mirror of
https://github.com/PaddlePaddle/FastDeploy.git
synced 2025-10-05 08:37:06 +08:00
[Other] Add runtime cpp demos (#515)
* add paddle_trt in benchmark * update benchmark in device * update benchmark * update result doc * fixed for CI * update python api_docs * update index.rst * add runtime cpp examples * deal with comments * Update infer_paddle_tensorrt.py Co-authored-by: Jason <928090362@qq.com>
This commit is contained in:
@@ -20,4 +20,8 @@ FastDeploy
|
||||
matting.md
|
||||
face_recognition.md
|
||||
face_detection.md
|
||||
face_alignment.md
|
||||
headpose.md
|
||||
vision_results_en.md
|
||||
runtime.md
|
||||
runtime_option.md
|
||||
|
9
docs/api_docs/python/runtime.md
Normal file
9
docs/api_docs/python/runtime.md
Normal file
@@ -0,0 +1,9 @@
|
||||
# Runtime API
|
||||
|
||||
## fastdeploy.Runtime
|
||||
|
||||
```{eval-rst}
|
||||
.. autoclass:: fastdeploy.Runtime
|
||||
:members:
|
||||
:inherited-members:
|
||||
```
|
9
docs/api_docs/python/runtime_option.md
Normal file
9
docs/api_docs/python/runtime_option.md
Normal file
@@ -0,0 +1,9 @@
|
||||
# Runtime Option API
|
||||
|
||||
## fastdeploy.RuntimeOption
|
||||
|
||||
```{eval-rst}
|
||||
.. autoclass:: fastdeploy.RuntimeOption
|
||||
:members:
|
||||
:inherited-members:
|
||||
```
|
14
examples/runtime/cpp/CMakeLists.txt
Normal file
14
examples/runtime/cpp/CMakeLists.txt
Normal file
@@ -0,0 +1,14 @@
|
||||
PROJECT(runtime_demo C CXX)
|
||||
CMAKE_MINIMUM_REQUIRED (VERSION 3.12)
|
||||
|
||||
# 指定下载解压后的fastdeploy库路径
|
||||
option(FASTDEPLOY_INSTALL_DIR "Path of downloaded fastdeploy sdk.")
|
||||
|
||||
include(${FASTDEPLOY_INSTALL_DIR}/FastDeploy.cmake)
|
||||
|
||||
# 添加FastDeploy依赖头文件
|
||||
include_directories(${FASTDEPLOY_INCS})
|
||||
|
||||
add_executable(runtime_demo ${PROJECT_SOURCE_DIR}/infer_onnx_openvino.cc)
|
||||
# 添加FastDeploy库依赖
|
||||
target_link_libraries(runtime_demo ${FASTDEPLOY_LIBS})
|
59
examples/runtime/cpp/infer_onnx_openvino.cc
Normal file
59
examples/runtime/cpp/infer_onnx_openvino.cc
Normal file
@@ -0,0 +1,59 @@
|
||||
// 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.
|
||||
|
||||
#include "fastdeploy/runtime.h"
|
||||
|
||||
namespace fd = fastdeploy;
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
std::string model_file = "mobilenetv2.onnx";
|
||||
|
||||
// setup option
|
||||
fd::RuntimeOption runtime_option;
|
||||
runtime_option.SetModelPath(model_file, "", fd::ModelFormat::ONNX);
|
||||
runtime_option.UseOpenVINOBackend();
|
||||
runtime_option.SetCpuThreadNum(12);
|
||||
// init runtime
|
||||
std::unique_ptr<fd::Runtime> runtime =
|
||||
std::unique_ptr<fd::Runtime>(new fd::Runtime());
|
||||
if (!runtime->Init(runtime_option)) {
|
||||
std::cerr << "--- Init FastDeploy Runitme Failed! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
return -1;
|
||||
} else {
|
||||
std::cout << "--- Init FastDeploy Runitme Done! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
}
|
||||
// init input tensor shape
|
||||
fd::TensorInfo info = runtime->GetInputInfo(0);
|
||||
info.shape = {1, 3, 224, 224};
|
||||
|
||||
std::vector<fd::FDTensor> input_tensors(1);
|
||||
std::vector<fd::FDTensor> output_tensors(1);
|
||||
|
||||
std::vector<float> inputs_data;
|
||||
inputs_data.resize(1 * 3 * 224 * 224);
|
||||
for (size_t i = 0; i < inputs_data.size(); ++i) {
|
||||
inputs_data[i] = std::rand() % 1000 / 1000.0f;
|
||||
}
|
||||
input_tensors[0].SetExternalData({1, 3, 224, 224}, fd::FDDataType::FP32, inputs_data.data());
|
||||
|
||||
//get input name
|
||||
input_tensors[0].name = info.name;
|
||||
|
||||
runtime->Infer(input_tensors, &output_tensors);
|
||||
|
||||
output_tensors[0].PrintInfo();
|
||||
return 0;
|
||||
}
|
60
examples/runtime/cpp/infer_onnx_tensorrt.cc
Normal file
60
examples/runtime/cpp/infer_onnx_tensorrt.cc
Normal file
@@ -0,0 +1,60 @@
|
||||
// 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.
|
||||
|
||||
#include "fastdeploy/runtime.h"
|
||||
|
||||
namespace fd = fastdeploy;
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
std::string model_file = "mobilenetv2.onnx";
|
||||
|
||||
// setup option
|
||||
fd::RuntimeOption runtime_option;
|
||||
runtime_option.SetModelPath(model_file, "", fd::ModelFormat::ONNX);
|
||||
runtime_option.UseGpu(0);
|
||||
runtime_option.UseTrtBackend();
|
||||
runtime_option.SetTrtInputShape("inputs", {1, 3, 224, 224});
|
||||
// init runtime
|
||||
std::unique_ptr<fd::Runtime> runtime =
|
||||
std::unique_ptr<fd::Runtime>(new fd::Runtime());
|
||||
if (!runtime->Init(runtime_option)) {
|
||||
std::cerr << "--- Init FastDeploy Runitme Failed! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
return -1;
|
||||
} else {
|
||||
std::cout << "--- Init FastDeploy Runitme Done! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
}
|
||||
// init input tensor shape
|
||||
fd::TensorInfo info = runtime->GetInputInfo(0);
|
||||
info.shape = {1, 3, 224, 224};
|
||||
|
||||
std::vector<fd::FDTensor> input_tensors(1);
|
||||
std::vector<fd::FDTensor> output_tensors(1);
|
||||
|
||||
std::vector<float> inputs_data;
|
||||
inputs_data.resize(1 * 3 * 224 * 224);
|
||||
for (size_t i = 0; i < inputs_data.size(); ++i) {
|
||||
inputs_data[i] = std::rand() % 1000 / 1000.0f;
|
||||
}
|
||||
input_tensors[0].SetExternalData({1, 3, 224, 224}, fd::FDDataType::FP32, inputs_data.data());
|
||||
|
||||
//get input name
|
||||
input_tensors[0].name = info.name;
|
||||
|
||||
runtime->Infer(input_tensors, &output_tensors);
|
||||
|
||||
output_tensors[0].PrintInfo();
|
||||
return 0;
|
||||
}
|
60
examples/runtime/cpp/infer_paddle_onnxruntime.cc
Normal file
60
examples/runtime/cpp/infer_paddle_onnxruntime.cc
Normal file
@@ -0,0 +1,60 @@
|
||||
// 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.
|
||||
|
||||
#include "fastdeploy/runtime.h"
|
||||
|
||||
namespace fd = fastdeploy;
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
std::string model_file = "mobilenetv2/inference.pdmodel";
|
||||
std::string params_file = "mobilenetv2/inference.pdiparams";
|
||||
|
||||
// setup option
|
||||
fd::RuntimeOption runtime_option;
|
||||
runtime_option.SetModelPath(model_file, params_file, fd::ModelFormat::PADDLE);
|
||||
runtime_option.UseOrtBackend();
|
||||
runtime_option.SetCpuThreadNum(12);
|
||||
// init runtime
|
||||
std::unique_ptr<fd::Runtime> runtime =
|
||||
std::unique_ptr<fd::Runtime>(new fd::Runtime());
|
||||
if (!runtime->Init(runtime_option)) {
|
||||
std::cerr << "--- Init FastDeploy Runitme Failed! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
return -1;
|
||||
} else {
|
||||
std::cout << "--- Init FastDeploy Runitme Done! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
}
|
||||
// init input tensor shape
|
||||
fd::TensorInfo info = runtime->GetInputInfo(0);
|
||||
info.shape = {1, 3, 224, 224};
|
||||
|
||||
std::vector<fd::FDTensor> input_tensors(1);
|
||||
std::vector<fd::FDTensor> output_tensors(1);
|
||||
|
||||
std::vector<float> inputs_data;
|
||||
inputs_data.resize(1 * 3 * 224 * 224);
|
||||
for (size_t i = 0; i < inputs_data.size(); ++i) {
|
||||
inputs_data[i] = std::rand() % 1000 / 1000.0f;
|
||||
}
|
||||
input_tensors[0].SetExternalData({1, 3, 224, 224}, fd::FDDataType::FP32, inputs_data.data());
|
||||
|
||||
//get input name
|
||||
input_tensors[0].name = info.name;
|
||||
|
||||
runtime->Infer(input_tensors, &output_tensors);
|
||||
|
||||
output_tensors[0].PrintInfo();
|
||||
return 0;
|
||||
}
|
60
examples/runtime/cpp/infer_paddle_openvino.cc
Normal file
60
examples/runtime/cpp/infer_paddle_openvino.cc
Normal file
@@ -0,0 +1,60 @@
|
||||
// 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.
|
||||
|
||||
#include "fastdeploy/runtime.h"
|
||||
|
||||
namespace fd = fastdeploy;
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
std::string model_file = "mobilenetv2/inference.pdmodel";
|
||||
std::string params_file = "mobilenetv2/inference.pdiparams";
|
||||
|
||||
// setup option
|
||||
fd::RuntimeOption runtime_option;
|
||||
runtime_option.SetModelPath(model_file, params_file, fd::ModelFormat::PADDLE);
|
||||
runtime_option.UseOpenVINOBackend();
|
||||
runtime_option.SetCpuThreadNum(12);
|
||||
// init runtime
|
||||
std::unique_ptr<fd::Runtime> runtime =
|
||||
std::unique_ptr<fd::Runtime>(new fd::Runtime());
|
||||
if (!runtime->Init(runtime_option)) {
|
||||
std::cerr << "--- Init FastDeploy Runitme Failed! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
return -1;
|
||||
} else {
|
||||
std::cout << "--- Init FastDeploy Runitme Done! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
}
|
||||
// init input tensor shape
|
||||
fd::TensorInfo info = runtime->GetInputInfo(0);
|
||||
info.shape = {1, 3, 224, 224};
|
||||
|
||||
std::vector<fd::FDTensor> input_tensors(1);
|
||||
std::vector<fd::FDTensor> output_tensors(1);
|
||||
|
||||
std::vector<float> inputs_data;
|
||||
inputs_data.resize(1 * 3 * 224 * 224);
|
||||
for (size_t i = 0; i < inputs_data.size(); ++i) {
|
||||
inputs_data[i] = std::rand() % 1000 / 1000.0f;
|
||||
}
|
||||
input_tensors[0].SetExternalData({1, 3, 224, 224}, fd::FDDataType::FP32, inputs_data.data());
|
||||
|
||||
//get input name
|
||||
input_tensors[0].name = info.name;
|
||||
|
||||
runtime->Infer(input_tensors, &output_tensors);
|
||||
|
||||
output_tensors[0].PrintInfo();
|
||||
return 0;
|
||||
}
|
65
examples/runtime/cpp/infer_paddle_paddle_inference.cc
Normal file
65
examples/runtime/cpp/infer_paddle_paddle_inference.cc
Normal file
@@ -0,0 +1,65 @@
|
||||
// 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.
|
||||
|
||||
#include "fastdeploy/runtime.h"
|
||||
|
||||
namespace fd = fastdeploy;
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
std::string model_file = "mobilenetv2/inference.pdmodel";
|
||||
std::string params_file = "mobilenetv2/inference.pdiparams";
|
||||
|
||||
// setup option
|
||||
fd::RuntimeOption runtime_option;
|
||||
runtime_option.SetModelPath(model_file, params_file, fd::ModelFormat::PADDLE);
|
||||
// CPU
|
||||
runtime_option.UsePaddleBackend();
|
||||
runtime_option.SetCpuThreadNum(12);
|
||||
// GPU
|
||||
// runtime_option.UseGpu(0);
|
||||
// IPU
|
||||
// runtime_option.UseIpu();
|
||||
// init runtime
|
||||
std::unique_ptr<fd::Runtime> runtime =
|
||||
std::unique_ptr<fd::Runtime>(new fd::Runtime());
|
||||
if (!runtime->Init(runtime_option)) {
|
||||
std::cerr << "--- Init FastDeploy Runitme Failed! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
return -1;
|
||||
} else {
|
||||
std::cout << "--- Init FastDeploy Runitme Done! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
}
|
||||
// init input tensor shape
|
||||
fd::TensorInfo info = runtime->GetInputInfo(0);
|
||||
info.shape = {1, 3, 224, 224};
|
||||
|
||||
std::vector<fd::FDTensor> input_tensors(1);
|
||||
std::vector<fd::FDTensor> output_tensors(1);
|
||||
|
||||
std::vector<float> inputs_data;
|
||||
inputs_data.resize(1 * 3 * 224 * 224);
|
||||
for (size_t i = 0; i < inputs_data.size(); ++i) {
|
||||
inputs_data[i] = std::rand() % 1000 / 1000.0f;
|
||||
}
|
||||
input_tensors[0].SetExternalData({1, 3, 224, 224}, fd::FDDataType::FP32, inputs_data.data());
|
||||
|
||||
//get input name
|
||||
input_tensors[0].name = info.name;
|
||||
|
||||
runtime->Infer(input_tensors, &output_tensors);
|
||||
|
||||
output_tensors[0].PrintInfo();
|
||||
return 0;
|
||||
}
|
61
examples/runtime/cpp/infer_paddle_tensorrt.cc
Normal file
61
examples/runtime/cpp/infer_paddle_tensorrt.cc
Normal file
@@ -0,0 +1,61 @@
|
||||
// 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.
|
||||
|
||||
#include "fastdeploy/runtime.h"
|
||||
|
||||
namespace fd = fastdeploy;
|
||||
|
||||
int main(int argc, char* argv[]) {
|
||||
std::string model_file = "mobilenetv2/inference.pdmodel";
|
||||
std::string params_file = "mobilenetv2/inference.pdiparams";
|
||||
|
||||
// setup option
|
||||
fd::RuntimeOption runtime_option;
|
||||
runtime_option.SetModelPath(model_file, params_file, fd::ModelFormat::PADDLE);
|
||||
runtime_option.UseGpu(0);
|
||||
runtime_option.UseTrtBackend();
|
||||
runtime_option.EnablePaddleToTrt();
|
||||
// init runtime
|
||||
std::unique_ptr<fd::Runtime> runtime =
|
||||
std::unique_ptr<fd::Runtime>(new fd::Runtime());
|
||||
if (!runtime->Init(runtime_option)) {
|
||||
std::cerr << "--- Init FastDeploy Runitme Failed! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
return -1;
|
||||
} else {
|
||||
std::cout << "--- Init FastDeploy Runitme Done! "
|
||||
<< "\n--- Model: " << model_file << std::endl;
|
||||
}
|
||||
// init input tensor shape
|
||||
fd::TensorInfo info = runtime->GetInputInfo(0);
|
||||
info.shape = {1, 3, 224, 224};
|
||||
|
||||
std::vector<fd::FDTensor> input_tensors(1);
|
||||
std::vector<fd::FDTensor> output_tensors(1);
|
||||
|
||||
std::vector<float> inputs_data;
|
||||
inputs_data.resize(1 * 3 * 224 * 224);
|
||||
for (size_t i = 0; i < inputs_data.size(); ++i) {
|
||||
inputs_data[i] = std::rand() % 1000 / 1000.0f;
|
||||
}
|
||||
input_tensors[0].SetExternalData({1, 3, 224, 224}, fd::FDDataType::FP32, inputs_data.data());
|
||||
|
||||
//get input name
|
||||
input_tensors[0].name = info.name;
|
||||
|
||||
runtime->Infer(input_tensors, &output_tensors);
|
||||
|
||||
output_tensors[0].PrintInfo();
|
||||
return 0;
|
||||
}
|
@@ -27,6 +27,8 @@ option.set_model_path("mobilenetv2/inference.pdmodel",
|
||||
# **** GPU 配置 ***
|
||||
option.use_gpu(0)
|
||||
option.use_trt_backend()
|
||||
# using TensorRT integrated in Paddle Inference
|
||||
# option.enable_paddle_to_trt()
|
||||
|
||||
# 初始化构造runtime
|
||||
runtime = fd.Runtime(option)
|
||||
|
Reference in New Issue
Block a user