.. _installation: Installation ============ MXtalTools has two classes of dependency: - **PyTorch + PyG** — must be installed manually because the correct wheels depend on your CUDA version. - **Everything else** — handled automatically by ``pip install mxtaltools``. Step 1 — Install PyTorch and PyTorch Geometric ----------------------------------------------- Choose the commands for your CUDA version from the official guides: - `PyTorch installation guide `_ - `PyG installation guide `_ For example, with **CUDA 11.8 and PyTorch 2.4**: .. code-block:: bash pip install torch==2.4.1 --index-url https://download.pytorch.org/whl/cu118 pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv \ -f https://data.pyg.org/whl/torch-2.4.0+cu118.html pip install torch-geometric==2.7.0 Step 2 — Install MXtalTools ----------------------------- **Users:** .. code-block:: bash pip install mxtaltools **Developers** (editable install from a clone): .. code-block:: bash git clone git@github.com:InfluenceFunctional/MXtalTools.git cd MXtalTools pip install -e . Optional Dependencies --------------------- **UMA model support** (``fairchem-core``) — only needed if you want to use the UMA machine-learning interatomic potential: .. code-block:: bash pip install mxtaltools[uma] # or, separately: pip install fairchem-core **CSD Python API** — only needed for constructing crystal datasets from ``.cif`` files. Requires a valid licence from `CCDC `_. Install separately following the CCDC instructions. **Weights & Biases** — required for model training. Already included in the base install; activate with: .. code-block:: bash wandb login **User config** — for model training, create ``configs/users/YOUR_USERNAME.yaml`` with your paths and W&B settings, then pass ``--user YOUR_USERNAME`` on the command line.