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Refactor for GHistIndex. (#7923)

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* Pass sparse page as adapter, which prepares for quantile dmatrix.
* Remove old external memory code like `rbegin` and extra `Init` function.
* Simplify type dispatch.
This commit is contained in:
Jiaming Yuan
2022-05-23 23:04:53 +08:00
committed by GitHub
parent d314680a15
commit 18a38f7ca0
6 changed files with 113 additions and 157 deletions
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78
src/data/gradient_index.h
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@@ -10,6 +10,7 @@
#include "../common/categorical.h"
#include "../common/hist_util.h"
#include "../common/threading_utils.h"
#include "adapter.h"
#include "xgboost/base.h"
#include "xgboost/data.h"
@@ -32,8 +33,38 @@ class GHistIndexMatrix {
* \param rbegin The beginning row index of current page. (total rows in previous pages)
* \param prev_sum Total number of entries in previous pages.
*/
void PushBatch(SparsePage const& batch, common::Span<FeatureType const> ft, size_t rbegin,
size_t prev_sum, uint32_t nbins, int32_t n_threads);
void PushBatch(SparsePage const& batch, common::Span<FeatureType const> ft,
bst_bin_t n_total_bins, int32_t n_threads);
template <typename Batch, typename BinIdxType, typename GetOffset, typename IsValid>
void SetIndexData(common::Span<BinIdxType> index_data_span, common::Span<FeatureType const> ft,
size_t batch_threads, Batch const& batch, IsValid&& is_valid, size_t nbins,
GetOffset&& get_offset) {
auto batch_size = batch.Size();
BinIdxType* index_data = index_data_span.data();
auto const& ptrs = cut.Ptrs();
auto const& values = cut.Values();
common::ParallelFor(batch_size, batch_threads, [&](size_t i) {
auto line = batch.GetLine(i);
size_t ibegin = row_ptr[i]; // index of first entry for current block
size_t k = 0;
auto tid = omp_get_thread_num();
for (size_t j = 0; j < line.Size(); ++j) {
data::COOTuple elem = line.GetElement(j);
if (is_valid(elem)) {
bst_bin_t bin_idx{-1};
if (common::IsCat(ft, elem.column_idx)) {
bin_idx = cut.SearchCatBin(elem.value, elem.column_idx);
} else {
bin_idx = cut.SearchBin(elem.value, elem.column_idx, ptrs, values);
}
index_data[ibegin + k] = get_offset(bin_idx, j);
++hit_count_tloc_[tid * nbins + bin_idx];
++k;
}
}
});
}
public:
/*! \brief row pointer to rows by element position */
@@ -50,52 +81,15 @@ class GHistIndexMatrix {
size_t base_rowid{0};
GHistIndexMatrix();
GHistIndexMatrix(DMatrix* x, int32_t max_bin, double sparse_thresh, bool sorted_sketch,
int32_t n_threads, common::Span<float> hess = {});
GHistIndexMatrix(DMatrix* x, bst_bin_t max_bins_per_feat, double sparse_thresh,
bool sorted_sketch, int32_t n_threads, common::Span<float> hess = {});
~GHistIndexMatrix();
// Create a global histogram matrix, given cut
void Init(DMatrix* p_fmat, int max_bins, double sparse_thresh, bool sorted_sketch,
int32_t n_threads, common::Span<float> hess);
// Create a global histogram matrix, given cut. Used by external memory
void Init(SparsePage const& page, common::Span<FeatureType const> ft,
common::HistogramCuts const& cuts, int32_t max_bins_per_feat, bool is_dense,
double sparse_thresh, int32_t n_threads);
// specific method for sparse data as no possibility to reduce allocated memory
template <typename BinIdxType, typename GetOffset>
void SetIndexData(common::Span<BinIdxType> index_data_span,
common::Span<FeatureType const> ft,
size_t batch_threads, const SparsePage &batch,
size_t rbegin, size_t nbins, GetOffset get_offset) {
const xgboost::Entry *data_ptr = batch.data.HostVector().data();
const std::vector<bst_row_t> &offset_vec = batch.offset.HostVector();
const size_t batch_size = batch.Size();
CHECK_LT(batch_size, offset_vec.size());
BinIdxType* index_data = index_data_span.data();
auto const& ptrs = cut.Ptrs();
auto const& values = cut.Values();
common::ParallelFor(batch_size, batch_threads, [&](omp_ulong ridx) {
const int tid = omp_get_thread_num();
size_t ibegin = row_ptr[rbegin + ridx]; // index of first entry for current block
size_t iend = row_ptr[rbegin + ridx + 1]; // first entry for next block
const size_t size = offset_vec[ridx + 1] - offset_vec[ridx];
SparsePage::Inst inst = {data_ptr + offset_vec[ridx], size};
CHECK_EQ(ibegin + inst.size(), iend);
for (bst_uint j = 0; j < inst.size(); ++j) {
auto e = inst[j];
if (common::IsCat(ft, e.index)) {
bst_bin_t bin_idx = cut.SearchCatBin(e);
index_data[ibegin + j] = get_offset(bin_idx, j);
++hit_count_tloc_[tid * nbins + bin_idx];
} else {
bst_bin_t bin_idx = cut.SearchBin(e.fvalue, e.index, ptrs, values);
index_data[ibegin + j] = get_offset(bin_idx, j);
++hit_count_tloc_[tid * nbins + bin_idx];
}
}
});
}
void ResizeIndex(const size_t n_index, const bool isDense);
void GetFeatureCounts(size_t* counts) const {