deepmd.dpmodel.atomic_model.base_atomic_model

Module Contents

Classes

BaseAtomicModel

Base Atomic Model provides the interfaces of an atomic model.

Attributes

BaseAtomicModel_

deepmd.dpmodel.atomic_model.base_atomic_model.BaseAtomicModel_

class deepmd.dpmodel.atomic_model.base_atomic_model.BaseAtomicModel(type_map: List[str], atom_exclude_types: List[int] = [], pair_exclude_types: List[Tuple[int, int]] = [], rcond: float | None = None, preset_out_bias: Dict[str, numpy.ndarray] | None = None)

Bases: BaseAtomicModel_

Base Atomic Model provides the interfaces of an atomic model.

init_out_stat()

Initialize the output bias.

__setitem__(key, value)

__getitem__(key)

get_type_map() → List[str]

Get the type map.

reinit_atom_exclude(exclude_types: List[int] = [])

reinit_pair_exclude(exclude_types: List[Tuple[int, int]] = [])

atomic_output_def() → deepmd.dpmodel.output_def.FittingOutputDef

Get the output def of the atomic model.

By default it is the same as FittingOutputDef, but it allows model level wrapper of the output defined by the developer.

forward_common_atomic(extended_coord: numpy.ndarray, extended_atype: numpy.ndarray, nlist: numpy.ndarray, mapping: numpy.ndarray | None = None, fparam: numpy.ndarray | None = None, aparam: numpy.ndarray | None = None) → Dict[str, numpy.ndarray]

Common interface for atomic inference.

This method accept extended coordinates, extended atom typs, neighbor list, and predict the atomic contribution of the fit property.

Parameters:

extended_coord

extended coodinates, shape: nf x (nall x 3)

extended_atype

extended atom typs, shape: nf x nall for a type < 0 indicating the atomic is virtual.

nlist

neighbor list, shape: nf x nloc x nsel

mapping

extended to local index mapping, shape: nf x nall

fparam

frame parameters, shape: nf x dim_fparam

aparam

atomic parameter, shape: nf x nloc x dim_aparam

Returns:

ret_dict

dict of output atomic properties. should implement the definition of fitting_output_def. ret_dict[“mask”] of shape nf x nloc will be provided. ret_dict[“mask”][ff,ii] == 1 indicating the ii-th atom of the ff-th frame is real. ret_dict[“mask”][ff,ii] == 0 indicating the ii-th atom of the ff-th frame is virtual.

serialize() → dict

classmethod deserialize(data: dict) → BaseAtomicModel

apply_out_stat(ret: Dict[str, numpy.ndarray], atype: numpy.ndarray)

Apply the stat to each atomic output. The developer may override the method to define how the bias is applied to the atomic output of the model.

Parameters:

ret

The returned dict by the forward_atomic method

atype

The atom types. nf x nloc

_varsize(shape: List[int]) → int

_get_bias_index(kk: str) → int

_fetch_out_stat(keys: List[str]) → Tuple[Dict[str, numpy.ndarray], Dict[str, numpy.ndarray]]