nn package¶
Submodules¶
nn.dataloader module¶
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class
nn.dataloader.
BidirectionalOneShotIterator
(dataloader_head, dataloader_tail, dataloader_neg=None, neg_ratio=1)¶ Bases:
object
ZincBase uses this class automatically when you want to train a model from a KB.
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next_no_neg
()¶
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next_with_neg
()¶
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static
one_shot_iterator
(dataloader)¶
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class
nn.dataloader.
NegDataset
(neg_triples)¶ Bases:
sphinx.ext.autodoc.importer._MockObject
Zincbase sets this up automatically from the knowledge base. It’s a generator used for negative examples.
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class
nn.dataloader.
TrainDataset
(triples, nrelation, negative_sample_size, mode)¶ Bases:
sphinx.ext.autodoc.importer._MockObject
Zincbase sets this up automatically from the knowledge base. It’s the generator for the RotatE algorithm.
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static
collate_fn
(data)¶
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static
count_frequency
(triples, start=4)¶
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static
get_true_attr
(triples)¶
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static
get_true_head_and_tail
(triples)¶
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static
nn.rotate module¶
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class
nn.rotate.
KGEModel
(model_name, nentity, nrelation, hidden_dim, gamma, double_entity_embedding=False, double_relation_embedding=False, node_attributes=[], pred_attributes=[], attr_loss_to_graph_loss=1.0, pred_loss_to_graph_loss=1.0, device='cuda')¶ Bases:
sphinx.ext.autodoc.importer._MockObject
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ComplEx
(head, relation, tail, mode)¶
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RotatE
(head, relation, tail, mode)¶
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forward
(sample, mode='single', attributes=True, predict_pred_prop=False, predict_only=False)¶ A single forward pass
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run_embedding
(embedding, attribute_name)¶
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static
train_step
(model, optimizer, train_iterator, args)¶
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