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190 lines
4.7 KiB
C++
190 lines
4.7 KiB
C++
#ifndef OPENCV_CUDA_SAMPLE_PERFORMANCE_H_
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#define OPENCV_CUDA_SAMPLE_PERFORMANCE_H_
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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 <string>
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#include <opencv2/core/utility.hpp>
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#include "opencv2/cuda.hpp"
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#define TAB " "
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class Runnable
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{
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public:
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explicit Runnable(const std::string& nameStr): name_(nameStr) {}
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virtual ~Runnable() {}
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const std::string& name() const { return name_; }
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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) { working_dir_ = val; }
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const std::string& workingDir() const { return working_dir_; }
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void setTestFilter(const std::string& val) { test_filter_ = val; }
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const std::string& testFilter() const { return test_filter_; }
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void setNumIters(int num_iters) { num_iters_ = num_iters; }
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void addInit(Runnable* init) { inits_.push_back(init); }
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void addTest(Runnable* test) { tests_.push_back(test); }
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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 { return cur_iter_idx_ >= num_iters_; }
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void cpuOn() { cpu_started_ = cv::getTickCount(); }
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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() { gpu_started_ = cv::getTickCount(); }
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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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bool isListMode() const { return is_list_mode_; }
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void setListMode(bool value) { is_list_mode_ = value; }
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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), speedup_total_(0.0),
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num_subtests_called_(0), is_list_mode_(false),
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num_iters_(10), cur_iter_idx_(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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}
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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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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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cpu_times_.clear();
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gpu_times_.clear();
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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(double cpu_time, double gpu_time, double speedup);
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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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double cpu_elapsed_;
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double gpu_elapsed_;
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double speedup_total_;
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int num_subtests_called_;
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bool is_list_mode_;
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int num_iters_;
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int cur_iter_idx_;
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std::vector<int64> cpu_times_;
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std::vector<int64> gpu_times_;
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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 TEST(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().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 CUDA_ON \
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while (!TestSystem::instance().stop()) { \
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TestSystem::instance().gpuOn()
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#define CUDA_OFF \
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TestSystem::instance().gpuOff(); \
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} TestSystem::instance().gpuComplete()
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// Generates a matrix
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void gen(cv::Mat& mat, int rows, int cols, int type, cv::Scalar low,
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cv::Scalar high);
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// Returns abs path taking into account test system working dir
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std::string abspath(const std::string& relpath);
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#endif // OPENCV_CUDA_SAMPLE_PERFORMANCE_H_
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