For our systems using NVIDIA GPUs (Matrix and RZVector), we recommend you install PyTorch using a cached wheel (https://wci-repo.llnl.gov/#browse/browse:pypi-wci:torch).
Python Module | Torch Included in System-Site Packages? |
---|---|
python/3.9.12 | no |
python/3.10.8 | no |
python/3.11.5 | no |
python/3.12.2 | yes; torch 2.4.0 (cuda 12.1) |
python/3.13.2 | yes; torch 2.7.0 (cuda 11.8) |
Option 1: Using a System Site PyTorch
To use a system-provided PyTorch installation, users must start with one of the python modules we list above. We then recommend that users create a virtual environment. The name "mytorchenv" is a variable that can be changed to meet your own needs.
module load python/3.12 python3 -m venv --system-site-packages mytorchenv source mytorchenv/bin/activate
Option 2: Installing Your Own PyTorch
To install your own PyTorch, you should create a virtual environment without system site packages. The name "mytorchenv" is a variable that can be changed to meet your own needs.
module load python/3.12 python3 -m venv mytorchenv source mytorchenv/bin/activate pip install torch torchvision torchaudio
This pip install command should fetch a default torch (and dependencies) version from Nexus.
If you need to explicitly control the torch version or cuda version, you can specify that with something like:
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu128
Basic PyTorch Test
Run the following command in a GPU allocation
python3 -c 'import torch ; print(torch.rand(5, 3)) ; print("Torch Version", torch.__version__) ; print("Built for Cuda", torch.version.cuda) ; print("Cuda available:", torch.cuda.is_available())'
Launching a Jupyter Notebook
To make your virtual environment (with torch installed) available via a Jupyter Notebook, you must run the following command:
python3 -m ipykernel install --prefix=$HOME/.local/ --name 'mytorchkernel' --display-name 'My Torch kernel'
The name and display name arguments can be customized to meet your own needs. For most personal-use installations, these are the only commands you should need to run to make the torch kernel available to a Jupyter Notebook.
Additional details and setup information can be found on the Orbit and Jupyter Notebooks page.