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[Other] Add onnx_ort_runtime cpp/python demos (#565)

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* add onnx_ort_runtime demo

* rm in requirements
This commit is contained in:
WJJ1995
2022-11-11 12:47:06 +08:00
committed by GitHub
parent 224c2cf1e8
commit 4bbfd977c7
9 changed files with 131 additions and 20 deletions
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6
benchmark/benchmark_ppcls.py
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@@ -16,9 +16,6 @@ import fastdeploy as fd
import cv2
import os
import numpy as np
import pynvml
import psutil
import GPUtil
import time
@@ -112,6 +109,8 @@ def build_option(args):
def get_current_memory_mb(gpu_id=None):
import pynvml
import psutil
pid = os.getpid()
p = psutil.Process(pid)
info = p.memory_full_info()
@@ -126,6 +125,7 @@ def get_current_memory_mb(gpu_id=None):
def get_current_gputil(gpu_id):
import GPUtil
GPUs = GPUtil.getGPUs()
gpu_load = GPUs[gpu_id].load
return gpu_load

8
benchmark/benchmark_ppdet.py
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@@ -16,11 +16,6 @@ import fastdeploy as fd
import cv2
import os
import numpy as np
import datetime
import json
import pynvml
import psutil
import GPUtil
import time
@@ -114,6 +109,8 @@ def build_option(args):
def get_current_memory_mb(gpu_id=None):
import pynvml
import psutil
pid = os.getpid()
p = psutil.Process(pid)
info = p.memory_full_info()
@@ -128,6 +125,7 @@ def get_current_memory_mb(gpu_id=None):
def get_current_gputil(gpu_id):
import GPUtil
GPUs = GPUtil.getGPUs()
gpu_load = GPUs[gpu_id].load
return gpu_load

6
benchmark/benchmark_ppseg.py
View File

@@ -16,9 +16,6 @@ import fastdeploy as fd
import cv2
import os
import numpy as np
import pynvml
import psutil
import GPUtil
import time
@@ -112,6 +109,8 @@ def build_option(args):
def get_current_memory_mb(gpu_id=None):
import pynvml
import psutil
pid = os.getpid()
p = psutil.Process(pid)
info = p.memory_full_info()
@@ -126,6 +125,7 @@ def get_current_memory_mb(gpu_id=None):
def get_current_gputil(gpu_id):
import GPUtil
GPUs = GPUtil.getGPUs()
gpu_load = GPUs[gpu_id].load
return gpu_load

8
benchmark/benchmark_yolo.py
View File

@@ -16,11 +16,6 @@ import fastdeploy as fd
import cv2
import os
import numpy as np
import datetime
import json
import pynvml
import psutil
import GPUtil
import time
@@ -114,6 +109,8 @@ def build_option(args):
def get_current_memory_mb(gpu_id=None):
import pynvml
import psutil
pid = os.getpid()
p = psutil.Process(pid)
info = p.memory_full_info()
@@ -128,6 +125,7 @@ def get_current_memory_mb(gpu_id=None):
def get_current_gputil(gpu_id):
import GPUtil
GPUs = GPUtil.getGPUs()
gpu_load = GPUs[gpu_id].load
return gpu_load

3
benchmark/requirements.txt
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@@ -1,4 +1 @@
numpy
pynvml
psutil
GPUtil

4
examples/runtime/README.md
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@@ -1,6 +1,6 @@
# FastDeploy Runtime examples
FastDeploy Runtime C++ 推理示例如下
FastDeploy Runtime 推理示例如下
## Python 示例
@@ -12,6 +12,7 @@ FastDeploy Runtime C++ 推理示例如下
| python/infer_paddle_onnxruntime.py | Python | Deploy Paddle model with ONNX Runtime(CPU/GPU) |
| python/infer_onnx_openvino.py | Python | Deploy ONNX model with OpenVINO(CPU) |
| python/infer_onnx_tensorrt.py | Python | Deploy ONNX model with TensorRT(GPU) |
| python/infer_onnx_onnxruntime.py | Python | Deploy ONNX model with ONNX Runtime(CPU/GPU) |
## C++ 示例
@@ -23,6 +24,7 @@ FastDeploy Runtime C++ 推理示例如下
| cpp/infer_paddle_onnxruntime.cc | C++ | Deploy Paddle model with ONNX Runtime(CPU/GPU) |
| cpp/infer_onnx_openvino.cc | C++ | Deploy ONNX model with OpenVINO(CPU) |
| cpp/infer_onnx_tensorrt.cc | C++ | Deploy ONNX model with TensorRT(GPU) |
| cpp/infer_onnx_onnxruntime.cc | C++ | Deploy ONNX model with ONNX Runtime(CPU/GPU) |
## 详细部署文档

64
examples/runtime/cpp/infer_onnx_onnxruntime.cc Normal file
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@@ -0,0 +1,64 @@
// 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.UseOrtBackend();
runtime_option.SetCpuThreadNum(12);
// **** GPU ****
// To use GPU, use the following commented code
// runtime_option.UseGpu(0);
// 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;
}

5
examples/runtime/cpp/infer_paddle_onnxruntime.cc
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@@ -25,6 +25,11 @@ int main(int argc, char* argv[]) {
runtime_option.SetModelPath(model_file, params_file, fd::ModelFormat::PADDLE);
runtime_option.UseOrtBackend();
runtime_option.SetCpuThreadNum(12);
// **** GPU ****
// To use GPU, use the following commented code
// runtime_option.UseGpu(0);
// init runtime
std::unique_ptr<fd::Runtime> runtime =
std::unique_ptr<fd::Runtime>(new fd::Runtime());

47
examples/runtime/python/infer_onnx_onnxruntime.py Normal file
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@@ -0,0 +1,47 @@
# 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.
import fastdeploy as fd
from fastdeploy import ModelFormat
import numpy as np
# 下载模型并解压
model_url = "https://bj.bcebos.com/fastdeploy/models/mobilenetv2.onnx"
fd.download(model_url, path=".")
option = fd.RuntimeOption()
option.set_model_path("mobilenetv2.onnx", model_format=ModelFormat.ONNX)
# **** CPU 配置 ****
option.use_cpu()
option.use_ort_backend()
option.set_cpu_thread_num(12)
# **** GPU 配置 ****
# 如需使用GPU，使用如下注释代码
# option.use_gpu(0)
# 初始化构造runtime
runtime = fd.Runtime(option)
# 获取模型输入名
input_name = runtime.get_input_info(0).name
# 构造随机数据进行推理
results = runtime.infer({
input_name: np.random.rand(1, 3, 224, 224).astype("float32")
})
print(results[0].shape)