xgboost/booster/xgboost_data.h

357 lines
14 KiB
C++

#ifndef XGBOOST_DATA_H
#define XGBOOST_DATA_H
/*!
* \file xgboost_data.h
* \brief the input data structure for gradient boosting
* \author Tianqi Chen: tianqi.tchen@gmail.com
*/
#include <vector>
#include <climits>
#include "../utils/xgboost_utils.h"
#include "../utils/xgboost_stream.h"
#include "../utils/xgboost_matrix_csr.h"
namespace xgboost{
namespace booster{
/*! \brief interger type used in boost */
typedef int bst_int;
/*! \brief unsigned interger type used in boost */
typedef unsigned bst_uint;
/*! \brief float type used in boost */
typedef float bst_float;
/*! \brief debug option for booster */
const bool bst_debug = false;
};
};
namespace xgboost{
namespace booster{
/**
* \brief This is a interface, defining the way to access features,
* by column or by row. This interface is used to make implementation
* of booster does not depend on how feature is stored.
*
* Why template instead of virtual class: for efficiency
* feature matrix is going to be used by most inner loop of the algorithm
*
* \tparam Derived type of actual implementation
* \sa FMatrixS: most of time FMatrixS is sufficient, refer to it if you find it confusing
*/
template<typename Derived>
struct FMatrix{
public:
/*! \brief exmaple iterator over one row */
struct RowIter{
/*!
* \brief move to next position
* \return whether there is element in next position
*/
inline bool Next( void );
/*! \return feature index in current position */
inline bst_uint findex( void ) const;
/*! \return feature value in current position */
inline bst_float fvalue( void ) const;
};
/*! \brief example iterator over one column */
struct ColIter{
/*!
* \brief move to next position
* \return whether there is element in next position
*/
inline bool Next( void );
/*! \return row index of current position */
inline bst_uint rindex( void ) const;
/*! \return feature value in current position */
inline bst_float fvalue( void ) const;
};
/*! \brief backward iterator over column */
struct ColBackIter : public ColIter {};
public:
/*!
* \brief get number of rows
* \return number of rows
*/
inline size_t NumRow( void ) const;
/*!
* \brief get number of columns
* \return number of columns
*/
inline size_t NumCol( void ) const;
/*!
* \brief get row iterator
* \param ridx row index
* \return row iterator
*/
inline RowIter GetRow( size_t ridx ) const;
/*! \return whether column access is enabled */
inline bool HaveColAccess( void ) const;
/*!
* \brief get column iterator, the columns must be sorted by feature value
* \param ridx column index
* \return column iterator
*/
inline ColIter GetSortedCol( size_t ridx ) const;
/*!
* \brief get column backward iterator, starts from biggest fvalue, and iterator back
* \param ridx column index
* \return reverse column iterator
*/
inline ColBackIter GetReverseSortedCol( size_t ridx ) const;
};
};
};
namespace xgboost{
namespace booster{
/*!
* \brief feature matrix to store training instance, in sparse CSR format
*/
class FMatrixS: public FMatrix<FMatrixS>{
public:
/*! \brief one entry in a row */
struct REntry{
/*! \brief feature index */
bst_uint findex;
/*! \brief feature value */
bst_float fvalue;
/*! \brief constructor */
REntry( void ){}
/*! \brief constructor */
REntry( bst_uint findex, bst_float fvalue ) : findex(findex), fvalue(fvalue){}
inline static bool cmp_fvalue( const REntry &a, const REntry &b ){
return a.fvalue < b.fvalue;
}
};
/*! \brief one row of sparse feature matrix */
struct Line{
/*! \brief array of feature index */
const REntry *data_;
/*! \brief size of the data */
bst_uint len;
/*! \brief get k-th element */
inline const REntry& operator[]( unsigned i ) const{
return data_[i];
}
};
/*! \brief row iterator */
struct RowIter{
const REntry *dptr_, *end_;
inline bool Next( void ){
if( dptr_ == end_ ) return false;
else{
++ dptr_; return true;
}
}
inline bst_uint findex( void ) const{
return dptr_->findex;
}
inline bst_float fvalue( void ) const{
return dptr_->fvalue;
}
};
/*! \brief column iterator */
struct ColIter: public RowIter{
inline bst_uint rindex( void ) const{
return this->findex();
}
};
/*! \brief reverse column iterator */
struct ColBackIter: public ColIter{
// shadows RowIter::Next
inline bool Next( void ){
if( dptr_ == end_ ) return false;
else{
-- dptr_; return true;
}
}
};
public:
/*! \brief constructor */
FMatrixS( void ){ this->Clear(); }
/*! \brief get number of rows */
inline size_t NumRow( void ) const{
return row_ptr_.size() - 1;
}
/*!
* \brief get number of nonzero entries
* \return number of nonzero entries
*/
inline size_t NumEntry( void ) const{
return row_data_.size();
}
/*! \brief clear the storage */
inline void Clear( void ){
row_ptr_.clear();
row_ptr_.push_back( 0 );
row_data_.clear();
col_ptr_.clear();
col_data_.clear();
}
/*! \brief get sparse part of current row */
inline Line operator[]( size_t sidx ) const{
Line sp;
utils::Assert( !bst_debug || sidx < this->NumRow(), "row id exceed bound" );
sp.len = static_cast<bst_uint>( row_ptr_[ sidx + 1 ] - row_ptr_[ sidx ] );
sp.data_ = &row_data_[ row_ptr_[ sidx ] ];
return sp;
}
/*!
* \brief add a row to the matrix, with data stored in STL container
* \param findex feature index
* \param fvalue feature value
* \param fstart start bound of feature
* \param fend end bound range of feature
* \return the row id added line
*/
inline size_t AddRow( const std::vector<bst_uint> &findex,
const std::vector<bst_float> &fvalue,
unsigned fstart = 0, unsigned fend = UINT_MAX ){
utils::Assert( findex.size() == fvalue.size() );
unsigned cnt = 0;
for( size_t i = 0; i < findex.size(); i ++ ){
if( findex[i] < fstart || findex[i] >= fend ) continue;
row_data_.push_back( REntry( findex[i], fvalue[i] ) );
cnt ++;
}
row_ptr_.push_back( row_ptr_.back() + cnt );
return row_ptr_.size() - 2;
}
/*! \brief get row iterator*/
inline RowIter GetRow( size_t ridx ) const{
utils::Assert( !bst_debug || ridx < this->NumRow(), "row id exceed bound" );
RowIter it;
it.dptr_ = &row_data_[ row_ptr_[ridx] ] - 1;
it.end_ = &row_data_[ row_ptr_[ridx+1] ] - 1;
return it;
}
public:
/*! \return whether column access is enabled */
inline bool HaveColAccess( void ) const{
return col_ptr_.size() != 0 && col_data_.size() == row_data_.size();
}
/*! \brief get number of colmuns */
inline size_t NumCol( void ) const{
utils::Assert( this->HaveColAccess() );
return col_ptr_.size() - 1;
}
/*! \brief get col iterator*/
inline ColIter GetSortedCol( size_t cidx ) const{
utils::Assert( !bst_debug || cidx < this->NumCol(), "col id exceed bound" );
ColIter it;
it.dptr_ = &col_data_[ col_ptr_[cidx] ] - 1;
it.end_ = &col_data_[ col_ptr_[cidx+1] ] - 1;
return it;
}
/*! \brief get col iterator */
inline ColBackIter GetReverseSortedCol( size_t cidx ) const{
utils::Assert( !bst_debug || cidx < this->NumCol(), "col id exceed bound" );
ColBackIter it;
it.dptr_ = &col_data_[ col_ptr_[cidx+1] ];
it.end_ = &col_data_[ col_ptr_[cidx] ];
return it;
}
/*!
* \brief intialize the data so that we have both column and row major
* access, call this whenever we need column access
*/
inline void InitData( void ){
utils::SparseCSRMBuilder<REntry> builder( col_ptr_, col_data_ );
builder.InitBudget( 0 );
for( size_t i = 0; i < this->NumRow(); i ++ ){
for( RowIter it = this->GetRow(i); it.Next(); ){
builder.AddBudget( it.findex() );
}
}
builder.InitStorage();
for( size_t i = 0; i < this->NumRow(); i ++ ){
for( RowIter it = this->GetRow(i); it.Next(); ){
builder.PushElem( it.findex(), REntry( (bst_uint)i, it.fvalue() ) );
}
}
// sort columns
unsigned ncol = static_cast<unsigned>( this->NumCol() );
for( unsigned i = 0; i < ncol; i ++ ){
std::sort( &col_data_[ col_ptr_[ i ] ], &col_data_[ col_ptr_[ i+1 ] ], REntry::cmp_fvalue );
}
}
/*!
* \brief save data to binary stream
* note: since we have size_t in ptr,
* the function is not consistent between 64bit and 32bit machine
* \param fo output stream
*/
inline void SaveBinary( utils::IStream &fo ) const{
FMatrixS::SaveBinary( fo, row_ptr_, row_data_ );
int col_access = this->HaveColAccess() ? 1 : 0;
fo.Write( &col_access, sizeof(int) );
if( col_access != 0 ){
FMatrixS::SaveBinary( fo, col_ptr_, col_data_ );
}
}
/*!
* \brief load data from binary stream
* note: since we have size_t in ptr,
* the function is not consistent between 64bit and 32bit machin
* \param fi input stream
*/
inline void LoadBinary( utils::IStream &fi ){
FMatrixS::LoadBinary( fi, row_ptr_, row_data_ );
int col_access;
fi.Read( &col_access, sizeof(int) );
if( col_access != 0 ){
FMatrixS::LoadBinary( fi, col_ptr_, col_data_ );
}
}
private:
/*!
* \brief save data to binary stream
* \param fo output stream
* \param ptr pointer data
* \param data data content
*/
inline static void SaveBinary( utils::IStream &fo,
const std::vector<size_t> &ptr,
const std::vector<REntry> &data ){
size_t nrow = ptr.size() - 1;
fo.Write( &nrow, sizeof(size_t) );
fo.Write( &ptr[0], ptr.size() * sizeof(size_t) );
if( data.size() != 0 ){
fo.Write( &data[0] , data.size() * sizeof(REntry) );
}
}
/*!
* \brief load data from binary stream
* \param fi input stream
* \param ptr pointer data
* \param data data content
*/
inline static void LoadBinary( utils::IStream &fi,
std::vector<size_t> &ptr,
std::vector<REntry> &data ){
size_t nrow;
utils::Assert( fi.Read( &nrow, sizeof(size_t) ) != 0, "Load FMatrixS" );
ptr.resize( nrow + 1 );
utils::Assert( fi.Read( &ptr[0], ptr.size() * sizeof(size_t) ), "Load FMatrixS" );
data.resize( ptr.back() );
if( data.size() != 0 ){
utils::Assert( fi.Read( &data[0] , data.size() * sizeof(REntry) ) , "Load FMatrixS" );
}
}
protected:
/*! \brief row pointer of CSR sparse storage */
std::vector<size_t> row_ptr_;
/*! \brief data in the row */
std::vector<REntry> row_data_;
/*! \brief column pointer of CSC format */
std::vector<size_t> col_ptr_;
/*! \brief column datas */
std::vector<REntry> col_data_;
};
};
};
#endif