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Span class. (#3548)

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* Add basic Span class based on ISO++20.

* Use Span<Entry const> instead of Inst in SparsePage.

* Add DeviceSpan in HostDeviceVector, use it in regression obj.
This commit is contained in:
trivialfis
2018-08-14 13:58:11 +08:00
committed by Rory Mitchell
parent 2b7a1c5780
commit 2c502784ff
28 changed files with 1927 additions and 138 deletions
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10
src/linear/coordinate_common.h
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@@ -69,7 +69,7 @@ inline std::pair<double, double> GetGradient(int group_idx, int num_group, int f
while (iter->Next()) {
auto &batch = iter->Value();
auto col = batch[fidx];
const auto ndata = static_cast<bst_omp_uint>(col.length);
const auto ndata = static_cast<bst_omp_uint>(col.size());
for (bst_omp_uint j = 0; j < ndata; ++j) {
const bst_float v = col[j].fvalue;
auto &p = gpair[col[j].index * num_group + group_idx];
@@ -100,7 +100,7 @@ inline std::pair<double, double> GetGradientParallel(int group_idx, int num_grou
while (iter->Next()) {
auto &batch = iter->Value();
auto col = batch[fidx];
const auto ndata = static_cast<bst_omp_uint>(col.length);
const auto ndata = static_cast<bst_omp_uint>(col.size());
#pragma omp parallel for schedule(static) reduction(+ : sum_grad, sum_hess)
for (bst_omp_uint j = 0; j < ndata; ++j) {
const bst_float v = col[j].fvalue;
@@ -159,7 +159,7 @@ inline void UpdateResidualParallel(int fidx, int group_idx, int num_group,
auto &batch = iter->Value();
auto col = batch[fidx];
// update grad value
const auto num_row = static_cast<bst_omp_uint>(col.length);
const auto num_row = static_cast<bst_omp_uint>(col.size());
#pragma omp parallel for schedule(static)
for (bst_omp_uint j = 0; j < num_row; ++j) {
GradientPair &p = (*in_gpair)[col[j].index * num_group + group_idx];
@@ -331,7 +331,7 @@ class GreedyFeatureSelector : public FeatureSelector {
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < nfeat; ++i) {
const auto col = batch[i];
const bst_uint ndata = col.length;
const bst_uint ndata = col.size();
auto &sums = gpair_sums_[group_idx * nfeat + i];
for (bst_uint j = 0u; j < ndata; ++j) {
const bst_float v = col[j].fvalue;
@@ -399,7 +399,7 @@ class ThriftyFeatureSelector : public FeatureSelector {
#pragma omp parallel for schedule(static)
for (bst_omp_uint i = 0; i < nfeat; ++i) {
const auto col = batch[i];
const bst_uint ndata = col.length;
const bst_uint ndata = col.size();
for (bst_uint gid = 0u; gid < ngroup; ++gid) {
auto &sums = gpair_sums_[gid * nfeat + i];
for (bst_uint j = 0u; j < ndata; ++j) {