deepmd.pt.model.atomic_model.property_atomic_model

deepmd.pt.model.atomic_model.property_atomic_model#

Classes#

DPPropertyAtomicModel

Model give atomic prediction of some physical property.

Module Contents#

class deepmd.pt.model.atomic_model.property_atomic_model.DPPropertyAtomicModel(descriptor: Any, fitting: Any, type_map: Any, **kwargs: Any)[source]#

Bases: deepmd.pt.model.atomic_model.dp_atomic_model.DPAtomicModel

Model give atomic prediction of some physical property.

Parameters:

descriptor: Descriptor
fitting_net: Fitting net
type_map: Mapping atom type to the name (str) of the type. For example type_map[1] gives the name of the type 1.

get_compute_stats_distinguish_types() → bool[source]#: Get whether the fitting net computes stats which are not distinguished between different types of atoms.

get_intensive() → bool[source]#: Whether the fitting property is intensive.

apply_out_stat(ret: dict[str, torch.Tensor], atype: torch.Tensor) → dict[str, torch.Tensor][source]#

Apply the stat to each atomic output. In property fitting, each output will be multiplied by label std and then plus the label average value.

Parameters:

ret: The returned dict by the forward_atomic method
atype: The atom types. nf x nloc. It is useless in property fitting.