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Aurora/test/Function2D_Cuda_Test.cpp
kradchen 5f906f78b8 Fix complex fft bug
2023-12-14 17:42:06 +08:00

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#include <gtest/gtest.h>
#include <chrono>
#include "AuroraDefs.h"
#include "CudaMatrix.h"
#include "Function.h"
#include "Matrix.h"
#include "TestUtility.h"
#include "Function2D.h"
#include "Function2D.cuh"
class Function2D_Cuda_Test:public ::testing::Test
{
protected:
static void SetUpFunction2DCudaTester(){
}
static void TearDownTestCase(){
}
public:
Aurora::Matrix B;
Aurora::CudaMatrix dB;
void SetUp(){
}
void TearDown(){
}
};
TEST_F(Function2D_Cuda_Test, min)
{
// big data for test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
{
float *dataB = Aurora::random(4096*41472);
B = Aurora::Matrix::fromRawData(dataB, 4096, 41472);
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::min(B, Aurora::Column,r,c);
auto ret2 = Aurora::min(dB, Aurora::Column,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
ret1 = Aurora::min(B, Aurora::FunctionDirection::Row,r,c);
ret2 = Aurora::min(dB, Aurora::FunctionDirection::Row,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// different size speed
// Aurora::Matrix Aurora::min(const Aurora::Matrix &aMatrix,
// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
// in col wise
{
float *dataB = Aurora::random(3157*111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::min(B, Aurora::FunctionDirection::Column,r,c);
auto ret2 = Aurora::min(dB, Aurora::FunctionDirection::Column,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
B.forceReshape( 111,3157, 1);
dB = B.toDeviceMatrix();
ret1 = Aurora::min(B, Aurora::FunctionDirection::Column,r,c);
ret2 = Aurora::min(dB, Aurora::FunctionDirection::Column,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix, float aValue)
{
float *dataB = Aurora::random(3157*111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
dB = B.toDeviceMatrix();
long r,c;
auto start_time_ = std::chrono::high_resolution_clock::now();
auto ret1 = Aurora::min(B, 500.5f);
auto ret2 = Aurora::min(dB, 500.5f);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// const Aurora::Matrix &aOther)
// with same size matrix
{
float *dataB = Aurora::random(3157*111);
float *dataA = Aurora::random(3157*111);
auto A = Aurora::Matrix::fromRawData(dataA, 3157, 111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
auto dA = A.toDeviceMatrix();
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::min(B, A);
auto ret2 = Aurora::min(dB, dA);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// const Aurora::Matrix &aOther)
// with col-vec and matrix
{
float *dataB = Aurora::random(3157*111);
float *dataA = Aurora::random(3157);
auto A = Aurora::Matrix::fromRawData(dataA, 3157, 1);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
auto dA = A.toDeviceMatrix();
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::min(B, A);
auto ret2 = Aurora::min(dB, dA);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
ret2 = Aurora::min(dA, dB);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// const Aurora::Matrix &aOther)
// with row-vec and matrix
{
float *dataB = Aurora::random(3157*111);
float *dataA = Aurora::random(111);
auto A = Aurora::Matrix::fromRawData(dataA, 1, 111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
auto dA = A.toDeviceMatrix();
dB = B.toDeviceMatrix();
long r,c;
auto start_time_ = std::chrono::high_resolution_clock::now();
auto ret1 = Aurora::min(B, A);
auto ret2 = Aurora::min(dB, dA);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
}
TEST_F(Function2D_Cuda_Test, max)
{
// big data for test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
{
float *dataB = Aurora::random(4096*41472);
B = Aurora::Matrix::fromRawData(dataB, 4096, 41472);
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::max(B, Aurora::FunctionDirection::Column,r,c);
auto ret2 = Aurora::max(dB, Aurora::FunctionDirection::Column,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
ret1 = Aurora::max(B, Aurora::FunctionDirection::Row,r,c);
ret2 = Aurora::max(dB, Aurora::FunctionDirection::Row,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// different size speed
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
// in col wise
{
float *dataB = Aurora::random(3157*111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::max(B, Aurora::FunctionDirection::Column,r,c);
auto ret2 = Aurora::max(dB, Aurora::FunctionDirection::Column,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
B.forceReshape( 111,3157, 1);
dB = B.toDeviceMatrix();
ret1 = Aurora::max(B, Aurora::FunctionDirection::Column,r,c);
ret2 = Aurora::max(dB, Aurora::FunctionDirection::Column,r,c);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix, float aValue)
{
float *dataB = Aurora::random(3157*111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::max(B, 500.5f);
auto ret2 = Aurora::max(dB, 500.5f);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// const Aurora::Matrix &aOther)
// with same size matrix
{
float *dataB = Aurora::random(3157*111);
float *dataA = Aurora::random(3157*111);
auto A = Aurora::Matrix::fromRawData(dataA, 3157, 111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
auto dA = A.toDeviceMatrix();
dB = B.toDeviceMatrix();
long r,c;
auto start_time_ = std::chrono::high_resolution_clock::now();
auto ret1 = Aurora::max(B, A);
auto ret2 = Aurora::max(dB, dA);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// const Aurora::Matrix &aOther)
// with col-vec and matrix
{
float *dataB = Aurora::random(3157*111);
float *dataA = Aurora::random(3157);
auto A = Aurora::Matrix::fromRawData(dataA, 3157, 1);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
auto dA = A.toDeviceMatrix();
dB = B.toDeviceMatrix();
long r,c;
auto ret1 = Aurora::max(B, A);
// mat x vec
auto ret2 = Aurora::max(dB, dA);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
// vec x mat
ret2 = Aurora::max(dA, dB);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
// test
// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
// const Aurora::Matrix &aOther)
// with row-vec and matrix
{
float *dataB = Aurora::random(3157*111);
float *dataA = Aurora::random(111);
auto A = Aurora::Matrix::fromRawData(dataA, 1, 111);
B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
auto dA = A.toDeviceMatrix();
dB = B.toDeviceMatrix();
long r,c;
auto start_time_ = std::chrono::high_resolution_clock::now();
auto ret1 = Aurora::max(B, A);
// mat x vec
auto ret2 = Aurora::max(dB, dA);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
//vec x mat
ret2 = Aurora::max(dA, dB);
ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
}
TEST_F(Function2D_Cuda_Test, sum)
{
//
{
// float *dataB = Aurora::random(4096*50000);
float* dataB = new float[4096*5000];
for (size_t i = 0; i < 4096*5000; i++)
{
dataB[i] = (i%2==0?1.0f:0.0f);
}
B = Aurora::Matrix::fromRawData(dataB, 4096, 5000);
// B = Aurora::Matrix::fromRawData(dataB, 200, 200);
auto dD = B.toDeviceMatrix();
auto ret1 = Aurora::sum(B, Aurora::FunctionDirection::All);
auto ret2 = Aurora::sum(dD, Aurora::FunctionDirection::All);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
ret1 = Aurora::sum(B, Aurora::FunctionDirection::Column);
ret2 = Aurora::sum(dD, Aurora::FunctionDirection::Column);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i))
}
ret1 = Aurora::sum(B, Aurora::FunctionDirection::Row);
ret2 = Aurora::sum(dD, Aurora::FunctionDirection::Row);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i))
}
}
//complex type
{
float* dataB = new float[3000*2000*2];
for (size_t i = 0; i < 3000*4000; i++)
{
dataB[i] = i%2==0?2.0f:1.0f;
}
B = Aurora::Matrix::fromRawData(dataB,3000, 2000,1,Aurora::Complex);
auto dD = B.toDeviceMatrix();
auto ret1 = Aurora::sum(B, Aurora::FunctionDirection::All);
auto ret2 = Aurora::sum(dD, Aurora::FunctionDirection::All);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize()*2; i++)
{
EXPECT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
ret1 = Aurora::sum(B, Aurora::FunctionDirection::Column);
ret2 = Aurora::sum(dD, Aurora::FunctionDirection::Column);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i))
}
ret1 = Aurora::sum(B, Aurora::FunctionDirection::Row);
ret2 = Aurora::sum(dD, Aurora::FunctionDirection::Row);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i))
}
}
}
TEST_F(Function2D_Cuda_Test, mean)
{
//
{
float* dataB = new float[4096*500];
for (size_t i = 0; i < 4096*500; i++)
{
dataB[i] = (float)(i%2==0?1:0);
}
B = Aurora::Matrix::fromRawData(dataB, 4096, 500);
// B = Aurora::Matrix::fromRawData(dataB, 200, 200);
auto dD = B.toDeviceMatrix();
auto ret1 = Aurora::mean(B, Aurora::FunctionDirection::All);
auto ret2 = Aurora::mean(dD, Aurora::FunctionDirection::All);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
ret1 = Aurora::mean(B, Aurora::FunctionDirection::Column);
ret2 = Aurora::mean(dD, Aurora::FunctionDirection::Column);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i))
}
ret1 = Aurora::mean(B, Aurora::FunctionDirection::Row);
ret2 = Aurora::mean(dD, Aurora::FunctionDirection::Row);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i))
}
}
}
TEST_F(Function2D_Cuda_Test, sort)
{
//
{
float* dataB = Aurora::random(25000000);
B = Aurora::Matrix::fromRawData(dataB, 500, 500);
// B = Aurora::Matrix::fromRawData(dataB, 200, 200);
auto dD = B.toDeviceMatrix();
auto ret1 = Aurora::sort(B, Aurora::Column);
auto ret2 = Aurora::sort(dD,Aurora::Column);
EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
}
}
}
TEST_F(Function2D_Cuda_Test, fft)
{
{
float *input = new float[20]{1,1,0,2,2,0,1,1,0,2,1,1,0,2,2,0,1,1,0,2};
auto ma = Aurora::Matrix::fromRawData(input,10,2).toDeviceMatrix();
auto fftrett = Aurora::fft(ma);
auto fftrettH = fftrett.toHostMatrix();
std::complex<float>* result = (std::complex<float>*)fftrettH.getData();
//检验fft结果与matlab是否对应
EXPECT_FLOAT_EQ(0.0729, fourDecimalRound(result[1].real()));
EXPECT_FLOAT_EQ(2.4899, fourDecimalRound(result[2].imag()));
EXPECT_FLOAT_EQ(0.0729, fourDecimalRound(result[11].real()));
EXPECT_FLOAT_EQ(2.4899, fourDecimalRound(result[12].imag()));
//检验fft的结果是否共轭
EXPECT_FLOAT_EQ(0, result[4].imag()+result[6].imag());
EXPECT_FLOAT_EQ(0, result[4].real()-result[6].real());
auto ret= Aurora::ifft(fftrett);
auto retH = ret.toHostMatrix();
std::complex<float>* ifftResult = (std::complex<float>*)retH.getData();
EXPECT_FLOAT_EQ(fourDecimalRound(ifftResult[1].real()),1.0);
EXPECT_FLOAT_EQ(fourDecimalRound(ifftResult[3].real()),2.0);
EXPECT_FLOAT_EQ(fourDecimalRound(ifftResult[11].real()),1.0);
EXPECT_FLOAT_EQ(fourDecimalRound(ifftResult[13].real()),2.0);
auto fftrett2 = Aurora::fft(ma,5);
auto fftrett2H =fftrett2.toHostMatrix();
auto result2 = (std::complex<float>*)fftrett2H.getData();
//检验fft结果与matlab是否对应
EXPECT_FLOAT_EQ(0.3090, fourDecimalRound(result2[1].real()));
EXPECT_FLOAT_EQ(-1.3143, fourDecimalRound(result2[2].imag()));
EXPECT_FLOAT_EQ(-0.8090, fourDecimalRound(result2[7].real()));
EXPECT_FLOAT_EQ(1.3143, fourDecimalRound(result2[8].imag()));
auto fftrett3 = Aurora::fft(ma,12);
auto fftrett3H = fftrett3.toHostMatrix();
auto result3 = (std::complex<float>*)fftrett3H.getData();
//检验fft结果与matlab是否对应
EXPECT_FLOAT_EQ(-1.0, fourDecimalRound(result3[1].real()));
EXPECT_FLOAT_EQ(-3.4641, fourDecimalRound(result3[4].imag()));
EXPECT_FLOAT_EQ(-1.0, fourDecimalRound(result3[13].real()));
EXPECT_FLOAT_EQ(-3.4641, fourDecimalRound(result3[16].imag()));
}
{
float *input = new float[20]{1,1,0,2,2,0,1,1,0,2,1,1,0,2,2,0,1,1,0,2};
auto ma = Aurora::Matrix::fromRawData(input,10,1, 1,Aurora::Complex);
auto maD = ma.toDeviceMatrix();
auto ret1 = Aurora::fft(ma);
auto ret2 = Aurora::fft(maD);
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i));
}
ret1 = Aurora::fft(ma,12);
ret2 = Aurora::fft(maD,12);
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i));
}
ret1 = Aurora::fft(ma,8);
ret2 = Aurora::fft(maD,8);
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i));
}
}
{
float *input = new float[20]{1,1,0,2,2,0,1,1,0,2,1,1,0,2,2,0,1,1,0,2};
auto ma = Aurora::Matrix::fromRawData(input,10,1,1, Aurora::Complex);
auto maD = ma.toDeviceMatrix();
auto ret1 = Aurora::ifft(Aurora::fft(ma),12);
auto ret2 = Aurora::ifft(Aurora::fft(maD),12);
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i));
}
ret1 = Aurora::ifft(Aurora::fft(ma),8);
ret2 = Aurora::ifft(Aurora::fft(maD),8);
for (size_t i = 0; i < ret1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(ret1[i], ret2.getValue(i));
}
}
{
float * data = new float[36];
for (size_t i = 0; i < 18; i++)
{
data[i*2] = i%9+1;
data[i*2+1] = 1;
}
auto fm = Aurora::Matrix::fromRawData(data,9,2,1,Aurora::Complex);
auto fmD = fm.toDeviceMatrix();
Aurora::fftshift(fm);
Aurora::fftshift(fmD);
for (size_t i = 0; i < fm.getDataSize()*2; i++)
{
EXPECT_FLOAT_AE(fm[i], fmD.getValue(i));
}
Aurora::ifftshift(fm);
Aurora::ifftshift(fmD);
for (size_t i = 0; i < fm.getDataSize()*2; i++)
{
EXPECT_FLOAT_AE(fm[i], fmD.getValue(i));
}
}
{
float * data = new float[250000];
for (size_t i = 0; i < 250000; i++)
{
data[i] = i%500;
}
auto fm = Aurora::Matrix::fromRawData(data,500,250,1,Aurora::Complex);
auto fmD = fm.toDeviceMatrix();
Aurora::fftshift(fm);
Aurora::fftshift(fmD);
for (size_t i = 0; i < fm.getDataSize()*2; i++)
{
EXPECT_FLOAT_AE(fm[i], fmD.getValue(i));
}
Aurora::ifftshift(fm);
Aurora::ifftshift(fmD);
for (size_t i = 0; i < fm.getDataSize()*2; i++)
{
EXPECT_FLOAT_AE(fm[i], fmD.getValue(i));
}
}
{
float * data = new float[333*500];
for (size_t i = 0; i < 333*500; i++)
{
data[i] = i%333;
}
auto fm = Aurora::Matrix::fromRawData(data,333,250,1,Aurora::Complex);
auto fmD = fm.toDeviceMatrix();
Aurora::fftshift(fm);
Aurora::fftshift(fmD);
for (size_t i = 0; i < fm.getDataSize()*2; i++)
{
ASSERT_FLOAT_EQ(fm[i], fmD.getValue(i))<<"index:"<<i;
}
Aurora::ifftshift(fm);
Aurora::ifftshift(fmD);
for (size_t i = 0; i < fm.getDataSize()*2; i++)
{
EXPECT_FLOAT_AE(fm[i], fmD.getValue(i));
}
}
}
TEST_F(Function2D_Cuda_Test, immse) {
auto matrixHost1 = Aurora::Matrix::fromRawData(Aurora::random(10000), 50,200);
auto matrixHost2 = Aurora::Matrix::fromRawData(Aurora::random(10000), 50,200);
auto matrixDevice1 = matrixHost1.toDeviceMatrix();
auto matrixDevice2 = matrixHost1.toDeviceMatrix();
auto result1 = Aurora::immse(matrixHost1, matrixHost2);
auto result2 = Aurora::immse(matrixDevice1, matrixDevice2);
EXPECT_FLOAT_AE(result1, result2);
}
TEST_F(Function2D_Cuda_Test, sortRows) {
auto matrixHost1 = Aurora::Matrix::fromRawData(Aurora::random(10000), 50,200);
Aurora::Matrix matrixHost2;
auto matrixDevice1 = matrixHost1.toDeviceMatrix();
Aurora::CudaMatrix matrixDevice2;
auto result1 = Aurora::sortrows(matrixHost1, &matrixHost2);
auto result2 = Aurora::sortrows(matrixDevice1, matrixDevice2).toHostMatrix();
auto result3 = matrixHost2;
auto result4 = matrixDevice2.toHostMatrix();
ASSERT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
for (size_t i = 0; i < result1.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(result1[i], result2[i]);
}
ASSERT_FLOAT_EQ(result3.getDataSize(), result4.getDataSize());
for (size_t i = 0; i < result3.getDataSize(); i++)
{
ASSERT_FLOAT_EQ(result3[i], result4[i]);
}
}
TEST_F(Function2D_Cuda_Test, inv) {
auto matrixHost = Aurora::Matrix::fromRawData(new float[16]{4,6,7,8,9,3,7,5,4,3,2,1,2,3,4,5}, 4,4);
auto matrixDevice = matrixHost.toDeviceMatrix();
auto result1 = Aurora::inv(matrixHost);
auto result2 = Aurora::inv(matrixDevice).toHostMatrix();
ASSERT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
for (size_t i = 0; i < result1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(result1[i], result2[i]);
}
}
TEST_F(Function2D_Cuda_Test, dot) {
auto matrixHost1 = Aurora::Matrix::fromRawData(new float[200000], 1000,200);
auto matrixHost2 = Aurora::Matrix::fromRawData(new float[200000], 1000,200);
for(unsigned int i=0; i<200000;++i)
{
matrixHost1[i] = i;
matrixHost2[i] = i + 1;
}
auto matrixDevice1 = matrixHost1.toDeviceMatrix();
Aurora::CudaMatrix matrixDevice2 = matrixHost2.toDeviceMatrix();
auto result1 = Aurora::dot(matrixHost1, matrixHost2);
auto result2 = Aurora::dot(matrixDevice1, matrixDevice2).toHostMatrix();
ASSERT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
for (size_t i = 0; i < result1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(result1[i], result2[i]);
}
}
TEST_F(Function2D_Cuda_Test, prod) {
auto matrixHost = Aurora::Matrix::fromRawData(new float[20], 4,5);
for(unsigned int i=0; i<20;++i)
{
matrixHost[i] = i + 1;
}
auto matrixDevice = matrixHost.toDeviceMatrix();
auto result1 = Aurora::prod(matrixHost);
auto result2 = Aurora::prod(matrixDevice).toHostMatrix();
ASSERT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
for (size_t i = 0; i < result1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(result1[i], result2[i]);
}
matrixHost = Aurora::Matrix::fromRawData(new float[20], 20,1);
for(unsigned int i=0; i<20;++i)
{
matrixHost[i] = i + 1;
}
matrixDevice = matrixHost.toDeviceMatrix();
result1 = Aurora::prod(matrixHost);
result2 = Aurora::prod(matrixDevice).toHostMatrix();
ASSERT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
for (size_t i = 0; i < result1.getDataSize(); i++)
{
EXPECT_FLOAT_AE(result1[i], result2[i]);
}
auto matrixHostComplex = Aurora::Matrix::fromRawData(new float[20], 2,5, 1,Aurora::Complex);
for(unsigned int i=0; i<20;++i)
{
matrixHost[i] = i + 1;
}
matrixDevice = matrixHostComplex.toDeviceMatrix();
result1 = Aurora::prod(matrixHostComplex);
result2 = Aurora::prod(matrixDevice).toHostMatrix();
ASSERT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
ASSERT_FLOAT_EQ(result1.getValueType(), result2.getValueType());
for (size_t i = 0; i < result1.getDataSize() * result1.getValueType(); i++)
{
EXPECT_FLOAT_AE(result1[i], result2[i]);
}
}
TEST_F(Function2D_Cuda_Test, sub2ind) {
float* dI1= new float[4]{1,2,1,2};
Aurora::Matrix I1(std::shared_ptr<float>(dI1,std::default_delete<float[]>()),std::vector<int>{4});
float* dI2= new float[4]{2,2,1,1};
Aurora::Matrix I2(std::shared_ptr<float>(dI2,std::default_delete<float[]>()),std::vector<int>{4});
float* dI4= new float[4]{1,1,2,2};
Aurora::Matrix I3(std::shared_ptr<float>(dI4,std::default_delete<float[]>()),std::vector<int>{4});
float* dsz= new float[3]{2,2,2};
Aurora::Matrix sz(std::shared_ptr<float>(dsz,std::default_delete<float[]>()),std::vector<int>{3});
auto result1 = Aurora::sub2ind(sz, {I1, I2, I3});
auto result2 = Aurora::sub2ind(sz.toDeviceMatrix(), {I1.toDeviceMatrix(), I2.toDeviceMatrix(), I3.toDeviceMatrix()}).toHostMatrix();
EXPECT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
for(unsigned int i=0; i<result1.getDataSize(); ++i)
{
EXPECT_FLOAT_EQ(result1[i], result2[i]);
}
}
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