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In the original paper, the author proposed three soft constraints and added a hyperparameter C to weight the importance of these constraints. While referring to the
I found a similar issue in OpenKE Weight C in TransH missing , is this the same reason ttorchkge ignores C though torchkge uses a different normalization method from OpenKE?
The text was updated successfully, but these errors were encountered:
Hi @thsno02, TorchKGE does not implement the soft constraint normalization proposed in the original article yet. Instead, the hard constraints can be enforced using the following :
constraint 2 (orthogonal) : the project static method can be used to project relation embedding vectors on relation-specific hyperplanes
constraints 1 and 3 (scale and unit normal vector) : the normalize_parameters method brings entity embeddings and normal vectors back to norm 1. This is indeed too strong a constraint as the scale of entity embeddings should be allowed to get very small.
I'll leave the issue open until someone contributes to add a soft constraint module. Feel free to do so.
In the original paper, the author proposed three soft constraints and added a hyperparameter
C
to weight the importance of these constraints. While referring to thetorchkge/torchkge/utils/losses.py
Line 12 in a3474b7
C
term.I found a similar issue in OpenKE Weight C in TransH missing , is this the same reason ttorchkge ignores
C
though torchkge uses a different normalization method from OpenKE?The text was updated successfully, but these errors were encountered: