Ubuntu 16.04上源码编译和安装pytorch教程，并编写C++ Demo CMakeLists.txt | tutorial to compile and use pytorch on ubuntu 16.04

2023-08-02 20:27:58

本文首发于个人博客https://kezunlin.me/post/54e7a3d8/，欢迎阅读最新内容！

tutorial to compile and use pytorch on ubuntu 16.04

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

output

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 channel pytorch will cost much time!

下载pytorch/linux-64::pytorch-1.1.0-py3.5_cuda9.0.176_cudnn7.5.1_0速度非常慢！

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源非常慢，用清华源代替。

see tsinghua anaconda

cat ～/.condarc

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:

  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'

or

python -c 'import torch; print(torch.cuda.is_available())'

True

pre-trained models

pre-trained model saved to /home/kezunlin/.cache/torch/checkpoints/

Downloading: "https://download.pytorch.org/models/shufflenetv2_x0.5-f707e7126e.pth" to /home/kezunlin/.cache/torch/checkpoints/shufflenetv2_x0.5-f707e7126e.pth

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 use stable version 1.1.0 from 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

set Torch_DIR to /home/kezunlin/program/libtorch/share/cmake/Torch

auto-set Torch_DIR to /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 LibTroch downloaded 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 compile opencv-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 USE anaconda version

编译的过程中，尽量避免使用anaconda目录下的lib

install libwebp

sudo apt-get -y install libwebp-dev

Reference

History

  • 20190626: created.

Copyright

上一篇：dom4j 通过 org.dom4j.DocumentFactory 设置命名空间来支持 带namespace 的 xpath


下一篇：ubuntu 16.04上源码编译和安装cgal并编写CMakeLists.txt | compile and install cgal on ubuntu 16.04