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Unverified Commit 9489f878 authored by shiyu1994's avatar shiyu1994 Committed by GitHub
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Add default definition for GetColWiseData and GetColWiseData (#5413) 

* add default definition for GetColWiseData and GetColWiseData

* fix warnings of template instantiation

* remove files in Makevars and LightGBM.vcxproj
parent 4a9b08ea
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Showing with 364 additions and 435 deletions
R-package/src/Makevars.in
View file @ 9489f878
...@@ -37,10 +37,6 @@ OBJECTS = \ ...@@ -37,10 +37,6 @@ OBJECTS = \
io/parser.o \ io/parser.o \
io/train_share_states.o \ io/train_share_states.o \
io/tree.o \ io/tree.o \
io/dense_bin.o \
io/sparse_bin.o \
io/multi_val_dense_bin.o \
io/multi_val_sparse_bin.o \
metric/dcg_calculator.o \ metric/dcg_calculator.o \
metric/metric.o \ metric/metric.o \
objective/objective_function.o \ objective/objective_function.o \
......
R-package/src/Makevars.win.in
View file @ 9489f878
...@@ -38,10 +38,6 @@ OBJECTS = \ ...@@ -38,10 +38,6 @@ OBJECTS = \
io/parser.o \ io/parser.o \
io/train_share_states.o \ io/train_share_states.o \
io/tree.o \ io/tree.o \
io/dense_bin.o \
io/sparse_bin.o \
io/multi_val_dense_bin.o \
io/multi_val_sparse_bin.o \
metric/dcg_calculator.o \ metric/dcg_calculator.o \
metric/metric.o \ metric/metric.o \
objective/objective_function.o \ objective/objective_function.o \
......
src/io/bin.cpp
View file @ 9489f878
...@@ -719,4 +719,368 @@ namespace LightGBM { ...@@ -719,4 +719,368 @@ namespace LightGBM {
} }
} }
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 8;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 16;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 32;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 4;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 8;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 16;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 32;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 4;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 8;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint8_t>(this, 0));
}
return nullptr;
}
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 16;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint16_t>(this, 0));
}
return nullptr;
}
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 32;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint32_t>(this, 0));
}
return nullptr;
}
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 8;
*bin_iterator = new SparseBinIterator<uint8_t>(this, 0);
return nullptr;
}
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 16;
*bin_iterator = new SparseBinIterator<uint16_t>(this, 0);
return nullptr;
}
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 32;
*bin_iterator = new SparseBinIterator<uint32_t>(this, 0);
return nullptr;
}
#ifdef USE_CUDA_EXP
template <>
const void* MultiValDenseBin<uint8_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
template <>
const void* MultiValDenseBin<uint16_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint16_t* data_ptr = data_.data();
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_ptr);
*bit_type = 16;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
template <>
const void* MultiValDenseBin<uint32_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint32_t* data_ptr = data_.data();
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_ptr);
*bit_type = 32;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
template <>
const void* MultiValSparseBin<uint16_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}
#endif // USE_CUDA_EXP
} // namespace LightGBM } // namespace LightGBM
src/io/dense_bin.cpp deleted 100644 → 0
View file @ 4a9b08ea
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for
* license information.
*/
#include "dense_bin.hpp"
namespace LightGBM {
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 8;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 16;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 32;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int /*num_threads*/) const {
*is_sparse = false;
*bit_type = 4;
bin_iterator->clear();
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint8_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 8;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint16_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 16;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint32_t, false>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 32;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
template <>
const void* DenseBin<uint8_t, true>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = false;
*bit_type = 4;
*bin_iterator = nullptr;
return reinterpret_cast<const void*>(data_.data());
}
} // namespace LightGBM
src/io/multi_val_dense_bin.cpp deleted 100644 → 0
View file @ 4a9b08ea
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for license information.
*/
#include "multi_val_dense_bin.hpp"
namespace LightGBM {
#ifdef USE_CUDA_EXP
template <>
const void* MultiValDenseBin<uint8_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
template <>
const void* MultiValDenseBin<uint16_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint16_t* data_ptr = data_.data();
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_ptr);
*bit_type = 16;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
template <>
const void* MultiValDenseBin<uint32_t>::GetRowWiseData(uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint32_t* data_ptr = data_.data();
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_ptr);
*bit_type = 32;
*total_size = static_cast<size_t>(num_data_) * static_cast<size_t>(num_feature_);
CHECK_EQ(*total_size, data_.size());
*is_sparse = false;
*out_data_ptr = nullptr;
*data_ptr_bit_type = 0;
return to_return;
}
#endif // USE_CUDA_EXP
} // namespace LightGBM
src/io/multi_val_sparse_bin.cpp deleted 100644 → 0
View file @ 4a9b08ea
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for license information.
*/
#include "multi_val_sparse_bin.hpp"
namespace LightGBM {
#ifdef USE_CUDA_EXP
template <>
const void* MultiValSparseBin<uint16_t, uint8_t>::GetRowWiseData(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = data_.data();
*bit_type = 8;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 16;
*total_size = data_.size();
*is_sparse = true;
*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(
uint8_t* bit_type,
size_t* total_size,
bool* is_sparse,
const void** out_data_ptr,
uint8_t* data_ptr_bit_type) const {
const uint8_t* to_return = reinterpret_cast<const uint8_t*>(data_.data());
*bit_type = 32;
*total_size = data_.size();
*is_sparse = true;
*out_data_ptr = reinterpret_cast<const uint8_t*>(row_ptr_.data());
*data_ptr_bit_type = 64;
return to_return;
}
#endif // USE_CUDA_EXP
} // namespace LightGBM
src/io/sparse_bin.cpp deleted 100644 → 0
View file @ 4a9b08ea
/*!
* Copyright (c) 2021 Microsoft Corporation. All rights reserved.
* Licensed under the MIT License. See LICENSE file in the project root for
* license information.
*/
#include "sparse_bin.hpp"
namespace LightGBM {
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 8;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint8_t>(this, 0));
}
return nullptr;
}
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 16;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint16_t>(this, 0));
}
return nullptr;
}
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
std::vector<BinIterator*>* bin_iterator,
const int num_threads) const {
*is_sparse = true;
*bit_type = 32;
for (int thread_index = 0; thread_index < num_threads; ++thread_index) {
bin_iterator->emplace_back(new SparseBinIterator<uint32_t>(this, 0));
}
return nullptr;
}
template <>
const void* SparseBin<uint8_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 8;
*bin_iterator = new SparseBinIterator<uint8_t>(this, 0);
return nullptr;
}
template <>
const void* SparseBin<uint16_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 16;
*bin_iterator = new SparseBinIterator<uint16_t>(this, 0);
return nullptr;
}
template <>
const void* SparseBin<uint32_t>::GetColWiseData(
uint8_t* bit_type,
bool* is_sparse,
BinIterator** bin_iterator) const {
*is_sparse = true;
*bit_type = 32;
*bin_iterator = new SparseBinIterator<uint32_t>(this, 0);
return nullptr;
}
} // namespace LightGBM
windows/LightGBM.vcxproj
View file @ 9489f878
...@@ -317,14 +317,10 @@ ...@@ -317,14 +317,10 @@
<ClCompile Include="..\src\io\config_auto.cpp" /> <ClCompile Include="..\src\io\config_auto.cpp" />
<ClCompile Include="..\src\io\dataset.cpp" /> <ClCompile Include="..\src\io\dataset.cpp" />
<ClCompile Include="..\src\io\dataset_loader.cpp" /> <ClCompile Include="..\src\io\dataset_loader.cpp" />
<ClCompile Include="..\src\io\dense_bin.cpp" />
<ClCompile Include="..\src\io\file_io.cpp" /> <ClCompile Include="..\src\io\file_io.cpp" />
<ClCompile Include="..\src\io\json11.cpp" /> <ClCompile Include="..\src\io\json11.cpp" />
<ClCompile Include="..\src\io\metadata.cpp" /> <ClCompile Include="..\src\io\metadata.cpp" />
<ClCompile Include="..\src\io\multi_val_dense_bin.cpp" />
<ClCompile Include="..\src\io\multi_val_sparse_bin.cpp" />
<ClCompile Include="..\src\io\parser.cpp" /> <ClCompile Include="..\src\io\parser.cpp" />
<ClCompile Include="..\src\io\sparse_bin.cpp" />
<ClCompile Include="..\src\io\train_share_states.cpp" /> <ClCompile Include="..\src\io\train_share_states.cpp" />
<ClCompile Include="..\src\io\tree.cpp" /> <ClCompile Include="..\src\io\tree.cpp" />
<ClCompile Include="..\src\metric\dcg_calculator.cpp" /> <ClCompile Include="..\src\metric\dcg_calculator.cpp" />
......
windows/LightGBM.vcxproj.filters
View file @ 9489f878
...@@ -326,17 +326,5 @@ ...@@ -326,17 +326,5 @@
<ClCompile Include="..\src\treelearner\linear_tree_learner.cpp"> <ClCompile Include="..\src\treelearner\linear_tree_learner.cpp">
<Filter>src\treelearner</Filter> <Filter>src\treelearner</Filter>
</ClCompile> </ClCompile>
<ClCompile Include="..\src\io\multi_val_dense_bin.cpp">
<Filter>src\io</Filter>
</ClCompile>
<ClCompile Include="..\src\io\multi_val_sparse_bin.cpp">
<Filter>src\io</Filter>
</ClCompile>
<ClCompile Include="..\src\io\dense_bin.cpp">
<Filter>src\io</Filter>
</ClCompile>
<ClCompile Include="..\src\io\sparse_bin.cpp">
<Filter>src\io</Filter>
</ClCompile>
</ItemGroup> </ItemGroup>
</Project> </Project>
\ No newline at end of file
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