Fix the test.

src/predictor/cpu_predictor.cc

@@ -188,21 +188,17 @@ class CPUPredictor : public Predictor {
     // update cache entry
     auto* out = &predts->predictions;
     if (predts->predictions.Size() == 0) {
-      std::cout << __func__ << " Building the cache from sratch." << std::endl;
       InitOutPredictions(m->Info(), out, model);
       this->PredLoopInternal(m, &out->HostVector(), model, 0, model.trees.size());
     } else if (model.learner_model_param_->num_output_group == 1 &&
                updaters->size() > 0 &&
                num_new_trees == 1 &&
                updaters->back()->UpdatePredictionCache(m, out)) {
-      std::cout << __func__ << " The cache is updated by updater." << std::endl;
       {}
     } else {
-      std::cout << __func__ << " The cache is updated by CPU Predictor." << std::endl;
       PredLoopInternal(m, &out->HostVector(), model, old_ntree, model.trees.size());
     }
     auto delta = num_new_trees / model.learner_model_param_->num_output_group;
-    std::cout << __func__ << " delta: " << delta;
     predts->Update(delta);
   }
 

tests/cpp/helpers.cc

@@ -263,13 +263,19 @@ std::unique_ptr<DMatrix> CreateSparsePageDMatrixWithRC(
   }
 }
 
-gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param) {
-  std::vector<std::unique_ptr<RegTree>> trees;
-  trees.push_back(std::unique_ptr<RegTree>(new RegTree));
-  (*trees.back())[0].SetLeaf(1.5f);
-  (*trees.back()).Stat(0).sum_hess = 1.0f;
+gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, size_t n_classes) {
   gbm::GBTreeModel model(param);
-  model.CommitModel(std::move(trees), 0);
+
+  for (size_t i = 0; i < n_classes; ++i) {
+    std::vector<std::unique_ptr<RegTree>> trees;
+    trees.push_back(std::unique_ptr<RegTree>(new RegTree));
+    if (i == 0) {
+      (*trees.back())[0].SetLeaf(1.5f);
+      (*trees.back()).Stat(0).sum_hess = 1.0f;
+    }
+    model.CommitModel(std::move(trees), i);
+  }
+
   return model;
 }
 

tests/cpp/helpers.h

@@ -209,7 +209,7 @@ std::unique_ptr<DMatrix> CreateSparsePageDMatrixWithRC(
     size_t n_rows, size_t n_cols, size_t page_size, bool deterministic,
     const dmlc::TemporaryDirectory& tempdir = dmlc::TemporaryDirectory());
 
-gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param);
+gbm::GBTreeModel CreateTestModel(LearnerModelParam const* param, size_t n_classes = 1);
 
 std::unique_ptr<GradientBooster> CreateTrainedGBM(
     std::string name, Args kwargs, size_t kRows, size_t kCols,

tests/cpp/predictor/test_gpu_predictor.cu

@@ -67,7 +67,7 @@ TEST(gpu_predictor, ExternalMemoryTest) {
   param.num_output_group = n_classes;
   param.base_score = 0.5;
 
-  gbm::GBTreeModel model = CreateTestModel(&param);
+  gbm::GBTreeModel model = CreateTestModel(&param, n_classes);
   std::vector<std::unique_ptr<DMatrix>> dmats;
   dmlc::TemporaryDirectory tmpdir;
   std::string file0 = tmpdir.path + "/big_0.libsvm";