🔥🪞 Fix relation prediction with inverses #1304
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mberr
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cthoyt
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Aug 8, 2023
| @@ -61,6 +65,10 @@ def invert_(self, batch: torch.LongTensor, index: int = 1) -> torch.LongTensor: | |||
| batch[:, index] += 1 | |||
| return batch | |||
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| # docstr-coverage: inherited | |||
| def is_inverse(self, ids: torch.LongTensor) -> torch.BoolTensor: # noqa: D102 | |||
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somewhere there is also the inverse index generator function, should these be coupled?
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This is exactly what this class is for 😉
The full inversion combines _map and invert_ defined in this concrete class, DefaultRelationInverter , in map in the base class, RelationInverter.
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This PR is mostly a fix for the prediction dataframe; there are still some inconsistencies to fix (e.g. that inverse relations are stored in a dataset instead of solely encapsulated in a model; that tf.relation_to_id contains only the relation ids before remapping, etc.), cf. this long-standing PR: #752
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Fix #1303