Ubuntu 16.04上源碼編譯和安裝pytorch教程，並編寫C++ Demo CMakeLists.txt
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tutorial to compile and use pytorch on ubuntu 16.04python
PyTorch for Python
install pytorch from anaconda
conda info --envs conda activate py35 # newest version # 1.1.0 pytorch/0.3.0 torchvision conda install pytorch torchvision cudatoolkit=9.0 -c pytorch # old version [NOT] # 0.4.1 pytorch/0.2.1 torchvision conda install pytorch=0.4.1 cuda90 -c pytorch
outputlinux
The following NEW packages will be INSTALLED: pytorch pytorch/linux-64::pytorch-1.1.0-py3.5_cuda9.0.176_cudnn7.5.1_0 torchvision pytorch/linux-64::torchvision-0.3.0-py35_cu9.0.176_1
download from channelpytorchwill cost much time!
下載pytorch/linux-64::pytorch-1.1.0-py3.5_cuda9.0.176_cudnn7.5.1_0速度很是慢！
install pytorch from tsinghua
add tsinghua pytorch channels
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/ # for legacy win-64 conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/peterjc123/ conda config --set show_channel_urls yes
使用anaconda官方pytorch源很是慢，用清華源代替。
see tsinghua anaconda
cat ～/.condarcios
channels: - https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud/pytorch/ - defaults
install pytorch from tsinghua
conda create --name torch python==3.7 conda activate torch conda install -y pytorch torchvision conda install -y scikit-learn scikit-image pandas matplotlib pillow opencv
The following NEW packages will be INSTALLED:c++
pytorch anaconda/cloud/pytorch/linux-64::pytorch-1.1.0-py3.5_cuda9.0.176_cudnn7.5.1_0 torchvision anaconda/cloud/pytorch/linux-64::torchvision-0.3.0-py35_cu9.0.176_1
test pytorch
import torch print(torch.__version__) '1.1.0'
orgit
python -c 'import torch; print(torch.cuda.is_available())' True
pre-trained models
pre-trained model saved to /home/kezunlin/.cache/torch/checkpoints/github
Downloading: "https://download.pytorch.org/models/shufflenetv2_x0.5-f707e7126e.pth" to /home/kezunlin/.cache/torch/checkpoints/shufflenetv2_x0.5-f707e7126e.pth
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PyTorch for C++
download LibTorch
download from LibTorch
compile from source
compile pytorch
# method 1 git clone --recursive https://github.com/pytorch/pytorch cd pytorch # method 2, if you are updating an existing checkout git clone https://github.com/pytorch/pytorch cd pytorch git submodule sync git submodule update --init --recursive
check tags
git tag -l v0.4.0 v0.4.1 v1.0.0 v1.0.1 v1.0rc0 v1.0rc1 v1.1.0
now compile
git checkout v1.1.0 # method 1: offical build will generate lots of errors #python setup.py install # method 2: normal make mkdir build && cd build && cmake-gui ..
with configs
BUILD_PYTHON OFF
be sure to usestable version 1.1.0from here instead of latest version 20190724 (unstable version 1.2.0)
because error will occurs when load models.
- for 1.1.0:
std::shared_ptr<torch::jit::script::Module> module = torch::jit::load("./model.pt");
- for latest 1.2.0
torch::jit::script::Module module = torch::jit::load("./model.pt");
configure output
******** Summary ********
General:
CMake version : 3.5.1
CMake command : /usr/bin/cmake
System : Linux
C++ compiler : /usr/bin/c++
C++ compiler id : GNU
C++ compiler version : 5.4.0
BLAS : MKL
CXX flags : -fvisibility-inlines-hidden -fopenmp -O2 -fPIC -Wno-narrowing -Wall -Wextra -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math
Build type : Release
Compile definitions : ONNX_ML=1;ONNX_NAMESPACE=onnx_torch;USE_GCC_ATOMICS=1;HAVE_MMAP=1;_FILE_OFFSET_BITS=64;HAVE_SHM_OPEN=1;HAVE_SHM_UNLINK=1;HAVE_MALLOC_USABLE_SIZE=1
CMAKE_PREFIX_PATH :
CMAKE_INSTALL_PREFIX : /usr/local
TORCH_VERSION : 1.1.0
CAFFE2_VERSION : 1.1.0
BUILD_CAFFE2_MOBILE : ON
BUILD_ATEN_ONLY : OFF
BUILD_BINARY : OFF
BUILD_CUSTOM_PROTOBUF : ON
Link local protobuf : ON
BUILD_DOCS : OFF
BUILD_PYTHON : OFF
BUILD_CAFFE2_OPS : ON
BUILD_SHARED_LIBS : ON
BUILD_TEST : OFF
INTERN_BUILD_MOBILE :
USE_ASAN : OFF
USE_CUDA : ON
CUDA static link : OFF
USE_CUDNN : ON
CUDA version : 9.2
cuDNN version : 7.1.4
CUDA root directory : /usr/local/cuda
CUDA library : /usr/local/cuda/lib64/stubs/libcuda.so
cudart library : /usr/local/cuda/lib64/libcudart.so
cublas library : /usr/local/cuda/lib64/libcublas.so
cufft library : /usr/local/cuda/lib64/libcufft.so
curand library : /usr/local/cuda/lib64/libcurand.so
cuDNN library : /usr/local/cuda/lib64/libcudnn.so
nvrtc : /usr/local/cuda/lib64/libnvrtc.so
CUDA include path : /usr/local/cuda/include
NVCC executable : /usr/local/cuda/bin/nvcc
CUDA host compiler : /usr/bin/cc
USE_TENSORRT : OFF
USE_ROCM : OFF
USE_EIGEN_FOR_BLAS : ON
USE_FBGEMM : OFF
USE_FFMPEG : OFF
USE_GFLAGS : OFF
USE_GLOG : OFF
USE_LEVELDB : OFF
USE_LITE_PROTO : OFF
USE_LMDB : OFF
USE_METAL : OFF
USE_MKL : OFF
USE_MKLDNN : OFF
USE_NCCL : ON
USE_SYSTEM_NCCL : OFF
USE_NNPACK : ON
USE_NUMPY : ON
USE_OBSERVERS : ON
USE_OPENCL : OFF
USE_OPENCV : OFF
USE_OPENMP : ON
USE_TBB : OFF
USE_PROF : OFF
USE_QNNPACK : ON
USE_REDIS : OFF
USE_ROCKSDB : OFF
USE_ZMQ : OFF
USE_DISTRIBUTED : ON
USE_MPI : ON
USE_GLOO : ON
USE_GLOO_IBVERBS : OFF
NAMEDTENSOR_ENABLED : OFF
Public Dependencies : Threads::Threads
Private Dependencies : qnnpack;nnpack;cpuinfo;/usr/lib/x86_64-linux-gnu/libnuma.so;fp16;/usr/lib/openmpi/lib/libmpi_cxx.so;/usr/lib/openmpi/lib/libmpi.so;gloo;aten_op_header_gen;foxi_loader;rt;gcc_s;gcc;dl
Configuring done
install pytorch
now compile and install
make -j8 sudo make install
output
Install the project... -- Install configuration: "Release" -- Old export file "/usr/local/share/cmake/Caffe2/Caffe2Targets.cmake" will be replaced. Removing files [/usr/local/share/cmake/Caffe2/Caffe2Targets-release.cmake]. -- Set runtime path of "/usr/local/bin/protoc" to "$ORIGIN" -- Old export file "/usr/local/share/cmake/Gloo/GlooTargets.cmake" will be replaced. Removing files [/usr/local/share/cmake/Gloo/GlooTargets-release.cmake]. -- Set runtime path of "/usr/local/lib/libonnxifi_dummy.so" to "$ORIGIN" -- Set runtime path of "/usr/local/lib/libonnxifi.so" to "$ORIGIN" -- Set runtime path of "/usr/local/lib/libfoxi_dummy.so" to "$ORIGIN" -- Set runtime path of "/usr/local/lib/libfoxi.so" to "$ORIGIN" -- Set runtime path of "/usr/local/lib/libc10.so" to "$ORIGIN" -- Set runtime path of "/usr/local/lib/libc10_cuda.so" to "$ORIGIN:/usr/local/cuda/lib64" -- Set runtime path of "/usr/local/lib/libthnvrtc.so" to "$ORIGIN:/usr/local/cuda/lib64/stubs:/usr/local/cuda/lib64" -- Set runtime path of "/usr/local/lib/libtorch.so" to "$ORIGIN:/usr/local/cuda/lib64:/usr/lib/openmpi/lib" -- Set runtime path of "/usr/local/lib/libcaffe2_detectron_ops_gpu.so" to "$ORIGIN:/usr/local/cuda/lib64" -- Set runtime path of "/usr/local/lib/libcaffe2_observers.so" to "$ORIGIN:/usr/local/cuda/lib64"
pytorch 1.1.0
compile and install will cost more than 2 hours
lib install to/usr/local/lib/libtorch.so
cmake install to/usr/local/share/cmake/Torch
C++ example
load pytorch model in c++
see load pytorch model in c++
cpp
#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().
std::shared_ptr<torch::jit::script::Module> module = torch::jit::load(argv[1]);
assert(module != nullptr);
std::cout << "ok\n";
// Create a vector of inputs.
std::vector<torch::jit::IValue> inputs;
inputs.push_back(torch::ones({1, 3, 224, 224}));
// 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)
# /usr/local/share/cmake/Torch
find_package(Torch REQUIRED)
MESSAGE( [Main] " TORCH_INCLUDE_DIRS = ${TORCH_INCLUDE_DIRS}")
MESSAGE( [Main] " TORCH_LIBRARIES = ${TORCH_LIBRARIES}")
include_directories(${TORCH_INCLUDE_DIRS})
add_executable(example-app example-app.cpp)
target_link_libraries(example-app "${TORCH_LIBRARIES}")
set_property(TARGET example-app PROPERTY CXX_STANDARD 11)
output
Found torch: /usr/local/lib/libtorch.so [Main] TORCH_INCLUDE_DIRS = /usr/local/include;/usr/local/include/torch/csrc/api/include [Main] TORCH_LIBRARIES = torch;torch_library;/usr/local/lib/libc10.so;/usr/local/cuda/lib64/stubs/libcuda.so;/usr/local/cuda/lib64/libnvrtc.so;/usr/local/cuda/lib64/libnvToolsExt.so;/usr/local/cuda/lib64/libcudart.so;/usr/local/lib/libc10_cuda.so [TOLOWER] ALGORITHM_TARGET = algorithm
make
mkdir build cd build && cmake-gui .. make -j8
setTorch_DIRto/home/kezunlin/program/libtorch/share/cmake/Torch
auto-setTorch_DIRto/usr/local/share/cmake/Torch
run
./example-app model.pt -0.2698 -0.0381 0.4023 -0.3010 -0.0448
errors and solutions
compile errors with libtorch
@soumith
You might be building libtorch with a compiler that is incompatible with the compiler building your final app.
For example, you built libtorch with gcc 4.9.2 and your final app with gcc 5.1, and the C++ ABI between both of them is not the same, so you are seeing linker errors like these
@christianperone
if ("${CMAKE_CXX_COMPILER_ID}" STREQUAL "GNU")
set(TORCH_CXX_FLAGS "-D_GLIBCXX_USE_CXX11_ABI=0")
endif()
Which forces GCC to use the old C++11 ABI.@ smth
we have that flag set because we build with gcc 4.9.x, which only has the old ABI.
In GCC 5.1, the ABI for std::string was changed, and binaries compiling with gcc >= 5.1 are not ABI-compatible with binaries build with gcc < 5.1 (like pytorch) unless you set that flag.
resons and solutions
- Reasons: LibTorch compiled with GCC-4.9.X (only has the old ABI), and binaries compiling with gcc >= 5.1 are not ABI-compatible
- Solution: compile pytorch from source instead of using
LibTrochdownloaded from the website.
runtime errors with pytorch
errors
/usr/local/lib/libopencv_imgcodecs.so.3.1.0: undefined reference to `TIFFReadRGBAStrip@LIBTIFF_4.0'
which means opencv link against libtiff 4.0.6
ldd check
ldd /usr/local/lib/libopencv_imgcodecs.so.3.1.0
linux-vdso.so.1 => (0x00007ffc92ffc000)
libopencv_imgproc.so.3.1 => /usr/local/lib/libopencv_imgproc.so.3.1 (0x00007f32afbca000)
libjpeg.so.8 => /usr/local/lib/libjpeg.so.8 (0x00007f32af948000)
libpng12.so.0 => /lib/x86_64-linux-gnu/libpng12.so.0 (0x00007f32af723000)
libtiff.so.5 => /usr/lib/x86_64-linux-gnu/libtiff.so.5 (0x00007f32af4ae000)
when compileopencv-3.1.0, cmake find/usr/lib/x86_64-linux-gnu/libtiff.so.5
locate libtiff
locate libtiff.so /home/kezunlin/anaconda3/envs/py35/lib/libtiff.so /home/kezunlin/anaconda3/envs/py35/lib/libtiff.so.5 /home/kezunlin/anaconda3/envs/py35/lib/libtiff.so.5.4.0 /home/kezunlin/anaconda3/lib/libtiff.so /home/kezunlin/anaconda3/lib/libtiff.so.5 /home/kezunlin/anaconda3/lib/libtiff.so.5.4.0 /home/kezunlin/anaconda3/pkgs/libtiff-4.0.10-h2733197_2/lib/libtiff.so /home/kezunlin/anaconda3/pkgs/libtiff-4.0.10-h2733197_2/lib/libtiff.so.5 /home/kezunlin/anaconda3/pkgs/libtiff-4.0.10-h2733197_2/lib/libtiff.so.5.4.0 /opt/MATLAB/R2016b/bin/glnxa64/libtiff.so.5 /opt/MATLAB/R2016b/bin/glnxa64/libtiff.so.5.0.5 /usr/lib/x86_64-linux-gnu/libtiff.so /usr/lib/x86_64-linux-gnu/libtiff.so.5 /usr/lib/x86_64-linux-gnu/libtiff.so.5.2.4
It seems that my OpenCV was compiled against libtiff 4, but I have libtiff 5, how to solve this problem?
re-compile opencv-3.1.0 again, new errors occur
see here
CMake Error: The following variables are used in this project, but they are set to NOTFOUND.
Please set them or make sure they are set and tested correctly in the CMake files:
CUDA_nppi_LIBRARY (ADVANCED)
linked by target "opencv_cudev" in directory /home/kezunlin/program/opencv-3.1.0/modules/cudev
linked by target "opencv_cudev" in directory /home/kezunlin/program/opencv-3.1.0/modules/cudev
linked by target "opencv_test_cudev" in directory /home/kezunlin/program/opencv-3.1.0/modules/cudev/test
solutions:
WITH_CUDA OFF WITH_VTK OFF WITH_TIFF OFF BUILD_PERF_TESTS OFF
for python2, use default/usr/bin/python2.7
for python3, NOT USEanacondaversion
編譯的過程當中，儘可能避免使用anaconda目錄下的lib
install libwebp
sudo apt-get -y install libwebp-dev
Reference
- pytorch
- pytorch github
- deep_learning_60min_blitz
- pytorch-tutorial
- pytorch notebooks
- pytorch-beginner
- pytorch cppdocs
History
- 20190626: created.
Copyright
- Post author: kezunlin
- Post link: https://kezunlin.me/post/54e7a3d8/
- Copyright Notice: All articles in this blog are licensed under CC BY-NC-SA 3.0 unless stating additionally.
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