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Add float32 histogram (#5624)

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* new single_precision_histogram param was added.

Co-authored-by: SHVETS, KIRILL <kirill.shvets@intel.com>
Co-authored-by: fis <jm.yuan@outlook.com>
This commit is contained in:
ShvetsKS
2020-06-03 06:24:53 +03:00
committed by GitHub
parent e49607af19
commit cd3d14ad0e
10 changed files with 618 additions and 303 deletions
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66
src/common/hist_util.h
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@@ -391,46 +391,52 @@ class GHistIndexBlockMatrix {
std::vector<Block> blocks_;
};
/*!
* \brief histogram of gradient statistics for a single node.
* Consists of multiple GradStats, each entry showing total gradient statistics
* for that particular bin
* Uses global bin id so as to represent all features simultaneously
*/
using GHistRow = Span<tree::GradStats>;
template<typename GradientSumT>
using GHistRow = Span<xgboost::detail::GradientPairInternal<GradientSumT> >;
/*!
* \brief fill a histogram by zeros
*/
void InitilizeHistByZeroes(GHistRow hist, size_t begin, size_t end);
template<typename GradientSumT>
void InitilizeHistByZeroes(GHistRow<GradientSumT> hist, size_t begin, size_t end);
/*!
* \brief Increment hist as dst += add in range [begin, end)
*/
void IncrementHist(GHistRow dst, const GHistRow add, size_t begin, size_t end);
template<typename GradientSumT>
void IncrementHist(GHistRow<GradientSumT> dst, const GHistRow<GradientSumT> add,
size_t begin, size_t end);
/*!
* \brief Copy hist from src to dst in range [begin, end)
*/
void CopyHist(GHistRow dst, const GHistRow src, size_t begin, size_t end);
template<typename GradientSumT>
void CopyHist(GHistRow<GradientSumT> dst, const GHistRow<GradientSumT> src,
size_t begin, size_t end);
/*!
* \brief Compute Subtraction: dst = src1 - src2 in range [begin, end)
*/
void SubtractionHist(GHistRow dst, const GHistRow src1, const GHistRow src2,
template<typename GradientSumT>
void SubtractionHist(GHistRow<GradientSumT> dst, const GHistRow<GradientSumT> src1,
const GHistRow<GradientSumT> src2,
size_t begin, size_t end);
/*!
* \brief histogram of gradient statistics for multiple nodes
*/
template<typename GradientSumT>
class HistCollection {
public:
using GHistRowT = GHistRow<GradientSumT>;
using GradientPairT = xgboost::detail::GradientPairInternal<GradientSumT>;
// access histogram for i-th node
GHistRow operator[](bst_uint nid) const {
GHistRowT operator[](bst_uint nid) const {
constexpr uint32_t kMax = std::numeric_limits<uint32_t>::max();
CHECK_NE(row_ptr_[nid], kMax);
tree::GradStats* ptr =
const_cast<tree::GradStats*>(dmlc::BeginPtr(data_) + row_ptr_[nid]);
GradientPairT* ptr =
const_cast<GradientPairT*>(dmlc::BeginPtr(data_) + row_ptr_[nid]);
return {ptr, nbins_};
}
@@ -473,7 +479,7 @@ class HistCollection {
/*! \brief amount of active nodes in hist collection */
uint32_t n_nodes_added_ = 0;
std::vector<tree::GradStats> data_;
std::vector<GradientPairT> data_;
/*! \brief row_ptr_[nid] locates bin for histogram of node nid */
std::vector<size_t> row_ptr_;
@@ -484,8 +490,11 @@ class HistCollection {
* Supports processing multiple tree-nodes for nested parallelism
* Able to reduce histograms across threads in efficient way
*/
template<typename GradientSumT>
class ParallelGHistBuilder {
public:
using GHistRowT = GHistRow<GradientSumT>;
void Init(size_t nbins) {
if (nbins != nbins_) {
hist_buffer_.Init(nbins);
@@ -496,7 +505,7 @@ class ParallelGHistBuilder {
// Add new elements if needed, mark all hists as unused
// targeted_hists - already allocated hists which should contain final results after Reduce() call
void Reset(size_t nthreads, size_t nodes, const BlockedSpace2d& space,
const std::vector<GHistRow>& targeted_hists) {
const std::vector<GHistRowT>& targeted_hists) {
hist_buffer_.Init(nbins_);
tid_nid_to_hist_.clear();
hist_memory_.clear();
@@ -518,12 +527,12 @@ class ParallelGHistBuilder {
}
// Get specified hist, initialize hist by zeros if it wasn't used before
GHistRow GetInitializedHist(size_t tid, size_t nid) {
GHistRowT GetInitializedHist(size_t tid, size_t nid) {
CHECK_LT(nid, nodes_);
CHECK_LT(tid, nthreads_);
size_t idx = tid_nid_to_hist_.at({tid, nid});
GHistRow hist = hist_memory_[idx];
GHistRowT hist = hist_memory_[idx];
if (!hist_was_used_[tid * nodes_ + nid]) {
InitilizeHistByZeroes(hist, 0, hist.size());
@@ -538,14 +547,14 @@ class ParallelGHistBuilder {
CHECK_GT(end, begin);
CHECK_LT(nid, nodes_);
GHistRow dst = targeted_hists_[nid];
GHistRowT dst = targeted_hists_[nid];
bool is_updated = false;
for (size_t tid = 0; tid < nthreads_; ++tid) {
if (hist_was_used_[tid * nodes_ + nid]) {
is_updated = true;
const size_t idx = tid_nid_to_hist_.at({tid, nid});
GHistRow src = hist_memory_[idx];
GHistRowT src = hist_memory_[idx];
if (dst.data() != src.data()) {
IncrementHist(dst, src, begin, end);
@@ -636,7 +645,7 @@ class ParallelGHistBuilder {
/*! \brief number of nodes which will be processed in parallel */
size_t nodes_ = 0;
/*! \brief Buffer for additional histograms for Parallel processing */
HistCollection hist_buffer_;
HistCollection<GradientSumT> hist_buffer_;
/*!
* \brief Marks which hists were used, it means that they should be merged.
* Contains only {true or false} values
@@ -647,9 +656,9 @@ class ParallelGHistBuilder {
/*! \brief Buffer for additional histograms for Parallel processing */
std::vector<bool> threads_to_nids_map_;
/*! \brief Contains histograms for final results */
std::vector<GHistRow> targeted_hists_;
std::vector<GHistRowT> targeted_hists_;
/*! \brief Allocated memory for histograms used for construction */
std::vector<GHistRow> hist_memory_;
std::vector<GHistRowT> hist_memory_;
/*! \brief map pair {tid, nid} to index of allocated histogram from hist_memory_ */
std::map<std::pair<size_t, size_t>, size_t> tid_nid_to_hist_;
};
@@ -657,8 +666,11 @@ class ParallelGHistBuilder {
/*!
* \brief builder for histograms of gradient statistics
*/
template<typename GradientSumT>
class GHistBuilder {
public:
using GHistRowT = GHistRow<GradientSumT>;
GHistBuilder() = default;
GHistBuilder(size_t nthread, uint32_t nbins) : nthread_{nthread}, nbins_{nbins} {}
@@ -666,15 +678,17 @@ class GHistBuilder {
void BuildHist(const std::vector<GradientPair>& gpair,
const RowSetCollection::Elem row_indices,
const GHistIndexMatrix& gmat,
GHistRow hist,
GHistRowT hist,
bool isDense);
// same, with feature grouping
void BuildBlockHist(const std::vector<GradientPair>& gpair,
const RowSetCollection::Elem row_indices,
const GHistIndexBlockMatrix& gmatb,
GHistRow hist);
GHistRowT hist);
// construct a histogram via subtraction trick
void SubtractionTrick(GHistRow self, GHistRow sibling, GHistRow parent);
void SubtractionTrick(GHistRowT self,
GHistRowT sibling,
GHistRowT parent);
uint32_t GetNumBins() const {
return nbins_;