NSSALoss¶
- class NSSALoss(margin=9.0, adversarial_temperature=1.0, reduction='mean')[source]¶
Bases:
pykeen.losses.SetwiseLoss
An implementation of the self-adversarial negative sampling loss function proposed by [sun2019].
Initialize the NSSA loss.
- Parameters
Note
The default hyperparameters are based the experiments for FB15K-237 in [sun2019].
Attributes Summary
The default strategy for optimizing the model’s hyper-parameters
Methods Summary
forward
(pos_scores, neg_scores)Calculate the loss for the given scores.
Attributes Documentation
- hpo_default: ClassVar[Mapping[str, Any]] = {'adversarial_temperature': {'high': 1.0, 'low': 0.5, 'type': <class 'float'>}, 'margin': {'high': 30, 'low': 3, 'q': 3, 'type': <class 'int'>}}¶
The default strategy for optimizing the model’s hyper-parameters
- synonyms: ClassVar[Optional[Set[str]]] = {'Negative Sampling Self-Adversarial Loss', 'Self-Adversarial Negative Sampling Loss'}¶
Methods Documentation