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Prepare external memory support for hist. (#7638)

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This PR prepares the GHistIndexMatrix to host the column matrix which is used by the hist tree method by accepting sparse_threshold parameter.

Some cleanups are made to ensure the correct batch param is being passed into DMatrix along with some additional tests for correctness of SimpleDMatrix.
This commit is contained in:
Jiaming Yuan
2022-02-10 16:58:02 +08:00
committed by GitHub
parent 87c01f49d8
commit 2775c2a1ab
24 changed files with 368 additions and 201 deletions
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43
src/data/gradient_index.cc
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@@ -2,13 +2,27 @@
* Copyright 2017-2022 by XGBoost Contributors
* \brief Data type for fast histogram aggregation.
*/
#include "gradient_index.h"
#include <algorithm>
#include <limits>
#include "gradient_index.h"
#include <memory>
#include "../common/column_matrix.h"
#include "../common/hist_util.h"
namespace xgboost {
GHistIndexMatrix::GHistIndexMatrix() : columns_{std::make_unique<common::ColumnMatrix>()} {}
GHistIndexMatrix::GHistIndexMatrix(DMatrix *x, int32_t max_bin, double sparse_thresh,
bool sorted_sketch, int32_t n_threads,
common::Span<float> hess) {
this->Init(x, max_bin, sparse_thresh, sorted_sketch, n_threads, hess);
}
GHistIndexMatrix::~GHistIndexMatrix() = default;
void GHistIndexMatrix::PushBatch(SparsePage const &batch,
common::Span<FeatureType const> ft,
size_t rbegin, size_t prev_sum, uint32_t nbins,
@@ -90,18 +104,15 @@ void GHistIndexMatrix::PushBatch(SparsePage const &batch,
[offsets](auto idx, auto j) {
return static_cast<uint8_t>(idx - offsets[j]);
});
} else if (curent_bin_size == common::kUint16BinsTypeSize) {
common::Span<uint16_t> index_data_span = {index.data<uint16_t>(),
n_index};
common::Span<uint16_t> index_data_span = {index.data<uint16_t>(), n_index};
SetIndexData(index_data_span, ft, batch_threads, batch, rbegin, nbins,
[offsets](auto idx, auto j) {
return static_cast<uint16_t>(idx - offsets[j]);
});
} else {
CHECK_EQ(curent_bin_size, common::kUint32BinsTypeSize);
common::Span<uint32_t> index_data_span = {index.data<uint32_t>(),
n_index};
common::Span<uint32_t> index_data_span = {index.data<uint32_t>(), n_index};
SetIndexData(index_data_span, ft, batch_threads, batch, rbegin, nbins,
[offsets](auto idx, auto j) {
return static_cast<uint32_t>(idx - offsets[j]);
@@ -125,8 +136,8 @@ void GHistIndexMatrix::PushBatch(SparsePage const &batch,
});
}
void GHistIndexMatrix::Init(DMatrix *p_fmat, int max_bins, bool sorted_sketch, int32_t n_threads,
common::Span<float> hess) {
void GHistIndexMatrix::Init(DMatrix *p_fmat, int max_bins, double sparse_thresh, bool sorted_sketch,
int32_t n_threads, common::Span<float> hess) {
// 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, n_threads, sorted_sketch, hess);
@@ -158,11 +169,9 @@ void GHistIndexMatrix::Init(DMatrix *p_fmat, int max_bins, bool sorted_sketch, i
}
}
void GHistIndexMatrix::Init(SparsePage const &batch,
common::Span<FeatureType const> ft,
common::HistogramCuts const &cuts,
int32_t max_bins_per_feat, bool isDense,
int32_t n_threads) {
void GHistIndexMatrix::Init(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) {
CHECK_GE(n_threads, 1);
base_rowid = batch.base_rowid;
isDense_ = isDense;
@@ -183,13 +192,13 @@ void GHistIndexMatrix::Init(SparsePage const &batch,
this->PushBatch(batch, ft, rbegin, prev_sum, nbins, n_threads);
}
void GHistIndexMatrix::ResizeIndex(const size_t n_index,
const bool isDense) {
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) {
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())) && isDense) {
} 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())) &&
isDense) {
index.SetBinTypeSize(common::kUint16BinsTypeSize);
index.Resize((sizeof(uint16_t)) * n_index);
} else {