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[Backend] Support onnxruntime DirectML inference. (#1304)

Browse Source 
* 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
This commit is contained in:
yunyaoXYY
2023-02-17 10:53:51 +08:00
committed by GitHub
parent efa46563f3
commit c38b7d4377
22 changed files with 393 additions and 60 deletions
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25
fastdeploy/runtime/enum_variables.h
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@@ -29,7 +29,8 @@ namespace fastdeploy {
/*! Inference backend supported in FastDeploy */
enum Backend {
UNKNOWN, ///< Unknown inference backend
ORT, ///< ONNX Runtime, support Paddle/ONNX format model, CPU / Nvidia GPU
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
@@ -58,7 +59,8 @@ enum FASTDEPLOY_DECL Device {
TIMVX,
KUNLUNXIN,
ASCEND,
SOPHGOTPUD
SOPHGOTPUD,
DIRECTML
};
/*! Deep learning model format */
@@ -93,13 +95,15 @@ static std::map<Device, std::vector<Backend>>
{Device::TIMVX, {Backend::LITE}},
{Device::KUNLUNXIN, {Backend::LITE}},
{Device::ASCEND, {Backend::LITE}},
{Device::SOPHGOTPUD, {Backend::SOPHGOTPU}}
{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;
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) {
@@ -107,15 +111,17 @@ inline bool Supported(ModelFormat format, Backend backend) {
return true;
}
}
std::string msg = Str(iter->second);
FDERROR << backend << " only supports " << msg << ", but now it's " << format << "." << std::endl;
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;
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) {
@@ -123,8 +129,9 @@ inline bool Supported(Device device, Backend backend) {
return true;
}
}
std::string msg = Str(iter->second);
FDERROR << backend << " only supports " << msg << ", but now it's " << device << "." << std::endl;
std::string msg = Str(iter->second);
FDERROR << backend << " only supports " << msg << ", but now it's "
<< device << "." << std::endl;
return false;
}