TuckerInteraction¶
-
class
TuckerInteraction(embedding_dim=200, relation_dim=None, head_dropout=0.3, relation_dropout=0.4, head_relation_dropout=0.5, apply_batch_normalization=True)[source]¶ Bases:
pykeen.nn.modules.FunctionalInteraction[torch.FloatTensor,torch.FloatTensor,torch.FloatTensor]A stateful module for the stateless Tucker interaction function.
Initialize the Tucker interaction function.
- Parameters
embedding_dim (
int) – The entity embedding dimension.relation_dim (
Optional[int]) – The relation embedding dimension.head_dropout (
float) – The dropout rate applied to the head representations.relation_dropout (
float) – The dropout rate applied to the relation representations.head_relation_dropout (
float) – The dropout rate applied to the combined head and relation representations.apply_batch_normalization (
bool) – Whether to use batch normalization on head representations and the combination of head and relation.
Methods Summary
func(r, t, core_tensor, do_h, do_r, do_hr, …)Evaluate the TuckEr interaction function.
Reset parameters the interaction function may have.
Methods Documentation
-
func(r, t, core_tensor, do_h, do_r, do_hr, bn_h, bn_hr)¶ Evaluate the TuckEr interaction function.
Compute scoring function W x_1 h x_2 r x_3 t as in the official implementation, i.e. as
\[DO_{hr}(BN_{hr}(DO_h(BN_h(h)) x_1 DO_r(W x_2 r))) x_3 t\]where BN denotes BatchNorm and DO denotes Dropout
- Parameters
h (
FloatTensor) – shape: (batch_size, num_heads, 1, 1, d_e) The head representations.r (
FloatTensor) – shape: (batch_size, 1, num_relations, 1, d_r) The relation representations.t (
FloatTensor) – shape: (batch_size, 1, 1, num_tails, d_e) The tail representations.core_tensor (
FloatTensor) – shape: (d_e, d_r, d_e) The core tensor.do_h (
Dropout) – The dropout layer for the head representations.do_r (
Dropout) – The first hidden dropout.do_hr (
Dropout) – The second hidden dropout.bn_h (
Optional[BatchNorm1d]) – The first batch normalization layer.bn_hr (
Optional[BatchNorm1d]) – The second batch normalization layer.
- Return type
FloatTensor- Returns
shape: (batch_size, num_heads, num_relations, num_tails) The scores.