mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 16:48:03 +08:00
89 lines
2.9 KiB
C++
89 lines
2.9 KiB
C++
// Copyright (c) 2022 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.
|
|
|
|
/*! \file enum_variables.h
|
|
\brief A brief file description.
|
|
|
|
More details
|
|
*/
|
|
|
|
#pragma once
|
|
#include "fastdeploy/utils/utils.h"
|
|
#include <ostream>
|
|
#include <map>
|
|
|
|
namespace fastdeploy {
|
|
|
|
|
|
/*! Inference backend supported in FastDeploy */
|
|
enum Backend {
|
|
UNKNOWN, ///< Unknown inference backend
|
|
ORT, ///< ONNX Runtime, support Paddle/ONNX format model, CPU / Nvidia GPU
|
|
TRT, ///< TensorRT, support Paddle/ONNX format model, Nvidia GPU only
|
|
PDINFER, ///< Paddle Inference, support Paddle format model, CPU / Nvidia GPU
|
|
POROS, ///< Poros, support TorchScript format model, CPU / Nvidia GPU
|
|
OPENVINO, ///< Intel OpenVINO, support Paddle/ONNX format, CPU only
|
|
LITE, ///< Paddle Lite, support Paddle format model, ARM CPU only
|
|
RKNPU2, ///< RKNPU2, support RKNN format model, Rockchip NPU only
|
|
SOPHGOTPU, ///< SOPHGOTPU, support SOPHGO format model, Sophgo TPU only
|
|
};
|
|
|
|
/**
|
|
* @brief Get all the available inference backend in FastDeploy
|
|
*/
|
|
FASTDEPLOY_DECL std::vector<Backend> GetAvailableBackends();
|
|
|
|
/**
|
|
* @brief Check if the inference backend available
|
|
*/
|
|
FASTDEPLOY_DECL bool IsBackendAvailable(const Backend& backend);
|
|
|
|
|
|
enum FASTDEPLOY_DECL Device {
|
|
CPU,
|
|
GPU,
|
|
RKNPU,
|
|
IPU,
|
|
TIMVX,
|
|
KUNLUNXIN,
|
|
ASCEND,
|
|
SOPHGOTPUD
|
|
};
|
|
|
|
/*! Deep learning model format */
|
|
enum ModelFormat {
|
|
AUTOREC, ///< Auto recognize the model format by model file name
|
|
PADDLE, ///< Model with paddlepaddle format
|
|
ONNX, ///< Model with ONNX format
|
|
RKNN, ///< Model with RKNN format
|
|
TORCHSCRIPT, ///< Model with TorchScript format
|
|
SOPHGO, ///< Model with SOPHGO format
|
|
};
|
|
|
|
/// Describle all the supported backends for specified model format
|
|
static std::map<ModelFormat, std::vector<Backend>> s_default_backends_cfg = {
|
|
{ModelFormat::PADDLE, {Backend::PDINFER, Backend::LITE,
|
|
Backend::ORT, Backend::OPENVINO, Backend::TRT}},
|
|
{ModelFormat::ONNX, {Backend::ORT, Backend::OPENVINO, Backend::TRT}},
|
|
{ModelFormat::RKNN, {Backend::RKNPU2}},
|
|
{ModelFormat::TORCHSCRIPT, {Backend::POROS}},
|
|
{ModelFormat::SOPHGO, {Backend::SOPHGOTPU}}
|
|
};
|
|
|
|
FASTDEPLOY_DECL std::ostream& operator<<(std::ostream& o, const Backend& b);
|
|
FASTDEPLOY_DECL std::ostream& operator<<(std::ostream& o, const Device& d);
|
|
FASTDEPLOY_DECL std::ostream& operator<<(std::ostream& o, const ModelFormat& f);
|
|
|
|
} // namespace fastdeploy
|