Small cleanup for histogram routines. (#9427)

* Small cleanup for histogram routines.

- Extract hist train param from GPU hist.
- Make histogram const after construction.
- Unify parameter names.

tests/cpp/tree/test_gpu_hist.cu

@@ -105,13 +105,13 @@ void TestBuildHist(bool use_shared_memory_histograms) {
   gpair.SetDevice(0);
 
   thrust::host_vector<common::CompressedByteT> h_gidx_buffer (page->gidx_buffer.HostVector());
-  maker.row_partitioner.reset(new RowPartitioner(0, kNRows));
+  maker.row_partitioner = std::make_unique<RowPartitioner>(0, kNRows);
 
   maker.hist.Init(0, page->Cuts().TotalBins());
   maker.hist.AllocateHistograms({0});
 
   maker.gpair = gpair.DeviceSpan();
-  maker.quantiser.reset(new GradientQuantiser(maker.gpair));
+  maker.quantiser = std::make_unique<GradientQuantiser>(maker.gpair);
   maker.page = page.get();
 
   maker.InitFeatureGroupsOnce();
@@ -246,6 +246,7 @@ void UpdateTree(Context const* ctx, HostDeviceVector<GradientPair>* gpair, DMatr
 
   ObjInfo task{ObjInfo::kRegression};
   tree::GPUHistMaker hist_maker{ctx, &task};
+  hist_maker.Configure(Args{});
 
   std::vector<HostDeviceVector<bst_node_t>> position(1);
   hist_maker.Update(&param, gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position},
@@ -397,14 +398,14 @@ TEST(GpuHist, ConfigIO) {
   std::unique_ptr<TreeUpdater> updater{TreeUpdater::Create("grow_gpu_hist", &ctx, &task)};
   updater->Configure(Args{});
 
-  Json j_updater { Object() };
+  Json j_updater{Object{}};
   updater->SaveConfig(&j_updater);
-  ASSERT_TRUE(IsA<Object>(j_updater["gpu_hist_train_param"]));
+  ASSERT_TRUE(IsA<Object>(j_updater["hist_train_param"]));
   updater->LoadConfig(j_updater);
 
-  Json j_updater_roundtrip { Object() };
+  Json j_updater_roundtrip{Object{}};
   updater->SaveConfig(&j_updater_roundtrip);
-  ASSERT_TRUE(IsA<Object>(j_updater_roundtrip["gpu_hist_train_param"]));
+  ASSERT_TRUE(IsA<Object>(j_updater_roundtrip["hist_train_param"]));
 
   ASSERT_EQ(j_updater, j_updater_roundtrip);
 }

tests/cpp/tree/test_histmaker.cc

@@ -39,6 +39,7 @@ TEST(GrowHistMaker, InteractionConstraint) {
     param.UpdateAllowUnknown(
         Args{{"interaction_constraints", "[[0, 1]]"}, {"num_feature", std::to_string(kCols)}});
     std::vector<HostDeviceVector<bst_node_t>> position(1);
+    updater->Configure(Args{});
     updater->Update(&param, p_gradients.get(), p_dmat.get(), position, {&tree});
 
     ASSERT_EQ(tree.NumExtraNodes(), 4);
@@ -55,6 +56,7 @@ TEST(GrowHistMaker, InteractionConstraint) {
     std::vector<HostDeviceVector<bst_node_t>> position(1);
     TrainParam param;
     param.Init(Args{});
+    updater->Configure(Args{});
     updater->Update(&param, p_gradients.get(), p_dmat.get(), position, {&tree});
 
     ASSERT_EQ(tree.NumExtraNodes(), 10);
@@ -81,6 +83,7 @@ void VerifyColumnSplit(int32_t rows, bst_feature_t cols, bool categorical,
   RegTree tree{1u, cols};
   TrainParam param;
   param.Init(Args{});
+  updater->Configure(Args{});
   updater->Update(&param, p_gradients.get(), sliced.get(), position, {&tree});
 
   Json json{Object{}};
@@ -104,6 +107,7 @@ void TestColumnSplit(bool categorical) {
     std::vector<HostDeviceVector<bst_node_t>> position(1);
     TrainParam param;
     param.Init(Args{});
+    updater->Configure(Args{});
     updater->Update(&param, p_gradients.get(), p_dmat.get(), position, {&expected_tree});
   }
 

tests/cpp/tree/test_prediction_cache.cc

@@ -73,6 +73,7 @@ class TestPredictionCache : public ::testing::Test {
       tree::TrainParam param;
       param.UpdateAllowUnknown(Args{{"max_bin", "64"}});
 
+      updater->Configure(Args{});
       std::vector<HostDeviceVector<bst_node_t>> position(1);
       updater->Update(&param, &gpair, Xy_.get(), position, trees);
       HostDeviceVector<float> out_prediction_cached;

tests/cpp/tree/test_quantile_hist.cc

@@ -13,7 +13,6 @@
 #include "../../../src/tree/common_row_partitioner.h"
 #include "../../../src/tree/hist/expand_entry.h"  // for MultiExpandEntry, CPUExpandEntry
 #include "../../../src/tree/param.h"
-#include "../../../src/tree/split_evaluator.h"
 #include "../helpers.h"
 #include "test_partitioner.h"
 #include "xgboost/data.h"
@@ -49,7 +48,7 @@ void TestPartitioner(bst_target_t n_targets) {
       auto min_value = gmat.cut.MinValues()[split_ind];
       RegTree tree{n_targets, n_features};
       CommonRowPartitioner partitioner{&ctx, n_samples, base_rowid, false};
-      if constexpr (std::is_same<ExpandEntry, CPUExpandEntry>::value) {
+      if constexpr (std::is_same_v<ExpandEntry, CPUExpandEntry>) {
         GetSplit(&tree, min_value, &candidates);
       } else {
         GetMultiSplitForTest(&tree, min_value, &candidates);
@@ -217,6 +216,7 @@ void VerifyColumnSplit(bst_row_t rows, bst_feature_t cols, bst_target_t n_target
   RegTree tree{n_targets, cols};
   TrainParam param;
   param.Init(Args{});
+  updater->Configure(Args{});
   updater->Update(&param, p_gradients.get(), sliced.get(), position, {&tree});
 
   Json json{Object{}};
@@ -241,6 +241,7 @@ void TestColumnSplit(bst_target_t n_targets) {
     std::vector<HostDeviceVector<bst_node_t>> position(1);
     TrainParam param;
     param.Init(Args{});
+    updater->Configure(Args{});
     updater->Update(&param, p_gradients.get(), Xy.get(), position, {&expected_tree});
   }
 

tests/test_distributed/test_with_dask/test_with_dask.py

@@ -1459,6 +1459,7 @@ class TestWithDask:
         tree_method: str,
     ) -> None:
         params["tree_method"] = tree_method
+        params["debug_synchronize"] = True
         params = dataset.set_params(params)
         # It doesn't make sense to distribute a completely
         # empty dataset.