Bug Fixes:

prepare_project done when projection_prop set
Wrong dgemm_ setting for PreasonLoss

src/loss_function/LossFunctionConvexHull.cpp

@@ -70,6 +70,7 @@ LossFunctionConvexHull::LossFunctionConvexHull(
     std::copy_n(prop_test.begin(), prop_test.size(), _prop_test.begin());
 
     setup_lp();
+    prepare_project();
 }
 
 LossFunctionConvexHull::LossFunctionConvexHull(std::shared_ptr<LossFunction> o) :
@@ -78,6 +79,7 @@ LossFunctionConvexHull::LossFunctionConvexHull(std::shared_ptr<LossFunction> o)
     _n_class(vector_utils::unique<double>(_prop_train).size())
 {
     setup_lp();
+    prepare_project();
 }
 
 void LossFunctionConvexHull::set_nfeat(int n_feat)
@@ -209,9 +211,8 @@ void LossFunctionConvexHull::reset_projection_prop(const std::vector<std::vector
         std::copy_n(_error_train.data(), _error_train.size(), &_projection_prop[mm * _n_samp]);
     }
 
-    _n_feat = models.back().size() + 1;
-    _n_dim =  _n_feat;
-    setup_lp();
+    set_nfeat(models.back().size() + 1);
+    prepare_project();
 }
 
 double LossFunctionConvexHull::operator()(const std::vector<int>& inds)

src/loss_function/LossFunctionPearsonRMSE.cpp

@@ -17,6 +17,7 @@ LossFunctionPearsonRMSE::LossFunctionPearsonRMSE(
 {
     set_nfeat(_n_feat);
     set_opt_lwork();
+    prepare_project();
 }
 
 LossFunctionPearsonRMSE::LossFunctionPearsonRMSE(std::shared_ptr<LossFunction> o) :
@@ -29,6 +30,7 @@ LossFunctionPearsonRMSE::LossFunctionPearsonRMSE(std::shared_ptr<LossFunction> o
 {
     set_nfeat(_n_feat);
     set_opt_lwork();
+    prepare_project();
 }
 
 void LossFunctionPearsonRMSE::set_nfeat(int n_feat)
@@ -56,6 +58,7 @@ void LossFunctionPearsonRMSE::reset_projection_prop(const std::vector<std::vecto
 
     set_nfeat(models.back().size() + 1);
     _n_project_prop = models.size();
+    prepare_project();
 }
 
 void LossFunctionPearsonRMSE::set_opt_lwork()
@@ -118,14 +121,14 @@ double LossFunctionPearsonRMSE::calc_max_pearson(double* feat_val_ptr)
     {
         double feat_std = util_funcs::stand_dev(feat_val_ptr + start, _task_sizes_train[tt]);
         dgemm_(
-            'N',
+            'T',
             'N',
             _n_project_prop,
             1,
             _task_sizes_train[tt],
             1.0 / feat_std / static_cast<double>(_task_sizes_train[tt]),
             &_projection_prop[start * _n_project_prop],
-            _n_project_prop,
+            _task_sizes_train[tt],
             feat_val_ptr + start,
             _task_sizes_train[tt],
             0.0,

src/utils/project.cpp

@@ -92,7 +92,6 @@ void project_funcs::project_loss(std::shared_ptr<LossFunction> loss, const std::
     #pragma omp parallel
     {
         std::shared_ptr<LossFunction> loss_copy = loss_function_util::copy(loss);
-        loss_copy->prepare_project();
         int start = (
             omp_get_thread_num() * (feats.size() / omp_get_num_threads()) +
             std::min(omp_get_thread_num(), static_cast<int>(feats.size()) % omp_get_num_threads())
@@ -116,7 +115,6 @@ void project_funcs::project_loss(std::shared_ptr<LossFunction> loss, const std::
 
 void project_funcs::project_loss_no_omp(std::shared_ptr<LossFunction> loss, const std::vector<node_ptr>& feats, double* scores)
 {
-    loss->prepare_project();
     std::fill_n(scores, feats.size(), std::numeric_limits<double>::max());
     std::transform(
         feats.begin(),