cu-tp-matrix-test.cc
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// cudamatrix/cu-tp-matrix-test.cc
//
// Copyright 2013 Ehsan Variani
// Lucas Ondel
// 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.
//
// UnitTests for testing cu-sp-matrix.h methods.
//
#include <iostream>
#include <vector>
#include <cstdlib>
#include "base/kaldi-common.h"
#include "cudamatrix/cu-device.h"
#include "cudamatrix/cu-tp-matrix.h"
#include "cudamatrix/cu-vector.h"
#include "cudamatrix/cu-math.h"
#include "cudamatrix/cu-sp-matrix.h"
using namespace kaldi;
namespace kaldi {
template<typename Real>
static void AssertEqual(const CuPackedMatrix<Real> &A,
const CuPackedMatrix<Real> &B,
float tol = 0.001) {
KALDI_ASSERT(A.NumRows() == B.NumRows());
for (MatrixIndexT i = 0; i < A.NumRows(); i++)
for (MatrixIndexT j = 0; j <= i; j++)
KALDI_ASSERT(std::abs(A(i, j) - B(i, j))
< tol * std::max(1.0, (double) (std::abs(A(i, j)) + std::abs(B(i, j)))));
}
template<typename Real>
static void AssertEqual(const PackedMatrix<Real> &A,
const PackedMatrix<Real> &B,
float tol = 0.001) {
KALDI_ASSERT(A.NumRows() == B.NumRows());
for (MatrixIndexT i = 0; i < A.NumRows(); i++)
for (MatrixIndexT j = 0; j <= i; j++)
KALDI_ASSERT(std::abs(A(i, j) - B(i, j))
< tol * std::max(1.0, (double) (std::abs(A(i, j)) + std::abs(B(i, j)))));
}
template<typename Real>
static void AssertEqual(const PackedMatrix<Real> &A,
const CuPackedMatrix<Real> &B,
float tol = 0.001) {
KALDI_ASSERT(A.NumRows() == B.NumRows());
for (MatrixIndexT i = 0; i < A.NumRows(); i++)
for (MatrixIndexT j = 0; j <= i; j++)
KALDI_ASSERT(std::abs(A(i, j) - B(i, j))
< tol * std::max(1.0, (double) (std::abs(A(i, j)) + std::abs(B(i, j)))));
}
/*
* Unit Tests
*/
template<typename Real>
static void UnitTestCuTpMatrixInvert() {
for (MatrixIndexT i = 1; i < 10; i++) {
MatrixIndexT dim = 5 * i + Rand() % 10;
TpMatrix<Real> A(dim);
A.SetRandn();
CuTpMatrix<Real> B(A);
AssertEqual<Real>(A, B, 0.005);
A.Invert();
B.Invert();
AssertEqual<Real>(A, B, 0.005);
}
}
template<typename Real>
static void UnitTestCuTpMatrixCopyFromTp() {
for (MatrixIndexT i = 1; i < 10; i++) {
MatrixIndexT dim = 5 * i + Rand() % 10;
TpMatrix<Real> A(dim);
A.SetRandn();
CuTpMatrix<Real> B(dim);
B.CopyFromTp(A);
CuTpMatrix<Real> C(dim);
C.CopyFromTp(B);
AssertEqual<Real>(A, B);
AssertEqual<Real>(B, C);
}
}
template<typename Real>
static void UnitTestCuTpMatrixCopyFromMat() {
for (MatrixIndexT i = 1; i < 10; i++) {
MatrixTransposeType trans = (i % 2 == 0 ? kNoTrans : kTrans);
MatrixIndexT dim = 10*i + Rand() % 5;
CuMatrix<Real> A(dim, dim);
A.SetRandn();
Matrix<Real> A2(A);
CuTpMatrix<Real> B(dim);
B.CopyFromMat(A, trans);
TpMatrix<Real> B2(dim);
B2.CopyFromMat(A2, trans);
TpMatrix<Real> B3(B);
AssertEqual(B2, B3);
KALDI_ASSERT(B3.Trace() != 0);
}
}
template<typename Real>
static void UnitTestCuTpMatrixCholesky() {
for (MatrixIndexT i = 1; i < 10; i++) {
MatrixIndexT dim = 1 + Rand() % 10;
if (i > 4) {
dim += 32 * (Rand() % 5);
}
Matrix<Real> M(dim, dim + 2);
M.SetRandn();
SpMatrix<Real> A(dim);
A.AddMat2(1.0, M, kNoTrans, 0.0); // sets A to random almost-surely +ve
// definite matrix.
CuSpMatrix<Real> B(A);
TpMatrix<Real> C(dim);
C.SetRandn();
CuTpMatrix<Real> D(C);
C.Cholesky(A);
D.Cholesky(B);
AssertEqual<Real>(C, D);
}
}
template<class Real>
static void UnitTestCuTpMatrixIO() {
for (int32 i = 0; i < 3; i++) {
int32 dimM = Rand() % 255 + 10;
if (i % 5 == 0) { dimM = 0; }
CuTpMatrix<Real> mat(dimM);
mat.SetRandn();
std::ostringstream os;
bool binary = (i % 4 < 2);
mat.Write(os, binary);
CuTpMatrix<Real> mat2;
std::istringstream is(os.str());
mat2.Read(is, binary);
AssertEqual(mat, mat2);
}
}
template<typename Real> void CudaTpMatrixUnitTest() {
UnitTestCuTpMatrixIO<Real>();
UnitTestCuTpMatrixInvert<Real>();
UnitTestCuTpMatrixCopyFromTp<Real>();
UnitTestCuTpMatrixCholesky<Real>();
UnitTestCuTpMatrixCopyFromMat<Real>();
}
} // namespace kaldi
int main() {
using namespace kaldi;
SetVerboseLevel(1);
int32 loop = 0;
#if HAVE_CUDA == 1
for (; loop < 2; loop++) {
CuDevice::Instantiate().SetDebugStrideMode(true);
if (loop == 0)
CuDevice::Instantiate().SelectGpuId("no"); // -1 means no GPU
else
CuDevice::Instantiate().SelectGpuId("yes"); // -2 .. automatic selection
#endif
kaldi::CudaTpMatrixUnitTest<float>();
#if HAVE_CUDA == 1
if (CuDevice::Instantiate().DoublePrecisionSupported()) {
kaldi::CudaTpMatrixUnitTest<double>();
} else {
KALDI_WARN << "Double precision not supported";
}
#else
kaldi::CudaTpMatrixUnitTest<double>();
#endif
if (loop == 0)
KALDI_LOG << "Tests without GPU use succeeded.";
else
KALDI_LOG << "Tests with GPU use (if available) succeeded.";
#if HAVE_CUDA == 1
}
CuDevice::Instantiate().PrintProfile();
#endif
return 0;
}