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Make HostDeviceVector single gpu only (#4773)

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* Make HostDeviceVector single gpu only
This commit is contained in:
Rong Ou
2019-08-25 14:51:13 -07:00
committed by Rory Mitchell
parent 41227d1933
commit 38ab79f889
54 changed files with 641 additions and 1621 deletions
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15
tests/cpp/test_learner.cc
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@@ -168,10 +168,9 @@ TEST(Learner, IO) {
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "auto"},
Arg{"predictor", "gpu_predictor"},
Arg{"n_gpus", "1"}});
Arg{"gpu_id", "0"}});
learner->UpdateOneIter(0, p_dmat.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 1);
dmlc::TemporaryDirectory tempdir;
const std::string fname = tempdir.path + "/model.bst";
@@ -185,7 +184,6 @@ TEST(Learner, IO) {
std::unique_ptr<dmlc::Stream> fi(dmlc::Stream::Create(fname.c_str(), "r"));
learner->Load(fi.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 0);
delete pp_dmat;
}
@@ -208,31 +206,27 @@ TEST(Learner, GPUConfiguration) {
Arg{"updater", "gpu_coord_descent"}});
learner->UpdateOneIter(0, p_dmat.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 1);
}
{
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "gpu_hist"}});
learner->UpdateOneIter(0, p_dmat.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 1);
}
{
// with CPU algorithm
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "hist"}});
learner->UpdateOneIter(0, p_dmat.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 0);
ASSERT_EQ(learner->GetGenericParameter().gpu_id, -1);
}
{
// with CPU algorithm, but `n_gpus` takes priority
// with CPU algorithm, but `gpu_id` takes priority
std::unique_ptr<Learner> learner {Learner::Create(mat)};
learner->SetParams({Arg{"tree_method", "hist"},
Arg{"n_gpus", "1"}});
Arg{"gpu_id", "0"}});
learner->UpdateOneIter(0, p_dmat.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 1);
}
{
// With CPU algorithm but GPU Predictor, this is to simulate when
@@ -243,7 +237,6 @@ TEST(Learner, GPUConfiguration) {
Arg{"predictor", "gpu_predictor"}});
learner->UpdateOneIter(0, p_dmat.get());
ASSERT_EQ(learner->GetGenericParameter().gpu_id, 0);
ASSERT_EQ(learner->GetGenericParameter().n_gpus, 1);
}
delete pp_dmat;