PyTorch Install

Pytorch install guide: https://pytorch.org/get-started/locally/

Procedure to install the most recent pytorch package compatible with your machine:

  1. Make sure your nvidia drivers is up to date.

    You can check that the Nvidia drivers is properly install with the command:

    nvidia-smi

    It should print something like this:

    +-----------------------------------------------------------------------------+
| NVIDIA-SMI 515.65.01    Driver Version: 515.65.01    CUDA Version: 11.7     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|                               |                      |               MIG M. |
|===============================+======================+======================|
|   0  NVIDIA GeForce ...  Off  | 00000000:01:00.0 Off |                  N/A |
| N/A   44C    P3    13W /  N/A |      4MiB /  4096MiB |      0%      Default |
|                               |                      |                  N/A |
+-------------------------------+----------------------+----------------------+

+-----------------------------------------------------------------------------+
| Processes:                                                                  |
|  GPU   GI   CI        PID   Type   Process name                  GPU Memory |
|        ID   ID                                                   Usage      |
|=============================================================================|
|    0   N/A  N/A      1090      G   /usr/lib/xorg/Xorg                  4MiB |
+-----------------------------------------------------------------------------+

  2. [OPTIONAL - Not Recommended] Install CUDA manually:

    Do this step only if you don’t want to install cuda using conda.

    Check Which version of CUDA you need to install using this link: https://pytorch.org/get-started/locally/

    ../../_images/pytorch_install.png

    CUDA Download link: https://developer.nvidia.com/cuda-toolkit-archive

    CUDA Installation guide: https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html

    Warning

    if you know your nvidia drivers matches with this CUDA version, when running the runfile installation of CUDA add --toolkit (sudo sh cuda_11.2.2_460.32.03_linux.run --toolkit) in the install command to make sure nvidia drivers won’t be updated.

    You will need to update environment variables PATH and LD_LIBRARY_PATH in your .bashrc: (It is not mandatory to define these variable globally, you can also set them only when activating your conda environment, see below)

    # These are symlinks ! be sure it point to the desired CUDA version you installed
export PATH="/usr/local/cuda/bin:$PATH"
export LD_LIBRARY_PATH="/usr/local/cuda/lib64:$LD_LIBRARY_PATH"
export LD_LIBRARY_PATH="/usr/local/cuda/include:$LD_LIBRARY_PATH"

    You can check if CUDA is properly installed by running the command (won’t work if you prefer to define environment variables for conda only):

    nvcc -V

  3. Install PyTorch

    # If you already installed CUDA previously
conda install pytorch torchvision torchaudio -c pytorch
conda env config vars set PATH="/usr/local/cuda-11.6/bin:$PATH"
conda env config vars set LD_LIBRARY_PATH="/usr/local/cuda-11.6/lib64:/usr/local/cuda-11.6/include:$LD_LIBRARY_PATH"
# If you didn't install CUDA yet (check the link to get the command for the latest version available)
conda install pytorch torchvision torchaudio cudatoolkit=11.6 -c pytorch -c conda-forge

    You can check pytorch properly detect your GPU using the command:

    import torch
is_available = torch.cuda.is_available()
cuda_version = torch.version.cuda
nb_devices = torch.cuda.device_count()
ind_device = torch.cuda.current_device()
device_name = torch.cuda.get_device_name(ind_device)

Sources: