mirror of
https://github.com/PaddlePaddle/PaddleOCR.git
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84 lines
3.3 KiB
C++
84 lines
3.3 KiB
C++
// Copyright (c) 2020 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 <chrono>
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#include <iomanip>
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#include <iostream>
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#include <ostream>
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#include <stdlib.h>
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#include <vector>
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#include <glog/logging.h>
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class AutoLogger {
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public:
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AutoLogger(std::string model_name,
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bool use_gpu,
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bool enable_tensorrt,
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bool enable_mkldnn,
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int cpu_threads,
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int batch_size,
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std::string input_shape,
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std::string model_precision,
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std::vector<double> time_info,
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int img_num) {
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this->model_name_ = model_name;
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this->use_gpu_ = use_gpu;
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this->enable_tensorrt_ = enable_tensorrt;
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this->enable_mkldnn_ = enable_mkldnn;
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this->cpu_threads_ = cpu_threads;
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this->batch_size_ = batch_size;
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this->input_shape_ = input_shape;
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this->model_precision_ = model_precision;
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this->time_info_ = time_info;
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this->img_num_ = img_num;
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}
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void report() {
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LOG(INFO) << "----------------------- Config info -----------------------";
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LOG(INFO) << "runtime_device: " << (this->use_gpu_ ? "gpu" : "cpu");
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LOG(INFO) << "ir_optim: " << "True";
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LOG(INFO) << "enable_memory_optim: " << "True";
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LOG(INFO) << "enable_tensorrt: " << this->enable_tensorrt_;
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LOG(INFO) << "enable_mkldnn: " << (this->enable_mkldnn_ ? "True" : "False");
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LOG(INFO) << "cpu_math_library_num_threads: " << this->cpu_threads_;
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LOG(INFO) << "----------------------- Data info -----------------------";
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LOG(INFO) << "batch_size: " << this->batch_size_;
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LOG(INFO) << "input_shape: " << this->input_shape_;
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LOG(INFO) << "data_num: " << this->img_num_;
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LOG(INFO) << "----------------------- Model info -----------------------";
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LOG(INFO) << "model_name: " << this->model_name_;
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LOG(INFO) << "precision: " << this->model_precision_;
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LOG(INFO) << "----------------------- Perf info ------------------------";
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LOG(INFO) << "Total time spent(ms): "
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<< std::accumulate(this->time_info_.begin(), this->time_info_.end(), 0);
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LOG(INFO) << "preprocess_time(ms): " << this->time_info_[0] / this->img_num_
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<< ", inference_time(ms): " << this->time_info_[1] / this->img_num_
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<< ", postprocess_time(ms): " << this->time_info_[2] / this->img_num_;
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}
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private:
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std::string model_name_;
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bool use_gpu_ = false;
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bool enable_tensorrt_ = false;
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bool enable_mkldnn_ = true;
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int cpu_threads_ = 10;
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int batch_size_ = 1;
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std::string input_shape_ = "dynamic";
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std::string model_precision_ = "fp32";
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std::vector<double> time_info_;
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int img_num_;
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};
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