Files
FastDeploy/benchmark/cpp/option.h
DefTruth 49c033a828 [XPU] Support XPU via Paddle Inference backend (#1987)
* [backend] Support XPU via Paddle Inference backend

* [backend] Support XPU via Paddle Inference backend

* [backend] Support XPU via Paddle Inference backend

* [XPU] support XPU benchmark via paddle inference

* [XPU] support XPU benchmark via paddle inference

* [benchmark] add xpu paddle h2d config files
2023-05-25 14:13:40 +08:00

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// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#pragma once
#include "fastdeploy/vision.h"
static void UpdateBaseCustomFlags(
std::unordered_map<std::string, std::string>& config_info) {
// see benchmark/cpp/flags.h
if (FLAGS_warmup > -1) {
config_info["warmup"] = std::to_string(FLAGS_warmup);
}
if (FLAGS_repeat > -1) {
config_info["repeat"] = std::to_string(FLAGS_repeat);
}
if (FLAGS_device_id > -1) {
config_info["device_id"] = std::to_string(FLAGS_device_id);
}
if (FLAGS_use_fp16) {
config_info["use_fp16"] = "true";
}
if (FLAGS_xpu_l3_cache >= 0) {
config_info["xpu_l3_cache"] = std::to_string(FLAGS_xpu_l3_cache);
}
if (FLAGS_enable_log_info) {
config_info["enable_log_info"] = "true";
} else {
config_info["enable_log_info"] = "false";
}
}
static bool CreateRuntimeOption(fastdeploy::RuntimeOption* option,
int argc, char* argv[], bool remove_flags) {
google::ParseCommandLineFlags(&argc, &argv, remove_flags);
option->DisableValidBackendCheck();
std::unordered_map<std::string, std::string> config_info;
fastdeploy::benchmark::ResultManager::LoadBenchmarkConfig(
FLAGS_config_path, &config_info);
UpdateBaseCustomFlags(config_info);
int warmup = std::stoi(config_info["warmup"]);
int repeat = std::stoi(config_info["repeat"]);
if (config_info["profile_mode"] == "runtime") {
option->EnableProfiling(config_info["include_h2d_d2h"] == "true",
repeat, warmup);
}
if (config_info["enable_log_info"] == "true") {
option->paddle_infer_option.enable_log_info = true;
}
if (config_info["device"] == "gpu") {
option->UseGpu(std::stoi(config_info["device_id"]));
if (config_info["backend"] == "ort") {
option->UseOrtBackend();
} else if (config_info["backend"] == "paddle") {
option->UsePaddleInferBackend();
} else if (config_info["backend"] == "trt" ||
config_info["backend"] == "paddle_trt") {
option->trt_option.serialize_file = FLAGS_model +
sep + "trt_serialized.trt";
option->UseTrtBackend();
if (config_info["backend"] == "paddle_trt") {
option->UsePaddleInferBackend();
option->paddle_infer_option.enable_trt = true;
}
if (config_info["use_fp16"] == "true") {
option->trt_option.enable_fp16 = true;
}
} else if (config_info["backend"] == "lite") {
option->UsePaddleLiteBackend();
if (config_info["use_fp16"] == "true") {
option->paddle_lite_option.enable_fp16 = true;
}
} else if (config_info["backend"] == "default") {
PrintBenchmarkInfo(config_info);
return true;
} else {
std::cout << "While inference with GPU, only support "
"default/ort/paddle/trt/paddle_trt now, "
<< config_info["backend"] << " is not supported." << std::endl;
PrintUsage();
return false;
}
} else if (config_info["device"] == "cpu") {
option->SetCpuThreadNum(std::stoi(config_info["cpu_thread_nums"]));
if (config_info["backend"] == "ort") {
option->UseOrtBackend();
} else if (config_info["backend"] == "ov") {
option->UseOpenVINOBackend();
} else if (config_info["backend"] == "paddle") {
option->UsePaddleInferBackend();
} else if (config_info["backend"] == "lite") {
option->UsePaddleLiteBackend();
if (config_info["use_fp16"] == "true") {
option->paddle_lite_option.enable_fp16 = true;
}
} else if (config_info["backend"] == "default") {
PrintBenchmarkInfo(config_info);
return true;
} else {
std::cout << "While inference with CPU, only support "
"default/ort/ov/paddle/lite now, "
<< config_info["backend"] << " is not supported." << std::endl;
PrintUsage();
return false;
}
} else if (config_info["device"] == "xpu") {
option->UseKunlunXin(std::stoi(config_info["device_id"]),
std::stoi(config_info["xpu_l3_cache"]));
if (config_info["backend"] == "ort") {
option->UseOrtBackend();
} else if (config_info["backend"] == "paddle") {
// Note: For inference + XPU fp16, As long as the
// model is fp16, it can automatically run on the
// fp16 precision.
option->UsePaddleInferBackend();
} else if (config_info["backend"] == "lite") {
option->UsePaddleLiteBackend();
if (config_info["use_fp16"] == "true") {
option->paddle_lite_option.enable_fp16 = true;
}
} else if (config_info["backend"] == "sophgo") {
option->UseSophgo();
option->UseSophgoBackend();
} else if (config_info["backend"] == "default") {
PrintBenchmarkInfo(config_info);
return true;
} else {
std::cout << "While inference with XPU, only support "
"default/ort/paddle/lite now, "
<< config_info["backend"] << " is not supported." << std::endl;
PrintUsage();
return false;
}
} else {
std::cerr << "Only support device CPU/GPU/XPU now, "
<< config_info["device"]
<< " is not supported." << std::endl;
PrintUsage();
return false;
}
PrintBenchmarkInfo(config_info);
return true;
}