968 lines
34 KiB
C++
968 lines
34 KiB
C++
#include <gtest/gtest.h>
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#include "CudaMatrix.h"
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#include "Matrix.h"
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#include "TestUtility.h"
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#include "Function1D.h"
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#include "Function1D.cuh"
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class Function1D_Cuda_Test:public ::testing::Test
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{
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protected:
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static void SetUpFunction1DCudaTester(){
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}
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static void TearDownTestCase(){
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}
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void SetUp(){
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}
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void TearDown(){
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}
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};
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TEST_F(Function1D_Cuda_Test, complex)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1,2,3,4,5,6,7,8}, 2,2,2);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::complex(hostMatrix);
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auto result2 = Aurora::complex(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * 2; ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, real)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1,2,3,4,5,6,7,8}, 2,2,1,Aurora::Complex);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::real(hostMatrix);
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auto result2 = Aurora::real(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, imag)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1,2,3,4,5,6,7,8}, 2,2,1,Aurora::Complex);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::imag(hostMatrix);
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auto result2 = Aurora::imag(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, ceil)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::ceil(hostMatrix);
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auto result2 = Aurora::ceil(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::ceil(hostMatrix);
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result2 = Aurora::ceil(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, round)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::round(hostMatrix);
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auto result2 = Aurora::round(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::round(hostMatrix);
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result2 = Aurora::round(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, floor)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::floor(hostMatrix);
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auto result2 = Aurora::floor(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::floor(hostMatrix);
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result2 = Aurora::floor(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, sqrt)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::sqrt(hostMatrix);
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auto result2 = Aurora::sqrt(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::sqrt(hostMatrix);
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result2 = Aurora::sqrt(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
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EXPECT_EQ(result2.getValueType(), result1.getValueType());
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, abs)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[10000]{0}, 1,10000);
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for (size_t i = 0; i < 10000; i++)
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{
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hostMatrix[i]=i;
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}
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::abs(hostMatrix);
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auto result2 = Aurora::abs(deviceMatrix).toHostMatrix();
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// EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::abs(hostMatrix);
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result2 = Aurora::abs(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, sign)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::sign(hostMatrix);
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auto result2 = Aurora::sign(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::sign(hostMatrix);
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result2 = Aurora::sign(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, repmat)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::repmat(hostMatrix,3,6);
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auto result2 = Aurora::repmat(deviceMatrix,3,6).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 8 * 3 * 6);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,2,1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::repmat(hostMatrix, 4, 8);
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result2 = Aurora::repmat(deviceMatrix, 4, 8).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 4 * 4 * 8);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9.9,10,11,12}, 3, 4, 1,Aurora::Normal);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::repmat(hostMatrix, 4, 8, 3);
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result2 = Aurora::repmat(deviceMatrix, 4, 8, 3).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 3 * 4 * 4 * 8 * 3);
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9.9,10,11,12}, 3, 2, 1,Aurora::Complex);
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deviceMatrix = hostMatrix.toDeviceMatrix();
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result1 = Aurora::repmat(hostMatrix, 4, 8, 3);
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result2 = Aurora::repmat(deviceMatrix, 4, 8, 3).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), 3 * 2 * 4 * 8 * 3);
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EXPECT_EQ(result2.getValueType(), Aurora::Complex);
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, repmat3d)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9,10,11,12}, 2,3,2);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::repmat3d(hostMatrix,3,6,4);
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auto result2 = Aurora::repmat3d(deviceMatrix,3,6,4).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
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EXPECT_EQ(result2.getValueType(), Aurora::Normal);
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for(size_t i=0; i<result1.getDataSize(); ++i)
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{
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EXPECT_EQ(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, log)
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{
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Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
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Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
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auto result1 = Aurora::log(hostMatrix);
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auto result2 = Aurora::log(deviceMatrix).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
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EXPECT_EQ(result2.getValueType(), result1.getValueType());
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_FLOAT_AE(result1[i], result2[i]);
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}
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result1 = Aurora::log(hostMatrix,3);
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result2 = Aurora::log(deviceMatrix,3).toHostMatrix();
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EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
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EXPECT_EQ(result2.getValueType(), result1.getValueType());
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for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
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{
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EXPECT_FLOAT_AE(result1[i], result2[i]);
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}
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}
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TEST_F(Function1D_Cuda_Test, compareSet)
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{
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Aurora::Matrix A =Aurora::Matrix::fromRawData(new float[9]{0},9,1);
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Aurora::Matrix B =Aurora::Matrix::fromRawData(new float[9]{0},9,1);
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for (int i = 0; i < 9; ++i) {
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A[i]=(float)(i-3);
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B[i]=(float)(i+2);
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}
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{
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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compareSet(dA,0,0,Aurora::LT);
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compareSet(A,0,0,Aurora::LT);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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{
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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auto A = dA.toHostMatrix();
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compareSet(dA,0,0,Aurora::GT);
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compareSet(A,0,0,Aurora::GT);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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{
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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auto A = dA.toHostMatrix();
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compareSet(dA,-1,0,Aurora::EQ);
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compareSet(A,-1,0,Aurora::EQ);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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{
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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auto A = dA.toHostMatrix();
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compareSet(dA,-1,0,Aurora::NE);
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compareSet(A,-1,0,Aurora::NE);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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{
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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auto A = dA.toHostMatrix();
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compareSet(dA,-1,0,Aurora::NL);
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compareSet(A,-1,0,Aurora::NL);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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{
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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auto A = dA.toHostMatrix();
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compareSet(dA,-1,0,Aurora::NG);
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compareSet(A,-1,0,Aurora::NG);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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//Function m m v v
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//NE
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{
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Aurora::CudaMatrix dB = B.toDeviceMatrix();
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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compareSet(dA,dB,4,-1,Aurora::NE);
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compareSet(A,B,4,-1,Aurora::NE);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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//EQ
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{
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Aurora::CudaMatrix dB = B.toDeviceMatrix();
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Aurora::CudaMatrix dA = A.toDeviceMatrix();
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compareSet(dA,dB,4,-1,Aurora::EQ);
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compareSet(A,B,4,-1,Aurora::EQ);
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for (size_t i = 0; i < 9; i++)
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{
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EXPECT_EQ(dA.getValue(i), A[i]);
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}
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}
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//GT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,1,-1,Aurora::GT);
|
|
compareSet(A,B,1,-1,Aurora::GT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,3,-1,Aurora::LT);
|
|
compareSet(A,B,3,-1,Aurora::LT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//NL
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,3,-1,Aurora::NL);
|
|
compareSet(A,B,3,-1,Aurora::NL);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,3,-1,Aurora::NG);
|
|
compareSet(A,B,3,-1,Aurora::NG);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//Function m m v
|
|
//NE
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,-1,Aurora::NE);
|
|
compareSet(A,B,-1,Aurora::NE);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//EQ
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,-1,Aurora::EQ);
|
|
compareSet(A,B,-1,Aurora::EQ);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//GT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,-1,Aurora::GT);
|
|
compareSet(A,B,-1,Aurora::GT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,-1,Aurora::LT);
|
|
compareSet(A,B,-1,Aurora::LT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//NL
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,-1,Aurora::NL);
|
|
compareSet(A,B,-1,Aurora::NL);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,-1,Aurora::NG);
|
|
compareSet(A,B,-1,Aurora::NG);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//Function m m v v
|
|
//NE
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,4,-1,Aurora::NE);
|
|
compareSet(A,B,4,-1,Aurora::NE);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//EQ
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,4,-1,Aurora::EQ);
|
|
compareSet(A,B,4,-1,Aurora::EQ);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//GT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,1,-1,Aurora::GT);
|
|
compareSet(A,B,1,-1,Aurora::GT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,3,-1,Aurora::LT);
|
|
compareSet(A,B,3,-1,Aurora::LT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//NL
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,3,-1,Aurora::NL);
|
|
compareSet(A,B,3,-1,Aurora::NL);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,dB,3,-1,Aurora::NG);
|
|
compareSet(A,B,3,-1,Aurora::NG);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//Function m v m
|
|
//NE
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,-1,dB,Aurora::NE);
|
|
compareSet(A,-1,B,Aurora::NE);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//EQ
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,-1,dB,Aurora::EQ);
|
|
compareSet(A,-1,B,Aurora::EQ);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//GT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,-1,dB,Aurora::GT);
|
|
compareSet(A,-1,B,Aurora::GT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,-1,dB,Aurora::LT);
|
|
compareSet(A,-1,B,Aurora::LT);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//NL
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,-1,dB,Aurora::NL);
|
|
compareSet(A,-1,B,Aurora::NL);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
//LT
|
|
{
|
|
Aurora::CudaMatrix dB = B.toDeviceMatrix();
|
|
Aurora::CudaMatrix dA = A.toDeviceMatrix();
|
|
compareSet(dA,-1,dB,Aurora::NG);
|
|
compareSet(A,-1,B,Aurora::NG);
|
|
for (size_t i = 0; i < 9; i++)
|
|
{
|
|
EXPECT_EQ(dA.getValue(i), A[i]);
|
|
}
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, exp)
|
|
{
|
|
Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
|
|
Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
|
|
auto result1 = Aurora::exp(hostMatrix);
|
|
auto result2 = Aurora::exp(deviceMatrix).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
|
|
hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9.9,10,11,12}, 3, 2, 1,Aurora::Complex);
|
|
deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
result1 = Aurora::exp(hostMatrix);
|
|
result2 = Aurora::exp(deviceMatrix).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, mod)
|
|
{
|
|
Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8}, 2,4);
|
|
Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
|
|
auto result1 = Aurora::mod(hostMatrix, 2);
|
|
auto result2 = Aurora::mod(deviceMatrix, 2).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
|
|
result1 = Aurora::mod(hostMatrix, 3);
|
|
result2 = Aurora::mod(deviceMatrix, 3).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, acos)
|
|
{
|
|
Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8}, 2,4);
|
|
Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
|
|
auto result1 = Aurora::acos(hostMatrix);
|
|
auto result2 = Aurora::acos(deviceMatrix).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, acosd)
|
|
{
|
|
Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8}, 2,4);
|
|
Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
|
|
auto result1 = Aurora::acosd(hostMatrix);
|
|
auto result2 = Aurora::acosd(deviceMatrix).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, conj)
|
|
{
|
|
Aurora::Matrix hostMatrix = Aurora::Matrix::fromRawData(new float[8]{0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8}, 2,4);
|
|
Aurora::CudaMatrix deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
|
|
auto result1 = Aurora::conj(hostMatrix);
|
|
auto result2 = Aurora::conj(deviceMatrix).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
|
|
hostMatrix = Aurora::Matrix::fromRawData(new float[12]{1.1,2.2,3.3,4.4,5.5,6.6,7.7,8.8,9.9,10,11,12}, 3, 2, 1,Aurora::Complex);
|
|
deviceMatrix = hostMatrix.toDeviceMatrix();
|
|
result1 = Aurora::conj(hostMatrix);
|
|
result2 = Aurora::conj(deviceMatrix).toHostMatrix();
|
|
EXPECT_EQ(result2.getDataSize(), result1.getDataSize());
|
|
EXPECT_EQ(result2.getValueType(), result1.getValueType());
|
|
for(size_t i=0; i<result1.getDataSize() * result1.getValueType(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, norm) {
|
|
//1Dim
|
|
float *data = new float[3]{1,2,-3};
|
|
auto matrix = Aurora::Matrix::fromRawData(data, 3);
|
|
auto deviceMatrix = matrix.toDeviceMatrix();
|
|
auto result = Aurora::norm(matrix.toDeviceMatrix(), Aurora::NormMethod::Norm1);
|
|
EXPECT_FLOAT_AE(result,6);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm2);
|
|
EXPECT_FLOAT_AE(result,3.74166);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
|
|
EXPECT_FLOAT_AE(result,3.74166);
|
|
|
|
//2Dims
|
|
data = new float[8]{1,2,-3,6,7,9,22.3,-8.6};
|
|
matrix = Aurora::Matrix::fromRawData(data, 4,2);
|
|
deviceMatrix = matrix.toDeviceMatrix();
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm1);
|
|
EXPECT_FLOAT_AE(result,46.9);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm2);
|
|
EXPECT_FLOAT_AE(result,26.7284);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
|
|
EXPECT_FLOAT_AE(result,27.4089);
|
|
|
|
//1Dim Complex
|
|
data = new float[6]{1,2,-3,4,5,-6};
|
|
matrix = Aurora::Matrix::fromRawData(data, 3,1,1,Aurora::Complex);
|
|
deviceMatrix = matrix.toDeviceMatrix();
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm1);
|
|
EXPECT_FLOAT_AE(result,15.0463);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm2);
|
|
EXPECT_FLOAT_AE(result,9.5394);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
|
|
EXPECT_FLOAT_AE(result,9.5394);
|
|
|
|
//2Dims Complex
|
|
data = new float[12]{1,2,-3,4,5,-6,7,8,9,22,24,25};
|
|
matrix = Aurora::Matrix::fromRawData(data, 3,2,1,Aurora::Complex);
|
|
deviceMatrix = matrix.toDeviceMatrix();
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::Norm1);
|
|
EXPECT_FLOAT_AE(result,69.0553);
|
|
//not support
|
|
//result = Aurora::norm(matrix,Aurora::NormMethod::Norm2);
|
|
//EXPECT_FLOAT_AE(result,43.5314);
|
|
result = Aurora::norm(deviceMatrix,Aurora::NormMethod::NormF);
|
|
EXPECT_FLOAT_AE(result,44.3847);
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, transpose) {
|
|
float *data = new float[6]{1,2,3,4,5,6};
|
|
auto matrix = Aurora::Matrix::fromRawData(data, 3,2).toDeviceMatrix();
|
|
auto result = Aurora::transpose(matrix).toHostMatrix();
|
|
|
|
EXPECT_FLOAT_EQ(result.getData()[0],1);
|
|
EXPECT_FLOAT_EQ(result.getData()[1],4);
|
|
EXPECT_FLOAT_EQ(result.getData()[2],2);
|
|
EXPECT_FLOAT_EQ(result.getData()[3],5);
|
|
EXPECT_FLOAT_EQ(result.getData()[4],3);
|
|
EXPECT_FLOAT_EQ(result.getData()[5],6);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),2);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),3);
|
|
|
|
data = new float[12]{1,2,3,4,5,6,7,8,9,10,11,12};
|
|
matrix = Aurora::Matrix::fromRawData(data, 3,2,1,Aurora::Complex).toDeviceMatrix();
|
|
result = Aurora::transpose(matrix).toHostMatrix();
|
|
EXPECT_FLOAT_EQ(result.getData()[0],1);
|
|
EXPECT_FLOAT_EQ(result.getData()[1],2);
|
|
EXPECT_FLOAT_EQ(result.getData()[2],7);
|
|
EXPECT_FLOAT_EQ(result.getData()[3],8);
|
|
EXPECT_FLOAT_EQ(result.getData()[4],3);
|
|
EXPECT_FLOAT_EQ(result.getData()[5],4);
|
|
EXPECT_FLOAT_EQ(result.getData()[6],9);
|
|
EXPECT_FLOAT_EQ(result.getData()[7],10);
|
|
EXPECT_FLOAT_EQ(result.getData()[8],5);
|
|
EXPECT_FLOAT_EQ(result.getData()[9],6);
|
|
EXPECT_FLOAT_EQ(result.getData()[10],11);
|
|
EXPECT_FLOAT_EQ(result.getData()[11],12);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),2);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),3);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),2);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),3);
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, horzcat) {
|
|
float *data1 = new float[6]{1,2,3,4,5,6};
|
|
auto matrix1 = Aurora::Matrix::fromRawData(data1, 3,2).toDeviceMatrix();
|
|
float *data2 = new float[9]{7,8,9,10,11,12,13,14,15};
|
|
auto matrix2 = Aurora::Matrix::fromRawData(data2, 3,3).toDeviceMatrix();
|
|
auto result = Aurora::horzcat(matrix1,matrix2).toHostMatrix();
|
|
EXPECT_FLOAT_EQ(result.getData()[0],1);
|
|
EXPECT_FLOAT_EQ(result.getData()[1],2);
|
|
EXPECT_FLOAT_EQ(result.getData()[10],11);
|
|
EXPECT_FLOAT_EQ(result.getData()[14],15);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),3);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),5);
|
|
|
|
data1 = new float[6]{1,2,3,4,5,6};
|
|
matrix1 = Aurora::Matrix::fromRawData(data1, 3,1,1,Aurora::Complex).toDeviceMatrix();
|
|
data2 = new float[6]{7,8,9,10,11,12};
|
|
matrix2 = Aurora::Matrix::fromRawData(data2, 3,1,1,Aurora::Complex).toDeviceMatrix();
|
|
result = Aurora::horzcat(matrix1,matrix2).toHostMatrix();
|
|
EXPECT_FLOAT_EQ(result.getData()[0],1);
|
|
EXPECT_FLOAT_EQ(result.getData()[1],2);
|
|
EXPECT_FLOAT_EQ(result.getData()[8],9);
|
|
EXPECT_FLOAT_EQ(result.getData()[9],10);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),3);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),2);
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, vertcat) {
|
|
float *data1 = new float[6]{1,2,3,4,5,6};
|
|
auto matrix1 = Aurora::Matrix::fromRawData(data1, 2,3).toDeviceMatrix();
|
|
float *data2 = new float[9]{7,8,9,10,11,12,13,14,15};
|
|
auto matrix2 = Aurora::Matrix::fromRawData(data2, 3,3).toDeviceMatrix();
|
|
auto result = Aurora::vertcat(matrix1,matrix2).toHostMatrix();
|
|
EXPECT_FLOAT_EQ(result.getData()[0],1);
|
|
EXPECT_FLOAT_EQ(result.getData()[1],2);
|
|
EXPECT_FLOAT_EQ(result.getData()[10],5);
|
|
EXPECT_FLOAT_EQ(result.getData()[14],15);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),5);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),3);
|
|
|
|
data1 = new float[6]{1,2,3,4,5,6};
|
|
matrix1 = Aurora::Matrix::fromRawData(data1, 3,1,1,Aurora::Complex).toDeviceMatrix();
|
|
data2 = new float[6]{7,8,9,10,11,12};
|
|
matrix2 = Aurora::Matrix::fromRawData(data2, 3,1,1,Aurora::Complex).toDeviceMatrix();
|
|
result = Aurora::vertcat(matrix1,matrix2).toHostMatrix();
|
|
EXPECT_FLOAT_EQ(result.getData()[0],1);
|
|
EXPECT_FLOAT_EQ(result.getData()[1],2);
|
|
EXPECT_FLOAT_EQ(result.getData()[8],9);
|
|
EXPECT_FLOAT_EQ(result.getData()[9],10);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(0),6);
|
|
EXPECT_FLOAT_EQ(result.getDimSize(1),1);
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, vecnorm) {
|
|
//1Dim
|
|
float *data = new float[3]{1,2,-3};
|
|
auto matrix = Aurora::Matrix::fromRawData(data, 3).toDeviceMatrix();
|
|
auto result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],6);
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],3.74166);
|
|
|
|
//2Dims
|
|
data = new float[8]{1,2,-3,6,7,9,22.3,-8.6};
|
|
matrix = Aurora::Matrix::fromRawData(data, 4,2).toDeviceMatrix();
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],12);
|
|
EXPECT_FLOAT_AE(result.getData()[1],46.9);
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],7.0711);
|
|
EXPECT_FLOAT_AE(result.getData()[1],26.4811);
|
|
|
|
//1Dim Complex
|
|
data = new float[6]{1,2,-3,4,5,-6};
|
|
matrix = Aurora::Matrix::fromRawData(data, 3,1,1,Aurora::Complex).toDeviceMatrix();
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],15.0463);
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],9.5394);
|
|
|
|
//2Dims Complex
|
|
data = new float[12]{1,2,-3,4,5,-6,7,8,9,22,24,25};
|
|
matrix = Aurora::Matrix::fromRawData(data, 3,2,1,Aurora::Complex).toDeviceMatrix();
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm1,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],15.0463);
|
|
EXPECT_FLOAT_AE(result.getData()[1],69.0553);
|
|
result = Aurora::vecnorm(matrix,Aurora::NormMethod::Norm2,1).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result.getData()[0],9.5394);
|
|
EXPECT_FLOAT_AE(result.getData()[1],43.3474);
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, linspace) {
|
|
auto result1 = Aurora::linspace(-5,5,7);
|
|
auto result2 = Aurora::linspaceCuda(-5,5,7).toHostMatrix();
|
|
EXPECT_FLOAT_EQ(result1.getDataSize(), result2.getDataSize());
|
|
for(int i=0; i<result1.getDataSize(); ++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|
|
|
|
TEST_F(Function1D_Cuda_Test, auroraUnion) {
|
|
float* data1 = new float[9]{3,3,2,2,2,1,4,4,7};
|
|
auto matrix1 = Aurora::Matrix::fromRawData(data1, 9,1,1);
|
|
float* data2 = new float[8]{6,6,7,7,8,1,2};
|
|
auto matrix2 = Aurora::Matrix::fromRawData(data2, 7,1,1);
|
|
|
|
auto result1 = Aurora::auroraUnion(matrix1, matrix2);
|
|
auto result2 = Aurora::auroraUnion(matrix1.toDeviceMatrix(), matrix2.toDeviceMatrix()).toHostMatrix();
|
|
EXPECT_FLOAT_AE(result1.getDataSize(), result2.getDataSize());
|
|
for(int i=0;i<result1.getDataSize();++i)
|
|
{
|
|
EXPECT_FLOAT_AE(result1[i], result2[i]);
|
|
}
|
|
}
|