add tests for depth-wise policy

Author: Dmitry Razdoburdin

tests/cpp/plugin/test_sycl_hist_updater.cc

@@ -73,6 +73,13 @@ class TestHistUpdater : public HistUpdater<GradientSumT> {
                                const USMVector<GradientPair, MemoryType::on_device> &gpair) {
     HistUpdater<GradientSumT>::ExpandWithLossGuide(gmat, p_tree, gpair);
   }
+
+  auto TestExpandWithDepthWise(const common::GHistIndexMatrix& gmat,
+                               DMatrix *p_fmat,
+                               RegTree* p_tree,
+                               const USMVector<GradientPair, MemoryType::on_device> &gpair) {
+    HistUpdater<GradientSumT>::ExpandWithDepthWise(gmat, p_tree, gpair);
+  }
 };
 
 void GenerateRandomGPairs(::sycl::queue* qu, GradientPair* gpair_ptr, size_t num_rows, bool has_neg_hess) {
@@ -532,6 +539,55 @@ void TestHistUpdaterExpandWithLossGuide(const xgboost::tree::TrainParam& param)
   ASSERT_NEAR(ans[2], -0.15, 1e-6);
 }
 
+template <typename GradientSumT>
+void TestHistUpdaterExpandWithDepthWise(const xgboost::tree::TrainParam& param) {
+  const size_t num_rows = 3;
+  const size_t num_columns = 1;
+  const size_t n_bins = 16;
+
+  Context ctx;
+  ctx.UpdateAllowUnknown(Args{{"device", "sycl"}});
+
+  DeviceManager device_manager;
+  auto qu = device_manager.GetQueue(ctx.Device());
+
+  std::vector<float> data = {7, 3, 15};
+  auto p_fmat = GetDMatrixFromData(data, num_rows, num_columns);
+
+  DeviceMatrix dmat;
+  dmat.Init(qu, p_fmat.get());
+  common::GHistIndexMatrix gmat;
+  gmat.Init(qu, &ctx, dmat, n_bins);
+
+  std::vector<GradientPair> gpair_host = {{1, 2}, {3, 1}, {1, 1}};
+  USMVector<GradientPair, MemoryType::on_device> gpair(&qu, gpair_host);
+
+  RegTree tree;
+  FeatureInteractionConstraintHost int_constraints;
+  ObjInfo task{ObjInfo::kRegression};
+  std::unique_ptr<TreeUpdater> pruner{TreeUpdater::Create("prune", &ctx, &task)};
+  TestHistUpdater<GradientSumT> updater(&ctx, qu, param, std::move(pruner), int_constraints, p_fmat.get());
+  updater.SetHistSynchronizer(new BatchHistSynchronizer<GradientSumT>());
+  updater.SetHistRowsAdder(new BatchHistRowsAdder<GradientSumT>());
+  auto* row_set_collection = updater.TestInitData(gmat, gpair, *p_fmat, tree);
+
+  updater.TestExpandWithDepthWise(gmat, p_fmat.get(), &tree, gpair);
+
+  const auto& nodes = tree.GetNodes();
+  std::vector<float> ans(data.size());
+  for (size_t data_idx = 0; data_idx < data.size(); ++data_idx) {
+      size_t node_idx = 0;
+      while (!nodes[node_idx].IsLeaf()) {
+        node_idx = data[data_idx] < nodes[node_idx].SplitCond() ? nodes[node_idx].LeftChild() : nodes[node_idx].RightChild();
+      }
+      ans[data_idx] = nodes[node_idx].LeafValue();
+  }
+
+  ASSERT_NEAR(ans[0], -0.15, 1e-6);
+  ASSERT_NEAR(ans[1], -0.45, 1e-6);
+  ASSERT_NEAR(ans[2], -0.15, 1e-6);
+}
+
 TEST(SyclHistUpdater, Sampling) {
   xgboost::tree::TrainParam param;
   param.UpdateAllowUnknown(Args{{"subsample", "0.7"}});
@@ -608,4 +664,12 @@ TEST(SyclHistUpdater, ExpandWithLossGuide) {
   TestHistUpdaterExpandWithLossGuide<double>(param);
 }
 
+TEST(SyclHistUpdater, ExpandWithDepthWise) {
+  xgboost::tree::TrainParam param;
+  param.UpdateAllowUnknown(Args{{"max_depth", "2"}});
+
+  TestHistUpdaterExpandWithDepthWise<float>(param);
+  TestHistUpdaterExpandWithDepthWise<double>(param);
+}
+
 }  // namespace xgboost::sycl::tree