ComplEx
- class ComplEx(*, embedding_dim: int = 200, entity_initializer: str | ~typing.Callable[[~torch.Tensor], ~torch.Tensor] | None = <function normal_>, relation_initializer: str | ~typing.Callable[[~torch.Tensor], ~torch.Tensor] | None = <function normal_>, regularizer: str | ~pykeen.regularizers.Regularizer | type[~pykeen.regularizers.Regularizer] | None = <class 'pykeen.regularizers.LpRegularizer'>, regularizer_kwargs: ~collections.abc.Mapping[str, ~typing.Any] | None = None, **kwargs)[source]
Bases:
ERModel[Tensor,Tensor,Tensor]An implementation of ComplEx [trouillon2016].
The ComplEx model combines complex-valued
pykeen.nn.Embeddingentity and relation representations with apykeen.nn.ComplExInteraction.Initialize ComplEx.
- Parameters:
embedding_dim (int) – the embedding dimension to use for entity and relation embeddings, cf.
Embedding.__init__()’s shape parameter.entity_initializer (str | Callable[[Tensor], Tensor] | None) – entity initializer function. Defaults to
torch.nn.init.normal_(). cf.Embedding.__init__().relation_initializer (str | Callable[[Tensor], Tensor] | None) – relation initializer function. Defaults to
torch.nn.init.normal_(). cf.Embedding.__init__().regularizer (str | Regularizer | type[Regularizer] | None) – the regularizer to apply to both, entity and relation, representations.
regularizer_kwargs (Mapping[str, Any] | None) – additional keyword arguments passed to the regularizer. Defaults to ComplEx.regularizer_default_kwargs.
kwargs – remaining keyword arguments to forward to
pykeen.models.ERModel
Attributes Summary
The default strategy for optimizing the model's hyper-parameters
The default parameters for the default loss function class
The LP settings used by [trouillon2016] for ComplEx.
Attributes Documentation
- hpo_default: ClassVar[Mapping[str, Any]] = {'embedding_dim': {'high': 256, 'low': 16, 'q': 16, 'type': <class 'int'>}}
The default strategy for optimizing the model’s hyper-parameters