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sparse-matrix.cc
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// matrix/sparse-matrix.cc
// Copyright 2015 Johns Hopkins University (author: Daniel Povey)
// 2015 Guoguo Chen
// 2017 Shiyin Kang
// See ../../COPYING for clarification regarding multiple authors
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#include <algorithm>
#include <limits>
#include <string>
#include "matrix/sparse-matrix.h"
#include "matrix/kaldi-matrix.h"
namespace kaldi {
template <typename Real>
std::pair<MatrixIndexT, Real>* SparseVector<Real>::Data() {
if (pairs_.empty())
return NULL;
else
return &(pairs_[0]);
}
template <typename Real>
const std::pair<MatrixIndexT, Real>* SparseVector<Real>::Data() const {
if (pairs_.empty())
return NULL;
else
return &(pairs_[0]);
}
template <typename Real>
Real SparseVector<Real>::Sum() const {
Real sum = 0;
for (int32 i = 0; i < pairs_.size(); ++i) {
sum += pairs_[i].second;
}
return sum;
}
template<typename Real>
void SparseVector<Real>::Scale(Real alpha) {
for (int32 i = 0; i < pairs_.size(); ++i)
pairs_[i].second *= alpha;
}
template <typename Real>
template <typename OtherReal>
void SparseVector<Real>::CopyElementsToVec(VectorBase<OtherReal> *vec) const {
KALDI_ASSERT(vec->Dim() == this->dim_);
vec->SetZero();
OtherReal *other_data = vec->Data();
typename std::vector<std::pair<MatrixIndexT, Real> >::const_iterator
iter = pairs_.begin(), end = pairs_.end();
for (; iter != end; ++iter)
other_data[iter->first] = iter->second;
}
template
void SparseVector<float>::CopyElementsToVec(VectorBase<float> *vec) const;
template
void SparseVector<float>::CopyElementsToVec(VectorBase<double> *vec) const;
template
void SparseVector<double>::CopyElementsToVec(VectorBase<float> *vec) const;
template
void SparseVector<double>::CopyElementsToVec(VectorBase<double> *vec) const;
template <typename Real>
template <typename OtherReal>
void SparseVector<Real>::AddToVec(Real alpha,
VectorBase<OtherReal> *vec) const {
KALDI_ASSERT(vec->Dim() == dim_);
OtherReal *other_data = vec->Data();
typename std::vector<std::pair<MatrixIndexT, Real> >::const_iterator
iter = pairs_.begin(), end = pairs_.end();
if (alpha == 1.0) { // treat alpha==1.0 case specially.
for (; iter != end; ++iter)
other_data[iter->first] += iter->second;
} else {
for (; iter != end; ++iter)
other_data[iter->first] += alpha * iter->second;
}
}
template
void SparseVector<float>::AddToVec(float alpha, VectorBase<float> *vec) const;
template
void SparseVector<float>::AddToVec(float alpha, VectorBase<double> *vec) const;
template
void SparseVector<double>::AddToVec(double alpha, VectorBase<float> *vec) const;
template
void SparseVector<double>::AddToVec(double alpha,
VectorBase<double> *vec) const;
template <typename Real>
template <typename OtherReal>
void SparseVector<Real>::CopyFromSvec(const SparseVector<OtherReal> &other) {
dim_ = other.Dim();
pairs_.clear();
if (dim_ == 0) return;
for (int32 i = 0; i < other.NumElements(); ++i) {
pairs_.push_back(std::make_pair(
other.GetElement(i).first,
static_cast<Real>(other.GetElement(i).second)));
}
}
template
void SparseVector<float>::CopyFromSvec(const SparseVector<float> &svec);
template
void SparseVector<float>::CopyFromSvec(const SparseVector<double> &svec);
template
void SparseVector<double>::CopyFromSvec(const SparseVector<float> &svec);
template
void SparseVector<double>::CopyFromSvec(const SparseVector<double> &svec);
template <typename Real>
SparseVector<Real>& SparseVector<Real>::operator = (
const SparseVector<Real> &other) {
this->CopyFromSvec(other);
dim_ = other.dim_;
pairs_ = other.pairs_;
return *this;
}
template <typename Real>
void SparseVector<Real>::Swap(SparseVector<Real> *other) {
pairs_.swap(other->pairs_);
std::swap(dim_, other->dim_);
}
template <typename Real>
void SparseVector<Real>::Write(std::ostream &os, bool binary) const {
if (binary) {
WriteToken(os, binary, "SV");
WriteBasicType(os, binary, dim_);
MatrixIndexT num_elems = pairs_.size();
WriteBasicType(os, binary, num_elems);
typename std::vector<std::pair<MatrixIndexT, Real> >::const_iterator
iter = pairs_.begin(), end = pairs_.end();
for (; iter != end; ++iter) {
WriteBasicType(os, binary, iter->first);
WriteBasicType(os, binary, iter->second);
}
} else {
// In text-mode, use a human-friendly, script-friendly format;
// format is "dim=5 [ 0 0.2 3 0.9 ] "
os << "dim=" << dim_ << " [ ";
typename std::vector<std::pair<MatrixIndexT, Real> >::const_iterator
iter = pairs_.begin(), end = pairs_.end();
for (; iter != end; ++iter)
os << iter->first << ' ' << iter->second << ' ';
os << "] ";
}
}
template <typename Real>
void SparseVector<Real>::Read(std::istream &is, bool binary) {
if (binary) {
ExpectToken(is, binary, "SV");
ReadBasicType(is, binary, &dim_);
KALDI_ASSERT(dim_ >= 0);
int32 num_elems;
ReadBasicType(is, binary, &num_elems);
KALDI_ASSERT(num_elems >= 0 && num_elems <= dim_);
pairs_.resize(num_elems);
typename std::vector<std::pair<MatrixIndexT, Real> >::iterator
iter = pairs_.begin(), end = pairs_.end();
for (; iter != end; ++iter) {
ReadBasicType(is, binary, &(iter->first));
ReadBasicType(is, binary, &(iter->second));
}
} else {
// In text-mode, format is "dim=5 [ 0 0.2 3 0.9 ]
std::string str;
is >> str;
if (str.substr(0, 4) != "dim=")
KALDI_ERR << "Reading sparse vector, expected 'dim=xxx', got " << str;
std::string dim_str = str.substr(4, std::string::npos);
std::istringstream dim_istr(dim_str);
int32 dim = -1;
dim_istr >> dim;
if (dim < 0 || dim_istr.fail()) {
KALDI_ERR << "Reading sparse vector, expected 'dim=[int]', got " << str;
}
dim_ = dim;
is >> std::ws;
is >> str;
if (str != "[")
KALDI_ERR << "Reading sparse vector, expected '[', got " << str;
pairs_.clear();
while (1) {
is >> std::ws;
if (is.peek() == ']') {
is.get();
break;
}
MatrixIndexT i;
BaseFloat p;
is >> i >> p;
if (is.fail())
KALDI_ERR << "Error reading sparse vector, expecting numbers.";
KALDI_ASSERT(i >= 0 && i < dim
&& (pairs_.empty() || i > pairs_.back().first));
pairs_.push_back(std::pair<MatrixIndexT, BaseFloat>(i, p));
}
}
}
namespace sparse_vector_utils {
template <typename Real>
struct CompareFirst {
inline bool operator() (const std::pair<MatrixIndexT, Real> &p1,
const std::pair<MatrixIndexT, Real> &p2) const {
return p1.first < p2.first;
}
};
}
template <typename Real>
SparseVector<Real>::SparseVector(
MatrixIndexT dim, const std::vector<std::pair<MatrixIndexT, Real> > &pairs):
dim_(dim),
pairs_(pairs) {
std::sort(pairs_.begin(), pairs_.end(),
sparse_vector_utils::CompareFirst<Real>());
typename std::vector<std::pair<MatrixIndexT, Real> >::iterator
out = pairs_.begin(), in = out, end = pairs_.end();
// special case: while there is nothing to be changed, skip over
// initial input (avoids unnecessary copying).
while (in + 1 < end && in[0].first != in[1].first && in[0].second != 0.0) {
in++;
out++;
}
while (in < end) {
// We reach this point only at the first element of
// each stretch of identical .first elements.
*out = *in;
++in;
while (in < end && in->first == out->first) {
out->second += in->second; // this is the merge operation.
++in;
}
if (out->second != Real(0.0)) // Don't keep zero elements.
out++;
}
pairs_.erase(out, end);
if (!pairs_.empty()) {
// range check.
KALDI_ASSERT(pairs_.front().first >= 0 && pairs_.back().first < dim_);
}
}
template <typename Real>
void SparseVector<Real>::SetRandn(BaseFloat zero_prob) {
pairs_.clear();
KALDI_ASSERT(zero_prob >= 0 && zero_prob <= 1.0);
for (MatrixIndexT i = 0; i < dim_; i++)
if (WithProb(1.0 - zero_prob))
pairs_.push_back(std::pair<MatrixIndexT, Real>(i, RandGauss()));
}
template <typename Real>
void SparseVector<Real>::Resize(MatrixIndexT dim,
MatrixResizeType resize_type) {
if (resize_type != kCopyData || dim == 0)
pairs_.clear();
KALDI_ASSERT(dim >= 0);
if (dim < dim_ && resize_type == kCopyData)
while (!pairs_.empty() && pairs_.back().first >= dim)
pairs_.pop_back();
dim_ = dim;
}
template <typename Real>
MatrixIndexT SparseMatrix<Real>::NumRows() const {
return rows_.size();
}
template <typename Real>
MatrixIndexT SparseMatrix<Real>::NumCols() const {
if (rows_.empty())
return 0.0;
else
return rows_[0].Dim();
}
template <typename Real>
MatrixIndexT SparseMatrix<Real>::NumElements() const {
int32 num_elements = 0;
for (int32 i = 0; i < rows_.size(); ++i) {
num_elements += rows_[i].NumElements();
}
return num_elements;
}
template <typename Real>
SparseVector<Real>* SparseMatrix<Real>::Data() {
if (rows_.empty())
return NULL;
else
return rows_.data();
}
template <typename Real>
const SparseVector<Real>* SparseMatrix<Real>::Data() const {
if (rows_.empty())
return NULL;
else
return rows_.data();
}
template <typename Real>
Real SparseMatrix<Real>::Sum() const {
Real sum = 0;
for (int32 i = 0; i < rows_.size(); ++i) {
sum += rows_[i].Sum();
}
return sum;
}
template<typename Real>
Real SparseMatrix<Real>::FrobeniusNorm() const {
Real squared_sum = 0;
for (int32 i = 0; i < rows_.size(); ++i) {
const std::pair<MatrixIndexT, Real> *row_data = rows_[i].Data();
for (int32 j = 0; j < rows_[i].NumElements(); ++j) {
squared_sum += row_data[j].second * row_data[j].second;
}
}
return std::sqrt(squared_sum);
}
template <typename Real>
template <typename OtherReal>
void SparseMatrix<Real>::CopyToMat(MatrixBase<OtherReal> *other,
MatrixTransposeType trans) const {
if (trans == kNoTrans) {
MatrixIndexT num_rows = rows_.size();
KALDI_ASSERT(other->NumRows() == num_rows);
for (MatrixIndexT i = 0; i < num_rows; i++) {
SubVector<OtherReal> vec(*other, i);
rows_[i].CopyElementsToVec(&vec);
}
} else {
OtherReal *other_col_data = other->Data();
MatrixIndexT other_stride = other->Stride(),
num_rows = NumRows(), num_cols = NumCols();
KALDI_ASSERT(num_rows == other->NumCols() && num_cols == other->NumRows());
other->SetZero();
for (MatrixIndexT row = 0; row < num_rows; row++, other_col_data++) {
const SparseVector<Real> &svec = rows_[row];
MatrixIndexT num_elems = svec.NumElements();
const std::pair<MatrixIndexT, Real> *sdata = svec.Data();
for (MatrixIndexT e = 0; e < num_elems; e++)
other_col_data[sdata[e].first * other_stride] = sdata[e].second;
}
}
}
template
void SparseMatrix<float>::CopyToMat(MatrixBase<float> *other,
MatrixTransposeType trans) const;
template
void SparseMatrix<float>::CopyToMat(MatrixBase<double> *other,
MatrixTransposeType trans) const;
template
void SparseMatrix<double>::CopyToMat(MatrixBase<float> *other,
MatrixTransposeType trans) const;
template
void SparseMatrix<double>::CopyToMat(MatrixBase<double> *other,
MatrixTransposeType trans) const;
template <typename Real>
void SparseMatrix<Real>::CopyElementsToVec(VectorBase<Real> *other) const {
KALDI_ASSERT(other->Dim() == NumElements());
Real *dst_data = other->Data();
int32 dst_index = 0;
for (int32 i = 0; i < rows_.size(); ++i) {
for (int32 j = 0; j < rows_[i].NumElements(); ++j) {
dst_data[dst_index] =
static_cast<Real>(rows_[i].GetElement(j).second);
dst_index++;
}
}
}
template<typename Real>
template<typename OtherReal>
void SparseMatrix<Real>::CopyFromSmat(const SparseMatrix<OtherReal> &other,
MatrixTransposeType trans) {
if (trans == kNoTrans) {
rows_.resize(other.NumRows());
if (rows_.size() == 0)
return;
for (int32 r = 0; r < rows_.size(); ++r) {
rows_[r].CopyFromSvec(other.Row(r));
}
} else {
std::vector<std::vector<std::pair<MatrixIndexT, Real> > > pairs(
other.NumCols());
for (MatrixIndexT i = 0; i < other.NumRows(); ++i) {
for (int id = 0; id < other.Row(i).NumElements(); ++id) {
MatrixIndexT j = other.Row(i).GetElement(id).first;
Real v = static_cast<Real>(other.Row(i).GetElement(id).second);
pairs[j].push_back( { i, v });
}
}
SparseMatrix<Real> temp(other.NumRows(), pairs);
Swap(&temp);
}
}
template
void SparseMatrix<float>::CopyFromSmat(const SparseMatrix<float> &other,
MatrixTransposeType trans);
template
void SparseMatrix<float>::CopyFromSmat(const SparseMatrix<double> &other,
MatrixTransposeType trans);
template
void SparseMatrix<double>::CopyFromSmat(const SparseMatrix<float> &other,
MatrixTransposeType trans);
template
void SparseMatrix<double>::CopyFromSmat(const SparseMatrix<double> &other,
MatrixTransposeType trans);
template <typename Real>
void SparseMatrix<Real>::Write(std::ostream &os, bool binary) const {
if (binary) {
// Note: we can use the same marker for float and double SparseMatrix,
// because internally we use WriteBasicType and ReadBasicType to read the
// floats and doubles, and this will automatically take care of type
// conversion.
WriteToken(os, binary, "SM");
int32 num_rows = rows_.size();
WriteBasicType(os, binary, num_rows);
for (int32 row = 0; row < num_rows; row++)
rows_[row].Write(os, binary);
} else {
// The format is "rows=10 dim=20 [ 1 0.4 9 1.2 ] dim=20 [ 3 1.7 19 0.6 ] ..
// not 100% efficient, but easy to work with, and we can re-use the
// read/write code from SparseVector.
int32 num_rows = rows_.size();
os << "rows=" << num_rows << " ";
for (int32 row = 0; row < num_rows; row++)
rows_[row].Write(os, binary);
os << "\n"; // Might make it a little more readable.
}
}
template <typename Real>
void SparseMatrix<Real>::Read(std::istream &is, bool binary) {
if (binary) {
ExpectToken(is, binary, "SM");
int32 num_rows;
ReadBasicType(is, binary, &num_rows);
KALDI_ASSERT(num_rows >= 0 && num_rows < 10000000);
rows_.resize(num_rows);
for (int32 row = 0; row < num_rows; row++)
rows_[row].Read(is, binary);
} else {
std::string str;
is >> str;
if (str.substr(0, 5) != "rows=")
KALDI_ERR << "Reading sparse matrix, expected 'rows=xxx', got " << str;
std::string rows_str = str.substr(5, std::string::npos);
std::istringstream rows_istr(rows_str);
int32 num_rows = -1;
rows_istr >> num_rows;
if (num_rows < 0 || rows_istr.fail()) {
KALDI_ERR << "Reading sparse vector, expected 'rows=[int]', got " << str;
}
rows_.resize(num_rows);
for (int32 row = 0; row < num_rows; row++)
rows_[row].Read(is, binary);
}
}
template <typename Real>
void SparseMatrix<Real>::AddToMat(BaseFloat alpha,
MatrixBase<Real> *other,
MatrixTransposeType trans) const {
if (trans == kNoTrans) {
MatrixIndexT num_rows = rows_.size();
KALDI_ASSERT(other->NumRows() == num_rows);
for (MatrixIndexT i = 0; i < num_rows; i++) {
SubVector<Real> vec(*other, i);
rows_[i].AddToVec(alpha, &vec);
}
} else {
Real *other_col_data = other->Data();
MatrixIndexT other_stride = other->Stride(),
num_rows = NumRows(), num_cols = NumCols();
KALDI_ASSERT(num_rows == other->NumCols() && num_cols == other->NumRows());
for (MatrixIndexT row = 0; row < num_rows; row++, other_col_data++) {
const SparseVector<Real> &svec = rows_[row];
MatrixIndexT num_elems = svec.NumElements();
const std::pair<MatrixIndexT, Real> *sdata = svec.Data();
for (MatrixIndexT e = 0; e < num_elems; e++)
other_col_data[sdata[e].first * other_stride] +=
alpha * sdata[e].second;
}
}
}
template <typename Real>
Real VecSvec(const VectorBase<Real> &vec,
const SparseVector<Real> &svec) {
KALDI_ASSERT(vec.Dim() == svec.Dim());
MatrixIndexT n = svec.NumElements();
const std::pair<MatrixIndexT, Real> *sdata = svec.Data();
const Real *data = vec.Data();
Real ans = 0.0;
for (MatrixIndexT i = 0; i < n; i++)
ans += data[sdata[i].first] * sdata[i].second;
return ans;
}
template
float VecSvec(const VectorBase<float> &vec,
const SparseVector<float> &svec);
template
double VecSvec(const VectorBase<double> &vec,
const SparseVector<double> &svec);
template <typename Real>
const SparseVector<Real> &SparseMatrix<Real>::Row(MatrixIndexT r) const {
KALDI_ASSERT(static_cast<size_t>(r) < rows_.size());
return rows_[r];
}
template <typename Real>
void SparseMatrix<Real>::SetRow(int32 r, const SparseVector<Real> &vec) {
KALDI_ASSERT(static_cast<size_t>(r) < rows_.size() &&
vec.Dim() == rows_[0].Dim());
rows_[r] = vec;
}
template<typename Real>
void SparseMatrix<Real>::SelectRows(const std::vector<int32> &row_indexes,
const SparseMatrix<Real> &smat_other) {
Resize(row_indexes.size(), smat_other.NumCols());
for (int i = 0; i < row_indexes.size(); ++i) {
SetRow(i, smat_other.Row(row_indexes[i]));
}
}
template<typename Real>
SparseMatrix<Real>::SparseMatrix(const std::vector<int32> &indexes, int32 dim,
MatrixTransposeType trans) {
const std::vector<int32>& idx = indexes;
std::vector<std::vector<std::pair<MatrixIndexT, Real> > > pair(idx.size());
for (int i = 0; i < idx.size(); ++i) {
if (idx[i] >= 0) {
pair[i].push_back( { idx[i], Real(1) });
}
}
SparseMatrix<Real> smat_cpu(dim, pair);
if (trans == kNoTrans) {
this->Swap(&smat_cpu);
} else {
SparseMatrix<Real> tmp(smat_cpu, kTrans);
this->Swap(&tmp);
}
}
template<typename Real>
SparseMatrix<Real>::SparseMatrix(const std::vector<int32> &indexes,
const VectorBase<Real> &weights, int32 dim,
MatrixTransposeType trans) {
const std::vector<int32>& idx = indexes;
const VectorBase<Real>& w = weights;
std::vector<std::vector<std::pair<MatrixIndexT, Real> > > pair(idx.size());
for (int i = 0; i < idx.size(); ++i) {
if (idx[i] >= 0) {
pair[i].push_back( { idx[i], w(i) });
}
}
SparseMatrix<Real> smat_cpu(dim, pair);
if (trans == kNoTrans) {
this->Swap(&smat_cpu);
} else {
SparseMatrix<Real> tmp(smat_cpu, kTrans);
this->Swap(&tmp);
}
}
template <typename Real>
SparseMatrix<Real>& SparseMatrix<Real>::operator = (
const SparseMatrix<Real> &other) {
rows_ = other.rows_;
return *this;
}
template <typename Real>
void SparseMatrix<Real>::Swap(SparseMatrix<Real> *other) {
rows_.swap(other->rows_);
}
template<typename Real>
SparseMatrix<Real>::SparseMatrix(
MatrixIndexT dim,
const std::vector<std::vector<std::pair<MatrixIndexT, Real> > > &pairs):
rows_(pairs.size()) {
MatrixIndexT num_rows = pairs.size();
for (MatrixIndexT row = 0; row < num_rows; row++) {
SparseVector<Real> svec(dim, pairs[row]);
rows_[row].Swap(&svec);
}
}
template <typename Real>
void SparseMatrix<Real>::SetRandn(BaseFloat zero_prob) {
MatrixIndexT num_rows = rows_.size();
for (MatrixIndexT row = 0; row < num_rows; row++)
rows_[row].SetRandn(zero_prob);
}
template <typename Real>
void SparseMatrix<Real>::Resize(MatrixIndexT num_rows,
MatrixIndexT num_cols,
MatrixResizeType resize_type) {
KALDI_ASSERT(num_rows >= 0 && num_cols >= 0);
if (resize_type == kSetZero || resize_type == kUndefined) {
rows_.clear();
Resize(num_rows, num_cols, kCopyData);
} else {
// Assume resize_type == kCopyData from here.
int32 old_num_rows = rows_.size(), old_num_cols = NumCols();
SparseVector<Real> initializer(num_cols);
rows_.resize(num_rows, initializer);
if (num_cols != old_num_cols)
for (int32 row = 0; row < old_num_rows; row++)
rows_[row].Resize(num_cols, kCopyData);
}
}
template <typename Real>
void SparseMatrix<Real>::AppendSparseMatrixRows(
std::vector<SparseMatrix<Real> > *inputs) {
rows_.clear();
size_t num_rows = 0;
typename std::vector<SparseMatrix<Real> >::iterator
input_iter = inputs->begin(),
input_end = inputs->end();
for (; input_iter != input_end; ++input_iter)
num_rows += input_iter->rows_.size();
rows_.resize(num_rows);
typename std::vector<SparseVector<Real> >::iterator
row_iter = rows_.begin(),
row_end = rows_.end();
for (input_iter = inputs->begin(); input_iter != input_end; ++input_iter) {
typename std::vector<SparseVector<Real> >::iterator
input_row_iter = input_iter->rows_.begin(),
input_row_end = input_iter->rows_.end();
for (; input_row_iter != input_row_end; ++input_row_iter, ++row_iter)
row_iter->Swap(&(*input_row_iter));
}
KALDI_ASSERT(row_iter == row_end);
int32 num_cols = NumCols();
for (row_iter = rows_.begin(); row_iter != row_end; ++row_iter) {
if (row_iter->Dim() != num_cols)
KALDI_ERR << "Appending rows with inconsistent dimensions, "
<< row_iter->Dim() << " vs. " << num_cols;
}
inputs->clear();
}
template<typename Real>
void SparseMatrix<Real>::Scale(Real alpha) {
MatrixIndexT num_rows = rows_.size();
for (MatrixIndexT row = 0; row < num_rows; row++)
rows_[row].Scale(alpha);
}
template<typename Real>
SparseMatrix<Real>::SparseMatrix(const MatrixBase<Real> &mat) {
MatrixIndexT num_rows = mat.NumRows();
rows_.resize(num_rows);
for (int32 row = 0; row < num_rows; row++) {
SparseVector<Real> this_row(mat.Row(row));
rows_[row].Swap(&this_row);
}
}
template<typename Real>
Real TraceMatSmat(const MatrixBase<Real> &A,
const SparseMatrix<Real> &B,
MatrixTransposeType trans) {
Real sum = 0.0;
if (trans == kTrans) {
MatrixIndexT num_rows = A.NumRows();
KALDI_ASSERT(B.NumRows() == num_rows);
for (MatrixIndexT r = 0; r < num_rows; r++)
sum += VecSvec(A.Row(r), B.Row(r));
} else {
const Real *A_col_data = A.Data();
MatrixIndexT Astride = A.Stride(), Acols = A.NumCols(), Arows = A.NumRows();
KALDI_ASSERT(Arows == B.NumCols() && Acols == B.NumRows());
sum = 0.0;
for (MatrixIndexT i = 0; i < Acols; i++, A_col_data++) {
Real col_sum = 0.0;
const SparseVector<Real> &svec = B.Row(i);
MatrixIndexT num_elems = svec.NumElements();
const std::pair<MatrixIndexT, Real> *sdata = svec.Data();
for (MatrixIndexT e = 0; e < num_elems; e++)
col_sum += A_col_data[Astride * sdata[e].first] * sdata[e].second;
sum += col_sum;
}
}
return sum;
}
template
float TraceMatSmat(const MatrixBase<float> &A,
const SparseMatrix<float> &B,
MatrixTransposeType trans);
template
double TraceMatSmat(const MatrixBase<double> &A,
const SparseMatrix<double> &B,
MatrixTransposeType trans);
void GeneralMatrix::Clear() {
mat_.Resize(0, 0);
cmat_.Clear();
smat_.Resize(0, 0);
}
GeneralMatrix& GeneralMatrix::operator= (const MatrixBase<BaseFloat> &mat) {
Clear();
mat_ = mat;
return *this;
}
GeneralMatrix& GeneralMatrix::operator= (const CompressedMatrix &cmat) {
Clear();
cmat_ = cmat;
return *this;
}
GeneralMatrix& GeneralMatrix::operator= (const SparseMatrix<BaseFloat> &smat) {
Clear();
smat_ = smat;
return *this;
}
GeneralMatrix& GeneralMatrix::operator= (const GeneralMatrix &gmat) {
mat_ = gmat.mat_;
smat_ = gmat.smat_;
cmat_ = gmat.cmat_;
return *this;
}
GeneralMatrixType GeneralMatrix::Type() const {
if (smat_.NumRows() != 0)
return kSparseMatrix;
else if (cmat_.NumRows() != 0)
return kCompressedMatrix;
else
return kFullMatrix;
}
MatrixIndexT GeneralMatrix::NumRows() const {
MatrixIndexT r = smat_.NumRows();
if (r != 0)
return r;
r = cmat_.NumRows();
if (r != 0)
return r;
return mat_.NumRows();
}
MatrixIndexT GeneralMatrix::NumCols() const {
MatrixIndexT r = smat_.NumCols();
if (r != 0)
return r;
r = cmat_.NumCols();
if (r != 0)
return r;
return mat_.NumCols();
}
void GeneralMatrix::Compress() {
if (mat_.NumRows() != 0) {
cmat_.CopyFromMat(mat_);
mat_.Resize(0, 0);
}
}
void GeneralMatrix::Uncompress() {
if (cmat_.NumRows() != 0) {
mat_.Resize(cmat_.NumRows(), cmat_.NumCols(), kUndefined);
cmat_.CopyToMat(&mat_);
cmat_.Clear();
}
}
void GeneralMatrix::GetMatrix(Matrix<BaseFloat> *mat) const {
if (mat_.NumRows() !=0) {
*mat = mat_;
} else if (cmat_.NumRows() != 0) {
mat->Resize(cmat_.NumRows(), cmat_.NumCols(), kUndefined);
cmat_.CopyToMat(mat);
} else if (smat_.NumRows() != 0) {
mat->Resize(smat_.NumRows(), smat_.NumCols(), kUndefined);
smat_.CopyToMat(mat);
} else {
mat->Resize(0, 0);
}
}
void GeneralMatrix::CopyToMat(MatrixBase<BaseFloat> *mat,
MatrixTransposeType trans) const {
if (mat_.NumRows() !=0) {
mat->CopyFromMat(mat_, trans);
} else if (cmat_.NumRows() != 0) {
cmat_.CopyToMat(mat, trans);
} else if (smat_.NumRows() != 0) {
smat_.CopyToMat(mat, trans);
} else {
KALDI_ASSERT(mat->NumRows() == 0);
}
}
void GeneralMatrix::Scale(BaseFloat alpha) {
if (mat_.NumRows() != 0) {
mat_.Scale(alpha);
} else if (cmat_.NumRows() != 0) {
cmat_.Scale(alpha);
} else if (smat_.NumRows() != 0) {
smat_.Scale(alpha);
}
}
const SparseMatrix<BaseFloat>& GeneralMatrix::GetSparseMatrix() const {
if (mat_.NumRows() != 0 || cmat_.NumRows() != 0)
KALDI_ERR << "GetSparseMatrix called on GeneralMatrix of wrong type.";
return smat_;
}
void GeneralMatrix::SwapSparseMatrix(SparseMatrix<BaseFloat> *smat) {
if (mat_.NumRows() != 0 || cmat_.NumRows() != 0)
KALDI_ERR << "GetSparseMatrix called on GeneralMatrix of wrong type.";
smat->Swap(&smat_);
}
void GeneralMatrix::SwapCompressedMatrix(CompressedMatrix *cmat) {
if (mat_.NumRows() != 0 || smat_.NumRows() != 0)
KALDI_ERR << "GetSparseMatrix called on GeneralMatrix of wrong type.";
cmat->Swap(&cmat_);
}
const CompressedMatrix &GeneralMatrix::GetCompressedMatrix() const {
if (mat_.NumRows() != 0 || smat_.NumRows() != 0)
KALDI_ERR << "GetCompressedMatrix called on GeneralMatrix of wrong type.";
return cmat_;
}
const Matrix<BaseFloat> &GeneralMatrix::GetFullMatrix() const {
if (smat_.NumRows() != 0 || cmat_.NumRows() != 0)
KALDI_ERR << "GetFullMatrix called on GeneralMatrix of wrong type.";
return mat_;
}
void GeneralMatrix::SwapFullMatrix(Matrix<BaseFloat> *mat) {
if (cmat_.NumRows() != 0 || smat_.NumRows() != 0)
KALDI_ERR << "SwapMatrix called on GeneralMatrix of wrong type.";
mat->Swap(&mat_);
}
void GeneralMatrix::Write(std::ostream &os, bool binary) const {
if (smat_.NumRows() != 0) {
smat_.Write(os, binary);
} else if (cmat_.NumRows() != 0) {
cmat_.Write(os, binary);
} else {
mat_.Write(os, binary);
}
}
void GeneralMatrix::Read(std::istream &is, bool binary) {
Clear();
if (binary) {
int peekval = is.peek();
if (peekval == 'C') {
// Token CM for compressed matrix
cmat_.Read(is, binary);
} else if (peekval == 'S') {
// Token SM for sparse matrix
smat_.Read(is, binary);
} else {
mat_.Read(is, binary);
}
} else {
// note: in text mode we will only ever read regular
// or sparse matrices, because the compressed-matrix format just
// gets written as a regular matrix in text mode.
is >> std::ws; // Eat up white space.
int peekval = is.peek();
if (peekval == 'r') { // sparse format starts rows=[int].
smat_.Read(is, binary);
} else {
mat_.Read(is, binary);
}
}
}
void AppendGeneralMatrixRows(const std::vector<const GeneralMatrix *> &src,
GeneralMatrix *mat) {
mat->Clear();
int32 size = src.size();
if (size == 0)
return;
bool all_sparse = true;
for (int32 i = 0; i < size; i++) {
if (src[i]->Type() != kSparseMatrix && src[i]->NumRows() != 0) {
all_sparse = false;
break;
}
}
if (all_sparse) {
std::vector<SparseMatrix<BaseFloat> > sparse_mats(size);
for (int32 i = 0; i < size; i++)
sparse_mats[i] = src[i]->GetSparseMatrix();
SparseMatrix<BaseFloat> appended_mat;
appended_mat.AppendSparseMatrixRows(&sparse_mats);
mat->SwapSparseMatrix(&appended_mat);
} else {
int32 tot_rows = 0, num_cols = -1;
for (int32 i = 0; i < size; i++) {
const GeneralMatrix &src_mat = *(src[i]);
int32 src_rows = src_mat.NumRows(), src_cols = src_mat.NumCols();
if (src_rows != 0) {
tot_rows += src_rows;
if (num_cols == -1) num_cols = src_cols;
else if (num_cols != src_cols)
KALDI_ERR << "Appending rows of matrices with inconsistent num-cols: "
<< num_cols << " vs. " << src_cols;
}
}
Matrix<BaseFloat> appended_mat(tot_rows, num_cols, kUndefined);
int32 row_offset = 0;
for (int32 i = 0; i < size; i++) {
const GeneralMatrix &src_mat = *(src[i]);
int32 src_rows = src_mat.NumRows();
if (src_rows != 0) {
SubMatrix<BaseFloat> dest_submat(appended_mat, row_offset, src_rows,
0, num_cols);
src_mat.CopyToMat(&dest_submat);
row_offset += src_rows;
}
}
KALDI_ASSERT(row_offset == tot_rows);
mat->SwapFullMatrix(&appended_mat);
}
}
void FilterCompressedMatrixRows(const CompressedMatrix &in,
const std::vector<bool> &keep_rows,
Matrix<BaseFloat> *out) {
KALDI_ASSERT(keep_rows.size() == static_cast<size_t>(in.NumRows()));
int32 num_kept_rows = 0;
std::vector<bool>::const_iterator iter = keep_rows.begin(),
end = keep_rows.end();
for (; iter != end; ++iter)
if (*iter)
num_kept_rows++;
if (num_kept_rows == 0)
KALDI_ERR << "No kept rows";
if (num_kept_rows == static_cast<int32>(keep_rows.size())) {
out->Resize(in.NumRows(), in.NumCols(), kUndefined);
in.CopyToMat(out);
return;
}
const BaseFloat heuristic = 0.33;
// should be > 0 and < 1.0. represents the performance hit we get from
// iterating row-wise versus column-wise in compressed-matrix uncompression.
if (num_kept_rows > heuristic * in.NumRows()) {