deepmd.pt.model.model.dp_zbl_model#

Attributes#

Classes#

DPZBLModel

Base class for final exported model that will be directly used for inference.

Module Contents#

deepmd.pt.model.model.dp_zbl_model.DPZBLModel_[source]#
class deepmd.pt.model.model.dp_zbl_model.DPZBLModel(*args, **kwargs)[source]#

Bases: DPZBLModel_

Base class for final exported model that will be directly used for inference.

The class defines some abstractmethods that will be directly called by the inference interface. If the final model class inherits some of those methods from other classes, BaseModel should be inherited as the last class to ensure the correct method resolution order.

This class is backend-indepedent.

See also

deepmd.dpmodel.model.base_model.BaseModel

BaseModel class for DPModel backend.

model_type = 'zbl'[source]#
translated_output_def()[source]#
forward(coord, atype, box: torch.Tensor | None = None, fparam: torch.Tensor | None = None, aparam: torch.Tensor | None = None, do_atomic_virial: bool = False) dict[str, torch.Tensor][source]#
forward_lower(extended_coord, extended_atype, nlist, mapping: torch.Tensor | None = None, fparam: torch.Tensor | None = None, aparam: torch.Tensor | None = None, do_atomic_virial: bool = False)[source]#
classmethod update_sel(train_data: deepmd.utils.data_system.DeepmdDataSystem, type_map: list[str] | None, local_jdata: dict) tuple[dict, float | None][source]#

Update the selection and perform neighbor statistics.

Parameters:
train_dataDeepmdDataSystem

data used to do neighbor statistics

type_maplist[str], optional

The name of each type of atoms

local_jdatadict

The local data refer to the current class

Returns:
dict

The updated local data

float

The minimum distance between two atoms