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Ubuntu 16.04上源码编译和安装pytorch教程，并编写C Demo CMakeLists.txt

發布時間：2023/12/29 Ubuntu 28 豆豆

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tutorial to compile and use pytorch on ubuntu 16.04

PyTorch for Python

install pytorch from anaconda

conda info --envsconda activate py35 # newest version# 1.1.0 pytorch/0.3.0 torchvisionconda install pytorch torchvision cudatoolkit=9.0 -c pytorch # old version [NOT]# 0.4.1 pytorch/0.2.1 torchvisionconda 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_0torchvision pytorch/linux-64::torchvision-0.3.0-py35_cu9.0.176_1

download from channel pytorch will cost much time!

下載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-64conda 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，用清華源代替。

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==3.7conda activate torch conda install -y pytorch torchvisionconda 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_0torchvision anaconda/cloud/pytorch/linux-64::torchvision-0.3.0-py35_cu9.0.176_1

test pytorch

import torchprint(torch.__version__)'1.1.0'

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 1git clone --recursive https://github.com/pytorch/pytorchcd pytorch # method 2, if you are updating an existing checkoutgit clone https://github.com/pytorch/pytorchcd pytorch git submodule syncgit submodule update --init --recursive

check tags

git tag -l v0.4.0v0.4.1v1.0.0v1.0.1v1.0rc0v1.0rc1v1.1.0

now compile

git checkout v1.1.0 # method 1: offical build will generate lots of errors#python setup.py install # method 2: normal makemkdir 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 : 3.5.1CMake command : /usr/bin/cmakeSystem : LinuxC compiler : /usr/bin/c C compiler id : GNUC compiler version : 5.4.0BLAS : MKLCXX 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-mathBuild type : ReleaseCompile 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=1CMAKE_PREFIX_PATH : CMAKE_INSTALL_PREFIX : /usr/local TORCH_VERSION : 1.1.0CAFFE2_VERSION : 1.1.0BUILD_CAFFE2_MOBILE : ONBUILD_ATEN_ONLY : OFFBUILD_BINARY : OFFBUILD_CUSTOM_PROTOBUF : ONLink local protobuf : ONBUILD_DOCS : OFFBUILD_PYTHON : OFFBUILD_CAFFE2_OPS : ONBUILD_SHARED_LIBS : ONBUILD_TEST : OFFINTERN_BUILD_MOBILE : USE_ASAN : OFFUSE_CUDA : ONCUDA static link : OFFUSE_CUDNN : ONCUDA version : 9.2cuDNN version : 7.1.4CUDA root directory : /usr/local/cudaCUDA library : /usr/local/cuda/lib64/stubs/libcuda.socudart library : /usr/local/cuda/lib64/libcudart.socublas library : /usr/local/cuda/lib64/libcublas.socufft library : /usr/local/cuda/lib64/libcufft.socurand library : /usr/local/cuda/lib64/libcurand.socuDNN library : /usr/local/cuda/lib64/libcudnn.sonvrtc : /usr/local/cuda/lib64/libnvrtc.soCUDA include path : /usr/local/cuda/includeNVCC executable : /usr/local/cuda/bin/nvccCUDA host compiler : /usr/bin/ccUSE_TENSORRT : OFFUSE_ROCM : OFFUSE_EIGEN_FOR_BLAS : ONUSE_FBGEMM : OFFUSE_FFMPEG : OFFUSE_GFLAGS : OFFUSE_GLOG : OFFUSE_LEVELDB : OFFUSE_LITE_PROTO : OFFUSE_LMDB : OFFUSE_METAL : OFFUSE_MKL : OFFUSE_MKLDNN : OFFUSE_NCCL : ONUSE_SYSTEM_NCCL : OFFUSE_NNPACK : ONUSE_NUMPY : ONUSE_OBSERVERS : ONUSE_OPENCL : OFFUSE_OPENCV : OFFUSE_OPENMP : ONUSE_TBB : OFFUSE_PROF : OFFUSE_QNNPACK : ONUSE_REDIS : OFFUSE_ROCKSDB : OFFUSE_ZMQ : OFFUSE_DISTRIBUTED : ONUSE_MPI : ONUSE_GLOO : ONUSE_GLOO_IBVERBS : OFFNAMEDTENSOR_ENABLED : OFFPublic Dependencies : Threads::ThreadsPrivate 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;dlConfiguring done

install pytorch

now compile and install

make -j8sudo 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

Build simple c example-cpp using Libtorch fails on arm with undefined reference to c10::Error::Error

@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

issues-linking-with-libtorch-c-11-abi

@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.3.1.0linux-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 occursee 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/cudevlinked by target "opencv_cudev" in directory /home/kezunlin/program/opencv-3.1.0/modules/cudevlinked by target "opencv_test_cudev" in directory /home/kezunlin/program/opencv-3.1.0/modules/cudev/test

solutions:

WITH_CUDA OFFWITH_VTK OFFWITH_TIFF OFFBUILD_PERF_TESTS OFF

for python2, use default /usr/bin/python2.7

for python3, NOT USE anaconda version

編譯的過程中，盡量避免使用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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