tfep.potentials.tblite.tblite_potential_energy

tfep.potentials.tblite.tblite_potential_energy(batch_positions: Tensor, method: str, numbers: ndarray, positions_unit: Unit | None = None, energy_unit: Unit | None = None, precompute_gradient: bool = False, parallelization_strategy: ParallelizationStrategy | None = None, verbosity: int = 0, return_nan_on_failure: bool = False)[source]

PyTorch-differentiable potential energy using tblite.

PyTorch ``Function``s do not accept keyword arguments. This function wraps TBLitePotentialEnergyFunc.apply() to enable standard functional notation. See the documentation on the original function for the input parameters.