Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Use context in SetInfo. (#7687)

Browse Source 
* Use the name `Context`.
* Pass a context object into `SetInfo`.
* Add context to proxy matrix.
* Add context to iterative DMatrix.

This is to remove the use of the default number of threads during `SetInfo` as a follow-up on
removing the global omp variable while preparing for CUDA stream semantic.  Currently, XGBoost
uses the legacy CUDA stream, we will gradually remove them in the future in favor of non-blocking streams.
This commit is contained in:
Jiaming Yuan
2022-03-24 22:16:26 +08:00
committed by GitHub
parent f5b20286e2
commit 64575591d8
19 changed files with 142 additions and 142 deletions
Download Patch File Download Diff File Expand all files Collapse all files

12
tests/cpp/test_learner.cc
View File

@@ -74,11 +74,9 @@ TEST(Learner, CheckGroup) {
labels[i] = i % 2;
}
p_mat->Info().SetInfo(
"weight", static_cast<void*>(weight.data()), DataType::kFloat32, kNumGroups);
p_mat->Info().SetInfo(
"group", group.data(), DataType::kUInt32, kNumGroups);
p_mat->Info().SetInfo("label", labels.data(), DataType::kFloat32, kNumRows);
p_mat->SetInfo("weight", static_cast<void *>(weight.data()), DataType::kFloat32, kNumGroups);
p_mat->SetInfo("group", group.data(), DataType::kUInt32, kNumGroups);
p_mat->SetInfo("label", labels.data(), DataType::kFloat32, kNumRows);
std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {p_mat};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
@@ -88,7 +86,7 @@ TEST(Learner, CheckGroup) {
group.resize(kNumGroups+1);
group[3] = 4;
group[4] = 1;
p_mat->Info().SetInfo("group", group.data(), DataType::kUInt32, kNumGroups+1);
p_mat->SetInfo("group", group.data(), DataType::kUInt32, kNumGroups+1);
EXPECT_ANY_THROW(learner->UpdateOneIter(0, p_mat));
}
@@ -105,7 +103,7 @@ TEST(Learner, SLOW_CheckMultiBatch) { // NOLINT
for (size_t i = 0; i < num_row; ++i) {
labels[i] = i % 2;
}
dmat->Info().SetInfo("label", labels.data(), DataType::kFloat32, num_row);
dmat->SetInfo("label", labels.data(), DataType::kFloat32, num_row);
std::vector<std::shared_ptr<DMatrix>> mat{dmat};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
learner->SetParams(Args{{"objective", "binary:logistic"}});