Installation¶

Requirements¶

Python >= 3.10
PyTorch >= 2.2. PyTorch can be installed following the instructions from their documentation. Note that neither torchvision nor torchaudio, included in the default install command, are needed for NequIP.

Note

PyTorch >= 2.6 is required for PyTorch 2.0 compilation utilities including using torch.compile for training and AOTInductor compilation for integrations such as ASE and LAMMPS.

Instructions¶

After installing torch, NequIP can be installed in the following ways.

from PyPI
```
pip install nequip
```

from source, using the latest release

git clone --depth 1 https://github.com/mir-group/nequip.git
cd nequip
pip install .

from source, using the latest develop branch

git clone https://github.com/mir-group/nequip.git
cd nequip
git checkout develop
pip install .

If you want to track your training runs with third-party services, like Weights and Biases, that are supported by PyTorch Lightning’s loggers, you may need to install extra packages. For example, one needs to pip install wandb to use Lightning’s WandbLogger.

Checking your installation¶

The easiest way to check if your installation is working is to train the tutorial model:

cd configs
python get_tutorial_data.py
nequip-train -cn tutorial.yaml

If you suspect something is wrong, encounter errors, or just want to confirm that everything is in working order, you can also run the unit tests:

pip install pytest
pytest tests/unit/

To run the full tests, including a set of longer/more intensive integration tests, run:

pytest tests/

If a GPU is present, the unit tests will use it.