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Remove omp_get_max_threads (#7608)

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This is the one last PR for removing omp global variable.

* Add context object to the `DMatrix`.  This bridges `DMatrix` with https://github.com/dmlc/xgboost/issues/7308 .
* Require context to be available at the construction time of booster.
* Add `n_threads` support for R csc DMatrix constructor.
* Remove `omp_get_max_threads` in R glue code.
* Remove threading utilities that rely on omp global variable.
This commit is contained in:
Jiaming Yuan
2022-01-28 16:09:22 +08:00
committed by GitHub
parent 028bdc1740
commit 81210420c6
31 changed files with 195 additions and 211 deletions
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27
tests/cpp/predictor/test_gpu_predictor.cu
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@@ -38,7 +38,9 @@ TEST(GPUPredictor, Basic) {
param.num_output_group = 1;
param.base_score = 0.5;
gbm::GBTreeModel model = CreateTestModel(&param);
GenericParameter ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&param, &ctx);
// Test predict batch
PredictionCacheEntry gpu_out_predictions;
@@ -100,7 +102,9 @@ TEST(GPUPredictor, ExternalMemoryTest) {
param.num_output_group = n_classes;
param.base_score = 0.5;
gbm::GBTreeModel model = CreateTestModel(&param, n_classes);
GenericParameter ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&param, &ctx, n_classes);
std::vector<std::unique_ptr<DMatrix>> dmats;
dmats.push_back(CreateSparsePageDMatrix(400));
@@ -167,11 +171,17 @@ TEST(GpuPredictor, LesserFeatures) {
// Very basic test of empty model
TEST(GPUPredictor, ShapStump) {
cudaSetDevice(0);
LearnerModelParam param;
param.num_feature = 1;
param.num_output_group = 1;
param.base_score = 0.5;
gbm::GBTreeModel model(&param);
GenericParameter ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model(&param, &ctx);
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
model.CommitModel(std::move(trees), 0);
@@ -197,7 +207,12 @@ TEST(GPUPredictor, Shap) {
param.num_feature = 1;
param.num_output_group = 1;
param.base_score = 0.5;
gbm::GBTreeModel model(&param);
GenericParameter ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model(&param, &ctx);
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
trees[0]->ExpandNode(0, 0, 0.5, true, 1.0, -1.0, 1.0, 0.0, 5.0, 2.0, 3.0);
@@ -249,7 +264,9 @@ TEST(GPUPredictor, PredictLeafBasic) {
param.base_score = 0.0;
param.num_output_group = 1;
gbm::GBTreeModel model = CreateTestModel(&param);
GenericParameter ctx;
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&param, &ctx);
HostDeviceVector<float> leaf_out_predictions;
gpu_predictor->PredictLeaf(dmat.get(), &leaf_out_predictions, model);