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Add support inference on SYCL devices (#9800)

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---------

Co-authored-by: Dmitry Razdoburdin <>
Co-authored-by: Nikolay Petrov <nikolay.a.petrov@intel.com>
Co-authored-by: Alexandra <alexandra.epanchinzeva@intel.com>
This commit is contained in:
Dmitry Razdoburdin
2023-12-04 09:15:57 +01:00
committed by GitHub
parent 7196c9d95e
commit 381f1d3dc9
31 changed files with 1369 additions and 1294 deletions
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92
tests/cpp/predictor/test_cpu_predictor.cc
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@@ -18,92 +18,17 @@
namespace xgboost {
namespace {
void TestBasic(DMatrix* dmat) {
Context ctx;
std::unique_ptr<Predictor> cpu_predictor =
std::unique_ptr<Predictor>(Predictor::Create("cpu_predictor", &ctx));
size_t const kRows = dmat->Info().num_row_;
size_t const kCols = dmat->Info().num_col_;
LearnerModelParam mparam{MakeMP(kCols, .0, 1)};
ctx.UpdateAllowUnknown(Args{});
gbm::GBTreeModel model = CreateTestModel(&mparam, &ctx);
// Test predict batch
PredictionCacheEntry out_predictions;
cpu_predictor->InitOutPredictions(dmat->Info(), &out_predictions.predictions, model);
cpu_predictor->PredictBatch(dmat, &out_predictions, model, 0);
std::vector<float>& out_predictions_h = out_predictions.predictions.HostVector();
for (size_t i = 0; i < out_predictions.predictions.Size(); i++) {
ASSERT_EQ(out_predictions_h[i], 1.5);
}
// Test predict instance
auto const& batch = *dmat->GetBatches<xgboost::SparsePage>().begin();
auto page = batch.GetView();
for (size_t i = 0; i < batch.Size(); i++) {
std::vector<float> instance_out_predictions;
cpu_predictor->PredictInstance(page[i], &instance_out_predictions, model, 0,
dmat->Info().IsColumnSplit());
ASSERT_EQ(instance_out_predictions[0], 1.5);
}
// Test predict leaf
HostDeviceVector<float> leaf_out_predictions;
cpu_predictor->PredictLeaf(dmat, &leaf_out_predictions, model);
auto const& h_leaf_out_predictions = leaf_out_predictions.ConstHostVector();
for (auto v : h_leaf_out_predictions) {
ASSERT_EQ(v, 0);
}
if (dmat->Info().IsColumnSplit()) {
// Predict contribution is not supported for column split.
return;
}
// Test predict contribution
HostDeviceVector<float> out_contribution_hdv;
auto& out_contribution = out_contribution_hdv.HostVector();
cpu_predictor->PredictContribution(dmat, &out_contribution_hdv, model);
ASSERT_EQ(out_contribution.size(), kRows * (kCols + 1));
for (size_t i = 0; i < out_contribution.size(); ++i) {
auto const& contri = out_contribution[i];
// shift 1 for bias, as test tree is a decision dump, only global bias is
// filled with LeafValue().
if ((i + 1) % (kCols + 1) == 0) {
ASSERT_EQ(out_contribution.back(), 1.5f);
} else {
ASSERT_EQ(contri, 0);
}
}
// Test predict contribution (approximate method)
cpu_predictor->PredictContribution(dmat, &out_contribution_hdv, model, 0, nullptr, true);
for (size_t i = 0; i < out_contribution.size(); ++i) {
auto const& contri = out_contribution[i];
// shift 1 for bias, as test tree is a decision dump, only global bias is
// filled with LeafValue().
if ((i + 1) % (kCols + 1) == 0) {
ASSERT_EQ(out_contribution.back(), 1.5f);
} else {
ASSERT_EQ(contri, 0);
}
}
}
} // anonymous namespace
TEST(CpuPredictor, Basic) {
Context ctx;
size_t constexpr kRows = 5;
size_t constexpr kCols = 5;
auto dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
TestBasic(dmat.get());
TestBasic(dmat.get(), &ctx);
}
namespace {
void TestColumnSplit() {
Context ctx;
size_t constexpr kRows = 5;
size_t constexpr kCols = 5;
auto dmat = RandomDataGenerator(kRows, kCols, 0).GenerateDMatrix();
@@ -112,7 +37,7 @@ void TestColumnSplit() {
auto const rank = collective::GetRank();
dmat = std::unique_ptr<DMatrix>{dmat->SliceCol(world_size, rank)};
TestBasic(dmat.get());
TestBasic(dmat.get(), &ctx);
}
} // anonymous namespace
@@ -132,10 +57,11 @@ TEST(CpuPredictor, IterationRangeColmnSplit) {
}
TEST(CpuPredictor, ExternalMemory) {
Context ctx;
size_t constexpr kPageSize = 64, kEntriesPerCol = 3;
size_t constexpr kEntries = kPageSize * kEntriesPerCol * 2;
std::unique_ptr<DMatrix> dmat = CreateSparsePageDMatrix(kEntries);
TestBasic(dmat.get());
TestBasic(dmat.get(), &ctx);
}
TEST(CpuPredictor, InplacePredict) {
@@ -235,12 +161,14 @@ TEST(CPUPredictor, CategoricalPredictionColumnSplit) {
}
TEST(CPUPredictor, CategoricalPredictLeaf) {
TestCategoricalPredictLeaf(false, false);
Context ctx;
TestCategoricalPredictLeaf(&ctx, false);
}
TEST(CPUPredictor, CategoricalPredictLeafColumnSplit) {
auto constexpr kWorldSize = 2;
RunWithInMemoryCommunicator(kWorldSize, TestCategoricalPredictLeaf, false, true);
Context ctx;
RunWithInMemoryCommunicator(kWorldSize, TestCategoricalPredictLeaf, &ctx, true);
}
TEST(CpuPredictor, UpdatePredictionCache) {