mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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c487359e33
* 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
93 lines
2.7 KiB
C++
Executable File
93 lines
2.7 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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#include "fastdeploy/benchmark/utils.h"
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namespace fastdeploy {
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namespace benchmark {
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void DumpCurrentCpuMemoryUsage(const std::string& name) {
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int iPid = static_cast<int>(getpid());
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std::string command = "pmap -x " + std::to_string(iPid) + " | grep total";
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FILE* pp = popen(command.data(), "r");
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if (!pp) return;
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char tmp[1024];
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while (fgets(tmp, sizeof(tmp), pp) != NULL) {
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std::ofstream write;
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write.open(name, std::ios::app);
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write << tmp;
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write.close();
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}
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pclose(pp);
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return;
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}
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void DumpCurrentGpuMemoryUsage(const std::string& name, int device_id) {
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std::string command = "nvidia-smi --id=" + std::to_string(device_id) +
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" --query-gpu=index,uuid,name,timestamp,memory.total,"
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"memory.free,memory.used,utilization.gpu,utilization."
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"memory --format=csv,noheader,nounits";
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FILE* pp = popen(command.data(), "r");
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if (!pp) return;
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char tmp[1024];
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while (fgets(tmp, sizeof(tmp), pp) != NULL) {
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std::ofstream write;
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write.open(name, std::ios::app);
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write << tmp;
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write.close();
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}
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pclose(pp);
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return;
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}
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float GetCpuMemoryUsage(const std::string& name) {
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std::ifstream read(name);
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std::string line;
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float max_cpu_mem = -1;
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while (getline(read, line)) {
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std::stringstream ss(line);
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std::string tmp;
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std::vector<std::string> nums;
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while (getline(ss, tmp, ' ')) {
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tmp = strip(tmp);
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if (tmp.empty()) continue;
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nums.push_back(tmp);
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}
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max_cpu_mem = std::max(max_cpu_mem, stof(nums[3]));
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}
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return max_cpu_mem / 1024;
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}
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float GetGpuMemoryUsage(const std::string& name) {
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std::ifstream read(name);
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std::string line;
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float max_gpu_mem = -1;
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while (getline(read, line)) {
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std::stringstream ss(line);
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std::string tmp;
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std::vector<std::string> nums;
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while (getline(ss, tmp, ',')) {
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tmp = strip(tmp);
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if (tmp.empty()) continue;
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nums.push_back(tmp);
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}
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max_gpu_mem = std::max(max_gpu_mem, stof(nums[6]));
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}
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return max_gpu_mem;
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}
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} // namespace benchmark
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} // namespace fastdeploy
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