Hendrik/xgboost
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Upgrade clang-tidy on CI. (#5469)

Browse Source 
* Correct all clang-tidy errors.
* Upgrade clang-tidy to 10 on CI.

Co-authored-by: Hyunsu Cho <chohyu01@cs.washington.edu>
This commit is contained in:
Jiaming Yuan
2020-04-05 04:42:29 +08:00
committed by GitHub
parent 30e94ddd04
commit 0012f2ef93
107 changed files with 932 additions and 903 deletions
Download Patch File Download Diff File Expand all files Collapse all files

64
src/common/hist_util.cc
View File

@@ -1,5 +1,5 @@
/*!
* Copyright 2017-2019 by Contributors
* Copyright 2017-2020 by Contributors
* \file hist_util.cc
*/
#include <dmlc/timer.h>
@@ -11,10 +11,10 @@
#include "xgboost/base.h"
#include "../common/common.h"
#include "./hist_util.h"
#include "./random.h"
#include "./column_matrix.h"
#include "./quantile.h"
#include "hist_util.h"
#include "random.h"
#include "column_matrix.h"
#include "quantile.h"
#include "./../tree/updater_quantile_hist.h"
#if defined(XGBOOST_MM_PREFETCH_PRESENT)
@@ -99,16 +99,16 @@ void GHistIndexMatrix::SetIndexDataForSparse(common::Span<uint32_t> index_data_s
void GHistIndexMatrix::ResizeIndex(const size_t rbegin, const SparsePage& batch,
const size_t n_offsets, 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(UINT8_BINS_TYPE_SIZE);
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) {
index.setBinTypeSize(UINT16_BINS_TYPE_SIZE);
index.resize((sizeof(uint16_t)) * n_index);
if ((max_num_bins - 1 <= static_cast<int>(std::numeric_limits<uint8_t>::max())) && isDense) {
index.SetBinTypeSize(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) {
index.SetBinTypeSize(kUint16BinsTypeSize);
index.Resize((sizeof(uint16_t)) * n_index);
} else {
index.setBinTypeSize(UINT32_BINS_TYPE_SIZE);
index.resize((sizeof(uint32_t)) * n_index);
index.SetBinTypeSize(kUint32BinsTypeSize);
index.Resize((sizeof(uint32_t)) * n_index);
}
}
@@ -449,15 +449,15 @@ void DenseCuts::Init
monitor_.Stop(__func__);
}
void GHistIndexMatrix::Init(DMatrix* p_fmat, int max_num_bins) {
cut.Build(p_fmat, max_num_bins);
max_num_bins_ = max_num_bins;
void GHistIndexMatrix::Init(DMatrix* p_fmat, int max_bins) {
cut.Build(p_fmat, max_bins);
max_num_bins = max_bins;
const int32_t nthread = omp_get_max_threads();
const uint32_t nbins = cut.Ptrs().back();
hit_count.resize(nbins, 0);
hit_count_tloc_.resize(nthread * nbins, 0);
this->p_fmat_ = p_fmat;
this->p_fmat = p_fmat;
size_t new_size = 1;
for (const auto &batch : p_fmat->GetBatches<SparsePage>()) {
new_size += batch.Size();
@@ -524,24 +524,24 @@ void GHistIndexMatrix::Init(DMatrix* p_fmat, int max_num_bins) {
uint32_t* offsets = nullptr;
if (isDense) {
index.resizeOffset(n_offsets);
offsets = index.offset();
index.ResizeOffset(n_offsets);
offsets = index.Offset();
for (size_t i = 0; i < n_offsets; ++i) {
offsets[i] = cut.Ptrs()[i];
}
}
if (isDense) {
BinTypeSize curent_bin_size = index.getBinTypeSize();
BinTypeSize curent_bin_size = index.GetBinTypeSize();
common::Span<const uint32_t> offsets_span = {offsets, n_offsets};
if (curent_bin_size == UINT8_BINS_TYPE_SIZE) {
if (curent_bin_size == kUint8BinsTypeSize) {
common::Span<uint8_t> index_data_span = {index.data<uint8_t>(), n_index};
SetIndexDataForDense(index_data_span, batch_threads, batch, rbegin, offsets_span, nbins);
} else if (curent_bin_size == UINT16_BINS_TYPE_SIZE) {
} else if (curent_bin_size == kUint16BinsTypeSize) {
common::Span<uint16_t> index_data_span = {index.data<uint16_t>(), n_index};
SetIndexDataForDense(index_data_span, batch_threads, batch, rbegin, offsets_span, nbins);
} else {
CHECK_EQ(curent_bin_size, UINT32_BINS_TYPE_SIZE);
CHECK_EQ(curent_bin_size, kUint32BinsTypeSize);
common::Span<uint32_t> index_data_span = {index.data<uint32_t>(), n_index};
SetIndexDataForDense(index_data_span, batch_threads, batch, rbegin, offsets_span, nbins);
}
@@ -689,16 +689,16 @@ FindGroups(const std::vector<unsigned>& feature_list,
}
BinTypeSize bins_type_size = colmat.GetTypeSize();
if (bins_type_size == UINT8_BINS_TYPE_SIZE) {
if (bins_type_size == kUint8BinsTypeSize) {
const auto column = colmat.GetColumn<uint8_t>(fid);
SetGroup(fid, *(column.get()), max_conflict_cnt, search_groups,
&group_conflict_cnt, &conflict_marks, &groups, &group_nnz, cur_fid_nnz, nrow);
} else if (bins_type_size == UINT16_BINS_TYPE_SIZE) {
} else if (bins_type_size == kUint16BinsTypeSize) {
const auto column = colmat.GetColumn<uint16_t>(fid);
SetGroup(fid, *(column.get()), max_conflict_cnt, search_groups,
&group_conflict_cnt, &conflict_marks, &groups, &group_nnz, cur_fid_nnz, nrow);
} else {
CHECK_EQ(bins_type_size, UINT32_BINS_TYPE_SIZE);
CHECK_EQ(bins_type_size, kUint32BinsTypeSize);
const auto column = colmat.GetColumn<uint32_t>(fid);
SetGroup(fid, *(column.get()), max_conflict_cnt, search_groups,
&group_conflict_cnt, &conflict_marks, &groups, &group_nnz, cur_fid_nnz, nrow);
@@ -909,7 +909,7 @@ void BuildHistDenseKernel(const std::vector<GradientPair>& gpair,
const size_t* rid = row_indices.begin;
const float* pgh = reinterpret_cast<const float*>(gpair.data());
const BinIdxType* gradient_index = gmat.index.data<BinIdxType>();
const uint32_t* offsets = gmat.index.offset();
const uint32_t* offsets = gmat.index.Offset();
FPType* hist_data = reinterpret_cast<FPType*>(hist.data());
const uint32_t two {2}; // Each element from 'gpair' and 'hist' contains
// 2 FP values: gradient and hessian.
@@ -1000,16 +1000,16 @@ void BuildHistKernel(const std::vector<GradientPair>& gpair,
const RowSetCollection::Elem row_indices,
const GHistIndexMatrix& gmat, const bool isDense, GHistRow hist) {
const bool is_dense = row_indices.Size() && isDense;
switch (gmat.index.getBinTypeSize()) {
case UINT8_BINS_TYPE_SIZE:
switch (gmat.index.GetBinTypeSize()) {
case kUint8BinsTypeSize:
BuildHistDispatchKernel<FPType, do_prefetch, uint8_t>(gpair, row_indices,
gmat, hist, is_dense);
break;
case UINT16_BINS_TYPE_SIZE:
case kUint16BinsTypeSize:
BuildHistDispatchKernel<FPType, do_prefetch, uint16_t>(gpair, row_indices,
gmat, hist, is_dense);
break;
case UINT32_BINS_TYPE_SIZE:
case kUint32BinsTypeSize:
BuildHistDispatchKernel<FPType, do_prefetch, uint32_t>(gpair, row_indices,
gmat, hist, is_dense);
break;