prob_calc.cpp

Intel开发的IPP库的应用实例

   File_Mixture *exstates=NULL;

   if (ready!=-2)                                           return -10;

   if (!(fptr=fopen(file, "rb")))
   if (!(fptr=create_param_file(file,6000,4,36,100)))       return -3;
   if (fread((void*)(&header), sizeof(Param_File_Header), 1, fptr)<1) {
      fclose(fptr); return -3;
   }

   state_number = header.mixNum;
   max_gauss    = 1;
   space_dim    = header.vecSize;
   max_len      = F;
   min_len      = M;

   gauss_num    = header.wgtNum;
   if (gauss_num<=0)                          {fclose(fptr); return -1;}
   if (header.fileType&0x0111!=0)             {fclose(fptr); return -1;}

   int ret=Init_Arrays();
   if (ret<0)                                 {fclose(fptr); return ret;};

   if (!(exstates  = (File_Mixture*)malloc(sizeof(File_Mixture)*state_number)))
      return -2;
   if ((int)fread((void*)exstates, sizeof(File_Mixture), state_number, fptr)<state_number) {
      fclose(fptr); free(exstates); return -3;
   }
   for (i=0; i<state_number; i++) {
      if (max_gauss<exstates[i].compNum) max_gauss=exstates[i].compNum;
      states[i].compInd=exstates[i].compInd;
      states[i].compNum=exstates[i].compNum;
   }
   free(exstates);

   if ((int)fread((void*)weights, sizeof(float), gauss_num, fptr)<gauss_num) {
      fclose(fptr); return -3;
   }
   if ((int)fread((void*)means, sizeof(float)*space_dim4, gauss_num, fptr)<gauss_num) {
      fclose(fptr); return -3;
   }
   if ((int)fread((void*)vars, sizeof(float)*space_dim4, gauss_num, fptr)<gauss_num) {
      fclose(fptr); return -3;
   }
   if ((int)fread((void*)dets, sizeof(float), gauss_num, fptr)<gauss_num) {
      fclose(fptr); return -3;
   }
   fclose(fptr);
   ippsOutProbPreCalc_32f_I(Weight(0),Det(0),gauss_num);

   ready=-1;
   return 0;
}

Prob_Calc::~Prob_Calc(void) {
   state_number = 0;
   max_gauss    = 0;
   space_dim    = 0;
   gauss_num    = 0;
   max_len      = 0;
   min_len      = 0;
   space_dim4   = 0;
   state_number4= 0;
   gauss_num4   = 0;
   curidx       = 0;
   lastidx      = 0;
   delta_delay  = 0;
   sen_end      = false;
   type         = calcNone;
   if (features) ippsFree(features);
   if (tmp_prob) ippsFree(tmp_prob);
   if (buffer)   ippsFree(buffer);
   if (flog)     fclose(flog);
   feat         = NULL;
   buffer       = NULL;
   features     = NULL;
   tmp_prob     = NULL;
   states       = NULL;
   weights      = NULL;
   dets         = NULL;
   means        = NULL;
   vars         = NULL;
   curfeat      = NULL;
   endfeat      = NULL;
   lastfeat     = NULL;
   flog         = NULL;
   ready        = -2;

   if (in)   ippsFree(in);
   if (length) ippsFree(length);
   in           = NULL;
   length       = NULL;
}

bool Prob_Calc::Attach_Feat(Feat_Calc *f) {
   if (ready!=-1)                                      return false;
   feat=f;
   if (!feat)                                          return false;
   if (!feat->Ready())                                 return false;
   if (feat->Feature_Length()!=space_dim)              return false;

   sen_end     = false;
   curfeat     = features;
   endfeat     = features;
   lastfeat    = features;
   curidx      = 0;
   lastidx     = 0;
   delta_delay = feat->Delta_Delay();

   if (flog)
      feat->Write_LogHeader(flog);

   ready       = 0;
   return true;
}

bool Prob_Calc::Detach_Feat(void) {
   if (ready!=0)                                       return false;
   sen_end=true;
   feat=NULL;
   curfeat=NULL;
   endfeat=NULL;
   lastfeat=NULL;
   curidx=0;
   lastidx=0;
   delta_delay=0;
   ready=-1;

   if (flog)
      fclose(flog);
   flog=NULL;

   return true;
}

bool Prob_Calc::Step_Forward(void) {
   if (ready!=0)                                       return false;
   curfeat+=space_dim4;
   curidx++;
   if ((sen_end)&&(lastidx==curidx)) {
      return false;
   } else if (curidx>=max_len-min_len-delta_delay) {  //  switch to buffer beginning
      ippsCopy_32f(curfeat,features,lastfeat-curfeat+delta_delay*space_dim4);
      lastfeat=features+(lastfeat-curfeat);
      lastidx=lastidx-curidx;
      curfeat=features;
      curidx=0;
   }
   return true;
}

int Prob_Calc::Obv_Prob_Vec(int state, float *result, int len) {
   int m,num;
   if (ready!=0)                                       return -1;
   if (!sen_end) {
      if (lastidx-curidx<min_len) {
         num=feat->Get_Feature(lastfeat,max_len-lastidx,&sen_end);
         if (flog)
            for (m=0; m<num; m++)
               fwrite((void*)(lastfeat+m*space_dim4), sizeof(float), space_dim, flog);
         // here wait if num==0 if features are consumed faster
         lastidx+=num;
         lastfeat+=num*space_dim4;
      }
   }

   num=lastidx-curidx;
   if (len<num) num=len;

   float *mean=Mean(state);
   float *var=Var(state);
   float *det=Det(state);
   float *feat=curfeat;

   switch (type) {
   case calcVect:
      ippsLogGauss_32f_D2(curfeat,space_dim4,mean,var,space_dim,result,num,det[0]);
      for (m=1; m<states[state].compNum; m++) {
         mean+=space_dim4;
         var+=space_dim4;
         ippsLogGaussAdd_32f_D2(curfeat,space_dim4,mean,var,space_dim,result,num,det[m]);
      }
      break;
   case calcVecM:
      ippsLogGauss_32f_D2(curfeat,space_dim4,mean,var,space_dim,result,num,det[0]);
      for (m=1; m<states[state].compNum; m++) {
         mean+=space_dim4;
         var+=space_dim4;
         ippsLogGaussMax_32f_D2(curfeat,space_dim4,mean,var,space_dim,result,num,det[m]);
      }
      break;
   case calcMMix:
      for (m=0; m<num; m++) {
         ippsCopy_32f(det,tmp_prob,states[state].compNum);
         ippsLogGaussMultiMix_32f_D2(mean,var,space_dim4,feat,space_dim,
            tmp_prob,states[state].compNum);
         ippsLogSum_32f(tmp_prob,result+m,states[state].compNum,ippAlgHintNone);
         feat+=space_dim4;
      }
      break;
   case calcMix:
      for (m=0; m<num; m++) {
         ippsLogGaussMixture_32f_D2(feat,mean,var,states[state].compNum,space_dim4,
            space_dim,det,result+m);
         feat+=space_dim4;
      }
      break;
   case calcNone:
      fake_sum=det[0];
      for (m=0; m<space_dim4*states[state].compNum; m+=8)
         fake_sum+=mean[m];
      for (m=0; m<space_dim4*states[state].compNum; m+=8)
         fake_sum+=var[m];
      for (m=0; m<space_dim4*num; m+=8)
         fake_sum+=curfeat[m];
      break;
   default:
      return -1;
   }

   return num;
}

void    Prob_Calc::AddState(int t,int state,float* curbuf,int vec_length){
   in[state].buf=curbuf;
   in[state].len=vec_length;

   in[in_end].next=state;
   in_end=state;
   in[state].t=t;

   return;
}

void    Prob_Calc::CalcState(void){
   int n;

   while(running){
      if(in[in_start].t>=0){
         n=Obv_Prob_Vec(in_start,in[in_start].buf,in[in_start].len);
         if(n<0)
            ready++;
         length[in_start]=n;
         in[in_start].t=-1;
         tmp_counter++;
      }

      if(in_start!=in_end){
         n=in_start;
         in_start=in[n].next;
         in[n].next=-1;
      }
   }
   return;
}

void    Prob_Calc::Sync(void){
   tmp_counter=-1;
   return;
}

int     Prob_Calc::ReadyState(void){
   return tmp_counter;
}

void    Prob_Calc::Stop(void){
   running=false;
   return;
}