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Use ellpack for prediction only when sparsepage doesn't exist. (#5504)

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This commit is contained in:
Jiaming Yuan
2020-04-10 12:15:46 +08:00
committed by GitHub
parent ad826e913f
commit 6671b42dd4
35 changed files with 166 additions and 116 deletions
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2
tests/cpp/tree/gpu_hist/test_histogram.cu
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@@ -11,7 +11,7 @@ void TestDeterminsticHistogram() {
size_t constexpr kBins = 24, kCols = 8, kRows = 32768, kRounds = 16;
float constexpr kLower = -1e-2, kUpper = 1e2;
auto matrix = RandomDataGenerator(kRows, kCols, 0.5).GenerateDMatix();
auto matrix = RandomDataGenerator(kRows, kCols, 0.5).GenerateDMatrix();
BatchParam batch_param{0, static_cast<int32_t>(kBins), 0};
for (auto const& batch : matrix->GetBatches<EllpackPage>(batch_param)) {

2
tests/cpp/tree/test_gpu_hist.cu
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@@ -314,7 +314,7 @@ TEST(GpuHist, MinSplitLoss) {
constexpr size_t kRows = 32;
constexpr size_t kCols = 16;
constexpr float kSparsity = 0.6;
auto dmat = RandomDataGenerator(kRows, kCols, kSparsity).Seed(3).GenerateDMatix();
auto dmat = RandomDataGenerator(kRows, kCols, kSparsity).Seed(3).GenerateDMatrix();
auto gpair = GenerateRandomGradients(kRows);
{

2
tests/cpp/tree/test_histmaker.cc
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@@ -15,7 +15,7 @@ TEST(GrowHistMaker, InteractionConstraint) {
GenericParameter param;
param.UpdateAllowUnknown(Args{{"gpu_id", "0"}});
auto p_dmat = RandomDataGenerator{kRows, kCols, 0.6f}.Seed(3).GenerateDMatix();
auto p_dmat = RandomDataGenerator{kRows, kCols, 0.6f}.Seed(3).GenerateDMatrix();
HostDeviceVector<GradientPair> gradients (kRows);
std::vector<GradientPair>& h_gradients = gradients.HostVector();

2
tests/cpp/tree/test_prune.cc
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@@ -29,7 +29,7 @@ TEST(Updater, Prune) {
{ {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f}, {0.50f, 0.25f},
{0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f}, {0.25f, 0.24f} };
std::shared_ptr<DMatrix> p_dmat {
RandomDataGenerator{32, 10, 0}.GenerateDMatix() };
RandomDataGenerator{32, 10, 0}.GenerateDMatrix() };
auto lparam = CreateEmptyGenericParam(GPUIDX);

4
tests/cpp/tree/test_quantile_hist.cc
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@@ -139,7 +139,7 @@ class QuantileHistMock : public QuantileHistMaker {
{ {1.23f, 0.24f}, {0.24f, 0.25f}, {0.26f, 0.27f}, {2.27f, 0.28f},
{0.27f, 0.29f}, {0.37f, 0.39f}, {-0.47f, 0.49f}, {0.57f, 0.59f} };
size_t constexpr kMaxBins = 4;
auto dmat = RandomDataGenerator(kNRows, kNCols, 0).Seed(3).GenerateDMatix();
auto dmat = RandomDataGenerator(kNRows, kNCols, 0).Seed(3).GenerateDMatrix();
// dense, no missing values
common::GHistIndexMatrix gmat;
@@ -238,7 +238,7 @@ class QuantileHistMock : public QuantileHistMaker {
cfg_{args} {
QuantileHistMaker::Configure(args);
spliteval_->Init(&param_);
dmat_ = RandomDataGenerator(kNRows, kNCols, 0.8).Seed(3).GenerateDMatix();
dmat_ = RandomDataGenerator(kNRows, kNCols, 0.8).Seed(3).GenerateDMatrix();
builder_.reset(
new BuilderMock(
param_,

2
tests/cpp/tree/test_refresh.cc
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@@ -22,7 +22,7 @@ TEST(Updater, Refresh) {
{ {0.23f, 0.24f}, {0.23f, 0.24f}, {0.23f, 0.24f}, {0.23f, 0.24f},
{0.27f, 0.29f}, {0.27f, 0.29f}, {0.27f, 0.29f}, {0.27f, 0.29f} };
std::shared_ptr<DMatrix> p_dmat{
RandomDataGenerator{kRows, kCols, 0.4f}.Seed(3).GenerateDMatix()};
RandomDataGenerator{kRows, kCols, 0.4f}.Seed(3).GenerateDMatrix()};
std::vector<std::pair<std::string, std::string>> cfg{
{"reg_alpha", "0.0"},
{"num_feature", std::to_string(kCols)},