Blame view
src/matrix/sparse-matrix-test.cc
8.72 KB
8dcb6dfcb
first commit
|
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 |
// 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;
}
|