mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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42817ddc18
* [Benchmark] Init benchmark precision api * [Benchmark] Init benchmark precision api * [Benchmark] Add benchmark precision api * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Calculate the statis of diff * [Benchmark] Add SplitDataLine utils * [Benchmark] Add LexSortByXY func * [Benchmark] Add LexSortByXY func * [Benchmark] Add LexSortDetectionResultByXY func * [Benchmark] Add LexSortDetectionResultByXY func * [Benchmark] Add tensor diff presicion test * [Benchmark] fixed conflicts * [Benchmark] fixed calc tensor diff * fixed build bugs * fixed ci bugs when WITH_TESTING=ON * [Docs] init cpp benchmark docs * [Doc] update cpp benchmark docs * [Doc] update cpp benchmark docs * [Doc] update cpp benchmark docs * [Doc] update cpp benchmark docs
104 lines
4.1 KiB
C++
Executable File
104 lines
4.1 KiB
C++
Executable File
// Copyright (c) 2023 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 "gflags/gflags.h"
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#include "fastdeploy/benchmark/utils.h"
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#ifdef WIN32
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static const char sep = '\\';
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#else
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static const char sep = '/';
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#endif
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DEFINE_string(model, "", "Directory of the inference model.");
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DEFINE_string(image, "", "Path of the image file.");
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DEFINE_string(device, "cpu",
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"Type of inference device, support 'cpu/gpu/xpu'.");
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DEFINE_int32(device_id, 0, "device(gpu/xpu/...) id.");
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DEFINE_int32(warmup, 200, "Number of warmup for profiling.");
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DEFINE_int32(repeat, 1000, "Number of repeats for profiling.");
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DEFINE_string(profile_mode, "runtime", "runtime or end2end.");
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DEFINE_string(backend, "default",
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"The inference runtime backend, support: ['default', 'ort', "
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"'paddle', 'ov', 'trt', 'paddle_trt', 'lite']");
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DEFINE_int32(cpu_thread_nums, 8, "Set numbers of cpu thread.");
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DEFINE_bool(
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include_h2d_d2h, false, "Whether run profiling with h2d and d2h.");
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DEFINE_bool(
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use_fp16, false,
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"Whether to use FP16 mode, only support 'trt', 'paddle_trt' "
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"and 'lite' backend");
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DEFINE_bool(
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collect_memory_info, false, "Whether to collect memory info");
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DEFINE_int32(sampling_interval, 50, "How often to collect memory info(ms).");
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// Only for ppocr
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DEFINE_string(det_model, "", "Path of Detection model of PPOCR.");
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DEFINE_string(cls_model, "", "Path of Classification model of PPOCR.");
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DEFINE_string(rec_model, "", "Path of Recognization model of PPOCR.");
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DEFINE_string(rec_label_file, "", "Path of Recognization label file of PPOCR.");
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DEFINE_string(image_rec, "", "Path of Recognization img file of PPOCR.");
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static void PrintUsage() {
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std::cout << "Usage: infer_demo --model model_path --image img_path --device "
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"[cpu|gpu|xpu] --backend "
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"[default|ort|paddle|ov|trt|paddle_trt|lite] "
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"--use_fp16 false"
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<< std::endl;
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std::cout << "Default value of device: cpu" << std::endl;
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std::cout << "Default value of backend: default" << std::endl;
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std::cout << "Default value of use_fp16: false" << std::endl;
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}
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static void PrintBenchmarkInfo() {
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#if defined(ENABLE_BENCHMARK) && defined(ENABLE_VISION)
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// Get model name
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std::vector<std::string> model_names;
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fastdeploy::benchmark::Split(FLAGS_model, model_names, sep);
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if (model_names.empty()) {
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std::cout << "Directory of the inference model is invalid!!!" << std::endl;
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return;
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}
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// Save benchmark info
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std::stringstream ss;
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ss.precision(3);
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ss << "\n======= Model Info =======\n";
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ss << "model_name: " << model_names[model_names.size() - 1] << std::endl;
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ss << "profile_mode: " << FLAGS_profile_mode << std::endl;
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if (FLAGS_profile_mode == "runtime") {
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ss << "include_h2d_d2h: " << FLAGS_include_h2d_d2h << std::endl;
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}
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ss << "\n======= Backend Info =======\n";
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ss << "warmup: " << FLAGS_warmup << std::endl;
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ss << "repeats: " << FLAGS_repeat << std::endl;
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ss << "device: " << FLAGS_device << std::endl;
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if (FLAGS_device == "gpu") {
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ss << "device_id: " << FLAGS_device_id << std::endl;
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}
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ss << "backend: " << FLAGS_backend << std::endl;
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if (FLAGS_device == "cpu") {
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ss << "cpu_thread_nums: " << FLAGS_cpu_thread_nums << std::endl;
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}
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ss << "use_fp16: " << FLAGS_use_fp16 << std::endl;
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ss << "collect_memory_info: " << FLAGS_collect_memory_info << std::endl;
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if (FLAGS_collect_memory_info) {
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ss << "sampling_interval: " << std::to_string(FLAGS_sampling_interval)
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<< "ms" << std::endl;
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}
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std::cout << ss.str() << std::endl;
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#endif
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return;
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}
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