mure_interaction
- mure_interaction(h, b_h, r_vec, r_mat, t, b_t, p=2, power_norm=False)[source]
Evaluate the MuRE interaction function from [balazevic2019b].
\[-\|Rh + r - t\| + b_h + b_t\]- Parameters:
h (
FloatTensor
) – shape: (*batch_dims, dim) The head representations.b_h (
FloatTensor
) – shape: batch_dims The head entity bias.r_vec (
FloatTensor
) – shape: (*batch_dims, dim) The relation vector.r_mat (
FloatTensor
) – shape: (*batch_dims, dim,) The diagonal relation matrix.t (
FloatTensor
) – shape: (*batch_dims, dim) The tail representations.b_t (
FloatTensor
) – shape: batch_dims The tail entity bias.p (
Union
[int
,float
,str
]) – The parameter p for selecting the norm, cf.torch.linalg.vector_norm()
.power_norm (
bool
) – Whether to return the powered norm instead.
- Return type:
FloatTensor
- Returns:
shape: batch_dims The scores.