fix omp for bug in obj

regrank/xgboost_regrank.h

@@ -200,6 +200,11 @@ namespace xgboost{
                 fprintf(fo, "[%d]", iter);
                 for (size_t i = 0; i < evals.size(); ++i){
                     this->PredictRaw(preds_, *evals[i]);
+                    for( size_t j = 0 ; j < preds_.size(); ++ j){
+                        if( fabsf(preds_[j]- 0.5f)>1e-6f){
+                            printf("p[%lu]=%f\n", j,preds_[j]);
+                        }
+                    }
                     obj_->PredTransform(preds_);
                     evaluator_.Eval(fo, evname[i].c_str(), preds_, evals[i]->info);
                 }
@@ -283,6 +288,10 @@ namespace xgboost{
                     #pragma omp parallel for schedule( static )
                     for (unsigned j = 0; j < ndata; ++j){
                         preds[j] = mparam.base_score + base_gbm.Predict(data.data, j, buffer_offset + j, data.info.GetRoot(j), bst_group );
+                        if( preds[j] != 0.5f ){
+                            printf("pred[%d:%u]=%f\n", bst_group, j, preds[j]);
+                        }
+                        utils::Assert( preds[j] == 0.5f, "BUG");
                     }
                 }else
                     #pragma omp parallel for schedule( static )

regrank/xgboost_regrank_eval.h

@@ -83,7 +83,7 @@ namespace xgboost{
                 float sum = 0.0f, wsum = 0.0f;
                 #pragma omp parallel for reduction(+:sum,wsum) schedule( static )
                 for (unsigned i = 0; i < ndata; ++i){
-                    const float wt = info.GetWeight(i);
+                    const float wt = info.GetWeight(i);                    
                     if (preds[i] > 0.5f){
                         if (info.labels[i] < 0.5f) sum += wt;
                     }
@@ -99,6 +99,28 @@ namespace xgboost{
             }
         };
 
+
+        /*! \brief Error */
+        struct EvalMatchError : public IEvaluator{
+            virtual float Eval(const std::vector<float> &preds,
+                               const DMatrix::Info &info) const {
+                const unsigned ndata = static_cast<unsigned>(preds.size());
+                float sum = 0.0f, wsum = 0.0f;
+                #pragma omp parallel for reduction(+:sum,wsum) schedule( static )
+                for (unsigned i = 0; i < ndata; ++i){
+                    const float wt = info.GetWeight(i);                    
+                    if (static_cast<int>(preds[i]) != static_cast<int>(info.labels[i]) ){
+                        sum += wt;
+                    }
+                    wsum += wt;
+                }
+                return sum / wsum;
+            }
+            virtual const char *Name(void) const{
+                return "merror";
+            }
+        };
+
         /*! \brief Area under curve, for both classification and rank */
         struct EvalAuc : public IEvaluator{
             virtual float Eval(const std::vector<float> &preds,
@@ -270,6 +292,7 @@ namespace xgboost{
                 }
                 if (!strcmp(name, "rmse"))    evals_.push_back(new EvalRMSE());
                 if (!strcmp(name, "error"))   evals_.push_back(new EvalError());
+                if (!strcmp(name, "merror"))   evals_.push_back(new EvalMatchError());
                 if (!strcmp(name, "logloss")) evals_.push_back(new EvalLogLoss());
                 if (!strcmp(name, "auc"))    evals_.push_back(new EvalAuc());
                 if (!strncmp(name, "pre@", 4)) evals_.push_back(new EvalPrecision(name));

regrank/xgboost_regrank_obj.hpp

@@ -75,7 +75,7 @@ namespace xgboost{
                 #pragma omp parallel
                 {
                     std::vector< float > rec;                    
-                    #pragma for schedule(static)
+                    #pragma omp for schedule(static)
                     for (unsigned k = 0; k < ngroup; ++k){
                         rec.clear();
                         int nhit = 0;
@@ -125,7 +125,7 @@ namespace xgboost{
                 #pragma omp parallel
                 {
                     std::vector<float> rec(nclass);
-                    #pragma for schedule(static)
+                    #pragma omp for schedule(static)
                     for (unsigned j = 0; j < ndata; ++j){
                         for( int k = 0; k < nclass; ++ k ){
                             rec[k] = preds[j + k * ndata];
@@ -149,22 +149,22 @@ namespace xgboost{
                 utils::Assert( nclass != 0, "must set num_class to use softmax" );
                 utils::Assert( preds.size() % nclass == 0, "SoftmaxMultiClassObj: label size and pred size does not match" );                
                 const unsigned ndata = static_cast<unsigned>(preds.size()/nclass);
+                
                 #pragma omp parallel
                 {
                     std::vector<float> rec(nclass);
-                    #pragma for schedule(static)
+                    #pragma omp for schedule(static)
                     for (unsigned j = 0; j < ndata; ++j){
                         for( int k = 0; k < nclass; ++ k ){
                             rec[k] = preds[j + k * ndata];
                         }
-                        Softmax( rec );
                         preds[j] = FindMaxIndex( rec );
                     }
                 }
                 preds.resize( ndata );
             }
             virtual const char* DefaultEvalMetric(void) {
-                return "error";
+                return "merror";
             }
         private:
             int nclass;
@@ -201,7 +201,7 @@ namespace xgboost{
                     // thread use its own random number generator, seed by thread id and current iteration
                     random::Random rnd; rnd.Seed( iter * 1111 + omp_get_thread_num() );
                     std::vector< std::pair<float,unsigned> > rec;
-                    #pragma for schedule(static)
+                    #pragma omp for schedule(static)
                     for (unsigned k = 0; k < ngroup; ++k){
                         rec.clear();
                         for(unsigned j = gptr[k]; j < gptr[k+1]; ++j ){

regrank/xgboost_regrank_utils.h

@@ -26,7 +26,9 @@ namespace xgboost{
         inline static int FindMaxIndex( std::vector<float>& rec ){
             size_t mxid = 0;
             for( size_t i = 1; i < rec.size(); ++ i ){
-                if( rec[i] > rec[mxid] ) mxid = i;
+                if( rec[i] > rec[mxid]+1e-6f ){
+                    mxid = i;
+                }
             }
             return (int)mxid;
         }