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Unverified Commit 50f11a9f authored by Nikita Titov's avatar Nikita Titov Committed by GitHub
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[ci][c++] fixed `whitespace/indent_namespace` errors from cpplint (#7056) 



* dev

* dev

* dev

* dev

* dev

---------
Co-authored-by: default avatarJames Lamb <jaylamb20@gmail.com>
parent 6f0d7cc2
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Showing with 1353 additions and 1355 deletions
.pre-commit-config.yaml
View file @ 50f11a9f
......@@ -28,7 +28,7 @@ repos:
- id: cpplint
args:
- --recursive
- --filter=-build/include_subdir,-build/header_guard,-whitespace/indent_namespace,-whitespace/line_length
- --filter=-build/include_subdir,-build/header_guard,-whitespace/line_length
- repo: local
hooks:
- id: check-omp-pragmas
......
include/LightGBM/meta.h
View file @ 50f11a9f
......@@ -83,7 +83,7 @@ const int kAlignedSize = 32;
// Refer to https://docs.microsoft.com/en-us/cpp/error-messages/compiler-warnings/compiler-warning-level-4-c4127?view=vs-2019
#ifdef _MSC_VER
#pragma warning(disable : 4127)
#pragma warning(disable : 4127)
#endif
} // namespace LightGBM
......
src/io/bin.cpp
View file @ 50f11a9f
......@@ -22,13 +22,13 @@
namespace LightGBM {
BinMapper::BinMapper(): num_bin_(1), is_trivial_(true), bin_type_(BinType::NumericalBin) {
BinMapper::BinMapper(): num_bin_(1), is_trivial_(true), bin_type_(BinType::NumericalBin) {
bin_upper_bound_.clear();
bin_upper_bound_.push_back(std::numeric_limits<double>::infinity());
}
}
// deep copy function for BinMapper
BinMapper::BinMapper(const BinMapper& other) {
// deep copy function for BinMapper
BinMapper::BinMapper(const BinMapper& other) {
num_bin_ = other.num_bin_;
missing_type_ = other.missing_type_;
is_trivial_ = other.is_trivial_;
......@@ -44,16 +44,16 @@ namespace LightGBM {
max_val_ = other.max_val_;
default_bin_ = other.default_bin_;
most_freq_bin_ = other.most_freq_bin_;
}
}
BinMapper::BinMapper(const void* memory) {
BinMapper::BinMapper(const void* memory) {
CopyFrom(reinterpret_cast<const char*>(memory));
}
}
BinMapper::~BinMapper() {
}
BinMapper::~BinMapper() {
}
bool NeedFilter(const std::vector<int>& cnt_in_bin, int total_cnt, int filter_cnt, BinType bin_type) {
bool NeedFilter(const std::vector<int>& cnt_in_bin, int total_cnt, int filter_cnt, BinType bin_type) {
if (bin_type == BinType::NumericalBin) {
int sum_left = 0;
for (size_t i = 0; i < cnt_in_bin.size() - 1; ++i) {
......@@ -75,9 +75,9 @@ namespace LightGBM {
}
}
return true;
}
}
std::vector<double> GreedyFindBin(const double* distinct_values, const int* counts,
std::vector<double> GreedyFindBin(const double* distinct_values, const int* counts,
int num_distinct_values, int max_bin,
size_t total_cnt, int min_data_in_bin) {
std::vector<double> bin_upper_bound;
......@@ -156,9 +156,9 @@ namespace LightGBM {
bin_upper_bound.push_back(std::numeric_limits<double>::infinity());
}
return bin_upper_bound;
}
}
std::vector<double> FindBinWithPredefinedBin(const double* distinct_values, const int* counts,
std::vector<double> FindBinWithPredefinedBin(const double* distinct_values, const int* counts,
int num_distinct_values, int max_bin,
size_t total_sample_cnt, int min_data_in_bin,
const std::vector<double>& forced_upper_bounds) {
......@@ -241,9 +241,9 @@ namespace LightGBM {
std::stable_sort(bin_upper_bound.begin(), bin_upper_bound.end());
CHECK_LE(bin_upper_bound.size(), static_cast<size_t>(max_bin));
return bin_upper_bound;
}
}
std::vector<double> FindBinWithZeroAsOneBin(const double* distinct_values, const int* counts, int num_distinct_values,
std::vector<double> FindBinWithZeroAsOneBin(const double* distinct_values, const int* counts, int num_distinct_values,
int max_bin, size_t total_sample_cnt, int min_data_in_bin) {
std::vector<double> bin_upper_bound;
int left_cnt_data = 0;
......@@ -299,9 +299,9 @@ namespace LightGBM {
}
CHECK_LE(bin_upper_bound.size(), static_cast<size_t>(max_bin));
return bin_upper_bound;
}
}
std::vector<double> FindBinWithZeroAsOneBin(const double* distinct_values, const int* counts, int num_distinct_values,
std::vector<double> FindBinWithZeroAsOneBin(const double* distinct_values, const int* counts, int num_distinct_values,
int max_bin, size_t total_sample_cnt, int min_data_in_bin,
const std::vector<double>& forced_upper_bounds) {
if (forced_upper_bounds.empty()) {
......@@ -310,9 +310,9 @@ namespace LightGBM {
return FindBinWithPredefinedBin(distinct_values, counts, num_distinct_values, max_bin, total_sample_cnt, min_data_in_bin,
forced_upper_bounds);
}
}
}
void BinMapper::FindBin(double* values, int num_sample_values, size_t total_sample_cnt,
void BinMapper::FindBin(double* values, int num_sample_values, size_t total_sample_cnt,
int max_bin, int min_data_in_bin, int min_split_data, bool pre_filter, BinType bin_type,
bool use_missing, bool zero_as_missing,
const std::vector<double>& forced_upper_bounds) {
......@@ -507,9 +507,9 @@ namespace LightGBM {
} else {
sparse_rate_ = 1.0f;
}
}
}
void BinMapper::CopyTo(char * buffer) const {
void BinMapper::CopyTo(char * buffer) const {
std::memcpy(buffer, &num_bin_, sizeof(num_bin_));
buffer += VirtualFileWriter::AlignedSize(sizeof(num_bin_));
std::memcpy(buffer, &missing_type_, sizeof(missing_type_));
......@@ -533,9 +533,9 @@ namespace LightGBM {
} else {
std::memcpy(buffer, bin_2_categorical_.data(), num_bin_ * sizeof(int));
}
}
}
void BinMapper::CopyFrom(const char * buffer) {
void BinMapper::CopyFrom(const char * buffer) {
std::memcpy(&num_bin_, buffer, sizeof(num_bin_));
buffer += VirtualFileWriter::AlignedSize(sizeof(num_bin_));
std::memcpy(&missing_type_, buffer, sizeof(missing_type_));
......@@ -565,9 +565,9 @@ namespace LightGBM {
categorical_2_bin_[bin_2_categorical_[i]] = static_cast<unsigned int>(i);
}
}
}
}
void BinMapper::SaveBinaryToFile(BinaryWriter* writer) const {
void BinMapper::SaveBinaryToFile(BinaryWriter* writer) const {
writer->AlignedWrite(&num_bin_, sizeof(num_bin_));
writer->AlignedWrite(&missing_type_, sizeof(missing_type_));
writer->AlignedWrite(&is_trivial_, sizeof(is_trivial_));
......@@ -582,9 +582,9 @@ namespace LightGBM {
} else {
writer->Write(bin_2_categorical_.data(), sizeof(int) * num_bin_);
}
}
}
size_t BinMapper::SizesInByte() const {
size_t BinMapper::SizesInByte() const {
size_t ret = VirtualFileWriter::AlignedSize(sizeof(num_bin_)) +
VirtualFileWriter::AlignedSize(sizeof(missing_type_)) +
VirtualFileWriter::AlignedSize(sizeof(is_trivial_)) +
......@@ -599,22 +599,22 @@ namespace LightGBM {
ret += sizeof(int) * num_bin_;
}
return ret;
}
}
template class DenseBin<uint8_t, true>;
template class DenseBin<uint8_t, false>;
template class DenseBin<uint16_t, false>;
template class DenseBin<uint32_t, false>;
template class DenseBin<uint8_t, true>;
template class DenseBin<uint8_t, false>;
template class DenseBin<uint16_t, false>;
template class DenseBin<uint32_t, false>;
template class SparseBin<uint8_t>;
template class SparseBin<uint16_t>;
template class SparseBin<uint32_t>;
template class SparseBin<uint8_t>;
template class SparseBin<uint16_t>;
template class SparseBin<uint32_t>;
template class MultiValDenseBin<uint8_t>;
template class MultiValDenseBin<uint16_t>;
template class MultiValDenseBin<uint32_t>;
template class MultiValDenseBin<uint8_t>;
template class MultiValDenseBin<uint16_t>;
template class MultiValDenseBin<uint32_t>;
Bin* Bin::CreateDenseBin(data_size_t num_data, int num_bin) {
Bin* Bin::CreateDenseBin(data_size_t num_data, int num_bin) {
if (num_bin <= 16) {
return new DenseBin<uint8_t, true>(num_data);
} else if (num_bin <= 256) {
......@@ -624,9 +624,9 @@ namespace LightGBM {
} else {
return new DenseBin<uint32_t, false>(num_data);
}
}
}
Bin* Bin::CreateSparseBin(data_size_t num_data, int num_bin) {
Bin* Bin::CreateSparseBin(data_size_t num_data, int num_bin) {
if (num_bin <= 256) {
return new SparseBin<uint8_t>(num_data);
} else if (num_bin <= 65536) {
......@@ -634,9 +634,9 @@ namespace LightGBM {
} else {
return new SparseBin<uint32_t>(num_data);
}
}
}
MultiValBin* MultiValBin::CreateMultiValBin(data_size_t num_data, int num_bin, int num_feature,
MultiValBin* MultiValBin::CreateMultiValBin(data_size_t num_data, int num_bin, int num_feature,
double sparse_rate, const std::vector<uint32_t>& offsets) {
if (sparse_rate >= multi_val_bin_sparse_threshold) {
const double average_element_per_row = (1.0 - sparse_rate) * num_feature;
......@@ -645,9 +645,9 @@ namespace LightGBM {
} else {
return CreateMultiValDenseBin(num_data, num_bin, num_feature, offsets);
}
}
}
MultiValBin* MultiValBin::CreateMultiValDenseBin(data_size_t num_data,
MultiValBin* MultiValBin::CreateMultiValDenseBin(data_size_t num_data,
int num_bin,
int num_feature,
const std::vector<uint32_t>& offsets) {
......@@ -666,9 +666,9 @@ namespace LightGBM {
} else {
return new MultiValDenseBin<uint32_t>(num_data, num_bin, num_feature, offsets);
}
}
}
MultiValBin* MultiValBin::CreateMultiValSparseBin(data_size_t num_data,
MultiValBin* MultiValBin::CreateMultiValSparseBin(data_size_t num_data,
int num_bin,
double estimate_element_per_row) {
size_t estimate_total_entries =
......@@ -707,10 +707,10 @@ namespace LightGBM {
num_data, num_bin, estimate_element_per_row);
}
}
}
}
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -719,10 +719,10 @@ namespace LightGBM {
*bit_type = 8;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -731,10 +731,10 @@ namespace LightGBM {
*bit_type = 16;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -743,10 +743,10 @@ namespace LightGBM {
*bit_type = 32;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -755,10 +755,10 @@ namespace LightGBM {
*bit_type = 4;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -766,10 +766,10 @@ namespace LightGBM {
*bit_type = 8;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -777,10 +777,10 @@ namespace LightGBM {
*bit_type = 16;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -788,10 +788,10 @@ namespace LightGBM {
*bit_type = 32;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -799,10 +799,10 @@ namespace LightGBM {
*bit_type = 4;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
}
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -813,10 +813,10 @@ namespace LightGBM {
bin_iterator->emplace_back(new SparseBinIterator<uint8_t>(this, 0));
}
return nullptr;
}
}
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -827,10 +827,10 @@ namespace LightGBM {
bin_iterator->emplace_back(new SparseBinIterator<uint16_t>(this, 0));
}
return nullptr;
}
}
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
......@@ -841,10 +841,10 @@ namespace LightGBM {
bin_iterator->emplace_back(new SparseBinIterator<uint32_t>(this, 0));
}
return nullptr;
}
}
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -852,10 +852,10 @@ namespace LightGBM {
*bit_type = 8;
*bin_iterator = new SparseBinIterator<uint8_t>(this, 0);
return nullptr;
}
}
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -863,10 +863,10 @@ namespace LightGBM {
*bit_type = 16;
*bin_iterator = new SparseBinIterator<uint16_t>(this, 0);
return nullptr;
}
}
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
......@@ -874,11 +874,11 @@ namespace LightGBM {
*bit_type = 32;
*bin_iterator = new SparseBinIterator<uint32_t>(this, 0);
return nullptr;
}
}
#ifdef USE_CUDA
template <>
const void* MultiValDenseBin<uint8_t>::GetRowWiseData(uint8_t* bit_type,
#ifdef USE_CUDA
template <>
const void* MultiValDenseBin<uint8_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
......@@ -891,10 +891,10 @@ namespace LightGBM {
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
}
template <>
const void* MultiValDenseBin<uint16_t>::GetRowWiseData(uint8_t* bit_type,
template <>
const void* MultiValDenseBin<uint16_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
......@@ -908,10 +908,10 @@ namespace LightGBM {
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
}
template <>
const void* MultiValDenseBin<uint32_t>::GetRowWiseData(uint8_t* bit_type,
template <>
const void* MultiValDenseBin<uint32_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
......@@ -925,10 +925,10 @@ namespace LightGBM {
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint16_t, uint8_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint16_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -941,10 +941,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 16;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint16_t, uint16_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint16_t, uint16_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -957,10 +957,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 16;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint16_t, uint32_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint16_t, uint32_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -973,10 +973,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 16;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint32_t, uint8_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint32_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -989,10 +989,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 32;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint32_t, uint16_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint32_t, uint16_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -1005,10 +1005,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 32;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint32_t, uint32_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint32_t, uint32_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -1021,10 +1021,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 32;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint64_t, uint8_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint64_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -1037,10 +1037,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint64_t, uint16_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint64_t, uint16_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -1053,10 +1053,10 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}
}
template <>
const void* MultiValSparseBin<uint64_t, uint32_t>::GetRowWiseData(
template <>
const void* MultiValSparseBin<uint64_t, uint32_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
......@@ -1069,8 +1069,8 @@ namespace LightGBM {
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}
}
#endif // USE_CUDA
#endif // USE_CUDA
} // namespace LightGBM
src/io/dataset.cpp
View file @ 50f11a9f
......@@ -28,10 +28,8 @@ namespace LightGBM {
const int Dataset::kSerializedReferenceVersionLength = 2;
const char* Dataset::serialized_reference_version = "v1";
const char* Dataset::binary_file_token =
"______LightGBM_Binary_File_Token______\n";
const char* Dataset::binary_serialized_reference_token =
"______LightGBM_Binary_Serialized_Token______\n";
const char* Dataset::binary_file_token = "______LightGBM_Binary_File_Token______\n";
const char* Dataset::binary_serialized_reference_token = "______LightGBM_Binary_Serialized_Token______\n";
Dataset::Dataset() {
data_filename_ = "noname";
......
src/metric/cuda/cuda_binary_metric.cpp
View file @ 50f11a9f
......@@ -12,8 +12,8 @@
namespace LightGBM {
CUDABinaryLoglossMetric::CUDABinaryLoglossMetric(const Config& config):
CUDABinaryMetricInterface<BinaryLoglossMetric, CUDABinaryLoglossMetric>(config) {}
CUDABinaryLoglossMetric::CUDABinaryLoglossMetric(
const Config& config):CUDABinaryMetricInterface<BinaryLoglossMetric, CUDABinaryLoglossMetric>(config) {}
template <typename HOST_METRIC, typename CUDA_METRIC>
std::vector<double> CUDABinaryMetricInterface<HOST_METRIC, CUDA_METRIC>::Eval(const double* score, const ObjectiveFunction* objective) const {
......
src/metric/xentropy_metric.hpp
View file @ 50f11a9f
......@@ -30,9 +30,9 @@
namespace LightGBM {
// label should be in interval [0, 1];
// prob should be in interval (0, 1); prob is clipped if needed
inline static double XentLoss(label_t label, double prob) {
// label should be in interval [0, 1];
// prob should be in interval (0, 1); prob is clipped if needed
inline static double XentLoss(label_t label, double prob) {
const double log_arg_epsilon = 1.0e-12;
double a = label;
if (prob > log_arg_epsilon) {
......@@ -47,23 +47,23 @@ namespace LightGBM {
b *= std::log(log_arg_epsilon);
}
return - (a + b);
}
}
// hhat >(=) 0 assumed; and weight > 0 required; but not checked here
inline static double XentLambdaLoss(label_t label, label_t weight, double hhat) {
// hhat >(=) 0 assumed; and weight > 0 required; but not checked here
inline static double XentLambdaLoss(label_t label, label_t weight, double hhat) {
return XentLoss(label, 1.0f - std::exp(-weight * hhat));
}
}
// Computes the (negative) entropy for label p; p should be in interval [0, 1];
// This is used to presum the KL-divergence offset term (to be _added_ to the cross-entropy loss).
// NOTE: x*log(x) = 0 for x=0,1; so only add when in (0, 1); avoid log(0)*0
inline static double YentLoss(double p) {
// Computes the (negative) entropy for label p; p should be in interval [0, 1];
// This is used to presum the KL-divergence offset term (to be _added_ to the cross-entropy loss).
// NOTE: x*log(x) = 0 for x=0,1; so only add when in (0, 1); avoid log(0)*0
inline static double YentLoss(double p) {
double hp = 0.0;
if (p > 0) hp += p * std::log(p);
double q = 1.0f - p;
if (q > 0) hp += q * std::log(q);
return hp;
}
}
//
// CrossEntropyMetric : "xentropy" : (optional) weights are used linearly
......
src/treelearner/data_parallel_tree_learner.cpp
View file @ 50f11a9f
......@@ -12,8 +12,7 @@
namespace LightGBM {
template <typename TREELEARNER_T>
DataParallelTreeLearner<TREELEARNER_T>::DataParallelTreeLearner(const Config* config)
:TREELEARNER_T(config) {
DataParallelTreeLearner<TREELEARNER_T>::DataParallelTreeLearner(const Config* config):TREELEARNER_T(config) {
}
template <typename TREELEARNER_T>
......
src/treelearner/feature_histogram.cpp
View file @ 50f11a9f
......@@ -384,8 +384,11 @@ void FeatureHistogram::FindBestThresholdCategoricalInner(double sum_gradient,
}
}
template <bool USE_RAND, bool USE_MC, bool USE_L1, bool USE_MAX_OUTPUT, bool USE_SMOOTHING, typename PACKED_HIST_BIN_T, typename PACKED_HIST_ACC_T,
typename HIST_BIN_T, typename HIST_ACC_T, int HIST_BITS_BIN, int HIST_BITS_ACC>
template <
bool USE_RAND, bool USE_MC, bool USE_L1, bool USE_MAX_OUTPUT, bool USE_SMOOTHING,
typename PACKED_HIST_BIN_T, typename PACKED_HIST_ACC_T, typename HIST_BIN_T, typename HIST_ACC_T,
int HIST_BITS_BIN, int HIST_BITS_ACC
>
void FeatureHistogram::FindBestThresholdCategoricalIntInner(int64_t int_sum_gradient_and_hessian,
const double grad_scale, const double hess_scale,
data_size_t num_data,
......
src/treelearner/feature_parallel_tree_learner.cpp
View file @ 50f11a9f
......@@ -11,8 +11,7 @@ namespace LightGBM {
template <typename TREELEARNER_T>
FeatureParallelTreeLearner<TREELEARNER_T>::FeatureParallelTreeLearner(const Config* config)
:TREELEARNER_T(config) {
FeatureParallelTreeLearner<TREELEARNER_T>::FeatureParallelTreeLearner(const Config* config):TREELEARNER_T(config) {
}
template <typename TREELEARNER_T>
......
src/treelearner/voting_parallel_tree_learner.cpp
View file @ 50f11a9f
......@@ -15,8 +15,7 @@
namespace LightGBM {
template <typename TREELEARNER_T>
VotingParallelTreeLearner<TREELEARNER_T>::VotingParallelTreeLearner(const Config* config)
:TREELEARNER_T(config) {
VotingParallelTreeLearner<TREELEARNER_T>::VotingParallelTreeLearner(const Config* config):TREELEARNER_T(config) {
top_k_ = this->config_->top_k;
}
......
tests/cpp_tests/testutils.cpp
View file @ 50f11a9f
......@@ -18,10 +18,10 @@ using LightGBM::Random;
namespace LightGBM {
/*!
* Creates a Dataset from the internal repository examples.
*/
int TestUtils::LoadDatasetFromExamples(const char* filename, const char* config, DatasetHandle* out) {
/*!
* Creates a Dataset from the internal repository examples.
*/
int TestUtils::LoadDatasetFromExamples(const char* filename, const char* config, DatasetHandle* out) {
std::string fullPath("examples/");
fullPath += filename;
Log::Info("Debug sample data path: %s", fullPath.c_str());
......@@ -30,12 +30,12 @@ namespace LightGBM {
config,
nullptr,
out);
}
}
/*!
* Creates fake data in the passed vectors.
*/
void TestUtils::CreateRandomDenseData(
/*!
* Creates fake data in the passed vectors.
*/
void TestUtils::CreateRandomDenseData(
int32_t nrows,
int32_t ncols,
int32_t nclasses,
......@@ -54,12 +54,12 @@ namespace LightGBM {
}
CreateRandomMetadata(nrows, nclasses, labels, weights, init_scores, groups);
}
}
/*!
* Creates fake data in the passed vectors.
*/
void TestUtils::CreateRandomSparseData(
/*!
* Creates fake data in the passed vectors.
*/
void TestUtils::CreateRandomSparseData(
int32_t nrows,
int32_t ncols,
int32_t nclasses,
......@@ -89,12 +89,12 @@ namespace LightGBM {
}
CreateRandomMetadata(nrows, nclasses, labels, weights, init_scores, groups);
}
}
/*!
* Creates fake data in the passed vectors.
*/
void TestUtils::CreateRandomMetadata(int32_t nrows,
/*!
* Creates fake data in the passed vectors.
*/
void TestUtils::CreateRandomMetadata(int32_t nrows,
int32_t nclasses,
std::vector<float>* labels,
std::vector<float>* weights,
......@@ -131,9 +131,9 @@ namespace LightGBM {
groups->push_back(group);
}
}
}
}
void TestUtils::StreamDenseDataset(DatasetHandle dataset_handle,
void TestUtils::StreamDenseDataset(DatasetHandle dataset_handle,
int32_t nrows,
int32_t ncols,
int32_t nclasses,
......@@ -206,9 +206,9 @@ namespace LightGBM {
auto cur_time = std::chrono::steady_clock::now();
Log::Info(" Time: %d", cur_time - start_time);
}
}
void TestUtils::StreamSparseDataset(DatasetHandle dataset_handle,
void TestUtils::StreamSparseDataset(DatasetHandle dataset_handle,
int32_t nrows,
int32_t nclasses,
int32_t batch_count,
......@@ -273,14 +273,14 @@ namespace LightGBM {
auto cur_time = std::chrono::steady_clock::now();
Log::Info(" Time: %d", cur_time - start_time);
}
}
/*!
/*!
* Pushes data from 1 thread into a Dataset based on thread_id and nrows.
* e.g. with 100 rows, thread 0 will push rows 0-49, and thread 2 will push rows 50-99.
* Note that rows are still pushed in microbatches within their range.
*/
void TestUtils::PushSparseBatch(DatasetHandle dataset_handle,
void TestUtils::PushSparseBatch(DatasetHandle dataset_handle,
int32_t nrows,
int32_t nclasses,
int32_t batch_count,
......@@ -346,10 +346,10 @@ namespace LightGBM {
groups_ptr += batch_count;
}
}
}
}
void TestUtils::AssertMetadata(const Metadata* metadata,
void TestUtils::AssertMetadata(const Metadata* metadata,
const std::vector<float>* ref_labels,
const std::vector<float>* ref_weights,
const std::vector<double>* ref_init_scores,
......@@ -419,9 +419,9 @@ namespace LightGBM {
} else if (ref_groups) {
FAIL() << "Expected non-null query_boundaries";
}
}
}
const double* TestUtils::CreateInitScoreBatch(std::vector<double>* init_score_batch,
const double* TestUtils::CreateInitScoreBatch(std::vector<double>* init_score_batch,
int32_t index,
int32_t nrows,
int32_t nclasses,
......@@ -435,6 +435,6 @@ namespace LightGBM {
}
}
return init_score_batch->data();
}
}
} // namespace LightGBM
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