deepmd.dpmodel.infer package

Submodules

class deepmd.dpmodel.infer.deep_eval.DeepEval(model_file: str, *args, **kwargs)[source]

NumPy backend implementaion of DeepEval.

Parameters

model_filePath: The name of the frozen model file.
output_defModelOutputDef: The output definition of the model.
*argslist: Positional arguments.
auto_batch_sizebool or int or AutomaticBatchSize, default: False: If True, automatic batch size will be used. If int, it will be used as the initial batch size.
neighbor_listase.neighborlist.NewPrimitiveNeighborList, optional: The ASE neighbor list class to produce the neighbor list. If None, the neighbor list will be built natively in the model.
**kwargsdict: Keyword arguments.

Attributes

Methods

`eval`(coords, cells, atom_types[, atomic, ...])	Evaluate the energy, force and virial by using this DP.
`eval_descriptor`(coords, cells, atom_types[, ...])	Evaluate descriptors by using this DP.
`eval_typeebd`()	Evaluate output of type embedding network by using this model.
`get_dim_aparam`()	Get the number (dimension) of atomic parameters of this DP.
`get_dim_fparam`()	Get the number (dimension) of frame parameters of this DP.
`get_has_efield`()	Check if the model has efield.
`get_ntypes`()	Get the number of atom types of this model.
`get_ntypes_spin`()	Get the number of spin atom types of this model.
`get_numb_dos`()	Get the number of DOS.
`get_rcut`()	Get the cutoff radius of this model.
`get_sel_type`()	Get the selected atom types of this model.
`get_type_map`()	Get the type map (element name of the atom types) of this model.

eval(coords: ndarray, cells: ndarray, atom_types: ndarray, atomic: bool = False, fparam: Optional[ndarray] = None, aparam: Optional[ndarray] = None, **kwargs: Dict[str, Any]) → Dict[str, ndarray][source]

Evaluate the energy, force and virial by using this DP.

Parameters

coords: The coordinates of atoms. The array should be of size nframes x natoms x 3
cells: The cell of the region. If None then non-PBC is assumed, otherwise using PBC. The array should be of size nframes x 9
atom_types: The atom types The list should contain natoms ints
atomic: Calculate the atomic energy and virial
fparam: The frame parameter. The array can be of size : - nframes x dim_fparam. - dim_fparam. Then all frames are assumed to be provided with the same fparam.
aparam: The atomic parameter The array can be of size : - nframes x natoms x dim_aparam. - natoms x dim_aparam. Then all frames are assumed to be provided with the same aparam. - dim_aparam. Then all frames and atoms are provided with the same aparam.
**kwargs: Other parameters

Returns

output_dictdict: The output of the evaluation. The keys are the names of the output variables, and the values are the corresponding output arrays.

get_dim_aparam() → int[source]: Get the number (dimension) of atomic parameters of this DP.

get_dim_fparam() → int[source]: Get the number (dimension) of frame parameters of this DP.

get_ntypes_spin()[source]: Get the number of spin atom types of this model.

get_sel_type() → List[int][source]

Get the selected atom types of this model.

Only atoms with selected atom types have atomic contribution to the result of the model. If returning an empty list, all atom types are selected.

get_type_map() → List[str][source]: Get the type map (element name of the atom types) of this model.

property model_type: Type[DeepEval]: The the evaluator of the model type.