deepmd.tf.loss.dos

Classes

DOSLoss

Loss function for DeepDOS models.

Module Contents

class deepmd.tf.loss.dos.DOSLoss(starter_learning_rate: float, numb_dos: int = 500, 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, protect_value: float = 1e-08, log_fit: bool = False, **kwargs: Any)

Bases: deepmd.tf.loss.loss.Loss

Loss function for DeepDOS models.

starter_learning_rate

numb_dos = 500

protect_value = 1e-08

log_fit = 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

build(learning_rate: deepmd.tf.env.tf.Tensor, natoms: deepmd.tf.env.tf.Tensor, model_dict: dict, label_dict: dict, suffix: str) → tuple[deepmd.tf.env.tf.Tensor, dict[str, deepmd.tf.env.tf.Tensor]]

Build the loss function graph.

Parameters:

learning_ratetf.Tensor

learning rate

natomstf.Tensor

number of atoms

model_dictdict[str, tf.Tensor]

A dictionary that maps model keys to tensors

label_dictdict[str, tf.Tensor]

A dictionary that maps label keys to tensors

suffixstr

suffix

Returns:

tf.Tensor

the total squared loss

dict[str, tf.Tensor]

A dictionary that maps loss keys to more loss tensors

eval(sess: deepmd.tf.env.tf.Session, feed_dict: dict, natoms: numpy.ndarray) → dict[str, Any]

Eval the loss function.

Parameters:

sesstf.Session

TensorFlow session

feed_dictdict[tf.placeholder, tf.Tensor]

A dictionary that maps graph elements to values

natomstf.Tensor

number of atoms

Returns:

dict

A dictionary that maps keys to values. It should contain key natoms

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

Return data label requirements needed for this loss calculation.