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Make `HistCutMatrix::Init' be aware of groups. (#4115)

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* Add checks for group size.
* Simple docs.
* Search group index during hist cut matrix initialization.

Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan
2019-02-16 04:39:41 +08:00
committed by GitHub
parent 37ddfd7d6e
commit 754fe8142b
6 changed files with 188 additions and 22 deletions
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65
tests/cpp/test_learner.cc
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@@ -6,9 +6,9 @@
namespace xgboost {
TEST(learner, Test) {
typedef std::pair<std::string, std::string> arg;
auto args = {arg("tree_method", "exact")};
TEST(Learner, Basic) {
typedef std::pair<std::string, std::string> Arg;
auto args = {Arg("tree_method", "exact")};
auto mat_ptr = CreateDMatrix(10, 10, 0);
std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {*mat_ptr};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
@@ -17,33 +17,33 @@ TEST(learner, Test) {
delete mat_ptr;
}
TEST(learner, SelectTreeMethod) {
using arg = std::pair<std::string, std::string>;
TEST(Learner, SelectTreeMethod) {
using Arg = std::pair<std::string, std::string>;
auto mat_ptr = CreateDMatrix(10, 10, 0);
std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {*mat_ptr};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
// Test if `tree_method` can be set
learner->Configure({arg("tree_method", "approx")});
learner->Configure({Arg("tree_method", "approx")});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_histmaker,prune");
learner->Configure({arg("tree_method", "exact")});
learner->Configure({Arg("tree_method", "exact")});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_colmaker,prune");
learner->Configure({arg("tree_method", "hist")});
learner->Configure({Arg("tree_method", "hist")});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_quantile_histmaker");
learner->Configure({arg{"booster", "dart"}, arg{"tree_method", "hist"}});
learner->Configure({Arg{"booster", "dart"}, Arg{"tree_method", "hist"}});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_quantile_histmaker");
#ifdef XGBOOST_USE_CUDA
learner->Configure({arg("tree_method", "gpu_exact")});
learner->Configure({Arg("tree_method", "gpu_exact")});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_gpu,prune");
learner->Configure({arg("tree_method", "gpu_hist")});
learner->Configure({Arg("tree_method", "gpu_hist")});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_gpu_hist");
learner->Configure({arg{"booster", "dart"}, arg{"tree_method", "gpu_hist"}});
learner->Configure({Arg{"booster", "dart"}, Arg{"tree_method", "gpu_hist"}});
ASSERT_EQ(learner->GetConfigurationArguments().at("updater"),
"grow_gpu_hist");
#endif
@@ -51,4 +51,45 @@ TEST(learner, SelectTreeMethod) {
delete mat_ptr;
}
TEST(Learner, CheckGroup) {
using Arg = std::pair<std::string, std::string>;
size_t constexpr kNumGroups = 4;
size_t constexpr kNumRows = 17;
size_t constexpr kNumCols = 15;
auto pp_mat = CreateDMatrix(kNumRows, kNumCols, 0);
auto& p_mat = *pp_mat;
std::vector<bst_float> weight(kNumGroups);
std::vector<bst_int> group(kNumGroups);
group[0] = 2;
group[1] = 3;
group[2] = 7;
group[3] = 5;
std::vector<bst_float> labels (kNumRows);
for (size_t i = 0; i < kNumRows; ++i) {
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);
std::vector<std::shared_ptr<xgboost::DMatrix>> mat = {p_mat};
auto learner = std::unique_ptr<Learner>(Learner::Create(mat));
learner->Configure({Arg{"objective", "rank:pairwise"}});
learner->InitModel();
EXPECT_NO_THROW(learner->UpdateOneIter(0, p_mat.get()));
group.resize(kNumGroups+1);
group[3] = 4;
group[4] = 1;
p_mat->Info().SetInfo("group", group.data(), DataType::kUInt32, kNumGroups+1);
EXPECT_ANY_THROW(learner->UpdateOneIter(0, p_mat.get()));
delete pp_mat;
}
} // namespace xgboost