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[breaking] Drop single precision histogram (#7892)

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Co-authored-by: Philip Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan
2022-05-13 19:54:55 +08:00
committed by GitHub
parent c8f9d4b6e6
commit 1b6538b4e5
18 changed files with 171 additions and 407 deletions
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63
tests/cpp/tree/hist/test_histogram.cc
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@@ -23,7 +23,6 @@ void InitRowPartitionForTest(common::RowSetCollection *row_set, size_t n_samples
}
} // anonymous namespace
template <typename GradientSumT>
void TestAddHistRows(bool is_distributed) {
std::vector<CPUExpandEntry> nodes_for_explicit_hist_build_;
std::vector<CPUExpandEntry> nodes_for_subtraction_trick_;
@@ -46,7 +45,7 @@ void TestAddHistRows(bool is_distributed) {
nodes_for_subtraction_trick_.emplace_back(5, tree.GetDepth(5), 0.0f);
nodes_for_subtraction_trick_.emplace_back(6, tree.GetDepth(6), 0.0f);
HistogramBuilder<GradientSumT, CPUExpandEntry> histogram_builder;
HistogramBuilder<CPUExpandEntry> histogram_builder;
histogram_builder.Reset(gmat.cut.TotalBins(), {kMaxBins, 0.5}, omp_get_max_threads(), 1,
is_distributed);
histogram_builder.AddHistRows(&starting_index, &sync_count,
@@ -66,14 +65,10 @@ void TestAddHistRows(bool is_distributed) {
TEST(CPUHistogram, AddRows) {
TestAddHistRows<float>(true);
TestAddHistRows<double>(true);
TestAddHistRows<float>(false);
TestAddHistRows<double>(false);
TestAddHistRows(true);
TestAddHistRows(false);
}
template <typename GradientSumT>
void TestSyncHist(bool is_distributed) {
size_t constexpr kNRows = 8, kNCols = 16;
int32_t constexpr kMaxBins = 4;
@@ -88,7 +83,7 @@ void TestSyncHist(bool is_distributed) {
RandomDataGenerator(kNRows, kNCols, 0.8).Seed(3).GenerateDMatrix();
auto const &gmat = *(p_fmat->GetBatches<GHistIndexMatrix>(BatchParam{kMaxBins, 0.5}).begin());
HistogramBuilder<GradientSumT, CPUExpandEntry> histogram;
HistogramBuilder<CPUExpandEntry> histogram;
uint32_t total_bins = gmat.cut.Ptrs().back();
histogram.Reset(total_bins, {kMaxBins, 0.5}, omp_get_max_threads(), 1, is_distributed);
@@ -153,7 +148,7 @@ void TestSyncHist(bool is_distributed) {
},
256);
std::vector<common::GHistRow<GradientSumT>> target_hists(n_nodes);
std::vector<common::GHistRow> target_hists(n_nodes);
for (size_t i = 0; i < nodes_for_explicit_hist_build_.size(); ++i) {
const int32_t nid = nodes_for_explicit_hist_build_[i].nid;
target_hists[i] = histogram.Histogram()[nid];
@@ -163,7 +158,7 @@ void TestSyncHist(bool is_distributed) {
std::vector<size_t> n_ids = {1, 2};
for (size_t i : n_ids) {
auto this_hist = histogram.Histogram()[i];
GradientSumT *p_hist = reinterpret_cast<GradientSumT *>(this_hist.data());
double *p_hist = reinterpret_cast<double *>(this_hist.data());
for (size_t bin_id = 0; bin_id < 2 * total_bins; ++bin_id) {
p_hist[bin_id] = 2 * bin_id;
}
@@ -172,7 +167,7 @@ void TestSyncHist(bool is_distributed) {
n_ids[1] = 5;
for (size_t i : n_ids) {
auto this_hist = histogram.Histogram()[i];
GradientSumT *p_hist = reinterpret_cast<GradientSumT *>(this_hist.data());
double *p_hist = reinterpret_cast<double *>(this_hist.data());
for (size_t bin_id = 0; bin_id < 2 * total_bins; ++bin_id) {
p_hist[bin_id] = bin_id;
}
@@ -190,15 +185,12 @@ void TestSyncHist(bool is_distributed) {
sync_count);
}
using GHistRowT = common::GHistRow<GradientSumT>;
auto check_hist = [](const GHistRowT parent, const GHistRowT left,
const GHistRowT right, size_t begin, size_t end) {
const GradientSumT *p_parent =
reinterpret_cast<const GradientSumT *>(parent.data());
const GradientSumT *p_left =
reinterpret_cast<const GradientSumT *>(left.data());
const GradientSumT *p_right =
reinterpret_cast<const GradientSumT *>(right.data());
using GHistRowT = common::GHistRow;
auto check_hist = [](const GHistRowT parent, const GHistRowT left, const GHistRowT right,
size_t begin, size_t end) {
const double *p_parent = reinterpret_cast<const double *>(parent.data());
const double *p_left = reinterpret_cast<const double *>(left.data());
const double *p_right = reinterpret_cast<const double *>(right.data());
for (size_t i = 2 * begin; i < 2 * end; ++i) {
ASSERT_EQ(p_parent[i], p_left[i] + p_right[i]);
}
@@ -230,14 +222,10 @@ void TestSyncHist(bool is_distributed) {
}
TEST(CPUHistogram, SyncHist) {
TestSyncHist<float>(true);
TestSyncHist<double>(true);
TestSyncHist<float>(false);
TestSyncHist<double>(false);
TestSyncHist(true);
TestSyncHist(false);
}
template <typename GradientSumT>
void TestBuildHistogram(bool is_distributed) {
size_t constexpr kNRows = 8, kNCols = 16;
int32_t constexpr kMaxBins = 4;
@@ -252,7 +240,7 @@ void TestBuildHistogram(bool is_distributed) {
{0.27f, 0.29f}, {0.37f, 0.39f}, {0.47f, 0.49f}, {0.57f, 0.59f}};
bst_node_t nid = 0;
HistogramBuilder<GradientSumT, CPUExpandEntry> histogram;
HistogramBuilder<CPUExpandEntry> histogram;
histogram.Reset(total_bins, {kMaxBins, 0.5}, omp_get_max_threads(), 1, is_distributed);
RegTree tree;
@@ -296,11 +284,8 @@ void TestBuildHistogram(bool is_distributed) {
}
TEST(CPUHistogram, BuildHist) {
TestBuildHistogram<float>(true);
TestBuildHistogram<double>(true);
TestBuildHistogram<float>(false);
TestBuildHistogram<double>(false);
TestBuildHistogram(true);
TestBuildHistogram(false);
}
namespace {
@@ -329,7 +314,7 @@ void TestHistogramCategorical(size_t n_categories) {
/**
* Generate hist with cat data.
*/
HistogramBuilder<double, CPUExpandEntry> cat_hist;
HistogramBuilder<CPUExpandEntry> cat_hist;
for (auto const &gidx : cat_m->GetBatches<GHistIndexMatrix>({kBins, 0.5})) {
auto total_bins = gidx.cut.TotalBins();
cat_hist.Reset(total_bins, {kBins, 0.5}, omp_get_max_threads(), 1, false);
@@ -342,7 +327,7 @@ void TestHistogramCategorical(size_t n_categories) {
*/
auto x_encoded = OneHotEncodeFeature(x, n_categories);
auto encode_m = GetDMatrixFromData(x_encoded, kRows, n_categories);
HistogramBuilder<double, CPUExpandEntry> onehot_hist;
HistogramBuilder<CPUExpandEntry> onehot_hist;
for (auto const &gidx : encode_m->GetBatches<GHistIndexMatrix>({kBins, 0.5})) {
auto total_bins = gidx.cut.TotalBins();
onehot_hist.Reset(total_bins, {kBins, 0.5}, omp_get_max_threads(), 1, false);
@@ -382,8 +367,8 @@ void TestHistogramExternalMemory(BatchParam batch_param, bool is_approx) {
std::vector<CPUExpandEntry> nodes;
nodes.emplace_back(0, tree.GetDepth(0), 0.0f);
common::GHistRow<double> multi_page;
HistogramBuilder<double, CPUExpandEntry> multi_build;
common::GHistRow multi_page;
HistogramBuilder<CPUExpandEntry> multi_build;
{
/**
* Multi page
@@ -417,8 +402,8 @@ void TestHistogramExternalMemory(BatchParam batch_param, bool is_approx) {
multi_page = multi_build.Histogram()[0];
}
HistogramBuilder<double, CPUExpandEntry> single_build;
common::GHistRow<double> single_page;
HistogramBuilder<CPUExpandEntry> single_build;
common::GHistRow single_page;
{
/**
* Single page