MACE
References: Batatia2022
This section specifies the input parameters for MACE potential type, a higher-order equivariant message-passing neural network. The MACE model must be exported to a TorchScript file that takes a single dictionary argument (see the create_cp2k_model.py helper). Requires linking with libtorch library from https://pytorch.org/cppdocs/installing.html. [Edit on GitHub]
Keywords
Keyword descriptions
- ATOMS
Type: string[ ]
Usage: ATOMS {KIND 1} {KIND 2} .. {KIND N}Description: Defines the atomic kinds involved in the MACE potential. Provide a list of each element, making sure that the mapping from the ATOMS list to MACE atom types is correct. This mapping should also be consistent for the atomic coordinates as specified in the sections COORDS or TOPOLOGY.
Mentions: ⭐MACE
- POT_FILE_NAME
Type: string
Aliases: MODEL_FILE_NAME
Usage: POT_FILE_NAME {FILENAME}Description: Specifies the filename that contains the exported MACE model. MACE models use standardized units (Angstrom for length, eV for energy, eV/Angstrom for forces), so no unit keywords are required.
Mentions: ⭐MACE