deepmd.pt.model.task.dos
Module Contents
Classes
Construct a fitting net for energy. |
Attributes
- class deepmd.pt.model.task.dos.DOSFittingNet(ntypes: int, dim_descrpt: int, numb_dos: int = 300, neuron: List[int] = [128, 128, 128], resnet_dt: bool = True, numb_fparam: int = 0, numb_aparam: int = 0, rcond: float | None = None, bias_dos: torch.Tensor | None = None, trainable: bool | List[bool] = True, seed: int | None = None, activation_function: str = 'tanh', precision: str = DEFAULT_PRECISION, exclude_types: List[int] = [], mixed_types: bool = True)[source]
Bases:
deepmd.pt.model.task.ener.InvarFitting
Construct a fitting net for energy.
- Parameters:
- var_name
str
The atomic property to fit, ‘energy’, ‘dipole’, and ‘polar’.
- ntypes
int
Element count.
- dim_descrpt
int
Embedding width per atom.
- dim_out
int
The output dimension of the fitting net.
- neuron
List
[int
] Number of neurons in each hidden layers of the fitting net.
- bias_atom_e
torch.Tensor
,optional
Average enery per atom for each element.
- resnet_dtbool
Using time-step in the ResNet construction.
- numb_fparam
int
Number of frame parameters.
- numb_aparam
int
Number of atomic parameters.
- activation_function
str
Activation function.
- precision
str
Numerical precision.
- mixed_typesbool
If true, use a uniform fitting net for all atom types, otherwise use different fitting nets for different atom types.
- rcond
float
,optional
The condition number for the regression of atomic energy.
- seed
int
,optional
Random seed.
- exclude_types: List[int]
Atomic contributions of the excluded atom types are set zero.
- atom_ener: List[Optional[torch.Tensor]], optional
Specifying atomic energy contribution in vacuum. The value is a list specifying the bias. the elements can be None or np.array of output shape. For example: [None, [2.]] means type 0 is not set, type 1 is set to [2.] The set_davg_zero key in the descrptor should be set.
- var_name
- output_def() deepmd.dpmodel.FittingOutputDef [source]
Returns the output def of the fitting net.
- classmethod deserialize(data: dict) DOSFittingNet [source]
Deserialize the fitting.
- Parameters:
- data
dict
The serialized data
- data
- Returns:
BF
The deserialized fitting