The best way to get a clean installation of PyTorch, is to install the pre-compiled binaries from the Anaconda distribution. Therefore, we need to setup Anaconda first.
- Go to the download section and download your desired Anaconda version for Linux
- Run the downloaded shell script and follow the install instruction, do
cd ~/Downloads
sh Anaconda3-2018.12-Linux-x86_64.sh # actual name depends on your download- To keep things clean, now setup an environment for Anaconda, do
conda create --name py37_torch python=3.7 # you can choose the name of the environment and the python version
- Activate the environment
conda activate py37_torch
There are two different ways on how to proceed.
- Go to pytorch.org and choose your desired settings like so
- Run the proposed command, here
conda install pytorch-cpu torchvision-cpu -c pytorch
Sometime you want to compile from source, due to specific dependencies for example. You can look up what to do here. The main steps are
- Get dependencies
conda install numpy pyyaml mkl mkl-include setuptools cmake cffi typing
- In case you want to use CUDA on a GPU, otherwise you can skip
# Add LAPACK support for the GPU if needed
conda install -c pytorch magma-cuda92 # or [magma-cuda80 | magma-cuda91] depending on your cuda version
- Clone PyTorch from GitHub
git clone --recursive https://github.com/pytorch/pytorch
cd pytorch
- Install PyTorch, make sure your environment is activated
export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
python setup.py install
Great you came this far, now lets see if everything worked well. Here is a minimal example, on how to link against the C++ API of Pytorch.