libtorch编译C++版本
一. 下载pytorch源码
git clone https://github.com/pytorch/pytorch.git
cd pytorch
git submodule sync
git submodule update --init --recursive
下面是上传至百度网盘的源码，pytorch-1.8.0
链接：https://pan.baidu.com/s/1lxh7ueDsrnHqLaf5_oP2gg 提取码：8kp8
二. 编译
1.安装依赖
# first: 安装cuda与cudnn，下载cuda10.0对应.run文件与对应的cudnn7.6.5
sh cuda_10.0.130_410.48_linux.run --no-opengl-libs
ldconfig /usr/local/cuda-10.0/lib64
tar -xvzf cudnn-10.0-linux-x64-v7.6.5.32.tgz
cp cuda/include/* /usr/local/cuda-10.0/include/
cp cuda/lib64/* /usr/local/cuda-10.0/lib64/
chmod +x /usr/local/cuda-10.0/include/cudnn.h
chmod +x /usr/local/cuda-10.0/lib64/libcudnn*
nvcc -V
# second:安装ｇｃｃ ｇ＋＋
apt install apt install software-properties-common
add-apt-repository ppa:ubuntu-toolchain-r/test
apt-get update
apt-get install gcc-7
apt-get install g++-7
update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-7 100
update-alternatives --config gcc
update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-7 100
update-alternatives --config g++
gcc --version
g++ --version
2.编译libtorch
cd pytorch
mkdir release
cd release
cmake -D CMAKE_BUILD_TYPE=RELEASE -D CMAKE_INSTALL_PREFIX=/opt/libtorch -D BUILD_CAFFE2_MOBILE=OFF -D BUILD_PYTHON=OFF -D BUILD_CAFFE2_OPS=OFF -D BUILD_TEST=OFF -D USE_CUDA=ON -D USE_CUDNN=ON -D USE_OPENCV=ON -D USE_TBB=OFF ..
make -j${nproc}
make install
三. 使用
python training
import torch
import io
class MyModule(torch.nn.Module):
def forward(self, x):
return x + 10
m = torch.jit.script(MyModule())
# Save to file
torch.jit.save(m, 'scriptmodule.pt')
# This line is equivalent to the previous
m.save("scriptmodule.pt")
# Save to io.BytesIO buffer
buffer = io.BytesIO()
torch.jit.save(m, buffer)
# Save with extra files
extra_files = {'foo.txt': b'bar'}
torch.jit.save(m, 'scriptmodule.pt', _extra_files=extra_files)
c++ inference
#include <torch/script.h> // One-stop header.
#include <iostream>
#include <memory>
int main(int argc, const char* argv[]) {
if (argc != 2) {
std::cerr << "usage: example-app <path-to-exported-script-module>\n";
return -1;
}
// Deserialize the ScriptModule from a file using torch::jit::load().
// libtorch verison 1.7.0
torch::jit::script::Module module = torch::jit::load(argv[1]);
std::cout << "ok\n";
//设置Device
torch::DeviceType device_type; //设置Device类型
device_type = torch::kCUDA; //torch::kCUDA and torch::kCPU
torch::Device device(device_type, 0);
//把模型和数据都送到Device中去(数据和模型必须都在同一个device,结果也是)
module.to(device);
// Create a vector of inputs.
std::vector<torch::jit::IValue> inputs;
inputs.push_back(torch::ones({1, 3, 224, 224}).to(device));
// Execute the model and turn its output into a tensor.
at::Tensor output = module.forward(inputs).toTensor();
std::cout << output.slice(/*dim=*/1, /*start=*/0, /*end=*/5) << '\n';
}
CMakeLists.txt
cmake_minimum_required(VERSION 3.0 FATAL_ERROR)
project(custom_ops)
set(CMAKE_CXX_STANDARD 11)
set(Torch_DIR /home/xxx/下载/libtorch/share/cmake/Torch) #TorchConfig.cmake上级目录
find_package(Torch REQUIRED)
set(OpenCV_DIR /opt/opencv440/lib/cmake/opencv4/) # OpenCVConfig.cmake上级目录
find_package(OpenCV REQUIRED)
include_directories(${OpenCV_LIBS})
include_directories(${TORCH_INCLUDE_DIRS})
add_executable(example-app example-app.cpp)
target_link_libraries(example-app ${OpenCV_LIBS} ${TORCH_LIBRARIES}) # 加入opencv/libTorch的库文件路径
