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

refactor tests to get rid of duplication (#4358)

Browse Source 
* refactor tests to get rid of duplication

* address review comments
This commit is contained in:
Rong Ou
2019-04-12 00:21:48 -07:00
committed by Philip Hyunsu Cho
parent 3078b5944d
commit f4521bf6aa
5 changed files with 50 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files

41
tests/cpp/predictor/test_cpu_predictor.cc
View File

@@ -9,14 +9,7 @@ TEST(cpu_predictor, Test) {
std::unique_ptr<Predictor> cpu_predictor =
std::unique_ptr<Predictor>(Predictor::Create("cpu_predictor"));
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
(*trees.back())[0].SetLeaf(1.5f);
(*trees.back()).Stat(0).sum_hess = 1.0f;
gbm::GBTreeModel model(0.5);
model.CommitModel(std::move(trees), 0);
model.param.num_output_group = 1;
model.base_margin = 0;
gbm::GBTreeModel model = CreateTestModel();
int n_row = 5;
int n_col = 5;
@@ -62,34 +55,16 @@ TEST(cpu_predictor, Test) {
}
TEST(cpu_predictor, ExternalMemoryTest) {
// Create sufficiently large data to make two row pages
dmlc::TemporaryDirectory tempdir;
const std::string tmp_file = tempdir.path + "/big.libsvm";
CreateBigTestData(tmp_file, 12);
xgboost::DMatrix *dmat = xgboost::DMatrix::Load(
tmp_file + "#" + tmp_file + ".cache", true, false, "auto", 64UL);
EXPECT_TRUE(FileExists(tmp_file + ".cache.row.page"));
int64_t batche_count = 0;
for (const auto &batch : dmat->GetRowBatches()) {
batche_count++;
}
EXPECT_EQ(batche_count, 2);
std::unique_ptr<DMatrix> dmat = CreateSparsePageDMatrix();
std::unique_ptr<Predictor> cpu_predictor =
std::unique_ptr<Predictor>(Predictor::Create("cpu_predictor"));
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
(*trees.back())[0].SetLeaf(1.5f);
(*trees.back()).Stat(0).sum_hess = 1.0f;
gbm::GBTreeModel model(0.5);
model.CommitModel(std::move(trees), 0);
model.param.num_output_group = 1;
model.base_margin = 0;
gbm::GBTreeModel model = CreateTestModel();
// Test predict batch
HostDeviceVector<float> out_predictions;
cpu_predictor->PredictBatch(dmat, &out_predictions, model, 0);
cpu_predictor->PredictBatch(dmat.get(), &out_predictions, model, 0);
std::vector<float> &out_predictions_h = out_predictions.HostVector();
EXPECT_EQ(out_predictions.Size(), dmat->Info().num_row_);
for (const auto& v : out_predictions_h) {
@@ -98,7 +73,7 @@ TEST(cpu_predictor, ExternalMemoryTest) {
// Test predict leaf
std::vector<float> leaf_out_predictions;
cpu_predictor->PredictLeaf(dmat, &leaf_out_predictions, model);
cpu_predictor->PredictLeaf(dmat.get(), &leaf_out_predictions, model);
EXPECT_EQ(leaf_out_predictions.size(), dmat->Info().num_row_);
for (const auto& v : leaf_out_predictions) {
ASSERT_EQ(v, 0);
@@ -106,7 +81,7 @@ TEST(cpu_predictor, ExternalMemoryTest) {
// Test predict contribution
std::vector<float> out_contribution;
cpu_predictor->PredictContribution(dmat, &out_contribution, model);
cpu_predictor->PredictContribution(dmat.get(), &out_contribution, model);
EXPECT_EQ(out_contribution.size(), dmat->Info().num_row_);
for (const auto& v : out_contribution) {
ASSERT_EQ(v, 1.5);
@@ -114,12 +89,10 @@ TEST(cpu_predictor, ExternalMemoryTest) {
// Test predict contribution (approximate method)
std::vector<float> out_contribution_approximate;
cpu_predictor->PredictContribution(dmat, &out_contribution_approximate, model, true);
cpu_predictor->PredictContribution(dmat.get(), &out_contribution_approximate, model, true);
EXPECT_EQ(out_contribution_approximate.size(), dmat->Info().num_row_);
for (const auto& v : out_contribution_approximate) {
ASSERT_EQ(v, 1.5);
}
delete dmat;
}
} // namespace xgboost

16
tests/cpp/predictor/test_gpu_predictor.cu
View File

@@ -33,13 +33,7 @@ TEST(gpu_predictor, Test) {
gpu_predictor->Init({}, {});
cpu_predictor->Init({}, {});
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree()));
(*trees.back())[0].SetLeaf(1.5f);
(*trees.back()).Stat(0).sum_hess = 1.0f;
gbm::GBTreeModel model(0.5);
model.CommitModel(std::move(trees), 0);
model.param.num_output_group = 1;
gbm::GBTreeModel model = CreateTestModel();
int n_row = 5;
int n_col = 5;
@@ -181,13 +175,7 @@ TEST(gpu_predictor, MGPU_Test) {
int n_row = i, n_col = i;
auto dmat = CreateDMatrix(n_row, n_col, 0);
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree()));
(*trees.back())[0].SetLeaf(1.5f);
(*trees.back()).Stat(0).sum_hess = 1.0f;
gbm::GBTreeModel model(0.5);
model.CommitModel(std::move(trees), 0);
model.param.num_output_group = 1;
gbm::GBTreeModel model = CreateTestModel();
// Test predict batch
HostDeviceVector<float> gpu_out_predictions;