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Use Booster context in DMatrix. (#8896)

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- Pass context from booster to DMatrix.
- Use context instead of integer for `n_threads`.
- Check the consistency configuration for `max_bin`.
- Test for all combinations of initialization options.
This commit is contained in:
Jiaming Yuan
2023-04-28 21:47:14 +08:00
committed by GitHub
parent 1f9a57d17b
commit 08ce495b5d
67 changed files with 1283 additions and 935 deletions
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54
tests/cpp/data/test_ellpack_page.cu
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@@ -1,17 +1,17 @@
/*!
* Copyright 2019-2020 XGBoost contributors
/**
* Copyright 2019-2023, XGBoost contributors
*/
#include <xgboost/base.h>
#include <utility>
#include "../helpers.h"
#include "../histogram_helpers.h"
#include "gtest/gtest.h"
#include "../../../src/common/categorical.h"
#include "../../../src/common/hist_util.h"
#include "../../../src/data/ellpack_page.cuh"
#include "../../../src/tree/param.h" // TrainParam
#include "../helpers.h"
#include "../histogram_helpers.h"
#include "gtest/gtest.h"
namespace xgboost {
@@ -19,7 +19,10 @@ TEST(EllpackPage, EmptyDMatrix) {
constexpr int kNRows = 0, kNCols = 0, kMaxBin = 256;
constexpr float kSparsity = 0;
auto dmat = RandomDataGenerator(kNRows, kNCols, kSparsity).GenerateDMatrix();
auto& page = *dmat->GetBatches<EllpackPage>({0, kMaxBin}).begin();
Context ctx{MakeCUDACtx(0)};
auto& page = *dmat->GetBatches<EllpackPage>(
&ctx, BatchParam{kMaxBin, tree::TrainParam::DftSparseThreshold()})
.begin();
auto impl = page.Impl();
ASSERT_EQ(impl->row_stride, 0);
ASSERT_EQ(impl->Cuts().TotalBins(), 0);
@@ -87,8 +90,9 @@ TEST(EllpackPage, FromCategoricalBasic) {
auto& h_ft = m->Info().feature_types.HostVector();
h_ft.resize(kCols, FeatureType::kCategorical);
BatchParam p{0, max_bins};
auto ellpack = EllpackPage(m.get(), p);
Context ctx{MakeCUDACtx(0)};
auto p = BatchParam{max_bins, tree::TrainParam::DftSparseThreshold()};
auto ellpack = EllpackPage(&ctx, m.get(), p);
auto accessor = ellpack.Impl()->GetDeviceAccessor(0);
ASSERT_EQ(kCats, accessor.NumBins());
@@ -142,8 +146,9 @@ TEST(EllpackPage, Copy) {
dmlc::TemporaryDirectory tmpdir;
std::unique_ptr<DMatrix>
dmat(CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
BatchParam param{0, 256};
auto page = (*dmat->GetBatches<EllpackPage>(param).begin()).Impl();
Context ctx{MakeCUDACtx(0)};
auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
auto page = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
// Create an empty result page.
EllpackPageImpl result(0, page->Cuts(), page->is_dense, page->row_stride,
@@ -151,7 +156,7 @@ TEST(EllpackPage, Copy) {
// Copy batch pages into the result page.
size_t offset = 0;
for (auto& batch : dmat->GetBatches<EllpackPage>(param)) {
for (auto& batch : dmat->GetBatches<EllpackPage>(&ctx, param)) {
size_t num_elements = result.Copy(0, batch.Impl(), offset);
offset += num_elements;
}
@@ -161,7 +166,7 @@ TEST(EllpackPage, Copy) {
thrust::device_vector<bst_float> row_result_d(kCols);
std::vector<bst_float> row(kCols);
std::vector<bst_float> row_result(kCols);
for (auto& page : dmat->GetBatches<EllpackPage>(param)) {
for (auto& page : dmat->GetBatches<EllpackPage>(&ctx, param)) {
auto impl = page.Impl();
EXPECT_EQ(impl->base_rowid, current_row);
@@ -186,10 +191,11 @@ TEST(EllpackPage, Compact) {
// Create a DMatrix with multiple batches.
dmlc::TemporaryDirectory tmpdir;
std::unique_ptr<DMatrix>
dmat(CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
BatchParam param{0, 256};
auto page = (*dmat->GetBatches<EllpackPage>(param).begin()).Impl();
std::unique_ptr<DMatrix> dmat(
CreateSparsePageDMatrixWithRC(kRows, kCols, kPageSize, true, tmpdir));
Context ctx{MakeCUDACtx(0)};
auto param = BatchParam{256, tree::TrainParam::DftSparseThreshold()};
auto page = (*dmat->GetBatches<EllpackPage>(&ctx, param).begin()).Impl();
// Create an empty result page.
EllpackPageImpl result(0, page->Cuts(), page->is_dense, page->row_stride,
@@ -201,7 +207,7 @@ TEST(EllpackPage, Compact) {
SIZE_MAX};
thrust::device_vector<size_t> row_indexes_d = row_indexes_h;
common::Span<size_t> row_indexes_span(row_indexes_d.data().get(), kRows);
for (auto& batch : dmat->GetBatches<EllpackPage>(param)) {
for (auto& batch : dmat->GetBatches<EllpackPage>(&ctx, param)) {
result.Compact(0, batch.Impl(), row_indexes_span);
}
@@ -210,7 +216,7 @@ TEST(EllpackPage, Compact) {
thrust::device_vector<bst_float> row_result_d(kCols);
std::vector<bst_float> row(kCols);
std::vector<bst_float> row_result(kCols);
for (auto& page : dmat->GetBatches<EllpackPage>(param)) {
for (auto& page : dmat->GetBatches<EllpackPage>(&ctx, param)) {
auto impl = page.Impl();
ASSERT_EQ(impl->base_rowid, current_row);
@@ -245,15 +251,17 @@ class EllpackPageTest : public testing::TestWithParam<float> {
// device.
size_t n_samples{128}, n_features{13};
Context ctx;
ctx.gpu_id = 0;
Context gpu_ctx{MakeCUDACtx(0)};
auto Xy = RandomDataGenerator{n_samples, n_features, sparsity}.GenerateDMatrix(true);
std::unique_ptr<EllpackPageImpl> from_ghist;
ASSERT_TRUE(Xy->SingleColBlock());
for (auto const& page : Xy->GetBatches<GHistIndexMatrix>(BatchParam{17, 0.6})) {
from_ghist.reset(new EllpackPageImpl{&ctx, page, {}});
for (auto const& page : Xy->GetBatches<GHistIndexMatrix>(&ctx, BatchParam{17, 0.6})) {
from_ghist.reset(new EllpackPageImpl{&gpu_ctx, page, {}});
}
for (auto const& page : Xy->GetBatches<EllpackPage>(BatchParam{0, 17})) {
for (auto const& page : Xy->GetBatches<EllpackPage>(
&gpu_ctx, BatchParam{17, tree::TrainParam::DftSparseThreshold()})) {
auto from_sparse_page = page.Impl();
ASSERT_EQ(from_sparse_page->is_dense, from_ghist->is_dense);
ASSERT_EQ(from_sparse_page->base_rowid, 0);