CompGCN
- class CompGCN(*, triples_factory, embedding_dim=64, encoder_kwargs=None, interaction=None, interaction_kwargs=None, **kwargs)[source]
Bases:
pykeen.models.nbase.ERModel
[torch.FloatTensor
,pykeen.typing.RelationRepresentation
,torch.FloatTensor
]An implementation of CompGCN from [vashishth2020].
This model uses graph convolutions, and composition functions.
Initialize the model.
- Parameters
triples_factory (
CoreTriplesFactory
) – The triples factory.embedding_dim (
int
) – The embedding dimension to be used ifembedding_specification
is not given explicitly inencoder_kwargs
.encoder_kwargs (
Optional
[Mapping
[str
,Any
]]) – Additional keyword arguments for the encoder, cf.pykeen.nn.representation.CombinedCompGCNRepresentations
.interaction (
Union
[str
,Interaction
[FloatTensor
, ~RelationRepresentation,FloatTensor
],None
]) – The interaction function to use as decoder.interaction_kwargs (
Optional
[Mapping
[str
,Any
]]) – Additional keyword based arguments for the interaction function.kwargs – Additional keyword based arguments passed to
pykeen.models.ERModel
.
Attributes Summary
The default strategy for optimizing the model's hyper-parameters
Attributes Documentation