deepmd.dpmodel.atomic_model.dipole_atomic_model

Classes

DPDipoleAtomicModel

Model give atomic prediction of some physical property.

Module Contents

class deepmd.dpmodel.atomic_model.dipole_atomic_model.DPDipoleAtomicModel(descriptor: deepmd.dpmodel.descriptor.base_descriptor.BaseDescriptor, fitting: deepmd.dpmodel.fitting.base_fitting.BaseFitting, type_map: list[str], **kwargs: Any)

Bases: deepmd.dpmodel.atomic_model.dp_atomic_model.DPAtomicModel

Model give atomic prediction of some physical property.

The atomic model computes atomic properties by first extracting a descriptor from the atomic environment, then passing it through a fitting network:

\[\mathcal{D}^i = \mathcal{D}(\mathbf{R}^i, \mathbf{R}_j, \alpha_j),\]

\[\mathbf{y}^i = \mathcal{F}(\mathcal{D}^i),\]

where \(\mathcal{D}^i\) is the descriptor for atom \(i\), \(\alpha_j\) is the atom type of neighbor \(j\), \(\mathcal{F}\) is the fitting network, and \(\mathbf{y}^i\) is the predicted atomic property (energy, dipole, etc.).

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.

apply_out_stat(ret: dict[str, deepmd.dpmodel.array_api.Array], atype: deepmd.dpmodel.array_api.Array) → dict[str, deepmd.dpmodel.array_api.Array]

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