这里主要是develop开发版的编译与安装。如果不是开发版，安装是非常容易的，anaconda已经做得非常到位了，可参考该帖的后面部分,https://blog.csdn.net/tanmx219/article/details/82831964
在自己编译的情况下，和官网相比，我每次重新编译总是缺些什么，所以决定记录一下，
https://github.com/pytorch/pytorchhttps://m.oldpan.me/archives/pytorch-build-simple-instruction
目前是pytorch v1.0 ------------------------------------------------------------------------------------
conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing pybind11
conda install cudnn (cudatoolkit: 9.2-0+cudnn:7.2.1-cuda9.2_0)
conda install ninja (optional, warning: C++ will not be compiled incrementally)
conda install -c pytorch magma-cuda92 (optional, Add LAPACK support for the GPU if needed)
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
如果不需要使用cuda的话，这里还要加上一句：export NO_CUDA=1
python setup.py install
对于开发者模式，可以使用
python setup.py build develop------------------------------------------------------------------------------------
源码安装的Pytorch，卸载需要执行：
pip uninstall torch
python setup.py clean------------------------------------------------------------------------------------
注意git clone之前确保已经安装git，如果没有安装，sudo apt-get install git-all安装一下。
碰到的问题
Linux的问题总是千奇百怪，每次都不一样，也记录一下
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Problem 1:
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Cuda的安装，网上讲的安装方法非常多，其中包括一种比较有意思的，https://askubuntu.com/questions/1028830/how-do-i-install-cuda-on-ubuntu-18-04
-----how to install-----
sudo add-apt-repository ppa:graphics-drivers/ppa
sudo apt update
sudo ubuntu-drivers autoinstall
reboot
sudo apt install nvidia-cuda-toolkit gcc-6
nvcc --version
-----replace------
sudo sh cuda_9.1.85_387.26_linux.run (--override)
to uninstall the NVIDIA Driver, run nvidia-uninstall
-----how to remove-----
sudo apt-get remove --purge nvidia-*
sudo apt-get remove --purge libnvidia-*
这个方法是通过PPA proprietary graphics driver team 开发的包安装，可参考：https://launchpad.net/~graphics-drivers/+archive/ubuntu/ppa 这里有其团队的信息，https://launchpad.net/~graphics-drivers 不过写这东东时我也是第一次用这种方式安装，检查了一下，貌似通过这种形式安装的都是最新版本，还没看到过详细文档。 官网上提到： Current long-lived branch release: `nvidia-410` (410.66) Dropped support for Fermi series (https://nvidia.custhelp.com/app/answers/detail/a_id/4656) Old long-lived branch release: `nvidia-390` (390.87) 默认是nvidia-410, 总之，通过这种方式会安装很多包，这里装了多少多余的东西俺就不知道了。
--------------------
那假设我就是想安装nvidia-390怎么办呢？还是老办法保险： sudo apt-get install nvidia-driver-390 sudo apt-get install nvidia-driver-390-dev
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Problem 2:
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CMake Error at cmake/public/cuda.cmake:318 (message): CUDA 9.1 is not compatible with std::tuple from GCC version >= 6. Please upgrade to CUDA 9.2 or use the following option to use another version (for example): -DCUDA_HOST_COMPILER=/usr/bin/gcc-5 ..... -- Configuring incomplete, errors occurred! See also "/home/matthew/dev/pytorch/build/CMakeFiles/CMakeOutput.log". See also "/home/matthew/dev/pytorch/build/CMakeFiles/CMakeError.log". Failed to run 'bash ../tools/build_pytorch_libs.sh --use-cuda --use-fbgemm --use-nnpack --use-mkldnn --use-qnnpack caffe2'
网上有不少解决办法，参考：https://github.com/pytorch/pytorch/issues/14152
Solution 1:
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版本不对，大概是先卸载再安装，参考：
step1: remove the previous cuda
sudo apt-get --purge remove nvidia-cuda-toolkit
conda remove cudnn (if has installed a different version needed)
step2: install cudnn (this will install cudnn7_cuda9.2）
conda install cudnnhttps://blog.csdn.net/tanmx219/article/details/86210023https://github.com/pytorch/pytorch/issues/14152
=========================================================================
Problem 3:
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$ python setup.py build develop Building wheel torch-1.1.0a0+964732f running build running build_deps setup.py::build_deps::run() + SYNC_COMMAND=cp ...... -- USE_GLOO_IBVERBS : OFF -- Public Dependencies : Threads::Threads;caffe2::mkl;caffe2::mkldnn -- Private Dependencies : qnnpack;nnpack;cpuinfo;fbgemm;fp16;gloo;aten_op_header_gen;onnxifi_loader;rt;gcc_s;gcc;dl -- Configuring done CMake Error in caffe2/CMakeLists.txt: Imported target "caffe2::mkl" includes non-existent path "/home/matthew/anaconda3/envs/torchdev/include" in its INTERFACE_INCLUDE_DIRECTORIES. Possible reasons include: * The path was deleted, renamed, or moved to another location. * An install or uninstall procedure did not complete successfully. * The installation package was faulty and references files it does not provide.
-- Generating done -- Build files have been written to: /home/matthew/dev/pytorch/build Failed to run 'bash ../tools/build_pytorch_libs.sh --use-fbgemm --use-nnpack --use-mkldnn --use-qnnpack caffe2'
解决办法 ---------------------------------------------------------------------------------------------------------------------------------
这个问题是因为上一次编译没编译完，这次接着编译，但命令路径变了，所以必须清空重来 python setup.py clean python setup.py build develop
=========================================================================
Problem 3:
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The Nouveau kernel driver is currently in use by your system. This driver is incompatible with the NVIDIA driver,
参考：https://tutorials.technology/tutorials/85-How-to-remove-Nouveau-kernel-driver-Nvidia-install-error.html How to remove Nouveau kernel driver (fix Nvidia install error)
sudo apt-get remove nvidia*
sudo apt autoremove
sudo apt-get install dkms build-essential linux-headers-generic
sudo vim /etc/modprobe.d/blacklist.conf
blacklist nouveau
blacklist lbm-nouveau
options nouveau modeset=0
alias nouveau off
alias lbm-nouveau off
echo options nouveau modeset=0 | sudo tee -a /etc/modprobe.d/nouveau-kms.conf
sudo update-initramfs -u
rebootsudo apt-get --purge remove xserver-xorg-video-nouveau
=========================================================================
Problem 4:
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-- Caffe2: Cannot find glog automatically. Using legacy find. -- Could NOT find glog (missing: GLOG_INCLUDE_DIR GLOG_LIBRARY) CMake Warning at cmake/public/glog.cmake:66 (message): Caffe2: glog cannot be found. Depending on whether you are building Caffe2 or a Caffe2 dependent library, the next warning / error will give you more info. Call Stack (most recent call first): cmake/Dependencies.cmake:291 (include) CMakeLists.txt:219 (include)
===>>>
$ sudo apt-get install libgflags-dev libgoogle-glog-dev
=========================================================================
Problem 5:
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-- Found CUDA: /usr/local/cuda (found version "10.0") -- Caffe2: CUDA detected: 10.0 -- Caffe2: CUDA nvcc is: /usr/local/cuda/bin/nvcc -- Caffe2: CUDA toolkit directory: /usr/local/cuda -- Caffe2: Header version is: 10.0 -- Could NOT find CUDNN (missing: CUDNN_INCLUDE_DIR CUDNN_LIBRARY) CMake Warning at cmake/public/cuda.cmake:101 (message): Caffe2: Cannot find cuDNN library. Turning the option off Call Stack (most recent call first): cmake/Dependencies.cmake:685 (include) CMakeLists.txt:219 (include)
===>>>
安装了cuda+cudnn后这个就会消失
