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% Pytorch.tex
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%
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% AI Documentation
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% Copyright (C) 2022, 2023, Jeff Moe
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%
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% This document is licensed under the Creative Commons Attribution 4.0
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% International Public License (CC BY-SA 4.0) by Jeff Moe.
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%
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\section{Installation}
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Pytorch gets installed via pip.
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Often it is better to install Pytorch first ``by hand'', and not just use
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it as installed via requirements.txt, as that may not have the exact version
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that is best for the hardware at hand.
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Take a look first what version of Python and Pytorch the project is most
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``comfortable'' with by looking at files like setup.py, requirements.txt
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and it's other iterations, .yaml files, Docker junk maybe sitting around,
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etc. Pain can be avoided by using the version of Python the project is
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written for, unless you want to port to a newer version or something.
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If it is Python 2.x, it needs porting or finding of a replacement.
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Also, same for Pytorch. See what version the project works best with.
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Sometimes a later version will work fine as well. It isn't the worst idea to
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just use the latest Pytorch stable release and see how it goes...
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The Pytorch website has a nice little interface for helping you pick the
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correct pip command, depending what hardware available and which Pytorch
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version needed. Site:
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* \url{https://pytorch.org/get-started/locally/}
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The default stable release, currently 2.0.1, with CUDA 11.7 is installed
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thusly:
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\begin{minted}{sh}
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pip3 install torch torchvision torchaudio
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\end{minted}
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With Nvidia A16, A40, and A100, these worked with Pytorch stable and
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CUDA 11.8:
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\begin{minted}{sh}
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
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\end{minted}
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If a recent AMD GPU is available that has ROCm support, Pytorch
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is installed thusly (untested; available AMD GPU was too old):
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\begin{minted}{sh}
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm5.4.2
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\end{minted}
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It may be possible to use a CPU, but will generally suck. To install:
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\begin{minted}{sh}
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pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cpu
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\end{minted}
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If CUDA 12.1 is needed, Pytorch nightly is required:
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\begin{minted}{sh}
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pip3 install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu121
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\end{minted}
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Other combinations are available at the site.
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Commands for older versions are avaiable here:
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* https://pytorch.org/get-started/previous-versions/
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XXX
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Below will likely mess up your machine.
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Lots of noise below, perhaps rebuilding pytorch with nvidia and older
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GCC toolchain (?). Generally not needed....
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\begin{minted}{sh}
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for i in `apt-cache search cuda|sort -V| grep cuda | grep 11-8 | grep -v -e cuda-demo-suite-11-8 -e cuda-documentation-11-8 -e cuda-gdb-11-8 -e cuda-gdb-src-11-8 | cut -f 1 -d " " ` ; do echo $i ; apt install $i ; echo ;done
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###################################################
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# build pytorch
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# need non-free to install intel-mkl
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apt install libzstd-dev libnuma-dev clang gcc-11 libfftw3-dev libopenblas64-dev libopenblas-dev libblis-dev libblis64-dev libclblast-dev libxnnpack-dev libopenblas-openmp-dev libopenblas64-openmp-dev libopenmpi-dev libcudnn8-dev intel-mkl-full nvidia-cuda-toolkit nvidia-cuda-toolkit-gcc
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sudo apt install `apt-cache search opencv|grep -i opencv |sort -V|grep dev |cut -f 1 -d " "`
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libmagma-dev libarmnn-dev libonnx-dev
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sudo apt install `apt-cache search lapack|grep -- -dev | cut -f 1 -d " " | grep -v ghc`
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libmimalloc-dev
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sudo apt install `apt-cache search vulkan | grep -- -dev | grep -i vulkan | cut -f 1 -d " "`
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glslc libshaderc-dev
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libideep-dev
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# using virtualenv from sd web
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git clone pytorch
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cd pytorch
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git checkout XXX
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git submodule sync
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git submodule update --init --recursive
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export CMAKE_CUDA_ARCHITECTURES=native
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export CPUINFO_BUILD_TOOLS=1
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export BUILD_BINARY=1
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export TORCH_USE_CUDA_DSA=1
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export USE_CUDA=1
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export USE_OPENCV=1
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export USE_FFMPEG=1
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export USE_ZSTD=1
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-DCMAKE_CUDA_COMPILER:PATH=/usr/local/cuda/bin/nvcc
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#python setup.py develop
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mkdir build
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cd build/
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cmake ..
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ccmake ..
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###################################################
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sudo update-alternatives --remove-all gcc
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sudo update-alternatives --remove-all g++
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sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-11 10
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sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-12 20
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sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-11 10
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sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-12 20
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sudo update-alternatives --install /usr/bin/cc cc /usr/bin/gcc 30
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sudo update-alternatives --set cc /usr/bin/gcc
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sudo update-alternatives --install /usr/bin/c++ c++ /usr/bin/g++ 30
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sudo update-alternatives --set c++ /usr/bin/g++
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sudo update-alternatives --config gcc
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sudo update-alternatives --config g++
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pip install mkl-devel
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sudo apt remove --purge --autoremove libcu++-dev
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sudo apt install nvidia-cuda-dev
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libleveldb-dev
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# ok
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# rm -rf build ; CUDACXX=/usr/local/cuda/bin/nvcc GCC="/usr/bin/gcc-11" CMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc python setup.py build
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# Test
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#rm -rf build ; CUDACXX=/usr/local/cuda/bin/nvcc CMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc python setup.py build
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cd .. ; rm -rf build ; mkdir build ; cd build/ ; \
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cmake -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc -DENABLE_CUDA=ON -DUSE_CUDA=ON -DUSE_CUDNN=ON -DUSE_NVRTC=ON -DUSE_OPENCV=ON -DUSE_ZSTD=ON -DUSE_MKL=ON -DBUILD_CAFFE2=ON .. ; \
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make -j12
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ccmake -DCMAKE_CUDA_COMPILER=/usr/local/cuda/bin/nvcc -DENABLE_CUDA=ON -DUSE_CUDA=ON -DUSE_CUDNN=ON -DUSE_NVRTC=ON -DUSE_OPENCV=ON -DUSE_ZSTD=ON -DUSE_MKL=ON -DBUILD_CAFFE2=ON ..
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# ? -Wno-dev
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# /home/jebba/devel/pytorch/pytorch/aten/src/ATen/native/quantized/cpu/qconv_prepack.cpp:412:73: error: ISO C++ forbids comparison between pointer and integer [-fpermissive]
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# nope
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sudo apt purge libideep-dev
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-DBUILD_CAFFE2=ON
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-DUSE_VULKAN=ON
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-DBUILD_BINARY=ON
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-DUSE_OPENCL=ON
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-DUSE_FFMPEG=ON
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# XXX where?
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TORCH_USE_CUDA_DSA
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\end{minted}
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