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

Clang-tidy static analysis (#3222)

Browse Source 
* Clang-tidy static analysis

* Modernise checks

* Google coding standard checks

* Identifier renaming according to Google style
This commit is contained in:
Rory Mitchell
2018-04-19 18:57:13 +12:00
committed by GitHub
parent 3242b0a378
commit ccf80703ef
97 changed files with 3407 additions and 3354 deletions
Download Patch File Download Diff File Expand all files Collapse all files

8
tests/cpp/predictor/test_cpu_predictor.cc
View File

@@ -11,8 +11,8 @@ TEST(cpu_predictor, Test) {
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
trees.back()->InitModel();
(*trees.back())[0].set_leaf(1.5f);
(*trees.back()).stat(0).sum_hess = 1.0f;
(*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;
@@ -26,8 +26,8 @@ TEST(cpu_predictor, Test) {
// Test predict batch
HostDeviceVector<float> out_predictions;
cpu_predictor->PredictBatch(dmat.get(), &out_predictions, model, 0);
std::vector<float>& out_predictions_h = out_predictions.data_h();
for (int i = 0; i < out_predictions.size(); i++) {
std::vector<float>& out_predictions_h = out_predictions.HostVector();
for (int i = 0; i < out_predictions.Size(); i++) {
ASSERT_EQ(out_predictions_h[i], 1.5);
}

10
tests/cpp/predictor/test_gpu_predictor.cu
View File

@@ -21,8 +21,8 @@ TEST(gpu_predictor, Test) {
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree()));
trees.back()->InitModel();
(*trees.back())[0].set_leaf(1.5f);
(*trees.back()).stat(0).sum_hess = 1.0f;
(*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;
@@ -37,10 +37,10 @@ TEST(gpu_predictor, Test) {
HostDeviceVector<float> cpu_out_predictions;
gpu_predictor->PredictBatch(dmat.get(), &gpu_out_predictions, model, 0);
cpu_predictor->PredictBatch(dmat.get(), &cpu_out_predictions, model, 0);
std::vector<float>& gpu_out_predictions_h = gpu_out_predictions.data_h();
std::vector<float>& cpu_out_predictions_h = cpu_out_predictions.data_h();
std::vector<float>& gpu_out_predictions_h = gpu_out_predictions.HostVector();
std::vector<float>& cpu_out_predictions_h = cpu_out_predictions.HostVector();
float abs_tolerance = 0.001;
for (int i = 0; i < gpu_out_predictions.size(); i++) {
for (int i = 0; i < gpu_out_predictions.Size(); i++) {
ASSERT_LT(std::abs(gpu_out_predictions_h[i] - cpu_out_predictions_h[i]),
abs_tolerance);
}