Add tests for prediction cache. (#7650)

* Extract the test from approx for other tree methods.
* Add note on how it works.

tests/cpp/tree/test_approx.cc

@@ -75,58 +75,5 @@ TEST(Approx, Partitioner) {
     }
   }
 }
-
-TEST(Approx, PredictionCache) {
-  size_t n_samples = 2048, n_features = 13;
-  auto Xy = RandomDataGenerator{n_samples, n_features, 0}.GenerateDMatrix(true);
-
-  {
-    omp_set_num_threads(1);
-    GenericParameter ctx;
-    ctx.InitAllowUnknown(Args{{"nthread", "8"}});
-    std::unique_ptr<TreeUpdater> approx{
-        TreeUpdater::Create("grow_histmaker", &ctx, ObjInfo{ObjInfo::kRegression})};
-    RegTree tree;
-    std::vector<RegTree *> trees{&tree};
-    auto gpair = GenerateRandomGradients(n_samples);
-    approx->Configure(Args{{"max_bin", "64"}});
-    approx->Update(&gpair, Xy.get(), trees);
-    HostDeviceVector<float> out_prediction_cached;
-    out_prediction_cached.Resize(n_samples);
-    auto cache = linalg::VectorView<float>{
-        out_prediction_cached.HostSpan(), {out_prediction_cached.Size()}, GenericParameter::kCpuId};
-    ASSERT_TRUE(approx->UpdatePredictionCache(Xy.get(), cache));
-  }
-
-  std::unique_ptr<Learner> learner{Learner::Create({Xy})};
-  learner->SetParam("tree_method", "approx");
-  learner->SetParam("nthread", "0");
-  learner->Configure();
-
-  for (size_t i = 0; i < 8; ++i) {
-    learner->UpdateOneIter(i, Xy);
-  }
-
-  HostDeviceVector<float> out_prediction_cached;
-  learner->Predict(Xy, false, &out_prediction_cached, 0, 0);
-
-  Json model{Object()};
-  learner->SaveModel(&model);
-
-  HostDeviceVector<float> out_prediction;
-  {
-    std::unique_ptr<Learner> learner{Learner::Create({Xy})};
-    learner->LoadModel(model);
-    learner->Predict(Xy, false, &out_prediction, 0, 0);
-  }
-
-  auto const h_predt_cached = out_prediction_cached.ConstHostSpan();
-  auto const h_predt = out_prediction.ConstHostSpan();
-
-  ASSERT_EQ(h_predt.size(), h_predt_cached.size());
-  for (size_t i = 0; i < h_predt.size(); ++i) {
-    ASSERT_NEAR(h_predt[i], h_predt_cached[i], kRtEps);
-  }
-}
 }  // namespace tree
 }  // namespace xgboost