Hi3559AV100 NNIE开发（4）mobilefacenet.cfg参数配置挖坑解决与SVP_NNIE

　　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