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Add tests for gpu_approx with column split and vertical federated #9553

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Sep 7, 2023
Merged

Add tests for gpu_approx with column split and vertical federated #9553

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5 changes: 5 additions & 0 deletions tests/cpp/plugin/test_federated_learner.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -120,6 +120,11 @@ TEST_P(VerticalFederatedLearnerTest, Hist) {
}

#if defined(XGBOOST_USE_CUDA)
TEST_P(VerticalFederatedLearnerTest, GPUApprox) {
std::string objective = GetParam();
this->Run("approx", "cuda:0", objective);
}

TEST_P(VerticalFederatedLearnerTest, GPUHist) {
std::string objective = GetParam();
this->Run("hist", "cuda:0", objective);
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60 changes: 55 additions & 5 deletions tests/cpp/tree/test_gpu_hist.cu
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Expand Up @@ -428,7 +428,7 @@ TEST(GpuHist, MaxDepth) {
}

namespace {
RegTree GetUpdatedTree(Context const* ctx, DMatrix* dmat) {
RegTree GetHistTree(Context const* ctx, DMatrix* dmat) {
ObjInfo task{ObjInfo::kRegression};
GPUHistMaker hist_maker{ctx, &task};
hist_maker.Configure(Args{});
Expand All @@ -446,15 +446,15 @@ RegTree GetUpdatedTree(Context const* ctx, DMatrix* dmat) {
return tree;
}

void VerifyColumnSplit(bst_row_t rows, bst_feature_t cols, RegTree const& expected_tree) {
void VerifyHistColumnSplit(bst_row_t rows, bst_feature_t cols, RegTree const& expected_tree) {
Context ctx(MakeCUDACtx(GPUIDX));

auto Xy = RandomDataGenerator{rows, cols, 0}.GenerateDMatrix(true);
auto const world_size = collective::GetWorldSize();
auto const rank = collective::GetRank();
std::unique_ptr<DMatrix> sliced{Xy->SliceCol(world_size, rank)};

RegTree tree = GetUpdatedTree(&ctx, sliced.get());
RegTree tree = GetHistTree(&ctx, sliced.get());

Json json{Object{}};
tree.SaveModel(&json);
Expand All @@ -472,8 +472,58 @@ TEST_F(MGPUHistTest, GPUHistColumnSplit) {

Context ctx(MakeCUDACtx(0));
auto dmat = RandomDataGenerator{kRows, kCols, 0}.GenerateDMatrix(true);
RegTree expected_tree = GetUpdatedTree(&ctx, dmat.get());
RegTree expected_tree = GetHistTree(&ctx, dmat.get());

DoTest(VerifyColumnSplit, kRows, kCols, expected_tree);
DoTest(VerifyHistColumnSplit, kRows, kCols, expected_tree);
}

namespace {
RegTree GetApproxTree(Context const* ctx, DMatrix* dmat) {
ObjInfo task{ObjInfo::kRegression};
GPUGlobalApproxMaker approx_maker{ctx, &task};
approx_maker.Configure(Args{});

TrainParam param;
param.UpdateAllowUnknown(Args{});

linalg::Matrix<GradientPair> gpair({dmat->Info().num_row_}, ctx->Ordinal());
gpair.Data()->Copy(GenerateRandomGradients(dmat->Info().num_row_));

std::vector<HostDeviceVector<bst_node_t>> position(1);
RegTree tree;
approx_maker.Update(&param, &gpair, dmat, common::Span<HostDeviceVector<bst_node_t>>{position},
{&tree});
return tree;
}

void VerifyApproxColumnSplit(bst_row_t rows, bst_feature_t cols, RegTree const& expected_tree) {
Context ctx(MakeCUDACtx(GPUIDX));

auto Xy = RandomDataGenerator{rows, cols, 0}.GenerateDMatrix(true);
auto const world_size = collective::GetWorldSize();
auto const rank = collective::GetRank();
std::unique_ptr<DMatrix> sliced{Xy->SliceCol(world_size, rank)};

RegTree tree = GetApproxTree(&ctx, sliced.get());

Json json{Object{}};
tree.SaveModel(&json);
Json expected_json{Object{}};
expected_tree.SaveModel(&expected_json);
ASSERT_EQ(json, expected_json);
}
} // anonymous namespace

class MGPUApproxTest : public BaseMGPUTest {};

TEST_F(MGPUApproxTest, GPUApproxColumnSplit) {
auto constexpr kRows = 32;
auto constexpr kCols = 16;

Context ctx(MakeCUDACtx(0));
auto dmat = RandomDataGenerator{kRows, kCols, 0}.GenerateDMatrix(true);
RegTree expected_tree = GetApproxTree(&ctx, dmat.get());

DoTest(VerifyApproxColumnSplit, kRows, kCols, expected_tree);
}
} // namespace xgboost::tree
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