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Commit 58ff4812 authored by Lukas Cejka's avatar Lukas Cejka
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Added another approach using Vector.h for test of vectorProduct function.... 

Added another approach using Vector.h for test of vectorProduct function. Added a concept test of performSORIteration function. Added test for save and load functions. Updated TODO.
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src/UnitTests/Matrices/SparseMatrixTest.h
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...@@ -16,7 +16,7 @@ ...@@ -16,7 +16,7 @@
* getSerializationTypeVirtual() ::TEST? This just calls getSerializationType(). * getSerializationTypeVirtual() ::TEST? This just calls getSerializationType().
* setDimensions() ::DONE * setDimensions() ::DONE
* setCompressedRowLengths() ::DONE * setCompressedRowLengths() ::DONE
* getRowLength() ::USED! in test_SetCompressedRowLengths() to verify the test itself. * getRowLength() ::USED! In test_SetCompressedRowLengths() to verify the test itself.
* getRowLengthFast() ::TEST? How to test __cuda_callable__? * getRowLengthFast() ::TEST? How to test __cuda_callable__?
* setLike() ::DONE * setLike() ::DONE
* reset() ::DONE * reset() ::DONE
...@@ -29,20 +29,20 @@ ...@@ -29,20 +29,20 @@
* addRowFast() ::TEST? How to test __cuda_callable__? * addRowFast() ::TEST? How to test __cuda_callable__?
* addRow() ::NOT IMPLEMENTED! Implement? Is it supposed to add an extra row to the matrix or arr elements of a row to another row in the matrix? * addRow() ::NOT IMPLEMENTED! Implement? Is it supposed to add an extra row to the matrix or arr elements of a row to another row in the matrix?
* getElementFast() ::TEST? How to test __cuda_callable__? * getElementFast() ::TEST? How to test __cuda_callable__?
* getElement() ::USED! in test_SetElement(), test_AddElement() and test_setRow() to verify the test itself. * getElement() ::USED! In test_SetElement(), test_AddElement() and test_setRow() to verify the test itself.
* getRowFast() ::TEST? How to test __cuda_callable__? * getRowFast() ::TEST? How to test __cuda_callable__?
* MatrixRow getRow() ::TEST? How to test __cuda_callable__? * MatrixRow getRow() ::TEST? How to test __cuda_callable__?
* ConstMatrixRow getRow() ::TEST? How to test __cuda_callable__? * ConstMatrixRow getRow() ::TEST? How to test __cuda_callable__?
* rowVectorProduct() ::TEST? How to test __cuda_callable__? * rowVectorProduct() ::TEST? How to test __cuda_callable__?
* vectorProduct() * vectorProduct() ::HOW? Throwing errors in CSR_impl.h (779) no instance matches the arguments when using int arrays. When tried using Vector_impl.h index out of bounds or CUDA illegal memory access
* addMatrix() * addMatrix() ::NOT IMPLEMENTED!
* getTransposition() * getTransposition() ::NOT IMPLMENETED!
* performSORIteration() * performSORIteration() ::HOW? What does this do? Ax=b but splitting A into D(:=Diagonal) L(:=Lower Triangular) U(=Upper Triangular) matrices. What is the omega(relaxation/residual factor??)? https://en.wikipedia.org/wiki/Successive_over-relaxation
* operator=() * operator=() ::HOW? What is this supposed to enable? Overloading operators?
* save( File& file) * save( File& file) ::USED! In save( String& fileName )
* load( File& file ) * load( File& file ) ::USED! In load( String& fileName )
* save( String& fileName ) * save( String& fileName ) ::DONE
* load( String& fileName ) * load( String& fileName ) ::DONE
* print() * print()
* setCudaKernelType() * setCudaKernelType()
* getCudaKernelType() ::TEST? How to test __cuda_callable__? * getCudaKernelType() ::TEST? How to test __cuda_callable__?
...@@ -352,7 +352,77 @@ void test_VectorProduct() ...@@ -352,7 +352,77 @@ void test_VectorProduct()
* | 0 8 9 10 | * | 0 8 9 10 |
* \ 0 0 11 12 / * \ 0 0 11 12 /
*/ */
// const int m_rows = 5; bool testRan = false;
const int m_rows = 5;
const int m_cols = 4;
Matrix m;
m.reset();
m.setDimensions( m_rows, m_cols );
typename Matrix::CompressedRowLengthsVector rowLengths;
rowLengths.setSize( m_rows );
rowLengths.setValue( 3 );
m.setCompressedRowLengths( rowLengths );
int value = 1;
for( int i = 0; i < m_cols - 1; i++ ) // 0th row
m.setElement( 0, i, value++ );
m.setElement( 1, 3, value++ ); // 1st row
for( int i = 0; i < m_cols - 1; i++ ) // 2nd row
m.setElement( 2, i, value++ );
for( int i = 1; i < m_cols; i++ ) // 3rd row
m.setElement( 3, i, value++ );
for( int i = 2; i < m_cols; i++ ) // 4th row
m.setElement( 4, i, value++ );
// #include <TNL/Containers/Vector.h>
// #include <TNL/Containers/VectorView.h>
//
// using namespace TNL;
// using namespace TNL::Containers;
// using namespace TNL::Containers::Algorithms;
//
// Vector< int, Devices::Host, int > inVector;
// inVector.setSize( 5 );
// for( int i = 0; i < inVector.getSize(); i++ )
// inVector.setElement( i, 1 );
//
// Vector< int, Devices::Host, int > outVector;
// outVector.setSize( 4 ); // ERROR: out of bounds, if set to 3 or 4. CUDA illegal memory access when set to 5.
// for( int j = 0; j < outVector.getSize(); j++ )
// outVector.setElement( j, 0 );//outVector[ j ] = 0;
// const int inVector [ 5 ] = { 1, 1, 1, 1, 1 };
// int outVector [ 4 ] = { 0, 0, 0, 0 };
//
// m.vectorProduct( inVector, outVector); // ERROR: This throws an error when Vector<> declarations are used.
// testRan = true;
// EXPECT_EQ( outVector.getElement( 0 ), 6 );
// EXPECT_EQ( outVector.getElement( 1 ), 16 );
// EXPECT_EQ( outVector.getElement( 2 ), 30 );
// EXPECT_EQ( outVector.getElement( 3 ), 26 );
EXPECT_TRUE( testRan );
std::cout << "TEST DID NOT RUN. NOT IMPLETENTED.\n";
}
template< typename Matrix >
void test_PerformSORIteration()
{
/*
* Sets up the following 5x4 sparse matrix:
*
* / 1 2 3 0 \
* | 0 4 0 5 |
* | 6 7 8 0 |
* \ 0 9 10 11 /
*/
bool testRan = false;
// const int m_rows = 4;
// const int m_cols = 4; // const int m_cols = 4;
// //
// Matrix m; // Matrix m;
...@@ -360,13 +430,14 @@ void test_VectorProduct() ...@@ -360,13 +430,14 @@ void test_VectorProduct()
// m.setDimensions( m_rows, m_cols ); // m.setDimensions( m_rows, m_cols );
// typename Matrix::CompressedRowLengthsVector rowLengths; // typename Matrix::CompressedRowLengthsVector rowLengths;
// rowLengths.setSize( m_rows ); // rowLengths.setSize( m_rows );
// rowLengths.setValue( 4 ); // rowLengths.setValue( 3 );
// m.setCompressedRowLengths( rowLengths ); // m.setCompressedRowLengths( rowLengths );
// //
// int value = 1; // int value = 1;
// for( int i = 0; i < m_cols - 1; i++ ) // 0th row // for( int i = 0; i < m_cols - 1; i++ ) // 0th row
// m.setElement( 0, i, value++ ); // m.setElement( 0, i, value++ );
// //
// m.setElement( 1, 1, value++ );
// m.setElement( 1, 3, value++ ); // 1st row // m.setElement( 1, 3, value++ ); // 1st row
// //
// for( int i = 0; i < m_cols - 1; i++ ) // 2nd row // for( int i = 0; i < m_cols - 1; i++ ) // 2nd row
...@@ -374,21 +445,117 @@ void test_VectorProduct() ...@@ -374,21 +445,117 @@ void test_VectorProduct()
// //
// for( int i = 1; i < m_cols; i++ ) // 3rd row // for( int i = 1; i < m_cols; i++ ) // 3rd row
// m.setElement( 3, i, value++ ); // m.setElement( 3, i, value++ );
//
// for( int i = 2; i < m_cols; i++ ) // 4th row
// m.setElement( 4, i, value++ );
//
// const int inVector [ 5 ] = { 1, 1, 1, 1, 1 };
// int outVector [ 4 ] = { 0, 0, 0, 0 };
// //
// m.vectorProduct( inVector, outVector); // // Print out the Matrix
// std::cout << "Matrix m: \n";
// for( int i = 0; i < m_rows; i++ )
// {
// std::cout << "| ";
// for(int j = 0; j < m_cols; j++ )
// std::cout << m.getElement( i, j ) << " ";
// std::cout << " |\n";
// }
// std::cout << std::endl;
//
// int bVector [ 4 ] = { 6, 9, 21, 30 };
// int xVector [ 4 ] = { 1, 1, 1, 1 };
// //
// EXPECT_EQ( outVector[0], 6 ); // m.performSORIteration( bVector, 0, xVector, 1);
// EXPECT_EQ( outVector[1], 16 ); // m.performSORIteration( bVector, 1, xVector, 1);
// EXPECT_EQ( outVector[2], 30 ); // m.performSORIteration( bVector, 2, xVector, 1);
// EXPECT_EQ( outVector[3], 26 ); // m.performSORIteration( bVector, 3, xVector, 1);
//
// std::cout << "\n[ ";
// for( int i = 0; i < 4; i++ )
// std::cout << xVector[ i ] << " ";
// std::cout << " ]\n";
//
// std::cout << "\n[ ";
// for( int i = 0; i < 4; i++ )
// std::cout << bVector[ i ] << " ";
// std::cout << " ]\n";
//
// testRan = true;
// EXPECT_EQ( xVector[ 0 ], 1 );
// EXPECT_EQ( xVector[ 1 ], 1 );
// EXPECT_EQ( xVector[ 2 ], 1 );
// EXPECT_EQ( xVector[ 3 ], 1 );
EXPECT_TRUE( testRan );
std::cout << "TEST DID NOT RUN. NOT IMPLETENTED.\n";
} }
template< typename Matrix >
void test_SaveAndLoad()
{
/*
* Sets up the following 5x4 sparse matrix:
*
* / 1 2 3 0 \
* | 0 4 0 5 |
* | 6 7 8 0 |
* \ 0 9 10 11 /
*/
const int m_rows = 4;
const int m_cols = 4;
Matrix savedMatrix;
savedMatrix.reset();
savedMatrix.setDimensions( m_rows, m_cols );
typename Matrix::CompressedRowLengthsVector rowLengths;
rowLengths.setSize( m_rows );
rowLengths.setValue( 3 );
savedMatrix.setCompressedRowLengths( rowLengths );
int value = 1;
for( int i = 0; i < m_cols - 1; i++ ) // 0th row
savedMatrix.setElement( 0, i, value++ );
savedMatrix.setElement( 1, 1, value++ );
savedMatrix.setElement( 1, 3, value++ ); // 1st row
for( int i = 0; i < m_cols - 1; i++ ) // 2nd row
savedMatrix.setElement( 2, i, value++ );
for( int i = 1; i < m_cols; i++ ) // 3rd row
savedMatrix.setElement( 3, i, value++ );
savedMatrix.save( "/home/lukas/m" );
Matrix loadedMatrix;
loadedMatrix.reset();
loadedMatrix.setDimensions( m_rows, m_cols );
typename Matrix::CompressedRowLengthsVector rowLengths2;
rowLengths2.setSize( m_rows );
rowLengths2.setValue( 3 );
loadedMatrix.setCompressedRowLengths( rowLengths2 );
loadedMatrix.load( "/home/lukas/m" );
EXPECT_EQ( savedMatrix.getElement( 0, 0 ), loadedMatrix.getElement( 0, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 0, 1 ), loadedMatrix.getElement( 0, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 0, 2 ), loadedMatrix.getElement( 0, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 0, 3 ), loadedMatrix.getElement( 0, 3 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 0 ), loadedMatrix.getElement( 1, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 1 ), loadedMatrix.getElement( 1, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 2 ), loadedMatrix.getElement( 1, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 1, 3 ), loadedMatrix.getElement( 1, 3 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 0 ), loadedMatrix.getElement( 2, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 1 ), loadedMatrix.getElement( 2, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 2 ), loadedMatrix.getElement( 2, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 2, 3 ), loadedMatrix.getElement( 2, 3 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 0 ), loadedMatrix.getElement( 3, 0 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 1 ), loadedMatrix.getElement( 3, 1 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 2 ), loadedMatrix.getElement( 3, 2 ) );
EXPECT_EQ( savedMatrix.getElement( 3, 3 ), loadedMatrix.getElement( 3, 3 ) );
}
TEST( SparseMatrixTest, CSR_GetTypeTest_Host ) TEST( SparseMatrixTest, CSR_GetTypeTest_Host )
{ {
host_test_GetType< CSR_host_float, CSR_host_int >(); host_test_GetType< CSR_host_float, CSR_host_int >();
...@@ -497,6 +664,30 @@ TEST( SparseMatrixTest, CSR_vectorProductTest_Cuda ) ...@@ -497,6 +664,30 @@ TEST( SparseMatrixTest, CSR_vectorProductTest_Cuda )
} }
#endif #endif
TEST( SparseMatrixTest, CSR_perforSORIterationTest_Host )
{
test_PerformSORIteration< CSR_host_int >();
}
#ifdef HAVE_CUDA
TEST( SparseMatrixTest, CSR_perforSORIterationTest_Cuda )
{
test_PerformSORIteration< CSR_cuda_int >();
}
#endif
TEST( SparseMatrixTest, CSR_saveAndLoadTest_Host )
{
test_SaveAndLoad< CSR_host_int >();
}
#ifdef HAVE_CUDA
TEST( SparseMatrixTest, CSR_saveAndLoadTest_Cuda )
{
test_SaveAndLoad< CSR_cuda_int >();
}
#endif
#endif #endif
#include "../GtestMissingError.h" #include "../GtestMissingError.h"
......
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