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Add travis sanitizers tests. (#3557)

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* Add travis sanitizers tests.

* Add gcc-7 in Travis.
* Add SANITIZER_PATH for CMake.
* Enable sanitizer tests in Travis.

* Fix memory leaks in tests.

* Fix all memory leaks reported by Address Sanitizer.
* tests/cpp/helpers.h/CreateDMatrix now returns raw pointer.
This commit is contained in:
trivialfis
2018-08-19 12:40:30 +08:00
committed by Rory Mitchell
parent 983cb0b374
commit cf2d86a4f6
30 changed files with 221 additions and 76 deletions
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12
tests/cpp/predictor/test_cpu_predictor.cc
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@@ -25,14 +25,14 @@ TEST(cpu_predictor, Test) {
// Test predict batch
HostDeviceVector<float> out_predictions;
cpu_predictor->PredictBatch(dmat.get(), &out_predictions, model, 0);
cpu_predictor->PredictBatch((*dmat).get(), &out_predictions, model, 0);
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);
}
// Test predict instance
auto batch = dmat->RowIterator()->Value();
auto batch = (*dmat)->RowIterator()->Value();
for (int i = 0; i < batch.Size(); i++) {
std::vector<float> instance_out_predictions;
cpu_predictor->PredictInstance(batch[i], &instance_out_predictions, model);
@@ -41,22 +41,24 @@ TEST(cpu_predictor, Test) {
// Test predict leaf
std::vector<float> leaf_out_predictions;
cpu_predictor->PredictLeaf(dmat.get(), &leaf_out_predictions, model);
cpu_predictor->PredictLeaf((*dmat).get(), &leaf_out_predictions, model);
for (int i = 0; i < leaf_out_predictions.size(); i++) {
ASSERT_EQ(leaf_out_predictions[i], 0);
}
// Test predict contribution
std::vector<float> out_contribution;
cpu_predictor->PredictContribution(dmat.get(), &out_contribution, model);
cpu_predictor->PredictContribution((*dmat).get(), &out_contribution, model);
for (int i = 0; i < out_contribution.size(); i++) {
ASSERT_EQ(out_contribution[i], 1.5);
}
// Test predict contribution (approximate method)
cpu_predictor->PredictContribution(dmat.get(), &out_contribution, model, true);
cpu_predictor->PredictContribution((*dmat).get(), &out_contribution, model, true);
for (int i = 0; i < out_contribution.size(); i++) {
ASSERT_EQ(out_contribution[i], 1.5);
}
delete dmat;
}
} // namespace xgboost

16
tests/cpp/predictor/test_gpu_predictor.cu
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@@ -35,8 +35,8 @@ TEST(gpu_predictor, Test) {
// Test predict batch
HostDeviceVector<float> gpu_out_predictions;
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);
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.HostVector();
std::vector<float>& cpu_out_predictions_h = cpu_out_predictions.HostVector();
float abs_tolerance = 0.001;
@@ -45,7 +45,7 @@ TEST(gpu_predictor, Test) {
abs_tolerance);
}
// Test predict instance
auto batch = dmat->RowIterator()->Value();
auto batch = (*dmat)->RowIterator()->Value();
for (int i = 0; i < batch.Size(); i++) {
std::vector<float> gpu_instance_out_predictions;
std::vector<float> cpu_instance_out_predictions;
@@ -59,8 +59,8 @@ TEST(gpu_predictor, Test) {
// Test predict leaf
std::vector<float> gpu_leaf_out_predictions;
std::vector<float> cpu_leaf_out_predictions;
cpu_predictor->PredictLeaf(dmat.get(), &cpu_leaf_out_predictions, model);
gpu_predictor->PredictLeaf(dmat.get(), &gpu_leaf_out_predictions, model);
cpu_predictor->PredictLeaf((*dmat).get(), &cpu_leaf_out_predictions, model);
gpu_predictor->PredictLeaf((*dmat).get(), &gpu_leaf_out_predictions, model);
for (int i = 0; i < gpu_leaf_out_predictions.size(); i++) {
ASSERT_EQ(gpu_leaf_out_predictions[i], cpu_leaf_out_predictions[i]);
}
@@ -68,11 +68,13 @@ TEST(gpu_predictor, Test) {
// Test predict contribution
std::vector<float> gpu_out_contribution;
std::vector<float> cpu_out_contribution;
cpu_predictor->PredictContribution(dmat.get(), &cpu_out_contribution, model);
gpu_predictor->PredictContribution(dmat.get(), &gpu_out_contribution, model);
cpu_predictor->PredictContribution((*dmat).get(), &cpu_out_contribution, model);
gpu_predictor->PredictContribution((*dmat).get(), &gpu_out_contribution, model);
for (int i = 0; i < gpu_out_contribution.size(); i++) {
ASSERT_EQ(gpu_out_contribution[i], cpu_out_contribution[i]);
}
delete dmat;
}
} // namespace predictor
} // namespace xgboost