PseudoTypedNegativeSampler
- class PseudoTypedNegativeSampler(*, triples_factory, **kwargs)[source]
Bases:
pykeen.sampling.negative_sampler.NegativeSampler
A sampler that accounts for which entities co-occur with a relation.
To generate a corrupted head entity for triple \((h, r, t)\), only those entities are considered which occur as a head entity in a triple with the relation \(r\).
Warning
With this type of sampler, filtering for false negatives is more important.
Instantiate the pseudo-typed negative sampler.
- Parameters
triples_factory (
CoreTriplesFactory
) – The factory holding the positive training tripleskwargs – Additional keyword based arguments passed to
pykeen.sampling.NegativeSampler
.
Methods Summary
corrupt_batch
(positive_batch)Generate negative samples from the positive batch without application of any filter.
Methods Documentation
- corrupt_batch(positive_batch)[source]
Generate negative samples from the positive batch without application of any filter.
- Parameters
positive_batch (
LongTensor
) – shape: (batch_size, 3) The positive triples.- Returns
shape: (batch_size, num_negs_per_pos, 3) The negative triples.
result[i, :, :]
contains the negative examples generated frompositive_batch[i, :]
.