TransRInteraction¶
-
class
TransRInteraction
(p, power_norm=True)[source]¶ Bases:
pykeen.nn.modules.TranslationalInteraction
[torch.FloatTensor
,Tuple
[torch.FloatTensor
,torch.FloatTensor
],torch.FloatTensor
]A stateful module for the TransR interaction function.
Initialize the translational interaction function.
- Parameters
p (
int
) – The norm used withtorch.norm()
. Typically is 1 or 2.power_norm (
bool
) – Whether to use the p-th power of the L_p norm. It has the advantage of being differentiable around 0, and numerically more stable.
Attributes Summary
The symbolic shapes for relation representations
Methods Summary
func
(r, t, m_r, p[, power_norm])Evaluate the TransR interaction function.
Attributes Documentation
Methods Documentation
-
func
(r, t, m_r, p, power_norm=True)¶ Evaluate the TransR interaction function.
- Parameters
h (
FloatTensor
) – shape: (batch_size, num_heads, 1, 1, d_e) Head embeddings.r (
FloatTensor
) – shape: (batch_size, 1, num_relations, 1, d_r) Relation embeddings.m_r (
FloatTensor
) – shape: (batch_size, 1, num_relations, 1, d_e, d_r) The relation specific linear transformations.t (
FloatTensor
) – shape: (batch_size, 1, 1, num_tails, d_e) Tail embeddings.p (
int
) – The parameter p for selecting the norm.power_norm (
bool
) – Whether to return the powered norm instead.
- Return type
FloatTensor
- Returns
shape: (batch_size, num_heads, num_relations, num_tails) The scores.