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Take advantage of C++17 features (#8858)

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Co-authored-by: Hyunsu Philip Cho <chohyu01@cs.washington.edu>
Co-authored-by: Jiaming Yuan <jm.yuan@outlook.com>
This commit is contained in:
Rong Ou 2023-03-03 08:24:13 -08:00 committed by GitHub
parent 69a50248b7
commit 2dc22e7aad
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GPG Key ID: 4AEE18F83AFDEB23
4 changed files with 8 additions and 33 deletions
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2
R-package/src/Makevars.in
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@ -3,7 +3,7 @@ PKGROOT=../../
ENABLE_STD_THREAD=1
# _*_ mode: Makefile; _*_
CXX_STD = CXX14
CXX_STD = CXX17
XGB_RFLAGS = -DXGBOOST_STRICT_R_MODE=1 -DDMLC_LOG_BEFORE_THROW=0\
-DDMLC_ENABLE_STD_THREAD=$(ENABLE_STD_THREAD) -DDMLC_DISABLE_STDIN=1\

2
R-package/src/Makevars.win
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@ -3,7 +3,7 @@ PKGROOT=../../
ENABLE_STD_THREAD=0
# _*_ mode: Makefile; _*_
CXX_STD = CXX14
CXX_STD = CXX17
XGB_RFLAGS = -DXGBOOST_STRICT_R_MODE=1 -DDMLC_LOG_BEFORE_THROW=0\
-DDMLC_ENABLE_STD_THREAD=$(ENABLE_STD_THREAD) -DDMLC_DISABLE_STDIN=1\

25
src/common/common.h
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@ -195,31 +195,6 @@ template <typename Indexable>
XGBOOST_DEVICE size_t LastOf(size_t group, Indexable const &indptr) {
return indptr[group + 1] - 1;
}
/**
* \brief A CRTP (curiously recurring template pattern) helper function.
*
* https://www.fluentcpp.com/2017/05/19/crtp-helper/
*
* Does two things:
* 1. Makes "crtp" explicit in the inheritance structure of a CRTP base class.
* 2. Avoids having to `static_cast` in a lot of places.
*
* \tparam T The derived class in a CRTP hierarchy.
*/
template <typename T>
struct Crtp {
T &Underlying() { return static_cast<T &>(*this); }
T const &Underlying() const { return static_cast<T const &>(*this); }
};
/**
* \brief C++17 std::as_const
*/
template <typename T>
typename std::add_const<T>::type &AsConst(T &v) noexcept { // NOLINT(runtime/references)
return v;
}
} // namespace common
} // namespace xgboost
#endif // XGBOOST_COMMON_COMMON_H_

12
src/learner.cc
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@ -21,7 +21,7 @@
#include <sstream>
#include <stack>
#include <string>
#include <utility>
#include <utility> // for as_const
#include <vector>
#include "collective/communicator-inl.h"
@ -257,11 +257,11 @@ LearnerModelParam::LearnerModelParam(Context const* ctx, LearnerModelParamLegacy
: LearnerModelParam{user_param, t} {
std::swap(base_score_, base_margin);
// Make sure read access everywhere for thread-safe prediction.
common::AsConst(base_score_).HostView();
std::as_const(base_score_).HostView();
if (!ctx->IsCPU()) {
common::AsConst(base_score_).View(ctx->gpu_id);
std::as_const(base_score_).View(ctx->gpu_id);
}
CHECK(common::AsConst(base_score_).Data()->HostCanRead());
CHECK(std::as_const(base_score_).Data()->HostCanRead());
}
linalg::TensorView<float const, 1> LearnerModelParam::BaseScore(int32_t device) const {
@ -287,9 +287,9 @@ void LearnerModelParam::Copy(LearnerModelParam const& that) {
base_score_.Reshape(that.base_score_.Shape());
base_score_.Data()->SetDevice(that.base_score_.DeviceIdx());
base_score_.Data()->Copy(*that.base_score_.Data());
common::AsConst(base_score_).HostView();
std::as_const(base_score_).HostView();
if (that.base_score_.DeviceIdx() != Context::kCpuId) {
common::AsConst(base_score_).View(that.base_score_.DeviceIdx());
std::as_const(base_score_).View(that.base_score_.DeviceIdx());
}
CHECK_EQ(base_score_.Data()->DeviceCanRead(), that.base_score_.Data()->DeviceCanRead());
CHECK(base_score_.Data()->HostCanRead());