Installation¶

You may install torch-fem via pip with

pip install torch-fem

GPU support (optional)¶

For optional GPU support, install CUDA, PyTorch for CUDA, and the corresponding CuPy version.

For CUDA 11.8:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install cupy-cuda11x # v11.2 - 11.8

For CUDA 12.9:

pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu129
pip install cupy-cuda12x # v12.x

Development (optional)¶

To develop new features for torch-fem, you should fork the GitHub repository and clone it to your machine via

git clone <repo_url> 

In the root of the cloned project, make the installation editable as

pip install -e .

Now, the package is linked to this local directory and whenever you use import torchfem, it will use the latest code.