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Upgrade clang-tidy on CI. (#5469)

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* 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
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28
src/tree/updater_gpu_hist.cu
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@@ -628,7 +628,7 @@ struct GPUHistMakerDevice {
auto d_node_hist_histogram = hist.GetNodeHistogram(nidx_histogram);
auto d_node_hist_subtraction = hist.GetNodeHistogram(nidx_subtraction);
dh::LaunchN(device_id, page->cuts_.TotalBins(), [=] __device__(size_t idx) {
dh::LaunchN(device_id, page->Cuts().TotalBins(), [=] __device__(size_t idx) {
d_node_hist_subtraction[idx] =
d_node_hist_parent[idx] - d_node_hist_histogram[idx];
});
@@ -756,7 +756,7 @@ struct GPUHistMakerDevice {
reducer->AllReduceSum(
reinterpret_cast<typename GradientSumT::ValueT*>(d_node_hist),
reinterpret_cast<typename GradientSumT::ValueT*>(d_node_hist),
page->cuts_.TotalBins() * (sizeof(GradientSumT) / sizeof(typename GradientSumT::ValueT)));
page->Cuts().TotalBins() * (sizeof(GradientSumT) / sizeof(typename GradientSumT::ValueT)));
reducer->Synchronize();
monitor.StopCuda("AllReduce");
@@ -945,20 +945,20 @@ inline void GPUHistMakerDevice<GradientSumT>::InitHistogram() {
// check if we can use shared memory for building histograms
// (assuming atleast we need 2 CTAs per SM to maintain decent latency
// hiding)
auto histogram_size = sizeof(GradientSumT) * page->cuts_.TotalBins();
auto histogram_size = sizeof(GradientSumT) * page->Cuts().TotalBins();
auto max_smem = dh::MaxSharedMemory(device_id);
if (histogram_size <= max_smem) {
use_shared_memory_histograms = true;
}
// Init histogram
hist.Init(device_id, page->cuts_.TotalBins());
hist.Init(device_id, page->Cuts().TotalBins());
}
template <typename GradientSumT>
class GPUHistMakerSpecialised {
public:
GPUHistMakerSpecialised() : initialised_{false}, p_last_fmat_{nullptr} {}
GPUHistMakerSpecialised() = default;
void Configure(const Args& args, GenericParameter const* generic_param) {
param_.UpdateAllowUnknown(args);
generic_param_ = generic_param;
@@ -1002,7 +1002,7 @@ class GPUHistMakerSpecialised {
device_ = generic_param_->gpu_id;
CHECK_GE(device_, 0) << "Must have at least one device";
info_ = &dmat->Info();
reducer_.Init({device_});
reducer_.Init({device_}); // NOLINT
// Synchronise the column sampling seed
uint32_t column_sampling_seed = common::GlobalRandom()();
@@ -1083,14 +1083,14 @@ class GPUHistMakerSpecialised {
std::unique_ptr<GPUHistMakerDevice<GradientSumT>> maker; // NOLINT
private:
bool initialised_;
bool initialised_ { false };
GPUHistMakerTrainParam hist_maker_param_;
GenericParameter const* generic_param_;
dh::AllReducer reducer_;
DMatrix* p_last_fmat_;
DMatrix* p_last_fmat_ { nullptr };
int device_{-1};
common::Monitor monitor_;
@@ -1123,22 +1123,22 @@ class GPUHistMaker : public TreeUpdater {
void LoadConfig(Json const& in) override {
auto const& config = get<Object const>(in);
fromJson(config.at("gpu_hist_train_param"), &this->hist_maker_param_);
FromJson(config.at("gpu_hist_train_param"), &this->hist_maker_param_);
if (hist_maker_param_.single_precision_histogram) {
float_maker_.reset(new GPUHistMakerSpecialised<GradientPair>());
fromJson(config.at("train_param"), &float_maker_->param_);
FromJson(config.at("train_param"), &float_maker_->param_);
} else {
double_maker_.reset(new GPUHistMakerSpecialised<GradientPairPrecise>());
fromJson(config.at("train_param"), &double_maker_->param_);
FromJson(config.at("train_param"), &double_maker_->param_);
}
}
void SaveConfig(Json* p_out) const override {
auto& out = *p_out;
out["gpu_hist_train_param"] = toJson(hist_maker_param_);
out["gpu_hist_train_param"] = ToJson(hist_maker_param_);
if (hist_maker_param_.single_precision_histogram) {
out["train_param"] = toJson(float_maker_->param_);
out["train_param"] = ToJson(float_maker_->param_);
} else {
out["train_param"] = toJson(double_maker_->param_);
out["train_param"] = ToJson(double_maker_->param_);
}
}