Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

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

Browse Source
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
Download Patch File Download Diff File Expand all files Collapse all files

12
tests/cpp/test_learner.cc
View File

@@ -16,7 +16,7 @@ namespace xgboost {
TEST(Learner, Basic) {
using Arg = std::pair<std::string, std::string>;
auto args = {Arg("tree_method", "exact")};
auto mat_ptr = RandomDataGenerator{10, 10, 0.0f}.GenerateDMatix();
auto mat_ptr = RandomDataGenerator{10, 10, 0.0f}.GenerateDMatrix();
auto learner = std::unique_ptr<Learner>(Learner::Create({mat_ptr}));
learner->SetParams(args);
@@ -34,7 +34,7 @@ TEST(Learner, ParameterValidation) {
ConsoleLogger::Configure({{"verbosity", "2"}});
size_t constexpr kRows = 1;
size_t constexpr kCols = 1;
auto p_mat = RandomDataGenerator{kRows, kCols, 0}.GenerateDMatix();
auto p_mat = RandomDataGenerator{kRows, kCols, 0}.GenerateDMatrix();
auto learner = std::unique_ptr<Learner>(Learner::Create({p_mat}));
learner->SetParam("validate_parameters", "1");
@@ -56,7 +56,7 @@ TEST(Learner, CheckGroup) {
bst_feature_t constexpr kNumCols = 15;
std::shared_ptr<DMatrix> p_mat{
RandomDataGenerator{kNumRows, kNumCols, 0.0f}.GenerateDMatix()};
RandomDataGenerator{kNumRows, kNumCols, 0.0f}.GenerateDMatrix()};
std::vector<bst_float> weight(kNumGroups);
std::vector<bst_int> group(kNumGroups);
group[0] = 2;
@@ -137,7 +137,7 @@ TEST(Learner, JsonModelIO) {
int32_t constexpr kIters = 4;
std::shared_ptr<DMatrix> p_dmat{
RandomDataGenerator{kRows, 10, 0}.GenerateDMatix()};
RandomDataGenerator{kRows, 10, 0}.GenerateDMatrix()};
p_dmat->Info().labels_.Resize(kRows);
CHECK_NE(p_dmat->Info().num_col_, 0);
@@ -179,7 +179,7 @@ TEST(Learner, JsonModelIO) {
TEST(Learner, BinaryModelIO) {
size_t constexpr kRows = 8;
int32_t constexpr kIters = 4;
auto p_dmat = RandomDataGenerator{kRows, 10, 0}.GenerateDMatix();
auto p_dmat = RandomDataGenerator{kRows, 10, 0}.GenerateDMatrix();
p_dmat->Info().labels_.Resize(kRows);
std::unique_ptr<Learner> learner{Learner::Create({p_dmat})};
@@ -213,7 +213,7 @@ TEST(Learner, BinaryModelIO) {
TEST(Learner, GPUConfiguration) {
using Arg = std::pair<std::string, std::string>;
size_t constexpr kRows = 10;
auto p_dmat = RandomDataGenerator(kRows, 10, 0).GenerateDMatix();
auto p_dmat = RandomDataGenerator(kRows, 10, 0).GenerateDMatrix();
std::vector<std::shared_ptr<DMatrix>> mat {p_dmat};
std::vector<bst_float> labels(kRows);
for (size_t i = 0; i < labels.size(); ++i) {