Remove test.

Author: trivialfis

tests/cpp/gbm/test_gbtree.cc

@@ -118,7 +118,7 @@ TEST(GBTree, ChoosePredictor) {
 
   auto p_dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
 
-  auto& data = (*(p_dmat->GetBatches<SparsePage>().begin())).data;
+  auto const& data = (*(p_dmat->GetBatches<SparsePage>().begin())).data;
   p_dmat->Info().labels.Reshape(kRows);
 
   auto learner = std::unique_ptr<Learner>(Learner::Create({p_dmat}));
@@ -145,7 +145,7 @@ TEST(GBTree, ChoosePredictor) {
   for (size_t i = 0; i < 4; ++i) {
     learner->UpdateOneIter(i, p_dmat);
   }
-  ASSERT_TRUE(data.HostCanWrite());
+  ASSERT_TRUE(data.HostCanRead());
 
   // pull data into device.
   data.HostVector();

tests/cpp/test_learner.cc

@@ -342,16 +342,6 @@ TEST(Learner, GPUConfiguration) {
     learner->UpdateOneIter(0, p_dmat);
     ASSERT_EQ(learner->Ctx()->gpu_id, 0);
   }
-  {
-    // With CPU algorithm but GPU Predictor, this is to simulate when
-    // XGBoost is only used for prediction, so tree method is not
-    // specified.
-    std::unique_ptr<Learner> learner {Learner::Create(mat)};
-    learner->SetParams({Arg{"tree_method", "hist"},
-                        Arg{"predictor", "gpu_predictor"}});
-    learner->UpdateOneIter(0, p_dmat);
-    ASSERT_EQ(learner->Ctx()->gpu_id, 0);
-  }
 }
 #endif  // defined(XGBOOST_USE_CUDA)