PairREInteraction
- class PairREInteraction(p, power_norm=False)[source]
Bases:
pykeen.nn.modules.NormBasedInteraction
[torch.FloatTensor
,Tuple
[torch.FloatTensor
,torch.FloatTensor
],torch.FloatTensor
]A stateful module for the PairRE interaction function.
Initialize the norm-based interaction function.
- Parameters
p (
int
) – The norm used withtorch.linalg.vector_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
(t, r_h, r_t[, p, power_norm])Evaluate the PairRE interaction function.
Attributes Documentation
Methods Documentation
- func(t, r_h, r_t, p=2, power_norm=True)
Evaluate the PairRE interaction function.
\[-\|h \odot r_h - t \odot r_t \|\]- Parameters
h (
FloatTensor
) – shape: (*batch_dims, dim) The head representations.t (
FloatTensor
) – shape: (*batch_dims, dim) The tail representations.r_h (
FloatTensor
) – shape: (*batch_dims, dim) The head part of the relation representations.r_t (
FloatTensor
) – shape: (*batch_dims, dim) The tail part of the relation representations.p (
Union
[int
,str
]) – The parameter p for selecting the norm.power_norm (
bool
) – Whether to return the powered norm instead.
- Return type
FloatTensor
- Returns
shape: batch_dims The scores.