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Use context in SetInfo. (#7687)

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* 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
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9
tests/cpp/common/test_hist_util.cu
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@@ -520,7 +520,7 @@ TEST(HistUtil, DeviceSketchFromGroupWeights) {
for (size_t i = 0; i < kGroups; ++i) {
groups[i] = kRows / kGroups;
}
m->Info().SetInfo("group", groups.data(), DataType::kUInt32, kGroups);
m->SetInfo("group", groups.data(), DataType::kUInt32, kGroups);
HistogramCuts weighted_cuts = DeviceSketch(0, m.get(), kBins, 0);
h_weights.clear();
@@ -550,6 +550,7 @@ void TestAdapterSketchFromWeights(bool with_group) {
RandomDataGenerator{kRows, kCols, 0}.Device(0).GenerateArrayInterface(
&storage);
MetaInfo info;
Context ctx;
auto& h_weights = info.weights_.HostVector();
if (with_group) {
h_weights.resize(kGroups);
@@ -563,7 +564,7 @@ void TestAdapterSketchFromWeights(bool with_group) {
for (size_t i = 0; i < kGroups; ++i) {
groups[i] = kRows / kGroups;
}
info.SetInfo("group", groups.data(), DataType::kUInt32, kGroups);
info.SetInfo(ctx, "group", groups.data(), DataType::kUInt32, kGroups);
}
info.weights_.SetDevice(0);
@@ -582,10 +583,10 @@ void TestAdapterSketchFromWeights(bool with_group) {
auto dmat = GetDMatrixFromData(storage.HostVector(), kRows, kCols);
if (with_group) {
dmat->Info().SetInfo("group", groups.data(), DataType::kUInt32, kGroups);
dmat->Info().SetInfo(ctx, "group", groups.data(), DataType::kUInt32, kGroups);
}
dmat->Info().SetInfo("weight", h_weights.data(), DataType::kFloat32, h_weights.size());
dmat->Info().SetInfo(ctx, "weight", h_weights.data(), DataType::kFloat32, h_weights.size());
dmat->Info().num_col_ = kCols;
dmat->Info().num_row_ = kRows;
ASSERT_EQ(cuts.Ptrs().size(), kCols + 1);