);
7 pu8PicAddr = (HI_U8*)(pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u64VirAddr);
8 for(n = 0; n < pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Num; n++)
9 {
10 for(i = 0;i < *(pu32StepAddr+n); i++)
11 {
12 s32Ret = fread(pu8PicAddr,u32Dim*u32VarSize,1,fp);
13 SAMPLE_SVP_CHECK_EXPR_GOTO(1 != s32Ret,FAIL,SAMPLE_SVP_ERR_LEVEL_ERROR,"Error,Read image file failed!\n");
14 pu8PicAddr += u32Stride;
15 }
16 u32TotalStepNum += *(pu32StepAddr+n);
17 }
18 SAMPLE_COMM_SVP_FlushCache(pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u64PhyAddr,
19 (HI_VOID *) pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u64VirAddr,
20 u32TotalStepNum*u32Stride);
21 }
22 else
23 {
24 u32Height = pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].unShape.stWhc.u32Height;
25 u32Width = pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].unShape.stWhc.u32Width;
26 u32Chn = pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].unShape.stWhc.u32Chn;
27 u32Stride = pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Stride;
28 pu8PicAddr = (HI_U8*)(pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u64VirAddr);
29 if(SVP_BLOB_TYPE_YVU420SP== pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].enType)
30 {
31 for(n = 0; n < pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Num; n++)
32 {
33 for(i = 0; i < u32Chn*u32Height/2; i++)
34 {
35 s32Ret = fread(pu8PicAddr,u32Width*u32VarSize,1,fp);
36 SAMPLE_SVP_CHECK_EXPR_GOTO(1 != s32Ret,FAIL,SAMPLE_SVP_ERR_LEVEL_ERROR,"Error,Read image file failed!\n");
37 pu8PicAddr += u32Stride;
38 }
39 }
40 }
41 else if(SVP_BLOB_TYPE_YVU422SP== pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].enType)
42 {
43 for(n = 0; n < pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Num; n++)
44 {
45 for(i = 0; i < u32Height*2; i++)
46 {
47 s32Ret = fread(pu8PicAddr,u32Width*u32VarSize,1,fp);
48 SAMPLE_SVP_CHECK_EXPR_GOTO(1 != s32Ret,FAIL,SAMPLE_SVP_ERR_LEVEL_ERROR,"Error,Read image file failed!\n");
49 pu8PicAddr += u32Stride;
50 }
51 }
52 }
53 else
54 {
55 for(n = 0; n < pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Num; n++)
56 {
57 for(i = 0;i < u32Chn; i++)
58 {
59 for(j = 0; j < u32Height; j++)
60 {
61 s32Ret = fread(pu8PicAddr,u32Width*u32VarSize,1,fp);
62 SAMPLE_SVP_CHECK_EXPR_GOTO(1 != s32Ret,FAIL,SAMPLE_SVP_ERR_LEVEL_ERROR,"Error,Read image file failed!\n");
63 pu8PicAddr += u32Stride;
64 }
65 }
66 }
67 }
68 SAMPLE_COMM_SVP_FlushCache(pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u64PhyAddr,
69 (HI_VOID *) pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u64VirAddr,
70 pstNnieParam->astSegData[u32SegIdx].astSrc[u32NodeIdx].u32Num*u32Chn*u32Height*u32Stride);
71 }
72
73 fclose(fp);
（6）step6为SAMPLE_SVP_NNIE_Forward实现NNIE process，便于分析先给出函数的调用及参数的定义：
1 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
2 /* SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel); */
3
4 stInputDataIdx.u32SegIdx = 0;
5 stInputDataIdx.u32NodeIdx = 0;
6
7 stProcSegIdx.u32SegIdx = 0;
8
9 s32Ret = SAMPLE_SVP_NNIE_Forward(&s_stCnnNnieParam,
10 &stInputDataIdx,
11 &stProcSegIdx,
12 HI_TRUE);
13
14 static HI_S32 SAMPLE_SVP_NNIE_Forward(
15 SAMPLE_SVP_NNIE_PARAM_S *pstNnieParam,
16 SAMPLE_SVP_NNIE_INPUT_DATA_INDEX_S* pstInputDataIdx,
17 SAMPLE_SVP_NNIE_PROCESS_SEG_INDEX_S* pstProcSegIdx,
18 HI_BOOL bInstant)
SAMPLE_SVP_NNIE_Forward中①SAMPLE_COMM_SVP_FlushCache函数主要实现将内存数据刷新到内存中；②HI_MPI_SVP_NNIE_Forward函数同时对输入样本(s)进行CNN预测，对对应样本(s)进行输出响应；③HI_MPI_SVP_NNIE_Query函数用于查询nnie上运行函数的状态，在阻塞模式下，系统等待，直到被查询的函数被调用；在非阻塞模式下，查询当前状态，不做任何操作。
（7）step7为SAMPLE_SVP_NNIE_Cnn_GetTopN实现软件过程，给出函数调用与参数细节：
1 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
2 /* SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel); */
3
4 s_stCnnSoftwareParam.u32TopN = 5;
5 SAMPLE_SVP_NNIE_Cnn_ParamInit(&stNnieCfg, //通过此函数对s_stCnnSoftwareParam进行了赋值操作
6 &s_stCnnNnieParam,
7 &s_stCnnSoftwareParam);
8
9 s32Ret = SAMPLE_SVP_NNIE_Cnn_GetTopN(&s_stCnnNnieParam,
10 &s_stCnnSoftwareParam);
11
12 HI_S32 SAMPLE_SVP_NNIE_Cnn_GetTopN(SAMPLE_SVP_NNIE_PARAM_S*pstNnieParam,
13 SAMPLE_SVP_NNIE_CNN_SOFTWARE_PARAM_S* pstSoftwareParam)
此函数目前基本不修改，函数内部具体实现目前暂不说明，只需注意一点如果改变了网络结构，请确保SAMPLE_SVP_NNIE_Cnn_GetTopN
函数的输入数据正确。
（8）step8为SAMPLE_SVP_NNIE_Cnn_PrintResult打印blob参数值，给出函数调用与参数细节：
1 s_stCnnNnieParam.pstModel = &s_stCnnModel.stModel;
2 /* SAMPLE_COMM_SVP_NNIE_LoadModel(pcModelName,&s_stCnnModel); */
3
4 s_stCnnSoftwareParam.u32TopN = 5;
5 SAMPLE_SVP_NNIE_Cnn_ParamInit(&stNnieCfg, //通过此函数对s_stCnnSoftwareParam进行了赋值操作
6 &s_stCnnNnieParam,
7 &s_stCnnSoftwareParam);
8
9 s32Ret = SAMPLE_SVP_NNIE_Cnn_PrintResult(&(s_stCnnSoftwareParam.stGetTopN),
10 s_stCnnSoftwareParam.u32TopN);
11
12 HI_S32 SAMPLE_SVP_NNIE_Cnn_PrintResult(SVP_BLOB_S *pstGetTopN,
13 HI_U32 u32TopN)
ps32GetTopN
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