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Refactor linear modelling and add new coordinate descent updater (#3103)

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* Refactor linear modelling and add new coordinate descent updater

* Allow unsorted column iterator

* Add prediction cacheing to gblinear
This commit is contained in:
Rory Mitchell
2018-02-17 09:17:01 +13:00
committed by GitHub
parent 9ffe8596f2
commit 10eb05a63a
23 changed files with 1252 additions and 271 deletions
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58
src/data/simple_dmatrix.cc
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@@ -54,16 +54,16 @@ dmlc::DataIter<ColBatch>* SimpleDMatrix::ColIterator(const std::vector<bst_uint>
void SimpleDMatrix::InitColAccess(const std::vector<bool> &enabled,
float pkeep,
size_t max_row_perbatch) {
if (this->HaveColAccess()) return;
size_t max_row_perbatch, bool sorted) {
if (this->HaveColAccess(sorted)) return;
col_iter_.sorted = sorted;
col_iter_.cpages_.clear();
if (info().num_row < max_row_perbatch) {
std::unique_ptr<SparsePage> page(new SparsePage());
this->MakeOneBatch(enabled, pkeep, page.get());
this->MakeOneBatch(enabled, pkeep, page.get(), sorted);
col_iter_.cpages_.push_back(std::move(page));
} else {
this->MakeManyBatch(enabled, pkeep, max_row_perbatch);
this->MakeManyBatch(enabled, pkeep, max_row_perbatch, sorted);
}
// setup col-size
col_size_.resize(info().num_col);
@@ -77,9 +77,8 @@ void SimpleDMatrix::InitColAccess(const std::vector<bool> &enabled,
}
// internal function to make one batch from row iter.
void SimpleDMatrix::MakeOneBatch(const std::vector<bool>& enabled,
float pkeep,
SparsePage *pcol) {
void SimpleDMatrix::MakeOneBatch(const std::vector<bool>& enabled, float pkeep,
SparsePage* pcol, bool sorted) {
// clear rowset
buffered_rowset_.clear();
// bit map
@@ -144,21 +143,24 @@ void SimpleDMatrix::MakeOneBatch(const std::vector<bool>& enabled,
}
CHECK_EQ(pcol->Size(), info().num_col);
// sort columns
bst_omp_uint ncol = static_cast<bst_omp_uint>(pcol->Size());
#pragma omp parallel for schedule(dynamic, 1) num_threads(nthread)
for (bst_omp_uint i = 0; i < ncol; ++i) {
if (pcol->offset[i] < pcol->offset[i + 1]) {
std::sort(dmlc::BeginPtr(pcol->data) + pcol->offset[i],
dmlc::BeginPtr(pcol->data) + pcol->offset[i + 1],
SparseBatch::Entry::CmpValue);
if (sorted) {
// sort columns
bst_omp_uint ncol = static_cast<bst_omp_uint>(pcol->Size());
#pragma omp parallel for schedule(dynamic, 1) num_threads(nthread)
for (bst_omp_uint i = 0; i < ncol; ++i) {
if (pcol->offset[i] < pcol->offset[i + 1]) {
std::sort(dmlc::BeginPtr(pcol->data) + pcol->offset[i],
dmlc::BeginPtr(pcol->data) + pcol->offset[i + 1],
SparseBatch::Entry::CmpValue);
}
}
}
}
void SimpleDMatrix::MakeManyBatch(const std::vector<bool>& enabled,
float pkeep,
size_t max_row_perbatch) {
size_t max_row_perbatch, bool sorted) {
size_t btop = 0;
std::bernoulli_distribution coin_flip(pkeep);
auto& rnd = common::GlobalRandom();
@@ -179,7 +181,7 @@ void SimpleDMatrix::MakeManyBatch(const std::vector<bool>& enabled,
}
if (tmp.Size() >= max_row_perbatch) {
std::unique_ptr<SparsePage> page(new SparsePage());
this->MakeColPage(tmp.GetRowBatch(0), btop, enabled, page.get());
this->MakeColPage(tmp.GetRowBatch(0), btop, enabled, page.get(), sorted);
col_iter_.cpages_.push_back(std::move(page));
btop = buffered_rowset_.size();
tmp.Clear();
@@ -189,7 +191,7 @@ void SimpleDMatrix::MakeManyBatch(const std::vector<bool>& enabled,
if (tmp.Size() != 0) {
std::unique_ptr<SparsePage> page(new SparsePage());
this->MakeColPage(tmp.GetRowBatch(0), btop, enabled, page.get());
this->MakeColPage(tmp.GetRowBatch(0), btop, enabled, page.get(), sorted);
col_iter_.cpages_.push_back(std::move(page));
}
}
@@ -198,7 +200,7 @@ void SimpleDMatrix::MakeManyBatch(const std::vector<bool>& enabled,
void SimpleDMatrix::MakeColPage(const RowBatch& batch,
size_t buffer_begin,
const std::vector<bool>& enabled,
SparsePage* pcol) {
SparsePage* pcol, bool sorted) {
const int nthread = std::min(omp_get_max_threads(), std::max(omp_get_num_procs() / 2 - 2, 1));
pcol->Clear();
common::ParallelGroupBuilder<SparseBatch::Entry>
@@ -231,13 +233,15 @@ void SimpleDMatrix::MakeColPage(const RowBatch& batch,
}
CHECK_EQ(pcol->Size(), info().num_col);
// sort columns
bst_omp_uint ncol = static_cast<bst_omp_uint>(pcol->Size());
#pragma omp parallel for schedule(dynamic, 1) num_threads(nthread)
for (bst_omp_uint i = 0; i < ncol; ++i) {
if (pcol->offset[i] < pcol->offset[i + 1]) {
std::sort(dmlc::BeginPtr(pcol->data) + pcol->offset[i],
dmlc::BeginPtr(pcol->data) + pcol->offset[i + 1],
SparseBatch::Entry::CmpValue);
if (sorted) {
bst_omp_uint ncol = static_cast<bst_omp_uint>(pcol->Size());
#pragma omp parallel for schedule(dynamic, 1) num_threads(nthread)
for (bst_omp_uint i = 0; i < ncol; ++i) {
if (pcol->offset[i] < pcol->offset[i + 1]) {
std::sort(dmlc::BeginPtr(pcol->data) + pcol->offset[i],
dmlc::BeginPtr(pcol->data) + pcol->offset[i + 1],
SparseBatch::Entry::CmpValue);
}
}
}
}