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/**
* Copyright 2019-2024, XGBoost Contributors
*/
#include <xgboost/data.h> // for DMatrix
#include "../../../src/common/compressed_iterator.h"
#include "../../../src/data/ellpack_page.cuh"
#include "../../../src/data/ellpack_page.h"
#include "../../../src/data/sparse_page_dmatrix.h"
#include "../../../src/tree/param.h" // TrainParam
#include "../filesystem.h" // dmlc::TemporaryDirectory
#include "../helpers.h"
namespace xgboost {
TEST(SparsePageDMatrix, EllpackPage) {
auto ctx = MakeCUDACtx(0);
auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
dmlc::TemporaryDirectory tempdir;
const std::string tmp_file = tempdir.path + "/simple.libsvm";
CreateSimpleTestData(tmp_file);
DMatrix* dmat = DMatrix::Load(tmp_file + "?format=libsvm" + "#" + tmp_file + ".cache");
// Loop over the batches and assert the data is as expected
size_t n = 0;
for (const auto& batch : dmat->GetBatches<EllpackPage>(&ctx, param)) {
n += batch.Size();
}
EXPECT_EQ(n, dmat->Info().num_row_);
auto path =
data::MakeId(tmp_file + ".cache", dynamic_cast<data::SparsePageDMatrix*>(dmat)) + ".row.page";
EXPECT_TRUE(FileExists(path));
path = data::MakeId(tmp_file + ".cache", dynamic_cast<data::SparsePageDMatrix*>(dmat)) +
".ellpack.page";
EXPECT_TRUE(FileExists(path));
delete dmat;
}
TEST(SparsePageDMatrix, EllpackSkipSparsePage) {
// Test Ellpack can avoid loading sparse page after the initialization.
std::size_t n_batches = 6;
auto Xy =
RandomDataGenerator{180, 12, 0.0}.Batches(n_batches).GenerateSparsePageDMatrix("temp", true);
auto ctx = MakeCUDACtx(0);
auto cpu = ctx.MakeCPU();
bst_bin_t n_bins{256};
double sparse_thresh{0.8};
BatchParam batch_param{n_bins, sparse_thresh};
auto check_ellpack = [&]() {
std::int32_t k = 0;
for (auto const& page : Xy->GetBatches<EllpackPage>(&ctx, batch_param)) {
auto impl = page.Impl();
ASSERT_EQ(page.Size(), 30);
ASSERT_EQ(k, impl->base_rowid);
k += page.Size();
}
};
auto casted = std::dynamic_pointer_cast<data::SparsePageDMatrix>(Xy);
CHECK(casted);
check_ellpack();
// Make the number of fetches don't change (no new fetch)
auto n_fetches = casted->SparsePageFetchCount();
for (std::size_t i = 0; i < 3; ++i) {
for ([[maybe_unused]] auto const& page : Xy->GetBatches<EllpackPage>(&ctx, batch_param)) {
}
auto casted = std::dynamic_pointer_cast<data::SparsePageDMatrix>(Xy);
ASSERT_EQ(casted->SparsePageFetchCount(), n_fetches);
}
check_ellpack();
dh::device_vector<float> hess(Xy->Info().num_row_, 1.0f);
for (std::size_t i = 0; i < 4; ++i) {
for ([[maybe_unused]] auto const& page : Xy->GetBatches<SparsePage>(&ctx)) {
}
for ([[maybe_unused]] auto const& page : Xy->GetBatches<SortedCSCPage>(&cpu)) {
}
for ([[maybe_unused]] auto const& page : Xy->GetBatches<EllpackPage>(&ctx, batch_param)) {
}
// Approx tree method pages
{
BatchParam regen{n_bins, dh::ToSpan(hess), false};
for ([[maybe_unused]] auto const& page : Xy->GetBatches<EllpackPage>(&ctx, regen)) {
}
}
{
BatchParam regen{n_bins, dh::ToSpan(hess), true};
for ([[maybe_unused]] auto const& page : Xy->GetBatches<EllpackPage>(&ctx, regen)) {
}
}
check_ellpack();
}
// half the pages
{
auto it = Xy->GetBatches<SparsePage>(&ctx).begin();
for (std::size_t i = 0; i < n_batches / 2; ++i) {
++it;
}
check_ellpack();
}
{
auto it = Xy->GetBatches<EllpackPage>(&ctx, batch_param).begin();
for (std::size_t i = 0; i < n_batches / 2; ++i) {
++it;
}
check_ellpack();
}
}
TEST(SparsePageDMatrix, MultipleEllpackPages) {
auto ctx = MakeCUDACtx(0);
auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
auto dmat = RandomDataGenerator{1024, 2, 0.5f}.Batches(2).GenerateSparsePageDMatrix("temp", true);
// Loop over the batches and count the records
std::int64_t batch_count = 0;
bst_idx_t row_count = 0;
for (const auto& batch : dmat->GetBatches<EllpackPage>(&ctx, param)) {
EXPECT_LT(batch.Size(), dmat->Info().num_row_);
batch_count++;
row_count += batch.Size();
}
EXPECT_GE(batch_count, 2);
EXPECT_EQ(row_count, dmat->Info().num_row_);
auto path =
data::MakeId("tmep", dynamic_cast<data::SparsePageDMatrix*>(dmat.get())) + ".ellpack.page";
}
TEST(SparsePageDMatrix, RetainEllpackPage) {
auto ctx = MakeCUDACtx(0);
auto param = BatchParam{32, tree::TrainParam::DftSparseThreshold()};
auto m = RandomDataGenerator{2048, 4, 0.0f}.Batches(8).GenerateSparsePageDMatrix("temp", true);
auto batches = m->GetBatches<EllpackPage>(&ctx, param);
auto begin = batches.begin();
auto end = batches.end();
std::vector<HostDeviceVector<common::CompressedByteT>> gidx_buffers;
std::vector<std::shared_ptr<EllpackPage const>> iterators;
for (auto it = begin; it != end; ++it) {
iterators.push_back(it.Page());
gidx_buffers.emplace_back();
gidx_buffers.back().SetDevice(ctx.Device());
gidx_buffers.back().Resize((*it).Impl()->gidx_buffer.size());
auto d_dst = gidx_buffers.back().DevicePointer();
auto const& d_src = (*it).Impl()->gidx_buffer;
dh::safe_cuda(cudaMemcpyAsync(d_dst, d_src.data(), d_src.size_bytes(), cudaMemcpyDefault));
}
ASSERT_EQ(iterators.size(), 8);
for (size_t i = 0; i < iterators.size(); ++i) {
std::vector<common::CompressedByteT> h_buf;
[[maybe_unused]] auto h_acc = (*iterators[i]).Impl()->GetHostAccessor(&ctx, &h_buf);
ASSERT_EQ(h_buf, gidx_buffers.at(i).HostVector());
// The last page is still kept in the DMatrix until Reset is called.
if (i == iterators.size() - 1) {
ASSERT_EQ(iterators[i].use_count(), 2);
} else {
ASSERT_EQ(iterators[i].use_count(), 1);
}
}
// make sure it's const and the caller can not modify the content of page.
for (auto& page : m->GetBatches<EllpackPage>(&ctx, param)) {
static_assert(std::is_const_v<std::remove_reference_t<decltype(page)>>);
break;
}
// The above iteration clears out all references inside DMatrix.
for (auto const& ptr : iterators) {
ASSERT_TRUE(ptr.unique());
}
}
namespace {
// Test comparing external DMatrix with in-core DMatrix
class TestEllpackPageExt : public ::testing::TestWithParam<std::tuple<bool, bool>> {
protected:
void Run(bool on_host, bool is_dense) {
float sparsity = is_dense ? 0.0 : 0.2;
auto ctx = MakeCUDACtx(0);
constexpr bst_idx_t kRows = 64;
constexpr size_t kCols = 2;
// Create an in-memory DMatrix.
auto p_fmat = RandomDataGenerator{kRows, kCols, sparsity}.GenerateDMatrix(true);
// Create a DMatrix with multiple batches.
auto p_ext_fmat = RandomDataGenerator{kRows, kCols, sparsity}
.Batches(4)
.Device(ctx.Device())
.OnHost(on_host)
.GenerateSparsePageDMatrix("temp", true);
auto param = BatchParam{2, tree::TrainParam::DftSparseThreshold()};
auto impl = (*p_fmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
ASSERT_EQ(impl->base_rowid, 0);
ASSERT_EQ(impl->n_rows, kRows);
ASSERT_EQ(impl->IsDense(), is_dense);
ASSERT_EQ(impl->info.row_stride, kCols);
ASSERT_EQ(impl->Cuts().TotalBins(), param.max_bin * kCols);
std::unique_ptr<EllpackPageImpl> impl_ext;
size_t offset = 0;
for (auto& batch : p_ext_fmat->GetBatches<EllpackPage>(&ctx, param)) {
if (!impl_ext) {
impl_ext = std::make_unique<EllpackPageImpl>(&ctx, batch.Impl()->CutsShared(),
batch.Impl()->is_dense,
batch.Impl()->info.row_stride, kRows);
}
auto n_elems = impl_ext->Copy(&ctx, batch.Impl(), offset);
offset += n_elems;
}
ASSERT_EQ(impl_ext->base_rowid, 0);
ASSERT_EQ(impl_ext->n_rows, kRows);
ASSERT_EQ(impl_ext->IsDense(), is_dense);
ASSERT_EQ(impl_ext->info.row_stride, 2);
ASSERT_EQ(impl_ext->Cuts().TotalBins(), 4);
std::vector<common::CompressedByteT> buffer;
[[maybe_unused]] auto h_acc = impl->GetHostAccessor(&ctx, &buffer);
std::vector<common::CompressedByteT> buffer_ext;
[[maybe_unused]] auto h_ext_acc = impl_ext->GetHostAccessor(&ctx, &buffer_ext);
ASSERT_EQ(buffer, buffer_ext);
}
};
} // anonymous namespace
TEST_P(TestEllpackPageExt, Data) {
auto [on_host, is_dense] = this->GetParam();
this->Run(on_host, is_dense);
}
INSTANTIATE_TEST_SUITE_P(EllpackPageExt, TestEllpackPageExt, ::testing::ValuesIn([]() {
std::vector<std::tuple<bool, bool>> values;
for (auto on_host : {true, false}) {
for (auto is_dense : {true, false}) {
values.emplace_back(on_host, is_dense);
}
}
return values;
}()),
[](::testing::TestParamInfo<TestEllpackPageExt::ParamType> const& info) {
auto on_host = std::get<0>(info.param);
auto is_dense = std::get<1>(info.param);
std::stringstream ss;
ss << (on_host ? "host" : "ext");
ss << "_";
ss << (is_dense ? "dense" : "sparse");
return ss.str();
});
struct ReadRowFunction {
EllpackDeviceAccessor matrix;
int row;
bst_float* row_data_d;
ReadRowFunction(EllpackDeviceAccessor matrix, int row, bst_float* row_data_d)
: matrix(std::move(matrix)), row(row), row_data_d(row_data_d) {}
__device__ void operator()(size_t col) {
auto value = matrix.GetFvalue(row, col);
if (isnan(value)) {
value = -1;
}
row_data_d[col] = value;
}
};
TEST(SparsePageDMatrix, MultipleEllpackPageContent) {
constexpr size_t kRows = 16;
constexpr size_t kCols = 2;
constexpr int kMaxBins = 256;
// Create an in-memory DMatrix.
auto dmat =
RandomDataGenerator{kRows, kCols, 0.0f}.Batches(1).GenerateSparsePageDMatrix("temp", true);
// Create a DMatrix with multiple batches.
auto dmat_ext =
RandomDataGenerator{kRows, kCols, 0.0f}.Batches(2).GenerateSparsePageDMatrix("temp", true);
auto ctx = MakeCUDACtx(0);
auto param = BatchParam{kMaxBins, tree::TrainParam::DftSparseThreshold()};
auto impl = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
EXPECT_EQ(impl->base_rowid, 0);
EXPECT_EQ(impl->n_rows, kRows);
size_t current_row = 0;
thrust::device_vector<bst_float> row_d(kCols);
thrust::device_vector<bst_float> row_ext_d(kCols);
std::vector<bst_float> row(kCols);
std::vector<bst_float> row_ext(kCols);
for (auto& page : dmat_ext->GetBatches<EllpackPage>(&ctx, param)) {
auto impl_ext = page.Impl();
EXPECT_EQ(impl_ext->base_rowid, current_row);
for (size_t i = 0; i < impl_ext->Size(); i++) {
dh::LaunchN(kCols,
ReadRowFunction(impl->GetDeviceAccessor(&ctx), current_row, row_d.data().get()));
thrust::copy(row_d.begin(), row_d.end(), row.begin());
dh::LaunchN(kCols, ReadRowFunction(impl_ext->GetDeviceAccessor(&ctx), current_row,
row_ext_d.data().get()));
thrust::copy(row_ext_d.begin(), row_ext_d.end(), row_ext.begin());
EXPECT_EQ(row, row_ext);
current_row++;
}
}
}
TEST(SparsePageDMatrix, EllpackPageMultipleLoops) {
constexpr size_t kRows = 1024;
constexpr size_t kCols = 16;
constexpr int kMaxBins = 256;
// Create an in-memory DMatrix.
auto dmat =
RandomDataGenerator{kRows, kCols, 0.0f}.Batches(1).GenerateSparsePageDMatrix("temp", true);
// Create a DMatrix with multiple batches.
auto dmat_ext =
RandomDataGenerator{kRows, kCols, 0.0f}.Batches(8).GenerateSparsePageDMatrix("temp", true);
auto ctx = MakeCUDACtx(0);
auto param = BatchParam{kMaxBins, tree::TrainParam::DftSparseThreshold()};
size_t current_row = 0;
for (auto& page : dmat_ext->GetBatches<EllpackPage>(&ctx, param)) {
auto impl_ext = page.Impl();
EXPECT_EQ(impl_ext->base_rowid, current_row);
current_row += impl_ext->n_rows;
}
}
} // namespace xgboost
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