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CPUSparseMatrix.cpp
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//
// Copyright (c) Microsoft. All rights reserved.
// Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
//
// Math.cpp : Defines the exported functions for the DLL application.
//
#include "stdafx.h"
#include "Basics.h"
#include "File.h"
#include <assert.h>
#include <stdexcept>
#include <omp.h>
#include <math.h>
#include "CPUMatrix.h"
#include "CPUSparseMatrix.h"
#include <random>
#include <chrono>
#include <iostream>
#ifdef LEAKDETECT
#include <vld.h>
#endif
#pragma warning(disable : 4127) // conditional expression is constant; "if (sizeof(ElemType)==sizeof(float))" triggers this
#ifdef USE_MKL
// requires MKL 10.0 and above
#include <mkl.h>
#else
#ifdef _MSC_VER
// Visual Studio doesn't define standard complex types properly
#define HAVE_LAPACK_CONFIG_H
#define LAPACK_COMPLEX_STRUCTURE
#endif
#include <cblas.h>
#include <lapacke.h>
#endif
// This is an example of an exported variable
//MATH_API int nMath=0;
// This is an example of an exported function.
//MATH_API int fnMath(void)
//{
// return 42;
//}
// TODO: Move to CommonMatrix.h
#define IDX2C(i, j, ld) (((j) * (ld)) + (i)) // 0 based indexing
namespace Microsoft { namespace MSR { namespace CNTK {
#pragma region Helpful Enum Definitions
enum class MatrixOrder
{
RowMajor = 101, // row-major arrays
ColMajor = 102 // column-major arrays
};
enum class MatrixTranspose : char
{
NoTrans = 'N', // trans='N'
Trans = 'T', // trans='T'
ConjTrans = 'C' // trans='C'
};
enum class SymMatrixType : char
{
Up = 'U', // symmetric matrix is stored in the upper part
Low = 'L', // symmetric matrix is stored in thelower part
Full = 'F', // full populated
NotSymmetric = 'N' // not a symmetric matrix
};
enum class MatrixOpSide : char
{
Left = 'L', // left multiply
Right = 'R', // right multiply
};
#pragma endregion Helpful Enum Definitions
#pragma region Constructors and Destructor
//-------------------------------------------------------------------------
// construction and conversion
//-------------------------------------------------------------------------
// should only be used by constructors.
template <class ElemType>
/*private*/ void CPUSparseMatrix<ElemType>::ZeroInit()
{
Base::ZeroInit();
SetComputeDeviceId(CPUDEVICE);
SetCompIndexSize(0);
SetColIdx(-1);
SetBuffer(nullptr, 0, false);
SetUnCompIndex(nullptr);
SetCompIndex(nullptr);
SetBlockSize(0);
SetBlockIdShift(0);
SetBlockIds(nullptr);
}
//should only be used by constructors.
template <class ElemType>
void CPUSparseMatrix<ElemType>::CheckInit(const MatrixFormat format)
{
if (format != MatrixFormat::matrixFormatSparseCSC && format != MatrixFormat::matrixFormatSparseCSR && format != MatrixFormat::matrixFormatSparseBlockCol && format != MatrixFormat::matrixFormatSparseBlockRow)
{
LogicError("CPUSparseMatrix: unsupported sparse matrix format");
}
SetFormat(format);
ZeroInit();
}
template <class ElemType>
CPUSparseMatrix<ElemType>::CPUSparseMatrix(const MatrixFormat format)
{
CheckInit(format);
}
template <class ElemType>
CPUSparseMatrix<ElemType>::CPUSparseMatrix(const MatrixFormat format, const size_t numRows, const size_t numCols, const size_t size)
{
CheckInit(format);
RequireSizeAndAllocate(numRows, numCols, size, true, false);
}
// copy constructor, deep copy
template <class ElemType>
CPUSparseMatrix<ElemType>::CPUSparseMatrix(const CPUSparseMatrix<ElemType>& deepCopyFrom)
{
ZeroInit();
if (!deepCopyFrom.IsEmpty())
SetValue(deepCopyFrom);
}
// assignment operator, deep copy
template <class ElemType>
CPUSparseMatrix<ElemType>& CPUSparseMatrix<ElemType>::operator=(const CPUSparseMatrix<ElemType>& deepCopyFrom)
{
if (!deepCopyFrom.IsEmpty())
SetValue(deepCopyFrom);
return *this;
}
// move constructor, shallow copy
template <class ElemType>
CPUSparseMatrix<ElemType>::CPUSparseMatrix(CPUSparseMatrix<ElemType>&& moveFrom)
{
Base::ShallowCopyFrom(moveFrom);
// release the pointer from the source object so that the destructor won't release it twice
moveFrom.ZeroValues();
}
//move assignment operator, shallow copy
template <class ElemType>
CPUSparseMatrix<ElemType>& CPUSparseMatrix<ElemType>::operator=(CPUSparseMatrix<ElemType>&& moveFrom)
{
if (this != &moveFrom)
{
Base::ShallowCopyFrom(moveFrom);
// release the pointer from the source object so that the destructor won't release it twice
moveFrom.ZeroValues();
}
return *this;
}
template <class ElemType>
CPUSparseMatrix<ElemType>::~CPUSparseMatrix()
{
ZeroValues();
}
#pragma endregion Constructors and Destructor
#pragma region Basic Operators
// make sure call order in column wise for CSC and row wise for CSR
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetValue(const size_t row, const size_t col, const ElemType v)
{
if (!OwnBuffer())
LogicError("Cannot modify since the buffer is managed externally.");
if (GetFormat() != MatrixFormat::matrixFormatSparseCSC && GetFormat() != MatrixFormat::matrixFormatSparseCSR)
{
LogicError("CPUSparseMatrix: unsupported SetValue() call.");
}
if ((GetFormat() == MatrixFormat::matrixFormatSparseCSC) && ((*this)(row, col) == v))
return;
let nz = NzCount();
if (GetSizeAllocated() < nz + 1) // automatic resize
{
Allocate(m_numRows, m_numCols, nz + 100, true, true); // allocate 100 more elelemnts and keep existing values
}
if (row < 0 || row >= m_numRows)
{
LogicError("CPUSparseMatrix: SetValue() invalid row id");
}
if (col < 0 || col >= m_numCols)
{
LogicError("CPUSparseMatrix: SetValue() invalid column id");
}
size_t r = (GetFormat() == matrixFormatSparseCSC) ? row : col;
size_t c = (GetFormat() == matrixFormatSparseCSC) ? col : row;
Data()[nz] = v;
MajorIndexLocation()[nz] = (CPUSPARSE_INDEX_TYPE) r;
// consistency check
if (nz > 0)
{
if (c == GetColIdx() && r <= MajorIndexLocation()[nz - 1])
{
LogicError("CPUSparseMatrix: SetValue is not called properly");
}
}
if (c != GetColIdx())
{
SecondaryIndexLocation()[c] = CPUSPARSE_INDEX_TYPE(nz);
SetColIdx((int) c);
}
// Note we don't have m_nz anymore. In order for the change from m_nz to
// NzCount to make sense, we need to propogate nz+1 to all col slices.
for (size_t max = c + 1; max < m_numCols + 1; max++)
{
SecondaryIndexLocation()[max] = CPUSPARSE_INDEX_TYPE(nz + 1);
}
}
// make sure call order in colume wise for CSC and row wise for CSR
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetValue(const CPUSparseMatrix<ElemType>& v)
{
SetFormat(v.GetFormat());
RequireSizeAndAllocate(v.GetNumRows(), v.GetNumCols(), v.NzCount() ); // TODO: rename to *Bytes/*Count instead of vague *Size if possible
let nz = v.NzCount();
auto matrixFormat = v.GetFormat();
if (((matrixFormat == matrixFormatSparseBlockCol) || (matrixFormat == matrixFormatSparseBlockRow)) && (v.GetBlockIdShift() > 0))
NOT_IMPLEMENTED;
if (nz > 0)
{
memcpy(NzValues(), v.NzValues(), v.NzSize());
if ((matrixFormat == matrixFormatSparseCSC) || (matrixFormat == matrixFormatSparseCSR))
{
memcpy(RowLocation(), v.RowLocation(), v.RowSize());
memcpy(ColLocation(), v.ColLocation(), v.ColSize());
}
else
{
memcpy(GetBlockIds(), v.GetBlockIds(), v.GetBlockSize() * sizeof(size_t)); // TODO: change block id from size_t to CPUSPARSE_INDEX_TYPE, and rename BlockSize to BlockCount
SetBlockSize(v.GetBlockSize());
}
}
if (v.m_sliceViewOffset > 0)
{
CPUSPARSE_INDEX_TYPE* loc = (GetFormat() == matrixFormatSparseCSC) ? ColLocation() : RowLocation();
size_t len = (GetFormat() == matrixFormatSparseCSC) ? ColSize() : RowSize();
CPUSPARSE_INDEX_TYPE offset = loc[0];
for (size_t c = 0; c < len; c++)
loc[c] -= offset;
}
}
#if 0
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetValue(const CPUMatrix<ElemType>& /*v*/)
{
NOT_IMPLEMENTED;
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetValue(const GPUMatrix<ElemType>& /*v*/)
{
NOT_IMPLEMENTED;
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetValue(const GPUSparseMatrix<ElemType>& /*v*/)
{
NOT_IMPLEMENTED;
}
#endif
template <class ElemType>
void CPUSparseMatrix<ElemType>::MaskColumnsValue(const CPUMatrix<char>& columnsMask, ElemType val, size_t numColsPerMaskEntry)
{
VerifyWritable(__func__);
if (GetNumCols() != (columnsMask.GetNumCols() * numColsPerMaskEntry))
RuntimeError("Matrix number of columns must equal 'number of columns in column mask * numColsPerMaskEntry'.");
if (val != 0)
LogicError("MaskColumnsValue is not implmented for a non-zero mask for sparse matrices.");
#ifdef _DEBUG
if (GetFormat() == MatrixFormat::matrixFormatSparseCSC)
{
// Get the binary columns mask
char* maskedCols = columnsMask.Data();
// If we're CSC, we only need to verify that the columns to be zeroed are empty.
GPUSPARSE_INDEX_TYPE* colVector = SecondaryIndexLocation();
auto n = columnsMask.GetNumCols();
#pragma omp parallel for
for (long j = 0; j < n; j++)
for (long k = 0; k < numColsPerMaskEntry; ++k)
if (maskedCols[j] == 0 && colVector[(j * numColsPerMaskEntry) + k + 1] != colVector[(j * numColsPerMaskEntry) + k])
LogicError("CPUSparseMatrix attempted to mask column %d, but it has %d elements in it.", (int)((j * numColsPerMaskEntry) + k), (int)(colVector[(j * numColsPerMaskEntry) + k + 1] - colVector[(j * numColsPerMaskEntry) + k]));
}
else
NOT_IMPLEMENTED;
#endif
}
template <class ElemType>
CPUSparseMatrix<ElemType>& CPUSparseMatrix<ElemType>::DoGatherColumnsOf(ElemType beta, const CPUMatrix<ElemType>& idx, const CPUSparseMatrix<ElemType>& a, ElemType alpha)
{
VerifyWritable(__func__);
if ((a.GetFormat() != matrixFormatSparseCSC) || (GetFormat() != matrixFormatSparseCSC))
NOT_IMPLEMENTED;
if (idx.GetNumRows() != 1) // index is 1-dimensional only
InvalidArgument("DoGatherColumnsOf: Map must be a row vector.");
if (beta != 0)
NOT_IMPLEMENTED;
// Determine the number of non-zero elements
size_t numCols = idx.GetNumCols();
size_t numNonZeroElements = 0;
// TODO: Does it make sense to parallelize this?
for (long j = 0; j < numCols; j++)
{
auto jInF = idx(0, j); // this is the column we need to get
if (std::isnan(jInF) || (jInF < 0)) // negative index means gap
continue;
size_t jIn = (size_t)jInF;
auto start = a.SecondaryIndexLocation()[jIn];
auto end = a.SecondaryIndexLocation()[jIn + 1];
numNonZeroElements += (end - start);
}
if (beta == 0)
RequireSizeAndAllocate(a.GetNumRows(), idx.GetNumCols(), numNonZeroElements); // output has same column format as a, but number of columns comes from idx
size_t offset = SecondaryIndexLocation()[0];
// TODO: Does it make sense to parallelize this?
for (long j = 0; j < numCols; j++)
{
auto jInF = idx(0, j); // this is the column we need to get
if (jInF >= 0) // negative or nan index means gap, but we still need to update the CompIndex
{
size_t jIn = (size_t)jInF;
auto start = a.SecondaryIndexLocation()[jIn];
auto end = a.SecondaryIndexLocation()[jIn + 1];
for (auto p = start; p < end; p++, offset++)
{
GetUnCompIndex()[offset] = a.GetUnCompIndex()[p];
Buffer()[offset] = a.Buffer()[p] * alpha;
}
}
SecondaryIndexLocation()[j + 1] = CPUSPARSE_INDEX_TYPE(offset);
}
return *this;
}
// *this[:,idx[j]] = a[:,j] * alpha + *this[:,idx[j]] * beta
template <class ElemType>
CPUSparseMatrix<ElemType>& CPUSparseMatrix<ElemType>::DoScatterColumnsOf(ElemType beta, const CPUMatrix<ElemType>& idx, const CPUSparseMatrix<ElemType>& a, ElemType alpha)
{
VerifyWritable(__func__);
if ((a.GetFormat() != matrixFormatSparseCSC) || (GetFormat() != matrixFormatSparseCSC))
NOT_IMPLEMENTED;
if (idx.GetNumRows() != 1) // index is 1-dimensional only
InvalidArgument("DoScatterColumnsOf: Map must be a row vector.");
if (beta != 0)
NOT_IMPLEMENTED;
if (NzCount() != 0)
InvalidArgument("CPUSparseMatrix::DoScatterColumnsOf: The target matrix cannot have pre-existing non-zero values when being scattered into");
size_t numNonZeroElements = a.NzCount();
if (beta == 0)
RequireSizeAndAllocate(GetNumRows(), GetNumCols(), numNonZeroElements);
// Setup the Secondary index
std::vector<int> columnElementCounts(GetNumCols(), 0);
size_t numColsToWrite = idx.GetNumCols();
for (long j = 0; j < numColsToWrite; j++)
{
auto jOutF = idx(0, j); // this is the column we need to write to
if (std::isnan(jOutF) || (jOutF < 0)) // negative index means gap
continue;
size_t jOut = (size_t)jOutF;
columnElementCounts[jOut] = a.SecondaryIndexLocation()[j + 1] - a.SecondaryIndexLocation()[j];
}
// TODO: Replace with std::exclusive_scan when we switch to C++17
for (size_t i = 1; i <= GetNumCols(); ++i)
SecondaryIndexLocation()[i] = SecondaryIndexLocation()[i - 1] + columnElementCounts[i - 1];
size_t offset = a.SecondaryIndexLocation()[0];
// TODO: Does it make sense to parallelize this?
for (long j = 0; j < numColsToWrite; j++)
{
auto jOutF = idx(0, j); // this is the column we need to write to
if (std::isnan(jOutF) || (jOutF < 0)) // negative index means gap
continue;
size_t jOut = (size_t)jOutF;
auto start = SecondaryIndexLocation()[jOut];
auto end = SecondaryIndexLocation()[jOut + 1];
for (auto p = start; p < end; p++, offset++)
{
GetUnCompIndex()[p] = a.GetUnCompIndex()[offset];
Buffer()[p] = a.Buffer()[offset] * alpha;
}
}
return *this;
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::Print(const char* matrixName) const
{
Print(matrixName, 0, 0, 0, 0);
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::Print(const char* matrixName, ptrdiff_t /*rowStart*/, ptrdiff_t /*rowEnd*/, ptrdiff_t /*colStart*/, ptrdiff_t /*colEnd*/) const
{
if (this->GetFormat() != matrixFormatSparseCSC && this->GetFormat() != matrixFormatSparseCSR)
{
return;
// NOT_IMPLEMENTED;
}
fprintf(stderr, "%s\n", matrixName);
const ElemType* dataBuffer = NzValues();
const size_t nz = MajorIndexCount();
CPUSPARSE_INDEX_TYPE* unCompressedIndex = MajorIndexLocation();
CPUSPARSE_INDEX_TYPE* compressedIndex = SecondaryIndexLocation();
for (size_t i = 0, j = 0; i < nz; ++i)
{
if (i >= compressedIndex[j])
{
fprintf(stderr, "\n");
j++;
}
fprintf(stderr, "%d:%.f ", unCompressedIndex[i], dataBuffer[i]);
}
fprintf(stderr, "\n");
}
template <class ElemType>
CPUSparseMatrix<ElemType> CPUSparseMatrix<ElemType>::ColumnSlice(size_t startColumn, size_t numCols) const
{
if (startColumn + numCols > m_numCols)
InvalidArgument("The slice (%d+%d) is out of range of the source matrix (%d).", (int) startColumn, (int) numCols, (int) m_numCols);
if (GetFormat() != MatrixFormat::matrixFormatSparseCSC && GetFormat() != MatrixFormat::matrixFormatSparseBlockCol)
NOT_IMPLEMENTED;
CPUSparseMatrix<ElemType> slice(GetFormat());
slice.ShallowCopyFrom(*this);
if ((startColumn != 0) || (slice.m_numCols != numCols))
{
slice.m_numCols = numCols;
if (GetFormat() == MatrixFormat::matrixFormatSparseCSC)
{
slice.m_sliceViewOffset = m_sliceViewOffset + startColumn;
}
else if (GetFormat() == MatrixFormat::matrixFormatSparseBlockCol)
{
long long startColBlock = 0, endColBlock = 0;
bool foundStart = false, foundEnd = false;
for (size_t j = 0; j < GetBlockSize(); j++)
{
if (j > 0)
{
assert(GetBlockIds()[j] > GetBlockIds()[j - 1]); // assume ids are increasing.Is this valid?
}
if (!foundStart && (long long)GetBlockIds()[j] - (long long)GetBlockIdShift() >= (long long)startColumn) // start column with values
{
startColBlock = j;
foundStart = true;
}
else if ((long long)GetBlockIds()[j] - (long long)GetBlockIdShift() >= (long long)(startColumn + numCols)) // end column with values
{
endColBlock = j;
foundEnd = true;
break;
}
}
if (!foundStart)
{
startColBlock = (long long)GetBlockSize();
}
if (!foundEnd)
{
endColBlock = (long long)GetBlockSize();
}
slice.m_sliceViewOffset = startColBlock;
slice.SetBlockIds((size_t*)GetBlockIds() + startColBlock); // the value stored in the block id is based on the original column numbers
slice.SetBlockSize((size_t)max((long long)0, endColBlock - startColBlock));
slice.SetBlockIdShift(GetBlockIdShift() + startColumn);
}
}
return slice;
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::AssignColumnSliceToDense(CPUMatrix<ElemType>& slice, size_t startColumn, size_t numCols) const
{
if (startColumn + numCols > m_numCols)
InvalidArgument("The slice (%d+%d) is out of range of the source matrix (%d).", (int) startColumn, (int) numCols, (int) m_numCols);
if ((GetFormat() != MatrixFormat::matrixFormatSparseCSC) && (GetFormat() != MatrixFormat::matrixFormatSparseBlockCol))
NOT_IMPLEMENTED;
// We can either error out or RequireSize. Because RequireSize will error out if it's not allowed, I think this makes more sense.
slice.RequireSize(m_numRows, numCols);
memset(slice.Data(), 0, sizeof(ElemType) * slice.GetNumElements());
if (GetFormat() == MatrixFormat::matrixFormatSparseCSC)
{
#pragma omp parallel for
for (long j = 0; j < numCols; j++)
{
long start = (long)SecondaryIndexLocation()[startColumn + j];
long end = (long)SecondaryIndexLocation()[startColumn + j + 1];
for (long p = start; p < end; p++)
{
size_t i = GetUnCompIndex()[p];
ElemType value = Buffer()[(size_t)p];
slice(i, (size_t)j) = value;
}
}
}
else
{
CPUSparseMatrix<ElemType> sparseSlice = ColumnSlice(startColumn, numCols);
size_t numColumnsWithNonZeroValues = sparseSlice.GetBlockSize();
#pragma omp parallel for
for (long j = 0; j < numColumnsWithNonZeroValues; j++)
{
size_t i = sparseSlice.GetBlockIds()[j] - sparseSlice.GetBlockIdShift();
size_t len = sparseSlice.GetNumRows();
size_t start = j * len;
for (size_t p = start; p < start + len; p++)
{
ElemType val = sparseSlice.Buffer()[p];
slice(p - start, i) = val;
}
}
}
}
template <class ElemType>
CPUMatrix<ElemType> CPUSparseMatrix<ElemType>::CopyColumnSliceToDense(size_t startColumn, size_t numCols) const
{
CPUMatrix<ElemType> slice(m_numRows, numCols);
AssignColumnSliceToDense(slice, startColumn, numCols);
return slice;
}
template <class ElemType>
CPUMatrix<ElemType> CPUSparseMatrix<ElemType>::DiagonalToDense() const
{
if (m_numRows != m_numCols)
LogicError("DiagonalToDense can be called only for square matrix.");
if (GetFormat() != MatrixFormat::matrixFormatSparseCSC)
NOT_IMPLEMENTED;
CPUMatrix<ElemType> diag(1, m_numCols);
#pragma omp parallel for
for (long j = 0; j < m_numCols; j++)
{
long start = (long) SecondaryIndexLocation()[j];
long end = (long) SecondaryIndexLocation()[j + 1];
for (long p = start; p < end; p++)
{
size_t i = MajorIndexLocation()[p];
if (i == (size_t) j)
{
diag(0, i) = Data()[(size_t) p];
}
}
}
return diag;
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetMatrixFromCSCFormat(const CPUSPARSE_INDEX_TYPE* h_CSCCol, const CPUSPARSE_INDEX_TYPE* h_Row, const ElemType* h_Val,
const size_t nz, const size_t numRows, const size_t numCols)
{
if (!OwnBuffer())
LogicError("Cannot modify since the buffer is managed externally.");
SetFormat(matrixFormatSparseCSC);
RequireSizeAndAllocate(numRows, numCols, nz, true, false);
// Note: This is a casualty of the switch away from m_nz. RowSize and NzSize depend on ColLocation being correct for format SparseCSC. Thus we must
// copy ColLocation before RowLocation and NzValues. That's ugly and error prone.
memcpy(ColLocation(), h_CSCCol, sizeof(CPUSPARSE_INDEX_TYPE)*(numCols + 1));
memcpy(RowLocation(), h_Row, sizeof(CPUSPARSE_INDEX_TYPE)*nz);
memcpy(NzValues(), h_Val, sizeof(ElemType)*nz);
}
#if 0 // add it back with test
template <class ElemType>
void CPUSparseMatrix<ElemType>::SetMatrixFromSBCFormat(const size_t* blockIds, const ElemType* val, const size_t numBlocks, const size_t numRows, const size_t numCols)
{
if (!OwnBuffer())
LogicError("Cannot modify since the buffer is managed externally.");
SetFormat(matrixFormatSparseBlockCol);
Resize(numRows, numCols, numBlocks * numRows);
SetBlockSize(numBlocks);
memcpy(GetBlockIds(), blockIds, sizeof(size_t)*(numBlocks));
memcpy(Data(), val, sizeof(ElemType)*numBlocks*numRows);
}
#endif
template <class ElemType>
ElemType* CPUSparseMatrix<ElemType>::Data() const
{
return (Buffer() +
((GetFormat() == matrixFormatSparseCSC || GetFormat() == matrixFormatSparseCSR) ? GetCompIndex()[m_sliceViewOffset] : 0));
}
// WARNING: When memory is reallocated, existing information will be lost.
// TODO: add keepExistingValues (default to true) argument so that the existing values are kept even after reallocation
template <class ElemType>
void CPUSparseMatrix<ElemType>::Allocate(const size_t numRows, const size_t numCols, const size_t numNZElemRequested, const bool growOnly /*= true*/, bool keepExistingValues /*= true*/)
{
if (m_numRows != numRows || m_numCols != numCols)
LogicError("Error, calling allocate with dimensions (%d, %d), but the matrix has dimension (%d, %d).", (int)numRows, (int)numCols, (int)GetNumRows(), (int)GetNumCols());
size_t numNZElemToReserve = max(numNZElemRequested, (size_t) 1);
size_t newCompIndexSize;
if (GetFormat() == MatrixFormat::matrixFormatSparseCSC)
newCompIndexSize = numCols + 1;
else if (GetFormat() == MatrixFormat::matrixFormatSparseCSR)
newCompIndexSize = numRows + 1;
else
newCompIndexSize = (numCols > numRows ? numCols : numRows) + 1;
bool reallocate = (GetSizeAllocated() < numNZElemToReserve || (GetSizeAllocated() > numNZElemToReserve && !growOnly) || GetCompIndexSize() < newCompIndexSize);
if (reallocate)
{
if (GetFormat() == MatrixFormat::matrixFormatSparseCSC || GetFormat() == MatrixFormat::matrixFormatSparseCSR)
{
// The initialization of the following buffer is done by new []().
auto* pArray = new ElemType[numNZElemToReserve]();
auto* unCompIndex = new CPUSPARSE_INDEX_TYPE[numNZElemToReserve]();
auto* compIndex = new CPUSPARSE_INDEX_TYPE[newCompIndexSize]();
if (keepExistingValues && (NzCount() > numNZElemToReserve || GetCompIndexSize() > newCompIndexSize))
LogicError("Allocate: To keep values m_nz should <= numNZElemToReserve and m_compIndexSize <= newCompIndexSize");
if (keepExistingValues && NzCount() > 0)
{
assert(GetCompIndexSize() > 0 && NzCount() < numNZElemToReserve);
memcpy(pArray, Data(), NzSize());
memcpy(unCompIndex, GetUnCompIndex(), MajorIndexSize());
memcpy(compIndex, GetCompIndex(), SecondaryIndexSize());
}
// TODO: This is super ugly. The internals of the storage object should be a shared_ptr.
delete[] Buffer();
delete[] GetUnCompIndex();
delete[] GetCompIndex();
SetBuffer(pArray, numNZElemToReserve, false);
SetUnCompIndex(unCompIndex);
SetCompIndex(compIndex);
}
else if (GetFormat() == MatrixFormat::matrixFormatSparseBlockCol || GetFormat() == MatrixFormat::matrixFormatSparseBlockRow)
{
ElemType* blockVal = new ElemType[numNZElemToReserve];
size_t* blockIds = new size_t[newCompIndexSize];
if (keepExistingValues && (NzCount() > numNZElemToReserve || GetCompIndexSize() > newCompIndexSize))
LogicError("Resize: To keep values m_nz should <= numNZElemToReserve and m_compIndexSize <= newCompIndexSize");
if (keepExistingValues && GetSizeAllocated() > 0)
{
assert(GetCompIndexSize() > 0 && GetSizeAllocated() < numNZElemToReserve);
memcpy(blockVal, Data(), NzSize());
memcpy(blockIds, GetBlockIds(), sizeof(size_t) * GetCompIndexSize());
}
delete[] Buffer();
delete[] GetBlockIds();
SetBuffer(blockVal, numNZElemToReserve, false);
SetBlockIds(blockIds);
}
SetSizeAllocated(numNZElemToReserve);
SetCompIndexSize(newCompIndexSize);
}
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::RequireSizeAndAllocate(const size_t numRows, const size_t numCols, const size_t numNZElemToReserve /*= 10000*/, const bool growOnly /*= true*/, bool keepExistingValues /*= false*/)
{
RequireSizeAndAllocate(numRows, numCols, numNZElemToReserve, GetFormat(), growOnly, keepExistingValues);
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::RequireSizeAndAllocate(const size_t numRows, const size_t numCols, const size_t numNZElemToReserve, const MatrixFormat matrixFormat, const bool growOnly /*= true*/, bool keepExistingValues /*= true*/)
{
RequireSize(numRows, numCols, numNZElemToReserve, matrixFormat, growOnly);
size_t newCompIndexSize = (numCols > numRows ? numCols : numRows) + 1;
bool reallocate = (GetSizeAllocated() < numNZElemToReserve || (GetSizeAllocated() > numNZElemToReserve && !growOnly) || GetCompIndexSize() < newCompIndexSize);
if (reallocate)
Allocate(numRows, numCols, numNZElemToReserve, growOnly, keepExistingValues);
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::RequireSize(const size_t numRows, const size_t numCols, const bool growOnly /*= true*/)
{
RequireSize(numRows, numCols, GetFormat(), growOnly);
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::RequireSize(const size_t numRows, const size_t numCols, const size_t numNZElemToReserve, const MatrixFormat matrixFormat, const bool growOnly /*= true*/)
{
if (GetFormat() != matrixFormat || GetNumRows() != numRows || GetNumCols() != numCols)
Resize(numRows, numCols, numNZElemToReserve, matrixFormat, growOnly);
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::Resize(const size_t numRows, const size_t numCols, const size_t numNZElemToReserve /*= 10000*/, const bool growOnly /*= true*/)
{
Resize(numRows, numCols, numNZElemToReserve, GetFormat(), growOnly);
}
template <class ElemType>
void CPUSparseMatrix<ElemType>::Resize(const size_t numRows, const size_t numCols, const size_t numNZElemToReserve, const MatrixFormat matrixFormat, const bool growOnly /*= true*/)
{
VerifyResizable(__func__);
m_sliceViewOffset = 0;
m_numRows = numRows;
m_numCols = numCols;
SetNumStorageRows(numRows);
SetNumStorageCols(numCols);
SetFormat(matrixFormat);
size_t newCompIndexSize = (numCols > numRows ? numCols : numRows) + 1;
bool reallocate = (GetCompIndexSize() < newCompIndexSize);
if (reallocate)
Allocate(numRows, numCols, numNZElemToReserve, growOnly, false);
else
Reset();
}
// Reset matrix to 0.
template <class ElemType>
void CPUSparseMatrix<ElemType>::Reset()
{
// This is equivalent to setting m_nz = 0; Note we can only do this for sparse CSC/CSR because CompIndexSize is overloaded.
if (GetFormat() == MatrixFormat::matrixFormatSparseCSC || GetFormat() == MatrixFormat::matrixFormatSparseCSR)
memset(GetCompIndex(), 0, sizeof(CPUSPARSE_INDEX_TYPE) * GetCompIndexSize());
SetColIdx(-1);
SetBlockSize(0);
SetBlockIdShift(0);
}
// Implements product of one sparse and one dense matrix updating a third dense matrix. Input matrices are optionally transposed.
// NOTE: The only for using a class template instead of a function template was that I couldn't make the function template compile.
template <class ElemType, bool denseTimesSparse /* false means SparseTimesDense */, bool transposeA, bool transposeB>
class MultiplyDenseAndSparse{
public:
// Note: Below the ordering of the matrix parameters 'sparse' and 'dense' does not imply the order of the matrices in the product which is instead controlled
// by the value of the boolean template parameter 'denseTimesSparse'.
static void MultiplyAndWeightedAdd(ElemType alpha, const CPUSparseMatrix<ElemType>& sparse, const CPUMatrix<ElemType>& dense, ElemType beta, CPUMatrix<ElemType>& c)
{
const BaseMatrix<ElemType>* lhs = denseTimesSparse ? (const BaseMatrix<ElemType>*) &dense : (const BaseMatrix<ElemType>*) &sparse;
const BaseMatrix<ElemType>* rhs = denseTimesSparse ? (const BaseMatrix<ElemType>*) &sparse : (const BaseMatrix<ElemType>*) &dense;
// C(m:n) is the product of matrices X * Y where we have the shapes X(m:k) and Y(l:n)
size_t m = transposeA ? lhs->GetNumCols() : lhs->GetNumRows();
size_t k = transposeA ? lhs->GetNumRows() : lhs->GetNumCols();
size_t l = transposeB ? rhs->GetNumCols() : rhs->GetNumRows();
size_t n = transposeB ? rhs->GetNumRows() : rhs->GetNumCols();
if (k != l)
InvalidArgument("CPUSparseMatrix::MultiplyAndWeightedAdd: The inner dimensions of a (= %lu) and b (= %lu) don't match.", k, l);
// Determine the dimension of the outer index of the dense matrix.
size_t outerDimensionDense;
if ( denseTimesSparse && !transposeA) outerDimensionDense = dense.GetNumRows();
else if ( denseTimesSparse && transposeA) outerDimensionDense = dense.GetNumCols();
else if (!denseTimesSparse && !transposeB) outerDimensionDense = dense.GetNumCols();
else if (!denseTimesSparse && transposeB) outerDimensionDense = dense.GetNumRows();
if (beta == 0)
c.RequireSize(m, n);
else
c.VerifySize(m, n); // Can't resize if beta != 0
if (beta == 0)
memset(c.Data(), 0, sizeof(ElemType)* c.GetNumElements());
else if (beta != 1)
{
#pragma omp parallel for
foreach_coord(i, j, c)
{
c(i, j) = beta * c(i, j);
}
}
else /* beta == 1*/
; // We keep the previous value of c before adding the matrix product.
// In case one factor in the matrix product is empty there is nothing to add to the output c so we can exit here.
if (sparse.IsEmpty() || dense.IsEmpty())
return;
// TODO: Implement CSR as a transposition of b, like we do for GPU.
if (sparse.GetFormat() != matrixFormatSparseCSC)
NOT_IMPLEMENTED;
// Up to here we have:
// * checked that the matrices are compatible in size
// * Initialized the output matrix c
// Now do the actual multiplication.
ElemType* valueBuffer = sparse.Buffer() + *sparse.SecondaryIndexLocation(); // Points to the value buffer of the current view (i.e. buffer containing values of non-zero elements).
int* rowIndexBuffer = sparse.MajorIndexLocation(); // Points to the index buffer of the current view (i.e. buffer containing indices of non-zero elements).
size_t iNonzero = 0; // Number of nonzero elements handled so far for curent slice view.
int numPreviosNonzero = sparse.SecondaryIndexLocation()[0]; // Total number of nonzero values handled in previous slices.
// Loop over columns of the sparse matrix
for (size_t colSparse = 0; colSparse < sparse.GetNumCols(); colSparse++)
{
size_t numNonzeroInSparseCol = sparse.SecondaryIndexLocation()[colSparse + 1] - numPreviosNonzero;
// Loop over the nonzero rows of the current column of the sparse matrix
for (; iNonzero < numNonzeroInSparseCol; iNonzero++)
{
size_t rowSparse = rowIndexBuffer[iNonzero]; // RowLocation
ElemType sparseVal = valueBuffer[iNonzero];
// Determine the index of the 'outer' dimension of the sparse matrix and the common inner index.
size_t outerIndexSparse;
size_t innerIndex;
// Below if-statements are evaluated at compile time.
if ( denseTimesSparse && !transposeB) { outerIndexSparse = colSparse; innerIndex = rowSparse; }
else if ( denseTimesSparse && transposeB) { outerIndexSparse = rowSparse; innerIndex = colSparse; }
else if (!denseTimesSparse && !transposeA) { outerIndexSparse = rowSparse; innerIndex = colSparse; }
else if (!denseTimesSparse && transposeA) { outerIndexSparse = colSparse; innerIndex = rowSparse; }
// Loop over the outer index of the dense matrix
for (size_t outerIndexDense = 0; outerIndexDense < outerDimensionDense; outerIndexDense++)
{
// Determine the row index of the dense input matrix.
// Below if-statements are evaluated at compile time.
ElemType denseVal;
if ( denseTimesSparse && !transposeA) denseVal = dense(outerIndexDense, innerIndex);
else if ( denseTimesSparse && transposeA) denseVal = dense( innerIndex, outerIndexDense);
else if (!denseTimesSparse && !transposeB) denseVal = dense( innerIndex, outerIndexDense);
else if (!denseTimesSparse && transposeB) denseVal = dense(outerIndexDense, innerIndex);
// Update matrix c.
if (denseTimesSparse)
c(outerIndexDense, outerIndexSparse) += alpha * denseVal * sparseVal;
else /*Sparse times dense */
c(outerIndexSparse, outerIndexDense) += alpha * denseVal * sparseVal;
}
}
}
}
};
// c = alpha * lhs * rhs + beta * c
// dense * sparse -> dense
template <class ElemType>
void CPUSparseMatrix<ElemType>::MultiplyAndWeightedAdd(ElemType alpha, const CPUMatrix<ElemType>& a, const bool transposeA,
const CPUSparseMatrix<ElemType>& b, const bool transposeB, ElemType beta, CPUMatrix<ElemType>& c)
{
// Mapping variables to compile time template parameters for efficiency
if ( transposeA && transposeB)
MultiplyDenseAndSparse<ElemType, true /* dense times sparse */, true /* transposeA */, true /*transposeB*/>::MultiplyAndWeightedAdd(alpha, b /*sparse*/, a /* dense */, beta, c /* matrix beeing updated */);
else if ( transposeA && !transposeB)
MultiplyDenseAndSparse<ElemType, true /* dense times sparse */, true /* transposeA */, false /*transposeB*/>::MultiplyAndWeightedAdd(alpha, b /*sparse*/, a /* dense */, beta, c /* matrix beeing updated */);
else if (!transposeA && transposeB)
MultiplyDenseAndSparse<ElemType, true /* dense times sparse */, false /* transposeA */, true /*transposeB*/>::MultiplyAndWeightedAdd(alpha, b /*sparse*/, a /* dense */, beta, c /* matrix beeing updated */);
else if (!transposeA && !transposeB)
MultiplyDenseAndSparse<ElemType, true /* dense times sparse */, false /* transposeA */, false /*transposeB*/>::MultiplyAndWeightedAdd(alpha, b /*sparse*/, a /* dense */, beta, c /* matrix beeing updated */);
}
// c = alpha * lhs * rhs + beta * c
// sparse * dense -> dense
template <class ElemType>
void CPUSparseMatrix<ElemType>::MultiplyAndWeightedAdd(ElemType alpha, const CPUSparseMatrix<ElemType>& a, const bool transposeA,
const CPUMatrix<ElemType>& b, const bool transposeB, ElemType beta, CPUMatrix<ElemType>& c)
{
// Mapping variables to compile time template parameters for efficiency
if (transposeA && transposeB)
MultiplyDenseAndSparse<ElemType, false /* dense times sparse */, true /* transposeA */, true /*transposeB*/>::MultiplyAndWeightedAdd(alpha, a /*sparse*/, b /* dense */, beta, c /* matrix beeing updated */);
else if (transposeA && !transposeB)
MultiplyDenseAndSparse<ElemType, false /* dense times sparse */, true /* transposeA */, false /*transposeB*/>::MultiplyAndWeightedAdd(alpha, a /*sparse*/, b /* dense */, beta, c /* matrix beeing updated */);
else if (!transposeA && transposeB)
MultiplyDenseAndSparse<ElemType, false /* dense times sparse */, false /* transposeA */, true /*transposeB*/>::MultiplyAndWeightedAdd(alpha, a /*sparse*/, b /* dense */, beta, c /* matrix beeing updated */);
else if (!transposeA && !transposeB)
MultiplyDenseAndSparse<ElemType, false /* dense times sparse */, false /* transposeA */, false /*transposeB*/>::MultiplyAndWeightedAdd(alpha, a /*sparse*/, b /* dense */, beta, c /* matrix beeing updated */);
}
// c = alpha * lhs * rhs
// dense * sparse -> sparse
template <class ElemType>
void CPUSparseMatrix<ElemType>::MultiplyAndAdd(ElemType alpha, const CPUMatrix<ElemType>& lhs, const bool transposeA,
const CPUSparseMatrix<ElemType>& rhs, const bool transposeB, CPUSparseMatrix<ElemType>& c)
{
if (!c.OwnBuffer())
LogicError("Cannot modify since the buffer is managed externally.");
if (lhs.IsEmpty() || rhs.IsEmpty())
LogicError("LeftMultiplyAndAdd: one of the input matrix is empty.");
size_t m = transposeA ? (int) lhs.GetNumCols() : (int) lhs.GetNumRows();
size_t k = transposeA ? (int) lhs.GetNumRows() : (int) lhs.GetNumCols();
size_t l = transposeB ? (int) rhs.GetNumCols() : (int) rhs.GetNumRows();
size_t n = transposeB ? (int) rhs.GetNumRows() : (int) rhs.GetNumCols();
assert(m > 0 && k > 0 && l > 0 && n > 0);
m;
n; // converting from size_t to int may cause overflow
assert(k == l);
if (k != l)
{
InvalidArgument("CPUSparseMatrix::MultiplyAndAdd: The inner dimensions of a (= %lu) and b (= %lu) don't match.", k, l);
}
if (!transposeA && !transposeB)
{
NOT_IMPLEMENTED;
}
else if (!transposeA && transposeB)
{
if (rhs.GetFormat() != matrixFormatSparseCSC)
NOT_IMPLEMENTED;
// allocate enough memory
c.SetFormat(matrixFormatSparseBlockCol);
size_t blockSizePrev = c.GetBlockSize();
if (blockSizePrev == 0)
{
c.RequireSizeAndAllocate(m, n, 0, true); // allocate for blockIds
}