616 lines
20 KiB
C++
616 lines
20 KiB
C++
#include <gtest/gtest.h>
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#include <chrono>
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#include "AuroraDefs.h"
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#include "CudaMatrix.h"
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#include "Function.h"
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#include "Matrix.h"
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#include "TestUtility.h"
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#include "Function2D.h"
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#include "Function2D.cuh"
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class Function2D_Cuda_Test:public ::testing::Test
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{
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protected:
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static void SetUpFunction2DCudaTester(){
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}
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static void TearDownTestCase(){
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}
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public:
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Aurora::Matrix B;
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Aurora::CudaMatrix dB;
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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(Function2D_Cuda_Test, min)
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{
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// big data for test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
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{
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float *dataB = Aurora::random(4096*41472);
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B = Aurora::Matrix::fromRawData(dataB, 4096, 41472);
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::min(B, Aurora::FunctionDirection::Column,r,c);
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auto ret2 = Aurora::min(dB, Aurora::FunctionDirection::Column,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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ret1 = Aurora::min(B, Aurora::FunctionDirection::Row,r,c);
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ret2 = Aurora::min(dB, Aurora::FunctionDirection::Row,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// different size speed
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// Aurora::Matrix Aurora::min(const Aurora::Matrix &aMatrix,
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// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
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// in col wise
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{
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float *dataB = Aurora::random(3157*111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::min(B, Aurora::FunctionDirection::Column,r,c);
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auto ret2 = Aurora::min(dB, Aurora::FunctionDirection::Column,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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B.forceReshape( 111,3157, 1);
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dB = B.toDeviceMatrix();
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ret1 = Aurora::min(B, Aurora::FunctionDirection::Column,r,c);
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ret2 = Aurora::min(dB, Aurora::FunctionDirection::Column,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix, float aValue)
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{
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float *dataB = Aurora::random(3157*111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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dB = B.toDeviceMatrix();
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long r,c;
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auto start_time_ = std::chrono::high_resolution_clock::now();
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auto ret1 = Aurora::min(B, 500.5f);
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auto ret2 = Aurora::min(dB, 500.5f);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// const Aurora::Matrix &aOther)
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// with same size matrix
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{
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float *dataB = Aurora::random(3157*111);
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float *dataA = Aurora::random(3157*111);
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auto A = Aurora::Matrix::fromRawData(dataA, 3157, 111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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auto dA = A.toDeviceMatrix();
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::min(B, A);
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auto ret2 = Aurora::min(dB, dA);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// const Aurora::Matrix &aOther)
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// with col-vec and matrix
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{
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float *dataB = Aurora::random(3157*111);
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float *dataA = Aurora::random(3157);
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auto A = Aurora::Matrix::fromRawData(dataA, 3157, 1);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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auto dA = A.toDeviceMatrix();
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::min(B, A);
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auto ret2 = Aurora::min(dB, dA);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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ret2 = Aurora::min(dA, dB);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// const Aurora::Matrix &aOther)
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// with row-vec and matrix
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{
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float *dataB = Aurora::random(3157*111);
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float *dataA = Aurora::random(111);
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auto A = Aurora::Matrix::fromRawData(dataA, 1, 111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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auto dA = A.toDeviceMatrix();
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dB = B.toDeviceMatrix();
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long r,c;
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auto start_time_ = std::chrono::high_resolution_clock::now();
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auto ret1 = Aurora::min(B, A);
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auto ret2 = Aurora::min(dB, dA);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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}
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TEST_F(Function2D_Cuda_Test, max)
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{
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// big data for test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
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{
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float *dataB = Aurora::random(4096*41472);
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B = Aurora::Matrix::fromRawData(dataB, 4096, 41472);
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::max(B, Aurora::FunctionDirection::Column,r,c);
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auto ret2 = Aurora::max(dB, Aurora::FunctionDirection::Column,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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ret1 = Aurora::max(B, Aurora::FunctionDirection::Row,r,c);
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ret2 = Aurora::max(dB, Aurora::FunctionDirection::Row,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// different size speed
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// Aurora::FunctionDirection direction, long &rowIdx, long &colIdx)
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// in col wise
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{
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float *dataB = Aurora::random(3157*111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::max(B, Aurora::FunctionDirection::Column,r,c);
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auto ret2 = Aurora::max(dB, Aurora::FunctionDirection::Column,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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B.forceReshape( 111,3157, 1);
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dB = B.toDeviceMatrix();
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ret1 = Aurora::max(B, Aurora::FunctionDirection::Column,r,c);
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ret2 = Aurora::max(dB, Aurora::FunctionDirection::Column,r,c);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix, float aValue)
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{
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float *dataB = Aurora::random(3157*111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::max(B, 500.5f);
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auto ret2 = Aurora::max(dB, 500.5f);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// const Aurora::Matrix &aOther)
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// with same size matrix
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{
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float *dataB = Aurora::random(3157*111);
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float *dataA = Aurora::random(3157*111);
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auto A = Aurora::Matrix::fromRawData(dataA, 3157, 111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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auto dA = A.toDeviceMatrix();
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dB = B.toDeviceMatrix();
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long r,c;
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auto start_time_ = std::chrono::high_resolution_clock::now();
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auto ret1 = Aurora::max(B, A);
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auto ret2 = Aurora::max(dB, dA);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// const Aurora::Matrix &aOther)
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// with col-vec and matrix
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{
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float *dataB = Aurora::random(3157*111);
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float *dataA = Aurora::random(3157);
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auto A = Aurora::Matrix::fromRawData(dataA, 3157, 1);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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auto dA = A.toDeviceMatrix();
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dB = B.toDeviceMatrix();
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long r,c;
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auto ret1 = Aurora::max(B, A);
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// mat x vec
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auto ret2 = Aurora::max(dB, dA);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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// vec x mat
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ret2 = Aurora::max(dA, dB);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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// test
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// Aurora::Matrix Aurora::max(const Aurora::Matrix &aMatrix,
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// const Aurora::Matrix &aOther)
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// with row-vec and matrix
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{
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float *dataB = Aurora::random(3157*111);
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float *dataA = Aurora::random(111);
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auto A = Aurora::Matrix::fromRawData(dataA, 1, 111);
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B = Aurora::Matrix::fromRawData(dataB, 3157, 111);
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auto dA = A.toDeviceMatrix();
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dB = B.toDeviceMatrix();
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long r,c;
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auto start_time_ = std::chrono::high_resolution_clock::now();
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auto ret1 = Aurora::max(B, A);
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// mat x vec
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auto ret2 = Aurora::max(dB, dA);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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//vec x mat
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ret2 = Aurora::max(dA, dB);
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ASSERT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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ASSERT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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ASSERT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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ASSERT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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}
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}
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TEST_F(Function2D_Cuda_Test, sum)
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{
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//
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{
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float *dataB = Aurora::random(4096*50000);
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// float* dataB = new float[4096*50000];
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// for (size_t i = 0; i < 4096*50000; i++)
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// {
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// dataB[i] = (float)(i/4096);
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// }
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B = Aurora::Matrix::fromRawData(dataB, 4096, 50000);
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// B = Aurora::Matrix::fromRawData(dataB, 200, 200);
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auto dD = B.toDeviceMatrix();
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auto ret1 = Aurora::sum(B, Aurora::FunctionDirection::All);
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auto ret2 = Aurora::sum(dD, Aurora::FunctionDirection::All);
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EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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EXPECT_EQ(ret1.getDimSize(2),ret2.getDimSize(2));
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for (size_t i = 0; i < ret1.getDataSize(); i++)
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{
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EXPECT_FLOAT_EQ(ret1[i], ret2.getValue(i))<<", index at :"<<i;
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}
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ret1 = Aurora::sum(B, Aurora::FunctionDirection::Column);
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ret2 = Aurora::sum(dD, Aurora::FunctionDirection::Column);
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EXPECT_EQ(ret1.getDimSize(0),ret2.getDimSize(0));
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EXPECT_EQ(ret1.getDimSize(1),ret2.getDimSize(1));
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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;
|
|
}
|
|
|
|
}
|
|
} |