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https://github.com/PaddlePaddle/FastDeploy.git
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* add GPL lisence * add GPL-3.0 lisence * add GPL-3.0 lisence * add GPL-3.0 lisence * support yolov8 * add pybind for yolov8 * add yolov8 readme * add cpp benchmark * add cpu and gpu mem * public part split * add runtime mode * fixed bugs * add cpu_thread_nums * deal with comments * deal with comments * deal with comments * rm useless code * add FASTDEPLOY_DECL * add FASTDEPLOY_DECL * fixed for windows * mv rss to pss * mv rss to pss * Update utils.cc * use thread to collect mem * Add ResourceUsageMonitor * rm useless code * fixed bug * fixed typo * update ResourceUsageMonitor * fixed bug * fixed bug * add note for ResourceUsageMonitor * deal with comments * add macros * deal with comments * deal with comments * deal with comments * re-lint * rm pmap and use mem api * rm pmap and use mem api * add mem api * Add PrintBenchmarkInfo func * Add PrintBenchmarkInfo func * Add PrintBenchmarkInfo func * deal with comments * fixed enable_paddle_to_trt * add log for paddle_trt * support ppcls benchmark * use new trt option api * update benchmark info * simplify benchmark.cc * simplify benchmark.cc * deal with comments * Add ppseg && ppocr benchmark * add OCR rec img * add ocr benchmark * fixed trt shape * add trt shape * resolve conflict * add ENABLE_BENCHMARK define * Add ClassifyDiff * Add Resize for ClassifyResult * deal with comments * add convert info script * resolve conflict * Add SaveBenchmarkResult func * fixed bug * fixed bug * fixed bug --------- Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
180 lines
6.2 KiB
C++
Executable File
180 lines
6.2 KiB
C++
Executable File
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <memory>
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#include <thread> // NOLINT
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#include "fastdeploy/utils/utils.h"
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#include "fastdeploy/core/fd_tensor.h"
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#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
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#include "fastdeploy/vision/common/result.h"
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#endif
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namespace fastdeploy {
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namespace benchmark {
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#if defined(ENABLE_BENCHMARK)
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/*! @brief ResourceUsageMonitor object used when to collect memory info.
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*/
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class FASTDEPLOY_DECL ResourceUsageMonitor {
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public:
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/** \brief Set sampling_interval_ms and gpu_id for ResourceUsageMonitor.
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*
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* \param[in] sampling_interval_ms How often to collect memory info(ms).
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* \param[in] gpu_id Device(gpu) id, default 0.
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*/
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explicit ResourceUsageMonitor(int sampling_interval_ms, int gpu_id = 0);
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~ResourceUsageMonitor() { StopInternal(); }
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/// Start memory info collect
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void Start();
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/// Stop memory info collect
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void Stop();
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/// Get maximum cpu memory usage
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float GetMaxCpuMem() const {
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if (!is_supported_ || check_memory_thd_ == nullptr) {
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return -1.0f;
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}
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return max_cpu_mem_;
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}
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/// Get maximum gpu memory usage
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float GetMaxGpuMem() const {
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if (!is_supported_ || check_memory_thd_ == nullptr) {
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return -1.0f;
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}
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return max_gpu_mem_;
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}
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/// Get maximum gpu util
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float GetMaxGpuUtil() const {
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if (!is_supported_ || check_memory_thd_ == nullptr) {
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return -1.0f;
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}
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return max_gpu_util_;
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}
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ResourceUsageMonitor(ResourceUsageMonitor&) = delete;
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ResourceUsageMonitor& operator=(const ResourceUsageMonitor&) = delete;
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ResourceUsageMonitor(ResourceUsageMonitor&&) = delete;
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ResourceUsageMonitor& operator=(const ResourceUsageMonitor&&) = delete;
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private:
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void StopInternal();
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// Get current gpu memory info
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std::string GetCurrentGpuMemoryInfo(int device_id);
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bool is_supported_ = false;
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bool stop_signal_ = false;
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const int sampling_interval_;
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float max_cpu_mem_ = 0.0f; // MB
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float max_gpu_mem_ = 0.0f; // MB
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float max_gpu_util_ = 0.0f;
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const int gpu_id_ = 0;
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std::unique_ptr<std::thread> check_memory_thd_ = nullptr;
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};
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// Remove the ch characters at both ends of str
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FASTDEPLOY_DECL std::string Strip(const std::string& str, char ch = ' ');
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// Split string
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FASTDEPLOY_DECL void Split(const std::string& s,
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std::vector<std::string>& tokens,
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char delim = ' ');
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/// Diff values for precision evaluation
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struct FASTDEPLOY_DECL BaseDiff {};
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struct FASTDEPLOY_DECL EvalStatis {
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double mean = -1.0;
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double min = -1.0;
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double max = -1.0;
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};
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struct FASTDEPLOY_DECL TensorDiff: public BaseDiff {
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EvalStatis data;
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};
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#if defined(ENABLE_VISION)
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struct FASTDEPLOY_DECL DetectionDiff: public BaseDiff {
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EvalStatis boxes;
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EvalStatis scores;
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EvalStatis labels;
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};
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struct FASTDEPLOY_DECL ClassifyDiff: public BaseDiff {
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EvalStatis scores;
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EvalStatis labels;
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};
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struct FASTDEPLOY_DECL SegmentationDiff: public BaseDiff {
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EvalStatis scores;
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EvalStatis labels;
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};
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struct FASTDEPLOY_DECL OCRDetDiff: public BaseDiff {
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EvalStatis boxes;
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};
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#endif // ENABLE_VISION
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#endif // ENABLE_BENCHMARK
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/// Utils for precision evaluation
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struct FASTDEPLOY_DECL ResultManager {
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#if defined(ENABLE_BENCHMARK)
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/// Save & Load functions for FDTensor result.
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static bool SaveFDTensor(const FDTensor& tensor, const std::string& path);
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static bool LoadFDTensor(FDTensor* tensor, const std::string& path);
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/// Calculate diff value between two FDTensor results.
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static TensorDiff CalculateDiffStatis(const FDTensor& lhs,
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const FDTensor& rhs);
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/// Save Benchmark data
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static void SaveBenchmarkResult(const std::string& res,
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const std::string& path);
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#if defined(ENABLE_VISION)
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/// Save & Load functions for basic results.
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static bool SaveDetectionResult(const vision::DetectionResult& res,
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const std::string& path);
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static bool LoadDetectionResult(vision::DetectionResult* res,
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const std::string& path);
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static bool SaveClassifyResult(const vision::ClassifyResult& res,
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const std::string& path);
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static bool LoadClassifyResult(vision::ClassifyResult* res,
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const std::string& path);
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static bool SaveSegmentationResult(const vision::SegmentationResult& res,
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const std::string& path);
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static bool LoadSegmentationResult(vision::SegmentationResult* res,
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const std::string& path);
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static bool SaveOCRDetResult(const std::vector<std::array<int, 8>>& res,
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const std::string& path);
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static bool LoadOCRDetResult(std::vector<std::array<int, 8>>* res,
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const std::string& path);
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/// Calculate diff value between two basic results.
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static DetectionDiff CalculateDiffStatis(const vision::DetectionResult& lhs,
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const vision::DetectionResult& rhs,
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const float& score_threshold = 0.3f);
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static ClassifyDiff CalculateDiffStatis(const vision::ClassifyResult& lhs,
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const vision::ClassifyResult& rhs);
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static SegmentationDiff CalculateDiffStatis(
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const vision::SegmentationResult& lhs,
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const vision::SegmentationResult& rhs);
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static OCRDetDiff CalculateDiffStatis(
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const std::vector<std::array<int, 8>>& lhs,
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const std::vector<std::array<int, 8>>& rhs);
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#endif // ENABLE_VISION
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#endif // ENABLE_BENCHMARK
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};
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} // namespace benchmark
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} // namespace fastdeploy
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