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Fix CPU bin compression with categorical data. (#8809)

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* Fix CPU bin compression with categorical data.

* The bug causes the maximum category to be lesser than 256 or the maximum number of bins when
the input data is dense.
This commit is contained in:
Jiaming Yuan
2023-02-16 04:20:34 +08:00
committed by GitHub
parent cce4af4acf
commit c0afdb6786
6 changed files with 49 additions and 20 deletions
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25
src/data/gradient_index.cc
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@@ -21,13 +21,13 @@ GHistIndexMatrix::GHistIndexMatrix() : columns_{std::make_unique<common::ColumnM
GHistIndexMatrix::GHistIndexMatrix(DMatrix *p_fmat, bst_bin_t max_bins_per_feat,
double sparse_thresh, bool sorted_sketch, int32_t n_threads,
common::Span<float> hess) {
common::Span<float> hess)
: max_numeric_bins_per_feat{max_bins_per_feat} {
CHECK(p_fmat->SingleColBlock());
// We use sorted sketching for approx tree method since it's more efficient in
// computation time (but higher memory usage).
cut = common::SketchOnDMatrix(p_fmat, max_bins_per_feat, n_threads, sorted_sketch, hess);
max_num_bins = max_bins_per_feat;
const uint32_t nbins = cut.Ptrs().back();
hit_count.resize(nbins, 0);
hit_count_tloc_.resize(n_threads * nbins, 0);
@@ -64,7 +64,7 @@ GHistIndexMatrix::GHistIndexMatrix(MetaInfo const &info, common::HistogramCuts &
: row_ptr(info.num_row_ + 1, 0),
hit_count(cuts.TotalBins(), 0),
cut{std::forward<common::HistogramCuts>(cuts)},
max_num_bins(max_bin_per_feat),
max_numeric_bins_per_feat(max_bin_per_feat),
isDense_{info.num_col_ * info.num_row_ == info.num_nonzero_} {}
#if !defined(XGBOOST_USE_CUDA)
@@ -87,13 +87,13 @@ void GHistIndexMatrix::PushBatch(SparsePage const &batch, common::Span<FeatureTy
}
GHistIndexMatrix::GHistIndexMatrix(SparsePage const &batch, common::Span<FeatureType const> ft,
common::HistogramCuts const &cuts, int32_t max_bins_per_feat,
bool isDense, double sparse_thresh, int32_t n_threads) {
common::HistogramCuts cuts, int32_t max_bins_per_feat,
bool isDense, double sparse_thresh, int32_t n_threads)
: cut{std::move(cuts)},
max_numeric_bins_per_feat{max_bins_per_feat},
base_rowid{batch.base_rowid},
isDense_{isDense} {
CHECK_GE(n_threads, 1);
base_rowid = batch.base_rowid;
isDense_ = isDense;
cut = cuts;
max_num_bins = max_bins_per_feat;
CHECK_EQ(row_ptr.size(), 0);
// The number of threads is pegged to the batch size. If the OMP
// block is parallelized on anything other than the batch/block size,
@@ -128,12 +128,13 @@ INSTANTIATION_PUSH(data::SparsePageAdapterBatch)
#undef INSTANTIATION_PUSH
void GHistIndexMatrix::ResizeIndex(const size_t n_index, const bool isDense) {
if ((max_num_bins - 1 <= static_cast<int>(std::numeric_limits<uint8_t>::max())) && isDense) {
if ((MaxNumBinPerFeat() - 1 <= static_cast<int>(std::numeric_limits<uint8_t>::max())) &&
isDense) {
// compress dense index to uint8
index.SetBinTypeSize(common::kUint8BinsTypeSize);
index.Resize((sizeof(uint8_t)) * n_index);
} else if ((max_num_bins - 1 > static_cast<int>(std::numeric_limits<uint8_t>::max()) &&
max_num_bins - 1 <= static_cast<int>(std::numeric_limits<uint16_t>::max())) &&
} else if ((MaxNumBinPerFeat() - 1 > static_cast<int>(std::numeric_limits<uint8_t>::max()) &&
MaxNumBinPerFeat() - 1 <= static_cast<int>(std::numeric_limits<uint16_t>::max())) &&
isDense) {
// compress dense index to uint16
index.SetBinTypeSize(common::kUint16BinsTypeSize);