xgboost/src/common/partition_builder.h
farfarawayzyt d7c14496d2
fix typo in arguments of PartitionBuilder::Init (#7113)
Co-authored-by: Yuntian Zhang <zhangyt@lamda.nju.edu.cn>
2021-07-16 15:46:22 +08:00

229 lines
8.2 KiB
C++

/*!
* Copyright 2021 by Contributors
* \file row_set.h
* \brief Quick Utility to compute subset of rows
* \author Philip Cho, Tianqi Chen
*/
#ifndef XGBOOST_COMMON_PARTITION_BUILDER_H_
#define XGBOOST_COMMON_PARTITION_BUILDER_H_
#include <xgboost/data.h>
#include <algorithm>
#include <vector>
#include <utility>
#include <memory>
#include "xgboost/tree_model.h"
#include "../common/column_matrix.h"
namespace xgboost {
namespace common {
// The builder is required for samples partition to left and rights children for set of nodes
// Responsible for:
// 1) Effective memory allocation for intermediate results for multi-thread work
// 2) Merging partial results produced by threads into original row set (row_set_collection_)
// BlockSize is template to enable memory alignment easily with C++11 'alignas()' feature
template<size_t BlockSize>
class PartitionBuilder {
public:
template<typename Func>
void Init(const size_t n_tasks, size_t n_nodes, Func funcNTask) {
left_right_nodes_sizes_.resize(n_nodes);
blocks_offsets_.resize(n_nodes+1);
blocks_offsets_[0] = 0;
for (size_t i = 1; i < n_nodes+1; ++i) {
blocks_offsets_[i] = blocks_offsets_[i-1] + funcNTask(i-1);
}
if (n_tasks > max_n_tasks_) {
mem_blocks_.resize(n_tasks);
max_n_tasks_ = n_tasks;
}
}
// split row indexes (rid_span) to 2 parts (left_part, right_part) depending
// on comparison of indexes values (idx_span) and split point (split_cond)
// Handle dense columns
// Analog of std::stable_partition, but in no-inplace manner
template <bool default_left, bool any_missing, typename ColumnType>
inline std::pair<size_t, size_t> PartitionKernel(const ColumnType& column,
common::Span<const size_t> rid_span, const int32_t split_cond,
common::Span<size_t> left_part, common::Span<size_t> right_part) {
size_t* p_left_part = left_part.data();
size_t* p_right_part = right_part.data();
size_t nleft_elems = 0;
size_t nright_elems = 0;
auto state = column.GetInitialState(rid_span.front());
for (auto rid : rid_span) {
const int32_t bin_id = column.GetBinIdx(rid, &state);
if (any_missing && bin_id == ColumnType::kMissingId) {
if (default_left) {
p_left_part[nleft_elems++] = rid;
} else {
p_right_part[nright_elems++] = rid;
}
} else {
if (bin_id <= split_cond) {
p_left_part[nleft_elems++] = rid;
} else {
p_right_part[nright_elems++] = rid;
}
}
}
return {nleft_elems, nright_elems};
}
template <typename BinIdxType, bool any_missing>
void Partition(const size_t node_in_set, const size_t nid, const common::Range1d range,
const int32_t split_cond,
const ColumnMatrix& column_matrix, const RegTree& tree, const size_t* rid) {
common::Span<const size_t> rid_span(rid + range.begin(), rid + range.end());
common::Span<size_t> left = GetLeftBuffer(node_in_set,
range.begin(), range.end());
common::Span<size_t> right = GetRightBuffer(node_in_set,
range.begin(), range.end());
const bst_uint fid = tree[nid].SplitIndex();
const bool default_left = tree[nid].DefaultLeft();
const auto column_ptr = column_matrix.GetColumn<BinIdxType, any_missing>(fid);
std::pair<size_t, size_t> child_nodes_sizes;
if (column_ptr->GetType() == xgboost::common::kDenseColumn) {
const common::DenseColumn<BinIdxType, any_missing>& column =
static_cast<const common::DenseColumn<BinIdxType, any_missing>& >(*(column_ptr.get()));
if (default_left) {
child_nodes_sizes = PartitionKernel<true, any_missing>(column, rid_span,
split_cond, left, right);
} else {
child_nodes_sizes = PartitionKernel<false, any_missing>(column, rid_span,
split_cond, left, right);
}
} else {
CHECK_EQ(any_missing, true);
const common::SparseColumn<BinIdxType>& column
= static_cast<const common::SparseColumn<BinIdxType>& >(*(column_ptr.get()));
if (default_left) {
child_nodes_sizes = PartitionKernel<true, any_missing>(column, rid_span,
split_cond, left, right);
} else {
child_nodes_sizes = PartitionKernel<false, any_missing>(column, rid_span,
split_cond, left, right);
}
}
const size_t n_left = child_nodes_sizes.first;
const size_t n_right = child_nodes_sizes.second;
SetNLeftElems(node_in_set, range.begin(), range.end(), n_left);
SetNRightElems(node_in_set, range.begin(), range.end(), n_right);
}
// allocate thread local memory, should be called for each specific task
void AllocateForTask(size_t id) {
if (mem_blocks_[id].get() == nullptr) {
BlockInfo* local_block_ptr = new BlockInfo;
CHECK_NE(local_block_ptr, (BlockInfo*)nullptr);
mem_blocks_[id].reset(local_block_ptr);
}
}
common::Span<size_t> GetLeftBuffer(int nid, size_t begin, size_t end) {
const size_t task_idx = GetTaskIdx(nid, begin);
return { mem_blocks_.at(task_idx)->Left(), end - begin };
}
common::Span<size_t> GetRightBuffer(int nid, size_t begin, size_t end) {
const size_t task_idx = GetTaskIdx(nid, begin);
return { mem_blocks_.at(task_idx)->Right(), end - begin };
}
void SetNLeftElems(int nid, size_t begin, size_t end, size_t n_left) {
size_t task_idx = GetTaskIdx(nid, begin);
mem_blocks_.at(task_idx)->n_left = n_left;
}
void SetNRightElems(int nid, size_t begin, size_t end, size_t n_right) {
size_t task_idx = GetTaskIdx(nid, begin);
mem_blocks_.at(task_idx)->n_right = n_right;
}
size_t GetNLeftElems(int nid) const {
return left_right_nodes_sizes_[nid].first;
}
size_t GetNRightElems(int nid) const {
return left_right_nodes_sizes_[nid].second;
}
// Each thread has partial results for some set of tree-nodes
// The function decides order of merging partial results into final row set
void CalculateRowOffsets() {
for (size_t i = 0; i < blocks_offsets_.size()-1; ++i) {
size_t n_left = 0;
for (size_t j = blocks_offsets_[i]; j < blocks_offsets_[i+1]; ++j) {
mem_blocks_[j]->n_offset_left = n_left;
n_left += mem_blocks_[j]->n_left;
}
size_t n_right = 0;
for (size_t j = blocks_offsets_[i]; j < blocks_offsets_[i+1]; ++j) {
mem_blocks_[j]->n_offset_right = n_left + n_right;
n_right += mem_blocks_[j]->n_right;
}
left_right_nodes_sizes_[i] = {n_left, n_right};
}
}
void MergeToArray(int nid, size_t begin, size_t* rows_indexes) {
size_t task_idx = GetTaskIdx(nid, begin);
size_t* left_result = rows_indexes + mem_blocks_[task_idx]->n_offset_left;
size_t* right_result = rows_indexes + mem_blocks_[task_idx]->n_offset_right;
const size_t* left = mem_blocks_[task_idx]->Left();
const size_t* right = mem_blocks_[task_idx]->Right();
std::copy_n(left, mem_blocks_[task_idx]->n_left, left_result);
std::copy_n(right, mem_blocks_[task_idx]->n_right, right_result);
}
size_t GetTaskIdx(int nid, size_t begin) {
return blocks_offsets_[nid] + begin / BlockSize;
}
protected:
struct BlockInfo{
size_t n_left;
size_t n_right;
size_t n_offset_left;
size_t n_offset_right;
size_t* Left() {
return &left_data_[0];
}
size_t* Right() {
return &right_data_[0];
}
private:
size_t left_data_[BlockSize];
size_t right_data_[BlockSize];
};
std::vector<std::pair<size_t, size_t>> left_right_nodes_sizes_;
std::vector<size_t> blocks_offsets_;
std::vector<std::shared_ptr<BlockInfo>> mem_blocks_;
size_t max_n_tasks_ = 0;
};
} // namespace common
} // namespace xgboost
#endif // XGBOOST_COMMON_PARTITION_BUILDER_H_