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Refactor DMatrix to return batches of different page types (#4686)

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* Use explicit template parameter for specifying page type.
This commit is contained in:
Rong Ou
2019-08-03 12:10:34 -07:00
committed by Jiaming Yuan
parent e930a8e54f
commit 6edddd7966
41 changed files with 477 additions and 470 deletions
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10
src/linear/coordinate_common.h
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@@ -80,7 +80,7 @@ inline std::pair<double, double> GetGradient(int group_idx, int num_group, int f
const std::vector<GradientPair> &gpair,
DMatrix *p_fmat) {
double sum_grad = 0.0, sum_hess = 0.0;
for (const auto &batch : p_fmat->GetColumnBatches()) {
for (const auto &batch : p_fmat->GetBatches<CSCPage>()) {
auto col = batch[fidx];
const auto ndata = static_cast<bst_omp_uint>(col.size());
for (bst_omp_uint j = 0; j < ndata; ++j) {
@@ -109,7 +109,7 @@ inline std::pair<double, double> GetGradientParallel(int group_idx, int num_grou
const std::vector<GradientPair> &gpair,
DMatrix *p_fmat) {
double sum_grad = 0.0, sum_hess = 0.0;
for (const auto &batch : p_fmat->GetColumnBatches()) {
for (const auto &batch : p_fmat->GetBatches<CSCPage>()) {
auto col = batch[fidx];
const auto ndata = static_cast<bst_omp_uint>(col.size());
#pragma omp parallel for schedule(static) reduction(+ : sum_grad, sum_hess)
@@ -164,7 +164,7 @@ inline void UpdateResidualParallel(int fidx, int group_idx, int num_group,
float dw, std::vector<GradientPair> *in_gpair,
DMatrix *p_fmat) {
if (dw == 0.0f) return;
for (const auto &batch : p_fmat->GetColumnBatches()) {
for (const auto &batch : p_fmat->GetBatches<CSCPage>()) {
auto col = batch[fidx];
// update grad value
const auto num_row = static_cast<bst_omp_uint>(col.size());
@@ -332,7 +332,7 @@ class GreedyFeatureSelector : public FeatureSelector {
const bst_omp_uint nfeat = model.param.num_feature;
// Calculate univariate gradient sums
std::fill(gpair_sums_.begin(), gpair_sums_.end(), std::make_pair(0., 0.));
for (const auto &batch : p_fmat->GetColumnBatches()) {
for (const auto &batch : p_fmat->GetBatches<CSCPage>()) {
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < nfeat; ++i) {
const auto col = batch[i];
@@ -397,7 +397,7 @@ class ThriftyFeatureSelector : public FeatureSelector {
}
// Calculate univariate gradient sums
std::fill(gpair_sums_.begin(), gpair_sums_.end(), std::make_pair(0., 0.));
for (const auto &batch : p_fmat->GetColumnBatches()) {
for (const auto &batch : p_fmat->GetBatches<CSCPage>()) {
// column-parallel is usually faster than row-parallel
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < nfeat; ++i) {

2
src/linear/updater_gpu_coordinate.cu
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@@ -186,7 +186,7 @@ class GPUCoordinateUpdater : public LinearUpdater {
}
CHECK(p_fmat->SingleColBlock());
SparsePage const& batch = *(p_fmat->GetColumnBatches().begin());
SparsePage const& batch = *(p_fmat->GetBatches<CSCPage>().begin());
shards_.resize(n_devices);
// Create device shards

2
src/linear/updater_shotgun.cc
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@@ -42,7 +42,7 @@ class ShotgunUpdater : public LinearUpdater {
// lock-free parallel updates of weights
selector_->Setup(*model, in_gpair->ConstHostVector(), p_fmat,
param_.reg_alpha_denorm, param_.reg_lambda_denorm, 0);
for (const auto &batch : p_fmat->GetColumnBatches()) {
for (const auto &batch : p_fmat->GetBatches<CSCPage>()) {
const auto nfeat = static_cast<bst_omp_uint>(batch.Size());
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < nfeat; ++i) {