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// matrix/sparse-matrix-test.cc
// Copyright 2015 Guoguo Chen
// 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 "matrix/matrix-lib.h"
#include "util/stl-utils.h"
namespace kaldi {
template <typename Real>
void UnitTestSparseVectorSum() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT dim = 10 + Rand() % 40;
SparseVector<Real> svec(dim);
svec.SetRandn(0.8);
Vector<Real> vec(dim);
vec.SetRandn();
svec.CopyElementsToVec(&vec);
Real sum1 = svec.Sum();
Real sum2 = vec.Sum();
AssertEqual(sum1, sum2, 0.00001);
}
}
template <typename Real>
void UnitTestSparseVectorAddToVec() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT dim = 10 + Rand() % 40;
SparseVector<Real> svec(dim);
svec.SetRandn(0.8);
Vector<Real> vec(dim);
vec.SetRandn();
svec.CopyElementsToVec(&vec);
Vector<Real> other_vec1(dim);
other_vec1.SetRandn();
Vector<Real> other_vec2 = other_vec1;
svec.AddToVec(0.7, &other_vec1);
other_vec2.AddVec(0.7, vec);
AssertEqual(other_vec1, other_vec2, 0.00001);
}
}
template <typename Real>
void UnitTestSparseVectorMax() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT dim = 10 + Rand() % 40;
if (RandInt(0, 3) == 0)
dim = RandInt(1, 5);
SparseVector<Real> svec(dim);
if (RandInt(0, 3) != 0)
svec.SetRandn(0.8);
Vector<Real> vec(dim);
vec.SetRandn();
svec.CopyElementsToVec(&vec);
int32 index1, index2;
Real max1, max2;
max1 = svec.Max(&index1);
max2 = vec.Max(&index2);
AssertEqual(max1, max2, 0.00001);
AssertEqual(index1, index2, 0.00001);
}
}
template <typename Real>
void UnitTestSparseVectorVecSvec() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT dim = 10 + Rand() % 40;
SparseVector<Real> svec(dim);
svec.SetRandn(0.8);
Vector<Real> vec(dim);
vec.SetRandn();
svec.CopyElementsToVec(&vec);
Vector<Real> other_vec(dim);
other_vec.SetRandn();
Real product1 = VecSvec(other_vec, svec);
Real product2 = VecVec(other_vec, vec);
KALDI_ASSERT(fabs(product1 - product2) < 1.0e-04);
}
}
template <typename Real>
void UnitTestSparseMatrixSum() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT row = 10 + Rand() % 40;
MatrixIndexT col = 10 + Rand() % 50;
SparseMatrix<Real> smat(row, col);
smat.SetRandn(0.8);
Matrix<Real> mat(row, col);
mat.SetRandn();
smat.CopyToMat(&mat);
Real sum1 = smat.Sum();
Real sum2 = mat.Sum();
AssertEqual(sum1, sum2, 0.00001);
}
}
template <typename Real>
void UnitTestSparseMatrixFrobeniusNorm() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT row = 10 + Rand() % 40;
MatrixIndexT col = 10 + Rand() % 50;
SparseMatrix<Real> smat(row, col);
smat.SetRandn(0.8);
Matrix<Real> mat(row, col);
mat.SetRandn();
smat.CopyToMat(&mat);
Real norm1 = smat.FrobeniusNorm();
Real norm2 = mat.FrobeniusNorm();
AssertEqual(norm1, norm2, 0.00001);
}
}
template <typename Real>
void UnitTestSparseMatrixAddToMat() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT row = 10 + Rand() % 40;
MatrixIndexT col = 10 + Rand() % 50;
SparseMatrix<Real> smat(row, col);
smat.SetRandn(0.8);
Matrix<Real> mat(row, col);
mat.SetRandn();
smat.CopyToMat(&mat);
Matrix<Real> other_mat1(row, col);
other_mat1.SetRandn();
Matrix<Real> other_mat2 = other_mat1;
smat.AddToMat(0.7, &other_mat1);
other_mat2.AddMat(0.7, mat);
AssertEqual(other_mat1, other_mat2, 0.00001);
}
}
template <typename Real>
void UnitTestSparseMatrixConstructor() {
int32 num_rows = RandInt(1, 10),
num_cols = RandInt(0, 10);
if (num_cols == 0)
num_rows = 0;
Matrix<Real> mat(num_rows, num_cols);
for (int32 r = 0; r < num_rows; r++) {
for (int32 c = 0; c < num_cols; c++) {
if (RandInt(0, 5) == 0)
mat(r, c) = RandGauss();
}
}
SparseMatrix<Real> smat(mat);
Matrix<Real> mat2(num_rows, num_cols);
mat2.SetRandn();
smat.CopyToMat(&mat2);
AssertEqual(mat, mat2);
}
template <typename Real>
void UnitTestSparseMatrixTraceMatSmat() {
for (int32 i = 0; i < 10; i++) {
MatrixIndexT row = 10 + Rand() % 40;
MatrixIndexT col = 10 + Rand() % 50;
Matrix<Real> mat1(row, col);
Matrix<Real> mat2(col, row);
Matrix<Real> mat3(row, col);
mat1.SetRandn();
mat2.SetRandn();
mat3.SetRandn();
SparseMatrix<Real> smat1(row, col);
SparseMatrix<Real> smat2(col, row);
smat1.SetRandn(0.8);
smat2.SetRandn(0.8);
smat1.CopyToMat(&mat1);
smat2.CopyToMat(&mat2);
Real trace1 = TraceMatMat(mat3, mat1, kTrans);
Real trace2 = TraceMatSmat(mat3, smat1, kTrans);
AssertEqual(trace1, trace2, 0.00001);
trace1 = TraceMatMat(mat3, mat2, kNoTrans);
trace2 = TraceMatSmat(mat3, smat2, kNoTrans);
AssertEqual(trace1, trace2, 0.00001);
}
}
template <typename Real>
void UnitTestMatrixAddMatSmat() {
for (int32 t = 0; t < 4; t++) {
MatrixIndexT m = RandInt(10, 20), n = RandInt(10, 20), o = RandInt(10, 20);
MatrixTransposeType Btrans = (RandInt(0, 1) == 0 ? kTrans : kNoTrans);
// we are effectively comparing trace(A B C) computed as
// trace((A B) C) vs. trace ((C A) B)
BaseFloat alpha = 0.333, beta = 1.764;
Matrix<Real> A(m, n);
A.SetRandn();
SparseMatrix<Real> B(Btrans == kNoTrans ? n : o,
Btrans == kNoTrans ? o : n);
B.SetRandn(0.5);
Matrix<Real> AB(m, o);
AB.SetRandn(); // this random extra part is used in testing the 'beta'.
Matrix<Real> C(o, m);
C.SetRandn();
Matrix<Real> CA(o, n);
CA.AddMatMat(1.0, C, kNoTrans, A, kNoTrans, 0.0);
Real trace_abc_alpha = TraceMatSmat(CA, B, Btrans);
Real trace_abc_beta = TraceMatMat(AB, C, kNoTrans);
AB.AddMatSmat(alpha, A, B, Btrans, beta);
// next line is in case I made certain mistakes like setting matrix to
// random.
KALDI_ASSERT(trace_abc_alpha != 0.0 && trace_abc_beta != 0.0);
Real result1 = TraceMatMat(AB, C, kNoTrans),
result2 = alpha * trace_abc_alpha + beta * trace_abc_beta;
AssertEqual(result1, result2, 0.01);
}
}
template <typename Real>
void UnitTestMatrixAddSmatMat() {
for (int32 t = 0; t < 4; t++) {
MatrixIndexT m = RandInt(10, 20), n = RandInt(10, 20), o = RandInt(10, 20);
MatrixTransposeType Btrans = (RandInt(0, 1) == 0 ? kTrans : kNoTrans);
// we are effectively comparing trace(A B C) computed as
// trace((A B) C) vs. trace ((C A) B)
BaseFloat alpha = 0.333, beta = 1.764;
Matrix<Real> A(m, n);
A.SetRandn();
SparseMatrix<Real> B(Btrans == kNoTrans ? n : o,
Btrans == kNoTrans ? o : n);
B.SetRandn(0.5);
Matrix<Real> C(o, m);
C.SetRandn();
Matrix<Real> BC(n, m);
BC.SetRandn(); // this random extra part is used in testing the 'beta'.
Matrix<Real> CA(o, n);
CA.AddMatMat(1.0, C, kNoTrans, A, kNoTrans, 0.0);
Real trace_abc_alpha = TraceMatSmat(CA, B, Btrans);
Real trace_abc_beta = TraceMatMat(A, BC, kNoTrans);
BC.AddSmatMat(alpha, B, Btrans, C, beta);
// next line is in case I made certain mistakes like setting matrix to
// random.
KALDI_ASSERT(trace_abc_alpha != 0.0 && trace_abc_beta != 0.0);
Real result1 = TraceMatMat(A, BC, kNoTrans),
result2 = alpha * trace_abc_alpha + beta * trace_abc_beta;
AssertEqual(result1, result2, 0.01);
}
}
template <typename Real>
void SparseMatrixUnitTest() {
// SparseVector
UnitTestSparseVectorSum<Real>();
UnitTestSparseVectorAddToVec<Real>();
UnitTestSparseVectorMax<Real>();
UnitTestSparseVectorVecSvec<Real>();
// SparseMatrix
UnitTestSparseMatrixSum<Real>();
UnitTestSparseMatrixFrobeniusNorm<Real>();
UnitTestSparseMatrixAddToMat<Real>();
UnitTestSparseMatrixTraceMatSmat<Real>();
for (int32 i = 0; i < 30; i++)
UnitTestSparseMatrixConstructor<Real>();
// Matrix functions involving sparse matrices.
UnitTestMatrixAddMatSmat<Real>();
UnitTestMatrixAddSmatMat<Real>();
}
} // namespace kaldi
int main() {
kaldi::SetVerboseLevel(5);
kaldi::SparseMatrixUnitTest<float>();
kaldi::SparseMatrixUnitTest<double>();
KALDI_LOG << "Tests succeeded.";
return 0;
}