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Initial GPU support for the approx tree method. (#9414)

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This commit is contained in:
Jiaming Yuan
2023-07-31 15:50:28 +08:00
committed by GitHub
parent 8f0efb4ab3
commit 912e341d57
23 changed files with 639 additions and 360 deletions
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46
tests/cpp/tree/test_tree_policy.cc
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@@ -20,10 +20,11 @@ class TestGrowPolicy : public ::testing::Test {
true);
}
std::unique_ptr<Learner> TrainOneIter(std::string tree_method, std::string policy,
int32_t max_leaves, int32_t max_depth) {
std::unique_ptr<Learner> TrainOneIter(Context const* ctx, std::string tree_method,
std::string policy, int32_t max_leaves, int32_t max_depth) {
std::unique_ptr<Learner> learner{Learner::Create({this->Xy_})};
learner->SetParam("tree_method", tree_method);
learner->SetParam("device", ctx->DeviceName());
if (max_leaves >= 0) {
learner->SetParam("max_leaves", std::to_string(max_leaves));
}
@@ -63,7 +64,7 @@ class TestGrowPolicy : public ::testing::Test {
if (max_leaves == 0 && max_depth == 0) {
// unconstrainted
if (tree_method != "gpu_hist") {
if (ctx->IsCPU()) {
// GPU pre-allocates for all nodes.
learner->UpdateOneIter(0, Xy_);
}
@@ -86,23 +87,23 @@ class TestGrowPolicy : public ::testing::Test {
return learner;
}
void TestCombination(std::string tree_method) {
void TestCombination(Context const* ctx, std::string tree_method) {
for (auto policy : {"depthwise", "lossguide"}) {
// -1 means default
for (auto leaves : {-1, 0, 3}) {
for (auto depth : {-1, 0, 3}) {
this->TrainOneIter(tree_method, policy, leaves, depth);
this->TrainOneIter(ctx, tree_method, policy, leaves, depth);
}
}
}
}
void TestTreeGrowPolicy(std::string tree_method, std::string policy) {
void TestTreeGrowPolicy(Context const* ctx, std::string tree_method, std::string policy) {
{
/**
* max_leaves
*/
auto learner = this->TrainOneIter(tree_method, policy, 16, -1);
auto learner = this->TrainOneIter(ctx, tree_method, policy, 16, -1);
Json model{Object{}};
learner->SaveModel(&model);
@@ -115,7 +116,7 @@ class TestGrowPolicy : public ::testing::Test {
/**
* max_depth
*/
auto learner = this->TrainOneIter(tree_method, policy, -1, 3);
auto learner = this->TrainOneIter(ctx, tree_method, policy, -1, 3);
Json model{Object{}};
learner->SaveModel(&model);
@@ -133,25 +134,36 @@ class TestGrowPolicy : public ::testing::Test {
};
TEST_F(TestGrowPolicy, Approx) {
this->TestTreeGrowPolicy("approx", "depthwise");
this->TestTreeGrowPolicy("approx", "lossguide");
Context ctx;
this->TestTreeGrowPolicy(&ctx, "approx", "depthwise");
this->TestTreeGrowPolicy(&ctx, "approx", "lossguide");
this->TestCombination("approx");
this->TestCombination(&ctx, "approx");
}
TEST_F(TestGrowPolicy, Hist) {
this->TestTreeGrowPolicy("hist", "depthwise");
this->TestTreeGrowPolicy("hist", "lossguide");
Context ctx;
this->TestTreeGrowPolicy(&ctx, "hist", "depthwise");
this->TestTreeGrowPolicy(&ctx, "hist", "lossguide");
this->TestCombination("hist");
this->TestCombination(&ctx, "hist");
}
#if defined(XGBOOST_USE_CUDA)
TEST_F(TestGrowPolicy, GpuHist) {
this->TestTreeGrowPolicy("gpu_hist", "depthwise");
this->TestTreeGrowPolicy("gpu_hist", "lossguide");
auto ctx = MakeCUDACtx(0);
this->TestTreeGrowPolicy(&ctx, "hist", "depthwise");
this->TestTreeGrowPolicy(&ctx, "hist", "lossguide");
this->TestCombination("gpu_hist");
this->TestCombination(&ctx, "hist");
}
TEST_F(TestGrowPolicy, GpuApprox) {
auto ctx = MakeCUDACtx(0);
this->TestTreeGrowPolicy(&ctx, "approx", "depthwise");
this->TestTreeGrowPolicy(&ctx, "approx", "lossguide");
this->TestCombination(&ctx, "approx");
}
#endif // defined(XGBOOST_USE_CUDA)
} // namespace xgboost