deepmd.pt.loss.dos

Classes

DOSLoss

Helper class that provides a standard way to create an ABC using

Module Contents

class deepmd.pt.loss.dos.DOSLoss(starter_learning_rate: float, numb_dos: int, start_pref_dos: float = 1.0, limit_pref_dos: float = 1.0, start_pref_cdf: float = 1000, limit_pref_cdf: float = 1.0, start_pref_ados: float = 0.0, limit_pref_ados: float = 0.0, start_pref_acdf: float = 0.0, limit_pref_acdf: float = 0.0, inference=False, **kwargs)

Bases: deepmd.pt.loss.loss.TaskLoss

Helper class that provides a standard way to create an ABC using inheritance.

starter_learning_rate

numb_dos

inference = False

start_pref_dos = 1.0

limit_pref_dos = 1.0

start_pref_cdf = 1000

limit_pref_cdf = 1.0

start_pref_ados = 0.0

limit_pref_ados = 0.0

start_pref_acdf = 0.0

limit_pref_acdf = 0.0

has_dos

has_cdf

has_ados

has_acdf

forward(input_dict, model, label, natoms, learning_rate=0.0, mae=False)

Return loss on local and global tensors.

Parameters:

input_dictdict[str, torch.Tensor]

Model inputs.

modeltorch.nn.Module

Model to be used to output the predictions.

labeldict[str, torch.Tensor]

Labels.

natomsint

The local atom number.

Returns:

model_pred: dict[str, torch.Tensor]

Model predictions.

loss: torch.Tensor

Loss for model to minimize.

more_loss: dict[str, torch.Tensor]

Other losses for display.

property label_requirement: list[deepmd.utils.data.DataRequirementItem]

Return data label requirements needed for this loss calculation.