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Use ellpack for prediction only when sparsepage doesn't exist. (#5504)

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This commit is contained in:
Jiaming Yuan
2020-04-10 12:15:46 +08:00
committed by GitHub
parent ad826e913f
commit 6671b42dd4
35 changed files with 166 additions and 116 deletions
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6
tests/cpp/helpers.cc
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@@ -260,8 +260,8 @@ void RandomDataGenerator::GenerateCSR(
}
std::shared_ptr<DMatrix>
RandomDataGenerator::GenerateDMatix(bool with_label, bool float_label,
size_t classes) const {
RandomDataGenerator::GenerateDMatrix(bool with_label, bool float_label,
size_t classes) const {
HostDeviceVector<float> data;
HostDeviceVector<bst_row_t> rptrs;
HostDeviceVector<bst_feature_t> columns;
@@ -399,7 +399,7 @@ std::unique_ptr<GradientBooster> CreateTrainedGBM(
std::unique_ptr<GradientBooster> gbm {
GradientBooster::Create(name, generic_param, learner_model_param)};
gbm->Configure(kwargs);
auto p_dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatix();
auto p_dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
std::vector<float> labels(kRows);
for (size_t i = 0; i < kRows; ++i) {