509 lines
13 KiB
C++
509 lines
13 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2010-2012, Multicoreware, Inc., all rights reserved.
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// Copyright (C) 2010-2012, Advanced Micro Devices, Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other oclMaterials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors as is and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#include <iomanip>
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#include <stdexcept>
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#include <string>
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#include <iostream>
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#include <cstdio>
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#include <vector>
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#include <numeric>
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#include "opencv2/core/core.hpp"
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#include "opencv2/imgproc/imgproc.hpp"
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#include "opencv2/highgui/highgui.hpp"
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#include "opencv2/calib3d/calib3d.hpp"
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#include "opencv2/video/video.hpp"
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#include "opencv2/objdetect/objdetect.hpp"
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#include "opencv2/features2d/features2d.hpp"
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#include "opencv2/ocl/ocl.hpp"
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#include "opencv2/ts/ts.hpp"
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#include "opencv2/ts/ts_perf.hpp"
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#include "opencv2/ts/ts_gtest.h"
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#define Min_Size 1000
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#define Max_Size 4000
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#define Multiple 2
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#define TAB " "
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using namespace std;
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using namespace cv;
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void gen(Mat &mat, int rows, int cols, int type, Scalar low, Scalar high);
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void gen(Mat &mat, int rows, int cols, int type, int low, int high, int n);
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string abspath(const string &relpath);
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int CV_CDECL cvErrorCallback(int, const char *, const char *, const char *, int, void *);
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typedef struct
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{
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short x;
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short y;
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} COOR;
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COOR do_meanShift(int x0, int y0, uchar *sptr, uchar *dptr, int sstep,
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cv::Size size, int sp, int sr, int maxIter, float eps, int *tab);
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void meanShiftProc_(const Mat &src_roi, Mat &dst_roi, Mat &dstCoor_roi,
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int sp, int sr, cv::TermCriteria crit);
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template<class T1, class T2>
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int ExpectedEQ(T1 expected, T2 actual)
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{
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if(expected == actual)
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return 1;
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return 0;
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}
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template<class T1>
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int EeceptDoubleEQ(T1 expected, T1 actual)
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{
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testing::internal::Double lhs(expected);
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testing::internal::Double rhs(actual);
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if (lhs.AlmostEquals(rhs))
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{
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return 1;
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}
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return 0;
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}
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template<class T>
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int AssertEQ(T expected, T actual)
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{
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if(expected == actual)
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{
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return 1;
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}
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return 0;
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}
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int ExceptDoubleNear(double val1, double val2, double abs_error);
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bool match_rect(cv::Rect r1, cv::Rect r2, int threshold);
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double checkNorm(const cv::Mat &m);
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double checkNorm(const cv::Mat &m1, const cv::Mat &m2);
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double checkSimilarity(const cv::Mat &m1, const cv::Mat &m2);
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int ExpectedMatNear(cv::Mat dst, cv::Mat cpu_dst, double eps);
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int ExceptedMatSimilar(cv::Mat dst, cv::Mat cpu_dst, double eps);
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class Runnable
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{
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public:
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explicit Runnable(const std::string &runname): name_(runname) {}
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virtual ~Runnable() {}
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const std::string &name() const
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{
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return name_;
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}
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virtual void run() = 0;
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private:
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std::string name_;
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};
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class TestSystem
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{
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public:
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static TestSystem &instance()
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{
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static TestSystem me;
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return me;
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}
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void setWorkingDir(const std::string &val)
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{
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working_dir_ = val;
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}
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const std::string &workingDir() const
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{
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return working_dir_;
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}
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void setTestFilter(const std::string &val)
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{
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test_filter_ = val;
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}
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const std::string &testFilter() const
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{
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return test_filter_;
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}
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void setNumIters(int num_iters)
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{
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num_iters_ = num_iters;
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}
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void setGPUWarmupIters(int num_iters)
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{
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gpu_warmup_iters_ = num_iters;
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}
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void setCPUIters(int num_iters)
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{
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cpu_num_iters_ = num_iters;
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}
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void setTopThreshold(double top)
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{
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top_ = top;
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}
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void setBottomThreshold(double bottom)
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{
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bottom_ = bottom;
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}
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void addInit(Runnable *init)
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{
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inits_.push_back(init);
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}
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void addTest(Runnable *test)
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{
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tests_.push_back(test);
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}
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void run();
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// It's public because OpenCV callback uses it
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void printError(const std::string &msg);
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std::stringstream &startNewSubtest()
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{
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finishCurrentSubtest();
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return cur_subtest_description_;
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}
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bool stop() const
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{
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return cur_iter_idx_ >= num_iters_;
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}
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bool cpu_stop() const
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{
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return cur_iter_idx_ >= cpu_num_iters_;
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}
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int get_cur_iter_idx()
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{
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return cur_iter_idx_;
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}
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int get_cpu_num_iters()
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{
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return cpu_num_iters_;
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}
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bool warmupStop()
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{
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return cur_warmup_idx_++ >= gpu_warmup_iters_;
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}
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void warmupComplete()
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{
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cur_warmup_idx_ = 0;
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}
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void cpuOn()
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{
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cpu_started_ = cv::getTickCount();
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}
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void cpuOff()
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{
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int64 delta = cv::getTickCount() - cpu_started_;
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cpu_times_.push_back(delta);
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++cur_iter_idx_;
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}
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void cpuComplete()
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{
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cpu_elapsed_ += meanTime(cpu_times_);
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cur_subtest_is_empty_ = false;
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cur_iter_idx_ = 0;
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}
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void gpuOn()
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{
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gpu_started_ = cv::getTickCount();
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}
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void gpuOff()
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{
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int64 delta = cv::getTickCount() - gpu_started_;
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gpu_times_.push_back(delta);
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++cur_iter_idx_;
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}
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void gpuComplete()
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{
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gpu_elapsed_ += meanTime(gpu_times_);
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cur_subtest_is_empty_ = false;
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cur_iter_idx_ = 0;
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}
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void gpufullOn()
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{
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gpu_full_started_ = cv::getTickCount();
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}
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void gpufullOff()
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{
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int64 delta = cv::getTickCount() - gpu_full_started_;
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gpu_full_times_.push_back(delta);
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++cur_iter_idx_;
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}
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void gpufullComplete()
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{
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gpu_full_elapsed_ += meanTime(gpu_full_times_);
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cur_subtest_is_empty_ = false;
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cur_iter_idx_ = 0;
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}
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bool isListMode() const
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{
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return is_list_mode_;
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}
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void setListMode(bool value)
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{
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is_list_mode_ = value;
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}
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void setRecordName(const std::string &name)
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{
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recordname_ = name;
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}
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void setCurrentTest(const std::string &name)
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{
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itname_ = name;
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itname_changed_ = true;
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}
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void setAccurate(int accurate, double diff)
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{
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is_accurate_ = accurate;
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accurate_diff_ = diff;
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}
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void ExpectMatsNear(vector<Mat>& dst, vector<Mat>& cpu_dst, vector<double>& eps)
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{
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assert(dst.size() == cpu_dst.size());
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assert(cpu_dst.size() == eps.size());
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is_accurate_ = 1;
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for(size_t i=0; i<dst.size(); i++)
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{
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double cur_diff = checkNorm(dst[i], cpu_dst[i]);
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accurate_diff_ = max(accurate_diff_, cur_diff);
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if(cur_diff > eps[i])
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is_accurate_ = 0;
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}
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}
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void ExpectedMatNear(cv::Mat& dst, cv::Mat& cpu_dst, double eps)
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{
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assert(dst.type() == cpu_dst.type());
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assert(dst.size() == cpu_dst.size());
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accurate_diff_ = checkNorm(dst, cpu_dst);
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if(accurate_diff_ <= eps)
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is_accurate_ = 1;
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else
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is_accurate_ = 0;
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}
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void ExceptedMatSimilar(cv::Mat& dst, cv::Mat& cpu_dst, double eps)
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{
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assert(dst.type() == cpu_dst.type());
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assert(dst.size() == cpu_dst.size());
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accurate_diff_ = checkSimilarity(cpu_dst, dst);
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if(accurate_diff_ <= eps)
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is_accurate_ = 1;
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else
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is_accurate_ = 0;
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}
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std::stringstream &getCurSubtestDescription()
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{
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return cur_subtest_description_;
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}
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private:
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TestSystem():
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cur_subtest_is_empty_(true), cpu_elapsed_(0),
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gpu_elapsed_(0), gpu_full_elapsed_(0), speedup_total_(0.0),
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num_subtests_called_(0),
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speedup_faster_count_(0), speedup_slower_count_(0), speedup_equal_count_(0),
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speedup_full_faster_count_(0), speedup_full_slower_count_(0), speedup_full_equal_count_(0), is_list_mode_(false),
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num_iters_(10), cpu_num_iters_(2),
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gpu_warmup_iters_(1), cur_iter_idx_(0), cur_warmup_idx_(0),
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record_(0), recordname_("performance"), itname_changed_(true),
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is_accurate_(-1), accurate_diff_(0.)
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{
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cpu_times_.reserve(num_iters_);
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gpu_times_.reserve(num_iters_);
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gpu_full_times_.reserve(num_iters_);
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}
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void finishCurrentSubtest();
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void resetCurrentSubtest()
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{
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cpu_elapsed_ = 0;
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gpu_elapsed_ = 0;
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gpu_full_elapsed_ = 0;
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cur_subtest_description_.str("");
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cur_subtest_is_empty_ = true;
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cur_iter_idx_ = 0;
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cur_warmup_idx_ = 0;
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cpu_times_.clear();
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gpu_times_.clear();
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gpu_full_times_.clear();
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is_accurate_ = -1;
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accurate_diff_ = 0.;
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}
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double meanTime(const std::vector<int64> &samples);
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void printHeading();
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void printSummary();
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void printMetrics(int is_accurate, double cpu_time, double gpu_time = 0.0f, double gpu_full_time = 0.0f, double speedup = 0.0f, double fullspeedup = 0.0f);
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void writeHeading();
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void writeSummary();
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void writeMetrics(double cpu_time, double gpu_time = 0.0f, double gpu_full_time = 0.0f,
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double speedup = 0.0f, double fullspeedup = 0.0f,
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double gpu_min = 0.0f, double gpu_max = 0.0f, double std_dev = 0.0f);
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std::string working_dir_;
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std::string test_filter_;
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std::vector<Runnable *> inits_;
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std::vector<Runnable *> tests_;
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std::stringstream cur_subtest_description_;
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bool cur_subtest_is_empty_;
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int64 cpu_started_;
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int64 gpu_started_;
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int64 gpu_full_started_;
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double cpu_elapsed_;
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double gpu_elapsed_;
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double gpu_full_elapsed_;
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double speedup_total_;
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double speedup_full_total_;
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int num_subtests_called_;
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int speedup_faster_count_;
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int speedup_slower_count_;
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int speedup_equal_count_;
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int speedup_full_faster_count_;
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int speedup_full_slower_count_;
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int speedup_full_equal_count_;
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bool is_list_mode_;
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double top_;
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double bottom_;
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int num_iters_;
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int cpu_num_iters_; //there's no need to set cpu running same times with gpu
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int gpu_warmup_iters_; //gpu warm up times, default is 1
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int cur_iter_idx_;
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int cur_warmup_idx_; //current gpu warm up times
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std::vector<int64> cpu_times_;
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std::vector<int64> gpu_times_;
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std::vector<int64> gpu_full_times_;
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FILE *record_;
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std::string recordname_;
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std::string itname_;
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bool itname_changed_;
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int is_accurate_;
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double accurate_diff_;
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};
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#define GLOBAL_INIT(name) \
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struct name##_init: Runnable { \
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name##_init(): Runnable(#name) { \
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TestSystem::instance().addInit(this); \
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} \
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void run(); \
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} name##_init_instance; \
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void name##_init::run()
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#define PERFTEST(name) \
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struct name##_test: Runnable { \
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name##_test(): Runnable(#name) { \
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TestSystem::instance().addTest(this); \
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} \
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void run(); \
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} name##_test_instance; \
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void name##_test::run()
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#define SUBTEST TestSystem::instance().startNewSubtest()
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#define CPU_ON \
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while (!TestSystem::instance().cpu_stop()) { \
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TestSystem::instance().cpuOn()
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#define CPU_OFF \
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TestSystem::instance().cpuOff(); \
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} TestSystem::instance().cpuComplete()
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#define GPU_ON \
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while (!TestSystem::instance().stop()) { \
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TestSystem::instance().gpuOn()
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#define GPU_OFF \
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ocl::finish();\
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TestSystem::instance().gpuOff(); \
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} TestSystem::instance().gpuComplete()
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#define GPU_FULL_ON \
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while (!TestSystem::instance().stop()) { \
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TestSystem::instance().gpufullOn()
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#define GPU_FULL_OFF \
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TestSystem::instance().gpufullOff(); \
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} TestSystem::instance().gpufullComplete()
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#define WARMUP_ON \
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while (!TestSystem::instance().warmupStop()) {
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#define WARMUP_OFF \
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ocl::finish();\
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} TestSystem::instance().warmupComplete()
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