predict_triples
- predict_triples(model, *, triples, triples_factory=None, batch_size=None, mode=None)[source]
Predict on labeled or mapped triples.
- Parameters:
model (
Model
) – The model.triples (
Union
[None
,LongTensor
,ndarray
,Tuple
[str
,str
,str
],Sequence
[Tuple
[str
,str
,str
]]]) –shape: (num_triples, 3) The triples in one of the following formats:
A single label-based triple.
A list of label-based triples.
An array of label-based triples
An array of ID-based triples.
None. In this case, a triples factory has to be provided, and its triples will be used.
triples_factory (
Optional
[CoreTriplesFactory
]) – The triples factory. Must be given if triples are label-based. If provided and triples are ID-based, add labels to result.batch_size (
Optional
[int
]) – The batch size to use. Use None for automatic memory optimization.mode (
Optional
[Literal
[‘training’, ‘validation’, ‘testing’]]) – The pass mode, which is None in the transductive setting and one of “training”, “validation”, or “testing” in the inductive setting.
- Return type:
- Returns:
a score pack of the triples with the predicted scores.