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Fix calling GPU predictor (#4836)

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* Fix calling GPU predictor
This commit is contained in:
Jiaming Yuan
2019-09-05 19:09:38 -04:00
committed by GitHub
parent 52d44e07fe
commit a5f232feb8
5 changed files with 85 additions and 5 deletions
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66
tests/cpp/gbm/test_gbtree.cc
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@@ -1,5 +1,8 @@
#include <gtest/gtest.h>
#include <dmlc/filesystem.h>
#include <xgboost/generic_parameters.h>
#include "xgboost/learner.h"
#include "../helpers.h"
#include "../../../src/gbm/gbtree.h"
@@ -43,4 +46,67 @@ TEST(GBTree, SelectTreeMethod) {
ASSERT_EQ(tparam.predictor, "gpu_predictor");
#endif
}
#ifdef XGBOOST_USE_CUDA
TEST(GBTree, ChoosePredictor) {
size_t constexpr kNumRows = 17;
size_t constexpr kCols = 15;
auto pp_mat = CreateDMatrix(kNumRows, kCols, 0);
auto& p_mat = *pp_mat;
std::vector<bst_float> labels (kNumRows);
for (size_t i = 0; i < kNumRows; ++i) {
labels[i] = i % 2;
}
p_mat->Info().SetInfo("label", labels.data(), DataType::kFloat32, kNumRows);
std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {p_mat};
std::string n_feat = std::to_string(kCols);
Args args {{"tree_method", "approx"}, {"num_feature", n_feat}};
GenericParameter generic_param;
generic_param.InitAllowUnknown(Args{{"gpu_id", "0"}});
auto& data = (*(p_mat->GetBatches<SparsePage>().begin())).data;
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
learner->SetParams(Args{{"tree_method", "gpu_hist"}});
for (size_t i = 0; i < 4; ++i) {
learner->UpdateOneIter(i, p_mat.get());
}
ASSERT_TRUE(data.HostCanWrite());
dmlc::TemporaryDirectory tempdir;
const std::string fname = tempdir.path + "/model_para.bst";
{
std::unique_ptr<dmlc::Stream> fo(dmlc::Stream::Create(fname.c_str(), "w"));
learner->Save(fo.get());
}
// a new learner
learner = std::unique_ptr<Learner>(Learner::Create(mat));
{
std::unique_ptr<dmlc::Stream> fi(dmlc::Stream::Create(fname.c_str(), "r"));
learner->Load(fi.get());
}
learner->SetParams(Args{{"tree_method", "gpu_hist"}, {"gpu_id", "0"}});
for (size_t i = 0; i < 4; ++i) {
learner->UpdateOneIter(i, p_mat.get());
}
ASSERT_TRUE(data.HostCanWrite());
// pull data into device.
data = HostDeviceVector<Entry>(data.HostVector(), 0);
data.DeviceSpan();
ASSERT_FALSE(data.HostCanWrite());
// another new learner
learner = std::unique_ptr<Learner>(Learner::Create(mat));
learner->SetParams(Args{{"tree_method", "gpu_hist"}, {"gpu_id", "0"}});
for (size_t i = 0; i < 4; ++i) {
learner->UpdateOneIter(i, p_mat.get());
}
// data is not pulled back into host
ASSERT_FALSE(data.HostCanWrite());
}
#endif
} // namespace xgboost