deepmd.loss package
Submodules
deepmd.loss.ener module
- class deepmd.loss.ener.EnerDipoleLoss(starter_learning_rate: float, start_pref_e: float = 0.1, limit_pref_e: float = 1.0, start_pref_ed: float = 1.0, limit_pref_ed: float = 1.0)[source]
Bases:
deepmd.loss.loss.Loss
Methods
build
(learning_rate, natoms, model_dict, ...)Build the loss function graph.
eval
(sess, feed_dict, natoms)Eval the loss function.
- build(learning_rate, natoms, model_dict, label_dict, suffix)[source]
Build the loss function graph.
- Parameters
- Returns
- class deepmd.loss.ener.EnerStdLoss(starter_learning_rate: float, start_pref_e: float = 0.02, limit_pref_e: float = 1.0, start_pref_f: float = 1000, limit_pref_f: float = 1.0, start_pref_v: float = 0.0, limit_pref_v: float = 0.0, start_pref_ae: float = 0.0, limit_pref_ae: float = 0.0, start_pref_pf: float = 0.0, limit_pref_pf: float = 0.0, relative_f: Optional[float] = None, enable_atom_ener_coeff: bool = False)[source]
Bases:
deepmd.loss.loss.Loss
Standard loss function for DP models
- Parameters
- enable_atom_ener_coeffbool
if true, the energy will be computed as sum_i c_i E_i
Methods
build
(learning_rate, natoms, model_dict, ...)Build the loss function graph.
eval
(sess, feed_dict, natoms)Eval the loss function.
- build(learning_rate, natoms, model_dict, label_dict, suffix)[source]
Build the loss function graph.
- Parameters
- Returns
deepmd.loss.loss module
- class deepmd.loss.loss.Loss[source]
Bases:
object
The abstract class for the loss function.
Methods
build
(learning_rate, natoms, model_dict, ...)Build the loss function graph.
eval
(sess, feed_dict, natoms)Eval the loss function.
- abstract build(learning_rate: tensorflow.python.framework.ops.Tensor, natoms: tensorflow.python.framework.ops.Tensor, model_dict: Dict[str, tensorflow.python.framework.ops.Tensor], label_dict: Dict[str, tensorflow.python.framework.ops.Tensor], suffix: str) Tuple[tensorflow.python.framework.ops.Tensor, Dict[str, tensorflow.python.framework.ops.Tensor]] [source]
Build the loss function graph.
- Parameters
- Returns
deepmd.loss.tensor module
- class deepmd.loss.tensor.TensorLoss(jdata, **kwarg)[source]
Bases:
deepmd.loss.loss.Loss
Loss function for tensorial properties.
Methods
build
(learning_rate, natoms, model_dict, ...)Build the loss function graph.
eval
(sess, feed_dict, natoms)Eval the loss function.
- build(learning_rate, natoms, model_dict, label_dict, suffix)[source]
Build the loss function graph.
- Parameters
- Returns