Files
FastDeploy/fastdeploy/runtime/enum_variables.h
yunyaoXYY c38b7d4377 [Backend] Support onnxruntime DirectML inference. (#1304)
* Fix links in readme

* Fix links in readme

* Update PPOCRv2/v3 examples

* Update auto compression configs

* Add neww quantization  support for paddleclas model

* Update quantized Yolov6s model download link

* Improve PPOCR comments

* Add English doc for quantization

* Fix PPOCR rec model bug

* Add  new paddleseg quantization support

* Add  new paddleseg quantization support

* Add  new paddleseg quantization support

* Add  new paddleseg quantization support

* Add Ascend model list

* Add ascend model list

* Add ascend model list

* Add ascend model list

* Add ascend model list

* Add ascend model list

* Add ascend model list

* Support DirectML in onnxruntime

* Support onnxruntime DirectML

* Support onnxruntime DirectML

* Support onnxruntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Support OnnxRuntime DirectML

* Remove DirectML vision model example

* Imporve OnnxRuntime DirectML

* Imporve OnnxRuntime DirectML

* fix opencv cmake in Windows

* recheck codestyle
2023-02-17 10:53:51 +08:00

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// 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 DirectML
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,
DIRECTML
};
/*! 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_by_format = {
{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}}
};
/// Describle all the supported backends for specified device
static std::map<Device, std::vector<Backend>>
s_default_backends_by_device = {
{Device::CPU, {Backend::LITE, Backend::PDINFER, Backend::ORT,
Backend::OPENVINO, Backend::POROS}},
{Device::GPU, {Backend::PDINFER, Backend::ORT, Backend::TRT, Backend::POROS}},
{Device::RKNPU, {Backend::RKNPU2}},
{Device::IPU, {Backend::PDINFER}},
{Device::TIMVX, {Backend::LITE}},
{Device::KUNLUNXIN, {Backend::LITE}},
{Device::ASCEND, {Backend::LITE}},
{Device::SOPHGOTPUD, {Backend::SOPHGOTPU}},
{Device::DIRECTML, {Backend::ORT}}
};
inline bool Supported(ModelFormat format, Backend backend) {
auto iter = s_default_backends_by_format.find(format);
if (iter == s_default_backends_by_format.end()) {
FDERROR << "Didn't find format is registered in " <<
"s_default_backends_by_format." << std::endl;
return false;
}
for (size_t i = 0; i < iter->second.size(); ++i) {
if (iter->second[i] == backend) {
return true;
}
}
std::string msg = Str(iter->second);
FDERROR << backend << " only supports " << msg << ", but now it's "
<< format << "." << std::endl;
return false;
}
inline bool Supported(Device device, Backend backend) {
auto iter = s_default_backends_by_device.find(device);
if (iter == s_default_backends_by_device.end()) {
FDERROR << "Didn't find device is registered in " <<
"s_default_backends_by_device." << std::endl;
return false;
}
for (size_t i = 0; i < iter->second.size(); ++i) {
if (iter->second[i] == backend) {
return true;
}
}
std::string msg = Str(iter->second);
FDERROR << backend << " only supports " << msg << ", but now it's "
<< device << "." << std::endl;
return false;
}
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