OGBEvaluator

class OGBEvaluator(filtered=False, **kwargs)[source]

Bases: SampledRankBasedEvaluator

A sampled, rank-based evaluator that applies a custom OGB evaluation.

Initialize the evaluator.

Parameters:

  • evaluation_factory – the factory with evaluation triples

  • additional_filter_triples – additional true triples to use for filtering; only relevant if not explicit negatives are given. cf. pykeen.evaluation.rank_based_evaluator.sample_negatives()

  • num_negatives – the number of negatives to sample; only relevant if not explicit negatives are given. cf. pykeen.evaluation.rank_based_evaluator.sample_negatives()

  • head_negatives – shape: (num_triples, num_negatives) the entity IDs of negative samples for head prediction for each evaluation triple

  • tail_negatives – shape: (num_triples, num_negatives) the entity IDs of negative samples for tail prediction for each evaluation triple

  • kwargs – additional keyword-based arguments passed to pykeen.evaluation.rank_based_evaluator.RankBasedEvaluator.__init__()

  • filtered (bool) –

Raises:

ValueError – if only a single side’s negatives are given, or the negatives are in wrong shape

Methods Summary

evaluate(model, mapped_triples[, ...])

Run evaluate_ogb() with this evaluator.

Methods Documentation

evaluate(model, mapped_triples, batch_size=None, slice_size=None, **kwargs)[source]

Run evaluate_ogb() with this evaluator.

Return type:

MetricResults

Parameters:

  • model (Model) –

  • mapped_triples (LongTensor) –

  • batch_size (int | None) –

  • slice_size (int | None) –