⌨️⚙️ Update torch type checking #1538
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mberr
reviewed
May 12, 2025
| @@ -120,5 +120,6 @@ def __call__(self, steps: Sequence[int]) -> Iterator[int]: | |||
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| #: a resolver for checkpoint keepers | |||
| keeper_resolver: ClassResolver[CheckpointKeeper] = ClassResolver.from_subclasses( | |||
| CheckpointKeeper, default=CheckpointKeeper | |||
| CheckpointKeeper, # type:ignore[type-abstract] | |||
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Is that something that can be fixed upstream?
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I did a little looking into mypy and I don't think they support differentiating between abstract subclasses or concrete subclasses. I agree this is not a pretty workaround to use so many type ignores
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Why does it even need to distinguish here? from_subclasses should accept any type (abstract or non-abstract), right?
mberr
reviewed
May 12, 2025
Comment on lines
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| if num_entities is None: | ||
| num_entities = mapped_triples[:, [0, 2]].max().item() + 1 |
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Could be replaced by pykeen.triples.utils.get_num_ids
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As a follow-up to #1537, this adds type annotations for torch. This is the most difficult step so far