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GPUTreeShap (#6038)

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This commit is contained in:
Rory Mitchell
2020-08-25 12:47:41 +12:00
committed by GitHub
parent b3193052b3
commit 9a4e8b1d81
9 changed files with 266 additions and 62 deletions
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56
tests/cpp/predictor/test_gpu_predictor.cu
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@@ -163,5 +163,61 @@ TEST(GPUPredictor, MGPU_InplacePredict) { // NOLINT
TEST(GpuPredictor, LesserFeatures) {
TestPredictionWithLesserFeatures("gpu_predictor");
}
// Very basic test of empty model
TEST(GPUPredictor, ShapStump) {
cudaSetDevice(0);
LearnerModelParam param;
param.num_feature = 1;
param.num_output_group = 1;
param.base_score = 0.5;
gbm::GBTreeModel model(&param);
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
model.CommitModel(std::move(trees), 0);
auto gpu_lparam = CreateEmptyGenericParam(0);
std::unique_ptr<Predictor> gpu_predictor =
std::unique_ptr<Predictor>(Predictor::Create("gpu_predictor", &gpu_lparam));
gpu_predictor->Configure({});
std::vector<float > phis;
auto dmat = RandomDataGenerator(3, 1, 0).GenerateDMatrix();
gpu_predictor->PredictContribution(dmat.get(), &phis, model);
EXPECT_EQ(phis[0], 0.0);
EXPECT_EQ(phis[1], param.base_score);
EXPECT_EQ(phis[2], 0.0);
EXPECT_EQ(phis[3], param.base_score);
EXPECT_EQ(phis[4], 0.0);
EXPECT_EQ(phis[5], param.base_score);
}
TEST(GPUPredictor, Shap) {
LearnerModelParam param;
param.num_feature = 1;
param.num_output_group = 1;
param.base_score = 0.5;
gbm::GBTreeModel model(&param);
std::vector<std::unique_ptr<RegTree>> trees;
trees.push_back(std::unique_ptr<RegTree>(new RegTree));
trees[0]->ExpandNode(0, 0, 0.5, true, 1.0, -1.0, 1.0, 0.0, 5.0, 2.0, 3.0);
model.CommitModel(std::move(trees), 0);
auto gpu_lparam = CreateEmptyGenericParam(0);
auto cpu_lparam = CreateEmptyGenericParam(-1);
std::unique_ptr<Predictor> gpu_predictor =
std::unique_ptr<Predictor>(Predictor::Create("gpu_predictor", &gpu_lparam));
std::unique_ptr<Predictor> cpu_predictor =
std::unique_ptr<Predictor>(Predictor::Create("cpu_predictor", &cpu_lparam));
gpu_predictor->Configure({});
cpu_predictor->Configure({});
std::vector<float > phis;
std::vector<float > cpu_phis;
auto dmat = RandomDataGenerator(3, 1, 0).GenerateDMatrix();
gpu_predictor->PredictContribution(dmat.get(), &phis, model);
cpu_predictor->PredictContribution(dmat.get(), &cpu_phis, model);
for(auto i = 0ull; i < phis.size(); i++)
{
EXPECT_NEAR(cpu_phis[i], phis[i], 1e-3);
}
}
} // namespace predictor
} // namespace xgboost